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Use .multiplyMatrices( a, b ) instead.\\\\\\\"),this.multiplyMatrices(t,e)):this.multiplyMatrices(this,t)}premultiply(t){return this.multiplyMatrices(t,this)}multiplyMatrices(t,e){const s=t.elements,i=e.elements,r=this.elements,n=s[0],a=s[4],o=s[8],h=s[12],u=s[1],c=s[5],l=s[9],d=s[13],p=s[2],m=s[6],f=s[10],y=s[14],g=s[3],x=s[7],b=s[11],M=s[15],w=i[0],v=i[4],_=i[8],T=i[12],S=i[1],A=i[5],E=i[9],z=i[13],R=i[2],I=i[6],k=i[10],L=i[14],O=i[3],P=i[7],B=i[11],N=i[15];return r[0]=n*w+a*S+o*R+h*O,r[4]=n*v+a*A+o*I+h*P,r[8]=n*_+a*E+o*k+h*B,r[12]=n*T+a*z+o*L+h*N,r[1]=u*w+c*S+l*R+d*O,r[5]=u*v+c*A+l*I+d*P,r[9]=u*_+c*E+l*k+d*B,r[13]=u*T+c*z+l*L+d*N,r[2]=p*w+m*S+f*R+y*O,r[6]=p*v+m*A+f*I+y*P,r[10]=p*_+m*E+f*k+y*B,r[14]=p*T+m*z+f*L+y*N,r[3]=g*w+x*S+b*R+M*O,r[7]=g*v+x*A+b*I+M*P,r[11]=g*_+x*E+b*k+M*B,r[15]=g*T+x*z+b*L+M*N,this}multiplyScalar(t){const e=this.elements;return e[0]*=t,e[4]*=t,e[8]*=t,e[12]*=t,e[1]*=t,e[5]*=t,e[9]*=t,e[13]*=t,e[2]*=t,e[6]*=t,e[10]*=t,e[14]*=t,e[3]*=t,e[7]*=t,e[11]*=t,e[15]*=t,this}determinant(){const t=this.elements,e=t[0],s=t[4],i=t[8],r=t[12],n=t[1],a=t[5],o=t[9],h=t[13],u=t[2],c=t[6],l=t[10],d=t[14];return t[3]*(+r*o*c-i*h*c-r*a*l+s*h*l+i*a*d-s*o*d)+t[7]*(+e*o*d-e*h*l+r*n*l-i*n*d+i*h*u-r*o*u)+t[11]*(+e*h*c-e*a*d-r*n*c+s*n*d+r*a*u-s*h*u)+t[15]*(-i*a*u-e*o*c+e*a*l+i*n*c-s*n*l+s*o*u)}transpose(){const t=this.elements;let e;return e=t[1],t[1]=t[4],t[4]=e,e=t[2],t[2]=t[8],t[8]=e,e=t[6],t[6]=t[9],t[9]=e,e=t[3],t[3]=t[12],t[12]=e,e=t[7],t[7]=t[13],t[13]=e,e=t[11],t[11]=t[14],t[14]=e,this}setPosition(t,e,s){const i=this.elements;return t.isVector3?(i[12]=t.x,i[13]=t.y,i[14]=t.z):(i[12]=t,i[13]=e,i[14]=s),this}invert(){const t=this.elements,e=t[0],s=t[1],i=t[2],r=t[3],n=t[4],a=t[5],o=t[6],h=t[7],u=t[8],c=t[9],l=t[10],d=t[11],p=t[12],m=t[13],f=t[14],y=t[15],g=c*f*h-m*l*h+m*o*d-a*f*d-c*o*y+a*l*y,x=p*l*h-u*f*h-p*o*d+n*f*d+u*o*y-n*l*y,b=u*m*h-p*c*h+p*a*d-n*m*d-u*a*y+n*c*y,M=p*c*o-u*m*o-p*a*l+n*m*l+u*a*f-n*c*f,w=e*g+s*x+i*b+r*M;if(0===w)return this.set(0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0);const v=1/w;return t[0]=g*v,t[1]=(m*l*r-c*f*r-m*i*d+s*f*d+c*i*y-s*l*y)*v,t[2]=(a*f*r-m*o*r+m*i*h-s*f*h-a*i*y+s*o*y)*v,t[3]=(c*o*r-a*l*r-c*i*h+s*l*h+a*i*d-s*o*d)*v,t[4]=x*v,t[5]=(u*f*r-p*l*r+p*i*d-e*f*d-u*i*y+e*l*y)*v,t[6]=(p*o*r-n*f*r-p*i*h+e*f*h+n*i*y-e*o*y)*v,t[7]=(n*l*r-u*o*r+u*i*h-e*l*h-n*i*d+e*o*d)*v,t[8]=b*v,t[9]=(p*c*r-u*m*r-p*s*d+e*m*d+u*s*y-e*c*y)*v,t[10]=(n*m*r-p*a*r+p*s*h-e*m*h-n*s*y+e*a*y)*v,t[11]=(u*a*r-n*c*r-u*s*h+e*c*h+n*s*d-e*a*d)*v,t[12]=M*v,t[13]=(u*m*i-p*c*i+p*s*l-e*m*l-u*s*f+e*c*f)*v,t[14]=(p*a*i-n*m*i-p*s*o+e*m*o+n*s*f-e*a*f)*v,t[15]=(n*c*i-u*a*i+u*s*o-e*c*o-n*s*l+e*a*l)*v,this}scale(t){const e=this.elements,s=t.x,i=t.y,r=t.z;return e[0]*=s,e[4]*=i,e[8]*=r,e[1]*=s,e[5]*=i,e[9]*=r,e[2]*=s,e[6]*=i,e[10]*=r,e[3]*=s,e[7]*=i,e[11]*=r,this}getMaxScaleOnAxis(){const t=this.elements,e=t[0]*t[0]+t[1]*t[1]+t[2]*t[2],s=t[4]*t[4]+t[5]*t[5]+t[6]*t[6],i=t[8]*t[8]+t[9]*t[9]+t[10]*t[10];return Math.sqrt(Math.max(e,s,i))}makeTranslation(t,e,s){return this.set(1,0,0,t,0,1,0,e,0,0,1,s,0,0,0,1),this}makeRotationX(t){const e=Math.cos(t),s=Math.sin(t);return this.set(1,0,0,0,0,e,-s,0,0,s,e,0,0,0,0,1),this}makeRotationY(t){const e=Math.cos(t),s=Math.sin(t);return this.set(e,0,s,0,0,1,0,0,-s,0,e,0,0,0,0,1),this}makeRotationZ(t){const e=Math.cos(t),s=Math.sin(t);return this.set(e,-s,0,0,s,e,0,0,0,0,1,0,0,0,0,1),this}makeRotationAxis(t,e){const s=Math.cos(e),i=Math.sin(e),r=1-s,n=t.x,a=t.y,o=t.z,h=r*n,u=r*a;return this.set(h*n+s,h*a-i*o,h*o+i*a,0,h*a+i*o,u*a+s,u*o-i*n,0,h*o-i*a,u*o+i*n,r*o*o+s,0,0,0,0,1),this}makeScale(t,e,s){return this.set(t,0,0,0,0,e,0,0,0,0,s,0,0,0,0,1),this}makeShear(t,e,s,i,r,n){return this.set(1,s,r,0,t,1,n,0,e,i,1,0,0,0,0,1),this}compose(t,e,s){const i=this.elements,r=e._x,n=e._y,a=e._z,o=e._w,h=r+r,u=n+n,c=a+a,l=r*h,d=r*u,p=r*c,m=n*u,f=n*c,y=a*c,g=o*h,x=o*u,b=o*c,M=s.x,w=s.y,v=s.z;return i[0]=(1-(m+y))*M,i[1]=(d+b)*M,i[2]=(p-x)*M,i[3]=0,i[4]=(d-b)*w,i[5]=(1-(l+y))*w,i[6]=(f+g)*w,i[7]=0,i[8]=(p+x)*v,i[9]=(f-g)*v,i[10]=(1-(l+m))*v,i[11]=0,i[12]=t.x,i[13]=t.y,i[14]=t.z,i[15]=1,this}decompose(t,e,s){const i=this.elements;let r=n.set(i[0],i[1],i[2]).length();const o=n.set(i[4],i[5],i[6]).length(),h=n.set(i[8],i[9],i[10]).length();this.determinant()<0&&(r=-r),t.x=i[12],t.y=i[13],t.z=i[14],a.copy(this);const u=1/r,c=1/o,l=1/h;return a.elements[0]*=u,a.elements[1]*=u,a.elements[2]*=u,a.elements[4]*=c,a.elements[5]*=c,a.elements[6]*=c,a.elements[8]*=l,a.elements[9]*=l,a.elements[10]*=l,e.setFromRotationMatrix(a),s.x=r,s.y=o,s.z=h,this}makePerspective(t,e,s,i,r,n){void 0===n&&console.warn(\\\\\\\"THREE.Matrix4: .makePerspective() has been redefined and has a new signature. Please check the docs.\\\\\\\");const a=this.elements,o=2*r/(e-t),h=2*r/(s-i),u=(e+t)/(e-t),c=(s+i)/(s-i),l=-(n+r)/(n-r),d=-2*n*r/(n-r);return a[0]=o,a[4]=0,a[8]=u,a[12]=0,a[1]=0,a[5]=h,a[9]=c,a[13]=0,a[2]=0,a[6]=0,a[10]=l,a[14]=d,a[3]=0,a[7]=0,a[11]=-1,a[15]=0,this}makeOrthographic(t,e,s,i,r,n){const a=this.elements,o=1/(e-t),h=1/(s-i),u=1/(n-r),c=(e+t)*o,l=(s+i)*h,d=(n+r)*u;return a[0]=2*o,a[4]=0,a[8]=0,a[12]=-c,a[1]=0,a[5]=2*h,a[9]=0,a[13]=-l,a[2]=0,a[6]=0,a[10]=-2*u,a[14]=-d,a[3]=0,a[7]=0,a[11]=0,a[15]=1,this}equals(t){const e=this.elements,s=t.elements;for(let t=0;t<16;t++)if(e[t]!==s[t])return!1;return!0}fromArray(t,e=0){for(let s=0;s<16;s++)this.elements[s]=t[s+e];return this}toArray(t=[],e=0){const s=this.elements;return t[e]=s[0],t[e+1]=s[1],t[e+2]=s[2],t[e+3]=s[3],t[e+4]=s[4],t[e+5]=s[5],t[e+6]=s[6],t[e+7]=s[7],t[e+8]=s[8],t[e+9]=s[9],t[e+10]=s[10],t[e+11]=s[11],t[e+12]=s[12],t[e+13]=s[13],t[e+14]=s[14],t[e+15]=s[15],t}}r.prototype.isMatrix4=!0;const n=new i.a,a=new r,o=new i.a(0,0,0),h=new i.a(1,1,1),u=new i.a,c=new i.a,l=new i.a},function(t,e,s){\\\\\\\"use strict\\\\\\\";s.d(e,\\\\\\\"a\\\\\\\",(function(){return c}));var i=s(3);const r={aliceblue:15792383,antiquewhite:16444375,aqua:65535,aquamarine:8388564,azure:15794175,beige:16119260,bisque:16770244,black:0,blanchedalmond:16772045,blue:255,blueviolet:9055202,brown:10824234,burlywood:14596231,cadetblue:6266528,chartreuse:8388352,chocolate:13789470,coral:16744272,cornflowerblue:6591981,cornsilk:16775388,crimson:14423100,cyan:65535,darkblue:139,darkcyan:35723,darkgoldenrod:12092939,darkgray:11119017,darkgreen:25600,darkgrey:11119017,darkkhaki:12433259,darkmagenta:9109643,darkolivegreen:5597999,darkorange:16747520,darkorchid:10040012,darkred:9109504,darksalmon:15308410,darkseagreen:9419919,darkslateblue:4734347,darkslategray:3100495,darkslategrey:3100495,darkturquoise:52945,darkviolet:9699539,deeppink:16716947,deepskyblue:49151,dimgray:6908265,dimgrey:6908265,dodgerblue:2003199,firebrick:11674146,floralwhite:16775920,forestgreen:2263842,fuchsia:16711935,gainsboro:14474460,ghostwhite:16316671,gold:16766720,goldenrod:14329120,gray:8421504,green:32768,greenyellow:11403055,grey:8421504,honeydew:15794160,hotpink:16738740,indianred:13458524,indigo:4915330,ivory:16777200,khaki:15787660,lavender:15132410,lavenderblush:16773365,lawngreen:8190976,lemonchiffon:16775885,lightblue:11393254,lightcoral:15761536,lightcyan:14745599,lightgoldenrodyellow:16448210,lightgray:13882323,lightgreen:9498256,lightgrey:13882323,lightpink:16758465,lightsalmon:16752762,lightseagreen:2142890,lightskyblue:8900346,lightslategray:7833753,lightslategrey:7833753,lightsteelblue:11584734,lightyellow:16777184,lime:65280,limegreen:3329330,linen:16445670,magenta:16711935,maroon:8388608,mediumaquamarine:6737322,mediumblue:205,mediumorchid:12211667,mediumpurple:9662683,mediumseagreen:3978097,mediumslateblue:8087790,mediumspringgreen:64154,mediumturquoise:4772300,mediumvioletred:13047173,midnightblue:1644912,mintcream:16121850,mistyrose:16770273,moccasin:16770229,navajowhite:16768685,navy:128,oldlace:16643558,olive:8421376,olivedrab:7048739,orange:16753920,orangered:16729344,orchid:14315734,palegoldenrod:15657130,palegreen:10025880,paleturquoise:11529966,palevioletred:14381203,papayawhip:16773077,peachpuff:16767673,peru:13468991,pink:16761035,plum:14524637,powderblue:11591910,purple:8388736,rebeccapurple:6697881,red:16711680,rosybrown:12357519,royalblue:4286945,saddlebrown:9127187,salmon:16416882,sandybrown:16032864,seagreen:3050327,seashell:16774638,sienna:10506797,silver:12632256,skyblue:8900331,slateblue:6970061,slategray:7372944,slategrey:7372944,snow:16775930,springgreen:65407,steelblue:4620980,tan:13808780,teal:32896,thistle:14204888,tomato:16737095,turquoise:4251856,violet:15631086,wheat:16113331,white:16777215,whitesmoke:16119285,yellow:16776960,yellowgreen:10145074},n={h:0,s:0,l:0},a={h:0,s:0,l:0};function o(t,e,s){return s<0&&(s+=1),s>1&&(s-=1),s<1/6?t+6*(e-t)*s:s<.5?e:s<2/3?t+6*(e-t)*(2/3-s):t}function h(t){return t<.04045?.0773993808*t:Math.pow(.9478672986*t+.0521327014,2.4)}function u(t){return t<.0031308?12.92*t:1.055*Math.pow(t,.41666)-.055}class c{constructor(t,e,s){return void 0===e&&void 0===s?this.set(t):this.setRGB(t,e,s)}set(t){return t&&t.isColor?this.copy(t):\\\\\\\"number\\\\\\\"==typeof t?this.setHex(t):\\\\\\\"string\\\\\\\"==typeof t&&this.setStyle(t),this}setScalar(t){return this.r=t,this.g=t,this.b=t,this}setHex(t){return t=Math.floor(t),this.r=(t>>16&255)/255,this.g=(t>>8&255)/255,this.b=(255&t)/255,this}setRGB(t,e,s){return this.r=t,this.g=e,this.b=s,this}setHSL(t,e,s){if(t=i.f(t,1),e=i.d(e,0,1),s=i.d(s,0,1),0===e)this.r=this.g=this.b=s;else{const i=s<=.5?s*(1+e):s+e-s*e,r=2*s-i;this.r=o(r,i,t+1/3),this.g=o(r,i,t),this.b=o(r,i,t-1/3)}return this}setStyle(t){function e(e){void 0!==e&&parseFloat(e)<1&&console.warn(\\\\\\\"THREE.Color: Alpha component of \\\\\\\"+t+\\\\\\\" will be ignored.\\\\\\\")}let s;if(s=/^((?:rgb|hsl)a?)\\\\(([^\\\\)]*)\\\\)/.exec(t)){let t;const i=s[1],r=s[2];switch(i){case\\\\\\\"rgb\\\\\\\":case\\\\\\\"rgba\\\\\\\":if(t=/^\\\\s*(\\\\d+)\\\\s*,\\\\s*(\\\\d+)\\\\s*,\\\\s*(\\\\d+)\\\\s*(?:,\\\\s*(\\\\d*\\\\.?\\\\d+)\\\\s*)?$/.exec(r))return this.r=Math.min(255,parseInt(t[1],10))/255,this.g=Math.min(255,parseInt(t[2],10))/255,this.b=Math.min(255,parseInt(t[3],10))/255,e(t[4]),this;if(t=/^\\\\s*(\\\\d+)\\\\%\\\\s*,\\\\s*(\\\\d+)\\\\%\\\\s*,\\\\s*(\\\\d+)\\\\%\\\\s*(?:,\\\\s*(\\\\d*\\\\.?\\\\d+)\\\\s*)?$/.exec(r))return this.r=Math.min(100,parseInt(t[1],10))/100,this.g=Math.min(100,parseInt(t[2],10))/100,this.b=Math.min(100,parseInt(t[3],10))/100,e(t[4]),this;break;case\\\\\\\"hsl\\\\\\\":case\\\\\\\"hsla\\\\\\\":if(t=/^\\\\s*(\\\\d*\\\\.?\\\\d+)\\\\s*,\\\\s*(\\\\d+)\\\\%\\\\s*,\\\\s*(\\\\d+)\\\\%\\\\s*(?:,\\\\s*(\\\\d*\\\\.?\\\\d+)\\\\s*)?$/.exec(r)){const s=parseFloat(t[1])/360,i=parseInt(t[2],10)/100,r=parseInt(t[3],10)/100;return e(t[4]),this.setHSL(s,i,r)}}}else if(s=/^\\\\#([A-Fa-f\\\\d]+)$/.exec(t)){const t=s[1],e=t.length;if(3===e)return this.r=parseInt(t.charAt(0)+t.charAt(0),16)/255,this.g=parseInt(t.charAt(1)+t.charAt(1),16)/255,this.b=parseInt(t.charAt(2)+t.charAt(2),16)/255,this;if(6===e)return this.r=parseInt(t.charAt(0)+t.charAt(1),16)/255,this.g=parseInt(t.charAt(2)+t.charAt(3),16)/255,this.b=parseInt(t.charAt(4)+t.charAt(5),16)/255,this}return t&&t.length>0?this.setColorName(t):this}setColorName(t){const e=r[t.toLowerCase()];return void 0!==e?this.setHex(e):console.warn(\\\\\\\"THREE.Color: Unknown color \\\\\\\"+t),this}clone(){return new this.constructor(this.r,this.g,this.b)}copy(t){return this.r=t.r,this.g=t.g,this.b=t.b,this}copyGammaToLinear(t,e=2){return this.r=Math.pow(t.r,e),this.g=Math.pow(t.g,e),this.b=Math.pow(t.b,e),this}copyLinearToGamma(t,e=2){const s=e>0?1/e:1;return this.r=Math.pow(t.r,s),this.g=Math.pow(t.g,s),this.b=Math.pow(t.b,s),this}convertGammaToLinear(t){return this.copyGammaToLinear(this,t),this}convertLinearToGamma(t){return this.copyLinearToGamma(this,t),this}copySRGBToLinear(t){return this.r=h(t.r),this.g=h(t.g),this.b=h(t.b),this}copyLinearToSRGB(t){return this.r=u(t.r),this.g=u(t.g),this.b=u(t.b),this}convertSRGBToLinear(){return this.copySRGBToLinear(this),this}convertLinearToSRGB(){return this.copyLinearToSRGB(this),this}getHex(){return 255*this.r<<16^255*this.g<<8^255*this.b<<0}getHexString(){return(\\\\\\\"000000\\\\\\\"+this.getHex().toString(16)).slice(-6)}getHSL(t){const e=this.r,s=this.g,i=this.b,r=Math.max(e,s,i),n=Math.min(e,s,i);let a,o;const h=(n+r)/2;if(n===r)a=0,o=0;else{const t=r-n;switch(o=h<=.5?t/(r+n):t/(2-r-n),r){case e:a=(s-i)/t+(s65535?o.i:o.h)(t,1):this.index=t,this}getAttribute(t){return this.attributes[t]}setAttribute(t,e){return this.attributes[t]=e,this}deleteAttribute(t){return delete this.attributes[t],this}hasAttribute(t){return void 0!==this.attributes[t]}addGroup(t,e,s=0){this.groups.push({start:t,count:e,materialIndex:s})}clearGroups(){this.groups=[]}setDrawRange(t,e){this.drawRange.start=t,this.drawRange.count=e}applyMatrix4(t){const e=this.attributes.position;void 0!==e&&(e.applyMatrix4(t),e.needsUpdate=!0);const s=this.attributes.normal;if(void 0!==s){const e=(new l.a).getNormalMatrix(t);s.applyNormalMatrix(e),s.needsUpdate=!0}const i=this.attributes.tangent;return void 0!==i&&(i.transformDirection(t),i.needsUpdate=!0),null!==this.boundingBox&&this.computeBoundingBox(),null!==this.boundingSphere&&this.computeBoundingSphere(),this}applyQuaternion(t){return f.makeRotationFromQuaternion(t),this.applyMatrix4(f),this}rotateX(t){return f.makeRotationX(t),this.applyMatrix4(f),this}rotateY(t){return f.makeRotationY(t),this.applyMatrix4(f),this}rotateZ(t){return f.makeRotationZ(t),this.applyMatrix4(f),this}translate(t,e,s){return f.makeTranslation(t,e,s),this.applyMatrix4(f),this}scale(t,e,s){return f.makeScale(t,e,s),this.applyMatrix4(f),this}lookAt(t){return y.lookAt(t),y.updateMatrix(),this.applyMatrix4(y.matrix),this}center(){return this.computeBoundingBox(),this.boundingBox.getCenter(g).negate(),this.translate(g.x,g.y,g.z),this}setFromPoints(t){const e=[];for(let s=0,i=t.length;s0&&(t.userData=this.userData),void 0!==this.parameters){const e=this.parameters;for(const s in e)void 0!==e[s]&&(t[s]=e[s]);return t}t.data={attributes:{}};const e=this.index;null!==e&&(t.data.index={type:e.array.constructor.name,array:Array.prototype.slice.call(e.array)});const s=this.attributes;for(const e in s){const i=s[e];t.data.attributes[e]=i.toJSON(t.data)}const i={};let r=!1;for(const e in this.morphAttributes){const s=this.morphAttributes[e],n=[];for(let e=0,i=s.length;e0&&(i[e]=n,r=!0)}r&&(t.data.morphAttributes=i,t.data.morphTargetsRelative=this.morphTargetsRelative);const n=this.groups;n.length>0&&(t.data.groups=JSON.parse(JSON.stringify(n)));const a=this.boundingSphere;return null!==a&&(t.data.boundingSphere={center:a.center.toArray(),radius:a.radius}),t}clone(){return(new this.constructor).copy(this)}copy(t){this.index=null,this.attributes={},this.morphAttributes={},this.groups=[],this.boundingBox=null,this.boundingSphere=null;const e={};this.name=t.name;const s=t.index;null!==s&&this.setIndex(s.clone(e));const i=t.attributes;for(const t in i){const s=i[t];this.setAttribute(t,s.clone(e))}const r=t.morphAttributes;for(const t in r){const s=[],i=r[t];for(let t=0,r=i.length;t=0?1:-1,i=1-e*e;if(i>Number.EPSILON){const r=Math.sqrt(i),n=Math.atan2(r,e*s);t=Math.sin(t*n)/r,a=Math.sin(a*n)/r}const r=a*s;if(o=o*t+l*r,h=h*t+d*r,u=u*t+p*r,c=c*t+m*r,t===1-a){const t=1/Math.sqrt(o*o+h*h+u*u+c*c);o*=t,h*=t,u*=t,c*=t}}t[e]=o,t[e+1]=h,t[e+2]=u,t[e+3]=c}static multiplyQuaternionsFlat(t,e,s,i,r,n){const a=s[i],o=s[i+1],h=s[i+2],u=s[i+3],c=r[n],l=r[n+1],d=r[n+2],p=r[n+3];return t[e]=a*p+u*c+o*d-h*l,t[e+1]=o*p+u*l+h*c-a*d,t[e+2]=h*p+u*d+a*l-o*c,t[e+3]=u*p-a*c-o*l-h*d,t}get x(){return this._x}set x(t){this._x=t,this._onChangeCallback()}get y(){return this._y}set y(t){this._y=t,this._onChangeCallback()}get z(){return this._z}set z(t){this._z=t,this._onChangeCallback()}get w(){return this._w}set w(t){this._w=t,this._onChangeCallback()}set(t,e,s,i){return this._x=t,this._y=e,this._z=s,this._w=i,this._onChangeCallback(),this}clone(){return new this.constructor(this._x,this._y,this._z,this._w)}copy(t){return this._x=t.x,this._y=t.y,this._z=t.z,this._w=t.w,this._onChangeCallback(),this}setFromEuler(t,e){if(!t||!t.isEuler)throw new Error(\\\\\\\"THREE.Quaternion: .setFromEuler() now expects an Euler rotation rather than a Vector3 and order.\\\\\\\");const s=t._x,i=t._y,r=t._z,n=t._order,a=Math.cos,o=Math.sin,h=a(s/2),u=a(i/2),c=a(r/2),l=o(s/2),d=o(i/2),p=o(r/2);switch(n){case\\\\\\\"XYZ\\\\\\\":this._x=l*u*c+h*d*p,this._y=h*d*c-l*u*p,this._z=h*u*p+l*d*c,this._w=h*u*c-l*d*p;break;case\\\\\\\"YXZ\\\\\\\":this._x=l*u*c+h*d*p,this._y=h*d*c-l*u*p,this._z=h*u*p-l*d*c,this._w=h*u*c+l*d*p;break;case\\\\\\\"ZXY\\\\\\\":this._x=l*u*c-h*d*p,this._y=h*d*c+l*u*p,this._z=h*u*p+l*d*c,this._w=h*u*c-l*d*p;break;case\\\\\\\"ZYX\\\\\\\":this._x=l*u*c-h*d*p,this._y=h*d*c+l*u*p,this._z=h*u*p-l*d*c,this._w=h*u*c+l*d*p;break;case\\\\\\\"YZX\\\\\\\":this._x=l*u*c+h*d*p,this._y=h*d*c+l*u*p,this._z=h*u*p-l*d*c,this._w=h*u*c-l*d*p;break;case\\\\\\\"XZY\\\\\\\":this._x=l*u*c-h*d*p,this._y=h*d*c-l*u*p,this._z=h*u*p+l*d*c,this._w=h*u*c+l*d*p;break;default:console.warn(\\\\\\\"THREE.Quaternion: .setFromEuler() encountered an unknown order: \\\\\\\"+n)}return!1!==e&&this._onChangeCallback(),this}setFromAxisAngle(t,e){const s=e/2,i=Math.sin(s);return this._x=t.x*i,this._y=t.y*i,this._z=t.z*i,this._w=Math.cos(s),this._onChangeCallback(),this}setFromRotationMatrix(t){const e=t.elements,s=e[0],i=e[4],r=e[8],n=e[1],a=e[5],o=e[9],h=e[2],u=e[6],c=e[10],l=s+a+c;if(l>0){const t=.5/Math.sqrt(l+1);this._w=.25/t,this._x=(u-o)*t,this._y=(r-h)*t,this._z=(n-i)*t}else if(s>a&&s>c){const t=2*Math.sqrt(1+s-a-c);this._w=(u-o)/t,this._x=.25*t,this._y=(i+n)/t,this._z=(r+h)/t}else if(a>c){const t=2*Math.sqrt(1+a-s-c);this._w=(r-h)/t,this._x=(i+n)/t,this._y=.25*t,this._z=(o+u)/t}else{const t=2*Math.sqrt(1+c-s-a);this._w=(n-i)/t,this._x=(r+h)/t,this._y=(o+u)/t,this._z=.25*t}return this._onChangeCallback(),this}setFromUnitVectors(t,e){let s=t.dot(e)+1;return sMath.abs(t.z)?(this._x=-t.y,this._y=t.x,this._z=0,this._w=s):(this._x=0,this._y=-t.z,this._z=t.y,this._w=s)):(this._x=t.y*e.z-t.z*e.y,this._y=t.z*e.x-t.x*e.z,this._z=t.x*e.y-t.y*e.x,this._w=s),this.normalize()}angleTo(t){return 2*Math.acos(Math.abs(i.d(this.dot(t),-1,1)))}rotateTowards(t,e){const s=this.angleTo(t);if(0===s)return this;const i=Math.min(1,e/s);return this.slerp(t,i),this}identity(){return this.set(0,0,0,1)}invert(){return this.conjugate()}conjugate(){return this._x*=-1,this._y*=-1,this._z*=-1,this._onChangeCallback(),this}dot(t){return this._x*t._x+this._y*t._y+this._z*t._z+this._w*t._w}lengthSq(){return this._x*this._x+this._y*this._y+this._z*this._z+this._w*this._w}length(){return Math.sqrt(this._x*this._x+this._y*this._y+this._z*this._z+this._w*this._w)}normalize(){let t=this.length();return 0===t?(this._x=0,this._y=0,this._z=0,this._w=1):(t=1/t,this._x=this._x*t,this._y=this._y*t,this._z=this._z*t,this._w=this._w*t),this._onChangeCallback(),this}multiply(t,e){return void 0!==e?(console.warn(\\\\\\\"THREE.Quaternion: .multiply() now only accepts one argument. Use .multiplyQuaternions( a, b ) instead.\\\\\\\"),this.multiplyQuaternions(t,e)):this.multiplyQuaternions(this,t)}premultiply(t){return this.multiplyQuaternions(t,this)}multiplyQuaternions(t,e){const s=t._x,i=t._y,r=t._z,n=t._w,a=e._x,o=e._y,h=e._z,u=e._w;return this._x=s*u+n*a+i*h-r*o,this._y=i*u+n*o+r*a-s*h,this._z=r*u+n*h+s*o-i*a,this._w=n*u-s*a-i*o-r*h,this._onChangeCallback(),this}slerp(t,e){if(0===e)return this;if(1===e)return this.copy(t);const s=this._x,i=this._y,r=this._z,n=this._w;let a=n*t._w+s*t._x+i*t._y+r*t._z;if(a<0?(this._w=-t._w,this._x=-t._x,this._y=-t._y,this._z=-t._z,a=-a):this.copy(t),a>=1)return this._w=n,this._x=s,this._y=i,this._z=r,this;const o=1-a*a;if(o<=Number.EPSILON){const t=1-e;return this._w=t*n+e*this._w,this._x=t*s+e*this._x,this._y=t*i+e*this._y,this._z=t*r+e*this._z,this.normalize(),this._onChangeCallback(),this}const h=Math.sqrt(o),u=Math.atan2(h,a),c=Math.sin((1-e)*u)/h,l=Math.sin(e*u)/h;return this._w=n*c+this._w*l,this._x=s*c+this._x*l,this._y=i*c+this._y*l,this._z=r*c+this._z*l,this._onChangeCallback(),this}slerpQuaternions(t,e,s){this.copy(t).slerp(e,s)}random(){const t=Math.random(),e=Math.sqrt(1-t),s=Math.sqrt(t),i=2*Math.PI*Math.random(),r=2*Math.PI*Math.random();return this.set(e*Math.cos(i),s*Math.sin(r),s*Math.cos(r),e*Math.sin(i))}equals(t){return t._x===this._x&&t._y===this._y&&t._z===this._z&&t._w===this._w}fromArray(t,e=0){return this._x=t[e],this._y=t[e+1],this._z=t[e+2],this._w=t[e+3],this._onChangeCallback(),this}toArray(t=[],e=0){return t[e]=this._x,t[e+1]=this._y,t[e+2]=this._z,t[e+3]=this._w,t}fromBufferAttribute(t,e){return this._x=t.getX(e),this._y=t.getY(e),this._z=t.getZ(e),this._w=t.getW(e),this}_onChange(t){return this._onChangeCallback=t,this}_onChangeCallback(){}}r.prototype.isQuaternion=!0},function(t,e,s){\\\\\\\"use strict\\\\\\\";s.d(e,\\\\\\\"a\\\\\\\",(function(){return i}));class i{constructor(t=0,e=0,s=0,i=1){this.x=t,this.y=e,this.z=s,this.w=i}get width(){return this.z}set width(t){this.z=t}get height(){return this.w}set height(t){this.w=t}set(t,e,s,i){return this.x=t,this.y=e,this.z=s,this.w=i,this}setScalar(t){return this.x=t,this.y=t,this.z=t,this.w=t,this}setX(t){return this.x=t,this}setY(t){return this.y=t,this}setZ(t){return this.z=t,this}setW(t){return this.w=t,this}setComponent(t,e){switch(t){case 0:this.x=e;break;case 1:this.y=e;break;case 2:this.z=e;break;case 3:this.w=e;break;default:throw new Error(\\\\\\\"index is out of range: \\\\\\\"+t)}return this}getComponent(t){switch(t){case 0:return this.x;case 1:return this.y;case 2:return this.z;case 3:return this.w;default:throw new Error(\\\\\\\"index is out of range: \\\\\\\"+t)}}clone(){return new this.constructor(this.x,this.y,this.z,this.w)}copy(t){return this.x=t.x,this.y=t.y,this.z=t.z,this.w=void 0!==t.w?t.w:1,this}add(t,e){return void 0!==e?(console.warn(\\\\\\\"THREE.Vector4: .add() now only accepts one argument. Use .addVectors( a, b ) instead.\\\\\\\"),this.addVectors(t,e)):(this.x+=t.x,this.y+=t.y,this.z+=t.z,this.w+=t.w,this)}addScalar(t){return this.x+=t,this.y+=t,this.z+=t,this.w+=t,this}addVectors(t,e){return this.x=t.x+e.x,this.y=t.y+e.y,this.z=t.z+e.z,this.w=t.w+e.w,this}addScaledVector(t,e){return this.x+=t.x*e,this.y+=t.y*e,this.z+=t.z*e,this.w+=t.w*e,this}sub(t,e){return void 0!==e?(console.warn(\\\\\\\"THREE.Vector4: .sub() now only accepts one argument. Use .subVectors( a, b ) instead.\\\\\\\"),this.subVectors(t,e)):(this.x-=t.x,this.y-=t.y,this.z-=t.z,this.w-=t.w,this)}subScalar(t){return this.x-=t,this.y-=t,this.z-=t,this.w-=t,this}subVectors(t,e){return this.x=t.x-e.x,this.y=t.y-e.y,this.z=t.z-e.z,this.w=t.w-e.w,this}multiply(t){return this.x*=t.x,this.y*=t.y,this.z*=t.z,this.w*=t.w,this}multiplyScalar(t){return this.x*=t,this.y*=t,this.z*=t,this.w*=t,this}applyMatrix4(t){const e=this.x,s=this.y,i=this.z,r=this.w,n=t.elements;return this.x=n[0]*e+n[4]*s+n[8]*i+n[12]*r,this.y=n[1]*e+n[5]*s+n[9]*i+n[13]*r,this.z=n[2]*e+n[6]*s+n[10]*i+n[14]*r,this.w=n[3]*e+n[7]*s+n[11]*i+n[15]*r,this}divideScalar(t){return this.multiplyScalar(1/t)}setAxisAngleFromQuaternion(t){this.w=2*Math.acos(t.w);const e=Math.sqrt(1-t.w*t.w);return e<1e-4?(this.x=1,this.y=0,this.z=0):(this.x=t.x/e,this.y=t.y/e,this.z=t.z/e),this}setAxisAngleFromRotationMatrix(t){let e,s,i,r;const n=.01,a=.1,o=t.elements,h=o[0],u=o[4],c=o[8],l=o[1],d=o[5],p=o[9],m=o[2],f=o[6],y=o[10];if(Math.abs(u-l)o&&t>g?tg?o1){for(let t=0;t1){for(let t=0;t0){i.children=[];for(let e=0;e0){i.animations=[];for(let e=0;e0&&(s.geometries=e),i.length>0&&(s.materials=i),r.length>0&&(s.textures=r),a.length>0&&(s.images=a),o.length>0&&(s.shapes=o),h.length>0&&(s.skeletons=h),u.length>0&&(s.animations=u)}return s.object=i,s;function n(t){const e=[];for(const s in t){const i=t[s];delete i.metadata,e.push(i)}return e}}clone(t){return(new this.constructor).copy(this,t)}copy(t,e=!0){if(this.name=t.name,this.up.copy(t.up),this.position.copy(t.position),this.rotation.order=t.rotation.order,this.quaternion.copy(t.quaternion),this.scale.copy(t.scale),this.matrix.copy(t.matrix),this.matrixWorld.copy(t.matrixWorld),this.matrixAutoUpdate=t.matrixAutoUpdate,this.matrixWorldNeedsUpdate=t.matrixWorldNeedsUpdate,this.layers.mask=t.layers.mask,this.visible=t.visible,this.castShadow=t.castShadow,this.receiveShadow=t.receiveShadow,this.frustumCulled=t.frustumCulled,this.renderOrder=t.renderOrder,this.userData=JSON.parse(JSON.stringify(t.userData)),!0===e)for(let e=0;e0&&console.error(\\\\\\\"THREE.Matrix3: the constructor no longer reads arguments. use .set() instead.\\\\\\\")}set(t,e,s,i,r,n,a,o,h){const u=this.elements;return u[0]=t,u[1]=i,u[2]=a,u[3]=e,u[4]=r,u[5]=o,u[6]=s,u[7]=n,u[8]=h,this}identity(){return this.set(1,0,0,0,1,0,0,0,1),this}copy(t){const e=this.elements,s=t.elements;return e[0]=s[0],e[1]=s[1],e[2]=s[2],e[3]=s[3],e[4]=s[4],e[5]=s[5],e[6]=s[6],e[7]=s[7],e[8]=s[8],this}extractBasis(t,e,s){return t.setFromMatrix3Column(this,0),e.setFromMatrix3Column(this,1),s.setFromMatrix3Column(this,2),this}setFromMatrix4(t){const e=t.elements;return this.set(e[0],e[4],e[8],e[1],e[5],e[9],e[2],e[6],e[10]),this}multiply(t){return this.multiplyMatrices(this,t)}premultiply(t){return this.multiplyMatrices(t,this)}multiplyMatrices(t,e){const s=t.elements,i=e.elements,r=this.elements,n=s[0],a=s[3],o=s[6],h=s[1],u=s[4],c=s[7],l=s[2],d=s[5],p=s[8],m=i[0],f=i[3],y=i[6],g=i[1],x=i[4],b=i[7],M=i[2],w=i[5],v=i[8];return r[0]=n*m+a*g+o*M,r[3]=n*f+a*x+o*w,r[6]=n*y+a*b+o*v,r[1]=h*m+u*g+c*M,r[4]=h*f+u*x+c*w,r[7]=h*y+u*b+c*v,r[2]=l*m+d*g+p*M,r[5]=l*f+d*x+p*w,r[8]=l*y+d*b+p*v,this}multiplyScalar(t){const e=this.elements;return e[0]*=t,e[3]*=t,e[6]*=t,e[1]*=t,e[4]*=t,e[7]*=t,e[2]*=t,e[5]*=t,e[8]*=t,this}determinant(){const t=this.elements,e=t[0],s=t[1],i=t[2],r=t[3],n=t[4],a=t[5],o=t[6],h=t[7],u=t[8];return e*n*u-e*a*h-s*r*u+s*a*o+i*r*h-i*n*o}invert(){const t=this.elements,e=t[0],s=t[1],i=t[2],r=t[3],n=t[4],a=t[5],o=t[6],h=t[7],u=t[8],c=u*n-a*h,l=a*o-u*r,d=h*r-n*o,p=e*c+s*l+i*d;if(0===p)return this.set(0,0,0,0,0,0,0,0,0);const m=1/p;return t[0]=c*m,t[1]=(i*h-u*s)*m,t[2]=(a*s-i*n)*m,t[3]=l*m,t[4]=(u*e-i*o)*m,t[5]=(i*r-a*e)*m,t[6]=d*m,t[7]=(s*o-h*e)*m,t[8]=(n*e-s*r)*m,this}transpose(){let t;const e=this.elements;return t=e[1],e[1]=e[3],e[3]=t,t=e[2],e[2]=e[6],e[6]=t,t=e[5],e[5]=e[7],e[7]=t,this}getNormalMatrix(t){return this.setFromMatrix4(t).invert().transpose()}transposeIntoArray(t){const e=this.elements;return t[0]=e[0],t[1]=e[3],t[2]=e[6],t[3]=e[1],t[4]=e[4],t[5]=e[7],t[6]=e[2],t[7]=e[5],t[8]=e[8],this}setUvTransform(t,e,s,i,r,n,a){const o=Math.cos(r),h=Math.sin(r);return this.set(s*o,s*h,-s*(o*n+h*a)+n+t,-i*h,i*o,-i*(-h*n+o*a)+a+e,0,0,1),this}scale(t,e){const s=this.elements;return s[0]*=t,s[3]*=t,s[6]*=t,s[1]*=e,s[4]*=e,s[7]*=e,this}rotate(t){const e=Math.cos(t),s=Math.sin(t),i=this.elements,r=i[0],n=i[3],a=i[6],o=i[1],h=i[4],u=i[7];return i[0]=e*r+s*o,i[3]=e*n+s*h,i[6]=e*a+s*u,i[1]=-s*r+e*o,i[4]=-s*n+e*h,i[7]=-s*a+e*u,this}translate(t,e){const s=this.elements;return s[0]+=t*s[2],s[3]+=t*s[5],s[6]+=t*s[8],s[1]+=e*s[2],s[4]+=e*s[5],s[7]+=e*s[8],this}equals(t){const e=this.elements,s=t.elements;for(let t=0;t<9;t++)if(e[t]!==s[t])return!1;return!0}fromArray(t,e=0){for(let s=0;s<9;s++)this.elements[s]=t[s+e];return this}toArray(t=[],e=0){const s=this.elements;return t[e]=s[0],t[e+1]=s[1],t[e+2]=s[2],t[e+3]=s[3],t[e+4]=s[4],t[e+5]=s[5],t[e+6]=s[6],t[e+7]=s[7],t[e+8]=s[8],t}clone(){return(new this.constructor).fromArray(this.elements)}}i.prototype.isMatrix3=!0},function(t,e,s){\\\\\\\"use strict\\\\\\\";s.d(e,\\\\\\\"a\\\\\\\",(function(){return o}));var i=s(15),r=s(1),n=s(3);let a=0;class o extends i.a{constructor(){super(),Object.defineProperty(this,\\\\\\\"id\\\\\\\",{value:a++}),this.uuid=n.h(),this.name=\\\\\\\"\\\\\\\",this.type=\\\\\\\"Material\\\\\\\",this.fog=!0,this.blending=r.xb,this.side=r.H,this.vertexColors=!1,this.opacity=1,this.format=r.Ib,this.transparent=!1,this.blendSrc=r.Nc,this.blendDst=r.Db,this.blendEquation=r.b,this.blendSrcAlpha=null,this.blendDstAlpha=null,this.blendEquationAlpha=null,this.depthFunc=r.T,this.depthTest=!0,this.depthWrite=!0,this.stencilWriteMask=255,this.stencilFunc=r.h,this.stencilRef=0,this.stencilFuncMask=255,this.stencilFail=r.R,this.stencilZFail=r.R,this.stencilZPass=r.R,this.stencilWrite=!1,this.clippingPlanes=null,this.clipIntersection=!1,this.clipShadows=!1,this.shadowSide=null,this.colorWrite=!0,this.precision=null,this.polygonOffset=!1,this.polygonOffsetFactor=0,this.polygonOffsetUnits=0,this.dithering=!1,this.alphaToCoverage=!1,this.premultipliedAlpha=!1,this.visible=!0,this.toneMapped=!0,this.userData={},this.version=0,this._alphaTest=0}get alphaTest(){return this._alphaTest}set alphaTest(t){this._alphaTest>0!=t>0&&this.version++,this._alphaTest=t}onBuild(){}onBeforeRender(){}onBeforeCompile(){}customProgramCacheKey(){return this.onBeforeCompile.toString()}setValues(t){if(void 0!==t)for(const e in t){const s=t[e];if(void 0===s){console.warn(\\\\\\\"THREE.Material: '\\\\\\\"+e+\\\\\\\"' parameter is undefined.\\\\\\\");continue}if(\\\\\\\"shading\\\\\\\"===e){console.warn(\\\\\\\"THREE.\\\\\\\"+this.type+\\\\\\\": .shading has been removed. Use the boolean .flatShading instead.\\\\\\\"),this.flatShading=s===r.F;continue}const i=this[e];void 0!==i?i&&i.isColor?i.set(s):i&&i.isVector3&&s&&s.isVector3?i.copy(s):this[e]=s:console.warn(\\\\\\\"THREE.\\\\\\\"+this.type+\\\\\\\": '\\\\\\\"+e+\\\\\\\"' is not a property of this material.\\\\\\\")}}toJSON(t){const e=void 0===t||\\\\\\\"string\\\\\\\"==typeof t;e&&(t={textures:{},images:{}});const s={metadata:{version:4.5,type:\\\\\\\"Material\\\\\\\",generator:\\\\\\\"Material.toJSON\\\\\\\"}};function i(t){const e=[];for(const s in t){const i=t[s];delete i.metadata,e.push(i)}return e}if(s.uuid=this.uuid,s.type=this.type,\\\\\\\"\\\\\\\"!==this.name&&(s.name=this.name),this.color&&this.color.isColor&&(s.color=this.color.getHex()),void 0!==this.roughness&&(s.roughness=this.roughness),void 0!==this.metalness&&(s.metalness=this.metalness),void 0!==this.sheen&&(s.sheen=this.sheen),this.sheenTint&&this.sheenTint.isColor&&(s.sheenTint=this.sheenTint.getHex()),void 0!==this.sheenRoughness&&(s.sheenRoughness=this.sheenRoughness),this.emissive&&this.emissive.isColor&&(s.emissive=this.emissive.getHex()),this.emissiveIntensity&&1!==this.emissiveIntensity&&(s.emissiveIntensity=this.emissiveIntensity),this.specular&&this.specular.isColor&&(s.specular=this.specular.getHex()),void 0!==this.specularIntensity&&(s.specularIntensity=this.specularIntensity),this.specularTint&&this.specularTint.isColor&&(s.specularTint=this.specularTint.getHex()),void 0!==this.shininess&&(s.shininess=this.shininess),void 0!==this.clearcoat&&(s.clearcoat=this.clearcoat),void 0!==this.clearcoatRoughness&&(s.clearcoatRoughness=this.clearcoatRoughness),this.clearcoatMap&&this.clearcoatMap.isTexture&&(s.clearcoatMap=this.clearcoatMap.toJSON(t).uuid),this.clearcoatRoughnessMap&&this.clearcoatRoughnessMap.isTexture&&(s.clearcoatRoughnessMap=this.clearcoatRoughnessMap.toJSON(t).uuid),this.clearcoatNormalMap&&this.clearcoatNormalMap.isTexture&&(s.clearcoatNormalMap=this.clearcoatNormalMap.toJSON(t).uuid,s.clearcoatNormalScale=this.clearcoatNormalScale.toArray()),this.map&&this.map.isTexture&&(s.map=this.map.toJSON(t).uuid),this.matcap&&this.matcap.isTexture&&(s.matcap=this.matcap.toJSON(t).uuid),this.alphaMap&&this.alphaMap.isTexture&&(s.alphaMap=this.alphaMap.toJSON(t).uuid),this.lightMap&&this.lightMap.isTexture&&(s.lightMap=this.lightMap.toJSON(t).uuid,s.lightMapIntensity=this.lightMapIntensity),this.aoMap&&this.aoMap.isTexture&&(s.aoMap=this.aoMap.toJSON(t).uuid,s.aoMapIntensity=this.aoMapIntensity),this.bumpMap&&this.bumpMap.isTexture&&(s.bumpMap=this.bumpMap.toJSON(t).uuid,s.bumpScale=this.bumpScale),this.normalMap&&this.normalMap.isTexture&&(s.normalMap=this.normalMap.toJSON(t).uuid,s.normalMapType=this.normalMapType,s.normalScale=this.normalScale.toArray()),this.displacementMap&&this.displacementMap.isTexture&&(s.displacementMap=this.displacementMap.toJSON(t).uuid,s.displacementScale=this.displacementScale,s.displacementBias=this.displacementBias),this.roughnessMap&&this.roughnessMap.isTexture&&(s.roughnessMap=this.roughnessMap.toJSON(t).uuid),this.metalnessMap&&this.metalnessMap.isTexture&&(s.metalnessMap=this.metalnessMap.toJSON(t).uuid),this.emissiveMap&&this.emissiveMap.isTexture&&(s.emissiveMap=this.emissiveMap.toJSON(t).uuid),this.specularMap&&this.specularMap.isTexture&&(s.specularMap=this.specularMap.toJSON(t).uuid),this.specularIntensityMap&&this.specularIntensityMap.isTexture&&(s.specularIntensityMap=this.specularIntensityMap.toJSON(t).uuid),this.specularTintMap&&this.specularTintMap.isTexture&&(s.specularTintMap=this.specularTintMap.toJSON(t).uuid),this.envMap&&this.envMap.isTexture&&(s.envMap=this.envMap.toJSON(t).uuid,void 0!==this.combine&&(s.combine=this.combine)),void 0!==this.envMapIntensity&&(s.envMapIntensity=this.envMapIntensity),void 0!==this.reflectivity&&(s.reflectivity=this.reflectivity),void 0!==this.refractionRatio&&(s.refractionRatio=this.refractionRatio),this.gradientMap&&this.gradientMap.isTexture&&(s.gradientMap=this.gradientMap.toJSON(t).uuid),void 0!==this.transmission&&(s.transmission=this.transmission),this.transmissionMap&&this.transmissionMap.isTexture&&(s.transmissionMap=this.transmissionMap.toJSON(t).uuid),void 0!==this.thickness&&(s.thickness=this.thickness),this.thicknessMap&&this.thicknessMap.isTexture&&(s.thicknessMap=this.thicknessMap.toJSON(t).uuid),void 0!==this.attenuationDistance&&(s.attenuationDistance=this.attenuationDistance),void 0!==this.attenuationTint&&(s.attenuationTint=this.attenuationTint.getHex()),void 0!==this.size&&(s.size=this.size),null!==this.shadowSide&&(s.shadowSide=this.shadowSide),void 0!==this.sizeAttenuation&&(s.sizeAttenuation=this.sizeAttenuation),this.blending!==r.xb&&(s.blending=this.blending),this.side!==r.H&&(s.side=this.side),this.vertexColors&&(s.vertexColors=!0),this.opacity<1&&(s.opacity=this.opacity),this.format!==r.Ib&&(s.format=this.format),!0===this.transparent&&(s.transparent=this.transparent),s.depthFunc=this.depthFunc,s.depthTest=this.depthTest,s.depthWrite=this.depthWrite,s.colorWrite=this.colorWrite,s.stencilWrite=this.stencilWrite,s.stencilWriteMask=this.stencilWriteMask,s.stencilFunc=this.stencilFunc,s.stencilRef=this.stencilRef,s.stencilFuncMask=this.stencilFuncMask,s.stencilFail=this.stencilFail,s.stencilZFail=this.stencilZFail,s.stencilZPass=this.stencilZPass,this.rotation&&0!==this.rotation&&(s.rotation=this.rotation),!0===this.polygonOffset&&(s.polygonOffset=!0),0!==this.polygonOffsetFactor&&(s.polygonOffsetFactor=this.polygonOffsetFactor),0!==this.polygonOffsetUnits&&(s.polygonOffsetUnits=this.polygonOffsetUnits),this.linewidth&&1!==this.linewidth&&(s.linewidth=this.linewidth),void 0!==this.dashSize&&(s.dashSize=this.dashSize),void 0!==this.gapSize&&(s.gapSize=this.gapSize),void 0!==this.scale&&(s.scale=this.scale),!0===this.dithering&&(s.dithering=!0),this.alphaTest>0&&(s.alphaTest=this.alphaTest),!0===this.alphaToCoverage&&(s.alphaToCoverage=this.alphaToCoverage),!0===this.premultipliedAlpha&&(s.premultipliedAlpha=this.premultipliedAlpha),!0===this.wireframe&&(s.wireframe=this.wireframe),this.wireframeLinewidth>1&&(s.wireframeLinewidth=this.wireframeLinewidth),\\\\\\\"round\\\\\\\"!==this.wireframeLinecap&&(s.wireframeLinecap=this.wireframeLinecap),\\\\\\\"round\\\\\\\"!==this.wireframeLinejoin&&(s.wireframeLinejoin=this.wireframeLinejoin),!0===this.flatShading&&(s.flatShading=this.flatShading),!1===this.visible&&(s.visible=!1),!1===this.toneMapped&&(s.toneMapped=!1),\\\\\\\"{}\\\\\\\"!==JSON.stringify(this.userData)&&(s.userData=this.userData),e){const e=i(t.textures),r=i(t.images);e.length>0&&(s.textures=e),r.length>0&&(s.images=r)}return s}clone(){return(new this.constructor).copy(this)}copy(t){this.name=t.name,this.fog=t.fog,this.blending=t.blending,this.side=t.side,this.vertexColors=t.vertexColors,this.opacity=t.opacity,this.format=t.format,this.transparent=t.transparent,this.blendSrc=t.blendSrc,this.blendDst=t.blendDst,this.blendEquation=t.blendEquation,this.blendSrcAlpha=t.blendSrcAlpha,this.blendDstAlpha=t.blendDstAlpha,this.blendEquationAlpha=t.blendEquationAlpha,this.depthFunc=t.depthFunc,this.depthTest=t.depthTest,this.depthWrite=t.depthWrite,this.stencilWriteMask=t.stencilWriteMask,this.stencilFunc=t.stencilFunc,this.stencilRef=t.stencilRef,this.stencilFuncMask=t.stencilFuncMask,this.stencilFail=t.stencilFail,this.stencilZFail=t.stencilZFail,this.stencilZPass=t.stencilZPass,this.stencilWrite=t.stencilWrite;const e=t.clippingPlanes;let s=null;if(null!==e){const t=e.length;s=new Array(t);for(let i=0;i!==t;++i)s[i]=e[i].clone()}return this.clippingPlanes=s,this.clipIntersection=t.clipIntersection,this.clipShadows=t.clipShadows,this.shadowSide=t.shadowSide,this.colorWrite=t.colorWrite,this.precision=t.precision,this.polygonOffset=t.polygonOffset,this.polygonOffsetFactor=t.polygonOffsetFactor,this.polygonOffsetUnits=t.polygonOffsetUnits,this.dithering=t.dithering,this.alphaTest=t.alphaTest,this.alphaToCoverage=t.alphaToCoverage,this.premultipliedAlpha=t.premultipliedAlpha,this.visible=t.visible,this.toneMapped=t.toneMapped,this.userData=JSON.parse(JSON.stringify(t.userData)),this}dispose(){this.dispatchEvent({type:\\\\\\\"dispose\\\\\\\"})}set needsUpdate(t){!0===t&&this.version++}}o.prototype.isMaterial=!0},function(t,e,s){\\\\\\\"use strict\\\\\\\";s.d(e,\\\\\\\"a\\\\\\\",(function(){return r}));var i=s(28);class r{constructor(t){this.manager=void 0!==t?t:i.a,this.crossOrigin=\\\\\\\"anonymous\\\\\\\",this.withCredentials=!1,this.path=\\\\\\\"\\\\\\\",this.resourcePath=\\\\\\\"\\\\\\\",this.requestHeader={}}load(){}loadAsync(t,e){const s=this;return new Promise((function(i,r){s.load(t,i,e,r)}))}parse(){}setCrossOrigin(t){return this.crossOrigin=t,this}setWithCredentials(t){return this.withCredentials=t,this}setPath(t){return this.path=t,this}setResourcePath(t){return this.resourcePath=t,this}setRequestHeader(t){return this.requestHeader=t,this}}},function(t,e,s){\\\\\\\"use strict\\\\\\\";s.d(e,\\\\\\\"a\\\\\\\",(function(){return I}));var i=s(0),r=s(2),n=s(18),a=s(39),o=s(5),h=s(10),u=s(40),c=s(1),l=s(29),d=s(7);const p=new o.a,m=new a.a,f=new n.a,y=new i.a,g=new i.a,x=new i.a,b=new i.a,M=new i.a,w=new i.a,v=new i.a,_=new i.a,T=new i.a,S=new r.a,A=new r.a,E=new r.a,z=new i.a,R=new i.a;class I extends h.a{constructor(t=new d.a,e=new l.a){super(),this.type=\\\\\\\"Mesh\\\\\\\",this.geometry=t,this.material=e,this.updateMorphTargets()}copy(t){return super.copy(t),void 0!==t.morphTargetInfluences&&(this.morphTargetInfluences=t.morphTargetInfluences.slice()),void 0!==t.morphTargetDictionary&&(this.morphTargetDictionary=Object.assign({},t.morphTargetDictionary)),this.material=t.material,this.geometry=t.geometry,this}updateMorphTargets(){const t=this.geometry;if(t.isBufferGeometry){const e=t.morphAttributes,s=Object.keys(e);if(s.length>0){const t=e[s[0]];if(void 0!==t){this.morphTargetInfluences=[],this.morphTargetDictionary={};for(let e=0,s=t.length;e0&&console.error(\\\\\\\"THREE.Mesh.updateMorphTargets() no longer supports THREE.Geometry. Use THREE.BufferGeometry instead.\\\\\\\")}}raycast(t,e){const s=this.geometry,i=this.material,r=this.matrixWorld;if(void 0===i)return;if(null===s.boundingSphere&&s.computeBoundingSphere(),f.copy(s.boundingSphere),f.applyMatrix4(r),!1===t.ray.intersectsSphere(f))return;if(p.copy(r).invert(),m.copy(t.ray).applyMatrix4(p),null!==s.boundingBox&&!1===m.intersectsBox(s.boundingBox))return;let n;if(s.isBufferGeometry){const r=s.index,a=s.attributes.position,o=s.morphAttributes.position,h=s.morphTargetsRelative,u=s.attributes.uv,c=s.attributes.uv2,l=s.groups,d=s.drawRange;if(null!==r)if(Array.isArray(i))for(let s=0,p=l.length;ss.far?null:{distance:u,point:R.clone(),object:t}}(t,e,s,n,y,g,x,z);if(k){l&&(S.fromBufferAttribute(l,p),A.fromBufferAttribute(l,m),E.fromBufferAttribute(l,f),k.uv=u.a.getUV(z,y,g,x,S,A,E,new r.a)),d&&(S.fromBufferAttribute(d,p),A.fromBufferAttribute(d,m),E.fromBufferAttribute(d,f),k.uv2=u.a.getUV(z,y,g,x,S,A,E,new r.a));const t={a:p,b:m,c:f,normal:new 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i=t.elements,r=i[0],n=i[4],o=i[8],h=i[1],u=i[5],c=i[9],l=i[2],d=i[6],p=i[10];switch(e){case\\\\\\\"XYZ\\\\\\\":this._y=Math.asin(Object(a.d)(o,-1,1)),Math.abs(o)<.9999999?(this._x=Math.atan2(-c,p),this._z=Math.atan2(-n,r)):(this._x=Math.atan2(d,u),this._z=0);break;case\\\\\\\"YXZ\\\\\\\":this._x=Math.asin(-Object(a.d)(c,-1,1)),Math.abs(c)<.9999999?(this._y=Math.atan2(o,p),this._z=Math.atan2(h,u)):(this._y=Math.atan2(-l,r),this._z=0);break;case\\\\\\\"ZXY\\\\\\\":this._x=Math.asin(Object(a.d)(d,-1,1)),Math.abs(d)<.9999999?(this._y=Math.atan2(-l,p),this._z=Math.atan2(-n,u)):(this._y=0,this._z=Math.atan2(h,r));break;case\\\\\\\"ZYX\\\\\\\":this._y=Math.asin(-Object(a.d)(l,-1,1)),Math.abs(l)<.9999999?(this._x=Math.atan2(d,p),this._z=Math.atan2(h,r)):(this._x=0,this._z=Math.atan2(-n,u));break;case\\\\\\\"YZX\\\\\\\":this._z=Math.asin(Object(a.d)(h,-1,1)),Math.abs(h)<.9999999?(this._x=Math.atan2(-c,u),this._y=Math.atan2(-l,r)):(this._x=0,this._y=Math.atan2(o,p));break;case\\\\\\\"XZY\\\\\\\":this._z=Math.asin(-Object(a.d)(n,-1,1)),Math.abs(n)<.9999999?(this._x=Math.atan2(d,u),this._y=Math.atan2(o,r)):(this._x=Math.atan2(-c,p),this._y=0);break;default:console.warn(\\\\\\\"THREE.Euler: 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this._onChangeCallback=t,this}_onChangeCallback(){}}u.prototype.isEuler=!0,u.DefaultOrder=\\\\\\\"XYZ\\\\\\\",u.RotationOrders=[\\\\\\\"XYZ\\\\\\\",\\\\\\\"YZX\\\\\\\",\\\\\\\"ZXY\\\\\\\",\\\\\\\"XZY\\\\\\\",\\\\\\\"YXZ\\\\\\\",\\\\\\\"ZYX\\\\\\\"]},function(t,e,s){\\\\\\\"use strict\\\\\\\";s.d(e,\\\\\\\"a\\\\\\\",(function(){return r})),s.d(e,\\\\\\\"b\\\\\\\",(function(){return i}));class i{constructor(t,e,s){const i=this;let r,n=!1,a=0,o=0;const h=[];this.onStart=void 0,this.onLoad=t,this.onProgress=e,this.onError=s,this.itemStart=function(t){o++,!1===n&&void 0!==i.onStart&&i.onStart(t,a,o),n=!0},this.itemEnd=function(t){a++,void 0!==i.onProgress&&i.onProgress(t,a,o),a===o&&(n=!1,void 0!==i.onLoad&&i.onLoad())},this.itemError=function(t){void 0!==i.onError&&i.onError(t)},this.resolveURL=function(t){return r?r(t):t},this.setURLModifier=function(t){return r=t,this},this.addHandler=function(t,e){return h.push(t,e),this},this.removeHandler=function(t){const e=h.indexOf(t);return-1!==e&&h.splice(e,2),this},this.getHandler=function(t){for(let e=0,s=h.length;e1?null:e.copy(s).multiplyScalar(r).add(t.start)}intersectsLine(t){const e=this.distanceToPoint(t.start),s=this.distanceToPoint(t.end);return e<0&&s>0||s<0&&e>0}intersectsBox(t){return t.intersectsPlane(this)}intersectsSphere(t){return t.intersectsPlane(this)}coplanarPoint(t){return t.copy(this.normal).multiplyScalar(-this.constant)}applyMatrix4(t,e){const s=e||o.getNormalMatrix(t),i=this.coplanarPoint(n).applyMatrix4(t),r=this.normal.applyMatrix3(s).normalize();return this.constant=-i.dot(r),this}translate(t){return this.constant-=t.dot(this.normal),this}equals(t){return t.normal.equals(this.normal)&&t.constant===this.constant}clone(){return(new this.constructor).copy(this)}}h.prototype.isPlane=!0},,function(t,e,s){\\\\\\\"use strict\\\\\\\";s.d(e,\\\\\\\"a\\\\\\\",(function(){return n}));var i=s(10),r=s(6);class n extends i.a{constructor(t,e=1){super(),this.type=\\\\\\\"Light\\\\\\\",this.color=new r.a(t),this.intensity=e}dispose(){}copy(t){return super.copy(t),this.color.copy(t.color),this.intensity=t.intensity,this}toJSON(t){const e=super.toJSON(t);return e.object.color=this.color.getHex(),e.object.intensity=this.intensity,void 0!==this.groundColor&&(e.object.groundColor=this.groundColor.getHex()),void 0!==this.distance&&(e.object.distance=this.distance),void 0!==this.angle&&(e.object.angle=this.angle),void 0!==this.decay&&(e.object.decay=this.decay),void 0!==this.penumbra&&(e.object.penumbra=this.penumbra),void 0!==this.shadow&&(e.object.shadow=this.shadow.toJSON()),e}}n.prototype.isLight=!0},function(t,e,s){\\\\\\\"use strict\\\\\\\";s.d(e,\\\\\\\"a\\\\\\\",(function(){return n}));var i=s(23),r=s(1);class n extends i.a{constructor(t=null,e=1,s=1,i,n,a,o,h,u=r.ob,c=r.ob,l,d){super(null,a,o,h,u,c,i,n,l,d),this.image={data:t,width:e,height:s},this.magFilter=u,this.minFilter=c,this.generateMipmaps=!1,this.flipY=!1,this.unpackAlignment=1,this.needsUpdate=!0}}n.prototype.isDataTexture=!0},function(t,e,s){\\\\\\\"use strict\\\\\\\";s.d(e,\\\\\\\"a\\\\\\\",(function(){return h}));var i=s(41),r=s(0),n=s(4);const a=new r.a,o=new r.a;class h extends i.a{constructor(t,e){super(t,e),this.type=\\\\\\\"LineSegments\\\\\\\"}computeLineDistances(){const t=this.geometry;if(t.isBufferGeometry)if(null===t.index){const e=t.attributes.position,s=[];for(let t=0,i=e.count;t=r)break t;{const a=e[1];t=r)break e}n=s,s=0}}for(;s>>1;t0)if(p=h*c-u,m=h*u-c,y=r*d,p>=0)if(m>=-y)if(m<=y){const t=1/d;p*=t,m*=t,f=p*(p+h*m+2*u)+m*(h*p+m+2*c)+l}else m=r,p=Math.max(0,-(h*m+u)),f=-p*p+m*(m+2*c)+l;else m=-r,p=Math.max(0,-(h*m+u)),f=-p*p+m*(m+2*c)+l;else m<=-y?(p=Math.max(0,-(-h*r+u)),m=p>0?-r:Math.min(Math.max(-r,-c),r),f=-p*p+m*(m+2*c)+l):m<=y?(p=0,m=Math.min(Math.max(-r,-c),r),f=m*(m+2*c)+l):(p=Math.max(0,-(h*r+u)),m=p>0?r:Math.min(Math.max(-r,-c),r),f=-p*p+m*(m+2*c)+l);else m=h>0?-r:r,p=Math.max(0,-(h*m+u)),f=-p*p+m*(m+2*c)+l;return s&&s.copy(this.direction).multiplyScalar(p).add(this.origin),i&&i.copy(a).multiplyScalar(m).add(n),f}intersectSphere(t,e){r.subVectors(t.center,this.origin);const s=r.dot(this.direction),i=r.dot(r)-s*s,n=t.radius*t.radius;if(i>n)return null;const a=Math.sqrt(n-i),o=s-a,h=s+a;return o<0&&h<0?null:o<0?this.at(h,e):this.at(o,e)}intersectsSphere(t){return this.distanceSqToPoint(t.center)<=t.radius*t.radius}distanceToPlane(t){const e=t.normal.dot(this.direction);if(0===e)return 0===t.distanceToPoint(this.origin)?0:null;const s=-(this.origin.dot(t.normal)+t.constant)/e;return s>=0?s:null}intersectPlane(t,e){const s=this.distanceToPlane(t);return null===s?null:this.at(s,e)}intersectsPlane(t){const e=t.distanceToPoint(this.origin);if(0===e)return!0;return t.normal.dot(this.direction)*e<0}intersectBox(t,e){let s,i,r,n,a,o;const h=1/this.direction.x,u=1/this.direction.y,c=1/this.direction.z,l=this.origin;return h>=0?(s=(t.min.x-l.x)*h,i=(t.max.x-l.x)*h):(s=(t.max.x-l.x)*h,i=(t.min.x-l.x)*h),u>=0?(r=(t.min.y-l.y)*u,n=(t.max.y-l.y)*u):(r=(t.max.y-l.y)*u,n=(t.min.y-l.y)*u),s>n||r>i?null:((r>s||s!=s)&&(s=r),(n=0?(a=(t.min.z-l.z)*c,o=(t.max.z-l.z)*c):(a=(t.max.z-l.z)*c,o=(t.min.z-l.z)*c),s>o||a>i?null:((a>s||s!=s)&&(s=a),(o=0?s:i,e)))}intersectsBox(t){return null!==this.intersectBox(t,r)}intersectTriangle(t,e,s,i,r){h.subVectors(e,t),u.subVectors(s,t),c.crossVectors(h,u);let n,a=this.direction.dot(c);if(a>0){if(i)return null;n=1}else{if(!(a<0))return null;n=-1,a=-a}o.subVectors(this.origin,t);const l=n*this.direction.dot(u.crossVectors(o,u));if(l<0)return null;const d=n*this.direction.dot(h.cross(o));if(d<0)return null;if(l+d>a)return null;const p=-n*o.dot(c);return p<0?null:this.at(p/a,r)}applyMatrix4(t){return this.origin.applyMatrix4(t),this.direction.transformDirection(t),this}equals(t){return t.origin.equals(this.origin)&&t.direction.equals(this.direction)}clone(){return(new this.constructor).copy(this)}}},function(t,e,s){\\\\\\\"use strict\\\\\\\";s.d(e,\\\\\\\"a\\\\\\\",(function(){return m}));var i=s(0);const r=new i.a,n=new i.a,a=new i.a,o=new i.a,h=new i.a,u=new i.a,c=new i.a,l=new i.a,d=new i.a,p=new i.a;class m{constructor(t=new i.a,e=new i.a,s=new i.a){this.a=t,this.b=e,this.c=s}static getNormal(t,e,s,i){i.subVectors(s,e),r.subVectors(t,e),i.cross(r);const n=i.lengthSq();return n>0?i.multiplyScalar(1/Math.sqrt(n)):i.set(0,0,0)}static getBarycoord(t,e,s,i,o){r.subVectors(i,e),n.subVectors(s,e),a.subVectors(t,e);const h=r.dot(r),u=r.dot(n),c=r.dot(a),l=n.dot(n),d=n.dot(a),p=h*l-u*u;if(0===p)return o.set(-2,-1,-1);const m=1/p,f=(l*c-u*d)*m,y=(h*d-u*c)*m;return o.set(1-f-y,y,f)}static containsPoint(t,e,s,i){return this.getBarycoord(t,e,s,i,o),o.x>=0&&o.y>=0&&o.x+o.y<=1}static getUV(t,e,s,i,r,n,a,h){return this.getBarycoord(t,e,s,i,o),h.set(0,0),h.addScaledVector(r,o.x),h.addScaledVector(n,o.y),h.addScaledVector(a,o.z),h}static isFrontFacing(t,e,s,i){return r.subVectors(s,e),n.subVectors(t,e),r.cross(n).dot(i)<0}set(t,e,s){return this.a.copy(t),this.b.copy(e),this.c.copy(s),this}setFromPointsAndIndices(t,e,s,i){return this.a.copy(t[e]),this.b.copy(t[s]),this.c.copy(t[i]),this}setFromAttributeAndIndices(t,e,s,i){return this.a.fromBufferAttribute(t,e),this.b.fromBufferAttribute(t,s),this.c.fromBufferAttribute(t,i),this}clone(){return(new this.constructor).copy(this)}copy(t){return this.a.copy(t.a),this.b.copy(t.b),this.c.copy(t.c),this}getArea(){return r.subVectors(this.c,this.b),n.subVectors(this.a,this.b),.5*r.cross(n).length()}getMidpoint(t){return t.addVectors(this.a,this.b).add(this.c).multiplyScalar(1/3)}getNormal(t){return m.getNormal(this.a,this.b,this.c,t)}getPlane(t){return t.setFromCoplanarPoints(this.a,this.b,this.c)}getBarycoord(t,e){return m.getBarycoord(t,this.a,this.b,this.c,e)}getUV(t,e,s,i,r){return m.getUV(t,this.a,this.b,this.c,e,s,i,r)}containsPoint(t){return m.containsPoint(t,this.a,this.b,this.c)}isFrontFacing(t){return m.isFrontFacing(this.a,this.b,this.c,t)}intersectsBox(t){return t.intersectsTriangle(this)}closestPointToPoint(t,e){const s=this.a,i=this.b,r=this.c;let n,a;h.subVectors(i,s),u.subVectors(r,s),l.subVectors(t,s);const o=h.dot(l),m=u.dot(l);if(o<=0&&m<=0)return e.copy(s);d.subVectors(t,i);const f=h.dot(d),y=u.dot(d);if(f>=0&&y<=f)return e.copy(i);const g=o*y-f*m;if(g<=0&&o>=0&&f<=0)return n=o/(o-f),e.copy(s).addScaledVector(h,n);p.subVectors(t,r);const x=h.dot(p),b=u.dot(p);if(b>=0&&x<=b)return e.copy(r);const M=x*m-o*b;if(M<=0&&m>=0&&b<=0)return a=m/(m-b),e.copy(s).addScaledVector(u,a);const w=f*b-x*y;if(w<=0&&y-f>=0&&x-b>=0)return c.subVectors(r,i),a=(y-f)/(y-f+(x-b)),e.copy(i).addScaledVector(c,a);const v=1/(w+M+g);return n=M*v,a=g*v,e.copy(s).addScaledVector(h,n).addScaledVector(u,a)}equals(t){return t.a.equals(this.a)&&t.b.equals(this.b)&&t.c.equals(this.c)}}},function(t,e,s){\\\\\\\"use strict\\\\\\\";s.d(e,\\\\\\\"a\\\\\\\",(function(){return y}));var i=s(18),r=s(39),n=s(5),a=s(10),o=s(0),h=s(24),u=s(7),c=s(4);const l=new o.a,d=new o.a,p=new n.a,m=new r.a,f=new i.a;class y extends a.a{constructor(t=new u.a,e=new h.a){super(),this.type=\\\\\\\"Line\\\\\\\",this.geometry=t,this.material=e,this.updateMorphTargets()}copy(t){return super.copy(t),this.material=t.material,this.geometry=t.geometry,this}computeLineDistances(){const t=this.geometry;if(t.isBufferGeometry)if(null===t.index){const e=t.attributes.position,s=[0];for(let t=1,i=e.count;th)continue;d.applyMatrix4(this.matrixWorld);const o=t.ray.origin.distanceTo(d);ot.far||e.push({distance:o,point:l.clone().applyMatrix4(this.matrixWorld),index:s,face:null,faceIndex:null,object:this})}}else{for(let s=Math.max(0,n.start),i=Math.min(r.count,n.start+n.count)-1;sh)continue;d.applyMatrix4(this.matrixWorld);const i=t.ray.origin.distanceTo(d);it.far||e.push({distance:i,point:l.clone().applyMatrix4(this.matrixWorld),index:s,face:null,faceIndex:null,object:this})}}}else s.isGeometry&&console.error(\\\\\\\"THREE.Line.raycast() no longer supports THREE.Geometry. Use THREE.BufferGeometry instead.\\\\\\\")}updateMorphTargets(){const t=this.geometry;if(t.isBufferGeometry){const e=t.morphAttributes,s=Object.keys(e);if(s.length>0){const t=e[s[0]];if(void 0!==t){this.morphTargetInfluences=[],this.morphTargetDictionary={};for(let e=0,s=t.length;e0&&console.error(\\\\\\\"THREE.Line.updateMorphTargets() does not support THREE.Geometry. Use THREE.BufferGeometry instead.\\\\\\\")}}}y.prototype.isLine=!0},function(t,e,s){\\\\\\\"use strict\\\\\\\";s.d(e,\\\\\\\"a\\\\\\\",(function(){return n}));var i=s(12),r=s(6);class n extends i.a{constructor(t){super(),this.type=\\\\\\\"PointsMaterial\\\\\\\",this.color=new r.a(16777215),this.map=null,this.alphaMap=null,this.size=1,this.sizeAttenuation=!0,this.setValues(t)}copy(t){return super.copy(t),this.color.copy(t.color),this.map=t.map,this.alphaMap=t.alphaMap,this.size=t.size,this.sizeAttenuation=t.sizeAttenuation,this}}n.prototype.isPointsMaterial=!0},function(t,e,s){\\\\\\\"use strict\\\\\\\";s.d(e,\\\\\\\"a\\\\\\\",(function(){return i}));class i{static decodeText(t){if(\\\\\\\"undefined\\\\\\\"!=typeof TextDecoder)return(new TextDecoder).decode(t);let e=\\\\\\\"\\\\\\\";for(let s=0,i=t.length;s0){const t=e[s[0]];if(void 0!==t){this.morphTargetInfluences=[],this.morphTargetDictionary={};for(let e=0,s=t.length;e0&&console.error(\\\\\\\"THREE.Points.updateMorphTargets() does not support THREE.Geometry. Use THREE.BufferGeometry instead.\\\\\\\")}}}function f(t,e,s,i,r,n,a){const h=l.distanceSqToPoint(t);if(hr.far)return;n.push({distance:u,distanceToRay:Math.sqrt(h),point:s,index:e,face:null,object:a})}}m.prototype.isPoints=!0},function(t,e,s){\\\\\\\"use strict\\\\\\\";s.d(e,\\\\\\\"a\\\\\\\",(function(){return r}));var i=s(26);class r extends i.a{}r.prototype.ValueTypeName=\\\\\\\"number\\\\\\\"},function(t,e,s){\\\\\\\"use strict\\\\\\\";s.d(e,\\\\\\\"a\\\\\\\",(function(){return r}));var i=s(26);class r extends i.a{}r.prototype.ValueTypeName=\\\\\\\"vector\\\\\\\"},function(t,e,s){\\\\\\\"use strict\\\\\\\";s.d(e,\\\\\\\"a\\\\\\\",(function(){return r}));var i=s(10);class r extends i.a{constructor(){super(),this.type=\\\\\\\"Bone\\\\\\\"}}r.prototype.isBone=!0},,function(t,e,s){\\\\\\\"use strict\\\\\\\";s.d(e,\\\\\\\"a\\\\\\\",(function(){return h}));var i=s(1),r=s(26),n=s(38),a=s(8);class o extends n.a{constructor(t,e,s,i){super(t,e,s,i)}interpolate_(t,e,s,i){const r=this.resultBuffer,n=this.sampleValues,o=this.valueSize,h=(s-e)/(i-e);let u=t*o;for(let t=u+o;u!==t;u+=4)a.a.slerpFlat(r,0,n,u-o,n,u,h);return r}}class h extends r.a{InterpolantFactoryMethodLinear(t){return new o(this.times,this.values,this.getValueSize(),t)}}h.prototype.ValueTypeName=\\\\\\\"quaternion\\\\\\\",h.prototype.DefaultInterpolation=i.P,h.prototype.InterpolantFactoryMethodSmooth=void 0},function(t,e,s){\\\\\\\"use strict\\\\\\\";s.d(e,\\\\\\\"a\\\\\\\",(function(){return o}));var i=s(1),r=s(12),n=s(2),a=s(6);class o extends r.a{constructor(t){super(),this.defines={STANDARD:\\\\\\\"\\\\\\\"},this.type=\\\\\\\"MeshStandardMaterial\\\\\\\",this.color=new a.a(16777215),this.roughness=1,this.metalness=0,this.map=null,this.lightMap=null,this.lightMapIntensity=1,this.aoMap=null,this.aoMapIntensity=1,this.emissive=new a.a(0),this.emissiveIntensity=1,this.emissiveMap=null,this.bumpMap=null,this.bumpScale=1,this.normalMap=null,this.normalMapType=i.Uc,this.normalScale=new n.a(1,1),this.displacementMap=null,this.displacementScale=1,this.displacementBias=0,this.roughnessMap=null,this.metalnessMap=null,this.alphaMap=null,this.envMap=null,this.envMapIntensity=1,this.refractionRatio=.98,this.wireframe=!1,this.wireframeLinewidth=1,this.wireframeLinecap=\\\\\\\"round\\\\\\\",this.wireframeLinejoin=\\\\\\\"round\\\\\\\",this.flatShading=!1,this.setValues(t)}copy(t){return super.copy(t),this.defines={STANDARD:\\\\\\\"\\\\\\\"},this.color.copy(t.color),this.roughness=t.roughness,this.metalness=t.metalness,this.map=t.map,this.lightMap=t.lightMap,this.lightMapIntensity=t.lightMapIntensity,this.aoMap=t.aoMap,this.aoMapIntensity=t.aoMapIntensity,this.emissive.copy(t.emissive),this.emissiveMap=t.emissiveMap,this.emissiveIntensity=t.emissiveIntensity,this.bumpMap=t.bumpMap,this.bumpScale=t.bumpScale,this.normalMap=t.normalMap,this.normalMapType=t.normalMapType,this.normalScale.copy(t.normalScale),this.displacementMap=t.displacementMap,this.displacementScale=t.displacementScale,this.displacementBias=t.displacementBias,this.roughnessMap=t.roughnessMap,this.metalnessMap=t.metalnessMap,this.alphaMap=t.alphaMap,this.envMap=t.envMap,this.envMapIntensity=t.envMapIntensity,this.refractionRatio=t.refractionRatio,this.wireframe=t.wireframe,this.wireframeLinewidth=t.wireframeLinewidth,this.wireframeLinecap=t.wireframeLinecap,this.wireframeLinejoin=t.wireframeLinejoin,this.flatShading=t.flatShading,this}}o.prototype.isMeshStandardMaterial=!0},,,function(t,e,s){\\\\\\\"use strict\\\\\\\";s.d(e,\\\\\\\"a\\\\\\\",(function(){return m}));var i=s(33),r=s(45),n=s(30),a=s(5),o=s(2),h=s(0),u=s(9);const c=new a.a,l=new h.a,d=new h.a;class p extends r.a{constructor(){super(new n.a(90,1,.5,500)),this._frameExtents=new o.a(4,2),this._viewportCount=6,this._viewports=[new u.a(2,1,1,1),new u.a(0,1,1,1),new u.a(3,1,1,1),new u.a(1,1,1,1),new u.a(3,0,1,1),new u.a(1,0,1,1)],this._cubeDirections=[new h.a(1,0,0),new h.a(-1,0,0),new h.a(0,0,1),new h.a(0,0,-1),new h.a(0,1,0),new h.a(0,-1,0)],this._cubeUps=[new h.a(0,1,0),new h.a(0,1,0),new h.a(0,1,0),new h.a(0,1,0),new h.a(0,0,1),new h.a(0,0,-1)]}updateMatrices(t,e=0){const s=this.camera,i=this.matrix,r=t.distance||s.far;r!==s.far&&(s.far=r,s.updateProjectionMatrix()),l.setFromMatrixPosition(t.matrixWorld),s.position.copy(l),d.copy(s.position),d.add(this._cubeDirections[e]),s.up.copy(this._cubeUps[e]),s.lookAt(d),s.updateMatrixWorld(),i.makeTranslation(-l.x,-l.y,-l.z),c.multiplyMatrices(s.projectionMatrix,s.matrixWorldInverse),this._frustum.setFromProjectionMatrix(c)}}p.prototype.isPointLightShadow=!0;class m extends i.a{constructor(t,e,s=0,i=1){super(t,e),this.type=\\\\\\\"PointLight\\\\\\\",this.distance=s,this.decay=i,this.shadow=new p}get power(){return 4*this.intensity*Math.PI}set power(t){this.intensity=t/(4*Math.PI)}dispose(){this.shadow.dispose()}copy(t){return super.copy(t),this.distance=t.distance,this.decay=t.decay,this.shadow=t.shadow.clone(),this}}m.prototype.isPointLight=!0},function(t,e,s){\\\\\\\"use strict\\\\\\\";s.d(e,\\\\\\\"a\\\\\\\",(function(){return o}));var i=s(2),r=s(55),n=s(6),a=s(3);class o extends r.a{constructor(t){super(),this.defines={STANDARD:\\\\\\\"\\\\\\\",PHYSICAL:\\\\\\\"\\\\\\\"},this.type=\\\\\\\"MeshPhysicalMaterial\\\\\\\",this.clearcoatMap=null,this.clearcoatRoughness=0,this.clearcoatRoughnessMap=null,this.clearcoatNormalScale=new i.a(1,1),this.clearcoatNormalMap=null,this.ior=1.5,Object.defineProperty(this,\\\\\\\"reflectivity\\\\\\\",{get:function(){return a.d(2.5*(this.ior-1)/(this.ior+1),0,1)},set:function(t){this.ior=(1+.4*t)/(1-.4*t)}}),this.sheenTint=new n.a(0),this.sheenRoughness=1,this.transmissionMap=null,this.thickness=.01,this.thicknessMap=null,this.attenuationDistance=0,this.attenuationTint=new n.a(1,1,1),this.specularIntensity=1,this.specularIntensityMap=null,this.specularTint=new n.a(1,1,1),this.specularTintMap=null,this._sheen=0,this._clearcoat=0,this._transmission=0,this.setValues(t)}get sheen(){return this._sheen}set sheen(t){this._sheen>0!=t>0&&this.version++,this._sheen=t}get clearcoat(){return this._clearcoat}set clearcoat(t){this._clearcoat>0!=t>0&&this.version++,this._clearcoat=t}get transmission(){return this._transmission}set transmission(t){this._transmission>0!=t>0&&this.version++,this._transmission=t}copy(t){return super.copy(t),this.defines={STANDARD:\\\\\\\"\\\\\\\",PHYSICAL:\\\\\\\"\\\\\\\"},this.clearcoat=t.clearcoat,this.clearcoatMap=t.clearcoatMap,this.clearcoatRoughness=t.clearcoatRoughness,this.clearcoatRoughnessMap=t.clearcoatRoughnessMap,this.clearcoatNormalMap=t.clearcoatNormalMap,this.clearcoatNormalScale.copy(t.clearcoatNormalScale),this.ior=t.ior,this.sheen=t.sheen,this.sheenTint.copy(t.sheenTint),this.sheenRoughness=t.sheenRoughness,this.transmission=t.transmission,this.transmissionMap=t.transmissionMap,this.thickness=t.thickness,this.thicknessMap=t.thicknessMap,this.attenuationDistance=t.attenuationDistance,this.attenuationTint.copy(t.attenuationTint),this.specularIntensity=t.specularIntensity,this.specularIntensityMap=t.specularIntensityMap,this.specularTint.copy(t.specularTint),this.specularTintMap=t.specularTintMap,this}}o.prototype.isMeshPhysicalMaterial=!0},function(t,e,s){\\\\\\\"use strict\\\\\\\";s.d(e,\\\\\\\"a\\\\\\\",(function(){return h}));var i=s(0),r=s(18),n=s(31);const a=new r.a,o=new i.a;class h{constructor(t=new n.a,e=new n.a,s=new n.a,i=new n.a,r=new n.a,a=new n.a){this.planes=[t,e,s,i,r,a]}set(t,e,s,i,r,n){const a=this.planes;return a[0].copy(t),a[1].copy(e),a[2].copy(s),a[3].copy(i),a[4].copy(r),a[5].copy(n),this}copy(t){const e=this.planes;for(let s=0;s<6;s++)e[s].copy(t.planes[s]);return this}setFromProjectionMatrix(t){const e=this.planes,s=t.elements,i=s[0],r=s[1],n=s[2],a=s[3],o=s[4],h=s[5],u=s[6],c=s[7],l=s[8],d=s[9],p=s[10],m=s[11],f=s[12],y=s[13],g=s[14],x=s[15];return e[0].setComponents(a-i,c-o,m-l,x-f).normalize(),e[1].setComponents(a+i,c+o,m+l,x+f).normalize(),e[2].setComponents(a+r,c+h,m+d,x+y).normalize(),e[3].setComponents(a-r,c-h,m-d,x-y).normalize(),e[4].setComponents(a-n,c-u,m-p,x-g).normalize(),e[5].setComponents(a+n,c+u,m+p,x+g).normalize(),this}intersectsObject(t){const e=t.geometry;return null===e.boundingSphere&&e.computeBoundingSphere(),a.copy(e.boundingSphere).applyMatrix4(t.matrixWorld),this.intersectsSphere(a)}intersectsSprite(t){return a.center.set(0,0,0),a.radius=.7071067811865476,a.applyMatrix4(t.matrixWorld),this.intersectsSphere(a)}intersectsSphere(t){const e=this.planes,s=t.center,i=-t.radius;for(let t=0;t<6;t++){if(e[t].distanceToPoint(s)0?t.max.x:t.min.x,o.y=i.normal.y>0?t.max.y:t.min.y,o.z=i.normal.z>0?t.max.z:t.min.z,i.distanceToPoint(o)<0)return!1}return!0}containsPoint(t){const e=this.planes;for(let s=0;s<6;s++)if(e[s].distanceToPoint(t)<0)return!1;return!0}clone(){return(new this.constructor).copy(this)}}},,,function(t,e,s){\\\\\\\"use strict\\\\\\\";s.d(e,\\\\\\\"a\\\\\\\",(function(){return a}));var i=s(17),r=s(13),n=s(20);class a extends r.a{constructor(t){super(t)}load(t,e,s,r){void 0!==this.path&&(t=this.path+t),t=this.manager.resolveURL(t);const a=this,o=i.a.get(t);if(void 0!==o)return a.manager.itemStart(t),setTimeout((function(){e&&e(o),a.manager.itemEnd(t)}),0),o;const h=Object(n.b)(\\\\\\\"img\\\\\\\");function u(){h.removeEventListener(\\\\\\\"load\\\\\\\",u,!1),h.removeEventListener(\\\\\\\"error\\\\\\\",c,!1),i.a.add(t,this),e&&e(this),a.manager.itemEnd(t)}function c(e){h.removeEventListener(\\\\\\\"load\\\\\\\",u,!1),h.removeEventListener(\\\\\\\"error\\\\\\\",c,!1),r&&r(e),a.manager.itemError(t),a.manager.itemEnd(t)}return h.addEventListener(\\\\\\\"load\\\\\\\",u,!1),h.addEventListener(\\\\\\\"error\\\\\\\",c,!1),\\\\\\\"data:\\\\\\\"!==t.substr(0,5)&&void 0!==this.crossOrigin&&(h.crossOrigin=this.crossOrigin),a.manager.itemStart(t),h.src=t,h}}},function(t,e,s){\\\\\\\"use strict\\\\\\\";s.d(e,\\\\\\\"a\\\\\\\",(function(){return p}));var i=s(19),r=s(26),n=s(1);class a extends r.a{}a.prototype.ValueTypeName=\\\\\\\"bool\\\\\\\",a.prototype.ValueBufferType=Array,a.prototype.DefaultInterpolation=n.O,a.prototype.InterpolantFactoryMethodLinear=void 0,a.prototype.InterpolantFactoryMethodSmooth=void 0;class o extends r.a{}o.prototype.ValueTypeName=\\\\\\\"color\\\\\\\";var h=s(50),u=s(54);class c extends r.a{}c.prototype.ValueTypeName=\\\\\\\"string\\\\\\\",c.prototype.ValueBufferType=Array,c.prototype.DefaultInterpolation=n.O,c.prototype.InterpolantFactoryMethodLinear=void 0,c.prototype.InterpolantFactoryMethodSmooth=void 0;var l=s(51),d=s(3);class p{constructor(t,e=-1,s,i=n.wb){this.name=t,this.tracks=s,this.duration=e,this.blendMode=i,this.uuid=d.h(),this.duration<0&&this.resetDuration()}static parse(t){const e=[],s=t.tracks,i=1/(t.fps||1);for(let t=0,r=s.length;t!==r;++t)e.push(m(s[t]).scale(i));const r=new this(t.name,t.duration,e,t.blendMode);return r.uuid=t.uuid,r}static toJSON(t){const e=[],s=t.tracks,i={name:t.name,duration:t.duration,tracks:e,uuid:t.uuid,blendMode:t.blendMode};for(let t=0,i=s.length;t!==i;++t)e.push(r.a.toJSON(s[t]));return i}static CreateFromMorphTargetSequence(t,e,s,r){const n=e.length,a=[];for(let t=0;t1){const t=n[1];let e=i[t];e||(i[t]=e=[]),e.push(s)}}const n=[];for(const t in i)n.push(this.CreateFromMorphTargetSequence(t,i[t],e,s));return n}static parseAnimation(t,e){if(!t)return console.error(\\\\\\\"THREE.AnimationClip: No animation in JSONLoader data.\\\\\\\"),null;const s=function(t,e,s,r,n){if(0!==s.length){const a=[],o=[];i.a.flattenJSON(s,a,o,r),0!==a.length&&n.push(new t(e,a,o))}},r=[],n=t.name||\\\\\\\"default\\\\\\\",a=t.fps||30,o=t.blendMode;let c=t.length||-1;const d=t.hierarchy||[];for(let t=0;t=2.0 are supported.\\\\\\\")));const h=new Wt(o,{path:e||this.resourcePath||\\\\\\\"\\\\\\\",crossOrigin:this.crossOrigin,requestHeader:this.requestHeader,manager:this.manager,ktx2Loader:this.ktx2Loader,meshoptDecoder:this.meshoptDecoder});h.fileLoader.setRequestHeader(this.requestHeader);for(let t=0;t=0&&void 0===a[e]&&console.warn('THREE.GLTFLoader: Unknown extension \\\\\\\"'+e+'\\\\\\\".')}}h.setExtensions(n),h.setPlugins(a),h.parse(s,i)}}function K(){let t={};return{get:function(e){return t[e]},add:function(e,s){t[e]=s},remove:function(e){delete t[e]},removeAll:function(){t={}}}}const Q={KHR_BINARY_GLTF:\\\\\\\"KHR_binary_glTF\\\\\\\",KHR_DRACO_MESH_COMPRESSION:\\\\\\\"KHR_draco_mesh_compression\\\\\\\",KHR_LIGHTS_PUNCTUAL:\\\\\\\"KHR_lights_punctual\\\\\\\",KHR_MATERIALS_CLEARCOAT:\\\\\\\"KHR_materials_clearcoat\\\\\\\",KHR_MATERIALS_IOR:\\\\\\\"KHR_materials_ior\\\\\\\",KHR_MATERIALS_PBR_SPECULAR_GLOSSINESS:\\\\\\\"KHR_materials_pbrSpecularGlossiness\\\\\\\",KHR_MATERIALS_SPECULAR:\\\\\\\"KHR_materials_specular\\\\\\\",KHR_MATERIALS_TRANSMISSION:\\\\\\\"KHR_materials_transmission\\\\\\\",KHR_MATERIALS_UNLIT:\\\\\\\"KHR_materials_unlit\\\\\\\",KHR_MATERIALS_VOLUME:\\\\\\\"KHR_materials_volume\\\\\\\",KHR_TEXTURE_BASISU:\\\\\\\"KHR_texture_basisu\\\\\\\",KHR_TEXTURE_TRANSFORM:\\\\\\\"KHR_texture_transform\\\\\\\",KHR_MESH_QUANTIZATION:\\\\\\\"KHR_mesh_quantization\\\\\\\",EXT_TEXTURE_WEBP:\\\\\\\"EXT_texture_webp\\\\\\\",EXT_MESHOPT_COMPRESSION:\\\\\\\"EXT_meshopt_compression\\\\\\\"};class ${constructor(t){this.parser=t,this.name=Q.KHR_LIGHTS_PUNCTUAL,this.cache={refs:{},uses:{}}}_markDefs(){const t=this.parser,e=this.parser.json.nodes||[];for(let s=0,i=e.length;s=0)throw new Error(\\\\\\\"THREE.GLTFLoader: setKTX2Loader must be called before loading KTX2 textures\\\\\\\");return null}return e.loadTextureImage(t,n,a)}}class ot{constructor(t){this.parser=t,this.name=Q.EXT_TEXTURE_WEBP,this.isSupported=null}loadTexture(t){const e=this.name,s=this.parser,i=s.json,r=i.textures[t];if(!r.extensions||!r.extensions[e])return null;const n=r.extensions[e],a=i.images[n.source];let o=s.textureLoader;if(a.uri){const t=s.options.manager.getHandler(a.uri);null!==t&&(o=t)}return this.detectSupport().then((function(r){if(r)return s.loadTextureImage(t,a,o);if(i.extensionsRequired&&i.extensionsRequired.indexOf(e)>=0)throw new Error(\\\\\\\"THREE.GLTFLoader: WebP required by asset but unsupported.\\\\\\\");return s.loadTexture(t)}))}detectSupport(){return this.isSupported||(this.isSupported=new Promise((function(t){const e=new Image;e.src=\\\\\\\"data:image/webp;base64,UklGRiIAAABXRUJQVlA4IBYAAAAwAQCdASoBAAEADsD+JaQAA3AAAAAA\\\\\\\",e.onload=e.onerror=function(){t(1===e.height)}}))),this.isSupported}}class ht{constructor(t){this.name=Q.EXT_MESHOPT_COMPRESSION,this.parser=t}loadBufferView(t){const e=this.parser.json,s=e.bufferViews[t];if(s.extensions&&s.extensions[this.name]){const t=s.extensions[this.name],i=this.parser.getDependency(\\\\\\\"buffer\\\\\\\",t.buffer),r=this.parser.options.meshoptDecoder;if(!r||!r.supported){if(e.extensionsRequired&&e.extensionsRequired.indexOf(this.name)>=0)throw new Error(\\\\\\\"THREE.GLTFLoader: setMeshoptDecoder must be called before loading compressed files\\\\\\\");return null}return Promise.all([i,r.ready]).then((function(e){const s=t.byteOffset||0,i=t.byteLength||0,n=t.count,a=t.byteStride,o=new ArrayBuffer(n*a),h=new Uint8Array(e[0],s,i);return r.decodeGltfBuffer(new Uint8Array(o),n,a,h,t.mode,t.filter),o}))}return null}}const ut=\\\\\\\"glTF\\\\\\\",ct=1313821514,lt=5130562;class dt{constructor(t){this.name=Q.KHR_BINARY_GLTF,this.content=null,this.body=null;const e=new DataView(t,0,12);if(this.header={magic:_.a.decodeText(new Uint8Array(t.slice(0,4))),version:e.getUint32(4,!0),length:e.getUint32(8,!0)},this.header.magic!==ut)throw new Error(\\\\\\\"THREE.GLTFLoader: Unsupported glTF-Binary header.\\\\\\\");if(this.header.version<2)throw new Error(\\\\\\\"THREE.GLTFLoader: Legacy binary file detected.\\\\\\\");const s=this.header.length-12,i=new DataView(t,12);let r=0;for(;r\\\\\\\",e).replace(\\\\\\\"#include \\\\\\\",s).replace(\\\\\\\"#include \\\\\\\",i).replace(\\\\\\\"#include \\\\\\\",r).replace(\\\\\\\"#include \\\\\\\",n)},Object.defineProperties(this,{specular:{get:function(){return a.specular.value},set:function(t){a.specular.value=t}},specularMap:{get:function(){return a.specularMap.value},set:function(t){a.specularMap.value=t,t?this.defines.USE_SPECULARMAP=\\\\\\\"\\\\\\\":delete this.defines.USE_SPECULARMAP}},glossiness:{get:function(){return a.glossiness.value},set:function(t){a.glossiness.value=t}},glossinessMap:{get:function(){return a.glossinessMap.value},set:function(t){a.glossinessMap.value=t,t?(this.defines.USE_GLOSSINESSMAP=\\\\\\\"\\\\\\\",this.defines.USE_UV=\\\\\\\"\\\\\\\"):(delete this.defines.USE_GLOSSINESSMAP,delete this.defines.USE_UV)}}}),delete this.metalness,delete this.roughness,delete this.metalnessMap,delete this.roughnessMap,this.setValues(t)}copy(t){return super.copy(t),this.specularMap=t.specularMap,this.specular.copy(t.specular),this.glossinessMap=t.glossinessMap,this.glossiness=t.glossiness,delete this.metalness,delete this.roughness,delete this.metalnessMap,delete this.roughnessMap,this}}class yt{constructor(){this.name=Q.KHR_MATERIALS_PBR_SPECULAR_GLOSSINESS,this.specularGlossinessParams=[\\\\\\\"color\\\\\\\",\\\\\\\"map\\\\\\\",\\\\\\\"lightMap\\\\\\\",\\\\\\\"lightMapIntensity\\\\\\\",\\\\\\\"aoMap\\\\\\\",\\\\\\\"aoMapIntensity\\\\\\\",\\\\\\\"emissive\\\\\\\",\\\\\\\"emissiveIntensity\\\\\\\",\\\\\\\"emissiveMap\\\\\\\",\\\\\\\"bumpMap\\\\\\\",\\\\\\\"bumpScale\\\\\\\",\\\\\\\"normalMap\\\\\\\",\\\\\\\"normalMapType\\\\\\\",\\\\\\\"displacementMap\\\\\\\",\\\\\\\"displacementScale\\\\\\\",\\\\\\\"displacementBias\\\\\\\",\\\\\\\"specularMap\\\\\\\",\\\\\\\"specular\\\\\\\",\\\\\\\"glossinessMap\\\\\\\",\\\\\\\"glossiness\\\\\\\",\\\\\\\"alphaMap\\\\\\\",\\\\\\\"envMap\\\\\\\",\\\\\\\"envMapIntensity\\\\\\\",\\\\\\\"refractionRatio\\\\\\\"]}getMaterialType(){return ft}extendParams(t,e,s){const i=e.extensions[this.name];t.color=new u.a(1,1,1),t.opacity=1;const r=[];if(Array.isArray(i.diffuseFactor)){const e=i.diffuseFactor;t.color.fromArray(e),t.opacity=e[3]}if(void 0!==i.diffuseTexture&&r.push(s.assignTexture(t,\\\\\\\"map\\\\\\\",i.diffuseTexture)),t.emissive=new u.a(0,0,0),t.glossiness=void 0!==i.glossinessFactor?i.glossinessFactor:1,t.specular=new u.a(1,1,1),Array.isArray(i.specularFactor)&&t.specular.fromArray(i.specularFactor),void 0!==i.specularGlossinessTexture){const e=i.specularGlossinessTexture;r.push(s.assignTexture(t,\\\\\\\"glossinessMap\\\\\\\",e)),r.push(s.assignTexture(t,\\\\\\\"specularMap\\\\\\\",e))}return Promise.all(r)}createMaterial(t){const e=new ft(t);return e.fog=!0,e.color=t.color,e.map=void 0===t.map?null:t.map,e.lightMap=null,e.lightMapIntensity=1,e.aoMap=void 0===t.aoMap?null:t.aoMap,e.aoMapIntensity=1,e.emissive=t.emissive,e.emissiveIntensity=1,e.emissiveMap=void 0===t.emissiveMap?null:t.emissiveMap,e.bumpMap=void 0===t.bumpMap?null:t.bumpMap,e.bumpScale=1,e.normalMap=void 0===t.normalMap?null:t.normalMap,e.normalMapType=h.Uc,t.normalScale&&(e.normalScale=t.normalScale),e.displacementMap=null,e.displacementScale=1,e.displacementBias=0,e.specularMap=void 0===t.specularMap?null:t.specularMap,e.specular=t.specular,e.glossinessMap=void 0===t.glossinessMap?null:t.glossinessMap,e.glossiness=t.glossiness,e.alphaMap=null,e.envMap=void 0===t.envMap?null:t.envMap,e.envMapIntensity=1,e.refractionRatio=.98,e}}class gt{constructor(){this.name=Q.KHR_MESH_QUANTIZATION}}class xt extends x.a{constructor(t,e,s,i){super(t,e,s,i)}copySampleValue_(t){const e=this.resultBuffer,s=this.sampleValues,i=this.valueSize,r=t*i*3+i;for(let t=0;t!==i;t++)e[t]=s[r+t];return e}}xt.prototype.beforeStart_=xt.prototype.copySampleValue_,xt.prototype.afterEnd_=xt.prototype.copySampleValue_,xt.prototype.interpolate_=function(t,e,s,i){const r=this.resultBuffer,n=this.sampleValues,a=this.valueSize,o=2*a,h=3*a,u=i-e,c=(s-e)/u,l=c*c,d=l*c,p=t*h,m=p-h,f=-2*d+3*l,y=d-l,g=1-f,x=y-l+c;for(let t=0;t!==a;t++){const e=n[m+t+a],s=n[m+t+o]*u,i=n[p+t+a],h=n[p+t]*u;r[t]=g*e+x*s+f*i+y*h}return r};const bt=new V.a;class Mt extends xt{interpolate_(t,e,s,i){const r=super.interpolate_(t,e,s,i);return bt.fromArray(r).normalize().toArray(r),r}}const wt=0,vt=1,_t=2,Tt=3,St=4,At=5,Et=6,zt={5120:Int8Array,5121:Uint8Array,5122:Int16Array,5123:Uint16Array,5125:Uint32Array,5126:Float32Array},Rt={9728:h.ob,9729:h.V,9984:h.sb,9985:h.Z,9986:h.rb,9987:h.Y},It={33071:h.n,33648:h.kb,10497:h.wc},kt={SCALAR:1,VEC2:2,VEC3:3,VEC4:4,MAT2:4,MAT3:9,MAT4:16},Lt={POSITION:\\\\\\\"position\\\\\\\",NORMAL:\\\\\\\"normal\\\\\\\",TANGENT:\\\\\\\"tangent\\\\\\\",TEXCOORD_0:\\\\\\\"uv\\\\\\\",TEXCOORD_1:\\\\\\\"uv2\\\\\\\",COLOR_0:\\\\\\\"color\\\\\\\",WEIGHTS_0:\\\\\\\"skinWeight\\\\\\\",JOINTS_0:\\\\\\\"skinIndex\\\\\\\"},Ot={scale:\\\\\\\"scale\\\\\\\",translation:\\\\\\\"position\\\\\\\",rotation:\\\\\\\"quaternion\\\\\\\",weights:\\\\\\\"morphTargetInfluences\\\\\\\"},Pt={CUBICSPLINE:void 0,LINEAR:h.P,STEP:h.O},Bt=\\\\\\\"OPAQUE\\\\\\\",Nt=\\\\\\\"MASK\\\\\\\",Ct=\\\\\\\"BLEND\\\\\\\";function Ft(t,e){return\\\\\\\"string\\\\\\\"!=typeof t||\\\\\\\"\\\\\\\"===t?\\\\\\\"\\\\\\\":(/^https?:\\\\/\\\\//i.test(e)&&/^\\\\//.test(t)&&(e=e.replace(/(^https?:\\\\/\\\\/[^\\\\/]+).*/i,\\\\\\\"$1\\\\\\\")),/^(https?:)?\\\\/\\\\//i.test(t)||/^data:.*,.*$/i.test(t)||/^blob:.*$/i.test(t)?t:e+t)}function Vt(t,e,s){for(const i in s.extensions)void 0===t[i]&&(e.userData.gltfExtensions=e.userData.gltfExtensions||{},e.userData.gltfExtensions[i]=s.extensions[i])}function Ht(t,e){void 0!==e.extras&&(\\\\\\\"object\\\\\\\"==typeof e.extras?Object.assign(t.userData,e.extras):console.warn(\\\\\\\"THREE.GLTFLoader: Ignoring primitive type .extras, \\\\\\\"+e.extras))}function Ut(t,e){if(t.updateMorphTargets(),void 0!==e.weights)for(let s=0,i=e.weights.length;s{const s=this.associations.get(t);null!=s&&this.associations.set(e,s);for(const[s,i]of t.children.entries())r(i,e.children[s])};return r(s,i),i.name+=\\\\\\\"_instance_\\\\\\\"+t.uses[e]++,i}_invokeOne(t){const e=Object.values(this.plugins);e.push(this);for(let s=0;s=2&&m.setY(e,l[t*n+1]),n>=3&&m.setZ(e,l[t*n+2]),n>=4&&m.setW(e,l[t*n+3]),n>=5)throw new Error(\\\\\\\"THREE.GLTFLoader: Unsupported itemSize in sparse BufferAttribute.\\\\\\\")}}return m}))}loadTexture(t){const e=this.json,s=this.options,i=e.textures[t],r=e.images[i.source];let n=this.textureLoader;if(r.uri){const t=s.manager.getHandler(r.uri);null!==t&&(n=t)}return this.loadTextureImage(t,r,n)}loadTextureImage(t,e,s){const i=this,r=this.json,n=this.options,a=r.textures[t],o=(e.uri||e.bufferView)+\\\\\\\":\\\\\\\"+a.sampler;if(this.textureCache[o])return this.textureCache[o];const u=self.URL||self.webkitURL;let c=e.uri||\\\\\\\"\\\\\\\",l=!1;if(void 0!==e.bufferView)c=i.getDependency(\\\\\\\"bufferView\\\\\\\",e.bufferView).then((function(t){l=!0;const s=new Blob([t],{type:e.mimeType});return c=u.createObjectURL(s),c}));else if(void 0===e.uri)throw new Error(\\\\\\\"THREE.GLTFLoader: Image \\\\\\\"+t+\\\\\\\" is missing URI and bufferView\\\\\\\");const d=Promise.resolve(c).then((function(t){return new Promise((function(e,i){let r=e;!0===s.isImageBitmapLoader&&(r=function(t){const s=new W.a(t);s.needsUpdate=!0,e(s)}),s.load(Ft(t,n.path),r,void 0,i)}))})).then((function(e){!0===l&&u.revokeObjectURL(c),e.flipY=!1,a.name&&(e.name=a.name);const s=(r.samplers||{})[a.sampler]||{};return e.magFilter=Rt[s.magFilter]||h.V,e.minFilter=Rt[s.minFilter]||h.Y,e.wrapS=It[s.wrapS]||h.wc,e.wrapT=It[s.wrapT]||h.wc,i.associations.set(e,{textures:t}),e})).catch((function(){return console.error(\\\\\\\"THREE.GLTFLoader: Couldn't load texture\\\\\\\",c),null}));return this.textureCache[o]=d,d}assignTexture(t,e,s){const i=this;return this.getDependency(\\\\\\\"texture\\\\\\\",s.index).then((function(r){if(void 0===s.texCoord||0==s.texCoord||\\\\\\\"aoMap\\\\\\\"===e&&1==s.texCoord||console.warn(\\\\\\\"THREE.GLTFLoader: Custom UV set 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t=i[Q.KHR_MATERIALS_UNLIT];n=t.getMaterialType(),c.push(t.extendParams(a,r,e))}else{const s=r.pbrMetallicRoughness||{};if(a.color=new u.a(1,1,1),a.opacity=1,Array.isArray(s.baseColorFactor)){const t=s.baseColorFactor;a.color.fromArray(t),a.opacity=t[3]}void 0!==s.baseColorTexture&&c.push(e.assignTexture(a,\\\\\\\"map\\\\\\\",s.baseColorTexture)),a.metalness=void 0!==s.metallicFactor?s.metallicFactor:1,a.roughness=void 0!==s.roughnessFactor?s.roughnessFactor:1,void 0!==s.metallicRoughnessTexture&&(c.push(e.assignTexture(a,\\\\\\\"metalnessMap\\\\\\\",s.metallicRoughnessTexture)),c.push(e.assignTexture(a,\\\\\\\"roughnessMap\\\\\\\",s.metallicRoughnessTexture))),n=this._invokeOne((function(e){return e.getMaterialType&&e.getMaterialType(t)})),c.push(Promise.all(this._invokeAll((function(e){return e.extendMaterialParams&&e.extendMaterialParams(t,a)}))))}!0===r.doubleSided&&(a.side=h.z);const l=r.alphaMode||Bt;if(l===Ct?(a.transparent=!0,a.depthWrite=!1):(a.format=h.ic,a.transparent=!1,l===Nt&&(a.alphaTest=void 0!==r.alphaCutoff?r.alphaCutoff:.5)),void 0!==r.normalTexture&&n!==z.a&&(c.push(e.assignTexture(a,\\\\\\\"normalMap\\\\\\\",r.normalTexture)),a.normalScale=new X.a(1,1),void 0!==r.normalTexture.scale)){const t=r.normalTexture.scale;a.normalScale.set(t,t)}return void 0!==r.occlusionTexture&&n!==z.a&&(c.push(e.assignTexture(a,\\\\\\\"aoMap\\\\\\\",r.occlusionTexture)),void 0!==r.occlusionTexture.strength&&(a.aoMapIntensity=r.occlusionTexture.strength)),void 0!==r.emissiveFactor&&n!==z.a&&(a.emissive=(new u.a).fromArray(r.emissiveFactor)),void 0!==r.emissiveTexture&&n!==z.a&&c.push(e.assignTexture(a,\\\\\\\"emissiveMap\\\\\\\",r.emissiveTexture)),Promise.all(c).then((function(){let s;return s=n===ft?i[Q.KHR_MATERIALS_PBR_SPECULAR_GLOSSINESS].createMaterial(a):new 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t.array.constructor(t.array),this.itemSize=t.itemSize,this.count=t.count,this.normalized=t.normalized,this.usage=t.usage,this}copyAt(t,e,n){t*=this.itemSize,n*=e.itemSize;for(let i=0,s=this.itemSize;i0&&console.error(\\\\\\\"THREE.Matrix4: the constructor no longer reads arguments. use .set() instead.\\\\\\\")}set(t,e,n,i,s,r,o,a,l,c,h,u,d,p,_,m){const f=this.elements;return f[0]=t,f[4]=e,f[8]=n,f[12]=i,f[1]=s,f[5]=r,f[9]=o,f[13]=a,f[2]=l,f[6]=c,f[10]=h,f[14]=u,f[3]=d,f[7]=p,f[11]=_,f[15]=m,this}identity(){return this.set(1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1),this}clone(){return(new s).fromArray(this.elements)}copy(t){const e=this.elements,n=t.elements;return e[0]=n[0],e[1]=n[1],e[2]=n[2],e[3]=n[3],e[4]=n[4],e[5]=n[5],e[6]=n[6],e[7]=n[7],e[8]=n[8],e[9]=n[9],e[10]=n[10],e[11]=n[11],e[12]=n[12],e[13]=n[13],e[14]=n[14],e[15]=n[15],this}copyPosition(t){const e=this.elements,n=t.elements;return e[12]=n[12],e[13]=n[13],e[14]=n[14],this}setFromMatrix3(t){const e=t.elements;return 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t=r*c,n=r*h,i=o*c,s=o*h;e[0]=a*c,e[4]=-a*h,e[8]=l,e[1]=n+i*l,e[5]=t-s*l,e[9]=-o*a,e[2]=s-t*l,e[6]=i+n*l,e[10]=r*a}else if(\\\\\\\"YXZ\\\\\\\"===t.order){const t=a*c,n=a*h,i=l*c,s=l*h;e[0]=t+s*o,e[4]=i*o-n,e[8]=r*l,e[1]=r*h,e[5]=r*c,e[9]=-o,e[2]=n*o-i,e[6]=s+t*o,e[10]=r*a}else if(\\\\\\\"ZXY\\\\\\\"===t.order){const t=a*c,n=a*h,i=l*c,s=l*h;e[0]=t-s*o,e[4]=-r*h,e[8]=i+n*o,e[1]=n+i*o,e[5]=r*c,e[9]=s-t*o,e[2]=-r*l,e[6]=o,e[10]=r*a}else if(\\\\\\\"ZYX\\\\\\\"===t.order){const t=r*c,n=r*h,i=o*c,s=o*h;e[0]=a*c,e[4]=i*l-n,e[8]=t*l+s,e[1]=a*h,e[5]=s*l+t,e[9]=n*l-i,e[2]=-l,e[6]=o*a,e[10]=r*a}else if(\\\\\\\"YZX\\\\\\\"===t.order){const t=r*a,n=r*l,i=o*a,s=o*l;e[0]=a*c,e[4]=s-t*h,e[8]=i*h+n,e[1]=h,e[5]=r*c,e[9]=-o*c,e[2]=-l*c,e[6]=n*h+i,e[10]=t-s*h}else if(\\\\\\\"XZY\\\\\\\"===t.order){const t=r*a,n=r*l,i=o*a,s=o*l;e[0]=a*c,e[4]=-h,e[8]=l*c,e[1]=t*h+s,e[5]=r*c,e[9]=n*h-i,e[2]=i*h-n,e[6]=o*c,e[10]=s*h+t}return e[3]=0,e[7]=0,e[11]=0,e[12]=0,e[13]=0,e[14]=0,e[15]=1,this}makeRotationFromQuaternion(t){return this.compose(a,t,l)}lookAt(t,e,n){const i=this.elements;return u.subVectors(t,e),0===u.lengthSq()&&(u.z=1),u.normalize(),c.crossVectors(n,u),0===c.lengthSq()&&(1===Math.abs(n.z)?u.x+=1e-4:u.z+=1e-4,u.normalize(),c.crossVectors(n,u)),c.normalize(),h.crossVectors(u,c),i[0]=c.x,i[4]=h.x,i[8]=u.x,i[1]=c.y,i[5]=h.y,i[9]=u.y,i[2]=c.z,i[6]=h.z,i[10]=u.z,this}multiply(t,e){return void 0!==e?(console.warn(\\\\\\\"THREE.Matrix4: .multiply() now only accepts one argument. Use .multiplyMatrices( a, b ) instead.\\\\\\\"),this.multiplyMatrices(t,e)):this.multiplyMatrices(this,t)}premultiply(t){return this.multiplyMatrices(t,this)}multiplyMatrices(t,e){const n=t.elements,i=e.elements,s=this.elements,r=n[0],o=n[4],a=n[8],l=n[12],c=n[1],h=n[5],u=n[9],d=n[13],p=n[2],_=n[6],m=n[10],f=n[14],g=n[3],v=n[7],y=n[11],x=n[15],b=i[0],w=i[4],T=i[8],A=i[12],M=i[1],E=i[5],S=i[9],C=i[13],N=i[2],L=i[6],O=i[10],P=i[14],R=i[3],I=i[7],F=i[11],D=i[15];return s[0]=r*b+o*M+a*N+l*R,s[4]=r*w+o*E+a*L+l*I,s[8]=r*T+o*S+a*O+l*F,s[12]=r*A+o*C+a*P+l*D,s[1]=c*b+h*M+u*N+d*R,s[5]=c*w+h*E+u*L+d*I,s[9]=c*T+h*S+u*O+d*F,s[13]=c*A+h*C+u*P+d*D,s[2]=p*b+_*M+m*N+f*R,s[6]=p*w+_*E+m*L+f*I,s[10]=p*T+_*S+m*O+f*F,s[14]=p*A+_*C+m*P+f*D,s[3]=g*b+v*M+y*N+x*R,s[7]=g*w+v*E+y*L+x*I,s[11]=g*T+v*S+y*O+x*F,s[15]=g*A+v*C+y*P+x*D,this}multiplyScalar(t){const e=this.elements;return e[0]*=t,e[4]*=t,e[8]*=t,e[12]*=t,e[1]*=t,e[5]*=t,e[9]*=t,e[13]*=t,e[2]*=t,e[6]*=t,e[10]*=t,e[14]*=t,e[3]*=t,e[7]*=t,e[11]*=t,e[15]*=t,this}determinant(){const t=this.elements,e=t[0],n=t[4],i=t[8],s=t[12],r=t[1],o=t[5],a=t[9],l=t[13],c=t[2],h=t[6],u=t[10],d=t[14];return t[3]*(+s*a*h-i*l*h-s*o*u+n*l*u+i*o*d-n*a*d)+t[7]*(+e*a*d-e*l*u+s*r*u-i*r*d+i*l*c-s*a*c)+t[11]*(+e*l*h-e*o*d-s*r*h+n*r*d+s*o*c-n*l*c)+t[15]*(-i*o*c-e*a*h+e*o*u+i*r*h-n*r*u+n*a*c)}transpose(){const t=this.elements;let e;return e=t[1],t[1]=t[4],t[4]=e,e=t[2],t[2]=t[8],t[8]=e,e=t[6],t[6]=t[9],t[9]=e,e=t[3],t[3]=t[12],t[12]=e,e=t[7],t[7]=t[13],t[13]=e,e=t[11],t[11]=t[14],t[14]=e,this}setPosition(t,e,n){const i=this.elements;return t.isVector3?(i[12]=t.x,i[13]=t.y,i[14]=t.z):(i[12]=t,i[13]=e,i[14]=n),this}invert(){const t=this.elements,e=t[0],n=t[1],i=t[2],s=t[3],r=t[4],o=t[5],a=t[6],l=t[7],c=t[8],h=t[9],u=t[10],d=t[11],p=t[12],_=t[13],m=t[14],f=t[15],g=h*m*l-_*u*l+_*a*d-o*m*d-h*a*f+o*u*f,v=p*u*l-c*m*l-p*a*d+r*m*d+c*a*f-r*u*f,y=c*_*l-p*h*l+p*o*d-r*_*d-c*o*f+r*h*f,x=p*h*a-c*_*a-p*o*u+r*_*u+c*o*m-r*h*m,b=e*g+n*v+i*y+s*x;if(0===b)return this.set(0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0);const w=1/b;return t[0]=g*w,t[1]=(_*u*s-h*m*s-_*i*d+n*m*d+h*i*f-n*u*f)*w,t[2]=(o*m*s-_*a*s+_*i*l-n*m*l-o*i*f+n*a*f)*w,t[3]=(h*a*s-o*u*s-h*i*l+n*u*l+o*i*d-n*a*d)*w,t[4]=v*w,t[5]=(c*m*s-p*u*s+p*i*d-e*m*d-c*i*f+e*u*f)*w,t[6]=(p*a*s-r*m*s-p*i*l+e*m*l+r*i*f-e*a*f)*w,t[7]=(r*u*s-c*a*s+c*i*l-e*u*l-r*i*d+e*a*d)*w,t[8]=y*w,t[9]=(p*h*s-c*_*s-p*n*d+e*_*d+c*n*f-e*h*f)*w,t[10]=(r*_*s-p*o*s+p*n*l-e*_*l-r*n*f+e*o*f)*w,t[11]=(c*o*s-r*h*s-c*n*l+e*h*l+r*n*d-e*o*d)*w,t[12]=x*w,t[13]=(c*_*i-p*h*i+p*n*u-e*_*u-c*n*m+e*h*m)*w,t[14]=(p*o*i-r*_*i-p*n*a+e*_*a+r*n*m-e*o*m)*w,t[15]=(r*h*i-c*o*i+c*n*a-e*h*a-r*n*u+e*o*u)*w,this}scale(t){const e=this.elements,n=t.x,i=t.y,s=t.z;return e[0]*=n,e[4]*=i,e[8]*=s,e[1]*=n,e[5]*=i,e[9]*=s,e[2]*=n,e[6]*=i,e[10]*=s,e[3]*=n,e[7]*=i,e[11]*=s,this}getMaxScaleOnAxis(){const t=this.elements,e=t[0]*t[0]+t[1]*t[1]+t[2]*t[2],n=t[4]*t[4]+t[5]*t[5]+t[6]*t[6],i=t[8]*t[8]+t[9]*t[9]+t[10]*t[10];return Math.sqrt(Math.max(e,n,i))}makeTranslation(t,e,n){return this.set(1,0,0,t,0,1,0,e,0,0,1,n,0,0,0,1),this}makeRotationX(t){const e=Math.cos(t),n=Math.sin(t);return this.set(1,0,0,0,0,e,-n,0,0,n,e,0,0,0,0,1),this}makeRotationY(t){const e=Math.cos(t),n=Math.sin(t);return this.set(e,0,n,0,0,1,0,0,-n,0,e,0,0,0,0,1),this}makeRotationZ(t){const e=Math.cos(t),n=Math.sin(t);return this.set(e,-n,0,0,n,e,0,0,0,0,1,0,0,0,0,1),this}makeRotationAxis(t,e){const n=Math.cos(e),i=Math.sin(e),s=1-n,r=t.x,o=t.y,a=t.z,l=s*r,c=s*o;return this.set(l*r+n,l*o-i*a,l*a+i*o,0,l*o+i*a,c*o+n,c*a-i*r,0,l*a-i*o,c*a+i*r,s*a*a+n,0,0,0,0,1),this}makeScale(t,e,n){return this.set(t,0,0,0,0,e,0,0,0,0,n,0,0,0,0,1),this}makeShear(t,e,n,i,s,r){return this.set(1,n,s,0,t,1,r,0,e,i,1,0,0,0,0,1),this}compose(t,e,n){const i=this.elements,s=e._x,r=e._y,o=e._z,a=e._w,l=s+s,c=r+r,h=o+o,u=s*l,d=s*c,p=s*h,_=r*c,m=r*h,f=o*h,g=a*l,v=a*c,y=a*h,x=n.x,b=n.y,w=n.z;return i[0]=(1-(_+f))*x,i[1]=(d+y)*x,i[2]=(p-v)*x,i[3]=0,i[4]=(d-y)*b,i[5]=(1-(u+f))*b,i[6]=(m+g)*b,i[7]=0,i[8]=(p+v)*w,i[9]=(m-g)*w,i[10]=(1-(u+_))*w,i[11]=0,i[12]=t.x,i[13]=t.y,i[14]=t.z,i[15]=1,this}decompose(t,e,n){const i=this.elements;let s=r.set(i[0],i[1],i[2]).length();const a=r.set(i[4],i[5],i[6]).length(),l=r.set(i[8],i[9],i[10]).length();this.determinant()<0&&(s=-s),t.x=i[12],t.y=i[13],t.z=i[14],o.copy(this);const c=1/s,h=1/a,u=1/l;return o.elements[0]*=c,o.elements[1]*=c,o.elements[2]*=c,o.elements[4]*=h,o.elements[5]*=h,o.elements[6]*=h,o.elements[8]*=u,o.elements[9]*=u,o.elements[10]*=u,e.setFromRotationMatrix(o),n.x=s,n.y=a,n.z=l,this}makePerspective(t,e,n,i,s,r){void 0===r&&console.warn(\\\\\\\"THREE.Matrix4: .makePerspective() has been redefined and has a new signature. Please check the docs.\\\\\\\");const o=this.elements,a=2*s/(e-t),l=2*s/(n-i),c=(e+t)/(e-t),h=(n+i)/(n-i),u=-(r+s)/(r-s),d=-2*r*s/(r-s);return o[0]=a,o[4]=0,o[8]=c,o[12]=0,o[1]=0,o[5]=l,o[9]=h,o[13]=0,o[2]=0,o[6]=0,o[10]=u,o[14]=d,o[3]=0,o[7]=0,o[11]=-1,o[15]=0,this}makeOrthographic(t,e,n,i,s,r){const o=this.elements,a=1/(e-t),l=1/(n-i),c=1/(r-s),h=(e+t)*a,u=(n+i)*l,d=(r+s)*c;return o[0]=2*a,o[4]=0,o[8]=0,o[12]=-h,o[1]=0,o[5]=2*l,o[9]=0,o[13]=-u,o[2]=0,o[6]=0,o[10]=-2*c,o[14]=-d,o[3]=0,o[7]=0,o[11]=0,o[15]=1,this}equals(t){const e=this.elements,n=t.elements;for(let t=0;t<16;t++)if(e[t]!==n[t])return!1;return!0}fromArray(t,e=0){for(let n=0;n<16;n++)this.elements[n]=t[n+e];return this}toArray(t=[],e=0){const n=this.elements;return t[e]=n[0],t[e+1]=n[1],t[e+2]=n[2],t[e+3]=n[3],t[e+4]=n[4],t[e+5]=n[5],t[e+6]=n[6],t[e+7]=n[7],t[e+8]=n[8],t[e+9]=n[9],t[e+10]=n[10],t[e+11]=n[11],t[e+12]=n[12],t[e+13]=n[13],t[e+14]=n[14],t[e+15]=n[15],t}}s.prototype.isMatrix4=!0;const r=new i.a,o=new s,a=new i.a(0,0,0),l=new i.a(1,1,1),c=new i.a,h=new i.a,u=new i.a},function(t,e,n){\\\\\\\"use strict\\\\\\\";n.d(e,\\\\\\\"a\\\\\\\",(function(){return h}));var i=n(3);const s={aliceblue:15792383,antiquewhite:16444375,aqua:65535,aquamarine:8388564,azure:15794175,beige:16119260,bisque:16770244,black:0,blanchedalmond:16772045,blue:255,blueviolet:9055202,brown:10824234,burlywood:14596231,cadetblue:6266528,chartreuse:8388352,chocolate:13789470,coral:16744272,cornflowerblue:6591981,cornsilk:16775388,crimson:14423100,cyan:65535,darkblue:139,darkcyan:35723,darkgoldenrod:12092939,darkgray:11119017,darkgreen:25600,darkgrey:11119017,darkkhaki:12433259,darkmagenta:9109643,darkolivegreen:5597999,darkorange:16747520,darkorchid:10040012,darkred:9109504,darksalmon:15308410,darkseagreen:9419919,darkslateblue:4734347,darkslategray:3100495,darkslategrey:3100495,darkturquoise:52945,darkviolet:9699539,deeppink:16716947,deepskyblue:49151,dimgray:6908265,dimgrey:6908265,dodgerblue:2003199,firebrick:11674146,floralwhite:16775920,forestgreen:2263842,fuchsia:16711935,gainsboro:14474460,ghostwhite:16316671,gold:16766720,goldenrod:14329120,gray:8421504,green:32768,greenyellow:11403055,grey:8421504,honeydew:15794160,hotpink:16738740,indianred:13458524,indigo:4915330,ivory:16777200,khaki:15787660,lavender:15132410,lavenderblush:16773365,lawngreen:8190976,lemonchiffon:16775885,lightblue:11393254,lightcoral:15761536,lightcyan:14745599,lightgoldenrodyellow:16448210,lightgray:13882323,lightgreen:9498256,lightgrey:13882323,lightpink:16758465,lightsalmon:16752762,lightseagreen:2142890,lightskyblue:8900346,lightslategray:7833753,lightslategrey:7833753,lightsteelblue:11584734,lightyellow:16777184,lime:65280,limegreen:3329330,linen:16445670,magenta:16711935,maroon:8388608,mediumaquamarine:6737322,mediumblue:205,mediumorchid:12211667,mediumpurple:9662683,mediumseagreen:3978097,mediumslateblue:8087790,mediumspringgreen:64154,mediumturquoise:4772300,mediumvioletred:13047173,midnightblue:1644912,mintcream:16121850,mistyrose:16770273,moccasin:16770229,navajowhite:16768685,navy:128,oldlace:16643558,olive:8421376,olivedrab:7048739,orange:16753920,orangered:16729344,orchid:14315734,palegoldenrod:15657130,palegreen:10025880,paleturquoise:11529966,palevioletred:14381203,papayawhip:16773077,peachpuff:16767673,peru:13468991,pink:16761035,plum:14524637,powderblue:11591910,purple:8388736,rebeccapurple:6697881,red:16711680,rosybrown:12357519,royalblue:4286945,saddlebrown:9127187,salmon:16416882,sandybrown:16032864,seagreen:3050327,seashell:16774638,sienna:10506797,silver:12632256,skyblue:8900331,slateblue:6970061,slategray:7372944,slategrey:7372944,snow:16775930,springgreen:65407,steelblue:4620980,tan:13808780,teal:32896,thistle:14204888,tomato:16737095,turquoise:4251856,violet:15631086,wheat:16113331,white:16777215,whitesmoke:16119285,yellow:16776960,yellowgreen:10145074},r={h:0,s:0,l:0},o={h:0,s:0,l:0};function a(t,e,n){return n<0&&(n+=1),n>1&&(n-=1),n<1/6?t+6*(e-t)*n:n<.5?e:n<2/3?t+6*(e-t)*(2/3-n):t}function l(t){return t<.04045?.0773993808*t:Math.pow(.9478672986*t+.0521327014,2.4)}function c(t){return t<.0031308?12.92*t:1.055*Math.pow(t,.41666)-.055}class h{constructor(t,e,n){return void 0===e&&void 0===n?this.set(t):this.setRGB(t,e,n)}set(t){return t&&t.isColor?this.copy(t):\\\\\\\"number\\\\\\\"==typeof t?this.setHex(t):\\\\\\\"string\\\\\\\"==typeof t&&this.setStyle(t),this}setScalar(t){return this.r=t,this.g=t,this.b=t,this}setHex(t){return t=Math.floor(t),this.r=(t>>16&255)/255,this.g=(t>>8&255)/255,this.b=(255&t)/255,this}setRGB(t,e,n){return this.r=t,this.g=e,this.b=n,this}setHSL(t,e,n){if(t=i.f(t,1),e=i.d(e,0,1),n=i.d(n,0,1),0===e)this.r=this.g=this.b=n;else{const i=n<=.5?n*(1+e):n+e-n*e,s=2*n-i;this.r=a(s,i,t+1/3),this.g=a(s,i,t),this.b=a(s,i,t-1/3)}return this}setStyle(t){function e(e){void 0!==e&&parseFloat(e)<1&&console.warn(\\\\\\\"THREE.Color: Alpha component of \\\\\\\"+t+\\\\\\\" will be ignored.\\\\\\\")}let n;if(n=/^((?:rgb|hsl)a?)\\\\(([^\\\\)]*)\\\\)/.exec(t)){let t;const i=n[1],s=n[2];switch(i){case\\\\\\\"rgb\\\\\\\":case\\\\\\\"rgba\\\\\\\":if(t=/^\\\\s*(\\\\d+)\\\\s*,\\\\s*(\\\\d+)\\\\s*,\\\\s*(\\\\d+)\\\\s*(?:,\\\\s*(\\\\d*\\\\.?\\\\d+)\\\\s*)?$/.exec(s))return this.r=Math.min(255,parseInt(t[1],10))/255,this.g=Math.min(255,parseInt(t[2],10))/255,this.b=Math.min(255,parseInt(t[3],10))/255,e(t[4]),this;if(t=/^\\\\s*(\\\\d+)\\\\%\\\\s*,\\\\s*(\\\\d+)\\\\%\\\\s*,\\\\s*(\\\\d+)\\\\%\\\\s*(?:,\\\\s*(\\\\d*\\\\.?\\\\d+)\\\\s*)?$/.exec(s))return this.r=Math.min(100,parseInt(t[1],10))/100,this.g=Math.min(100,parseInt(t[2],10))/100,this.b=Math.min(100,parseInt(t[3],10))/100,e(t[4]),this;break;case\\\\\\\"hsl\\\\\\\":case\\\\\\\"hsla\\\\\\\":if(t=/^\\\\s*(\\\\d*\\\\.?\\\\d+)\\\\s*,\\\\s*(\\\\d+)\\\\%\\\\s*,\\\\s*(\\\\d+)\\\\%\\\\s*(?:,\\\\s*(\\\\d*\\\\.?\\\\d+)\\\\s*)?$/.exec(s)){const n=parseFloat(t[1])/360,i=parseInt(t[2],10)/100,s=parseInt(t[3],10)/100;return e(t[4]),this.setHSL(n,i,s)}}}else if(n=/^\\\\#([A-Fa-f\\\\d]+)$/.exec(t)){const t=n[1],e=t.length;if(3===e)return this.r=parseInt(t.charAt(0)+t.charAt(0),16)/255,this.g=parseInt(t.charAt(1)+t.charAt(1),16)/255,this.b=parseInt(t.charAt(2)+t.charAt(2),16)/255,this;if(6===e)return this.r=parseInt(t.charAt(0)+t.charAt(1),16)/255,this.g=parseInt(t.charAt(2)+t.charAt(3),16)/255,this.b=parseInt(t.charAt(4)+t.charAt(5),16)/255,this}return t&&t.length>0?this.setColorName(t):this}setColorName(t){const e=s[t.toLowerCase()];return void 0!==e?this.setHex(e):console.warn(\\\\\\\"THREE.Color: Unknown color \\\\\\\"+t),this}clone(){return new this.constructor(this.r,this.g,this.b)}copy(t){return this.r=t.r,this.g=t.g,this.b=t.b,this}copyGammaToLinear(t,e=2){return this.r=Math.pow(t.r,e),this.g=Math.pow(t.g,e),this.b=Math.pow(t.b,e),this}copyLinearToGamma(t,e=2){const n=e>0?1/e:1;return this.r=Math.pow(t.r,n),this.g=Math.pow(t.g,n),this.b=Math.pow(t.b,n),this}convertGammaToLinear(t){return this.copyGammaToLinear(this,t),this}convertLinearToGamma(t){return this.copyLinearToGamma(this,t),this}copySRGBToLinear(t){return this.r=l(t.r),this.g=l(t.g),this.b=l(t.b),this}copyLinearToSRGB(t){return this.r=c(t.r),this.g=c(t.g),this.b=c(t.b),this}convertSRGBToLinear(){return this.copySRGBToLinear(this),this}convertLinearToSRGB(){return this.copyLinearToSRGB(this),this}getHex(){return 255*this.r<<16^255*this.g<<8^255*this.b<<0}getHexString(){return(\\\\\\\"000000\\\\\\\"+this.getHex().toString(16)).slice(-6)}getHSL(t){const e=this.r,n=this.g,i=this.b,s=Math.max(e,n,i),r=Math.min(e,n,i);let o,a;const l=(r+s)/2;if(r===s)o=0,a=0;else{const t=s-r;switch(a=l<=.5?t/(s+r):t/(2-s-r),s){case e:o=(n-i)/t+(n65535?a.i:a.h)(t,1):this.index=t,this}getAttribute(t){return this.attributes[t]}setAttribute(t,e){return this.attributes[t]=e,this}deleteAttribute(t){return delete this.attributes[t],this}hasAttribute(t){return void 0!==this.attributes[t]}addGroup(t,e,n=0){this.groups.push({start:t,count:e,materialIndex:n})}clearGroups(){this.groups=[]}setDrawRange(t,e){this.drawRange.start=t,this.drawRange.count=e}applyMatrix4(t){const e=this.attributes.position;void 0!==e&&(e.applyMatrix4(t),e.needsUpdate=!0);const n=this.attributes.normal;if(void 0!==n){const e=(new u.a).getNormalMatrix(t);n.applyNormalMatrix(e),n.needsUpdate=!0}const i=this.attributes.tangent;return void 0!==i&&(i.transformDirection(t),i.needsUpdate=!0),null!==this.boundingBox&&this.computeBoundingBox(),null!==this.boundingSphere&&this.computeBoundingSphere(),this}applyQuaternion(t){return m.makeRotationFromQuaternion(t),this.applyMatrix4(m),this}rotateX(t){return m.makeRotationX(t),this.applyMatrix4(m),this}rotateY(t){return m.makeRotationY(t),this.applyMatrix4(m),this}rotateZ(t){return m.makeRotationZ(t),this.applyMatrix4(m),this}translate(t,e,n){return m.makeTranslation(t,e,n),this.applyMatrix4(m),this}scale(t,e,n){return m.makeScale(t,e,n),this.applyMatrix4(m),this}lookAt(t){return f.lookAt(t),f.updateMatrix(),this.applyMatrix4(f.matrix),this}center(){return this.computeBoundingBox(),this.boundingBox.getCenter(g).negate(),this.translate(g.x,g.y,g.z),this}setFromPoints(t){const e=[];for(let n=0,i=t.length;n0&&(t.userData=this.userData),void 0!==this.parameters){const e=this.parameters;for(const n in e)void 0!==e[n]&&(t[n]=e[n]);return t}t.data={attributes:{}};const e=this.index;null!==e&&(t.data.index={type:e.array.constructor.name,array:Array.prototype.slice.call(e.array)});const n=this.attributes;for(const e in n){const i=n[e];t.data.attributes[e]=i.toJSON(t.data)}const i={};let s=!1;for(const e in this.morphAttributes){const n=this.morphAttributes[e],r=[];for(let e=0,i=n.length;e0&&(i[e]=r,s=!0)}s&&(t.data.morphAttributes=i,t.data.morphTargetsRelative=this.morphTargetsRelative);const r=this.groups;r.length>0&&(t.data.groups=JSON.parse(JSON.stringify(r)));const o=this.boundingSphere;return null!==o&&(t.data.boundingSphere={center:o.center.toArray(),radius:o.radius}),t}clone(){return(new this.constructor).copy(this)}copy(t){this.index=null,this.attributes={},this.morphAttributes={},this.groups=[],this.boundingBox=null,this.boundingSphere=null;const e={};this.name=t.name;const n=t.index;null!==n&&this.setIndex(n.clone(e));const i=t.attributes;for(const t in i){const n=i[t];this.setAttribute(t,n.clone(e))}const s=t.morphAttributes;for(const t in s){const n=[],i=s[t];for(let t=0,s=i.length;t=0?1:-1,i=1-e*e;if(i>Number.EPSILON){const s=Math.sqrt(i),r=Math.atan2(s,e*n);t=Math.sin(t*r)/s,o=Math.sin(o*r)/s}const s=o*n;if(a=a*t+u*s,l=l*t+d*s,c=c*t+p*s,h=h*t+_*s,t===1-o){const t=1/Math.sqrt(a*a+l*l+c*c+h*h);a*=t,l*=t,c*=t,h*=t}}t[e]=a,t[e+1]=l,t[e+2]=c,t[e+3]=h}static multiplyQuaternionsFlat(t,e,n,i,s,r){const o=n[i],a=n[i+1],l=n[i+2],c=n[i+3],h=s[r],u=s[r+1],d=s[r+2],p=s[r+3];return t[e]=o*p+c*h+a*d-l*u,t[e+1]=a*p+c*u+l*h-o*d,t[e+2]=l*p+c*d+o*u-a*h,t[e+3]=c*p-o*h-a*u-l*d,t}get x(){return this._x}set x(t){this._x=t,this._onChangeCallback()}get y(){return this._y}set y(t){this._y=t,this._onChangeCallback()}get z(){return this._z}set z(t){this._z=t,this._onChangeCallback()}get w(){return this._w}set w(t){this._w=t,this._onChangeCallback()}set(t,e,n,i){return this._x=t,this._y=e,this._z=n,this._w=i,this._onChangeCallback(),this}clone(){return new this.constructor(this._x,this._y,this._z,this._w)}copy(t){return this._x=t.x,this._y=t.y,this._z=t.z,this._w=t.w,this._onChangeCallback(),this}setFromEuler(t,e){if(!t||!t.isEuler)throw new Error(\\\\\\\"THREE.Quaternion: .setFromEuler() now expects an Euler rotation rather than a Vector3 and order.\\\\\\\");const n=t._x,i=t._y,s=t._z,r=t._order,o=Math.cos,a=Math.sin,l=o(n/2),c=o(i/2),h=o(s/2),u=a(n/2),d=a(i/2),p=a(s/2);switch(r){case\\\\\\\"XYZ\\\\\\\":this._x=u*c*h+l*d*p,this._y=l*d*h-u*c*p,this._z=l*c*p+u*d*h,this._w=l*c*h-u*d*p;break;case\\\\\\\"YXZ\\\\\\\":this._x=u*c*h+l*d*p,this._y=l*d*h-u*c*p,this._z=l*c*p-u*d*h,this._w=l*c*h+u*d*p;break;case\\\\\\\"ZXY\\\\\\\":this._x=u*c*h-l*d*p,this._y=l*d*h+u*c*p,this._z=l*c*p+u*d*h,this._w=l*c*h-u*d*p;break;case\\\\\\\"ZYX\\\\\\\":this._x=u*c*h-l*d*p,this._y=l*d*h+u*c*p,this._z=l*c*p-u*d*h,this._w=l*c*h+u*d*p;break;case\\\\\\\"YZX\\\\\\\":this._x=u*c*h+l*d*p,this._y=l*d*h+u*c*p,this._z=l*c*p-u*d*h,this._w=l*c*h-u*d*p;break;case\\\\\\\"XZY\\\\\\\":this._x=u*c*h-l*d*p,this._y=l*d*h-u*c*p,this._z=l*c*p+u*d*h,this._w=l*c*h+u*d*p;break;default:console.warn(\\\\\\\"THREE.Quaternion: .setFromEuler() encountered an unknown order: \\\\\\\"+r)}return!1!==e&&this._onChangeCallback(),this}setFromAxisAngle(t,e){const n=e/2,i=Math.sin(n);return this._x=t.x*i,this._y=t.y*i,this._z=t.z*i,this._w=Math.cos(n),this._onChangeCallback(),this}setFromRotationMatrix(t){const e=t.elements,n=e[0],i=e[4],s=e[8],r=e[1],o=e[5],a=e[9],l=e[2],c=e[6],h=e[10],u=n+o+h;if(u>0){const t=.5/Math.sqrt(u+1);this._w=.25/t,this._x=(c-a)*t,this._y=(s-l)*t,this._z=(r-i)*t}else if(n>o&&n>h){const t=2*Math.sqrt(1+n-o-h);this._w=(c-a)/t,this._x=.25*t,this._y=(i+r)/t,this._z=(s+l)/t}else if(o>h){const t=2*Math.sqrt(1+o-n-h);this._w=(s-l)/t,this._x=(i+r)/t,this._y=.25*t,this._z=(a+c)/t}else{const t=2*Math.sqrt(1+h-n-o);this._w=(r-i)/t,this._x=(s+l)/t,this._y=(a+c)/t,this._z=.25*t}return this._onChangeCallback(),this}setFromUnitVectors(t,e){let n=t.dot(e)+1;return nMath.abs(t.z)?(this._x=-t.y,this._y=t.x,this._z=0,this._w=n):(this._x=0,this._y=-t.z,this._z=t.y,this._w=n)):(this._x=t.y*e.z-t.z*e.y,this._y=t.z*e.x-t.x*e.z,this._z=t.x*e.y-t.y*e.x,this._w=n),this.normalize()}angleTo(t){return 2*Math.acos(Math.abs(i.d(this.dot(t),-1,1)))}rotateTowards(t,e){const n=this.angleTo(t);if(0===n)return this;const i=Math.min(1,e/n);return this.slerp(t,i),this}identity(){return this.set(0,0,0,1)}invert(){return this.conjugate()}conjugate(){return this._x*=-1,this._y*=-1,this._z*=-1,this._onChangeCallback(),this}dot(t){return this._x*t._x+this._y*t._y+this._z*t._z+this._w*t._w}lengthSq(){return this._x*this._x+this._y*this._y+this._z*this._z+this._w*this._w}length(){return Math.sqrt(this._x*this._x+this._y*this._y+this._z*this._z+this._w*this._w)}normalize(){let t=this.length();return 0===t?(this._x=0,this._y=0,this._z=0,this._w=1):(t=1/t,this._x=this._x*t,this._y=this._y*t,this._z=this._z*t,this._w=this._w*t),this._onChangeCallback(),this}multiply(t,e){return void 0!==e?(console.warn(\\\\\\\"THREE.Quaternion: .multiply() now only accepts one argument. Use .multiplyQuaternions( a, b ) instead.\\\\\\\"),this.multiplyQuaternions(t,e)):this.multiplyQuaternions(this,t)}premultiply(t){return this.multiplyQuaternions(t,this)}multiplyQuaternions(t,e){const n=t._x,i=t._y,s=t._z,r=t._w,o=e._x,a=e._y,l=e._z,c=e._w;return this._x=n*c+r*o+i*l-s*a,this._y=i*c+r*a+s*o-n*l,this._z=s*c+r*l+n*a-i*o,this._w=r*c-n*o-i*a-s*l,this._onChangeCallback(),this}slerp(t,e){if(0===e)return this;if(1===e)return this.copy(t);const n=this._x,i=this._y,s=this._z,r=this._w;let o=r*t._w+n*t._x+i*t._y+s*t._z;if(o<0?(this._w=-t._w,this._x=-t._x,this._y=-t._y,this._z=-t._z,o=-o):this.copy(t),o>=1)return this._w=r,this._x=n,this._y=i,this._z=s,this;const a=1-o*o;if(a<=Number.EPSILON){const t=1-e;return this._w=t*r+e*this._w,this._x=t*n+e*this._x,this._y=t*i+e*this._y,this._z=t*s+e*this._z,this.normalize(),this._onChangeCallback(),this}const l=Math.sqrt(a),c=Math.atan2(l,o),h=Math.sin((1-e)*c)/l,u=Math.sin(e*c)/l;return this._w=r*h+this._w*u,this._x=n*h+this._x*u,this._y=i*h+this._y*u,this._z=s*h+this._z*u,this._onChangeCallback(),this}slerpQuaternions(t,e,n){this.copy(t).slerp(e,n)}random(){const t=Math.random(),e=Math.sqrt(1-t),n=Math.sqrt(t),i=2*Math.PI*Math.random(),s=2*Math.PI*Math.random();return this.set(e*Math.cos(i),n*Math.sin(s),n*Math.cos(s),e*Math.sin(i))}equals(t){return t._x===this._x&&t._y===this._y&&t._z===this._z&&t._w===this._w}fromArray(t,e=0){return this._x=t[e],this._y=t[e+1],this._z=t[e+2],this._w=t[e+3],this._onChangeCallback(),this}toArray(t=[],e=0){return t[e]=this._x,t[e+1]=this._y,t[e+2]=this._z,t[e+3]=this._w,t}fromBufferAttribute(t,e){return this._x=t.getX(e),this._y=t.getY(e),this._z=t.getZ(e),this._w=t.getW(e),this}_onChange(t){return this._onChangeCallback=t,this}_onChangeCallback(){}}s.prototype.isQuaternion=!0},function(t,e,n){\\\\\\\"use strict\\\\\\\";n.d(e,\\\\\\\"a\\\\\\\",(function(){return i}));class i{constructor(t=0,e=0,n=0,i=1){this.x=t,this.y=e,this.z=n,this.w=i}get width(){return this.z}set width(t){this.z=t}get height(){return this.w}set height(t){this.w=t}set(t,e,n,i){return this.x=t,this.y=e,this.z=n,this.w=i,this}setScalar(t){return this.x=t,this.y=t,this.z=t,this.w=t,this}setX(t){return this.x=t,this}setY(t){return this.y=t,this}setZ(t){return this.z=t,this}setW(t){return this.w=t,this}setComponent(t,e){switch(t){case 0:this.x=e;break;case 1:this.y=e;break;case 2:this.z=e;break;case 3:this.w=e;break;default:throw new Error(\\\\\\\"index is out of range: \\\\\\\"+t)}return this}getComponent(t){switch(t){case 0:return this.x;case 1:return this.y;case 2:return this.z;case 3:return this.w;default:throw new Error(\\\\\\\"index is out of range: \\\\\\\"+t)}}clone(){return new this.constructor(this.x,this.y,this.z,this.w)}copy(t){return this.x=t.x,this.y=t.y,this.z=t.z,this.w=void 0!==t.w?t.w:1,this}add(t,e){return void 0!==e?(console.warn(\\\\\\\"THREE.Vector4: .add() now only accepts one argument. Use .addVectors( a, b ) instead.\\\\\\\"),this.addVectors(t,e)):(this.x+=t.x,this.y+=t.y,this.z+=t.z,this.w+=t.w,this)}addScalar(t){return this.x+=t,this.y+=t,this.z+=t,this.w+=t,this}addVectors(t,e){return this.x=t.x+e.x,this.y=t.y+e.y,this.z=t.z+e.z,this.w=t.w+e.w,this}addScaledVector(t,e){return this.x+=t.x*e,this.y+=t.y*e,this.z+=t.z*e,this.w+=t.w*e,this}sub(t,e){return void 0!==e?(console.warn(\\\\\\\"THREE.Vector4: .sub() now only accepts one argument. Use .subVectors( a, b ) instead.\\\\\\\"),this.subVectors(t,e)):(this.x-=t.x,this.y-=t.y,this.z-=t.z,this.w-=t.w,this)}subScalar(t){return this.x-=t,this.y-=t,this.z-=t,this.w-=t,this}subVectors(t,e){return this.x=t.x-e.x,this.y=t.y-e.y,this.z=t.z-e.z,this.w=t.w-e.w,this}multiply(t){return this.x*=t.x,this.y*=t.y,this.z*=t.z,this.w*=t.w,this}multiplyScalar(t){return this.x*=t,this.y*=t,this.z*=t,this.w*=t,this}applyMatrix4(t){const e=this.x,n=this.y,i=this.z,s=this.w,r=t.elements;return this.x=r[0]*e+r[4]*n+r[8]*i+r[12]*s,this.y=r[1]*e+r[5]*n+r[9]*i+r[13]*s,this.z=r[2]*e+r[6]*n+r[10]*i+r[14]*s,this.w=r[3]*e+r[7]*n+r[11]*i+r[15]*s,this}divideScalar(t){return this.multiplyScalar(1/t)}setAxisAngleFromQuaternion(t){this.w=2*Math.acos(t.w);const e=Math.sqrt(1-t.w*t.w);return e<1e-4?(this.x=1,this.y=0,this.z=0):(this.x=t.x/e,this.y=t.y/e,this.z=t.z/e),this}setAxisAngleFromRotationMatrix(t){let e,n,i,s;const r=.01,o=.1,a=t.elements,l=a[0],c=a[4],h=a[8],u=a[1],d=a[5],p=a[9],_=a[2],m=a[6],f=a[10];if(Math.abs(c-u)a&&t>g?tg?a1){for(let t=0;t1){for(let t=0;t0){i.children=[];for(let e=0;e0){i.animations=[];for(let e=0;e0&&(n.geometries=e),i.length>0&&(n.materials=i),s.length>0&&(n.textures=s),o.length>0&&(n.images=o),a.length>0&&(n.shapes=a),l.length>0&&(n.skeletons=l),c.length>0&&(n.animations=c)}return n.object=i,n;function r(t){const e=[];for(const n in t){const i=t[n];delete i.metadata,e.push(i)}return e}}clone(t){return(new this.constructor).copy(this,t)}copy(t,e=!0){if(this.name=t.name,this.up.copy(t.up),this.position.copy(t.position),this.rotation.order=t.rotation.order,this.quaternion.copy(t.quaternion),this.scale.copy(t.scale),this.matrix.copy(t.matrix),this.matrixWorld.copy(t.matrixWorld),this.matrixAutoUpdate=t.matrixAutoUpdate,this.matrixWorldNeedsUpdate=t.matrixWorldNeedsUpdate,this.layers.mask=t.layers.mask,this.visible=t.visible,this.castShadow=t.castShadow,this.receiveShadow=t.receiveShadow,this.frustumCulled=t.frustumCulled,this.renderOrder=t.renderOrder,this.userData=JSON.parse(JSON.stringify(t.userData)),!0===e)for(let e=0;e0&&console.error(\\\\\\\"THREE.Matrix3: the constructor no longer reads arguments. use .set() instead.\\\\\\\")}set(t,e,n,i,s,r,o,a,l){const c=this.elements;return c[0]=t,c[1]=i,c[2]=o,c[3]=e,c[4]=s,c[5]=a,c[6]=n,c[7]=r,c[8]=l,this}identity(){return this.set(1,0,0,0,1,0,0,0,1),this}copy(t){const e=this.elements,n=t.elements;return e[0]=n[0],e[1]=n[1],e[2]=n[2],e[3]=n[3],e[4]=n[4],e[5]=n[5],e[6]=n[6],e[7]=n[7],e[8]=n[8],this}extractBasis(t,e,n){return t.setFromMatrix3Column(this,0),e.setFromMatrix3Column(this,1),n.setFromMatrix3Column(this,2),this}setFromMatrix4(t){const e=t.elements;return this.set(e[0],e[4],e[8],e[1],e[5],e[9],e[2],e[6],e[10]),this}multiply(t){return this.multiplyMatrices(this,t)}premultiply(t){return this.multiplyMatrices(t,this)}multiplyMatrices(t,e){const n=t.elements,i=e.elements,s=this.elements,r=n[0],o=n[3],a=n[6],l=n[1],c=n[4],h=n[7],u=n[2],d=n[5],p=n[8],_=i[0],m=i[3],f=i[6],g=i[1],v=i[4],y=i[7],x=i[2],b=i[5],w=i[8];return s[0]=r*_+o*g+a*x,s[3]=r*m+o*v+a*b,s[6]=r*f+o*y+a*w,s[1]=l*_+c*g+h*x,s[4]=l*m+c*v+h*b,s[7]=l*f+c*y+h*w,s[2]=u*_+d*g+p*x,s[5]=u*m+d*v+p*b,s[8]=u*f+d*y+p*w,this}multiplyScalar(t){const e=this.elements;return e[0]*=t,e[3]*=t,e[6]*=t,e[1]*=t,e[4]*=t,e[7]*=t,e[2]*=t,e[5]*=t,e[8]*=t,this}determinant(){const t=this.elements,e=t[0],n=t[1],i=t[2],s=t[3],r=t[4],o=t[5],a=t[6],l=t[7],c=t[8];return e*r*c-e*o*l-n*s*c+n*o*a+i*s*l-i*r*a}invert(){const t=this.elements,e=t[0],n=t[1],i=t[2],s=t[3],r=t[4],o=t[5],a=t[6],l=t[7],c=t[8],h=c*r-o*l,u=o*a-c*s,d=l*s-r*a,p=e*h+n*u+i*d;if(0===p)return this.set(0,0,0,0,0,0,0,0,0);const _=1/p;return t[0]=h*_,t[1]=(i*l-c*n)*_,t[2]=(o*n-i*r)*_,t[3]=u*_,t[4]=(c*e-i*a)*_,t[5]=(i*s-o*e)*_,t[6]=d*_,t[7]=(n*a-l*e)*_,t[8]=(r*e-n*s)*_,this}transpose(){let t;const e=this.elements;return t=e[1],e[1]=e[3],e[3]=t,t=e[2],e[2]=e[6],e[6]=t,t=e[5],e[5]=e[7],e[7]=t,this}getNormalMatrix(t){return this.setFromMatrix4(t).invert().transpose()}transposeIntoArray(t){const e=this.elements;return t[0]=e[0],t[1]=e[3],t[2]=e[6],t[3]=e[1],t[4]=e[4],t[5]=e[7],t[6]=e[2],t[7]=e[5],t[8]=e[8],this}setUvTransform(t,e,n,i,s,r,o){const a=Math.cos(s),l=Math.sin(s);return this.set(n*a,n*l,-n*(a*r+l*o)+r+t,-i*l,i*a,-i*(-l*r+a*o)+o+e,0,0,1),this}scale(t,e){const n=this.elements;return n[0]*=t,n[3]*=t,n[6]*=t,n[1]*=e,n[4]*=e,n[7]*=e,this}rotate(t){const e=Math.cos(t),n=Math.sin(t),i=this.elements,s=i[0],r=i[3],o=i[6],a=i[1],l=i[4],c=i[7];return i[0]=e*s+n*a,i[3]=e*r+n*l,i[6]=e*o+n*c,i[1]=-n*s+e*a,i[4]=-n*r+e*l,i[7]=-n*o+e*c,this}translate(t,e){const n=this.elements;return n[0]+=t*n[2],n[3]+=t*n[5],n[6]+=t*n[8],n[1]+=e*n[2],n[4]+=e*n[5],n[7]+=e*n[8],this}equals(t){const e=this.elements,n=t.elements;for(let t=0;t<9;t++)if(e[t]!==n[t])return!1;return!0}fromArray(t,e=0){for(let n=0;n<9;n++)this.elements[n]=t[n+e];return this}toArray(t=[],e=0){const n=this.elements;return t[e]=n[0],t[e+1]=n[1],t[e+2]=n[2],t[e+3]=n[3],t[e+4]=n[4],t[e+5]=n[5],t[e+6]=n[6],t[e+7]=n[7],t[e+8]=n[8],t}clone(){return(new this.constructor).fromArray(this.elements)}}i.prototype.isMatrix3=!0},function(t,e,n){\\\\\\\"use strict\\\\\\\";n.d(e,\\\\\\\"a\\\\\\\",(function(){return a}));var i=n(15),s=n(1),r=n(3);let o=0;class a extends i.a{constructor(){super(),Object.defineProperty(this,\\\\\\\"id\\\\\\\",{value:o++}),this.uuid=r.h(),this.name=\\\\\\\"\\\\\\\",this.type=\\\\\\\"Material\\\\\\\",this.fog=!0,this.blending=s.xb,this.side=s.H,this.vertexColors=!1,this.opacity=1,this.format=s.Ib,this.transparent=!1,this.blendSrc=s.Nc,this.blendDst=s.Db,this.blendEquation=s.b,this.blendSrcAlpha=null,this.blendDstAlpha=null,this.blendEquationAlpha=null,this.depthFunc=s.T,this.depthTest=!0,this.depthWrite=!0,this.stencilWriteMask=255,this.stencilFunc=s.h,this.stencilRef=0,this.stencilFuncMask=255,this.stencilFail=s.R,this.stencilZFail=s.R,this.stencilZPass=s.R,this.stencilWrite=!1,this.clippingPlanes=null,this.clipIntersection=!1,this.clipShadows=!1,this.shadowSide=null,this.colorWrite=!0,this.precision=null,this.polygonOffset=!1,this.polygonOffsetFactor=0,this.polygonOffsetUnits=0,this.dithering=!1,this.alphaToCoverage=!1,this.premultipliedAlpha=!1,this.visible=!0,this.toneMapped=!0,this.userData={},this.version=0,this._alphaTest=0}get alphaTest(){return this._alphaTest}set alphaTest(t){this._alphaTest>0!=t>0&&this.version++,this._alphaTest=t}onBuild(){}onBeforeRender(){}onBeforeCompile(){}customProgramCacheKey(){return this.onBeforeCompile.toString()}setValues(t){if(void 0!==t)for(const e in t){const n=t[e];if(void 0===n){console.warn(\\\\\\\"THREE.Material: '\\\\\\\"+e+\\\\\\\"' parameter is undefined.\\\\\\\");continue}if(\\\\\\\"shading\\\\\\\"===e){console.warn(\\\\\\\"THREE.\\\\\\\"+this.type+\\\\\\\": .shading has been removed. Use the boolean .flatShading instead.\\\\\\\"),this.flatShading=n===s.F;continue}const i=this[e];void 0!==i?i&&i.isColor?i.set(n):i&&i.isVector3&&n&&n.isVector3?i.copy(n):this[e]=n:console.warn(\\\\\\\"THREE.\\\\\\\"+this.type+\\\\\\\": '\\\\\\\"+e+\\\\\\\"' is not a property of this material.\\\\\\\")}}toJSON(t){const e=void 0===t||\\\\\\\"string\\\\\\\"==typeof t;e&&(t={textures:{},images:{}});const n={metadata:{version:4.5,type:\\\\\\\"Material\\\\\\\",generator:\\\\\\\"Material.toJSON\\\\\\\"}};function i(t){const e=[];for(const n in t){const i=t[n];delete i.metadata,e.push(i)}return e}if(n.uuid=this.uuid,n.type=this.type,\\\\\\\"\\\\\\\"!==this.name&&(n.name=this.name),this.color&&this.color.isColor&&(n.color=this.color.getHex()),void 0!==this.roughness&&(n.roughness=this.roughness),void 0!==this.metalness&&(n.metalness=this.metalness),void 0!==this.sheen&&(n.sheen=this.sheen),this.sheenTint&&this.sheenTint.isColor&&(n.sheenTint=this.sheenTint.getHex()),void 0!==this.sheenRoughness&&(n.sheenRoughness=this.sheenRoughness),this.emissive&&this.emissive.isColor&&(n.emissive=this.emissive.getHex()),this.emissiveIntensity&&1!==this.emissiveIntensity&&(n.emissiveIntensity=this.emissiveIntensity),this.specular&&this.specular.isColor&&(n.specular=this.specular.getHex()),void 0!==this.specularIntensity&&(n.specularIntensity=this.specularIntensity),this.specularTint&&this.specularTint.isColor&&(n.specularTint=this.specularTint.getHex()),void 0!==this.shininess&&(n.shininess=this.shininess),void 0!==this.clearcoat&&(n.clearcoat=this.clearcoat),void 0!==this.clearcoatRoughness&&(n.clearcoatRoughness=this.clearcoatRoughness),this.clearcoatMap&&this.clearcoatMap.isTexture&&(n.clearcoatMap=this.clearcoatMap.toJSON(t).uuid),this.clearcoatRoughnessMap&&this.clearcoatRoughnessMap.isTexture&&(n.clearcoatRoughnessMap=this.clearcoatRoughnessMap.toJSON(t).uuid),this.clearcoatNormalMap&&this.clearcoatNormalMap.isTexture&&(n.clearcoatNormalMap=this.clearcoatNormalMap.toJSON(t).uuid,n.clearcoatNormalScale=this.clearcoatNormalScale.toArray()),this.map&&this.map.isTexture&&(n.map=this.map.toJSON(t).uuid),this.matcap&&this.matcap.isTexture&&(n.matcap=this.matcap.toJSON(t).uuid),this.alphaMap&&this.alphaMap.isTexture&&(n.alphaMap=this.alphaMap.toJSON(t).uuid),this.lightMap&&this.lightMap.isTexture&&(n.lightMap=this.lightMap.toJSON(t).uuid,n.lightMapIntensity=this.lightMapIntensity),this.aoMap&&this.aoMap.isTexture&&(n.aoMap=this.aoMap.toJSON(t).uuid,n.aoMapIntensity=this.aoMapIntensity),this.bumpMap&&this.bumpMap.isTexture&&(n.bumpMap=this.bumpMap.toJSON(t).uuid,n.bumpScale=this.bumpScale),this.normalMap&&this.normalMap.isTexture&&(n.normalMap=this.normalMap.toJSON(t).uuid,n.normalMapType=this.normalMapType,n.normalScale=this.normalScale.toArray()),this.displacementMap&&this.displacementMap.isTexture&&(n.displacementMap=this.displacementMap.toJSON(t).uuid,n.displacementScale=this.displacementScale,n.displacementBias=this.displacementBias),this.roughnessMap&&this.roughnessMap.isTexture&&(n.roughnessMap=this.roughnessMap.toJSON(t).uuid),this.metalnessMap&&this.metalnessMap.isTexture&&(n.metalnessMap=this.metalnessMap.toJSON(t).uuid),this.emissiveMap&&this.emissiveMap.isTexture&&(n.emissiveMap=this.emissiveMap.toJSON(t).uuid),this.specularMap&&this.specularMap.isTexture&&(n.specularMap=this.specularMap.toJSON(t).uuid),this.specularIntensityMap&&this.specularIntensityMap.isTexture&&(n.specularIntensityMap=this.specularIntensityMap.toJSON(t).uuid),this.specularTintMap&&this.specularTintMap.isTexture&&(n.specularTintMap=this.specularTintMap.toJSON(t).uuid),this.envMap&&this.envMap.isTexture&&(n.envMap=this.envMap.toJSON(t).uuid,void 0!==this.combine&&(n.combine=this.combine)),void 0!==this.envMapIntensity&&(n.envMapIntensity=this.envMapIntensity),void 0!==this.reflectivity&&(n.reflectivity=this.reflectivity),void 0!==this.refractionRatio&&(n.refractionRatio=this.refractionRatio),this.gradientMap&&this.gradientMap.isTexture&&(n.gradientMap=this.gradientMap.toJSON(t).uuid),void 0!==this.transmission&&(n.transmission=this.transmission),this.transmissionMap&&this.transmissionMap.isTexture&&(n.transmissionMap=this.transmissionMap.toJSON(t).uuid),void 0!==this.thickness&&(n.thickness=this.thickness),this.thicknessMap&&this.thicknessMap.isTexture&&(n.thicknessMap=this.thicknessMap.toJSON(t).uuid),void 0!==this.attenuationDistance&&(n.attenuationDistance=this.attenuationDistance),void 0!==this.attenuationTint&&(n.attenuationTint=this.attenuationTint.getHex()),void 0!==this.size&&(n.size=this.size),null!==this.shadowSide&&(n.shadowSide=this.shadowSide),void 0!==this.sizeAttenuation&&(n.sizeAttenuation=this.sizeAttenuation),this.blending!==s.xb&&(n.blending=this.blending),this.side!==s.H&&(n.side=this.side),this.vertexColors&&(n.vertexColors=!0),this.opacity<1&&(n.opacity=this.opacity),this.format!==s.Ib&&(n.format=this.format),!0===this.transparent&&(n.transparent=this.transparent),n.depthFunc=this.depthFunc,n.depthTest=this.depthTest,n.depthWrite=this.depthWrite,n.colorWrite=this.colorWrite,n.stencilWrite=this.stencilWrite,n.stencilWriteMask=this.stencilWriteMask,n.stencilFunc=this.stencilFunc,n.stencilRef=this.stencilRef,n.stencilFuncMask=this.stencilFuncMask,n.stencilFail=this.stencilFail,n.stencilZFail=this.stencilZFail,n.stencilZPass=this.stencilZPass,this.rotation&&0!==this.rotation&&(n.rotation=this.rotation),!0===this.polygonOffset&&(n.polygonOffset=!0),0!==this.polygonOffsetFactor&&(n.polygonOffsetFactor=this.polygonOffsetFactor),0!==this.polygonOffsetUnits&&(n.polygonOffsetUnits=this.polygonOffsetUnits),this.linewidth&&1!==this.linewidth&&(n.linewidth=this.linewidth),void 0!==this.dashSize&&(n.dashSize=this.dashSize),void 0!==this.gapSize&&(n.gapSize=this.gapSize),void 0!==this.scale&&(n.scale=this.scale),!0===this.dithering&&(n.dithering=!0),this.alphaTest>0&&(n.alphaTest=this.alphaTest),!0===this.alphaToCoverage&&(n.alphaToCoverage=this.alphaToCoverage),!0===this.premultipliedAlpha&&(n.premultipliedAlpha=this.premultipliedAlpha),!0===this.wireframe&&(n.wireframe=this.wireframe),this.wireframeLinewidth>1&&(n.wireframeLinewidth=this.wireframeLinewidth),\\\\\\\"round\\\\\\\"!==this.wireframeLinecap&&(n.wireframeLinecap=this.wireframeLinecap),\\\\\\\"round\\\\\\\"!==this.wireframeLinejoin&&(n.wireframeLinejoin=this.wireframeLinejoin),!0===this.flatShading&&(n.flatShading=this.flatShading),!1===this.visible&&(n.visible=!1),!1===this.toneMapped&&(n.toneMapped=!1),\\\\\\\"{}\\\\\\\"!==JSON.stringify(this.userData)&&(n.userData=this.userData),e){const e=i(t.textures),s=i(t.images);e.length>0&&(n.textures=e),s.length>0&&(n.images=s)}return n}clone(){return(new this.constructor).copy(this)}copy(t){this.name=t.name,this.fog=t.fog,this.blending=t.blending,this.side=t.side,this.vertexColors=t.vertexColors,this.opacity=t.opacity,this.format=t.format,this.transparent=t.transparent,this.blendSrc=t.blendSrc,this.blendDst=t.blendDst,this.blendEquation=t.blendEquation,this.blendSrcAlpha=t.blendSrcAlpha,this.blendDstAlpha=t.blendDstAlpha,this.blendEquationAlpha=t.blendEquationAlpha,this.depthFunc=t.depthFunc,this.depthTest=t.depthTest,this.depthWrite=t.depthWrite,this.stencilWriteMask=t.stencilWriteMask,this.stencilFunc=t.stencilFunc,this.stencilRef=t.stencilRef,this.stencilFuncMask=t.stencilFuncMask,this.stencilFail=t.stencilFail,this.stencilZFail=t.stencilZFail,this.stencilZPass=t.stencilZPass,this.stencilWrite=t.stencilWrite;const e=t.clippingPlanes;let n=null;if(null!==e){const t=e.length;n=new Array(t);for(let i=0;i!==t;++i)n[i]=e[i].clone()}return this.clippingPlanes=n,this.clipIntersection=t.clipIntersection,this.clipShadows=t.clipShadows,this.shadowSide=t.shadowSide,this.colorWrite=t.colorWrite,this.precision=t.precision,this.polygonOffset=t.polygonOffset,this.polygonOffsetFactor=t.polygonOffsetFactor,this.polygonOffsetUnits=t.polygonOffsetUnits,this.dithering=t.dithering,this.alphaTest=t.alphaTest,this.alphaToCoverage=t.alphaToCoverage,this.premultipliedAlpha=t.premultipliedAlpha,this.visible=t.visible,this.toneMapped=t.toneMapped,this.userData=JSON.parse(JSON.stringify(t.userData)),this}dispose(){this.dispatchEvent({type:\\\\\\\"dispose\\\\\\\"})}set needsUpdate(t){!0===t&&this.version++}}a.prototype.isMaterial=!0},function(t,e,n){\\\\\\\"use strict\\\\\\\";n.d(e,\\\\\\\"a\\\\\\\",(function(){return s}));var i=n(28);class s{constructor(t){this.manager=void 0!==t?t:i.a,this.crossOrigin=\\\\\\\"anonymous\\\\\\\",this.withCredentials=!1,this.path=\\\\\\\"\\\\\\\",this.resourcePath=\\\\\\\"\\\\\\\",this.requestHeader={}}load(){}loadAsync(t,e){const n=this;return new Promise((function(i,s){n.load(t,i,e,s)}))}parse(){}setCrossOrigin(t){return this.crossOrigin=t,this}setWithCredentials(t){return this.withCredentials=t,this}setPath(t){return this.path=t,this}setResourcePath(t){return this.resourcePath=t,this}setRequestHeader(t){return this.requestHeader=t,this}}},function(t,e,n){\\\\\\\"use strict\\\\\\\";n.d(e,\\\\\\\"a\\\\\\\",(function(){return L}));var i=n(0),s=n(2),r=n(18),o=n(39),a=n(5),l=n(10),c=n(40),h=n(1),u=n(29),d=n(7);const p=new a.a,_=new o.a,m=new r.a,f=new i.a,g=new i.a,v=new i.a,y=new i.a,x=new i.a,b=new i.a,w=new i.a,T=new i.a,A=new i.a,M=new s.a,E=new s.a,S=new s.a,C=new i.a,N=new i.a;class L extends l.a{constructor(t=new d.a,e=new u.a){super(),this.type=\\\\\\\"Mesh\\\\\\\",this.geometry=t,this.material=e,this.updateMorphTargets()}copy(t){return super.copy(t),void 0!==t.morphTargetInfluences&&(this.morphTargetInfluences=t.morphTargetInfluences.slice()),void 0!==t.morphTargetDictionary&&(this.morphTargetDictionary=Object.assign({},t.morphTargetDictionary)),this.material=t.material,this.geometry=t.geometry,this}updateMorphTargets(){const t=this.geometry;if(t.isBufferGeometry){const e=t.morphAttributes,n=Object.keys(e);if(n.length>0){const t=e[n[0]];if(void 0!==t){this.morphTargetInfluences=[],this.morphTargetDictionary={};for(let e=0,n=t.length;e0&&console.error(\\\\\\\"THREE.Mesh.updateMorphTargets() no longer supports THREE.Geometry. Use THREE.BufferGeometry instead.\\\\\\\")}}raycast(t,e){const n=this.geometry,i=this.material,s=this.matrixWorld;if(void 0===i)return;if(null===n.boundingSphere&&n.computeBoundingSphere(),m.copy(n.boundingSphere),m.applyMatrix4(s),!1===t.ray.intersectsSphere(m))return;if(p.copy(s).invert(),_.copy(t.ray).applyMatrix4(p),null!==n.boundingBox&&!1===_.intersectsBox(n.boundingBox))return;let r;if(n.isBufferGeometry){const s=n.index,o=n.attributes.position,a=n.morphAttributes.position,l=n.morphTargetsRelative,c=n.attributes.uv,h=n.attributes.uv2,u=n.groups,d=n.drawRange;if(null!==s)if(Array.isArray(i))for(let n=0,p=u.length;nn.far?null:{distance:c,point:N.clone(),object:t}}(t,e,n,r,f,g,v,C);if(O){u&&(M.fromBufferAttribute(u,p),E.fromBufferAttribute(u,_),S.fromBufferAttribute(u,m),O.uv=c.a.getUV(C,f,g,v,M,E,S,new s.a)),d&&(M.fromBufferAttribute(d,p),E.fromBufferAttribute(d,_),S.fromBufferAttribute(d,m),O.uv2=c.a.getUV(C,f,g,v,M,E,S,new s.a));const t={a:p,b:_,c:m,normal:new 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y(t){this._y=t,this._onChangeCallback()}get z(){return this._z}set z(t){this._z=t,this._onChangeCallback()}get order(){return this._order}set order(t){this._order=t,this._onChangeCallback()}set(t,e,n,i=this._order){return this._x=t,this._y=e,this._z=n,this._order=i,this._onChangeCallback(),this}clone(){return new this.constructor(this._x,this._y,this._z,this._order)}copy(t){return this._x=t._x,this._y=t._y,this._z=t._z,this._order=t._order,this._onChangeCallback(),this}setFromRotationMatrix(t,e=this._order,n=!0){const i=t.elements,s=i[0],r=i[4],a=i[8],l=i[1],c=i[5],h=i[9],u=i[2],d=i[6],p=i[10];switch(e){case\\\\\\\"XYZ\\\\\\\":this._y=Math.asin(Object(o.d)(a,-1,1)),Math.abs(a)<.9999999?(this._x=Math.atan2(-h,p),this._z=Math.atan2(-r,s)):(this._x=Math.atan2(d,c),this._z=0);break;case\\\\\\\"YXZ\\\\\\\":this._x=Math.asin(-Object(o.d)(h,-1,1)),Math.abs(h)<.9999999?(this._y=Math.atan2(a,p),this._z=Math.atan2(l,c)):(this._y=Math.atan2(-u,s),this._z=0);break;case\\\\\\\"ZXY\\\\\\\":this._x=Math.asin(Object(o.d)(d,-1,1)),Math.abs(d)<.9999999?(this._y=Math.atan2(-u,p),this._z=Math.atan2(-r,c)):(this._y=0,this._z=Math.atan2(l,s));break;case\\\\\\\"ZYX\\\\\\\":this._y=Math.asin(-Object(o.d)(u,-1,1)),Math.abs(u)<.9999999?(this._x=Math.atan2(d,p),this._z=Math.atan2(l,s)):(this._x=0,this._z=Math.atan2(-r,c));break;case\\\\\\\"YZX\\\\\\\":this._z=Math.asin(Object(o.d)(l,-1,1)),Math.abs(l)<.9999999?(this._x=Math.atan2(-h,c),this._y=Math.atan2(-u,s)):(this._x=0,this._y=Math.atan2(a,p));break;case\\\\\\\"XZY\\\\\\\":this._z=Math.asin(-Object(o.d)(r,-1,1)),Math.abs(r)<.9999999?(this._x=Math.atan2(d,c),this._y=Math.atan2(a,s)):(this._x=Math.atan2(-h,p),this._y=0);break;default:console.warn(\\\\\\\"THREE.Euler: .setFromRotationMatrix() encountered an unknown order: \\\\\\\"+e)}return this._order=e,!0===n&&this._onChangeCallback(),this}setFromQuaternion(t,e,n){return a.makeRotationFromQuaternion(t),this.setFromRotationMatrix(a,e,n)}setFromVector3(t,e=this._order){return this.set(t.x,t.y,t.z,e)}reorder(t){return l.setFromEuler(this),this.setFromQuaternion(l,t)}equals(t){return t._x===this._x&&t._y===this._y&&t._z===this._z&&t._order===this._order}fromArray(t){return this._x=t[0],this._y=t[1],this._z=t[2],void 0!==t[3]&&(this._order=t[3]),this._onChangeCallback(),this}toArray(t=[],e=0){return t[e]=this._x,t[e+1]=this._y,t[e+2]=this._z,t[e+3]=this._order,t}toVector3(t){return t?t.set(this._x,this._y,this._z):new s.a(this._x,this._y,this._z)}_onChange(t){return this._onChangeCallback=t,this}_onChangeCallback(){}}c.prototype.isEuler=!0,c.DefaultOrder=\\\\\\\"XYZ\\\\\\\",c.RotationOrders=[\\\\\\\"XYZ\\\\\\\",\\\\\\\"YZX\\\\\\\",\\\\\\\"ZXY\\\\\\\",\\\\\\\"XZY\\\\\\\",\\\\\\\"YXZ\\\\\\\",\\\\\\\"ZYX\\\\\\\"]},function(t,e,n){\\\\\\\"use strict\\\\\\\";n.d(e,\\\\\\\"a\\\\\\\",(function(){return s})),n.d(e,\\\\\\\"b\\\\\\\",(function(){return i}));class i{constructor(t,e,n){const i=this;let s,r=!1,o=0,a=0;const l=[];this.onStart=void 0,this.onLoad=t,this.onProgress=e,this.onError=n,this.itemStart=function(t){a++,!1===r&&void 0!==i.onStart&&i.onStart(t,o,a),r=!0},this.itemEnd=function(t){o++,void 0!==i.onProgress&&i.onProgress(t,o,a),o===a&&(r=!1,void 0!==i.onLoad&&i.onLoad())},this.itemError=function(t){void 0!==i.onError&&i.onError(t)},this.resolveURL=function(t){return s?s(t):t},this.setURLModifier=function(t){return s=t,this},this.addHandler=function(t,e){return l.push(t,e),this},this.removeHandler=function(t){const e=l.indexOf(t);return-1!==e&&l.splice(e,2),this},this.getHandler=function(t){for(let e=0,n=l.length;e1?null:e.copy(n).multiplyScalar(s).add(t.start)}intersectsLine(t){const e=this.distanceToPoint(t.start),n=this.distanceToPoint(t.end);return e<0&&n>0||n<0&&e>0}intersectsBox(t){return t.intersectsPlane(this)}intersectsSphere(t){return t.intersectsPlane(this)}coplanarPoint(t){return t.copy(this.normal).multiplyScalar(-this.constant)}applyMatrix4(t,e){const n=e||a.getNormalMatrix(t),i=this.coplanarPoint(r).applyMatrix4(t),s=this.normal.applyMatrix3(n).normalize();return this.constant=-i.dot(s),this}translate(t){return this.constant-=t.dot(this.normal),this}equals(t){return t.normal.equals(this.normal)&&t.constant===this.constant}clone(){return(new this.constructor).copy(this)}}l.prototype.isPlane=!0},function(t,e,n){\\\\\\\"use strict\\\\\\\";function i(t,e,n,i,s){const r=.5*(i-e),o=.5*(s-n),a=t*t;return(2*n-2*i+r+o)*(t*a)+(-3*n+3*i-2*r-o)*a+r*t+n}function s(t,e,n,i){return function(t,e){const n=1-t;return n*n*e}(t,e)+function(t,e){return 2*(1-t)*t*e}(t,n)+function(t,e){return t*t*e}(t,i)}function r(t,e,n,i,s){return function(t,e){const n=1-t;return n*n*n*e}(t,e)+function(t,e){const n=1-t;return 3*n*n*t*e}(t,n)+function(t,e){return 3*(1-t)*t*t*e}(t,i)+function(t,e){return t*t*t*e}(t,s)}n.d(e,\\\\\\\"a\\\\\\\",(function(){return i})),n.d(e,\\\\\\\"c\\\\\\\",(function(){return s})),n.d(e,\\\\\\\"b\\\\\\\",(function(){return r}))},function(t,e,n){\\\\\\\"use strict\\\\\\\";n.d(e,\\\\\\\"a\\\\\\\",(function(){return r}));var i=n(10),s=n(6);class r extends i.a{constructor(t,e=1){super(),this.type=\\\\\\\"Light\\\\\\\",this.color=new s.a(t),this.intensity=e}dispose(){}copy(t){return super.copy(t),this.color.copy(t.color),this.intensity=t.intensity,this}toJSON(t){const e=super.toJSON(t);return e.object.color=this.color.getHex(),e.object.intensity=this.intensity,void 0!==this.groundColor&&(e.object.groundColor=this.groundColor.getHex()),void 0!==this.distance&&(e.object.distance=this.distance),void 0!==this.angle&&(e.object.angle=this.angle),void 0!==this.decay&&(e.object.decay=this.decay),void 0!==this.penumbra&&(e.object.penumbra=this.penumbra),void 0!==this.shadow&&(e.object.shadow=this.shadow.toJSON()),e}}r.prototype.isLight=!0},function(t,e,n){\\\\\\\"use strict\\\\\\\";n.d(e,\\\\\\\"a\\\\\\\",(function(){return r}));var i=n(23),s=n(1);class r extends i.a{constructor(t=null,e=1,n=1,i,r,o,a,l,c=s.ob,h=s.ob,u,d){super(null,o,a,l,c,h,i,r,u,d),this.image={data:t,width:e,height:n},this.magFilter=c,this.minFilter=h,this.generateMipmaps=!1,this.flipY=!1,this.unpackAlignment=1,this.needsUpdate=!0}}r.prototype.isDataTexture=!0},function(t,e,n){\\\\\\\"use strict\\\\\\\";n.d(e,\\\\\\\"a\\\\\\\",(function(){return l}));var i=n(41),s=n(0),r=n(4);const o=new s.a,a=new s.a;class l extends i.a{constructor(t,e){super(t,e),this.type=\\\\\\\"LineSegments\\\\\\\"}computeLineDistances(){const t=this.geometry;if(t.isBufferGeometry)if(null===t.index){const e=t.attributes.position,n=[];for(let t=0,i=e.count;t=s)break t;{const o=e[1];t=s)break e}r=n,n=0}}for(;n>>1;t0)if(p=l*h-c,_=l*c-h,f=s*d,p>=0)if(_>=-f)if(_<=f){const t=1/d;p*=t,_*=t,m=p*(p+l*_+2*c)+_*(l*p+_+2*h)+u}else _=s,p=Math.max(0,-(l*_+c)),m=-p*p+_*(_+2*h)+u;else _=-s,p=Math.max(0,-(l*_+c)),m=-p*p+_*(_+2*h)+u;else _<=-f?(p=Math.max(0,-(-l*s+c)),_=p>0?-s:Math.min(Math.max(-s,-h),s),m=-p*p+_*(_+2*h)+u):_<=f?(p=0,_=Math.min(Math.max(-s,-h),s),m=_*(_+2*h)+u):(p=Math.max(0,-(l*s+c)),_=p>0?s:Math.min(Math.max(-s,-h),s),m=-p*p+_*(_+2*h)+u);else _=l>0?-s:s,p=Math.max(0,-(l*_+c)),m=-p*p+_*(_+2*h)+u;return n&&n.copy(this.direction).multiplyScalar(p).add(this.origin),i&&i.copy(o).multiplyScalar(_).add(r),m}intersectSphere(t,e){s.subVectors(t.center,this.origin);const n=s.dot(this.direction),i=s.dot(s)-n*n,r=t.radius*t.radius;if(i>r)return null;const o=Math.sqrt(r-i),a=n-o,l=n+o;return a<0&&l<0?null:a<0?this.at(l,e):this.at(a,e)}intersectsSphere(t){return this.distanceSqToPoint(t.center)<=t.radius*t.radius}distanceToPlane(t){const e=t.normal.dot(this.direction);if(0===e)return 0===t.distanceToPoint(this.origin)?0:null;const n=-(this.origin.dot(t.normal)+t.constant)/e;return n>=0?n:null}intersectPlane(t,e){const n=this.distanceToPlane(t);return null===n?null:this.at(n,e)}intersectsPlane(t){const e=t.distanceToPoint(this.origin);if(0===e)return!0;return t.normal.dot(this.direction)*e<0}intersectBox(t,e){let n,i,s,r,o,a;const l=1/this.direction.x,c=1/this.direction.y,h=1/this.direction.z,u=this.origin;return l>=0?(n=(t.min.x-u.x)*l,i=(t.max.x-u.x)*l):(n=(t.max.x-u.x)*l,i=(t.min.x-u.x)*l),c>=0?(s=(t.min.y-u.y)*c,r=(t.max.y-u.y)*c):(s=(t.max.y-u.y)*c,r=(t.min.y-u.y)*c),n>r||s>i?null:((s>n||n!=n)&&(n=s),(r=0?(o=(t.min.z-u.z)*h,a=(t.max.z-u.z)*h):(o=(t.max.z-u.z)*h,a=(t.min.z-u.z)*h),n>a||o>i?null:((o>n||n!=n)&&(n=o),(a=0?n:i,e)))}intersectsBox(t){return null!==this.intersectBox(t,s)}intersectTriangle(t,e,n,i,s){l.subVectors(e,t),c.subVectors(n,t),h.crossVectors(l,c);let r,o=this.direction.dot(h);if(o>0){if(i)return null;r=1}else{if(!(o<0))return null;r=-1,o=-o}a.subVectors(this.origin,t);const u=r*this.direction.dot(c.crossVectors(a,c));if(u<0)return null;const d=r*this.direction.dot(l.cross(a));if(d<0)return null;if(u+d>o)return null;const p=-r*a.dot(h);return p<0?null:this.at(p/o,s)}applyMatrix4(t){return this.origin.applyMatrix4(t),this.direction.transformDirection(t),this}equals(t){return t.origin.equals(this.origin)&&t.direction.equals(this.direction)}clone(){return(new this.constructor).copy(this)}}},function(t,e,n){\\\\\\\"use strict\\\\\\\";n.d(e,\\\\\\\"a\\\\\\\",(function(){return _}));var i=n(0);const s=new i.a,r=new i.a,o=new i.a,a=new i.a,l=new i.a,c=new i.a,h=new i.a,u=new i.a,d=new i.a,p=new i.a;class _{constructor(t=new i.a,e=new i.a,n=new i.a){this.a=t,this.b=e,this.c=n}static getNormal(t,e,n,i){i.subVectors(n,e),s.subVectors(t,e),i.cross(s);const r=i.lengthSq();return r>0?i.multiplyScalar(1/Math.sqrt(r)):i.set(0,0,0)}static getBarycoord(t,e,n,i,a){s.subVectors(i,e),r.subVectors(n,e),o.subVectors(t,e);const l=s.dot(s),c=s.dot(r),h=s.dot(o),u=r.dot(r),d=r.dot(o),p=l*u-c*c;if(0===p)return a.set(-2,-1,-1);const _=1/p,m=(u*h-c*d)*_,f=(l*d-c*h)*_;return a.set(1-m-f,f,m)}static containsPoint(t,e,n,i){return this.getBarycoord(t,e,n,i,a),a.x>=0&&a.y>=0&&a.x+a.y<=1}static getUV(t,e,n,i,s,r,o,l){return this.getBarycoord(t,e,n,i,a),l.set(0,0),l.addScaledVector(s,a.x),l.addScaledVector(r,a.y),l.addScaledVector(o,a.z),l}static isFrontFacing(t,e,n,i){return s.subVectors(n,e),r.subVectors(t,e),s.cross(r).dot(i)<0}set(t,e,n){return this.a.copy(t),this.b.copy(e),this.c.copy(n),this}setFromPointsAndIndices(t,e,n,i){return this.a.copy(t[e]),this.b.copy(t[n]),this.c.copy(t[i]),this}setFromAttributeAndIndices(t,e,n,i){return this.a.fromBufferAttribute(t,e),this.b.fromBufferAttribute(t,n),this.c.fromBufferAttribute(t,i),this}clone(){return(new this.constructor).copy(this)}copy(t){return this.a.copy(t.a),this.b.copy(t.b),this.c.copy(t.c),this}getArea(){return s.subVectors(this.c,this.b),r.subVectors(this.a,this.b),.5*s.cross(r).length()}getMidpoint(t){return t.addVectors(this.a,this.b).add(this.c).multiplyScalar(1/3)}getNormal(t){return _.getNormal(this.a,this.b,this.c,t)}getPlane(t){return t.setFromCoplanarPoints(this.a,this.b,this.c)}getBarycoord(t,e){return _.getBarycoord(t,this.a,this.b,this.c,e)}getUV(t,e,n,i,s){return _.getUV(t,this.a,this.b,this.c,e,n,i,s)}containsPoint(t){return _.containsPoint(t,this.a,this.b,this.c)}isFrontFacing(t){return _.isFrontFacing(this.a,this.b,this.c,t)}intersectsBox(t){return t.intersectsTriangle(this)}closestPointToPoint(t,e){const n=this.a,i=this.b,s=this.c;let r,o;l.subVectors(i,n),c.subVectors(s,n),u.subVectors(t,n);const a=l.dot(u),_=c.dot(u);if(a<=0&&_<=0)return e.copy(n);d.subVectors(t,i);const m=l.dot(d),f=c.dot(d);if(m>=0&&f<=m)return e.copy(i);const g=a*f-m*_;if(g<=0&&a>=0&&m<=0)return r=a/(a-m),e.copy(n).addScaledVector(l,r);p.subVectors(t,s);const v=l.dot(p),y=c.dot(p);if(y>=0&&v<=y)return e.copy(s);const x=v*_-a*y;if(x<=0&&_>=0&&y<=0)return o=_/(_-y),e.copy(n).addScaledVector(c,o);const b=m*y-v*f;if(b<=0&&f-m>=0&&v-y>=0)return h.subVectors(s,i),o=(f-m)/(f-m+(v-y)),e.copy(i).addScaledVector(h,o);const w=1/(b+x+g);return r=x*w,o=g*w,e.copy(n).addScaledVector(l,r).addScaledVector(c,o)}equals(t){return t.a.equals(this.a)&&t.b.equals(this.b)&&t.c.equals(this.c)}}},function(t,e,n){\\\\\\\"use strict\\\\\\\";n.d(e,\\\\\\\"a\\\\\\\",(function(){return f}));var i=n(18),s=n(39),r=n(5),o=n(10),a=n(0),l=n(24),c=n(7),h=n(4);const u=new a.a,d=new a.a,p=new r.a,_=new s.a,m=new i.a;class f extends o.a{constructor(t=new c.a,e=new l.a){super(),this.type=\\\\\\\"Line\\\\\\\",this.geometry=t,this.material=e,this.updateMorphTargets()}copy(t){return super.copy(t),this.material=t.material,this.geometry=t.geometry,this}computeLineDistances(){const t=this.geometry;if(t.isBufferGeometry)if(null===t.index){const e=t.attributes.position,n=[0];for(let t=1,i=e.count;tl)continue;d.applyMatrix4(this.matrixWorld);const a=t.ray.origin.distanceTo(d);at.far||e.push({distance:a,point:u.clone().applyMatrix4(this.matrixWorld),index:n,face:null,faceIndex:null,object:this})}}else{for(let n=Math.max(0,r.start),i=Math.min(s.count,r.start+r.count)-1;nl)continue;d.applyMatrix4(this.matrixWorld);const i=t.ray.origin.distanceTo(d);it.far||e.push({distance:i,point:u.clone().applyMatrix4(this.matrixWorld),index:n,face:null,faceIndex:null,object:this})}}}else n.isGeometry&&console.error(\\\\\\\"THREE.Line.raycast() no longer supports THREE.Geometry. Use THREE.BufferGeometry instead.\\\\\\\")}updateMorphTargets(){const t=this.geometry;if(t.isBufferGeometry){const e=t.morphAttributes,n=Object.keys(e);if(n.length>0){const t=e[n[0]];if(void 0!==t){this.morphTargetInfluences=[],this.morphTargetDictionary={};for(let e=0,n=t.length;e0&&console.error(\\\\\\\"THREE.Line.updateMorphTargets() does not support THREE.Geometry. 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e.set((t.x-this.min.x)/(this.max.x-this.min.x),(t.y-this.min.y)/(this.max.y-this.min.y))}intersectsBox(t){return!(t.max.xthis.max.x||t.max.ythis.max.y)}clampPoint(t,e){return e.copy(t).clamp(this.min,this.max)}distanceToPoint(t){return s.copy(t).clamp(this.min,this.max).sub(t).length()}intersect(t){return this.min.max(t.min),this.max.min(t.max),this}union(t){return this.min.min(t.min),this.max.max(t.max),this}translate(t){return this.min.add(t),this.max.add(t),this}equals(t){return t.min.equals(this.min)&&t.max.equals(this.max)}}r.prototype.isBox2=!0;var o=n(7),a=n(22),l=n(4),c=n(13),h=n(11),u=n(47),d=n(46),p=n(48),_=n(53),m=n(0);class f extends c.a{constructor(t){super(t),this.defaultDPI=90,this.defaultUnit=\\\\\\\"px\\\\\\\"}load(t,e,n,i){const s=this,r=new a.a(s.manager);r.setPath(s.path),r.setRequestHeader(s.requestHeader),r.setWithCredentials(s.withCredentials),r.load(t,(function(n){try{e(s.parse(n))}catch(e){i?i(e):console.error(e),s.manager.itemError(t)}}),n,i)}parse(t){const e=this;function n(t,e,n,i,r,o,a,l){if(0==e||0==n)return void t.lineTo(l.x,l.y);i=i*Math.PI/180,e=Math.abs(e),n=Math.abs(n);const c=(a.x-l.x)/2,h=(a.y-l.y)/2,u=Math.cos(i)*c+Math.sin(i)*h,d=-Math.sin(i)*c+Math.cos(i)*h;let p=e*e,_=n*n;const m=u*u,f=d*d,g=m/p+f/_;if(g>1){const t=Math.sqrt(g);p=(e*=t)*e,_=(n*=t)*n}const v=p*f+_*m,y=(p*_-v)/v;let x=Math.sqrt(Math.max(0,y));r===o&&(x=-x);const b=x*e*d/n,w=-x*n*u/e,T=Math.cos(i)*b-Math.sin(i)*w+(a.x+l.x)/2,A=Math.sin(i)*b+Math.cos(i)*w+(a.y+l.y)/2,M=s(1,0,(u-b)/e,(d-w)/n),E=s((u-b)/e,(d-w)/n,(-u-b)/e,(-d-w)/n)%(2*Math.PI);t.currentPath.absellipse(T,A,e,n,M,M+E,0===o,i)}function s(t,e,n,i){const s=t*n+e*i,r=Math.sqrt(t*t+e*e)*Math.sqrt(n*n+i*i);let o=Math.acos(Math.max(-1,Math.min(1,s/r)));return t*i-e*n<0&&(o=-o),o}function r(t,e){e=Object.assign({},e);let n={};if(t.hasAttribute(\\\\\\\"class\\\\\\\")){const e=t.getAttribute(\\\\\\\"class\\\\\\\").split(/\\\\s/).filter(Boolean).map((t=>t.trim()));for(let t=0;t=0;t--){const s=i[t].trim();if(\\\\\\\"\\\\\\\"===s)continue;const r=s.indexOf(\\\\\\\"(\\\\\\\"),o=s.length;if(r>0&&r=1){const t=e[0];let i=t;e.length>=2&&(i=e[1]),n.translate(t,i)}break;case\\\\\\\"rotate\\\\\\\":if(e.length>=1){let t=0,i=0,s=0;t=-e[0]*Math.PI/180,e.length>=3&&(i=e[1],s=e[2]),b.identity().translate(-i,-s),w.identity().rotate(t),T.multiplyMatrices(w,b),b.identity().translate(i,s),n.multiplyMatrices(b,T)}break;case\\\\\\\"scale\\\\\\\":if(e.length>=1){const t=e[0];let i=t;e.length>=2&&(i=e[1]),n.scale(t,i)}break;case\\\\\\\"skewX\\\\\\\":1===e.length&&n.set(1,Math.tan(e[0]*Math.PI/180),0,0,1,0,0,0,1);break;case\\\\\\\"skewY\\\\\\\":1===e.length&&n.set(1,0,0,Math.tan(e[0]*Math.PI/180),1,0,0,0,1);break;case\\\\\\\"matrix\\\\\\\":6===e.length&&n.set(e[0],e[2],e[4],e[1],e[3],e[5],0,0,1)}}e.premultiply(n)}}return e}(t);y.length>0&&e.premultiply(y[y.length-1]);return E.copy(e),y.push(e),e}(e);let c=!0,m=null;switch(e.nodeName){case\\\\\\\"svg\\\\\\\":break;case\\\\\\\"style\\\\\\\":!function(t){if(!t.sheet||!t.sheet.cssRules||!t.sheet.cssRules.length)return;for(let e=0;et.trim()));for(let t=0;t0&&(s.copy(l),e.currentPath.currentPoint.copy(s),c=!0);break;default:console.warn(i)}h=!1}return e}(e));break;case\\\\\\\"rect\\\\\\\":s=r(e,s),m=function(t){const e=d(t.getAttribute(\\\\\\\"x\\\\\\\")||0),n=d(t.getAttribute(\\\\\\\"y\\\\\\\")||0),i=d(t.getAttribute(\\\\\\\"rx\\\\\\\")||t.getAttribute(\\\\\\\"ry\\\\\\\")||0),s=d(t.getAttribute(\\\\\\\"ry\\\\\\\")||t.getAttribute(\\\\\\\"rx\\\\\\\")||0),r=d(t.getAttribute(\\\\\\\"width\\\\\\\")),o=d(t.getAttribute(\\\\\\\"height\\\\\\\")),a=.448084975506,l=new p.a;l.moveTo(e+i,n),l.lineTo(e+r-i,n),(0!==i||0!==s)&&l.bezierCurveTo(e+r-i*a,n,e+r,n+s*a,e+r,n+s);l.lineTo(e+r,n+o-s),(0!==i||0!==s)&&l.bezierCurveTo(e+r,n+o-s*a,e+r-i*a,n+o,e+r-i,n+o);l.lineTo(e+i,n+o),(0!==i||0!==s)&&l.bezierCurveTo(e+i*a,n+o,e,n+o-s*a,e,n+o-s);l.lineTo(e,n+s),(0!==i||0!==s)&&l.bezierCurveTo(e,n+s*a,e+i*a,n,e+i,n);return l}(e);break;case\\\\\\\"polygon\\\\\\\":s=r(e,s),m=function(t){function e(t,e,n){const r=d(e),o=d(n);0===s?i.moveTo(r,o):i.lineTo(r,o),s++}const n=/(-?[\\\\d\\\\.?]+)[,|\\\\s](-?[\\\\d\\\\.?]+)/g,i=new p.a;let s=0;return t.getAttribute(\\\\\\\"points\\\\\\\").replace(n,e),i.currentPath.autoClose=!0,i}(e);break;case\\\\\\\"polyline\\\\\\\":s=r(e,s),m=function(t){function e(t,e,n){const r=d(e),o=d(n);0===s?i.moveTo(r,o):i.lineTo(r,o),s++}const n=/(-?[\\\\d\\\\.?]+)[,|\\\\s](-?[\\\\d\\\\.?]+)/g,i=new p.a;let s=0;return t.getAttribute(\\\\\\\"points\\\\\\\").replace(n,e),i.currentPath.autoClose=!1,i}(e);break;case\\\\\\\"circle\\\\\\\":s=r(e,s),m=function(t){const e=d(t.getAttribute(\\\\\\\"cx\\\\\\\")||0),n=d(t.getAttribute(\\\\\\\"cy\\\\\\\")||0),i=d(t.getAttribute(\\\\\\\"r\\\\\\\")||0),s=new u.a;s.absarc(e,n,i,0,2*Math.PI);const r=new p.a;return r.subPaths.push(s),r}(e);break;case\\\\\\\"ellipse\\\\\\\":s=r(e,s),m=function(t){const e=d(t.getAttribute(\\\\\\\"cx\\\\\\\")||0),n=d(t.getAttribute(\\\\\\\"cy\\\\\\\")||0),i=d(t.getAttribute(\\\\\\\"rx\\\\\\\")||0),s=d(t.getAttribute(\\\\\\\"ry\\\\\\\")||0),r=new u.a;r.absellipse(e,n,i,s,0,2*Math.PI);const o=new p.a;return o.subPaths.push(r),o}(e);break;case\\\\\\\"line\\\\\\\":s=r(e,s),m=function(t){const e=d(t.getAttribute(\\\\\\\"x1\\\\\\\")||0),n=d(t.getAttribute(\\\\\\\"y1\\\\\\\")||0),i=d(t.getAttribute(\\\\\\\"x2\\\\\\\")||0),s=d(t.getAttribute(\\\\\\\"y2\\\\\\\")||0),r=new p.a;return r.moveTo(e,n),r.lineTo(i,s),r.currentPath.autoClose=!1,r}(e);break;case\\\\\\\"defs\\\\\\\":c=!1;break;case\\\\\\\"use\\\\\\\":s=r(e,s);const l=e.href.baseVal.substring(1),h=e.viewportElement.getElementById(l);h?t(h,s):console.warn(\\\\\\\"SVGLoader: 'use node' references non-existent node id: \\\\\\\"+l)}if(m&&(void 0!==s.fill&&\\\\\\\"none\\\\\\\"!==s.fill&&m.color.setStyle(s.fill),function(t,e){function n(t){M.set(t.x,t.y,1).applyMatrix3(e),t.set(M.x,M.y)}const i=function(t){return 0!==t.elements[1]||0!==t.elements[3]}(e),s=t.subPaths;for(let t=0,r=s.length;t0?E.copy(y[y.length-1]):E.identity())}(S.documentElement,{fill:\\\\\\\"#000\\\\\\\",fillOpacity:1,strokeOpacity:1,strokeWidth:1,strokeLineJoin:\\\\\\\"miter\\\\\\\",strokeLineCap:\\\\\\\"butt\\\\\\\",strokeMiterLimit:4});return{paths:g,xml:S.documentElement}}static createShapes(t){const e=999999999,n=0,s=1,o=2,a=3,l=4,c=5,h=6,p={loc:n,t:0};function m(t,e,i,s){const r=t.x,a=e.x,l=i.x,c=s.x,h=t.y,u=e.y,d=i.y,_=s.y,m=(c-l)*(h-d)-(_-d)*(r-l),g=(_-d)*(a-r)-(c-l)*(u-h),v=m/g,y=((a-r)*(h-d)-(u-h)*(r-l))/g;if(0===g&&0!==m||v<=0||v>=1||y<0||y>1)return null;if(0===m&&0===g){for(let l=0;l<2;l++){if(f(0===l?i:s,t,e),p.loc==n){const t=0===l?i:s;return{x:t.x,y:t.y,t:p.t}}if(p.loc==o){return{x:+(r+p.t*(a-r)).toPrecision(10),y:+(h+p.t*(u-h)).toPrecision(10),t:p.t}}}return null}for(let r=0;r<2;r++)if(f(0===r?i:s,t,e),p.loc==n){const t=0===r?i:s;return{x:t.x,y:t.y,t:p.t}}return{x:+(r+v*(a-r)).toPrecision(10),y:+(h+v*(u-h)).toPrecision(10),t:v}}function f(t,e,i){const r=i.x-e.x,u=i.y-e.y,d=t.x-e.x,_=t.y-e.y,m=r*_-d*u;if(t.x===e.x&&t.y===e.y)return p.loc=n,void(p.t=0);if(t.x===i.x&&t.y===i.y)return p.loc=s,void(p.t=1);if(m<-Number.EPSILON)return void(p.loc=a);if(m>Number.EPSILON)return void(p.loc=l);if(r*d<0||u*_<0)return void(p.loc=c);if(Math.sqrt(r*r+u*u){if(e.boundingBox.containsPoint(s)){(function(t,e){const n=[],s=[];for(let 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${s}`),!1}disconnect(t,e){this._remove_connection(t.graphNodeId(),e.graphNodeId()),t.dirtyController.clearSuccessorsCacheWithPredecessors()}disconnectPredecessors(t){const e=this.predecessors(t);for(let n of e)this.disconnect(n,t)}disconnectSuccessors(t){const e=this.successors(t);for(let n of e)this.disconnect(t,n)}predecessorIds(t){const e=this._predecessors.get(t);if(e){const t=[];return e.forEach(((e,n)=>{t.push(n)})),t}return[]}predecessors(t){const e=this.predecessorIds(t.graphNodeId());return this.nodesFromIds(e)}successorIds(t){const e=this._successors.get(t);if(e){const t=[];return e.forEach(((e,n)=>{t.push(n)})),t}return[]}successors(t){const e=this.successorIds(t.graphNodeId())||[];return this.nodesFromIds(e)}allPredecessorIds(t){return this.allNextIds(t,\\\\\\\"predecessorIds\\\\\\\")}allSuccessorIds(t){return this.allNextIds(t,\\\\\\\"successorIds\\\\\\\")}allPredecessors(t){const e=this.allPredecessorIds(t);return this.nodesFromIds(e)}allSuccessors(t){const e=this.allSuccessorIds(t);return this.nodesFromIds(e)}_createConnection(t,e){let n=this._successors.get(t);if(n||(n=new Set,this._successors.set(t,n)),n.has(e))return;n.add(e);let i=this._predecessors.get(e);i||(i=new Set,this._predecessors.set(e,i)),i.add(t)}_remove_connection(t,e){let n=this._successors.get(t);n&&(n.delete(e),0==n.size&&this._successors.delete(t));let i=this._predecessors.get(e);i&&(i.delete(t),0==i.size&&this._predecessors.delete(e))}allNextIds(t,e){const n=new Map,i=[];let s=this[e](t.graphNodeId());for(;s.length>0;){const t=[];for(let n of s)for(let i of this[e](n))t.push(i);for(let t of s)n.set(t,!0);for(let e of t)s.push(e);s=t}return n.forEach(((t,e)=>{i.push(e)})),i}_hasPredecessor(t,e){const n=this.predecessorIds(t);if(n){if(n.includes(e))return!0;for(let t of n)return this._hasPredecessor(t,e)}return!1}}class c{constructor(t){this._node=t,this._cooks_count=0,this._total_cook_time=0,this._total_inputs_time=0,this._total_params_time=0}update_cook_data(t){this._cooks_count+=1,this._total_cook_time+=t.cookTime,this._total_inputs_time+=t.inputsTime,this._total_params_time+=t.paramsTime}total_time(){return this._total_cook_time+this._total_inputs_time+this._total_params_time}total_cook_time(){return this._total_cook_time}cook_time_per_iteration(){return this._cooks_count>0?this._total_cook_time/this._cooks_count:0}total_inputs_time(){return this._total_inputs_time}inputs_time_per_iteration(){return this._cooks_count>0?this._total_inputs_time/this._cooks_count:0}total_params_time2(){return this._total_params_time}params_time_per_iteration2(){return this._cooks_count>0?this._total_params_time/this._cooks_count:0}cooks_count(){return 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t)e+=n;return e}static compact(t){const e=[];for(let n of t)null!=n&&e.push(n);return e}static uniq(t){const e=new Set;for(let n of t)e.add(n);const n=new Array(e.size);let i=0;return e.forEach((t=>{n[i]=t,i++})),n}static chunk(t,e){const n=[];let i=[];n.push(i);for(let s=0;sn.push(t))),n}static intersection(t,e){const n=[];return u.intersection(this.toSet(t),this.toSet(e)).forEach((t=>n.push(t))),n}static difference(t,e){const n=[];return u.difference(this.toSet(t),this.toSet(e)).forEach((t=>n.push(t))),n}static toSet(t){const e=new Set;for(let n of t)e.add(n);return e}static isEqual(t,e){if(t.length!=e.length)return!1;const n=t.length;for(let i=0;i{s[r]=t,r++})),m.isString(s[0])?s.sort():s.sort(((t,e)=>t-e));const o=new Array(t.length);r=0;for(let t of s){const e=n.get(t);if(e)for(let t of e)o[r]=t,r++}return o}static range(t,e,n=1){null==e&&(e=t,t=0);const i=Math.floor((e-t)/n),s=new Array(i);for(let e=0;e0?1:-1,c.push(C.x,C.y,C.z),h.push(a/f),h.push(1-r/g),E+=1}}for(let t=0;t0&&(e.defines=this.defines),e.vertexShader=this.vertexShader,e.fragmentShader=this.fragmentShader;const n={};for(const t in this.extensions)!0===this.extensions[t]&&(n[t]=!0);return Object.keys(n).length>0&&(e.extensions=n),e}}F.prototype.isShaderMaterial=!0;var D=n(6),B=n(14),z=\\\\\\\"\\\\n#ifdef USE_SHADOWMAP\\\\n\\\\n\\\\t#if NUM_DIR_LIGHT_SHADOWS > 0\\\\n\\\\n\\\\t\\\\tuniform sampler2D directionalShadowMap[ NUM_DIR_LIGHT_SHADOWS ];\\\\n\\\\t\\\\tvarying vec4 vDirectionalShadowCoord[ NUM_DIR_LIGHT_SHADOWS ];\\\\n\\\\n\\\\t\\\\tstruct DirectionalLightShadow {\\\\n\\\\t\\\\t\\\\tfloat shadowBias;\\\\n\\\\t\\\\t\\\\tfloat shadowNormalBias;\\\\n\\\\t\\\\t\\\\tfloat shadowRadius;\\\\n\\\\t\\\\t\\\\tvec2 shadowMapSize;\\\\n\\\\t\\\\t};\\\\n\\\\n\\\\t\\\\tuniform DirectionalLightShadow directionalLightShadows[ NUM_DIR_LIGHT_SHADOWS ];\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\t#if NUM_SPOT_LIGHT_SHADOWS > 0\\\\n\\\\n\\\\t\\\\tuniform sampler2D spotShadowMap[ NUM_SPOT_LIGHT_SHADOWS ];\\\\n\\\\t\\\\tvarying vec4 vSpotShadowCoord[ NUM_SPOT_LIGHT_SHADOWS ];\\\\n\\\\n\\\\t\\\\tstruct SpotLightShadow {\\\\n\\\\t\\\\t\\\\tfloat shadowBias;\\\\n\\\\t\\\\t\\\\tfloat shadowNormalBias;\\\\n\\\\t\\\\t\\\\tfloat shadowRadius;\\\\n\\\\t\\\\t\\\\tvec2 shadowMapSize;\\\\n\\\\t\\\\t};\\\\n\\\\n\\\\t\\\\tuniform SpotLightShadow spotLightShadows[ NUM_SPOT_LIGHT_SHADOWS ];\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\t#if NUM_POINT_LIGHT_SHADOWS > 0\\\\n\\\\n\\\\t\\\\tuniform sampler2D pointShadowMap[ NUM_POINT_LIGHT_SHADOWS ];\\\\n\\\\t\\\\tvarying vec4 vPointShadowCoord[ NUM_POINT_LIGHT_SHADOWS ];\\\\n\\\\n\\\\t\\\\tstruct PointLightShadow {\\\\n\\\\t\\\\t\\\\tfloat shadowBias;\\\\n\\\\t\\\\t\\\\tfloat shadowNormalBias;\\\\n\\\\t\\\\t\\\\tfloat shadowRadius;\\\\n\\\\t\\\\t\\\\tvec2 shadowMapSize;\\\\n\\\\t\\\\t\\\\tfloat shadowCameraNear;\\\\n\\\\t\\\\t\\\\tfloat shadowCameraFar;\\\\n\\\\t\\\\t};\\\\n\\\\n\\\\t\\\\tuniform PointLightShadow pointLightShadows[ NUM_POINT_LIGHT_SHADOWS ];\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\t/*\\\\n\\\\t#if NUM_RECT_AREA_LIGHTS > 0\\\\n\\\\n\\\\t\\\\t// TODO (abelnation): create uniforms for area light shadows\\\\n\\\\n\\\\t#endif\\\\n\\\\t*/\\\\n\\\\n\\\\tfloat texture2DCompare( sampler2D depths, vec2 uv, float compare ) {\\\\n\\\\n\\\\t\\\\treturn step( compare, unpackRGBAToDepth( texture2D( depths, uv ) ) );\\\\n\\\\n\\\\t}\\\\n\\\\n\\\\tvec2 texture2DDistribution( sampler2D shadow, vec2 uv ) {\\\\n\\\\n\\\\t\\\\treturn unpackRGBATo2Half( texture2D( shadow, uv ) );\\\\n\\\\n\\\\t}\\\\n\\\\n\\\\tfloat VSMShadow (sampler2D shadow, vec2 uv, float compare ){\\\\n\\\\n\\\\t\\\\tfloat occlusion = 1.0;\\\\n\\\\n\\\\t\\\\tvec2 distribution = texture2DDistribution( shadow, uv );\\\\n\\\\n\\\\t\\\\tfloat hard_shadow = step( compare , distribution.x ); // Hard Shadow\\\\n\\\\n\\\\t\\\\tif (hard_shadow != 1.0 ) {\\\\n\\\\n\\\\t\\\\t\\\\tfloat distance = compare - distribution.x ;\\\\n\\\\t\\\\t\\\\tfloat variance = max( 0.00000, distribution.y * distribution.y );\\\\n\\\\t\\\\t\\\\tfloat softness_probability = variance / (variance + distance * distance ); // Chebeyshevs inequality\\\\n\\\\t\\\\t\\\\tsoftness_probability = clamp( ( softness_probability - 0.3 ) / ( 0.95 - 0.3 ), 0.0, 1.0 ); // 0.3 reduces light bleed\\\\n\\\\t\\\\t\\\\tocclusion = clamp( max( hard_shadow, softness_probability ), 0.0, 1.0 );\\\\n\\\\n\\\\t\\\\t}\\\\n\\\\t\\\\treturn occlusion;\\\\n\\\\n\\\\t}\\\\n\\\\n\\\\tfloat getShadow( sampler2D shadowMap, vec2 shadowMapSize, float shadowBias, float shadowRadius, vec4 shadowCoord ) {\\\\n\\\\n\\\\t\\\\tfloat shadow = 1.0;\\\\n\\\\n\\\\t\\\\tshadowCoord.xyz /= shadowCoord.w;\\\\n\\\\t\\\\tshadowCoord.z += shadowBias;\\\\n\\\\n\\\\t\\\\t// if ( something && something ) breaks ATI OpenGL shader compiler\\\\n\\\\t\\\\t// if ( all( something, something ) ) using this instead\\\\n\\\\n\\\\t\\\\tbvec4 inFrustumVec = bvec4 ( shadowCoord.x >= 0.0, shadowCoord.x <= 1.0, shadowCoord.y >= 0.0, shadowCoord.y <= 1.0 );\\\\n\\\\t\\\\tbool inFrustum = all( inFrustumVec );\\\\n\\\\n\\\\t\\\\tbvec2 frustumTestVec = bvec2( inFrustum, shadowCoord.z <= 1.0 );\\\\n\\\\n\\\\t\\\\tbool frustumTest = all( frustumTestVec );\\\\n\\\\n\\\\t\\\\tif ( frustumTest ) {\\\\n\\\\n\\\\t\\\\t#if defined( SHADOWMAP_TYPE_PCF )\\\\n\\\\n\\\\t\\\\t\\\\tvec2 texelSize = vec2( 1.0 ) / shadowMapSize;\\\\n\\\\n\\\\t\\\\t\\\\tfloat dx0 = - texelSize.x * shadowRadius;\\\\n\\\\t\\\\t\\\\tfloat dy0 = - texelSize.y * shadowRadius;\\\\n\\\\t\\\\t\\\\tfloat dx1 = + texelSize.x * shadowRadius;\\\\n\\\\t\\\\t\\\\tfloat dy1 = + texelSize.y * shadowRadius;\\\\n\\\\t\\\\t\\\\tfloat dx2 = dx0 / 2.0;\\\\n\\\\t\\\\t\\\\tfloat dy2 = dy0 / 2.0;\\\\n\\\\t\\\\t\\\\tfloat dx3 = dx1 / 2.0;\\\\n\\\\t\\\\t\\\\tfloat dy3 = dy1 / 2.0;\\\\n\\\\n\\\\t\\\\t\\\\tshadow = (\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx0, dy0 ), shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( 0.0, dy0 ), shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx1, dy0 ), shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx2, dy2 ), shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( 0.0, dy2 ), shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx3, dy2 ), shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx0, 0.0 ), shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx2, 0.0 ), shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, shadowCoord.xy, shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx3, 0.0 ), shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx1, 0.0 ), shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx2, dy3 ), shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( 0.0, dy3 ), shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx3, dy3 ), shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx0, dy1 ), shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( 0.0, dy1 ), shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx1, dy1 ), shadowCoord.z )\\\\n\\\\t\\\\t\\\\t) * ( 1.0 / 17.0 );\\\\n\\\\n\\\\t\\\\t#elif defined( SHADOWMAP_TYPE_PCF_SOFT )\\\\n\\\\n\\\\t\\\\t\\\\tvec2 texelSize = vec2( 1.0 ) / shadowMapSize;\\\\n\\\\t\\\\t\\\\tfloat dx = texelSize.x;\\\\n\\\\t\\\\t\\\\tfloat dy = texelSize.y;\\\\n\\\\n\\\\t\\\\t\\\\tvec2 uv = shadowCoord.xy;\\\\n\\\\t\\\\t\\\\tvec2 f = fract( uv * shadowMapSize + 0.5 );\\\\n\\\\t\\\\t\\\\tuv -= f * texelSize;\\\\n\\\\n\\\\t\\\\t\\\\tshadow = (\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, uv, shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, uv + vec2( dx, 0.0 ), shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, uv + vec2( 0.0, dy ), shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, uv + texelSize, shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\tmix( texture2DCompare( shadowMap, uv + vec2( -dx, 0.0 ), shadowCoord.z ), \\\\n\\\\t\\\\t\\\\t\\\\t\\\\t texture2DCompare( shadowMap, uv + vec2( 2.0 * dx, 0.0 ), shadowCoord.z ),\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t f.x ) +\\\\n\\\\t\\\\t\\\\t\\\\tmix( texture2DCompare( shadowMap, uv + vec2( -dx, dy ), shadowCoord.z ), \\\\n\\\\t\\\\t\\\\t\\\\t\\\\t texture2DCompare( shadowMap, uv + vec2( 2.0 * dx, dy ), shadowCoord.z ),\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t f.x ) +\\\\n\\\\t\\\\t\\\\t\\\\tmix( texture2DCompare( shadowMap, uv + vec2( 0.0, -dy ), shadowCoord.z ), \\\\n\\\\t\\\\t\\\\t\\\\t\\\\t texture2DCompare( shadowMap, uv + vec2( 0.0, 2.0 * dy ), shadowCoord.z ),\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t f.y ) +\\\\n\\\\t\\\\t\\\\t\\\\tmix( texture2DCompare( shadowMap, uv + vec2( dx, -dy ), shadowCoord.z ), \\\\n\\\\t\\\\t\\\\t\\\\t\\\\t texture2DCompare( shadowMap, uv + vec2( dx, 2.0 * dy ), shadowCoord.z ),\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t f.y ) +\\\\n\\\\t\\\\t\\\\t\\\\tmix( mix( texture2DCompare( shadowMap, uv + vec2( -dx, -dy ), shadowCoord.z ), \\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t texture2DCompare( shadowMap, uv + vec2( 2.0 * dx, -dy ), shadowCoord.z ),\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t f.x ),\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t mix( texture2DCompare( shadowMap, uv + vec2( -dx, 2.0 * dy ), shadowCoord.z ), \\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t texture2DCompare( shadowMap, uv + vec2( 2.0 * dx, 2.0 * dy ), shadowCoord.z ),\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t f.x ),\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t f.y )\\\\n\\\\t\\\\t\\\\t) * ( 1.0 / 9.0 );\\\\n\\\\n\\\\t\\\\t#elif defined( SHADOWMAP_TYPE_VSM )\\\\n\\\\n\\\\t\\\\t\\\\tshadow = VSMShadow( shadowMap, shadowCoord.xy, shadowCoord.z );\\\\n\\\\n\\\\t\\\\t#else // no percentage-closer filtering:\\\\n\\\\n\\\\t\\\\t\\\\tshadow = texture2DCompare( shadowMap, shadowCoord.xy, shadowCoord.z );\\\\n\\\\n\\\\t\\\\t#endif\\\\n\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\treturn shadow;\\\\n\\\\n\\\\t}\\\\n\\\\n\\\\t// cubeToUV() maps a 3D direction vector suitable for cube texture mapping to a 2D\\\\n\\\\t// vector suitable for 2D texture mapping. This code uses the following layout for the\\\\n\\\\t// 2D texture:\\\\n\\\\t//\\\\n\\\\t// xzXZ\\\\n\\\\t// y Y\\\\n\\\\t//\\\\n\\\\t// Y - Positive y direction\\\\n\\\\t// y - Negative y direction\\\\n\\\\t// X - Positive x direction\\\\n\\\\t// x - Negative x direction\\\\n\\\\t// Z - Positive z direction\\\\n\\\\t// z - Negative z direction\\\\n\\\\t//\\\\n\\\\t// Source and test bed:\\\\n\\\\t// https://gist.github.com/tschw/da10c43c467ce8afd0c4\\\\n\\\\n\\\\tvec2 cubeToUV( vec3 v, float texelSizeY ) {\\\\n\\\\n\\\\t\\\\t// Number of texels to avoid at the edge of each square\\\\n\\\\n\\\\t\\\\tvec3 absV = abs( v );\\\\n\\\\n\\\\t\\\\t// Intersect unit cube\\\\n\\\\n\\\\t\\\\tfloat scaleToCube = 1.0 / max( absV.x, max( absV.y, absV.z ) );\\\\n\\\\t\\\\tabsV *= scaleToCube;\\\\n\\\\n\\\\t\\\\t// Apply scale to avoid seams\\\\n\\\\n\\\\t\\\\t// two texels less per square (one texel will do for NEAREST)\\\\n\\\\t\\\\tv *= scaleToCube * ( 1.0 - 2.0 * texelSizeY );\\\\n\\\\n\\\\t\\\\t// Unwrap\\\\n\\\\n\\\\t\\\\t// space: -1 ... 1 range for each square\\\\n\\\\t\\\\t//\\\\n\\\\t\\\\t// #X##\\\\t\\\\tdim := ( 4 , 2 )\\\\n\\\\t\\\\t// # #\\\\t\\\\tcenter := ( 1 , 1 )\\\\n\\\\n\\\\t\\\\tvec2 planar = v.xy;\\\\n\\\\n\\\\t\\\\tfloat almostATexel = 1.5 * texelSizeY;\\\\n\\\\t\\\\tfloat almostOne = 1.0 - almostATexel;\\\\n\\\\n\\\\t\\\\tif ( absV.z >= almostOne ) {\\\\n\\\\n\\\\t\\\\t\\\\tif ( v.z > 0.0 )\\\\n\\\\t\\\\t\\\\t\\\\tplanar.x = 4.0 - v.x;\\\\n\\\\n\\\\t\\\\t} else if ( absV.x >= almostOne ) {\\\\n\\\\n\\\\t\\\\t\\\\tfloat signX = sign( v.x );\\\\n\\\\t\\\\t\\\\tplanar.x = v.z * signX + 2.0 * signX;\\\\n\\\\n\\\\t\\\\t} else if ( absV.y >= almostOne ) {\\\\n\\\\n\\\\t\\\\t\\\\tfloat signY = sign( v.y );\\\\n\\\\t\\\\t\\\\tplanar.x = v.x + 2.0 * signY + 2.0;\\\\n\\\\t\\\\t\\\\tplanar.y = v.z * signY - 2.0;\\\\n\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\t// Transform to UV space\\\\n\\\\n\\\\t\\\\t// scale := 0.5 / dim\\\\n\\\\t\\\\t// translate := ( center + 0.5 ) / dim\\\\n\\\\t\\\\treturn vec2( 0.125, 0.25 ) * planar + vec2( 0.375, 0.75 );\\\\n\\\\n\\\\t}\\\\n\\\\n\\\\tfloat getPointShadow( sampler2D shadowMap, vec2 shadowMapSize, float shadowBias, float shadowRadius, vec4 shadowCoord, float shadowCameraNear, float shadowCameraFar ) {\\\\n\\\\n\\\\t\\\\tvec2 texelSize = vec2( 1.0 ) / ( shadowMapSize * vec2( 4.0, 2.0 ) );\\\\n\\\\n\\\\t\\\\t// for point lights, the uniform @vShadowCoord is re-purposed to hold\\\\n\\\\t\\\\t// the vector from the light to the world-space position of the fragment.\\\\n\\\\t\\\\tvec3 lightToPosition = shadowCoord.xyz;\\\\n\\\\n\\\\t\\\\t// dp = normalized distance from light to fragment position\\\\n\\\\t\\\\tfloat dp = ( length( lightToPosition ) - shadowCameraNear ) / ( shadowCameraFar - shadowCameraNear ); // need to clamp?\\\\n\\\\t\\\\tdp += shadowBias;\\\\n\\\\n\\\\t\\\\t// bd3D = base direction 3D\\\\n\\\\t\\\\tvec3 bd3D = normalize( lightToPosition );\\\\n\\\\n\\\\t\\\\t#if defined( SHADOWMAP_TYPE_PCF ) || defined( SHADOWMAP_TYPE_PCF_SOFT ) || defined( SHADOWMAP_TYPE_VSM )\\\\n\\\\n\\\\t\\\\t\\\\tvec2 offset = vec2( - 1, 1 ) * shadowRadius * texelSize.y;\\\\n\\\\n\\\\t\\\\t\\\\treturn (\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.xyy, texelSize.y ), dp ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.yyy, texelSize.y ), dp ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.xyx, texelSize.y ), dp ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.yyx, texelSize.y ), dp ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, cubeToUV( bd3D, texelSize.y ), dp ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.xxy, texelSize.y ), dp ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.yxy, texelSize.y ), dp ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.xxx, texelSize.y ), dp ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.yxx, texelSize.y ), dp )\\\\n\\\\t\\\\t\\\\t) * ( 1.0 / 9.0 );\\\\n\\\\n\\\\t\\\\t#else // no percentage-closer filtering\\\\n\\\\n\\\\t\\\\t\\\\treturn texture2DCompare( shadowMap, cubeToUV( bd3D, texelSize.y ), dp );\\\\n\\\\n\\\\t\\\\t#endif\\\\n\\\\n\\\\t}\\\\n\\\\n#endif\\\\n\\\\\\\",k=\\\\\\\"\\\\n#ifdef USE_TRANSMISSION\\\\n\\\\n\\\\tfloat transmissionAlpha = 1.0;\\\\n\\\\tfloat transmissionFactor = transmission;\\\\n\\\\tfloat thicknessFactor = thickness;\\\\n\\\\n\\\\t#ifdef USE_TRANSMISSIONMAP\\\\n\\\\n\\\\t\\\\ttransmissionFactor *= texture2D( transmissionMap, vUv ).r;\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\t#ifdef USE_THICKNESSMAP\\\\n\\\\n\\\\t\\\\tthicknessFactor *= texture2D( thicknessMap, vUv ).g;\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\tvec3 pos = vWorldPosition;\\\\n\\\\tvec3 v = normalize( cameraPosition - pos );\\\\n\\\\tvec3 n = inverseTransformDirection( normal, viewMatrix );\\\\n\\\\n\\\\tvec4 transmission = getIBLVolumeRefraction(\\\\n\\\\t\\\\tn, v, roughnessFactor, material.diffuseColor, material.specularColor, material.specularF90,\\\\n\\\\t\\\\tpos, modelMatrix, viewMatrix, projectionMatrix, ior, thicknessFactor,\\\\n\\\\t\\\\tattenuationTint, attenuationDistance );\\\\n\\\\n\\\\ttotalDiffuse = mix( totalDiffuse, transmission.rgb, transmissionFactor );\\\\n\\\\ttransmissionAlpha = mix( transmissionAlpha, transmission.a, transmissionFactor );\\\\n#endif\\\\n\\\\\\\";const U={alphamap_fragment:\\\\\\\"\\\\n#ifdef USE_ALPHAMAP\\\\n\\\\n\\\\tdiffuseColor.a *= texture2D( alphaMap, vUv ).g;\\\\n\\\\n#endif\\\\n\\\\\\\",alphamap_pars_fragment:\\\\\\\"\\\\n#ifdef USE_ALPHAMAP\\\\n\\\\n\\\\tuniform sampler2D alphaMap;\\\\n\\\\n#endif\\\\n\\\\\\\",alphatest_fragment:\\\\\\\"\\\\n#ifdef USE_ALPHATEST\\\\n\\\\n\\\\tif ( diffuseColor.a < alphaTest ) discard;\\\\n\\\\n#endif\\\\n\\\\\\\",alphatest_pars_fragment:\\\\\\\"\\\\n#ifdef USE_ALPHATEST\\\\n\\\\tuniform float alphaTest;\\\\n#endif\\\\n\\\\\\\",aomap_fragment:\\\\\\\"\\\\n#ifdef USE_AOMAP\\\\n\\\\n\\\\t// reads channel R, compatible with a combined OcclusionRoughnessMetallic (RGB) texture\\\\n\\\\tfloat ambientOcclusion = ( texture2D( aoMap, vUv2 ).r - 1.0 ) * aoMapIntensity + 1.0;\\\\n\\\\n\\\\treflectedLight.indirectDiffuse *= ambientOcclusion;\\\\n\\\\n\\\\t#if defined( USE_ENVMAP ) && defined( STANDARD )\\\\n\\\\n\\\\t\\\\tfloat dotNV = saturate( dot( geometry.normal, geometry.viewDir ) );\\\\n\\\\n\\\\t\\\\treflectedLight.indirectSpecular *= computeSpecularOcclusion( dotNV, ambientOcclusion, material.roughness );\\\\n\\\\n\\\\t#endif\\\\n\\\\n#endif\\\\n\\\\\\\",aomap_pars_fragment:\\\\\\\"\\\\n#ifdef USE_AOMAP\\\\n\\\\n\\\\tuniform sampler2D aoMap;\\\\n\\\\tuniform float aoMapIntensity;\\\\n\\\\n#endif\\\\n\\\\\\\",begin_vertex:\\\\\\\"\\\\nvec3 transformed = vec3( position );\\\\n\\\\\\\",beginnormal_vertex:\\\\\\\"\\\\nvec3 objectNormal = vec3( normal );\\\\n\\\\n#ifdef USE_TANGENT\\\\n\\\\n\\\\tvec3 objectTangent = vec3( tangent.xyz );\\\\n\\\\n#endif\\\\n\\\\\\\",bsdfs:'\\\\n\\\\nvec3 BRDF_Lambert( const in vec3 diffuseColor ) {\\\\n\\\\n\\\\treturn RECIPROCAL_PI * diffuseColor;\\\\n\\\\n} // validated\\\\n\\\\nvec3 F_Schlick( const in vec3 f0, const in float f90, const in float dotVH ) {\\\\n\\\\n\\\\t// Original approximation by Christophe Schlick \\\\'94\\\\n\\\\t// float fresnel = pow( 1.0 - dotVH, 5.0 );\\\\n\\\\n\\\\t// Optimized variant (presented by Epic at SIGGRAPH \\\\'13)\\\\n\\\\t// https://cdn2.unrealengine.com/Resources/files/2013SiggraphPresentationsNotes-26915738.pdf\\\\n\\\\tfloat fresnel = exp2( ( - 5.55473 * dotVH - 6.98316 ) * dotVH );\\\\n\\\\n\\\\treturn f0 * ( 1.0 - fresnel ) + ( f90 * fresnel );\\\\n\\\\n} // validated\\\\n\\\\n// Moving Frostbite to Physically Based Rendering 3.0 - page 12, listing 2\\\\n// https://seblagarde.files.wordpress.com/2015/07/course_notes_moving_frostbite_to_pbr_v32.pdf\\\\nfloat V_GGX_SmithCorrelated( const in float alpha, const in float dotNL, const in float dotNV ) {\\\\n\\\\n\\\\tfloat a2 = pow2( alpha );\\\\n\\\\n\\\\tfloat gv = dotNL * sqrt( a2 + ( 1.0 - a2 ) * pow2( dotNV ) );\\\\n\\\\tfloat gl = dotNV * sqrt( a2 + ( 1.0 - a2 ) * pow2( dotNL ) );\\\\n\\\\n\\\\treturn 0.5 / max( gv + gl, EPSILON );\\\\n\\\\n}\\\\n\\\\n// Microfacet Models for Refraction through Rough Surfaces - equation (33)\\\\n// http://graphicrants.blogspot.com/2013/08/specular-brdf-reference.html\\\\n// alpha is \\\\\\\"roughness squared\\\\\\\" in Disney’s reparameterization\\\\nfloat D_GGX( const in float alpha, const in float dotNH ) {\\\\n\\\\n\\\\tfloat a2 = pow2( alpha );\\\\n\\\\n\\\\tfloat denom = pow2( dotNH ) * ( a2 - 1.0 ) + 1.0; // avoid alpha = 0 with dotNH = 1\\\\n\\\\n\\\\treturn RECIPROCAL_PI * a2 / pow2( denom );\\\\n\\\\n}\\\\n\\\\n// GGX Distribution, Schlick Fresnel, GGX_SmithCorrelated Visibility\\\\nvec3 BRDF_GGX( const in vec3 lightDir, const in vec3 viewDir, const in vec3 normal, const in vec3 f0, const in float f90, const in float roughness ) {\\\\n\\\\n\\\\tfloat alpha = pow2( roughness ); // UE4\\\\'s roughness\\\\n\\\\n\\\\tvec3 halfDir = normalize( lightDir + viewDir );\\\\n\\\\n\\\\tfloat dotNL = saturate( dot( normal, lightDir ) );\\\\n\\\\tfloat dotNV = saturate( dot( normal, viewDir ) );\\\\n\\\\tfloat dotNH = saturate( dot( normal, halfDir ) );\\\\n\\\\tfloat dotVH = saturate( dot( viewDir, halfDir ) );\\\\n\\\\n\\\\tvec3 F = F_Schlick( f0, f90, dotVH );\\\\n\\\\n\\\\tfloat V = V_GGX_SmithCorrelated( alpha, dotNL, dotNV );\\\\n\\\\n\\\\tfloat D = D_GGX( alpha, dotNH );\\\\n\\\\n\\\\treturn F * ( V * D );\\\\n\\\\n}\\\\n\\\\n// Rect Area Light\\\\n\\\\n// Real-Time Polygonal-Light Shading with Linearly Transformed Cosines\\\\n// by Eric Heitz, Jonathan Dupuy, Stephen Hill and David Neubelt\\\\n// code: https://github.com/selfshadow/ltc_code/\\\\n\\\\nvec2 LTC_Uv( const in vec3 N, const in vec3 V, const in float roughness ) {\\\\n\\\\n\\\\tconst float LUT_SIZE = 64.0;\\\\n\\\\tconst float LUT_SCALE = ( LUT_SIZE - 1.0 ) / LUT_SIZE;\\\\n\\\\tconst float LUT_BIAS = 0.5 / LUT_SIZE;\\\\n\\\\n\\\\tfloat dotNV = saturate( dot( N, V ) );\\\\n\\\\n\\\\t// texture parameterized by sqrt( GGX alpha ) and sqrt( 1 - cos( theta ) )\\\\n\\\\tvec2 uv = vec2( roughness, sqrt( 1.0 - dotNV ) );\\\\n\\\\n\\\\tuv = uv * LUT_SCALE + LUT_BIAS;\\\\n\\\\n\\\\treturn uv;\\\\n\\\\n}\\\\n\\\\nfloat LTC_ClippedSphereFormFactor( const in vec3 f ) {\\\\n\\\\n\\\\t// Real-Time Area Lighting: a Journey from Research to Production (p.102)\\\\n\\\\t// An approximation of the form factor of a horizon-clipped rectangle.\\\\n\\\\n\\\\tfloat l = length( f );\\\\n\\\\n\\\\treturn max( ( l * l + f.z ) / ( l + 1.0 ), 0.0 );\\\\n\\\\n}\\\\n\\\\nvec3 LTC_EdgeVectorFormFactor( const in vec3 v1, const in vec3 v2 ) {\\\\n\\\\n\\\\tfloat x = dot( v1, v2 );\\\\n\\\\n\\\\tfloat y = abs( x );\\\\n\\\\n\\\\t// rational polynomial approximation to theta / sin( theta ) / 2PI\\\\n\\\\tfloat a = 0.8543985 + ( 0.4965155 + 0.0145206 * y ) * y;\\\\n\\\\tfloat b = 3.4175940 + ( 4.1616724 + y ) * y;\\\\n\\\\tfloat v = a / b;\\\\n\\\\n\\\\tfloat theta_sintheta = ( x > 0.0 ) ? v : 0.5 * inversesqrt( max( 1.0 - x * x, 1e-7 ) ) - v;\\\\n\\\\n\\\\treturn cross( v1, v2 ) * theta_sintheta;\\\\n\\\\n}\\\\n\\\\nvec3 LTC_Evaluate( const in vec3 N, const in vec3 V, const in vec3 P, const in mat3 mInv, const in vec3 rectCoords[ 4 ] ) {\\\\n\\\\n\\\\t// bail if point is on back side of plane of light\\\\n\\\\t// assumes ccw winding order of light vertices\\\\n\\\\tvec3 v1 = rectCoords[ 1 ] - rectCoords[ 0 ];\\\\n\\\\tvec3 v2 = rectCoords[ 3 ] - rectCoords[ 0 ];\\\\n\\\\tvec3 lightNormal = cross( v1, v2 );\\\\n\\\\n\\\\tif( dot( lightNormal, P - rectCoords[ 0 ] ) < 0.0 ) return vec3( 0.0 );\\\\n\\\\n\\\\t// construct orthonormal basis around N\\\\n\\\\tvec3 T1, T2;\\\\n\\\\tT1 = normalize( V - N * dot( V, N ) );\\\\n\\\\tT2 = - cross( N, T1 ); // negated from paper; possibly due to a different handedness of world coordinate system\\\\n\\\\n\\\\t// compute transform\\\\n\\\\tmat3 mat = mInv * transposeMat3( mat3( T1, T2, N ) );\\\\n\\\\n\\\\t// transform rect\\\\n\\\\tvec3 coords[ 4 ];\\\\n\\\\tcoords[ 0 ] = mat * ( rectCoords[ 0 ] - P );\\\\n\\\\tcoords[ 1 ] = mat * ( rectCoords[ 1 ] - P );\\\\n\\\\tcoords[ 2 ] = mat * ( rectCoords[ 2 ] - P );\\\\n\\\\tcoords[ 3 ] = mat * ( rectCoords[ 3 ] - P );\\\\n\\\\n\\\\t// project rect onto sphere\\\\n\\\\tcoords[ 0 ] = normalize( coords[ 0 ] );\\\\n\\\\tcoords[ 1 ] = normalize( coords[ 1 ] );\\\\n\\\\tcoords[ 2 ] = normalize( coords[ 2 ] );\\\\n\\\\tcoords[ 3 ] = normalize( coords[ 3 ] );\\\\n\\\\n\\\\t// calculate vector form factor\\\\n\\\\tvec3 vectorFormFactor = vec3( 0.0 );\\\\n\\\\tvectorFormFactor += LTC_EdgeVectorFormFactor( coords[ 0 ], coords[ 1 ] );\\\\n\\\\tvectorFormFactor += LTC_EdgeVectorFormFactor( coords[ 1 ], coords[ 2 ] );\\\\n\\\\tvectorFormFactor += LTC_EdgeVectorFormFactor( coords[ 2 ], coords[ 3 ] );\\\\n\\\\tvectorFormFactor += LTC_EdgeVectorFormFactor( coords[ 3 ], coords[ 0 ] );\\\\n\\\\n\\\\t// adjust for horizon clipping\\\\n\\\\tfloat result = LTC_ClippedSphereFormFactor( vectorFormFactor );\\\\n\\\\n/*\\\\n\\\\t// alternate method of adjusting for horizon clipping (see referece)\\\\n\\\\t// refactoring required\\\\n\\\\tfloat len = length( vectorFormFactor );\\\\n\\\\tfloat z = vectorFormFactor.z / len;\\\\n\\\\n\\\\tconst float LUT_SIZE = 64.0;\\\\n\\\\tconst float LUT_SCALE = ( LUT_SIZE - 1.0 ) / LUT_SIZE;\\\\n\\\\tconst float LUT_BIAS = 0.5 / LUT_SIZE;\\\\n\\\\n\\\\t// tabulated horizon-clipped sphere, apparently...\\\\n\\\\tvec2 uv = vec2( z * 0.5 + 0.5, len );\\\\n\\\\tuv = uv * LUT_SCALE + LUT_BIAS;\\\\n\\\\n\\\\tfloat scale = texture2D( ltc_2, uv ).w;\\\\n\\\\n\\\\tfloat result = len * scale;\\\\n*/\\\\n\\\\n\\\\treturn vec3( result );\\\\n\\\\n}\\\\n\\\\n// End Rect Area Light\\\\n\\\\n\\\\nfloat G_BlinnPhong_Implicit( /* const in float dotNL, const in float dotNV */ ) {\\\\n\\\\n\\\\t// geometry term is (n dot l)(n dot v) / 4(n dot l)(n dot v)\\\\n\\\\treturn 0.25;\\\\n\\\\n}\\\\n\\\\nfloat D_BlinnPhong( const in float shininess, const in float dotNH ) {\\\\n\\\\n\\\\treturn RECIPROCAL_PI * ( shininess * 0.5 + 1.0 ) * pow( dotNH, shininess );\\\\n\\\\n}\\\\n\\\\nvec3 BRDF_BlinnPhong( const in vec3 lightDir, const in vec3 viewDir, const in vec3 normal, const in vec3 specularColor, const in float shininess ) {\\\\n\\\\n\\\\tvec3 halfDir = normalize( lightDir + viewDir );\\\\n\\\\n\\\\tfloat dotNH = saturate( dot( normal, halfDir ) );\\\\n\\\\tfloat dotVH = saturate( dot( viewDir, halfDir ) );\\\\n\\\\n\\\\tvec3 F = F_Schlick( specularColor, 1.0, dotVH );\\\\n\\\\n\\\\tfloat G = G_BlinnPhong_Implicit( /* dotNL, dotNV */ );\\\\n\\\\n\\\\tfloat D = D_BlinnPhong( shininess, dotNH );\\\\n\\\\n\\\\treturn F * ( G * D );\\\\n\\\\n} // validated\\\\n\\\\n#if defined( USE_SHEEN )\\\\n\\\\n// https://github.com/google/filament/blob/master/shaders/src/brdf.fs\\\\nfloat D_Charlie( float roughness, float dotNH ) {\\\\n\\\\n\\\\tfloat alpha = pow2( roughness );\\\\n\\\\n\\\\t// Estevez and Kulla 2017, \\\\\\\"Production Friendly Microfacet Sheen BRDF\\\\\\\"\\\\n\\\\tfloat invAlpha = 1.0 / alpha;\\\\n\\\\tfloat cos2h = dotNH * dotNH;\\\\n\\\\tfloat sin2h = max( 1.0 - cos2h, 0.0078125 ); // 2^(-14/2), so sin2h^2 > 0 in fp16\\\\n\\\\n\\\\treturn ( 2.0 + invAlpha ) * pow( sin2h, invAlpha * 0.5 ) / ( 2.0 * PI );\\\\n\\\\n}\\\\n\\\\n// https://github.com/google/filament/blob/master/shaders/src/brdf.fs\\\\nfloat V_Neubelt( float dotNV, float dotNL ) {\\\\n\\\\n\\\\t// Neubelt and Pettineo 2013, \\\\\\\"Crafting a Next-gen Material Pipeline for The Order: 1886\\\\\\\"\\\\n\\\\treturn saturate( 1.0 / ( 4.0 * ( dotNL + dotNV - dotNL * dotNV ) ) );\\\\n\\\\n}\\\\n\\\\nvec3 BRDF_Sheen( const in vec3 lightDir, const in vec3 viewDir, const in vec3 normal, vec3 sheenTint, const in float sheenRoughness ) {\\\\n\\\\n\\\\tvec3 halfDir = normalize( lightDir + viewDir );\\\\n\\\\n\\\\tfloat dotNL = saturate( dot( normal, lightDir ) );\\\\n\\\\tfloat dotNV = saturate( dot( normal, viewDir ) );\\\\n\\\\tfloat dotNH = saturate( dot( normal, halfDir ) );\\\\n\\\\n\\\\tfloat D = D_Charlie( sheenRoughness, dotNH );\\\\n\\\\tfloat V = V_Neubelt( dotNV, dotNL );\\\\n\\\\n\\\\treturn sheenTint * ( D * V );\\\\n\\\\n}\\\\n\\\\n#endif\\\\n',bumpmap_pars_fragment:\\\\\\\"\\\\n#ifdef USE_BUMPMAP\\\\n\\\\n\\\\tuniform sampler2D bumpMap;\\\\n\\\\tuniform float bumpScale;\\\\n\\\\n\\\\t// Bump Mapping Unparametrized Surfaces on the GPU by Morten S. Mikkelsen\\\\n\\\\t// http://api.unrealengine.com/attachments/Engine/Rendering/LightingAndShadows/BumpMappingWithoutTangentSpace/mm_sfgrad_bump.pdf\\\\n\\\\n\\\\t// Evaluate the derivative of the height w.r.t. screen-space using forward differencing (listing 2)\\\\n\\\\n\\\\tvec2 dHdxy_fwd() {\\\\n\\\\n\\\\t\\\\tvec2 dSTdx = dFdx( vUv );\\\\n\\\\t\\\\tvec2 dSTdy = dFdy( vUv );\\\\n\\\\n\\\\t\\\\tfloat Hll = bumpScale * texture2D( bumpMap, vUv ).x;\\\\n\\\\t\\\\tfloat dBx = bumpScale * texture2D( bumpMap, vUv + dSTdx ).x - Hll;\\\\n\\\\t\\\\tfloat dBy = bumpScale * texture2D( bumpMap, vUv + dSTdy ).x - Hll;\\\\n\\\\n\\\\t\\\\treturn vec2( dBx, dBy );\\\\n\\\\n\\\\t}\\\\n\\\\n\\\\tvec3 perturbNormalArb( vec3 surf_pos, vec3 surf_norm, vec2 dHdxy, float faceDirection ) {\\\\n\\\\n\\\\t\\\\t// Workaround for Adreno 3XX dFd*( vec3 ) bug. See #9988\\\\n\\\\n\\\\t\\\\tvec3 vSigmaX = vec3( dFdx( surf_pos.x ), dFdx( surf_pos.y ), dFdx( surf_pos.z ) );\\\\n\\\\t\\\\tvec3 vSigmaY = vec3( dFdy( surf_pos.x ), dFdy( surf_pos.y ), dFdy( surf_pos.z ) );\\\\n\\\\t\\\\tvec3 vN = surf_norm;\\\\t\\\\t// normalized\\\\n\\\\n\\\\t\\\\tvec3 R1 = cross( vSigmaY, vN );\\\\n\\\\t\\\\tvec3 R2 = cross( vN, vSigmaX );\\\\n\\\\n\\\\t\\\\tfloat fDet = dot( vSigmaX, R1 ) * faceDirection;\\\\n\\\\n\\\\t\\\\tvec3 vGrad = sign( fDet ) * ( dHdxy.x * R1 + dHdxy.y * R2 );\\\\n\\\\t\\\\treturn normalize( abs( fDet ) * surf_norm - vGrad );\\\\n\\\\n\\\\t}\\\\n\\\\n#endif\\\\n\\\\\\\",clipping_planes_fragment:\\\\\\\"\\\\n#if NUM_CLIPPING_PLANES > 0\\\\n\\\\n\\\\tvec4 plane;\\\\n\\\\n\\\\t#pragma unroll_loop_start\\\\n\\\\tfor ( int i = 0; i < UNION_CLIPPING_PLANES; i ++ ) {\\\\n\\\\n\\\\t\\\\tplane = clippingPlanes[ i ];\\\\n\\\\t\\\\tif ( dot( vClipPosition, plane.xyz ) > plane.w ) discard;\\\\n\\\\n\\\\t}\\\\n\\\\t#pragma unroll_loop_end\\\\n\\\\n\\\\t#if UNION_CLIPPING_PLANES < NUM_CLIPPING_PLANES\\\\n\\\\n\\\\t\\\\tbool clipped = true;\\\\n\\\\n\\\\t\\\\t#pragma unroll_loop_start\\\\n\\\\t\\\\tfor ( int i = UNION_CLIPPING_PLANES; i < NUM_CLIPPING_PLANES; i ++ ) {\\\\n\\\\n\\\\t\\\\t\\\\tplane = clippingPlanes[ i ];\\\\n\\\\t\\\\t\\\\tclipped = ( dot( vClipPosition, plane.xyz ) > plane.w ) && clipped;\\\\n\\\\n\\\\t\\\\t}\\\\n\\\\t\\\\t#pragma unroll_loop_end\\\\n\\\\n\\\\t\\\\tif ( clipped ) discard;\\\\n\\\\n\\\\t#endif\\\\n\\\\n#endif\\\\n\\\\\\\",clipping_planes_pars_fragment:\\\\\\\"\\\\n#if NUM_CLIPPING_PLANES > 0\\\\n\\\\n\\\\tvarying vec3 vClipPosition;\\\\n\\\\n\\\\tuniform vec4 clippingPlanes[ NUM_CLIPPING_PLANES ];\\\\n\\\\n#endif\\\\n\\\\\\\",clipping_planes_pars_vertex:\\\\\\\"\\\\n#if NUM_CLIPPING_PLANES > 0\\\\n\\\\n\\\\tvarying vec3 vClipPosition;\\\\n\\\\n#endif\\\\n\\\\\\\",clipping_planes_vertex:\\\\\\\"\\\\n#if NUM_CLIPPING_PLANES > 0\\\\n\\\\n\\\\tvClipPosition = - mvPosition.xyz;\\\\n\\\\n#endif\\\\n\\\\\\\",color_fragment:\\\\\\\"\\\\n#if defined( USE_COLOR_ALPHA )\\\\n\\\\n\\\\tdiffuseColor *= vColor;\\\\n\\\\n#elif defined( USE_COLOR )\\\\n\\\\n\\\\tdiffuseColor.rgb *= vColor;\\\\n\\\\n#endif\\\\n\\\\\\\",color_pars_fragment:\\\\\\\"\\\\n#if defined( USE_COLOR_ALPHA )\\\\n\\\\n\\\\tvarying vec4 vColor;\\\\n\\\\n#elif defined( USE_COLOR )\\\\n\\\\n\\\\tvarying vec3 vColor;\\\\n\\\\n#endif\\\\n\\\\\\\",color_pars_vertex:\\\\\\\"\\\\n#if defined( USE_COLOR_ALPHA )\\\\n\\\\n\\\\tvarying vec4 vColor;\\\\n\\\\n#elif defined( USE_COLOR ) || defined( USE_INSTANCING_COLOR )\\\\n\\\\n\\\\tvarying vec3 vColor;\\\\n\\\\n#endif\\\\n\\\\\\\",color_vertex:\\\\\\\"\\\\n#if defined( USE_COLOR_ALPHA )\\\\n\\\\n\\\\tvColor = vec4( 1.0 );\\\\n\\\\n#elif defined( USE_COLOR ) || defined( USE_INSTANCING_COLOR )\\\\n\\\\n\\\\tvColor = vec3( 1.0 );\\\\n\\\\n#endif\\\\n\\\\n#ifdef USE_COLOR\\\\n\\\\n\\\\tvColor *= color;\\\\n\\\\n#endif\\\\n\\\\n#ifdef USE_INSTANCING_COLOR\\\\n\\\\n\\\\tvColor.xyz *= instanceColor.xyz;\\\\n\\\\n#endif\\\\n\\\\\\\",common:\\\\\\\"\\\\n#define PI 3.141592653589793\\\\n#define PI2 6.283185307179586\\\\n#define PI_HALF 1.5707963267948966\\\\n#define RECIPROCAL_PI 0.3183098861837907\\\\n#define RECIPROCAL_PI2 0.15915494309189535\\\\n#define EPSILON 1e-6\\\\n\\\\n#ifndef saturate\\\\n// may have defined saturate() already\\\\n#define saturate( a ) clamp( a, 0.0, 1.0 )\\\\n#endif\\\\n#define whiteComplement( a ) ( 1.0 - saturate( a ) )\\\\n\\\\nfloat pow2( const in float x ) { return x*x; }\\\\nfloat pow3( const in float x ) { return x*x*x; }\\\\nfloat pow4( const in float x ) { float x2 = x*x; return x2*x2; }\\\\nfloat max3( const in vec3 v ) { return max( max( v.x, v.y ), v.z ); }\\\\nfloat average( const in vec3 color ) { return dot( color, vec3( 0.3333 ) ); }\\\\n\\\\n// expects values in the range of [0,1]x[0,1], returns values in the [0,1] range.\\\\n// do not collapse into a single function per: http://byteblacksmith.com/improvements-to-the-canonical-one-liner-glsl-rand-for-opengl-es-2-0/\\\\nhighp float rand( const in vec2 uv ) {\\\\n\\\\n\\\\tconst highp float a = 12.9898, b = 78.233, c = 43758.5453;\\\\n\\\\thighp float dt = dot( uv.xy, vec2( a,b ) ), sn = mod( dt, PI );\\\\n\\\\n\\\\treturn fract( sin( sn ) * c );\\\\n\\\\n}\\\\n\\\\n#ifdef HIGH_PRECISION\\\\n\\\\tfloat precisionSafeLength( vec3 v ) { return length( v ); }\\\\n#else\\\\n\\\\tfloat precisionSafeLength( vec3 v ) {\\\\n\\\\t\\\\tfloat maxComponent = max3( abs( v ) );\\\\n\\\\t\\\\treturn length( v / maxComponent ) * maxComponent;\\\\n\\\\t}\\\\n#endif\\\\n\\\\nstruct IncidentLight {\\\\n\\\\tvec3 color;\\\\n\\\\tvec3 direction;\\\\n\\\\tbool visible;\\\\n};\\\\n\\\\nstruct ReflectedLight {\\\\n\\\\tvec3 directDiffuse;\\\\n\\\\tvec3 directSpecular;\\\\n\\\\tvec3 indirectDiffuse;\\\\n\\\\tvec3 indirectSpecular;\\\\n};\\\\n\\\\nstruct GeometricContext {\\\\n\\\\tvec3 position;\\\\n\\\\tvec3 normal;\\\\n\\\\tvec3 viewDir;\\\\n#ifdef USE_CLEARCOAT\\\\n\\\\tvec3 clearcoatNormal;\\\\n#endif\\\\n};\\\\n\\\\nvec3 transformDirection( in vec3 dir, in mat4 matrix ) {\\\\n\\\\n\\\\treturn normalize( ( matrix * vec4( dir, 0.0 ) ).xyz );\\\\n\\\\n}\\\\n\\\\nvec3 inverseTransformDirection( in vec3 dir, in mat4 matrix ) {\\\\n\\\\n\\\\t// dir can be either a direction vector or a normal vector\\\\n\\\\t// upper-left 3x3 of matrix is assumed to be orthogonal\\\\n\\\\n\\\\treturn normalize( ( vec4( dir, 0.0 ) * matrix ).xyz );\\\\n\\\\n}\\\\n\\\\nmat3 transposeMat3( const in mat3 m ) {\\\\n\\\\n\\\\tmat3 tmp;\\\\n\\\\n\\\\ttmp[ 0 ] = vec3( m[ 0 ].x, m[ 1 ].x, m[ 2 ].x );\\\\n\\\\ttmp[ 1 ] = vec3( m[ 0 ].y, m[ 1 ].y, m[ 2 ].y );\\\\n\\\\ttmp[ 2 ] = vec3( m[ 0 ].z, m[ 1 ].z, m[ 2 ].z );\\\\n\\\\n\\\\treturn tmp;\\\\n\\\\n}\\\\n\\\\n// https://en.wikipedia.org/wiki/Relative_luminance\\\\nfloat linearToRelativeLuminance( const in vec3 color ) {\\\\n\\\\n\\\\tvec3 weights = vec3( 0.2126, 0.7152, 0.0722 );\\\\n\\\\n\\\\treturn dot( weights, color.rgb );\\\\n\\\\n}\\\\n\\\\nbool isPerspectiveMatrix( mat4 m ) {\\\\n\\\\n\\\\treturn m[ 2 ][ 3 ] == - 1.0;\\\\n\\\\n}\\\\n\\\\nvec2 equirectUv( in vec3 dir ) {\\\\n\\\\n\\\\t// dir is assumed to be unit length\\\\n\\\\n\\\\tfloat u = atan( dir.z, dir.x ) * RECIPROCAL_PI2 + 0.5;\\\\n\\\\n\\\\tfloat v = asin( clamp( dir.y, - 1.0, 1.0 ) ) * RECIPROCAL_PI + 0.5;\\\\n\\\\n\\\\treturn vec2( u, v );\\\\n\\\\n}\\\\n\\\\\\\",cube_uv_reflection_fragment:\\\\\\\"\\\\n#ifdef ENVMAP_TYPE_CUBE_UV\\\\n\\\\n\\\\t#define cubeUV_maxMipLevel 8.0\\\\n\\\\t#define cubeUV_minMipLevel 4.0\\\\n\\\\t#define cubeUV_maxTileSize 256.0\\\\n\\\\t#define cubeUV_minTileSize 16.0\\\\n\\\\n\\\\t// These shader functions convert between the UV coordinates of a single face of\\\\n\\\\t// a cubemap, the 0-5 integer index of a cube face, and the direction vector for\\\\n\\\\t// sampling a textureCube (not generally normalized ).\\\\n\\\\n\\\\tfloat getFace( vec3 direction ) {\\\\n\\\\n\\\\t\\\\tvec3 absDirection = abs( direction );\\\\n\\\\n\\\\t\\\\tfloat face = - 1.0;\\\\n\\\\n\\\\t\\\\tif ( absDirection.x > absDirection.z ) {\\\\n\\\\n\\\\t\\\\t\\\\tif ( absDirection.x > absDirection.y )\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tface = direction.x > 0.0 ? 0.0 : 3.0;\\\\n\\\\n\\\\t\\\\t\\\\telse\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tface = direction.y > 0.0 ? 1.0 : 4.0;\\\\n\\\\n\\\\t\\\\t} else {\\\\n\\\\n\\\\t\\\\t\\\\tif ( absDirection.z > absDirection.y )\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tface = direction.z > 0.0 ? 2.0 : 5.0;\\\\n\\\\n\\\\t\\\\t\\\\telse\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tface = direction.y > 0.0 ? 1.0 : 4.0;\\\\n\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\treturn face;\\\\n\\\\n\\\\t}\\\\n\\\\n\\\\t// RH coordinate system; PMREM face-indexing convention\\\\n\\\\tvec2 getUV( vec3 direction, float face ) {\\\\n\\\\n\\\\t\\\\tvec2 uv;\\\\n\\\\n\\\\t\\\\tif ( face == 0.0 ) {\\\\n\\\\n\\\\t\\\\t\\\\tuv = vec2( direction.z, direction.y ) / abs( direction.x ); // pos x\\\\n\\\\n\\\\t\\\\t} else if ( face == 1.0 ) {\\\\n\\\\n\\\\t\\\\t\\\\tuv = vec2( - direction.x, - direction.z ) / abs( direction.y ); // pos y\\\\n\\\\n\\\\t\\\\t} else if ( face == 2.0 ) {\\\\n\\\\n\\\\t\\\\t\\\\tuv = vec2( - direction.x, direction.y ) / abs( direction.z ); // pos z\\\\n\\\\n\\\\t\\\\t} else if ( face == 3.0 ) {\\\\n\\\\n\\\\t\\\\t\\\\tuv = vec2( - direction.z, direction.y ) / abs( direction.x ); // neg x\\\\n\\\\n\\\\t\\\\t} else if ( face == 4.0 ) {\\\\n\\\\n\\\\t\\\\t\\\\tuv = vec2( - direction.x, direction.z ) / abs( direction.y ); // neg y\\\\n\\\\n\\\\t\\\\t} else {\\\\n\\\\n\\\\t\\\\t\\\\tuv = vec2( direction.x, direction.y ) / abs( direction.z ); // neg z\\\\n\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\treturn 0.5 * ( uv + 1.0 );\\\\n\\\\n\\\\t}\\\\n\\\\n\\\\tvec3 bilinearCubeUV( sampler2D envMap, vec3 direction, float mipInt ) {\\\\n\\\\n\\\\t\\\\tfloat face = getFace( direction );\\\\n\\\\n\\\\t\\\\tfloat filterInt = max( cubeUV_minMipLevel - mipInt, 0.0 );\\\\n\\\\n\\\\t\\\\tmipInt = max( mipInt, cubeUV_minMipLevel );\\\\n\\\\n\\\\t\\\\tfloat faceSize = exp2( mipInt );\\\\n\\\\n\\\\t\\\\tfloat texelSize = 1.0 / ( 3.0 * cubeUV_maxTileSize );\\\\n\\\\n\\\\t\\\\tvec2 uv = getUV( direction, face ) * ( faceSize - 1.0 );\\\\n\\\\n\\\\t\\\\tvec2 f = fract( uv );\\\\n\\\\n\\\\t\\\\tuv += 0.5 - f;\\\\n\\\\n\\\\t\\\\tif ( face > 2.0 ) {\\\\n\\\\n\\\\t\\\\t\\\\tuv.y += faceSize;\\\\n\\\\n\\\\t\\\\t\\\\tface -= 3.0;\\\\n\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\tuv.x += face * faceSize;\\\\n\\\\n\\\\t\\\\tif ( mipInt < cubeUV_maxMipLevel ) {\\\\n\\\\n\\\\t\\\\t\\\\tuv.y += 2.0 * cubeUV_maxTileSize;\\\\n\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\tuv.y += filterInt * 2.0 * cubeUV_minTileSize;\\\\n\\\\n\\\\t\\\\tuv.x += 3.0 * max( 0.0, cubeUV_maxTileSize - 2.0 * faceSize );\\\\n\\\\n\\\\t\\\\tuv *= texelSize;\\\\n\\\\n\\\\t\\\\tvec3 tl = envMapTexelToLinear( texture2D( envMap, uv ) ).rgb;\\\\n\\\\n\\\\t\\\\tuv.x += texelSize;\\\\n\\\\n\\\\t\\\\tvec3 tr = envMapTexelToLinear( texture2D( envMap, uv ) ).rgb;\\\\n\\\\n\\\\t\\\\tuv.y += texelSize;\\\\n\\\\n\\\\t\\\\tvec3 br = envMapTexelToLinear( texture2D( envMap, uv ) ).rgb;\\\\n\\\\n\\\\t\\\\tuv.x -= texelSize;\\\\n\\\\n\\\\t\\\\tvec3 bl = envMapTexelToLinear( texture2D( envMap, uv ) ).rgb;\\\\n\\\\n\\\\t\\\\tvec3 tm = mix( tl, tr, f.x );\\\\n\\\\n\\\\t\\\\tvec3 bm = mix( bl, br, f.x );\\\\n\\\\n\\\\t\\\\treturn mix( tm, bm, f.y );\\\\n\\\\n\\\\t}\\\\n\\\\n\\\\t// These defines must match with PMREMGenerator\\\\n\\\\n\\\\t#define r0 1.0\\\\n\\\\t#define v0 0.339\\\\n\\\\t#define m0 - 2.0\\\\n\\\\t#define r1 0.8\\\\n\\\\t#define v1 0.276\\\\n\\\\t#define m1 - 1.0\\\\n\\\\t#define r4 0.4\\\\n\\\\t#define v4 0.046\\\\n\\\\t#define m4 2.0\\\\n\\\\t#define r5 0.305\\\\n\\\\t#define v5 0.016\\\\n\\\\t#define m5 3.0\\\\n\\\\t#define r6 0.21\\\\n\\\\t#define v6 0.0038\\\\n\\\\t#define m6 4.0\\\\n\\\\n\\\\tfloat roughnessToMip( float roughness ) {\\\\n\\\\n\\\\t\\\\tfloat mip = 0.0;\\\\n\\\\n\\\\t\\\\tif ( roughness >= r1 ) {\\\\n\\\\n\\\\t\\\\t\\\\tmip = ( r0 - roughness ) * ( m1 - m0 ) / ( r0 - r1 ) + m0;\\\\n\\\\n\\\\t\\\\t} else if ( roughness >= r4 ) {\\\\n\\\\n\\\\t\\\\t\\\\tmip = ( r1 - roughness ) * ( m4 - m1 ) / ( r1 - r4 ) + m1;\\\\n\\\\n\\\\t\\\\t} else if ( roughness >= r5 ) {\\\\n\\\\n\\\\t\\\\t\\\\tmip = ( r4 - roughness ) * ( m5 - m4 ) / ( r4 - r5 ) + m4;\\\\n\\\\n\\\\t\\\\t} else if ( roughness >= r6 ) {\\\\n\\\\n\\\\t\\\\t\\\\tmip = ( r5 - roughness ) * ( m6 - m5 ) / ( r5 - r6 ) + m5;\\\\n\\\\n\\\\t\\\\t} else {\\\\n\\\\n\\\\t\\\\t\\\\tmip = - 2.0 * log2( 1.16 * roughness ); // 1.16 = 1.79^0.25\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\treturn mip;\\\\n\\\\n\\\\t}\\\\n\\\\n\\\\tvec4 textureCubeUV( sampler2D envMap, vec3 sampleDir, float roughness ) {\\\\n\\\\n\\\\t\\\\tfloat mip = clamp( roughnessToMip( roughness ), m0, cubeUV_maxMipLevel );\\\\n\\\\n\\\\t\\\\tfloat mipF = fract( mip );\\\\n\\\\n\\\\t\\\\tfloat mipInt = floor( mip );\\\\n\\\\n\\\\t\\\\tvec3 color0 = bilinearCubeUV( envMap, sampleDir, mipInt );\\\\n\\\\n\\\\t\\\\tif ( mipF == 0.0 ) {\\\\n\\\\n\\\\t\\\\t\\\\treturn vec4( color0, 1.0 );\\\\n\\\\n\\\\t\\\\t} else {\\\\n\\\\n\\\\t\\\\t\\\\tvec3 color1 = bilinearCubeUV( envMap, sampleDir, mipInt + 1.0 );\\\\n\\\\n\\\\t\\\\t\\\\treturn vec4( mix( color0, color1, mipF ), 1.0 );\\\\n\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\t}\\\\n\\\\n#endif\\\\n\\\\\\\",defaultnormal_vertex:\\\\\\\"\\\\nvec3 transformedNormal = objectNormal;\\\\n\\\\n#ifdef USE_INSTANCING\\\\n\\\\n\\\\t// this is in lieu of a per-instance normal-matrix\\\\n\\\\t// shear transforms in the instance matrix are not supported\\\\n\\\\n\\\\tmat3 m = mat3( instanceMatrix );\\\\n\\\\n\\\\ttransformedNormal /= vec3( dot( m[ 0 ], m[ 0 ] ), dot( m[ 1 ], m[ 1 ] ), dot( m[ 2 ], m[ 2 ] ) );\\\\n\\\\n\\\\ttransformedNormal = m * transformedNormal;\\\\n\\\\n#endif\\\\n\\\\ntransformedNormal = normalMatrix * transformedNormal;\\\\n\\\\n#ifdef FLIP_SIDED\\\\n\\\\n\\\\ttransformedNormal = - transformedNormal;\\\\n\\\\n#endif\\\\n\\\\n#ifdef USE_TANGENT\\\\n\\\\n\\\\tvec3 transformedTangent = ( modelViewMatrix * vec4( objectTangent, 0.0 ) ).xyz;\\\\n\\\\n\\\\t#ifdef FLIP_SIDED\\\\n\\\\n\\\\t\\\\ttransformedTangent = - transformedTangent;\\\\n\\\\n\\\\t#endif\\\\n\\\\n#endif\\\\n\\\\\\\",displacementmap_pars_vertex:\\\\\\\"\\\\n#ifdef USE_DISPLACEMENTMAP\\\\n\\\\n\\\\tuniform sampler2D displacementMap;\\\\n\\\\tuniform float displacementScale;\\\\n\\\\tuniform float displacementBias;\\\\n\\\\n#endif\\\\n\\\\\\\",displacementmap_vertex:\\\\\\\"\\\\n#ifdef USE_DISPLACEMENTMAP\\\\n\\\\n\\\\ttransformed += normalize( objectNormal ) * ( texture2D( displacementMap, vUv ).x * displacementScale + displacementBias );\\\\n\\\\n#endif\\\\n\\\\\\\",emissivemap_fragment:\\\\\\\"\\\\n#ifdef USE_EMISSIVEMAP\\\\n\\\\n\\\\tvec4 emissiveColor = texture2D( emissiveMap, vUv );\\\\n\\\\n\\\\temissiveColor.rgb = emissiveMapTexelToLinear( emissiveColor ).rgb;\\\\n\\\\n\\\\ttotalEmissiveRadiance *= emissiveColor.rgb;\\\\n\\\\n#endif\\\\n\\\\\\\",emissivemap_pars_fragment:\\\\\\\"\\\\n#ifdef USE_EMISSIVEMAP\\\\n\\\\n\\\\tuniform sampler2D emissiveMap;\\\\n\\\\n#endif\\\\n\\\\\\\",encodings_fragment:\\\\\\\"\\\\ngl_FragColor = linearToOutputTexel( gl_FragColor );\\\\n\\\\\\\",encodings_pars_fragment:\\\\\\\"\\\\n// For a discussion of what this is, please read this: http://lousodrome.net/blog/light/2013/05/26/gamma-correct-and-hdr-rendering-in-a-32-bits-buffer/\\\\n\\\\nvec4 LinearToLinear( in vec4 value ) {\\\\n\\\\treturn value;\\\\n}\\\\n\\\\nvec4 GammaToLinear( in vec4 value, in float gammaFactor ) {\\\\n\\\\treturn vec4( pow( value.rgb, vec3( gammaFactor ) ), value.a );\\\\n}\\\\n\\\\nvec4 LinearToGamma( in vec4 value, in float gammaFactor ) {\\\\n\\\\treturn vec4( pow( value.rgb, vec3( 1.0 / gammaFactor ) ), value.a );\\\\n}\\\\n\\\\nvec4 sRGBToLinear( in vec4 value ) {\\\\n\\\\treturn vec4( mix( pow( value.rgb * 0.9478672986 + vec3( 0.0521327014 ), vec3( 2.4 ) ), value.rgb * 0.0773993808, vec3( lessThanEqual( value.rgb, vec3( 0.04045 ) ) ) ), value.a );\\\\n}\\\\n\\\\nvec4 LinearTosRGB( in vec4 value ) {\\\\n\\\\treturn vec4( mix( pow( value.rgb, vec3( 0.41666 ) ) * 1.055 - vec3( 0.055 ), value.rgb * 12.92, vec3( lessThanEqual( value.rgb, vec3( 0.0031308 ) ) ) ), value.a );\\\\n}\\\\n\\\\nvec4 RGBEToLinear( in vec4 value ) {\\\\n\\\\treturn vec4( value.rgb * exp2( value.a * 255.0 - 128.0 ), 1.0 );\\\\n}\\\\n\\\\nvec4 LinearToRGBE( in vec4 value ) {\\\\n\\\\tfloat maxComponent = max( max( value.r, value.g ), value.b );\\\\n\\\\tfloat fExp = clamp( ceil( log2( maxComponent ) ), -128.0, 127.0 );\\\\n\\\\treturn vec4( value.rgb / exp2( fExp ), ( fExp + 128.0 ) / 255.0 );\\\\n\\\\t// return vec4( value.brg, ( 3.0 + 128.0 ) / 256.0 );\\\\n}\\\\n\\\\n// reference: http://iwasbeingirony.blogspot.ca/2010/06/difference-between-rgbm-and-rgbd.html\\\\nvec4 RGBMToLinear( in vec4 value, in float maxRange ) {\\\\n\\\\treturn vec4( value.rgb * value.a * maxRange, 1.0 );\\\\n}\\\\n\\\\nvec4 LinearToRGBM( in vec4 value, in float maxRange ) {\\\\n\\\\tfloat maxRGB = max( value.r, max( value.g, value.b ) );\\\\n\\\\tfloat M = clamp( maxRGB / maxRange, 0.0, 1.0 );\\\\n\\\\tM = ceil( M * 255.0 ) / 255.0;\\\\n\\\\treturn vec4( value.rgb / ( M * maxRange ), M );\\\\n}\\\\n\\\\n// reference: http://iwasbeingirony.blogspot.ca/2010/06/difference-between-rgbm-and-rgbd.html\\\\nvec4 RGBDToLinear( in vec4 value, in float maxRange ) {\\\\n\\\\treturn vec4( value.rgb * ( ( maxRange / 255.0 ) / value.a ), 1.0 );\\\\n}\\\\n\\\\nvec4 LinearToRGBD( in vec4 value, in float maxRange ) {\\\\n\\\\tfloat maxRGB = max( value.r, max( value.g, value.b ) );\\\\n\\\\tfloat D = max( maxRange / maxRGB, 1.0 );\\\\n\\\\t// NOTE: The implementation with min causes the shader to not compile on\\\\n\\\\t// a common Alcatel A502DL in Chrome 78/Android 8.1. Some research suggests \\\\n\\\\t// that the chipset is Mediatek MT6739 w/ IMG PowerVR GE8100 GPU.\\\\n\\\\t// D = min( floor( D ) / 255.0, 1.0 );\\\\n\\\\tD = clamp( floor( D ) / 255.0, 0.0, 1.0 );\\\\n\\\\treturn vec4( value.rgb * ( D * ( 255.0 / maxRange ) ), D );\\\\n}\\\\n\\\\n// LogLuv reference: http://graphicrants.blogspot.ca/2009/04/rgbm-color-encoding.html\\\\n\\\\n// M matrix, for encoding\\\\nconst mat3 cLogLuvM = mat3( 0.2209, 0.3390, 0.4184, 0.1138, 0.6780, 0.7319, 0.0102, 0.1130, 0.2969 );\\\\nvec4 LinearToLogLuv( in vec4 value ) {\\\\n\\\\tvec3 Xp_Y_XYZp = cLogLuvM * value.rgb;\\\\n\\\\tXp_Y_XYZp = max( Xp_Y_XYZp, vec3( 1e-6, 1e-6, 1e-6 ) );\\\\n\\\\tvec4 vResult;\\\\n\\\\tvResult.xy = Xp_Y_XYZp.xy / Xp_Y_XYZp.z;\\\\n\\\\tfloat Le = 2.0 * log2(Xp_Y_XYZp.y) + 127.0;\\\\n\\\\tvResult.w = fract( Le );\\\\n\\\\tvResult.z = ( Le - ( floor( vResult.w * 255.0 ) ) / 255.0 ) / 255.0;\\\\n\\\\treturn vResult;\\\\n}\\\\n\\\\n// Inverse M matrix, for decoding\\\\nconst mat3 cLogLuvInverseM = mat3( 6.0014, -2.7008, -1.7996, -1.3320, 3.1029, -5.7721, 0.3008, -1.0882, 5.6268 );\\\\nvec4 LogLuvToLinear( in vec4 value ) {\\\\n\\\\tfloat Le = value.z * 255.0 + value.w;\\\\n\\\\tvec3 Xp_Y_XYZp;\\\\n\\\\tXp_Y_XYZp.y = exp2( ( Le - 127.0 ) / 2.0 );\\\\n\\\\tXp_Y_XYZp.z = Xp_Y_XYZp.y / value.y;\\\\n\\\\tXp_Y_XYZp.x = value.x * Xp_Y_XYZp.z;\\\\n\\\\tvec3 vRGB = cLogLuvInverseM * Xp_Y_XYZp.rgb;\\\\n\\\\treturn vec4( max( vRGB, 0.0 ), 1.0 );\\\\n}\\\\n\\\\\\\",envmap_fragment:\\\\\\\"\\\\n#ifdef USE_ENVMAP\\\\n\\\\n\\\\t#ifdef ENV_WORLDPOS\\\\n\\\\n\\\\t\\\\tvec3 cameraToFrag;\\\\n\\\\n\\\\t\\\\tif ( isOrthographic ) {\\\\n\\\\n\\\\t\\\\t\\\\tcameraToFrag = normalize( vec3( - viewMatrix[ 0 ][ 2 ], - viewMatrix[ 1 ][ 2 ], - viewMatrix[ 2 ][ 2 ] ) );\\\\n\\\\n\\\\t\\\\t} else {\\\\n\\\\n\\\\t\\\\t\\\\tcameraToFrag = normalize( vWorldPosition - cameraPosition );\\\\n\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\t// Transforming Normal Vectors with the Inverse Transformation\\\\n\\\\t\\\\tvec3 worldNormal = inverseTransformDirection( normal, viewMatrix );\\\\n\\\\n\\\\t\\\\t#ifdef ENVMAP_MODE_REFLECTION\\\\n\\\\n\\\\t\\\\t\\\\tvec3 reflectVec = reflect( cameraToFrag, worldNormal );\\\\n\\\\n\\\\t\\\\t#else\\\\n\\\\n\\\\t\\\\t\\\\tvec3 reflectVec = refract( cameraToFrag, worldNormal, refractionRatio );\\\\n\\\\n\\\\t\\\\t#endif\\\\n\\\\n\\\\t#else\\\\n\\\\n\\\\t\\\\tvec3 reflectVec = vReflect;\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\t#ifdef ENVMAP_TYPE_CUBE\\\\n\\\\n\\\\t\\\\tvec4 envColor = textureCube( envMap, vec3( flipEnvMap * reflectVec.x, reflectVec.yz ) );\\\\n\\\\n\\\\t\\\\tenvColor = envMapTexelToLinear( envColor );\\\\n\\\\n\\\\t#elif defined( ENVMAP_TYPE_CUBE_UV )\\\\n\\\\n\\\\t\\\\tvec4 envColor = textureCubeUV( envMap, reflectVec, 0.0 );\\\\n\\\\n\\\\t#else\\\\n\\\\n\\\\t\\\\tvec4 envColor = vec4( 0.0 );\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\t#ifdef ENVMAP_BLENDING_MULTIPLY\\\\n\\\\n\\\\t\\\\toutgoingLight = mix( outgoingLight, outgoingLight * envColor.xyz, specularStrength * reflectivity );\\\\n\\\\n\\\\t#elif defined( ENVMAP_BLENDING_MIX )\\\\n\\\\n\\\\t\\\\toutgoingLight = mix( outgoingLight, envColor.xyz, specularStrength * reflectivity );\\\\n\\\\n\\\\t#elif defined( ENVMAP_BLENDING_ADD )\\\\n\\\\n\\\\t\\\\toutgoingLight += envColor.xyz * specularStrength * reflectivity;\\\\n\\\\n\\\\t#endif\\\\n\\\\n#endif\\\\n\\\\\\\",envmap_common_pars_fragment:\\\\\\\"\\\\n#ifdef USE_ENVMAP\\\\n\\\\n\\\\tuniform float envMapIntensity;\\\\n\\\\tuniform float flipEnvMap;\\\\n\\\\tuniform int maxMipLevel;\\\\n\\\\n\\\\t#ifdef ENVMAP_TYPE_CUBE\\\\n\\\\t\\\\tuniform samplerCube envMap;\\\\n\\\\t#else\\\\n\\\\t\\\\tuniform sampler2D envMap;\\\\n\\\\t#endif\\\\n\\\\t\\\\n#endif\\\\n\\\\\\\",envmap_pars_fragment:\\\\\\\"\\\\n#ifdef USE_ENVMAP\\\\n\\\\n\\\\tuniform float reflectivity;\\\\n\\\\n\\\\t#if defined( USE_BUMPMAP ) || defined( USE_NORMALMAP ) || defined( PHONG )\\\\n\\\\n\\\\t\\\\t#define ENV_WORLDPOS\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\t#ifdef ENV_WORLDPOS\\\\n\\\\n\\\\t\\\\tvarying vec3 vWorldPosition;\\\\n\\\\t\\\\tuniform float refractionRatio;\\\\n\\\\t#else\\\\n\\\\t\\\\tvarying vec3 vReflect;\\\\n\\\\t#endif\\\\n\\\\n#endif\\\\n\\\\\\\",envmap_pars_vertex:\\\\\\\"\\\\n#ifdef USE_ENVMAP\\\\n\\\\n\\\\t#if defined( USE_BUMPMAP ) || defined( USE_NORMALMAP ) ||defined( PHONG )\\\\n\\\\n\\\\t\\\\t#define ENV_WORLDPOS\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\t#ifdef ENV_WORLDPOS\\\\n\\\\t\\\\t\\\\n\\\\t\\\\tvarying vec3 vWorldPosition;\\\\n\\\\n\\\\t#else\\\\n\\\\n\\\\t\\\\tvarying vec3 vReflect;\\\\n\\\\t\\\\tuniform float refractionRatio;\\\\n\\\\n\\\\t#endif\\\\n\\\\n#endif\\\\n\\\\\\\",envmap_physical_pars_fragment:\\\\\\\"\\\\n#if defined( USE_ENVMAP )\\\\n\\\\n\\\\t#ifdef ENVMAP_MODE_REFRACTION\\\\n\\\\n\\\\t\\\\tuniform float refractionRatio;\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\tvec3 getIBLIrradiance( const in vec3 normal ) {\\\\n\\\\n\\\\t\\\\t#if defined( ENVMAP_TYPE_CUBE_UV )\\\\n\\\\n\\\\t\\\\t\\\\tvec3 worldNormal = inverseTransformDirection( normal, viewMatrix );\\\\n\\\\n\\\\t\\\\t\\\\tvec4 envMapColor = textureCubeUV( envMap, worldNormal, 1.0 );\\\\n\\\\n\\\\t\\\\t\\\\treturn PI * envMapColor.rgb * envMapIntensity;\\\\n\\\\n\\\\t\\\\t#else\\\\n\\\\n\\\\t\\\\t\\\\treturn vec3( 0.0 );\\\\n\\\\n\\\\t\\\\t#endif\\\\n\\\\n\\\\t}\\\\n\\\\n\\\\tvec3 getIBLRadiance( const in vec3 viewDir, const in vec3 normal, const in float roughness ) {\\\\n\\\\n\\\\t\\\\t#if defined( ENVMAP_TYPE_CUBE_UV )\\\\n\\\\n\\\\t\\\\t\\\\tvec3 reflectVec;\\\\n\\\\n\\\\t\\\\t\\\\t#ifdef ENVMAP_MODE_REFLECTION\\\\n\\\\n\\\\t\\\\t\\\\t\\\\treflectVec = reflect( - viewDir, normal );\\\\n\\\\n\\\\t\\\\t\\\\t\\\\t// Mixing the reflection with the normal is more accurate and keeps rough objects from gathering light from behind their tangent plane.\\\\n\\\\t\\\\t\\\\t\\\\treflectVec = normalize( mix( reflectVec, normal, roughness * roughness) );\\\\n\\\\n\\\\t\\\\t\\\\t#else\\\\n\\\\n\\\\t\\\\t\\\\t\\\\treflectVec = refract( - viewDir, normal, refractionRatio );\\\\n\\\\n\\\\t\\\\t\\\\t#endif\\\\n\\\\n\\\\t\\\\t\\\\treflectVec = inverseTransformDirection( reflectVec, viewMatrix );\\\\n\\\\n\\\\t\\\\t\\\\tvec4 envMapColor = textureCubeUV( envMap, reflectVec, roughness );\\\\n\\\\n\\\\t\\\\t\\\\treturn envMapColor.rgb * envMapIntensity;\\\\n\\\\n\\\\t\\\\t#else\\\\n\\\\n\\\\t\\\\t\\\\treturn vec3( 0.0 );\\\\n\\\\n\\\\t\\\\t#endif\\\\n\\\\n\\\\t}\\\\n\\\\n#endif\\\\n\\\\\\\",envmap_vertex:\\\\\\\"\\\\n#ifdef USE_ENVMAP\\\\n\\\\n\\\\t#ifdef ENV_WORLDPOS\\\\n\\\\n\\\\t\\\\tvWorldPosition = worldPosition.xyz;\\\\n\\\\n\\\\t#else\\\\n\\\\n\\\\t\\\\tvec3 cameraToVertex;\\\\n\\\\n\\\\t\\\\tif ( isOrthographic ) {\\\\n\\\\n\\\\t\\\\t\\\\tcameraToVertex = normalize( vec3( - viewMatrix[ 0 ][ 2 ], - viewMatrix[ 1 ][ 2 ], - viewMatrix[ 2 ][ 2 ] ) );\\\\n\\\\n\\\\t\\\\t} else {\\\\n\\\\n\\\\t\\\\t\\\\tcameraToVertex = normalize( worldPosition.xyz - cameraPosition );\\\\n\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\tvec3 worldNormal = inverseTransformDirection( transformedNormal, viewMatrix );\\\\n\\\\n\\\\t\\\\t#ifdef ENVMAP_MODE_REFLECTION\\\\n\\\\n\\\\t\\\\t\\\\tvReflect = reflect( cameraToVertex, worldNormal );\\\\n\\\\n\\\\t\\\\t#else\\\\n\\\\n\\\\t\\\\t\\\\tvReflect = refract( cameraToVertex, worldNormal, refractionRatio );\\\\n\\\\n\\\\t\\\\t#endif\\\\n\\\\n\\\\t#endif\\\\n\\\\n#endif\\\\n\\\\\\\",fog_vertex:\\\\\\\"\\\\n#ifdef USE_FOG\\\\n\\\\n\\\\tvFogDepth = - mvPosition.z;\\\\n\\\\n#endif\\\\n\\\\\\\",fog_pars_vertex:\\\\\\\"\\\\n#ifdef USE_FOG\\\\n\\\\n\\\\tvarying float vFogDepth;\\\\n\\\\n#endif\\\\n\\\\\\\",fog_fragment:\\\\\\\"\\\\n#ifdef USE_FOG\\\\n\\\\n\\\\t#ifdef FOG_EXP2\\\\n\\\\n\\\\t\\\\tfloat fogFactor = 1.0 - exp( - fogDensity * fogDensity * vFogDepth * vFogDepth );\\\\n\\\\n\\\\t#else\\\\n\\\\n\\\\t\\\\tfloat fogFactor = smoothstep( fogNear, fogFar, vFogDepth );\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\tgl_FragColor.rgb = mix( gl_FragColor.rgb, fogColor, fogFactor );\\\\n\\\\n#endif\\\\n\\\\\\\",fog_pars_fragment:\\\\\\\"\\\\n#ifdef USE_FOG\\\\n\\\\n\\\\tuniform vec3 fogColor;\\\\n\\\\tvarying float vFogDepth;\\\\n\\\\n\\\\t#ifdef FOG_EXP2\\\\n\\\\n\\\\t\\\\tuniform float fogDensity;\\\\n\\\\n\\\\t#else\\\\n\\\\n\\\\t\\\\tuniform float fogNear;\\\\n\\\\t\\\\tuniform float fogFar;\\\\n\\\\n\\\\t#endif\\\\n\\\\n#endif\\\\n\\\\\\\",gradientmap_pars_fragment:\\\\\\\"\\\\n\\\\n#ifdef USE_GRADIENTMAP\\\\n\\\\n\\\\tuniform sampler2D gradientMap;\\\\n\\\\n#endif\\\\n\\\\nvec3 getGradientIrradiance( vec3 normal, vec3 lightDirection ) {\\\\n\\\\n\\\\t// dotNL will be from -1.0 to 1.0\\\\n\\\\tfloat dotNL = dot( normal, lightDirection );\\\\n\\\\tvec2 coord = vec2( dotNL * 0.5 + 0.5, 0.0 );\\\\n\\\\n\\\\t#ifdef USE_GRADIENTMAP\\\\n\\\\n\\\\t\\\\treturn texture2D( gradientMap, coord ).rgb;\\\\n\\\\n\\\\t#else\\\\n\\\\n\\\\t\\\\treturn ( coord.x < 0.7 ) ? vec3( 0.7 ) : vec3( 1.0 );\\\\n\\\\n\\\\t#endif\\\\n\\\\n}\\\\n\\\\\\\",lightmap_fragment:\\\\\\\"\\\\n#ifdef USE_LIGHTMAP\\\\n\\\\n\\\\tvec4 lightMapTexel = texture2D( lightMap, vUv2 );\\\\n\\\\tvec3 lightMapIrradiance = lightMapTexelToLinear( lightMapTexel ).rgb * lightMapIntensity;\\\\n\\\\n\\\\t#ifndef PHYSICALLY_CORRECT_LIGHTS\\\\n\\\\n\\\\t\\\\tlightMapIrradiance *= PI;\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\treflectedLight.indirectDiffuse += lightMapIrradiance;\\\\n\\\\n#endif\\\\n\\\\\\\",lightmap_pars_fragment:\\\\\\\"\\\\n#ifdef USE_LIGHTMAP\\\\n\\\\n\\\\tuniform sampler2D lightMap;\\\\n\\\\tuniform float lightMapIntensity;\\\\n\\\\n#endif\\\\n\\\\\\\",lights_lambert_vertex:\\\\\\\"\\\\nvec3 diffuse = vec3( 1.0 );\\\\n\\\\nGeometricContext geometry;\\\\ngeometry.position = mvPosition.xyz;\\\\ngeometry.normal = normalize( transformedNormal );\\\\ngeometry.viewDir = ( isOrthographic ) ? vec3( 0, 0, 1 ) : normalize( -mvPosition.xyz );\\\\n\\\\nGeometricContext backGeometry;\\\\nbackGeometry.position = geometry.position;\\\\nbackGeometry.normal = -geometry.normal;\\\\nbackGeometry.viewDir = geometry.viewDir;\\\\n\\\\nvLightFront = vec3( 0.0 );\\\\nvIndirectFront = vec3( 0.0 );\\\\n#ifdef DOUBLE_SIDED\\\\n\\\\tvLightBack = vec3( 0.0 );\\\\n\\\\tvIndirectBack = vec3( 0.0 );\\\\n#endif\\\\n\\\\nIncidentLight directLight;\\\\nfloat dotNL;\\\\nvec3 directLightColor_Diffuse;\\\\n\\\\nvIndirectFront += getAmbientLightIrradiance( ambientLightColor );\\\\n\\\\nvIndirectFront += getLightProbeIrradiance( lightProbe, geometry.normal );\\\\n\\\\n#ifdef DOUBLE_SIDED\\\\n\\\\n\\\\tvIndirectBack += getAmbientLightIrradiance( ambientLightColor );\\\\n\\\\n\\\\tvIndirectBack += getLightProbeIrradiance( lightProbe, backGeometry.normal );\\\\n\\\\n#endif\\\\n\\\\n#if NUM_POINT_LIGHTS > 0\\\\n\\\\n\\\\t#pragma unroll_loop_start\\\\n\\\\tfor ( int i = 0; i < NUM_POINT_LIGHTS; i ++ ) {\\\\n\\\\n\\\\t\\\\tgetPointLightInfo( pointLights[ i ], geometry, directLight );\\\\n\\\\n\\\\t\\\\tdotNL = dot( geometry.normal, directLight.direction );\\\\n\\\\t\\\\tdirectLightColor_Diffuse = directLight.color;\\\\n\\\\n\\\\t\\\\tvLightFront += saturate( dotNL ) * directLightColor_Diffuse;\\\\n\\\\n\\\\t\\\\t#ifdef DOUBLE_SIDED\\\\n\\\\n\\\\t\\\\t\\\\tvLightBack += saturate( - dotNL ) * directLightColor_Diffuse;\\\\n\\\\n\\\\t\\\\t#endif\\\\n\\\\n\\\\t}\\\\n\\\\t#pragma unroll_loop_end\\\\n\\\\n#endif\\\\n\\\\n#if NUM_SPOT_LIGHTS > 0\\\\n\\\\n\\\\t#pragma unroll_loop_start\\\\n\\\\tfor ( int i = 0; i < NUM_SPOT_LIGHTS; i ++ ) {\\\\n\\\\n\\\\t\\\\tgetSpotLightInfo( spotLights[ i ], geometry, directLight );\\\\n\\\\n\\\\t\\\\tdotNL = dot( geometry.normal, directLight.direction );\\\\n\\\\t\\\\tdirectLightColor_Diffuse = directLight.color;\\\\n\\\\n\\\\t\\\\tvLightFront += saturate( dotNL ) * directLightColor_Diffuse;\\\\n\\\\n\\\\t\\\\t#ifdef DOUBLE_SIDED\\\\n\\\\n\\\\t\\\\t\\\\tvLightBack += saturate( - dotNL ) * directLightColor_Diffuse;\\\\n\\\\n\\\\t\\\\t#endif\\\\n\\\\t}\\\\n\\\\t#pragma unroll_loop_end\\\\n\\\\n#endif\\\\n\\\\n#if NUM_DIR_LIGHTS > 0\\\\n\\\\n\\\\t#pragma unroll_loop_start\\\\n\\\\tfor ( int i = 0; i < NUM_DIR_LIGHTS; i ++ ) {\\\\n\\\\n\\\\t\\\\tgetDirectionalLightInfo( directionalLights[ i ], geometry, directLight );\\\\n\\\\n\\\\t\\\\tdotNL = dot( geometry.normal, directLight.direction );\\\\n\\\\t\\\\tdirectLightColor_Diffuse = directLight.color;\\\\n\\\\n\\\\t\\\\tvLightFront += saturate( dotNL ) * directLightColor_Diffuse;\\\\n\\\\n\\\\t\\\\t#ifdef DOUBLE_SIDED\\\\n\\\\n\\\\t\\\\t\\\\tvLightBack += saturate( - dotNL ) * directLightColor_Diffuse;\\\\n\\\\n\\\\t\\\\t#endif\\\\n\\\\n\\\\t}\\\\n\\\\t#pragma unroll_loop_end\\\\n\\\\n#endif\\\\n\\\\n#if NUM_HEMI_LIGHTS > 0\\\\n\\\\n\\\\t#pragma unroll_loop_start\\\\n\\\\tfor ( int i = 0; i < NUM_HEMI_LIGHTS; i ++ ) {\\\\n\\\\n\\\\t\\\\tvIndirectFront += getHemisphereLightIrradiance( hemisphereLights[ i ], geometry.normal );\\\\n\\\\n\\\\t\\\\t#ifdef DOUBLE_SIDED\\\\n\\\\n\\\\t\\\\t\\\\tvIndirectBack += getHemisphereLightIrradiance( hemisphereLights[ i ], backGeometry.normal );\\\\n\\\\n\\\\t\\\\t#endif\\\\n\\\\n\\\\t}\\\\n\\\\t#pragma unroll_loop_end\\\\n\\\\n#endif\\\\n\\\\\\\",lights_pars_begin:\\\\\\\"\\\\nuniform bool receiveShadow;\\\\nuniform vec3 ambientLightColor;\\\\nuniform vec3 lightProbe[ 9 ];\\\\n\\\\n// get the irradiance (radiance convolved with cosine lobe) at the point 'normal' on the unit sphere\\\\n// source: https://graphics.stanford.edu/papers/envmap/envmap.pdf\\\\nvec3 shGetIrradianceAt( in vec3 normal, in vec3 shCoefficients[ 9 ] ) {\\\\n\\\\n\\\\t// normal is assumed to have unit length\\\\n\\\\n\\\\tfloat x = normal.x, y = normal.y, z = normal.z;\\\\n\\\\n\\\\t// band 0\\\\n\\\\tvec3 result = shCoefficients[ 0 ] * 0.886227;\\\\n\\\\n\\\\t// band 1\\\\n\\\\tresult += shCoefficients[ 1 ] * 2.0 * 0.511664 * y;\\\\n\\\\tresult += shCoefficients[ 2 ] * 2.0 * 0.511664 * z;\\\\n\\\\tresult += shCoefficients[ 3 ] * 2.0 * 0.511664 * x;\\\\n\\\\n\\\\t// band 2\\\\n\\\\tresult += shCoefficients[ 4 ] * 2.0 * 0.429043 * x * y;\\\\n\\\\tresult += shCoefficients[ 5 ] * 2.0 * 0.429043 * y * z;\\\\n\\\\tresult += shCoefficients[ 6 ] * ( 0.743125 * z * z - 0.247708 );\\\\n\\\\tresult += shCoefficients[ 7 ] * 2.0 * 0.429043 * x * z;\\\\n\\\\tresult += shCoefficients[ 8 ] * 0.429043 * ( x * x - y * y );\\\\n\\\\n\\\\treturn result;\\\\n\\\\n}\\\\n\\\\nvec3 getLightProbeIrradiance( const in vec3 lightProbe[ 9 ], const in vec3 normal ) {\\\\n\\\\n\\\\tvec3 worldNormal = inverseTransformDirection( normal, viewMatrix );\\\\n\\\\n\\\\tvec3 irradiance = shGetIrradianceAt( worldNormal, lightProbe );\\\\n\\\\n\\\\treturn irradiance;\\\\n\\\\n}\\\\n\\\\nvec3 getAmbientLightIrradiance( const in vec3 ambientLightColor ) {\\\\n\\\\n\\\\tvec3 irradiance = ambientLightColor;\\\\n\\\\n\\\\treturn irradiance;\\\\n\\\\n}\\\\n\\\\nfloat getDistanceAttenuation( const in float lightDistance, const in float cutoffDistance, const in float decayExponent ) {\\\\n\\\\n\\\\t#if defined ( PHYSICALLY_CORRECT_LIGHTS )\\\\n\\\\n\\\\t\\\\t// based upon Frostbite 3 Moving to Physically-based Rendering\\\\n\\\\t\\\\t// page 32, equation 26: E[window1]\\\\n\\\\t\\\\t// https://seblagarde.files.wordpress.com/2015/07/course_notes_moving_frostbite_to_pbr_v32.pdf\\\\n\\\\t\\\\tfloat distanceFalloff = 1.0 / max( pow( lightDistance, decayExponent ), 0.01 );\\\\n\\\\n\\\\t\\\\tif ( cutoffDistance > 0.0 ) {\\\\n\\\\n\\\\t\\\\t\\\\tdistanceFalloff *= pow2( saturate( 1.0 - pow4( lightDistance / cutoffDistance ) ) );\\\\n\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\treturn distanceFalloff;\\\\n\\\\n\\\\t#else\\\\n\\\\n\\\\t\\\\tif ( cutoffDistance > 0.0 && decayExponent > 0.0 ) {\\\\n\\\\n\\\\t\\\\t\\\\treturn pow( saturate( - lightDistance / cutoffDistance + 1.0 ), decayExponent );\\\\n\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\treturn 1.0;\\\\n\\\\n\\\\t#endif\\\\n\\\\n}\\\\n\\\\nfloat getSpotAttenuation( const in float coneCosine, const in float penumbraCosine, const in float angleCosine ) {\\\\n\\\\n\\\\treturn smoothstep( coneCosine, penumbraCosine, angleCosine );\\\\n\\\\n}\\\\n\\\\n#if NUM_DIR_LIGHTS > 0\\\\n\\\\n\\\\tstruct DirectionalLight {\\\\n\\\\t\\\\tvec3 direction;\\\\n\\\\t\\\\tvec3 color;\\\\n\\\\t};\\\\n\\\\n\\\\tuniform DirectionalLight directionalLights[ NUM_DIR_LIGHTS ];\\\\n\\\\n\\\\tvoid getDirectionalLightInfo( const in DirectionalLight directionalLight, const in GeometricContext geometry, out IncidentLight light ) {\\\\n\\\\n\\\\t\\\\tlight.color = directionalLight.color;\\\\n\\\\t\\\\tlight.direction = directionalLight.direction;\\\\n\\\\t\\\\tlight.visible = true;\\\\n\\\\n\\\\t}\\\\n\\\\n#endif\\\\n\\\\n\\\\n#if NUM_POINT_LIGHTS > 0\\\\n\\\\n\\\\tstruct PointLight {\\\\n\\\\t\\\\tvec3 position;\\\\n\\\\t\\\\tvec3 color;\\\\n\\\\t\\\\tfloat distance;\\\\n\\\\t\\\\tfloat decay;\\\\n\\\\t};\\\\n\\\\n\\\\tuniform PointLight pointLights[ NUM_POINT_LIGHTS ];\\\\n\\\\n\\\\t// light is an out parameter as having it as a return value caused compiler errors on some devices\\\\n\\\\tvoid getPointLightInfo( const in PointLight pointLight, const in GeometricContext geometry, out IncidentLight light ) {\\\\n\\\\n\\\\t\\\\tvec3 lVector = pointLight.position - geometry.position;\\\\n\\\\n\\\\t\\\\tlight.direction = normalize( lVector );\\\\n\\\\n\\\\t\\\\tfloat lightDistance = length( lVector );\\\\n\\\\n\\\\t\\\\tlight.color = pointLight.color;\\\\n\\\\t\\\\tlight.color *= getDistanceAttenuation( lightDistance, pointLight.distance, pointLight.decay );\\\\n\\\\t\\\\tlight.visible = ( light.color != vec3( 0.0 ) );\\\\n\\\\n\\\\t}\\\\n\\\\n#endif\\\\n\\\\n\\\\n#if NUM_SPOT_LIGHTS > 0\\\\n\\\\n\\\\tstruct SpotLight {\\\\n\\\\t\\\\tvec3 position;\\\\n\\\\t\\\\tvec3 direction;\\\\n\\\\t\\\\tvec3 color;\\\\n\\\\t\\\\tfloat distance;\\\\n\\\\t\\\\tfloat decay;\\\\n\\\\t\\\\tfloat coneCos;\\\\n\\\\t\\\\tfloat penumbraCos;\\\\n\\\\t};\\\\n\\\\n\\\\tuniform SpotLight spotLights[ NUM_SPOT_LIGHTS ];\\\\n\\\\n\\\\t// light is an out parameter as having it as a return value caused compiler errors on some devices\\\\n\\\\tvoid getSpotLightInfo( const in SpotLight spotLight, const in GeometricContext geometry, out IncidentLight light ) {\\\\n\\\\n\\\\t\\\\tvec3 lVector = spotLight.position - geometry.position;\\\\n\\\\n\\\\t\\\\tlight.direction = normalize( lVector );\\\\n\\\\n\\\\t\\\\tfloat angleCos = dot( light.direction, spotLight.direction );\\\\n\\\\n\\\\t\\\\tfloat spotAttenuation = getSpotAttenuation( spotLight.coneCos, spotLight.penumbraCos, angleCos );\\\\n\\\\n\\\\t\\\\tif ( spotAttenuation > 0.0 ) {\\\\n\\\\n\\\\t\\\\t\\\\tfloat lightDistance = length( lVector );\\\\n\\\\n\\\\t\\\\t\\\\tlight.color = spotLight.color * spotAttenuation;\\\\n\\\\t\\\\t\\\\tlight.color *= getDistanceAttenuation( lightDistance, spotLight.distance, spotLight.decay );\\\\n\\\\t\\\\t\\\\tlight.visible = ( light.color != vec3( 0.0 ) );\\\\n\\\\n\\\\t\\\\t} else {\\\\n\\\\n\\\\t\\\\t\\\\tlight.color = vec3( 0.0 );\\\\n\\\\t\\\\t\\\\tlight.visible = false;\\\\n\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\t}\\\\n\\\\n#endif\\\\n\\\\n\\\\n#if NUM_RECT_AREA_LIGHTS > 0\\\\n\\\\n\\\\tstruct RectAreaLight {\\\\n\\\\t\\\\tvec3 color;\\\\n\\\\t\\\\tvec3 position;\\\\n\\\\t\\\\tvec3 halfWidth;\\\\n\\\\t\\\\tvec3 halfHeight;\\\\n\\\\t};\\\\n\\\\n\\\\t// Pre-computed values of LinearTransformedCosine approximation of BRDF\\\\n\\\\t// BRDF approximation Texture is 64x64\\\\n\\\\tuniform sampler2D ltc_1; // RGBA Float\\\\n\\\\tuniform sampler2D ltc_2; // RGBA Float\\\\n\\\\n\\\\tuniform RectAreaLight rectAreaLights[ NUM_RECT_AREA_LIGHTS ];\\\\n\\\\n#endif\\\\n\\\\n\\\\n#if NUM_HEMI_LIGHTS > 0\\\\n\\\\n\\\\tstruct HemisphereLight {\\\\n\\\\t\\\\tvec3 direction;\\\\n\\\\t\\\\tvec3 skyColor;\\\\n\\\\t\\\\tvec3 groundColor;\\\\n\\\\t};\\\\n\\\\n\\\\tuniform HemisphereLight hemisphereLights[ NUM_HEMI_LIGHTS ];\\\\n\\\\n\\\\tvec3 getHemisphereLightIrradiance( const in HemisphereLight hemiLight, const in vec3 normal ) {\\\\n\\\\n\\\\t\\\\tfloat dotNL = dot( normal, hemiLight.direction );\\\\n\\\\t\\\\tfloat hemiDiffuseWeight = 0.5 * dotNL + 0.5;\\\\n\\\\n\\\\t\\\\tvec3 irradiance = mix( hemiLight.groundColor, hemiLight.skyColor, hemiDiffuseWeight );\\\\n\\\\n\\\\t\\\\treturn irradiance;\\\\n\\\\n\\\\t}\\\\n\\\\n#endif\\\\n\\\\\\\",lights_toon_fragment:\\\\\\\"\\\\nToonMaterial material;\\\\nmaterial.diffuseColor = diffuseColor.rgb;\\\\n\\\\\\\",lights_toon_pars_fragment:\\\\\\\"\\\\nvarying vec3 vViewPosition;\\\\n\\\\nstruct ToonMaterial {\\\\n\\\\n\\\\tvec3 diffuseColor;\\\\n\\\\n};\\\\n\\\\nvoid RE_Direct_Toon( const in IncidentLight directLight, const in GeometricContext geometry, const in ToonMaterial material, inout ReflectedLight reflectedLight ) {\\\\n\\\\n\\\\tvec3 irradiance = getGradientIrradiance( geometry.normal, directLight.direction ) * directLight.color;\\\\n\\\\n\\\\treflectedLight.directDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );\\\\n\\\\n}\\\\n\\\\nvoid RE_IndirectDiffuse_Toon( const in vec3 irradiance, const in GeometricContext geometry, const in ToonMaterial material, inout ReflectedLight reflectedLight ) {\\\\n\\\\n\\\\treflectedLight.indirectDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );\\\\n\\\\n}\\\\n\\\\n#define RE_Direct\\\\t\\\\t\\\\t\\\\tRE_Direct_Toon\\\\n#define RE_IndirectDiffuse\\\\t\\\\tRE_IndirectDiffuse_Toon\\\\n\\\\n#define Material_LightProbeLOD( material )\\\\t(0)\\\\n\\\\\\\",lights_phong_fragment:\\\\\\\"\\\\nBlinnPhongMaterial material;\\\\nmaterial.diffuseColor = diffuseColor.rgb;\\\\nmaterial.specularColor = specular;\\\\nmaterial.specularShininess = shininess;\\\\nmaterial.specularStrength = specularStrength;\\\\n\\\\\\\",lights_phong_pars_fragment:\\\\\\\"\\\\nvarying vec3 vViewPosition;\\\\n\\\\nstruct BlinnPhongMaterial {\\\\n\\\\n\\\\tvec3 diffuseColor;\\\\n\\\\tvec3 specularColor;\\\\n\\\\tfloat specularShininess;\\\\n\\\\tfloat specularStrength;\\\\n\\\\n};\\\\n\\\\nvoid RE_Direct_BlinnPhong( const in IncidentLight directLight, const in GeometricContext geometry, const in BlinnPhongMaterial material, inout ReflectedLight reflectedLight ) {\\\\n\\\\n\\\\tfloat dotNL = saturate( dot( geometry.normal, directLight.direction ) );\\\\n\\\\tvec3 irradiance = dotNL * directLight.color;\\\\n\\\\n\\\\treflectedLight.directDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );\\\\n\\\\n\\\\treflectedLight.directSpecular += irradiance * BRDF_BlinnPhong( directLight.direction, geometry.viewDir, geometry.normal, material.specularColor, material.specularShininess ) * material.specularStrength;\\\\n\\\\n}\\\\n\\\\nvoid RE_IndirectDiffuse_BlinnPhong( const in vec3 irradiance, const in GeometricContext geometry, const in BlinnPhongMaterial material, inout ReflectedLight reflectedLight ) {\\\\n\\\\n\\\\treflectedLight.indirectDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );\\\\n\\\\n}\\\\n\\\\n#define RE_Direct\\\\t\\\\t\\\\t\\\\tRE_Direct_BlinnPhong\\\\n#define RE_IndirectDiffuse\\\\t\\\\tRE_IndirectDiffuse_BlinnPhong\\\\n\\\\n#define Material_LightProbeLOD( material )\\\\t(0)\\\\n\\\\\\\",lights_physical_fragment:\\\\\\\"\\\\nPhysicalMaterial material;\\\\nmaterial.diffuseColor = diffuseColor.rgb * ( 1.0 - metalnessFactor );\\\\n\\\\nvec3 dxy = max( abs( dFdx( geometryNormal ) ), abs( dFdy( geometryNormal ) ) );\\\\nfloat geometryRoughness = max( max( dxy.x, dxy.y ), dxy.z );\\\\n\\\\nmaterial.roughness = max( roughnessFactor, 0.0525 );// 0.0525 corresponds to the base mip of a 256 cubemap.\\\\nmaterial.roughness += geometryRoughness;\\\\nmaterial.roughness = min( material.roughness, 1.0 );\\\\n\\\\n#ifdef IOR\\\\n\\\\n\\\\t#ifdef SPECULAR\\\\n\\\\n\\\\t\\\\tfloat specularIntensityFactor = specularIntensity;\\\\n\\\\t\\\\tvec3 specularTintFactor = specularTint;\\\\n\\\\n\\\\t\\\\t#ifdef USE_SPECULARINTENSITYMAP\\\\n\\\\n\\\\t\\\\t\\\\tspecularIntensityFactor *= texture2D( specularIntensityMap, vUv ).a;\\\\n\\\\n\\\\t\\\\t#endif\\\\n\\\\n\\\\t\\\\t#ifdef USE_SPECULARTINTMAP\\\\n\\\\n\\\\t\\\\t\\\\tspecularTintFactor *= specularTintMapTexelToLinear( texture2D( specularTintMap, vUv ) ).rgb;\\\\n\\\\n\\\\t\\\\t#endif\\\\n\\\\n\\\\t\\\\tmaterial.specularF90 = mix( specularIntensityFactor, 1.0, metalnessFactor );\\\\n\\\\n\\\\t#else\\\\n\\\\n\\\\t\\\\tfloat specularIntensityFactor = 1.0;\\\\n\\\\t\\\\tvec3 specularTintFactor = vec3( 1.0 );\\\\n\\\\t\\\\tmaterial.specularF90 = 1.0;\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\tmaterial.specularColor = mix( min( pow2( ( ior - 1.0 ) / ( ior + 1.0 ) ) * specularTintFactor, vec3( 1.0 ) ) * specularIntensityFactor, diffuseColor.rgb, metalnessFactor );\\\\n\\\\n#else\\\\n\\\\n\\\\tmaterial.specularColor = mix( vec3( 0.04 ), diffuseColor.rgb, metalnessFactor );\\\\n\\\\tmaterial.specularF90 = 1.0;\\\\n\\\\n#endif\\\\n\\\\n#ifdef USE_CLEARCOAT\\\\n\\\\n\\\\tmaterial.clearcoat = clearcoat;\\\\n\\\\tmaterial.clearcoatRoughness = clearcoatRoughness;\\\\n\\\\tmaterial.clearcoatF0 = vec3( 0.04 );\\\\n\\\\tmaterial.clearcoatF90 = 1.0;\\\\n\\\\n\\\\t#ifdef USE_CLEARCOATMAP\\\\n\\\\n\\\\t\\\\tmaterial.clearcoat *= texture2D( clearcoatMap, vUv ).x;\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\t#ifdef USE_CLEARCOAT_ROUGHNESSMAP\\\\n\\\\n\\\\t\\\\tmaterial.clearcoatRoughness *= texture2D( clearcoatRoughnessMap, vUv ).y;\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\tmaterial.clearcoat = saturate( material.clearcoat ); // Burley clearcoat model\\\\n\\\\tmaterial.clearcoatRoughness = max( material.clearcoatRoughness, 0.0525 );\\\\n\\\\tmaterial.clearcoatRoughness += geometryRoughness;\\\\n\\\\tmaterial.clearcoatRoughness = min( material.clearcoatRoughness, 1.0 );\\\\n\\\\n#endif\\\\n\\\\n#ifdef USE_SHEEN\\\\n\\\\n\\\\tmaterial.sheenTint = sheenTint;\\\\n\\\\tmaterial.sheenRoughness = clamp( sheenRoughness, 0.07, 1.0 );\\\\n\\\\n#endif\\\\n\\\\\\\",lights_physical_pars_fragment:'\\\\nstruct PhysicalMaterial {\\\\n\\\\n\\\\tvec3 diffuseColor;\\\\n\\\\tfloat roughness;\\\\n\\\\tvec3 specularColor;\\\\n\\\\tfloat specularF90;\\\\n\\\\n\\\\t#ifdef USE_CLEARCOAT\\\\n\\\\t\\\\tfloat clearcoat;\\\\n\\\\t\\\\tfloat clearcoatRoughness;\\\\n\\\\t\\\\tvec3 clearcoatF0;\\\\n\\\\t\\\\tfloat clearcoatF90;\\\\n\\\\t#endif\\\\n\\\\n\\\\t#ifdef USE_SHEEN\\\\n\\\\t\\\\tvec3 sheenTint;\\\\n\\\\t\\\\tfloat sheenRoughness;\\\\n\\\\t#endif\\\\n\\\\n};\\\\n\\\\n// temporary\\\\nvec3 clearcoatSpecular = vec3( 0.0 );\\\\n\\\\n// Analytical approximation of the DFG LUT, one half of the\\\\n// split-sum approximation used in indirect specular lighting.\\\\n// via \\\\'environmentBRDF\\\\' from \\\\\\\"Physically Based Shading on Mobile\\\\\\\"\\\\n// https://www.unrealengine.com/blog/physically-based-shading-on-mobile\\\\nvec2 DFGApprox( const in vec3 normal, const in vec3 viewDir, const in float roughness ) {\\\\n\\\\n\\\\tfloat dotNV = saturate( dot( normal, viewDir ) );\\\\n\\\\n\\\\tconst vec4 c0 = vec4( - 1, - 0.0275, - 0.572, 0.022 );\\\\n\\\\n\\\\tconst vec4 c1 = vec4( 1, 0.0425, 1.04, - 0.04 );\\\\n\\\\n\\\\tvec4 r = roughness * c0 + c1;\\\\n\\\\n\\\\tfloat a004 = min( r.x * r.x, exp2( - 9.28 * dotNV ) ) * r.x + r.y;\\\\n\\\\n\\\\tvec2 fab = vec2( - 1.04, 1.04 ) * a004 + r.zw;\\\\n\\\\n\\\\treturn fab;\\\\n\\\\n}\\\\n\\\\nvec3 EnvironmentBRDF( const in vec3 normal, const in vec3 viewDir, const in vec3 specularColor, const in float specularF90, const in float roughness ) {\\\\n\\\\n\\\\tvec2 fab = DFGApprox( normal, viewDir, roughness );\\\\n\\\\n\\\\treturn specularColor * fab.x + specularF90 * fab.y;\\\\n\\\\n}\\\\n\\\\n// Fdez-Agüera\\\\'s \\\\\\\"Multiple-Scattering Microfacet Model for Real-Time Image Based Lighting\\\\\\\"\\\\n// Approximates multiscattering in order to preserve energy.\\\\n// http://www.jcgt.org/published/0008/01/03/\\\\nvoid computeMultiscattering( const in vec3 normal, const in vec3 viewDir, const in vec3 specularColor, const in float specularF90, const in float roughness, inout vec3 singleScatter, inout vec3 multiScatter ) {\\\\n\\\\n\\\\tvec2 fab = DFGApprox( normal, viewDir, roughness );\\\\n\\\\n\\\\tvec3 FssEss = specularColor * fab.x + specularF90 * fab.y;\\\\n\\\\n\\\\tfloat Ess = fab.x + fab.y;\\\\n\\\\tfloat Ems = 1.0 - Ess;\\\\n\\\\n\\\\tvec3 Favg = specularColor + ( 1.0 - specularColor ) * 0.047619; // 1/21\\\\n\\\\tvec3 Fms = FssEss * Favg / ( 1.0 - Ems * Favg );\\\\n\\\\n\\\\tsingleScatter += FssEss;\\\\n\\\\tmultiScatter += Fms * Ems;\\\\n\\\\n}\\\\n\\\\n#if NUM_RECT_AREA_LIGHTS > 0\\\\n\\\\n\\\\tvoid RE_Direct_RectArea_Physical( const in RectAreaLight rectAreaLight, const in GeometricContext geometry, const in PhysicalMaterial material, inout ReflectedLight reflectedLight ) {\\\\n\\\\n\\\\t\\\\tvec3 normal = geometry.normal;\\\\n\\\\t\\\\tvec3 viewDir = geometry.viewDir;\\\\n\\\\t\\\\tvec3 position = geometry.position;\\\\n\\\\t\\\\tvec3 lightPos = rectAreaLight.position;\\\\n\\\\t\\\\tvec3 halfWidth = rectAreaLight.halfWidth;\\\\n\\\\t\\\\tvec3 halfHeight = rectAreaLight.halfHeight;\\\\n\\\\t\\\\tvec3 lightColor = rectAreaLight.color;\\\\n\\\\t\\\\tfloat roughness = material.roughness;\\\\n\\\\n\\\\t\\\\tvec3 rectCoords[ 4 ];\\\\n\\\\t\\\\trectCoords[ 0 ] = lightPos + halfWidth - halfHeight; // counterclockwise; light shines in local neg z direction\\\\n\\\\t\\\\trectCoords[ 1 ] = lightPos - halfWidth - halfHeight;\\\\n\\\\t\\\\trectCoords[ 2 ] = lightPos - halfWidth + halfHeight;\\\\n\\\\t\\\\trectCoords[ 3 ] = lightPos + halfWidth + halfHeight;\\\\n\\\\n\\\\t\\\\tvec2 uv = LTC_Uv( normal, viewDir, roughness );\\\\n\\\\n\\\\t\\\\tvec4 t1 = texture2D( ltc_1, uv );\\\\n\\\\t\\\\tvec4 t2 = texture2D( ltc_2, uv );\\\\n\\\\n\\\\t\\\\tmat3 mInv = mat3(\\\\n\\\\t\\\\t\\\\tvec3( t1.x, 0, t1.y ),\\\\n\\\\t\\\\t\\\\tvec3( 0, 1, 0 ),\\\\n\\\\t\\\\t\\\\tvec3( t1.z, 0, t1.w )\\\\n\\\\t\\\\t);\\\\n\\\\n\\\\t\\\\t// LTC Fresnel Approximation by Stephen Hill\\\\n\\\\t\\\\t// http://blog.selfshadow.com/publications/s2016-advances/s2016_ltc_fresnel.pdf\\\\n\\\\t\\\\tvec3 fresnel = ( material.specularColor * t2.x + ( vec3( 1.0 ) - material.specularColor ) * t2.y );\\\\n\\\\n\\\\t\\\\treflectedLight.directSpecular += lightColor * fresnel * LTC_Evaluate( normal, viewDir, position, mInv, rectCoords );\\\\n\\\\n\\\\t\\\\treflectedLight.directDiffuse += lightColor * material.diffuseColor * LTC_Evaluate( normal, viewDir, position, mat3( 1.0 ), rectCoords );\\\\n\\\\n\\\\t}\\\\n\\\\n#endif\\\\n\\\\nvoid RE_Direct_Physical( const in IncidentLight directLight, const in GeometricContext geometry, const in PhysicalMaterial material, inout ReflectedLight reflectedLight ) {\\\\n\\\\n\\\\tfloat dotNL = saturate( dot( geometry.normal, directLight.direction ) );\\\\n\\\\n\\\\tvec3 irradiance = dotNL * directLight.color;\\\\n\\\\n\\\\t#ifdef USE_CLEARCOAT\\\\n\\\\n\\\\t\\\\tfloat dotNLcc = saturate( dot( geometry.clearcoatNormal, directLight.direction ) );\\\\n\\\\n\\\\t\\\\tvec3 ccIrradiance = dotNLcc * directLight.color;\\\\n\\\\n\\\\t\\\\tclearcoatSpecular += ccIrradiance * BRDF_GGX( directLight.direction, geometry.viewDir, geometry.clearcoatNormal, material.clearcoatF0, material.clearcoatF90, material.clearcoatRoughness );\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\t#ifdef USE_SHEEN\\\\n\\\\n\\\\t\\\\treflectedLight.directSpecular += irradiance * BRDF_Sheen( directLight.direction, geometry.viewDir, geometry.normal, material.sheenTint, material.sheenRoughness );\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\treflectedLight.directSpecular += irradiance * BRDF_GGX( directLight.direction, geometry.viewDir, geometry.normal, material.specularColor, material.specularF90, material.roughness );\\\\n\\\\n\\\\n\\\\treflectedLight.directDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );\\\\n}\\\\n\\\\nvoid RE_IndirectDiffuse_Physical( const in vec3 irradiance, const in GeometricContext geometry, const in PhysicalMaterial material, inout ReflectedLight reflectedLight ) {\\\\n\\\\n\\\\treflectedLight.indirectDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );\\\\n\\\\n}\\\\n\\\\nvoid RE_IndirectSpecular_Physical( const in vec3 radiance, const in vec3 irradiance, const in vec3 clearcoatRadiance, const in GeometricContext geometry, const in PhysicalMaterial material, inout ReflectedLight reflectedLight) {\\\\n\\\\n\\\\t#ifdef USE_CLEARCOAT\\\\n\\\\n\\\\t\\\\tclearcoatSpecular += clearcoatRadiance * EnvironmentBRDF( geometry.clearcoatNormal, geometry.viewDir, material.clearcoatF0, material.clearcoatF90, material.clearcoatRoughness );\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\t// Both indirect specular and indirect diffuse light accumulate here\\\\n\\\\n\\\\tvec3 singleScattering = vec3( 0.0 );\\\\n\\\\tvec3 multiScattering = vec3( 0.0 );\\\\n\\\\tvec3 cosineWeightedIrradiance = irradiance * RECIPROCAL_PI;\\\\n\\\\n\\\\tcomputeMultiscattering( geometry.normal, geometry.viewDir, material.specularColor, material.specularF90, material.roughness, singleScattering, multiScattering );\\\\n\\\\n\\\\tvec3 diffuse = material.diffuseColor * ( 1.0 - ( singleScattering + multiScattering ) );\\\\n\\\\n\\\\treflectedLight.indirectSpecular += radiance * singleScattering;\\\\n\\\\treflectedLight.indirectSpecular += multiScattering * cosineWeightedIrradiance;\\\\n\\\\n\\\\treflectedLight.indirectDiffuse += diffuse * cosineWeightedIrradiance;\\\\n\\\\n}\\\\n\\\\n#define RE_Direct\\\\t\\\\t\\\\t\\\\tRE_Direct_Physical\\\\n#define RE_Direct_RectArea\\\\t\\\\tRE_Direct_RectArea_Physical\\\\n#define RE_IndirectDiffuse\\\\t\\\\tRE_IndirectDiffuse_Physical\\\\n#define RE_IndirectSpecular\\\\t\\\\tRE_IndirectSpecular_Physical\\\\n\\\\n// ref: https://seblagarde.files.wordpress.com/2015/07/course_notes_moving_frostbite_to_pbr_v32.pdf\\\\nfloat computeSpecularOcclusion( const in float dotNV, const in float ambientOcclusion, const in float roughness ) {\\\\n\\\\n\\\\treturn saturate( pow( dotNV + ambientOcclusion, exp2( - 16.0 * roughness - 1.0 ) ) - 1.0 + ambientOcclusion );\\\\n\\\\n}\\\\n',lights_fragment_begin:\\\\\\\"\\\\n/**\\\\n * This is a template that can be used to light a material, it uses pluggable\\\\n * RenderEquations (RE)for specific lighting scenarios.\\\\n *\\\\n * Instructions for use:\\\\n * - Ensure that both RE_Direct, RE_IndirectDiffuse and RE_IndirectSpecular are defined\\\\n * - If you have defined an RE_IndirectSpecular, you need to also provide a Material_LightProbeLOD. <---- ???\\\\n * - Create a material parameter that is to be passed as the third parameter to your lighting functions.\\\\n *\\\\n * TODO:\\\\n * - Add area light support.\\\\n * - Add sphere light support.\\\\n * - Add diffuse light probe (irradiance cubemap) support.\\\\n */\\\\n\\\\nGeometricContext geometry;\\\\n\\\\ngeometry.position = - vViewPosition;\\\\ngeometry.normal = normal;\\\\ngeometry.viewDir = ( isOrthographic ) ? vec3( 0, 0, 1 ) : normalize( vViewPosition );\\\\n\\\\n#ifdef USE_CLEARCOAT\\\\n\\\\n\\\\tgeometry.clearcoatNormal = clearcoatNormal;\\\\n\\\\n#endif\\\\n\\\\nIncidentLight directLight;\\\\n\\\\n#if ( NUM_POINT_LIGHTS > 0 ) && defined( RE_Direct )\\\\n\\\\n\\\\tPointLight pointLight;\\\\n\\\\t#if defined( USE_SHADOWMAP ) && NUM_POINT_LIGHT_SHADOWS > 0\\\\n\\\\tPointLightShadow pointLightShadow;\\\\n\\\\t#endif\\\\n\\\\n\\\\t#pragma unroll_loop_start\\\\n\\\\tfor ( int i = 0; i < NUM_POINT_LIGHTS; i ++ ) {\\\\n\\\\n\\\\t\\\\tpointLight = pointLights[ i ];\\\\n\\\\n\\\\t\\\\tgetPointLightInfo( pointLight, geometry, directLight );\\\\n\\\\n\\\\t\\\\t#if defined( USE_SHADOWMAP ) && ( UNROLLED_LOOP_INDEX < NUM_POINT_LIGHT_SHADOWS )\\\\n\\\\t\\\\tpointLightShadow = pointLightShadows[ i ];\\\\n\\\\t\\\\tdirectLight.color *= all( bvec2( directLight.visible, receiveShadow ) ) ? getPointShadow( pointShadowMap[ i ], pointLightShadow.shadowMapSize, pointLightShadow.shadowBias, pointLightShadow.shadowRadius, vPointShadowCoord[ i ], pointLightShadow.shadowCameraNear, pointLightShadow.shadowCameraFar ) : 1.0;\\\\n\\\\t\\\\t#endif\\\\n\\\\n\\\\t\\\\tRE_Direct( directLight, geometry, material, reflectedLight );\\\\n\\\\n\\\\t}\\\\n\\\\t#pragma unroll_loop_end\\\\n\\\\n#endif\\\\n\\\\n#if ( NUM_SPOT_LIGHTS > 0 ) && defined( RE_Direct )\\\\n\\\\n\\\\tSpotLight spotLight;\\\\n\\\\t#if defined( USE_SHADOWMAP ) && NUM_SPOT_LIGHT_SHADOWS > 0\\\\n\\\\tSpotLightShadow spotLightShadow;\\\\n\\\\t#endif\\\\n\\\\n\\\\t#pragma unroll_loop_start\\\\n\\\\tfor ( int i = 0; i < NUM_SPOT_LIGHTS; i ++ ) {\\\\n\\\\n\\\\t\\\\tspotLight = spotLights[ i ];\\\\n\\\\n\\\\t\\\\tgetSpotLightInfo( spotLight, geometry, directLight );\\\\n\\\\n\\\\t\\\\t#if defined( USE_SHADOWMAP ) && ( UNROLLED_LOOP_INDEX < NUM_SPOT_LIGHT_SHADOWS )\\\\n\\\\t\\\\tspotLightShadow = spotLightShadows[ i ];\\\\n\\\\t\\\\tdirectLight.color *= all( bvec2( directLight.visible, receiveShadow ) ) ? getShadow( spotShadowMap[ i ], spotLightShadow.shadowMapSize, spotLightShadow.shadowBias, spotLightShadow.shadowRadius, vSpotShadowCoord[ i ] ) : 1.0;\\\\n\\\\t\\\\t#endif\\\\n\\\\n\\\\t\\\\tRE_Direct( directLight, geometry, material, reflectedLight );\\\\n\\\\n\\\\t}\\\\n\\\\t#pragma unroll_loop_end\\\\n\\\\n#endif\\\\n\\\\n#if ( NUM_DIR_LIGHTS > 0 ) && defined( RE_Direct )\\\\n\\\\n\\\\tDirectionalLight directionalLight;\\\\n\\\\t#if defined( USE_SHADOWMAP ) && NUM_DIR_LIGHT_SHADOWS > 0\\\\n\\\\tDirectionalLightShadow directionalLightShadow;\\\\n\\\\t#endif\\\\n\\\\n\\\\t#pragma unroll_loop_start\\\\n\\\\tfor ( int i = 0; i < NUM_DIR_LIGHTS; i ++ ) {\\\\n\\\\n\\\\t\\\\tdirectionalLight = directionalLights[ i ];\\\\n\\\\n\\\\t\\\\tgetDirectionalLightInfo( directionalLight, geometry, directLight );\\\\n\\\\n\\\\t\\\\t#if defined( USE_SHADOWMAP ) && ( UNROLLED_LOOP_INDEX < NUM_DIR_LIGHT_SHADOWS )\\\\n\\\\t\\\\tdirectionalLightShadow = directionalLightShadows[ i ];\\\\n\\\\t\\\\tdirectLight.color *= all( bvec2( directLight.visible, receiveShadow ) ) ? getShadow( directionalShadowMap[ i ], directionalLightShadow.shadowMapSize, directionalLightShadow.shadowBias, directionalLightShadow.shadowRadius, vDirectionalShadowCoord[ i ] ) : 1.0;\\\\n\\\\t\\\\t#endif\\\\n\\\\n\\\\t\\\\tRE_Direct( directLight, geometry, material, reflectedLight );\\\\n\\\\n\\\\t}\\\\n\\\\t#pragma unroll_loop_end\\\\n\\\\n#endif\\\\n\\\\n#if ( NUM_RECT_AREA_LIGHTS > 0 ) && defined( RE_Direct_RectArea )\\\\n\\\\n\\\\tRectAreaLight rectAreaLight;\\\\n\\\\n\\\\t#pragma unroll_loop_start\\\\n\\\\tfor ( int i = 0; i < NUM_RECT_AREA_LIGHTS; i ++ ) {\\\\n\\\\n\\\\t\\\\trectAreaLight = rectAreaLights[ i ];\\\\n\\\\t\\\\tRE_Direct_RectArea( rectAreaLight, geometry, material, reflectedLight );\\\\n\\\\n\\\\t}\\\\n\\\\t#pragma unroll_loop_end\\\\n\\\\n#endif\\\\n\\\\n#if defined( RE_IndirectDiffuse )\\\\n\\\\n\\\\tvec3 iblIrradiance = vec3( 0.0 );\\\\n\\\\n\\\\tvec3 irradiance = getAmbientLightIrradiance( ambientLightColor );\\\\n\\\\n\\\\tirradiance += getLightProbeIrradiance( lightProbe, geometry.normal );\\\\n\\\\n\\\\t#if ( NUM_HEMI_LIGHTS > 0 )\\\\n\\\\n\\\\t\\\\t#pragma unroll_loop_start\\\\n\\\\t\\\\tfor ( int i = 0; i < NUM_HEMI_LIGHTS; i ++ ) {\\\\n\\\\n\\\\t\\\\t\\\\tirradiance += getHemisphereLightIrradiance( hemisphereLights[ i ], geometry.normal );\\\\n\\\\n\\\\t\\\\t}\\\\n\\\\t\\\\t#pragma unroll_loop_end\\\\n\\\\n\\\\t#endif\\\\n\\\\n#endif\\\\n\\\\n#if defined( RE_IndirectSpecular )\\\\n\\\\n\\\\tvec3 radiance = vec3( 0.0 );\\\\n\\\\tvec3 clearcoatRadiance = vec3( 0.0 );\\\\n\\\\n#endif\\\\n\\\\\\\",lights_fragment_maps:\\\\\\\"\\\\n#if defined( RE_IndirectDiffuse )\\\\n\\\\n\\\\t#ifdef USE_LIGHTMAP\\\\n\\\\n\\\\t\\\\tvec4 lightMapTexel = texture2D( lightMap, vUv2 );\\\\n\\\\t\\\\tvec3 lightMapIrradiance = lightMapTexelToLinear( lightMapTexel ).rgb * lightMapIntensity;\\\\n\\\\n\\\\t\\\\t#ifndef PHYSICALLY_CORRECT_LIGHTS\\\\n\\\\n\\\\t\\\\t\\\\tlightMapIrradiance *= PI;\\\\n\\\\n\\\\t\\\\t#endif\\\\n\\\\n\\\\t\\\\tirradiance += lightMapIrradiance;\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\t#if defined( USE_ENVMAP ) && defined( STANDARD ) && defined( ENVMAP_TYPE_CUBE_UV )\\\\n\\\\n\\\\t\\\\tiblIrradiance += getIBLIrradiance( geometry.normal );\\\\n\\\\n\\\\t#endif\\\\n\\\\n#endif\\\\n\\\\n#if defined( USE_ENVMAP ) && defined( RE_IndirectSpecular )\\\\n\\\\n\\\\tradiance += getIBLRadiance( geometry.viewDir, geometry.normal, material.roughness );\\\\n\\\\n\\\\t#ifdef USE_CLEARCOAT\\\\n\\\\n\\\\t\\\\tclearcoatRadiance += getIBLRadiance( geometry.viewDir, geometry.clearcoatNormal, material.clearcoatRoughness );\\\\n\\\\n\\\\t#endif\\\\n\\\\n#endif\\\\n\\\\\\\",lights_fragment_end:\\\\\\\"\\\\n#if defined( RE_IndirectDiffuse )\\\\n\\\\n\\\\tRE_IndirectDiffuse( irradiance, geometry, material, reflectedLight );\\\\n\\\\n#endif\\\\n\\\\n#if defined( RE_IndirectSpecular )\\\\n\\\\n\\\\tRE_IndirectSpecular( radiance, iblIrradiance, clearcoatRadiance, geometry, material, reflectedLight );\\\\n\\\\n#endif\\\\n\\\\\\\",logdepthbuf_fragment:\\\\\\\"\\\\n#if defined( USE_LOGDEPTHBUF ) && defined( USE_LOGDEPTHBUF_EXT )\\\\n\\\\n\\\\t// Doing a strict comparison with == 1.0 can cause noise artifacts\\\\n\\\\t// on some platforms. See issue #17623.\\\\n\\\\tgl_FragDepthEXT = vIsPerspective == 0.0 ? gl_FragCoord.z : log2( vFragDepth ) * logDepthBufFC * 0.5;\\\\n\\\\n#endif\\\\n\\\\\\\",logdepthbuf_pars_fragment:\\\\\\\"\\\\n#if defined( USE_LOGDEPTHBUF ) && defined( USE_LOGDEPTHBUF_EXT )\\\\n\\\\n\\\\tuniform float logDepthBufFC;\\\\n\\\\tvarying float vFragDepth;\\\\n\\\\tvarying float vIsPerspective;\\\\n\\\\n#endif\\\\n\\\\\\\",logdepthbuf_pars_vertex:\\\\\\\"\\\\n#ifdef USE_LOGDEPTHBUF\\\\n\\\\n\\\\t#ifdef USE_LOGDEPTHBUF_EXT\\\\n\\\\n\\\\t\\\\tvarying float vFragDepth;\\\\n\\\\t\\\\tvarying float vIsPerspective;\\\\n\\\\n\\\\t#else\\\\n\\\\n\\\\t\\\\tuniform float logDepthBufFC;\\\\n\\\\n\\\\t#endif\\\\n\\\\n#endif\\\\n\\\\\\\",logdepthbuf_vertex:\\\\\\\"\\\\n#ifdef USE_LOGDEPTHBUF\\\\n\\\\n\\\\t#ifdef USE_LOGDEPTHBUF_EXT\\\\n\\\\n\\\\t\\\\tvFragDepth = 1.0 + gl_Position.w;\\\\n\\\\t\\\\tvIsPerspective = float( isPerspectiveMatrix( projectionMatrix ) );\\\\n\\\\n\\\\t#else\\\\n\\\\n\\\\t\\\\tif ( isPerspectiveMatrix( projectionMatrix ) ) {\\\\n\\\\n\\\\t\\\\t\\\\tgl_Position.z = log2( max( EPSILON, gl_Position.w + 1.0 ) ) * logDepthBufFC - 1.0;\\\\n\\\\n\\\\t\\\\t\\\\tgl_Position.z *= gl_Position.w;\\\\n\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\t#endif\\\\n\\\\n#endif\\\\n\\\\\\\",map_fragment:\\\\\\\"\\\\n#ifdef USE_MAP\\\\n\\\\n\\\\tvec4 texelColor = texture2D( map, vUv );\\\\n\\\\n\\\\ttexelColor = mapTexelToLinear( texelColor );\\\\n\\\\tdiffuseColor *= texelColor;\\\\n\\\\n#endif\\\\n\\\\\\\",map_pars_fragment:\\\\\\\"\\\\n#ifdef USE_MAP\\\\n\\\\n\\\\tuniform sampler2D map;\\\\n\\\\n#endif\\\\n\\\\\\\",map_particle_fragment:\\\\\\\"\\\\n#if defined( USE_MAP ) || defined( USE_ALPHAMAP )\\\\n\\\\n\\\\tvec2 uv = ( uvTransform * vec3( gl_PointCoord.x, 1.0 - gl_PointCoord.y, 1 ) ).xy;\\\\n\\\\n#endif\\\\n\\\\n#ifdef USE_MAP\\\\n\\\\n\\\\tvec4 mapTexel = texture2D( map, uv );\\\\n\\\\tdiffuseColor *= mapTexelToLinear( mapTexel );\\\\n\\\\n#endif\\\\n\\\\n#ifdef USE_ALPHAMAP\\\\n\\\\n\\\\tdiffuseColor.a *= texture2D( alphaMap, uv ).g;\\\\n\\\\n#endif\\\\n\\\\\\\",map_particle_pars_fragment:\\\\\\\"\\\\n#if defined( USE_MAP ) || defined( USE_ALPHAMAP )\\\\n\\\\n\\\\tuniform mat3 uvTransform;\\\\n\\\\n#endif\\\\n\\\\n#ifdef USE_MAP\\\\n\\\\n\\\\tuniform sampler2D map;\\\\n\\\\n#endif\\\\n\\\\n#ifdef USE_ALPHAMAP\\\\n\\\\n\\\\tuniform sampler2D alphaMap;\\\\n\\\\n#endif\\\\n\\\\\\\",metalnessmap_fragment:\\\\\\\"\\\\nfloat metalnessFactor = metalness;\\\\n\\\\n#ifdef USE_METALNESSMAP\\\\n\\\\n\\\\tvec4 texelMetalness = texture2D( metalnessMap, vUv );\\\\n\\\\n\\\\t// reads channel B, compatible with a combined OcclusionRoughnessMetallic (RGB) texture\\\\n\\\\tmetalnessFactor *= texelMetalness.b;\\\\n\\\\n#endif\\\\n\\\\\\\",metalnessmap_pars_fragment:\\\\\\\"\\\\n#ifdef USE_METALNESSMAP\\\\n\\\\n\\\\tuniform sampler2D metalnessMap;\\\\n\\\\n#endif\\\\n\\\\\\\",morphnormal_vertex:\\\\\\\"\\\\n#ifdef USE_MORPHNORMALS\\\\n\\\\n\\\\t// morphTargetBaseInfluence is set based on BufferGeometry.morphTargetsRelative value:\\\\n\\\\t// When morphTargetsRelative is false, this is set to 1 - sum(influences); this results in normal = sum((target - base) * influence)\\\\n\\\\t// When morphTargetsRelative is true, this is set to 1; as a result, all morph targets are simply added to the base after weighting\\\\n\\\\tobjectNormal *= morphTargetBaseInfluence;\\\\n\\\\n\\\\t#ifdef MORPHTARGETS_TEXTURE\\\\n\\\\n\\\\t\\\\tfor ( int i = 0; i < MORPHTARGETS_COUNT; i ++ ) {\\\\n\\\\n\\\\t\\\\t\\\\tif ( morphTargetInfluences[ i ] > 0.0 ) objectNormal += getMorph( gl_VertexID, i, 1, 2 ) * morphTargetInfluences[ i ];\\\\n\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\t#else\\\\n\\\\n\\\\t\\\\tobjectNormal += morphNormal0 * morphTargetInfluences[ 0 ];\\\\n\\\\t\\\\tobjectNormal += morphNormal1 * morphTargetInfluences[ 1 ];\\\\n\\\\t\\\\tobjectNormal += morphNormal2 * morphTargetInfluences[ 2 ];\\\\n\\\\t\\\\tobjectNormal += morphNormal3 * morphTargetInfluences[ 3 ];\\\\n\\\\n\\\\t#endif\\\\n\\\\n#endif\\\\n\\\\\\\",morphtarget_pars_vertex:\\\\\\\"\\\\n#ifdef USE_MORPHTARGETS\\\\n\\\\n\\\\tuniform float morphTargetBaseInfluence;\\\\n\\\\n\\\\t#ifdef MORPHTARGETS_TEXTURE\\\\n\\\\n\\\\t\\\\tuniform float morphTargetInfluences[ MORPHTARGETS_COUNT ];\\\\n\\\\t\\\\tuniform sampler2DArray morphTargetsTexture;\\\\n\\\\t\\\\tuniform vec2 morphTargetsTextureSize;\\\\n\\\\n\\\\t\\\\tvec3 getMorph( const in int vertexIndex, const in int morphTargetIndex, const in int offset, const in int stride ) {\\\\n\\\\n\\\\t\\\\t\\\\tfloat texelIndex = float( vertexIndex * stride + offset );\\\\n\\\\t\\\\t\\\\tfloat y = floor( texelIndex / morphTargetsTextureSize.x );\\\\n\\\\t\\\\t\\\\tfloat x = texelIndex - y * morphTargetsTextureSize.x;\\\\n\\\\n\\\\t\\\\t\\\\tvec3 morphUV = vec3( ( x + 0.5 ) / morphTargetsTextureSize.x, y / morphTargetsTextureSize.y, morphTargetIndex );\\\\n\\\\t\\\\t\\\\treturn texture( morphTargetsTexture, morphUV ).xyz;\\\\n\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\t#else\\\\n\\\\n\\\\t\\\\t#ifndef USE_MORPHNORMALS\\\\n\\\\n\\\\t\\\\t\\\\tuniform float morphTargetInfluences[ 8 ];\\\\n\\\\n\\\\t\\\\t#else\\\\n\\\\n\\\\t\\\\t\\\\tuniform float morphTargetInfluences[ 4 ];\\\\n\\\\n\\\\t\\\\t#endif\\\\n\\\\n\\\\t#endif\\\\n\\\\n#endif\\\\n\\\\\\\",morphtarget_vertex:\\\\\\\"\\\\n#ifdef USE_MORPHTARGETS\\\\n\\\\n\\\\t// morphTargetBaseInfluence is set based on BufferGeometry.morphTargetsRelative value:\\\\n\\\\t// When morphTargetsRelative is false, this is set to 1 - sum(influences); this results in position = sum((target - base) * influence)\\\\n\\\\t// When morphTargetsRelative is true, this is set to 1; as a result, all morph targets are simply added to the base after weighting\\\\n\\\\ttransformed *= morphTargetBaseInfluence;\\\\n\\\\n\\\\t#ifdef MORPHTARGETS_TEXTURE\\\\n\\\\n\\\\t\\\\tfor ( int i = 0; i < MORPHTARGETS_COUNT; i ++ ) {\\\\n\\\\n\\\\t\\\\t\\\\t#ifndef USE_MORPHNORMALS\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tif ( morphTargetInfluences[ i ] > 0.0 ) transformed += getMorph( gl_VertexID, i, 0, 1 ) * morphTargetInfluences[ i ];\\\\n\\\\n\\\\t\\\\t\\\\t#else\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tif ( morphTargetInfluences[ i ] > 0.0 ) transformed += getMorph( gl_VertexID, i, 0, 2 ) * morphTargetInfluences[ i ];\\\\n\\\\n\\\\t\\\\t\\\\t#endif\\\\n\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\t#else\\\\n\\\\n\\\\t\\\\ttransformed += morphTarget0 * morphTargetInfluences[ 0 ];\\\\n\\\\t\\\\ttransformed += morphTarget1 * morphTargetInfluences[ 1 ];\\\\n\\\\t\\\\ttransformed += morphTarget2 * morphTargetInfluences[ 2 ];\\\\n\\\\t\\\\ttransformed += morphTarget3 * morphTargetInfluences[ 3 ];\\\\n\\\\n\\\\t\\\\t#ifndef USE_MORPHNORMALS\\\\n\\\\n\\\\t\\\\t\\\\ttransformed += morphTarget4 * morphTargetInfluences[ 4 ];\\\\n\\\\t\\\\t\\\\ttransformed += morphTarget5 * morphTargetInfluences[ 5 ];\\\\n\\\\t\\\\t\\\\ttransformed += morphTarget6 * morphTargetInfluences[ 6 ];\\\\n\\\\t\\\\t\\\\ttransformed += morphTarget7 * morphTargetInfluences[ 7 ];\\\\n\\\\n\\\\t\\\\t#endif\\\\n\\\\n\\\\t#endif\\\\n\\\\n#endif\\\\n\\\\\\\",normal_fragment_begin:\\\\\\\"\\\\nfloat faceDirection = gl_FrontFacing ? 1.0 : - 1.0;\\\\n\\\\n#ifdef FLAT_SHADED\\\\n\\\\n\\\\t// Workaround for Adreno GPUs not able to do dFdx( vViewPosition )\\\\n\\\\n\\\\tvec3 fdx = vec3( dFdx( vViewPosition.x ), dFdx( vViewPosition.y ), dFdx( vViewPosition.z ) );\\\\n\\\\tvec3 fdy = vec3( dFdy( vViewPosition.x ), dFdy( vViewPosition.y ), dFdy( vViewPosition.z ) );\\\\n\\\\tvec3 normal = normalize( cross( fdx, fdy ) );\\\\n\\\\n#else\\\\n\\\\n\\\\tvec3 normal = normalize( vNormal );\\\\n\\\\n\\\\t#ifdef DOUBLE_SIDED\\\\n\\\\n\\\\t\\\\tnormal = normal * faceDirection;\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\t#ifdef USE_TANGENT\\\\n\\\\n\\\\t\\\\tvec3 tangent = normalize( vTangent );\\\\n\\\\t\\\\tvec3 bitangent = normalize( vBitangent );\\\\n\\\\n\\\\t\\\\t#ifdef DOUBLE_SIDED\\\\n\\\\n\\\\t\\\\t\\\\ttangent = tangent * faceDirection;\\\\n\\\\t\\\\t\\\\tbitangent = bitangent * faceDirection;\\\\n\\\\n\\\\t\\\\t#endif\\\\n\\\\n\\\\t\\\\t#if defined( TANGENTSPACE_NORMALMAP ) || defined( USE_CLEARCOAT_NORMALMAP )\\\\n\\\\n\\\\t\\\\t\\\\tmat3 vTBN = mat3( tangent, bitangent, normal );\\\\n\\\\n\\\\t\\\\t#endif\\\\n\\\\n\\\\t#endif\\\\n\\\\n#endif\\\\n\\\\n// non perturbed normal for clearcoat among others\\\\n\\\\nvec3 geometryNormal = normal;\\\\n\\\\n\\\\\\\",normal_fragment_maps:\\\\\\\"\\\\n\\\\n#ifdef OBJECTSPACE_NORMALMAP\\\\n\\\\n\\\\tnormal = texture2D( normalMap, vUv ).xyz * 2.0 - 1.0; // overrides both flatShading and attribute normals\\\\n\\\\n\\\\t#ifdef FLIP_SIDED\\\\n\\\\n\\\\t\\\\tnormal = - normal;\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\t#ifdef DOUBLE_SIDED\\\\n\\\\n\\\\t\\\\tnormal = normal * faceDirection;\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\tnormal = normalize( normalMatrix * normal );\\\\n\\\\n#elif defined( TANGENTSPACE_NORMALMAP )\\\\n\\\\n\\\\tvec3 mapN = texture2D( normalMap, vUv ).xyz * 2.0 - 1.0;\\\\n\\\\tmapN.xy *= normalScale;\\\\n\\\\n\\\\t#ifdef USE_TANGENT\\\\n\\\\n\\\\t\\\\tnormal = normalize( vTBN * mapN );\\\\n\\\\n\\\\t#else\\\\n\\\\n\\\\t\\\\tnormal = perturbNormal2Arb( - vViewPosition, normal, mapN, faceDirection );\\\\n\\\\n\\\\t#endif\\\\n\\\\n#elif defined( USE_BUMPMAP )\\\\n\\\\n\\\\tnormal = perturbNormalArb( - vViewPosition, normal, dHdxy_fwd(), faceDirection );\\\\n\\\\n#endif\\\\n\\\\\\\",normal_pars_fragment:\\\\\\\"\\\\n#ifndef FLAT_SHADED\\\\n\\\\n\\\\tvarying vec3 vNormal;\\\\n\\\\n\\\\t#ifdef USE_TANGENT\\\\n\\\\n\\\\t\\\\tvarying vec3 vTangent;\\\\n\\\\t\\\\tvarying vec3 vBitangent;\\\\n\\\\n\\\\t#endif\\\\n\\\\n#endif\\\\n\\\\\\\",normal_pars_vertex:\\\\\\\"\\\\n#ifndef FLAT_SHADED\\\\n\\\\n\\\\tvarying vec3 vNormal;\\\\n\\\\n\\\\t#ifdef USE_TANGENT\\\\n\\\\n\\\\t\\\\tvarying vec3 vTangent;\\\\n\\\\t\\\\tvarying vec3 vBitangent;\\\\n\\\\n\\\\t#endif\\\\n\\\\n#endif\\\\n\\\\\\\",normal_vertex:\\\\\\\"\\\\n#ifndef FLAT_SHADED // normal is computed with derivatives when FLAT_SHADED\\\\n\\\\n\\\\tvNormal = normalize( transformedNormal );\\\\n\\\\n\\\\t#ifdef USE_TANGENT\\\\n\\\\n\\\\t\\\\tvTangent = normalize( transformedTangent );\\\\n\\\\t\\\\tvBitangent = normalize( cross( vNormal, vTangent ) * tangent.w );\\\\n\\\\n\\\\t#endif\\\\n\\\\n#endif\\\\n\\\\\\\",normalmap_pars_fragment:\\\\\\\"\\\\n#ifdef USE_NORMALMAP\\\\n\\\\n\\\\tuniform sampler2D normalMap;\\\\n\\\\tuniform vec2 normalScale;\\\\n\\\\n#endif\\\\n\\\\n#ifdef OBJECTSPACE_NORMALMAP\\\\n\\\\n\\\\tuniform mat3 normalMatrix;\\\\n\\\\n#endif\\\\n\\\\n#if ! defined ( USE_TANGENT ) && ( defined ( TANGENTSPACE_NORMALMAP ) || defined ( USE_CLEARCOAT_NORMALMAP ) )\\\\n\\\\n\\\\t// Normal Mapping Without Precomputed Tangents\\\\n\\\\t// http://www.thetenthplanet.de/archives/1180\\\\n\\\\n\\\\tvec3 perturbNormal2Arb( vec3 eye_pos, vec3 surf_norm, vec3 mapN, float faceDirection ) {\\\\n\\\\n\\\\t\\\\t// Workaround for Adreno 3XX dFd*( vec3 ) bug. See #9988\\\\n\\\\n\\\\t\\\\tvec3 q0 = vec3( dFdx( eye_pos.x ), dFdx( eye_pos.y ), dFdx( eye_pos.z ) );\\\\n\\\\t\\\\tvec3 q1 = vec3( dFdy( eye_pos.x ), dFdy( eye_pos.y ), dFdy( eye_pos.z ) );\\\\n\\\\t\\\\tvec2 st0 = dFdx( vUv.st );\\\\n\\\\t\\\\tvec2 st1 = dFdy( vUv.st );\\\\n\\\\n\\\\t\\\\tvec3 N = surf_norm; // normalized\\\\n\\\\n\\\\t\\\\tvec3 q1perp = cross( q1, N );\\\\n\\\\t\\\\tvec3 q0perp = cross( N, q0 );\\\\n\\\\n\\\\t\\\\tvec3 T = q1perp * st0.x + q0perp * st1.x;\\\\n\\\\t\\\\tvec3 B = q1perp * st0.y + q0perp * st1.y;\\\\n\\\\n\\\\t\\\\tfloat det = max( dot( T, T ), dot( B, B ) );\\\\n\\\\t\\\\tfloat scale = ( det == 0.0 ) ? 0.0 : faceDirection * inversesqrt( det );\\\\n\\\\n\\\\t\\\\treturn normalize( T * ( mapN.x * scale ) + B * ( mapN.y * scale ) + N * mapN.z );\\\\n\\\\n\\\\t}\\\\n\\\\n#endif\\\\n\\\\\\\",clearcoat_normal_fragment_begin:\\\\\\\"\\\\n#ifdef USE_CLEARCOAT\\\\n\\\\n\\\\tvec3 clearcoatNormal = geometryNormal;\\\\n\\\\n#endif\\\\n\\\\\\\",clearcoat_normal_fragment_maps:\\\\\\\"\\\\n#ifdef USE_CLEARCOAT_NORMALMAP\\\\n\\\\n\\\\tvec3 clearcoatMapN = texture2D( clearcoatNormalMap, vUv ).xyz * 2.0 - 1.0;\\\\n\\\\tclearcoatMapN.xy *= clearcoatNormalScale;\\\\n\\\\n\\\\t#ifdef USE_TANGENT\\\\n\\\\n\\\\t\\\\tclearcoatNormal = normalize( vTBN * clearcoatMapN );\\\\n\\\\n\\\\t#else\\\\n\\\\n\\\\t\\\\tclearcoatNormal = perturbNormal2Arb( - vViewPosition, clearcoatNormal, clearcoatMapN, faceDirection );\\\\n\\\\n\\\\t#endif\\\\n\\\\n#endif\\\\n\\\\\\\",clearcoat_pars_fragment:\\\\\\\"\\\\n\\\\n#ifdef USE_CLEARCOATMAP\\\\n\\\\n\\\\tuniform sampler2D clearcoatMap;\\\\n\\\\n#endif\\\\n\\\\n#ifdef USE_CLEARCOAT_ROUGHNESSMAP\\\\n\\\\n\\\\tuniform sampler2D clearcoatRoughnessMap;\\\\n\\\\n#endif\\\\n\\\\n#ifdef USE_CLEARCOAT_NORMALMAP\\\\n\\\\n\\\\tuniform sampler2D clearcoatNormalMap;\\\\n\\\\tuniform vec2 clearcoatNormalScale;\\\\n\\\\n#endif\\\\n\\\\\\\",output_fragment:\\\\\\\"\\\\n#ifdef OPAQUE\\\\ndiffuseColor.a = 1.0;\\\\n#endif\\\\n\\\\n// https://github.com/mrdoob/three.js/pull/22425\\\\n#ifdef USE_TRANSMISSION\\\\ndiffuseColor.a *= transmissionAlpha + 0.1;\\\\n#endif\\\\n\\\\ngl_FragColor = vec4( outgoingLight, diffuseColor.a );\\\\n\\\\\\\",packing:\\\\\\\"\\\\nvec3 packNormalToRGB( const in vec3 normal ) {\\\\n\\\\treturn normalize( normal ) * 0.5 + 0.5;\\\\n}\\\\n\\\\nvec3 unpackRGBToNormal( const in vec3 rgb ) {\\\\n\\\\treturn 2.0 * rgb.xyz - 1.0;\\\\n}\\\\n\\\\nconst float PackUpscale = 256. / 255.; // fraction -> 0..1 (including 1)\\\\nconst float UnpackDownscale = 255. / 256.; // 0..1 -> fraction (excluding 1)\\\\n\\\\nconst vec3 PackFactors = vec3( 256. * 256. * 256., 256. * 256., 256. );\\\\nconst vec4 UnpackFactors = UnpackDownscale / vec4( PackFactors, 1. );\\\\n\\\\nconst float ShiftRight8 = 1. / 256.;\\\\n\\\\nvec4 packDepthToRGBA( const in float v ) {\\\\n\\\\tvec4 r = vec4( fract( v * PackFactors ), v );\\\\n\\\\tr.yzw -= r.xyz * ShiftRight8; // tidy overflow\\\\n\\\\treturn r * PackUpscale;\\\\n}\\\\n\\\\nfloat unpackRGBAToDepth( const in vec4 v ) {\\\\n\\\\treturn dot( v, UnpackFactors );\\\\n}\\\\n\\\\nvec4 pack2HalfToRGBA( vec2 v ) {\\\\n\\\\tvec4 r = vec4( v.x, fract( v.x * 255.0 ), v.y, fract( v.y * 255.0 ) );\\\\n\\\\treturn vec4( r.x - r.y / 255.0, r.y, r.z - r.w / 255.0, r.w );\\\\n}\\\\n\\\\nvec2 unpackRGBATo2Half( vec4 v ) {\\\\n\\\\treturn vec2( v.x + ( v.y / 255.0 ), v.z + ( v.w / 255.0 ) );\\\\n}\\\\n\\\\n// NOTE: viewZ/eyeZ is < 0 when in front of the camera per OpenGL conventions\\\\n\\\\nfloat viewZToOrthographicDepth( const in float viewZ, const in float near, const in float far ) {\\\\n\\\\treturn ( viewZ + near ) / ( near - far );\\\\n}\\\\nfloat orthographicDepthToViewZ( const in float linearClipZ, const in float near, const in float far ) {\\\\n\\\\treturn linearClipZ * ( near - far ) - near;\\\\n}\\\\n\\\\n// NOTE: https://twitter.com/gonnavis/status/1377183786949959682\\\\n\\\\nfloat viewZToPerspectiveDepth( const in float viewZ, const in float near, const in float far ) {\\\\n\\\\treturn ( ( near + viewZ ) * far ) / ( ( far - near ) * viewZ );\\\\n}\\\\nfloat perspectiveDepthToViewZ( const in float invClipZ, const in float near, const in float far ) {\\\\n\\\\treturn ( near * far ) / ( ( far - near ) * invClipZ - far );\\\\n}\\\\n\\\\\\\",premultiplied_alpha_fragment:\\\\\\\"\\\\n#ifdef PREMULTIPLIED_ALPHA\\\\n\\\\n\\\\t// Get get normal blending with premultipled, use with CustomBlending, OneFactor, OneMinusSrcAlphaFactor, AddEquation.\\\\n\\\\tgl_FragColor.rgb *= gl_FragColor.a;\\\\n\\\\n#endif\\\\n\\\\\\\",project_vertex:\\\\\\\"\\\\nvec4 mvPosition = vec4( transformed, 1.0 );\\\\n\\\\n#ifdef USE_INSTANCING\\\\n\\\\n\\\\tmvPosition = instanceMatrix * mvPosition;\\\\n\\\\n#endif\\\\n\\\\nmvPosition = modelViewMatrix * mvPosition;\\\\n\\\\ngl_Position = projectionMatrix * mvPosition;\\\\n\\\\\\\",dithering_fragment:\\\\\\\"\\\\n#ifdef DITHERING\\\\n\\\\n\\\\tgl_FragColor.rgb = dithering( gl_FragColor.rgb );\\\\n\\\\n#endif\\\\n\\\\\\\",dithering_pars_fragment:\\\\\\\"\\\\n#ifdef DITHERING\\\\n\\\\n\\\\t// based on https://www.shadertoy.com/view/MslGR8\\\\n\\\\tvec3 dithering( vec3 color ) {\\\\n\\\\t\\\\t//Calculate grid position\\\\n\\\\t\\\\tfloat grid_position = rand( gl_FragCoord.xy );\\\\n\\\\n\\\\t\\\\t//Shift the individual colors differently, thus making it even harder to see the dithering pattern\\\\n\\\\t\\\\tvec3 dither_shift_RGB = vec3( 0.25 / 255.0, -0.25 / 255.0, 0.25 / 255.0 );\\\\n\\\\n\\\\t\\\\t//modify shift acording to grid position.\\\\n\\\\t\\\\tdither_shift_RGB = mix( 2.0 * dither_shift_RGB, -2.0 * dither_shift_RGB, grid_position );\\\\n\\\\n\\\\t\\\\t//shift the color by dither_shift\\\\n\\\\t\\\\treturn color + dither_shift_RGB;\\\\n\\\\t}\\\\n\\\\n#endif\\\\n\\\\\\\",roughnessmap_fragment:\\\\\\\"\\\\nfloat roughnessFactor = roughness;\\\\n\\\\n#ifdef USE_ROUGHNESSMAP\\\\n\\\\n\\\\tvec4 texelRoughness = texture2D( roughnessMap, vUv );\\\\n\\\\n\\\\t// reads channel G, compatible with a combined OcclusionRoughnessMetallic (RGB) texture\\\\n\\\\troughnessFactor *= texelRoughness.g;\\\\n\\\\n#endif\\\\n\\\\\\\",roughnessmap_pars_fragment:\\\\\\\"\\\\n#ifdef USE_ROUGHNESSMAP\\\\n\\\\n\\\\tuniform sampler2D roughnessMap;\\\\n\\\\n#endif\\\\n\\\\\\\",shadowmap_pars_fragment:z,shadowmap_pars_vertex:\\\\\\\"\\\\n#ifdef USE_SHADOWMAP\\\\n\\\\n\\\\t#if NUM_DIR_LIGHT_SHADOWS > 0\\\\n\\\\n\\\\t\\\\tuniform mat4 directionalShadowMatrix[ NUM_DIR_LIGHT_SHADOWS ];\\\\n\\\\t\\\\tvarying vec4 vDirectionalShadowCoord[ NUM_DIR_LIGHT_SHADOWS ];\\\\n\\\\n\\\\t\\\\tstruct DirectionalLightShadow {\\\\n\\\\t\\\\t\\\\tfloat shadowBias;\\\\n\\\\t\\\\t\\\\tfloat shadowNormalBias;\\\\n\\\\t\\\\t\\\\tfloat shadowRadius;\\\\n\\\\t\\\\t\\\\tvec2 shadowMapSize;\\\\n\\\\t\\\\t};\\\\n\\\\n\\\\t\\\\tuniform DirectionalLightShadow directionalLightShadows[ NUM_DIR_LIGHT_SHADOWS ];\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\t#if NUM_SPOT_LIGHT_SHADOWS > 0\\\\n\\\\n\\\\t\\\\tuniform mat4 spotShadowMatrix[ NUM_SPOT_LIGHT_SHADOWS ];\\\\n\\\\t\\\\tvarying vec4 vSpotShadowCoord[ NUM_SPOT_LIGHT_SHADOWS ];\\\\n\\\\n\\\\t\\\\tstruct SpotLightShadow {\\\\n\\\\t\\\\t\\\\tfloat shadowBias;\\\\n\\\\t\\\\t\\\\tfloat shadowNormalBias;\\\\n\\\\t\\\\t\\\\tfloat shadowRadius;\\\\n\\\\t\\\\t\\\\tvec2 shadowMapSize;\\\\n\\\\t\\\\t};\\\\n\\\\n\\\\t\\\\tuniform SpotLightShadow spotLightShadows[ NUM_SPOT_LIGHT_SHADOWS ];\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\t#if NUM_POINT_LIGHT_SHADOWS > 0\\\\n\\\\n\\\\t\\\\tuniform mat4 pointShadowMatrix[ NUM_POINT_LIGHT_SHADOWS ];\\\\n\\\\t\\\\tvarying vec4 vPointShadowCoord[ NUM_POINT_LIGHT_SHADOWS ];\\\\n\\\\n\\\\t\\\\tstruct PointLightShadow {\\\\n\\\\t\\\\t\\\\tfloat shadowBias;\\\\n\\\\t\\\\t\\\\tfloat shadowNormalBias;\\\\n\\\\t\\\\t\\\\tfloat shadowRadius;\\\\n\\\\t\\\\t\\\\tvec2 shadowMapSize;\\\\n\\\\t\\\\t\\\\tfloat shadowCameraNear;\\\\n\\\\t\\\\t\\\\tfloat shadowCameraFar;\\\\n\\\\t\\\\t};\\\\n\\\\n\\\\t\\\\tuniform PointLightShadow pointLightShadows[ NUM_POINT_LIGHT_SHADOWS ];\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\t/*\\\\n\\\\t#if NUM_RECT_AREA_LIGHTS > 0\\\\n\\\\n\\\\t\\\\t// TODO (abelnation): uniforms for area light shadows\\\\n\\\\n\\\\t#endif\\\\n\\\\t*/\\\\n\\\\n#endif\\\\n\\\\\\\",shadowmap_vertex:\\\\\\\"\\\\n#ifdef USE_SHADOWMAP\\\\n\\\\n\\\\t#if NUM_DIR_LIGHT_SHADOWS > 0 || NUM_SPOT_LIGHT_SHADOWS > 0 || NUM_POINT_LIGHT_SHADOWS > 0\\\\n\\\\n\\\\t\\\\t// Offsetting the position used for querying occlusion along the world normal can be used to reduce shadow acne.\\\\n\\\\t\\\\tvec3 shadowWorldNormal = inverseTransformDirection( transformedNormal, viewMatrix );\\\\n\\\\t\\\\tvec4 shadowWorldPosition;\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\t#if NUM_DIR_LIGHT_SHADOWS > 0\\\\n\\\\n\\\\t#pragma unroll_loop_start\\\\n\\\\tfor ( int i = 0; i < NUM_DIR_LIGHT_SHADOWS; i ++ ) {\\\\n\\\\n\\\\t\\\\tshadowWorldPosition = worldPosition + vec4( shadowWorldNormal * directionalLightShadows[ i ].shadowNormalBias, 0 );\\\\n\\\\t\\\\tvDirectionalShadowCoord[ i ] = directionalShadowMatrix[ i ] * shadowWorldPosition;\\\\n\\\\n\\\\t}\\\\n\\\\t#pragma unroll_loop_end\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\t#if NUM_SPOT_LIGHT_SHADOWS > 0\\\\n\\\\n\\\\t#pragma unroll_loop_start\\\\n\\\\tfor ( int i = 0; i < NUM_SPOT_LIGHT_SHADOWS; i ++ ) {\\\\n\\\\n\\\\t\\\\tshadowWorldPosition = worldPosition + vec4( shadowWorldNormal * spotLightShadows[ i ].shadowNormalBias, 0 );\\\\n\\\\t\\\\tvSpotShadowCoord[ i ] = spotShadowMatrix[ i ] * shadowWorldPosition;\\\\n\\\\n\\\\t}\\\\n\\\\t#pragma unroll_loop_end\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\t#if NUM_POINT_LIGHT_SHADOWS > 0\\\\n\\\\n\\\\t#pragma unroll_loop_start\\\\n\\\\tfor ( int i = 0; i < NUM_POINT_LIGHT_SHADOWS; i ++ ) {\\\\n\\\\n\\\\t\\\\tshadowWorldPosition = worldPosition + vec4( shadowWorldNormal * pointLightShadows[ i ].shadowNormalBias, 0 );\\\\n\\\\t\\\\tvPointShadowCoord[ i ] = pointShadowMatrix[ i ] * shadowWorldPosition;\\\\n\\\\n\\\\t}\\\\n\\\\t#pragma unroll_loop_end\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\t/*\\\\n\\\\t#if NUM_RECT_AREA_LIGHTS > 0\\\\n\\\\n\\\\t\\\\t// TODO (abelnation): update vAreaShadowCoord with area light info\\\\n\\\\n\\\\t#endif\\\\n\\\\t*/\\\\n\\\\n#endif\\\\n\\\\\\\",shadowmask_pars_fragment:\\\\\\\"\\\\nfloat getShadowMask() {\\\\n\\\\n\\\\tfloat shadow = 1.0;\\\\n\\\\n\\\\t#ifdef USE_SHADOWMAP\\\\n\\\\n\\\\t#if NUM_DIR_LIGHT_SHADOWS > 0\\\\n\\\\n\\\\tDirectionalLightShadow directionalLight;\\\\n\\\\n\\\\t#pragma unroll_loop_start\\\\n\\\\tfor ( int i = 0; i < NUM_DIR_LIGHT_SHADOWS; i ++ ) {\\\\n\\\\n\\\\t\\\\tdirectionalLight = directionalLightShadows[ i ];\\\\n\\\\t\\\\tshadow *= receiveShadow ? getShadow( directionalShadowMap[ i ], directionalLight.shadowMapSize, directionalLight.shadowBias, directionalLight.shadowRadius, vDirectionalShadowCoord[ i ] ) : 1.0;\\\\n\\\\n\\\\t}\\\\n\\\\t#pragma unroll_loop_end\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\t#if NUM_SPOT_LIGHT_SHADOWS > 0\\\\n\\\\n\\\\tSpotLightShadow spotLight;\\\\n\\\\n\\\\t#pragma unroll_loop_start\\\\n\\\\tfor ( int i = 0; i < NUM_SPOT_LIGHT_SHADOWS; i ++ ) {\\\\n\\\\n\\\\t\\\\tspotLight = spotLightShadows[ i ];\\\\n\\\\t\\\\tshadow *= receiveShadow ? getShadow( spotShadowMap[ i ], spotLight.shadowMapSize, spotLight.shadowBias, spotLight.shadowRadius, vSpotShadowCoord[ i ] ) : 1.0;\\\\n\\\\n\\\\t}\\\\n\\\\t#pragma unroll_loop_end\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\t#if NUM_POINT_LIGHT_SHADOWS > 0\\\\n\\\\n\\\\tPointLightShadow pointLight;\\\\n\\\\n\\\\t#pragma unroll_loop_start\\\\n\\\\tfor ( int i = 0; i < NUM_POINT_LIGHT_SHADOWS; i ++ ) {\\\\n\\\\n\\\\t\\\\tpointLight = pointLightShadows[ i ];\\\\n\\\\t\\\\tshadow *= receiveShadow ? getPointShadow( pointShadowMap[ i ], pointLight.shadowMapSize, pointLight.shadowBias, pointLight.shadowRadius, vPointShadowCoord[ i ], pointLight.shadowCameraNear, pointLight.shadowCameraFar ) : 1.0;\\\\n\\\\n\\\\t}\\\\n\\\\t#pragma unroll_loop_end\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\t/*\\\\n\\\\t#if NUM_RECT_AREA_LIGHTS > 0\\\\n\\\\n\\\\t\\\\t// TODO (abelnation): update shadow for Area light\\\\n\\\\n\\\\t#endif\\\\n\\\\t*/\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\treturn shadow;\\\\n\\\\n}\\\\n\\\\\\\",skinbase_vertex:\\\\\\\"\\\\n#ifdef USE_SKINNING\\\\n\\\\n\\\\tmat4 boneMatX = getBoneMatrix( skinIndex.x );\\\\n\\\\tmat4 boneMatY = getBoneMatrix( skinIndex.y );\\\\n\\\\tmat4 boneMatZ = getBoneMatrix( skinIndex.z );\\\\n\\\\tmat4 boneMatW = getBoneMatrix( skinIndex.w );\\\\n\\\\n#endif\\\\n\\\\\\\",skinning_pars_vertex:\\\\\\\"\\\\n#ifdef USE_SKINNING\\\\n\\\\n\\\\tuniform mat4 bindMatrix;\\\\n\\\\tuniform mat4 bindMatrixInverse;\\\\n\\\\n\\\\t#ifdef BONE_TEXTURE\\\\n\\\\n\\\\t\\\\tuniform highp sampler2D boneTexture;\\\\n\\\\t\\\\tuniform int boneTextureSize;\\\\n\\\\n\\\\t\\\\tmat4 getBoneMatrix( const in float i ) {\\\\n\\\\n\\\\t\\\\t\\\\tfloat j = i * 4.0;\\\\n\\\\t\\\\t\\\\tfloat x = mod( j, float( boneTextureSize ) );\\\\n\\\\t\\\\t\\\\tfloat y = floor( j / float( boneTextureSize ) );\\\\n\\\\n\\\\t\\\\t\\\\tfloat dx = 1.0 / float( boneTextureSize );\\\\n\\\\t\\\\t\\\\tfloat dy = 1.0 / float( boneTextureSize );\\\\n\\\\n\\\\t\\\\t\\\\ty = dy * ( y + 0.5 );\\\\n\\\\n\\\\t\\\\t\\\\tvec4 v1 = texture2D( boneTexture, vec2( dx * ( x + 0.5 ), y ) );\\\\n\\\\t\\\\t\\\\tvec4 v2 = texture2D( boneTexture, vec2( dx * ( x + 1.5 ), y ) );\\\\n\\\\t\\\\t\\\\tvec4 v3 = texture2D( boneTexture, vec2( dx * ( x + 2.5 ), y ) );\\\\n\\\\t\\\\t\\\\tvec4 v4 = texture2D( boneTexture, vec2( dx * ( x + 3.5 ), y ) );\\\\n\\\\n\\\\t\\\\t\\\\tmat4 bone = mat4( v1, v2, v3, v4 );\\\\n\\\\n\\\\t\\\\t\\\\treturn bone;\\\\n\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\t#else\\\\n\\\\n\\\\t\\\\tuniform mat4 boneMatrices[ MAX_BONES ];\\\\n\\\\n\\\\t\\\\tmat4 getBoneMatrix( const in float i ) {\\\\n\\\\n\\\\t\\\\t\\\\tmat4 bone = boneMatrices[ int(i) ];\\\\n\\\\t\\\\t\\\\treturn bone;\\\\n\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\t#endif\\\\n\\\\n#endif\\\\n\\\\\\\",skinning_vertex:\\\\\\\"\\\\n#ifdef USE_SKINNING\\\\n\\\\n\\\\tvec4 skinVertex = bindMatrix * vec4( transformed, 1.0 );\\\\n\\\\n\\\\tvec4 skinned = vec4( 0.0 );\\\\n\\\\tskinned += boneMatX * skinVertex * skinWeight.x;\\\\n\\\\tskinned += boneMatY * skinVertex * skinWeight.y;\\\\n\\\\tskinned += boneMatZ * skinVertex * skinWeight.z;\\\\n\\\\tskinned += boneMatW * skinVertex * skinWeight.w;\\\\n\\\\n\\\\ttransformed = ( bindMatrixInverse * skinned ).xyz;\\\\n\\\\n#endif\\\\n\\\\\\\",skinnormal_vertex:\\\\\\\"\\\\n#ifdef USE_SKINNING\\\\n\\\\n\\\\tmat4 skinMatrix = mat4( 0.0 );\\\\n\\\\tskinMatrix += skinWeight.x * boneMatX;\\\\n\\\\tskinMatrix += skinWeight.y * boneMatY;\\\\n\\\\tskinMatrix += skinWeight.z * boneMatZ;\\\\n\\\\tskinMatrix += skinWeight.w * boneMatW;\\\\n\\\\tskinMatrix = bindMatrixInverse * skinMatrix * bindMatrix;\\\\n\\\\n\\\\tobjectNormal = vec4( skinMatrix * vec4( objectNormal, 0.0 ) ).xyz;\\\\n\\\\n\\\\t#ifdef USE_TANGENT\\\\n\\\\n\\\\t\\\\tobjectTangent = vec4( skinMatrix * vec4( objectTangent, 0.0 ) ).xyz;\\\\n\\\\n\\\\t#endif\\\\n\\\\n#endif\\\\n\\\\\\\",specularmap_fragment:\\\\\\\"\\\\nfloat specularStrength;\\\\n\\\\n#ifdef USE_SPECULARMAP\\\\n\\\\n\\\\tvec4 texelSpecular = texture2D( specularMap, vUv );\\\\n\\\\tspecularStrength = texelSpecular.r;\\\\n\\\\n#else\\\\n\\\\n\\\\tspecularStrength = 1.0;\\\\n\\\\n#endif\\\\n\\\\\\\",specularmap_pars_fragment:\\\\\\\"\\\\n#ifdef USE_SPECULARMAP\\\\n\\\\n\\\\tuniform sampler2D specularMap;\\\\n\\\\n#endif\\\\n\\\\\\\",tonemapping_fragment:\\\\\\\"\\\\n#if defined( TONE_MAPPING )\\\\n\\\\n\\\\tgl_FragColor.rgb = toneMapping( gl_FragColor.rgb );\\\\n\\\\n#endif\\\\n\\\\\\\",tonemapping_pars_fragment:\\\\\\\"\\\\n#ifndef saturate\\\\n// may have defined saturate() already\\\\n#define saturate( a ) clamp( a, 0.0, 1.0 )\\\\n#endif\\\\n\\\\nuniform float toneMappingExposure;\\\\n\\\\n// exposure only\\\\nvec3 LinearToneMapping( vec3 color ) {\\\\n\\\\n\\\\treturn toneMappingExposure * color;\\\\n\\\\n}\\\\n\\\\n// source: https://www.cs.utah.edu/~reinhard/cdrom/\\\\nvec3 ReinhardToneMapping( vec3 color ) {\\\\n\\\\n\\\\tcolor *= toneMappingExposure;\\\\n\\\\treturn saturate( color / ( vec3( 1.0 ) + color ) );\\\\n\\\\n}\\\\n\\\\n// source: http://filmicworlds.com/blog/filmic-tonemapping-operators/\\\\nvec3 OptimizedCineonToneMapping( vec3 color ) {\\\\n\\\\n\\\\t// optimized filmic operator by Jim Hejl and Richard Burgess-Dawson\\\\n\\\\tcolor *= toneMappingExposure;\\\\n\\\\tcolor = max( vec3( 0.0 ), color - 0.004 );\\\\n\\\\treturn pow( ( color * ( 6.2 * color + 0.5 ) ) / ( color * ( 6.2 * color + 1.7 ) + 0.06 ), vec3( 2.2 ) );\\\\n\\\\n}\\\\n\\\\n// source: https://github.com/selfshadow/ltc_code/blob/master/webgl/shaders/ltc/ltc_blit.fs\\\\nvec3 RRTAndODTFit( vec3 v ) {\\\\n\\\\n\\\\tvec3 a = v * ( v + 0.0245786 ) - 0.000090537;\\\\n\\\\tvec3 b = v * ( 0.983729 * v + 0.4329510 ) + 0.238081;\\\\n\\\\treturn a / b;\\\\n\\\\n}\\\\n\\\\n// this implementation of ACES is modified to accommodate a brighter viewing environment.\\\\n// the scale factor of 1/0.6 is subjective. see discussion in #19621.\\\\n\\\\nvec3 ACESFilmicToneMapping( vec3 color ) {\\\\n\\\\n\\\\t// sRGB => XYZ => D65_2_D60 => AP1 => RRT_SAT\\\\n\\\\tconst mat3 ACESInputMat = mat3(\\\\n\\\\t\\\\tvec3( 0.59719, 0.07600, 0.02840 ), // transposed from source\\\\n\\\\t\\\\tvec3( 0.35458, 0.90834, 0.13383 ),\\\\n\\\\t\\\\tvec3( 0.04823, 0.01566, 0.83777 )\\\\n\\\\t);\\\\n\\\\n\\\\t// ODT_SAT => XYZ => D60_2_D65 => sRGB\\\\n\\\\tconst mat3 ACESOutputMat = mat3(\\\\n\\\\t\\\\tvec3( 1.60475, -0.10208, -0.00327 ), // transposed from source\\\\n\\\\t\\\\tvec3( -0.53108, 1.10813, -0.07276 ),\\\\n\\\\t\\\\tvec3( -0.07367, -0.00605, 1.07602 )\\\\n\\\\t);\\\\n\\\\n\\\\tcolor *= toneMappingExposure / 0.6;\\\\n\\\\n\\\\tcolor = ACESInputMat * color;\\\\n\\\\n\\\\t// Apply RRT and ODT\\\\n\\\\tcolor = RRTAndODTFit( color );\\\\n\\\\n\\\\tcolor = ACESOutputMat * color;\\\\n\\\\n\\\\t// Clamp to [0, 1]\\\\n\\\\treturn saturate( color );\\\\n\\\\n}\\\\n\\\\nvec3 CustomToneMapping( vec3 color ) { return color; }\\\\n\\\\\\\",transmission_fragment:k,transmission_pars_fragment:\\\\\\\"\\\\n#ifdef USE_TRANSMISSION\\\\n\\\\n\\\\t// Transmission code is based on glTF-Sampler-Viewer\\\\n\\\\t// https://github.com/KhronosGroup/glTF-Sample-Viewer\\\\n\\\\n\\\\tuniform float transmission;\\\\n\\\\tuniform float thickness;\\\\n\\\\tuniform float attenuationDistance;\\\\n\\\\tuniform vec3 attenuationTint;\\\\n\\\\n\\\\t#ifdef USE_TRANSMISSIONMAP\\\\n\\\\n\\\\t\\\\tuniform sampler2D transmissionMap;\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\t#ifdef USE_THICKNESSMAP\\\\n\\\\n\\\\t\\\\tuniform sampler2D thicknessMap;\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\tuniform vec2 transmissionSamplerSize;\\\\n\\\\tuniform sampler2D transmissionSamplerMap;\\\\n\\\\n\\\\tuniform mat4 modelMatrix;\\\\n\\\\tuniform mat4 projectionMatrix;\\\\n\\\\n\\\\tvarying vec3 vWorldPosition;\\\\n\\\\n\\\\tvec3 getVolumeTransmissionRay( vec3 n, vec3 v, float thickness, float ior, mat4 modelMatrix ) {\\\\n\\\\n\\\\t\\\\t// Direction of refracted light.\\\\n\\\\t\\\\tvec3 refractionVector = refract( - v, normalize( n ), 1.0 / ior );\\\\n\\\\n\\\\t\\\\t// Compute rotation-independant scaling of the model matrix.\\\\n\\\\t\\\\tvec3 modelScale;\\\\n\\\\t\\\\tmodelScale.x = length( vec3( modelMatrix[ 0 ].xyz ) );\\\\n\\\\t\\\\tmodelScale.y = length( vec3( modelMatrix[ 1 ].xyz ) );\\\\n\\\\t\\\\tmodelScale.z = length( vec3( modelMatrix[ 2 ].xyz ) );\\\\n\\\\n\\\\t\\\\t// The thickness is specified in local space.\\\\n\\\\t\\\\treturn normalize( refractionVector ) * thickness * modelScale;\\\\n\\\\n\\\\t}\\\\n\\\\n\\\\tfloat applyIorToRoughness( float roughness, float ior ) {\\\\n\\\\n\\\\t\\\\t// Scale roughness with IOR so that an IOR of 1.0 results in no microfacet refraction and\\\\n\\\\t\\\\t// an IOR of 1.5 results in the default amount of microfacet refraction.\\\\n\\\\t\\\\treturn roughness * clamp( ior * 2.0 - 2.0, 0.0, 1.0 );\\\\n\\\\n\\\\t}\\\\n\\\\n\\\\tvec4 getTransmissionSample( vec2 fragCoord, float roughness, float ior ) {\\\\n\\\\n\\\\t\\\\tfloat framebufferLod = log2( transmissionSamplerSize.x ) * applyIorToRoughness( roughness, ior );\\\\n\\\\n\\\\t\\\\t#ifdef TEXTURE_LOD_EXT\\\\n\\\\n\\\\t\\\\t\\\\treturn texture2DLodEXT( transmissionSamplerMap, fragCoord.xy, framebufferLod );\\\\n\\\\n\\\\t\\\\t#else\\\\n\\\\n\\\\t\\\\t\\\\treturn texture2D( transmissionSamplerMap, fragCoord.xy, framebufferLod );\\\\n\\\\n\\\\t\\\\t#endif\\\\n\\\\n\\\\t}\\\\n\\\\n\\\\tvec3 applyVolumeAttenuation( vec3 radiance, float transmissionDistance, vec3 attenuationColor, float attenuationDistance ) {\\\\n\\\\n\\\\t\\\\tif ( attenuationDistance == 0.0 ) {\\\\n\\\\n\\\\t\\\\t\\\\t// Attenuation distance is +∞ (which we indicate by zero), i.e. the transmitted color is not attenuated at all.\\\\n\\\\t\\\\t\\\\treturn radiance;\\\\n\\\\n\\\\t\\\\t} else {\\\\n\\\\n\\\\t\\\\t\\\\t// Compute light attenuation using Beer's law.\\\\n\\\\t\\\\t\\\\tvec3 attenuationCoefficient = -log( attenuationColor ) / attenuationDistance;\\\\n\\\\t\\\\t\\\\tvec3 transmittance = exp( - attenuationCoefficient * transmissionDistance ); // Beer's law\\\\n\\\\t\\\\t\\\\treturn transmittance * radiance;\\\\n\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\t}\\\\n\\\\n\\\\tvec4 getIBLVolumeRefraction( vec3 n, vec3 v, float roughness, vec3 diffuseColor, vec3 specularColor, float specularF90,\\\\n\\\\t\\\\tvec3 position, mat4 modelMatrix, mat4 viewMatrix, mat4 projMatrix, float ior, float thickness,\\\\n\\\\t\\\\tvec3 attenuationColor, float attenuationDistance ) {\\\\n\\\\n\\\\t\\\\tvec3 transmissionRay = getVolumeTransmissionRay( n, v, thickness, ior, modelMatrix );\\\\n\\\\t\\\\tvec3 refractedRayExit = position + transmissionRay;\\\\n\\\\n\\\\t\\\\t// Project refracted vector on the framebuffer, while mapping to normalized device coordinates.\\\\n\\\\t\\\\tvec4 ndcPos = projMatrix * viewMatrix * vec4( refractedRayExit, 1.0 );\\\\n\\\\t\\\\tvec2 refractionCoords = ndcPos.xy / ndcPos.w;\\\\n\\\\t\\\\trefractionCoords += 1.0;\\\\n\\\\t\\\\trefractionCoords /= 2.0;\\\\n\\\\n\\\\t\\\\t// Sample framebuffer to get pixel the refracted ray hits.\\\\n\\\\t\\\\tvec4 transmittedLight = getTransmissionSample( refractionCoords, roughness, ior );\\\\n\\\\n\\\\t\\\\tvec3 attenuatedColor = applyVolumeAttenuation( transmittedLight.rgb, length( transmissionRay ), attenuationColor, attenuationDistance );\\\\n\\\\n\\\\t\\\\t// Get the specular component.\\\\n\\\\t\\\\tvec3 F = EnvironmentBRDF( n, v, specularColor, specularF90, roughness );\\\\n\\\\n\\\\t\\\\treturn vec4( ( 1.0 - F ) * attenuatedColor * diffuseColor, transmittedLight.a );\\\\n\\\\n\\\\t}\\\\n#endif\\\\n\\\\\\\",uv_pars_fragment:\\\\\\\"\\\\n#if ( defined( USE_UV ) && ! defined( UVS_VERTEX_ONLY ) )\\\\n\\\\n\\\\tvarying vec2 vUv;\\\\n\\\\n#endif\\\\n\\\\\\\",uv_pars_vertex:\\\\\\\"\\\\n#ifdef USE_UV\\\\n\\\\n\\\\t#ifdef UVS_VERTEX_ONLY\\\\n\\\\n\\\\t\\\\tvec2 vUv;\\\\n\\\\n\\\\t#else\\\\n\\\\n\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\tuniform mat3 uvTransform;\\\\n\\\\n#endif\\\\n\\\\\\\",uv_vertex:\\\\\\\"\\\\n#ifdef USE_UV\\\\n\\\\n\\\\tvUv = ( uvTransform * vec3( uv, 1 ) ).xy;\\\\n\\\\n#endif\\\\n\\\\\\\",uv2_pars_fragment:\\\\\\\"\\\\n#if defined( USE_LIGHTMAP ) || defined( USE_AOMAP )\\\\n\\\\n\\\\tvarying vec2 vUv2;\\\\n\\\\n#endif\\\\n\\\\\\\",uv2_pars_vertex:\\\\\\\"\\\\n#if defined( USE_LIGHTMAP ) || defined( USE_AOMAP )\\\\n\\\\n\\\\tattribute vec2 uv2;\\\\n\\\\tvarying vec2 vUv2;\\\\n\\\\n\\\\tuniform mat3 uv2Transform;\\\\n\\\\n#endif\\\\n\\\\\\\",uv2_vertex:\\\\\\\"\\\\n#if defined( USE_LIGHTMAP ) || defined( USE_AOMAP )\\\\n\\\\n\\\\tvUv2 = ( uv2Transform * vec3( uv2, 1 ) ).xy;\\\\n\\\\n#endif\\\\n\\\\\\\",worldpos_vertex:\\\\\\\"\\\\n#if defined( USE_ENVMAP ) || defined( DISTANCE ) || defined ( USE_SHADOWMAP ) || defined ( USE_TRANSMISSION )\\\\n\\\\n\\\\tvec4 worldPosition = vec4( transformed, 1.0 );\\\\n\\\\n\\\\t#ifdef USE_INSTANCING\\\\n\\\\n\\\\t\\\\tworldPosition = instanceMatrix * worldPosition;\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\tworldPosition = modelMatrix * worldPosition;\\\\n\\\\n#endif\\\\n\\\\\\\",background_vert:\\\\\\\"\\\\nvarying vec2 vUv;\\\\nuniform mat3 uvTransform;\\\\n\\\\nvoid main() {\\\\n\\\\n\\\\tvUv = ( uvTransform * vec3( uv, 1 ) ).xy;\\\\n\\\\n\\\\tgl_Position = vec4( position.xy, 1.0, 1.0 );\\\\n\\\\n}\\\\n\\\\\\\",background_frag:\\\\\\\"\\\\nuniform sampler2D t2D;\\\\n\\\\nvarying vec2 vUv;\\\\n\\\\nvoid main() {\\\\n\\\\n\\\\tvec4 texColor = texture2D( t2D, vUv );\\\\n\\\\n\\\\tgl_FragColor = mapTexelToLinear( texColor );\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n}\\\\n\\\\\\\",cube_vert:\\\\\\\"\\\\nvarying vec3 vWorldDirection;\\\\n\\\\n#include \\\\n\\\\nvoid main() {\\\\n\\\\n\\\\tvWorldDirection = transformDirection( position, modelMatrix );\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\tgl_Position.z = gl_Position.w; // set z to camera.far\\\\n\\\\n}\\\\n\\\\\\\",cube_frag:\\\\\\\"\\\\n#include \\\\nuniform float opacity;\\\\n\\\\nvarying vec3 vWorldDirection;\\\\n\\\\n#include \\\\n\\\\nvoid main() {\\\\n\\\\n\\\\tvec3 vReflect = vWorldDirection;\\\\n\\\\t#include \\\\n\\\\n\\\\tgl_FragColor = envColor;\\\\n\\\\tgl_FragColor.a *= opacity;\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n}\\\\n\\\\\\\",depth_vert:\\\\\\\"\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n\\\\n// This is used for computing an equivalent of gl_FragCoord.z that is as high precision as possible.\\\\n// Some platforms compute gl_FragCoord at a lower precision which makes the manually computed value better for\\\\n// depth-based postprocessing effects. Reproduced on iPad with A10 processor / iPadOS 13.3.1.\\\\nvarying vec2 vHighPrecisionZW;\\\\n\\\\nvoid main() {\\\\n\\\\n\\\\t#include \\\\n\\\\n\\\\t#include \\\\n\\\\n\\\\t#ifdef USE_DISPLACEMENTMAP\\\\n\\\\n\\\\t\\\\t#include \\\\n\\\\t\\\\t#include \\\\n\\\\t\\\\t#include \\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\tvHighPrecisionZW = gl_Position.zw;\\\\n\\\\n}\\\\n\\\\\\\",depth_frag:\\\\\\\"\\\\n#if DEPTH_PACKING == 3200\\\\n\\\\n\\\\tuniform float opacity;\\\\n\\\\n#endif\\\\n\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n\\\\nvarying vec2 vHighPrecisionZW;\\\\n\\\\nvoid main() {\\\\n\\\\n\\\\t#include \\\\n\\\\n\\\\tvec4 diffuseColor = vec4( 1.0 );\\\\n\\\\n\\\\t#if DEPTH_PACKING == 3200\\\\n\\\\n\\\\t\\\\tdiffuseColor.a = opacity;\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\t#include \\\\n\\\\n\\\\t// Higher precision equivalent of gl_FragCoord.z. This assumes depthRange has been left to its default values.\\\\n\\\\tfloat fragCoordZ = 0.5 * vHighPrecisionZW[0] / vHighPrecisionZW[1] + 0.5;\\\\n\\\\n\\\\t#if DEPTH_PACKING == 3200\\\\n\\\\n\\\\t\\\\tgl_FragColor = vec4( vec3( 1.0 - fragCoordZ ), opacity );\\\\n\\\\n\\\\t#elif DEPTH_PACKING == 3201\\\\n\\\\n\\\\t\\\\tgl_FragColor = packDepthToRGBA( fragCoordZ );\\\\n\\\\n\\\\t#endif\\\\n\\\\n}\\\\n\\\\\\\",distanceRGBA_vert:\\\\\\\"\\\\n#define DISTANCE\\\\n\\\\nvarying vec3 vWorldPosition;\\\\n\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n\\\\nvoid main() {\\\\n\\\\n\\\\t#include \\\\n\\\\n\\\\t#include \\\\n\\\\n\\\\t#ifdef USE_DISPLACEMENTMAP\\\\n\\\\n\\\\t\\\\t#include \\\\n\\\\t\\\\t#include \\\\n\\\\t\\\\t#include \\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\tvWorldPosition = worldPosition.xyz;\\\\n\\\\n}\\\\n\\\\\\\",distanceRGBA_frag:\\\\\\\"\\\\n#define DISTANCE\\\\n\\\\nuniform vec3 referencePosition;\\\\nuniform float nearDistance;\\\\nuniform float farDistance;\\\\nvarying vec3 vWorldPosition;\\\\n\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n\\\\nvoid main () {\\\\n\\\\n\\\\t#include \\\\n\\\\n\\\\tvec4 diffuseColor = vec4( 1.0 );\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\tfloat dist = length( vWorldPosition - referencePosition );\\\\n\\\\tdist = ( dist - nearDistance ) / ( farDistance - nearDistance );\\\\n\\\\tdist = saturate( dist ); // clamp to [ 0, 1 ]\\\\n\\\\n\\\\tgl_FragColor = packDepthToRGBA( dist );\\\\n\\\\n}\\\\n\\\\\\\",equirect_vert:\\\\\\\"\\\\nvarying vec3 vWorldDirection;\\\\n\\\\n#include \\\\n\\\\nvoid main() {\\\\n\\\\n\\\\tvWorldDirection = transformDirection( position, modelMatrix );\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n}\\\\n\\\\\\\",equirect_frag:\\\\\\\"\\\\nuniform sampler2D tEquirect;\\\\n\\\\nvarying vec3 vWorldDirection;\\\\n\\\\n#include \\\\n\\\\nvoid main() {\\\\n\\\\n\\\\tvec3 direction = normalize( vWorldDirection );\\\\n\\\\n\\\\tvec2 sampleUV = equirectUv( direction );\\\\n\\\\n\\\\tvec4 texColor = texture2D( tEquirect, sampleUV );\\\\n\\\\n\\\\tgl_FragColor = mapTexelToLinear( texColor );\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n}\\\\n\\\\\\\",linedashed_vert:\\\\\\\"\\\\nuniform float scale;\\\\nattribute float lineDistance;\\\\n\\\\nvarying float vLineDistance;\\\\n\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n\\\\nvoid main() {\\\\n\\\\n\\\\tvLineDistance = scale * lineDistance;\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n}\\\\n\\\\\\\",linedashed_frag:\\\\\\\"\\\\nuniform vec3 diffuse;\\\\nuniform float opacity;\\\\n\\\\nuniform float dashSize;\\\\nuniform float totalSize;\\\\n\\\\nvarying float vLineDistance;\\\\n\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n\\\\nvoid main() {\\\\n\\\\n\\\\t#include \\\\n\\\\n\\\\tif ( mod( vLineDistance, totalSize ) > dashSize ) {\\\\n\\\\n\\\\t\\\\tdiscard;\\\\n\\\\n\\\\t}\\\\n\\\\n\\\\tvec3 outgoingLight = vec3( 0.0 );\\\\n\\\\tvec4 diffuseColor = vec4( diffuse, opacity );\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\toutgoingLight = diffuseColor.rgb; // simple shader\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n}\\\\n\\\\\\\",meshbasic_vert:\\\\\\\"\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n\\\\nvoid main() {\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\t#if defined ( USE_ENVMAP ) || defined ( USE_SKINNING )\\\\n\\\\n\\\\t\\\\t#include \\\\n\\\\t\\\\t#include \\\\n\\\\t\\\\t#include \\\\n\\\\t\\\\t#include \\\\n\\\\t\\\\t#include \\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n}\\\\n\\\\\\\",meshbasic_frag:\\\\\\\"\\\\nuniform vec3 diffuse;\\\\nuniform float opacity;\\\\n\\\\n#ifndef FLAT_SHADED\\\\n\\\\n\\\\tvarying vec3 vNormal;\\\\n\\\\n#endif\\\\n\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n\\\\nvoid main() {\\\\n\\\\n\\\\t#include \\\\n\\\\n\\\\tvec4 diffuseColor = vec4( diffuse, opacity );\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\tReflectedLight reflectedLight = ReflectedLight( vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ) );\\\\n\\\\n\\\\t// accumulation (baked indirect lighting only)\\\\n\\\\t#ifdef USE_LIGHTMAP\\\\n\\\\n\\\\t\\\\tvec4 lightMapTexel= texture2D( lightMap, vUv2 );\\\\n\\\\t\\\\treflectedLight.indirectDiffuse += lightMapTexelToLinear( lightMapTexel ).rgb * lightMapIntensity;\\\\n\\\\n\\\\t#else\\\\n\\\\n\\\\t\\\\treflectedLight.indirectDiffuse += vec3( 1.0 );\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\t// modulation\\\\n\\\\t#include \\\\n\\\\n\\\\treflectedLight.indirectDiffuse *= diffuseColor.rgb;\\\\n\\\\n\\\\tvec3 outgoingLight = reflectedLight.indirectDiffuse;\\\\n\\\\n\\\\t#include \\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n}\\\\n\\\\\\\",meshlambert_vert:\\\\\\\"\\\\n#define LAMBERT\\\\n\\\\nvarying vec3 vLightFront;\\\\nvarying vec3 vIndirectFront;\\\\n\\\\n#ifdef DOUBLE_SIDED\\\\n\\\\tvarying vec3 vLightBack;\\\\n\\\\tvarying vec3 vIndirectBack;\\\\n#endif\\\\n\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n\\\\nvoid main() {\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n}\\\\n\\\\\\\",meshlambert_frag:\\\\\\\"\\\\nuniform vec3 diffuse;\\\\nuniform vec3 emissive;\\\\nuniform float opacity;\\\\n\\\\nvarying vec3 vLightFront;\\\\nvarying vec3 vIndirectFront;\\\\n\\\\n#ifdef DOUBLE_SIDED\\\\n\\\\tvarying vec3 vLightBack;\\\\n\\\\tvarying vec3 vIndirectBack;\\\\n#endif\\\\n\\\\n\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n\\\\nvoid main() {\\\\n\\\\n\\\\t#include \\\\n\\\\n\\\\tvec4 diffuseColor = vec4( diffuse, opacity );\\\\n\\\\tReflectedLight reflectedLight = ReflectedLight( vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ) );\\\\n\\\\tvec3 totalEmissiveRadiance = emissive;\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\t// accumulation\\\\n\\\\n\\\\t#ifdef DOUBLE_SIDED\\\\n\\\\n\\\\t\\\\treflectedLight.indirectDiffuse += ( gl_FrontFacing ) ? vIndirectFront : vIndirectBack;\\\\n\\\\n\\\\t#else\\\\n\\\\n\\\\t\\\\treflectedLight.indirectDiffuse += vIndirectFront;\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\t#include \\\\n\\\\n\\\\treflectedLight.indirectDiffuse *= BRDF_Lambert( diffuseColor.rgb );\\\\n\\\\n\\\\t#ifdef DOUBLE_SIDED\\\\n\\\\n\\\\t\\\\treflectedLight.directDiffuse = ( gl_FrontFacing ) ? vLightFront : vLightBack;\\\\n\\\\n\\\\t#else\\\\n\\\\n\\\\t\\\\treflectedLight.directDiffuse = vLightFront;\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\treflectedLight.directDiffuse *= BRDF_Lambert( diffuseColor.rgb ) * getShadowMask();\\\\n\\\\n\\\\t// modulation\\\\n\\\\n\\\\t#include \\\\n\\\\n\\\\tvec3 outgoingLight = reflectedLight.directDiffuse + reflectedLight.indirectDiffuse + totalEmissiveRadiance;\\\\n\\\\n\\\\t#include \\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n}\\\\n\\\\\\\",meshmatcap_vert:\\\\\\\"\\\\n#define MATCAP\\\\n\\\\nvarying vec3 vViewPosition;\\\\n\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n\\\\n#include \\\\n#include \\\\n\\\\nvoid main() {\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\tvViewPosition = - mvPosition.xyz;\\\\n\\\\n}\\\\n\\\\\\\",meshmatcap_frag:\\\\\\\"\\\\n#define MATCAP\\\\n\\\\nuniform vec3 diffuse;\\\\nuniform float opacity;\\\\nuniform sampler2D matcap;\\\\n\\\\nvarying vec3 vViewPosition;\\\\n\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n\\\\nvoid main() {\\\\n\\\\n\\\\t#include \\\\n\\\\n\\\\tvec4 diffuseColor = vec4( diffuse, opacity );\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\tvec3 viewDir = normalize( vViewPosition );\\\\n\\\\tvec3 x = normalize( vec3( viewDir.z, 0.0, - viewDir.x ) );\\\\n\\\\tvec3 y = cross( viewDir, x );\\\\n\\\\tvec2 uv = vec2( dot( x, normal ), dot( y, normal ) ) * 0.495 + 0.5; // 0.495 to remove artifacts caused by undersized matcap disks\\\\n\\\\n\\\\t#ifdef USE_MATCAP\\\\n\\\\n\\\\t\\\\tvec4 matcapColor = texture2D( matcap, uv );\\\\n\\\\t\\\\tmatcapColor = matcapTexelToLinear( matcapColor );\\\\n\\\\n\\\\t#else\\\\n\\\\n\\\\t\\\\tvec4 matcapColor = vec4( 1.0 );\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\tvec3 outgoingLight = diffuseColor.rgb * matcapColor.rgb;\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n}\\\\n\\\\\\\",meshnormal_vert:\\\\\\\"\\\\n#define NORMAL\\\\n\\\\n#if defined( FLAT_SHADED ) || defined( USE_BUMPMAP ) || defined( TANGENTSPACE_NORMALMAP )\\\\n\\\\n\\\\tvarying vec3 vViewPosition;\\\\n\\\\n#endif\\\\n\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n\\\\nvoid main() {\\\\n\\\\n\\\\t#include \\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n#if defined( FLAT_SHADED ) || defined( USE_BUMPMAP ) || defined( TANGENTSPACE_NORMALMAP )\\\\n\\\\n\\\\tvViewPosition = - mvPosition.xyz;\\\\n\\\\n#endif\\\\n\\\\n}\\\\n\\\\\\\",meshnormal_frag:\\\\\\\"\\\\n#define NORMAL\\\\n\\\\nuniform float opacity;\\\\n\\\\n#if defined( FLAT_SHADED ) || defined( USE_BUMPMAP ) || defined( TANGENTSPACE_NORMALMAP )\\\\n\\\\n\\\\tvarying vec3 vViewPosition;\\\\n\\\\n#endif\\\\n\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n\\\\nvoid main() {\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\tgl_FragColor = vec4( packNormalToRGB( normal ), opacity );\\\\n\\\\n}\\\\n\\\\\\\",meshphong_vert:\\\\\\\"\\\\n#define PHONG\\\\n\\\\nvarying vec3 vViewPosition;\\\\n\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n\\\\nvoid main() {\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\tvViewPosition = - mvPosition.xyz;\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n}\\\\n\\\\\\\",meshphong_frag:\\\\\\\"\\\\n#define PHONG\\\\n\\\\nuniform vec3 diffuse;\\\\nuniform vec3 emissive;\\\\nuniform vec3 specular;\\\\nuniform float shininess;\\\\nuniform float opacity;\\\\n\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n\\\\nvoid main() {\\\\n\\\\n\\\\t#include \\\\n\\\\n\\\\tvec4 diffuseColor = vec4( diffuse, opacity );\\\\n\\\\tReflectedLight reflectedLight = ReflectedLight( vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ) );\\\\n\\\\tvec3 totalEmissiveRadiance = emissive;\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\t// accumulation\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\t// modulation\\\\n\\\\t#include \\\\n\\\\n\\\\tvec3 outgoingLight = reflectedLight.directDiffuse + reflectedLight.indirectDiffuse + reflectedLight.directSpecular + reflectedLight.indirectSpecular + totalEmissiveRadiance;\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n}\\\\n\\\\\\\",meshphysical_vert:\\\\\\\"\\\\n#define STANDARD\\\\n\\\\nvarying vec3 vViewPosition;\\\\n\\\\n#ifdef USE_TRANSMISSION\\\\n\\\\n\\\\tvarying vec3 vWorldPosition;\\\\n\\\\n#endif\\\\n\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n\\\\nvoid main() {\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\tvViewPosition = - mvPosition.xyz;\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n#ifdef USE_TRANSMISSION\\\\n\\\\n\\\\tvWorldPosition = worldPosition.xyz;\\\\n\\\\n#endif\\\\n}\\\\n\\\\\\\",meshphysical_frag:\\\\\\\"\\\\n#define STANDARD\\\\n\\\\n#ifdef PHYSICAL\\\\n\\\\t#define IOR\\\\n\\\\t#define SPECULAR\\\\n#endif\\\\n\\\\nuniform vec3 diffuse;\\\\nuniform vec3 emissive;\\\\nuniform float roughness;\\\\nuniform float metalness;\\\\nuniform float opacity;\\\\n\\\\n#ifdef IOR\\\\n\\\\tuniform float ior;\\\\n#endif\\\\n\\\\n#ifdef SPECULAR\\\\n\\\\tuniform float specularIntensity;\\\\n\\\\tuniform vec3 specularTint;\\\\n\\\\n\\\\t#ifdef USE_SPECULARINTENSITYMAP\\\\n\\\\t\\\\tuniform sampler2D specularIntensityMap;\\\\n\\\\t#endif\\\\n\\\\n\\\\t#ifdef USE_SPECULARTINTMAP\\\\n\\\\t\\\\tuniform sampler2D specularTintMap;\\\\n\\\\t#endif\\\\n#endif\\\\n\\\\n#ifdef USE_CLEARCOAT\\\\n\\\\tuniform float clearcoat;\\\\n\\\\tuniform float clearcoatRoughness;\\\\n#endif\\\\n\\\\n#ifdef USE_SHEEN\\\\n\\\\tuniform vec3 sheenTint;\\\\n\\\\tuniform float sheenRoughness;\\\\n#endif\\\\n\\\\nvarying vec3 vViewPosition;\\\\n\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n\\\\nvoid main() {\\\\n\\\\n\\\\t#include \\\\n\\\\n\\\\tvec4 diffuseColor = vec4( diffuse, opacity );\\\\n\\\\tReflectedLight reflectedLight = ReflectedLight( vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ) );\\\\n\\\\tvec3 totalEmissiveRadiance = emissive;\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\t// accumulation\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\t// modulation\\\\n\\\\t#include \\\\n\\\\n\\\\tvec3 totalDiffuse = reflectedLight.directDiffuse + reflectedLight.indirectDiffuse;\\\\n\\\\tvec3 totalSpecular = reflectedLight.directSpecular + reflectedLight.indirectSpecular;\\\\n\\\\n\\\\t#include \\\\n\\\\n\\\\tvec3 outgoingLight = totalDiffuse + totalSpecular + totalEmissiveRadiance;\\\\n\\\\n\\\\t#ifdef USE_CLEARCOAT\\\\n\\\\n\\\\t\\\\tfloat dotNVcc = saturate( dot( geometry.clearcoatNormal, geometry.viewDir ) );\\\\n\\\\n\\\\t\\\\tvec3 Fcc = F_Schlick( material.clearcoatF0, material.clearcoatF90, dotNVcc );\\\\n\\\\n\\\\t\\\\toutgoingLight = outgoingLight * ( 1.0 - clearcoat * Fcc ) + clearcoatSpecular * clearcoat;\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n}\\\\n\\\\\\\",meshtoon_vert:\\\\\\\"\\\\n#define TOON\\\\n\\\\nvarying vec3 vViewPosition;\\\\n\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n\\\\nvoid main() {\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\tvViewPosition = - mvPosition.xyz;\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n}\\\\n\\\\\\\",meshtoon_frag:\\\\\\\"\\\\n#define TOON\\\\n\\\\nuniform vec3 diffuse;\\\\nuniform vec3 emissive;\\\\nuniform float opacity;\\\\n\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n\\\\nvoid main() {\\\\n\\\\n\\\\t#include \\\\n\\\\n\\\\tvec4 diffuseColor = vec4( diffuse, opacity );\\\\n\\\\tReflectedLight reflectedLight = ReflectedLight( vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ) );\\\\n\\\\tvec3 totalEmissiveRadiance = emissive;\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\t// accumulation\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\t// modulation\\\\n\\\\t#include \\\\n\\\\n\\\\tvec3 outgoingLight = reflectedLight.directDiffuse + reflectedLight.indirectDiffuse + totalEmissiveRadiance;\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n}\\\\n\\\\\\\",points_vert:\\\\\\\"\\\\nuniform float size;\\\\nuniform float scale;\\\\n\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n\\\\nvoid main() {\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\tgl_PointSize = size;\\\\n\\\\n\\\\t#ifdef USE_SIZEATTENUATION\\\\n\\\\n\\\\t\\\\tbool isPerspective = isPerspectiveMatrix( projectionMatrix );\\\\n\\\\n\\\\t\\\\tif ( isPerspective ) gl_PointSize *= ( scale / - mvPosition.z );\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n}\\\\n\\\\\\\",points_frag:\\\\\\\"\\\\nuniform vec3 diffuse;\\\\nuniform float opacity;\\\\n\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n\\\\nvoid main() {\\\\n\\\\n\\\\t#include \\\\n\\\\n\\\\tvec3 outgoingLight = vec3( 0.0 );\\\\n\\\\tvec4 diffuseColor = vec4( diffuse, opacity );\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\toutgoingLight = diffuseColor.rgb;\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n}\\\\n\\\\\\\",shadow_vert:\\\\\\\"\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n\\\\nvoid main() {\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n}\\\\n\\\\\\\",shadow_frag:\\\\\\\"\\\\nuniform vec3 color;\\\\nuniform float opacity;\\\\n\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n\\\\nvoid main() {\\\\n\\\\n\\\\tgl_FragColor = vec4( color, opacity * ( 1.0 - getShadowMask() ) );\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n}\\\\n\\\\\\\",sprite_vert:\\\\\\\"\\\\nuniform float rotation;\\\\nuniform vec2 center;\\\\n\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n\\\\nvoid main() {\\\\n\\\\n\\\\t#include \\\\n\\\\n\\\\tvec4 mvPosition = modelViewMatrix * vec4( 0.0, 0.0, 0.0, 1.0 );\\\\n\\\\n\\\\tvec2 scale;\\\\n\\\\tscale.x = length( vec3( modelMatrix[ 0 ].x, modelMatrix[ 0 ].y, modelMatrix[ 0 ].z ) );\\\\n\\\\tscale.y = length( vec3( modelMatrix[ 1 ].x, modelMatrix[ 1 ].y, modelMatrix[ 1 ].z ) );\\\\n\\\\n\\\\t#ifndef USE_SIZEATTENUATION\\\\n\\\\n\\\\t\\\\tbool isPerspective = isPerspectiveMatrix( projectionMatrix );\\\\n\\\\n\\\\t\\\\tif ( isPerspective ) scale *= - mvPosition.z;\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\tvec2 alignedPosition = ( position.xy - ( center - vec2( 0.5 ) ) ) * scale;\\\\n\\\\n\\\\tvec2 rotatedPosition;\\\\n\\\\trotatedPosition.x = cos( rotation ) * alignedPosition.x - sin( rotation ) * alignedPosition.y;\\\\n\\\\trotatedPosition.y = sin( rotation ) * alignedPosition.x + cos( rotation ) * alignedPosition.y;\\\\n\\\\n\\\\tmvPosition.xy += rotatedPosition;\\\\n\\\\n\\\\tgl_Position = projectionMatrix * mvPosition;\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n}\\\\n\\\\\\\",sprite_frag:\\\\\\\"\\\\nuniform vec3 diffuse;\\\\nuniform float opacity;\\\\n\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n\\\\nvoid main() {\\\\n\\\\n\\\\t#include \\\\n\\\\n\\\\tvec3 outgoingLight = vec3( 0.0 );\\\\n\\\\tvec4 diffuseColor = vec4( diffuse, opacity );\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\toutgoingLight = diffuseColor.rgb;\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n}\\\\n\\\\\\\"};var G=n(11);const V={common:{diffuse:{value:new D.a(16777215)},opacity:{value:1},map:{value:null},uvTransform:{value:new G.a},uv2Transform:{value:new G.a},alphaMap:{value:null},alphaTest:{value:0}},specularmap:{specularMap:{value:null}},envmap:{envMap:{value:null},flipEnvMap:{value:-1},reflectivity:{value:1},ior:{value:1.5},refractionRatio:{value:.98},maxMipLevel:{value:0}},aomap:{aoMap:{value:null},aoMapIntensity:{value:1}},lightmap:{lightMap:{value:null},lightMapIntensity:{value:1}},emissivemap:{emissiveMap:{value:null}},bumpmap:{bumpMap:{value:null},bumpScale:{value:1}},normalmap:{normalMap:{value:null},normalScale:{value:new d.a(1,1)}},displacementmap:{displacementMap:{value:null},displacementScale:{value:1},displacementBias:{value:0}},roughnessmap:{roughnessMap:{value:null}},metalnessmap:{metalnessMap:{value:null}},gradientmap:{gradientMap:{value:null}},fog:{fogDensity:{value:25e-5},fogNear:{value:1},fogFar:{value:2e3},fogColor:{value:new D.a(16777215)}},lights:{ambientLightColor:{value:[]},lightProbe:{value:[]},directionalLights:{value:[],properties:{direction:{},color:{}}},directionalLightShadows:{value:[],properties:{shadowBias:{},shadowNormalBias:{},shadowRadius:{},shadowMapSize:{}}},directionalShadowMap:{value:[]},directionalShadowMatrix:{value:[]},spotLights:{value:[],properties:{color:{},position:{},direction:{},distance:{},coneCos:{},penumbraCos:{},decay:{}}},spotLightShadows:{value:[],properties:{shadowBias:{},shadowNormalBias:{},shadowRadius:{},shadowMapSize:{}}},spotShadowMap:{value:[]},spotShadowMatrix:{value:[]},pointLights:{value:[],properties:{color:{},position:{},decay:{},distance:{}}},pointLightShadows:{value:[],properties:{shadowBias:{},shadowNormalBias:{},shadowRadius:{},shadowMapSize:{},shadowCameraNear:{},shadowCameraFar:{}}},pointShadowMap:{value:[]},pointShadowMatrix:{value:[]},hemisphereLights:{value:[],properties:{direction:{},skyColor:{},groundColor:{}}},rectAreaLights:{value:[],properties:{color:{},position:{},width:{},height:{}}},ltc_1:{value:null},ltc_2:{value:null}},points:{diffuse:{value:new 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Tt{constructor(t){this._renderer=t,this._pingPongRenderTarget=null,this._blurMaterial=function(t){const e=new Float32Array(t),n=new p.a(0,1,0);return new at({name:\\\\\\\"SphericalGaussianBlur\\\\\\\",defines:{n:t},uniforms:{envMap:{value:null},samples:{value:1},weights:{value:e},latitudinal:{value:!1},dTheta:{value:0},mipInt:{value:0},poleAxis:{value:n},inputEncoding:{value:pt[w.U]},outputEncoding:{value:pt[w.U]}},vertexShader:Lt(),fragmentShader:`\\\\n\\\\n\\\\t\\\\t\\\\tprecision mediump float;\\\\n\\\\t\\\\t\\\\tprecision mediump int;\\\\n\\\\n\\\\t\\\\t\\\\tvarying vec3 vOutputDirection;\\\\n\\\\n\\\\t\\\\t\\\\tuniform sampler2D envMap;\\\\n\\\\t\\\\t\\\\tuniform int samples;\\\\n\\\\t\\\\t\\\\tuniform float weights[ n ];\\\\n\\\\t\\\\t\\\\tuniform bool latitudinal;\\\\n\\\\t\\\\t\\\\tuniform float dTheta;\\\\n\\\\t\\\\t\\\\tuniform float mipInt;\\\\n\\\\t\\\\t\\\\tuniform vec3 poleAxis;\\\\n\\\\n\\\\t\\\\t\\\\t${Ot()}\\\\n\\\\n\\\\t\\\\t\\\\t#define 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s=this._allocateTargets();return this._sceneToCubeUV(t,n,i,s),e>0&&this._blur(s,0,0,e),this._applyPMREM(s),this._cleanup(s),s}fromEquirectangular(t){return this._fromTexture(t)}fromCubemap(t){return this._fromTexture(t)}compileCubemapShader(){null===this._cubemapShader&&(this._cubemapShader=Nt(),this._compileMaterial(this._cubemapShader))}compileEquirectangularShader(){null===this._equirectShader&&(this._equirectShader=Ct(),this._compileMaterial(this._equirectShader))}dispose(){this._blurMaterial.dispose(),null!==this._cubemapShader&&this._cubemapShader.dispose(),null!==this._equirectShader&&this._equirectShader.dispose();for(let t=0;t2?ct:0,ct,ct),a.setRenderTarget(i),p&&a.render(d,s),a.render(t,s)}d.geometry.dispose(),d.material.dispose(),a.toneMapping=h,a.outputEncoding=c,a.autoClear=l,t.background=_}_setEncoding(t,e){!0===this._renderer.capabilities.isWebGL2&&e.format===w.Ib&&e.type===w.Zc&&e.encoding===w.ld?t.value=pt[w.U]:t.value=pt[e.encoding]}_textureToCubeUV(t,e){const n=this._renderer;t.isCubeTexture?null==this._cubemapShader&&(this._cubemapShader=Nt()):null==this._equirectShader&&(this._equirectShader=Ct());const i=t.isCubeTexture?this._cubemapShader:this._equirectShader,s=new B.a(mt[0],i),r=i.uniforms;r.envMap.value=t,t.isCubeTexture||r.texelSize.value.set(1/t.image.width,1/t.image.height),this._setEncoding(r.inputEncoding,t),this._setEncoding(r.outputEncoding,e.texture),St(e,0,0,3*ct,2*ct),n.setRenderTarget(e),n.render(s,_t)}_applyPMREM(t){const e=this._renderer,n=e.autoClear;e.autoClear=!1;for(let e=1;edt&&console.warn(`sigmaRadians, ${s}, is too large and will clip, as it requested ${_} samples when the maximum is set to 20`);const m=[];let f=0;for(let t=0;t4?i-8+4:0),3*g,2*g),a.setRenderTarget(e),a.render(c,_t)}}function At(t){return void 0!==t&&t.type===w.Zc&&(t.encoding===w.U||t.encoding===w.ld||t.encoding===w.J)}function Mt(){const t=[],e=[],n=[];let i=8;for(let s=0;s4?o=ht[s-8+4-1]:0==s&&(o=0),n.push(o);const a=1/(r-1),l=-a/2,c=1+a/2,h=[l,l,c,l,c,c,l,l,c,c,l,c],u=6,d=6,p=3,_=2,m=1,f=new Float32Array(p*d*u),g=new Float32Array(_*d*u),v=new Float32Array(m*d*u);for(let t=0;t2?0:-1,i=[e,n,0,e+2/3,n,0,e+2/3,n+1,0,e,n,0,e+2/3,n+1,0,e,n+1,0];f.set(i,p*d*t),g.set(h,_*d*t);const s=[t,t,t,t,t,t];v.set(s,m*d*t)}const y=new S.a;y.setAttribute(\\\\\\\"position\\\\\\\",new C.a(f,p)),y.setAttribute(\\\\\\\"uv\\\\\\\",new C.a(g,_)),y.setAttribute(\\\\\\\"faceIndex\\\\\\\",new C.a(v,m)),t.push(y),i>4&&i--}return{_lodPlanes:t,_sizeLods:e,_sigmas:n}}function Et(t){const e=new K(3*ct,3*ct,t);return e.texture.mapping=w.q,e.texture.name=\\\\\\\"PMREM.cubeUv\\\\\\\",e.scissorTest=!0,e}function St(t,e,n,i,s){t.viewport.set(e,n,i,s),t.scissor.set(e,n,i,s)}function Ct(){const t=new d.a(1,1);return new at({name:\\\\\\\"EquirectangularToCubeUV\\\\\\\",uniforms:{envMap:{value:null},texelSize:{value:t},inputEncoding:{value:pt[w.U]},outputEncoding:{value:pt[w.U]}},vertexShader:Lt(),fragmentShader:`\\\\n\\\\n\\\\t\\\\t\\\\tprecision mediump float;\\\\n\\\\t\\\\t\\\\tprecision mediump int;\\\\n\\\\n\\\\t\\\\t\\\\tvarying vec3 vOutputDirection;\\\\n\\\\n\\\\t\\\\t\\\\tuniform sampler2D envMap;\\\\n\\\\t\\\\t\\\\tuniform vec2 texelSize;\\\\n\\\\n\\\\t\\\\t\\\\t${Ot()}\\\\n\\\\n\\\\t\\\\t\\\\t#include \\\\n\\\\n\\\\t\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tgl_FragColor = vec4( 0.0, 0.0, 0.0, 1.0 );\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tvec3 outputDirection = normalize( vOutputDirection );\\\\n\\\\t\\\\t\\\\t\\\\tvec2 uv = equirectUv( outputDirection );\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tvec2 f = fract( uv / texelSize - 0.5 );\\\\n\\\\t\\\\t\\\\t\\\\tuv -= f * texelSize;\\\\n\\\\t\\\\t\\\\t\\\\tvec3 tl = envMapTexelToLinear( texture2D ( envMap, uv ) ).rgb;\\\\n\\\\t\\\\t\\\\t\\\\tuv.x += texelSize.x;\\\\n\\\\t\\\\t\\\\t\\\\tvec3 tr = envMapTexelToLinear( texture2D ( envMap, uv ) ).rgb;\\\\n\\\\t\\\\t\\\\t\\\\tuv.y += texelSize.y;\\\\n\\\\t\\\\t\\\\t\\\\tvec3 br = envMapTexelToLinear( texture2D ( envMap, uv ) ).rgb;\\\\n\\\\t\\\\t\\\\t\\\\tuv.x -= texelSize.x;\\\\n\\\\t\\\\t\\\\t\\\\tvec3 bl = envMapTexelToLinear( texture2D ( envMap, uv ) ).rgb;\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tvec3 tm = mix( tl, tr, f.x );\\\\n\\\\t\\\\t\\\\t\\\\tvec3 bm = mix( bl, br, f.x );\\\\n\\\\t\\\\t\\\\t\\\\tgl_FragColor.rgb = mix( tm, bm, f.y );\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tgl_FragColor = linearToOutputTexel( gl_FragColor );\\\\n\\\\n\\\\t\\\\t\\\\t}\\\\n\\\\t\\\\t`,blending:w.ub,depthTest:!1,depthWrite:!1})}function Nt(){return new at({name:\\\\\\\"CubemapToCubeUV\\\\\\\",uniforms:{envMap:{value:null},inputEncoding:{value:pt[w.U]},outputEncoding:{value:pt[w.U]}},vertexShader:Lt(),fragmentShader:`\\\\n\\\\n\\\\t\\\\t\\\\tprecision mediump float;\\\\n\\\\t\\\\t\\\\tprecision mediump int;\\\\n\\\\n\\\\t\\\\t\\\\tvarying vec3 vOutputDirection;\\\\n\\\\n\\\\t\\\\t\\\\tuniform samplerCube envMap;\\\\n\\\\n\\\\t\\\\t\\\\t${Ot()}\\\\n\\\\n\\\\t\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tgl_FragColor = vec4( 0.0, 0.0, 0.0, 1.0 );\\\\n\\\\t\\\\t\\\\t\\\\tgl_FragColor.rgb = envMapTexelToLinear( textureCube( envMap, vec3( - vOutputDirection.x, vOutputDirection.yz ) ) ).rgb;\\\\n\\\\t\\\\t\\\\t\\\\tgl_FragColor = linearToOutputTexel( gl_FragColor );\\\\n\\\\n\\\\t\\\\t\\\\t}\\\\n\\\\t\\\\t`,blending:w.ub,depthTest:!1,depthWrite:!1})}function Lt(){return\\\\\\\"\\\\n\\\\n\\\\t\\\\tprecision mediump float;\\\\n\\\\t\\\\tprecision mediump int;\\\\n\\\\n\\\\t\\\\tattribute vec3 position;\\\\n\\\\t\\\\tattribute vec2 uv;\\\\n\\\\t\\\\tattribute float faceIndex;\\\\n\\\\n\\\\t\\\\tvarying vec3 vOutputDirection;\\\\n\\\\n\\\\t\\\\t// RH coordinate system; PMREM face-indexing convention\\\\n\\\\t\\\\tvec3 getDirection( vec2 uv, float face ) {\\\\n\\\\n\\\\t\\\\t\\\\tuv = 2.0 * uv - 1.0;\\\\n\\\\n\\\\t\\\\t\\\\tvec3 direction = vec3( uv, 1.0 );\\\\n\\\\n\\\\t\\\\t\\\\tif ( face == 0.0 ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tdirection = direction.zyx; // ( 1, v, u ) pos x\\\\n\\\\n\\\\t\\\\t\\\\t} else if ( face == 1.0 ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tdirection = direction.xzy;\\\\n\\\\t\\\\t\\\\t\\\\tdirection.xz *= -1.0; // ( -u, 1, -v ) pos y\\\\n\\\\n\\\\t\\\\t\\\\t} else if ( face == 2.0 ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tdirection.x *= -1.0; // ( -u, v, 1 ) pos z\\\\n\\\\n\\\\t\\\\t\\\\t} else if ( face == 3.0 ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tdirection = direction.zyx;\\\\n\\\\t\\\\t\\\\t\\\\tdirection.xz *= -1.0; // ( -1, v, -u ) neg x\\\\n\\\\n\\\\t\\\\t\\\\t} else if ( face == 4.0 ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tdirection = direction.xzy;\\\\n\\\\t\\\\t\\\\t\\\\tdirection.xy *= -1.0; // ( -u, -1, v ) neg y\\\\n\\\\n\\\\t\\\\t\\\\t} else if ( face == 5.0 ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tdirection.z *= -1.0; // ( u, v, -1 ) neg z\\\\n\\\\n\\\\t\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\t\\\\treturn direction;\\\\n\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\tvOutputDirection = getDirection( uv, faceIndex );\\\\n\\\\t\\\\t\\\\tgl_Position = vec4( position, 1.0 );\\\\n\\\\n\\\\t\\\\t}\\\\n\\\\t\\\\\\\"}function Ot(){return\\\\\\\"\\\\n\\\\n\\\\t\\\\tuniform int inputEncoding;\\\\n\\\\t\\\\tuniform int outputEncoding;\\\\n\\\\n\\\\t\\\\t#include \\\\n\\\\n\\\\t\\\\tvec4 inputTexelToLinear( vec4 value ) {\\\\n\\\\n\\\\t\\\\t\\\\tif ( inputEncoding == 0 ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\treturn value;\\\\n\\\\n\\\\t\\\\t\\\\t} else if ( inputEncoding == 1 ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\treturn sRGBToLinear( value );\\\\n\\\\n\\\\t\\\\t\\\\t} else if ( inputEncoding == 2 ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\treturn RGBEToLinear( value );\\\\n\\\\n\\\\t\\\\t\\\\t} else if ( inputEncoding == 3 ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\treturn RGBMToLinear( value, 7.0 );\\\\n\\\\n\\\\t\\\\t\\\\t} else if ( inputEncoding == 4 ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\treturn RGBMToLinear( value, 16.0 );\\\\n\\\\n\\\\t\\\\t\\\\t} else if ( inputEncoding == 5 ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\treturn RGBDToLinear( value, 256.0 );\\\\n\\\\n\\\\t\\\\t\\\\t} else {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\treturn GammaToLinear( value, 2.2 );\\\\n\\\\n\\\\t\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\tvec4 linearToOutputTexel( vec4 value ) {\\\\n\\\\n\\\\t\\\\t\\\\tif ( outputEncoding == 0 ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\treturn value;\\\\n\\\\n\\\\t\\\\t\\\\t} else if ( outputEncoding == 1 ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\treturn LinearTosRGB( value );\\\\n\\\\n\\\\t\\\\t\\\\t} else if ( outputEncoding == 2 ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\treturn LinearToRGBE( value );\\\\n\\\\n\\\\t\\\\t\\\\t} else if ( outputEncoding == 3 ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\treturn LinearToRGBM( value, 7.0 );\\\\n\\\\n\\\\t\\\\t\\\\t} else if ( outputEncoding == 4 ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\treturn LinearToRGBM( value, 16.0 );\\\\n\\\\n\\\\t\\\\t\\\\t} else if ( outputEncoding == 5 ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\treturn LinearToRGBD( value, 256.0 );\\\\n\\\\n\\\\t\\\\t\\\\t} else {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\treturn LinearToGamma( value, 2.2 );\\\\n\\\\n\\\\t\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\tvec4 envMapTexelToLinear( vec4 color ) {\\\\n\\\\n\\\\t\\\\t\\\\treturn inputTexelToLinear( color );\\\\n\\\\n\\\\t\\\\t}\\\\n\\\\t\\\\\\\"}function Pt(t){let e=new WeakMap,n=null;function i(t){const n=t.target;n.removeEventListener(\\\\\\\"dispose\\\\\\\",i);const s=e.get(n);void 0!==s&&(e.delete(n),s.dispose())}return{get:function(s){if(s&&s.isTexture&&!1===s.isRenderTargetTexture){const r=s.mapping,o=r===w.D||r===w.E,a=r===w.o||r===w.p;if(o||a){if(e.has(s))return e.get(s).texture;{const r=s.image;if(o&&r&&r.height>0||a&&r&&function(t){let e=0;const n=6;for(let i=0;i65535?C.i:C.h)(n,1);a.version=o;const l=r.get(t);l&&e.remove(l),r.set(t,a)}return{get:function(t,e){return!0===s[e.id]||(e.addEventListener(\\\\\\\"dispose\\\\\\\",o),s[e.id]=!0,n.memory.geometries++),e},update:function(n){const i=n.attributes;for(const n in i)e.update(i[n],t.ARRAY_BUFFER);const s=n.morphAttributes;for(const n in s){const i=s[n];for(let n=0,s=i.length;ne.maxTextureSize&&(u=Math.ceil(h/e.maxTextureSize),h=e.maxTextureSize);const p=new Float32Array(h*u*4*i),_=new zt(p,h,u,i);_.format=w.Ib,_.type=w.G;const m=4*l;for(let e=0;e0)return t;const s=e*n;let r=Jt[s];if(void 0===r&&(r=new Float32Array(s),Jt[s]=r),0!==e){i.toArray(r,0);for(let i=1,s=0;i!==e;++i)s+=n,t[i].toArray(r,s)}return r}function ne(t,e){if(t.length!==e.length)return!1;for(let n=0,i=t.length;n/gm;function on(t){return t.replace(rn,an)}function an(t,e){const n=U[e];if(void 0===n)throw new Error(\\\\\\\"Can not resolve #include <\\\\\\\"+e+\\\\\\\">\\\\\\\");return on(n)}const ln=/#pragma unroll_loop[\\\\s]+?for \\\\( int i \\\\= (\\\\d+)\\\\; i < (\\\\d+)\\\\; i \\\\+\\\\+ \\\\) \\\\{([\\\\s\\\\S]+?)(?=\\\\})\\\\}/g,cn=/#pragma unroll_loop_start\\\\s+for\\\\s*\\\\(\\\\s*int\\\\s+i\\\\s*=\\\\s*(\\\\d+)\\\\s*;\\\\s*i\\\\s*<\\\\s*(\\\\d+)\\\\s*;\\\\s*i\\\\s*\\\\+\\\\+\\\\s*\\\\)\\\\s*{([\\\\s\\\\S]+?)}\\\\s+#pragma unroll_loop_end/g;function hn(t){return t.replace(cn,dn).replace(ln,un)}function un(t,e,n,i){return console.warn(\\\\\\\"WebGLProgram: #pragma unroll_loop shader syntax is deprecated. Please use #pragma unroll_loop_start syntax instead.\\\\\\\"),dn(t,e,n,i)}function dn(t,e,n,i){let s=\\\\\\\"\\\\\\\";for(let t=parseInt(e);t0?t.gammaFactor:1,p=n.isWebGL2?\\\\\\\"\\\\\\\":function(t){return[t.extensionDerivatives||t.envMapCubeUV||t.bumpMap||t.tangentSpaceNormalMap||t.clearcoatNormalMap||t.flatShading||\\\\\\\"physical\\\\\\\"===t.shaderID?\\\\\\\"#extension GL_OES_standard_derivatives : enable\\\\\\\":\\\\\\\"\\\\\\\",(t.extensionFragDepth||t.logarithmicDepthBuffer)&&t.rendererExtensionFragDepth?\\\\\\\"#extension GL_EXT_frag_depth : enable\\\\\\\":\\\\\\\"\\\\\\\",t.extensionDrawBuffers&&t.rendererExtensionDrawBuffers?\\\\\\\"#extension GL_EXT_draw_buffers : require\\\\\\\":\\\\\\\"\\\\\\\",(t.extensionShaderTextureLOD||t.envMap||t.transmission)&&t.rendererExtensionShaderTextureLod?\\\\\\\"#extension GL_EXT_shader_texture_lod : enable\\\\\\\":\\\\\\\"\\\\\\\"].filter(en).join(\\\\\\\"\\\\n\\\\\\\")}(n),_=function(t){const e=[];for(const n in t){const i=t[n];!1!==i&&e.push(\\\\\\\"#define \\\\\\\"+n+\\\\\\\" \\\\\\\"+i)}return e.join(\\\\\\\"\\\\n\\\\\\\")}(r),m=s.createProgram();let f,g,v=n.glslVersion?\\\\\\\"#version \\\\\\\"+n.glslVersion+\\\\\\\"\\\\n\\\\\\\":\\\\\\\"\\\\\\\";n.isRawShaderMaterial?(f=[_].filter(en).join(\\\\\\\"\\\\n\\\\\\\"),f.length>0&&(f+=\\\\\\\"\\\\n\\\\\\\"),g=[p,_].filter(en).join(\\\\\\\"\\\\n\\\\\\\"),g.length>0&&(g+=\\\\\\\"\\\\n\\\\\\\")):(f=[pn(n),\\\\\\\"#define SHADER_NAME \\\\\\\"+n.shaderName,_,n.instancing?\\\\\\\"#define USE_INSTANCING\\\\\\\":\\\\\\\"\\\\\\\",n.instancingColor?\\\\\\\"#define USE_INSTANCING_COLOR\\\\\\\":\\\\\\\"\\\\\\\",n.supportsVertexTextures?\\\\\\\"#define VERTEX_TEXTURES\\\\\\\":\\\\\\\"\\\\\\\",\\\\\\\"#define GAMMA_FACTOR \\\\\\\"+d,\\\\\\\"#define MAX_BONES \\\\\\\"+n.maxBones,n.useFog&&n.fog?\\\\\\\"#define USE_FOG\\\\\\\":\\\\\\\"\\\\\\\",n.useFog&&n.fogExp2?\\\\\\\"#define FOG_EXP2\\\\\\\":\\\\\\\"\\\\\\\",n.map?\\\\\\\"#define USE_MAP\\\\\\\":\\\\\\\"\\\\\\\",n.envMap?\\\\\\\"#define USE_ENVMAP\\\\\\\":\\\\\\\"\\\\\\\",n.envMap?\\\\\\\"#define \\\\\\\"+h:\\\\\\\"\\\\\\\",n.lightMap?\\\\\\\"#define USE_LIGHTMAP\\\\\\\":\\\\\\\"\\\\\\\",n.aoMap?\\\\\\\"#define USE_AOMAP\\\\\\\":\\\\\\\"\\\\\\\",n.emissiveMap?\\\\\\\"#define USE_EMISSIVEMAP\\\\\\\":\\\\\\\"\\\\\\\",n.bumpMap?\\\\\\\"#define USE_BUMPMAP\\\\\\\":\\\\\\\"\\\\\\\",n.normalMap?\\\\\\\"#define USE_NORMALMAP\\\\\\\":\\\\\\\"\\\\\\\",n.normalMap&&n.objectSpaceNormalMap?\\\\\\\"#define OBJECTSPACE_NORMALMAP\\\\\\\":\\\\\\\"\\\\\\\",n.normalMap&&n.tangentSpaceNormalMap?\\\\\\\"#define TANGENTSPACE_NORMALMAP\\\\\\\":\\\\\\\"\\\\\\\",n.clearcoatMap?\\\\\\\"#define USE_CLEARCOATMAP\\\\\\\":\\\\\\\"\\\\\\\",n.clearcoatRoughnessMap?\\\\\\\"#define USE_CLEARCOAT_ROUGHNESSMAP\\\\\\\":\\\\\\\"\\\\\\\",n.clearcoatNormalMap?\\\\\\\"#define USE_CLEARCOAT_NORMALMAP\\\\\\\":\\\\\\\"\\\\\\\",n.displacementMap&&n.supportsVertexTextures?\\\\\\\"#define USE_DISPLACEMENTMAP\\\\\\\":\\\\\\\"\\\\\\\",n.specularMap?\\\\\\\"#define USE_SPECULARMAP\\\\\\\":\\\\\\\"\\\\\\\",n.specularIntensityMap?\\\\\\\"#define USE_SPECULARINTENSITYMAP\\\\\\\":\\\\\\\"\\\\\\\",n.specularTintMap?\\\\\\\"#define USE_SPECULARTINTMAP\\\\\\\":\\\\\\\"\\\\\\\",n.roughnessMap?\\\\\\\"#define USE_ROUGHNESSMAP\\\\\\\":\\\\\\\"\\\\\\\",n.metalnessMap?\\\\\\\"#define USE_METALNESSMAP\\\\\\\":\\\\\\\"\\\\\\\",n.alphaMap?\\\\\\\"#define USE_ALPHAMAP\\\\\\\":\\\\\\\"\\\\\\\",n.transmission?\\\\\\\"#define USE_TRANSMISSION\\\\\\\":\\\\\\\"\\\\\\\",n.transmissionMap?\\\\\\\"#define USE_TRANSMISSIONMAP\\\\\\\":\\\\\\\"\\\\\\\",n.thicknessMap?\\\\\\\"#define USE_THICKNESSMAP\\\\\\\":\\\\\\\"\\\\\\\",n.vertexTangents?\\\\\\\"#define USE_TANGENT\\\\\\\":\\\\\\\"\\\\\\\",n.vertexColors?\\\\\\\"#define USE_COLOR\\\\\\\":\\\\\\\"\\\\\\\",n.vertexAlphas?\\\\\\\"#define USE_COLOR_ALPHA\\\\\\\":\\\\\\\"\\\\\\\",n.vertexUvs?\\\\\\\"#define USE_UV\\\\\\\":\\\\\\\"\\\\\\\",n.uvsVertexOnly?\\\\\\\"#define UVS_VERTEX_ONLY\\\\\\\":\\\\\\\"\\\\\\\",n.flatShading?\\\\\\\"#define FLAT_SHADED\\\\\\\":\\\\\\\"\\\\\\\",n.skinning?\\\\\\\"#define USE_SKINNING\\\\\\\":\\\\\\\"\\\\\\\",n.useVertexTexture?\\\\\\\"#define BONE_TEXTURE\\\\\\\":\\\\\\\"\\\\\\\",n.morphTargets?\\\\\\\"#define USE_MORPHTARGETS\\\\\\\":\\\\\\\"\\\\\\\",n.morphNormals&&!1===n.flatShading?\\\\\\\"#define USE_MORPHNORMALS\\\\\\\":\\\\\\\"\\\\\\\",n.morphTargets&&n.isWebGL2?\\\\\\\"#define MORPHTARGETS_TEXTURE\\\\\\\":\\\\\\\"\\\\\\\",n.morphTargets&&n.isWebGL2?\\\\\\\"#define MORPHTARGETS_COUNT \\\\\\\"+n.morphTargetsCount:\\\\\\\"\\\\\\\",n.doubleSided?\\\\\\\"#define DOUBLE_SIDED\\\\\\\":\\\\\\\"\\\\\\\",n.flipSided?\\\\\\\"#define FLIP_SIDED\\\\\\\":\\\\\\\"\\\\\\\",n.shadowMapEnabled?\\\\\\\"#define USE_SHADOWMAP\\\\\\\":\\\\\\\"\\\\\\\",n.shadowMapEnabled?\\\\\\\"#define \\\\\\\"+l:\\\\\\\"\\\\\\\",n.sizeAttenuation?\\\\\\\"#define USE_SIZEATTENUATION\\\\\\\":\\\\\\\"\\\\\\\",n.logarithmicDepthBuffer?\\\\\\\"#define USE_LOGDEPTHBUF\\\\\\\":\\\\\\\"\\\\\\\",n.logarithmicDepthBuffer&&n.rendererExtensionFragDepth?\\\\\\\"#define USE_LOGDEPTHBUF_EXT\\\\\\\":\\\\\\\"\\\\\\\",\\\\\\\"uniform mat4 modelMatrix;\\\\\\\",\\\\\\\"uniform mat4 modelViewMatrix;\\\\\\\",\\\\\\\"uniform mat4 projectionMatrix;\\\\\\\",\\\\\\\"uniform mat4 viewMatrix;\\\\\\\",\\\\\\\"uniform mat3 normalMatrix;\\\\\\\",\\\\\\\"uniform vec3 cameraPosition;\\\\\\\",\\\\\\\"uniform bool isOrthographic;\\\\\\\",\\\\\\\"#ifdef USE_INSTANCING\\\\\\\",\\\\\\\"\\\\tattribute mat4 instanceMatrix;\\\\\\\",\\\\\\\"#endif\\\\\\\",\\\\\\\"#ifdef USE_INSTANCING_COLOR\\\\\\\",\\\\\\\"\\\\tattribute vec3 instanceColor;\\\\\\\",\\\\\\\"#endif\\\\\\\",\\\\\\\"attribute vec3 position;\\\\\\\",\\\\\\\"attribute vec3 normal;\\\\\\\",\\\\\\\"attribute vec2 uv;\\\\\\\",\\\\\\\"#ifdef USE_TANGENT\\\\\\\",\\\\\\\"\\\\tattribute vec4 tangent;\\\\\\\",\\\\\\\"#endif\\\\\\\",\\\\\\\"#if defined( USE_COLOR_ALPHA )\\\\\\\",\\\\\\\"\\\\tattribute vec4 color;\\\\\\\",\\\\\\\"#elif defined( USE_COLOR )\\\\\\\",\\\\\\\"\\\\tattribute vec3 color;\\\\\\\",\\\\\\\"#endif\\\\\\\",\\\\\\\"#if ( defined( USE_MORPHTARGETS ) && ! defined( MORPHTARGETS_TEXTURE ) )\\\\\\\",\\\\\\\"\\\\tattribute vec3 morphTarget0;\\\\\\\",\\\\\\\"\\\\tattribute vec3 morphTarget1;\\\\\\\",\\\\\\\"\\\\tattribute vec3 morphTarget2;\\\\\\\",\\\\\\\"\\\\tattribute vec3 morphTarget3;\\\\\\\",\\\\\\\"\\\\t#ifdef USE_MORPHNORMALS\\\\\\\",\\\\\\\"\\\\t\\\\tattribute vec3 morphNormal0;\\\\\\\",\\\\\\\"\\\\t\\\\tattribute vec3 morphNormal1;\\\\\\\",\\\\\\\"\\\\t\\\\tattribute vec3 morphNormal2;\\\\\\\",\\\\\\\"\\\\t\\\\tattribute vec3 morphNormal3;\\\\\\\",\\\\\\\"\\\\t#else\\\\\\\",\\\\\\\"\\\\t\\\\tattribute vec3 morphTarget4;\\\\\\\",\\\\\\\"\\\\t\\\\tattribute vec3 morphTarget5;\\\\\\\",\\\\\\\"\\\\t\\\\tattribute vec3 morphTarget6;\\\\\\\",\\\\\\\"\\\\t\\\\tattribute vec3 morphTarget7;\\\\\\\",\\\\\\\"\\\\t#endif\\\\\\\",\\\\\\\"#endif\\\\\\\",\\\\\\\"#ifdef USE_SKINNING\\\\\\\",\\\\\\\"\\\\tattribute vec4 skinIndex;\\\\\\\",\\\\\\\"\\\\tattribute vec4 skinWeight;\\\\\\\",\\\\\\\"#endif\\\\\\\",\\\\\\\"\\\\n\\\\\\\"].filter(en).join(\\\\\\\"\\\\n\\\\\\\"),g=[p,pn(n),\\\\\\\"#define SHADER_NAME \\\\\\\"+n.shaderName,_,\\\\\\\"#define GAMMA_FACTOR \\\\\\\"+d,n.useFog&&n.fog?\\\\\\\"#define USE_FOG\\\\\\\":\\\\\\\"\\\\\\\",n.useFog&&n.fogExp2?\\\\\\\"#define FOG_EXP2\\\\\\\":\\\\\\\"\\\\\\\",n.map?\\\\\\\"#define USE_MAP\\\\\\\":\\\\\\\"\\\\\\\",n.matcap?\\\\\\\"#define USE_MATCAP\\\\\\\":\\\\\\\"\\\\\\\",n.envMap?\\\\\\\"#define USE_ENVMAP\\\\\\\":\\\\\\\"\\\\\\\",n.envMap?\\\\\\\"#define \\\\\\\"+c:\\\\\\\"\\\\\\\",n.envMap?\\\\\\\"#define \\\\\\\"+h:\\\\\\\"\\\\\\\",n.envMap?\\\\\\\"#define \\\\\\\"+u:\\\\\\\"\\\\\\\",n.lightMap?\\\\\\\"#define USE_LIGHTMAP\\\\\\\":\\\\\\\"\\\\\\\",n.aoMap?\\\\\\\"#define USE_AOMAP\\\\\\\":\\\\\\\"\\\\\\\",n.emissiveMap?\\\\\\\"#define USE_EMISSIVEMAP\\\\\\\":\\\\\\\"\\\\\\\",n.bumpMap?\\\\\\\"#define USE_BUMPMAP\\\\\\\":\\\\\\\"\\\\\\\",n.normalMap?\\\\\\\"#define USE_NORMALMAP\\\\\\\":\\\\\\\"\\\\\\\",n.normalMap&&n.objectSpaceNormalMap?\\\\\\\"#define OBJECTSPACE_NORMALMAP\\\\\\\":\\\\\\\"\\\\\\\",n.normalMap&&n.tangentSpaceNormalMap?\\\\\\\"#define TANGENTSPACE_NORMALMAP\\\\\\\":\\\\\\\"\\\\\\\",n.clearcoat?\\\\\\\"#define USE_CLEARCOAT\\\\\\\":\\\\\\\"\\\\\\\",n.clearcoatMap?\\\\\\\"#define USE_CLEARCOATMAP\\\\\\\":\\\\\\\"\\\\\\\",n.clearcoatRoughnessMap?\\\\\\\"#define USE_CLEARCOAT_ROUGHNESSMAP\\\\\\\":\\\\\\\"\\\\\\\",n.clearcoatNormalMap?\\\\\\\"#define USE_CLEARCOAT_NORMALMAP\\\\\\\":\\\\\\\"\\\\\\\",n.specularMap?\\\\\\\"#define USE_SPECULARMAP\\\\\\\":\\\\\\\"\\\\\\\",n.specularIntensityMap?\\\\\\\"#define USE_SPECULARINTENSITYMAP\\\\\\\":\\\\\\\"\\\\\\\",n.specularTintMap?\\\\\\\"#define USE_SPECULARTINTMAP\\\\\\\":\\\\\\\"\\\\\\\",n.roughnessMap?\\\\\\\"#define USE_ROUGHNESSMAP\\\\\\\":\\\\\\\"\\\\\\\",n.metalnessMap?\\\\\\\"#define USE_METALNESSMAP\\\\\\\":\\\\\\\"\\\\\\\",n.alphaMap?\\\\\\\"#define USE_ALPHAMAP\\\\\\\":\\\\\\\"\\\\\\\",n.alphaTest?\\\\\\\"#define USE_ALPHATEST\\\\\\\":\\\\\\\"\\\\\\\",n.sheen?\\\\\\\"#define USE_SHEEN\\\\\\\":\\\\\\\"\\\\\\\",n.transmission?\\\\\\\"#define USE_TRANSMISSION\\\\\\\":\\\\\\\"\\\\\\\",n.transmissionMap?\\\\\\\"#define USE_TRANSMISSIONMAP\\\\\\\":\\\\\\\"\\\\\\\",n.thicknessMap?\\\\\\\"#define USE_THICKNESSMAP\\\\\\\":\\\\\\\"\\\\\\\",n.vertexTangents?\\\\\\\"#define USE_TANGENT\\\\\\\":\\\\\\\"\\\\\\\",n.vertexColors||n.instancingColor?\\\\\\\"#define USE_COLOR\\\\\\\":\\\\\\\"\\\\\\\",n.vertexAlphas?\\\\\\\"#define USE_COLOR_ALPHA\\\\\\\":\\\\\\\"\\\\\\\",n.vertexUvs?\\\\\\\"#define USE_UV\\\\\\\":\\\\\\\"\\\\\\\",n.uvsVertexOnly?\\\\\\\"#define UVS_VERTEX_ONLY\\\\\\\":\\\\\\\"\\\\\\\",n.gradientMap?\\\\\\\"#define USE_GRADIENTMAP\\\\\\\":\\\\\\\"\\\\\\\",n.flatShading?\\\\\\\"#define FLAT_SHADED\\\\\\\":\\\\\\\"\\\\\\\",n.doubleSided?\\\\\\\"#define DOUBLE_SIDED\\\\\\\":\\\\\\\"\\\\\\\",n.flipSided?\\\\\\\"#define FLIP_SIDED\\\\\\\":\\\\\\\"\\\\\\\",n.shadowMapEnabled?\\\\\\\"#define USE_SHADOWMAP\\\\\\\":\\\\\\\"\\\\\\\",n.shadowMapEnabled?\\\\\\\"#define \\\\\\\"+l:\\\\\\\"\\\\\\\",n.premultipliedAlpha?\\\\\\\"#define PREMULTIPLIED_ALPHA\\\\\\\":\\\\\\\"\\\\\\\",n.physicallyCorrectLights?\\\\\\\"#define PHYSICALLY_CORRECT_LIGHTS\\\\\\\":\\\\\\\"\\\\\\\",n.logarithmicDepthBuffer?\\\\\\\"#define USE_LOGDEPTHBUF\\\\\\\":\\\\\\\"\\\\\\\",n.logarithmicDepthBuffer&&n.rendererExtensionFragDepth?\\\\\\\"#define USE_LOGDEPTHBUF_EXT\\\\\\\":\\\\\\\"\\\\\\\",(n.extensionShaderTextureLOD||n.envMap)&&n.rendererExtensionShaderTextureLod?\\\\\\\"#define TEXTURE_LOD_EXT\\\\\\\":\\\\\\\"\\\\\\\",\\\\\\\"uniform mat4 viewMatrix;\\\\\\\",\\\\\\\"uniform vec3 cameraPosition;\\\\\\\",\\\\\\\"uniform bool isOrthographic;\\\\\\\",n.toneMapping!==w.vb?\\\\\\\"#define TONE_MAPPING\\\\\\\":\\\\\\\"\\\\\\\",n.toneMapping!==w.vb?U.tonemapping_pars_fragment:\\\\\\\"\\\\\\\",n.toneMapping!==w.vb?tn(\\\\\\\"toneMapping\\\\\\\",n.toneMapping):\\\\\\\"\\\\\\\",n.dithering?\\\\\\\"#define DITHERING\\\\\\\":\\\\\\\"\\\\\\\",n.format===w.ic?\\\\\\\"#define OPAQUE\\\\\\\":\\\\\\\"\\\\\\\",U.encodings_pars_fragment,n.map?Ke(\\\\\\\"mapTexelToLinear\\\\\\\",n.mapEncoding):\\\\\\\"\\\\\\\",n.matcap?Ke(\\\\\\\"matcapTexelToLinear\\\\\\\",n.matcapEncoding):\\\\\\\"\\\\\\\",n.envMap?Ke(\\\\\\\"envMapTexelToLinear\\\\\\\",n.envMapEncoding):\\\\\\\"\\\\\\\",n.emissiveMap?Ke(\\\\\\\"emissiveMapTexelToLinear\\\\\\\",n.emissiveMapEncoding):\\\\\\\"\\\\\\\",n.specularTintMap?Ke(\\\\\\\"specularTintMapTexelToLinear\\\\\\\",n.specularTintMapEncoding):\\\\\\\"\\\\\\\",n.lightMap?Ke(\\\\\\\"lightMapTexelToLinear\\\\\\\",n.lightMapEncoding):\\\\\\\"\\\\\\\",Qe(\\\\\\\"linearToOutputTexel\\\\\\\",n.outputEncoding),n.depthPacking?\\\\\\\"#define DEPTH_PACKING \\\\\\\"+n.depthPacking:\\\\\\\"\\\\\\\",\\\\\\\"\\\\n\\\\\\\"].filter(en).join(\\\\\\\"\\\\n\\\\\\\")),o=on(o),o=nn(o,n),o=sn(o,n),a=on(a),a=nn(a,n),a=sn(a,n),o=hn(o),a=hn(a),n.isWebGL2&&!0!==n.isRawShaderMaterial&&(v=\\\\\\\"#version 300 es\\\\n\\\\\\\",f=[\\\\\\\"precision mediump sampler2DArray;\\\\\\\",\\\\\\\"#define attribute in\\\\\\\",\\\\\\\"#define varying out\\\\\\\",\\\\\\\"#define texture2D texture\\\\\\\"].join(\\\\\\\"\\\\n\\\\\\\")+\\\\\\\"\\\\n\\\\\\\"+f,g=[\\\\\\\"#define varying in\\\\\\\",n.glslVersion===w.I?\\\\\\\"\\\\\\\":\\\\\\\"out highp vec4 pc_fragColor;\\\\\\\",n.glslVersion===w.I?\\\\\\\"\\\\\\\":\\\\\\\"#define gl_FragColor pc_fragColor\\\\\\\",\\\\\\\"#define gl_FragDepthEXT gl_FragDepth\\\\\\\",\\\\\\\"#define texture2D texture\\\\\\\",\\\\\\\"#define textureCube texture\\\\\\\",\\\\\\\"#define texture2DProj textureProj\\\\\\\",\\\\\\\"#define texture2DLodEXT textureLod\\\\\\\",\\\\\\\"#define texture2DProjLodEXT textureProjLod\\\\\\\",\\\\\\\"#define textureCubeLodEXT textureLod\\\\\\\",\\\\\\\"#define texture2DGradEXT textureGrad\\\\\\\",\\\\\\\"#define texture2DProjGradEXT textureProjGrad\\\\\\\",\\\\\\\"#define textureCubeGradEXT textureGrad\\\\\\\"].join(\\\\\\\"\\\\n\\\\\\\")+\\\\\\\"\\\\n\\\\\\\"+g);const y=v+f+o,x=v+g+a,b=Ye(s,s.VERTEX_SHADER,y),T=Ye(s,s.FRAGMENT_SHADER,x);if(s.attachShader(m,b),s.attachShader(m,T),void 0!==n.index0AttributeName?s.bindAttribLocation(m,0,n.index0AttributeName):!0===n.morphTargets&&s.bindAttribLocation(m,0,\\\\\\\"position\\\\\\\"),s.linkProgram(m),t.debug.checkShaderErrors){const t=s.getProgramInfoLog(m).trim(),e=s.getShaderInfoLog(b).trim(),n=s.getShaderInfoLog(T).trim();let i=!0,r=!0;if(!1===s.getProgramParameter(m,s.LINK_STATUS)){i=!1;const e=Ze(s,b,\\\\\\\"vertex\\\\\\\"),n=Ze(s,T,\\\\\\\"fragment\\\\\\\");console.error(\\\\\\\"THREE.WebGLProgram: Shader Error \\\\\\\"+s.getError()+\\\\\\\" - VALIDATE_STATUS \\\\\\\"+s.getProgramParameter(m,s.VALIDATE_STATUS)+\\\\\\\"\\\\n\\\\nProgram Info Log: \\\\\\\"+t+\\\\\\\"\\\\n\\\\\\\"+e+\\\\\\\"\\\\n\\\\\\\"+n)}else\\\\\\\"\\\\\\\"!==t?console.warn(\\\\\\\"THREE.WebGLProgram: Program Info 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0!==r.depthPacking&&r.depthPacking,index0AttributeName:r.index0AttributeName,extensionDerivatives:r.extensions&&r.extensions.derivatives,extensionFragDepth:r.extensions&&r.extensions.fragDepth,extensionDrawBuffers:r.extensions&&r.extensions.drawBuffers,extensionShaderTextureLOD:r.extensions&&r.extensions.shaderTextureLOD,rendererExtensionFragDepth:l||i.has(\\\\\\\"EXT_frag_depth\\\\\\\"),rendererExtensionDrawBuffers:l||i.has(\\\\\\\"WEBGL_draw_buffers\\\\\\\"),rendererExtensionShaderTextureLod:l||i.has(\\\\\\\"EXT_shader_texture_lod\\\\\\\"),customProgramCacheKey:r.customProgramCacheKey()}},getProgramCacheKey:function(e){const n=[];if(e.shaderID?n.push(e.shaderID):(n.push(e.fragmentShader),n.push(e.vertexShader)),void 0!==e.defines)for(const t in e.defines)n.push(t),n.push(e.defines[t]);if(!1===e.isRawShaderMaterial){for(let t=0;t0?s.push(h):!0===n.transparent?r.push(h):i.push(h)},unshift:function(t,e,n,o,l,c){const h=a(t,e,n,o,l,c);n.transmission>0?s.unshift(h):!0===n.transparent?r.unshift(h):i.unshift(h)},finish:function(){for(let t=n,i=e.length;t1&&i.sort(t||gn),s.length>1&&s.sort(e||vn),r.length>1&&r.sort(e||vn)}}}function xn(t){let e=new WeakMap;return{get:function(n,i){let s;return!1===e.has(n)?(s=new yn(t),e.set(n,[s])):i>=e.get(n).length?(s=new yn(t),e.get(n).push(s)):s=e.get(n)[i],s},dispose:function(){e=new WeakMap}}}function bn(){const t={};return{get:function(e){if(void 0!==t[e.id])return t[e.id];let n;switch(e.type){case\\\\\\\"DirectionalLight\\\\\\\":n={direction:new p.a,color:new D.a};break;case\\\\\\\"SpotLight\\\\\\\":n={position:new p.a,direction:new p.a,color:new D.a,distance:0,coneCos:0,penumbraCos:0,decay:0};break;case\\\\\\\"PointLight\\\\\\\":n={position:new p.a,color:new D.a,distance:0,decay:0};break;case\\\\\\\"HemisphereLight\\\\\\\":n={direction:new p.a,skyColor:new D.a,groundColor:new D.a};break;case\\\\\\\"RectAreaLight\\\\\\\":n={color:new D.a,position:new p.a,halfWidth:new p.a,halfHeight:new p.a}}return t[e.id]=n,n}}}let wn=0;function Tn(t,e){return(e.castShadow?1:0)-(t.castShadow?1:0)}function An(t,e){const n=new bn,i=function(){const t={};return{get:function(e){if(void 0!==t[e.id])return t[e.id];let n;switch(e.type){case\\\\\\\"DirectionalLight\\\\\\\":case\\\\\\\"SpotLight\\\\\\\":n={shadowBias:0,shadowNormalBias:0,shadowRadius:1,shadowMapSize:new d.a};break;case\\\\\\\"PointLight\\\\\\\":n={shadowBias:0,shadowNormalBias:0,shadowRadius:1,shadowMapSize:new d.a,shadowCameraNear:1,shadowCameraFar:1e3}}return t[e.id]=n,n}}}(),s={version:0,hash:{directionalLength:-1,pointLength:-1,spotLength:-1,rectAreaLength:-1,hemiLength:-1,numDirectionalShadows:-1,numPointShadows:-1,numSpotShadows:-1},ambient:[0,0,0],probe:[],directional:[],directionalShadow:[],directionalShadowMap:[],directionalShadowMatrix:[],spot:[],spotShadow:[],spotShadowMap:[],spotShadowMatrix:[],rectArea:[],rectAreaLTC1:null,rectAreaLTC2:null,point:[],pointShadow:[],pointShadowMap:[],pointShadowMatrix:[],hemi:[]};for(let t=0;t<9;t++)s.probe.push(new p.a);const r=new p.a,o=new A.a,a=new A.a;return{setup:function(r,o){let a=0,l=0,c=0;for(let t=0;t<9;t++)s.probe[t].set(0,0,0);let h=0,u=0,d=0,p=0,_=0,m=0,f=0,g=0;r.sort(Tn);const v=!0!==o?Math.PI:1;for(let t=0,e=r.length;t0&&(e.isWebGL2||!0===t.has(\\\\\\\"OES_texture_float_linear\\\\\\\")?(s.rectAreaLTC1=V.LTC_FLOAT_1,s.rectAreaLTC2=V.LTC_FLOAT_2):!0===t.has(\\\\\\\"OES_texture_half_float_linear\\\\\\\")?(s.rectAreaLTC1=V.LTC_HALF_1,s.rectAreaLTC2=V.LTC_HALF_2):console.error(\\\\\\\"THREE.WebGLRenderer: Unable to use RectAreaLight. Missing WebGL extensions.\\\\\\\")),s.ambient[0]=a,s.ambient[1]=l,s.ambient[2]=c;const y=s.hash;y.directionalLength===h&&y.pointLength===u&&y.spotLength===d&&y.rectAreaLength===p&&y.hemiLength===_&&y.numDirectionalShadows===m&&y.numPointShadows===f&&y.numSpotShadows===g||(s.directional.length=h,s.spot.length=d,s.rectArea.length=p,s.point.length=u,s.hemi.length=_,s.directionalShadow.length=m,s.directionalShadowMap.length=m,s.pointShadow.length=f,s.pointShadowMap.length=f,s.spotShadow.length=g,s.spotShadowMap.length=g,s.directionalShadowMatrix.length=m,s.pointShadowMatrix.length=f,s.spotShadowMatrix.length=g,y.directionalLength=h,y.pointLength=u,y.spotLength=d,y.rectAreaLength=p,y.hemiLength=_,y.numDirectionalShadows=m,y.numPointShadows=f,y.numSpotShadows=g,s.version=wn++)},setupView:function(t,e){let n=0,i=0,l=0,c=0,h=0;const u=e.matrixWorldInverse;for(let e=0,d=t.length;e=n.get(i).length?(r=new Mn(t,e),n.get(i).push(r)):r=n.get(i)[s],r},dispose:function(){n=new WeakMap}}}class Sn extends O.a{constructor(t){super(),this.type=\\\\\\\"MeshDepthMaterial\\\\\\\",this.depthPacking=w.j,this.map=null,this.alphaMap=null,this.displacementMap=null,this.displacementScale=1,this.displacementBias=0,this.wireframe=!1,this.wireframeLinewidth=1,this.fog=!1,this.setValues(t)}copy(t){return super.copy(t),this.depthPacking=t.depthPacking,this.map=t.map,this.alphaMap=t.alphaMap,this.displacementMap=t.displacementMap,this.displacementScale=t.displacementScale,this.displacementBias=t.displacementBias,this.wireframe=t.wireframe,this.wireframeLinewidth=t.wireframeLinewidth,this}}Sn.prototype.isMeshDepthMaterial=!0;class Cn extends O.a{constructor(t){super(),this.type=\\\\\\\"MeshDistanceMaterial\\\\\\\",this.referencePosition=new p.a,this.nearDistance=1,this.farDistance=1e3,this.map=null,this.alphaMap=null,this.displacementMap=null,this.displacementScale=1,this.displacementBias=0,this.fog=!1,this.setValues(t)}copy(t){return super.copy(t),this.referencePosition.copy(t.referencePosition),this.nearDistance=t.nearDistance,this.farDistance=t.farDistance,this.map=t.map,this.alphaMap=t.alphaMap,this.displacementMap=t.displacementMap,this.displacementScale=t.displacementScale,this.displacementBias=t.displacementBias,this}}Cn.prototype.isMeshDistanceMaterial=!0;function Nn(t,e,n){let i=new T.a;const s=new d.a,r=new d.a,o=new _.a,a=new Sn({depthPacking:w.Hb}),l=new Cn,c={},h=n.maxTextureSize,u={0:w.i,1:w.H,2:w.z},p=new F({uniforms:{shadow_pass:{value:null},resolution:{value:new d.a},radius:{value:4},samples:{value:8}},vertexShader:\\\\\\\"\\\\nvoid main() {\\\\n\\\\n\\\\tgl_Position = vec4( position, 1.0 );\\\\n\\\\n}\\\\n\\\\\\\",fragmentShader:\\\\\\\"\\\\nuniform sampler2D shadow_pass;\\\\nuniform vec2 resolution;\\\\nuniform float radius;\\\\nuniform float samples;\\\\n\\\\n#include \\\\n\\\\nvoid main() {\\\\n\\\\n\\\\tfloat mean = 0.0;\\\\n\\\\tfloat squared_mean = 0.0;\\\\n\\\\n\\\\t// This seems totally useless but it's a crazy work around for a Adreno compiler bug\\\\n\\\\t// float depth = unpackRGBAToDepth( texture2D( shadow_pass, ( gl_FragCoord.xy ) / resolution ) );\\\\n\\\\n\\\\tfloat uvStride = samples <= 1.0 ? 0.0 : 2.0 / ( samples - 1.0 );\\\\n\\\\tfloat uvStart = samples <= 1.0 ? 0.0 : - 1.0;\\\\n\\\\tfor ( float i = 0.0; i < samples; i ++ ) {\\\\n\\\\n\\\\t\\\\tfloat uvOffset = uvStart + i * uvStride;\\\\n\\\\n\\\\t\\\\t#ifdef HORIZONTAL_PASS\\\\n\\\\n\\\\t\\\\t\\\\tvec2 distribution = unpackRGBATo2Half( texture2D( shadow_pass, ( gl_FragCoord.xy + vec2( uvOffset, 0.0 ) * radius ) / resolution ) );\\\\n\\\\t\\\\t\\\\tmean += distribution.x;\\\\n\\\\t\\\\t\\\\tsquared_mean += distribution.y * distribution.y + distribution.x * distribution.x;\\\\n\\\\n\\\\t\\\\t#else\\\\n\\\\n\\\\t\\\\t\\\\tfloat depth = unpackRGBAToDepth( texture2D( shadow_pass, ( gl_FragCoord.xy + vec2( 0.0, uvOffset ) * radius ) / resolution ) );\\\\n\\\\t\\\\t\\\\tmean += depth;\\\\n\\\\t\\\\t\\\\tsquared_mean += depth * depth;\\\\n\\\\n\\\\t\\\\t#endif\\\\n\\\\n\\\\t}\\\\n\\\\n\\\\tmean = mean / samples;\\\\n\\\\tsquared_mean = squared_mean / samples;\\\\n\\\\n\\\\tfloat std_dev = sqrt( squared_mean - mean * mean );\\\\n\\\\n\\\\tgl_FragColor = pack2HalfToRGBA( vec2( mean, std_dev ) );\\\\n\\\\n}\\\\n\\\\\\\"}),m=p.clone();m.defines.HORIZONTAL_PASS=1;const f=new S.a;f.setAttribute(\\\\\\\"position\\\\\\\",new C.a(new Float32Array([-1,-1,.5,3,-1,.5,-1,3,.5]),3));const g=new B.a(f,p),v=this;function y(n,i){const s=e.update(g);p.uniforms.shadow_pass.value=n.map.texture,p.uniforms.resolution.value=n.mapSize,p.uniforms.radius.value=n.radius,p.uniforms.samples.value=n.blurSamples,t.setRenderTarget(n.mapPass),t.clear(),t.renderBufferDirect(i,null,s,p,g,null),m.uniforms.shadow_pass.value=n.mapPass.texture,m.uniforms.resolution.value=n.mapSize,m.uniforms.radius.value=n.radius,m.uniforms.samples.value=n.blurSamples,t.setRenderTarget(n.map),t.clear(),t.renderBufferDirect(i,null,s,m,g,null)}function x(e,n,i,s,r,o,h){let d=null;const p=!0===s.isPointLight?e.customDistanceMaterial:e.customDepthMaterial;if(d=void 0!==p?p:!0===s.isPointLight?l:a,t.localClippingEnabled&&!0===i.clipShadows&&0!==i.clippingPlanes.length||i.displacementMap&&0!==i.displacementScale||i.alphaMap&&i.alphaTest>0){const t=d.uuid,e=i.uuid;let n=c[t];void 0===n&&(n={},c[t]=n);let s=n[e];void 0===s&&(s=d.clone(),n[e]=s),d=s}return 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l=0,c=e.length;lh||s.y>h)&&(s.x>h&&(r.x=Math.floor(h/p.x),s.x=r.x*p.x,u.mapSize.x=r.x),s.y>h&&(r.y=Math.floor(h/p.y),s.y=r.y*p.y,u.mapSize.y=r.y)),null===u.map&&!u.isPointLightShadow&&this.type===w.gd){const t={minFilter:w.V,magFilter:w.V,format:w.Ib};u.map=new K(s.x,s.y,t),u.map.texture.name=c.name+\\\\\\\".shadowMap\\\\\\\",u.mapPass=new K(s.x,s.y,t),u.camera.updateProjectionMatrix()}if(null===u.map){const t={minFilter:w.ob,magFilter:w.ob,format:w.Ib};u.map=new K(s.x,s.y,t),u.map.texture.name=c.name+\\\\\\\".shadowMap\\\\\\\",u.camera.updateProjectionMatrix()}t.setRenderTarget(u.map),t.clear();const _=u.getViewportCount();for(let t=0;t<_;t++){const e=u.getViewport(t);o.set(r.x*e.x,r.y*e.y,r.x*e.z,r.y*e.w),d.viewport(o),u.updateMatrices(c,t),i=u.getFrustum(),b(n,a,u.camera,c,this.type)}u.isPointLightShadow||this.type!==w.gd||y(u,a),u.needsUpdate=!1}v.needsUpdate=!1,t.setRenderTarget(l,c,u)}}function Ln(t,e,n){const i=n.isWebGL2;const s=new function(){let e=!1;const n=new _.a;let 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function(){let e=!1,n=null,i=null,s=null,r=null,o=null,a=null,l=null,c=null;return{setTest:function(n){e||(n?k(t.STENCIL_TEST):U(t.STENCIL_TEST))},setMask:function(i){n===i||e||(t.stencilMask(i),n=i)},setFunc:function(e,n,o){i===e&&s===n&&r===o||(t.stencilFunc(e,n,o),i=e,s=n,r=o)},setOp:function(e,n,i){o===e&&a===n&&l===i||(t.stencilOp(e,n,i),o=e,a=n,l=i)},setLocked:function(t){e=t},setClear:function(e){c!==e&&(t.clearStencil(e),c=e)},reset:function(){e=!1,n=null,i=null,s=null,r=null,o=null,a=null,l=null,c=null}}};let a={},l=null,c={},h=null,u=!1,d=null,p=null,m=null,f=null,g=null,v=null,y=null,x=!1,b=null,T=null,A=null,M=null,E=null;const S=t.getParameter(t.MAX_COMBINED_TEXTURE_IMAGE_UNITS);let C=!1,N=0;const L=t.getParameter(t.VERSION);-1!==L.indexOf(\\\\\\\"WebGL\\\\\\\")?(N=parseFloat(/^WebGL (\\\\d)/.exec(L)[1]),C=N>=1):-1!==L.indexOf(\\\\\\\"OpenGL ES\\\\\\\")&&(N=parseFloat(/^OpenGL ES (\\\\d)/.exec(L)[1]),C=N>=2);let O=null,P={};const 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0!==s&&(s.isWebGLRenderTarget&&(s=s.texture),!0===s.matrixAutoUpdate&&s.updateMatrix(),e.uvTransform.value.copy(s.matrix)),n.aoMap?r=n.aoMap:n.lightMap&&(r=n.lightMap),void 0!==r&&(r.isWebGLRenderTarget&&(r=r.texture),!0===r.matrixAutoUpdate&&r.updateMatrix(),e.uv2Transform.value.copy(r.matrix))}function n(e,n){e.roughness.value=n.roughness,e.metalness.value=n.metalness,n.roughnessMap&&(e.roughnessMap.value=n.roughnessMap),n.metalnessMap&&(e.metalnessMap.value=n.metalnessMap),n.emissiveMap&&(e.emissiveMap.value=n.emissiveMap),n.bumpMap&&(e.bumpMap.value=n.bumpMap,e.bumpScale.value=n.bumpScale,n.side===w.i&&(e.bumpScale.value*=-1)),n.normalMap&&(e.normalMap.value=n.normalMap,e.normalScale.value.copy(n.normalScale),n.side===w.i&&e.normalScale.value.negate()),n.displacementMap&&(e.displacementMap.value=n.displacementMap,e.displacementScale.value=n.displacementScale,e.displacementBias.value=n.displacementBias);t.get(n).envMap&&(e.envMapIntensity.value=n.envMapIntensity)}return{refreshFogUniforms:function(t,e){t.fogColor.value.copy(e.color),e.isFog?(t.fogNear.value=e.near,t.fogFar.value=e.far):e.isFogExp2&&(t.fogDensity.value=e.density)},refreshMaterialUniforms:function(t,i,s,r,o){i.isMeshBasicMaterial?e(t,i):i.isMeshLambertMaterial?(e(t,i),function(t,e){e.emissiveMap&&(t.emissiveMap.value=e.emissiveMap)}(t,i)):i.isMeshToonMaterial?(e(t,i),function(t,e){e.gradientMap&&(t.gradientMap.value=e.gradientMap);e.emissiveMap&&(t.emissiveMap.value=e.emissiveMap);e.bumpMap&&(t.bumpMap.value=e.bumpMap,t.bumpScale.value=e.bumpScale,e.side===w.i&&(t.bumpScale.value*=-1));e.normalMap&&(t.normalMap.value=e.normalMap,t.normalScale.value.copy(e.normalScale),e.side===w.i&&t.normalScale.value.negate());e.displacementMap&&(t.displacementMap.value=e.displacementMap,t.displacementScale.value=e.displacementScale,t.displacementBias.value=e.displacementBias)}(t,i)):i.isMeshPhongMaterial?(e(t,i),function(t,e){t.specular.value.copy(e.specular),t.shininess.value=Math.max(e.shininess,1e-4),e.emissiveMap&&(t.emissiveMap.value=e.emissiveMap);e.bumpMap&&(t.bumpMap.value=e.bumpMap,t.bumpScale.value=e.bumpScale,e.side===w.i&&(t.bumpScale.value*=-1));e.normalMap&&(t.normalMap.value=e.normalMap,t.normalScale.value.copy(e.normalScale),e.side===w.i&&t.normalScale.value.negate());e.displacementMap&&(t.displacementMap.value=e.displacementMap,t.displacementScale.value=e.displacementScale,t.displacementBias.value=e.displacementBias)}(t,i)):i.isMeshStandardMaterial?(e(t,i),i.isMeshPhysicalMaterial?function(t,e,i){n(t,e),t.ior.value=e.ior,e.sheen>0&&(t.sheenTint.value.copy(e.sheenTint).multiplyScalar(e.sheen),t.sheenRoughness.value=e.sheenRoughness);e.clearcoat>0&&(t.clearcoat.value=e.clearcoat,t.clearcoatRoughness.value=e.clearcoatRoughness,e.clearcoatMap&&(t.clearcoatMap.value=e.clearcoatMap),e.clearcoatRoughnessMap&&(t.clearcoatRoughnessMap.value=e.clearcoatRoughnessMap),e.clearcoatNormalMap&&(t.clearcoatNormalScale.value.copy(e.clearcoatNormalScale),t.clearcoatNormalMap.value=e.clearcoatNormalMap,e.side===w.i&&t.clearcoatNormalScale.value.negate()));e.transmission>0&&(t.transmission.value=e.transmission,t.transmissionSamplerMap.value=i.texture,t.transmissionSamplerSize.value.set(i.width,i.height),e.transmissionMap&&(t.transmissionMap.value=e.transmissionMap),t.thickness.value=e.thickness,e.thicknessMap&&(t.thicknessMap.value=e.thicknessMap),t.attenuationDistance.value=e.attenuationDistance,t.attenuationTint.value.copy(e.attenuationTint));t.specularIntensity.value=e.specularIntensity,t.specularTint.value.copy(e.specularTint),e.specularIntensityMap&&(t.specularIntensityMap.value=e.specularIntensityMap);e.specularTintMap&&(t.specularTintMap.value=e.specularTintMap)}(t,i,o):n(t,i)):i.isMeshMatcapMaterial?(e(t,i),function(t,e){e.matcap&&(t.matcap.value=e.matcap);e.bumpMap&&(t.bumpMap.value=e.bumpMap,t.bumpScale.value=e.bumpScale,e.side===w.i&&(t.bumpScale.value*=-1));e.normalMap&&(t.normalMap.value=e.normalMap,t.normalScale.value.copy(e.normalScale),e.side===w.i&&t.normalScale.value.negate());e.displacementMap&&(t.displacementMap.value=e.displacementMap,t.displacementScale.value=e.displacementScale,t.displacementBias.value=e.displacementBias)}(t,i)):i.isMeshDepthMaterial?(e(t,i),function(t,e){e.displacementMap&&(t.displacementMap.value=e.displacementMap,t.displacementScale.value=e.displacementScale,t.displacementBias.value=e.displacementBias)}(t,i)):i.isMeshDistanceMaterial?(e(t,i),function(t,e){e.displacementMap&&(t.displacementMap.value=e.displacementMap,t.displacementScale.value=e.displacementScale,t.displacementBias.value=e.displacementBias);t.referencePosition.value.copy(e.referencePosition),t.nearDistance.value=e.nearDistance,t.farDistance.value=e.farDistance}(t,i)):i.isMeshNormalMaterial?(e(t,i),function(t,e){e.bumpMap&&(t.bumpMap.value=e.bumpMap,t.bumpScale.value=e.bumpScale,e.side===w.i&&(t.bumpScale.value*=-1));e.normalMap&&(t.normalMap.value=e.normalMap,t.normalScale.value.copy(e.normalScale),e.side===w.i&&t.normalScale.value.negate());e.displacementMap&&(t.displacementMap.value=e.displacementMap,t.displacementScale.value=e.displacementScale,t.displacementBias.value=e.displacementBias)}(t,i)):i.isLineBasicMaterial?(function(t,e){t.diffuse.value.copy(e.color),t.opacity.value=e.opacity}(t,i),i.isLineDashedMaterial&&function(t,e){t.dashSize.value=e.dashSize,t.totalSize.value=e.dashSize+e.gapSize,t.scale.value=e.scale}(t,i)):i.isPointsMaterial?function(t,e,n,i){t.diffuse.value.copy(e.color),t.opacity.value=e.opacity,t.size.value=e.size*n,t.scale.value=.5*i,e.map&&(t.map.value=e.map);e.alphaMap&&(t.alphaMap.value=e.alphaMap);e.alphaTest>0&&(t.alphaTest.value=e.alphaTest);let s;e.map?s=e.map:e.alphaMap&&(s=e.alphaMap);void 0!==s&&(!0===s.matrixAutoUpdate&&s.updateMatrix(),t.uvTransform.value.copy(s.matrix))}(t,i,s,r):i.isSpriteMaterial?function(t,e){t.diffuse.value.copy(e.color),t.opacity.value=e.opacity,t.rotation.value=e.rotation,e.map&&(t.map.value=e.map);e.alphaMap&&(t.alphaMap.value=e.alphaMap);e.alphaTest>0&&(t.alphaTest.value=e.alphaTest);let n;e.map?n=e.map:e.alphaMap&&(n=e.alphaMap);void 0!==n&&(!0===n.matrixAutoUpdate&&n.updateMatrix(),t.uvTransform.value.copy(n.matrix))}(t,i):i.isShadowMaterial?(t.color.value.copy(i.color),t.opacity.value=i.opacity):i.isShaderMaterial&&(i.uniformsNeedUpdate=!1)}}}function Un(t={}){const e=void 0!==t.canvas?t.canvas:function(){const t=Object(It.b)(\\\\\\\"canvas\\\\\\\");return t.style.display=\\\\\\\"block\\\\\\\",t}(),n=void 0!==t.context?t.context:null,i=void 0!==t.alpha&&t.alpha,s=void 0===t.depth||t.depth,r=void 0===t.stencil||t.stencil,o=void 0!==t.antialias&&t.antialias,a=void 0===t.premultipliedAlpha||t.premultipliedAlpha,l=void 0!==t.preserveDrawingBuffer&&t.preserveDrawingBuffer,c=void 0!==t.powerPreference?t.powerPreference:\\\\\\\"default\\\\\\\",h=void 0!==t.failIfMajorPerformanceCaveat&&t.failIfMajorPerformanceCaveat;let u=null,d=null;const m=[],f=[];this.domElement=e,this.debug={checkShaderErrors:!0},this.autoClear=!0,this.autoClearColor=!0,this.autoClearDepth=!0,this.autoClearStencil=!0,this.sortObjects=!0,this.clippingPlanes=[],this.localClippingEnabled=!1,this.gammaFactor=2,this.outputEncoding=w.U,this.physicallyCorrectLights=!1,this.toneMapping=w.vb,this.toneMappingExposure=1;const g=this;let v=!1,y=0,x=0,b=null,S=-1,C=null;const N=new _.a,L=new _.a;let O=null,P=e.width,R=e.height,I=1,F=null,D=null;const B=new _.a(0,0,P,R),z=new _.a(0,0,P,R);let k=!1;const U=[],G=new T.a;let V=!1,H=!1,Y=null;const J=new A.a,Z=new p.a,Q={background:null,fog:null,environment:null,overrideMaterial:null,isScene:!0};function tt(){return null===b?I:1}let et,nt,it,st,ot,at,lt,ct,ht,ut,dt,pt,_t,mt,ft,gt,vt,yt,xt,bt,wt,Tt,At,Mt=n;function Et(t,n){for(let i=0;i0&&function(t,e,n){if(null===Y){const t=!0===o&&!0===nt.isWebGL2;Y=new(t?Ht:K)(1024,1024,{generateMipmaps:!0,type:null!==Tt.convert(w.M)?w.M:w.Zc,minFilter:w.Y,magFilter:w.ob,wrapS:w.n,wrapT:w.n})}const i=g.getRenderTarget();g.setRenderTarget(Y),g.clear();const s=g.toneMapping;g.toneMapping=w.vb,Xt(t,e,n),g.toneMapping=s,at.updateMultisampleRenderTarget(Y),at.updateRenderTargetMipmap(Y),g.setRenderTarget(i)}(s,e,n),i&&it.viewport(N.copy(i)),s.length>0&&Xt(s,e,n),r.length>0&&Xt(r,e,n),a.length>0&&Xt(a,e,n)}function Xt(t,e,n){const i=!0===e.isScene?e.overrideMaterial:null;for(let s=0,r=t.length;s0?f[f.length-1]:null,m.pop(),u=m.length>0?m[m.length-1]:null},this.getActiveCubeFace=function(){return y},this.getActiveMipmapLevel=function(){return x},this.getRenderTarget=function(){return b},this.setRenderTarget=function(t,e=0,n=0){b=t,y=e,x=n,t&&void 0===ot.get(t).__webglFramebuffer&&at.setupRenderTarget(t);let i=null,s=!1,r=!1;if(t){const n=t.texture;(n.isDataTexture3D||n.isDataTexture2DArray)&&(r=!0);const o=ot.get(t).__webglFramebuffer;t.isWebGLCubeRenderTarget?(i=o[e],s=!0):i=t.isWebGLMultisampleRenderTarget?ot.get(t).__webglMultisampledFramebuffer:o,N.copy(t.viewport),L.copy(t.scissor),O=t.scissorTest}else N.copy(B).multiplyScalar(I).floor(),L.copy(z).multiplyScalar(I).floor(),O=k;if(it.bindFramebuffer(Mt.FRAMEBUFFER,i)&&nt.drawBuffers){let e=!1;if(t)if(t.isWebGLMultipleRenderTargets){const n=t.texture;if(U.length!==n.length||U[0]!==Mt.COLOR_ATTACHMENT0){for(let t=0,e=n.length;t=0&&e<=t.width-i&&n>=0&&n<=t.height-s&&Mt.readPixels(e,n,i,s,Tt.convert(a),Tt.convert(l),r):console.error(\\\\\\\"THREE.WebGLRenderer.readRenderTargetPixels: readPixels from renderTarget failed. Framebuffer not complete.\\\\\\\")}finally{const t=null!==b?ot.get(b).__webglFramebuffer:null;it.bindFramebuffer(Mt.FRAMEBUFFER,t)}}},this.copyFramebufferToTexture=function(t,e,n=0){const i=Math.pow(2,-n),s=Math.floor(e.image.width*i),r=Math.floor(e.image.height*i);let o=Tt.convert(e.format);nt.isWebGL2&&(o===Mt.RGB&&(o=Mt.RGB8),o===Mt.RGBA&&(o=Mt.RGBA8)),at.setTexture2D(e,0),Mt.copyTexImage2D(Mt.TEXTURE_2D,n,o,t.x,t.y,s,r,0),it.unbindTexture()},this.copyTextureToTexture=function(t,e,n,i=0){const s=e.image.width,r=e.image.height,o=Tt.convert(n.format),a=Tt.convert(n.type);at.setTexture2D(n,0),Mt.pixelStorei(Mt.UNPACK_FLIP_Y_WEBGL,n.flipY),Mt.pixelStorei(Mt.UNPACK_PREMULTIPLY_ALPHA_WEBGL,n.premultiplyAlpha),Mt.pixelStorei(Mt.UNPACK_ALIGNMENT,n.unpackAlignment),e.isDataTexture?Mt.texSubImage2D(Mt.TEXTURE_2D,i,t.x,t.y,s,r,o,a,e.image.data):e.isCompressedTexture?Mt.compressedTexSubImage2D(Mt.TEXTURE_2D,i,t.x,t.y,e.mipmaps[0].width,e.mipmaps[0].height,o,e.mipmaps[0].data):Mt.texSubImage2D(Mt.TEXTURE_2D,i,t.x,t.y,o,a,e.image),0===i&&n.generateMipmaps&&Mt.generateMipmap(Mt.TEXTURE_2D),it.unbindTexture()},this.copyTextureToTexture3D=function(t,e,n,i,s=0){if(g.isWebGL1Renderer)return void console.warn(\\\\\\\"THREE.WebGLRenderer.copyTextureToTexture3D: can only be used with WebGL2.\\\\\\\");const r=t.max.x-t.min.x+1,o=t.max.y-t.min.y+1,a=t.max.z-t.min.z+1,l=Tt.convert(i.format),c=Tt.convert(i.type);let h;if(i.isDataTexture3D)at.setTexture3D(i,0),h=Mt.TEXTURE_3D;else{if(!i.isDataTexture2DArray)return void console.warn(\\\\\\\"THREE.WebGLRenderer.copyTextureToTexture3D: only supports THREE.DataTexture3D and THREE.DataTexture2DArray.\\\\\\\");at.setTexture2DArray(i,0),h=Mt.TEXTURE_2D_ARRAY}Mt.pixelStorei(Mt.UNPACK_FLIP_Y_WEBGL,i.flipY),Mt.pixelStorei(Mt.UNPACK_PREMULTIPLY_ALPHA_WEBGL,i.premultiplyAlpha),Mt.pixelStorei(Mt.UNPACK_ALIGNMENT,i.unpackAlignment);const u=Mt.getParameter(Mt.UNPACK_ROW_LENGTH),d=Mt.getParameter(Mt.UNPACK_IMAGE_HEIGHT),p=Mt.getParameter(Mt.UNPACK_SKIP_PIXELS),_=Mt.getParameter(Mt.UNPACK_SKIP_ROWS),m=Mt.getParameter(Mt.UNPACK_SKIP_IMAGES),f=n.isCompressedTexture?n.mipmaps[0]:n.image;Mt.pixelStorei(Mt.UNPACK_ROW_LENGTH,f.width),Mt.pixelStorei(Mt.UNPACK_IMAGE_HEIGHT,f.height),Mt.pixelStorei(Mt.UNPACK_SKIP_PIXELS,t.min.x),Mt.pixelStorei(Mt.UNPACK_SKIP_ROWS,t.min.y),Mt.pixelStorei(Mt.UNPACK_SKIP_IMAGES,t.min.z),n.isDataTexture||n.isDataTexture3D?Mt.texSubImage3D(h,s,e.x,e.y,e.z,r,o,a,l,c,f.data):n.isCompressedTexture?(console.warn(\\\\\\\"THREE.WebGLRenderer.copyTextureToTexture3D: untested support for compressed srcTexture.\\\\\\\"),Mt.compressedTexSubImage3D(h,s,e.x,e.y,e.z,r,o,a,l,f.data)):Mt.texSubImage3D(h,s,e.x,e.y,e.z,r,o,a,l,c,f),Mt.pixelStorei(Mt.UNPACK_ROW_LENGTH,u),Mt.pixelStorei(Mt.UNPACK_IMAGE_HEIGHT,d),Mt.pixelStorei(Mt.UNPACK_SKIP_PIXELS,p),Mt.pixelStorei(Mt.UNPACK_SKIP_ROWS,_),Mt.pixelStorei(Mt.UNPACK_SKIP_IMAGES,m),0===s&&i.generateMipmaps&&Mt.generateMipmap(h),it.unbindTexture()},this.initTexture=function(t){at.setTexture2D(t,0),it.unbindTexture()},this.resetState=function(){y=0,x=0,b=null,it.reset(),At.reset()},\\\\\\\"undefined\\\\\\\"!=typeof __THREE_DEVTOOLS__&&__THREE_DEVTOOLS__.dispatchEvent(new CustomEvent(\\\\\\\"observe\\\\\\\",{detail:this}))}const Gn={};var Vn,Hn,jn;!function(t){t.WEBGL=\\\\\\\"webgl\\\\\\\",t.WEBGL2=\\\\\\\"webgl2\\\\\\\",t.EXPERIMENTAL_WEBGL=\\\\\\\"experimental-webgl\\\\\\\",t.EXPERIMENTAL_WEBGL2=\\\\\\\"experimental-webgl2\\\\\\\"}(Vn||(Vn={}));class Wn{constructor(){this._next_renderer_id=0,this._renderers={},this._printDebug=!1,this._require_webgl2=!1,this._resolves=[]}setPrintDebug(t=!0){this._printDebug=t}printDebug(){return this._printDebug}printDebugMessage(t){this._printDebug&&console.warn(\\\\\\\"[Poly debug]\\\\\\\",t)}setRequireWebGL2(){this._require_webgl2||(this._require_webgl2=!0)}webgl2Available(){return void 0===this._webgl2_available&&(this._webgl2_available=this._set_webgl2_available()),this._webgl2_available}_set_webgl2_available(){const t=document.createElement(\\\\\\\"canvas\\\\\\\");return null!=(window.WebGL2RenderingContext&&t.getContext(Vn.WEBGL2))}createWebGLRenderer(t){const e=new Un(t);return this.printDebugMessage([\\\\\\\"create renderer:\\\\\\\",t]),e}createRenderingContext(t){let e=null;return this._require_webgl2&&(e=this._getRenderingContextWebgl(t,!0),e||console.warn(\\\\\\\"failed to create webgl2 context\\\\\\\")),e||(e=this._getRenderingContextWebgl(t,!1)),e}_getRenderingContextWebgl(t,e){let n;n=this.webgl2Available()||e?Vn.WEBGL2:Vn.WEBGL;let i=t.getContext(n,Gn);return i?this.printDebugMessage(`create gl context: ${n}.`):(n=e?Vn.EXPERIMENTAL_WEBGL2:Vn.EXPERIMENTAL_WEBGL,this.printDebugMessage(`create gl context: ${n}.`),i=t.getContext(n,Gn)),i}registerRenderer(t){if(t._polygon_id)throw new Error(\\\\\\\"render already registered\\\\\\\");t._polygon_id=this._next_renderer_id+=1,this._renderers[t._polygon_id]=t,1==Object.keys(this._renderers).length&&this.flush_callbacks_with_renderer(t)}deregisterRenderer(t){delete this._renderers[t._polygon_id],t.dispose()}firstRenderer(){const t=Object.keys(this._renderers)[0];return t?this._renderers[t]:null}renderers(){return Object.values(this._renderers)}flush_callbacks_with_renderer(t){let e;for(;e=this._resolves.pop();)e(t)}async waitForRenderer(){const t=this.firstRenderer();return t||new Promise(((t,e)=>{this._resolves.push(t)}))}renderTarget(t,e,n){return this.webgl2Available()?new Ht(t,e,n):new K(t,e,n)}}class qn{constructor(){this._root=\\\\\\\"/three/js/libs\\\\\\\",this._BASISPath=\\\\\\\"/basis\\\\\\\",this._DRACOPath=\\\\\\\"/draco\\\\\\\",this._DRACOGLTFPath=\\\\\\\"/draco/gltf\\\\\\\"}root(){return this._root}setRoot(t){this._root=t}BASISPath(){return this._BASISPath}DRACOPath(){return this._DRACOPath}DRACOGLTFPath(){return this._DRACOGLTFPath}}class Xn{constructor(t){this.poly=t,this._node_register=new Map,this._node_register_categories=new Map,this._node_register_options=new Map}static type(t){return this.filterType(t.type())}static filterType(t){return t.toLowerCase()}register(t,e,n){const i=t.context(),s=Xn.type(t);let r=this._node_register.get(i);r||(r=new Map,this._node_register.set(i,r));if(r.get(s))console.error(`node ${i}/${s} already registered`);else{if(r.set(s,t),e){let t=this._node_register_categories.get(i);t||(t=new Map,this._node_register_categories.set(i,t)),t.set(s,e)}if(n){let t=this._node_register_options.get(i);t||(t=new Map,this._node_register_options.set(i,t)),t.set(s,n)}this.poly.pluginsRegister.registerNode(t)}}deregister(t,e){var n,i,s;e=Xn.filterType(e),null===(n=this._node_register.get(t))||void 0===n||n.delete(e),null===(i=this._node_register_categories.get(t))||void 0===i||i.delete(e),null===(s=this._node_register_options.get(t))||void 0===s||s.delete(e)}isRegistered(t,e){const n=this._node_register.get(t);return!!n&&(e=Xn.filterType(e),null!=n.get(e))}nodeOptions(t,e){var n;return e=Xn.filterType(e),null===(n=this._node_register_options.get(t))||void 0===n?void 0:n.get(e)}registeredNodesForContextAndParentType(t,e){var n;if(this._node_register.get(t)){const i=[];return null===(n=this._node_register.get(t))||void 0===n||n.forEach(((t,e)=>{i.push(t)})),i.filter((n=>{var i;const s=Xn.type(n),r=null===(i=this._node_register_options.get(t))||void 0===i?void 0:i.get(s);if(r){const n=r.only,i=r.except,s=`${t}/${e}`;return n?n.includes(s):!i||!i.includes(s)}return!0}))}return[]}registeredNodes(t,e){const n={},i=this.registeredNodesForContextAndParentType(t,e);for(let t of i){n[Xn.type(t)]=t}return n}registeredCategory(t,e){var n;return e=Xn.filterType(e),null===(n=this._node_register_categories.get(t))||void 0===n?void 0:n.get(e)}map(){return this._node_register}}class Yn{constructor(t){this.poly=t,this._operation_register=new Map}static type(t){return this.filterType(t.type())}static filterType(t){return t.toLowerCase()}register(t){const e=t.context();let n=this._operation_register.get(e);n||(n=new Map,this._operation_register.set(e,n));const i=Yn.type(t);if(n.get(i)){const t=`operation ${e}/${i} already registered`;console.error(t)}else n.set(i,t),this.poly.pluginsRegister.registerOperation(t)}registeredOperationsForContextAndParentType(t,e){var n;if(this._operation_register.get(t)){const e=[];return null===(n=this._operation_register.get(t))||void 0===n||n.forEach(((t,n)=>{e.push(t)})),e}return[]}registeredOperation(t,e){const n=this._operation_register.get(t);if(n)return e=Yn.filterType(e),n.get(e)}}class $n extends class{constructor(){this._methods_names=[],this._methods_by_name=new Map}register(t,e){this._methods_names.push(e),this._methods_by_name.set(e,t)}getMethod(t){return this._methods_by_name.get(t)}availableMethods(){return this._methods_names}}{getMethod(t){return super.getMethod(t)}}!function(t){t.BasisTextureLoader=\\\\\\\"BasisTextureLoader\\\\\\\",t.DRACOLoader=\\\\\\\"DRACOLoader\\\\\\\",t.EXRLoader=\\\\\\\"EXRLoader\\\\\\\",t.FBXLoader=\\\\\\\"FBXLoader\\\\\\\",t.GLTFLoader=\\\\\\\"GLTFLoader\\\\\\\",t.OBJLoader=\\\\\\\"OBJLoader\\\\\\\",t.PDBLoader=\\\\\\\"PDBLoader\\\\\\\",t.PLYLoader=\\\\\\\"PLYLoader\\\\\\\",t.RGBELoader=\\\\\\\"RGBELoader\\\\\\\",t.SVGLoader=\\\\\\\"SVGLoader\\\\\\\",t.STLLoader=\\\\\\\"STLLoader\\\\\\\",t.TTFLoader=\\\\\\\"TTFLoader\\\\\\\"}(Hn||(Hn={}));class Jn extends class{constructor(){this._module_by_name=new Map}register(t,e){this._module_by_name.set(t,e)}moduleNames(){const t=[];return this._module_by_name.forEach(((e,n)=>{t.push(n)})),t}module(t){return this._module_by_name.get(t)}}{}!function(t){t.GL_MESH_BASIC=\\\\\\\"GL_MESH_BASIC\\\\\\\",t.GL_MESH_LAMBERT=\\\\\\\"GL_MESH_LAMBERT\\\\\\\",t.GL_MESH_STANDARD=\\\\\\\"GL_MESH_STANDARD\\\\\\\",t.GL_MESH_PHONG=\\\\\\\"GL_MESH_PHONG\\\\\\\",t.GL_MESH_PHYSICAL=\\\\\\\"GL_MESH_PHYSICAL\\\\\\\",t.GL_PARTICLES=\\\\\\\"GL_PARTICLES\\\\\\\",t.GL_POINTS=\\\\\\\"GL_POINTS\\\\\\\",t.GL_LINE=\\\\\\\"GL_LINE\\\\\\\",t.GL_TEXTURE=\\\\\\\"GL_TEXTURE\\\\\\\",t.GL_VOLUME=\\\\\\\"GL_VOLUME\\\\\\\"}(jn||(jn={}));class Zn extends class{constructor(){this._controller_assembler_by_name=new Map}register(t,e,n){this._controller_assembler_by_name.set(t,{controller:e,assembler:n})}unregister(t){this._controller_assembler_by_name.delete(t)}}{assembler(t,e){const n=this._controller_assembler_by_name.get(e);if(n){return new(0,n.controller)(t,n.assembler)}return n}unregister(t){const e=this._controller_assembler_by_name.get(t);return super.unregister(t),e}}class Kn{constructor(t){this.poly=t,this._plugins_by_name=new Map,this._plugin_name_by_node_context_by_type=new Map,this._plugin_name_by_operation_context_by_type=new Map}register(t){this._current_plugin=t,this._plugins_by_name.set(t.name(),t),t.init(this.poly),this._current_plugin=void 0}pluginByName(t){return this._plugins_by_name.get(t)}registerNode(t){if(!this._current_plugin)return;const e=t.context(),n=t.type();let i=this._plugin_name_by_node_context_by_type.get(e);i||(i=new Map,this._plugin_name_by_node_context_by_type.set(e,i)),i.set(n,this._current_plugin.name())}registerOperation(t){if(!this._current_plugin)return;const e=t.context(),n=t.type();let i=this._plugin_name_by_operation_context_by_type.get(e);i||(i=new Map,this._plugin_name_by_operation_context_by_type.set(e,i)),i.set(n,this._current_plugin.name())}toJson(){const t={plugins:{},nodes:{},operations:{}};return this._plugins_by_name.forEach(((e,n)=>{t.plugins[n]=e.toJSON()})),this._plugin_name_by_node_context_by_type.forEach(((e,n)=>{t.nodes[n]={},e.forEach(((e,i)=>{t.nodes[n][i]=e}))})),this._plugin_name_by_operation_context_by_type.forEach(((e,n)=>{t.operations[n]={},e.forEach(((e,i)=>{t.operations[n][i]=e}))})),t}}class Qn{constructor(t){this._camera_types=[]}register(t){const e=t.type();this._camera_types.includes(e)||this._camera_types.push(e)}registeredTypes(){return this._camera_types}}var ti=n(86);class ei{constructor(){this._blobUrlsByStoredUrl=new Map,this._blobsByStoredUrl=new Map,this._blobDataByNodeId=new Map,this._globalBlobsByStoredUrl=new Map}registerBlobUrl(t){li.playerMode()&&this._blobUrlsByStoredUrl.set(t.storedUrl,t.blobUrl)}deregisterUrl(t){this._blobUrlsByStoredUrl.delete(t)}blobUrl(t){return this._blobUrlsByStoredUrl.get(t)}clear(){this._blobUrlsByStoredUrl.clear(),this._blobsByStoredUrl.clear(),this._blobDataByNodeId.clear()}_clearBlobForNode(t){const e=this._blobDataByNodeId.get(t.graphNodeId());e&&(this._blobsByStoredUrl.delete(e.storedUrl),this._blobUrlsByStoredUrl.delete(e.storedUrl)),this._blobDataByNodeId.delete(t.graphNodeId())}_assignBlobToNode(t,e){this._clearBlobForNode(t),this._blobDataByNodeId.set(t.graphNodeId(),{storedUrl:e.storedUrl,fullUrl:e.fullUrl})}async fetchBlobGlobal(t){if(li.playerMode())return{};try{if(this._blobUrlsByStoredUrl.get(t.storedUrl))return{};const e=li.assetUrls.remapedUrl(t.fullUrl),n=await fetch(e||t.fullUrl);if(n.ok){const e=await n.blob();return this._blobsByStoredUrl.set(t.storedUrl,e),this._blobUrlsByStoredUrl.set(t.storedUrl,this.createBlobUrl(e)),this._globalBlobsByStoredUrl.set(t.storedUrl,e),{blobData:{storedUrl:t.storedUrl,fullUrl:t.fullUrl}}}return{error:`failed to fetch ${t.fullUrl}`}}catch(e){return{error:`failed to fetch ${t.fullUrl}`}}}async fetchBlobForNode(t){if(li.playerMode())return{};try{if(this._blobUrlsByStoredUrl.get(t.storedUrl))return{};const e=li.assetUrls.remapedUrl(t.fullUrl),n=await fetch(e||t.fullUrl);if(n.ok){const e=await n.blob();return this._blobsByStoredUrl.set(t.storedUrl,e),this._blobUrlsByStoredUrl.set(t.storedUrl,this.createBlobUrl(e)),this._scene=t.node.scene(),this._assignBlobToNode(t.node,{storedUrl:t.storedUrl,fullUrl:t.fullUrl}),{blobData:{storedUrl:t.storedUrl,fullUrl:t.fullUrl}}}return{error:`failed to fetch ${t.fullUrl}`}}catch(e){return{error:`failed to fetch ${t.fullUrl}`}}}forEachBlob(t){this._blobDataByNodeId.forEach(((e,n)=>{if(this._scene){if(this._scene.graph.nodeFromId(n)){const{storedUrl:n}=e,i=this._blobsByStoredUrl.get(n);i&&t(i,n)}}}));let e=[];const n=new Map;this._globalBlobsByStoredUrl.forEach(((t,i)=>{e.push(i),n.set(i,t)})),e=e.sort(),e.forEach((e=>{const n=this._globalBlobsByStoredUrl.get(e);n&&t(n,e)}))}createBlobUrl(t){return Object(ti.a)(t)}}class ni{setMap(t){this._map=t}remapedUrl(t){if(!this._map)return;const e=t.split(\\\\\\\"?\\\\\\\"),n=e[0],i=e[1],s=this._map[n];return s?i?`${s}?${i}`:s:void 0}}var ii=n(91),si=n(83);class ri{markAsLoaded(t,e){this._sceneJsonImporterContructor=e,t()}load(t){if(!this._sceneJsonImporterContructor)return;const e=[];t.forEach(((t,n)=>{e.push(n)}));for(let n of e){const e=t.get(n);e&&(this._loadElement(n,e,this._sceneJsonImporterContructor),t.delete(n))}}async _loadElement(t,e,n){const{sceneData:i,assetsManifest:s,unzippedData:r}=e,o=Object.keys(s);for(let t of o){const e=r[`assets/${s[t]}`];if(!e)return void console.error(t,e);const n=new Blob([e]),i={storedUrl:t,blobUrl:li.blobs.createBlobUrl(n)};li.blobs.registerBlobUrl(i)}li.setPlayerMode(!0),li.libs.setRoot(null);const a=`${Math.random()}`.replace(\\\\\\\".\\\\\\\",\\\\\\\"_\\\\\\\"),l={Poly:`___POLY_polyConfig_configurePolygonjs_${a}`,scriptElementId:`___POLY_polyConfig_scriptElement_${a}`,loadSceneArgs:`___POLY_polyConfig_loadSceneArgs_${a}`};window[l.Poly]=li;const c={method:this._loadScene.bind(this),element:t,sceneData:i,sceneJsonImporterContructor:n};window[l.loadSceneArgs]=c;this._loadPolyConfig(l,r)||this._loadScene(t,i,n)}_loadPolyConfig(t,e){const n=e[si.a.POLY_CONFIG];if(!n)return!1;const i=this._createJsBlob(n,\\\\\\\"polyConfig\\\\\\\");let s=document.getElementById(t.scriptElementId);const r=[];return r.push(`import {configurePolygonjs, configureScene} from '${i}';`),r.push(`configurePolygonjs(window.${t.Poly});`),r.push(`window.${t.loadSceneArgs}.method(window.${t.loadSceneArgs}.element, window.${t.loadSceneArgs}.sceneData, window.${t.loadSceneArgs}.sceneJsonImporterContructor, configureScene);`),r.push(`delete window.${t.loadSceneArgs};`),s||(s=document.createElement(\\\\\\\"script\\\\\\\"),s.setAttribute(\\\\\\\"type\\\\\\\",\\\\\\\"module\\\\\\\"),s.text=r.join(\\\\\\\"\\\\n\\\\\\\"),document.body.append(s)),!0}async _loadScene(t,e,n,i){this._fadeOutPoster(t);const s=new n(e),r=await s.scene();i&&i(r);const o=r.mainCameraNode();if(!o)return void console.warn(\\\\\\\"no master camera found\\\\\\\");const a=o.createViewer(t);r.play(),t.scene=r,t.viewer=a}_fadeOutPoster(t){const e=t.firstElementChild;e&&(e.style.pointerEvents=\\\\\\\"none\\\\\\\",ii.a.fadeOut(e).then((()=>{var t;null===(t=e.parentElement)||void 0===t||t.removeChild(e)})))}_createJsBlob(t,e){const n=new Blob([t]),i=new File([n],`${e}.js`,{type:\\\\\\\"application/javascript\\\\\\\"});return Object(ti.a)(i)}}class oi{setPerformanceManager(t){this._performanceManager=t}performanceManager(){return this._performanceManager||window.performance}}class ai{constructor(){this.renderersController=new Wn,this.nodesRegister=new Xn(this),this.operationsRegister=new Yn(this),this.expressionsRegister=new $n,this.modulesRegister=new Jn,this.assemblersRegister=new Zn,this.pluginsRegister=new Kn(this),this.camerasRegister=new Qn(this),this.blobs=new ei,this.assetUrls=new ni,this.selfContainedScenesLoader=new ri,this.performance=new oi,this.scenesByUuid={},this._player_mode=!0,this._logger=null}static _instance_(){if(window.__POLYGONJS_POLY_INSTANCE__)return window.__POLYGONJS_POLY_INSTANCE__;{const t=new ai;return window.__POLYGONJS_POLY_INSTANCE__=t,window.__POLYGONJS_POLY_INSTANCE__}}setPlayerMode(t){this._player_mode=t}playerMode(){return this._player_mode}registerNode(t,e,n){this.nodesRegister.register(t,e,n)}registerOperation(t){this.operationsRegister.register(t)}registerCamera(t){this.camerasRegister.register(t)}registerPlugin(t){this.pluginsRegister.register(t)}registeredNodes(t,e){return this.nodesRegister.registeredNodes(t,e)}registeredOperation(t,e){return this.operationsRegister.registeredOperation(t,e)}registeredCameraTypes(){return this.camerasRegister.registeredTypes()}inWorkerThread(){return!1}desktopController(){}get libs(){return this._libs_controller=this._libs_controller||new qn}setEnv(t){this._env=t}env(){return this._env}setLogger(t){this._logger=t}log(t,...e){var n;null===(n=this._logger)||void 0===n||n.log(t,...e)}warn(t,...e){var n;null===(n=this._logger)||void 0===n||n.warn(t,...e)}error(t,...e){var n;null===(n=this._logger)||void 0===n||n.error(t,...e)}}const li=ai._instance_();class ci{constructor(){this._started=!1,this._start_time=0,this._previous_timestamp=0,this._nodes_cook_data={},this._durations_by_name={},this._durations_count_by_name={}}profile(t,e){const n=li.performance.performanceManager(),i=n.now();e();const s=n.now()-i;console.log(`${t}: ${s}`)}start(){if(!this._started){this.reset(),this._started=!0;const t=li.performance.performanceManager();this._start_time=t.now(),this._nodes_cook_data={},this._previous_timestamp=this._start_time}}stop(){this.reset()}reset(){this._started=!1,this._start_time=null,this._durations_by_name={},this._durations_count_by_name={},this._nodes_cook_data={}}started(){return this._started}record_node_cook_data(t,e){const n=t.graphNodeId();null==this._nodes_cook_data[n]&&(this._nodes_cook_data[n]=new c(t)),this._nodes_cook_data[n].update_cook_data(e)}record(t){this.started()||this.start();const e=performance.now();return null==this._durations_by_name[t]&&(this._durations_by_name[t]=0),this._durations_by_name[t]+=e-this._previous_timestamp,null==this._durations_count_by_name[t]&&(this._durations_count_by_name[t]=0),this._durations_count_by_name[t]+=1,this._previous_timestamp=e}print(){this.print_node_cook_data(),this.print_recordings()}print_node_cook_data(){let t=Object.values(this._nodes_cook_data);t=f.sortBy(t,(t=>t.total_cook_time()));const e=t.map((t=>t.print_object()));console.log(\\\\\\\"--------------- NODES COOK TIME -----------\\\\\\\");const n=[],i=f.sortBy(e,(t=>-t.total_cook_time));for(let t of i)n.push(t);return console.table(n),e}print_recordings(){const t=b.clone(this._durations_by_name),e=b.clone(this._durations_count_by_name),n=[],i={};for(let e of Object.keys(t)){const s=t[e];n.push(s),null==i[s]&&(i[s]=[]),i[s].push(e)}n.sort(((t,e)=>t-e));const s=f.uniq(n);console.log(\\\\\\\"--------------- PERF RECORDINGS -----------\\\\\\\");const r=[];for(let t of s){const n=i[t];for(let i of n){const n=e[i],s={duration:t,name:i,count:n,duration_per_iteration:t/n};r.push(s)}}return console.table(r),r}}class hi{constructor(t){this.scene=t}setListener(t){this._events_listener?console.warn(\\\\\\\"scene already has a listener\\\\\\\"):(this._events_listener=t,this.run_on_add_listener_callbacks())}onAddListener(t){this._events_listener?t():(this._on_add_listener_callbacks=this._on_add_listener_callbacks||[],this._on_add_listener_callbacks.push(t))}run_on_add_listener_callbacks(){if(this._on_add_listener_callbacks){let t;for(;t=this._on_add_listener_callbacks.pop();)t();this._on_add_listener_callbacks=void 0}}get eventsListener(){return this._events_listener}dispatch(t,e,n){var i;null===(i=this._events_listener)||void 0===i||i.process_events(t,e,n)}emitAllowed(){return null!=this._events_listener&&this.scene.loadingController.loaded()&&this.scene.loadingController.autoUpdating()}}class ui{constructor(){this._params_by_id=new Map}registerParam(t){this._params_by_id.set(t.graphNodeId(),t)}deregisterParam(t){this._params_by_id.delete(t.graphNodeId())}regenerateReferringExpressions(t){t.nameController.graph_node.setSuccessorsDirty(t)}}class di{constructor(t){this.scene=t,this._lifecycle_on_create_allowed=!0}onCreateHookAllowed(){return this.scene.loadingController.loaded()&&this._lifecycle_on_create_allowed}onCreatePrevent(t){this._lifecycle_on_create_allowed=!1,t(),this._lifecycle_on_create_allowed=!0}}class pi{constructor(t){this.dispatcher=t,this._nodes_by_graph_node_id=new Map,this._require_canvas_event_listeners=!1,this._activeEventDatas=[]}registerNode(t){this._nodes_by_graph_node_id.set(t.graphNodeId(),t),this.updateViewerEventListeners()}unregisterNode(t){this._nodes_by_graph_node_id.delete(t.graphNodeId()),this.updateViewerEventListeners()}processEvent(t){0!=this._activeEventDatas.length&&this._nodes_by_graph_node_id.forEach((e=>e.processEvent(t)))}updateViewerEventListeners(){this._update_active_event_types(),this._require_canvas_event_listeners&&this.dispatcher.scene.viewersRegister.traverseViewers((t=>{t.eventsController.updateEvents(this)}))}activeEventDatas(){return this._activeEventDatas}_update_active_event_types(){const t=new Map;this._nodes_by_graph_node_id.forEach((e=>{if(e.parent()){const n=e.activeEventDatas();for(let e of n)t.set(e,!0)}})),this._activeEventDatas=[],t.forEach(((t,e)=>{this._activeEventDatas.push(e)}))}}var _i;!function(t){t.LOADED=\\\\\\\"sceneLoaded\\\\\\\",t.PLAY=\\\\\\\"play\\\\\\\",t.PAUSE=\\\\\\\"pause\\\\\\\",t.TICK=\\\\\\\"tick\\\\\\\"}(_i||(_i={}));const mi=[_i.LOADED,_i.PLAY,_i.PAUSE,_i.TICK];class fi extends pi{type(){return\\\\\\\"scene\\\\\\\"}acceptedEventTypes(){return mi.map((t=>`${t}`))}}class gi{constructor(t){this.scene=t,this._loading_state=!1,this._auto_updating=!0,this._first_object_loaded=!1}get LOADED_EVENT_CONTEXT(){return this._LOADED_EVENT_CONTEXT=this._LOADED_EVENT_CONTEXT||{event:new Event(_i.LOADED)}}markAsLoading(){this._set_loading_state(!0)}async markAsLoaded(){this.scene.missingExpressionReferencesController.resolveMissingReferences(),await this._set_loading_state(!1),this.trigger_loaded_event()}trigger_loaded_event(){globalThis.Event&&this.scene.eventsDispatcher.sceneEventsController.processEvent(this.LOADED_EVENT_CONTEXT)}async _set_loading_state(t){this._loading_state=t,await this.set_auto_update(!this._loading_state)}isLoading(){return this._loading_state}loaded(){return!this._loading_state}autoUpdating(){return this._auto_updating}async set_auto_update(t){if(this._auto_updating!==t&&(this._auto_updating=t,this._auto_updating)){const t=this.scene.root();t&&await t.processQueue()}}on_first_object_loaded(){var t;if(!this._first_object_loaded){this._first_object_loaded=!0;const e=document.getElementById(\\\\\\\"scene_loading_container\\\\\\\");e&&(null===(t=e.parentElement)||void 0===t||t.removeChild(e))}}}const vi={EMPTY:\\\\\\\"\\\\\\\",UV:\\\\\\\"/COP/imageUv\\\\\\\",ENV_MAP:\\\\\\\"/COP/envMap\\\\\\\",CUBE_MAP:\\\\\\\"/COP/cubeCamera\\\\\\\"};class yi{constructor(t=\\\\\\\"\\\\\\\"){this._path=t,this._node=null}set_path(t){this._path=t}set_node(t){this._node=t}path(){return this._path}node(){return this._node}resolve(t){this._node=bi.findNode(t,this._path)}clone(){const t=new yi(this._path);return t.set_node(this._node),t}nodeWithContext(t,e){const n=this.node();if(!n)return void(null==e||e.set(`no node found at ${this.path()}`));const i=n.context();return i==t?n:void(null==e||e.set(`expected ${t} node, but got a ${i}`))}}class xi{constructor(t=\\\\\\\"\\\\\\\"){this._path=t,this._param=null}set_path(t){this._path=t}set_param(t){this._param=t}path(){return this._path}param(){return this._param}resolve(t){this._param=bi.findParam(t,this._path)}clone(){const t=new xi(this._path);return t.set_param(this._param),t}paramWithType(t,e){const n=this.param();if(n)return n.type()==t?n:void(null==e||e.set(`expected ${t} node, but got a ${n.type()}`));null==e||e.set(`no param found at ${this.path()}`)}}class bi{static split_parent_child(t){const e=t.split(bi.SEPARATOR).filter((t=>t.length>0)),n=e.pop();return{parent:e.join(bi.SEPARATOR),child:n}}static findNode(t,e,n){if(!t)return null;const i=e.split(bi.SEPARATOR).filter((t=>t.length>0)),s=i[0];let r=null;if(e[0]!==bi.SEPARATOR){switch(s){case bi.PARENT:null==n||n.add_path_element(s),r=t.parent();break;case bi.CURRENT:null==n||n.add_path_element(s),r=t;break;default:r=t.node(s),r&&(null==n||n.add_node(s,r))}if(null!=r&&i.length>1){const t=i.slice(1).join(bi.SEPARATOR);r=this.findNode(r,t,n)}return r}{const i=e.substr(1);r=this.findNode(t.root(),i,n)}return r}static findParam(t,e,n){if(!t)return null;const i=e.split(bi.SEPARATOR);if(1===i.length)return t.params.get(i[0]);{const e=i.slice(0,+(i.length-2)+1||void 0).join(bi.SEPARATOR),s=this.findNode(t,e,n);if(null!=s){const t=i[i.length-1],e=s.params.get(t);return n&&e&&n.add_node(t,e),e}return null}}static relativePath(t,e){const n=this.closestCommonParent(t,e);if(n){const i=this.distanceToParent(t,n);let s=\\\\\\\"\\\\\\\";if(i>0){let t=0;const e=[];for(;t++t.length>0)),o=e.path().split(bi.SEPARATOR).filter((t=>t.length>0)),a=[];let l=0;for(let t of o)r[l]||a.push(t),l++;return`${s}${a.join(bi.SEPARATOR)}`}return e.path()}static closestCommonParent(t,e){const n=this.parents(t).reverse().concat([t]),i=this.parents(e).reverse().concat([e]),s=Math.min(n.length,i.length);let r=null;for(let t=0;t{for(let n of e)this._is_reference_resolvable(n)&&t.push(n)}));for(let e of t)e.resolveMissingDependencies()}_is_reference_resolvable(t){const e=t.absolutePath();if(e){if(this.scene.node(e))return!0;{const t=bi.split_parent_child(e);if(t.child){const e=this.scene.node(t.parent);if(e){if(e.params.get(t.child))return!0}}}}}checkForMissingReferences(t){this._checkForMissingReferencesForNode(t);for(let e of t.params.all)this._checkForMissingReferencesForParam(e)}_checkForMissingReferencesForNode(t){const e=t.graphNodeId(),n=h.arrayFromValues(this.references);for(let i of n){let n=!1;const s=u.toArray(i);for(let e of s)e.matchesPath(t.path())&&(n=!0,e.resolveMissingDependencies());n&&this.references.delete(e)}}_checkForMissingReferencesForParam(t){const e=t.graphNodeId(),n=h.arrayFromValues(this.references);for(let i of n){let n=!1;const s=u.toArray(i);for(let e of s)e.matchesPath(t.path())&&(n=!0,e.resolveMissingDependencies());n&&this.references.delete(e)}}}class Ai{constructor(t){this.node=t,this._dirty_count=0,this._dirty=!0}dispose(){this._cached_successors=void 0,this._post_dirty_hooks=void 0,this._post_dirty_hook_names=void 0}isDirty(){return!0===this._dirty}dirtyTimestamp(){return this._dirty_timestamp}dirtyCount(){return this._dirty_count}addPostDirtyHook(t,e){this._post_dirty_hook_names=this._post_dirty_hook_names||[],this._post_dirty_hooks=this._post_dirty_hooks||[],this._post_dirty_hook_names.includes(t)?console.warn(`hook with name ${t} already exists`,this.node):(this._post_dirty_hook_names.push(t),this._post_dirty_hooks.push(e))}removePostDirtyHook(t){if(this._post_dirty_hook_names&&this._post_dirty_hooks){const e=this._post_dirty_hook_names.indexOf(t);e>=0&&(this._post_dirty_hook_names.splice(e,1),this._post_dirty_hooks.splice(e,1))}}hasHook(t){return!!this._post_dirty_hook_names&&this._post_dirty_hook_names.includes(t)}removeDirtyState(){this._dirty=!1}setForbiddenTriggerNodes(t){this._forbidden_trigger_nodes=t.map((t=>t.graphNodeId()))}setDirty(t,e){if(null==e&&(e=!0),t&&this._forbidden_trigger_nodes&&this._forbidden_trigger_nodes.includes(t.graphNodeId()))return;null==t&&(t=this.node),this._dirty=!0;const n=li.performance.performanceManager();this._dirty_timestamp=n.now(),this._dirty_count+=1,this.runPostDirtyHooks(t),!0===e&&this.setSuccessorsDirty(t)}runPostDirtyHooks(t){if(this._post_dirty_hooks){const e=this.node.scene().cooker;if(e.blocked)e.enqueue(this.node,t);else for(let e of this._post_dirty_hooks)e(t)}}setSuccessorsDirty(t){this._cached_successors=this._cached_successors||this.node.graphAllSuccessors();for(let e of this._cached_successors)e.dirtyController.setDirty(t,false)}clearSuccessorsCache(){this._cached_successors=void 0}clearSuccessorsCacheWithPredecessors(){this.clearSuccessorsCache();for(let t of this.node.graphAllPredecessors())t.dirtyController.clearSuccessorsCache()}}class Mi{constructor(t,e){this._scene=t,this._name=e,this._dirty_controller=new Ai(this),this._graph_node_id=t.graph.nextId(),t.graph.addNode(this),this._graph=t.graph}dispose(){this._dirty_controller.dispose(),this.graphRemove()}name(){return this._name}setName(t){this._name=t}scene(){return this._scene}graphNodeId(){return this._graph_node_id}get dirtyController(){return this._dirty_controller}setDirty(t){t=t||this,this._dirty_controller.setDirty(t)}setSuccessorsDirty(t){this._dirty_controller.setSuccessorsDirty(t)}removeDirtyState(){this._dirty_controller.removeDirtyState()}isDirty(){return this._dirty_controller.isDirty()}addPostDirtyHook(t,e){this._dirty_controller.addPostDirtyHook(t,e)}graphRemove(){this._graph.removeNode(this)}addGraphInput(t,e=!0){return this._graph.connect(t,this,e)}removeGraphInput(t){this._graph.disconnect(t,this)}graphDisconnectPredecessors(){this._graph.disconnectPredecessors(this)}graphDisconnectSuccessors(){this._graph.disconnectSuccessors(this)}graphPredecessorIds(){return this._graph.predecessorIds(this._graph_node_id)||[]}graphPredecessors(){return this._graph.predecessors(this)}graphSuccessors(){return this._graph.successors(this)}graphAllPredecessors(){return this._graph.allPredecessors(this)}graphAllSuccessors(){return this._graph.allSuccessors(this)}}var Ei;!function(t){t.CREATED=\\\\\\\"node_created\\\\\\\",t.DELETED=\\\\\\\"node_deleted\\\\\\\",t.NAME_UPDATED=\\\\\\\"node_name_update\\\\\\\",t.OVERRIDE_CLONABLE_STATE_UPDATE=\\\\\\\"node_override_clonable_state_update\\\\\\\",t.NAMED_OUTPUTS_UPDATED=\\\\\\\"node_named_outputs_updated\\\\\\\",t.NAMED_INPUTS_UPDATED=\\\\\\\"node_named_inputs_updated\\\\\\\",t.INPUTS_UPDATED=\\\\\\\"node_inputs_updated\\\\\\\",t.PARAMS_UPDATED=\\\\\\\"node_params_updated\\\\\\\",t.UI_DATA_POSITION_UPDATED=\\\\\\\"node_ui_data_position_updated\\\\\\\",t.UI_DATA_COMMENT_UPDATED=\\\\\\\"node_ui_data_comment_updated\\\\\\\",t.ERROR_UPDATED=\\\\\\\"node_error_updated\\\\\\\",t.FLAG_BYPASS_UPDATED=\\\\\\\"bypass_flag_updated\\\\\\\",t.FLAG_DISPLAY_UPDATED=\\\\\\\"display_flag_updated\\\\\\\",t.FLAG_OPTIMIZE_UPDATED=\\\\\\\"optimize_flag_updated\\\\\\\",t.SELECTION_UPDATED=\\\\\\\"selection_updated\\\\\\\"}(Ei||(Ei={}));class Si{constructor(t,e=0,n=0){this.node=t,this._position=new d.a,this._width=50,this._color=new D.a(.75,.75,.75),this._layout_vertical=!0,this._json={x:0,y:0},this._position.x=e,this._position.y=n}setComment(t){this._comment=t,this.node.emit(Ei.UI_DATA_COMMENT_UPDATED)}comment(){return this._comment}setColor(t){this._color=t}color(){return this._color}setLayoutHorizontal(){this._layout_vertical=!1}isLayoutVertical(){return this._layout_vertical}copy(t){this._position.copy(t.position()),this._color.copy(t.color())}position(){return this._position}setPosition(t,e=0){if(m.isNumber(t)){const n=t;this._position.set(n,e)}else this._position.copy(t);this.node.emit(Ei.UI_DATA_POSITION_UPDATED)}translate(t,e=!1){this._position.add(t),e&&(this._position.x=Math.round(this._position.x),this._position.y=Math.round(this._position.y)),this.node.emit(Ei.UI_DATA_POSITION_UPDATED)}toJSON(){return this._json.x=this._position.x,this._json.y=this._position.y,this._json.comment=this._comment,this._json}}class Ci{constructor(t){this.node=t,this._state=!0,this._hooks=null}onUpdate(t){this._hooks=this._hooks||[],this._hooks.push(t)}_on_update(){}set(t){this._state!=t&&(this._state=t,this._on_update(),this.runHooks())}active(){return this._state}toggle(){this.set(!this._state)}runHooks(){if(this._hooks)for(let t of this._hooks)t()}}class Ni extends Ci{constructor(){super(...arguments),this._state=!1}_on_update(){this.node.emit(Ei.FLAG_BYPASS_UPDATED),this.node.setDirty()}}class Li extends Ci{_on_update(){this.node.emit(Ei.FLAG_DISPLAY_UPDATED)}}class Oi extends Ci{constructor(){super(...arguments),this._state=!1}_on_update(){this.node.emit(Ei.FLAG_OPTIMIZE_UPDATED)}}class Pi{constructor(t){this.node=t}hasDisplay(){return!1}hasBypass(){return!1}hasOptimize(){return!1}}function Ri(t){return class extends t{constructor(){super(...arguments),this.display=new Li(this.node)}hasDisplay(){return!0}}}function Ii(t){return class extends t{constructor(){super(...arguments),this.bypass=new Ni(this.node)}hasBypass(){return!0}}}function Fi(t){return class extends t{constructor(){super(...arguments),this.optimize=new Oi(this.node)}hasOptimize(){return!0}}}class Di extends(Ri(Pi)){}class Bi extends(Ii(Pi)){}class zi extends(Ii(Ri(Pi))){}class ki extends(Fi(Ii(Pi))){}class Ui extends(Fi(Ii(Ri(Pi)))){}class Gi{constructor(t){this.node=t}}class Vi extends Gi{active(){return this.paramsTimeDependent()||this.inputsTimeDependent()}paramsTimeDependent(){const t=this.node.params.names;for(let e of t){const t=this.node.params.get(e);if(t&&t.states.timeDependent.active())return!0}return!1}inputsTimeDependent(){const t=this.node.io.inputs.inputs();for(let e of t)if(e&&e.states.timeDependent.active())return!0;return!1}forceTimeDependent(){const t=this.node.graphPredecessors().map((t=>t.graphNodeId())),e=this.node.scene().timeController.graphNode;t.includes(e.graphNodeId())||this.node.addGraphInput(e,!1)}unforceTimeDependent(){const t=this.node.scene().timeController.graphNode;this.node.removeGraphInput(t)}}class Hi extends Gi{set(t){this._message!=t&&(t&&li.error(`[${this.node.path()}] error: '${t}'`),this._message=t,this.onUpdate())}message(){return this._message}clear(){this.set(void 0)}active(){return null!=this._message}onUpdate(){null!=this._message&&this.node._setContainer(null,`from error '${this._message}'`),this.node.emit(Ei.ERROR_UPDATED)}}class ji{constructor(t){this.node=t,this.timeDependent=new Vi(this.node),this.error=new Hi(this.node)}}class Wi{constructor(t){this.node=t,this._graph_node=new Mi(t.scene(),\\\\\\\"node_name_controller\\\\\\\")}dispose(){this._graph_node.dispose(),this._on_set_name_hooks=void 0,this._on_set_fullPath_hooks=void 0}get graph_node(){return this._graph_node}static base_name(t){let e=t.type();const n=e[e.length-1];return m.isNaN(parseInt(n))||(e+=\\\\\\\"_\\\\\\\"),`${e}1`}requestNameToParent(t){const e=this.node.parent();e&&e.childrenAllowed()&&e.childrenController?e.childrenController.setChildName(this.node,t):console.warn(\\\\\\\"requestNameToParent failed, no parent found\\\\\\\")}setName(t){t!=this.node.name()&&this.requestNameToParent(t)}updateNameFromParent(t){var e;if(this.node._set_core_name(t),this._postSetName(),this.runPostSetFullPathHooks(),this.node.childrenAllowed()){const t=null===(e=this.node.childrenController)||void 0===e?void 0:e.children();if(t)for(let e of t)e.nameController.runPostSetFullPathHooks()}this.node.lifecycle.creationCompleted()&&(this.node.scene().missingExpressionReferencesController.checkForMissingReferences(this.node),this.node.scene().expressionsController.regenerateReferringExpressions(this.node)),this.node.scene().referencesController.notifyNameUpdated(this.node),this.node.emit(Ei.NAME_UPDATED)}add_post_set_name_hook(t){this._on_set_name_hooks=this._on_set_name_hooks||[],this._on_set_name_hooks.push(t)}add_post_set_fullPath_hook(t){this._on_set_fullPath_hooks=this._on_set_fullPath_hooks||[],this._on_set_fullPath_hooks.push(t)}_postSetName(){if(this._on_set_name_hooks)for(let t of this._on_set_name_hooks)t()}runPostSetFullPathHooks(){if(this._on_set_fullPath_hooks)for(let t of this._on_set_fullPath_hooks)t()}}class qi{constructor(t){this.node=t,this._parent=null}parent(){return this._parent}setParent(t){t!=this.node.parentController.parent()&&(this._parent=t,this._parent&&this.node.nameController.requestNameToParent(Wi.base_name(this.node)))}firstAncestorWithContext(t){return this._parent?this._parent.context()==t?this._parent:this._parent.parentController.firstAncestorWithContext(t):null}path(t){const e=bi.SEPARATOR;if(null!=this._parent){if(this._parent==t)return this.node.name();{const n=this._parent.path(t);return n===e?n+this.node.name():n+e+this.node.name()}}return e}onSetParent(){if(this._on_set_parent_hooks)for(let t of this._on_set_parent_hooks)t()}findNode(t){if(null==t)return null;if(t==bi.CURRENT||t==bi.CURRENT_WITH_SLASH)return this.node;if(t==bi.PARENT||t==bi.PARENT_WITH_SLASH)return this.node.parent();const e=bi.SEPARATOR;if(t===e)return this.node.scene().root();if(t[0]===e)return t=t.substring(1,t.length),this.node.scene().root().node(t);if(t.split){const n=t.split(e);if(1===n.length){const t=n[0];return this.node.childrenController?this.node.childrenController.childByName(t):null}return bi.findNode(this.node,t)}return console.error(\\\\\\\"unexpected path given:\\\\\\\",t),null}}const Xi=/[, ]/,Yi=/\\\\d+$/,$i=/^0+/,Ji=/,| /,Zi=/^-?\\\\d+\\\\.?\\\\d*$/;var Ki,Qi,ts,es,ns,is;!function(t){t.TRUE=\\\\\\\"true\\\\\\\",t.FALSE=\\\\\\\"false\\\\\\\"}(Ki||(Ki={}));class ss{static isBoolean(t){return t==Ki.TRUE||t==Ki.FALSE}static toBoolean(t){return t==Ki.TRUE}static isNumber(t){return Zi.test(t)}static tailDigits(t){const e=t.match(Yi);return e?parseInt(e[0]):0}static increment(t){const e=t.match(Yi);if(e){let n=e[0],i=\\\\\\\"\\\\\\\";const s=n.match($i);s&&(i=s[0]);const r=parseInt(n);0==r&&i.length>0&&\\\\\\\"0\\\\\\\"==i[i.length-1]&&(i=i.slice(0,-1));return`${t.substring(0,t.length-e[0].length)}${i}${r+1}`}return`${t}1`}static pluralize(t){return\\\\\\\"s\\\\\\\"!==t[t.length-1]?`${t}s`:t}static camelCase(t){const e=t.replace(/_/g,\\\\\\\" \\\\\\\").split(\\\\\\\" \\\\\\\");let n=\\\\\\\"\\\\\\\";for(let t=0;t0&&(i=this.upperFirst(i)),n+=i}return n}static upperFirst(t){return t[0].toUpperCase()+t.substr(1)}static titleize(t){return t.split(/\\\\s|_/g).map((t=>this.upperFirst(t))).join(\\\\\\\" \\\\\\\")}static precision(t,e=2){e=Math.max(e,0);const n=`${t}`.split(\\\\\\\".\\\\\\\");if(e<=0)return n[0];let i=n[1];if(void 0!==i)return i.length>e&&(i=i.substring(0,e)),i=i.padEnd(e,\\\\\\\"0\\\\\\\"),`${n[0]}.${i}`;{const n=`${t}.`,i=n.length+e;return n.padEnd(i,\\\\\\\"0\\\\\\\")}}static ensureFloat(t){const e=`${t}`;return e.indexOf(\\\\\\\".\\\\\\\")>=0?e:`${e}.0`}static ensureInteger(t){const e=`${t}`;return e.indexOf(\\\\\\\".\\\\\\\")>=0?e.split(\\\\\\\".\\\\\\\")[0]:e}static matchMask(t,e){if(\\\\\\\"*\\\\\\\"===e)return!0;if(t==e)return!0;const n=e.split(\\\\\\\" \\\\\\\");if(n.length>1){for(let e of n){if(this.matchMask(t,e))return!0}return!1}e=`^${e=e.split(\\\\\\\"*\\\\\\\").join(\\\\\\\".*\\\\\\\")}$`;return new RegExp(e).test(t)}static matchesOneMask(t,e){let n=!1;for(let i of e)ss.matchMask(t,i)&&(n=!0);return n}static attribNames(t){const e=t.split(Xi),n=new Set;for(let t of e)t=t.trim(),t.length>0&&n.add(t);const i=new Array(n.size);let s=0;return n.forEach((t=>{i[s]=t,s++})),i}static indices(t){const e=t.split(Ji);if(e.length>1){const t=e.flatMap((t=>this.indices(t)));return f.uniq(t).sort(((t,e)=>t-e))}{const t=e[0];if(t){const e=\\\\\\\"-\\\\\\\";if(t.indexOf(e)>0){const n=t.split(e);return f.range(parseInt(n[0]),parseInt(n[1])+1)}{const e=parseInt(t);return m.isNumber(e)?[e]:[]}}return[]}}static escapeLineBreaks(t){return t.replace(/(\\\\r\\\\n|\\\\n|\\\\r)/gm,\\\\\\\"\\\\\\\\n\\\\\\\")}static sanitizeName(t){return t=(t=t.replace(/[^A-Za-z0-9]/g,\\\\\\\"_\\\\\\\")).replace(/^[0-9]/,\\\\\\\"_\\\\\\\")}}class rs{constructor(t){this._node=t,this._node_ids=[],this._json=[]}node(){return this._node}nodes(){return this._node.scene().graph.nodesFromIds(this._node_ids)}contains(t){return this._node_ids.includes(t.graphNodeId())}equals(t){const e=t.map((t=>t.graphNodeId())).sort();return f.isEqual(e,this._node_ids)}clear(){this._node_ids=[],this.send_update_event()}set(t){this._node_ids=[],this.add(t)}add(t){const e=t.map((t=>t.graphNodeId()));this._node_ids=f.union(this._node_ids,e),this.send_update_event()}remove(t){const e=t.map((t=>t.graphNodeId()));this._node_ids=f.difference(this._node_ids,e),this.send_update_event()}send_update_event(){this._node.emit(Ei.SELECTION_UPDATED)}toJSON(){return this._json=this._json||[],this._json=this._node_ids.map((t=>t)),this._json}}!function(t){t.ALWAYS=\\\\\\\"always\\\\\\\",t.NEVER=\\\\\\\"never\\\\\\\",t.FROM_NODE=\\\\\\\"from_node\\\\\\\"}(Qi||(Qi={}));class os{static unreachable(t){throw new Error(\\\\\\\"Didn't expect to get here\\\\\\\")}}class as{constructor(t){this.inputs_controller=t,this._clone_required_states=[],this._overridden=!1}init_inputs_cloned_state(t){m.isArray(t)?this._cloned_states=t:this._cloned_state=t,this._update_clone_required_state()}override_cloned_state_allowed(){if(this._cloned_states)for(let t of this._cloned_states)if(t==Qi.FROM_NODE)return!0;return!!this._cloned_state&&this._cloned_state==Qi.FROM_NODE}clone_required_state(t){return this._clone_required_states[t]}clone_required_states(){return this._clone_required_states}_get_clone_required_state(t){const e=this._cloned_states;if(e){const n=e[t];if(null!=n)return this.clone_required_from_state(n)}return!this._cloned_state||this.clone_required_from_state(this._cloned_state)}clone_required_from_state(t){switch(t){case Qi.ALWAYS:return!0;case Qi.NEVER:return!1;case Qi.FROM_NODE:return!this._overridden}return os.unreachable(t)}override_cloned_state(t){this._overridden=t,this._update_clone_required_state()}overriden(){return this._overridden}_update_clone_required_state(){if(this._cloned_states){const t=[];for(let e=0;e=1:e;if(m.isString(e)){if(n){if(n instanceof yi)return n.set_path(e);if(n instanceof xi)return n.set_path(e)}return e}m.isArray(e)&&this.params[t].fromArray(e)}setInput(t,e){this._inputs=this._inputs||[],this._inputs[t]=e}inputs_count(){return this._inputs?this._inputs.length:0}inputsController(){return this._inputs_controller=this._inputs_controller||new ls(this)}_init_cloned_states(){const t=this.operation.constructor.INPUT_CLONED_STATE;this.inputsController().init_inputs_cloned_state(t)}input_clone_required(t){return!this._inputs_controller||this._inputs_controller.clone_required(t)}override_input_clone_state(t){this.inputsController().override_cloned_state(t)}cook(t){return this.operation.cook(t,this.params)}}{constructor(t,e,n){super(t,e,n),this.operation=t,this.name=e,this.init_params=n,this._inputs=[],this._current_input_index=0,this._dirty=!0}add_input(t){super.setInput(this._current_input_index,t),this.increment_input_index()}increment_input_index(){this._current_input_index++}current_input_index(){return this._current_input_index}setDirty(){if(!this._dirty){this._compute_result=void 0;for(let t=0;t{n[i]=t[e]}));for(let i=0;i{t.push(e)})),t}childrenNames(){const t=[];return this._childrenByName.forEach(((e,n)=>{t.push(n)})),t}traverseChildren(t){this._childrenByName.forEach((e=>{var n;t(e),null===(n=e.childrenController)||void 0===n||n.traverseChildren(t)}))}}class us{constructor(t){this.node=t,this._creation_completed=!1}dispose(){this._on_child_add_hooks=void 0,this._on_child_remove_hooks=void 0,this._on_create_hooks=void 0,this._on_add_hooks=void 0,this._on_delete_hooks=void 0}setCreationCompleted(){this._creation_completed||(this._creation_completed=!0)}creationCompleted(){return this.node.scene().loadingController.loaded()&&this._creation_completed}add_on_child_add_hook(t){this._on_child_add_hooks=this._on_child_add_hooks||[],this._on_child_add_hooks.push(t)}run_on_child_add_hooks(t){this.execute_hooks_with_child_node(this._on_child_add_hooks,t)}add_on_child_remove_hook(t){this._on_child_remove_hooks=this._on_child_remove_hooks||[],this._on_child_remove_hooks.push(t)}run_on_child_remove_hooks(t){this.execute_hooks_with_child_node(this._on_child_remove_hooks,t)}add_on_create_hook(t){this._on_create_hooks=this._on_create_hooks||[],this._on_create_hooks.push(t)}run_on_create_hooks(){this.execute_hooks(this._on_create_hooks)}add_on_add_hook(t){this._on_add_hooks=this._on_add_hooks||[],this._on_add_hooks.push(t)}run_on_add_hooks(){this.execute_hooks(this._on_add_hooks)}add_delete_hook(t){this._on_delete_hooks=this._on_delete_hooks||[],this._on_delete_hooks.push(t)}run_on_delete_hooks(){this.execute_hooks(this._on_delete_hooks)}execute_hooks(t){if(t){let e;for(e of t)e()}}execute_hooks_with_child_node(t,e){if(t){let n;for(n of t)n(e)}}}!function(t){t.ANIM=\\\\\\\"anim\\\\\\\",t.COP=\\\\\\\"cop\\\\\\\",t.EVENT=\\\\\\\"event\\\\\\\",t.GL=\\\\\\\"gl\\\\\\\",t.JS=\\\\\\\"js\\\\\\\",t.MANAGER=\\\\\\\"manager\\\\\\\",t.MAT=\\\\\\\"mat\\\\\\\",t.OBJ=\\\\\\\"obj\\\\\\\",t.POST=\\\\\\\"post\\\\\\\",t.ROP=\\\\\\\"rop\\\\\\\",t.SOP=\\\\\\\"sop\\\\\\\"}(ts||(ts={})),function(t){t.ANIM=\\\\\\\"animationsNetwork\\\\\\\",t.COP=\\\\\\\"copNetwork\\\\\\\",t.EVENT=\\\\\\\"eventsNetwork\\\\\\\",t.MAT=\\\\\\\"materialsNetwork\\\\\\\",t.POST=\\\\\\\"postProcessNetwork\\\\\\\",t.ROP=\\\\\\\"renderersNetwork\\\\\\\"}(es||(es={})),function(t){t.INPUT=\\\\\\\"subnetInput\\\\\\\",t.OUTPUT=\\\\\\\"subnetOutput\\\\\\\"}(ns||(ns={})),function(t){t.PERSPECTIVE=\\\\\\\"perspectiveCamera\\\\\\\",t.ORTHOGRAPHIC=\\\\\\\"orthographicCamera\\\\\\\"}(is||(is={}));const ds=[is.ORTHOGRAPHIC,is.PERSPECTIVE];var ps,_s;!function(t){t.ATTRIBUTE=\\\\\\\"attribute\\\\\\\"}(ps||(ps={})),function(t){t.DEVICE_ORIENTATION=\\\\\\\"cameraDeviceOrientationControls\\\\\\\",t.MAP=\\\\\\\"cameraMapControls\\\\\\\",t.ORBIT=\\\\\\\"cameraOrbitControls\\\\\\\",t.FIRST_PERSON=\\\\\\\"firstPersonControls\\\\\\\",t.PLAYER=\\\\\\\"playerControls\\\\\\\",t.MOBILE_JOYSTICK=\\\\\\\"mobileJoystickControls\\\\\\\"}(_s||(_s={}));const ms=[_s.DEVICE_ORIENTATION,_s.MAP,_s.ORBIT,_s.FIRST_PERSON,_s.MOBILE_JOYSTICK];class fs{constructor(t){this._node=t}set_node(t){this._node=t}node(){return this._node}set_content(t){this._content=t,this._post_set_content()}has_content(){return null!=this._content}content(){return this._content}_post_set_content(){}coreContent(){return this._content}coreContentCloned(){return this._content}infos(){return[]}}var gs=n(69);class vs extends Q.a{constructor(){super(),this.type=\\\\\\\"Scene\\\\\\\",this.background=null,this.environment=null,this.fog=null,this.overrideMaterial=null,this.autoUpdate=!0,\\\\\\\"undefined\\\\\\\"!=typeof __THREE_DEVTOOLS__&&__THREE_DEVTOOLS__.dispatchEvent(new CustomEvent(\\\\\\\"observe\\\\\\\",{detail:this}))}copy(t,e){return super.copy(t,e),null!==t.background&&(this.background=t.background.clone()),null!==t.environment&&(this.environment=t.environment.clone()),null!==t.fog&&(this.fog=t.fog.clone()),null!==t.overrideMaterial&&(this.overrideMaterial=t.overrideMaterial.clone()),this.autoUpdate=t.autoUpdate,this.matrixAutoUpdate=t.matrixAutoUpdate,this}toJSON(t){const e=super.toJSON(t);return null!==this.fog&&(e.object.fog=this.fog.toJSON()),e}}vs.prototype.isScene=!0;var ys=n(49),xs=n(52),bs=n(42),ws=n(55),Ts=n(62),As=n(24),Ms=n(35);const Es=new p.a,Ss=new p.a;class Cs extends Q.a{constructor(){super(),this._currentLevel=0,this.type=\\\\\\\"LOD\\\\\\\",Object.defineProperties(this,{levels:{enumerable:!0,value:[]},isLOD:{value:!0}}),this.autoUpdate=!0}copy(t){super.copy(t,!1);const e=t.levels;for(let t=0,n=e.length;t0){let n,i;for(n=1,i=e.length;n0){Es.setFromMatrixPosition(this.matrixWorld);const n=t.ray.origin.distanceTo(Es);this.getObjectForDistance(n).raycast(t,e)}}update(t){const e=this.levels;if(e.length>1){Es.setFromMatrixPosition(t.matrixWorld),Ss.setFromMatrixPosition(this.matrixWorld);const n=Es.distanceTo(Ss)/t.zoom;let i,s;for(e[0].object.visible=!0,i=1,s=e.length;i=e[i].distance;i++)e[i-1].object.visible=!1,e[i].object.visible=!0;for(this._currentLevel=i-1;in?n:t}static fit01(t,e,n){return this.fit(t,0,1,e,n)}static fit(t,e,n,i,s){return(t-e)/(n-e)*(s-i)+i}static blend(t,e,n){return(1-n)*t+n*e}static degrees_to_radians(t){return t*rr}static radians_to_degrees(t){return t/rr}static deg2rad(t){return this.degrees_to_radians(t)}static rad2deg(t){return this.radians_to_degrees(t)}static rand(t){return m.isNumber(t)?this.randFloat(t):this.randVec2(t)}static round(t,e){const n=t/e;return(t<0?Math.ceil(n):Math.floor(n))*e}static highest_even(t){return 2*Math.ceil(.5*t)}static randFloat(t,e=136574){return this._vec.x=t,this._vec.y=e,this.randVec2(this._vec)}static randVec2(t){const e=(12.9898*t.x+78.233*t.y)%Math.PI;return this.fract(43758.5453*Math.sin(e))}static geodesic_distance(t,e){var n=this.deg2rad(t.lat),i=this.deg2rad(e.lat),s=this.deg2rad(e.lat-t.lat),r=this.deg2rad(e.lng-t.lng),o=Math.sin(s/2)*Math.sin(s/2)+Math.cos(n)*Math.cos(i)*Math.sin(r/2)*Math.sin(r/2);return 6371e3*(2*Math.atan2(Math.sqrt(o),Math.sqrt(1-o)))}static expand_triangle(t,e){t.getMidpoint(this._triangle_mid),this._triangle_mid_to_corner.copy(t.a).sub(this._triangle_mid),this._triangle_mid_to_corner.normalize().multiplyScalar(e),t.a.add(this._triangle_mid_to_corner),this._triangle_mid_to_corner.copy(t.b).sub(this._triangle_mid),this._triangle_mid_to_corner.normalize().multiplyScalar(e),t.b.add(this._triangle_mid_to_corner),this._triangle_mid_to_corner.copy(t.c).sub(this._triangle_mid),this._triangle_mid_to_corner.normalize().multiplyScalar(e),t.c.add(this._triangle_mid_to_corner)}static nearestPower2(t){return Math.pow(2,Math.ceil(Math.log(t)/Math.log(2)))}}or.Easing=sr,or.fract=t=>t-Math.floor(t),or._vec={x:0,y:136574},or._triangle_mid=new p.a,or._triangle_mid_to_corner=new p.a;class ar{constructor(t,e){this._coreGeometry=t,this._index=e,this._geometry=this._coreGeometry.geometry()}index(){return this._index}points(){return this._points=this._points||this._get_points()}applyMatrix4(t){for(let e of this.points())e.applyMatrix4(t)}_get_points(){var t;const e=(null===(t=this._geometry.index)||void 0===t?void 0:t.array)||[],n=3*this._index;return[new Qs(this._coreGeometry,e[n+0]),new Qs(this._coreGeometry,e[n+1]),new Qs(this._coreGeometry,e[n+2])]}positions(){return this._positions=this._positions||this._getPositions()}_getPositions(){const t=this.points();return[t[0].position(),t[1].position(),t[2].position()]}triangle(){return this._triangle=this._triangle||this._get_triangle()}_get_triangle(){const t=this.positions();return new tr.a(t[0],t[1],t[2])}deltas(){return this._deltas=this._deltas||this._getDeltas()}_getDeltas(){const t=this.positions();return[t[1].clone().sub(t[0]),t[2].clone().sub(t[0])]}area(){return this.triangle().getArea()}center(t){const e=this.positions();return t.x=(e[0].x+e[1].x+e[2].x)/3,t.y=(e[0].y+e[1].y+e[2].y)/3,t.z=(e[0].z+e[1].z+e[2].z)/3,t}randomPosition(t){let e=[or.randFloat(t),or.randFloat(6541*t)];return e[0]+e[1]>1&&(e[0]=1-e[0],e[1]=1-e[1]),this.positions()[0].clone().add(this.deltas()[0].clone().multiplyScalar(e[0])).add(this.deltas()[1].clone().multiplyScalar(e[1]))}attribValueAtPosition(t,e){const n=new p.a;this.triangle().getBarycoord(e,n);const i=n.toArray(),s=this._geometry.attributes[t].itemSize,r=this.points().map((e=>e.attribValue(t)));let o,a,l=0;switch(s){case 1:a=0;for(let t of r)a+=t*i[l],l++;o=a;break;default:for(let t of r){const e=t.multiplyScalar(i[l]);a?a.add(e):a=e,l++}o=a}return o}static interpolatedValue(t,e,n,i){const s=[e.a,e.b,e.c],r=t.getAttribute(\\\\\\\"position\\\\\\\").array,o=s.map((t=>new p.a(r[3*t+0],r[3*t+1],r[3*t+2]))),a=i.itemSize,l=i.array;let c=[];switch(a){case 1:c=s.map((t=>l[t]));break;case 2:c=s.map((t=>new d.a(l[2*t+0],l[2*t+1])));break;case 3:c=s.map((t=>new p.a(l[3*t+0],l[3*t+1],l[3*t+2])))}const h=s.map(((t,e)=>n.distanceTo(o[e]))),u=f.sum([h[0]*h[1],h[0]*h[2],h[1]*h[2]]),_=[h[1]*h[2]/u,h[0]*h[2]/u,h[0]*h[1]/u];let m;switch(a){case 1:m=f.sum(s.map(((t,e)=>_[e]*c[e])));break;default:var g=s.map(((t,e)=>c[e].multiplyScalar(_[e])));m=null;for(let t of g)m?m.add(t):m=t}return m}}class lr{from_points(t){t=this._filter_points(t);const e=new S.a,n=new fr(e),i=t[0];if(null!=i){const s=i.geometry(),r=i.coreGeometry(),o={};for(let e=0;et.indexedAttribValue(i)))),r={};s.forEach(((t,e)=>r[t]=e)),n.userDataAttribs()[i]=s;const o=[];for(let e of t){const t=r[e.indexedAttribValue(i)];o.push(t)}e.setAttribute(i,new C.c(o,1))}else{const n=l[i].itemSize,s=new Array(t.length*n);switch(n){case 1:for(let e=0;enew fr(t))),n=e[0].indexedAttributeNames(),i={};for(let t of n){const n={},s=[];for(let i of e){const e=i.points();for(let i of e){s.push(i);const e=i.indexedAttribValue(t);null!=n[e]?n[e]:n[e]=Object.keys(n).length}}const r=Object.keys(n);for(let e of s){const i=n[e.indexedAttribValue(t)];e.setAttribIndex(t,i)}i[t]=r}const s=ur(t),r=new fr(s);return Object.keys(i).forEach((t=>{const e=i[t];r.setIndexedAttributeValues(t,e)})),s&&delete s.userData.mergedUserData,s}}const mr=\\\\\\\"indexed_attrib_values\\\\\\\";class fr{constructor(t){this._geometry=t}geometry(){return this._geometry}uuid(){return this._geometry.uuid}boundingBox(){return this._bounding_box=this._bounding_box||this._create_bounding_box()}_create_bounding_box(){if(this._geometry.computeBoundingBox(),this._geometry.boundingBox)return this._geometry.boundingBox}markAsInstance(){this._geometry.userData.isInstance=!0}static markedAsInstance(t){return!0===t.userData.isInstance}markedAsInstance(){return fr.markedAsInstance(this._geometry)}positionAttribName(){let t=\\\\\\\"position\\\\\\\";return this.markedAsInstance()&&(t=\\\\\\\"instancePosition\\\\\\\"),t}computeVertexNormals(){this._geometry.computeVertexNormals()}userDataAttribs(){return this._geometry.userData[mr]=this._geometry.userData[mr]||{}}indexedAttributeNames(){return Object.keys(this.userDataAttribs()||{})}userDataAttrib(t){return t=Xs.remapName(t),this.userDataAttribs()[t]}isAttribIndexed(t){return t=Xs.remapName(t),null!=this.userDataAttrib(t)}hasAttrib(t){return\\\\\\\"ptnum\\\\\\\"===t||(t=Xs.remapName(t),null!=this._geometry.attributes[t])}attribType(t){return this.isAttribIndexed(t)?zs.STRING:zs.NUMERIC}static attribNames(t){return Object.keys(t.attributes)}attribNames(){return fr.attribNames(this._geometry)}static attribNamesMatchingMask(t,e){const n=ss.attribNames(e),i=[];for(let e of this.attribNames(t))for(let t of n)ss.matchMask(e,t)&&i.push(e);return f.uniq(i)}attribSizes(){const t={};for(let e of this.attribNames())t[e]=this._geometry.attributes[e].itemSize;return t}attribSize(t){let e;return t=Xs.remapName(t),null!=(e=this._geometry.attributes[t])?e.itemSize:\\\\\\\"ptnum\\\\\\\"===t?1:0}setIndexedAttributeValues(t,e){this.userDataAttribs()[t]=e}setIndexedAttribute(t,e,n){this.setIndexedAttributeValues(t,e),this._geometry.setAttribute(t,new C.f(n,1))}addNumericAttrib(t,e=1,n=0){const i=[];let s=!1;if(m.isNumber(n)){for(let t=0;t1)if(m.isArray(n)){for(let t=0;tnew ar(this,t)))}}var gr;fr._mesh_builder=new class extends lr{_filter_points(t){var e;const n=t[0];if(n){const i=null===(e=n.geometry().getIndex())||void 0===e?void 0:e.array;if(i){const e={};for(let n of t)e[n.index()]=n;const n=[],s=i.length;let r,o,a;for(let t=0;t{};class yr{static node(t,e){return t.node(e.name)}static clone(t){const e=t.clone(),n=t.uniforms;return n&&(e.uniforms=I.clone(n)),e}static add_user_data_render_hook(t,e){t.userData.POLY_render_hook=e}static apply_render_hook(t,e){if(e.userData){const n=e.userData.POLY_render_hook;if(n)return void(t.onBeforeRender=(e,i,s,r,o,a)=>{n(e,i,s,r,o,a,t)})}t.onBeforeRender=vr}static applyCustomMaterials(t,e){const n=e;if(n.customMaterials)for(let e of Object.keys(n.customMaterials)){const i=e,s=n.customMaterials[i];s&&(t[i]=s,s.needsUpdate=!0)}}static assign_custom_uniforms(t,e,n){const i=t;if(i.customMaterials)for(let t of Object.keys(i.customMaterials)){const s=t,r=i.customMaterials[s];r&&(r.uniforms[e].value=n)}}static init_custom_material_uniforms(t,e,n){const i=t;if(i.customMaterials)for(let t of Object.keys(i.customMaterials)){const s=t,r=i.customMaterials[s];r&&(r.uniforms[e]=r.uniforms[e]||n)}}}const xr=\\\\\\\"name\\\\\\\";class br extends Ys{constructor(t,e){super(e),this._object=t,null==this._object.userData.attributes&&(this._object.userData.attributes={})}object(){return this._object}geometry(){return this._object.geometry}coreGeometry(){const t=this.geometry();return t?new fr(t):null}points(){var t;return(null===(t=this.coreGeometry())||void 0===t?void 0:t.points())||[]}pointsFromGroup(t){if(t){const e=ss.indices(t);if(e){const t=this.points();return e.map((e=>t[e]))}return[]}return this.points()}static isInGroup(t,e){const n=t.trim();if(0==n.length)return!0;const i=n.split(\\\\\\\"=\\\\\\\"),s=i[0];if(\\\\\\\"@\\\\\\\"==s[0]){const t=s.substr(1);return i[1]==this.attribValue(e,t)}return!1}computeVertexNormals(){var t;null===(t=this.coreGeometry())||void 0===t||t.computeVertexNormals()}static _convert_array_to_vector(t){switch(t.length){case 1:return t[0];case 2:return new d.a(t[0],t[1]);case 3:return new p.a(t[0],t[1],t[2]);case 4:return new _.a(t[0],t[1],t[2],t[3])}}static addAttribute(t,e,n){if(m.isArray(n)){if(!this._convert_array_to_vector(n)){const t=\\\\\\\"attribute_value invalid\\\\\\\";throw console.error(t,n),new Error(t)}}const i=n,s=t.userData;s.attributes=s.attributes||{},s.attributes[e]=i}addAttribute(t,e){br.addAttribute(this._object,t,e)}addNumericAttrib(t,e){this.addAttribute(t,e)}setAttribValue(t,e){this.addAttribute(t,e)}addNumericVertexAttrib(t,e,n){var i;null==n&&(n=Xs.default_value(e)),null===(i=this.coreGeometry())||void 0===i||i.addNumericAttrib(t,e,n)}attributeNames(){return Object.keys(this._object.userData.attributes)}attribNames(){return this.attributeNames()}hasAttrib(t){return this.attributeNames().includes(t)}renameAttrib(t,e){const n=this.attribValue(t);null!=n?(this.addAttribute(e,n),this.deleteAttribute(t)):console.warn(`attribute ${t} not found`)}deleteAttribute(t){delete this._object.userData.attributes[t]}static attribValue(t,e,n=0,i){if(\\\\\\\"ptnum\\\\\\\"===e)return n;if(t.userData&&t.userData.attributes){const n=t.userData.attributes[e];if(null==n){if(e==xr)return t.name}else if(m.isArray(n)&&i)return i.fromArray(n),i;return n}return e==xr?t.name:void 0}static stringAttribValue(t,e,n=0){const i=this.attribValue(t,e,n);if(null!=i)return m.isString(i)?i:`${i}`}attribValue(t,e){return br.attribValue(this._object,t,this._index,e)}stringAttribValue(t){return br.stringAttribValue(this._object,t,this._index)}name(){return this.attribValue(xr)}humanType(){return js.CONSTRUCTOR_NAMES_BY_CONSTRUCTOR_NAME[this._object.constructor.name]}attribTypes(){const t={};for(let e of this.attribNames()){const n=this.attribType(e);null!=n&&(t[e]=n)}return t}attribType(t){const e=this.attribValue(t);return m.isString(e)?zs.STRING:zs.NUMERIC}attribSizes(){const t={};for(let e of this.attribNames()){const n=this.attribSize(e);null!=n&&(t[e]=n)}return t}attribSize(t){const e=this.attribValue(t);return null==e?null:Xs.attribSizeFromValue(e)}clone(){return br.clone(this._object)}static clone(t){const e=t.clone();var n=new Map,i=new Map;return br.parallelTraverse(t,e,(function(t,e){n.set(e,t),i.set(t,e)})),e.traverse((function(e){const s=n.get(e),r=e;if(r.geometry){const t=s.geometry;r.geometry=fr.clone(t);const e=r.geometry;e.userData&&(e.userData=b.cloneDeep(t.userData))}if(r.material){r.material=s.material,yr.applyCustomMaterials(e,r.material);const t=r.material;null==t.color&&(t.color=new D.a(1,1,1))}t.userData&&(e.userData=b.cloneDeep(s.userData));const o=s;o.animations&&(e.animations=o.animations.map((t=>t.clone())));const a=e;if(a.isSkinnedMesh){var l=a,c=s,h=c.skeleton.bones;l.skeleton=c.skeleton.clone(),l.bindMatrix.copy(c.bindMatrix);const t=h.map((function(t){return i.get(t)}));l.skeleton.bones=t,l.bind(l.skeleton,l.bindMatrix)}})),e}static parallelTraverse(t,e,n){n(t,e);for(var i=0;i{const i=e.attributes[n];t[n]=i.itemSize})),t}objectAttributeSizesByName(){let t={};const e=this.firstCoreObject();if(e){const n=e.attribNames();for(let i of n){const n=e.attribSize(i);null!=n&&(t[i]=n)}}return t}pointAttributeTypesByName(){let t={};const e=this.firstGeometry();if(e){const n=new fr(e);Object.keys(e.attributes).forEach((e=>{t[e]=n.attribType(e)}))}return t}objectAttributeTypesByName(){let t={};const e=this.firstCoreObject();if(e)for(let n of e.attribNames())t[n]=e.attribType(n);return t}objectAttributeNames(){let t=[];const e=this.firstObject();return e&&(t=Object.keys(e.userData.attributes||{})),t}pointsCount(){return this._content?this._content.pointsCount():0}totalPointsCount(){return this._content?this._content.totalPointsCount():0}objectsData(){return this._content?this._content.objectsData():[]}boundingBox(t=!1){return this._content.boundingBox(t)}center(){return this._content.center()}size(){return this._content.size()}}};class Tr{constructor(t){this.node=t,this._callbacks=[],this._callbacks_tmp=[];const e=wr[t.context()];this._container=new e(this.node)}container(){return this._container}async compute(){var t,e;if(null===(e=null===(t=this.node.flags)||void 0===t?void 0:t.bypass)||void 0===e?void 0:e.active()){const t=await this.requestInputContainer(0)||this._container;return this.node.cookController.endCook(),t}return this.node.isDirty()?new Promise(((t,e)=>{this._callbacks.push(t),this.node.cookController.cookMain()})):this._container}async requestInputContainer(t){const e=this.node.io.inputs.input(t);return e?await e.compute():(this.node.states.error.set(`input ${t} required`),this.notifyRequesters(),null)}notifyRequesters(t){let e;for(this._callbacks_tmp=this._callbacks.slice(),this._callbacks.splice(0,this._callbacks.length),t||(t=this.node.containerController.container());e=this._callbacks_tmp.pop();)e(t);this.node.scene().cookController.removeNode(this.node)}}const Ar=li.performance.performanceManager();class Mr{constructor(t){this.cookController=t,this._inputs_start=0,this._params_start=0,this._cook_start=0,this._cooksCount=0,this._data={inputsTime:0,paramsTime:0,cookTime:0}}cooksCount(){return this._cooksCount}data2(){return this._data}active(){return this.cookController.performanceRecordStarted()}recordInputsStart(){this.active()&&(this._inputs_start=Ar.now())}recordInputsEnd(){this.active()&&(this._data.inputsTime=Ar.now()-this._inputs_start)}recordParamsStart(){this.active()&&(this._params_start=Ar.now())}recordParamsEnd(){this.active()&&(this._data.paramsTime=Ar.now()-this._params_start)}recordCookStart(){this.active()&&(this._cook_start=Ar.now())}recordCookEnd(){this.active()&&(this._data.cookTime=Ar.now()-this._cook_start,this._cooksCount+=1)}}class Er{constructor(t){this.node=t,this._cooking=!1,this._performanceController=new Mr(this),this._inputs_evaluation_required=!0,this._core_performance=this.node.scene().performance}performanceRecordStarted(){return this._core_performance.started()}disallowInputsEvaluation(){this._inputs_evaluation_required=!1}isCooking(){return!0===this._cooking}_start_cook_if_no_errors(t){if(this.node.states.error.active())this.endCook();else try{this._performanceController.recordCookStart(),this.node.cook(t)}catch(t){this.node.states.error.set(`node internal error: '${t}'.`),li.warn(t),this.endCook()}}async cookMain(){if(this.isCooking())return;let t;this._initCookingState(),this.node.states.error.clear(),this.node.scene().cookController.addNode(this.node),t=this._inputs_evaluation_required?await this._evaluateInputs():[],this.node.params.paramsEvalRequired()&&await this._evaluateParams(),this._start_cook_if_no_errors(t)}async cookMainWithoutInputs(){this.node.scene().cookController.addNode(this.node),this.isCooking()?li.warn(\\\\\\\"cook_main_without_inputs already cooking\\\\\\\",this.node.path()):(this._initCookingState(),this.node.states.error.clear(),this.node.params.paramsEvalRequired()&&await this._evaluateParams(),this._start_cook_if_no_errors([]))}endCook(t){this._finalizeCookPerformance();const e=this.node.dirtyController.dirtyTimestamp();null==e||e===this._cooking_dirty_timestamp?(this.node.removeDirtyState(),this._terminateCookProcess()):(li.log(\\\\\\\"COOK AGAIN\\\\\\\",e,this._cooking_dirty_timestamp,this.node.path()),this._cooking=!1,this.cookMain())}_initCookingState(){this._cooking=!0,this._cooking_dirty_timestamp=this.node.dirtyController.dirtyTimestamp()}_terminateCookProcess(){this.isCooking()&&(this._cooking=!1,this.node.containerController.notifyRequesters(),this._run_on_cook_complete_hooks())}async _evaluateInputs(){this._performanceController.recordInputsStart();let t=[];const e=this.node.io.inputs;this._inputs_evaluation_required&&(t=e.is_any_input_dirty()?await e.eval_required_inputs():await e.containers_without_evaluation());const n=e.inputs(),i=[];let s;for(let r=0;rt.graphNodeId()))}maxInputsCount(){return this.node.io.inputs.maxInputsCount()}inputIds(){return this.node.io.inputs.inputs().map((t=>null!=t?t.graphNodeId():void 0))}inputConnectionOutputIndices(){var t;return null===(t=this.node.io.connections.inputConnections())||void 0===t?void 0:t.map((t=>null!=t?t.output_index:void 0))}namedInputConnectionPoints(){return this.node.io.inputs.namedInputConnectionPoints().map((t=>t.toJSON()))}namedOutputConnectionPoints(){return this.node.io.outputs.namedOutputConnectionPoints().map((t=>t.toJSON()))}to_json_params_from_names(t,e=!1){return t.map((t=>this.node.params.get(t).graphNodeId()))}to_json_params(t=!1){return this.to_json_params_from_names(this.node.params.names,t)}}var Cr,Nr;!function(t){t.BOOLEAN=\\\\\\\"boolean\\\\\\\",t.BUTTON=\\\\\\\"button\\\\\\\",t.COLOR=\\\\\\\"color\\\\\\\",t.FLOAT=\\\\\\\"float\\\\\\\",t.FOLDER=\\\\\\\"folder\\\\\\\",t.INTEGER=\\\\\\\"integer\\\\\\\",t.OPERATOR_PATH=\\\\\\\"operator_path\\\\\\\",t.PARAM_PATH=\\\\\\\"param_path\\\\\\\",t.NODE_PATH=\\\\\\\"node_path\\\\\\\",t.RAMP=\\\\\\\"ramp\\\\\\\",t.STRING=\\\\\\\"string\\\\\\\",t.VECTOR2=\\\\\\\"vector2\\\\\\\",t.VECTOR3=\\\\\\\"vector3\\\\\\\",t.VECTOR4=\\\\\\\"vector4\\\\\\\"}(Cr||(Cr={})),function(t){t.VISIBLE_UPDATED=\\\\\\\"param_visible_updated\\\\\\\",t.RAW_INPUT_UPDATED=\\\\\\\"raw_input_updated\\\\\\\",t.VALUE_UPDATED=\\\\\\\"param_value_updated\\\\\\\",t.EXPRESSION_UPDATED=\\\\\\\"param_expression_update\\\\\\\",t.ERROR_UPDATED=\\\\\\\"param_error_updated\\\\\\\",t.DELETED=\\\\\\\"param_deleted\\\\\\\"}(Nr||(Nr={}));const Lr=\\\\\\\"dependentOnFoundNode\\\\\\\",Or=\\\\\\\"visibleIf\\\\\\\";var Pr,Rr;!function(t){t.TYPESCRIPT=\\\\\\\"typescript\\\\\\\"}(Pr||(Pr={})),function(t){t.AUDIO=\\\\\\\"audio\\\\\\\",t.TEXTURE_IMAGE=\\\\\\\"texture_image\\\\\\\",t.TEXTURE_VIDEO=\\\\\\\"texture_video\\\\\\\",t.GEOMETRY=\\\\\\\"geometry\\\\\\\",t.FONT=\\\\\\\"font\\\\\\\",t.SVG=\\\\\\\"svg\\\\\\\",t.JSON=\\\\\\\"json\\\\\\\"}(Rr||(Rr={}));class Ir{constructor(t){this._param=t,this._programatic_visible_state=!0,this._callbackAllowed=!1,this._updateVisibilityAndRemoveDirtyBound=this.updateVisibilityAndRemoveDirty.bind(this),this._ui_data_dependency_set=!1}dispose(){var t;try{this._options.callback=void 0,this._options.callbackString=void 0}catch(t){}null===(t=this._visibility_graph_node)||void 0===t||t.dispose()}set(t){this._default_options=t,this._options=b.cloneDeep(this._default_options),this.post_set_options()}copy(t){this._default_options=b.cloneDeep(t.default()),this._options=b.cloneDeep(t.current()),this.post_set_options()}setOption(t,e){if(this._options[t]=e,this._param.components)for(let n of this._param.components)n.options.setOption(t,e)}post_set_options(){this._handleComputeOnDirty()}param(){return this._param}node(){return this._param.node}default(){return this._default_options}current(){return this._options}hasOptionsOverridden(){return!b.isEqual(this._options,this._default_options)}overriddenOptions(){const t={},e=Object.keys(this._options);for(let n of e)if(!b.isEqual(this._options[n],this._default_options[n])){const e=b.cloneDeep(this._options[n]);Object.assign(t,{[n]:e})}return t}overriddenOptionNames(){return Object.keys(this.overriddenOptions())}computeOnDirty(){return this._options.computeOnDirty||!1}_handleComputeOnDirty(){this.computeOnDirty()&&(this._computeOnDirty_callback_added||(this.param().addPostDirtyHook(\\\\\\\"computeOnDirty\\\\\\\",this._computeParam.bind(this)),this._computeOnDirty_callback_added=!0))}async _computeParam(){await this.param().compute()}hasCallback(){return null!=this._options.callback||null!=this._options.callbackString}allowCallback(){this._callbackAllowed=!0}executeCallback(){if(!this._callbackAllowed)return;if(!this.node())return;const t=this.getCallback();if(!t)return;if(!this.node().scene().loadingController.loaded())return;const e=this.param().parent_param;e?e.options.executeCallback():t(this.node(),this.param())}getCallback(){if(this.hasCallback())return this._options.callback=this._options.callback||this.createCallbackFromString()}createCallbackFromString(){const t=this._options.callbackString;if(t){const e=new Function(\\\\\\\"node\\\\\\\",\\\\\\\"scene\\\\\\\",\\\\\\\"window\\\\\\\",\\\\\\\"location\\\\\\\",t);return()=>{e(this.node(),this.node().scene(),null,null)}}}colorConversion(){return this._options.conversion}makesNodeDirtyWhenDirty(){let t;if(null!=this.param().parent_param)return!1;let e=!0;return null!=(t=this._options.cook)&&(e=t),e}fileBrowseOption(){return this._options.fileBrowse}fileBrowseAllowed(){return null!=this.fileBrowseOption()}fileBrowseType(){const t=this.fileBrowseOption();return t?t.type:null}separatorBefore(){return this._options.separatorBefore}separatorAfter(){return this._options.separatorAfter}isExpressionForEntities(){const t=this._options.expression;return t&&t.forEntities||!1}level(){return this._options.level||0}hasMenu(){return null!=this.menuOptions()||null!=this.menuStringOptions()}menuOptions(){return this._options.menu}menuStringOptions(){return this._options.menuString}menuEntries(){const t=this.menuOptions()||this.menuStringOptions();return t?t.entries:[]}isMultiline(){return!0===this._options.multiline}language(){return this._options.language}isCode(){return null!=this.language()}nodeSelectionOptions(){return this._options.nodeSelection}nodeSelectionContext(){const t=this.nodeSelectionOptions();if(t)return t.context}nodeSelectionTypes(){const t=this.nodeSelectionOptions();if(t)return t.types}dependentOnFoundNode(){return!(Lr in this._options)||this._options.dependentOnFoundNode}isSelectingParam(){return null!=this.paramSelectionOptions()}paramSelectionOptions(){return this._options.paramSelection}paramSelectionType(){const t=this.paramSelectionOptions();if(t){const e=t;if(!m.isBoolean(e))return e}}range(){return this._options.range||[0,1]}step(){return this._options.step}rangeLocked(){return this._options.rangeLocked||[!1,!1]}ensureInRange(t){const e=this.range();return t>=e[0]&&t<=e[1]?t:tObject.keys(t))).flat()):Object.keys(t);const n=this.param().node;return f.compact(e.map((t=>{const e=n.params.get(t);if(e)return e;console.error(`param ${t} not found as visibility condition for ${this.param().name()} in node ${this.param().node.type()}`)})))}setUiDataDependency(){if(this._ui_data_dependency_set)return;this._ui_data_dependency_set=!0;const t=this.visibilityPredecessors();if(t.length>0){this._visibility_graph_node=new Mi(this.param().scene(),\\\\\\\"param_visibility\\\\\\\");for(let e of t)this._visibility_graph_node.addGraphInput(e);this._visibility_graph_node.addPostDirtyHook(\\\\\\\"_update_visibility_and_remove_dirty\\\\\\\",this._updateVisibilityAndRemoveDirtyBound)}}updateVisibilityAndRemoveDirty(){this.updateVisibility(),this.param().removeDirtyState()}async updateVisibility(){const t=this._options.visibleIf;if(t){const e=this.visibilityPredecessors(),n=e.map((t=>{if(t.isDirty())return t.compute()}));if(this._programatic_visible_state=!1,await Promise.all(n),m.isArray(t))for(let n of t){e.filter((t=>t.value==n[t.name()])).length==e.length&&(this._programatic_visible_state=!0)}else{const n=e.filter((e=>e.value==t[e.name()]));this._programatic_visible_state=n.length==e.length}this.param().emit(Nr.VISIBLE_UPDATED)}}}class Fr{constructor(t){this.param=t,this._blocked_emit=!1,this._blocked_parent_emit=!1,this._count_by_event_name={}}emitAllowed(){return!0!==this._blocked_emit&&(!this.param.scene().loadingController.isLoading()&&this.param.scene().dispatchController.emitAllowed())}blockEmit(){if(this._blocked_emit=!0,this.param.isMultiple()&&this.param.components)for(let t of this.param.components)t.emitController.blockEmit();return!0}unblockEmit(){if(this._blocked_emit=!1,this.param.isMultiple()&&this.param.components)for(let t of this.param.components)t.emitController.unblockEmit();return!0}blockParentEmit(){return this._blocked_parent_emit=!0,!0}unblockParentEmit(){return this._blocked_parent_emit=!1,!0}incrementCount(t){this._count_by_event_name[t]=this._count_by_event_name[t]||0,this._count_by_event_name[t]+=1}eventsCount(t){return this._count_by_event_name[t]||0}emit(t){this.emitAllowed()&&(this.param.emit(t),null!=this.param.parent_param&&!0!==this._blocked_parent_emit&&this.param.parent_param.emit(t))}}class Dr{constructor(t){this.param=t}toJSON(){const t={name:this.param.name(),type:this.param.type(),raw_input:this.rawInput(),value:this.value(),value_pre_conversion:this.value_pre_conversion(),expression:this.expression(),graph_node_id:this.param.graphNodeId(),error_message:this.error_message(),is_visible:this.is_visible(),components:void 0};return this.param.isMultiple()&&this.param.components&&(t.components=this.param.components.map((t=>t.graphNodeId()))),t}rawInput(){return this.param.rawInputSerialized()}value(){return this.param.valueSerialized()}value_pre_conversion(){return this.param.valuePreConversionSerialized()}expression(){var t;return this.param.hasExpression()?null===(t=this.param.expressionController)||void 0===t?void 0:t.expression():void 0}error_message(){return this.param.states.error.message()}is_visible(){return this.param.options.isVisible()}}class Br{constructor(t){this.param=t}active(){const t=this.param.scene().timeController.graphNode.graphNodeId();return this.param.graphPredecessorIds().includes(t)}}class zr{constructor(t){this.param=t}set(t){this._message!=t&&(this._message=t,this._message&&li.warn(this.param.path(),this._message),this.param.emitController.emit(Nr.ERROR_UPDATED))}message(){return this._message}clear(){this.set(void 0)}active(){return null!=this._message}}class kr{constructor(t){this.param=t,this.timeDependent=new Br(this.param),this.error=new zr(this.param)}}class Ur extends Mi{constructor(t,e,n){var i;super(t.scene(),\\\\\\\"MethodDependency\\\\\\\"),this.param=t,this.path_argument=e,this.decomposed_path=n,this._update_from_name_change_bound=this._update_from_name_change.bind(this),null===(i=t.expressionController)||void 0===i||i.registerMethodDependency(this),this.addPostDirtyHook(\\\\\\\"_update_from_name_change\\\\\\\",this._update_from_name_change_bound)}_update_from_name_change(t){if(t&&this.decomposed_path){const e=t;this.decomposed_path.update_from_name_change(e);const n=this.decomposed_path.to_path(),i=this.jsep_node;i&&(i.value=`${i.value}`.replace(`${this.path_argument}`,n),i.raw=i.raw.replace(`${this.path_argument}`,n)),this.param.expressionController&&this.param.expressionController.updateFromMethodDependencyNameChange()}}reset(){this.graphDisconnectPredecessors()}listen_for_name_changes(){if(this.jsep_node&&this.decomposed_path)for(let t of this.decomposed_path.named_nodes())if(t){const e=t;e.nameController&&this.addGraphInput(e.nameController.graph_node)}}set_jsep_node(t){this.jsep_node=t}set_resolved_graph_node(t){this.resolved_graph_node=t}set_unresolved_path(t){this.unresolved_path=t}static create(t,e,n,i){const s=m.isNumber(e),r=new Ur(t,e,i);if(n)r.set_resolved_graph_node(n);else if(!s){const t=e;r.set_unresolved_path(t)}return r}}const Gr=[];class Vr extends Mi{constructor(t,e){super(t,\\\\\\\"BaseParam\\\\\\\"),this._options=new Ir(this),this._emit_controller=new Fr(this),this._is_computing=!1,this._node=e,this.initialize_param()}get options(){return this._options=this._options||new Ir(this)}get emitController(){return this._emit_controller=this._emit_controller||new Fr(this)}get expressionController(){return this._expression_controller}get serializer(){return this._serializer=this._serializer||new Dr(this)}get states(){return this._states=this._states||new kr(this)}dispose(){var t,e;const n=this.graphPredecessors();for(let t of n)t instanceof Ur&&t.dispose();this.scene().missingExpressionReferencesController.deregisterParam(this),null===(t=this._expression_controller)||void 0===t||t.dispose(),super.dispose(),null===(e=this._options)||void 0===e||e.dispose()}initialize_param(){}static type(){return Cr.FLOAT}type(){return this.constructor.type()}isNumeric(){return!1}setName(t){super.setName(t)}get value(){return this._value}copy_value(t){t.type()==this.type()?this._copy_value(t):console.warn(`cannot copy value from ${t.type()} to ${this.type()}`)}_copy_value(t){throw\\\\\\\"abstract method param._copy_value\\\\\\\"}valuePreConversionSerialized(){}convert(t){return null}static are_raw_input_equal(t,e){return!1}is_raw_input_equal(t){return this.constructor.are_raw_input_equal(this._raw_input,t)}static are_values_equal(t,e){return!1}is_value_equal(t){return this.constructor.are_values_equal(this.value,t)}_clone_raw_input(t){return t}set(t){this._raw_input=this._clone_raw_input(this._prefilter_invalid_raw_input(t)),this.emitController.emit(Nr.RAW_INPUT_UPDATED),this.processRawInput()}_prefilter_invalid_raw_input(t){return t}defaultValue(){return this._default_value}isDefault(){return this._raw_input==this._default_value}rawInput(){return this._raw_input}processRawInput(){}async compute(){if(this.scene().loadingController.isLoading()&&console.warn(`param attempt to compute ${this.path()}`),this.isDirty()){if(this._is_computing)return new Promise(((t,e)=>{this._compute_resolves=this._compute_resolves||[],this._compute_resolves.push(t)}));if(this._is_computing=!0,await this.processComputation(),this._is_computing=!1,this._compute_resolves){let t;for(;t=this._compute_resolves.pop();)t()}}}async processComputation(){}setInitValue(t){this._default_value=this._clone_raw_input(this._prefilter_invalid_raw_input(t))}_setupNodeDependencies(t){var e,n;if(t?(this.options.allowCallback(),this.parent_param||(this.options.makesNodeDirtyWhenDirty()?null===(n=t.params.params_node)||void 0===n||n.addGraphInput(this,!1):this.dirtyController.addPostDirtyHook(\\\\\\\"run callback\\\\\\\",(async()=>{await this.compute(),this.options.executeCallback()})))):this._node&&(null===(e=this._node.params.params_node)||void 0===e||e.removeGraphInput(this)),this.components)for(let e of this.components)e._setupNodeDependencies(t)}get node(){return this._node}parent(){return this.node}set_parent_param(t){t.addGraphInput(this,!1),this._parent_param=t}get parent_param(){return this._parent_param}has_parent_param(){return null!=this._parent_param}path(){var t;return(null===(t=this.node)||void 0===t?void 0:t.path())+\\\\\\\"/\\\\\\\"+this.name()}pathRelativeTo(t){const e=bi.relativePath(t,this.node);return e.length>0?`${e}${bi.SEPARATOR}${this.name()}`:this.name()}emit(t){this.emitController.emitAllowed()&&(this.emitController.incrementCount(t),this.scene().dispatchController.dispatch(this,t))}get components(){return this._components}componentNames(){return Gr}isMultiple(){return this.componentNames().length>0}initComponents(){}hasExpression(){return null!=this.expressionController&&this.expressionController.active()}toJSON(){return this.serializer.toJSON()}}var Hr=n(94),jr=n.n(Hr);jr.a.addUnaryOp(\\\\\\\"@\\\\\\\");jr.a.addBinaryOp(\\\\\\\"**\\\\\\\",10);class Wr{constructor(){}parse_expression(t){try{this.reset(),this.node=jr()(t)}catch(e){const n=`could not parse the expression '${t}' (error: ${e})`;this.error_message=n}}parse_expression_for_string_param(t){try{this.reset();const e=Wr.string_value_elements(t),n=[];for(let t=0;t0){const e=\\\\\\\"const coreGeometry = entities[0].coreGeometry();\\\\\\\";t.push(e)}for(let e of this._attributeNames)t.push(Xr.assignItemSizeLine(e)),t.push(Xr.assignArrayLine(e));return t.join(\\\\\\\";\\\\n\\\\\\\")}return\\\\\\\"\\\\\\\"}attributePresenceCheckLine(){if(this._attributeNames){const t=[];for(let e of this._attributeNames){const n=Xr._varAttribute(e);t.push(n)}if(t.length>0)return t.join(\\\\\\\" && \\\\\\\")}return\\\\\\\"true\\\\\\\"}add(t){this._attributeNames=this._attributeNames||new Set,this._attributeNames.add(t)}static assignAttributeLine(t){return`const ${this._varAttribute(t)} = entities[0].geometry().attributes['${t}']`}static assignItemSizeLine(t){const e=this._varAttribute(t);return`const ${this._varAttribSize(t)} = ${e}.itemSize`}static assignArrayLine(t){const e=this._varAttribute(t);return`const ${this._varArray(t)} = ${`coreGeometry.isAttribIndexed('${t}')`} ? ${`entities.map(e=>e.indexedAttribValue('${t}'))`} : ${`${e}.array`}`}static _varAttribute(t){return`attrib_${t}`}static _varAttribSize(t){return`attrib_size_${t}`}static _varArray(t){return`array_${t}`}varAttributeSize(t){return Xr._varAttribSize(t)}varArray(t){return Xr._varArray(t)}}const Yr={math_random:\\\\\\\"random\\\\\\\"},$r=Object.keys(sr),Jr={};[\\\\\\\"abs\\\\\\\",\\\\\\\"acos\\\\\\\",\\\\\\\"acosh\\\\\\\",\\\\\\\"asin\\\\\\\",\\\\\\\"asinh\\\\\\\",\\\\\\\"atan\\\\\\\",\\\\\\\"atan2\\\\\\\",\\\\\\\"atanh\\\\\\\",\\\\\\\"ceil\\\\\\\",\\\\\\\"cos\\\\\\\",\\\\\\\"cosh\\\\\\\",\\\\\\\"exp\\\\\\\",\\\\\\\"expm1\\\\\\\",\\\\\\\"floor\\\\\\\",\\\\\\\"log\\\\\\\",\\\\\\\"log1p\\\\\\\",\\\\\\\"log2\\\\\\\",\\\\\\\"log10\\\\\\\",\\\\\\\"max\\\\\\\",\\\\\\\"min\\\\\\\",\\\\\\\"pow\\\\\\\",\\\\\\\"round\\\\\\\",\\\\\\\"sign\\\\\\\",\\\\\\\"sin\\\\\\\",\\\\\\\"sinh\\\\\\\",\\\\\\\"sqrt\\\\\\\",\\\\\\\"tan\\\\\\\",\\\\\\\"tanh\\\\\\\"].forEach((t=>{Jr[t]=`Math.${t}`})),[\\\\\\\"cbrt\\\\\\\",\\\\\\\"hypot\\\\\\\",\\\\\\\"log10\\\\\\\",\\\\\\\"trunc\\\\\\\"].forEach((t=>{Jr[t]=`Math.${t}`})),Object.keys(Yr).forEach((t=>{const e=Yr[t];Jr[t]=`Math.${e}`})),[\\\\\\\"fit\\\\\\\",\\\\\\\"fit01\\\\\\\",\\\\\\\"fract\\\\\\\",\\\\\\\"deg2rad\\\\\\\",\\\\\\\"rad2deg\\\\\\\",\\\\\\\"rand\\\\\\\",\\\\\\\"clamp\\\\\\\"].forEach((t=>{Jr[t]=`Core.Math.${t}`})),$r.forEach((t=>{Jr[t]=`Core.Math.Easing.${t}`})),[\\\\\\\"precision\\\\\\\"].forEach((t=>{Jr[t]=`Core.String.${t}`}));const Zr={if:class{static if(t){return`(${t[0]}) ? (${t[1]}) : (${t[2]})`}}.if},Kr={};[\\\\\\\"E\\\\\\\",\\\\\\\"LN2\\\\\\\",\\\\\\\"LN10\\\\\\\",\\\\\\\"LOG10E\\\\\\\",\\\\\\\"LOG2E\\\\\\\",\\\\\\\"PI\\\\\\\",\\\\\\\"SQRT1_2\\\\\\\",\\\\\\\"SQRT2\\\\\\\"].forEach((t=>{Kr[t]=`Math.${t}`}));const Qr={x:0,y:1,z:2,w:3,r:0,g:1,b:2};class to extends qr{constructor(t){super(t),this.param=t,this._attribute_requirements_controller=new Xr,this.methods=[],this.method_index=-1,this.method_dependencies=[],this.immutable_dependencies=[]}parse_tree(t){if(this.reset(),null==t.error_message){try{if(this._attribute_requirements_controller=new Xr,t.node){const e=this.traverse_node(t.node);e&&!this.is_errored()&&(this.function_main_string=e)}else console.warn(\\\\\\\"no parsed_tree.node\\\\\\\")}catch(t){console.warn(`error in expression for param ${this.param.path()}`),console.warn(t)}if(this.function_main_string)try{const t=this._functionBody();this.function=new Function(\\\\\\\"Core\\\\\\\",\\\\\\\"param\\\\\\\",\\\\\\\"methods\\\\\\\",\\\\\\\"_set_error_from_error\\\\\\\",`\\\\n\\\\t\\\\t\\\\t\\\\t\\\\ttry {\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t${t}\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t} catch(e) {\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t_set_error_from_error(e)\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\treturn null;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t}`)}catch(t){console.warn(t),this.set_error(\\\\\\\"cannot generate function\\\\\\\")}else this.set_error(\\\\\\\"cannot generate function body\\\\\\\")}else this.set_error(\\\\\\\"cannot parse expression\\\\\\\")}reset(){super.reset(),this.function_main_string=void 0,this.methods=[],this.method_index=-1,this.function=void 0,this.method_dependencies=[],this.immutable_dependencies=[]}_functionBody(){return this.param.options.isExpressionForEntities()?`\\\\n\\\\t\\\\t\\\\tconst entities = param.expressionController.entities();\\\\n\\\\t\\\\t\\\\tif(entities){\\\\n\\\\t\\\\t\\\\t\\\\treturn new Promise( async (resolve, reject)=>{\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tlet entity;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tconst entity_callback = param.expressionController.entity_callback();\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t// assign_attributes_lines\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t${this._attribute_requirements_controller.assignAttributesLines()}\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t// check if attributes are present\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tif( ${this._attribute_requirements_controller.attributePresenceCheckLine()} ){\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t// assign_arrays_lines\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t${this._attribute_requirements_controller.assignArraysLines()}\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tfor(let index=0; index < entities.length; index++){\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tentity = entities[index];\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tresult = ${this.function_main_string};\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tentity_callback(entity, result);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t}\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tresolve()\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t} else {\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tconst error = new Error('attribute not found')\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t_set_error_from_error(error)\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\treject(error)\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t}\\\\n\\\\t\\\\t\\\\t\\\\t})\\\\n\\\\t\\\\t\\\\t}\\\\n\\\\t\\\\t\\\\treturn []`:`\\\\n\\\\t\\\\t\\\\treturn new Promise( async (resolve, reject)=>{\\\\n\\\\t\\\\t\\\\t\\\\ttry {\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tconst value = ${this.function_main_string}\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tresolve(value)\\\\n\\\\t\\\\t\\\\t\\\\t} catch(e) {\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t_set_error_from_error(e)\\\\n\\\\t\\\\t\\\\t\\\\t\\\\treject()\\\\n\\\\t\\\\t\\\\t\\\\t}\\\\n\\\\t\\\\t\\\\t})\\\\n\\\\t\\\\t\\\\t`}evalAllowed(){return null!=this.function}evalFunction(){if(this.function){this.clear_error();const t={Math:or,String:ss};return this.function(t,this.param,this.methods,this._set_error_from_error_bound)}}traverse_CallExpression(t){const e=t.arguments.map((t=>this.traverse_node(t))),n=t.callee.name;if(n){const i=Zr[n];if(i)return i(e);const s=`${e.join(\\\\\\\", \\\\\\\")}`,r=Jr[n];if(r)return`${r}(${s})`;const o=li.expressionsRegister;if(o.getMethod(n)){const i=t.arguments[0],r=`return ${e[0]}`;let o,a=[];try{o=new Function(r),a=o()}catch{}return this._create_method_and_dependencies(n,a,i),`(await methods[${this.method_index}].processArguments([${s}]))`}{const t=`method not found (${n}), available methods are: ${o.availableMethods().join(\\\\\\\", \\\\\\\")}`;li.warn(t)}}this.set_error(`unknown method: ${n}`)}traverse_BinaryExpression(t){return`(${this.traverse_node(t.left)} ${t.operator} ${this.traverse_node(t.right)})`}traverse_LogicalExpression(t){return`(${this.traverse_node(t.left)} ${t.operator} ${this.traverse_node(t.right)})`}traverse_MemberExpression(t){return`${this.traverse_node(t.object)}.${this.traverse_node(t.property)}`}traverse_UnaryExpression(t){if(\\\\\\\"@\\\\\\\"===t.operator){let e,n,i=t.argument;switch(i.type){case\\\\\\\"Identifier\\\\\\\":e=i.name;break;case\\\\\\\"MemberExpression\\\\\\\":{const t=i,s=t.object,r=t.property;e=s.name,n=r.name;break}}if(e){if(e=Xs.remapName(e),\\\\\\\"ptnum\\\\\\\"==e)return\\\\\\\"((entity != null) ? entity.index() : 0)\\\\\\\";{const t=this._attribute_requirements_controller.varAttributeSize(e),i=this._attribute_requirements_controller.varArray(e);if(this._attribute_requirements_controller.add(e),n){return`${i}[entity.index()*${t}+${Qr[n]}]`}return`${i}[entity.index()*${t}]`}}return console.warn(\\\\\\\"attribute not found\\\\\\\"),\\\\\\\"\\\\\\\"}return`${t.operator}${this.traverse_node(t.argument)}`}traverse_Literal(t){return`${t.raw}`}traverse_Identifier(t){if(\\\\\\\"$\\\\\\\"!=t.name[0])return t.name;{const e=t.name.substr(1),n=Kr[e];if(n)return n;const i=`traverse_Identifier_${e}`;if(this[i])return this[i]();this.set_error(`identifier unknown: ${t.name}`)}}traverse_Identifier_F(){return this.immutable_dependencies.push(this.param.scene().timeController.graphNode),\\\\\\\"param.scene().timeController.frame()\\\\\\\"}traverse_Identifier_T(){return this.immutable_dependencies.push(this.param.scene().timeController.graphNode),\\\\\\\"param.scene().timeController.time()\\\\\\\"}traverse_Identifier_OS(){return`'${this.param.node.name()}'`}traverse_Identifier_CH(){return`'${this.param.name()}'`}traverse_Identifier_CEX(){return this._method_centroid(\\\\\\\"x\\\\\\\")}traverse_Identifier_CEY(){return this._method_centroid(\\\\\\\"y\\\\\\\")}traverse_Identifier_CEZ(){return this._method_centroid(\\\\\\\"z\\\\\\\")}_method_centroid(t){const e=[0,`'${t}'`].join(\\\\\\\", \\\\\\\");return this._create_method_and_dependencies(\\\\\\\"centroid\\\\\\\",0),`(await methods[${this.method_index}].processArguments([${e}]))`}_create_method_and_dependencies(t,e,n){const i=li.expressionsRegister,s=i.getMethod(t);if(!s){const e=`method not found (${t}), available methods are: ${i.availableMethods().join(\\\\\\\", \\\\\\\")}`;return this.set_error(e),void li.warn(e)}const r=new s(this.param);if(this.method_index+=1,this.methods[this.method_index]=r,r.require_dependency()){const t=r.findDependency(e);t?(n&&t.set_jsep_node(n),this.method_dependencies.push(t)):n&&m.isString(e)&&this.param.scene().missingExpressionReferencesController.register(this.param,e)}}}class eo extends qr{constructor(t){super(t),this.param=t}parse_tree(t){if(null==t.error_message&&t.node)try{return this.traverse_node(t.node)}catch(t){this.set_error(\\\\\\\"could not traverse tree\\\\\\\")}else this.set_error(\\\\\\\"cannot parse tree\\\\\\\")}traverse_CallExpression(t){const e=`${t.arguments.map((t=>this.traverse_node(t))).join(\\\\\\\", \\\\\\\")}`;return`${t.callee.name}(${e})`}traverse_UnaryExpression(t){return`${t.operator}${this.traverse_node(t.argument)}`}traverse_Identifier(t){return`${t.name}`}}class no{constructor(t){this.param=t,this.cyclic_graph_detected=!1,this.method_dependencies=[]}set_error(t){this.error_message=this.error_message||t}reset(){this.param.graphDisconnectPredecessors(),this.method_dependencies.forEach((t=>{t.reset()})),this.method_dependencies=[]}update(t){this.cyclic_graph_detected=!1,this.connect_immutable_dependencies(t),this.method_dependencies=t.method_dependencies,this.handle_method_dependencies(),this.listen_for_name_changes()}connect_immutable_dependencies(t){t.immutable_dependencies.forEach((t=>{if(0==this.cyclic_graph_detected&&0==this.param.addGraphInput(t))return this.cyclic_graph_detected=!0,this.set_error(\\\\\\\"cannot create expression, infinite graph detected\\\\\\\"),void this.reset()}))}handle_method_dependencies(){this.method_dependencies.forEach((t=>{0==this.cyclic_graph_detected&&this.handle_method_dependency(t)}))}handle_method_dependency(t){const e=t.resolved_graph_node;if(e&&!this.param.addGraphInput(e))return this.cyclic_graph_detected=!0,this.set_error(\\\\\\\"cannot create expression, infinite graph detected\\\\\\\"),void this.reset()}listen_for_name_changes(){this.method_dependencies.forEach((t=>{t.listen_for_name_changes()}))}}class io{constructor(t){this.param=t,this.parse_completed=!1,this.parse_started=!1,this.parsed_tree=new Wr,this._functionGenerator=new to(this.param),this.dependencies_controller=new no(this.param)}parseExpression(t){if(this.parse_started)throw new Error(`parse in progress for param ${this.param.path()}`);this.parse_started=!0,this.parse_completed=!1,this.parsed_tree=this.parsed_tree||new Wr,this.reset(),this.param.type()==Cr.STRING?this.parsed_tree.parse_expression_for_string_param(t):this.parsed_tree.parse_expression(t),this._functionGenerator.parse_tree(this.parsed_tree),null==this._functionGenerator.error_message()&&(this.dependencies_controller.update(this._functionGenerator),this.dependencies_controller.error_message?this.param.states.error.set(this.dependencies_controller.error_message):(this.parse_completed=!0,this.parse_started=!1))}async computeFunction(){if(!this._computeAllowed())return new Promise(((t,e)=>{t(null)}));try{return await this._functionGenerator.evalFunction()}catch(t){return}}reset(){this.parse_completed=!1,this.parse_started=!1,this.dependencies_controller.reset(),this._functionGenerator.reset()}is_errored(){return this._functionGenerator.is_errored()}error_message(){return this._functionGenerator.error_message()}_computeAllowed(){return this._functionGenerator.evalAllowed()}updateFromMethodDependencyNameChange(){this.expression_string_generator=this.expression_string_generator||new eo(this.param);const t=this.expression_string_generator.parse_tree(this.parsed_tree);t?this.param.set(t):console.warn(\\\\\\\"failed to regenerate expression\\\\\\\")}}class so{constructor(t){this.param=t}dispose(){this.param.scene().expressionsController.deregisterParam(this.param),this._resetMethodDependencies()}_resetMethodDependencies(){var t,e;null===(t=this._method_dependencies_by_graph_node_id)||void 0===t||t.forEach((t=>{t.dispose()})),null===(e=this._method_dependencies_by_graph_node_id)||void 0===e||e.clear()}registerMethodDependency(t){this._method_dependencies_by_graph_node_id=this._method_dependencies_by_graph_node_id||new Map,this._method_dependencies_by_graph_node_id.set(t.graphNodeId(),t)}active(){return null!=this._expression}expression(){return this._expression}is_errored(){return!!this._manager&&this._manager.is_errored()}error_message(){return this._manager?this._manager.error_message():null}requires_entities(){return this.param.options.isExpressionForEntities()}set_expression(t,e=!0){var n;this.param.scene().missingExpressionReferencesController.deregisterParam(this.param),this.param.scene().expressionsController.deregisterParam(this.param),this._expression!=t&&(this._resetMethodDependencies(),this._expression=t,this._expression?(this._manager=this._manager||new io(this.param),this._manager.parseExpression(this._expression)):null===(n=this._manager)||void 0===n||n.reset(),e&&this.param.setDirty())}updateFromMethodDependencyNameChange(){this._manager&&this.active()&&this._manager.updateFromMethodDependencyNameChange()}async computeExpression(){if(this._manager&&this.active()){return await this._manager.computeFunction()}}async computeExpressionForEntities(t,e){var n,i;this.set_entities(t,e),await this.computeExpression(),(null===(n=this._manager)||void 0===n?void 0:n.error_message())&&this.param.node.states.error.set(`expression evalution error: ${null===(i=this._manager)||void 0===i?void 0:i.error_message()}`),this.reset_entities()}computeExpressionForPoints(t,e){return this.computeExpressionForEntities(t,e)}computeExpressionForObjects(t,e){return this.computeExpressionForEntities(t,e)}entities(){return this._entities}entity_callback(){return this._entity_callback}set_entities(t,e){this._entities=t,this._entity_callback=e}reset_entities(){this._entities=void 0,this._entity_callback=void 0}}class ro extends Vr{isNumeric(){return!0}isDefault(){return this._raw_input==this._default_value}_prefilter_invalid_raw_input(t){return m.isArray(t)?t[0]:t}processRawInput(){this.states.error.clear();const t=this.convert(this._raw_input);null!=t?(this._expression_controller&&(this._expression_controller.set_expression(void 0,!1),this.emitController.emit(Nr.EXPRESSION_UPDATED)),t!=this._value&&(this._update_value(t),this.setSuccessorsDirty(this))):m.isString(this._raw_input)?(this._expression_controller=this._expression_controller||new so(this),this._raw_input!=this._expression_controller.expression()&&(this._expression_controller.set_expression(this._raw_input),this.emitController.emit(Nr.EXPRESSION_UPDATED))):this.states.error.set(`param input is invalid (${this.path()})`)}async processComputation(){var t;if((null===(t=this.expressionController)||void 0===t?void 0:t.active())&&!this.expressionController.requires_entities()){const t=await this.expressionController.computeExpression();if(this.expressionController.is_errored())this.states.error.set(`expression error: \\\\\\\"${this.expressionController.expression()}\\\\\\\" (${this.expressionController.error_message()})`);else{const e=this.convert(t);null!=e?(this.states.error.active()&&this.states.error.clear(),this._update_value(e)):this.states.error.set(`expression returns an invalid type (${t}) (${this.expressionController.expression()})`)}}}_update_value(t){this._value=t,this.parent_param&&this.parent_param.set_value_from_components(),this.options.executeCallback(),this.emitController.emit(Nr.VALUE_UPDATED),this.removeDirtyState()}}class oo extends ro{static type(){return Cr.FLOAT}defaultValueSerialized(){return this._default_value}rawInputSerialized(){return this._raw_input}valueSerialized(){return this.value}_copy_value(t){this.set(t.valueSerialized())}_prefilter_invalid_raw_input(t){return m.isArray(t)?t[0]:m.isString(t)&&ss.isNumber(t)?parseFloat(t):t}static are_raw_input_equal(t,e){return t==e}static are_values_equal(t,e){return t==e}static convert(t){if(m.isNumber(t))return t;if(m.isBoolean(t))return t?1:0;if(ss.isNumber(t)){const e=parseFloat(t);if(m.isNumber(e))return e}return null}convert(t){const e=oo.convert(t);return e?this.options.ensureInRange(e):e}}class ao extends Vr{constructor(){super(...arguments),this._components_contructor=oo}get components(){return this._components}isNumeric(){return!0}isDefault(){for(let t of this.components)if(!t.isDefault())return!1;return!0}rawInput(){return this._components.map((t=>t.rawInput()))}rawInputSerialized(){return this._components.map((t=>t.rawInputSerialized()))}_copy_value(t){for(let e=0;ee))}}processRawInput(){const t=this.scene().cooker;t.block();const e=this.components;for(let t of e)t.emitController.blockParentEmit();const n=this._raw_input;let i=0;if(m.isArray(n))for(let t=0;t linear\\\\\\\",t.LINEAR_TO_GAMMA=\\\\\\\"linear -> gamma\\\\\\\",t.SRGB_TO_LINEAR=\\\\\\\"sRGB -> linear\\\\\\\",t.LINEAR_TO_SRGB=\\\\\\\"linear -> sRGB\\\\\\\"}(lo||(lo={}));lo.NONE,lo.GAMMA_TO_LINEAR,lo.LINEAR_TO_GAMMA,lo.SRGB_TO_LINEAR,lo.LINEAR_TO_SRGB;class co{static set_hsv(t,e,n,i){t=Object(On.f)(t,1),e=Object(On.d)(e,0,1),n=Object(On.d)(n,0,1),i.setHSL(t,e*n/((t=(2-e)*n)<1?t:2-t),.5*t)}}const ho=[\\\\\\\"r\\\\\\\",\\\\\\\"g\\\\\\\",\\\\\\\"b\\\\\\\"];class uo extends ro{static type(){return Cr.INTEGER}defaultValueSerialized(){return this._default_value}rawInputSerialized(){return this._raw_input}valueSerialized(){return this.value}_copy_value(t){this.set(t.valueSerialized())}_prefilter_invalid_raw_input(t){return m.isArray(t)?t[0]:m.isString(t)&&ss.isNumber(t)?parseInt(t):t}static are_raw_input_equal(t,e){return t==e}static are_values_equal(t,e){return t==e}static convert(t){if(m.isNumber(t))return Math.round(t);if(m.isBoolean(t))return t?1:0;if(ss.isNumber(t)){const e=parseInt(t);if(m.isNumber(e))return e}return null}convert(t){const e=uo.convert(t);return e?this.options.ensureInRange(e):e}}class po{constructor(){this._index=-1,this._path_elements=[],this._named_nodes=[],this._graph_node_ids=[],this._node_element_by_graph_node_id=new Map}reset(){this._index=-1,this._path_elements=[],this._named_nodes=[],this._graph_node_ids=[],this._node_element_by_graph_node_id.clear()}add_node(t,e){this._index+=1,t==e.name()&&(this._named_nodes[this._index]=e),this._graph_node_ids[this._index]=e.graphNodeId(),this._node_element_by_graph_node_id.set(e.graphNodeId(),t)}add_path_element(t){this._index+=1,this._path_elements[this._index]=t}named_graph_nodes(){return this._named_nodes}named_nodes(){const t=[];for(let e of this._named_nodes)if(e){const n=e;n.nameController&&t.push(n)}return t}update_from_name_change(t){this._named_nodes.map((t=>null==t?void 0:t.graphNodeId())).includes(t.graphNodeId())&&this._node_element_by_graph_node_id.set(t.graphNodeId(),t.name())}to_path(){const t=new Array(this._index);for(let e=0;e<=this._index;e++){const n=this._named_nodes[e];if(n){const i=this._node_element_by_graph_node_id.get(n.graphNodeId());i&&(t[e]=i)}else{const n=this._path_elements[e];n&&(t[e]=n)}}let e=t.join(bi.SEPARATOR);const n=e[0];return n&&(bi.NON_LETTER_PREFIXES.includes(n)||(e=`${bi.SEPARATOR}${e}`)),e}}class _o extends Vr{constructor(){super(...arguments),this.decomposed_path=new po}_handleReferences(t,e){this.scene().referencesController.setNamedNodesFromParam(this),t?this.scene().referencesController.setReferenceFromParam(this,t):this.scene().missingExpressionReferencesController.register(this,e)}}var mo;!function(t){t.NODE=\\\\\\\"NODE\\\\\\\",t.PARAM=\\\\\\\"PARAM\\\\\\\"}(mo||(mo={}));class fo extends _o{constructor(){super(...arguments),this._found_node=null,this._found_node_with_expected_type=null,this._found_param=null,this._found_param_with_expected_type=null}static type(){return Cr.OPERATOR_PATH}defaultValueSerialized(){return this._default_value}rawInputSerialized(){return`${this._raw_input}`}valueSerialized(){return`${this.value}`}_copy_value(t){this.set(t.valueSerialized())}static are_raw_input_equal(t,e){return t==e}static are_values_equal(t,e){return t==e}isDefault(){return this._value==this._default_value}setNode(t){this.set(t.path())}processRawInput(){this._value!=this._raw_input&&(this._value=this._raw_input,this.setDirty(),this.emitController.emit(Nr.VALUE_UPDATED))}async processComputation(){this.find_target()}find_target(){if(!this.node)return;const t=this._value;let e=null,n=null;const i=null!=t&&\\\\\\\"\\\\\\\"!==t,s=this.options.paramSelectionOptions()?mo.PARAM:mo.NODE;this.scene().referencesController.resetReferenceFromParam(this),this.decomposed_path.reset(),i&&(s==mo.PARAM?n=bi.findParam(this.node,t,this.decomposed_path):e=bi.findNode(this.node,t,this.decomposed_path));const r=s==mo.PARAM?this._found_param:this._found_node,o=s==mo.PARAM?n:e;if(this._handleReferences(e,t),(null==r?void 0:r.graphNodeId())!==(null==o?void 0:o.graphNodeId())){const t=this.options.dependentOnFoundNode();this._found_node&&t&&this.removeGraphInput(this._found_node),s==mo.PARAM?(this._found_param=n,this._found_node=null):(this._found_node=e,this._found_param=null),e&&this._assign_found_node(e),n&&this._assign_found_param(n),this.options.executeCallback()}this.removeDirtyState()}_assign_found_node(t){const e=this.options.dependentOnFoundNode();this._is_node_expected_context(t)?this._is_node_expected_type(t)?(this._found_node_with_expected_type=t,e&&this.addGraphInput(t)):this.states.error.set(`node type is ${t.type()} but the params expects one of ${(this._expected_node_types()||[]).join(\\\\\\\", \\\\\\\")}`):this.states.error.set(`node context is ${t.context()} but the params expects a ${this._expected_context()}`)}_assign_found_param(t){this._is_param_expected_type(t)?this._found_param_with_expected_type=t:this.states.error.set(`param type is ${t.type()} but the params expects a ${this._expected_param_type()}`)}found_node(){return this._found_node}found_param(){return this._found_param}found_node_with_context(t){return this._found_node_with_expected_type}found_node_with_context_and_type(t,e){const n=this.found_node_with_context(t);if(n)if(m.isArray(e)){for(let t of e)if(n.type()==t)return n;this.states.error.set(`expected node type to be ${e.join(\\\\\\\", \\\\\\\")}, but was instead ${n.type()}`)}else{const t=e;if(n.type()==t)return n;this.states.error.set(`expected node type to be ${t}, but was instead ${n.type()}`)}}found_param_with_type(t){if(this._found_param_with_expected_type)return this._found_param_with_expected_type}found_node_with_expected_type(){return this._found_node_with_expected_type}_expected_context(){return this.options.nodeSelectionContext()}_is_node_expected_context(t){var e,n;const i=this._expected_context();if(null==i)return!0;return i==(null===(n=null===(e=t.parent())||void 0===e?void 0:e.childrenController)||void 0===n?void 0:n.context)}_expected_node_types(){return this.options.nodeSelectionTypes()}_expected_param_type(){return this.options.paramSelectionType()}_is_node_expected_type(t){const e=this._expected_node_types();return null==e||(null==e?void 0:e.includes(t.type()))}_is_param_expected_type(t){const e=this._expected_node_types();return null==e||e.includes(t.type())}notifyPathRebuildRequired(t){this.decomposed_path.update_from_name_change(t);const e=this.decomposed_path.to_path();this.set(e)}notifyTargetParamOwnerParamsUpdated(t){this.setDirty()}}var go,vo=n(34),yo=n(70);class xo{constructor(t=0,e=0){this._position=t,this._value=e}toJSON(){return{position:this._position,value:this._value}}position(){return this._position}value(){return this._value}copy(t){this._position=t.position(),this._value=t.value()}clone(){const t=new xo;return t.copy(this),t}isEqual(t){return this._position==t.position()&&this._value==t.value()}isEqualJSON(t){return this._position==t.position&&this._value==t.value}fromJSON(t){this._position=t.position,this._value=t.value}static areEqualJSON(t,e){return t.position==e.position&&t.value==e.value}static fromJSON(t){return new xo(t.position,t.value)}}!function(t){t.LINEAR=\\\\\\\"linear\\\\\\\"}(go||(go={}));class bo{constructor(t=go.LINEAR,e=[]){this._interpolation=t,this._points=e,this._uuid=Object(On.h)()}uuid(){return this._uuid}interpolation(){return this._interpolation}points(){return this._points}static fromJSON(t){const e=[];for(let n of t.points)e.push(xo.fromJSON(n));return new bo(t.interpolation,e)}toJSON(){return{interpolation:this._interpolation,points:this._points.map((t=>t.toJSON()))}}clone(){const t=new bo;return t.copy(this),t}copy(t){this._interpolation=t.interpolation();let e=0;for(let n of t.points()){const t=this._points[e];t?t.copy(n):this._points.push(n.clone()),e+=1}}is_equal(t){if(this._interpolation!=t.interpolation())return!1;const e=t.points();if(this._points.length!=e.length)return!1;let n=0;for(let t of this._points){const i=e[n];if(!t.isEqual(i))return!1;n+=1}return!0}is_equal_json(t){if(this._interpolation!=t.interpolation)return!1;if(this._points.length!=t.points.length)return!1;let e=0;for(let n of this._points){const i=t.points[e];if(!n.isEqualJSON(i))return!1;e+=1}return!0}static are_json_equal(t,e){if(t.interpolation!=e.interpolation)return!1;if(t.points.length!=e.points.length)return!1;let n=0;for(let i of t.points){const t=e.points[n];if(!xo.areEqualJSON(i,t))return!1;n+=1}return!0}from_json(t){this._interpolation=t.interpolation;let e=0;for(let n of t.points){const t=this._points[e];t?t.fromJSON(n):this._points.push(xo.fromJSON(n)),e+=1}}}const wo=1024,To=255;class Ao extends Vr{constructor(){super(...arguments),this._texture_data=new Uint8Array(3072),this._ramp_texture=new vo.a(this._texture_data,wo,1,w.ic)}static type(){return Cr.RAMP}defaultValueSerialized(){return this._default_value instanceof bo?this._default_value.toJSON():this._default_value}_clone_raw_input(t){return t instanceof bo?t.clone():bo.fromJSON(t).toJSON()}rawInputSerialized(){return this._raw_input instanceof bo?this._raw_input.toJSON():bo.fromJSON(this._raw_input).toJSON()}valueSerialized(){return this.value.toJSON()}_copy_value(t){this.set(t.valueSerialized())}static are_raw_input_equal(t,e){return t instanceof bo?e instanceof bo?t.is_equal(e):t.is_equal_json(e):e instanceof bo?e.is_equal_json(t):bo.are_json_equal(t,e)}static are_values_equal(t,e){return t.is_equal(e)}isDefault(){return this._default_value instanceof bo?this.value.is_equal(this._default_value):this.value.is_equal_json(this._default_value)}processRawInput(){this._raw_input instanceof bo?this._value?this._value.copy(this._raw_input):this._value=this._raw_input:this._value?this._value.from_json(this._raw_input):this._value=bo.fromJSON(this._raw_input),this._resetRampInterpolant(),this._updateRampTexture(),this.options.executeCallback(),this.emitController.emit(Nr.VALUE_UPDATED),this.setSuccessorsDirty(this)}hasExpression(){return!1}_resetRampInterpolant(){this._ramp_interpolant=void 0}rampTexture(){return this._ramp_texture}_updateRampTexture(){this._updateRampTextureData(),this.rampTexture().needsUpdate=!0}_updateRampTextureData(){let t=0,e=0,n=0;for(var i=0;i<1024;i++)t=3*i,e=i/wo,n=this.valueAtPosition(e),n<=0?(this._texture_data[t+0]=(Object(On.d)(n,-1,0)+1)*To,this._texture_data[t+1]=0,this._texture_data[t+2]=0):n<=1?(this._texture_data[t+0]=To,this._texture_data[t+1]=Object(On.d)(n,0,1)*To,this._texture_data[t+2]=0):(this._texture_data[t+0]=To,this._texture_data[t+1]=To,this._texture_data[t+2]=(Object(On.d)(n,1,2)-1)*To)}static createInterpolant(t,e){const n=new Float32Array(1);return new yo.a(t,e,1,n)}interpolant(){return this._ramp_interpolant=this._ramp_interpolant||this._createInterpolant()}_createInterpolant(){const t=this.value.points(),e=f.sortBy(t,(t=>t.position())),n=new Float32Array(e.length),i=new Float32Array(e.length);let s=0;for(let t of e)n[s]=t.position(),i[s]=t.value(),s++;return Ao.createInterpolant(n,i)}valueAtPosition(t){return this.interpolant().evaluate(t)[0]}}Ao.DEFAULT_VALUE=new bo(go.LINEAR,[new xo(0,0),new xo(1,1)]),Ao.DEFAULT_VALUE_JSON=Ao.DEFAULT_VALUE.toJSON();class Mo extends Vr{static type(){return Cr.STRING}defaultValueSerialized(){return this._default_value}_clone_raw_input(t){return`${t}`}rawInputSerialized(){return`${this._raw_input}`}valueSerialized(){return`${this.value}`}_copy_value(t){this.set(t.value)}static are_raw_input_equal(t,e){return t==e}static are_values_equal(t,e){return t==e}isDefault(){return this._raw_input==this._default_value}convert(t){return m.isString(t)?t:`${t}`}rawInput(){return this._raw_input}processRawInput(){this.states.error.clear(),this._value_elements(this._raw_input).length>=3?(this._expression_controller=this._expression_controller||new so(this),this._raw_input!=this._expression_controller.expression()&&(this._expression_controller.set_expression(this._raw_input),this.setDirty(),this.emitController.emit(Nr.EXPRESSION_UPDATED))):this._raw_input!=this._value&&(this._value=this._raw_input,this.removeDirtyState(),this.setSuccessorsDirty(this),this.emitController.emit(Nr.VALUE_UPDATED),this.options.executeCallback(),this._expression_controller&&(this._expression_controller.set_expression(void 0,!1),this.emitController.emit(Nr.EXPRESSION_UPDATED)))}async processComputation(){var t;if((null===(t=this.expressionController)||void 0===t?void 0:t.active())&&!this.expressionController.requires_entities()){const t=await this.expressionController.computeExpression();if(this.expressionController.is_errored())this.states.error.set(`expression error: ${this.expressionController.error_message()}`);else{const e=this.convert(t);null!=e?(this._value=e,this.emitController.emit(Nr.VALUE_UPDATED),this.options.executeCallback()):this.states.error.set(`expression returns an invalid type (${t})`),this.removeDirtyState()}}}_value_elements(t){return Wr.string_value_elements(t)}}const Eo=[\\\\\\\"x\\\\\\\",\\\\\\\"y\\\\\\\"];const So=[\\\\\\\"x\\\\\\\",\\\\\\\"y\\\\\\\",\\\\\\\"z\\\\\\\"];const Co=[\\\\\\\"x\\\\\\\",\\\\\\\"y\\\\\\\",\\\\\\\"z\\\\\\\",\\\\\\\"w\\\\\\\"];const No={[Cr.BOOLEAN]:class extends ro{static type(){return Cr.BOOLEAN}defaultValueSerialized(){return m.isString(this._default_value)?this._default_value:this.convert(this._default_value)||!1}rawInputSerialized(){return this._raw_input}valueSerialized(){return this.value}_copy_value(t){this.set(t.value)}static are_raw_input_equal(t,e){return t==e}static are_values_equal(t,e){return t==e}convert(t){if(m.isBoolean(t))return t;if(m.isNumber(t))return t>=1;if(m.isString(t)){if(ss.isBoolean(t))return ss.toBoolean(t);if(ss.isNumber(t)){return parseFloat(t)>=1}}return null}},[Cr.BUTTON]:class extends Vr{static type(){return Cr.BUTTON}defaultValueSerialized(){return this._default_value}rawInputSerialized(){return this._raw_input}valueSerialized(){return this.value}_copy_value(t){}static are_raw_input_equal(t,e){return!0}static are_values_equal(t,e){return!0}async pressButton(){(this.node.isDirty()||this.node.cookController.isCooking())&&await this.node.compute(),this.options.executeCallback()}},[Cr.COLOR]:class extends ao{constructor(){super(...arguments),this._value=new D.a,this._value_pre_conversion=new D.a,this._value_serialized_dirty=!1,this._value_serialized=[0,0,0],this._value_pre_conversion_serialized=[0,0,0],this._copied_value=[0,0,0]}static type(){return Cr.COLOR}componentNames(){return ho}defaultValueSerialized(){return m.isArray(this._default_value)?this._default_value:this._default_value.toArray()}valueSerialized(){return this._update_value_serialized_if_required(),this._value_serialized}valuePreConversionSerialized(){return this._update_value_serialized_if_required(),this._value_pre_conversion_serialized}_copy_value(t){t.value.toArray(this._copied_value),this.set(this._copied_value)}_clone_raw_input(t){if(t instanceof D.a)return t.clone();{const e=[t[0],t[1],t[2]];return null==e[0]&&(e[0]=e[0]||0),null==e[1]&&(e[1]=e[1]||e[0]),null==e[2]&&(e[2]=e[2]||e[1]),e}}static are_raw_input_equal(t,e){return t instanceof D.a?e instanceof D.a?t.equals(e):t.r==e[0]&&t.g==e[1]&&t.b==e[2]:e instanceof D.a?t[0]==e.r&&t[1]==e.g&&t[2]==e.b:t[0]==e[0]&&t[1]==e[1]&&t[2]==e[2]}static are_values_equal(t,e){return t.equals(e)}initComponents(){super.initComponents(),this.r=this.components[0],this.g=this.components[1],this.b=this.components[2],this._value_serialized_dirty=!0}_update_value_serialized_if_required(){this._value_serialized_dirty&&(this._value_serialized[0]=this._value.r,this._value_serialized[1]=this._value.g,this._value_serialized[2]=this._value.b,this._value_pre_conversion_serialized[0]=this._value_pre_conversion.r,this._value_pre_conversion_serialized[1]=this._value_pre_conversion.g,this._value_pre_conversion_serialized[2]=this._value_pre_conversion.b)}valuePreConversion(){return this._value_pre_conversion}set_value_from_components(){this._value_pre_conversion.r=this.r.value,this._value_pre_conversion.g=this.g.value,this._value_pre_conversion.b=this.b.value,this._value.copy(this._value_pre_conversion);const t=this.options.colorConversion();if(null!=t&&t!=lo.NONE){switch(t){case lo.GAMMA_TO_LINEAR:return void this._value.convertGammaToLinear();case lo.LINEAR_TO_GAMMA:return void this._value.convertLinearToGamma();case lo.SRGB_TO_LINEAR:return void this._value.convertSRGBToLinear();case lo.LINEAR_TO_SRGB:return void this._value.convertLinearToSRGB()}os.unreachable(t)}this._value_serialized_dirty=!0}},[Cr.FLOAT]:oo,[Cr.FOLDER]:class extends Vr{static type(){return Cr.FOLDER}defaultValueSerialized(){return this._default_value}rawInputSerialized(){return this._raw_input}valueSerialized(){return this.value}_copy_value(t){}static are_raw_input_equal(t,e){return!0}static are_values_equal(t,e){return!0}},[Cr.INTEGER]:uo,[Cr.OPERATOR_PATH]:fo,[Cr.PARAM_PATH]:class extends _o{static type(){return Cr.PARAM_PATH}initialize_param(){this._value=new xi}defaultValueSerialized(){return this._default_value}rawInputSerialized(){return`${this._raw_input}`}valueSerialized(){return`${this.value}`}_copy_value(t){this.set(t.valueSerialized())}static are_raw_input_equal(t,e){return t==e}static are_values_equal(t,e){return t==e}isDefault(){return this._raw_input==this._default_value}setParam(t){this.set(t.path())}processRawInput(){this._value.path()!=this._raw_input&&(this._value.set_path(this._raw_input),this.find_target(),this.setDirty(),this.emitController.emit(Nr.VALUE_UPDATED))}async processComputation(){this.find_target()}find_target(){if(!this.node)return;const t=this._raw_input;let e=null;const n=null!=t&&\\\\\\\"\\\\\\\"!==t;this.scene().referencesController.resetReferenceFromParam(this),this.decomposed_path.reset(),n&&(e=bi.findParam(this.node,t,this.decomposed_path));const i=this._value.param(),s=e;if(this._handleReferences(e,t),(null==i?void 0:i.graphNodeId())!==(null==s?void 0:s.graphNodeId())){const t=this.options.dependentOnFoundNode(),n=this._value.param();n&&t&&this.removeGraphInput(n),e?this._assign_found_node(e):this._value.set_param(null),this.options.executeCallback()}this.removeDirtyState()}_assign_found_node(t){const e=this.options.dependentOnFoundNode();this._value.set_param(t),e&&this.addGraphInput(t)}notifyPathRebuildRequired(t){this.decomposed_path.update_from_name_change(t);const e=this.decomposed_path.to_path();this.set(e)}notifyTargetParamOwnerParamsUpdated(t){this.setDirty()}},[Cr.NODE_PATH]:class extends _o{static type(){return Cr.NODE_PATH}initialize_param(){this._value=new yi}defaultValueSerialized(){return this._default_value}rawInputSerialized(){return`${this._raw_input}`}valueSerialized(){return`${this.value}`}_copy_value(t){this.set(t.valueSerialized())}static are_raw_input_equal(t,e){return t==e}static are_values_equal(t,e){return t==e}isDefault(){return this._raw_input==this._default_value}setNode(t){this.set(t.path())}processRawInput(){this._value.path()!=this._raw_input&&(this._value.set_path(this._raw_input),this._findTarget(),this.setDirty(),this.emitController.emit(Nr.VALUE_UPDATED))}async processComputation(){this._findTarget()}_findTarget(){if(!this.node)return;const t=this._raw_input;let e=null;const n=null!=t&&\\\\\\\"\\\\\\\"!==t;this.scene().referencesController.resetReferenceFromParam(this),this.decomposed_path.reset(),n&&(e=bi.findNode(this.node,t,this.decomposed_path));const i=this._value.node(),s=e;if(this._handleReferences(e,t),(null==i?void 0:i.graphNodeId())!==(null==s?void 0:s.graphNodeId())){const t=this.options.dependentOnFoundNode(),n=this._value.node();n&&t&&this.removeGraphInput(n),e?this._assign_found_node(e):this._value.set_node(null),this.options.executeCallback()}n&&!e&&this.scene().loadingController.loaded()&&n&&this.states.error.set(`no node found at path '${t}'`),this.removeDirtyState()}_assign_found_node(t){const e=this.options.dependentOnFoundNode();this._isNodeExpectedContext(t)?this._is_node_expected_type(t)?(this.states.error.clear(),this._value.set_node(t),e&&this.addGraphInput(t)):this.states.error.set(`node type is ${t.type()} but the params expects one of ${(this._expected_node_types()||[]).join(\\\\\\\", \\\\\\\")}`):this.states.error.set(`node context is ${t.context()} but the params expects a ${this._expectedContext()}`)}_expectedContext(){return this.options.nodeSelectionContext()}_isNodeExpectedContext(t){var e,n;const i=this._expectedContext();if(null==i)return!0;return i==(null===(n=null===(e=t.parent())||void 0===e?void 0:e.childrenController)||void 0===n?void 0:n.context)}_expected_node_types(){return this.options.nodeSelectionTypes()}_is_node_expected_type(t){const e=this._expected_node_types();return null==e||(null==e?void 0:e.includes(t.type()))}notifyPathRebuildRequired(t){this.decomposed_path.update_from_name_change(t);const e=this.decomposed_path.to_path();this.set(e)}notifyTargetParamOwnerParamsUpdated(t){this.setDirty()}},[Cr.RAMP]:Ao,[Cr.STRING]:Mo,[Cr.VECTOR2]:class extends ao{constructor(){super(...arguments),this._value=new d.a,this._copied_value=[0,0]}static type(){return Cr.VECTOR2}componentNames(){return Eo}defaultValueSerialized(){return m.isArray(this._default_value)?this._default_value:this._default_value.toArray()}valueSerialized(){return this.value.toArray()}_copy_value(t){t.value.toArray(this._copied_value),this.set(this._copied_value)}_clone_raw_input(t){if(t instanceof d.a)return t.clone();{const e=[t[0],t[1]];return null==e[0]&&(e[0]=e[0]||0),null==e[1]&&(e[1]=e[1]||e[0]),e}}static are_raw_input_equal(t,e){return t instanceof d.a?e instanceof d.a?t.equals(e):t.x==e[0]&&t.y==e[1]:e instanceof d.a?t[0]==e.x&&t[1]==e.y:t[0]==e[0]&&t[1]==e[1]}static are_values_equal(t,e){return t.equals(e)}initComponents(){super.initComponents(),this.x=this.components[0],this.y=this.components[1]}set_value_from_components(){this._value.x=this.x.value,this._value.y=this.y.value}},[Cr.VECTOR3]:class extends ao{constructor(){super(...arguments),this._value=new p.a,this._copied_value=[0,0,0]}static type(){return Cr.VECTOR3}componentNames(){return So}defaultValueSerialized(){return m.isArray(this._default_value)?this._default_value:this._default_value.toArray()}valueSerialized(){return this.value.toArray()}_copy_value(t){t.value.toArray(this._copied_value),this.set(this._copied_value)}_clone_raw_input(t){if(t instanceof p.a)return t.clone();{const e=[t[0],t[1],t[2]];return null==e[0]&&(e[0]=e[0]||0),null==e[1]&&(e[1]=e[1]||e[0]),null==e[2]&&(e[2]=e[2]||e[1]),e}}static are_raw_input_equal(t,e){return t instanceof p.a?e instanceof p.a?t.equals(e):t.x==e[0]&&t.y==e[1]&&t.z==e[2]:e instanceof p.a?t[0]==e.x&&t[1]==e.y&&t[2]==e.z:t[0]==e[0]&&t[1]==e[1]&&t[2]==e[2]}static are_values_equal(t,e){return t.equals(e)}initComponents(){super.initComponents(),this.x=this.components[0],this.y=this.components[1],this.z=this.components[2]}set_value_from_components(){this._value.x=this.x.value,this._value.y=this.y.value,this._value.z=this.z.value}},[Cr.VECTOR4]:class extends ao{constructor(){super(...arguments),this._value=new _.a,this._copied_value=[0,0,0,0]}static type(){return Cr.VECTOR4}componentNames(){return Co}defaultValueSerialized(){return m.isArray(this._default_value)?this._default_value:this._default_value.toArray()}valueSerialized(){return this.value.toArray()}_copy_value(t){t.value.toArray(this._copied_value),this.set(this._copied_value)}_clone_raw_input(t){if(t instanceof _.a)return t.clone();{const e=[t[0],t[1],t[2],t[3]];return null==e[0]&&(e[0]=e[0]||0),null==e[1]&&(e[1]=e[1]||e[0]),null==e[2]&&(e[2]=e[2]||e[1]),null==e[3]&&(e[3]=e[3]||e[2]),e}}static are_raw_input_equal(t,e){return t instanceof _.a?e instanceof _.a?t.equals(e):t.x==e[0]&&t.y==e[1]&&t.z==e[2]&&t.w==e[3]:e instanceof _.a?t[0]==e.x&&t[1]==e.y&&t[2]==e.z&&t[3]==e.w:t[0]==e[0]&&t[1]==e[1]&&t[2]==e[2]&&t[3]==e[3]}static are_values_equal(t,e){return t.equals(e)}initComponents(){super.initComponents(),this.x=this.components[0],this.y=this.components[1],this.z=this.components[2],this.w=this.components[3]}set_value_from_components(){this._value.x=this.x.value,this._value.y=this.y.value,this._value.z=this.z.value,this._value.w=this.w.value}}};class Lo{dispose(){this._callback=void 0}params(){return this._params}callback(){return this._callback}init(t,e){if(this._params=t,e)this._callback=e;else{const t=this._params[0];switch(t.type()){case Cr.STRING:return this._handle_string_param(t);case Cr.OPERATOR_PATH:return this._handle_operator_path_param(t);case Cr.NODE_PATH:return this._handle_node_path_param(t);case Cr.PARAM_PATH:return this._handle_param_path_param(t);case Cr.FLOAT:case Cr.INTEGER:return this._handle_number_param(t)}}}_handle_string_param(t){this._callback=()=>t.value}_handle_operator_path_param(t){this._callback=()=>t.value}_handle_node_path_param(t){this._callback=()=>t.value.path()}_handle_param_path_param(t){this._callback=()=>t.value.path()}_handle_number_param(t){this._callback=()=>`${t.value}`}}class Oo{constructor(t){this.node=t,this._param_create_mode=!1,this._params_created=!1,this._params_by_name={},this._params_list=[],this._param_names=[],this._non_spare_params=[],this._spare_params=[],this._non_spare_param_names=[],this._spare_param_names=[],this._params_added_since_last_params_eval=!1}get label(){return this._label_controller=this._label_controller||new Lo}hasLabelController(){return null!=this._label_controller}dispose(){var t;this._params_node&&this._params_node.dispose();for(let t of this.all)t.dispose();this._post_create_params_hook_names=void 0,this._post_create_params_hooks=void 0,this._on_scene_load_hooks=void 0,this._on_scene_load_hook_names=void 0,null===(t=this._label_controller)||void 0===t||t.dispose()}initDependencyNode(){this._params_node||(this._params_node=new Mi(this.node.scene(),\\\\\\\"params\\\\\\\"),this.node.addGraphInput(this._params_node,!1))}init(){this.initDependencyNode(),this._param_create_mode=!0,this._initFromParamsConfig(),this.node.createParams(),this._postCreateParams()}_postCreateParams(){this._updateCaches(),this._initParamAccessors(),this._param_create_mode=!1,this._params_created=!0,this._runPostCreateParamsHooks()}postCreateSpareParams(){this._updateCaches(),this._initParamAccessors(),this.node.scene().referencesController.notifyParamsUpdated(this.node),this.node.emit(Ei.PARAMS_UPDATED)}updateParams(t){let e=!1,n=!1;if(t.namesToDelete)for(let e of t.namesToDelete)this.has(e)&&(this._deleteParam(e),n=!0);if(t.toAdd)for(let n of t.toAdd){const t=this.addParam(n.type,n.name,n.init_value,n.options);t&&(null!=n.raw_input&&t.set(n.raw_input),e=!0)}(n||e)&&this.postCreateSpareParams()}_initFromParamsConfig(){const t=this.node.paramsConfig;let e=!1;if(t)for(let n of Object.keys(t)){const i=t[n];let s;this.node.params_init_value_overrides&&(s=this.node.params_init_value_overrides[n],e=!0),this.addParam(i.type,n,i.init_value,i.options,s)}e&&this.node.setDirty(),this.node.params_init_value_overrides=void 0}_initParamAccessors(){let t=Object.getOwnPropertyNames(this.node.pv);this._removeUnneededAccessors(t),t=Object.getOwnPropertyNames(this.node.pv);for(let e of this.all){const n=e.options.isSpare();(!t.includes(e.name())||n)&&(Object.defineProperty(this.node.pv,e.name(),{get:()=>e.value,configurable:n}),Object.defineProperty(this.node.p,e.name(),{get:()=>e,configurable:n}))}}_removeUnneededAccessors(t){const e=this._param_names,n=[];for(let i of t)e.includes(i)||n.push(i);for(let t of n)Object.defineProperty(this.node.pv,t,{get:()=>{},configurable:!0}),Object.defineProperty(this.node.p,t,{get:()=>{},configurable:!0})}get params_node(){return this._params_node}get all(){return this._params_list}get non_spare(){return this._non_spare_params}get spare(){return this._spare_params}get names(){return this._param_names}get non_spare_names(){return this._non_spare_param_names}get spare_names(){return this._spare_param_names}set_with_type(t,e,n){const i=this.param_with_type(t,n);i?i.set(e):li.warn(`param ${t} not found with type ${n}`)}set_float(t,e){this.set_with_type(t,e,Cr.FLOAT)}set_vector3(t,e){this.set_with_type(t,e,Cr.VECTOR3)}has_param(t){return null!=this._params_by_name[t]}has(t){return this.has_param(t)}get(t){return this.param(t)}param_with_type(t,e){const n=this.param(t);if(n&&n.type()==e)return n}get_float(t){return this.param_with_type(t,Cr.FLOAT)}get_operator_path(t){return this.param_with_type(t,Cr.OPERATOR_PATH)}value(t){var e;return null===(e=this.param(t))||void 0===e?void 0:e.value}value_with_type(t,e){var n;return null===(n=this.param_with_type(t,e))||void 0===n?void 0:n.value}boolean(t){return this.value_with_type(t,Cr.BOOLEAN)}float(t){return this.value_with_type(t,Cr.FLOAT)}integer(t){return this.value_with_type(t,Cr.INTEGER)}string(t){return this.value_with_type(t,Cr.STRING)}vector2(t){return this.value_with_type(t,Cr.VECTOR2)}vector3(t){return this.value_with_type(t,Cr.VECTOR3)}color(t){return this.value_with_type(t,Cr.COLOR)}param(t){const e=this._params_by_name[t];return null!=e?e:(li.warn(`tried to access param '${t}' in node ${this.node.path()}, but existing params are: ${this.names} on node ${this.node.path()}`),null)}_deleteParam(t){const e=this._params_by_name[t];if(!e)throw new Error(`param '${t}' does not exist on node ${this.node.path()}`);if(this._params_node&&this._params_node.removeGraphInput(this._params_by_name[t]),e._setupNodeDependencies(null),delete this._params_by_name[t],e.isMultiple()&&e.components)for(let t of e.components){const e=t.name();delete this._params_by_name[e]}}addParam(t,e,n,i={},s){const r=i.spare||!1;!1!==this._param_create_mode||r||li.warn(`node ${this.node.path()} (${this.node.type()}) param '${e}' cannot be created outside of create_params`),null==this.node.scene()&&li.warn(`node ${this.node.path()} (${this.node.type()}) has no scene assigned`);const o=No[t];if(null!=o){const a=this._params_by_name[e];a&&(r?a.type()!=t&&this._deleteParam(a.name()):li.warn(`a param named ${e} already exists`,this.node));const l=new o(this.node.scene(),this.node);if(l.options.set(i),l.setName(e),l.setInitValue(n),l.initComponents(),null==s)l.set(n);else if(l.options.isExpressionForEntities()&&l.set(n),null!=s.raw_input)l.set(s.raw_input);else if(null!=s.simple_data)l.set(s.simple_data);else if(null!=s.complex_data){const t=s.complex_data.raw_input;t?l.set(t):l.set(n);const e=s.complex_data.overriden_options;if(null!=e){const t=Object.keys(e);for(let n of t)l.options.setOption(n,e[n])}}if(l._setupNodeDependencies(this.node),this._params_by_name[l.name()]=l,l.isMultiple()&&l.components)for(let t of l.components)this._params_by_name[t.name()]=t;return this._params_added_since_last_params_eval=!0,l}}_updateCaches(){this._params_list=Object.values(this._params_by_name),this._param_names=Object.keys(this._params_by_name),this._non_spare_params=Object.values(this._params_by_name).filter((t=>!t.options.isSpare())),this._spare_params=Object.values(this._params_by_name).filter((t=>t.options.isSpare())),this._non_spare_param_names=Object.values(this._params_by_name).filter((t=>!t.options.isSpare())).map((t=>t.name())),this._spare_param_names=Object.values(this._params_by_name).filter((t=>t.options.isSpare())).map((t=>t.name()))}async _evalParam(t){t.isDirty()&&(await t.compute(),t.states.error.active()&&this.node.states.error.set(`param '${t.name()}' error: ${t.states.error.message()}`))}async evalParams(t){const e=[];for(let n of t)n.isDirty()&&e.push(this._evalParam(n));await Promise.all(e),this.node.states.error.active()&&this.node._setContainer(null)}paramsEvalRequired(){return null!=this._params_node&&(this._params_node.isDirty()||this._params_added_since_last_params_eval)}async evalAll(){var t;this.paramsEvalRequired()&&(await this.evalParams(this._params_list),null===(t=this._params_node)||void 0===t||t.removeDirtyState(),this._params_added_since_last_params_eval=!1)}onParamsCreated(t,e){if(this._params_created)e();else{if(this._post_create_params_hook_names&&this._post_create_params_hook_names.includes(t))return void li.error(`hook name ${t} already exists`);this._post_create_params_hook_names=this._post_create_params_hook_names||[],this._post_create_params_hook_names.push(t),this._post_create_params_hooks=this._post_create_params_hooks||[],this._post_create_params_hooks.push(e)}}addOnSceneLoadHook(t,e){this._on_scene_load_hook_names=this._on_scene_load_hook_names||[],this._on_scene_load_hooks=this._on_scene_load_hooks||[],this._on_scene_load_hook_names.includes(t)?li.warn(`hook with name ${t} already exists`,this.node):(this._on_scene_load_hook_names.push(t),this._on_scene_load_hooks.push(e))}_runPostCreateParamsHooks(){if(this._post_create_params_hooks)for(let t of this._post_create_params_hooks)t()}runOnSceneLoadHooks(){if(this._on_scene_load_hooks)for(let t of this._on_scene_load_hooks)t()}}class Po{constructor(){}}class Ro{constructor(t,e,n=0,i=0){if(this._node_src=t,this._node_dest=e,this._output_index=n,this._input_index=i,null==this._output_index)throw\\\\\\\"bad output index\\\\\\\";if(null==this._input_index)throw\\\\\\\"bad input index\\\\\\\";this._id=Ro._next_id++,this._node_src.io.connections&&this._node_dest.io.connections&&(this._node_src.io.connections.addOutputConnection(this),this._node_dest.io.connections.addInputConnection(this))}get id(){return this._id}get node_src(){return this._node_src}get node_dest(){return this._node_dest}get output_index(){return this._output_index}get input_index(){return this._input_index}src_connection_point(){const t=this._node_src,e=this._output_index;return t.io.outputs.namedOutputConnectionPoints()[e]}dest_connection_point(){const t=this._node_dest,e=this._input_index;return t.io.inputs.namedInputConnectionPoints()[e]}disconnect(t={}){this._node_src.io.connections&&this._node_dest.io.connections&&(this._node_src.io.connections.removeOutputConnection(this),this._node_dest.io.connections.removeInputConnection(this)),!0===t.setInput&&this._node_dest.io.inputs.setInput(this._input_index,null)}}Ro._next_id=0;class Io{constructor(t){this.inputs_controller=t,this._clone_required_states=[],this._overridden=!1,this.node=t.node}initInputsClonedState(t){m.isArray(t)?this._cloned_states=t:this._cloned_state=t,this._update_clone_required_state()}overrideClonedStateAllowed(){if(this._cloned_states)for(let t of this._cloned_states)if(t==Qi.FROM_NODE)return!0;return!!this._cloned_state&&this._cloned_state==Qi.FROM_NODE}cloneRequiredState(t){return this._clone_required_states[t]}cloneRequiredStates(){return this._clone_required_states}_get_clone_required_state(t){const e=this._cloned_states;if(e){const n=e[t];if(null!=n)return this.clone_required_from_state(n)}return!this._cloned_state||this.clone_required_from_state(this._cloned_state)}clone_required_from_state(t){switch(t){case Qi.ALWAYS:return!0;case Qi.NEVER:return!1;case Qi.FROM_NODE:return!this._overridden}return os.unreachable(t)}overrideClonedState(t){this._overridden=t,this._update_clone_required_state(),this.node.emit(Ei.OVERRIDE_CLONABLE_STATE_UPDATE),this.node.setDirty()}overriden(){return this._overridden}_update_clone_required_state(){if(this._cloned_states){const t=[];for(let e=0;e=t.length&&n.disconnect({setInput:!0});this._named_input_connection_points=t,this.setMinCount(0),this.setMaxCount(t.length),this._initGraphNodeInputs(),this.node.emit(Ei.NAMED_INPUTS_UPDATED)}hasNamedInputs(){return this._has_named_inputs}namedInputConnectionPoints(){return this._named_input_connection_points||[]}_initGraphNodeInputs(){for(let t=0;t0)for(let e=0;e0){const n=this.existing_input_indices();if(n.length0){const n=[];let i;for(let t=0;tt.name()));return void console.warn(`node ${e.path()} does not have an output named ${n}. inputs are: ${t.join(\\\\\\\", \\\\\\\")}`)}const r=this._graph_node_inputs[i];if(null==r){const t=`graph_input_node not found at index ${i}`;throw console.warn(t),new Error(t)}if(e&&this.node.parent()!=e.parent())return;const o=this._inputs[i];let a,l=null;this.node.io.connections&&(a=this.node.io.connections.inputConnection(i)),a&&(l=a.output_index),e===o&&s==l||(null!=o&&this._depends_on_inputs&&r.removeGraphInput(o),null!=e?r.addGraphInput(e)?(this._depends_on_inputs||r.removeGraphInput(e),a&&a.disconnect({setInput:!1}),this._inputs[i]=e,new Ro(e,this.node,s,i)):console.warn(`cannot connect ${e.path()} to ${this.node.path()}`):(this._inputs[i]=null,a&&a.disconnect({setInput:!1})),this._run_on_set_input_hooks(),r.setSuccessorsDirty(),this.node.emit(Ei.INPUTS_UPDATED))}remove_input(t){const e=this.inputs();let n;for(let i=0;i=0}has_input(t){return null!=this._inputs[t]}inputs(){return this._inputs}initInputsClonedState(t){this._cloned_states_controller||(this._cloned_states_controller=new Io(this),this._cloned_states_controller.initInputsClonedState(t))}overrideClonedStateAllowed(){var t;return(null===(t=this._cloned_states_controller)||void 0===t?void 0:t.overrideClonedStateAllowed())||!1}overrideClonedState(t){var e;null===(e=this._cloned_states_controller)||void 0===e||e.overrideClonedState(t)}clonedStateOverriden(){var t;return(null===(t=this._cloned_states_controller)||void 0===t?void 0:t.overriden())||!1}cloneRequired(t){var e;const n=null===(e=this._cloned_states_controller)||void 0===e?void 0:e.cloneRequiredState(t);return null==n||n}cloneRequiredStates(){var t;const e=null===(t=this._cloned_states_controller)||void 0===t?void 0:t.cloneRequiredStates();return null==e||e}add_on_set_input_hook(t,e){this._on_update_hooks=this._on_update_hooks||[],this._on_update_hook_names=this._on_update_hook_names||[],this._on_update_hook_names.includes(t)?console.warn(`hook with name ${t} already exists`,this.node):(this._on_update_hooks.push(e),this._on_update_hook_names.push(t))}_run_on_set_input_hooks(){if(this._on_update_hooks)for(let t of this._on_update_hooks)t()}}class Do{constructor(t){this.node=t,this._has_outputs=!1,this._has_named_outputs=!1}setHasOneOutput(){this._has_outputs=!0}setHasNoOutput(){this._has_outputs=!1}hasOutputs(){return this._has_outputs}hasNamedOutputs(){return this._has_named_outputs}hasNamedOutput(t){return this.getNamedOutputIndex(t)>=0}namedOutputConnectionPoints(){return this._named_output_connection_points||[]}namedOutputConnection(t){if(this._named_output_connection_points)return this._named_output_connection_points[t]}getNamedOutputIndex(t){var e;if(this._named_output_connection_points)for(let n=0;n=t.length&&e.disconnect({setInput:!0});this._named_output_connection_points=t,e&&this.node.scene()&&this.node.setDirty(this.node),this.node.emit(Ei.NAMED_OUTPUTS_UPDATED)}used_output_names(){var t;const e=this.node.io.connections;if(e){let n=e.outputConnections().map((t=>t?t.output_index:null));n=f.uniq(n);const i=[];n.forEach((t=>{m.isNumber(t)&&i.push(t)}));const s=[];for(let e of i){const n=null===(t=this.namedOutputConnectionPoints()[e])||void 0===t?void 0:t.name();n&&s.push(n)}return s}return[]}}class Bo{constructor(t){this._node=t,this._output_connections=new Map}initInputs(){const t=this._node.io.inputs.maxInputsCount();for(this._input_connections=this._input_connections||new Array(t);this._input_connections.length1&&void 0===t[t.length-1];)t.pop();return t}addOutputConnection(t){const e=t.output_index,n=t.id;let i=this._output_connections.get(e);i||(i=new Map,this._output_connections.set(e,i)),i.set(n,t)}removeOutputConnection(t){const e=t.output_index,n=t.id;let i=this._output_connections.get(e);i&&i.delete(n)}outputConnections(){let t=[];return this._output_connections.forEach(((e,n)=>{e.forEach(((e,n)=>{e&&t.push(e)}))})),t}}class zo{constructor(t){this._node=t}set_in(t){this._in=t}set_out(t){this._out=t}clear(){this._in=void 0,this._out=void 0}in(){return this._in}out(){return this._out}}class ko{constructor(t,e,n){this._name=t,this._type=e,this._init_value=n}get init_value(){return this._init_value}name(){return this._name}type(){return this._type}are_types_matched(t,e){return!0}toJSON(){return this._json=this._json||this._create_json()}_create_json(){return{name:this._name,type:this._type}}}var Uo;!function(t){t.BOOL=\\\\\\\"bool\\\\\\\",t.INT=\\\\\\\"int\\\\\\\",t.FLOAT=\\\\\\\"float\\\\\\\",t.VEC2=\\\\\\\"vec2\\\\\\\",t.VEC3=\\\\\\\"vec3\\\\\\\",t.VEC4=\\\\\\\"vec4\\\\\\\",t.SAMPLER_2D=\\\\\\\"sampler2D\\\\\\\",t.SSS_MODEL=\\\\\\\"SSSModel\\\\\\\"}(Uo||(Uo={}));const Go=[Uo.BOOL,Uo.INT,Uo.FLOAT,Uo.VEC2,Uo.VEC3,Uo.VEC4],Vo={[Uo.BOOL]:Cr.BOOLEAN,[Uo.INT]:Cr.INTEGER,[Uo.FLOAT]:Cr.FLOAT,[Uo.VEC2]:Cr.VECTOR2,[Uo.VEC3]:Cr.VECTOR3,[Uo.VEC4]:Cr.VECTOR4,[Uo.SAMPLER_2D]:Cr.RAMP,[Uo.SSS_MODEL]:Cr.STRING},Ho={[Cr.BOOLEAN]:Uo.BOOL,[Cr.COLOR]:Uo.VEC3,[Cr.INTEGER]:Uo.INT,[Cr.FLOAT]:Uo.FLOAT,[Cr.FOLDER]:void 0,[Cr.VECTOR2]:Uo.VEC2,[Cr.VECTOR3]:Uo.VEC3,[Cr.VECTOR4]:Uo.VEC4,[Cr.BUTTON]:void 0,[Cr.OPERATOR_PATH]:void 0,[Cr.PARAM_PATH]:void 0,[Cr.NODE_PATH]:void 0,[Cr.RAMP]:void 0,[Cr.STRING]:void 0},jo={[Uo.BOOL]:!1,[Uo.INT]:0,[Uo.FLOAT]:0,[Uo.VEC2]:[0,0],[Uo.VEC3]:[0,0,0],[Uo.VEC4]:[0,0,0,0],[Uo.SAMPLER_2D]:Ao.DEFAULT_VALUE_JSON,[Uo.SSS_MODEL]:\\\\\\\"SSSModel()\\\\\\\"},Wo={[Uo.BOOL]:1,[Uo.INT]:1,[Uo.FLOAT]:1,[Uo.VEC2]:2,[Uo.VEC3]:3,[Uo.VEC4]:4,[Uo.SAMPLER_2D]:1,[Uo.SSS_MODEL]:1};class qo extends ko{constructor(t,e,n){super(t,e),this._name=t,this._type=e,this._init_value=n,this._init_value=this._init_value||jo[this._type]}type(){return this._type}are_types_matched(t,e){return t==e}get param_type(){return Vo[this._type]}get init_value(){return this._init_value}toJSON(){return this._json=this._json||this._create_json()}_create_json(){return{name:this._name,type:this._type}}}var Xo;!function(t){t.BOOL=\\\\\\\"bool\\\\\\\",t.INT=\\\\\\\"int\\\\\\\",t.FLOAT=\\\\\\\"float\\\\\\\",t.VEC2=\\\\\\\"vec2\\\\\\\",t.VEC3=\\\\\\\"vec3\\\\\\\",t.VEC4=\\\\\\\"vec4\\\\\\\"}(Xo||(Xo={}));const Yo=[Xo.BOOL,Xo.INT,Xo.FLOAT,Xo.VEC2,Xo.VEC3,Xo.VEC4],$o={[Xo.BOOL]:Cr.BOOLEAN,[Xo.INT]:Cr.INTEGER,[Xo.FLOAT]:Cr.FLOAT,[Xo.VEC2]:Cr.VECTOR2,[Xo.VEC3]:Cr.VECTOR3,[Xo.VEC4]:Cr.VECTOR4},Jo={[Cr.BOOLEAN]:Xo.BOOL,[Cr.COLOR]:Xo.VEC3,[Cr.INTEGER]:Xo.INT,[Cr.FLOAT]:Xo.FLOAT,[Cr.FOLDER]:void 0,[Cr.VECTOR2]:Xo.VEC2,[Cr.VECTOR3]:Xo.VEC3,[Cr.VECTOR4]:Xo.VEC4,[Cr.BUTTON]:void 0,[Cr.OPERATOR_PATH]:void 0,[Cr.PARAM_PATH]:void 0,[Cr.NODE_PATH]:void 0,[Cr.RAMP]:void 0,[Cr.STRING]:void 0},Zo={[Xo.BOOL]:!1,[Xo.INT]:0,[Xo.FLOAT]:0,[Xo.VEC2]:[0,0],[Xo.VEC3]:[0,0,0],[Xo.VEC4]:[0,0,0,0]};Xo.BOOL,Xo.INT,Xo.FLOAT,Xo.VEC2,Xo.VEC3,Xo.VEC4;class Ko extends ko{constructor(t,e){super(t,e),this._name=t,this._type=e,this._init_value=Zo[this._type]}type(){return this._type}are_types_matched(t,e){return t==e}get param_type(){return $o[this._type]}get init_value(){return this._init_value}toJSON(){return this._json=this._json||this._create_json()}_create_json(){return{name:this._name,type:this._type}}}var Qo;!function(t){t.BASE=\\\\\\\"base\\\\\\\",t.DRAG=\\\\\\\"drag\\\\\\\",t.KEYBOARD=\\\\\\\"keyboard\\\\\\\",t.MOUSE=\\\\\\\"mouse\\\\\\\",t.POINTER=\\\\\\\"pointer\\\\\\\"}(Qo||(Qo={}));class ta extends ko{constructor(t,e,n){super(t,e),this._name=t,this._type=e,this._event_listener=n}type(){return this._type}get param_type(){return Cr.FLOAT}are_types_matched(t,e){return e==Qo.BASE||t==e}get event_listener(){return this._event_listener}toJSON(){return this._json=this._json||this._create_json()}_create_json(){return{name:this._name,type:this._type}}}const ea={[ts.ANIM]:void 0,[ts.COP]:void 0,[ts.EVENT]:Qo.BASE,[ts.GL]:Uo.FLOAT,[ts.JS]:Xo.FLOAT,[ts.MANAGER]:void 0,[ts.MAT]:void 0,[ts.OBJ]:void 0,[ts.POST]:void 0,[ts.ROP]:void 0,[ts.SOP]:void 0};function na(t,e,n){switch(t){case ts.EVENT:return new ta(e,n);case ts.GL:return new qo(e,n);case ts.JS:return new Ko(e,n);default:return}}class ia{constructor(t,e){this.node=t,this._context=e,this._raw_input_serialized_by_param_name=new Map,this._default_value_serialized_by_param_name=new Map,this._initialized=!1}initializeNode(){this._initialized?console.warn(\\\\\\\"already initialized\\\\\\\",this.node):(this._initialized=!0,this.node.params.onParamsCreated(\\\\\\\"create_inputs_from_params\\\\\\\",this.create_inputs_from_params.bind(this)))}initialized(){return this._initialized}create_inputs_from_params(){const t=function(t){switch(t){case ts.EVENT:return;case ts.GL:return Ho;case ts.JS:return Jo;default:return}}(this._context);if(!t)return;const e=[];for(let n of this.node.params.names){let i=!0;if(this._inputless_param_names&&this._inputless_param_names.length>0&&this._inputless_param_names.includes(n)&&(i=!1),i&&this.node.params.has(n)){const i=this.node.params.get(n);if(i&&!i.parent_param){const n=t[i.type()];if(n){const t=na(this._context,i.name(),n);t&&e.push(t)}}}}this.node.io.inputs.setNamedInputConnectionPoints(e)}set_inputless_param_names(t){return this._inputless_param_names=t}createSpareParameters(){if(this.node.scene().loadingController.isLoading())return;const t=this.node.params.spare_names,e={};for(let n of t)if(this.node.params.has(n)){const t=this.node.params.get(n);t&&(this._raw_input_serialized_by_param_name.set(n,t.rawInputSerialized()),this._default_value_serialized_by_param_name.set(n,t.defaultValueSerialized()),e.namesToDelete=e.namesToDelete||[],e.namesToDelete.push(n))}for(let t of this.node.io.inputs.namedInputConnectionPoints())if(t){const n=t.name(),i=t.param_type;let s=t.init_value;const r=this._default_value_serialized_by_param_name.get(n);let o=this.node.paramDefaultValue(n);if(s=null!=o?o:null!=r?r:t.init_value,m.isArray(t.init_value))if(m.isNumber(s)){const e=new Array(t.init_value.length);e.fill(s),s=e}else m.isArray(s)&&s.length==t.init_value.length&&null!=r&&(s=t.init_value);null!=s&&(e.toAdd=e.toAdd||[],e.toAdd.push({name:n,type:i,init_value:b.clone(s),raw_input:b.clone(s),options:{spare:!0}}))}this.node.params.updateParams(e);for(let t of this.node.params.spare)if(!t.parent_param){const e=this._raw_input_serialized_by_param_name.get(t.name());e&&t.set(e)}}}class sa{constructor(t,e){this.node=t,this._context=e,this._create_spare_params_from_inputs=!0,this._functions_overridden=!1,this._input_name_function=t=>`in${t}`,this._output_name_function=t=>0==t?\\\\\\\"val\\\\\\\":`val${t}`,this._expected_input_types_function=()=>{const t=this.first_input_connection_type()||this.default_connection_type();return[t,t]},this._expected_output_types_function=()=>[this._expected_input_types_function()[0]],this._update_signature_if_required_bound=this.update_signature_if_required.bind(this),this._initialized=!1,this._spare_params_controller=new ia(this.node,this._context)}default_connection_type(){return ea[this._context]}create_connection_point(t,e){return na(this._context,t,e)}functions_overridden(){return this._functions_overridden}initialized(){return this._initialized}set_create_spare_params_from_inputs(t){this._create_spare_params_from_inputs=t}set_input_name_function(t){this._initialize_if_required(),this._input_name_function=t}set_output_name_function(t){this._initialize_if_required(),this._output_name_function=t}set_expected_input_types_function(t){this._initialize_if_required(),this._functions_overridden=!0,this._expected_input_types_function=t}set_expected_output_types_function(t){this._initialize_if_required(),this._functions_overridden=!0,this._expected_output_types_function=t}input_name(t){return this._wrapped_input_name_function(t)}output_name(t){return this._wrapped_output_name_function(t)}initializeNode(){this._initialized?console.warn(\\\\\\\"already initialized\\\\\\\",this.node):(this._initialized=!0,this.node.io.inputs.add_on_set_input_hook(\\\\\\\"_update_signature_if_required\\\\\\\",this._update_signature_if_required_bound),this.node.params.addOnSceneLoadHook(\\\\\\\"_update_signature_if_required\\\\\\\",this._update_signature_if_required_bound),this.node.params.onParamsCreated(\\\\\\\"_update_signature_if_required_bound\\\\\\\",this._update_signature_if_required_bound),this.node.addPostDirtyHook(\\\\\\\"_update_signature_if_required\\\\\\\",this._update_signature_if_required_bound),this._spare_params_controller.initialized()||this._spare_params_controller.initializeNode())}_initialize_if_required(){this._initialized||this.initializeNode()}get spare_params(){return this._spare_params_controller}update_signature_if_required(t){this.node.lifecycle.creationCompleted()&&this._connections_match_inputs()||(this.update_connection_types(),this.node.removeDirtyState(),this.node.scene().loadingController.isLoading()||this.make_successors_update_signatures())}make_successors_update_signatures(){const t=this.node.graphAllSuccessors();if(this.node.childrenAllowed()){const e=this.node.nodesByType(ns.INPUT),n=this.node.nodesByType(ns.OUTPUT);for(let n of e)t.push(n);for(let e of n)t.push(e)}for(let e of t){const t=e;t.io&&t.io.has_connection_points_controller&&t.io.connection_points.initialized()&&t.io.connection_points.update_signature_if_required(this.node)}}update_connection_types(){const t=this._wrapped_expected_input_types_function(),e=this._wrapped_expected_output_types_function(),n=[];for(let e=0;enull==t?void 0:t.type())),e=this.node.io.outputs.namedOutputConnectionPoints().map((t=>null==t?void 0:t.type())),n=this._wrapped_expected_input_types_function(),i=this._wrapped_expected_output_types_function();if(n.length!=t.length)return!1;if(i.length!=e.length)return!1;for(let e=0;et.type))}return this._expected_input_types_function()}_wrapped_expected_output_types_function(){if(this.node.scene().loadingController.isLoading()){const t=this.node.io.saved_connection_points_data.out();if(t)return t.map((t=>t.type))}return this._expected_output_types_function()}_wrapped_input_name_function(t){if(this.node.scene().loadingController.isLoading()){const e=this.node.io.saved_connection_points_data.in();if(e)return e[t].name}return this._input_name_function(t)}_wrapped_output_name_function(t){if(this.node.scene().loadingController.isLoading()){const e=this.node.io.saved_connection_points_data.out();if(e)return e[t].name}return this._output_name_function(t)}first_input_connection_type(){return this.input_connection_type(0)}input_connection_type(t){const e=this.node.io.connections.inputConnections();if(e){const n=e[t];if(n)return n.src_connection_point().type()}}}class ra{constructor(t){this.node=t,this._connections=new Bo(this.node)}get connections(){return this._connections}get inputs(){return this._inputs=this._inputs||new Fo(this.node)}has_inputs(){return null!=this._inputs}get outputs(){return this._outputs=this._outputs||new Do(this.node)}has_outputs(){return null!=this._outputs}get connection_points(){return this._connection_points=this._connection_points||new sa(this.node,this.node.context())}get has_connection_points_controller(){return null!=this._connection_points}get saved_connection_points_data(){return this._saved_connection_points_data=this._saved_connection_points_data||new zo(this.node)}clear_saved_connection_points_data(){this._saved_connection_points_data&&(this._saved_connection_points_data.clear(),this._saved_connection_points_data=void 0)}}class oa{constructor(){}}class aa extends Mi{constructor(t,e=\\\\\\\"BaseNode\\\\\\\",n){super(t,e),this.params_init_value_overrides=n,this.containerController=new Tr(this),this.pv=new Po,this.p=new oa,this._initialized=!1}copy_param_values(t){const e=this.params.non_spare;for(let n of e){const e=t.params.get(n.name());e&&n.copy_value(e)}}get parentController(){return this._parent_controller=this._parent_controller||new qi(this)}static displayedInputNames(){return[]}get childrenControllerContext(){return this._children_controller_context}_create_children_controller(){if(this._children_controller_context)return new hs(this,this._children_controller_context)}get childrenController(){return this._children_controller=this._children_controller||this._create_children_controller()}childrenAllowed(){return null!=this._children_controller_context}get uiData(){return this._ui_data=this._ui_data||new Si(this)}get states(){return this._states=this._states||new ji(this)}get lifecycle(){return this._lifecycle=this._lifecycle||new us(this)}get serializer(){return this._serializer=this._serializer||new Sr(this)}get cookController(){return this._cook_controller=this._cook_controller||new Er(this)}get io(){return this._io=this._io||new ra(this)}get nameController(){return this._name_controller=this._name_controller||new Wi(this)}setName(t){this.nameController.setName(t)}_set_core_name(t){this._name=t}get params(){return this._params_controller=this._params_controller||new Oo(this)}initialize_base_and_node(){var t;this._initialized?console.warn(\\\\\\\"node already initialized\\\\\\\"):(this._initialized=!0,null===(t=this.displayNodeController)||void 0===t||t.initializeNode(),this.initializeBaseNode(),this.initializeNode(),this.polyNodeController&&this.polyNodeController.initializeNode())}initializeBaseNode(){}initializeNode(){}static type(){throw\\\\\\\"type to be overriden\\\\\\\"}type(){return this.constructor.type()}static context(){throw console.error(\\\\\\\"node has no node_context\\\\\\\",this),\\\\\\\"context requires override\\\\\\\"}context(){return this.constructor.context()}static require_webgl2(){return!1}require_webgl2(){return this.constructor.require_webgl2()}setParent(t){this.parentController.setParent(t)}parent(){return this.parentController.parent()}firstAncestorWithContext(t){return this.parentController.firstAncestorWithContext(t)}root(){return this._scene.root()}path(t){return this.parentController.path(t)}createParams(){}addParam(t,e,n,i){var s;return null===(s=this._params_controller)||void 0===s?void 0:s.addParam(t,e,n,i)}paramDefaultValue(t){return null}cook(t){return null}onCookEnd(t,e){this.cookController.registerOnCookEnd(t,e)}async compute(){var t,e;return this.isDirty()||(null===(e=null===(t=this.flags)||void 0===t?void 0:t.bypass)||void 0===e?void 0:e.active())?await this.containerController.compute():this.containerController.container()}_setContainer(t,e=null){this.containerController.container().set_content(t),null!=t&&(t.name||(t.name=this.path()),t.node||(t.node=this)),this.cookController.endCook(e)}createNode(t,e){var n;return null===(n=this.childrenController)||void 0===n?void 0:n.createNode(t,e)}create_operation_container(t,e,n){var i;return null===(i=this.childrenController)||void 0===i?void 0:i.create_operation_container(t,e,n)}removeNode(t){var e;null===(e=this.childrenController)||void 0===e||e.removeNode(t)}dispose(){var t,e;super.dispose(),this.setParent(null),this.io.inputs.dispose(),this.lifecycle.dispose(),null===(t=this.displayNodeController)||void 0===t||t.dispose(),this.nameController.dispose(),null===(e=this.childrenController)||void 0===e||e.dispose(),this.params.dispose()}children(){var t;return(null===(t=this.childrenController)||void 0===t?void 0:t.children())||[]}node(t){var e;return(null===(e=this.parentController)||void 0===e?void 0:e.findNode(t))||null}nodeSibbling(t){var e;const n=this.parent();if(n){const i=null===(e=n.childrenController)||void 0===e?void 0:e.childByName(t);if(i)return i}return null}nodesByType(t){var e;return(null===(e=this.childrenController)||void 0===e?void 0:e.nodesByType(t))||[]}setInput(t,e,n=0){this.io.inputs.setInput(t,e,n)}emit(t,e=null){this.scene().dispatchController.dispatch(this,t,e)}toJSON(t=!1){return this.serializer.toJSON(t)}async requiredModules(){}usedAssembler(){}integrationData(){}}class la extends aa{static context(){return ts.MANAGER}}class ca{constructor(t,e,n){this.type=t,this.init_value=e,this.options=n}}class ha{static BUTTON(t,e){return new ca(Cr.BUTTON,t,e)}static BOOLEAN(t,e){return new ca(Cr.BOOLEAN,t,e)}static COLOR(t,e){return t instanceof D.a&&(t=t.toArray()),new ca(Cr.COLOR,t,e)}static FLOAT(t,e){return new ca(Cr.FLOAT,t,e)}static FOLDER(t=null,e){return new ca(Cr.FOLDER,t,e)}static INTEGER(t,e){return new ca(Cr.INTEGER,t,e)}static RAMP(t=Ao.DEFAULT_VALUE,e){return new ca(Cr.RAMP,t,e)}static STRING(t=\\\\\\\"\\\\\\\",e){return new ca(Cr.STRING,t,e)}static VECTOR2(t,e){return t instanceof d.a&&(t=t.toArray()),new ca(Cr.VECTOR2,t,e)}static VECTOR3(t,e){return t instanceof p.a&&(t=t.toArray()),new ca(Cr.VECTOR3,t,e)}static VECTOR4(t,e){return t instanceof _.a&&(t=t.toArray()),new ca(Cr.VECTOR4,t,e)}static OPERATOR_PATH(t,e){return new ca(Cr.OPERATOR_PATH,t,e)}static NODE_PATH(t,e){return new ca(Cr.NODE_PATH,t,e)}static PARAM_PATH(t,e){return new ca(Cr.PARAM_PATH,t,e)}}class ua{}class da{constructor(t){this.scene=t}findObjectByMask(t){return this.findObjectByMaskInObject(t,this.scene.threejsScene())}findObjectByMaskInObject(t,e,n=\\\\\\\"\\\\\\\"){for(let i of e.children){const e=this._removeTrailingOrHeadingSlash(i.name),s=`${n=this._removeTrailingOrHeadingSlash(n)}/${e}`;if(ss.matchMask(s,t))return i;const r=this.findObjectByMaskInObject(t,i,s);if(r)return r}}objectsByMask(t){return this.objectsByMaskInObject(t,this.scene.threejsScene(),[],\\\\\\\"\\\\\\\")}objectsByMaskInObject(t,e,n=[],i=\\\\\\\"\\\\\\\"){for(let s of e.children){const e=this._removeTrailingOrHeadingSlash(s.name),r=`${i=this._removeTrailingOrHeadingSlash(i)}/${e}`;ss.matchMask(r,t)&&n.push(s),this.objectsByMaskInObject(t,s,n,r)}return n}_removeTrailingOrHeadingSlash(t){return\\\\\\\"/\\\\\\\"==t[0]&&(t=t.substr(1)),\\\\\\\"/\\\\\\\"==t[t.length-1]&&(t=t.substr(0,t.length-1)),t}}const pa={computeOnDirty:!1,callback:t=>{ma.update(t)}};function _a(t){return class extends t{constructor(){super(...arguments),this.autoUpdate=ha.BOOLEAN(1,pa)}}}_a(ua);class ma{constructor(t){this.node=t}async update(){const t=this.node.object,e=this.node.pv;e.autoUpdate!=t.autoUpdate&&(t.autoUpdate=e.autoUpdate)}static async update(t){t.sceneAutoUpdateController.update()}}var fa;!function(t){t.NONE=\\\\\\\"none\\\\\\\",t.COLOR=\\\\\\\"color\\\\\\\",t.TEXTURE=\\\\\\\"texture\\\\\\\"}(fa||(fa={}));const ga=[fa.NONE,fa.COLOR,fa.TEXTURE],va={computeOnDirty:!1,callback:t=>{xa.update(t)}};function ya(t){return class extends t{constructor(){super(...arguments),this.backgroundMode=ha.INTEGER(ga.indexOf(fa.NONE),{menu:{entries:ga.map(((t,e)=>({name:t,value:e})))},...va}),this.bgColor=ha.COLOR([0,0,0],{visibleIf:{backgroundMode:ga.indexOf(fa.COLOR)},...va}),this.bgTexture=ha.NODE_PATH(\\\\\\\"\\\\\\\",{visibleIf:{backgroundMode:ga.indexOf(fa.TEXTURE)},nodeSelection:{context:ts.COP},dependentOnFoundNode:!1,...va})}}}ya(ua);class xa{constructor(t){this.node=t}update(){const t=this.node.object,e=this.node.pv;if(e.backgroundMode==ga.indexOf(fa.NONE))t.background=null;else if(e.backgroundMode==ga.indexOf(fa.COLOR))t.background=e.bgColor;else{const n=e.bgTexture.nodeWithContext(ts.COP);n?n.compute().then((e=>{t.background=e.texture()})):this.node.states.error.set(\\\\\\\"bgTexture node not found\\\\\\\")}}static update(t){t.sceneBackgroundController.update()}}const ba={computeOnDirty:!1,callback:t=>{Ta.update(t)}};function wa(t){return class extends t{constructor(){super(...arguments),this.useEnvironment=ha.BOOLEAN(0,ba),this.environment=ha.NODE_PATH(\\\\\\\"\\\\\\\",{visibleIf:{useEnvironment:1},nodeSelection:{context:ts.COP},dependentOnFoundNode:!1,...ba})}}}wa(ua);class Ta{constructor(t){this.node=t}async update(){const t=this.node.object,e=this.node.pv;if(e.useEnvironment){const n=e.environment.nodeWithContext(ts.COP);n?n.compute().then((e=>{t.environment=e.texture()})):this.node.states.error.set(\\\\\\\"bgTexture node not found\\\\\\\")}else t.environment=null}static async update(t){t.sceneEnvController.update()}}class Aa{constructor(t,e=1,n=1e3){this.name=\\\\\\\"\\\\\\\",this.color=new D.a(t),this.near=e,this.far=n}clone(){return new Aa(this.color,this.near,this.far)}toJSON(){return{type:\\\\\\\"Fog\\\\\\\",color:this.color.getHex(),near:this.near,far:this.far}}}Aa.prototype.isFog=!0;class Ma{constructor(t,e=25e-5){this.name=\\\\\\\"\\\\\\\",this.color=new D.a(t),this.density=e}clone(){return new Ma(this.color,this.density)}toJSON(){return{type:\\\\\\\"FogExp2\\\\\\\",color:this.color.getHex(),density:this.density}}}Ma.prototype.isFogExp2=!0;const Ea={computeOnDirty:!1,callback:t=>{La.update(t)}};var Sa;!function(t){t.LINEAR=\\\\\\\"linear\\\\\\\",t.EXPONENTIAL=\\\\\\\"exponential\\\\\\\"}(Sa||(Sa={}));const Ca=[Sa.LINEAR,Sa.EXPONENTIAL];function Na(t){return class extends t{constructor(){super(...arguments),this.useFog=ha.BOOLEAN(0,Ea),this.fogType=ha.INTEGER(Ca.indexOf(Sa.EXPONENTIAL),{visibleIf:{useFog:1},menu:{entries:Ca.map(((t,e)=>({name:t,value:e})))},...Ea}),this.fogColor=ha.COLOR([1,1,1],{visibleIf:{useFog:1},...Ea}),this.fogNear=ha.FLOAT(1,{range:[0,100],rangeLocked:[!0,!1],visibleIf:{useFog:1,fogType:Ca.indexOf(Sa.LINEAR)},...Ea}),this.fogFar=ha.FLOAT(100,{range:[0,100],rangeLocked:[!0,!1],visibleIf:{useFog:1,fogType:Ca.indexOf(Sa.LINEAR)},...Ea}),this.fogDensity=ha.FLOAT(25e-5,{visibleIf:{useFog:1,fogType:Ca.indexOf(Sa.EXPONENTIAL)},...Ea})}}}Na(ua);class La{constructor(t){this.node=t}async update(){const t=this.node.object,e=this.node.pv;if(e.useFog)if(e.fogType==Ca.indexOf(Sa.LINEAR)){const n=this.fog2(e);t.fog=n,n.color=e.fogColor,n.near=e.fogNear,n.far=e.fogFar}else{const n=this.fogExp2(e);t.fog=this.fogExp2(e),n.color=e.fogColor,n.density=e.fogDensity}else{t.fog&&(t.fog=null)}}fog2(t){return this._fog=this._fog||new Aa(16777215,t.fogNear,t.fogFar)}fogExp2(t){return this._fogExp2=this._fogExp2||new Ma(16777215,t.fogDensity)}static async update(t){t.sceneFogController.update()}}const Oa={computeOnDirty:!1,callback:t=>{Ra.update(t)}};function Pa(t){return class extends t{constructor(){super(...arguments),this.useOverrideMaterial=ha.BOOLEAN(0,Oa),this.overrideMaterial=ha.NODE_PATH(\\\\\\\"\\\\\\\",{visibleIf:{useOverrideMaterial:1},nodeSelection:{context:ts.MAT},dependentOnFoundNode:!1,...Oa})}}}Pa(ua);class Ra{constructor(t){this.node=t}async update(){const t=this.node.object,e=this.node.pv;if(e.useOverrideMaterial){const n=e.overrideMaterial.nodeWithContext(ts.MAT);n?n.compute().then((e=>{t.overrideMaterial=e.material()})):this.node.states.error.set(\\\\\\\"bgTexture node not found\\\\\\\")}else t.overrideMaterial=null}static async update(t){t.SceneMaterialOverrideController.update()}}class Ia extends(Pa(wa(Na(ya(_a(ua)))))){}const Fa=new Ia;class Da extends la{constructor(){super(...arguments),this.paramsConfig=Fa,this._object=this._createScene(),this._queued_nodes_by_id=new Map,this.sceneAutoUpdateController=new ma(this),this.sceneBackgroundController=new xa(this),this.sceneEnvController=new Ta(this),this.sceneFogController=new La(this),this.sceneMaterialOverrideController=new Ra(this),this._children_controller_context=ts.OBJ}static type(){return\\\\\\\"obj\\\\\\\"}initializeNode(){this._object.matrixAutoUpdate=!1,this.lifecycle.add_on_child_add_hook(this._on_child_add.bind(this)),this.lifecycle.add_on_child_remove_hook(this._on_child_remove.bind(this))}_createScene(){const t=new vs;return t.name=\\\\\\\"/\\\\\\\",t.matrixAutoUpdate=!1,t}get object(){return this._object}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}_updateScene(){this.sceneAutoUpdateController.update(),this.sceneBackgroundController.update(),this.sceneEnvController.update(),this.sceneFogController.update(),this.sceneMaterialOverrideController.update()}_addToQueue(t){const e=t.graphNodeId();return this._queued_nodes_by_id.has(e)||this._queued_nodes_by_id.set(e,t),t}async processQueue(){this._updateScene();const t=new Map,e=[];this._queued_nodes_by_id.forEach(((n,i)=>{const s=`_____${n.renderOrder}__${n.path()}`;e.push(s),t.set(s,n)})),this._queued_nodes_by_id.clear();for(let n of e){const e=t.get(n);e&&(t.delete(n),this._addToScene(e))}}_update_object(t){return this.scene().loadingController.autoUpdating()?this._addToScene(t):this._addToQueue(t)}getParentForNode(t){if(t.attachableToHierarchy()){const e=t.io.inputs.input(0);return e?e.children_group:this._object}return null}_addToScene(t){var e;if(t.attachableToHierarchy()){const n=this.getParentForNode(t);n&&(t.usedInScene()?(null===(e=t.childrenDisplayController)||void 0===e||e.request_display_node_container(),t.addObjectToParent(n)):t.removeObjectFromParent())}}_removeFromScene(t){t.removeObjectFromParent()}areChildrenCooking(){const t=this.children();for(let e of t)if(e.cookController.isCooking()||e.isDisplayNodeCooking())return!0;return!1}addToParentTransform(t){this._update_object(t)}removeFromParentTransform(t){this._update_object(t)}_on_child_add(t){t&&this._update_object(t)}_on_child_remove(t){t&&this._removeFromScene(t)}}class Ba{constructor(t){this.scene=t,this._node_context_signatures={},this._instanciated_nodes_by_context_and_type={}}init(){this._root=new Da(this.scene),this._root.initialize_base_and_node(),this._root.params.init(),this._root._set_core_name(\\\\\\\"RootNode\\\\\\\")}root(){return this._root}_traverseNode(t,e){const n=t.children();if(n&&0!=n.length)for(let t of n)e(t),t.childrenController&&this._traverseNode(t,e)}clear(){var t;const e=this.root().children();for(let n of e)null===(t=this.root().childrenController)||void 0===t||t.removeNode(n)}node(t){return\\\\\\\"/\\\\\\\"===t?this.root():this.root().node(t)}allNodes(){let t=[this.root()],e=[this.root()],n=0;for(;e.length>0&&n<10;){const i=e.map((t=>t.childrenAllowed()?t.children():[])).flat();t=t.concat(i),e=i,n+=1}return t.flat()}nodesFromMask(t){const e=this.allNodes(),n=[];for(let i of e){const e=i.path();ss.matchMask(e,t)&&n.push(i)}return n}reset_node_context_signatures(){this._node_context_signatures={}}register_node_context_signature(t){t.childrenAllowed()&&t.childrenController&&(this._node_context_signatures[t.childrenController.node_context_signature()]=!0)}node_context_signatures(){return Object.keys(this._node_context_signatures).sort().map((t=>t.toLowerCase()))}addToInstanciatedNode(t){const e=t.context(),n=t.type();this._instanciated_nodes_by_context_and_type[e]=this._instanciated_nodes_by_context_and_type[e]||{},this._instanciated_nodes_by_context_and_type[e][n]=this._instanciated_nodes_by_context_and_type[e][n]||{},this._instanciated_nodes_by_context_and_type[e][n][t.graphNodeId()]=t}removeFromInstanciatedNode(t){const e=t.context(),n=t.type();delete this._instanciated_nodes_by_context_and_type[e][n][t.graphNodeId()]}nodesByType(t){const e=[];return this._traverseNode(this.scene.root(),(n=>{n.type()==t&&e.push(n)})),e}nodesByContextAndType(t,e){const n=[],i=this._instanciated_nodes_by_context_and_type[t];if(i){const t=i[e];if(t)for(let e of Object.keys(t))n.push(t[e])}return n}}class za{constructor(t){this.scene=t}toJSON(t=!1){const e={},n={};for(let i of this.scene.nodesController.allNodes()){const s=new Sr(i);e[i.graphNodeId()]=s.toJSON(t);const r=i.params.all;for(let t of r)n[t.graphNodeId()]=t.toJSON()}return{nodes_by_graph_node_id:e,params_by_graph_node_id:n}}}var ka;!function(t){t.auxclick=\\\\\\\"auxclick\\\\\\\",t.click=\\\\\\\"click\\\\\\\",t.contextmenu=\\\\\\\"contextmenu\\\\\\\",t.dblclick=\\\\\\\"dblclick\\\\\\\",t.mousedown=\\\\\\\"mousedown\\\\\\\",t.mouseenter=\\\\\\\"mouseenter\\\\\\\",t.mouseleave=\\\\\\\"mouseleave\\\\\\\",t.mousemove=\\\\\\\"mousemove\\\\\\\",t.mouseover=\\\\\\\"mouseover\\\\\\\",t.mouseout=\\\\\\\"mouseout\\\\\\\",t.mouseup=\\\\\\\"mouseup\\\\\\\",t.pointerlockchange=\\\\\\\"pointerlockchange\\\\\\\",t.pointerlockerror=\\\\\\\"pointerlockerror\\\\\\\",t.select=\\\\\\\"select\\\\\\\",t.wheel=\\\\\\\"wheel\\\\\\\"}(ka||(ka={}));const Ua=[ka.auxclick,ka.click,ka.contextmenu,ka.dblclick,ka.mousedown,ka.mouseenter,ka.mouseleave,ka.mousemove,ka.mouseover,ka.mouseout,ka.mouseup,ka.pointerlockchange,ka.pointerlockerror,ka.select,ka.wheel];class Ga extends pi{constructor(){super(...arguments),this._require_canvas_event_listeners=!0}type(){return\\\\\\\"mouse\\\\\\\"}acceptedEventTypes(){return Ua.map((t=>`${t}`))}}class Va extends aa{constructor(){super(...arguments),this._cook_without_inputs_bound=this._cook_without_inputs.bind(this)}static context(){return ts.EVENT}initializeBaseNode(){this.uiData.setLayoutHorizontal(),this.addPostDirtyHook(\\\\\\\"cook_without_inputs_on_dirty\\\\\\\",this._cook_without_inputs_bound),this.io.inputs.set_depends_on_inputs(!1),this.io.connections.initInputs(),this.io.connection_points.spare_params.initializeNode()}_cook_without_inputs(){this.cookController.cookMainWithoutInputs()}cook(){this.cookController.endCook()}processEventViaConnectionPoint(t,e){e.event_listener?e.event_listener(t):this.processEvent(t)}processEvent(t){}async dispatchEventToOutput(t,e){this.run_on_dispatch_hook(t,e);const n=this.io.outputs.getOutputIndex(t);if(n>=0){const t=this.io.connections.outputConnections().filter((t=>t.output_index==n));let i;for(let n of t){i=n.node_dest;const t=i.io.inputs.namedInputConnectionPoints()[n.input_index];i.processEventViaConnectionPoint(e,t)}}else console.warn(`requested output '${t}' does not exist on node '${this.path()}'`)}onDispatch(t,e){this._on_dispatch_hooks_by_output_name=this._on_dispatch_hooks_by_output_name||new Map,h.pushOnArrayAtEntry(this._on_dispatch_hooks_by_output_name,t,e)}run_on_dispatch_hook(t,e){if(this._on_dispatch_hooks_by_output_name){const n=this._on_dispatch_hooks_by_output_name.get(t);if(n)for(let t of n)t(e)}}}var Ha;!function(t){t.CANVAS=\\\\\\\"canvas\\\\\\\",t.DOCUMENT=\\\\\\\"document\\\\\\\"}(Ha||(Ha={}));const ja=[Ha.CANVAS,Ha.DOCUMENT];class Wa{constructor(t){this.viewer=t,this._bound_listener_map_by_event_controller_type=new Map}updateEvents(t){const e=this.canvas();if(!e)return;const n=t.type();let i=this._bound_listener_map_by_event_controller_type.get(n);i||(i=new Map,this._bound_listener_map_by_event_controller_type.set(n,i)),i.forEach(((t,n)=>{this._eventOwner(t.data,e).removeEventListener(n,t.listener)})),i.clear();const s=e=>{this.processEvent(e,t)};for(let n of t.activeEventDatas()){this._eventOwner(n,e).addEventListener(n.type,s),i.set(n.type,{listener:s,data:n})}}_eventOwner(t,e){return\\\\\\\"resize\\\\\\\"==t.type?window:t.emitter==Ha.CANVAS?e:document}cameraNode(){return this.viewer.camerasController.cameraNode()}canvas(){return this.viewer.canvas()}init(){this.canvas&&this.viewer.scene().eventsDispatcher.traverseControllers((t=>{this.updateEvents(t)}))}registeredEventTypes(){const t=[];return this._bound_listener_map_by_event_controller_type.forEach((e=>{e.forEach(((e,n)=>{t.push(n)}))})),t}dispose(){const t=this.canvas();this._bound_listener_map_by_event_controller_type.forEach((e=>{t&&e.forEach(((e,n)=>{this._eventOwner(e.data,t).removeEventListener(n,e.listener)}))}))}processEvent(t,e){if(!this.canvas())return;const n={viewer:this.viewer,event:t,cameraNode:this.cameraNode()};e.processEvent(n)}}const qa={visibleIf:{active:1},callback:t=>{Ya.PARAM_CALLBACK_updateRegister(t)}};class Xa extends Va{constructor(){super(...arguments),this._activeEventDatas=[]}initializeBaseNode(){super.initializeBaseNode();this.lifecycle.add_on_add_hook((()=>{this.scene().eventsDispatcher.registerEventNode(this)})),this.lifecycle.add_delete_hook((()=>{this.scene().eventsDispatcher.unregisterEventNode(this)})),this.params.onParamsCreated(\\\\\\\"update_register\\\\\\\",(()=>{this._updateRegister()}))}processEvent(t){this.pv.active&&t.event&&this.dispatchEventToOutput(t.event.type,t)}static PARAM_CALLBACK_updateRegister(t){t._updateRegister()}_updateRegister(){this._updateActiveEventDatas(),this.scene().eventsDispatcher.updateViewerEventListeners(this)}_updateActiveEventDatas(){if(this._activeEventDatas=[],this.pv.active){const t=this.acceptedEventTypes();for(let e of t){const t=this.params.get(e);t&&t.value&&this._activeEventDatas.push({type:e,emitter:ja[this.pv.element]})}}}activeEventDatas(){return this._activeEventDatas}}class Ya extends Xa{acceptedEventTypes(){return[]}}const $a=new class extends ua{constructor(){super(...arguments),this.active=ha.BOOLEAN(!0,{callback:t=>{Ja.PARAM_CALLBACK_updateRegister(t)},separatorAfter:!0}),this.element=ha.INTEGER(ja.indexOf(Ha.CANVAS),{menu:{entries:ja.map(((t,e)=>({name:t,value:e})))},separatorAfter:!0}),this.auxclick=ha.BOOLEAN(0,qa),this.click=ha.BOOLEAN(0,qa),this.contextmenu=ha.BOOLEAN(0,qa),this.dblclick=ha.BOOLEAN(0,qa),this.mousedown=ha.BOOLEAN(1,qa),this.mouseenter=ha.BOOLEAN(0,qa),this.mouseleave=ha.BOOLEAN(0,qa),this.mousemove=ha.BOOLEAN(1,qa),this.mouseover=ha.BOOLEAN(0,qa),this.mouseout=ha.BOOLEAN(0,qa),this.mouseup=ha.BOOLEAN(1,qa),this.pointerlockchange=ha.BOOLEAN(0,qa),this.pointerlockerror=ha.BOOLEAN(0,qa),this.select=ha.BOOLEAN(0,qa),this.wheel=ha.BOOLEAN(0,qa),this.ctrlKey=ha.BOOLEAN(0,{...qa,separatorBefore:!0}),this.altKey=ha.BOOLEAN(0,qa),this.shiftKey=ha.BOOLEAN(0,qa),this.metaKey=ha.BOOLEAN(0,qa)}};class Ja extends Xa{constructor(){super(...arguments),this.paramsConfig=$a}static type(){return\\\\\\\"mouse\\\\\\\"}acceptedEventTypes(){return Ua.map((t=>`${t}`))}initializeNode(){this.io.outputs.setNamedOutputConnectionPoints(Ua.map((t=>new ta(t,Qo.MOUSE)))),this.scene().dispatchController.onAddListener((()=>{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{const t=[this.p.auxclick,this.p.click,this.p.dblclick,this.p.mousedown,this.p.mouseenter,this.p.mouseleave,this.p.mousemove,this.p.mouseout,this.p.mouseout,this.p.mouseup,this.p.pointerlockchange,this.p.pointerlockerror,this.p.select,this.p.wheel];this.params.label.init(t,(()=>t.map((t=>t.value?t.name():void 0)).filter((t=>t)).join(\\\\\\\", \\\\\\\")))}))}))}processEvent(t){if(!this.pv.active)return;if(!t.event)return;const e=t.event;e.ctrlKey==this.pv.ctrlKey&&e.shiftKey==this.pv.shiftKey&&e.altKey==this.pv.altKey&&e.metaKey==this.pv.metaKey&&this.dispatchEventToOutput(t.event.type,t)}}var Za;!function(t){t.pointerdown=\\\\\\\"pointerdown\\\\\\\",t.pointermove=\\\\\\\"pointermove\\\\\\\",t.pointerup=\\\\\\\"pointerup\\\\\\\"}(Za||(Za={}));const Ka=[Za.pointerdown,Za.pointermove,Za.pointerup];class Qa extends pi{constructor(){super(...arguments),this._require_canvas_event_listeners=!0}type(){return\\\\\\\"pointer\\\\\\\"}acceptedEventTypes(){return Ka.map((t=>`${t}`))}}const tl=new class extends ua{constructor(){super(...arguments),this.active=ha.BOOLEAN(!0,{callback:t=>{el.PARAM_CALLBACK_updateRegister(t)},separatorAfter:!0}),this.element=ha.INTEGER(ja.indexOf(Ha.CANVAS),{menu:{entries:ja.map(((t,e)=>({name:t,value:e})))},separatorAfter:!0}),this.pointerdown=ha.BOOLEAN(1,qa),this.pointermove=ha.BOOLEAN(0,qa),this.pointerup=ha.BOOLEAN(0,qa),this.ctrlKey=ha.BOOLEAN(0,{...qa,separatorBefore:!0}),this.altKey=ha.BOOLEAN(0,qa),this.shiftKey=ha.BOOLEAN(0,qa),this.metaKey=ha.BOOLEAN(0,qa)}};class el extends Xa{constructor(){super(...arguments),this.paramsConfig=tl}static type(){return\\\\\\\"pointer\\\\\\\"}acceptedEventTypes(){return Ka.map((t=>`${t}`))}initializeNode(){this.io.outputs.setNamedOutputConnectionPoints(Ka.map((t=>new ta(t,Qo.POINTER)))),this.scene().dispatchController.onAddListener((()=>{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{const t=[this.p.pointerdown,this.p.pointermove,this.p.pointerup];this.params.label.init(t,(()=>t.map((t=>t.value?t.name():void 0)).filter((t=>t)).join(\\\\\\\", \\\\\\\")))}))}))}processEvent(t){if(!this.pv.active)return;if(!t.event)return;const e=t.event;e.ctrlKey==this.pv.ctrlKey&&e.shiftKey==this.pv.shiftKey&&e.altKey==this.pv.altKey&&e.metaKey==this.pv.metaKey&&this.dispatchEventToOutput(t.event.type,t)}}var nl,il;!function(t){t.SET_FRAME=\\\\\\\"setFrame\\\\\\\"}(nl||(nl={})),function(t){t.TIME_REACHED=\\\\\\\"timeReached\\\\\\\"}(il||(il={}));const sl=new class extends ua{constructor(){super(...arguments),this.active=ha.BOOLEAN(!0,{callback:(t,e)=>{rl.PARAM_CALLBACK_updateRegister(t)},separatorAfter:!0}),this.element=ha.INTEGER(0,{hidden:!0}),this.sceneLoaded=ha.BOOLEAN(1,qa),this.play=ha.BOOLEAN(1,qa),this.pause=ha.BOOLEAN(1,qa),this.tick=ha.BOOLEAN(1,{separatorAfter:!0,...qa}),this.treachedTime=ha.BOOLEAN(0,{callback:t=>{rl.PARAM_CALLBACK_update_time_dependency(t)}}),this.reachedTime=ha.INTEGER(10,{visibleIf:{treachedTime:1},range:[0,100],separatorAfter:!0}),this.setFrameValue=ha.INTEGER(1,{range:[0,100]}),this.setFrame=ha.BUTTON(null,{callback:t=>{rl.PARAM_CALLBACK_setFrame(t)}})}};class rl extends Xa{constructor(){super(...arguments),this.paramsConfig=sl}static type(){return\\\\\\\"scene\\\\\\\"}acceptedEventTypes(){return mi.map((t=>`${t}`))}dispose(){var t;null===(t=this.graph_node)||void 0===t||t.dispose(),super.dispose()}initializeNode(){this.io.inputs.setNamedInputConnectionPoints([new ta(nl.SET_FRAME,Qo.BASE,this._onSetFrame.bind(this)),new ta(_i.PLAY,Qo.BASE,this._play.bind(this)),new ta(_i.PAUSE,Qo.BASE,this._pause.bind(this))]);const t=mi.map((t=>new ta(t,Qo.BASE)));t.push(new ta(il.TIME_REACHED,Qo.BASE)),this.io.outputs.setNamedOutputConnectionPoints(t),this.params.onParamsCreated(\\\\\\\"update_time_dependency\\\\\\\",(()=>{this.update_time_dependency()}))}_onSetFrame(t){this.scene().setFrame(this.pv.setFrameValue)}_play(t){this.scene().play()}_pause(t){this.scene().pause()}_onFrameUpdate(){this.scene().time()>=this.pv.reachedTime&&this.dispatchEventToOutput(il.TIME_REACHED,{})}update_time_dependency(){this.pv.treachedTime?(this.graph_node=this.graph_node||new Mi(this.scene(),\\\\\\\"scene_node_time_graph_node\\\\\\\"),this.graph_node.addGraphInput(this.scene().timeController.graphNode),this.graph_node.addPostDirtyHook(\\\\\\\"time_update\\\\\\\",this._onFrameUpdate.bind(this))):this.graph_node&&this.graph_node.graphDisconnectPredecessors()}static PARAM_CALLBACK_setFrame(t){t._onSetFrame({})}static PARAM_CALLBACK_update_time_dependency(t){t.update_time_dependency()}}var ol;!function(t){t.keydown=\\\\\\\"keydown\\\\\\\",t.keypress=\\\\\\\"keypress\\\\\\\",t.keyup=\\\\\\\"keyup\\\\\\\"}(ol||(ol={}));const al=[ol.keydown,ol.keypress,ol.keyup];class ll extends pi{constructor(){super(...arguments),this._require_canvas_event_listeners=!0}type(){return\\\\\\\"keyboard\\\\\\\"}acceptedEventTypes(){return al.map((t=>`${t}`))}}const cl=new class extends ua{constructor(){super(...arguments),this.active=ha.BOOLEAN(!0,{callback:(t,e)=>{hl.PARAM_CALLBACK_updateRegister(t)},separatorAfter:!0}),this.element=ha.INTEGER(ja.indexOf(Ha.CANVAS),{menu:{entries:ja.map(((t,e)=>({name:t,value:e})))},separatorAfter:!0}),this.keydown=ha.BOOLEAN(1,qa),this.keypress=ha.BOOLEAN(0,qa),this.keyup=ha.BOOLEAN(0,qa),this.keyCodes=ha.STRING(\\\\\\\"Digit1 KeyE ArrowDown\\\\\\\",qa),this.ctrlKey=ha.BOOLEAN(0,qa),this.altKey=ha.BOOLEAN(0,qa),this.shiftKey=ha.BOOLEAN(0,qa),this.metaKey=ha.BOOLEAN(0,qa)}};class hl extends Xa{constructor(){super(...arguments),this.paramsConfig=cl}static type(){return\\\\\\\"keyboard\\\\\\\"}acceptedEventTypes(){return al.map((t=>`${t}`))}initializeNode(){this.io.outputs.setNamedOutputConnectionPoints(al.map((t=>new ta(t,Qo.KEYBOARD)))),this.scene().dispatchController.onAddListener((()=>{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{const t=[this.p.keydown,this.p.keypress,this.p.keyup];this.params.label.init(t.concat([this.p.keyCodes]),(()=>`${t.map((t=>t.value?t.name():void 0)).filter((t=>t)).join(\\\\\\\", \\\\\\\")} (${this.pv.keyCodes})`))}))}))}processEvent(t){if(!this.pv.active)return;if(!t.event)return;const e=t.event;if(e.ctrlKey!=this.pv.ctrlKey)return;if(e.shiftKey!=this.pv.shiftKey)return;if(e.altKey!=this.pv.altKey)return;if(e.metaKey!=this.pv.metaKey)return;if(this.pv.keyCodes.trim().length>0){if(!this.pv.keyCodes.split(\\\\\\\" \\\\\\\").includes(e.code))return}this.dispatchEventToOutput(t.event.type,t)}}var ul;!function(t){t.resize=\\\\\\\"resize\\\\\\\"}(ul||(ul={}));const dl=[ul.resize];class pl extends pi{constructor(){super(...arguments),this._require_canvas_event_listeners=!0}type(){return\\\\\\\"window\\\\\\\"}acceptedEventTypes(){return dl.map((t=>`${t}`))}}const _l=new class extends ua{constructor(){super(...arguments),this.active=ha.BOOLEAN(!0,{callback:t=>{ml.PARAM_CALLBACK_updateRegister(t)},separatorAfter:!0}),this.element=ha.INTEGER(0,{hidden:!0}),this.resize=ha.BOOLEAN(1,qa)}};class ml extends Xa{constructor(){super(...arguments),this.paramsConfig=_l}static type(){return\\\\\\\"window\\\\\\\"}acceptedEventTypes(){return dl.map((t=>`${t}`))}initializeNode(){this.io.outputs.setNamedOutputConnectionPoints(dl.map((t=>new ta(t,Qo.POINTER)))),this.scene().dispatchController.onAddListener((()=>{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{const t=[this.p.resize];this.params.label.init(t,(()=>t.map((t=>t.value?t.name():void 0)).filter((t=>t)).join(\\\\\\\", \\\\\\\")))}))}))}processEvent(t){this.pv.active&&t.event&&this.dispatchEventToOutput(t.event.type,t)}}var fl;!function(t){t.dragover=\\\\\\\"dragover\\\\\\\"}(fl||(fl={}));const gl=[fl.dragover];class vl extends pi{constructor(){super(...arguments),this._require_canvas_event_listeners=!0}type(){return\\\\\\\"drag\\\\\\\"}acceptedEventTypes(){return gl.map((t=>`${t}`))}}var yl;!function(t){t.touchstart=\\\\\\\"touchstart\\\\\\\",t.touchmove=\\\\\\\"touchmove\\\\\\\",t.touchend=\\\\\\\"touchend\\\\\\\"}(yl||(yl={}));const xl=[yl.touchstart,yl.touchmove,yl.touchend];class bl extends pi{constructor(){super(...arguments),this._require_canvas_event_listeners=!0}type(){return\\\\\\\"touch\\\\\\\"}acceptedEventTypes(){return xl.map((t=>`${t}`))}}const wl=new class extends ua{constructor(){super(...arguments),this.active=ha.BOOLEAN(!0,{callback:t=>{Tl.PARAM_CALLBACK_updateRegister(t)},separatorAfter:!0}),this.element=ha.INTEGER(ja.indexOf(Ha.CANVAS),{menu:{entries:ja.map(((t,e)=>({name:t,value:e})))},separatorAfter:!0}),this.dragover=ha.BOOLEAN(1,qa),this.ctrlKey=ha.BOOLEAN(0,{...qa,separatorBefore:!0}),this.altKey=ha.BOOLEAN(0,qa),this.shiftKey=ha.BOOLEAN(0,qa),this.metaKey=ha.BOOLEAN(0,qa)}};class Tl extends Xa{constructor(){super(...arguments),this.paramsConfig=wl}static type(){return\\\\\\\"drag\\\\\\\"}acceptedEventTypes(){return gl.map((t=>`${t}`))}initializeNode(){this.io.outputs.setNamedOutputConnectionPoints(gl.map((t=>new ta(t,Qo.DRAG)))),this.scene().dispatchController.onAddListener((()=>{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{const t=[this.p.dragover];this.params.label.init(t,(()=>t.map((t=>t.value?t.name():void 0)).filter((t=>t)).join(\\\\\\\", \\\\\\\")))}))}))}processEvent(t){if(!this.pv.active)return;if(!t.event)return;const e=t.event;e.ctrlKey==this.pv.ctrlKey&&e.shiftKey==this.pv.shiftKey&&e.altKey==this.pv.altKey&&e.metaKey==this.pv.metaKey&&this.dispatchEventToOutput(t.event.type,t)}}const Al=new class extends ua{constructor(){super(...arguments),this.active=ha.BOOLEAN(!0,{callback:t=>{Ml.PARAM_CALLBACK_updateRegister(t)},separatorAfter:!0}),this.element=ha.INTEGER(ja.indexOf(Ha.CANVAS),{menu:{entries:ja.map(((t,e)=>({name:t,value:e})))},separatorAfter:!0}),this.touchstart=ha.BOOLEAN(1,qa),this.touchmove=ha.BOOLEAN(0,qa),this.touchend=ha.BOOLEAN(0,qa)}};class Ml extends Xa{constructor(){super(...arguments),this.paramsConfig=Al}static type(){return\\\\\\\"touch\\\\\\\"}acceptedEventTypes(){return xl.map((t=>`${t}`))}initializeNode(){this.io.outputs.setNamedOutputConnectionPoints(xl.map((t=>new ta(t,Qo.DRAG)))),this.scene().dispatchController.onAddListener((()=>{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{const t=[this.p.touchstart,this.p.touchmove,this.p.touchend];this.params.label.init(t,(()=>t.map((t=>t.value?t.name():void 0)).filter((t=>t)).join(\\\\\\\", \\\\\\\")))}))}))}processEvent(t){this.pv.active&&t.event&&this.dispatchEventToOutput(t.event.type,t)}}class El{constructor(t){this.scene=t,this._controllers=[]}registerEventNode(t){const e=this._find_or_create_controller_for_node(t);e&&e.registerNode(t)}unregisterEventNode(t){const e=this._find_or_create_controller_for_node(t);e&&e.unregisterNode(t)}updateViewerEventListeners(t){const e=this._find_or_create_controller_for_node(t);e&&e.updateViewerEventListeners()}traverseControllers(t){for(let e of this._controllers)t(e)}_find_or_create_controller_for_node(t){switch(t.type()){case hl.type():return this.keyboardEventsController;case Ja.type():return this.mouseEventsController;case Tl.type():return this.dragEventsController;case el.type():return this.pointerEventsController;case rl.type():return this.sceneEventsController;case Ml.type():return this.touchEventsController;case ml.type():return this.windowEventsController}}get keyboardEventsController(){return this._keyboard_events_controller=this._keyboard_events_controller||this._create_controller(ll)}get mouseEventsController(){return this._mouse_events_controller=this._mouse_events_controller||this._create_controller(Ga)}get dragEventsController(){return this._drag_events_controller=this._drag_events_controller||this._create_controller(vl)}get pointerEventsController(){return this._pointer_events_controller=this._pointer_events_controller||this._create_controller(Qa)}get sceneEventsController(){return this._scene_events_controller=this._scene_events_controller||this._create_controller(fi)}get windowEventsController(){return this._window_events_controller=this._window_events_controller||this._create_controller(pl)}get touchEventsController(){return this._touch_events_controller=this._touch_events_controller||this._create_controller(bl)}_create_controller(t){const e=new t(this);return this._controllers.includes(e)||this._controllers.push(e),e}}class Sl{constructor(t){this.scene=t,this._referenced_nodes_by_src_param_id=new Map,this._referencing_params_by_referenced_node_id=new Map,this._referencing_params_by_all_named_node_ids=new Map}setReferenceFromParam(t,e){this._referenced_nodes_by_src_param_id.set(t.graphNodeId(),e),h.pushOnArrayAtEntry(this._referencing_params_by_referenced_node_id,e.graphNodeId(),t)}setNamedNodesFromParam(t){const e=t.decomposed_path.named_nodes();for(let n of e)h.pushOnArrayAtEntry(this._referencing_params_by_all_named_node_ids,n.graphNodeId(),t)}resetReferenceFromParam(t){const e=this._referenced_nodes_by_src_param_id.get(t.graphNodeId());if(e){h.popFromArrayAtEntry(this._referencing_params_by_referenced_node_id,e.graphNodeId(),t);const n=t.decomposed_path.named_nodes();for(let e of n)h.popFromArrayAtEntry(this._referencing_params_by_all_named_node_ids,e.graphNodeId(),t);this._referenced_nodes_by_src_param_id.delete(t.graphNodeId())}}referencing_params(t){return this._referencing_params_by_referenced_node_id.get(t.graphNodeId())}referencing_nodes(t){const e=this._referencing_params_by_referenced_node_id.get(t.graphNodeId());if(e){const t=new Map;for(let n of e){const e=n.node;t.set(e.graphNodeId(),e)}const n=[];return t.forEach((t=>{n.push(t)})),n}}nodes_referenced_by(t){const e=new Set([Cr.OPERATOR_PATH,Cr.NODE_PATH]),n=[];for(let i of t.params.all)e.has(i.type())&&n.push(i);const i=new Map,s=[];for(let t of n)this._check_param(t,i,s);for(let t of s)i.set(t.node.graphNodeId(),t.node);const r=[];return i.forEach((t=>{r.push(t)})),r}_check_param(t,e,n){if(t instanceof fo){const i=t.found_node(),s=t.found_param();return i&&e.set(i.graphNodeId(),i),void(s&&n.push(s))}}notifyNameUpdated(t){const e=this._referencing_params_by_all_named_node_ids.get(t.graphNodeId());if(e){const n=f.shallowClone(e);for(let e of n)e.notifyPathRebuildRequired(t)}}notifyParamsUpdated(t){const e=this._referencing_params_by_all_named_node_ids.get(t.graphNodeId());if(e){const n=f.shallowClone(e);for(let e of n)e.options.isSelectingParam()&&e.notifyTargetParamOwnerParamsUpdated(t)}}}var Cl;!function(t){t.MAX_FRAME_UPDATED=\\\\\\\"scene_maxFrameUpdated\\\\\\\",t.REALTIME_STATUS_UPDATED=\\\\\\\"scene_realtime_status_updated\\\\\\\",t.FRAME_UPDATED=\\\\\\\"scene_frame_updated\\\\\\\",t.PLAY_STATE_UPDATED=\\\\\\\"scene_play_state_updated\\\\\\\"}(Cl||(Cl={}));class Nl{constructor(t){this.scene=t,this._frame=0,this._time=0,this._realtimeState=!0,this._maxFrame=600,this._maxFrameLocked=!1,this._playing=!1,this._delta=0,this._graph_node=new Mi(t,\\\\\\\"time controller\\\\\\\")}get PLAY_EVENT_CONTEXT(){return this._PLAY_EVENT_CONTEXT=this._PLAY_EVENT_CONTEXT||{event:new Event(_i.PLAY)}}get PAUSE_EVENT_CONTEXT(){return this._PAUSE_EVENT_CONTEXT=this._PAUSE_EVENT_CONTEXT||{event:new Event(_i.PAUSE)}}get TICK_EVENT_CONTEXT(){return this._TICK_EVENT_CONTEXT=this._TICK_EVENT_CONTEXT||{event:new Event(_i.TICK)}}get graphNode(){return this._graph_node}frame(){return this._frame}time(){return this._time}maxFrame(){return this._maxFrame}maxFrameLocked(){return this._maxFrameLocked}realtimeState(){return this._realtimeState}setMaxFrame(t){this._maxFrame=Math.floor(t),this.scene.dispatchController.dispatch(this._graph_node,Cl.MAX_FRAME_UPDATED)}setMaxFrameLocked(t){this._maxFrameLocked=t,this.scene.dispatchController.dispatch(this._graph_node,Cl.MAX_FRAME_UPDATED)}setRealtimeState(t){this._realtimeState=t,this.scene.dispatchController.dispatch(this._graph_node,Cl.REALTIME_STATUS_UPDATED)}setTime(t,e=!0){var n,i;if(t!=this._time){if(this._time=t,null===(n=this._onBeforeTickCallbacks)||void 0===n||n.forEach((t=>t(this._delta))),e){const t=Math.floor(60*this._time),e=this._ensureFrameWithinBounds(t);t!=e?this.setFrame(e,!0):this._frame=t}this.scene.dispatchController.dispatch(this._graph_node,Cl.FRAME_UPDATED),this.scene.uniformsController.updateTimeDependentUniformOwners(),this.scene.cooker.block(),this.graphNode.setSuccessorsDirty(),this.scene.cooker.unblock(),this.scene.eventsDispatcher.sceneEventsController.processEvent(this.TICK_EVENT_CONTEXT),null===(i=this._onAfterTickCallbacks)||void 0===i||i.forEach((t=>t(this._delta)))}}setFrame(t,e=!0){t!=this._frame&&(t=this._ensureFrameWithinBounds(t))!=this._frame&&(this._frame=t,e&&this.setTime(this._frame/60,!1))}setFrameToStart(){this.setFrame(Nl.START_FRAME,!0)}incrementTimeIfPlaying(t){this._playing&&(this.scene.root().areChildrenCooking()||this.incrementTime(t))}incrementTime(t){if(this._realtimeState){this._delta=t;const e=this._time+this._delta;this.setTime(e)}else this.setFrame(this.frame()+1)}_ensureFrameWithinBounds(t){if(this._playing){if(this._maxFrameLocked&&t>this._maxFrame)return Nl.START_FRAME}else{if(this._maxFrameLocked&&t>this._maxFrame)return this._maxFrame;if(t=0&&this._time_dependent_uniform_owners_ids.splice(e,1)}}updateTimeDependentUniformOwners(){const t=this.scene.time();if(this._time_dependent_uniform_owners_ids)for(let e of this._time_dependent_uniform_owners_ids){this._time_dependent_uniform_owners[e].time.value=t}}addResolutionDependentUniformOwner(t,e){this._resolution_dependent_uniform_owners[t]=e,this._resolution_dependent_uniform_owners_ids||(this._resolution_dependent_uniform_owners_ids=[]),this._resolution_dependent_uniform_owners_ids.includes(t)||this._resolution_dependent_uniform_owners_ids.push(t),this._resolution&&this.updateResolutionDependentUniforms(e)}removeResolutionDependentUniformOwner(t){if(delete this._resolution_dependent_uniform_owners[t],this._resolution_dependent_uniform_owners_ids){const e=this._resolution_dependent_uniform_owners_ids.indexOf(t);e>=0&&this._resolution_dependent_uniform_owners_ids.splice(e,1)}}updateResolutionDependentUniformOwners(t){this._resolution.copy(t);for(let t of this._resolution_dependent_uniform_owners_ids){const e=this._resolution_dependent_uniform_owners[t];this.updateResolutionDependentUniforms(e)}}updateResolutionDependentUniforms(t){t.resolution.value.x=this._resolution.x,t.resolution.value.y=this._resolution.y}}class Ol{constructor(t){this.scene=t,this._viewers_by_id=new Map}registerViewer(t){this._viewers_by_id.set(t.id(),t)}unregisterViewer(t){this._viewers_by_id.delete(t.id())}traverseViewers(t){this._viewers_by_id.forEach(t)}}class Pl{constructor(){this._require_webgl2=!1}require_webgl2(){return this._require_webgl2}set_require_webgl2(){this._require_webgl2||(this._require_webgl2=!0,li.renderersController.setRequireWebGL2())}}class Rl{constructor(t){this._scene=t,this._onWindowResizeBound=this._onWindowResize.bind(this)}graphNode(){return this._coreGraphNode=this._coreGraphNode||this._createGraphNode()}_createGraphNode(){const t=new Mi(this._scene,\\\\\\\"SceneWindowController\\\\\\\");return window.addEventListener(\\\\\\\"resize\\\\\\\",this._onWindowResizeBound),t}_onWindowResize(){this.graphNode().setSuccessorsDirty()}dispose(){window.removeEventListener(\\\\\\\"resize\\\\\\\",this._onWindowResizeBound)}}class Il{constructor(){this._params_by_id=new Map,this._assets_root=null}register_param(t){this._params_by_id.set(t.graphNodeId(),t)}deregister_param(t){this._params_by_id.delete(t.graphNodeId())}traverse_params(t){this._params_by_id.forEach(((e,n)=>{t(e)}))}root(){return this._assets_root}setRoot(t){\\\\\\\"\\\\\\\"==t&&(t=null),this._assets_root=t}}class Fl{constructor(){this._cameras_controller=new r(this),this._cooker=new o(this),this.cookController=new a,this._graph=new l,this._missing_expression_references_controller=new Ti(this),this._expressions_controller=new ui,this._nodes_controller=new Ba(this),this._objects_controller=new da(this),this._references_controller=new Sl(this),this._time_controller=new Nl(this),this._read_only=!1,this._graph.setScene(this),this.nodesController.init()}threejsScene(){return this.root().object}setUuid(t){return this._uuid=t}get uuid(){return this._uuid}setName(t){return t=ss.sanitizeName(t),this._name=t}name(){return this._name}get camerasController(){return this._cameras_controller}mainCameraNode(){return this.camerasController.mainCameraNode()}get cooker(){return this._cooker}get assets(){return this._assets_controller=this._assets_controller||new Il}async waitForCooksCompleted(){return this.cookController.waitForCooksCompleted()}get dispatchController(){return this._dispatch_controller=this._dispatch_controller||new hi(this)}get eventsDispatcher(){return this._events_dispatcher=this._events_dispatcher||new El(this)}get graph(){return this._graph}get lifecycleController(){return this._lifecycle_controller=this._lifecycle_controller||new di(this)}get loadingController(){return this._loading_controller=this._loading_controller||new gi(this)}get missingExpressionReferencesController(){return this._missing_expression_references_controller}get expressionsController(){return this._expressions_controller}get nodesController(){return this._nodes_controller}createNode(t,e){return this.root().createNode(t,e)}nodesByType(t){return this.nodesController.nodesByType(t)}get objectsController(){return this._objects_controller}findObjectByMask(t){return this._objects_controller.findObjectByMask(t)}objectsByMask(t){return this._objects_controller.objectsByMask(t)}get referencesController(){return this._references_controller}get performance(){return this._performance=this._performance||new ci}get viewersRegister(){return this._viewers_register=this._viewers_register||new Ol(this)}get timeController(){return this._time_controller}setFrame(t){this.timeController.setFrame(t)}setFrameToStart(){this.timeController.setFrameToStart()}frame(){return this.timeController.frame()}time(){return this.timeController.time()}maxFrame(){return this.timeController.maxFrame()}play(){this.timeController.play()}pause(){this.timeController.pause()}get serializer(){return this._serializer=this._serializer||new za(this)}toJSON(){return this.serializer.toJSON()}markAsReadOnly(t){this._read_only||(this._read_only_requester=t,this._read_only=!0)}readOnly(){return this._read_only}readOnlyRequester(){return this._read_only_requester}get uniformsController(){return this._uniformsController=this._uniformsController||new Ll(this)}get webgl_controller(){return this._webgl_controller=this._webgl_controller||new Pl}get windowController(){return this._windowController=this._windowController||new Rl(this)}dispose(){var t;null===(t=this._windowController)||void 0===t||t.dispose()}batchUpdates(t){this._cooker.block(),t(),this._cooker.unblock()}node(t){return this.nodesController.node(t)}root(){return this.nodesController.root()}registerOnBeforeTick(t,e){this.timeController.registerOnBeforeTick(t,e)}unRegisterOnBeforeTick(t){this.timeController.unRegisterOnBeforeTick(t)}registeredBeforeTickCallbacks(){return this.timeController.registeredBeforeTickCallbacks()}registerOnAfterTick(t,e){this.timeController.registerOnAfterTick(t,e)}unRegisterOnAfterTick(t){this.timeController.unRegisterOnAfterTick(t)}registeredAfterTickCallbacks(){return this.timeController.registeredAfterTickCallbacks()}}class Dl{constructor(t){this._param=t}process_data(t){const e=t.raw_input;void 0!==e&&this._param.set(e),this.add_main(t)}add_main(t){}static spare_params_data(t){return this.params_data(!0,t)}static non_spare_params_data_value(t){return this.params_data_value(!1,t)}static params_data(t,e){let n;if(e){n={};const t=Object.keys(e);let i;for(let s of t)i=e[s],i&&(n[s]=e)}return n}static params_data_value(t,e){let n;if(e){n={};const i=Object.keys(e);let s;for(let r of i)if(s=e[r],null!=s){const e=s.options,i=s.overriden_options;if(e||i){const o=s;e&&e.spare==t?null!=o.raw_input&&(n[r]={complex_data:o}):i&&(n[r]={complex_data:o})}else{const t=s;(i||null!=t)&&(n[r]={simple_data:t})}}}return n}}const Bl=\\\\\\\"operationsComposer\\\\\\\";class zl{constructor(t,e,n){this._scene=t,this.states=e,this._node=n}static type(){throw\\\\\\\"type to be overriden\\\\\\\"}type(){return this.constructor.type()}static context(){throw console.error(\\\\\\\"operation has no node_context\\\\\\\",this),\\\\\\\"context requires override\\\\\\\"}context(){return this.constructor.context()}scene(){return this._scene}cook(t,e){}}zl.DEFAULT_PARAMS={},zl.INPUT_CLONED_STATE=[];class kl{constructor(t){this._node=t,this._nodes=[],this._optimized_root_node_names=new Set,this._operation_containers_by_name=new Map,this._node_inputs=[]}nodes(){return this._nodes}process_data(t,e){var n,i,s;if(!e)return;if(!this._node.childrenAllowed()||!this._node.childrenController)return;const{optimized_names:r}=kl.child_names_by_optimized_state(e);this._nodes=[],this._optimized_root_node_names=new Set;for(let t of r)kl.is_optimized_root_node(e,t)&&this._optimized_root_node_names.add(t);for(let r of this._optimized_root_node_names){const o=e[r],a=this._node.createNode(Bl);if(a){a.setName(r),this._nodes.push(a),(null===(n=o.flags)||void 0===n?void 0:n.display)&&(null===(s=null===(i=a.flags)||void 0===i?void 0:i.display)||void 0===s||s.set(!0));const e=this._create_operation_container(t,a,o,a.name());a.set_output_operation_container(e)}}for(let n of this._nodes){const i=n.output_operation_container();if(i){this._node_inputs=[],this._add_optimized_node_inputs(t,n,e,n.name(),i),n.io.inputs.setCount(this._node_inputs.length);for(let t=0;t0}static is_optimized_root_node(t,e){const n=this.node_outputs(t,e);let i=0;return n.forEach((e=>{const n=t[e];this.is_node_optimized(n)||i++})),this.is_optimized_root_node_generic({outputs_count:n.size,non_optimized_count:i})}static is_optimized_root_node_from_node(t){var e,n,i,s;if(!(null===(n=null===(e=t.flags)||void 0===e?void 0:e.optimize)||void 0===n?void 0:n.active()))return!1;const r=t.io.connections.outputConnections().map((t=>t.node_dest));let o=0;for(let t of r)(null===(s=null===(i=t.flags)||void 0===i?void 0:i.optimize)||void 0===s?void 0:s.active())||o++;return this.is_optimized_root_node_generic({outputs_count:r.length,non_optimized_count:o})}static node_outputs(t,e){const n=Object.keys(t),i=new Set;for(let s of n)if(s!=e){const n=t[s].inputs;if(n)for(let t of n)if(m.isString(t)){t==e&&i.add(s)}}return i}_create_operation_container(t,e,n,i){const s=Dl.non_spare_params_data_value(n.params),r=kl.operation_type(n),o=this._node.create_operation_container(r,i,s);return o&&(this._operation_containers_by_name.set(i,o),o.path_param_resolve_required()&&(e.add_operation_container_with_path_param_resolve_required(o),t.add_operations_composer_node_with_path_param_resolve_required(e))),o}static operation_type(t){return kl.is_node_bypassed(t)?\\\\\\\"null\\\\\\\":t.type}static is_node_optimized(t){const e=t.flags;return!(!e||!e.optimize)}static is_node_bypassed(t){const e=t.flags;return!(!e||!e.bypass)}}class Ul{constructor(t){this._node=t}process_data(t,e){var n;if(!e)return;if(!this._node.childrenAllowed()||!this._node.childrenController)return;const{optimized_names:i,non_optimized_names:s}=kl.child_names_by_optimized_state(e),r=[];for(let n of s){const i=e[n],s=i.type.toLowerCase(),o=Dl.non_spare_params_data_value(i.params);try{const t=this._node.createNode(s,o);t&&(t.setName(n),r.push(t))}catch(e){console.error(`error importing node: cannot create with type ${s}`,e);const i=ss.camelCase(s);try{const t=this._node.createNode(i,o);t&&(t.setName(n),r.push(t))}catch(e){const a=`${s}Network`;try{const t=this._node.createNode(a,o);t&&(t.setName(n),r.push(t))}catch(e){const n=`failed to create node with type '${s}', '${i}' or '${a}'`;t.report.addWarning(n),li.warn(n,e)}}}}if(i.length>0){const i=new kl(this._node);if(i.process_data(t,e),this._node.childrenController.context==ts.SOP){const t=Object.keys(e);let s;for(let i of t){(null===(n=e[i].flags)||void 0===n?void 0:n.display)&&(s=i)}if(s){const t=r.map((t=>t.name())),e=i.nodes();for(let n of e)t.push(n.name());if(!t.includes(s)){const t=`node '${`${this._node.path()}/${s}`}' with display flag has been optimized and does not exist in player mode`;console.error(t)}}}}const o=new Map;for(let n of r){if(e[n.name()]){const i=Yl.dispatch_node(n);o.set(n.name(),i),i.process_data(t,e[n.name()])}else li.warn(`possible import error for node ${n.name()}`)}for(let t of r){const n=o.get(t.name());n&&n.process_inputs_data(e[t.name()])}}}const Gl=[\\\\\\\"overriden_options\\\\\\\",\\\\\\\"type\\\\\\\"];class Vl{constructor(t){this._node=t}process_data(t,e){if(this.set_connection_points(e.connection_points),this._node.childrenAllowed()&&this.create_nodes(t,e.nodes),this.set_selection(e.selection),this._node.io.inputs.overrideClonedStateAllowed()){const t=e.cloned_state_overriden;t&&this._node.io.inputs.overrideClonedState(t)}this.set_flags(e),this.set_params(e.params),e.persisted_config&&this.set_persisted_config(e.persisted_config),this.from_data_custom(e)}process_inputs_data(t){const e=t.maxInputsCount;if(null!=e){const t=this._node.io.inputs.minCount();this._node.io.inputs.setCount(t,e)}this.setInputs(t.inputs)}process_ui_data(t,e){if(!e)return;if(li.playerMode())return;const n=this._node.uiData,i=e.pos;if(i){const t=(new d.a).fromArray(i);n.setPosition(t)}const s=e.comment;s&&n.setComment(s),this._node.childrenAllowed()&&this.process_nodes_ui_data(t,e.nodes)}create_nodes(t,e){if(!e)return;new Ul(this._node).process_data(t,e)}set_selection(t){if(this._node.childrenAllowed()&&this._node.childrenController&&t&&t.length>0){const e=[];t.forEach((t=>{const n=this._node.node(t);n&&e.push(n)})),this._node.childrenController.selection.set(e)}}set_flags(t){var e,n,i,s,r,o;const a=t.flags;if(a){const t=a.bypass;null!=t&&(null===(n=null===(e=this._node.flags)||void 0===e?void 0:e.bypass)||void 0===n||n.set(t));const l=a.display;null!=l&&(null===(s=null===(i=this._node.flags)||void 0===i?void 0:i.display)||void 0===s||s.set(l));const c=a.optimize;null!=c&&(null===(o=null===(r=this._node.flags)||void 0===r?void 0:r.optimize)||void 0===o||o.set(c))}}set_connection_points(t){t&&(t.in&&this._node.io.saved_connection_points_data.set_in(t.in),t.out&&this._node.io.saved_connection_points_data.set_out(t.out),this._node.io.has_connection_points_controller&&this._node.io.connection_points.update_signature_if_required())}setInputs(t){if(!t)return;let e;for(let n=0;n0,s=n.toAdd&&n.toAdd.length>0;if(i||s){this._node.params.updateParams(n);for(let e of this._node.params.spare){const n=t[e.name()];!e.parent_param&&n&&(this._is_param_data_complex(n)?this._process_param_data_complex(e.name(),n):this._process_param_data_simple(e.name(),n))}}this._node.params.runOnSceneLoadHooks()}_process_param_data_simple(t,e){var n;null===(n=this._node.params.get(t))||void 0===n||n.set(e)}_process_param_data_complex(t,e){const n=this._node.params.get(t);n&&Yl.dispatch_param(n).process_data(e)}_is_param_data_complex(t){if(m.isString(t)||m.isNumber(t)||m.isArray(t)||m.isBoolean(t))return!1;if(m.isObject(t)){const e=Object.keys(t);for(let t of Gl)if(e.includes(t))return!0}return!1}set_persisted_config(t){this._node.persisted_config&&this._node.persisted_config.load(t)}from_data_custom(t){}}class Hl extends Dl{add_main(t){}}const jl=/\\\\\\\\n+/g;class Wl extends Dl{add_main(t){let e=t.raw_input;void 0!==e&&(e=e.replace(jl,\\\\\\\"\\\\n\\\\\\\"),this._param.set(e))}}class ql extends Dl{add_main(t){const e=t.raw_input;e&&this._param.set(e)}}class Xl extends Vl{create_nodes(t,e){const n=this._node.polyNodeController;n&&n.createChildNodesFromDefinition()}}class Yl{static dispatch_node(t){return t.polyNodeController?new Xl(t):new Vl(t)}static dispatch_param(t){return t instanceof ao?new Hl(t):t instanceof Mo?new Wl(t):t instanceof Ao?new ql(t):new Dl(t)}}class $l{constructor(t){this._warnings=[]}warnings(){return this._warnings}reset(){this._warnings=[]}addWarning(t){this._warnings.push(t)}}class Jl{constructor(t){this._data=t,this.report=new $l(this)}static async loadData(t){const e=new Jl(t);return await e.scene()}async scene(){const t=new Fl;t.loadingController.markAsLoading();const e=this._data.properties;if(e){const n=e.maxFrame||600;t.timeController.setMaxFrame(n);const i=e.maxFrameLocked;i&&t.timeController.setMaxFrameLocked(i);const s=e.realtimeState;null!=s&&t.timeController.setRealtimeState(s),t.setFrame(e.frame||Nl.START_FRAME),e.mainCameraNodePath&&t.camerasController.setMainCameraNodePath(e.mainCameraNodePath)}t.cooker.block(),this._base_operations_composer_nodes_with_resolve_required=void 0;const n=Yl.dispatch_node(t.root());return this._data.root&&n.process_data(this,this._data.root),this._data.ui&&n.process_ui_data(this,this._data.ui),this._resolve_operation_containers_with_path_param_resolve(),await t.loadingController.markAsLoaded(),t.cooker.unblock(),t}add_operations_composer_node_with_path_param_resolve_required(t){this._base_operations_composer_nodes_with_resolve_required||(this._base_operations_composer_nodes_with_resolve_required=[]),this._base_operations_composer_nodes_with_resolve_required.push(t)}_resolve_operation_containers_with_path_param_resolve(){if(this._base_operations_composer_nodes_with_resolve_required)for(let t of this._base_operations_composer_nodes_with_resolve_required)t.resolve_operation_containers_path_params()}}class Zl{static async importSceneData(t){null==t.editorMode&&(t.editorMode=!1);const{manifest:e,urlPrefix:n}=t,i=Object.keys(e.nodes),s=[];for(let t of i){const i=`${n}/root/${t}.json?t=${e.nodes[t]}`;s.push(i)}const r=[`${n}/root.json?t=${e.root}`,`${n}/properties.json?t=${e.properties}`];if(t.editorMode){const t=Date.now();r.push(`${n}/ui.json?t=${t}`)}for(let t of s)r.push(t);let o=0;const a=r.length,l=r.map((async e=>{const n=await fetch(e);return t.onProgress&&(o++,t.onProgress({count:o,total:a})),n})),c=await Promise.all(l),h=[];for(let t of c)h.push(await t.json());const u={root:h[0],properties:h[1]};let d=2;t.editorMode&&(u.ui=h[2],d+=1);const p={},_=Object.keys(e.nodes);for(let t=0;t<_.length;t++){const e=_[t],n=h[t+d];p[e]=n}return this.assemble(u,_,p)}static async assemble(t,e,n){const i={root:t.root,properties:t.properties,ui:t.ui};for(let t=0;t{r.matrixAutoUpdate=!0},c.onComplete=()=>{r.matrixAutoUpdate=t,r.matrixAutoUpdate||r.updateMatrix()}}if(o instanceof hh.a&&this._targetValue instanceof hh.a){const t={value:0},e=o,n=(new hh.a).copy(o),i=this._targetValue;c.onUpdate=()=>{e.slerpQuaternions(n,i,t.value)},a=t,c.value=1}if(m.isNumber(this._targetValue)){if(m.isNumber(o))for(let t of l)c[t]=this.withOp(o,this._targetValue,i)}else if(!m.isNumber(o))for(let t of l)c[t]=this.withOp(o[t],this._targetValue[t],i);a&&this._startTimeline(e,n,c,a)}}}_sceneGraphProps(t,e){const n=e.split(\\\\\\\".\\\\\\\");if(!(n.length>1)){const n=t[e];let i=null;const s=[];return m.isNumber(n)?(i=t,s.push(e)):(i=n,this._targetValue instanceof d.a&&s.push(\\\\\\\"x\\\\\\\",\\\\\\\"y\\\\\\\"),this._targetValue instanceof p.a&&s.push(\\\\\\\"x\\\\\\\",\\\\\\\"y\\\\\\\",\\\\\\\"z\\\\\\\"),this._targetValue instanceof _.a&&s.push(\\\\\\\"x\\\\\\\",\\\\\\\"y\\\\\\\",\\\\\\\"z\\\\\\\",\\\\\\\"w\\\\\\\"),this._targetValue,hh.a),{targetProperty:n,toTarget:i,propertyNames:s}}{const e=t[n.shift()];if(e){const t=n.join(\\\\\\\".\\\\\\\");return this._sceneGraphProps(e,t)}}}_populateWithNode(t,e,n){this._printDebug([\\\\\\\"_populateWithNode\\\\\\\",t]);const i=t.p[this._propertyName];this._printDebug([\\\\\\\"targetParam\\\\\\\",i]),i?i&&this._populateVarsForParam(i,e,n):li.warn(`${this._propertyName} not found on node ${t.path()}`)}_populateVarsForParam(t,e,n){switch(this._printDebug([\\\\\\\"_populateVarsForParam\\\\\\\",t]),t.type()){case Cr.INTEGER:return this._populateVarsForParamInteger(t,e,n);case Cr.FLOAT:return this._populateVarsForParamFloat(t,e,n);case Cr.VECTOR2:return this._populateVarsForParamVector2(t,e,n);case Cr.VECTOR3:return this._populateVarsForParamVector3(t,e,n);case Cr.COLOR:return this._populateVarsForParamColor(t,e,n);case Cr.VECTOR4:return this._populateVarsForParamVector4(t,e,n)}li.warn(`param type cannot be animated (yet): '${t.type()}' '${t.path()}'`)}_populateVarsForParamInteger(t,e,n){if(!m.isNumber(this._targetValue))return void li.warn(`TimelineBuilderProperty error: cannot animate integer param '${t.path()}' with targetValue`,this._targetValue);const i=this._commonVars(e),s={num:t.value};i.onUpdate=()=>{t.set(s.num)};const r=e.operation();i.num=this.withOp(t.value,this._targetValue,r),this._startTimeline(e,n,i,s)}_populateVarsForParamFloat(t,e,n){if(!m.isNumber(this._targetValue))return void li.warn(`TimelineBuilderProperty error: cannot animate float param '${t.path()}' with targetValue`,this._targetValue);const i=this._commonVars(e),s={num:t.value};i.onUpdate=()=>{t.set(s.num)};const r=e.operation();i.num=this.withOp(t.value,this._targetValue,r),this._startTimeline(e,n,i,s)}_populateVarsForParamVector2(t,e,n){if(!(this._targetValue instanceof d.a))return void li.warn(`TimelineBuilderProperty error: cannot animate vector2 param '${t.path()}' with targetValue`,this._targetValue);const i=this._commonVars(e),s=t.value.clone(),r=[0,0];i.onUpdate=()=>{s.toArray(r),t.set(r)};const o=e.operation();i.x=this.withOp(t.value.x,this._targetValue.x,o),i.y=this.withOp(t.value.y,this._targetValue.y,o),this._startTimeline(e,n,i,s)}_populateVarsForParamVector3(t,e,n){if(!(this._targetValue instanceof p.a))return void li.warn(`TimelineBuilderProperty error: cannot animate vector3 param '${t.path()}' with targetValue`,this._targetValue);const i=this._commonVars(e),s=t.value.clone(),r=[0,0,0];i.onUpdate=()=>{s.toArray(r),t.set(r)};const o=e.operation();i.x=this.withOp(t.value.x,this._targetValue.x,o),i.y=this.withOp(t.value.y,this._targetValue.y,o),i.z=this.withOp(t.value.z,this._targetValue.z,o),this._startTimeline(e,n,i,s)}_populateVarsForParamVector4(t,e,n){if(!(this._targetValue instanceof _.a))return void li.warn(`TimelineBuilderProperty error: cannot animate vector4 param '${t.path()}' with targetValue`,this._targetValue);const i=this._commonVars(e),s=t.value.clone(),r=[0,0,0,0];i.onUpdate=()=>{s.toArray(r),t.set(r)};const o=e.operation();i.x=this.withOp(t.value.x,this._targetValue.x,o),i.y=this.withOp(t.value.y,this._targetValue.y,o),i.z=this.withOp(t.value.z,this._targetValue.z,o),i.w=this.withOp(t.value.w,this._targetValue.w,o),this._startTimeline(e,n,i,s)}_populateVarsForParamColor(t,e,n){if(!(this._targetValue instanceof p.a))return void li.warn(`TimelineBuilderProperty error: cannot animate color param '${t.path()}' with targetValue`,this._targetValue);const i=this._commonVars(e),s=t.valuePreConversion(),r=new p.a(s.r,s.g,s.b),o=[0,0,0];i.onUpdate=()=>{r.toArray(o),t.set(o)};const a=e.operation();i.x=this.withOp(t.value.r,this._targetValue.x,a),i.y=this.withOp(t.value.g,this._targetValue.y,a),i.z=this.withOp(t.value.b,this._targetValue.z,a),this._startTimeline(e,n,i,r)}withOp(t,e,n){switch(n){case I_.SET:return e;case I_.ADD:return t+e;case I_.SUBSTRACT:return t-e}os.unreachable(n)}_commonVars(t){const e={duration:t.duration()},n=t.easing()||ch.NONE;n&&(e.ease=n);const i=t.delay();null!=i&&(e.delay=i);const s=t.repeatParams();return s&&(e.repeat=s.count,e.repeatDelay=s.delay,e.yoyo=s.yoyo),e}_startTimeline(t,e,n,i){const s=t.position(),r=s?s.toParameter():void 0;e.to(i,n,r)}}function mh(t){if(void 0===t)throw new ReferenceError(\\\\\\\"this hasn't been initialised - super() hasn't been called\\\\\\\");return t}function fh(t,e){t.prototype=Object.create(e.prototype),t.prototype.constructor=t,t.__proto__=e}var gh,vh,yh,xh,bh,wh,Th,Ah,Mh,Eh,Sh,Ch,Nh,Lh={autoSleep:120,force3D:\\\\\\\"auto\\\\\\\",nullTargetWarn:1,units:{lineHeight:\\\\\\\"\\\\\\\"}},Oh={duration:.5,overwrite:!1,delay:0},Ph=1e8,Rh=1e-8,Ih=2*Math.PI,Fh=Ih/4,Dh=0,Bh=Math.sqrt,zh=Math.cos,kh=Math.sin,Uh=function(t){return\\\\\\\"string\\\\\\\"==typeof t},Gh=function(t){return\\\\\\\"function\\\\\\\"==typeof t},Vh=function(t){return\\\\\\\"number\\\\\\\"==typeof 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oh{constructor(){super(...arguments),this.paramsConfig=rm}static type(){return\\\\\\\"position\\\\\\\"}initializeNode(){this.io.inputs.setCount(0,1),this.scene().dispatchController.onAddListener((()=>{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{this.params.label.init([this.p.mode,this.p.relativeTo,this.p.offset],(()=>{switch(X_[this.pv.mode]){case q_.RELATIVE:return this._relative_label();case q_.ABSOLUTE:return this._absolute_label()}}))}))}))}_relative_label(){const t=this.pv.offset>0?\\\\\\\"after\\\\\\\":\\\\\\\"before\\\\\\\",e=$_[this.pv.relativeTo];return`${Math.abs(this.pv.offset)} ${t} ${e}`}_absolute_label(){return\\\\\\\"absolute\\\\\\\"}cook(t){const e=t[0]||new B_,n=new J_;n.setMode(X_[this.pv.mode]),n.setRelativeTo($_[this.pv.relativeTo]),n.setOffset(this.pv.offset),e.setPosition(n),this.setTimelineBuilder(e)}}const am=new class extends ua{constructor(){super(...arguments),this.name=ha.STRING(\\\\\\\"position\\\\\\\")}};class lm extends oh{constructor(){super(...arguments),this.paramsConfig=am}static type(){return\\\\\\\"propertyName\\\\\\\"}initializeNode(){this.io.inputs.setCount(0,1),this.scene().dispatchController.onAddListener((()=>{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{this.params.label.init([this.p.name])}))}))}cook(t){const e=t[0]||new B_;e.setPropertyName(this.pv.name),this.setTimelineBuilder(e)}}var cm;!function(t){t.CUSTOM=\\\\\\\"custom\\\\\\\",t.FROM_SCENE_GRAPH=\\\\\\\"from scene graph\\\\\\\",t.FROM_NODE=\\\\\\\"from node\\\\\\\"}(cm||(cm={}));const hm=[cm.CUSTOM,cm.FROM_SCENE_GRAPH,cm.FROM_NODE],um=hm.indexOf(cm.CUSTOM),dm=hm.indexOf(cm.FROM_SCENE_GRAPH),pm=hm.indexOf(cm.FROM_NODE);const _m=new class extends ua{constructor(){super(...arguments),this.mode=ha.INTEGER(um,{menu:{entries:hm.map(((t,e)=>({name:t,value:e})))}}),this.nodePath=ha.NODE_PATH(\\\\\\\"\\\\\\\",{visibleIf:{mode:pm}}),this.objectMask=ha.STRING(\\\\\\\"*geo1\\\\\\\",{visibleIf:{mode:dm}}),this.printResolve=ha.BUTTON(null,{visibleIf:{mode:dm},callback:t=>{mm.PARAM_CALLBACK_printResolve(t)}}),this.overridePropertyName=ha.BOOLEAN(0,{visibleIf:[{mode:dm},{mode:pm}]}),this.propertyName=ha.STRING(\\\\\\\"\\\\\\\",{visibleIf:[{overridePropertyName:!0,mode:dm},{overridePropertyName:!0,mode:pm}]}),this.size=ha.INTEGER(3,{range:[1,4],rangeLocked:[!0,!0],visibleIf:{mode:um}}),this.value1=ha.FLOAT(0,{visibleIf:{mode:um,size:1}}),this.value2=ha.VECTOR2([0,0],{visibleIf:{mode:um,size:2}}),this.value3=ha.VECTOR3([0,0,0],{visibleIf:{mode:um,size:3}}),this.value4=ha.VECTOR4([0,0,0,0],{visibleIf:{mode:um,size:4}})}};class mm extends oh{constructor(){super(...arguments),this.paramsConfig=_m}static type(){return\\\\\\\"propertyValue\\\\\\\"}initializeNode(){this.io.inputs.setCount(0,1)}async cook(t){const e=t[0]||new B_;await this._prepareTimelineBuilder(e),this.setTimelineBuilder(e)}setMode(t){this.p.mode.set(hm.indexOf(t))}async _prepareTimelineBuilder(t){const e=hm[this.pv.mode];switch(e){case cm.CUSTOM:return this._prepareTimebuilderCustom(t);case cm.FROM_SCENE_GRAPH:return this._prepareTimebuilderFromSceneGraph(t);case cm.FROM_NODE:return await this._prepareTimebuilderFromNode(t)}os.unreachable(e)}_prepareTimebuilderCustom(t){const e=[this.pv.value1,this.pv.value2.clone(),this.pv.value3.clone(),this.pv.value4.clone()][this.pv.size-1];t.setPropertyValue(e)}_prepareTimebuilderFromSceneGraph(t){const e=this.pv.overridePropertyName?this.pv.propertyName:t.propertyName();if(!e)return;const n=this._foundObjectFromSceneGraph();if(n){const i=n[e];i&&(m.isNumber(i)||m.isVector(i)||i instanceof hh.a)&&t.setPropertyValue(i)}}async _prepareTimebuilderFromNode(t){const e=this.pv.overridePropertyName?this.pv.propertyName:t.propertyName();if(!e)return;const n=this.pv.nodePath.node();if(!n)return;const i=n.params.get(e);if(!i)return;i.isDirty()&&await i.compute();const s=i.value;s&&(m.isNumber(s)||m.isVector(s))&&t.setPropertyValue(s)}static PARAM_CALLBACK_printResolve(t){t.printResolve()}_foundObjectFromSceneGraph(){return this.scene().findObjectByMask(this.pv.objectMask)}printResolve(){const t=this._foundObjectFromSceneGraph();console.log(t)}}const fm=new class extends ua{constructor(){super(...arguments),this.unlimited=ha.BOOLEAN(0),this.count=ha.INTEGER(1,{range:[0,10],visibleIf:{unlimited:0}}),this.delay=ha.FLOAT(0),this.yoyo=ha.BOOLEAN(0)}};class gm extends oh{constructor(){super(...arguments),this.paramsConfig=fm}static type(){return\\\\\\\"repeat\\\\\\\"}initializeNode(){this.io.inputs.setCount(0,1),this.scene().dispatchController.onAddListener((()=>{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{this.params.label.init([this.p.unlimited,this.p.count,this.p.yoyo],(()=>`${`${this.p.unlimited?\\\\\\\"unlimited\\\\\\\":this.pv.count}`} (yoyo: ${this.pv.yoyo})`))}))}))}_repeat_params(){return{count:this.pv.unlimited?-1:this.pv.count,delay:this.pv.delay,yoyo:this.pv.yoyo}}cook(t){const e=t[0]||new B_;e.setRepeatParams(this._repeat_params()),this.setTimelineBuilder(e)}}const vm=new class extends ua{constructor(){super(...arguments),this.input=ha.INTEGER(0,{range:[0,3],rangeLocked:[!0,!0]})}};class ym extends oh{constructor(){super(...arguments),this.paramsConfig=vm}static type(){return\\\\\\\"switch\\\\\\\"}initializeNode(){this.io.inputs.setCount(0,4)}cook(t){const e=t[this.pv.input];e?this.setTimelineBuilder(e):this.states.error.set(`input ${this.pv.input} is not valid`)}}class xm{constructor(t,e){this._scene=t,this._options=e}clone(){return new xm(this._scene,this._options)}objects(){const t=this._options.objectMask;if(t)return this._scene.objectsByMask(t)}node(){if(!this._options.node)return;const t=this._options.node;return t.relativeTo.node(t.path)}}class bm{constructor(){this._update_matrix=!1}clone(){const t=new bm;return t.setUpdateMatrix(this._update_matrix),t}setUpdateMatrix(t){this._update_matrix=t}updateMatrix(){return this._update_matrix}}var wm;!function(t){t.SCENE_GRAPH=\\\\\\\"scene graph\\\\\\\",t.NODE=\\\\\\\"node\\\\\\\"}(wm||(wm={}));const Tm=[wm.SCENE_GRAPH,wm.NODE],Am=Tm.indexOf(wm.SCENE_GRAPH),Mm=Tm.indexOf(wm.NODE);const Em=new class extends ua{constructor(){super(...arguments),this.type=ha.INTEGER(Am,{menu:{entries:Tm.map(((t,e)=>({name:t,value:e})))}}),this.nodePath=ha.OPERATOR_PATH(\\\\\\\"\\\\\\\",{visibleIf:{type:Mm}}),this.objectMask=ha.STRING(\\\\\\\"/geo*\\\\\\\",{visibleIf:{type:Am}}),this.updateMatrix=ha.BOOLEAN(0,{visibleIf:{type:Am}}),this.printResolve=ha.BUTTON(null,{callback:(t,e)=>{Sm.PARAM_CALLBACK_print_resolve(t)}})}};class Sm extends oh{constructor(){super(...arguments),this.paramsConfig=Em}static type(){return\\\\\\\"target\\\\\\\"}initializeNode(){this.io.inputs.setCount(0,1),this.scene().dispatchController.onAddListener((()=>{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{this.params.label.init([this.p.type,this.p.nodePath,this.p.objectMask],(()=>{const t=Tm[this.pv.type];switch(t){case wm.NODE:return this.pv.nodePath;case wm.SCENE_GRAPH:return this.pv.objectMask}os.unreachable(t)}))}))}))}cook(t){const e=t[0]||new B_,n=this._create_target(e);e.setTarget(n),this._set_update_callback(e),this.setTimelineBuilder(e)}setTargetType(t){this.p.type.set(Tm.indexOf(t))}_create_target(t){const e=Tm[this.pv.type];switch(e){case wm.NODE:return new xm(this.scene(),{node:{path:this.pv.nodePath,relativeTo:this}});case wm.SCENE_GRAPH:return new xm(this.scene(),{objectMask:this.pv.objectMask})}os.unreachable(e)}_set_update_callback(t){const e=Tm[this.pv.type];let n=t.updateCallback();switch(e){case wm.NODE:return;case wm.SCENE_GRAPH:return void(this.pv.updateMatrix&&(n=n||new bm,n.setUpdateMatrix(this.pv.updateMatrix),t.setUpdateCallback(n)))}os.unreachable(e)}static PARAM_CALLBACK_print_resolve(t){t.print_resolve()}print_resolve(){const t=Tm[this.pv.type],e=new B_,n=this._create_target(e);switch(t){case wm.NODE:return console.log(n.node());case wm.SCENE_GRAPH:return console.log(n.objects())}}}class Cm extends aa{static context(){return ts.ANIM}cook(){this.cookController.endCook()}}class Nm extends Cm{}class Lm extends Nm{constructor(){super(...arguments),this._children_controller_context=ts.ANIM}static type(){return es.ANIM}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}}class Om extends Nm{constructor(){super(...arguments),this._children_controller_context=ts.COP}static type(){return es.COP}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}}class Pm extends Nm{constructor(){super(...arguments),this._children_controller_context=ts.EVENT}static type(){return es.EVENT}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}}class Rm extends Nm{constructor(){super(...arguments),this._children_controller_context=ts.MAT}static type(){return es.MAT}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}}const Im={dependsOnDisplayNode:!0};class Fm{constructor(t,e,n=Im){this.node=t,this.options=n,this._initialized=!1,this._display_node=void 0,this._graph_node=new Mi(t.scene(),\\\\\\\"DisplayNodeController\\\\\\\"),this._graph_node.node=t,this._on_display_node_remove_callback=e.onDisplayNodeRemove,this._on_display_node_set_callback=e.onDisplayNodeSet,this._on_display_node_update_callback=e.onDisplayNodeUpdate}dispose(){this._graph_node.dispose()}displayNode(){return this._display_node}initializeNode(){this._initialized?console.error(\\\\\\\"display node controller already initialed\\\\\\\",this.node):(this._initialized=!0,this.node.lifecycle.add_on_child_add_hook((t=>{var e,n;this._display_node||null===(n=null===(e=t.flags)||void 0===e?void 0:e.display)||void 0===n||n.set(!0)})),this.node.lifecycle.add_on_child_remove_hook((t=>{var e,n,i;if(t.graphNodeId()==(null===(e=this._display_node)||void 0===e?void 0:e.graphNodeId())){const t=this.node.children(),e=t[t.length-1];e?null===(i=null===(n=e.flags)||void 0===n?void 0:n.display)||void 0===i||i.set(!0):this.setDisplayNode(void 0)}})),this._graph_node.dirtyController.addPostDirtyHook(\\\\\\\"_request_display_node_container\\\\\\\",(()=>{this._on_display_node_update_callback&&this._on_display_node_update_callback()})))}async setDisplayNode(t){if(this._initialized||console.error(\\\\\\\"display node controller not initialized\\\\\\\",this.node),this._display_node!=t){const e=this._display_node;e&&(e.flags.display.set(!1),this.options.dependsOnDisplayNode&&this._graph_node.removeGraphInput(e),this._on_display_node_remove_callback&&this._on_display_node_remove_callback()),this._display_node=t,this._display_node&&(this.options.dependsOnDisplayNode&&this._graph_node.addGraphInput(this._display_node),this._on_display_node_set_callback&&this._on_display_node_set_callback())}}}class Dm{constructor(t=!0){this.autoStart=t,this.startTime=0,this.oldTime=0,this.elapsedTime=0,this.running=!1}start(){this.startTime=Bm(),this.oldTime=this.startTime,this.elapsedTime=0,this.running=!0}stop(){this.getElapsedTime(),this.running=!1,this.autoStart=!1}getElapsedTime(){return this.getDelta(),this.elapsedTime}getDelta(){let t=0;if(this.autoStart&&!this.running)return this.start(),0;if(this.running){const e=Bm();t=(e-this.oldTime)/1e3,this.oldTime=e,this.elapsedTime+=t}return t}}function Bm(){return(\\\\\\\"undefined\\\\\\\"==typeof performance?Date:performance).now()}var zm={uniforms:{tDiffuse:{value:null},opacity:{value:1}},vertexShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\tvUv = uv;\\\\n\\\\t\\\\t\\\\tgl_Position = projectionMatrix * modelViewMatrix * vec4( position, 1.0 );\\\\n\\\\n\\\\t\\\\t}\\\\\\\",fragmentShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\tuniform float opacity;\\\\n\\\\n\\\\t\\\\tuniform sampler2D tDiffuse;\\\\n\\\\n\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\tvec4 texel = texture2D( tDiffuse, vUv );\\\\n\\\\t\\\\t\\\\tgl_FragColor = opacity * texel;\\\\n\\\\n\\\\t\\\\t}\\\\\\\"};class km{constructor(){this.enabled=!0,this.needsSwap=!0,this.clear=!1,this.renderToScreen=!1}setSize(){}render(){console.error(\\\\\\\"THREE.Pass: .render() must be implemented in derived pass.\\\\\\\")}}const Um=new ot.a(-1,1,1,-1,0,1),Gm=new S.a;Gm.setAttribute(\\\\\\\"position\\\\\\\",new C.c([-1,3,0,-1,-1,0,3,-1,0],3)),Gm.setAttribute(\\\\\\\"uv\\\\\\\",new C.c([0,2,0,0,2,0],2));class Vm{constructor(t){this._mesh=new B.a(Gm,t)}dispose(){this._mesh.geometry.dispose()}render(t){t.render(this._mesh,Um)}get material(){return this._mesh.material}set material(t){this._mesh.material=t}}class Hm extends km{constructor(t,e){super(),this.textureID=void 0!==e?e:\\\\\\\"tDiffuse\\\\\\\",t instanceof F?(this.uniforms=t.uniforms,this.material=t):t&&(this.uniforms=I.clone(t.uniforms),this.material=new F({defines:Object.assign({},t.defines),uniforms:this.uniforms,vertexShader:t.vertexShader,fragmentShader:t.fragmentShader})),this.fsQuad=new Vm(this.material)}render(t,e,n){this.uniforms[this.textureID]&&(this.uniforms[this.textureID].value=n.texture),this.fsQuad.material=this.material,this.renderToScreen?(t.setRenderTarget(null),this.fsQuad.render(t)):(t.setRenderTarget(e),this.clear&&t.clear(t.autoClearColor,t.autoClearDepth,t.autoClearStencil),this.fsQuad.render(t))}}class jm extends km{constructor(t,e){super(),this.scene=t,this.camera=e,this.clear=!0,this.needsSwap=!1,this.inverse=!1}render(t,e,n){const i=t.getContext(),s=t.state;let r,o;s.buffers.color.setMask(!1),s.buffers.depth.setMask(!1),s.buffers.color.setLocked(!0),s.buffers.depth.setLocked(!0),this.inverse?(r=0,o=1):(r=1,o=0),s.buffers.stencil.setTest(!0),s.buffers.stencil.setOp(i.REPLACE,i.REPLACE,i.REPLACE),s.buffers.stencil.setFunc(i.ALWAYS,r,4294967295),s.buffers.stencil.setClear(o),s.buffers.stencil.setLocked(!0),t.setRenderTarget(n),this.clear&&t.clear(),t.render(this.scene,this.camera),t.setRenderTarget(e),this.clear&&t.clear(),t.render(this.scene,this.camera),s.buffers.color.setLocked(!1),s.buffers.depth.setLocked(!1),s.buffers.stencil.setLocked(!1),s.buffers.stencil.setFunc(i.EQUAL,1,4294967295),s.buffers.stencil.setOp(i.KEEP,i.KEEP,i.KEEP),s.buffers.stencil.setLocked(!0)}}class Wm extends km{constructor(){super(),this.needsSwap=!1}render(t){t.state.buffers.stencil.setLocked(!1),t.state.buffers.stencil.setTest(!1)}}class qm{constructor(t,e){if(this.renderer=t,void 0===e){const n={minFilter:w.V,magFilter:w.V,format:w.Ib},i=t.getSize(new d.a);this._pixelRatio=t.getPixelRatio(),this._width=i.width,this._height=i.height,(e=new K(this._width*this._pixelRatio,this._height*this._pixelRatio,n)).texture.name=\\\\\\\"EffectComposer.rt1\\\\\\\"}else this._pixelRatio=1,this._width=e.width,this._height=e.height;this.renderTarget1=e,this.renderTarget2=e.clone(),this.renderTarget2.texture.name=\\\\\\\"EffectComposer.rt2\\\\\\\",this.writeBuffer=this.renderTarget1,this.readBuffer=this.renderTarget2,this.renderToScreen=!0,this.passes=[],void 0===zm&&console.error(\\\\\\\"THREE.EffectComposer relies on CopyShader\\\\\\\"),void 0===Hm&&console.error(\\\\\\\"THREE.EffectComposer relies on ShaderPass\\\\\\\"),this.copyPass=new Hm(zm),this.clock=new Dm}swapBuffers(){const t=this.readBuffer;this.readBuffer=this.writeBuffer,this.writeBuffer=t}addPass(t){this.passes.push(t),t.setSize(this._width*this._pixelRatio,this._height*this._pixelRatio)}insertPass(t,e){this.passes.splice(e,0,t),t.setSize(this._width*this._pixelRatio,this._height*this._pixelRatio)}removePass(t){const e=this.passes.indexOf(t);-1!==e&&this.passes.splice(e,1)}isLastEnabledPass(t){for(let e=t+1;e({name:Object.keys(t)[0],value:Object.values(t)[0]}))),tf=Jm.map((t=>({name:Object.keys(t)[0],value:Object.values(t)[0]})));class ef extends ua{constructor(){super(...arguments),this.prependRenderPass=ha.BOOLEAN(1),this.useRenderTarget=ha.BOOLEAN(1),this.tmagFilter=ha.BOOLEAN(0,{visibleIf:{useRenderTarget:1}}),this.magFilter=ha.INTEGER(Zm,{visibleIf:{useRenderTarget:1,tmagFilter:1},menu:{entries:Qm}}),this.tminFilter=ha.BOOLEAN(0,{visibleIf:{useRenderTarget:1}}),this.minFilter=ha.INTEGER(Km,{visibleIf:{useRenderTarget:1,tminFilter:1},menu:{entries:tf}}),this.stencilBuffer=ha.BOOLEAN(0,{visibleIf:{useRenderTarget:1}}),this.sampling=ha.INTEGER(1,{range:[1,4],rangeLocked:[!0,!1]})}}class nf{constructor(t){this.node=t,this._renderer_size=new d.a}displayNodeControllerCallbacks(){return{onDisplayNodeRemove:()=>{},onDisplayNodeSet:()=>{this.node.setDirty()},onDisplayNodeUpdate:()=>{this.node.setDirty()}}}createEffectsComposer(t){const e=t.renderer;let n;if(this.node.pv.useRenderTarget){const t=this._create_render_target(e);n=new qm(e,t)}else n=new qm(e);return n.setPixelRatio(window.devicePixelRatio*this.node.pv.sampling),this._build_passes(n,t),n}_create_render_target(t){let e;t.autoClear=!1;const n={format:w.ic,stencilBuffer:this.node.pv.stencilBuffer};return this.node.pv.tminFilter&&(n.minFilter=this.node.pv.minFilter),this.node.pv.tmagFilter&&(n.magFilter=this.node.pv.magFilter),t.getDrawingBufferSize(this._renderer_size),e=li.renderersController.renderTarget(this._renderer_size.x,this._renderer_size.y,n),e}_build_passes(t,e){if(this.node.pv.prependRenderPass){const n=new Ym(e.scene,e.camera);t.addPass(n)}const n=this.node.displayNodeController.displayNode();n&&n.setupComposer({composer:t,camera:e.camera,resolution:e.resolution,camera_node:e.camera_node,scene:e.scene,requester:e.requester})}}class sf extends Cm{constructor(){super(...arguments),this.paramsConfig=new ef,this.effectsComposerController=new nf(this),this.displayNodeController=new Fm(this,this.effectsComposerController.displayNodeControllerCallbacks()),this._children_controller_context=ts.POST}static type(){return es.POST}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}}class rf extends Nm{constructor(){super(...arguments),this._children_controller_context=ts.ROP}static type(){return es.ROP}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}}var of=n(44);const af=\\\\\\\"input texture\\\\\\\",lf=[af,af,af,af];for(var cf=new Uint16Array(32),hf=0;hf<32;hf++)cf[hf]=28898;const uf=new vo.a(cf,32,1,w.gb,w.M);class df extends aa{constructor(t){super(t,\\\\\\\"BaseCopNode\\\\\\\"),this.flags=new ki(this)}static context(){return ts.COP}static displayedInputNames(){return lf}initializeBaseNode(){this.io.outputs.setHasOneOutput()}setTexture(t){t.name=this.path();const e=this.containerController.container().texture();if(e){if(e.uuid!=t.uuid){const n=Object.keys(t);for(let i of n)e[i]=t[i];e.needsUpdate=!0}this._setContainer(e)}else this._setContainer(t)}_clearTexture(){this._setContainer(uf)}}class pf extends df{}class _f{constructor(){this._id=_f.__next_id++}id(){return this._id}handle_globals_node(t,e,n){}}_f.__next_id=0;class mf{static any(t){return m.isString(t)?t:m.isBoolean(t)?`${t}`:m.isNumber(t)?`${ss.ensureFloat(t)}`:m.isArray(t)?this.numeric_array(t):t instanceof d.a||t instanceof p.a||t instanceof _.a||t instanceof D.a?this.numeric_array(t.toArray()):`ThreeToGl error: unknown value type '${t}'`}static numeric_array(t){const e=new Array(t.length);for(let n=0;n`${ss.ensureFloat(t)}`)).join(\\\\\\\", \\\\\\\")})`}static vector3(t){if(m.isString(t))return t;return`vec3(${t.toArray().map((t=>`${ss.ensureFloat(t)}`)).join(\\\\\\\", \\\\\\\")})`}static vector2(t){if(m.isString(t))return t;return`vec2(${t.toArray().map((t=>`${ss.ensureFloat(t)}`)).join(\\\\\\\", \\\\\\\")})`}static vector3_float(t,e){return m.isNumber(e)&&(e=ss.ensureFloat(e)),`vec4(${this.vector3(t)}, ${e})`}static float4(t,e,n,i){return m.isNumber(t)&&(t=ss.ensureFloat(t)),m.isNumber(e)&&(e=ss.ensureFloat(e)),m.isNumber(n)&&(n=ss.ensureFloat(n)),m.isNumber(i)&&(i=ss.ensureFloat(i)),`vec4(${t}, ${e}, ${n}, ${i})`}static float3(t,e,n){return m.isNumber(t)&&(t=ss.ensureFloat(t)),m.isNumber(e)&&(e=ss.ensureFloat(e)),m.isNumber(n)&&(n=ss.ensureFloat(n)),`vec3(${t}, ${e}, ${n})`}static float2(t,e){return m.isNumber(t)&&(t=ss.ensureFloat(t)),m.isNumber(e)&&(e=ss.ensureFloat(e)),`vec2(${t}, ${e})`}static float(t){if(m.isNumber(t))return ss.ensureFloat(t);{const e=parseFloat(t);return m.isNaN(e)?t:ss.ensureFloat(e)}}static integer(t){if(m.isNumber(t))return ss.ensureInteger(t);{const e=parseInt(t);return m.isNaN(e)?t:ss.ensureInteger(e)}}static bool(t){return m.isBoolean(t)?`${t}`:t}}const ff=/\\\\/+/g;class gf extends aa{static context(){return ts.GL}initializeBaseNode(){this.uiData.setLayoutHorizontal(),this.io.connections.initInputs(),this.io.connection_points.spare_params.initializeNode()}cook(){console.warn(\\\\\\\"gl nodes should never cook\\\\\\\")}_set_mat_to_recompile(){var t,e;null===(e=null===(t=this.material_node)||void 0===t?void 0:t.assemblerController)||void 0===e||e.set_compilation_required_and_dirty(this)}get material_node(){var t;const e=this.parent();if(e)return e.context()==ts.GL?null===(t=e)||void 0===t?void 0:t.material_node:e}glVarName(t){return`v_POLY_${this.path(this.material_node).replace(ff,\\\\\\\"_\\\\\\\")}_${t}`}variableForInputParam(t){return this.variableForInput(t.name())}variableForInput(t){var e;const n=this.io.inputs.get_input_index(t),i=this.io.connections.inputConnection(n);if(i){const e=i.node_src,n=e.io.outputs.namedOutputConnectionPoints()[i.output_index];if(n){const t=n.name();return e.glVarName(t)}throw console.warn(`no output called '${t}' for gl node ${e.path()}`),\\\\\\\"variable_for_input ERROR\\\\\\\"}if(this.params.has(t))return mf.any(null===(e=this.params.get(t))||void 0===e?void 0:e.value);{const t=this.io.inputs.namedInputConnectionPoints()[n];return mf.any(t.init_value)}}setLines(t){}reset_code(){var t;null===(t=this._param_configs_controller)||void 0===t||t.reset()}setParamConfigs(){}param_configs(){var t;return null===(t=this._param_configs_controller)||void 0===t?void 0:t.list()}paramsGenerating(){return!1}paramDefaultValue(t){return null}}const vf=new class extends ua{};class yf extends gf{constructor(){super(...arguments),this.paramsConfig=vf}}const xf=[Uo.FLOAT,Uo.VEC2,Uo.VEC3,Uo.VEC4];const bf=new class extends ua{constructor(){super(...arguments),this.name=ha.STRING(\\\\\\\"\\\\\\\"),this.type=ha.INTEGER(0,{menu:{entries:xf.map(((t,e)=>({name:t,value:e})))}}),this.texportWhenConnected=ha.BOOLEAN(0,{hidden:!0}),this.exportWhenConnected=ha.BOOLEAN(0,{visibleIf:{texportWhenConnected:1}})}};class wf extends gf{constructor(){super(...arguments),this.paramsConfig=bf,this._on_create_set_name_if_none_bound=this._on_create_set_name_if_none.bind(this),this._bound_setExportWhenConnectedStatus=this._setExportWhenConnectedStatus.bind(this)}static type(){return ps.ATTRIBUTE}initializeNode(){this.addPostDirtyHook(\\\\\\\"_set_mat_to_recompile\\\\\\\",this._set_mat_to_recompile_if_is_exporting.bind(this)),this.lifecycle.add_on_create_hook(this._on_create_set_name_if_none_bound),this.io.connection_points.initializeNode(),this.io.connection_points.set_expected_input_types_function((()=>{var t,e;return(null===(e=null===(t=this.material_node)||void 0===t?void 0:t.assemblerController)||void 0===e?void 0:e.allow_attribute_exports())?[xf[this.pv.type]]:[]})),this.io.connection_points.set_input_name_function((t=>wf.INPUT_NAME)),this.io.connection_points.set_expected_output_types_function((()=>[xf[this.pv.type]])),this.scene().dispatchController.onAddListener((()=>{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{this.params.label.init([this.p.name,this.p.exportWhenConnected],(()=>this.pv.exportWhenConnected?`${this.pv.name} (EXPORTED)`:this.pv.name))}))})),this.lifecycle.add_on_add_hook(this._bound_setExportWhenConnectedStatus),this.params.addOnSceneLoadHook(\\\\\\\"prepare params\\\\\\\",this._bound_setExportWhenConnectedStatus)}_setExportWhenConnectedStatus(){var t,e;(null===(e=null===(t=this.material_node)||void 0===t?void 0:t.assemblerController)||void 0===e?void 0:e.allow_attribute_exports())&&this.p.texportWhenConnected.set(1)}setAttribSize(t){this.p.type.set(t-1)}get input_name(){return wf.INPUT_NAME}get output_name(){return wf.OUTPUT_NAME}setLines(t){t.assembler().set_node_lines_attribute(this,t)}get attribute_name(){return this.pv.name.trim()}gl_type(){return this.io.outputs.namedOutputConnectionPoints()[0].type()}set_gl_type(t){this.p.type.set(xf.indexOf(t))}connected_input_node(){return this.io.inputs.named_input(wf.INPUT_NAME)}connected_input_connection_point(){return this.io.inputs.named_input_connection_point(wf.INPUT_NAME)}output_connection_point(){return this.io.outputs.namedOutputConnectionPointsByName(this.output_name)}isImporting(){return this.io.outputs.used_output_names().length>0}isExporting(){if(this.pv.exportWhenConnected){return null!=this.io.inputs.named_input(wf.INPUT_NAME)}return!1}_set_mat_to_recompile_if_is_exporting(){this.isExporting()&&this._set_mat_to_recompile()}_on_create_set_name_if_none(){\\\\\\\"\\\\\\\"==this.pv.name&&this.p.name.set(this.name())}}wf.INPUT_NAME=\\\\\\\"in\\\\\\\",wf.OUTPUT_NAME=\\\\\\\"val\\\\\\\";class Tf{constructor(t=[]){this._definitions=t,this._errored=!1}get errored(){return this._errored}get error_message(){return this._error_message}uniq(){const t=new Map,e=[];for(let n of this._definitions)if(!this._errored){const i=n.name(),s=t.get(i);s?s.data_type!=n.data_type&&(this._errored=!0,this._error_message=`attempt to create '${n.name()}' with types '${n.data_type}' by node '${n.node.path()}', when there is already an existing with type ${s.data_type} from node '${s.node.path()}'`,console.warn(\\\\\\\"emitting error message:\\\\\\\",this._error_message)):(t.set(i,n),e.push(i))}const n=[];for(let i of e){const e=t.get(i);e&&n.push(e)}return n}}var Af,Mf;!function(t){t.ATTRIBUTE=\\\\\\\"attribute\\\\\\\",t.FUNCTION=\\\\\\\"function\\\\\\\",t.UNIFORM=\\\\\\\"uniform\\\\\\\",t.VARYING=\\\\\\\"varying\\\\\\\"}(Af||(Af={}));class Ef{constructor(t,e,n,i){this._definition_type=t,this._data_type=e,this._node=n,this._name=i}get definition_type(){return this._definition_type}get data_type(){return this._data_type}get node(){return this._node}name(){return this._name}collection_instance(){return new Tf}}class Sf extends Ef{constructor(t,e,n){super(Af.ATTRIBUTE,e,t,n),this._node=t,this._data_type=e,this._name=n}get line(){return`attribute ${this.data_type} ${this.name()}`}}class Cf extends Ef{constructor(t,e){super(Af.FUNCTION,Uo.FLOAT,t,e),this._node=t,this._name=e}get line(){return this.name()}}class Nf extends Ef{constructor(t,e,n){super(Af.UNIFORM,e,t,n),this._node=t,this._data_type=e,this._name=n}get line(){return`uniform ${this.data_type} ${this.name()}`}}class Lf extends Ef{constructor(t,e,n){super(Af.VARYING,e,t,n),this._node=t,this._data_type=e,this._name=n}get line(){return`varying ${this.data_type} ${this.name()}`}}!function(t){t.VERTEX=\\\\\\\"vertex\\\\\\\",t.FRAGMENT=\\\\\\\"fragment\\\\\\\",t.LEAVES_FROM_NODES_SHADER=\\\\\\\"leaves_from_nodes_shader\\\\\\\"}(Mf||(Mf={}));const Of={position:\\\\\\\"vec3( position )\\\\\\\"};class Pf extends _f{handle_globals_node(t,e,n){var i,s;const r=t.io.outputs.namedOutputConnectionPointsByName(e);if(!r)return;const o=t.glVarName(e),a=r.type(),l=new Lf(t,a,o);n.addDefinitions(t,[l]);const c=null===(s=null===(i=t.material_node)||void 0===i?void 0:i.assemblerController)||void 0===s?void 0:s.assembler;if(!c)return;const h=c.shader_config(n.current_shader_name);if(!h)return;const u=h.dependencies(),d=[],p=`${o} = modelMatrix * vec4( position, 1.0 )`,_=`${o} = normalize( mat3( modelMatrix[0].xyz, modelMatrix[1].xyz, modelMatrix[2].xyz ) * normal )`;switch(e){case\\\\\\\"worldPosition\\\\\\\":d.push(p);break;case\\\\\\\"worldNormal\\\\\\\":d.push(_);break;default:d.push(`${o} = ${a}(${e})`)}for(let e of u)n.addDefinitions(t,[l],e),n.addBodyLines(t,d,e);0==u.length&&n.addBodyLines(t,d)}static variable_config_default(t){return Of[t]}variable_config_default(t){return Pf.variable_config_default(t)}read_attribute(t,e,n,i){return Pf.read_attribute(t,e,n,i)}static read_attribute(t,e,n,i){var s,r;Pf.PRE_DEFINED_ATTRIBUTES.indexOf(n)<0&&i.addDefinitions(t,[new Sf(t,e,n)],Mf.VERTEX);const o=i.current_shader_name;switch(o){case Mf.VERTEX:return n;case Mf.FRAGMENT:{if(!(t instanceof wf))return;const a=\\\\\\\"varying_\\\\\\\"+t.glVarName(t.output_name),l=new Lf(t,e,a),c=new Map;c.set(Mf.FRAGMENT,[]);const u=new Map;u.set(Mf.FRAGMENT,[]),h.pushOnArrayAtEntry(c,o,l);const d=`${a} = ${e}(${n})`,p=null===(r=null===(s=t.material_node)||void 0===s?void 0:s.assemblerController)||void 0===r?void 0:r.assembler.shader_config(o);if(p){const e=p.dependencies();for(let t of e)h.pushOnArrayAtEntry(c,t,l),h.pushOnArrayAtEntry(u,t,d);c.forEach(((e,n)=>{i.addDefinitions(t,e,n)})),u.forEach(((e,n)=>{i.addBodyLines(t,e,n)}))}return a}}}handle_attribute_node(t,e,n,i){return Pf.read_attribute(t,e,n,i)}}Pf.PRE_DEFINED_ATTRIBUTES=[\\\\\\\"position\\\\\\\",\\\\\\\"color\\\\\\\",\\\\\\\"normal\\\\\\\",\\\\\\\"uv\\\\\\\",\\\\\\\"uv2\\\\\\\",\\\\\\\"morphTarget0\\\\\\\",\\\\\\\"morphTarget1\\\\\\\",\\\\\\\"morphTarget2\\\\\\\",\\\\\\\"morphTarget3\\\\\\\",\\\\\\\"skinIndex\\\\\\\",\\\\\\\"skinWeight\\\\\\\"],Pf.IF_RULE={uv:\\\\\\\"defined( USE_MAP ) || defined( USE_BUMPMAP ) || defined( USE_NORMALMAP ) || defined( USE_SPECULARMAP ) || defined( USE_ALPHAMAP ) || defined( USE_EMISSIVEMAP ) || defined( USE_ROUGHNESSMAP ) || defined( USE_METALNESSMAP )\\\\\\\"};const Rf=[Uo.FLOAT,Uo.VEC2,Uo.VEC3,Uo.VEC4];const If=new class extends ua{constructor(){super(...arguments),this.name=ha.STRING(\\\\\\\"\\\\\\\"),this.type=ha.INTEGER(0,{menu:{entries:Rf.map(((t,e)=>({name:t,value:e})))}})}};class Ff extends gf{constructor(){super(...arguments),this.paramsConfig=If,this._on_create_set_name_if_none_bound=this._on_create_set_name_if_none.bind(this)}static type(){return\\\\\\\"varyingWrite\\\\\\\"}initializeNode(){this.addPostDirtyHook(\\\\\\\"_set_mat_to_recompile\\\\\\\",this._set_mat_to_recompile.bind(this)),this.lifecycle.add_on_create_hook(this._on_create_set_name_if_none_bound),this.io.connection_points.initializeNode(),this.io.connection_points.set_input_name_function((()=>this.input_name)),this.io.connection_points.set_expected_input_types_function((()=>[Rf[this.pv.type]])),this.io.connection_points.set_expected_output_types_function((()=>[])),this.scene().dispatchController.onAddListener((()=>{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{this.params.label.init([this.p.name])}))}))}get input_name(){return Ff.INPUT_NAME}setLines(t){if(t.current_shader_name==Mf.VERTEX){const e=this.gl_type();if(!e)return;const n=this.pv.name,i=new Lf(this,e,n),s=`${n} = ${mf.any(this.variableForInput(Ff.INPUT_NAME))}`;t.addDefinitions(this,[i],Mf.VERTEX),t.addBodyLines(this,[s],Mf.VERTEX)}}get attribute_name(){return this.pv.name.trim()}gl_type(){const t=this.io.inputs.namedInputConnectionPoints()[0];if(t)return t.type()}set_gl_type(t){this.p.type.set(Rf.indexOf(t))}_on_create_set_name_if_none(){\\\\\\\"\\\\\\\"==this.pv.name&&this.p.name.set(this.name())}}Ff.INPUT_NAME=\\\\\\\"vertex\\\\\\\";class Df{static findOutputNodes(t){return t.nodesByType(\\\\\\\"output\\\\\\\")}static findParamGeneratingNodes(t){var e;const n=[];return null===(e=t.childrenController)||void 0===e||e.traverseChildren((t=>{const e=t;e.paramsGenerating()&&n.push(e)})),n}static findVaryingNodes(t){return t.nodesByType(Ff.type())}static findAttributeExportNodes(t){return t.nodesByType(wf.type()).filter((t=>t.isExporting()))}}class Bf{static overlay(t,e){return new Promise(((n,i)=>{let s=document.createElement(\\\\\\\"canvas\\\\\\\");s.width=Math.max(t.width,e.width),s.height=Math.max(t.height,e.height);let r=s.getContext(\\\\\\\"2d\\\\\\\");r.drawImage(t,0,0,t.width,t.height),r.drawImage(e,0,0,e.width,e.height);const o=s.toDataURL(\\\\\\\"image/png\\\\\\\"),a=new Image;a.onload=()=>{n(a)},a.src=o}))}static create_white_image(t,e){return new Promise(((n,i)=>{let s=document.createElement(\\\\\\\"canvas\\\\\\\");s.width=t,s.height=e;let r=s.getContext(\\\\\\\"2d\\\\\\\");r.beginPath(),r.rect(0,0,t,e),r.fillStyle=\\\\\\\"white\\\\\\\",r.fill();const o=s.toDataURL(\\\\\\\"image/png\\\\\\\"),a=new Image;a.onload=()=>{n(a)},a.src=o}))}static make_square(t){return new Promise(((e,n)=>{let i=document.createElement(\\\\\\\"canvas\\\\\\\");const s=Math.min(t.width,t.height),r=t.width/t.height;i.width=s,i.height=s;let o=i.getContext(\\\\\\\"2d\\\\\\\");const a=r>1,l=a?(t.width-s)/2:(t.height-s)/2;a?o.drawImage(t,l,0,s,s,0,0,s,s):o.drawImage(t,0,l,s,s,0,0,s,s);const c=i.toDataURL(\\\\\\\"image/png\\\\\\\"),h=new Image;h.onload=()=>{e(h)},h.src=c}))}static async image_to_blob(t){return new Promise((function(e,n){try{let i=new XMLHttpRequest;i.open(\\\\\\\"GET\\\\\\\",t.src),i.responseType=\\\\\\\"blob\\\\\\\",i.onerror=function(){n(\\\\\\\"Network error.\\\\\\\")},i.onload=function(){200===i.status?e(i.response):n(\\\\\\\"Loading error:\\\\\\\"+i.statusText)},i.send()}catch(t){n(t.message)}}))}static data_from_url(t){return new Promise(((e,n)=>{const i=new Image;i.crossOrigin=\\\\\\\"Anonymous\\\\\\\",i.onload=()=>{const t=this.data_from_image(i);e(t)},i.src=t}))}static data_from_image(t){const e=document.createElement(\\\\\\\"canvas\\\\\\\");e.width=t.width,e.height=t.height;const n=e.getContext(\\\\\\\"2d\\\\\\\");return n.drawImage(t,0,0,t.width,t.height),n.getImageData(0,0,t.width,t.height)}}var zf;!function(t){t.Uint8Array=\\\\\\\"Uint8Array\\\\\\\",t.Uint8ClampedArray=\\\\\\\"Uint8ClampedArray\\\\\\\",t.Float32Array=\\\\\\\"Float32Array\\\\\\\"}(zf||(zf={}));class kf{constructor(t){this.buffer_type=t}from_render_target(t,e){return this._data_texture&&this._same_dimensions(e.texture)||(this._data_texture=this._create_data_texture(e.texture)),this._copy_to_data_texture(t,e),this._data_texture}from_texture(t){const e=Bf.data_from_image(t.image);this._data_texture&&this._same_dimensions(t)||(this._data_texture=this._create_data_texture(t));const n=e.width*e.height,i=e.data,s=this._data_texture.image.data,r=4*n;for(let t=0;t0:s.vertexColors=t.vertexColors),void 0!==t.uniforms)for(const e in t.uniforms){const i=t.uniforms[e];switch(s.uniforms[e]={},i.type){case\\\\\\\"t\\\\\\\":s.uniforms[e].value=n(i.value);break;case\\\\\\\"c\\\\\\\":s.uniforms[e].value=(new D.a).setHex(i.value);break;case\\\\\\\"v2\\\\\\\":s.uniforms[e].value=(new d.a).fromArray(i.value);break;case\\\\\\\"v3\\\\\\\":s.uniforms[e].value=(new p.a).fromArray(i.value);break;case\\\\\\\"v4\\\\\\\":s.uniforms[e].value=(new _.a).fromArray(i.value);break;case\\\\\\\"m3\\\\\\\":s.uniforms[e].value=(new G.a).fromArray(i.value);break;case\\\\\\\"m4\\\\\\\":s.uniforms[e].value=(new A.a).fromArray(i.value);break;default:s.uniforms[e].value=i.value}}if(void 0!==t.defines&&(s.defines=t.defines),void 0!==t.vertexShader&&(s.vertexShader=t.vertexShader),void 0!==t.fragmentShader&&(s.fragmentShader=t.fragmentShader),void 0!==t.extensions)for(const e in t.extensions)s.extensions[e]=t.extensions[e];if(void 0!==t.shading&&(s.flatShading=1===t.shading),void 0!==t.size&&(s.size=t.size),void 0!==t.sizeAttenuation&&(s.sizeAttenuation=t.sizeAttenuation),void 0!==t.map&&(s.map=n(t.map)),void 0!==t.matcap&&(s.matcap=n(t.matcap)),void 0!==t.alphaMap&&(s.alphaMap=n(t.alphaMap)),void 0!==t.bumpMap&&(s.bumpMap=n(t.bumpMap)),void 0!==t.bumpScale&&(s.bumpScale=t.bumpScale),void 0!==t.normalMap&&(s.normalMap=n(t.normalMap)),void 0!==t.normalMapType&&(s.normalMapType=t.normalMapType),void 0!==t.normalScale){let e=t.normalScale;!1===Array.isArray(e)&&(e=[e,e]),s.normalScale=(new d.a).fromArray(e)}return void 0!==t.displacementMap&&(s.displacementMap=n(t.displacementMap)),void 0!==t.displacementScale&&(s.displacementScale=t.displacementScale),void 0!==t.displacementBias&&(s.displacementBias=t.displacementBias),void 0!==t.roughnessMap&&(s.roughnessMap=n(t.roughnessMap)),void 0!==t.metalnessMap&&(s.metalnessMap=n(t.metalnessMap)),void 0!==t.emissiveMap&&(s.emissiveMap=n(t.emissiveMap)),void 0!==t.emissiveIntensity&&(s.emissiveIntensity=t.emissiveIntensity),void 0!==t.specularMap&&(s.specularMap=n(t.specularMap)),void 0!==t.specularIntensityMap&&(s.specularIntensityMap=n(t.specularIntensityMap)),void 0!==t.specularTintMap&&(s.specularTintMap=n(t.specularTintMap)),void 0!==t.envMap&&(s.envMap=n(t.envMap)),void 0!==t.envMapIntensity&&(s.envMapIntensity=t.envMapIntensity),void 0!==t.reflectivity&&(s.reflectivity=t.reflectivity),void 0!==t.refractionRatio&&(s.refractionRatio=t.refractionRatio),void 0!==t.lightMap&&(s.lightMap=n(t.lightMap)),void 0!==t.lightMapIntensity&&(s.lightMapIntensity=t.lightMapIntensity),void 0!==t.aoMap&&(s.aoMap=n(t.aoMap)),void 0!==t.aoMapIntensity&&(s.aoMapIntensity=t.aoMapIntensity),void 0!==t.gradientMap&&(s.gradientMap=n(t.gradientMap)),void 0!==t.clearcoatMap&&(s.clearcoatMap=n(t.clearcoatMap)),void 0!==t.clearcoatRoughnessMap&&(s.clearcoatRoughnessMap=n(t.clearcoatRoughnessMap)),void 0!==t.clearcoatNormalMap&&(s.clearcoatNormalMap=n(t.clearcoatNormalMap)),void 0!==t.clearcoatNormalScale&&(s.clearcoatNormalScale=(new d.a).fromArray(t.clearcoatNormalScale)),void 0!==t.transmissionMap&&(s.transmissionMap=n(t.transmissionMap)),void 0!==t.thicknessMap&&(s.thicknessMap=n(t.thicknessMap)),s}setTextures(t){return this.textures=t,this}}class Kf{constructor(t){this.node=t,this._found_uniform_texture_by_id=new Map,this._found_uniform_textures_id_by_uniform_name=new Map,this._found_param_texture_by_id=new Map,this._found_param_textures_id_by_uniform_name=new Map}toJSON(){}load(t){}_materialToJson(t,e){let n;this._unassignTextures(t);try{n=t.toJSON({}),n&&(n.shadowSide=t.shadowSide,n.colorWrite=t.colorWrite)}catch(e){console.error(\\\\\\\"failed to save material data\\\\\\\"),console.log(t)}return n&&null!=t.lights&&(n.lights=t.lights),n&&(n.uuid=`${e.node.path()}-${e.suffix}`),this._reassignTextures(t),n}_unassignTextures(t){this._found_uniform_texture_by_id.clear(),this._found_uniform_textures_id_by_uniform_name.clear(),this._found_param_texture_by_id.clear(),this._found_param_textures_id_by_uniform_name.clear();const e=t.uniforms,n=Object.keys(e);for(let t of n){const n=e[t].value;if(n&&n.uuid){const i=n;this._found_uniform_texture_by_id.set(i.uuid,n),this._found_uniform_textures_id_by_uniform_name.set(t,i.uuid),e[t].value=null}}const i=Object.keys(t);for(let e of i){const n=t[e];if(n&&n.uuid){const i=n;this._found_param_texture_by_id.set(i.uuid,i),this._found_param_textures_id_by_uniform_name.set(e,i.uuid),t[e]=null}}}_reassignTextures(t){const e=[],n=[];this._found_uniform_textures_id_by_uniform_name.forEach(((t,n)=>{e.push(n)})),this._found_param_textures_id_by_uniform_name.forEach(((t,e)=>{n.push(e)}));const i=t.uniforms;for(let t of e){const e=this._found_uniform_textures_id_by_uniform_name.get(t);if(e){const n=this._found_uniform_texture_by_id.get(e);n&&(i[t].value=n)}}for(let e of n){const n=this._found_param_textures_id_by_uniform_name.get(e);if(n){const i=this._found_param_texture_by_id.get(n);i&&(t[e]=i)}}}_loadMaterial(t){t.color=void 0;const e=(new Zf).parse(t);t.shadowSide&&(e.shadowSide=t.shadowSide),null!=t.lights&&(e.lights=t.lights);const n=e.uniforms.uv2Transform;n&&this.mat4ToMat3(n);const i=e.uniforms.uvTransform;return i&&this.mat4ToMat3(i),e}mat4ToMat3(t){const e=t.value;if(null==e.elements[e.elements.length-1]){const n=new G.a;for(let t=0;t{const n=t.texture();e.value=n}));else{const t=n.containerController.container().texture();e.value=t}else e.value=null}static async set_uniform_value_from_texture_from_node_path_param(t,e){t.isDirty()&&await t.compute();const n=t.value.nodeWithContext(ts.COP);if(n)if(n.isDirty())n.compute().then((t=>{const n=t.texture();e.value=n}));else{const t=n.containerController.container().texture();e.value=t}else e.value=null}set_uniform_value_from_ramp(t,e){e.value=t.rampTexture()}}class eg extends Kf{constructor(t){super(t),this.node=t}toJSON(){const t=this.node.assemblerController;if(!t)return;const e=[],n=t.assembler.param_configs();for(let t of n)e.push([t.name(),t.uniform_name]);return{fragment_shader:this.node.texture_material.fragmentShader,uniforms:this.node.texture_material.uniforms,param_uniform_pairs:e,uniforms_time_dependent:t.assembler.uniformsTimeDependent(),uniforms_resolution_dependent:t.assembler.uniforms_resolution_dependent()}}load(t){this.node.texture_material.fragmentShader=t.fragment_shader,this.node.texture_material.uniforms=t.uniforms,rg.handleDependencies(this.node,t.uniforms_time_dependent||!1,t.uniforms);for(let e of t.param_uniform_pairs){const n=this.node.params.get(e[0]),i=t.uniforms[e[1]];n&&i&&n.options.set({callback:()=>{tg.callback(n,i)}})}}}class ng{static isChrome(){return navigator&&null!=navigator.userAgent&&-1!=navigator.userAgent.indexOf(\\\\\\\"Chrome\\\\\\\")}static isMobile(){return/Android|webOS|iPhone|iPad|iPod|BlackBerry|IEMobile|Opera Mini/i.test(navigator.userAgent)}static isiOS(){return/(iPad|iPhone|iPod)/g.test(navigator.userAgent)}static isAndroid(){return/(Android)/g.test(navigator.userAgent)}static isTouchDevice(){var t=document.createElement(\\\\\\\"div\\\\\\\");return t.setAttribute(\\\\\\\"ongesturestart\\\\\\\",\\\\\\\"return;\\\\\\\"),\\\\\\\"function\\\\\\\"==typeof t.ongesturestart}}const ig=[256,256];const sg=new class extends ua{constructor(){super(...arguments),this.resolution=ha.VECTOR2(ig),this.useCameraRenderer=ha.BOOLEAN(0)}};class rg extends df{constructor(){super(...arguments),this.paramsConfig=sg,this.persisted_config=new eg(this),this._assembler_controller=this._create_assembler_controller(),this._texture_mesh=new B.a(new L(2,2)),this.texture_material=new F({uniforms:{},vertexShader:\\\\\\\"\\\\nvoid main()\\\\t{\\\\n\\\\tgl_Position = vec4( position, 1.0 );\\\\n}\\\\n\\\\\\\",fragmentShader:\\\\\\\"\\\\\\\"}),this._texture_scene=new vs,this._texture_camera=new of.a,this._children_controller_context=ts.GL,this._cook_main_without_inputs_when_dirty_bound=this._cook_main_without_inputs_when_dirty.bind(this),this._boundRenderOnTarget=this.renderOnTarget.bind(this)}static type(){return\\\\\\\"builder\\\\\\\"}usedAssembler(){return jn.GL_TEXTURE}_create_assembler_controller(){const t=li.assemblersRegister.assembler(this,this.usedAssembler());if(t){const e=new Pf;return t.set_assembler_globals_handler(e),t}}get assemblerController(){return this._assembler_controller}initializeNode(){this._texture_mesh.material=this.texture_material,this._texture_mesh.scale.multiplyScalar(.25),this._texture_scene.add(this._texture_mesh),this._texture_camera.position.z=1,this.addPostDirtyHook(\\\\\\\"_cook_main_without_inputs_when_dirty\\\\\\\",(()=>{setTimeout(this._cook_main_without_inputs_when_dirty_bound,0)}))}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}childrenAllowed(){return this.assemblerController?super.childrenAllowed():(this.scene().markAsReadOnly(this),!1)}async _cook_main_without_inputs_when_dirty(){await this.cookController.cookMainWithoutInputs()}async cook(){this.compileIfRequired(),this.renderOnTarget()}shaders_by_name(){return{fragment:this._fragment_shader}}compileIfRequired(){var t;(null===(t=this.assemblerController)||void 0===t?void 0:t.compileRequired())&&this.compile()}compile(){const t=this.assemblerController;if(!t)return;const e=Df.findOutputNodes(this);if(e.length>1)return void this.states.error.set(\\\\\\\"only one output node allowed\\\\\\\");if(e[0]){const n=e;t.assembler.set_root_nodes(n),t.assembler.update_fragment_shader();const i=t.assembler.fragment_shader(),s=t.assembler.uniforms();i&&s&&(this._fragment_shader=i,this._uniforms=s),rg.handleDependencies(this,t.assembler.uniformsTimeDependent())}this._fragment_shader&&this._uniforms&&(this.texture_material.fragmentShader=this._fragment_shader,this.texture_material.uniforms=this._uniforms,this.texture_material.needsUpdate=!0,this.texture_material.uniforms.resolution={value:this.pv.resolution}),t.post_compile()}static handleDependencies(t,e,n){const i=t.scene();if(e){n&&i.uniformsController.addTimeDependentUniformOwner(t._uniformCallbackName(),n);const e=t._callbackName();i.registeredBeforeTickCallbacks().has(e)||i.registerOnBeforeTick(e,t._boundRenderOnTarget)}else t._removeCallbacks()}_callbackName(){return`cop/builder_${this.graphNodeId()}`}_uniformCallbackName(){return`cop/builder_uniforms_${this.graphNodeId()}`}dispose(){super.dispose(),this._removeCallbacks()}_removeCallbacks(){const t=this.scene();t.uniformsController.removeTimeDependentUniformOwner(this._uniformCallbackName()),t.unRegisterOnBeforeTick(this._callbackName())}async renderOnTarget(){if(this.createRenderTargetIfRequired(),!this._render_target)return;this._renderer_controller=this._renderer_controller||new Uf(this);const t=await this._renderer_controller.renderer(),e=t.getRenderTarget();if(t.setRenderTarget(this._render_target),t.clear(),t.render(this._texture_scene,this._texture_camera),t.setRenderTarget(e),this._render_target.texture)if(this.pv.useCameraRenderer)this.setTexture(this._render_target.texture);else{this._data_texture_controller=this._data_texture_controller||new kf(zf.Float32Array);const e=this._data_texture_controller.from_render_target(t,this._render_target);this.setTexture(e)}else this.cookController.endCook()}renderTarget(){return this._render_target=this._render_target||this._createRenderTarget(this.pv.resolution.x,this.pv.resolution.y)}createRenderTargetIfRequired(){var t;this._render_target&&this._renderTargetResolutionValid()||(this._render_target=this._createRenderTarget(this.pv.resolution.x,this.pv.resolution.y),null===(t=this._data_texture_controller)||void 0===t||t.reset())}_renderTargetResolutionValid(){if(this._render_target){const t=this._render_target.texture.image;return t.width==this.pv.resolution.x&&t.height==this.pv.resolution.y}return!1}_createRenderTarget(t,e){if(this._render_target){const n=this._render_target.texture.image;if(n.width==t&&n.height==e)return this._render_target}const n=w.n,i=w.n,s=w.V,r=w.ob;var o=new K(t,e,{wrapS:n,wrapT:i,minFilter:s,magFilter:r,format:w.Ib,type:ng.isiOS()?w.M:w.G,stencilBuffer:!1,depthBuffer:!1});return li.warn(\\\\\\\"created render target\\\\\\\",this.path(),t,e),o}}const og=[{LinearEncoding:w.U},{sRGBEncoding:w.ld},{GammaEncoding:w.J},{RGBEEncoding:w.gc},{LogLuvEncoding:w.bb},{RGBM7Encoding:w.lc},{RGBM16Encoding:w.kc},{RGBDEncoding:w.fc},{BasicDepthPacking:w.j},{RGBADepthPacking:w.Hb}],ag=[{ClampToEdgeWrapping:w.n},{RepeatWrapping:w.wc},{MirroredRepeatWrapping:w.kb}],lg=[{UVMapping:w.Yc},{CubeReflectionMapping:w.o},{CubeRefractionMapping:w.p},{EquirectangularReflectionMapping:w.D},{EquirectangularRefractionMapping:w.E},{CubeUVReflectionMapping:w.q},{CubeUVRefractionMapping:w.r}],cg=[{UnsignedByteType:w.Zc},{ByteType:w.l},{ShortType:w.Mc},{UnsignedShortType:w.fd},{IntType:w.N},{UnsignedIntType:w.bd},{FloatType:w.G},{HalfFloatType:w.M},{UnsignedShort4444Type:w.cd},{UnsignedShort5551Type:w.dd},{UnsignedShort565Type:w.ed},{UnsignedInt248Type:w.ad}],hg=[{AlphaFormat:w.f},{RedFormat:w.tc},{RedIntegerFormat:w.uc},{RGFormat:w.rc},{RGIntegerFormat:w.sc},{RGBFormat:w.ic},{RGBIntegerFormat:w.jc},{RGBAFormat:w.Ib},{RGBAIntegerFormat:w.Jb},{LuminanceFormat:w.gb},{LuminanceAlphaFormat:w.fb},{DepthFormat:w.x},{DepthStencilFormat:w.y}];function ug(t){return{cook:!1,callback:e=>{Sg[t](e)}}}const dg={ENCODING:w.U,FORMAT:w.Ib,MAPPING:w.Yc,MIN_FILTER:w.V,MAG_FILTER:w.V,TYPE:w.Zc,WRAPPING:w.wc},pg=ug(\\\\\\\"PARAM_CALLBACK_update_encoding\\\\\\\"),_g=ug(\\\\\\\"PARAM_CALLBACK_update_mapping\\\\\\\"),mg=ug(\\\\\\\"PARAM_CALLBACK_update_wrap\\\\\\\"),fg=ug(\\\\\\\"PARAM_CALLBACK_update_filter\\\\\\\"),gg=ug(\\\\\\\"PARAM_CALLBACK_update_anisotropy\\\\\\\"),vg=ug(\\\\\\\"PARAM_CALLBACK_update_flipY\\\\\\\"),yg=ug(\\\\\\\"PARAM_CALLBACK_update_transform\\\\\\\"),xg=ug(\\\\\\\"PARAM_CALLBACK_update_repeat\\\\\\\"),bg=ug(\\\\\\\"PARAM_CALLBACK_update_offset\\\\\\\"),wg=ug(\\\\\\\"PARAM_CALLBACK_update_rotation\\\\\\\"),Tg=ug(\\\\\\\"PARAM_CALLBACK_update_center\\\\\\\"),Ag=ug(\\\\\\\"PARAM_CALLBACK_update_advanced\\\\\\\");function Mg(t,e){return class extends t{constructor(){super(...arguments),this.tencoding=ha.BOOLEAN((null==e?void 0:e.tencoding)||0,{...pg}),this.encoding=ha.INTEGER((null==e?void 0:e.encoding)||dg.ENCODING,{visibleIf:{tencoding:1},menu:{entries:og.map((t=>({name:Object.keys(t)[0],value:Object.values(t)[0]})))},...pg}),this.tmapping=ha.BOOLEAN(0,{..._g}),this.mapping=ha.INTEGER(dg.MAPPING,{visibleIf:{tmapping:1},menu:{entries:lg.map((t=>({name:Object.keys(t)[0],value:Object.values(t)[0]})))},..._g}),this.twrap=ha.BOOLEAN(0,{...mg}),this.wrapS=ha.INTEGER(dg.WRAPPING,{visibleIf:{twrap:1},menu:{entries:ag.map((t=>({name:Object.keys(t)[0],value:Object.values(t)[0]})))},...mg}),this.wrapT=ha.INTEGER(dg.WRAPPING,{visibleIf:{twrap:1},menu:{entries:ag.map((t=>({name:Object.keys(t)[0],value:Object.values(t)[0]})))},separatorAfter:!0,...mg}),this.tminFilter=ha.BOOLEAN(0,{...fg}),this.minFilter=ha.INTEGER(Km,{visibleIf:{tminFilter:1},menu:{entries:tf},...fg}),this.tmagFilter=ha.BOOLEAN(0,{...fg}),this.magFilter=ha.INTEGER(Zm,{visibleIf:{tmagFilter:1},menu:{entries:Qm},...fg}),this.tanisotropy=ha.BOOLEAN(0,{...gg}),this.useRendererMaxAnisotropy=ha.BOOLEAN(0,{visibleIf:{tanisotropy:1},...gg}),this.anisotropy=ha.INTEGER(2,{visibleIf:{tanisotropy:1,useRendererMaxAnisotropy:0},range:[0,32],rangeLocked:[!0,!1],...gg}),this.tflipY=ha.BOOLEAN(0,{...vg}),this.flipY=ha.BOOLEAN(0,{visibleIf:{tflipY:1},...vg}),this.ttransform=ha.BOOLEAN(0,{...yg}),this.offset=ha.VECTOR2([0,0],{visibleIf:{ttransform:1},...bg}),this.repeat=ha.VECTOR2([1,1],{visibleIf:{ttransform:1},...xg}),this.rotation=ha.FLOAT(0,{range:[-1,1],visibleIf:{ttransform:1},...wg}),this.center=ha.VECTOR2([0,0],{visibleIf:{ttransform:1},...Tg}),this.tadvanced=ha.BOOLEAN(0,{...Ag}),this.tformat=ha.BOOLEAN(0,{visibleIf:{tadvanced:1},...Ag}),this.format=ha.INTEGER(dg.FORMAT,{visibleIf:{tadvanced:1,tformat:1},menu:{entries:hg.map((t=>({name:Object.keys(t)[0],value:Object.values(t)[0]})))},...Ag}),this.ttype=ha.BOOLEAN(0,{visibleIf:{tadvanced:1},...Ag}),this.type=ha.INTEGER(dg.TYPE,{visibleIf:{tadvanced:1,ttype:1},menu:{entries:cg.map((t=>({name:Object.keys(t)[0],value:Object.values(t)[0]})))},...Ag})}}}class Eg extends(Mg(ua)){}new Eg;class Sg{constructor(t){this.node=t}async update(t){const e=this.node.pv;this._updateEncoding(t,e),this._updateAdvanced(t,e),this._updateMapping(t,e),this._updateWrap(t,e),this._updateFilter(t,e),this._updateFlip(t,e),await this._updateAnisotropy(t,e),this._updateTransform(t)}_updateEncoding(t,e){e.tencoding?t.encoding=e.encoding:t.encoding=dg.ENCODING,t.needsUpdate=!0}_updateAdvanced(t,e){e.tadvanced&&(e.tformat?t.format=e.format:t.format=dg.FORMAT,e.ttype?t.type=e.type:t.type=dg.TYPE),t.needsUpdate=!0}_updateMapping(t,e){e.tmapping?t.mapping=e.mapping:t.mapping=dg.MAPPING,t.needsUpdate=!0}_updateWrap(t,e){e.twrap?(t.wrapS=e.wrapS,t.wrapT=e.wrapT):(t.wrapS=dg.WRAPPING,t.wrapT=dg.WRAPPING),t.needsUpdate=!0}_updateFilter(t,e){e.tminFilter?t.minFilter=e.minFilter:t.minFilter=w.V,e.tmagFilter?t.magFilter=e.magFilter:t.magFilter=w.V,t.needsUpdate=!0}_updateFlip(t,e){t.flipY=e.tflipY&&e.flipY,t.needsUpdate=!0}async _updateAnisotropy(t,e){if(e.tanisotropy){if(e.useRendererMaxAnisotropy)t.anisotropy=await this._maxRendererAnisotropy();else{const n=e.anisotropy;t.anisotropy=n<=2?n:Math.min(n,await this._maxRendererAnisotropy())}t.needsUpdate=!0}else t.anisotropy=1}async _maxRendererAnisotropy(){this._renderer_controller=this._renderer_controller||new Uf(this.node);return(await this._renderer_controller.renderer()).capabilities.getMaxAnisotropy()}_updateTransform(t){if(!this.node.pv.ttransform)return t.offset.set(0,0),t.rotation=0,t.repeat.set(1,1),void t.center.set(0,0);this._updateTransformOffset(t,!1),this._updateTransformRepeat(t,!1),this._updateTransformRotation(t,!1),this._updateTransformCenter(t,!1),t.updateMatrix()}async _updateTransformOffset(t,e){t.offset.copy(this.node.pv.offset),e&&t.updateMatrix()}async _updateTransformRepeat(t,e){t.repeat.copy(this.node.pv.repeat),e&&t.updateMatrix()}async _updateTransformRotation(t,e){t.rotation=this.node.pv.rotation,e&&t.updateMatrix()}async _updateTransformCenter(t,e){t.center.copy(this.node.pv.center),e&&t.updateMatrix()}static PARAM_CALLBACK_update_encoding(t){const e=t.containerController.container().texture();e&&t.textureParamsController._updateEncoding(e,t.pv)}static PARAM_CALLBACK_update_mapping(t){const e=t.containerController.container().texture();e&&t.textureParamsController._updateMapping(e,t.pv)}static PARAM_CALLBACK_update_wrap(t){const e=t.containerController.container().texture();e&&t.textureParamsController._updateWrap(e,t.pv)}static PARAM_CALLBACK_update_filter(t){const e=t.containerController.container().texture();e&&t.textureParamsController._updateFilter(e,t.pv)}static PARAM_CALLBACK_update_anisotropy(t){const e=t.containerController.container().texture();e&&t.textureParamsController._updateAnisotropy(e,t.pv)}static PARAM_CALLBACK_update_flipY(t){const e=t.containerController.container().texture();e&&t.textureParamsController._updateFlip(e,t.pv)}static PARAM_CALLBACK_update_transform(t){const e=t.containerController.container().texture();e&&t.textureParamsController._updateTransform(e)}static PARAM_CALLBACK_update_offset(t){const e=t.containerController.container().texture();e&&t.textureParamsController._updateTransformOffset(e,!0)}static PARAM_CALLBACK_update_repeat(t){const e=t.containerController.container().texture();e&&t.textureParamsController._updateTransformRepeat(e,!0)}static PARAM_CALLBACK_update_rotation(t){const e=t.containerController.container().texture();e&&t.textureParamsController._updateTransformRotation(e,!0)}static PARAM_CALLBACK_update_center(t){const e=t.containerController.container().texture();e&&t.textureParamsController._updateTransformCenter(e,!0)}static PARAM_CALLBACK_update_advanced(t){const e=t.containerController.container().texture();e&&t.textureParamsController._updateAdvanced(e,t.pv)}static copyTextureAttributes(t,e){t.encoding=e.encoding,t.mapping=e.mapping,t.wrapS=e.wrapS,t.wrapT=e.wrapT,t.minFilter=e.minFilter,t.magFilter=e.magFilter,t.magFilter=e.magFilter,t.anisotropy=e.anisotropy,t.flipY=e.flipY,t.repeat.copy(e.repeat),t.offset.copy(e.offset),t.center.copy(e.center),t.rotation=e.rotation,t.type=e.type,t.format=e.format,t.needsUpdate=!0}paramLabelsParams(){const t=this.node.p;return[t.tencoding,t.encoding,t.tmapping,t.mapping,t.twrap,t.wrapS,t.wrapT,t.tminFilter,t.minFilter,t.tmagFilter,t.magFilter,t.tflipY,t.flipY]}paramLabels(){const t=[],e=this.node.pv;if(e.tencoding)for(let n of og){const i=Object.keys(n)[0];n[i]==e.encoding&&t.push(`encoding: ${i}`)}if(e.tmapping)for(let n of lg){const i=Object.keys(n)[0];n[i]==e.mapping&&t.push(`mapping: ${i}`)}if(e.twrap){function n(n){for(let i of ag){const s=Object.keys(i)[0];i[s]==e[n]&&t.push(`${n}: ${s}`)}}n(\\\\\\\"wrapS\\\\\\\"),n(\\\\\\\"wrapT\\\\\\\")}if(e.tminFilter)for(let n of Jm){const i=Object.keys(n)[0];n[i]==e.minFilter&&t.push(`minFilter: ${i}`)}if(e.tmagFilter)for(let n of $m){const i=Object.keys(n)[0];n[i]==e.magFilter&&t.push(`magFilter: ${i}`)}return e.tflipY&&t.push(`flipY: ${e.flipY}`),t}}class Cg extends Z.a{constructor(t,e,n,i,s,r,o,a,l){super(t,e,n,i,s,r,o,a,l),this.needsUpdate=!0}}Cg.prototype.isCanvasTexture=!0;class Ng extends(Mg(function(t){return class extends t{constructor(){super(...arguments),this.canvasId=ha.STRING(\\\\\\\"canvas-id\\\\\\\"),this.update=ha.BUTTON(null,{cook:!1,callback:t=>{Og.PARAM_CALLBACK_update(t)}})}}}(ua))){}const Lg=new Ng;class Og extends df{constructor(){super(...arguments),this.paramsConfig=Lg,this.textureParamsController=new Sg(this)}static type(){return\\\\\\\"canvas\\\\\\\"}async cook(){const t=this.pv.canvasId,e=document.getElementById(t);if(!e)return this.states.error.set(`element with id '${t}' not found`),void this.cookController.endCook();if(!(e instanceof HTMLCanvasElement))return this.states.error.set(\\\\\\\"element found is not a canvas\\\\\\\"),void this.cookController.endCook();const n=new Cg(e);await this.textureParamsController.update(n),this.setTexture(n)}static PARAM_CALLBACK_update(t){t.markTextureNeedsUpdate()}markTextureNeedsUpdate(){const t=this.containerController.container().texture();t&&(t.needsUpdate=!0)}}const Pg=new class extends ua{constructor(){super(...arguments),this.resolution=ha.VECTOR2([256,256],{callback:t=>{Rg.PARAM_CALLBACK_reset(t)}}),this.color=ha.COLOR([1,1,1])}};class Rg extends df{constructor(){super(...arguments),this.paramsConfig=Pg}static type(){return\\\\\\\"color\\\\\\\"}cook(){const t=this.pv.resolution.x,e=this.pv.resolution.y;this._data_texture=this._data_texture||this._create_data_texture(t,e);const n=e*t,i=this.pv.color.toArray(),s=255*i[0],r=255*i[1],o=255*i[2],a=this._data_texture.image.data;for(let t=0;t({name:t,value:e})))}})}};class kg extends df{constructor(){super(...arguments),this.paramsConfig=zg}static type(){return Fg.CUBE_CAMERA}async cook(){const t=this.pv.cubeCamera.nodeWithContext(ts.OBJ,this.states.error);if(!t)return this.states.error.set(`cubeCamera not found at '${this.pv.cubeCamera.path()}'`),this.cookController.endCook();const e=t.renderTarget();if(!e)return this.states.error.set(\\\\\\\"cubeCamera has no render target'\\\\\\\"),this.cookController.endCook();const n=e.texture;Bg[this.pv.mode]==Dg.REFLECTION?n.mapping=w.o:n.mapping=w.p,this.setTexture(n)}}var Ug;!function(t){t.REFLECTION=\\\\\\\"reflection\\\\\\\",t.REFRACTION=\\\\\\\"refraction\\\\\\\"}(Ug||(Ug={}));const Gg=[Ug.REFLECTION,Ug.REFRACTION];const Vg=new class extends ua{constructor(){super(...arguments),this.useCameraRenderer=ha.BOOLEAN(1),this.mode=ha.INTEGER(0,{menu:{entries:Gg.map(((t,e)=>({name:t,value:e})))}})}};class Hg extends df{constructor(){super(...arguments),this.paramsConfig=Vg}static type(){return\\\\\\\"envMap\\\\\\\"}initializeNode(){this.io.inputs.setCount(1),this.io.inputs.initInputsClonedState(Qi.NEVER)}async cook(t){const e=t[0];this.convert_texture_to_env_map(e)}async convert_texture_to_env_map(t){this._renderer_controller=this._renderer_controller||new Uf(this);const e=await this._renderer_controller.renderer();if(e){const n=new Tt(e).fromEquirectangular(t);if(this.pv.useCameraRenderer)this._set_mapping(n.texture),this.setTexture(n.texture);else{this._data_texture_controller=this._data_texture_controller||new kf(zf.Uint8Array);const t=this._data_texture_controller.from_render_target(e,n);this._set_mapping(t),this.setTexture(t)}}else this.states.error.set(\\\\\\\"no renderer found to convert the texture to an env map\\\\\\\"),this.cookController.endCook()}_set_mapping(t){Gg[this.pv.mode]==Ug.REFLECTION?t.mapping=w.q:t.mapping=w.r}}class jg extends Z.a{constructor(t,e,n,i,s,r,o,a,l){super(t,e,n,i,s,r,o,a,l),this.format=void 0!==o?o:w.ic,this.minFilter=void 0!==r?r:w.V,this.magFilter=void 0!==s?s:w.V,this.generateMipmaps=!1;const c=this;\\\\\\\"requestVideoFrameCallback\\\\\\\"in t&&t.requestVideoFrameCallback((function e(){c.needsUpdate=!0,t.requestVideoFrameCallback(e)}))}clone(){return new this.constructor(this.image).copy(this)}update(){const t=this.image;!1===\\\\\\\"requestVideoFrameCallback\\\\\\\"in t&&t.readyState>=t.HAVE_CURRENT_DATA&&(this.needsUpdate=!0)}}jg.prototype.isVideoTexture=!0;var Wg=n(80);const qg=\\\\\\\"https://raw.githubusercontent.com/polygonjs/polygonjs-assets/master/\\\\\\\";var Xg=n(28);const Yg=new Xg.b;Yg.setURLModifier((t=>{const e=li.assetUrls.remapedUrl(t);if(e)return e;const n=li.blobs.blobUrl(t);return n||t}));class $g{constructor(t,e,n){this._url=t,this._scene=e,this._node=n,this.loadingManager=Yg}static extension(t){let e=null;try{e=new URL(t).searchParams.get(\\\\\\\"ext\\\\\\\")}catch(t){}if(!e){const n=t.split(\\\\\\\"?\\\\\\\")[0].split(\\\\\\\".\\\\\\\");e=n[n.length-1].toLowerCase()}return e}extension(){return $g.extension(this._url)}async _urlToLoad(){const{storedUrl:t,fullUrl:e}=this._urlData();this._node&&await li.blobs.fetchBlobForNode({storedUrl:t,fullUrl:e,node:this._node});return li.blobs.blobUrl(t)||e}deregisterUrl(){const{storedUrl:t}=this._urlData();li.blobs.deregisterUrl(t)}_urlData(){let t=this._url;const e=this._url.split(\\\\\\\"?\\\\\\\")[0];if(\\\\\\\"h\\\\\\\"!=t[0]){const e=this._scene.assets.root();e&&(t=`${e}${t}`)}return{fullUrl:t,storedUrl:e}}static async _loadMultipleBlobGlobal(t){const e=[];for(let n of t.files){const i=n.storedUrl,s=n.fullUrl,r=t.node;e.push(li.blobs.fetchBlobGlobal({storedUrl:i,fullUrl:s,node:r}))}const n=await Promise.all(e);for(let e of n)e.error&&t.node.states.error.set(t.error)}}$g.loadingManager=Yg;const Jg=[\\\\\\\"mp4\\\\\\\",\\\\\\\"ogv\\\\\\\",\\\\\\\"ogg\\\\\\\"];var Zg;!function(t){t.JPG=\\\\\\\"jpg\\\\\\\",t.JPEG=\\\\\\\"jpeg\\\\\\\",t.PNG=\\\\\\\"png\\\\\\\",t.EXR=\\\\\\\"exr\\\\\\\",t.BASIS=\\\\\\\"basis\\\\\\\",t.HDR=\\\\\\\"hdr\\\\\\\"}(Zg||(Zg={}));const Kg=[Zg.JPEG,Zg.JPG,Zg.PNG,Zg.EXR,Zg.BASIS,Zg.HDR];function Qg(t){const e=t.split(\\\\\\\"?\\\\\\\")[0].split(\\\\\\\".\\\\\\\");return e[e.length-1]}class tv extends $g{constructor(t,e,n,i,s){super(t,i,n),this._param=e,this._node=n,this._scene=i,this._forceVideo=!1,this._forceImage=!1,this._forceVideo=(null==s?void 0:s.forceVideo)||this._forceVideo,this._forceImage=(null==s?void 0:s.forceImage)||this._forceImage}static onTextureLoaded(t){this._onTextureLoadedCallback=t}async load_texture_from_url_or_op(t){let e=null,n=null;if(\\\\\\\"op:\\\\\\\"==this._url.substring(0,3)){const t=this._url.substring(3);if(n=bi.findNode(this._node,t),n)if(n instanceof pf){e=(await n.compute()).texture()}else this._node.states.error.set(\\\\\\\"found node is not a texture node\\\\\\\");else this._node.states.error.set(`no node found in path '${t}'`)}else e=await this._loadUrl(t),e||this._node.states.error.set(`could not load texture ${this._url}`);return n&&this._param.graphPredecessors()[0]!=n&&(this._param.graphDisconnectPredecessors(),this._param.addGraphInput(n)),e}async _loadUrl(t){return new Promise((async(e,n)=>{const i=this.extension(),s=await this._urlToLoad();if(this._forceVideo||Jg.includes(i)){e(await this._loadVideo(s))}else if(this._forceImage||Kg.includes(i))try{e(await this._loadImage(s,t))}catch(t){n()}}))}_loadImage(t,e){return new Promise((async(n,i)=>{const s=this.extension();this.loader_for_ext(s,e).then((async e=>{e?(tv.incrementInProgressLoadsCount(),await tv.waitForMaxConcurrentLoadsQueueFreed(),e.load(t,(e=>{tv.decrementInProgressLoadsCount();const i=tv._onTextureLoadedCallback;i&&i(t,e),n(e)}),void 0,(t=>{tv.decrementInProgressLoadsCount(),li.warn(\\\\\\\"error\\\\\\\",t),i()}))):i()}))}))}_loadVideo(t){return new Promise((async(e,n)=>{tv.incrementInProgressLoadsCount(),await tv.waitForMaxConcurrentLoadsQueueFreed();const i=document.createElement(\\\\\\\"video\\\\\\\");i.setAttribute(\\\\\\\"crossOrigin\\\\\\\",\\\\\\\"anonymous\\\\\\\"),i.setAttribute(\\\\\\\"autoplay\\\\\\\",\\\\\\\"true\\\\\\\"),i.setAttribute(\\\\\\\"loop\\\\\\\",\\\\\\\"true\\\\\\\"),i.onloadedmetadata=function(){i.pause();const n=new jg(i);tv.decrementInProgressLoadsCount();const s=tv._onTextureLoadedCallback;s&&s(t,n),e(n)};const s=document.createElement(\\\\\\\"source\\\\\\\"),r=$g.extension(t);let o=tv.VIDEO_SOURCE_TYPE_BY_EXT[r];o=o||tv._default_video_source_type(t),s.setAttribute(\\\\\\\"type\\\\\\\",o),s.setAttribute(\\\\\\\"src\\\\\\\",t),i.appendChild(s);let a=t;a=\\\\\\\"mp4\\\\\\\"==r?tv.replaceExtension(t,\\\\\\\"ogv\\\\\\\"):tv.replaceExtension(t,\\\\\\\"mp4\\\\\\\");const l=document.createElement(\\\\\\\"source\\\\\\\"),c=$g.extension(a);o=tv.VIDEO_SOURCE_TYPE_BY_EXT[c],o=o||tv._default_video_source_type(t),l.setAttribute(\\\\\\\"type\\\\\\\",o),l.setAttribute(\\\\\\\"src\\\\\\\",t),i.appendChild(l)}))}static module_names(t){switch(t){case Zg.EXR:return[Hn.EXRLoader];case Zg.HDR:return[Hn.RGBELoader];case Zg.BASIS:return[Hn.BasisTextureLoader]}}async loader_for_ext(t,e){switch(t.toLowerCase()){case Zg.EXR:return await this._exr_loader(e);case Zg.HDR:return await this._hdr_loader(e);case Zg.BASIS:return await tv._basis_loader(this._node)}return new Wg.a(this.loadingManager)}async _exr_loader(t){const e=await li.modulesRegister.module(Hn.EXRLoader);if(e){const n=new e(this.loadingManager);return t.tdataType&&n.setDataType(t.dataType),n}}async _hdr_loader(t){const e=await li.modulesRegister.module(Hn.RGBELoader);if(e){const n=new e(this.loadingManager);return t.tdataType&&n.setDataType(t.dataType),n}}static async _basis_loader(t){const e=await li.modulesRegister.module(Hn.BasisTextureLoader);if(e){const n=new e(this.loadingManager),i=li.libs.root(),s=li.libs.BASISPath();if(i||s){const e=`${i||\\\\\\\"\\\\\\\"}${s||\\\\\\\"\\\\\\\"}/`;if(t){const n=[\\\\\\\"basis_transcoder.js\\\\\\\",\\\\\\\"basis_transcoder.wasm\\\\\\\"];await this._loadMultipleBlobGlobal({files:n.map((t=>({storedUrl:`${s}/${t}`,fullUrl:`${e}${t}`}))),node:t,error:\\\\\\\"failed to load basis libraries. Make sure to install them to load .basis files\\\\\\\"})}n.setTranscoderPath(e)}else n.setTranscoderPath(void 0);const r=await li.renderersController.waitForRenderer();return r?n.detectSupport(r):li.warn(\\\\\\\"texture loader found no renderer for basis texture loader\\\\\\\"),n}}static _default_video_source_type(t){return`video/${$g.extension(t)}`}static pixel_data(t){const e=t.image,n=document.createElement(\\\\\\\"canvas\\\\\\\");n.width=e.width,n.height=e.height;const i=n.getContext(\\\\\\\"2d\\\\\\\");if(i)return i.drawImage(e,0,0,e.width,e.height),i.getImageData(0,0,e.width,e.height)}static replaceExtension(t,e){const n=t.split(\\\\\\\"?\\\\\\\"),i=n[0].split(\\\\\\\".\\\\\\\");return i.pop(),i.push(e),[i.join(\\\\\\\".\\\\\\\"),n[1]].join(\\\\\\\"?\\\\\\\")}static setMaxConcurrentLoadsCount(t){this._maxConcurrentLoadsCountMethod=t}static _init_max_concurrent_loads_count(){return this._maxConcurrentLoadsCountMethod?this._maxConcurrentLoadsCountMethod():ng.isChrome()?10:4}static _init_concurrent_loads_delay(){return ng.isChrome()?0:10}static incrementInProgressLoadsCount(){this.in_progress_loads_count++}static decrementInProgressLoadsCount(){this.in_progress_loads_count--;const t=this._queue.pop();if(t){const e=this.CONCURRENT_LOADS_DELAY;setTimeout((()=>{t()}),e)}}static async waitForMaxConcurrentLoadsQueueFreed(){return this.in_progress_loads_count<=this.MAX_CONCURRENT_LOADS_COUNT?void 0:new Promise((t=>{this._queue.push(t)}))}}tv.PARAM_DEFAULT=`${qg}/textures/uv.jpg`,tv.PARAM_ENV_DEFAULT=`${qg}/textures/piz_compressed.exr`,tv.VIDEO_SOURCE_TYPE_BY_EXT={ogg:'video/ogg; codecs=\\\\\\\"theora, vorbis\\\\\\\"',ogv:'video/ogg; codecs=\\\\\\\"theora, vorbis\\\\\\\"',mp4:'video/mp4; codecs=\\\\\\\"avc1.42E01E, mp4a.40.2\\\\\\\"'},tv.MAX_CONCURRENT_LOADS_COUNT=tv._init_max_concurrent_loads_count(),tv.CONCURRENT_LOADS_DELAY=tv._init_concurrent_loads_delay(),tv.in_progress_loads_count=0,tv._queue=[];var ev=n(114);class nv extends(Mg(function(t){return class extends t{constructor(){super(...arguments),this.url=ha.STRING(tv.PARAM_DEFAULT,{fileBrowse:{type:[Rr.TEXTURE_IMAGE]}}),this.reload=ha.BUTTON(null,{callback:(t,e)=>{sv.PARAM_CALLBACK_reload(t)}}),this.play=ha.BOOLEAN(1,{cook:!1,callback:t=>{sv.PARAM_CALLBACK_gifUpdatePlay(t)}}),this.gifFrame=ha.INTEGER(0,{cook:!1,range:[0,100],rangeLocked:[!0,!1],callback:t=>{sv.PARAM_CALLBACK_gifUpdateFrameIndex(t)}})}}}(ua))){}const iv=new nv;class sv extends df{constructor(){super(...arguments),this.paramsConfig=iv,this.textureParamsController=new Sg(this),this._gifCanvasContext=null,this._tmpCanvasContext=null,this._parsedFrames=[],this._frameDelay=100,this._frameIndex=0}static type(){return\\\\\\\"gif\\\\\\\"}async requiredModules(){this.p.url.isDirty()&&await this.p.url.compute();const t=$g.extension(this.pv.url||\\\\\\\"\\\\\\\");return tv.module_names(t)}static displayedInputNames(){return[\\\\\\\"optional texture to copy attributes from\\\\\\\"]}initializeNode(){this.io.inputs.setCount(0,1),this.io.inputs.initInputsClonedState(Qi.NEVER),this.scene().dispatchController.onAddListener((()=>{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{let t=[this.p.url];t=t.concat(this.textureParamsController.paramLabelsParams()),this.params.label.init(t,(()=>{const t=this.p.url.rawInput();if(t){const e=t.split(\\\\\\\"/\\\\\\\"),n=e[e.length-1],i=this.textureParamsController.paramLabels();return[n].concat(i)}return\\\\\\\"\\\\\\\"}))}))}))}async cook(t){if(\\\\\\\"gif\\\\\\\"!=Qg(this.pv.url).toLowerCase())this.states.error.set(\\\\\\\"url is not an image\\\\\\\");else{tv.incrementInProgressLoadsCount(),await tv.waitForMaxConcurrentLoadsQueueFreed();const t=await fetch(this.pv.url),e=await t.arrayBuffer(),n=await Object(ev.parseGIF)(e),i=!0;this._parsedFrames=await Object(ev.decompressFrames)(n,i);const s=this._parsedFrames[0];if(this._frameDelay=s.delay,this._frameIndex=this.pv.gifFrame-1,this._createCanvas(),tv.decrementInProgressLoadsCount(),this._gifCanvasElement){const t=new Cg(this._gifCanvasElement);await this.textureParamsController.update(t),this.setTexture(t)}else this.states.error.set(\\\\\\\"failed to create canvas\\\\\\\")}}_createCanvas(){const t=this._parsedFrames[0];this._gifCanvasElement=document.createElement(\\\\\\\"canvas\\\\\\\"),this._tmpCanvasElement=document.createElement(\\\\\\\"canvas\\\\\\\"),this._gifCanvasElement.width=t.dims.width,this._gifCanvasElement.height=t.dims.height,this._tmpCanvasElement.width=t.dims.width,this._tmpCanvasElement.height=t.dims.height,this._gifCanvasContext=this._gifCanvasElement.getContext(\\\\\\\"2d\\\\\\\"),this._tmpCanvasContext=this._tmpCanvasElement.getContext(\\\\\\\"2d\\\\\\\"),this._drawNextFrame()}_drawOnCanvas(){if(!(this._gifCanvasContext&&this._tmpCanvasElement&&this._tmpCanvasContext))return;let t=this._parsedFrames[this._frameIndex];if(t||(console.warn(`no frame at index ${this._frameIndex}, using last frame`),t=this._parsedFrames[this._parsedFrames.length-1]),t){const e=t.dims;this._frameImageData&&e.width==this._frameImageData.width&&e.height==this._frameImageData.height||(this._tmpCanvasElement.width=e.width,this._tmpCanvasElement.height=e.height,this._frameImageData=this._tmpCanvasContext.createImageData(e.width,e.height)),this._frameImageData.data.set(t.patch),this._tmpCanvasContext.putImageData(this._frameImageData,0,0),this._gifCanvasContext.drawImage(this._tmpCanvasElement,e.left,e.top);const n=this.containerController.container().texture();if(!n)return;n.needsUpdate=!0}}_drawNextFrame(){this._frameIndex++,this._frameIndex>=this._parsedFrames.length&&(this._frameIndex=0),this._drawOnCanvas(),this.pv.play&&setTimeout((()=>{this._drawNextFrame()}),this._frameDelay)}gifUpdateFrameIndex(){this._frameIndex=this.pv.gifFrame,this._drawOnCanvas()}static PARAM_CALLBACK_reload(t){t.paramCallbackReload()}paramCallbackReload(){this.p.url.setDirty()}static PARAM_CALLBACK_gifUpdatePlay(t){t.gifUpdatePlay()}gifUpdatePlay(){this.pv.play&&this._drawNextFrame()}static PARAM_CALLBACK_gifUpdateFrameIndex(t){t.gifUpdateFrameIndex()}}function rv(t){return class extends t{constructor(){super(...arguments),this.checkFileType=ha.BOOLEAN(!0)}}}class ov extends(rv(Mg(function(t){return class extends t{constructor(){super(...arguments),this.url=ha.STRING(tv.PARAM_DEFAULT,{fileBrowse:{type:[Rr.TEXTURE_IMAGE]}}),this.reload=ha.BUTTON(null,{callback:(t,e)=>{lv.PARAM_CALLBACK_reload(t,e)}})}}}(ua)))){}const av=new ov;class lv extends df{constructor(){super(...arguments),this.paramsConfig=av,this.textureParamsController=new Sg(this)}static type(){return\\\\\\\"image\\\\\\\"}async requiredModules(){this.p.url.isDirty()&&await this.p.url.compute();const t=$g.extension(this.pv.url||\\\\\\\"\\\\\\\");return tv.module_names(t)}static displayedInputNames(){return[\\\\\\\"optional texture to copy attributes from\\\\\\\"]}initializeNode(){this.io.inputs.setCount(0,1),this.io.inputs.initInputsClonedState(Qi.NEVER),this.scene().dispatchController.onAddListener((()=>{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{let t=[this.p.url];t=t.concat(this.textureParamsController.paramLabelsParams()),this.params.label.init(t,(()=>{const t=this.p.url.rawInput();if(t){const e=t.split(\\\\\\\"/\\\\\\\"),n=e[e.length-1],i=this.textureParamsController.paramLabels();return[n].concat(i)}return\\\\\\\"\\\\\\\"}))}))}))}async cook(t){if(this.pv.checkFileType&&(e=this.pv.url,!Kg.includes(Qg(e).toLowerCase())))this.states.error.set(\\\\\\\"url is not an image\\\\\\\");else{const e=await this._loadTexture();if(e){const n=t[0];n&&Sg.copyTextureAttributes(e,n),await this.textureParamsController.update(e),this.setTexture(e)}else this._clearTexture()}var e}static PARAM_CALLBACK_reload(t,e){t.paramCallbackReload()}paramCallbackReload(){this.clearLoadedBlob(),this.p.url.setDirty()}_loader(){return new tv(this.pv.url,this.p.url,this,this.scene(),{forceImage:!this.pv.checkFileType})}async _loadTexture(){let t=null;try{t=await this._loader().load_texture_from_url_or_op({tdataType:this.pv.ttype&&this.pv.tadvanced,dataType:this.pv.type}),t&&(t.matrixAutoUpdate=!1)}catch(t){}return t||this.states.error.set(`could not load texture '${this.pv.url}'`),t}clearLoadedBlob(){this._loader().deregisterUrl()}}var cv=n(33);const hv=.005;class uv{constructor(t,e=1024){this.renderer=t,this.res=e,this.objectTargets=[],this.lights=[],this.scene=new vs,this.buffer1Active=!1,this._params={lightRadius:1,iterations:1,iterationBlend:hv,blur:!1,blurAmount:0},this._objectStateByObject=new WeakMap,this._previousRenderTarget=null,this._lightHierarchyStateByLight=new WeakMap,this._lightMatrixStateByLight=new WeakMap,this._t=new p.a,this._q=new hh.a,this._s=new p.a;const n=ng.isAndroid()||ng.isiOS()?w.M:w.G;this.progressiveLightMap1=new K(this.res,this.res,{type:n}),this.progressiveLightMap2=new K(this.res,this.res,{type:n}),this.uvMat=this._createUVMat()}textureRenderTarget(){return this.progressiveLightMap2}texture(){return this.textureRenderTarget().texture}setParams(t){this._params.lightRadius=t.lightRadius,this._params.iterations=t.iterations,this._params.iterationBlend=t.iterationBlend,this._params.blur=t.blur,this._params.blurAmount=t.blurAmount}init(t,e){this._setObjects(t),this._setLights(e)}_setObjects(t){this.objectTargets=[];for(let e of t)null==this.blurringPlane&&this._initializeBlurPlane(this.res,this.progressiveLightMap1),this.objectTargets.push(e);this._saveObjectsState()}_setLights(t){this.lights=t;for(let e of t)this._saveLightHierarchyState(e),this.scene.attach(e),this._saveLightMatrixState(e)}_saveLightHierarchyState(t){this._lightHierarchyStateByLight.set(t,{parent:t.parent,matrixAutoUpdate:t.matrixAutoUpdate}),t.matrixAutoUpdate=!0}_saveLightMatrixState(t){t.updateMatrix(),t.matrix.decompose(this._t,this._q,this._s),this._lightMatrixStateByLight.set(t,{matrix:t.matrix.clone(),position:this._t.clone()})}_saveObjectsState(){let t=0;for(let e of this.objectTargets)this._objectStateByObject.set(e,{frustumCulled:e.frustumCulled,material:e.material,parent:e.parent,castShadow:e.castShadow,receiveShadow:e.receiveShadow}),e.material=this.uvMat,e.frustumCulled=!1,e.castShadow=!0,e.receiveShadow=!0,e.renderOrder=1e3+t,this.scene.attach(e),t++;this._previousRenderTarget=this.renderer.getRenderTarget()}_moveLights(){const t=this._params.lightRadius;for(let e of this.lights){const n=this._lightMatrixStateByLight.get(e);if(n){const i=n.position;e.position.x=i.x+t*(Math.random()-.5),e.position.y=i.y+t*(Math.random()-.5),e.position.z=i.z+t*(Math.random()-.5)}}}restoreState(){this._restoreObjectsState(),this._restoreLightsState(),this.renderer.setRenderTarget(this._previousRenderTarget)}_restoreObjectsState(){for(let t of this.objectTargets){const e=this._objectStateByObject.get(t);if(e){t.frustumCulled=e.frustumCulled,t.castShadow=e.castShadow,t.receiveShadow=e.receiveShadow,t.material=e.material;const n=e.parent;n&&n.add(t)}}}_restoreLightsState(){var t;for(let e of this.lights){const n=this._lightHierarchyStateByLight.get(e),i=this._lightMatrixStateByLight.get(e);n&&i&&(e.matrixAutoUpdate=n.matrixAutoUpdate,e.matrix.copy(i.matrix),e.matrix.decompose(e.position,e.quaternion,e.scale),e.updateMatrix(),null===(t=n.parent)||void 0===t||t.attach(e))}}runUpdates(t){if(!this.blurMaterial)return;if(null==this.blurringPlane)return;const e=this._params.iterations;this.blurMaterial.uniforms.pixelOffset.value=this._params.blurAmount/this.res,this.blurringPlane.visible=this._params.blur,this.uvMat.uniforms.iterationBlend.value=this._params.iterationBlend,this._clear(t);for(let n=0;n{i.vertexShader=\\\\\\\"#define USE_UV\\\\n\\\\\\\"+i.vertexShader.slice(0,-2)+\\\\\\\"\\\\tgl_Position = vec4((uv - 0.5) * 2.0, 1.0, 1.0); }\\\\\\\";const s=i.fragmentShader.indexOf(\\\\\\\"void main() {\\\\\\\");i.fragmentShader=\\\\\\\"#define USE_UV\\\\n\\\\\\\"+i.fragmentShader.slice(0,s)+\\\\\\\"\\\\tuniform sampler2D previousShadowMap;\\\\n\\\\tuniform float pixelOffset;\\\\n\\\\\\\"+i.fragmentShader.slice(s-1,-2)+\\\\\\\"\\\\tgl_FragColor.rgb = (\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\ttexture2D(previousShadowMap, vUv + vec2( pixelOffset, 0.0 )).rgb +\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\ttexture2D(previousShadowMap, vUv + vec2( 0.0 , pixelOffset)).rgb +\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\ttexture2D(previousShadowMap, vUv + vec2( 0.0 , -pixelOffset)).rgb +\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\ttexture2D(previousShadowMap, vUv + vec2(-pixelOffset, 0.0 )).rgb +\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\ttexture2D(previousShadowMap, vUv + vec2( pixelOffset, pixelOffset)).rgb +\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\ttexture2D(previousShadowMap, vUv + vec2(-pixelOffset, pixelOffset)).rgb +\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\ttexture2D(previousShadowMap, vUv + vec2( pixelOffset, -pixelOffset)).rgb +\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\ttexture2D(previousShadowMap, vUv + vec2(-pixelOffset, -pixelOffset)).rgb)/8.0;\\\\n\\\\t\\\\t\\\\t\\\\t}\\\\\\\";const r={previousShadowMap:{value:e.texture},pixelOffset:{value:.5/t}};i.uniforms.previousShadowMap=r.previousShadowMap,i.uniforms.pixelOffset=r.pixelOffset,n.uniforms.previousShadowMap=r.previousShadowMap,n.uniforms.pixelOffset=r.pixelOffset,n.userData.shader=i},n}_createUVMat(){const t=new qf.a;return t.uniforms={previousShadowMap:{value:null},iterationBlend:{value:hv}},t.name=\\\\\\\"uvMat\\\\\\\",t.onBeforeCompile=e=>{e.vertexShader=\\\\\\\"#define USE_LIGHTMAP\\\\n\\\\\\\"+e.vertexShader.slice(0,-2)+\\\\\\\"\\\\tgl_Position = vec4((uv2 - 0.5) * 2.0, 1.0, 1.0); }\\\\\\\";const n=e.fragmentShader.indexOf(\\\\\\\"void main() {\\\\\\\");e.fragmentShader=\\\\\\\"varying vec2 vUv2;\\\\n\\\\\\\"+e.fragmentShader.slice(0,n)+\\\\\\\"\\\\tuniform sampler2D previousShadowMap;\\\\n\\\\tuniform float iterationBlend;\\\\n\\\\\\\"+e.fragmentShader.slice(n-1,-2)+\\\\\\\"\\\\nvec3 texelOld = texture2D(previousShadowMap, vUv2).rgb;\\\\n\\\\t\\\\t\\\\t\\\\tgl_FragColor.rgb = mix(texelOld, gl_FragColor.rgb, iterationBlend);\\\\n\\\\t\\\\t\\\\t\\\\t// gl_FragColor.rgb = vec3(vUv2,1.0);\\\\n\\\\t\\\\t\\\\t}\\\\\\\";const i={previousShadowMap:{value:this.progressiveLightMap1.texture},iterationBlend:{value:hv}};e.uniforms.previousShadowMap=i.previousShadowMap,e.uniforms.iterationBlend=i.iterationBlend,t.uniforms.previousShadowMap=i.previousShadowMap,t.uniforms.iterationBlend=i.iterationBlend,t.userData.shader=e},t}}const dv=new class extends ua{constructor(){super(...arguments),this.update=ha.BUTTON(null,{callback:t=>{pv.PARAM_CALLBACK_updateManual(t)}}),this.useCameraRenderer=ha.BOOLEAN(1),this.lightMapRes=ha.INTEGER(1024,{range:[1,2048],rangeLocked:[!0,!1]}),this.iterations=ha.INTEGER(512,{range:[1,2048],rangeLocked:[!0,!1]}),this.iterationBlend=ha.FLOAT(hv,{range:[0,1],rangeLocked:[!0,!0]}),this.blur=ha.BOOLEAN(1),this.blurAmount=ha.FLOAT(1,{visibleIf:{blur:1},range:[0,1],rangeLocked:[!0,!1]}),this.lightRadius=ha.FLOAT(1,{range:[0,10]}),this.objectsMask=ha.STRING(\\\\\\\"\\\\\\\"),this.lightsMask=ha.STRING(\\\\\\\"*\\\\\\\"),this.printResolveObjectsList=ha.BUTTON(null,{callback:t=>{pv.PARAM_CALLBACK_printResolveObjectsList(t)}})}};class pv extends df{constructor(){super(...arguments),this.paramsConfig=dv,this._includedObjects=[],this._includedLights=[]}static type(){return\\\\\\\"lightMap\\\\\\\"}async cook(){this._updateManual()}async _createLightMapController(){const t=await li.renderersController.firstRenderer();if(!t)return void console.warn(\\\\\\\"no renderer found\\\\\\\");return new uv(t,this.pv.lightMapRes)}static PARAM_CALLBACK_update_updateMode(t){}async _updateManual(){if(this.lightMapController=this.lightMapController||await this._createLightMapController(),!this.lightMapController)return;const t=this.scene().mainCameraNode();if(!t)return;this._updateObjectsAndLightsList(),this.lightMapController.init(this._includedObjects,this._includedLights);const e=t.camera();this.lightMapController.setParams({lightRadius:this.pv.lightRadius,iterations:this.pv.iterations,iterationBlend:this.pv.iterationBlend,blur:this.pv.blur,blurAmount:this.pv.blurAmount}),this.lightMapController.runUpdates(e),this.lightMapController.restoreState();const n=this.lightMapController.textureRenderTarget();if(this.pv.useCameraRenderer)this.setTexture(n.texture);else{this._data_texture_controller=this._data_texture_controller||new kf(zf.Float32Array),this._renderer_controller=this._renderer_controller||new Uf(this);const t=await this._renderer_controller.renderer(),e=this._data_texture_controller.from_render_target(t,n);this.setTexture(e)}}static PARAM_CALLBACK_updateManual(t){t._updateManual()}_updateObjectsAndLightsList(){let t=[],e=[];this._includedLights=[],this._includedObjects=[];const n=new WeakSet;if(\\\\\\\"\\\\\\\"!=this.pv.lightsMask){e=this.scene().objectsByMask(this.pv.lightsMask);for(let t of e)t instanceof cv.a&&(this._includedLights.push(t),n.add(t))}if(\\\\\\\"\\\\\\\"!=this.pv.objectsMask){t=this.scene().objectsByMask(this.pv.objectsMask);for(let e of t)e instanceof cv.a||!n.has(e)&&e instanceof B.a&&this._includedObjects.push(e)}}static PARAM_CALLBACK_printResolveObjectsList(t){t._printResolveObjectsList()}_printResolveObjectsList(){this._updateObjectsAndLightsList(),console.log(\\\\\\\"included objects:\\\\\\\"),console.log(this._includedObjects),console.log(\\\\\\\"included lights:\\\\\\\"),console.log(this._includedLights)}}const _v=new ua;class mv extends df{constructor(){super(...arguments),this.paramsConfig=_v}static type(){return\\\\\\\"null\\\\\\\"}initializeNode(){this.io.inputs.setCount(1),this.io.inputs.initInputsClonedState(Qi.NEVER)}async cook(t){const e=t[0];this.setTexture(e)}}class fv extends(Mg(function(t){return class extends t{constructor(){super(...arguments),this.camera=ha.NODE_PATH(\\\\\\\"\\\\\\\",{nodeSelection:{context:ts.OBJ,types:ds}}),this.resolution=ha.VECTOR2([1024,1024]),this.useCameraRenderer=ha.BOOLEAN(1),this.render=ha.BUTTON(null,{callback:t=>{vv.PARAM_CALLBACK_render(t)}})}}}(ua))){}const gv=new fv;class vv extends df{constructor(){super(...arguments),this.paramsConfig=gv,this.textureParamsController=new Sg(this)}static type(){return\\\\\\\"render\\\\\\\"}async cook(){this._texture_scene=this.scene().threejsScene(),this._camera_node=this.pv.camera.nodeWithContext(ts.OBJ),this._camera_node&&ds.includes(this._camera_node.type())?(this._texture_camera=this._camera_node.object,await this._camera_node.compute(),this.renderOnTarget()):this._texture_camera=void 0}async renderOnTarget(){if(await this.createRenderTargetIfRequired(),!(this._render_target&&this._texture_scene&&this._texture_camera))return;this._renderer_controller=this._renderer_controller||new Uf(this);const t=await this._renderer_controller.renderer(),e=t.getRenderTarget();if(t.setRenderTarget(this._render_target),t.clear(),t.render(this._texture_scene,this._texture_camera),t.setRenderTarget(e),this._render_target.texture)if(this.pv.useCameraRenderer)this.setTexture(this._render_target.texture);else{this._data_texture_controller=this._data_texture_controller||new kf(zf.Float32Array);const e=this._data_texture_controller.from_render_target(t,this._render_target);await this.textureParamsController.update(e),this.setTexture(e)}else this.cookController.endCook()}async renderTarget(){return this._render_target=this._render_target||await this._createRenderTarget(this.pv.resolution.x,this.pv.resolution.y)}async createRenderTargetIfRequired(){var t;this._render_target&&this._renderTargetResolutionValid()||(this._render_target=await this._createRenderTarget(this.pv.resolution.x,this.pv.resolution.y),null===(t=this._data_texture_controller)||void 0===t||t.reset())}_renderTargetResolutionValid(){if(this._render_target){const t=this._render_target.texture.image;return t.width==this.pv.resolution.x&&t.height==this.pv.resolution.y}return!1}async _createRenderTarget(t,e){if(this._render_target){const n=this._render_target.texture.image;if(n.width==t&&n.height==e)return this._render_target}const n=w.n,i=w.n,s=w.V,r=w.ob;var o=new K(t,e,{wrapS:n,wrapT:i,minFilter:s,magFilter:r,format:w.Ib,generateMipmaps:!0,type:ng.isiOS()?w.M:w.G,stencilBuffer:!1,depthBuffer:!1});return await this.textureParamsController.update(o.texture),li.warn(\\\\\\\"created render target\\\\\\\",this.path(),t,e),o}static PARAM_CALLBACK_render(t){t.renderOnTarget()}}const yv=t=>(t.preventDefault(),!1);class xv{static disableContextMenu(){document.addEventListener(\\\\\\\"contextmenu\\\\\\\",yv)}static reEstablishContextMenu(){document.removeEventListener(\\\\\\\"contextmenu\\\\\\\",yv)}static isHTMLVideoElementLoaded(t){return 4===t.readyState}}class bv extends(function(t){return class extends t{constructor(){super(...arguments),this.capture=ha.BUTTON(null,{callback:t=>{Tv.PARAM_CALLBACK_snapshot(t)}})}}}(ua)){}const wv=new bv;class Tv extends df{constructor(){super(...arguments),this.paramsConfig=wv}static type(){return Fg.SNAPSHOT}static displayedInputNames(){return[\\\\\\\"input to take a snapshot of\\\\\\\"]}initializeNode(){this.io.inputs.setCount(1),this.io.inputs.initInputsClonedState(Qi.NEVER)}async cook(t){const e=t[0];if(e&&e instanceof jg){const t=await this._canvasToTexture(e);if(t)return Sg.copyTextureAttributes(t,e),void this.setTexture(t)}else this.states.error.set(\\\\\\\"input texture is not a video\\\\\\\");this.cookController.endCook()}static PARAM_CALLBACK_snapshot(t){t.paramCallbackSnapshot()}paramCallbackSnapshot(){this.setDirty()}_videoSnapshotCanvas(t){const e=t.image;if(!xv.isHTMLVideoElementLoaded(e))return void this.states.error.set(\\\\\\\"video not loaded\\\\\\\");const n=document.createElement(\\\\\\\"canvas\\\\\\\");n.width=t.image.videoWidth,n.height=t.image.videoHeight;return n.getContext(\\\\\\\"2d\\\\\\\").drawImage(t.image,0,0,n.width,n.height),n}_canvasToTexture(t){const e=this._canvas;let n=!0;const i=this._videoSnapshotCanvas(t);if(i)return e&&i.width==e.width&&i.height==e.height&&(n=!1),this._canvas=i,new Promise((e=>{if(!this._canvas)return;const i=this._canvas.toDataURL(\\\\\\\"image/png\\\\\\\"),s=new Image;s.onload=()=>{let i;n?(i=new Z.a(s),i.encoding=t.encoding):(i=this.containerController.container().coreContent(),i.copy(t)),i.needsUpdate=!0,e(i)},s.src=i}))}}const Av=new class extends ua{constructor(){super(...arguments),this.input=ha.INTEGER(0,{range:[0,3],rangeLocked:[!0,!0]})}};class Mv extends df{constructor(){super(...arguments),this.paramsConfig=Av}static type(){return\\\\\\\"switch\\\\\\\"}initializeNode(){this.io.inputs.setCount(0,4),this.io.inputs.initInputsClonedState(Qi.NEVER),this.cookController.disallowInputsEvaluation()}async cook(){const t=this.pv.input;if(this.io.inputs.has_input(t)){const e=await this.containerController.requestInputContainer(t);if(e)return void this.setTexture(e.texture())}else this.states.error.set(`no input ${t}`);this.cookController.endCook()}}class Ev extends(Mg(ua)){}const Sv=new Ev;class Cv extends df{constructor(){super(...arguments),this.paramsConfig=Sv,this.textureParamsController=new Sg(this)}static type(){return\\\\\\\"textureProperties\\\\\\\"}initializeNode(){this.io.inputs.setCount(1),this.io.inputs.initInputsClonedState([Qi.FROM_NODE])}async cook(t){const e=t[0];this.textureParamsController.update(e),this.setTexture(e)}}class Nv extends(rv(Mg(function(t){return class extends t{constructor(){super(...arguments),this.url=ha.STRING(tv.PARAM_DEFAULT,{fileBrowse:{type:[Rr.TEXTURE_VIDEO]}}),this.reload=ha.BUTTON(null,{callback:(t,e)=>{Ov.PARAM_CALLBACK_reload(t,e)}}),this.play=ha.BOOLEAN(1,{cook:!1,callback:t=>{Ov.PARAM_CALLBACK_video_update_play(t)}}),this.muted=ha.BOOLEAN(1,{cook:!1,callback:t=>{Ov.PARAM_CALLBACK_video_update_muted(t)}}),this.loop=ha.BOOLEAN(1,{cook:!1,callback:t=>{Ov.PARAM_CALLBACK_video_update_loop(t)}}),this.videoTime=ha.FLOAT(0,{cook:!1}),this.setVideoTime=ha.BUTTON(null,{cook:!1,callback:t=>{Ov.PARAM_CALLBACK_video_update_time(t)}})}}}(ua)))){}const Lv=new Nv;class Ov extends df{constructor(){super(...arguments),this.paramsConfig=Lv,this.textureParamsController=new Sg(this)}static type(){return Fg.VIDEO}async requiredModules(){this.p.url.isDirty()&&await this.p.url.compute();const t=$g.extension(this.pv.url||\\\\\\\"\\\\\\\");return tv.module_names(t)}HTMLVideoElement(){return this._video}static displayedInputNames(){return[\\\\\\\"optional texture to copy attributes from\\\\\\\"]}initializeNode(){this.io.inputs.setCount(0,1),this.io.inputs.initInputsClonedState(Qi.NEVER),this.scene().dispatchController.onAddListener((()=>{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{this.params.label.init([this.p.url],(()=>{const t=this.p.url.rawInput();if(t){const e=t.split(\\\\\\\"/\\\\\\\");return e[e.length-1]}return\\\\\\\"\\\\\\\"}))}))}))}async cook(t){if(this.pv.checkFileType&&(e=this.pv.url,!Jg.includes(Qg(e).toLowerCase())))this.states.error.set(\\\\\\\"url is not a video\\\\\\\");else{const e=await this._load_texture(this.pv.url);if(e){this._video=e.image,this._video&&document.body.appendChild(this._video);const n=t[0];n&&Sg.copyTextureAttributes(e,n),this.video_update_loop(),this.video_update_muted(),this.video_update_play(),this.video_update_time(),await this.textureParamsController.update(e),this.setTexture(e)}else this.cookController.endCook()}var e}dispose(){var t;super.dispose(),this._video&&(null===(t=this._video.parentElement)||void 0===t||t.removeChild(this._video))}static PARAM_CALLBACK_video_update_time(t){t.video_update_time()}static PARAM_CALLBACK_video_update_play(t){t.video_update_play()}static PARAM_CALLBACK_video_update_muted(t){t.video_update_muted()}static PARAM_CALLBACK_video_update_loop(t){t.video_update_loop()}async video_update_time(){if(this._video){const t=this.p.videoTime;t.isDirty()&&await t.compute(),this._video.currentTime=t.value}}video_update_muted(){this._video&&(this._video.muted=this.pv.muted)}video_update_loop(){this._video&&(this._video.loop=this.pv.loop)}video_update_play(){this._video&&(this.pv.play?this._video.play():this._video.pause())}static PARAM_CALLBACK_reload(t,e){t.paramCallbackReload()}paramCallbackReload(){this.p.url.setDirty()}async _load_texture(t){let e=null;const n=this.p.url;this._texture_loader=this._texture_loader||new tv(t,n,this,this.scene(),{forceVideo:!this.pv.checkFileType});try{e=await this._texture_loader.load_texture_from_url_or_op({tdataType:this.pv.ttype&&this.pv.tadvanced,dataType:this.pv.type}),e&&(e.matrixAutoUpdate=!1)}catch(t){}return e||this.states.error.set(`could not load texture '${t}'`),e}}class Pv extends(Mg(function(t){return class extends t{constructor(){super(...arguments),this.res=ha.VECTOR2([1024,1024])}}}(ua),{tencoding:!0,encoding:w.ld})){}const Rv=new Pv;class Iv extends df{constructor(){super(...arguments),this.paramsConfig=Rv,this.textureParamsController=new Sg(this)}static type(){return Fg.WEB_CAM}HTMLVideoElement(){return this._video}static displayedInputNames(){return[\\\\\\\"optional texture to copy attributes from\\\\\\\"]}initializeNode(){this.io.inputs.setCount(0,1),this.io.inputs.initInputsClonedState(Qi.NEVER)}dispose(){super.dispose(),this._cancelWebcamRequest()}_cancelWebcamRequest(){try{this._stream&&this._stream.getTracks().forEach((function(t){t.stop()}))}catch(t){console.error(t),console.warn(\\\\\\\"failed to cancel webcam request\\\\\\\")}}_createHTMLVideoElement(){this._video&&document.body.removeChild(this._video);const t=document.createElement(\\\\\\\"video\\\\\\\");return t.style.display=\\\\\\\"none\\\\\\\",t.width=this.pv.res.x,t.height=this.pv.res.y,t.autoplay=!0,t.setAttribute(\\\\\\\"autoplay\\\\\\\",\\\\\\\"true\\\\\\\"),t.setAttribute(\\\\\\\"muted\\\\\\\",\\\\\\\"true\\\\\\\"),t.setAttribute(\\\\\\\"playsinline\\\\\\\",\\\\\\\"true\\\\\\\"),document.body.appendChild(t),t}async cook(t){this._video=this._createHTMLVideoElement();const e=new jg(this._video),n=t[0];if(n&&Sg.copyTextureAttributes(e,n),await this.textureParamsController.update(e),navigator&&navigator.mediaDevices&&navigator.mediaDevices.getUserMedia){const t={video:{width:this.pv.res.x,height:this.pv.res.y,facingMode:\\\\\\\"user\\\\\\\"}};navigator.mediaDevices.getUserMedia(t).then((t=>{this._stream=t,this._video&&(this._video.srcObject=t,this._video.play(),this.setTexture(e))})).catch((t=>{this.states.error.set(\\\\\\\"Unable to access the camera/webcam\\\\\\\")}))}else this.states.error.set(\\\\\\\"MediaDevices interface not available.\\\\\\\")}}class Fv extends aa{static context(){return ts.COP}cook(){this.cookController.endCook()}}class Dv extends Fv{}class Bv extends Dv{constructor(){super(...arguments),this._children_controller_context=ts.ANIM}static type(){return es.ANIM}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}}class zv extends Dv{constructor(){super(...arguments),this._children_controller_context=ts.EVENT}static type(){return es.EVENT}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}}class kv extends Dv{constructor(){super(...arguments),this._children_controller_context=ts.COP}static type(){return es.COP}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}}class Uv extends Dv{constructor(){super(...arguments),this._children_controller_context=ts.MAT}static type(){return es.MAT}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}}class Gv extends Fv{constructor(){super(...arguments),this.paramsConfig=new ef,this.effectsComposerController=new nf(this),this.displayNodeController=new Fm(this,this.effectsComposerController.displayNodeControllerCallbacks()),this._children_controller_context=ts.POST}static type(){return es.POST}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}}class Vv extends Dv{constructor(){super(...arguments),this._children_controller_context=ts.ROP}static type(){return es.ROP}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}}var Hv,jv;!function(t){t.START=\\\\\\\"start\\\\\\\",t.STOP=\\\\\\\"stop\\\\\\\",t.UPDATE=\\\\\\\"update\\\\\\\"}(Hv||(Hv={})),function(t){t.START=\\\\\\\"start\\\\\\\",t.COMPLETE=\\\\\\\"completed\\\\\\\"}(jv||(jv={}));const Wv=new class extends ua{constructor(){super(...arguments),this.animation=ha.NODE_PATH(\\\\\\\"\\\\\\\",{nodeSelection:{context:ts.ANIM},dependentOnFoundNode:!1}),this.play=ha.BUTTON(null,{callback:t=>{qv.PARAM_CALLBACK_play(t)}}),this.pause=ha.BUTTON(null,{callback:t=>{qv.PARAM_CALLBACK_pause(t)}})}};class qv extends Va{constructor(){super(...arguments),this.paramsConfig=Wv}static type(){return\\\\\\\"animation\\\\\\\"}initializeNode(){this.io.inputs.setNamedInputConnectionPoints([new ta(Hv.START,Qo.BASE,this._play.bind(this)),new ta(Hv.STOP,Qo.BASE,this._pause.bind(this))]),this.io.outputs.setNamedOutputConnectionPoints([new ta(jv.START,Qo.BASE),new ta(jv.COMPLETE,Qo.BASE)]),this.scene().dispatchController.onAddListener((()=>{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{this.params.label.init([this.p.animation],(()=>this.pv.animation.path()))}))}))}processEvent(t){}static PARAM_CALLBACK_play(t){t._play({})}static PARAM_CALLBACK_pause(t){t._pause()}async _play(t){const e=this.p.animation;e.isDirty()&&await e.compute();const n=e.value.nodeWithContext(ts.ANIM);if(!n)return;const i=await n.compute();i&&(this._timelineBuilder=i.coreContent(),this._timelineBuilder&&(this._timeline&&this._timeline.kill(),this._timeline=F_.timeline(),this._timelineBuilder.populate(this._timeline),this._timeline.vars.onStart=()=>{this._triggerAnimationStarted(t)},this._timeline.vars.onComplete=()=>{this._timeline&&this._timeline.kill(),this._triggerAnimationCompleted(t)}))}_pause(){this._timeline&&this._timeline.pause()}_triggerAnimationStarted(t){this.dispatchEventToOutput(jv.START,t)}_triggerAnimationCompleted(t){this.dispatchEventToOutput(jv.COMPLETE,t)}}const Xv=\\\\\\\"event\\\\\\\";const Yv=new class extends ua{constructor(){super(...arguments),this.active=ha.BOOLEAN(1),this.inputsCount=ha.INTEGER(5,{range:[1,10],rangeLocked:[!0,!1]})}};class $v extends Va{constructor(){super(...arguments),this.paramsConfig=Yv}static type(){return\\\\\\\"any\\\\\\\"}initializeNode(){this.io.connection_points.set_expected_input_types_function(this._expected_input_types.bind(this)),this.io.connection_points.set_input_name_function(this._input_name.bind(this)),this.io.connection_points.set_output_name_function((()=>Xv)),this.io.connection_points.set_expected_output_types_function((()=>[Qo.BASE]))}_expected_input_types(){const t=new Array(this.pv.inputsCount);return t.fill(Qo.BASE),t}_input_name(t){return`trigger${t}`}async processEvent(t){this.p.active.isDirty()&&await this.p.active.compute(),this.pv.active&&this.dispatchEventToOutput(Xv,t)}}const Jv=new class extends ua{constructor(){super(...arguments),this.blocking=ha.BOOLEAN(1)}};class Zv extends Va{constructor(){super(...arguments),this.paramsConfig=Jv}static type(){return\\\\\\\"block\\\\\\\"}initializeNode(){this.io.inputs.setNamedInputConnectionPoints([new ta(\\\\\\\"in\\\\\\\",Qo.BASE,this._process_incoming_event.bind(this))]),this.io.outputs.setNamedOutputConnectionPoints([new ta(Zv.OUTPUT,Qo.BASE)]),this.scene().dispatchController.onAddListener((()=>{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{this.params.label.init([this.p.blocking],(()=>this.pv.blocking?\\\\\\\"blocking (X)\\\\\\\":\\\\\\\"pass-through (--\\\\x3e)\\\\\\\"))}))}))}trigger_output(t){this.dispatchEventToOutput(Zv.OUTPUT,t)}_process_incoming_event(t){this.pv.blocking||this.trigger_output(t)}}var Kv;Zv.OUTPUT=\\\\\\\"output\\\\\\\",function(t){t.OUT=\\\\\\\"out\\\\\\\"}(Kv||(Kv={}));const Qv=new class extends ua{constructor(){super(...arguments),this.dispatch=ha.BUTTON(null,{callback:t=>{ty.PARAM_CALLBACK_execute(t)}})}};class ty extends Va{constructor(){super(...arguments),this.paramsConfig=Qv}static type(){return\\\\\\\"button\\\\\\\"}initializeNode(){this.io.outputs.setNamedOutputConnectionPoints([new ta(Kv.OUT,Qo.BASE)])}processEvent(t){}process_event_execute(t){this.dispatchEventToOutput(Kv.OUT,t)}static PARAM_CALLBACK_execute(t){t.process_event_execute({})}}class ey extends Va{constructor(){super(...arguments),this._controls_by_viewer=new Map}async apply_controls(t,e){var n;null===(n=e.controlsController)||void 0===n||n.dispose_controls();const i=e.canvas();if(!i)return;const s=await this.createControlsInstance(t,i),r=this._controls_by_viewer.get(e);r&&r.dispose(),this._controls_by_viewer.set(e,s);const o=li.performance.performanceManager().now();return s.name=`${this.path()}:${t.name}:${o}:${this.controls_id()}`,await this.params.evalAll(),this.setupControls(s),s}controls_id(){return JSON.stringify(this.params.all.map((t=>t.valueSerialized())))}}var ny=n(27);const iy=new p.a(0,0,1),sy=new ny.a,ry=new hh.a,oy=new hh.a(-Math.sqrt(.5),0,0,Math.sqrt(.5)),ay={type:\\\\\\\"change\\\\\\\"};class ly extends J.a{constructor(t){super(),!1===window.isSecureContext&&console.error(\\\\\\\"THREE.DeviceOrientationControls: DeviceOrientationEvent is only available in secure contexts (https)\\\\\\\");const e=this,n=new hh.a;this.object=t,this.object.rotation.reorder(\\\\\\\"YXZ\\\\\\\"),this.enabled=!0,this.deviceOrientation={},this.screenOrientation=0,this.alphaOffset=0;const i=function(t){e.deviceOrientation=t},s=function(){e.screenOrientation=window.orientation||0};this.connect=function(){s(),void 0!==window.DeviceOrientationEvent&&\\\\\\\"function\\\\\\\"==typeof window.DeviceOrientationEvent.requestPermission?window.DeviceOrientationEvent.requestPermission().then((function(t){\\\\\\\"granted\\\\\\\"==t&&(window.addEventListener(\\\\\\\"orientationchange\\\\\\\",s),window.addEventListener(\\\\\\\"deviceorientation\\\\\\\",i))})).catch((function(t){console.error(\\\\\\\"THREE.DeviceOrientationControls: Unable to use DeviceOrientation API:\\\\\\\",t)})):(window.addEventListener(\\\\\\\"orientationchange\\\\\\\",s),window.addEventListener(\\\\\\\"deviceorientation\\\\\\\",i)),e.enabled=!0},this.disconnect=function(){window.removeEventListener(\\\\\\\"orientationchange\\\\\\\",s),window.removeEventListener(\\\\\\\"deviceorientation\\\\\\\",i),e.enabled=!1},this.update=function(){if(!1===e.enabled)return;const t=e.deviceOrientation;if(t){const i=t.alpha?On.e(t.alpha)+e.alphaOffset:0,s=t.beta?On.e(t.beta):0,r=t.gamma?On.e(t.gamma):0,o=e.screenOrientation?On.e(e.screenOrientation):0;!function(t,e,n,i,s){sy.set(n,e,-i,\\\\\\\"YXZ\\\\\\\"),t.setFromEuler(sy),t.multiply(oy),t.multiply(ry.setFromAxisAngle(iy,-s))}(e.object.quaternion,i,s,r,o),8*(1-n.dot(e.object.quaternion))>1e-6&&(n.copy(e.object.quaternion),e.dispatchEvent(ay))}},this.dispose=function(){e.disconnect()},this.connect()}}const cy=new class extends ua{constructor(){super(...arguments),this.enabled=ha.BOOLEAN(1)}};class hy extends ey{constructor(){super(...arguments),this.paramsConfig=cy,this._controls_by_element_id=new Map}static type(){return _s.DEVICE_ORIENTATION}endEventName(){return\\\\\\\"end\\\\\\\"}async createControlsInstance(t,e){const n=new ly(t);return this._controls_by_element_id.set(e.id,n),n}setupControls(t){t.enabled=this.pv.enabled}updateRequired(){return!0}disposeControlsForHtmlElementId(t){const e=this._controls_by_element_id.get(t);e&&(e.dispose(),this._controls_by_element_id.delete(t))}}class uy{constructor(t=1,e=0,n=0){return this.radius=t,this.phi=e,this.theta=n,this}set(t,e,n){return this.radius=t,this.phi=e,this.theta=n,this}copy(t){return this.radius=t.radius,this.phi=t.phi,this.theta=t.theta,this}makeSafe(){const t=1e-6;return this.phi=Math.max(t,Math.min(Math.PI-t,this.phi)),this}setFromVector3(t){return this.setFromCartesianCoords(t.x,t.y,t.z)}setFromCartesianCoords(t,e,n){return this.radius=Math.sqrt(t*t+e*e+n*n),0===this.radius?(this.theta=0,this.phi=0):(this.theta=Math.atan2(t,n),this.phi=Math.acos(On.d(e/this.radius,-1,1))),this}clone(){return(new this.constructor).copy(this)}}const dy={type:\\\\\\\"change\\\\\\\"},py={type:\\\\\\\"start\\\\\\\"},_y={type:\\\\\\\"end\\\\\\\"};class my extends J.a{constructor(t,e){super(),void 0===e&&console.warn('THREE.OrbitControls: The second parameter \\\\\\\"domElement\\\\\\\" is now mandatory.'),e===document&&console.error('THREE.OrbitControls: \\\\\\\"document\\\\\\\" should not be used as the target \\\\\\\"domElement\\\\\\\". Please use \\\\\\\"renderer.domElement\\\\\\\" instead.'),this.object=t,this.domElement=e,this.domElement.style.touchAction=\\\\\\\"none\\\\\\\",this.enabled=!0,this.target=new p.a,this.minDistance=0,this.maxDistance=1/0,this.minZoom=0,this.maxZoom=1/0,this.minPolarAngle=0,this.maxPolarAngle=Math.PI,this.minAzimuthAngle=-1/0,this.maxAzimuthAngle=1/0,this.enableDamping=!1,this.dampingFactor=.05,this.enableZoom=!0,this.zoomSpeed=1,this.enableRotate=!0,this.rotateSpeed=1,this.enablePan=!0,this.panSpeed=1,this.screenSpacePanning=!0,this.keyPanSpeed=7,this.autoRotate=!1,this.autoRotateSpeed=2,this.enableKeys=!0,this.keyMode=\\\\\\\"pan\\\\\\\",this.keyRotateSpeedVertical=1,this.keyRotateSpeedHorizontal=1,this.keys={LEFT:\\\\\\\"ArrowLeft\\\\\\\",UP:\\\\\\\"ArrowUp\\\\\\\",RIGHT:\\\\\\\"ArrowRight\\\\\\\",BOTTOM:\\\\\\\"ArrowDown\\\\\\\"},this.mouseButtons={LEFT:w.hb.ROTATE,MIDDLE:w.hb.DOLLY,RIGHT:w.hb.PAN},this.touches={ONE:w.Tc.ROTATE,TWO:w.Tc.DOLLY_PAN},this.target0=this.target.clone(),this.position0=this.object.position.clone(),this.zoom0=this.object.zoom,this._domElementKeyEvents=null,this.getPolarAngle=function(){return o.phi},this.getAzimuthalAngle=function(){return o.theta},this.getDistance=function(){return this.object.position.distanceTo(this.target)},this.listenToKeyEvents=function(t){t.addEventListener(\\\\\\\"keydown\\\\\\\",q),this._domElementKeyEvents=t},this.saveState=function(){n.target0.copy(n.target),n.position0.copy(n.object.position),n.zoom0=n.object.zoom},this.reset=function(){n.target.copy(n.target0),n.object.position.copy(n.position0),n.object.zoom=n.zoom0,n.object.updateProjectionMatrix(),n.dispatchEvent(dy),n.update(),s=i.NONE},this.update=function(){const e=new p.a,u=(new hh.a).setFromUnitVectors(t.up,new p.a(0,1,0)),d=u.clone().invert(),_=new p.a,m=new hh.a,f=2*Math.PI;let g=!1;return function(){const t=n.object.position;if(e.copy(t).sub(n.target),e.applyQuaternion(u),o.setFromVector3(e),n.autoRotate&&s===i.NONE&&E(2*Math.PI/60/60*n.autoRotateSpeed),n.enableDamping){const t=a.theta*n.dampingFactor,e=a.phi*n.dampingFactor;tMath.PI&&(p-=f),v<-Math.PI?v+=f:v>Math.PI&&(v-=f),o.theta=p(p+v)/2?Math.max(p,o.theta):Math.min(v,o.theta)),o.phi=Math.max(n.minPolarAngle,Math.min(n.maxPolarAngle,o.phi)),o.makeSafe(),o.radius*=l,o.radius=Math.max(n.minDistance,Math.min(n.maxDistance,o.radius)),!0===n.enableDamping?n.target.addScaledVector(c,n.dampingFactor):n.target.add(c),e.setFromSpherical(o),e.applyQuaternion(d),t.copy(n.target).add(e),n.object.lookAt(n.target),!0===n.enableDamping?(a.theta*=1-n.dampingFactor,a.phi*=1-n.dampingFactor,c.multiplyScalar(1-n.dampingFactor)):(a.set(0,0,0),c.set(0,0,0)),l=1,!!(h||_.distanceToSquared(n.object.position)>r||8*(1-m.dot(n.object.quaternion))>r)&&(n.dispatchEvent(dy),_.copy(n.object.position),m.copy(n.object.quaternion),h=!1,!0)}}(),this.dispose=function(){n.domElement.removeEventListener(\\\\\\\"contextmenu\\\\\\\",X,!1),n.domElement.removeEventListener(\\\\\\\"pointerdown\\\\\\\",G,!1),n.domElement.removeEventListener(\\\\\\\"pointercancel\\\\\\\",j),n.domElement.removeEventListener(\\\\\\\"wheel\\\\\\\",W,!1),n.domElement.ownerDocument.removeEventListener(\\\\\\\"pointermove\\\\\\\",V,!1),n.domElement.ownerDocument.removeEventListener(\\\\\\\"pointerup\\\\\\\",H,!1),null!==n._domElementKeyEvents&&n._domElementKeyEvents.removeEventListener(\\\\\\\"keydown\\\\\\\",q)};const n=this,i={NONE:-1,ROTATE:0,DOLLY:1,PAN:2,TOUCH_ROTATE:3,TOUCH_PAN:4,TOUCH_DOLLY_PAN:5,TOUCH_DOLLY_ROTATE:6};let s=i.NONE;const r=1e-6,o=new uy,a=new uy;let l=1;const c=new p.a;let h=!1;const u=new d.a,_=new d.a,m=new d.a,f=new d.a,g=new d.a,v=new d.a,y=new d.a,x=new d.a,b=new d.a,T=[],A={};function M(){return Math.pow(.95,n.zoomSpeed)}function E(t){a.theta-=t}function S(t){a.phi-=t}const C=function(){const t=new p.a;return function(e,n){t.setFromMatrixColumn(n,0),t.multiplyScalar(-e),c.add(t)}}(),N=function(){const t=new p.a;return function(e,i){!0===n.screenSpacePanning?t.setFromMatrixColumn(i,1):(t.setFromMatrixColumn(i,0),t.crossVectors(n.object.up,t)),t.multiplyScalar(e),c.add(t)}}(),L=function(){const t=new p.a;return function(e,i){const s=n.domElement;if(n.object.isPerspectiveCamera){const r=n.object.position;t.copy(r).sub(n.target);let o=t.length();o*=Math.tan(n.object.fov/2*Math.PI/180),C(2*e*o/s.clientHeight,n.object.matrix),N(2*i*o/s.clientHeight,n.object.matrix)}else n.object.isOrthographicCamera?(C(e*(n.object.right-n.object.left)/n.object.zoom/s.clientWidth,n.object.matrix),N(i*(n.object.top-n.object.bottom)/n.object.zoom/s.clientHeight,n.object.matrix)):(console.warn(\\\\\\\"WARNING: OrbitControls.js encountered an unknown camera type - pan disabled.\\\\\\\"),n.enablePan=!1)}}();function O(t){n.object.isPerspectiveCamera?l/=t:n.object.isOrthographicCamera?(n.object.zoom=Math.max(n.minZoom,Math.min(n.maxZoom,n.object.zoom*t)),n.object.updateProjectionMatrix(),h=!0):(console.warn(\\\\\\\"WARNING: OrbitControls.js encountered an unknown camera type - dolly/zoom disabled.\\\\\\\"),n.enableZoom=!1)}function P(t){n.object.isPerspectiveCamera?l*=t:n.object.isOrthographicCamera?(n.object.zoom=Math.max(n.minZoom,Math.min(n.maxZoom,n.object.zoom/t)),n.object.updateProjectionMatrix(),h=!0):(console.warn(\\\\\\\"WARNING: OrbitControls.js encountered an unknown camera type - dolly/zoom disabled.\\\\\\\"),n.enableZoom=!1)}function R(t){u.set(t.clientX,t.clientY)}function I(t){f.set(t.clientX,t.clientY)}function F(){if(1===T.length)u.set(T[0].pageX,T[0].pageY);else{const t=.5*(T[0].pageX+T[1].pageX),e=.5*(T[0].pageY+T[1].pageY);u.set(t,e)}}function D(){if(1===T.length)f.set(T[0].pageX,T[0].pageY);else{const t=.5*(T[0].pageX+T[1].pageX),e=.5*(T[0].pageY+T[1].pageY);f.set(t,e)}}function B(){const t=T[0].pageX-T[1].pageX,e=T[0].pageY-T[1].pageY,n=Math.sqrt(t*t+e*e);y.set(0,n)}function z(t){if(1==T.length)_.set(t.pageX,t.pageY);else{const e=J(t),n=.5*(t.pageX+e.x),i=.5*(t.pageY+e.y);_.set(n,i)}m.subVectors(_,u).multiplyScalar(n.rotateSpeed);const e=n.domElement;E(2*Math.PI*m.x/e.clientHeight),S(2*Math.PI*m.y/e.clientHeight),u.copy(_)}function k(t){if(1===T.length)g.set(t.pageX,t.pageY);else{const e=J(t),n=.5*(t.pageX+e.x),i=.5*(t.pageY+e.y);g.set(n,i)}v.subVectors(g,f).multiplyScalar(n.panSpeed),L(v.x,v.y),f.copy(g)}function U(t){const e=J(t),i=t.pageX-e.x,s=t.pageY-e.y,r=Math.sqrt(i*i+s*s);x.set(0,r),b.set(0,Math.pow(x.y/y.y,n.zoomSpeed)),O(b.y),y.copy(x)}function G(t){!1!==n.enabled&&(0===T.length&&(n.domElement.setPointerCapture(t.pointerId),n.domElement.ownerDocument.addEventListener(\\\\\\\"pointermove\\\\\\\",V),n.domElement.ownerDocument.addEventListener(\\\\\\\"pointerup\\\\\\\",H)),function(t){T.push(t)}(t),\\\\\\\"touch\\\\\\\"===t.pointerType?function(t){switch($(t),T.length){case 1:switch(n.touches.ONE){case w.Tc.ROTATE:if(!1===n.enableRotate)return;F(),s=i.TOUCH_ROTATE;break;case w.Tc.PAN:if(!1===n.enablePan)return;D(),s=i.TOUCH_PAN;break;default:s=i.NONE}break;case 2:switch(n.touches.TWO){case w.Tc.DOLLY_PAN:if(!1===n.enableZoom&&!1===n.enablePan)return;n.enableZoom&&B(),n.enablePan&&D(),s=i.TOUCH_DOLLY_PAN;break;case w.Tc.DOLLY_ROTATE:if(!1===n.enableZoom&&!1===n.enableRotate)return;n.enableZoom&&B(),n.enableRotate&&F(),s=i.TOUCH_DOLLY_ROTATE;break;default:s=i.NONE}break;default:s=i.NONE}s!==i.NONE&&n.dispatchEvent(py)}(t):function(t){let e;switch(t.button){case 0:e=n.mouseButtons.LEFT;break;case 1:e=n.mouseButtons.MIDDLE;break;case 2:e=n.mouseButtons.RIGHT;break;default:e=-1}switch(e){case w.hb.DOLLY:if(!1===n.enableZoom)return;!function(t){y.set(t.clientX,t.clientY)}(t),s=i.DOLLY;break;case w.hb.ROTATE:if(t.ctrlKey||t.metaKey||t.shiftKey){if(!1===n.enablePan)return;I(t),s=i.PAN}else{if(!1===n.enableRotate)return;R(t),s=i.ROTATE}break;case w.hb.PAN:if(t.ctrlKey||t.metaKey||t.shiftKey){if(!1===n.enableRotate)return;R(t),s=i.ROTATE}else{if(!1===n.enablePan)return;I(t),s=i.PAN}break;default:s=i.NONE}s!==i.NONE&&n.dispatchEvent(py)}(t))}function V(t){!1!==n.enabled&&(\\\\\\\"touch\\\\\\\"===t.pointerType?function(t){switch($(t),s){case i.TOUCH_ROTATE:if(!1===n.enableRotate)return;z(t),n.update();break;case i.TOUCH_PAN:if(!1===n.enablePan)return;k(t),n.update();break;case i.TOUCH_DOLLY_PAN:if(!1===n.enableZoom&&!1===n.enablePan)return;!function(t){n.enableZoom&&U(t),n.enablePan&&k(t)}(t),n.update();break;case i.TOUCH_DOLLY_ROTATE:if(!1===n.enableZoom&&!1===n.enableRotate)return;!function(t){n.enableZoom&&U(t),n.enableRotate&&z(t)}(t),n.update();break;default:s=i.NONE}}(t):function(t){if(!1===n.enabled)return;switch(s){case i.ROTATE:if(!1===n.enableRotate)return;!function(t){_.set(t.clientX,t.clientY),m.subVectors(_,u).multiplyScalar(n.rotateSpeed);var e=n.domElement;E(2*Math.PI*m.x/e.clientHeight),S(2*Math.PI*m.y/e.clientHeight),u.copy(_),n.update()}(t);break;case i.DOLLY:if(!1===n.enableZoom)return;!function(t){x.set(t.clientX,t.clientY),b.subVectors(x,y),b.y>0?O(M()):b.y<0&&P(M()),y.copy(x),n.update()}(t);break;case i.PAN:if(!1===n.enablePan)return;!function(t){g.set(t.clientX,t.clientY),v.subVectors(g,f).multiplyScalar(n.panSpeed),L(v.x,v.y),f.copy(g),n.update()}(t)}}(t))}function H(t){!1!==n.enabled&&(t.pointerType,n.dispatchEvent(_y),s=i.NONE,Y(t),0===T.length&&(n.domElement.releasePointerCapture(t.pointerId),n.domElement.ownerDocument.removeEventListener(\\\\\\\"pointermove\\\\\\\",V),n.domElement.ownerDocument.removeEventListener(\\\\\\\"pointerup\\\\\\\",H)))}function j(t){Y(t)}function W(t){!1===n.enabled||!1===n.enableZoom||s!==i.NONE&&s!==i.ROTATE||(t.preventDefault(),n.dispatchEvent(py),function(t){t.deltaY<0?P(M()):t.deltaY>0&&O(M()),n.update()}(t),n.dispatchEvent(_y))}function q(t){!1!==n.enabled&&!1!==n.enablePan&&function(t){let e=!1;if(\\\\\\\"pan\\\\\\\"==n.keyMode)switch(t.code){case n.keys.UP:L(0,n.keyPanSpeed),e=!0;break;case n.keys.BOTTOM:L(0,-n.keyPanSpeed),e=!0;break;case n.keys.LEFT:L(n.keyPanSpeed,0),e=!0;break;case n.keys.RIGHT:L(-n.keyPanSpeed,0),e=!0}else switch(t.code){case n.keys.UP:S(n.keyRotateSpeedVertical),e=!0;break;case n.keys.BOTTOM:S(-n.keyRotateSpeedVertical),e=!0;break;case n.keys.LEFT:E(n.keyRotateSpeedHorizontal),e=!0;break;case n.keys.RIGHT:E(-n.keyRotateSpeedHorizontal),e=!0}e&&(t.preventDefault(),n.update())}(t)}function X(t){!1!==n.enabled&&t.preventDefault()}function Y(t){delete A[t.pointerId];for(let e=0;e{wy.PARAM_CALLBACK_update_target(t)}}),this.enableKeys=ha.BOOLEAN(0),this.keysMode=ha.INTEGER(xy.indexOf(yy.PAN),{visibleIf:{enableKeys:1},menu:{entries:xy.map(((t,e)=>({name:t,value:e})))}}),this.keysPanSpeed=ha.FLOAT(7,{range:[0,10],rangeLocked:[!1,!1],visibleIf:{enableKeys:1,keysMode:xy.indexOf(yy.PAN)}}),this.keysRotateSpeedVertical=ha.FLOAT(1,{range:[0,1],rangeLocked:[!1,!1],visibleIf:{enableKeys:1,keysMode:xy.indexOf(yy.ROTATE)}}),this.keysRotateSpeedHorizontal=ha.FLOAT(1,{range:[0,1],rangeLocked:[!1,!1],visibleIf:{enableKeys:1,keysMode:xy.indexOf(yy.ROTATE)}})}};class wy extends ey{constructor(){super(...arguments),this.paramsConfig=by,this._controls_by_element_id=new Map,this._target_array=[0,0,0]}static type(){return _s.ORBIT}endEventName(){return\\\\\\\"end\\\\\\\"}initializeNode(){this.io.outputs.setNamedOutputConnectionPoints([new ta(gy,Qo.BASE),new ta(vy,Qo.BASE),new ta(\\\\\\\"end\\\\\\\",Qo.BASE)])}async createControlsInstance(t,e){const n=new my(t,e);return n.addEventListener(\\\\\\\"end\\\\\\\",(()=>{this._on_controls_end(n)})),this._controls_by_element_id.set(e.id,n),this._bind_listeners_to_controls_instance(n),n}_bind_listeners_to_controls_instance(t){t.addEventListener(\\\\\\\"start\\\\\\\",(()=>{this.dispatchEventToOutput(gy,{})})),t.addEventListener(\\\\\\\"change\\\\\\\",(()=>{this.dispatchEventToOutput(vy,{})})),t.addEventListener(\\\\\\\"end\\\\\\\",(()=>{this.dispatchEventToOutput(\\\\\\\"end\\\\\\\",{})}))}setupControls(t){t.enabled=this.pv.enabled,t.enablePan=this.pv.allowPan,t.enableRotate=this.pv.allowRotate,t.enableZoom=this.pv.allowZoom,t.enableDamping=this.pv.tdamping,t.dampingFactor=this.pv.damping,t.rotateSpeed=this.pv.rotateSpeed,t.screenSpacePanning=this.pv.screenSpacePanning,t.minDistance=this.pv.minDistance,t.maxDistance=this.pv.maxDistance,this._set_azimuth_angle(t),t.minPolarAngle=this.pv.polarAngleRange.x,t.maxPolarAngle=this.pv.polarAngleRange.y,t.target.copy(this.pv.target),t.enabled&&t.update(),t.enableKeys=this.pv.enableKeys,t.enableKeys&&(t.keyMode=xy[this.pv.keysMode],t.keyRotateSpeedVertical=this.pv.keysRotateSpeedVertical,t.keyRotateSpeedHorizontal=this.pv.keysRotateSpeedHorizontal,t.keyPanSpeed=this.pv.keysPanSpeed)}_set_azimuth_angle(t){this.pv.limitAzimuthAngle?(t.minAzimuthAngle=this.pv.azimuthAngleRange.x,t.maxAzimuthAngle=this.pv.azimuthAngleRange.y):(t.minAzimuthAngle=1/0,t.maxAzimuthAngle=1/0)}updateRequired(){return this.pv.tdamping}_on_controls_end(t){this.pv.allowPan&&(t.target.toArray(this._target_array),this.p.target.set(this._target_array))}static PARAM_CALLBACK_update_target(t){t._update_target()}_update_target(){const t=this.pv.target;this._controls_by_element_id.forEach(((e,n)=>{const i=e.target;i.equals(t)||(i.copy(t),e.update())}))}disposeControlsForHtmlElementId(t){this._controls_by_element_id.get(t)&&this._controls_by_element_id.delete(t)}}class Ty extends wy{static type(){return _s.MAP}async create_controls_instance(t,e){const n=new fy(t,e);return this._bind_listeners_to_controls_instance(n),n}}const Ay=new class extends ua{constructor(){super(...arguments),this.delay=ha.INTEGER(1e3,{range:[0,1e3],rangeLocked:[!0,!1]})}};class My extends Va{constructor(){super(...arguments),this.paramsConfig=Ay}static type(){return\\\\\\\"delay\\\\\\\"}initializeNode(){this.io.inputs.setNamedInputConnectionPoints([new ta(\\\\\\\"in\\\\\\\",Qo.BASE,this._process_input.bind(this))]),this.io.outputs.setNamedOutputConnectionPoints([new ta(\\\\\\\"out\\\\\\\",Qo.BASE)])}_process_input(t){setTimeout((()=>{this.dispatchEventToOutput(\\\\\\\"out\\\\\\\",t)}),this.pv.delay)}}const Ey={type:\\\\\\\"change\\\\\\\"},Sy={type:\\\\\\\"lock\\\\\\\"},Cy={type:\\\\\\\"unlock\\\\\\\"},Ny=Math.PI/2,Ly=new p.a,Oy=new uy;class Py extends J.a{constructor(t,e,n){super(),this.camera=t,this.domElement=e,this.player=n,this.isLocked=!1,this.minPolarAngle=0,this.maxPolarAngle=Math.PI,this.rotateSpeed=1,this.euler=new ny.a(0,0,0,\\\\\\\"YXZ\\\\\\\"),this.boundMethods={onMouseMove:this.onMouseMove.bind(this),onPointerlockChange:this.onPointerlockChange.bind(this),onPointerlockError:this.onPointerlockError.bind(this)},this._azimuthalAngle=0,this.connect()}onMouseMove(t){if(!1!==this.isLocked){var e=t.movementX||t.mozMovementX||t.webkitMovementX||0,n=t.movementY||t.mozMovementY||t.webkitMovementY||0;this.euler.setFromQuaternion(this.camera.quaternion),this.euler.y-=.002*e*this.rotateSpeed,this.euler.x-=.002*n*this.rotateSpeed,this.euler.x=Math.max(Ny-this.maxPolarAngle,Math.min(Ny-this.minPolarAngle,this.euler.x)),this.camera.quaternion.setFromEuler(this.euler),this._computeAzimuthalAngle(),this.dispatchEvent(Ey)}}_computeAzimuthalAngle(){this.camera.updateMatrixWorld(),Ly.set(0,0,1),this.camera.localToWorld(Ly),Ly.sub(this.camera.position),Oy.setFromVector3(Ly),this._azimuthalAngle=Oy.theta}onPointerlockChange(){this.domElement.ownerDocument.pointerLockElement===this.domElement?(this.dispatchEvent(Sy),this.isLocked=!0):(this.dispatchEvent(Cy),this.isLocked=!1)}onPointerlockError(){console.error(\\\\\\\"THREE.PointerLockControls: Unable to use Pointer Lock API (Note that you need to wait for 2 seconds to lock the pointer after having just unlocked it)\\\\\\\")}connect(){this.domElement.ownerDocument.addEventListener(\\\\\\\"mousemove\\\\\\\",this.boundMethods.onMouseMove),this.domElement.ownerDocument.addEventListener(\\\\\\\"pointerlockchange\\\\\\\",this.boundMethods.onPointerlockChange),this.domElement.ownerDocument.addEventListener(\\\\\\\"pointerlockerror\\\\\\\",this.boundMethods.onPointerlockError)}disconnect(){this.domElement.ownerDocument.removeEventListener(\\\\\\\"mousemove\\\\\\\",this.boundMethods.onMouseMove),this.domElement.ownerDocument.removeEventListener(\\\\\\\"pointerlockchange\\\\\\\",this.boundMethods.onPointerlockChange),this.domElement.ownerDocument.removeEventListener(\\\\\\\"pointerlockerror\\\\\\\",this.boundMethods.onPointerlockError)}dispose(){this.disconnect()}getObject(){return this.camera}lock(){this.domElement.requestPointerLock()}unlock(){this.domElement.ownerDocument.exitPointerLock()}update(t){this.player&&(this.player.setAzimuthalAngle(this._azimuthalAngle),this.player.update(t))}}var Ry=n(16);const Iy=new p.a,Fy=new p.a;class Dy{constructor(t=new p.a,e=new p.a){this.start=t,this.end=e}set(t,e){return this.start.copy(t),this.end.copy(e),this}copy(t){return this.start.copy(t.start),this.end.copy(t.end),this}getCenter(t){return t.addVectors(this.start,this.end).multiplyScalar(.5)}delta(t){return t.subVectors(this.end,this.start)}distanceSq(){return this.start.distanceToSquared(this.end)}distance(){return this.start.distanceTo(this.end)}at(t,e){return this.delta(e).multiplyScalar(t).add(this.start)}closestPointToPointParameter(t,e){Iy.subVectors(t,this.start),Fy.subVectors(this.end,this.start);const n=Fy.dot(Fy);let i=Fy.dot(Iy)/n;return e&&(i=On.d(i,0,1)),i}closestPointToPoint(t,e,n){const i=this.closestPointToPointParameter(t,e);return this.delta(n).multiplyScalar(i).add(this.start)}applyMatrix4(t){return this.start.applyMatrix4(t),this.end.applyMatrix4(t),this}equals(t){return t.start.equals(this.start)&&t.end.equals(this.end)}clone(){return(new this.constructor).copy(this)}}const By=new p.a;function zy(t,e,n,i,s,r){const o=2*Math.PI*s/4,a=Math.max(r-2*s,0),l=Math.PI/4;By.copy(e),By[i]=0,By.normalize();const c=.5*o/(o+a),h=1-By.angleTo(t)/l;if(1===Math.sign(By[n]))return h*c;return a/(o+a)+c+c*(1-h)}class ky extends N{constructor(t=1,e=1,n=1,i=2,s=.1){if(i=2*i+1,s=Math.min(t/2,e/2,n/2,s),super(1,1,1,i,i,i),1===i)return;const r=this.toNonIndexed();this.index=null,this.attributes.position=r.attributes.position,this.attributes.normal=r.attributes.normal,this.attributes.uv=r.attributes.uv;const o=new p.a,a=new p.a,l=new p.a(t,e,n).divideScalar(2).subScalar(s),c=this.attributes.position.array,h=this.attributes.normal.array,u=this.attributes.uv.array,d=c.length/6,_=new p.a,m=.5/i;for(let i=0,r=0;ithis.object.position.y<-25,this.object=t.object,this.object.matrixAutoUpdate=!0,this.collider=t.collider,t.meshName&&(this._mesh=new B.a,this._mesh.geometry=Uy({radius:this.capsuleInfo.radius,height:1}),this._mesh.name=t.meshName,this._mesh.receiveShadow=!0,this._mesh.castShadow=!0)}setCollider(t){this.collider=t}setCapsule(t){this.capsuleInfo.radius=t.radius,this.capsuleInfo.segment.end.y=-t.height,this._mesh&&(this._mesh.geometry=Uy(t))}setUsePlayerMesh(t){t?(this._mesh=this._mesh||this._createMesh(),this.object.add(this._mesh)):this._mesh&&this.object.remove(this._mesh)}_createMesh(){const t=new B.a;return t.geometry=Uy({radius:this.capsuleInfo.radius,height:1}),t.name=this._meshName||\\\\\\\"defaultPlayerMeshName\\\\\\\",t.receiveShadow=!0,t.castShadow=!0,t}setMaterial(t){this._mesh&&(this._mesh.material=t)}reset(){this.stop(),this.object.position.copy(this.startPosition),Yy.copy(this.startRotation).multiplyScalar(On.a),this.object.rotation.setFromVector3(Yy)}stop(){this._pressed.forward=!1,this._pressed.backward=!1,this._pressed.left=!1,this._pressed.right=!1,this._running=!1}setResetRequiredCallback(t){this._resetRequiredCallback=t}setAzimuthalAngle(t){this._azimuthalAngle=t}update(t){const e=Math.min(t,.1);for(let t=0;tt.intersectsBox(Wy),intersectsTriangle:t=>{const e=Hy,n=jy,s=t.closestPointToSegment(Xy,e,n);if(sMath.abs(t*this._velocity.y*.25);const o=Math.max(0,r.length()-1e-5);r.normalize().multiplyScalar(o),this.object.position.add(r),this._onGround?this._velocity.set(0,0,0):(r.normalize(),this._velocity.addScaledVector(r,-r.dot(this._velocity))),this._resetRequiredCallback()&&this.reset()}setForward(t){this._pressed.forward=t}setBackward(t){this._pressed.backward=t}setLeft(t){this._pressed.left=t}setRight(t){this._pressed.right=t}jump(){this._onGround&&this.jumpAllowed&&(this._velocity.y=this.jumpStrength)}setRun(t){t?this._onGround&&this.runAllowed&&(this._running=!0):this._running=!1}running(){return this._running}}function Jy(t){t.preventDefault()}class Zy{constructor(t){this.player=t,this._bounds={keydown:this._onKeyDown.bind(this),keyup:this._onKeyUp.bind(this)}}_onKeyDown(t){if(!t.ctrlKey)switch(t.code){case\\\\\\\"ArrowUp\\\\\\\":case\\\\\\\"KeyW\\\\\\\":this.player.setForward(!0),Jy(t);break;case\\\\\\\"ArrowDown\\\\\\\":case\\\\\\\"KeyS\\\\\\\":this.player.setBackward(!0),Jy(t);break;case\\\\\\\"ArrowRight\\\\\\\":case\\\\\\\"KeyD\\\\\\\":this.player.setRight(!0),Jy(t);break;case\\\\\\\"ArrowLeft\\\\\\\":case\\\\\\\"KeyA\\\\\\\":this.player.setLeft(!0),Jy(t);break;case\\\\\\\"Space\\\\\\\":this.player.jump(),Jy(t);break;case\\\\\\\"ShiftLeft\\\\\\\":case\\\\\\\"ShiftRight\\\\\\\":this.player.setRun(!0),Jy(t)}}_onKeyUp(t){switch(t.code){case\\\\\\\"ArrowUp\\\\\\\":case\\\\\\\"KeyW\\\\\\\":this.player.setForward(!1);break;case\\\\\\\"ArrowDown\\\\\\\":case\\\\\\\"KeyS\\\\\\\":this.player.setBackward(!1);break;case\\\\\\\"ArrowRight\\\\\\\":case\\\\\\\"KeyD\\\\\\\":this.player.setRight(!1);break;case\\\\\\\"ArrowLeft\\\\\\\":case\\\\\\\"KeyA\\\\\\\":this.player.setLeft(!1);break;case\\\\\\\"ShiftLeft\\\\\\\":case\\\\\\\"ShiftRight\\\\\\\":this.player.setRun(!1),Jy(t)}}addEvents(){document.addEventListener(\\\\\\\"keydown\\\\\\\",this._bounds.keydown),document.addEventListener(\\\\\\\"keyup\\\\\\\",this._bounds.keyup)}removeEvents(){document.removeEventListener(\\\\\\\"keydown\\\\\\\",this._bounds.keydown),document.removeEventListener(\\\\\\\"keyup\\\\\\\",this._bounds.keyup)}}Ky=ua;var Ky;class Qy extends Va{static PARAM_CALLBACK_updateCollider(t){}}class tx{constructor(t){this.node=t}_colliderNodeGraphNode(){return this.__colliderNodeGraphNode=this.__colliderNodeGraphNode||new Mi(this.node.scene(),\\\\\\\"colliderGraphNode\\\\\\\")}async getCollider(){var t;const e=this.node.pv.colliderObject.nodeWithContext(ts.SOP);if(!e)return void this.node.states.error.set(\\\\\\\"collider node not found\\\\\\\");(null===(t=this._colliderNode)||void 0===t?void 0:t.graphNodeId())!=e.graphNodeId()&&(this._colliderNode&&this._colliderNodeGraphNode().removeGraphInput(this._colliderNode),this._colliderNodeGraphNode().addGraphInput(e),this._colliderNodeGraphNode().addPostDirtyHook(\\\\\\\"onColliderDirty\\\\\\\",(()=>{this.updateCollider()})),this._colliderNode=e);const n=(await e.compute()).coreContent();if(!n)return void this.node.states.error.set(\\\\\\\"invalid collider node\\\\\\\");return n.objects()[0]}async updateCollider(){var t;const e=await this.getCollider();e?null===(t=this.node.player())||void 0===t||t.setCollider(e):this.node.states.error.set(\\\\\\\"invalid collider\\\\\\\")}}const ex=\\\\\\\"lock\\\\\\\",nx=\\\\\\\"change\\\\\\\",ix=\\\\\\\"unlock\\\\\\\";function sx(){return{cook:!1,callback:t=>{ox.PARAM_CALLBACK_updatePlayerParams(t)}}}const rx=new class extends ua{constructor(){super(...arguments),this.main=ha.FOLDER(),this.colliderObject=ha.NODE_PATH(\\\\\\\"\\\\\\\",{nodeSelection:{context:ts.SOP},dependentOnFoundNode:!1,callback:t=>{ox.PARAM_CALLBACK_updateCollider(t)}}),this.lock=ha.BUTTON(null,{callback:t=>{ox.PARAM_CALLBACK_lockControls(t)}}),this.unlock=ha.BUTTON(null,{callback:t=>{ox.PARAM_CALLBACK_unlockControls(t)}}),this.capsuleRadius=ha.FLOAT(.5,{range:[0,1],rangeLocked:[!0,!1],...sx()}),this.capsuleHeight=ha.FLOAT(1,{range:[0,2],rangeLocked:[!0,!1],...sx()}),this.physics=ha.FOLDER(),this.physicsSteps=ha.INTEGER(5,{range:[1,10],rangeLocked:[!0,!1],...sx()}),this.gravity=ha.VECTOR3([0,-30,0],{...sx()}),this.translateSpeed=ha.FLOAT(1,{range:[0,10],rangeLocked:[!0,!1],...sx()}),this.rotateSpeed=ha.FLOAT(1,{range:[0,10],rangeLocked:[!0,!1]}),this.jumpAllowed=ha.BOOLEAN(!0,{...sx()}),this.jumpStrength=ha.FLOAT(10,{range:[0,100],rangeLocked:[!0,!1],...sx()}),this.runAllowed=ha.BOOLEAN(!0,{...sx()}),this.runSpeedMult=ha.FLOAT(2,{range:[0,10],rangeLocked:[!0,!1],...sx()}),this.updateCollider=ha.BUTTON(null,{callback:t=>{ox.PARAM_CALLBACK_updateCollider(t)}}),this.init=ha.FOLDER(),this.startPosition=ha.VECTOR3([0,2,0],{...sx()}),this.startRotation=ha.VECTOR3([0,0,0],{...sx()}),this.reset=ha.BUTTON(null,{callback:t=>{ox.PARAM_CALLBACK_resetPlayer(t)}}),this.minPolarAngle=ha.FLOAT(0,{range:[0,Math.PI],rangeLocked:[!0,!0]}),this.maxPolarAngle=ha.FLOAT(\\\\\\\"$PI\\\\\\\",{range:[0,Math.PI],rangeLocked:[!0,!0]})}};class ox extends ey{constructor(){super(...arguments),this.paramsConfig=rx,this._controls_by_element_id=new Map}static type(){return _s.FIRST_PERSON}endEventName(){return\\\\\\\"unlock\\\\\\\"}collisionController(){return this._collisionController=this._collisionController||new tx(this)}initializeNode(){this.io.inputs.setNamedInputConnectionPoints([new ta(ex,Qo.BASE,this.lockControls.bind(this)),new ta(ox.INPUT_UPDATE_COLLIDER,Qo.BASE,this._updateCollider.bind(this))]),this.io.outputs.setNamedOutputConnectionPoints([new ta(ex,Qo.BASE),new ta(nx,Qo.BASE),new ta(ix,Qo.BASE)])}async createControlsInstance(t,e){await this._initPlayer(t);const n=new Py(t,e,this._player);return this._controls_by_element_id.set(e.id,n),this._bind_listeners_to_controls_instance(n),n}async _initPlayer(t){this._player=this._player||await this._createPlayer(t),this._player&&(this._updatePlayerParams(),this._player.reset())}player(){return this._player}async _updatePlayerParams(){this._player&&(this._player.startPosition.copy(this.pv.startPosition),this._player.startRotation.copy(this.pv.startRotation),this._player.physicsSteps=this.pv.physicsSteps,this._player.jumpAllowed=this.pv.jumpAllowed,this._player.jumpStrength=this.pv.jumpStrength,this._player.runAllowed=this.pv.runAllowed,this._player.runSpeedMult=this.pv.runSpeedMult,this._player.gravity.copy(this.pv.gravity),this._player.speed=this.pv.translateSpeed,this._player.setCapsule({radius:this.pv.capsuleRadius,height:this.pv.capsuleHeight}))}async _createPlayer(t){const e=t,n=await this.collisionController().getCollider();if(!n)return void this.states.error.set(\\\\\\\"invalid collider\\\\\\\");return new $y({object:e,collider:n})}_resetPlayer(){var t;null===(t=this._player)||void 0===t||t.reset()}async _updateCollider(){await this.collisionController().updateCollider()}_bind_listeners_to_controls_instance(t){t.addEventListener(ex,(()=>{this.dispatchEventToOutput(ex,{})})),t.addEventListener(nx,(()=>{this.dispatchEventToOutput(nx,{})})),t.addEventListener(ix,(()=>{this.dispatchEventToOutput(ix,{})}))}updateRequired(){return!0}setupControls(t){t.minPolarAngle=this.pv.minPolarAngle,t.maxPolarAngle=this.pv.maxPolarAngle,t.rotateSpeed=this.pv.rotateSpeed}disposeControlsForHtmlElementId(t){const e=this._controls_by_element_id.get(t);e&&(e.dispose(),this._controls_by_element_id.delete(t))}unlockControls(){const t=this._firstControls();t&&t.unlock()}lockControls(){const t=this._firstControls();if(t){if(this._player){this._corePlayerKeyEvents=this._corePlayerKeyEvents||new Zy(this._player),this._corePlayerKeyEvents.addEvents();const e=()=>{var n,i;t&&t.domElement.ownerDocument.pointerLockElement!=t.domElement&&(t.domElement.ownerDocument.removeEventListener(\\\\\\\"pointerlockchange\\\\\\\",e),null===(n=this._corePlayerKeyEvents)||void 0===n||n.removeEvents(),null===(i=this._player)||void 0===i||i.stop())};t.domElement.ownerDocument.addEventListener(\\\\\\\"pointerlockchange\\\\\\\",e)}t.lock()}}_firstControls(){let t;return this._controls_by_element_id.forEach(((e,n)=>{t=t||e})),t}static PARAM_CALLBACK_lockControls(t){t.lockControls()}static PARAM_CALLBACK_unlockControls(t){t.unlockControls()}static PARAM_CALLBACK_updateCollider(t){t._updateCollider()}static PARAM_CALLBACK_updatePlayerParams(t){t._updatePlayerParams()}static PARAM_CALLBACK_resetPlayer(t){t._resetPlayer()}}var ax,lx;ox.INPUT_UPDATE_COLLIDER=\\\\\\\"updateCollider\\\\\\\",function(t){t.TRIGGER=\\\\\\\"trigger\\\\\\\",t.RESET=\\\\\\\"reset\\\\\\\"}(ax||(ax={})),function(t){t.OUT=\\\\\\\"out\\\\\\\",t.LAST=\\\\\\\"last\\\\\\\"}(lx||(lx={}));const cx=new class extends ua{constructor(){super(...arguments),this.maxCount=ha.INTEGER(5,{range:[0,10],rangeLocked:[!0,!1]}),this.reset=ha.BUTTON(null,{callback:t=>{hx.PARAM_CALLBACK_reset(t)}})}};class hx extends Va{constructor(){super(...arguments),this.paramsConfig=cx,this._process_count=0,this._last_dispatched=!1}static type(){return\\\\\\\"limit\\\\\\\"}initializeNode(){this.io.inputs.setNamedInputConnectionPoints([new ta(ax.TRIGGER,Qo.BASE,this.processEventTrigger.bind(this)),new ta(ax.RESET,Qo.BASE,this.process_event_reset.bind(this))]),this.io.outputs.setNamedOutputConnectionPoints([new ta(lx.OUT,Qo.BASE),new ta(lx.LAST,Qo.BASE)])}processEvent(t){}processEventTrigger(t){this._process_count>8&255]+sb[t>>16&255]+sb[t>>24&255]+\\\\\\\"-\\\\\\\"+sb[255&e]+sb[e>>8&255]+\\\\\\\"-\\\\\\\"+sb[e>>16&15|64]+sb[e>>24&255]+\\\\\\\"-\\\\\\\"+sb[63&n|128]+sb[n>>8&255]+\\\\\\\"-\\\\\\\"+sb[n>>16&255]+sb[n>>24&255]+sb[255&i]+sb[i>>8&255]+sb[i>>16&255]+sb[i>>24&255]).toUpperCase()}function ab(t,e,n){return Math.max(e,Math.min(n,t))}function lb(t,e){return(t%e+e)%e}function cb(t,e,n){return(1-n)*t+n*e}function hb(t){return 0==(t&t-1)&&0!==t}function ub(t){return Math.pow(2,Math.ceil(Math.log(t)/Math.LN2))}function db(t){return Math.pow(2,Math.floor(Math.log(t)/Math.LN2))}var pb=Object.freeze({__proto__:null,DEG2RAD:nb,RAD2DEG:ib,generateUUID:ob,clamp:ab,euclideanModulo:lb,mapLinear:function(t,e,n,i,s){return i+(t-e)*(s-i)/(n-e)},inverseLerp:function(t,e,n){return t!==e?(n-t)/(e-t):0},lerp:cb,damp:function(t,e,n,i){return cb(t,e,1-Math.exp(-n*i))},pingpong:function(t,e=1){return e-Math.abs(lb(t,2*e)-e)},smoothstep:function(t,e,n){return t<=e?0:t>=n?1:(t=(t-e)/(n-e))*t*(3-2*t)},smootherstep:function(t,e,n){return t<=e?0:t>=n?1:(t=(t-e)/(n-e))*t*t*(t*(6*t-15)+10)},randInt:function(t,e){return t+Math.floor(Math.random()*(e-t+1))},randFloat:function(t,e){return t+Math.random()*(e-t)},randFloatSpread:function(t){return t*(.5-Math.random())},seededRandom:function(t){return void 0!==t&&(eb=t%2147483647),eb=16807*eb%2147483647,(eb-1)/2147483646},degToRad:function(t){return t*nb},radToDeg:function(t){return t*ib},isPowerOfTwo:hb,ceilPowerOfTwo:ub,floorPowerOfTwo:db,setQuaternionFromProperEuler:function(t,e,n,i,s){const r=Math.cos,o=Math.sin,a=r(n/2),l=o(n/2),c=r((e+i)/2),h=o((e+i)/2),u=r((e-i)/2),d=o((e-i)/2),p=r((i-e)/2),_=o((i-e)/2);switch(s){case\\\\\\\"XYX\\\\\\\":t.set(a*h,l*u,l*d,a*c);break;case\\\\\\\"YZY\\\\\\\":t.set(l*d,a*h,l*u,a*c);break;case\\\\\\\"ZXZ\\\\\\\":t.set(l*u,l*d,a*h,a*c);break;case\\\\\\\"XZX\\\\\\\":t.set(a*h,l*_,l*p,a*c);break;case\\\\\\\"YXY\\\\\\\":t.set(l*p,a*h,l*_,a*c);break;case\\\\\\\"ZYZ\\\\\\\":t.set(l*_,l*p,a*h,a*c);break;default:console.warn(\\\\\\\"THREE.MathUtils: .setQuaternionFromProperEuler() encountered an unknown order: \\\\\\\"+s)}}});class _b{constructor(t=0,e=0){this.x=t,this.y=e}get width(){return this.x}set width(t){this.x=t}get height(){return this.y}set height(t){this.y=t}set(t,e){return this.x=t,this.y=e,this}setScalar(t){return this.x=t,this.y=t,this}setX(t){return this.x=t,this}setY(t){return this.y=t,this}setComponent(t,e){switch(t){case 0:this.x=e;break;case 1:this.y=e;break;default:throw new Error(\\\\\\\"index is out of range: \\\\\\\"+t)}return this}getComponent(t){switch(t){case 0:return this.x;case 1:return this.y;default:throw new Error(\\\\\\\"index is out of range: \\\\\\\"+t)}}clone(){return new this.constructor(this.x,this.y)}copy(t){return this.x=t.x,this.y=t.y,this}add(t,e){return void 0!==e?(console.warn(\\\\\\\"THREE.Vector2: .add() now only accepts one argument. Use .addVectors( a, b ) instead.\\\\\\\"),this.addVectors(t,e)):(this.x+=t.x,this.y+=t.y,this)}addScalar(t){return this.x+=t,this.y+=t,this}addVectors(t,e){return this.x=t.x+e.x,this.y=t.y+e.y,this}addScaledVector(t,e){return this.x+=t.x*e,this.y+=t.y*e,this}sub(t,e){return void 0!==e?(console.warn(\\\\\\\"THREE.Vector2: .sub() now only accepts one argument. Use .subVectors( a, b ) instead.\\\\\\\"),this.subVectors(t,e)):(this.x-=t.x,this.y-=t.y,this)}subScalar(t){return this.x-=t,this.y-=t,this}subVectors(t,e){return this.x=t.x-e.x,this.y=t.y-e.y,this}multiply(t){return this.x*=t.x,this.y*=t.y,this}multiplyScalar(t){return this.x*=t,this.y*=t,this}divide(t){return this.x/=t.x,this.y/=t.y,this}divideScalar(t){return this.multiplyScalar(1/t)}applyMatrix3(t){const e=this.x,n=this.y,i=t.elements;return this.x=i[0]*e+i[3]*n+i[6],this.y=i[1]*e+i[4]*n+i[7],this}min(t){return this.x=Math.min(this.x,t.x),this.y=Math.min(this.y,t.y),this}max(t){return this.x=Math.max(this.x,t.x),this.y=Math.max(this.y,t.y),this}clamp(t,e){return this.x=Math.max(t.x,Math.min(e.x,this.x)),this.y=Math.max(t.y,Math.min(e.y,this.y)),this}clampScalar(t,e){return this.x=Math.max(t,Math.min(e,this.x)),this.y=Math.max(t,Math.min(e,this.y)),this}clampLength(t,e){const n=this.length();return this.divideScalar(n||1).multiplyScalar(Math.max(t,Math.min(e,n)))}floor(){return this.x=Math.floor(this.x),this.y=Math.floor(this.y),this}ceil(){return this.x=Math.ceil(this.x),this.y=Math.ceil(this.y),this}round(){return this.x=Math.round(this.x),this.y=Math.round(this.y),this}roundToZero(){return this.x=this.x<0?Math.ceil(this.x):Math.floor(this.x),this.y=this.y<0?Math.ceil(this.y):Math.floor(this.y),this}negate(){return this.x=-this.x,this.y=-this.y,this}dot(t){return this.x*t.x+this.y*t.y}cross(t){return this.x*t.y-this.y*t.x}lengthSq(){return this.x*this.x+this.y*this.y}length(){return Math.sqrt(this.x*this.x+this.y*this.y)}manhattanLength(){return Math.abs(this.x)+Math.abs(this.y)}normalize(){return this.divideScalar(this.length()||1)}angle(){return Math.atan2(-this.y,-this.x)+Math.PI}distanceTo(t){return Math.sqrt(this.distanceToSquared(t))}distanceToSquared(t){const e=this.x-t.x,n=this.y-t.y;return e*e+n*n}manhattanDistanceTo(t){return Math.abs(this.x-t.x)+Math.abs(this.y-t.y)}setLength(t){return this.normalize().multiplyScalar(t)}lerp(t,e){return this.x+=(t.x-this.x)*e,this.y+=(t.y-this.y)*e,this}lerpVectors(t,e,n){return this.x=t.x+(e.x-t.x)*n,this.y=t.y+(e.y-t.y)*n,this}equals(t){return t.x===this.x&&t.y===this.y}fromArray(t,e=0){return this.x=t[e],this.y=t[e+1],this}toArray(t=[],e=0){return t[e]=this.x,t[e+1]=this.y,t}fromBufferAttribute(t,e,n){return void 0!==n&&console.warn(\\\\\\\"THREE.Vector2: offset has been removed from .fromBufferAttribute().\\\\\\\"),this.x=t.getX(e),this.y=t.getY(e),this}rotateAround(t,e){const n=Math.cos(e),i=Math.sin(e),s=this.x-t.x,r=this.y-t.y;return this.x=s*n-r*i+t.x,this.y=s*i+r*n+t.y,this}random(){return this.x=Math.random(),this.y=Math.random(),this}*[Symbol.iterator](){yield this.x,yield this.y}}_b.prototype.isVector2=!0;class mb{constructor(){this.elements=[1,0,0,0,1,0,0,0,1],arguments.length>0&&console.error(\\\\\\\"THREE.Matrix3: the constructor no longer reads arguments. use .set() instead.\\\\\\\")}set(t,e,n,i,s,r,o,a,l){const c=this.elements;return c[0]=t,c[1]=i,c[2]=o,c[3]=e,c[4]=s,c[5]=a,c[6]=n,c[7]=r,c[8]=l,this}identity(){return this.set(1,0,0,0,1,0,0,0,1),this}copy(t){const e=this.elements,n=t.elements;return e[0]=n[0],e[1]=n[1],e[2]=n[2],e[3]=n[3],e[4]=n[4],e[5]=n[5],e[6]=n[6],e[7]=n[7],e[8]=n[8],this}extractBasis(t,e,n){return t.setFromMatrix3Column(this,0),e.setFromMatrix3Column(this,1),n.setFromMatrix3Column(this,2),this}setFromMatrix4(t){const e=t.elements;return this.set(e[0],e[4],e[8],e[1],e[5],e[9],e[2],e[6],e[10]),this}multiply(t){return this.multiplyMatrices(this,t)}premultiply(t){return this.multiplyMatrices(t,this)}multiplyMatrices(t,e){const n=t.elements,i=e.elements,s=this.elements,r=n[0],o=n[3],a=n[6],l=n[1],c=n[4],h=n[7],u=n[2],d=n[5],p=n[8],_=i[0],m=i[3],f=i[6],g=i[1],v=i[4],y=i[7],x=i[2],b=i[5],w=i[8];return s[0]=r*_+o*g+a*x,s[3]=r*m+o*v+a*b,s[6]=r*f+o*y+a*w,s[1]=l*_+c*g+h*x,s[4]=l*m+c*v+h*b,s[7]=l*f+c*y+h*w,s[2]=u*_+d*g+p*x,s[5]=u*m+d*v+p*b,s[8]=u*f+d*y+p*w,this}multiplyScalar(t){const e=this.elements;return e[0]*=t,e[3]*=t,e[6]*=t,e[1]*=t,e[4]*=t,e[7]*=t,e[2]*=t,e[5]*=t,e[8]*=t,this}determinant(){const t=this.elements,e=t[0],n=t[1],i=t[2],s=t[3],r=t[4],o=t[5],a=t[6],l=t[7],c=t[8];return e*r*c-e*o*l-n*s*c+n*o*a+i*s*l-i*r*a}invert(){const t=this.elements,e=t[0],n=t[1],i=t[2],s=t[3],r=t[4],o=t[5],a=t[6],l=t[7],c=t[8],h=c*r-o*l,u=o*a-c*s,d=l*s-r*a,p=e*h+n*u+i*d;if(0===p)return this.set(0,0,0,0,0,0,0,0,0);const _=1/p;return t[0]=h*_,t[1]=(i*l-c*n)*_,t[2]=(o*n-i*r)*_,t[3]=u*_,t[4]=(c*e-i*a)*_,t[5]=(i*s-o*e)*_,t[6]=d*_,t[7]=(n*a-l*e)*_,t[8]=(r*e-n*s)*_,this}transpose(){let t;const e=this.elements;return t=e[1],e[1]=e[3],e[3]=t,t=e[2],e[2]=e[6],e[6]=t,t=e[5],e[5]=e[7],e[7]=t,this}getNormalMatrix(t){return this.setFromMatrix4(t).invert().transpose()}transposeIntoArray(t){const e=this.elements;return t[0]=e[0],t[1]=e[3],t[2]=e[6],t[3]=e[1],t[4]=e[4],t[5]=e[7],t[6]=e[2],t[7]=e[5],t[8]=e[8],this}setUvTransform(t,e,n,i,s,r,o){const a=Math.cos(s),l=Math.sin(s);return this.set(n*a,n*l,-n*(a*r+l*o)+r+t,-i*l,i*a,-i*(-l*r+a*o)+o+e,0,0,1),this}scale(t,e){const n=this.elements;return n[0]*=t,n[3]*=t,n[6]*=t,n[1]*=e,n[4]*=e,n[7]*=e,this}rotate(t){const e=Math.cos(t),n=Math.sin(t),i=this.elements,s=i[0],r=i[3],o=i[6],a=i[1],l=i[4],c=i[7];return i[0]=e*s+n*a,i[3]=e*r+n*l,i[6]=e*o+n*c,i[1]=-n*s+e*a,i[4]=-n*r+e*l,i[7]=-n*o+e*c,this}translate(t,e){const n=this.elements;return n[0]+=t*n[2],n[3]+=t*n[5],n[6]+=t*n[8],n[1]+=e*n[2],n[4]+=e*n[5],n[7]+=e*n[8],this}equals(t){const e=this.elements,n=t.elements;for(let t=0;t<9;t++)if(e[t]!==n[t])return!1;return!0}fromArray(t,e=0){for(let n=0;n<9;n++)this.elements[n]=t[n+e];return this}toArray(t=[],e=0){const n=this.elements;return t[e]=n[0],t[e+1]=n[1],t[e+2]=n[2],t[e+3]=n[3],t[e+4]=n[4],t[e+5]=n[5],t[e+6]=n[6],t[e+7]=n[7],t[e+8]=n[8],t}clone(){return(new this.constructor).fromArray(this.elements)}}function fb(t){if(0===t.length)return-1/0;let e=t[0];for(let n=1,i=t.length;ne&&(e=t[n]);return e}mb.prototype.isMatrix3=!0;Int8Array,Uint8Array,Uint8ClampedArray,Int16Array,Uint16Array,Int32Array,Uint32Array,Float32Array,Float64Array;function gb(t){return document.createElementNS(\\\\\\\"http://www.w3.org/1999/xhtml\\\\\\\",t)}let vb;class yb{static getDataURL(t){if(/^data:/i.test(t.src))return t.src;if(\\\\\\\"undefined\\\\\\\"==typeof HTMLCanvasElement)return t.src;let e;if(t instanceof HTMLCanvasElement)e=t;else{void 0===vb&&(vb=gb(\\\\\\\"canvas\\\\\\\")),vb.width=t.width,vb.height=t.height;const n=vb.getContext(\\\\\\\"2d\\\\\\\");t instanceof ImageData?n.putImageData(t,0,0):n.drawImage(t,0,0,t.width,t.height),e=vb}return e.width>2048||e.height>2048?(console.warn(\\\\\\\"THREE.ImageUtils.getDataURL: Image converted to jpg for performance reasons\\\\\\\",t),e.toDataURL(\\\\\\\"image/jpeg\\\\\\\",.6)):e.toDataURL(\\\\\\\"image/png\\\\\\\")}}let xb=0;class bb extends tb{constructor(t=bb.DEFAULT_IMAGE,e=bb.DEFAULT_MAPPING,n=1001,i=1001,s=1006,r=1008,o=1023,a=1009,l=1,c=3e3){super(),Object.defineProperty(this,\\\\\\\"id\\\\\\\",{value:xb++}),this.uuid=ob(),this.name=\\\\\\\"\\\\\\\",this.image=t,this.mipmaps=[],this.mapping=e,this.wrapS=n,this.wrapT=i,this.magFilter=s,this.minFilter=r,this.anisotropy=l,this.format=o,this.internalFormat=null,this.type=a,this.offset=new _b(0,0),this.repeat=new _b(1,1),this.center=new _b(0,0),this.rotation=0,this.matrixAutoUpdate=!0,this.matrix=new mb,this.generateMipmaps=!0,this.premultiplyAlpha=!1,this.flipY=!0,this.unpackAlignment=4,this.encoding=c,this.version=0,this.onUpdate=null,this.isRenderTargetTexture=!1}updateMatrix(){this.matrix.setUvTransform(this.offset.x,this.offset.y,this.repeat.x,this.repeat.y,this.rotation,this.center.x,this.center.y)}clone(){return(new this.constructor).copy(this)}copy(t){return this.name=t.name,this.image=t.image,this.mipmaps=t.mipmaps.slice(0),this.mapping=t.mapping,this.wrapS=t.wrapS,this.wrapT=t.wrapT,this.magFilter=t.magFilter,this.minFilter=t.minFilter,this.anisotropy=t.anisotropy,this.format=t.format,this.internalFormat=t.internalFormat,this.type=t.type,this.offset.copy(t.offset),this.repeat.copy(t.repeat),this.center.copy(t.center),this.rotation=t.rotation,this.matrixAutoUpdate=t.matrixAutoUpdate,this.matrix.copy(t.matrix),this.generateMipmaps=t.generateMipmaps,this.premultiplyAlpha=t.premultiplyAlpha,this.flipY=t.flipY,this.unpackAlignment=t.unpackAlignment,this.encoding=t.encoding,this}toJSON(t){const e=void 0===t||\\\\\\\"string\\\\\\\"==typeof t;if(!e&&void 0!==t.textures[this.uuid])return t.textures[this.uuid];const n={metadata:{version:4.5,type:\\\\\\\"Texture\\\\\\\",generator:\\\\\\\"Texture.toJSON\\\\\\\"},uuid:this.uuid,name:this.name,mapping:this.mapping,repeat:[this.repeat.x,this.repeat.y],offset:[this.offset.x,this.offset.y],center:[this.center.x,this.center.y],rotation:this.rotation,wrap:[this.wrapS,this.wrapT],format:this.format,type:this.type,encoding:this.encoding,minFilter:this.minFilter,magFilter:this.magFilter,anisotropy:this.anisotropy,flipY:this.flipY,premultiplyAlpha:this.premultiplyAlpha,unpackAlignment:this.unpackAlignment};if(void 0!==this.image){const i=this.image;if(void 0===i.uuid&&(i.uuid=ob()),!e&&void 0===t.images[i.uuid]){let e;if(Array.isArray(i)){e=[];for(let t=0,n=i.length;t1)switch(this.wrapS){case xx:t.x=t.x-Math.floor(t.x);break;case bx:t.x=t.x<0?0:1;break;case wx:1===Math.abs(Math.floor(t.x)%2)?t.x=Math.ceil(t.x)-t.x:t.x=t.x-Math.floor(t.x)}if(t.y<0||t.y>1)switch(this.wrapT){case xx:t.y=t.y-Math.floor(t.y);break;case bx:t.y=t.y<0?0:1;break;case wx:1===Math.abs(Math.floor(t.y)%2)?t.y=Math.ceil(t.y)-t.y:t.y=t.y-Math.floor(t.y)}return this.flipY&&(t.y=1-t.y),t}set needsUpdate(t){!0===t&&this.version++}}function wb(t){return\\\\\\\"undefined\\\\\\\"!=typeof HTMLImageElement&&t instanceof HTMLImageElement||\\\\\\\"undefined\\\\\\\"!=typeof HTMLCanvasElement&&t instanceof HTMLCanvasElement||\\\\\\\"undefined\\\\\\\"!=typeof ImageBitmap&&t instanceof ImageBitmap?yb.getDataURL(t):t.data?{data:Array.prototype.slice.call(t.data),width:t.width,height:t.height,type:t.data.constructor.name}:(console.warn(\\\\\\\"THREE.Texture: Unable to serialize Texture.\\\\\\\"),{})}bb.DEFAULT_IMAGE=void 0,bb.DEFAULT_MAPPING=300,bb.prototype.isTexture=!0;class Tb{constructor(t=0,e=0,n=0,i=1){this.x=t,this.y=e,this.z=n,this.w=i}get width(){return this.z}set width(t){this.z=t}get height(){return this.w}set height(t){this.w=t}set(t,e,n,i){return this.x=t,this.y=e,this.z=n,this.w=i,this}setScalar(t){return this.x=t,this.y=t,this.z=t,this.w=t,this}setX(t){return this.x=t,this}setY(t){return this.y=t,this}setZ(t){return this.z=t,this}setW(t){return this.w=t,this}setComponent(t,e){switch(t){case 0:this.x=e;break;case 1:this.y=e;break;case 2:this.z=e;break;case 3:this.w=e;break;default:throw new Error(\\\\\\\"index is out of range: \\\\\\\"+t)}return this}getComponent(t){switch(t){case 0:return this.x;case 1:return this.y;case 2:return this.z;case 3:return this.w;default:throw new Error(\\\\\\\"index is out of range: \\\\\\\"+t)}}clone(){return new this.constructor(this.x,this.y,this.z,this.w)}copy(t){return this.x=t.x,this.y=t.y,this.z=t.z,this.w=void 0!==t.w?t.w:1,this}add(t,e){return void 0!==e?(console.warn(\\\\\\\"THREE.Vector4: .add() now only accepts one argument. Use .addVectors( a, b ) instead.\\\\\\\"),this.addVectors(t,e)):(this.x+=t.x,this.y+=t.y,this.z+=t.z,this.w+=t.w,this)}addScalar(t){return this.x+=t,this.y+=t,this.z+=t,this.w+=t,this}addVectors(t,e){return this.x=t.x+e.x,this.y=t.y+e.y,this.z=t.z+e.z,this.w=t.w+e.w,this}addScaledVector(t,e){return this.x+=t.x*e,this.y+=t.y*e,this.z+=t.z*e,this.w+=t.w*e,this}sub(t,e){return void 0!==e?(console.warn(\\\\\\\"THREE.Vector4: .sub() now only accepts one argument. Use .subVectors( a, b ) instead.\\\\\\\"),this.subVectors(t,e)):(this.x-=t.x,this.y-=t.y,this.z-=t.z,this.w-=t.w,this)}subScalar(t){return this.x-=t,this.y-=t,this.z-=t,this.w-=t,this}subVectors(t,e){return this.x=t.x-e.x,this.y=t.y-e.y,this.z=t.z-e.z,this.w=t.w-e.w,this}multiply(t){return this.x*=t.x,this.y*=t.y,this.z*=t.z,this.w*=t.w,this}multiplyScalar(t){return this.x*=t,this.y*=t,this.z*=t,this.w*=t,this}applyMatrix4(t){const e=this.x,n=this.y,i=this.z,s=this.w,r=t.elements;return this.x=r[0]*e+r[4]*n+r[8]*i+r[12]*s,this.y=r[1]*e+r[5]*n+r[9]*i+r[13]*s,this.z=r[2]*e+r[6]*n+r[10]*i+r[14]*s,this.w=r[3]*e+r[7]*n+r[11]*i+r[15]*s,this}divideScalar(t){return this.multiplyScalar(1/t)}setAxisAngleFromQuaternion(t){this.w=2*Math.acos(t.w);const e=Math.sqrt(1-t.w*t.w);return e<1e-4?(this.x=1,this.y=0,this.z=0):(this.x=t.x/e,this.y=t.y/e,this.z=t.z/e),this}setAxisAngleFromRotationMatrix(t){let e,n,i,s;const r=.01,o=.1,a=t.elements,l=a[0],c=a[4],h=a[8],u=a[1],d=a[5],p=a[9],_=a[2],m=a[6],f=a[10];if(Math.abs(c-u)a&&t>g?tg?a=0?1:-1,i=1-e*e;if(i>Number.EPSILON){const s=Math.sqrt(i),r=Math.atan2(s,e*n);t=Math.sin(t*r)/s,o=Math.sin(o*r)/s}const s=o*n;if(a=a*t+u*s,l=l*t+d*s,c=c*t+p*s,h=h*t+_*s,t===1-o){const t=1/Math.sqrt(a*a+l*l+c*c+h*h);a*=t,l*=t,c*=t,h*=t}}t[e]=a,t[e+1]=l,t[e+2]=c,t[e+3]=h}static multiplyQuaternionsFlat(t,e,n,i,s,r){const o=n[i],a=n[i+1],l=n[i+2],c=n[i+3],h=s[r],u=s[r+1],d=s[r+2],p=s[r+3];return t[e]=o*p+c*h+a*d-l*u,t[e+1]=a*p+c*u+l*h-o*d,t[e+2]=l*p+c*d+o*u-a*h,t[e+3]=c*p-o*h-a*u-l*d,t}get x(){return this._x}set x(t){this._x=t,this._onChangeCallback()}get y(){return this._y}set y(t){this._y=t,this._onChangeCallback()}get z(){return this._z}set z(t){this._z=t,this._onChangeCallback()}get w(){return this._w}set w(t){this._w=t,this._onChangeCallback()}set(t,e,n,i){return this._x=t,this._y=e,this._z=n,this._w=i,this._onChangeCallback(),this}clone(){return new this.constructor(this._x,this._y,this._z,this._w)}copy(t){return this._x=t.x,this._y=t.y,this._z=t.z,this._w=t.w,this._onChangeCallback(),this}setFromEuler(t,e){if(!t||!t.isEuler)throw new Error(\\\\\\\"THREE.Quaternion: .setFromEuler() now expects an Euler rotation rather than a Vector3 and order.\\\\\\\");const n=t._x,i=t._y,s=t._z,r=t._order,o=Math.cos,a=Math.sin,l=o(n/2),c=o(i/2),h=o(s/2),u=a(n/2),d=a(i/2),p=a(s/2);switch(r){case\\\\\\\"XYZ\\\\\\\":this._x=u*c*h+l*d*p,this._y=l*d*h-u*c*p,this._z=l*c*p+u*d*h,this._w=l*c*h-u*d*p;break;case\\\\\\\"YXZ\\\\\\\":this._x=u*c*h+l*d*p,this._y=l*d*h-u*c*p,this._z=l*c*p-u*d*h,this._w=l*c*h+u*d*p;break;case\\\\\\\"ZXY\\\\\\\":this._x=u*c*h-l*d*p,this._y=l*d*h+u*c*p,this._z=l*c*p+u*d*h,this._w=l*c*h-u*d*p;break;case\\\\\\\"ZYX\\\\\\\":this._x=u*c*h-l*d*p,this._y=l*d*h+u*c*p,this._z=l*c*p-u*d*h,this._w=l*c*h+u*d*p;break;case\\\\\\\"YZX\\\\\\\":this._x=u*c*h+l*d*p,this._y=l*d*h+u*c*p,this._z=l*c*p-u*d*h,this._w=l*c*h-u*d*p;break;case\\\\\\\"XZY\\\\\\\":this._x=u*c*h-l*d*p,this._y=l*d*h-u*c*p,this._z=l*c*p+u*d*h,this._w=l*c*h+u*d*p;break;default:console.warn(\\\\\\\"THREE.Quaternion: .setFromEuler() encountered an unknown order: \\\\\\\"+r)}return!1!==e&&this._onChangeCallback(),this}setFromAxisAngle(t,e){const n=e/2,i=Math.sin(n);return this._x=t.x*i,this._y=t.y*i,this._z=t.z*i,this._w=Math.cos(n),this._onChangeCallback(),this}setFromRotationMatrix(t){const e=t.elements,n=e[0],i=e[4],s=e[8],r=e[1],o=e[5],a=e[9],l=e[2],c=e[6],h=e[10],u=n+o+h;if(u>0){const t=.5/Math.sqrt(u+1);this._w=.25/t,this._x=(c-a)*t,this._y=(s-l)*t,this._z=(r-i)*t}else if(n>o&&n>h){const t=2*Math.sqrt(1+n-o-h);this._w=(c-a)/t,this._x=.25*t,this._y=(i+r)/t,this._z=(s+l)/t}else if(o>h){const t=2*Math.sqrt(1+o-n-h);this._w=(s-l)/t,this._x=(i+r)/t,this._y=.25*t,this._z=(a+c)/t}else{const t=2*Math.sqrt(1+h-n-o);this._w=(r-i)/t,this._x=(s+l)/t,this._y=(a+c)/t,this._z=.25*t}return this._onChangeCallback(),this}setFromUnitVectors(t,e){let n=t.dot(e)+1;return nMath.abs(t.z)?(this._x=-t.y,this._y=t.x,this._z=0,this._w=n):(this._x=0,this._y=-t.z,this._z=t.y,this._w=n)):(this._x=t.y*e.z-t.z*e.y,this._y=t.z*e.x-t.x*e.z,this._z=t.x*e.y-t.y*e.x,this._w=n),this.normalize()}angleTo(t){return 2*Math.acos(Math.abs(ab(this.dot(t),-1,1)))}rotateTowards(t,e){const n=this.angleTo(t);if(0===n)return this;const i=Math.min(1,e/n);return this.slerp(t,i),this}identity(){return this.set(0,0,0,1)}invert(){return this.conjugate()}conjugate(){return this._x*=-1,this._y*=-1,this._z*=-1,this._onChangeCallback(),this}dot(t){return this._x*t._x+this._y*t._y+this._z*t._z+this._w*t._w}lengthSq(){return this._x*this._x+this._y*this._y+this._z*this._z+this._w*this._w}length(){return Math.sqrt(this._x*this._x+this._y*this._y+this._z*this._z+this._w*this._w)}normalize(){let t=this.length();return 0===t?(this._x=0,this._y=0,this._z=0,this._w=1):(t=1/t,this._x=this._x*t,this._y=this._y*t,this._z=this._z*t,this._w=this._w*t),this._onChangeCallback(),this}multiply(t,e){return void 0!==e?(console.warn(\\\\\\\"THREE.Quaternion: .multiply() now only accepts one argument. Use .multiplyQuaternions( a, b ) instead.\\\\\\\"),this.multiplyQuaternions(t,e)):this.multiplyQuaternions(this,t)}premultiply(t){return this.multiplyQuaternions(t,this)}multiplyQuaternions(t,e){const n=t._x,i=t._y,s=t._z,r=t._w,o=e._x,a=e._y,l=e._z,c=e._w;return this._x=n*c+r*o+i*l-s*a,this._y=i*c+r*a+s*o-n*l,this._z=s*c+r*l+n*a-i*o,this._w=r*c-n*o-i*a-s*l,this._onChangeCallback(),this}slerp(t,e){if(0===e)return this;if(1===e)return this.copy(t);const n=this._x,i=this._y,s=this._z,r=this._w;let o=r*t._w+n*t._x+i*t._y+s*t._z;if(o<0?(this._w=-t._w,this._x=-t._x,this._y=-t._y,this._z=-t._z,o=-o):this.copy(t),o>=1)return this._w=r,this._x=n,this._y=i,this._z=s,this;const a=1-o*o;if(a<=Number.EPSILON){const t=1-e;return this._w=t*r+e*this._w,this._x=t*n+e*this._x,this._y=t*i+e*this._y,this._z=t*s+e*this._z,this.normalize(),this._onChangeCallback(),this}const l=Math.sqrt(a),c=Math.atan2(l,o),h=Math.sin((1-e)*c)/l,u=Math.sin(e*c)/l;return this._w=r*h+this._w*u,this._x=n*h+this._x*u,this._y=i*h+this._y*u,this._z=s*h+this._z*u,this._onChangeCallback(),this}slerpQuaternions(t,e,n){this.copy(t).slerp(e,n)}random(){const t=Math.random(),e=Math.sqrt(1-t),n=Math.sqrt(t),i=2*Math.PI*Math.random(),s=2*Math.PI*Math.random();return this.set(e*Math.cos(i),n*Math.sin(s),n*Math.cos(s),e*Math.sin(i))}equals(t){return t._x===this._x&&t._y===this._y&&t._z===this._z&&t._w===this._w}fromArray(t,e=0){return this._x=t[e],this._y=t[e+1],this._z=t[e+2],this._w=t[e+3],this._onChangeCallback(),this}toArray(t=[],e=0){return t[e]=this._x,t[e+1]=this._y,t[e+2]=this._z,t[e+3]=this._w,t}fromBufferAttribute(t,e){return this._x=t.getX(e),this._y=t.getY(e),this._z=t.getZ(e),this._w=t.getW(e),this}_onChange(t){return this._onChangeCallback=t,this}_onChangeCallback(){}}Eb.prototype.isQuaternion=!0;class Sb{constructor(t=0,e=0,n=0){this.x=t,this.y=e,this.z=n}set(t,e,n){return void 0===n&&(n=this.z),this.x=t,this.y=e,this.z=n,this}setScalar(t){return this.x=t,this.y=t,this.z=t,this}setX(t){return this.x=t,this}setY(t){return this.y=t,this}setZ(t){return this.z=t,this}setComponent(t,e){switch(t){case 0:this.x=e;break;case 1:this.y=e;break;case 2:this.z=e;break;default:throw new Error(\\\\\\\"index is out of range: \\\\\\\"+t)}return this}getComponent(t){switch(t){case 0:return this.x;case 1:return this.y;case 2:return this.z;default:throw new Error(\\\\\\\"index is out of range: \\\\\\\"+t)}}clone(){return new this.constructor(this.x,this.y,this.z)}copy(t){return this.x=t.x,this.y=t.y,this.z=t.z,this}add(t,e){return void 0!==e?(console.warn(\\\\\\\"THREE.Vector3: .add() now only accepts one argument. Use .addVectors( a, b ) instead.\\\\\\\"),this.addVectors(t,e)):(this.x+=t.x,this.y+=t.y,this.z+=t.z,this)}addScalar(t){return this.x+=t,this.y+=t,this.z+=t,this}addVectors(t,e){return this.x=t.x+e.x,this.y=t.y+e.y,this.z=t.z+e.z,this}addScaledVector(t,e){return this.x+=t.x*e,this.y+=t.y*e,this.z+=t.z*e,this}sub(t,e){return void 0!==e?(console.warn(\\\\\\\"THREE.Vector3: .sub() now only accepts one argument. Use .subVectors( a, b ) instead.\\\\\\\"),this.subVectors(t,e)):(this.x-=t.x,this.y-=t.y,this.z-=t.z,this)}subScalar(t){return this.x-=t,this.y-=t,this.z-=t,this}subVectors(t,e){return this.x=t.x-e.x,this.y=t.y-e.y,this.z=t.z-e.z,this}multiply(t,e){return void 0!==e?(console.warn(\\\\\\\"THREE.Vector3: .multiply() now only accepts one argument. Use .multiplyVectors( a, b ) instead.\\\\\\\"),this.multiplyVectors(t,e)):(this.x*=t.x,this.y*=t.y,this.z*=t.z,this)}multiplyScalar(t){return this.x*=t,this.y*=t,this.z*=t,this}multiplyVectors(t,e){return this.x=t.x*e.x,this.y=t.y*e.y,this.z=t.z*e.z,this}applyEuler(t){return t&&t.isEuler||console.error(\\\\\\\"THREE.Vector3: .applyEuler() now expects an Euler rotation rather than a Vector3 and order.\\\\\\\"),this.applyQuaternion(Nb.setFromEuler(t))}applyAxisAngle(t,e){return this.applyQuaternion(Nb.setFromAxisAngle(t,e))}applyMatrix3(t){const e=this.x,n=this.y,i=this.z,s=t.elements;return this.x=s[0]*e+s[3]*n+s[6]*i,this.y=s[1]*e+s[4]*n+s[7]*i,this.z=s[2]*e+s[5]*n+s[8]*i,this}applyNormalMatrix(t){return this.applyMatrix3(t).normalize()}applyMatrix4(t){const e=this.x,n=this.y,i=this.z,s=t.elements,r=1/(s[3]*e+s[7]*n+s[11]*i+s[15]);return this.x=(s[0]*e+s[4]*n+s[8]*i+s[12])*r,this.y=(s[1]*e+s[5]*n+s[9]*i+s[13])*r,this.z=(s[2]*e+s[6]*n+s[10]*i+s[14])*r,this}applyQuaternion(t){const e=this.x,n=this.y,i=this.z,s=t.x,r=t.y,o=t.z,a=t.w,l=a*e+r*i-o*n,c=a*n+o*e-s*i,h=a*i+s*n-r*e,u=-s*e-r*n-o*i;return this.x=l*a+u*-s+c*-o-h*-r,this.y=c*a+u*-r+h*-s-l*-o,this.z=h*a+u*-o+l*-r-c*-s,this}project(t){return this.applyMatrix4(t.matrixWorldInverse).applyMatrix4(t.projectionMatrix)}unproject(t){return this.applyMatrix4(t.projectionMatrixInverse).applyMatrix4(t.matrixWorld)}transformDirection(t){const e=this.x,n=this.y,i=this.z,s=t.elements;return this.x=s[0]*e+s[4]*n+s[8]*i,this.y=s[1]*e+s[5]*n+s[9]*i,this.z=s[2]*e+s[6]*n+s[10]*i,this.normalize()}divide(t){return this.x/=t.x,this.y/=t.y,this.z/=t.z,this}divideScalar(t){return this.multiplyScalar(1/t)}min(t){return this.x=Math.min(this.x,t.x),this.y=Math.min(this.y,t.y),this.z=Math.min(this.z,t.z),this}max(t){return this.x=Math.max(this.x,t.x),this.y=Math.max(this.y,t.y),this.z=Math.max(this.z,t.z),this}clamp(t,e){return this.x=Math.max(t.x,Math.min(e.x,this.x)),this.y=Math.max(t.y,Math.min(e.y,this.y)),this.z=Math.max(t.z,Math.min(e.z,this.z)),this}clampScalar(t,e){return this.x=Math.max(t,Math.min(e,this.x)),this.y=Math.max(t,Math.min(e,this.y)),this.z=Math.max(t,Math.min(e,this.z)),this}clampLength(t,e){const n=this.length();return this.divideScalar(n||1).multiplyScalar(Math.max(t,Math.min(e,n)))}floor(){return this.x=Math.floor(this.x),this.y=Math.floor(this.y),this.z=Math.floor(this.z),this}ceil(){return this.x=Math.ceil(this.x),this.y=Math.ceil(this.y),this.z=Math.ceil(this.z),this}round(){return this.x=Math.round(this.x),this.y=Math.round(this.y),this.z=Math.round(this.z),this}roundToZero(){return this.x=this.x<0?Math.ceil(this.x):Math.floor(this.x),this.y=this.y<0?Math.ceil(this.y):Math.floor(this.y),this.z=this.z<0?Math.ceil(this.z):Math.floor(this.z),this}negate(){return this.x=-this.x,this.y=-this.y,this.z=-this.z,this}dot(t){return this.x*t.x+this.y*t.y+this.z*t.z}lengthSq(){return this.x*this.x+this.y*this.y+this.z*this.z}length(){return Math.sqrt(this.x*this.x+this.y*this.y+this.z*this.z)}manhattanLength(){return Math.abs(this.x)+Math.abs(this.y)+Math.abs(this.z)}normalize(){return this.divideScalar(this.length()||1)}setLength(t){return this.normalize().multiplyScalar(t)}lerp(t,e){return this.x+=(t.x-this.x)*e,this.y+=(t.y-this.y)*e,this.z+=(t.z-this.z)*e,this}lerpVectors(t,e,n){return this.x=t.x+(e.x-t.x)*n,this.y=t.y+(e.y-t.y)*n,this.z=t.z+(e.z-t.z)*n,this}cross(t,e){return void 0!==e?(console.warn(\\\\\\\"THREE.Vector3: .cross() now only accepts one argument. Use .crossVectors( a, b ) instead.\\\\\\\"),this.crossVectors(t,e)):this.crossVectors(this,t)}crossVectors(t,e){const n=t.x,i=t.y,s=t.z,r=e.x,o=e.y,a=e.z;return this.x=i*a-s*o,this.y=s*r-n*a,this.z=n*o-i*r,this}projectOnVector(t){const e=t.lengthSq();if(0===e)return this.set(0,0,0);const n=t.dot(this)/e;return this.copy(t).multiplyScalar(n)}projectOnPlane(t){return Cb.copy(this).projectOnVector(t),this.sub(Cb)}reflect(t){return this.sub(Cb.copy(t).multiplyScalar(2*this.dot(t)))}angleTo(t){const e=Math.sqrt(this.lengthSq()*t.lengthSq());if(0===e)return Math.PI/2;const n=this.dot(t)/e;return Math.acos(ab(n,-1,1))}distanceTo(t){return Math.sqrt(this.distanceToSquared(t))}distanceToSquared(t){const e=this.x-t.x,n=this.y-t.y,i=this.z-t.z;return e*e+n*n+i*i}manhattanDistanceTo(t){return Math.abs(this.x-t.x)+Math.abs(this.y-t.y)+Math.abs(this.z-t.z)}setFromSpherical(t){return this.setFromSphericalCoords(t.radius,t.phi,t.theta)}setFromSphericalCoords(t,e,n){const i=Math.sin(e)*t;return this.x=i*Math.sin(n),this.y=Math.cos(e)*t,this.z=i*Math.cos(n),this}setFromCylindrical(t){return this.setFromCylindricalCoords(t.radius,t.theta,t.y)}setFromCylindricalCoords(t,e,n){return this.x=t*Math.sin(e),this.y=n,this.z=t*Math.cos(e),this}setFromMatrixPosition(t){const e=t.elements;return this.x=e[12],this.y=e[13],this.z=e[14],this}setFromMatrixScale(t){const e=this.setFromMatrixColumn(t,0).length(),n=this.setFromMatrixColumn(t,1).length(),i=this.setFromMatrixColumn(t,2).length();return this.x=e,this.y=n,this.z=i,this}setFromMatrixColumn(t,e){return this.fromArray(t.elements,4*e)}setFromMatrix3Column(t,e){return this.fromArray(t.elements,3*e)}equals(t){return t.x===this.x&&t.y===this.y&&t.z===this.z}fromArray(t,e=0){return this.x=t[e],this.y=t[e+1],this.z=t[e+2],this}toArray(t=[],e=0){return t[e]=this.x,t[e+1]=this.y,t[e+2]=this.z,t}fromBufferAttribute(t,e,n){return void 0!==n&&console.warn(\\\\\\\"THREE.Vector3: offset has been removed from .fromBufferAttribute().\\\\\\\"),this.x=t.getX(e),this.y=t.getY(e),this.z=t.getZ(e),this}random(){return this.x=Math.random(),this.y=Math.random(),this.z=Math.random(),this}randomDirection(){const t=2*(Math.random()-.5),e=Math.random()*Math.PI*2,n=Math.sqrt(1-t**2);return this.x=n*Math.cos(e),this.y=n*Math.sin(e),this.z=t,this}*[Symbol.iterator](){yield this.x,yield this.y,yield this.z}}Sb.prototype.isVector3=!0;const Cb=new Sb,Nb=new Eb;class Lb{constructor(t=new Sb(1/0,1/0,1/0),e=new Sb(-1/0,-1/0,-1/0)){this.min=t,this.max=e}set(t,e){return this.min.copy(t),this.max.copy(e),this}setFromArray(t){let e=1/0,n=1/0,i=1/0,s=-1/0,r=-1/0,o=-1/0;for(let a=0,l=t.length;as&&(s=l),c>r&&(r=c),h>o&&(o=h)}return this.min.set(e,n,i),this.max.set(s,r,o),this}setFromBufferAttribute(t){let e=1/0,n=1/0,i=1/0,s=-1/0,r=-1/0,o=-1/0;for(let a=0,l=t.count;as&&(s=l),c>r&&(r=c),h>o&&(o=h)}return this.min.set(e,n,i),this.max.set(s,r,o),this}setFromPoints(t){this.makeEmpty();for(let e=0,n=t.length;ethis.max.x||t.ythis.max.y||t.zthis.max.z)}containsBox(t){return this.min.x<=t.min.x&&t.max.x<=this.max.x&&this.min.y<=t.min.y&&t.max.y<=this.max.y&&this.min.z<=t.min.z&&t.max.z<=this.max.z}getParameter(t,e){return e.set((t.x-this.min.x)/(this.max.x-this.min.x),(t.y-this.min.y)/(this.max.y-this.min.y),(t.z-this.min.z)/(this.max.z-this.min.z))}intersectsBox(t){return!(t.max.xthis.max.x||t.max.ythis.max.y||t.max.zthis.max.z)}intersectsSphere(t){return this.clampPoint(t.center,Pb),Pb.distanceToSquared(t.center)<=t.radius*t.radius}intersectsPlane(t){let e,n;return t.normal.x>0?(e=t.normal.x*this.min.x,n=t.normal.x*this.max.x):(e=t.normal.x*this.max.x,n=t.normal.x*this.min.x),t.normal.y>0?(e+=t.normal.y*this.min.y,n+=t.normal.y*this.max.y):(e+=t.normal.y*this.max.y,n+=t.normal.y*this.min.y),t.normal.z>0?(e+=t.normal.z*this.min.z,n+=t.normal.z*this.max.z):(e+=t.normal.z*this.max.z,n+=t.normal.z*this.min.z),e<=-t.constant&&n>=-t.constant}intersectsTriangle(t){if(this.isEmpty())return!1;this.getCenter(Ub),Gb.subVectors(this.max,Ub),Ib.subVectors(t.a,Ub),Fb.subVectors(t.b,Ub),Db.subVectors(t.c,Ub),Bb.subVectors(Fb,Ib),zb.subVectors(Db,Fb),kb.subVectors(Ib,Db);let e=[0,-Bb.z,Bb.y,0,-zb.z,zb.y,0,-kb.z,kb.y,Bb.z,0,-Bb.x,zb.z,0,-zb.x,kb.z,0,-kb.x,-Bb.y,Bb.x,0,-zb.y,zb.x,0,-kb.y,kb.x,0];return!!jb(e,Ib,Fb,Db,Gb)&&(e=[1,0,0,0,1,0,0,0,1],!!jb(e,Ib,Fb,Db,Gb)&&(Vb.crossVectors(Bb,zb),e=[Vb.x,Vb.y,Vb.z],jb(e,Ib,Fb,Db,Gb)))}clampPoint(t,e){return e.copy(t).clamp(this.min,this.max)}distanceToPoint(t){return Pb.copy(t).clamp(this.min,this.max).sub(t).length()}getBoundingSphere(t){return this.getCenter(t.center),t.radius=.5*this.getSize(Pb).length(),t}intersect(t){return this.min.max(t.min),this.max.min(t.max),this.isEmpty()&&this.makeEmpty(),this}union(t){return this.min.min(t.min),this.max.max(t.max),this}applyMatrix4(t){return this.isEmpty()||(Ob[0].set(this.min.x,this.min.y,this.min.z).applyMatrix4(t),Ob[1].set(this.min.x,this.min.y,this.max.z).applyMatrix4(t),Ob[2].set(this.min.x,this.max.y,this.min.z).applyMatrix4(t),Ob[3].set(this.min.x,this.max.y,this.max.z).applyMatrix4(t),Ob[4].set(this.max.x,this.min.y,this.min.z).applyMatrix4(t),Ob[5].set(this.max.x,this.min.y,this.max.z).applyMatrix4(t),Ob[6].set(this.max.x,this.max.y,this.min.z).applyMatrix4(t),Ob[7].set(this.max.x,this.max.y,this.max.z).applyMatrix4(t),this.setFromPoints(Ob)),this}translate(t){return this.min.add(t),this.max.add(t),this}equals(t){return t.min.equals(this.min)&&t.max.equals(this.max)}}Lb.prototype.isBox3=!0;const Ob=[new Sb,new Sb,new Sb,new Sb,new Sb,new Sb,new Sb,new Sb],Pb=new Sb,Rb=new Lb,Ib=new Sb,Fb=new Sb,Db=new Sb,Bb=new Sb,zb=new Sb,kb=new Sb,Ub=new Sb,Gb=new Sb,Vb=new Sb,Hb=new Sb;function jb(t,e,n,i,s){for(let r=0,o=t.length-3;r<=o;r+=3){Hb.fromArray(t,r);const o=s.x*Math.abs(Hb.x)+s.y*Math.abs(Hb.y)+s.z*Math.abs(Hb.z),a=e.dot(Hb),l=n.dot(Hb),c=i.dot(Hb);if(Math.max(-Math.max(a,l,c),Math.min(a,l,c))>o)return!1}return!0}const Wb=new Lb,qb=new Sb,Xb=new Sb,Yb=new Sb;class $b{constructor(t=new Sb,e=-1){this.center=t,this.radius=e}set(t,e){return this.center.copy(t),this.radius=e,this}setFromPoints(t,e){const n=this.center;void 0!==e?n.copy(e):Wb.setFromPoints(t).getCenter(n);let i=0;for(let e=0,s=t.length;ethis.radius*this.radius&&(e.sub(this.center).normalize(),e.multiplyScalar(this.radius).add(this.center)),e}getBoundingBox(t){return this.isEmpty()?(t.makeEmpty(),t):(t.set(this.center,this.center),t.expandByScalar(this.radius),t)}applyMatrix4(t){return this.center.applyMatrix4(t),this.radius=this.radius*t.getMaxScaleOnAxis(),this}translate(t){return this.center.add(t),this}expandByPoint(t){Yb.subVectors(t,this.center);const e=Yb.lengthSq();if(e>this.radius*this.radius){const t=Math.sqrt(e),n=.5*(t-this.radius);this.center.add(Yb.multiplyScalar(n/t)),this.radius+=n}return this}union(t){return Xb.subVectors(t.center,this.center).normalize().multiplyScalar(t.radius),this.expandByPoint(qb.copy(t.center).add(Xb)),this.expandByPoint(qb.copy(t.center).sub(Xb)),this}equals(t){return t.center.equals(this.center)&&t.radius===this.radius}clone(){return(new this.constructor).copy(this)}}const Jb=new Sb,Zb=new Sb,Kb=new Sb,Qb=new Sb,tw=new Sb,ew=new Sb,nw=new Sb;class iw{constructor(t=new Sb,e=new Sb(0,0,-1)){this.origin=t,this.direction=e}set(t,e){return this.origin.copy(t),this.direction.copy(e),this}copy(t){return this.origin.copy(t.origin),this.direction.copy(t.direction),this}at(t,e){return e.copy(this.direction).multiplyScalar(t).add(this.origin)}lookAt(t){return this.direction.copy(t).sub(this.origin).normalize(),this}recast(t){return this.origin.copy(this.at(t,Jb)),this}closestPointToPoint(t,e){e.subVectors(t,this.origin);const n=e.dot(this.direction);return n<0?e.copy(this.origin):e.copy(this.direction).multiplyScalar(n).add(this.origin)}distanceToPoint(t){return Math.sqrt(this.distanceSqToPoint(t))}distanceSqToPoint(t){const e=Jb.subVectors(t,this.origin).dot(this.direction);return e<0?this.origin.distanceToSquared(t):(Jb.copy(this.direction).multiplyScalar(e).add(this.origin),Jb.distanceToSquared(t))}distanceSqToSegment(t,e,n,i){Zb.copy(t).add(e).multiplyScalar(.5),Kb.copy(e).sub(t).normalize(),Qb.copy(this.origin).sub(Zb);const s=.5*t.distanceTo(e),r=-this.direction.dot(Kb),o=Qb.dot(this.direction),a=-Qb.dot(Kb),l=Qb.lengthSq(),c=Math.abs(1-r*r);let h,u,d,p;if(c>0)if(h=r*a-o,u=r*o-a,p=s*c,h>=0)if(u>=-p)if(u<=p){const t=1/c;h*=t,u*=t,d=h*(h+r*u+2*o)+u*(r*h+u+2*a)+l}else u=s,h=Math.max(0,-(r*u+o)),d=-h*h+u*(u+2*a)+l;else u=-s,h=Math.max(0,-(r*u+o)),d=-h*h+u*(u+2*a)+l;else u<=-p?(h=Math.max(0,-(-r*s+o)),u=h>0?-s:Math.min(Math.max(-s,-a),s),d=-h*h+u*(u+2*a)+l):u<=p?(h=0,u=Math.min(Math.max(-s,-a),s),d=u*(u+2*a)+l):(h=Math.max(0,-(r*s+o)),u=h>0?s:Math.min(Math.max(-s,-a),s),d=-h*h+u*(u+2*a)+l);else u=r>0?-s:s,h=Math.max(0,-(r*u+o)),d=-h*h+u*(u+2*a)+l;return n&&n.copy(this.direction).multiplyScalar(h).add(this.origin),i&&i.copy(Kb).multiplyScalar(u).add(Zb),d}intersectSphere(t,e){Jb.subVectors(t.center,this.origin);const n=Jb.dot(this.direction),i=Jb.dot(Jb)-n*n,s=t.radius*t.radius;if(i>s)return null;const r=Math.sqrt(s-i),o=n-r,a=n+r;return o<0&&a<0?null:o<0?this.at(a,e):this.at(o,e)}intersectsSphere(t){return this.distanceSqToPoint(t.center)<=t.radius*t.radius}distanceToPlane(t){const e=t.normal.dot(this.direction);if(0===e)return 0===t.distanceToPoint(this.origin)?0:null;const n=-(this.origin.dot(t.normal)+t.constant)/e;return n>=0?n:null}intersectPlane(t,e){const n=this.distanceToPlane(t);return null===n?null:this.at(n,e)}intersectsPlane(t){const e=t.distanceToPoint(this.origin);if(0===e)return!0;return t.normal.dot(this.direction)*e<0}intersectBox(t,e){let n,i,s,r,o,a;const l=1/this.direction.x,c=1/this.direction.y,h=1/this.direction.z,u=this.origin;return l>=0?(n=(t.min.x-u.x)*l,i=(t.max.x-u.x)*l):(n=(t.max.x-u.x)*l,i=(t.min.x-u.x)*l),c>=0?(s=(t.min.y-u.y)*c,r=(t.max.y-u.y)*c):(s=(t.max.y-u.y)*c,r=(t.min.y-u.y)*c),n>r||s>i?null:((s>n||n!=n)&&(n=s),(r=0?(o=(t.min.z-u.z)*h,a=(t.max.z-u.z)*h):(o=(t.max.z-u.z)*h,a=(t.min.z-u.z)*h),n>a||o>i?null:((o>n||n!=n)&&(n=o),(a=0?n:i,e)))}intersectsBox(t){return null!==this.intersectBox(t,Jb)}intersectTriangle(t,e,n,i,s){tw.subVectors(e,t),ew.subVectors(n,t),nw.crossVectors(tw,ew);let r,o=this.direction.dot(nw);if(o>0){if(i)return null;r=1}else{if(!(o<0))return null;r=-1,o=-o}Qb.subVectors(this.origin,t);const a=r*this.direction.dot(ew.crossVectors(Qb,ew));if(a<0)return null;const l=r*this.direction.dot(tw.cross(Qb));if(l<0)return null;if(a+l>o)return null;const c=-r*Qb.dot(nw);return c<0?null:this.at(c/o,s)}applyMatrix4(t){return this.origin.applyMatrix4(t),this.direction.transformDirection(t),this}equals(t){return t.origin.equals(this.origin)&&t.direction.equals(this.direction)}clone(){return(new this.constructor).copy(this)}}class sw{constructor(){this.elements=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1],arguments.length>0&&console.error(\\\\\\\"THREE.Matrix4: the constructor no longer reads arguments. use .set() instead.\\\\\\\")}set(t,e,n,i,s,r,o,a,l,c,h,u,d,p,_,m){const f=this.elements;return f[0]=t,f[4]=e,f[8]=n,f[12]=i,f[1]=s,f[5]=r,f[9]=o,f[13]=a,f[2]=l,f[6]=c,f[10]=h,f[14]=u,f[3]=d,f[7]=p,f[11]=_,f[15]=m,this}identity(){return this.set(1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1),this}clone(){return(new sw).fromArray(this.elements)}copy(t){const e=this.elements,n=t.elements;return e[0]=n[0],e[1]=n[1],e[2]=n[2],e[3]=n[3],e[4]=n[4],e[5]=n[5],e[6]=n[6],e[7]=n[7],e[8]=n[8],e[9]=n[9],e[10]=n[10],e[11]=n[11],e[12]=n[12],e[13]=n[13],e[14]=n[14],e[15]=n[15],this}copyPosition(t){const e=this.elements,n=t.elements;return e[12]=n[12],e[13]=n[13],e[14]=n[14],this}setFromMatrix3(t){const e=t.elements;return this.set(e[0],e[3],e[6],0,e[1],e[4],e[7],0,e[2],e[5],e[8],0,0,0,0,1),this}extractBasis(t,e,n){return t.setFromMatrixColumn(this,0),e.setFromMatrixColumn(this,1),n.setFromMatrixColumn(this,2),this}makeBasis(t,e,n){return this.set(t.x,e.x,n.x,0,t.y,e.y,n.y,0,t.z,e.z,n.z,0,0,0,0,1),this}extractRotation(t){const e=this.elements,n=t.elements,i=1/rw.setFromMatrixColumn(t,0).length(),s=1/rw.setFromMatrixColumn(t,1).length(),r=1/rw.setFromMatrixColumn(t,2).length();return e[0]=n[0]*i,e[1]=n[1]*i,e[2]=n[2]*i,e[3]=0,e[4]=n[4]*s,e[5]=n[5]*s,e[6]=n[6]*s,e[7]=0,e[8]=n[8]*r,e[9]=n[9]*r,e[10]=n[10]*r,e[11]=0,e[12]=0,e[13]=0,e[14]=0,e[15]=1,this}makeRotationFromEuler(t){t&&t.isEuler||console.error(\\\\\\\"THREE.Matrix4: .makeRotationFromEuler() now expects a Euler rotation rather than a Vector3 and order.\\\\\\\");const e=this.elements,n=t.x,i=t.y,s=t.z,r=Math.cos(n),o=Math.sin(n),a=Math.cos(i),l=Math.sin(i),c=Math.cos(s),h=Math.sin(s);if(\\\\\\\"XYZ\\\\\\\"===t.order){const t=r*c,n=r*h,i=o*c,s=o*h;e[0]=a*c,e[4]=-a*h,e[8]=l,e[1]=n+i*l,e[5]=t-s*l,e[9]=-o*a,e[2]=s-t*l,e[6]=i+n*l,e[10]=r*a}else if(\\\\\\\"YXZ\\\\\\\"===t.order){const t=a*c,n=a*h,i=l*c,s=l*h;e[0]=t+s*o,e[4]=i*o-n,e[8]=r*l,e[1]=r*h,e[5]=r*c,e[9]=-o,e[2]=n*o-i,e[6]=s+t*o,e[10]=r*a}else if(\\\\\\\"ZXY\\\\\\\"===t.order){const t=a*c,n=a*h,i=l*c,s=l*h;e[0]=t-s*o,e[4]=-r*h,e[8]=i+n*o,e[1]=n+i*o,e[5]=r*c,e[9]=s-t*o,e[2]=-r*l,e[6]=o,e[10]=r*a}else if(\\\\\\\"ZYX\\\\\\\"===t.order){const t=r*c,n=r*h,i=o*c,s=o*h;e[0]=a*c,e[4]=i*l-n,e[8]=t*l+s,e[1]=a*h,e[5]=s*l+t,e[9]=n*l-i,e[2]=-l,e[6]=o*a,e[10]=r*a}else if(\\\\\\\"YZX\\\\\\\"===t.order){const t=r*a,n=r*l,i=o*a,s=o*l;e[0]=a*c,e[4]=s-t*h,e[8]=i*h+n,e[1]=h,e[5]=r*c,e[9]=-o*c,e[2]=-l*c,e[6]=n*h+i,e[10]=t-s*h}else if(\\\\\\\"XZY\\\\\\\"===t.order){const t=r*a,n=r*l,i=o*a,s=o*l;e[0]=a*c,e[4]=-h,e[8]=l*c,e[1]=t*h+s,e[5]=r*c,e[9]=n*h-i,e[2]=i*h-n,e[6]=o*c,e[10]=s*h+t}return e[3]=0,e[7]=0,e[11]=0,e[12]=0,e[13]=0,e[14]=0,e[15]=1,this}makeRotationFromQuaternion(t){return this.compose(aw,t,lw)}lookAt(t,e,n){const i=this.elements;return uw.subVectors(t,e),0===uw.lengthSq()&&(uw.z=1),uw.normalize(),cw.crossVectors(n,uw),0===cw.lengthSq()&&(1===Math.abs(n.z)?uw.x+=1e-4:uw.z+=1e-4,uw.normalize(),cw.crossVectors(n,uw)),cw.normalize(),hw.crossVectors(uw,cw),i[0]=cw.x,i[4]=hw.x,i[8]=uw.x,i[1]=cw.y,i[5]=hw.y,i[9]=uw.y,i[2]=cw.z,i[6]=hw.z,i[10]=uw.z,this}multiply(t,e){return void 0!==e?(console.warn(\\\\\\\"THREE.Matrix4: .multiply() now only accepts one argument. Use .multiplyMatrices( a, b ) instead.\\\\\\\"),this.multiplyMatrices(t,e)):this.multiplyMatrices(this,t)}premultiply(t){return this.multiplyMatrices(t,this)}multiplyMatrices(t,e){const n=t.elements,i=e.elements,s=this.elements,r=n[0],o=n[4],a=n[8],l=n[12],c=n[1],h=n[5],u=n[9],d=n[13],p=n[2],_=n[6],m=n[10],f=n[14],g=n[3],v=n[7],y=n[11],x=n[15],b=i[0],w=i[4],T=i[8],A=i[12],M=i[1],E=i[5],S=i[9],C=i[13],N=i[2],L=i[6],O=i[10],P=i[14],R=i[3],I=i[7],F=i[11],D=i[15];return s[0]=r*b+o*M+a*N+l*R,s[4]=r*w+o*E+a*L+l*I,s[8]=r*T+o*S+a*O+l*F,s[12]=r*A+o*C+a*P+l*D,s[1]=c*b+h*M+u*N+d*R,s[5]=c*w+h*E+u*L+d*I,s[9]=c*T+h*S+u*O+d*F,s[13]=c*A+h*C+u*P+d*D,s[2]=p*b+_*M+m*N+f*R,s[6]=p*w+_*E+m*L+f*I,s[10]=p*T+_*S+m*O+f*F,s[14]=p*A+_*C+m*P+f*D,s[3]=g*b+v*M+y*N+x*R,s[7]=g*w+v*E+y*L+x*I,s[11]=g*T+v*S+y*O+x*F,s[15]=g*A+v*C+y*P+x*D,this}multiplyScalar(t){const e=this.elements;return e[0]*=t,e[4]*=t,e[8]*=t,e[12]*=t,e[1]*=t,e[5]*=t,e[9]*=t,e[13]*=t,e[2]*=t,e[6]*=t,e[10]*=t,e[14]*=t,e[3]*=t,e[7]*=t,e[11]*=t,e[15]*=t,this}determinant(){const t=this.elements,e=t[0],n=t[4],i=t[8],s=t[12],r=t[1],o=t[5],a=t[9],l=t[13],c=t[2],h=t[6],u=t[10],d=t[14];return t[3]*(+s*a*h-i*l*h-s*o*u+n*l*u+i*o*d-n*a*d)+t[7]*(+e*a*d-e*l*u+s*r*u-i*r*d+i*l*c-s*a*c)+t[11]*(+e*l*h-e*o*d-s*r*h+n*r*d+s*o*c-n*l*c)+t[15]*(-i*o*c-e*a*h+e*o*u+i*r*h-n*r*u+n*a*c)}transpose(){const t=this.elements;let e;return e=t[1],t[1]=t[4],t[4]=e,e=t[2],t[2]=t[8],t[8]=e,e=t[6],t[6]=t[9],t[9]=e,e=t[3],t[3]=t[12],t[12]=e,e=t[7],t[7]=t[13],t[13]=e,e=t[11],t[11]=t[14],t[14]=e,this}setPosition(t,e,n){const i=this.elements;return t.isVector3?(i[12]=t.x,i[13]=t.y,i[14]=t.z):(i[12]=t,i[13]=e,i[14]=n),this}invert(){const t=this.elements,e=t[0],n=t[1],i=t[2],s=t[3],r=t[4],o=t[5],a=t[6],l=t[7],c=t[8],h=t[9],u=t[10],d=t[11],p=t[12],_=t[13],m=t[14],f=t[15],g=h*m*l-_*u*l+_*a*d-o*m*d-h*a*f+o*u*f,v=p*u*l-c*m*l-p*a*d+r*m*d+c*a*f-r*u*f,y=c*_*l-p*h*l+p*o*d-r*_*d-c*o*f+r*h*f,x=p*h*a-c*_*a-p*o*u+r*_*u+c*o*m-r*h*m,b=e*g+n*v+i*y+s*x;if(0===b)return this.set(0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0);const w=1/b;return t[0]=g*w,t[1]=(_*u*s-h*m*s-_*i*d+n*m*d+h*i*f-n*u*f)*w,t[2]=(o*m*s-_*a*s+_*i*l-n*m*l-o*i*f+n*a*f)*w,t[3]=(h*a*s-o*u*s-h*i*l+n*u*l+o*i*d-n*a*d)*w,t[4]=v*w,t[5]=(c*m*s-p*u*s+p*i*d-e*m*d-c*i*f+e*u*f)*w,t[6]=(p*a*s-r*m*s-p*i*l+e*m*l+r*i*f-e*a*f)*w,t[7]=(r*u*s-c*a*s+c*i*l-e*u*l-r*i*d+e*a*d)*w,t[8]=y*w,t[9]=(p*h*s-c*_*s-p*n*d+e*_*d+c*n*f-e*h*f)*w,t[10]=(r*_*s-p*o*s+p*n*l-e*_*l-r*n*f+e*o*f)*w,t[11]=(c*o*s-r*h*s-c*n*l+e*h*l+r*n*d-e*o*d)*w,t[12]=x*w,t[13]=(c*_*i-p*h*i+p*n*u-e*_*u-c*n*m+e*h*m)*w,t[14]=(p*o*i-r*_*i-p*n*a+e*_*a+r*n*m-e*o*m)*w,t[15]=(r*h*i-c*o*i+c*n*a-e*h*a-r*n*u+e*o*u)*w,this}scale(t){const e=this.elements,n=t.x,i=t.y,s=t.z;return e[0]*=n,e[4]*=i,e[8]*=s,e[1]*=n,e[5]*=i,e[9]*=s,e[2]*=n,e[6]*=i,e[10]*=s,e[3]*=n,e[7]*=i,e[11]*=s,this}getMaxScaleOnAxis(){const t=this.elements,e=t[0]*t[0]+t[1]*t[1]+t[2]*t[2],n=t[4]*t[4]+t[5]*t[5]+t[6]*t[6],i=t[8]*t[8]+t[9]*t[9]+t[10]*t[10];return Math.sqrt(Math.max(e,n,i))}makeTranslation(t,e,n){return this.set(1,0,0,t,0,1,0,e,0,0,1,n,0,0,0,1),this}makeRotationX(t){const e=Math.cos(t),n=Math.sin(t);return this.set(1,0,0,0,0,e,-n,0,0,n,e,0,0,0,0,1),this}makeRotationY(t){const e=Math.cos(t),n=Math.sin(t);return this.set(e,0,n,0,0,1,0,0,-n,0,e,0,0,0,0,1),this}makeRotationZ(t){const e=Math.cos(t),n=Math.sin(t);return this.set(e,-n,0,0,n,e,0,0,0,0,1,0,0,0,0,1),this}makeRotationAxis(t,e){const n=Math.cos(e),i=Math.sin(e),s=1-n,r=t.x,o=t.y,a=t.z,l=s*r,c=s*o;return this.set(l*r+n,l*o-i*a,l*a+i*o,0,l*o+i*a,c*o+n,c*a-i*r,0,l*a-i*o,c*a+i*r,s*a*a+n,0,0,0,0,1),this}makeScale(t,e,n){return this.set(t,0,0,0,0,e,0,0,0,0,n,0,0,0,0,1),this}makeShear(t,e,n,i,s,r){return this.set(1,n,s,0,t,1,r,0,e,i,1,0,0,0,0,1),this}compose(t,e,n){const i=this.elements,s=e._x,r=e._y,o=e._z,a=e._w,l=s+s,c=r+r,h=o+o,u=s*l,d=s*c,p=s*h,_=r*c,m=r*h,f=o*h,g=a*l,v=a*c,y=a*h,x=n.x,b=n.y,w=n.z;return i[0]=(1-(_+f))*x,i[1]=(d+y)*x,i[2]=(p-v)*x,i[3]=0,i[4]=(d-y)*b,i[5]=(1-(u+f))*b,i[6]=(m+g)*b,i[7]=0,i[8]=(p+v)*w,i[9]=(m-g)*w,i[10]=(1-(u+_))*w,i[11]=0,i[12]=t.x,i[13]=t.y,i[14]=t.z,i[15]=1,this}decompose(t,e,n){const i=this.elements;let s=rw.set(i[0],i[1],i[2]).length();const r=rw.set(i[4],i[5],i[6]).length(),o=rw.set(i[8],i[9],i[10]).length();this.determinant()<0&&(s=-s),t.x=i[12],t.y=i[13],t.z=i[14],ow.copy(this);const a=1/s,l=1/r,c=1/o;return ow.elements[0]*=a,ow.elements[1]*=a,ow.elements[2]*=a,ow.elements[4]*=l,ow.elements[5]*=l,ow.elements[6]*=l,ow.elements[8]*=c,ow.elements[9]*=c,ow.elements[10]*=c,e.setFromRotationMatrix(ow),n.x=s,n.y=r,n.z=o,this}makePerspective(t,e,n,i,s,r){void 0===r&&console.warn(\\\\\\\"THREE.Matrix4: .makePerspective() has been redefined and has a new signature. Please check the docs.\\\\\\\");const o=this.elements,a=2*s/(e-t),l=2*s/(n-i),c=(e+t)/(e-t),h=(n+i)/(n-i),u=-(r+s)/(r-s),d=-2*r*s/(r-s);return o[0]=a,o[4]=0,o[8]=c,o[12]=0,o[1]=0,o[5]=l,o[9]=h,o[13]=0,o[2]=0,o[6]=0,o[10]=u,o[14]=d,o[3]=0,o[7]=0,o[11]=-1,o[15]=0,this}makeOrthographic(t,e,n,i,s,r){const o=this.elements,a=1/(e-t),l=1/(n-i),c=1/(r-s),h=(e+t)*a,u=(n+i)*l,d=(r+s)*c;return o[0]=2*a,o[4]=0,o[8]=0,o[12]=-h,o[1]=0,o[5]=2*l,o[9]=0,o[13]=-u,o[2]=0,o[6]=0,o[10]=-2*c,o[14]=-d,o[3]=0,o[7]=0,o[11]=0,o[15]=1,this}equals(t){const e=this.elements,n=t.elements;for(let t=0;t<16;t++)if(e[t]!==n[t])return!1;return!0}fromArray(t,e=0){for(let n=0;n<16;n++)this.elements[n]=t[n+e];return this}toArray(t=[],e=0){const n=this.elements;return t[e]=n[0],t[e+1]=n[1],t[e+2]=n[2],t[e+3]=n[3],t[e+4]=n[4],t[e+5]=n[5],t[e+6]=n[6],t[e+7]=n[7],t[e+8]=n[8],t[e+9]=n[9],t[e+10]=n[10],t[e+11]=n[11],t[e+12]=n[12],t[e+13]=n[13],t[e+14]=n[14],t[e+15]=n[15],t}}sw.prototype.isMatrix4=!0;const rw=new Sb,ow=new sw,aw=new Sb(0,0,0),lw=new Sb(1,1,1),cw=new Sb,hw=new Sb,uw=new Sb,dw=new sw,pw=new Eb;class _w{constructor(t=0,e=0,n=0,i=_w.DefaultOrder){this._x=t,this._y=e,this._z=n,this._order=i}get x(){return this._x}set x(t){this._x=t,this._onChangeCallback()}get y(){return this._y}set y(t){this._y=t,this._onChangeCallback()}get z(){return this._z}set z(t){this._z=t,this._onChangeCallback()}get order(){return this._order}set order(t){this._order=t,this._onChangeCallback()}set(t,e,n,i=this._order){return this._x=t,this._y=e,this._z=n,this._order=i,this._onChangeCallback(),this}clone(){return new this.constructor(this._x,this._y,this._z,this._order)}copy(t){return this._x=t._x,this._y=t._y,this._z=t._z,this._order=t._order,this._onChangeCallback(),this}setFromRotationMatrix(t,e=this._order,n=!0){const i=t.elements,s=i[0],r=i[4],o=i[8],a=i[1],l=i[5],c=i[9],h=i[2],u=i[6],d=i[10];switch(e){case\\\\\\\"XYZ\\\\\\\":this._y=Math.asin(ab(o,-1,1)),Math.abs(o)<.9999999?(this._x=Math.atan2(-c,d),this._z=Math.atan2(-r,s)):(this._x=Math.atan2(u,l),this._z=0);break;case\\\\\\\"YXZ\\\\\\\":this._x=Math.asin(-ab(c,-1,1)),Math.abs(c)<.9999999?(this._y=Math.atan2(o,d),this._z=Math.atan2(a,l)):(this._y=Math.atan2(-h,s),this._z=0);break;case\\\\\\\"ZXY\\\\\\\":this._x=Math.asin(ab(u,-1,1)),Math.abs(u)<.9999999?(this._y=Math.atan2(-h,d),this._z=Math.atan2(-r,l)):(this._y=0,this._z=Math.atan2(a,s));break;case\\\\\\\"ZYX\\\\\\\":this._y=Math.asin(-ab(h,-1,1)),Math.abs(h)<.9999999?(this._x=Math.atan2(u,d),this._z=Math.atan2(a,s)):(this._x=0,this._z=Math.atan2(-r,l));break;case\\\\\\\"YZX\\\\\\\":this._z=Math.asin(ab(a,-1,1)),Math.abs(a)<.9999999?(this._x=Math.atan2(-c,l),this._y=Math.atan2(-h,s)):(this._x=0,this._y=Math.atan2(o,d));break;case\\\\\\\"XZY\\\\\\\":this._z=Math.asin(-ab(r,-1,1)),Math.abs(r)<.9999999?(this._x=Math.atan2(u,l),this._y=Math.atan2(o,s)):(this._x=Math.atan2(-c,d),this._y=0);break;default:console.warn(\\\\\\\"THREE.Euler: .setFromRotationMatrix() encountered an unknown order: \\\\\\\"+e)}return this._order=e,!0===n&&this._onChangeCallback(),this}setFromQuaternion(t,e,n){return dw.makeRotationFromQuaternion(t),this.setFromRotationMatrix(dw,e,n)}setFromVector3(t,e=this._order){return this.set(t.x,t.y,t.z,e)}reorder(t){return pw.setFromEuler(this),this.setFromQuaternion(pw,t)}equals(t){return t._x===this._x&&t._y===this._y&&t._z===this._z&&t._order===this._order}fromArray(t){return this._x=t[0],this._y=t[1],this._z=t[2],void 0!==t[3]&&(this._order=t[3]),this._onChangeCallback(),this}toArray(t=[],e=0){return t[e]=this._x,t[e+1]=this._y,t[e+2]=this._z,t[e+3]=this._order,t}toVector3(t){return t?t.set(this._x,this._y,this._z):new Sb(this._x,this._y,this._z)}_onChange(t){return this._onChangeCallback=t,this}_onChangeCallback(){}}_w.prototype.isEuler=!0,_w.DefaultOrder=\\\\\\\"XYZ\\\\\\\",_w.RotationOrders=[\\\\\\\"XYZ\\\\\\\",\\\\\\\"YZX\\\\\\\",\\\\\\\"ZXY\\\\\\\",\\\\\\\"XZY\\\\\\\",\\\\\\\"YXZ\\\\\\\",\\\\\\\"ZYX\\\\\\\"];class mw{constructor(){this.mask=1}set(t){this.mask=1<1){for(let t=0;t1){for(let t=0;t0){i.children=[];for(let e=0;e0){i.animations=[];for(let e=0;e0&&(n.geometries=e),i.length>0&&(n.materials=i),s.length>0&&(n.textures=s),o.length>0&&(n.images=o),a.length>0&&(n.shapes=a),l.length>0&&(n.skeletons=l),c.length>0&&(n.animations=c)}return n.object=i,n;function r(t){const e=[];for(const n in t){const i=t[n];delete i.metadata,e.push(i)}return e}}clone(t){return(new this.constructor).copy(this,t)}copy(t,e=!0){if(this.name=t.name,this.up.copy(t.up),this.position.copy(t.position),this.rotation.order=t.rotation.order,this.quaternion.copy(t.quaternion),this.scale.copy(t.scale),this.matrix.copy(t.matrix),this.matrixWorld.copy(t.matrixWorld),this.matrixAutoUpdate=t.matrixAutoUpdate,this.matrixWorldNeedsUpdate=t.matrixWorldNeedsUpdate,this.layers.mask=t.layers.mask,this.visible=t.visible,this.castShadow=t.castShadow,this.receiveShadow=t.receiveShadow,this.frustumCulled=t.frustumCulled,this.renderOrder=t.renderOrder,this.userData=JSON.parse(JSON.stringify(t.userData)),!0===e)for(let e=0;e0?i.multiplyScalar(1/Math.sqrt(s)):i.set(0,0,0)}static getBarycoord(t,e,n,i,s){Lw.subVectors(i,e),Ow.subVectors(n,e),Pw.subVectors(t,e);const r=Lw.dot(Lw),o=Lw.dot(Ow),a=Lw.dot(Pw),l=Ow.dot(Ow),c=Ow.dot(Pw),h=r*l-o*o;if(0===h)return s.set(-2,-1,-1);const u=1/h,d=(l*a-o*c)*u,p=(r*c-o*a)*u;return s.set(1-d-p,p,d)}static containsPoint(t,e,n,i){return this.getBarycoord(t,e,n,i,Rw),Rw.x>=0&&Rw.y>=0&&Rw.x+Rw.y<=1}static getUV(t,e,n,i,s,r,o,a){return this.getBarycoord(t,e,n,i,Rw),a.set(0,0),a.addScaledVector(s,Rw.x),a.addScaledVector(r,Rw.y),a.addScaledVector(o,Rw.z),a}static isFrontFacing(t,e,n,i){return Lw.subVectors(n,e),Ow.subVectors(t,e),Lw.cross(Ow).dot(i)<0}set(t,e,n){return this.a.copy(t),this.b.copy(e),this.c.copy(n),this}setFromPointsAndIndices(t,e,n,i){return this.a.copy(t[e]),this.b.copy(t[n]),this.c.copy(t[i]),this}setFromAttributeAndIndices(t,e,n,i){return this.a.fromBufferAttribute(t,e),this.b.fromBufferAttribute(t,n),this.c.fromBufferAttribute(t,i),this}clone(){return(new this.constructor).copy(this)}copy(t){return this.a.copy(t.a),this.b.copy(t.b),this.c.copy(t.c),this}getArea(){return Lw.subVectors(this.c,this.b),Ow.subVectors(this.a,this.b),.5*Lw.cross(Ow).length()}getMidpoint(t){return t.addVectors(this.a,this.b).add(this.c).multiplyScalar(1/3)}getNormal(t){return Uw.getNormal(this.a,this.b,this.c,t)}getPlane(t){return t.setFromCoplanarPoints(this.a,this.b,this.c)}getBarycoord(t,e){return Uw.getBarycoord(t,this.a,this.b,this.c,e)}getUV(t,e,n,i,s){return Uw.getUV(t,this.a,this.b,this.c,e,n,i,s)}containsPoint(t){return Uw.containsPoint(t,this.a,this.b,this.c)}isFrontFacing(t){return Uw.isFrontFacing(this.a,this.b,this.c,t)}intersectsBox(t){return t.intersectsTriangle(this)}closestPointToPoint(t,e){const n=this.a,i=this.b,s=this.c;let r,o;Iw.subVectors(i,n),Fw.subVectors(s,n),Bw.subVectors(t,n);const a=Iw.dot(Bw),l=Fw.dot(Bw);if(a<=0&&l<=0)return e.copy(n);zw.subVectors(t,i);const c=Iw.dot(zw),h=Fw.dot(zw);if(c>=0&&h<=c)return e.copy(i);const u=a*h-c*l;if(u<=0&&a>=0&&c<=0)return r=a/(a-c),e.copy(n).addScaledVector(Iw,r);kw.subVectors(t,s);const d=Iw.dot(kw),p=Fw.dot(kw);if(p>=0&&d<=p)return e.copy(s);const _=d*l-a*p;if(_<=0&&l>=0&&p<=0)return o=l/(l-p),e.copy(n).addScaledVector(Fw,o);const m=c*p-d*h;if(m<=0&&h-c>=0&&d-p>=0)return Dw.subVectors(s,i),o=(h-c)/(h-c+(d-p)),e.copy(i).addScaledVector(Dw,o);const f=1/(m+_+u);return r=_*f,o=u*f,e.copy(n).addScaledVector(Iw,r).addScaledVector(Fw,o)}equals(t){return t.a.equals(this.a)&&t.b.equals(this.b)&&t.c.equals(this.c)}}let Gw=0;class Vw extends tb{constructor(){super(),Object.defineProperty(this,\\\\\\\"id\\\\\\\",{value:Gw++}),this.uuid=ob(),this.name=\\\\\\\"\\\\\\\",this.type=\\\\\\\"Material\\\\\\\",this.fog=!0,this.blending=1,this.side=0,this.vertexColors=!1,this.opacity=1,this.format=Dx,this.transparent=!1,this.blendSrc=204,this.blendDst=205,this.blendEquation=px,this.blendSrcAlpha=null,this.blendDstAlpha=null,this.blendEquationAlpha=null,this.depthFunc=3,this.depthTest=!0,this.depthWrite=!0,this.stencilWriteMask=255,this.stencilFunc=519,this.stencilRef=0,this.stencilFuncMask=255,this.stencilFail=Jx,this.stencilZFail=Jx,this.stencilZPass=Jx,this.stencilWrite=!1,this.clippingPlanes=null,this.clipIntersection=!1,this.clipShadows=!1,this.shadowSide=null,this.colorWrite=!0,this.precision=null,this.polygonOffset=!1,this.polygonOffsetFactor=0,this.polygonOffsetUnits=0,this.dithering=!1,this.alphaToCoverage=!1,this.premultipliedAlpha=!1,this.visible=!0,this.toneMapped=!0,this.userData={},this.version=0,this._alphaTest=0}get alphaTest(){return this._alphaTest}set alphaTest(t){this._alphaTest>0!=t>0&&this.version++,this._alphaTest=t}onBuild(){}onBeforeRender(){}onBeforeCompile(){}customProgramCacheKey(){return this.onBeforeCompile.toString()}setValues(t){if(void 0!==t)for(const e in t){const n=t[e];if(void 0===n){console.warn(\\\\\\\"THREE.Material: '\\\\\\\"+e+\\\\\\\"' parameter is undefined.\\\\\\\");continue}if(\\\\\\\"shading\\\\\\\"===e){console.warn(\\\\\\\"THREE.\\\\\\\"+this.type+\\\\\\\": .shading has been removed. Use the boolean .flatShading instead.\\\\\\\"),this.flatShading=1===n;continue}const i=this[e];void 0!==i?i&&i.isColor?i.set(n):i&&i.isVector3&&n&&n.isVector3?i.copy(n):this[e]=n:console.warn(\\\\\\\"THREE.\\\\\\\"+this.type+\\\\\\\": '\\\\\\\"+e+\\\\\\\"' is not a property of this material.\\\\\\\")}}toJSON(t){const e=void 0===t||\\\\\\\"string\\\\\\\"==typeof t;e&&(t={textures:{},images:{}});const n={metadata:{version:4.5,type:\\\\\\\"Material\\\\\\\",generator:\\\\\\\"Material.toJSON\\\\\\\"}};function i(t){const e=[];for(const n in t){const i=t[n];delete i.metadata,e.push(i)}return e}if(n.uuid=this.uuid,n.type=this.type,\\\\\\\"\\\\\\\"!==this.name&&(n.name=this.name),this.color&&this.color.isColor&&(n.color=this.color.getHex()),void 0!==this.roughness&&(n.roughness=this.roughness),void 0!==this.metalness&&(n.metalness=this.metalness),void 0!==this.sheen&&(n.sheen=this.sheen),this.sheenTint&&this.sheenTint.isColor&&(n.sheenTint=this.sheenTint.getHex()),void 0!==this.sheenRoughness&&(n.sheenRoughness=this.sheenRoughness),this.emissive&&this.emissive.isColor&&(n.emissive=this.emissive.getHex()),this.emissiveIntensity&&1!==this.emissiveIntensity&&(n.emissiveIntensity=this.emissiveIntensity),this.specular&&this.specular.isColor&&(n.specular=this.specular.getHex()),void 0!==this.specularIntensity&&(n.specularIntensity=this.specularIntensity),this.specularTint&&this.specularTint.isColor&&(n.specularTint=this.specularTint.getHex()),void 0!==this.shininess&&(n.shininess=this.shininess),void 0!==this.clearcoat&&(n.clearcoat=this.clearcoat),void 0!==this.clearcoatRoughness&&(n.clearcoatRoughness=this.clearcoatRoughness),this.clearcoatMap&&this.clearcoatMap.isTexture&&(n.clearcoatMap=this.clearcoatMap.toJSON(t).uuid),this.clearcoatRoughnessMap&&this.clearcoatRoughnessMap.isTexture&&(n.clearcoatRoughnessMap=this.clearcoatRoughnessMap.toJSON(t).uuid),this.clearcoatNormalMap&&this.clearcoatNormalMap.isTexture&&(n.clearcoatNormalMap=this.clearcoatNormalMap.toJSON(t).uuid,n.clearcoatNormalScale=this.clearcoatNormalScale.toArray()),this.map&&this.map.isTexture&&(n.map=this.map.toJSON(t).uuid),this.matcap&&this.matcap.isTexture&&(n.matcap=this.matcap.toJSON(t).uuid),this.alphaMap&&this.alphaMap.isTexture&&(n.alphaMap=this.alphaMap.toJSON(t).uuid),this.lightMap&&this.lightMap.isTexture&&(n.lightMap=this.lightMap.toJSON(t).uuid,n.lightMapIntensity=this.lightMapIntensity),this.aoMap&&this.aoMap.isTexture&&(n.aoMap=this.aoMap.toJSON(t).uuid,n.aoMapIntensity=this.aoMapIntensity),this.bumpMap&&this.bumpMap.isTexture&&(n.bumpMap=this.bumpMap.toJSON(t).uuid,n.bumpScale=this.bumpScale),this.normalMap&&this.normalMap.isTexture&&(n.normalMap=this.normalMap.toJSON(t).uuid,n.normalMapType=this.normalMapType,n.normalScale=this.normalScale.toArray()),this.displacementMap&&this.displacementMap.isTexture&&(n.displacementMap=this.displacementMap.toJSON(t).uuid,n.displacementScale=this.displacementScale,n.displacementBias=this.displacementBias),this.roughnessMap&&this.roughnessMap.isTexture&&(n.roughnessMap=this.roughnessMap.toJSON(t).uuid),this.metalnessMap&&this.metalnessMap.isTexture&&(n.metalnessMap=this.metalnessMap.toJSON(t).uuid),this.emissiveMap&&this.emissiveMap.isTexture&&(n.emissiveMap=this.emissiveMap.toJSON(t).uuid),this.specularMap&&this.specularMap.isTexture&&(n.specularMap=this.specularMap.toJSON(t).uuid),this.specularIntensityMap&&this.specularIntensityMap.isTexture&&(n.specularIntensityMap=this.specularIntensityMap.toJSON(t).uuid),this.specularTintMap&&this.specularTintMap.isTexture&&(n.specularTintMap=this.specularTintMap.toJSON(t).uuid),this.envMap&&this.envMap.isTexture&&(n.envMap=this.envMap.toJSON(t).uuid,void 0!==this.combine&&(n.combine=this.combine)),void 0!==this.envMapIntensity&&(n.envMapIntensity=this.envMapIntensity),void 0!==this.reflectivity&&(n.reflectivity=this.reflectivity),void 0!==this.refractionRatio&&(n.refractionRatio=this.refractionRatio),this.gradientMap&&this.gradientMap.isTexture&&(n.gradientMap=this.gradientMap.toJSON(t).uuid),void 0!==this.transmission&&(n.transmission=this.transmission),this.transmissionMap&&this.transmissionMap.isTexture&&(n.transmissionMap=this.transmissionMap.toJSON(t).uuid),void 0!==this.thickness&&(n.thickness=this.thickness),this.thicknessMap&&this.thicknessMap.isTexture&&(n.thicknessMap=this.thicknessMap.toJSON(t).uuid),void 0!==this.attenuationDistance&&(n.attenuationDistance=this.attenuationDistance),void 0!==this.attenuationTint&&(n.attenuationTint=this.attenuationTint.getHex()),void 0!==this.size&&(n.size=this.size),null!==this.shadowSide&&(n.shadowSide=this.shadowSide),void 0!==this.sizeAttenuation&&(n.sizeAttenuation=this.sizeAttenuation),1!==this.blending&&(n.blending=this.blending),0!==this.side&&(n.side=this.side),this.vertexColors&&(n.vertexColors=!0),this.opacity<1&&(n.opacity=this.opacity),this.format!==Dx&&(n.format=this.format),!0===this.transparent&&(n.transparent=this.transparent),n.depthFunc=this.depthFunc,n.depthTest=this.depthTest,n.depthWrite=this.depthWrite,n.colorWrite=this.colorWrite,n.stencilWrite=this.stencilWrite,n.stencilWriteMask=this.stencilWriteMask,n.stencilFunc=this.stencilFunc,n.stencilRef=this.stencilRef,n.stencilFuncMask=this.stencilFuncMask,n.stencilFail=this.stencilFail,n.stencilZFail=this.stencilZFail,n.stencilZPass=this.stencilZPass,this.rotation&&0!==this.rotation&&(n.rotation=this.rotation),!0===this.polygonOffset&&(n.polygonOffset=!0),0!==this.polygonOffsetFactor&&(n.polygonOffsetFactor=this.polygonOffsetFactor),0!==this.polygonOffsetUnits&&(n.polygonOffsetUnits=this.polygonOffsetUnits),this.linewidth&&1!==this.linewidth&&(n.linewidth=this.linewidth),void 0!==this.dashSize&&(n.dashSize=this.dashSize),void 0!==this.gapSize&&(n.gapSize=this.gapSize),void 0!==this.scale&&(n.scale=this.scale),!0===this.dithering&&(n.dithering=!0),this.alphaTest>0&&(n.alphaTest=this.alphaTest),!0===this.alphaToCoverage&&(n.alphaToCoverage=this.alphaToCoverage),!0===this.premultipliedAlpha&&(n.premultipliedAlpha=this.premultipliedAlpha),!0===this.wireframe&&(n.wireframe=this.wireframe),this.wireframeLinewidth>1&&(n.wireframeLinewidth=this.wireframeLinewidth),\\\\\\\"round\\\\\\\"!==this.wireframeLinecap&&(n.wireframeLinecap=this.wireframeLinecap),\\\\\\\"round\\\\\\\"!==this.wireframeLinejoin&&(n.wireframeLinejoin=this.wireframeLinejoin),!0===this.flatShading&&(n.flatShading=this.flatShading),!1===this.visible&&(n.visible=!1),!1===this.toneMapped&&(n.toneMapped=!1),\\\\\\\"{}\\\\\\\"!==JSON.stringify(this.userData)&&(n.userData=this.userData),e){const e=i(t.textures),s=i(t.images);e.length>0&&(n.textures=e),s.length>0&&(n.images=s)}return n}clone(){return(new this.constructor).copy(this)}copy(t){this.name=t.name,this.fog=t.fog,this.blending=t.blending,this.side=t.side,this.vertexColors=t.vertexColors,this.opacity=t.opacity,this.format=t.format,this.transparent=t.transparent,this.blendSrc=t.blendSrc,this.blendDst=t.blendDst,this.blendEquation=t.blendEquation,this.blendSrcAlpha=t.blendSrcAlpha,this.blendDstAlpha=t.blendDstAlpha,this.blendEquationAlpha=t.blendEquationAlpha,this.depthFunc=t.depthFunc,this.depthTest=t.depthTest,this.depthWrite=t.depthWrite,this.stencilWriteMask=t.stencilWriteMask,this.stencilFunc=t.stencilFunc,this.stencilRef=t.stencilRef,this.stencilFuncMask=t.stencilFuncMask,this.stencilFail=t.stencilFail,this.stencilZFail=t.stencilZFail,this.stencilZPass=t.stencilZPass,this.stencilWrite=t.stencilWrite;const e=t.clippingPlanes;let n=null;if(null!==e){const t=e.length;n=new Array(t);for(let i=0;i!==t;++i)n[i]=e[i].clone()}return this.clippingPlanes=n,this.clipIntersection=t.clipIntersection,this.clipShadows=t.clipShadows,this.shadowSide=t.shadowSide,this.colorWrite=t.colorWrite,this.precision=t.precision,this.polygonOffset=t.polygonOffset,this.polygonOffsetFactor=t.polygonOffsetFactor,this.polygonOffsetUnits=t.polygonOffsetUnits,this.dithering=t.dithering,this.alphaTest=t.alphaTest,this.alphaToCoverage=t.alphaToCoverage,this.premultipliedAlpha=t.premultipliedAlpha,this.visible=t.visible,this.toneMapped=t.toneMapped,this.userData=JSON.parse(JSON.stringify(t.userData)),this}dispose(){this.dispatchEvent({type:\\\\\\\"dispose\\\\\\\"})}set needsUpdate(t){!0===t&&this.version++}}Vw.prototype.isMaterial=!0;const Hw={aliceblue:15792383,antiquewhite:16444375,aqua:65535,aquamarine:8388564,azure:15794175,beige:16119260,bisque:16770244,black:0,blanchedalmond:16772045,blue:255,blueviolet:9055202,brown:10824234,burlywood:14596231,cadetblue:6266528,chartreuse:8388352,chocolate:13789470,coral:16744272,cornflowerblue:6591981,cornsilk:16775388,crimson:14423100,cyan:65535,darkblue:139,darkcyan:35723,darkgoldenrod:12092939,darkgray:11119017,darkgreen:25600,darkgrey:11119017,darkkhaki:12433259,darkmagenta:9109643,darkolivegreen:5597999,darkorange:16747520,darkorchid:10040012,darkred:9109504,darksalmon:15308410,darkseagreen:9419919,darkslateblue:4734347,darkslategray:3100495,darkslategrey:3100495,darkturquoise:52945,darkviolet:9699539,deeppink:16716947,deepskyblue:49151,dimgray:6908265,dimgrey:6908265,dodgerblue:2003199,firebrick:11674146,floralwhite:16775920,forestgreen:2263842,fuchsia:16711935,gainsboro:14474460,ghostwhite:16316671,gold:16766720,goldenrod:14329120,gray:8421504,green:32768,greenyellow:11403055,grey:8421504,honeydew:15794160,hotpink:16738740,indianred:13458524,indigo:4915330,ivory:16777200,khaki:15787660,lavender:15132410,lavenderblush:16773365,lawngreen:8190976,lemonchiffon:16775885,lightblue:11393254,lightcoral:15761536,lightcyan:14745599,lightgoldenrodyellow:16448210,lightgray:13882323,lightgreen:9498256,lightgrey:13882323,lightpink:16758465,lightsalmon:16752762,lightseagreen:2142890,lightskyblue:8900346,lightslategray:7833753,lightslategrey:7833753,lightsteelblue:11584734,lightyellow:16777184,lime:65280,limegreen:3329330,linen:16445670,magenta:16711935,maroon:8388608,mediumaquamarine:6737322,mediumblue:205,mediumorchid:12211667,mediumpurple:9662683,mediumseagreen:3978097,mediumslateblue:8087790,mediumspringgreen:64154,mediumturquoise:4772300,mediumvioletred:13047173,midnightblue:1644912,mintcream:16121850,mistyrose:16770273,moccasin:16770229,navajowhite:16768685,navy:128,oldlace:16643558,olive:8421376,olivedrab:7048739,orange:16753920,orangered:16729344,orchid:14315734,palegoldenrod:15657130,palegreen:10025880,paleturquoise:11529966,palevioletred:14381203,papayawhip:16773077,peachpuff:16767673,peru:13468991,pink:16761035,plum:14524637,powderblue:11591910,purple:8388736,rebeccapurple:6697881,red:16711680,rosybrown:12357519,royalblue:4286945,saddlebrown:9127187,salmon:16416882,sandybrown:16032864,seagreen:3050327,seashell:16774638,sienna:10506797,silver:12632256,skyblue:8900331,slateblue:6970061,slategray:7372944,slategrey:7372944,snow:16775930,springgreen:65407,steelblue:4620980,tan:13808780,teal:32896,thistle:14204888,tomato:16737095,turquoise:4251856,violet:15631086,wheat:16113331,white:16777215,whitesmoke:16119285,yellow:16776960,yellowgreen:10145074},jw={h:0,s:0,l:0},Ww={h:0,s:0,l:0};function qw(t,e,n){return n<0&&(n+=1),n>1&&(n-=1),n<1/6?t+6*(e-t)*n:n<.5?e:n<2/3?t+6*(e-t)*(2/3-n):t}function Xw(t){return t<.04045?.0773993808*t:Math.pow(.9478672986*t+.0521327014,2.4)}function Yw(t){return t<.0031308?12.92*t:1.055*Math.pow(t,.41666)-.055}class $w{constructor(t,e,n){return void 0===e&&void 0===n?this.set(t):this.setRGB(t,e,n)}set(t){return t&&t.isColor?this.copy(t):\\\\\\\"number\\\\\\\"==typeof t?this.setHex(t):\\\\\\\"string\\\\\\\"==typeof t&&this.setStyle(t),this}setScalar(t){return this.r=t,this.g=t,this.b=t,this}setHex(t){return t=Math.floor(t),this.r=(t>>16&255)/255,this.g=(t>>8&255)/255,this.b=(255&t)/255,this}setRGB(t,e,n){return this.r=t,this.g=e,this.b=n,this}setHSL(t,e,n){if(t=lb(t,1),e=ab(e,0,1),n=ab(n,0,1),0===e)this.r=this.g=this.b=n;else{const i=n<=.5?n*(1+e):n+e-n*e,s=2*n-i;this.r=qw(s,i,t+1/3),this.g=qw(s,i,t),this.b=qw(s,i,t-1/3)}return this}setStyle(t){function e(e){void 0!==e&&parseFloat(e)<1&&console.warn(\\\\\\\"THREE.Color: Alpha component of \\\\\\\"+t+\\\\\\\" will be ignored.\\\\\\\")}let n;if(n=/^((?:rgb|hsl)a?)\\\\(([^\\\\)]*)\\\\)/.exec(t)){let t;const i=n[1],s=n[2];switch(i){case\\\\\\\"rgb\\\\\\\":case\\\\\\\"rgba\\\\\\\":if(t=/^\\\\s*(\\\\d+)\\\\s*,\\\\s*(\\\\d+)\\\\s*,\\\\s*(\\\\d+)\\\\s*(?:,\\\\s*(\\\\d*\\\\.?\\\\d+)\\\\s*)?$/.exec(s))return this.r=Math.min(255,parseInt(t[1],10))/255,this.g=Math.min(255,parseInt(t[2],10))/255,this.b=Math.min(255,parseInt(t[3],10))/255,e(t[4]),this;if(t=/^\\\\s*(\\\\d+)\\\\%\\\\s*,\\\\s*(\\\\d+)\\\\%\\\\s*,\\\\s*(\\\\d+)\\\\%\\\\s*(?:,\\\\s*(\\\\d*\\\\.?\\\\d+)\\\\s*)?$/.exec(s))return this.r=Math.min(100,parseInt(t[1],10))/100,this.g=Math.min(100,parseInt(t[2],10))/100,this.b=Math.min(100,parseInt(t[3],10))/100,e(t[4]),this;break;case\\\\\\\"hsl\\\\\\\":case\\\\\\\"hsla\\\\\\\":if(t=/^\\\\s*(\\\\d*\\\\.?\\\\d+)\\\\s*,\\\\s*(\\\\d+)\\\\%\\\\s*,\\\\s*(\\\\d+)\\\\%\\\\s*(?:,\\\\s*(\\\\d*\\\\.?\\\\d+)\\\\s*)?$/.exec(s)){const n=parseFloat(t[1])/360,i=parseInt(t[2],10)/100,s=parseInt(t[3],10)/100;return e(t[4]),this.setHSL(n,i,s)}}}else if(n=/^\\\\#([A-Fa-f\\\\d]+)$/.exec(t)){const t=n[1],e=t.length;if(3===e)return this.r=parseInt(t.charAt(0)+t.charAt(0),16)/255,this.g=parseInt(t.charAt(1)+t.charAt(1),16)/255,this.b=parseInt(t.charAt(2)+t.charAt(2),16)/255,this;if(6===e)return this.r=parseInt(t.charAt(0)+t.charAt(1),16)/255,this.g=parseInt(t.charAt(2)+t.charAt(3),16)/255,this.b=parseInt(t.charAt(4)+t.charAt(5),16)/255,this}return t&&t.length>0?this.setColorName(t):this}setColorName(t){const e=Hw[t.toLowerCase()];return void 0!==e?this.setHex(e):console.warn(\\\\\\\"THREE.Color: Unknown color \\\\\\\"+t),this}clone(){return new this.constructor(this.r,this.g,this.b)}copy(t){return this.r=t.r,this.g=t.g,this.b=t.b,this}copyGammaToLinear(t,e=2){return this.r=Math.pow(t.r,e),this.g=Math.pow(t.g,e),this.b=Math.pow(t.b,e),this}copyLinearToGamma(t,e=2){const n=e>0?1/e:1;return this.r=Math.pow(t.r,n),this.g=Math.pow(t.g,n),this.b=Math.pow(t.b,n),this}convertGammaToLinear(t){return this.copyGammaToLinear(this,t),this}convertLinearToGamma(t){return this.copyLinearToGamma(this,t),this}copySRGBToLinear(t){return this.r=Xw(t.r),this.g=Xw(t.g),this.b=Xw(t.b),this}copyLinearToSRGB(t){return this.r=Yw(t.r),this.g=Yw(t.g),this.b=Yw(t.b),this}convertSRGBToLinear(){return this.copySRGBToLinear(this),this}convertLinearToSRGB(){return this.copyLinearToSRGB(this),this}getHex(){return 255*this.r<<16^255*this.g<<8^255*this.b<<0}getHexString(){return(\\\\\\\"000000\\\\\\\"+this.getHex().toString(16)).slice(-6)}getHSL(t){const e=this.r,n=this.g,i=this.b,s=Math.max(e,n,i),r=Math.min(e,n,i);let o,a;const l=(r+s)/2;if(r===s)o=0,a=0;else{const t=s-r;switch(a=l<=.5?t/(s+r):t/(2-s-r),s){case e:o=(n-i)/t+(n65535?eT:tT)(t,1):this.index=t,this}getAttribute(t){return this.attributes[t]}setAttribute(t,e){return this.attributes[t]=e,this}deleteAttribute(t){return delete this.attributes[t],this}hasAttribute(t){return void 0!==this.attributes[t]}addGroup(t,e,n=0){this.groups.push({start:t,count:e,materialIndex:n})}clearGroups(){this.groups=[]}setDrawRange(t,e){this.drawRange.start=t,this.drawRange.count=e}applyMatrix4(t){const e=this.attributes.position;void 0!==e&&(e.applyMatrix4(t),e.needsUpdate=!0);const n=this.attributes.normal;if(void 0!==n){const e=(new mb).getNormalMatrix(t);n.applyNormalMatrix(e),n.needsUpdate=!0}const i=this.attributes.tangent;return void 0!==i&&(i.transformDirection(t),i.needsUpdate=!0),null!==this.boundingBox&&this.computeBoundingBox(),null!==this.boundingSphere&&this.computeBoundingSphere(),this}applyQuaternion(t){return sT.makeRotationFromQuaternion(t),this.applyMatrix4(sT),this}rotateX(t){return sT.makeRotationX(t),this.applyMatrix4(sT),this}rotateY(t){return sT.makeRotationY(t),this.applyMatrix4(sT),this}rotateZ(t){return sT.makeRotationZ(t),this.applyMatrix4(sT),this}translate(t,e,n){return sT.makeTranslation(t,e,n),this.applyMatrix4(sT),this}scale(t,e,n){return sT.makeScale(t,e,n),this.applyMatrix4(sT),this}lookAt(t){return rT.lookAt(t),rT.updateMatrix(),this.applyMatrix4(rT.matrix),this}center(){return this.computeBoundingBox(),this.boundingBox.getCenter(oT).negate(),this.translate(oT.x,oT.y,oT.z),this}setFromPoints(t){const e=[];for(let n=0,i=t.length;n0&&(t.userData=this.userData),void 0!==this.parameters){const e=this.parameters;for(const n in e)void 0!==e[n]&&(t[n]=e[n]);return t}t.data={attributes:{}};const e=this.index;null!==e&&(t.data.index={type:e.array.constructor.name,array:Array.prototype.slice.call(e.array)});const n=this.attributes;for(const e in n){const i=n[e];t.data.attributes[e]=i.toJSON(t.data)}const i={};let s=!1;for(const e in this.morphAttributes){const n=this.morphAttributes[e],r=[];for(let e=0,i=n.length;e0&&(i[e]=r,s=!0)}s&&(t.data.morphAttributes=i,t.data.morphTargetsRelative=this.morphTargetsRelative);const r=this.groups;r.length>0&&(t.data.groups=JSON.parse(JSON.stringify(r)));const o=this.boundingSphere;return null!==o&&(t.data.boundingSphere={center:o.center.toArray(),radius:o.radius}),t}clone(){return(new this.constructor).copy(this)}copy(t){this.index=null,this.attributes={},this.morphAttributes={},this.groups=[],this.boundingBox=null,this.boundingSphere=null;const e={};this.name=t.name;const n=t.index;null!==n&&this.setIndex(n.clone(e));const i=t.attributes;for(const t in i){const n=i[t];this.setAttribute(t,n.clone(e))}const s=t.morphAttributes;for(const t in s){const n=[],i=s[t];for(let t=0,s=i.length;t0){const t=e[n[0]];if(void 0!==t){this.morphTargetInfluences=[],this.morphTargetDictionary={};for(let e=0,n=t.length;e0&&console.error(\\\\\\\"THREE.Mesh.updateMorphTargets() no longer supports THREE.Geometry. Use THREE.BufferGeometry instead.\\\\\\\")}}raycast(t,e){const n=this.geometry,i=this.material,s=this.matrixWorld;if(void 0===i)return;if(null===n.boundingSphere&&n.computeBoundingSphere(),pT.copy(n.boundingSphere),pT.applyMatrix4(s),!1===t.ray.intersectsSphere(pT))return;if(uT.copy(s).invert(),dT.copy(t.ray).applyMatrix4(uT),null!==n.boundingBox&&!1===dT.intersectsBox(n.boundingBox))return;let r;if(n.isBufferGeometry){const s=n.index,o=n.attributes.position,a=n.morphAttributes.position,l=n.morphTargetsRelative,c=n.attributes.uv,h=n.attributes.uv2,u=n.groups,d=n.drawRange;if(null!==s)if(Array.isArray(i))for(let n=0,p=u.length;nn.far?null:{distance:c,point:ST.clone(),object:t}}(t,e,n,i,_T,mT,fT,ET);if(p){a&&(TT.fromBufferAttribute(a,c),AT.fromBufferAttribute(a,h),MT.fromBufferAttribute(a,u),p.uv=Uw.getUV(ET,_T,mT,fT,TT,AT,MT,new _b)),l&&(TT.fromBufferAttribute(l,c),AT.fromBufferAttribute(l,h),MT.fromBufferAttribute(l,u),p.uv2=Uw.getUV(ET,_T,mT,fT,TT,AT,MT,new _b));const t={a:c,b:h,c:u,normal:new Sb,materialIndex:0};Uw.getNormal(_T,mT,fT,t.normal),p.face=t}return p}CT.prototype.isMesh=!0;class LT extends hT{constructor(t=1,e=1,n=1,i=1,s=1,r=1){super(),this.type=\\\\\\\"BoxGeometry\\\\\\\",this.parameters={width:t,height:e,depth:n,widthSegments:i,heightSegments:s,depthSegments:r};const o=this;i=Math.floor(i),s=Math.floor(s),r=Math.floor(r);const a=[],l=[],c=[],h=[];let u=0,d=0;function p(t,e,n,i,s,r,p,_,m,f,g){const v=r/m,y=p/f,x=r/2,b=p/2,w=_/2,T=m+1,A=f+1;let M=0,E=0;const S=new Sb;for(let r=0;r0?1:-1,c.push(S.x,S.y,S.z),h.push(a/m),h.push(1-r/f),M+=1}}for(let t=0;t0&&(e.defines=this.defines),e.vertexShader=this.vertexShader,e.fragmentShader=this.fragmentShader;const n={};for(const t in this.extensions)!0===this.extensions[t]&&(n[t]=!0);return Object.keys(n).length>0&&(e.extensions=n),e}}IT.prototype.isShaderMaterial=!0;class FT extends Nw{constructor(){super(),this.type=\\\\\\\"Camera\\\\\\\",this.matrixWorldInverse=new sw,this.projectionMatrix=new sw,this.projectionMatrixInverse=new sw}copy(t,e){return super.copy(t,e),this.matrixWorldInverse.copy(t.matrixWorldInverse),this.projectionMatrix.copy(t.projectionMatrix),this.projectionMatrixInverse.copy(t.projectionMatrixInverse),this}getWorldDirection(t){this.updateWorldMatrix(!0,!1);const e=this.matrixWorld.elements;return t.set(-e[8],-e[9],-e[10]).normalize()}updateMatrixWorld(t){super.updateMatrixWorld(t),this.matrixWorldInverse.copy(this.matrixWorld).invert()}updateWorldMatrix(t,e){super.updateWorldMatrix(t,e),this.matrixWorldInverse.copy(this.matrixWorld).invert()}clone(){return(new this.constructor).copy(this)}}FT.prototype.isCamera=!0;class DT extends FT{constructor(t=50,e=1,n=.1,i=2e3){super(),this.type=\\\\\\\"PerspectiveCamera\\\\\\\",this.fov=t,this.zoom=1,this.near=n,this.far=i,this.focus=10,this.aspect=e,this.view=null,this.filmGauge=35,this.filmOffset=0,this.updateProjectionMatrix()}copy(t,e){return super.copy(t,e),this.fov=t.fov,this.zoom=t.zoom,this.near=t.near,this.far=t.far,this.focus=t.focus,this.aspect=t.aspect,this.view=null===t.view?null:Object.assign({},t.view),this.filmGauge=t.filmGauge,this.filmOffset=t.filmOffset,this}setFocalLength(t){const e=.5*this.getFilmHeight()/t;this.fov=2*ib*Math.atan(e),this.updateProjectionMatrix()}getFocalLength(){const t=Math.tan(.5*nb*this.fov);return.5*this.getFilmHeight()/t}getEffectiveFOV(){return 2*ib*Math.atan(Math.tan(.5*nb*this.fov)/this.zoom)}getFilmWidth(){return this.filmGauge*Math.min(this.aspect,1)}getFilmHeight(){return this.filmGauge/Math.max(this.aspect,1)}setViewOffset(t,e,n,i,s,r){this.aspect=t/e,null===this.view&&(this.view={enabled:!0,fullWidth:1,fullHeight:1,offsetX:0,offsetY:0,width:1,height:1}),this.view.enabled=!0,this.view.fullWidth=t,this.view.fullHeight=e,this.view.offsetX=n,this.view.offsetY=i,this.view.width=s,this.view.height=r,this.updateProjectionMatrix()}clearViewOffset(){null!==this.view&&(this.view.enabled=!1),this.updateProjectionMatrix()}updateProjectionMatrix(){const t=this.near;let e=t*Math.tan(.5*nb*this.fov)/this.zoom,n=2*e,i=this.aspect*n,s=-.5*i;const r=this.view;if(null!==this.view&&this.view.enabled){const t=r.fullWidth,o=r.fullHeight;s+=r.offsetX*i/t,e-=r.offsetY*n/o,i*=r.width/t,n*=r.height/o}const o=this.filmOffset;0!==o&&(s+=t*o/this.getFilmWidth()),this.projectionMatrix.makePerspective(s,s+i,e,e-n,t,this.far),this.projectionMatrixInverse.copy(this.projectionMatrix).invert()}toJSON(t){const e=super.toJSON(t);return e.object.fov=this.fov,e.object.zoom=this.zoom,e.object.near=this.near,e.object.far=this.far,e.object.focus=this.focus,e.object.aspect=this.aspect,null!==this.view&&(e.object.view=Object.assign({},this.view)),e.object.filmGauge=this.filmGauge,e.object.filmOffset=this.filmOffset,e}}DT.prototype.isPerspectiveCamera=!0;const BT=90;class zT extends Nw{constructor(t,e,n){if(super(),this.type=\\\\\\\"CubeCamera\\\\\\\",!0!==n.isWebGLCubeRenderTarget)return void console.error(\\\\\\\"THREE.CubeCamera: The constructor now expects an instance of WebGLCubeRenderTarget as third parameter.\\\\\\\");this.renderTarget=n;const i=new DT(BT,1,t,e);i.layers=this.layers,i.up.set(0,-1,0),i.lookAt(new Sb(1,0,0)),this.add(i);const s=new DT(BT,1,t,e);s.layers=this.layers,s.up.set(0,-1,0),s.lookAt(new Sb(-1,0,0)),this.add(s);const r=new DT(BT,1,t,e);r.layers=this.layers,r.up.set(0,0,1),r.lookAt(new Sb(0,1,0)),this.add(r);const o=new DT(BT,1,t,e);o.layers=this.layers,o.up.set(0,0,-1),o.lookAt(new Sb(0,-1,0)),this.add(o);const a=new DT(BT,1,t,e);a.layers=this.layers,a.up.set(0,-1,0),a.lookAt(new Sb(0,0,1)),this.add(a);const l=new DT(BT,1,t,e);l.layers=this.layers,l.up.set(0,-1,0),l.lookAt(new Sb(0,0,-1)),this.add(l)}update(t,e){null===this.parent&&this.updateMatrixWorld();const n=this.renderTarget,[i,s,r,o,a,l]=this.children,c=t.xr.enabled,h=t.getRenderTarget();t.xr.enabled=!1;const u=n.texture.generateMipmaps;n.texture.generateMipmaps=!1,t.setRenderTarget(n,0),t.render(e,i),t.setRenderTarget(n,1),t.render(e,s),t.setRenderTarget(n,2),t.render(e,r),t.setRenderTarget(n,3),t.render(e,o),t.setRenderTarget(n,4),t.render(e,a),n.texture.generateMipmaps=u,t.setRenderTarget(n,5),t.render(e,l),t.setRenderTarget(h),t.xr.enabled=c}}class kT extends bb{constructor(t,e,n,i,s,r,o,a,l,c){super(t=void 0!==t?t:[],e=void 0!==e?e:_x,n,i,s,r,o,a,l,c),this.flipY=!1}get images(){return this.image}set images(t){this.image=t}}kT.prototype.isCubeTexture=!0;class UT extends Ab{constructor(t,e,n){Number.isInteger(e)&&(console.warn(\\\\\\\"THREE.WebGLCubeRenderTarget: constructor signature is now WebGLCubeRenderTarget( size, options )\\\\\\\"),e=n),super(t,t,e),e=e||{},this.texture=new kT(void 0,e.mapping,e.wrapS,e.wrapT,e.magFilter,e.minFilter,e.format,e.type,e.anisotropy,e.encoding),this.texture.isRenderTargetTexture=!0,this.texture.generateMipmaps=void 0!==e.generateMipmaps&&e.generateMipmaps,this.texture.minFilter=void 0!==e.minFilter?e.minFilter:Ex,this.texture._needsFlipEnvMap=!1}fromEquirectangularTexture(t,e){this.texture.type=e.type,this.texture.format=Dx,this.texture.encoding=e.encoding,this.texture.generateMipmaps=e.generateMipmaps,this.texture.minFilter=e.minFilter,this.texture.magFilter=e.magFilter;const n={uniforms:{tEquirect:{value:null}},vertexShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tvarying vec3 vWorldDirection;\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tvec3 transformDirection( in vec3 dir, in mat4 matrix ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\t\\\\treturn normalize( ( matrix * vec4( dir, 0.0 ) ).xyz );\\\\n\\\\n\\\\t\\\\t\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tvWorldDirection = transformDirection( position, modelMatrix );\\\\n\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t#include \\\\n\\\\t\\\\t\\\\t\\\\t\\\\t#include \\\\n\\\\n\\\\t\\\\t\\\\t\\\\t}\\\\n\\\\t\\\\t\\\\t\\\\\\\",fragmentShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tuniform sampler2D tEquirect;\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tvarying vec3 vWorldDirection;\\\\n\\\\n\\\\t\\\\t\\\\t\\\\t#include \\\\n\\\\n\\\\t\\\\t\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tvec3 direction = normalize( vWorldDirection );\\\\n\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tvec2 sampleUV = equirectUv( direction );\\\\n\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tgl_FragColor = texture2D( tEquirect, sampleUV );\\\\n\\\\n\\\\t\\\\t\\\\t\\\\t}\\\\n\\\\t\\\\t\\\\t\\\\\\\"},i=new LT(5,5,5),s=new IT({name:\\\\\\\"CubemapFromEquirect\\\\\\\",uniforms:OT(n.uniforms),vertexShader:n.vertexShader,fragmentShader:n.fragmentShader,side:1,blending:0});s.uniforms.tEquirect.value=e;const r=new CT(i,s),o=e.minFilter;e.minFilter===Cx&&(e.minFilter=Ex);return new zT(1,10,this).update(t,r),e.minFilter=o,r.geometry.dispose(),r.material.dispose(),this}clear(t,e,n,i){const s=t.getRenderTarget();for(let s=0;s<6;s++)t.setRenderTarget(this,s),t.clear(e,n,i);t.setRenderTarget(s)}}UT.prototype.isWebGLCubeRenderTarget=!0;const GT=new Sb,VT=new Sb,HT=new mb;class jT{constructor(t=new Sb(1,0,0),e=0){this.normal=t,this.constant=e}set(t,e){return this.normal.copy(t),this.constant=e,this}setComponents(t,e,n,i){return this.normal.set(t,e,n),this.constant=i,this}setFromNormalAndCoplanarPoint(t,e){return this.normal.copy(t),this.constant=-e.dot(this.normal),this}setFromCoplanarPoints(t,e,n){const i=GT.subVectors(n,e).cross(VT.subVectors(t,e)).normalize();return this.setFromNormalAndCoplanarPoint(i,t),this}copy(t){return this.normal.copy(t.normal),this.constant=t.constant,this}normalize(){const t=1/this.normal.length();return this.normal.multiplyScalar(t),this.constant*=t,this}negate(){return this.constant*=-1,this.normal.negate(),this}distanceToPoint(t){return this.normal.dot(t)+this.constant}distanceToSphere(t){return this.distanceToPoint(t.center)-t.radius}projectPoint(t,e){return e.copy(this.normal).multiplyScalar(-this.distanceToPoint(t)).add(t)}intersectLine(t,e){const n=t.delta(GT),i=this.normal.dot(n);if(0===i)return 0===this.distanceToPoint(t.start)?e.copy(t.start):null;const s=-(t.start.dot(this.normal)+this.constant)/i;return s<0||s>1?null:e.copy(n).multiplyScalar(s).add(t.start)}intersectsLine(t){const e=this.distanceToPoint(t.start),n=this.distanceToPoint(t.end);return e<0&&n>0||n<0&&e>0}intersectsBox(t){return t.intersectsPlane(this)}intersectsSphere(t){return t.intersectsPlane(this)}coplanarPoint(t){return t.copy(this.normal).multiplyScalar(-this.constant)}applyMatrix4(t,e){const n=e||HT.getNormalMatrix(t),i=this.coplanarPoint(GT).applyMatrix4(t),s=this.normal.applyMatrix3(n).normalize();return this.constant=-i.dot(s),this}translate(t){return this.constant-=t.dot(this.normal),this}equals(t){return t.normal.equals(this.normal)&&t.constant===this.constant}clone(){return(new this.constructor).copy(this)}}jT.prototype.isPlane=!0;const WT=new $b,qT=new Sb;class XT{constructor(t=new jT,e=new jT,n=new jT,i=new jT,s=new jT,r=new jT){this.planes=[t,e,n,i,s,r]}set(t,e,n,i,s,r){const o=this.planes;return o[0].copy(t),o[1].copy(e),o[2].copy(n),o[3].copy(i),o[4].copy(s),o[5].copy(r),this}copy(t){const e=this.planes;for(let n=0;n<6;n++)e[n].copy(t.planes[n]);return this}setFromProjectionMatrix(t){const e=this.planes,n=t.elements,i=n[0],s=n[1],r=n[2],o=n[3],a=n[4],l=n[5],c=n[6],h=n[7],u=n[8],d=n[9],p=n[10],_=n[11],m=n[12],f=n[13],g=n[14],v=n[15];return e[0].setComponents(o-i,h-a,_-u,v-m).normalize(),e[1].setComponents(o+i,h+a,_+u,v+m).normalize(),e[2].setComponents(o+s,h+l,_+d,v+f).normalize(),e[3].setComponents(o-s,h-l,_-d,v-f).normalize(),e[4].setComponents(o-r,h-c,_-p,v-g).normalize(),e[5].setComponents(o+r,h+c,_+p,v+g).normalize(),this}intersectsObject(t){const e=t.geometry;return null===e.boundingSphere&&e.computeBoundingSphere(),WT.copy(e.boundingSphere).applyMatrix4(t.matrixWorld),this.intersectsSphere(WT)}intersectsSprite(t){return WT.center.set(0,0,0),WT.radius=.7071067811865476,WT.applyMatrix4(t.matrixWorld),this.intersectsSphere(WT)}intersectsSphere(t){const e=this.planes,n=t.center,i=-t.radius;for(let t=0;t<6;t++){if(e[t].distanceToPoint(n)0?t.max.x:t.min.x,qT.y=i.normal.y>0?t.max.y:t.min.y,qT.z=i.normal.z>0?t.max.z:t.min.z,i.distanceToPoint(qT)<0)return!1}return!0}containsPoint(t){const e=this.planes;for(let n=0;n<6;n++)if(e[n].distanceToPoint(t)<0)return!1;return!0}clone(){return(new this.constructor).copy(this)}}function YT(){let t=null,e=!1,n=null,i=null;function s(e,r){n(e,r),i=t.requestAnimationFrame(s)}return{start:function(){!0!==e&&null!==n&&(i=t.requestAnimationFrame(s),e=!0)},stop:function(){t.cancelAnimationFrame(i),e=!1},setAnimationLoop:function(t){n=t},setContext:function(e){t=e}}}function $T(t,e){const n=e.isWebGL2,i=new WeakMap;return{get:function(t){return t.isInterleavedBufferAttribute&&(t=t.data),i.get(t)},remove:function(e){e.isInterleavedBufferAttribute&&(e=e.data);const n=i.get(e);n&&(t.deleteBuffer(n.buffer),i.delete(e))},update:function(e,s){if(e.isGLBufferAttribute){const t=i.get(e);return void((!t||t.version 0.0 ) ? v : 0.5 * inversesqrt( max( 1.0 - x * x, 1e-7 ) ) - v;\\\\n\\\\treturn cross( v1, v2 ) * theta_sintheta;\\\\n}\\\\nvec3 LTC_Evaluate( const in vec3 N, const in vec3 V, const in vec3 P, const in mat3 mInv, const in vec3 rectCoords[ 4 ] ) {\\\\n\\\\tvec3 v1 = rectCoords[ 1 ] - rectCoords[ 0 ];\\\\n\\\\tvec3 v2 = rectCoords[ 3 ] - rectCoords[ 0 ];\\\\n\\\\tvec3 lightNormal = cross( v1, v2 );\\\\n\\\\tif( dot( lightNormal, P - rectCoords[ 0 ] ) < 0.0 ) return vec3( 0.0 );\\\\n\\\\tvec3 T1, T2;\\\\n\\\\tT1 = normalize( V - N * dot( V, N ) );\\\\n\\\\tT2 = - cross( N, T1 );\\\\n\\\\tmat3 mat = mInv * transposeMat3( mat3( T1, T2, N ) );\\\\n\\\\tvec3 coords[ 4 ];\\\\n\\\\tcoords[ 0 ] = mat * ( rectCoords[ 0 ] - P );\\\\n\\\\tcoords[ 1 ] = mat * ( rectCoords[ 1 ] - P );\\\\n\\\\tcoords[ 2 ] = mat * ( rectCoords[ 2 ] - P );\\\\n\\\\tcoords[ 3 ] = mat * ( rectCoords[ 3 ] - P );\\\\n\\\\tcoords[ 0 ] = normalize( coords[ 0 ] );\\\\n\\\\tcoords[ 1 ] = normalize( coords[ 1 ] );\\\\n\\\\tcoords[ 2 ] = normalize( coords[ 2 ] );\\\\n\\\\tcoords[ 3 ] = normalize( coords[ 3 ] );\\\\n\\\\tvec3 vectorFormFactor = vec3( 0.0 );\\\\n\\\\tvectorFormFactor += LTC_EdgeVectorFormFactor( coords[ 0 ], coords[ 1 ] );\\\\n\\\\tvectorFormFactor += LTC_EdgeVectorFormFactor( coords[ 1 ], coords[ 2 ] );\\\\n\\\\tvectorFormFactor += LTC_EdgeVectorFormFactor( coords[ 2 ], coords[ 3 ] );\\\\n\\\\tvectorFormFactor += LTC_EdgeVectorFormFactor( coords[ 3 ], coords[ 0 ] );\\\\n\\\\tfloat result = LTC_ClippedSphereFormFactor( vectorFormFactor );\\\\n\\\\treturn vec3( result );\\\\n}\\\\nfloat G_BlinnPhong_Implicit( ) {\\\\n\\\\treturn 0.25;\\\\n}\\\\nfloat D_BlinnPhong( const in float shininess, const in float dotNH ) {\\\\n\\\\treturn RECIPROCAL_PI * ( shininess * 0.5 + 1.0 ) * pow( dotNH, shininess );\\\\n}\\\\nvec3 BRDF_BlinnPhong( const in vec3 lightDir, const in vec3 viewDir, const in vec3 normal, const in vec3 specularColor, const in float shininess ) {\\\\n\\\\tvec3 halfDir = normalize( lightDir + viewDir );\\\\n\\\\tfloat dotNH = saturate( dot( normal, halfDir ) );\\\\n\\\\tfloat dotVH = saturate( dot( viewDir, halfDir ) );\\\\n\\\\tvec3 F = F_Schlick( specularColor, 1.0, dotVH );\\\\n\\\\tfloat G = G_BlinnPhong_Implicit( );\\\\n\\\\tfloat D = D_BlinnPhong( shininess, dotNH );\\\\n\\\\treturn F * ( G * D );\\\\n}\\\\n#if defined( USE_SHEEN )\\\\nfloat D_Charlie( float roughness, float dotNH ) {\\\\n\\\\tfloat alpha = pow2( roughness );\\\\n\\\\tfloat invAlpha = 1.0 / alpha;\\\\n\\\\tfloat cos2h = dotNH * dotNH;\\\\n\\\\tfloat sin2h = max( 1.0 - cos2h, 0.0078125 );\\\\n\\\\treturn ( 2.0 + invAlpha ) * pow( sin2h, invAlpha * 0.5 ) / ( 2.0 * PI );\\\\n}\\\\nfloat V_Neubelt( float dotNV, float dotNL ) {\\\\n\\\\treturn saturate( 1.0 / ( 4.0 * ( dotNL + dotNV - dotNL * dotNV ) ) );\\\\n}\\\\nvec3 BRDF_Sheen( const in vec3 lightDir, const in vec3 viewDir, const in vec3 normal, vec3 sheenTint, const in float sheenRoughness ) {\\\\n\\\\tvec3 halfDir = normalize( lightDir + viewDir );\\\\n\\\\tfloat dotNL = saturate( dot( normal, lightDir ) );\\\\n\\\\tfloat dotNV = saturate( dot( normal, viewDir ) );\\\\n\\\\tfloat dotNH = saturate( dot( normal, halfDir ) );\\\\n\\\\tfloat D = D_Charlie( sheenRoughness, dotNH );\\\\n\\\\tfloat V = V_Neubelt( dotNV, dotNL );\\\\n\\\\treturn sheenTint * ( D * V );\\\\n}\\\\n#endif\\\\\\\",bumpmap_pars_fragment:\\\\\\\"#ifdef USE_BUMPMAP\\\\n\\\\tuniform sampler2D bumpMap;\\\\n\\\\tuniform float bumpScale;\\\\n\\\\tvec2 dHdxy_fwd() {\\\\n\\\\t\\\\tvec2 dSTdx = dFdx( vUv );\\\\n\\\\t\\\\tvec2 dSTdy = dFdy( vUv );\\\\n\\\\t\\\\tfloat Hll = bumpScale * texture2D( bumpMap, vUv ).x;\\\\n\\\\t\\\\tfloat dBx = bumpScale * texture2D( bumpMap, vUv + dSTdx ).x - Hll;\\\\n\\\\t\\\\tfloat dBy = bumpScale * texture2D( bumpMap, vUv + dSTdy ).x - Hll;\\\\n\\\\t\\\\treturn vec2( dBx, dBy );\\\\n\\\\t}\\\\n\\\\tvec3 perturbNormalArb( vec3 surf_pos, vec3 surf_norm, vec2 dHdxy, float faceDirection ) {\\\\n\\\\t\\\\tvec3 vSigmaX = vec3( dFdx( surf_pos.x ), dFdx( surf_pos.y ), dFdx( surf_pos.z ) );\\\\n\\\\t\\\\tvec3 vSigmaY = vec3( dFdy( surf_pos.x ), dFdy( surf_pos.y ), dFdy( surf_pos.z ) );\\\\n\\\\t\\\\tvec3 vN = surf_norm;\\\\n\\\\t\\\\tvec3 R1 = cross( vSigmaY, vN );\\\\n\\\\t\\\\tvec3 R2 = cross( vN, vSigmaX );\\\\n\\\\t\\\\tfloat fDet = dot( vSigmaX, R1 ) * faceDirection;\\\\n\\\\t\\\\tvec3 vGrad = sign( fDet ) * ( dHdxy.x * R1 + dHdxy.y * R2 );\\\\n\\\\t\\\\treturn normalize( abs( fDet ) * surf_norm - vGrad );\\\\n\\\\t}\\\\n#endif\\\\\\\",clipping_planes_fragment:\\\\\\\"#if NUM_CLIPPING_PLANES > 0\\\\n\\\\tvec4 plane;\\\\n\\\\t#pragma unroll_loop_start\\\\n\\\\tfor ( int i = 0; i < UNION_CLIPPING_PLANES; i ++ ) {\\\\n\\\\t\\\\tplane = clippingPlanes[ i ];\\\\n\\\\t\\\\tif ( dot( vClipPosition, plane.xyz ) > plane.w ) discard;\\\\n\\\\t}\\\\n\\\\t#pragma unroll_loop_end\\\\n\\\\t#if UNION_CLIPPING_PLANES < NUM_CLIPPING_PLANES\\\\n\\\\t\\\\tbool clipped = true;\\\\n\\\\t\\\\t#pragma unroll_loop_start\\\\n\\\\t\\\\tfor ( int i = UNION_CLIPPING_PLANES; i < NUM_CLIPPING_PLANES; i ++ ) {\\\\n\\\\t\\\\t\\\\tplane = clippingPlanes[ i ];\\\\n\\\\t\\\\t\\\\tclipped = ( dot( vClipPosition, plane.xyz ) > plane.w ) && clipped;\\\\n\\\\t\\\\t}\\\\n\\\\t\\\\t#pragma unroll_loop_end\\\\n\\\\t\\\\tif ( clipped ) discard;\\\\n\\\\t#endif\\\\n#endif\\\\\\\",clipping_planes_pars_fragment:\\\\\\\"#if NUM_CLIPPING_PLANES > 0\\\\n\\\\tvarying vec3 vClipPosition;\\\\n\\\\tuniform vec4 clippingPlanes[ NUM_CLIPPING_PLANES ];\\\\n#endif\\\\\\\",clipping_planes_pars_vertex:\\\\\\\"#if NUM_CLIPPING_PLANES > 0\\\\n\\\\tvarying vec3 vClipPosition;\\\\n#endif\\\\\\\",clipping_planes_vertex:\\\\\\\"#if NUM_CLIPPING_PLANES > 0\\\\n\\\\tvClipPosition = - mvPosition.xyz;\\\\n#endif\\\\\\\",color_fragment:\\\\\\\"#if defined( USE_COLOR_ALPHA )\\\\n\\\\tdiffuseColor *= vColor;\\\\n#elif defined( USE_COLOR )\\\\n\\\\tdiffuseColor.rgb *= vColor;\\\\n#endif\\\\\\\",color_pars_fragment:\\\\\\\"#if defined( USE_COLOR_ALPHA )\\\\n\\\\tvarying vec4 vColor;\\\\n#elif defined( USE_COLOR )\\\\n\\\\tvarying vec3 vColor;\\\\n#endif\\\\\\\",color_pars_vertex:\\\\\\\"#if defined( USE_COLOR_ALPHA )\\\\n\\\\tvarying vec4 vColor;\\\\n#elif defined( USE_COLOR ) || defined( USE_INSTANCING_COLOR )\\\\n\\\\tvarying vec3 vColor;\\\\n#endif\\\\\\\",color_vertex:\\\\\\\"#if defined( USE_COLOR_ALPHA )\\\\n\\\\tvColor = vec4( 1.0 );\\\\n#elif defined( USE_COLOR ) || defined( USE_INSTANCING_COLOR )\\\\n\\\\tvColor = vec3( 1.0 );\\\\n#endif\\\\n#ifdef USE_COLOR\\\\n\\\\tvColor *= color;\\\\n#endif\\\\n#ifdef USE_INSTANCING_COLOR\\\\n\\\\tvColor.xyz *= instanceColor.xyz;\\\\n#endif\\\\\\\",common:\\\\\\\"#define PI 3.141592653589793\\\\n#define PI2 6.283185307179586\\\\n#define PI_HALF 1.5707963267948966\\\\n#define RECIPROCAL_PI 0.3183098861837907\\\\n#define RECIPROCAL_PI2 0.15915494309189535\\\\n#define EPSILON 1e-6\\\\n#ifndef saturate\\\\n#define saturate( a ) clamp( a, 0.0, 1.0 )\\\\n#endif\\\\n#define whiteComplement( a ) ( 1.0 - saturate( a ) )\\\\nfloat pow2( const in float x ) { return x*x; }\\\\nfloat pow3( const in float x ) { return x*x*x; }\\\\nfloat pow4( const in float x ) { float x2 = x*x; return x2*x2; }\\\\nfloat max3( const in vec3 v ) { return max( max( v.x, v.y ), v.z ); }\\\\nfloat average( const in vec3 color ) { return dot( color, vec3( 0.3333 ) ); }\\\\nhighp float rand( const in vec2 uv ) {\\\\n\\\\tconst highp float a = 12.9898, b = 78.233, c = 43758.5453;\\\\n\\\\thighp float dt = dot( uv.xy, vec2( a,b ) ), sn = mod( dt, PI );\\\\n\\\\treturn fract( sin( sn ) * c );\\\\n}\\\\n#ifdef HIGH_PRECISION\\\\n\\\\tfloat precisionSafeLength( vec3 v ) { return length( v ); }\\\\n#else\\\\n\\\\tfloat precisionSafeLength( vec3 v ) {\\\\n\\\\t\\\\tfloat maxComponent = max3( abs( v ) );\\\\n\\\\t\\\\treturn length( v / maxComponent ) * maxComponent;\\\\n\\\\t}\\\\n#endif\\\\nstruct IncidentLight {\\\\n\\\\tvec3 color;\\\\n\\\\tvec3 direction;\\\\n\\\\tbool visible;\\\\n};\\\\nstruct ReflectedLight {\\\\n\\\\tvec3 directDiffuse;\\\\n\\\\tvec3 directSpecular;\\\\n\\\\tvec3 indirectDiffuse;\\\\n\\\\tvec3 indirectSpecular;\\\\n};\\\\nstruct GeometricContext {\\\\n\\\\tvec3 position;\\\\n\\\\tvec3 normal;\\\\n\\\\tvec3 viewDir;\\\\n#ifdef USE_CLEARCOAT\\\\n\\\\tvec3 clearcoatNormal;\\\\n#endif\\\\n};\\\\nvec3 transformDirection( in vec3 dir, in mat4 matrix ) {\\\\n\\\\treturn normalize( ( matrix * vec4( dir, 0.0 ) ).xyz );\\\\n}\\\\nvec3 inverseTransformDirection( in vec3 dir, in mat4 matrix ) {\\\\n\\\\treturn normalize( ( vec4( dir, 0.0 ) * matrix ).xyz );\\\\n}\\\\nmat3 transposeMat3( const in mat3 m ) {\\\\n\\\\tmat3 tmp;\\\\n\\\\ttmp[ 0 ] = vec3( m[ 0 ].x, m[ 1 ].x, m[ 2 ].x );\\\\n\\\\ttmp[ 1 ] = vec3( m[ 0 ].y, m[ 1 ].y, m[ 2 ].y );\\\\n\\\\ttmp[ 2 ] = vec3( m[ 0 ].z, m[ 1 ].z, m[ 2 ].z );\\\\n\\\\treturn tmp;\\\\n}\\\\nfloat linearToRelativeLuminance( const in vec3 color ) {\\\\n\\\\tvec3 weights = vec3( 0.2126, 0.7152, 0.0722 );\\\\n\\\\treturn dot( weights, color.rgb );\\\\n}\\\\nbool isPerspectiveMatrix( mat4 m ) {\\\\n\\\\treturn m[ 2 ][ 3 ] == - 1.0;\\\\n}\\\\nvec2 equirectUv( in vec3 dir ) {\\\\n\\\\tfloat u = atan( dir.z, dir.x ) * RECIPROCAL_PI2 + 0.5;\\\\n\\\\tfloat v = asin( clamp( dir.y, - 1.0, 1.0 ) ) * RECIPROCAL_PI + 0.5;\\\\n\\\\treturn vec2( u, v );\\\\n}\\\\\\\",cube_uv_reflection_fragment:\\\\\\\"#ifdef ENVMAP_TYPE_CUBE_UV\\\\n\\\\t#define cubeUV_maxMipLevel 8.0\\\\n\\\\t#define cubeUV_minMipLevel 4.0\\\\n\\\\t#define cubeUV_maxTileSize 256.0\\\\n\\\\t#define cubeUV_minTileSize 16.0\\\\n\\\\tfloat getFace( vec3 direction ) {\\\\n\\\\t\\\\tvec3 absDirection = abs( direction );\\\\n\\\\t\\\\tfloat face = - 1.0;\\\\n\\\\t\\\\tif ( absDirection.x > absDirection.z ) {\\\\n\\\\t\\\\t\\\\tif ( absDirection.x > absDirection.y )\\\\n\\\\t\\\\t\\\\t\\\\tface = direction.x > 0.0 ? 0.0 : 3.0;\\\\n\\\\t\\\\t\\\\telse\\\\n\\\\t\\\\t\\\\t\\\\tface = direction.y > 0.0 ? 1.0 : 4.0;\\\\n\\\\t\\\\t} else {\\\\n\\\\t\\\\t\\\\tif ( absDirection.z > absDirection.y )\\\\n\\\\t\\\\t\\\\t\\\\tface = direction.z > 0.0 ? 2.0 : 5.0;\\\\n\\\\t\\\\t\\\\telse\\\\n\\\\t\\\\t\\\\t\\\\tface = direction.y > 0.0 ? 1.0 : 4.0;\\\\n\\\\t\\\\t}\\\\n\\\\t\\\\treturn face;\\\\n\\\\t}\\\\n\\\\tvec2 getUV( vec3 direction, float face ) {\\\\n\\\\t\\\\tvec2 uv;\\\\n\\\\t\\\\tif ( face == 0.0 ) {\\\\n\\\\t\\\\t\\\\tuv = vec2( direction.z, direction.y ) / abs( direction.x );\\\\n\\\\t\\\\t} else if ( face == 1.0 ) {\\\\n\\\\t\\\\t\\\\tuv = vec2( - direction.x, - direction.z ) / abs( direction.y );\\\\n\\\\t\\\\t} else if ( face == 2.0 ) {\\\\n\\\\t\\\\t\\\\tuv = vec2( - direction.x, direction.y ) / abs( direction.z );\\\\n\\\\t\\\\t} else if ( face == 3.0 ) {\\\\n\\\\t\\\\t\\\\tuv = vec2( - direction.z, direction.y ) / abs( direction.x );\\\\n\\\\t\\\\t} else if ( face == 4.0 ) {\\\\n\\\\t\\\\t\\\\tuv = vec2( - direction.x, direction.z ) / abs( direction.y );\\\\n\\\\t\\\\t} else {\\\\n\\\\t\\\\t\\\\tuv = vec2( direction.x, direction.y ) / abs( direction.z );\\\\n\\\\t\\\\t}\\\\n\\\\t\\\\treturn 0.5 * ( uv + 1.0 );\\\\n\\\\t}\\\\n\\\\tvec3 bilinearCubeUV( sampler2D envMap, vec3 direction, float mipInt ) {\\\\n\\\\t\\\\tfloat face = getFace( direction );\\\\n\\\\t\\\\tfloat filterInt = max( cubeUV_minMipLevel - mipInt, 0.0 );\\\\n\\\\t\\\\tmipInt = max( mipInt, cubeUV_minMipLevel );\\\\n\\\\t\\\\tfloat faceSize = exp2( mipInt );\\\\n\\\\t\\\\tfloat texelSize = 1.0 / ( 3.0 * cubeUV_maxTileSize );\\\\n\\\\t\\\\tvec2 uv = getUV( direction, face ) * ( faceSize - 1.0 );\\\\n\\\\t\\\\tvec2 f = fract( uv );\\\\n\\\\t\\\\tuv += 0.5 - f;\\\\n\\\\t\\\\tif ( face > 2.0 ) {\\\\n\\\\t\\\\t\\\\tuv.y += faceSize;\\\\n\\\\t\\\\t\\\\tface -= 3.0;\\\\n\\\\t\\\\t}\\\\n\\\\t\\\\tuv.x += face * faceSize;\\\\n\\\\t\\\\tif ( mipInt < cubeUV_maxMipLevel ) {\\\\n\\\\t\\\\t\\\\tuv.y += 2.0 * cubeUV_maxTileSize;\\\\n\\\\t\\\\t}\\\\n\\\\t\\\\tuv.y += filterInt * 2.0 * cubeUV_minTileSize;\\\\n\\\\t\\\\tuv.x += 3.0 * max( 0.0, cubeUV_maxTileSize - 2.0 * faceSize );\\\\n\\\\t\\\\tuv *= texelSize;\\\\n\\\\t\\\\tvec3 tl = envMapTexelToLinear( texture2D( envMap, uv ) ).rgb;\\\\n\\\\t\\\\tuv.x += texelSize;\\\\n\\\\t\\\\tvec3 tr = envMapTexelToLinear( texture2D( envMap, uv ) ).rgb;\\\\n\\\\t\\\\tuv.y += texelSize;\\\\n\\\\t\\\\tvec3 br = envMapTexelToLinear( texture2D( envMap, uv ) ).rgb;\\\\n\\\\t\\\\tuv.x -= texelSize;\\\\n\\\\t\\\\tvec3 bl = envMapTexelToLinear( texture2D( envMap, uv ) ).rgb;\\\\n\\\\t\\\\tvec3 tm = mix( tl, tr, f.x );\\\\n\\\\t\\\\tvec3 bm = mix( bl, br, f.x );\\\\n\\\\t\\\\treturn mix( tm, bm, f.y );\\\\n\\\\t}\\\\n\\\\t#define r0 1.0\\\\n\\\\t#define v0 0.339\\\\n\\\\t#define m0 - 2.0\\\\n\\\\t#define r1 0.8\\\\n\\\\t#define v1 0.276\\\\n\\\\t#define m1 - 1.0\\\\n\\\\t#define r4 0.4\\\\n\\\\t#define v4 0.046\\\\n\\\\t#define m4 2.0\\\\n\\\\t#define r5 0.305\\\\n\\\\t#define v5 0.016\\\\n\\\\t#define m5 3.0\\\\n\\\\t#define r6 0.21\\\\n\\\\t#define v6 0.0038\\\\n\\\\t#define m6 4.0\\\\n\\\\tfloat roughnessToMip( float roughness ) {\\\\n\\\\t\\\\tfloat mip = 0.0;\\\\n\\\\t\\\\tif ( roughness >= r1 ) {\\\\n\\\\t\\\\t\\\\tmip = ( r0 - roughness ) * ( m1 - m0 ) / ( r0 - r1 ) + m0;\\\\n\\\\t\\\\t} else if ( roughness >= r4 ) {\\\\n\\\\t\\\\t\\\\tmip = ( r1 - roughness ) * ( m4 - m1 ) / ( r1 - r4 ) + m1;\\\\n\\\\t\\\\t} else if ( roughness >= r5 ) {\\\\n\\\\t\\\\t\\\\tmip = ( r4 - roughness ) * ( m5 - m4 ) / ( r4 - r5 ) + m4;\\\\n\\\\t\\\\t} else if ( roughness >= r6 ) {\\\\n\\\\t\\\\t\\\\tmip = ( r5 - roughness ) * ( m6 - m5 ) / ( r5 - r6 ) + m5;\\\\n\\\\t\\\\t} else {\\\\n\\\\t\\\\t\\\\tmip = - 2.0 * log2( 1.16 * roughness );\\\\t\\\\t}\\\\n\\\\t\\\\treturn mip;\\\\n\\\\t}\\\\n\\\\tvec4 textureCubeUV( sampler2D envMap, vec3 sampleDir, float roughness ) {\\\\n\\\\t\\\\tfloat mip = clamp( roughnessToMip( roughness ), m0, cubeUV_maxMipLevel );\\\\n\\\\t\\\\tfloat mipF = fract( mip );\\\\n\\\\t\\\\tfloat mipInt = floor( mip );\\\\n\\\\t\\\\tvec3 color0 = bilinearCubeUV( envMap, sampleDir, mipInt );\\\\n\\\\t\\\\tif ( mipF == 0.0 ) {\\\\n\\\\t\\\\t\\\\treturn vec4( color0, 1.0 );\\\\n\\\\t\\\\t} else {\\\\n\\\\t\\\\t\\\\tvec3 color1 = bilinearCubeUV( envMap, sampleDir, mipInt + 1.0 );\\\\n\\\\t\\\\t\\\\treturn vec4( mix( color0, color1, mipF ), 1.0 );\\\\n\\\\t\\\\t}\\\\n\\\\t}\\\\n#endif\\\\\\\",defaultnormal_vertex:\\\\\\\"vec3 transformedNormal = objectNormal;\\\\n#ifdef USE_INSTANCING\\\\n\\\\tmat3 m = mat3( instanceMatrix );\\\\n\\\\ttransformedNormal /= vec3( dot( m[ 0 ], m[ 0 ] ), dot( m[ 1 ], m[ 1 ] ), dot( m[ 2 ], m[ 2 ] ) );\\\\n\\\\ttransformedNormal = m * transformedNormal;\\\\n#endif\\\\ntransformedNormal = normalMatrix * transformedNormal;\\\\n#ifdef FLIP_SIDED\\\\n\\\\ttransformedNormal = - transformedNormal;\\\\n#endif\\\\n#ifdef USE_TANGENT\\\\n\\\\tvec3 transformedTangent = ( modelViewMatrix * vec4( objectTangent, 0.0 ) ).xyz;\\\\n\\\\t#ifdef FLIP_SIDED\\\\n\\\\t\\\\ttransformedTangent = - transformedTangent;\\\\n\\\\t#endif\\\\n#endif\\\\\\\",displacementmap_pars_vertex:\\\\\\\"#ifdef USE_DISPLACEMENTMAP\\\\n\\\\tuniform sampler2D displacementMap;\\\\n\\\\tuniform float displacementScale;\\\\n\\\\tuniform float displacementBias;\\\\n#endif\\\\\\\",displacementmap_vertex:\\\\\\\"#ifdef USE_DISPLACEMENTMAP\\\\n\\\\ttransformed += normalize( objectNormal ) * ( texture2D( displacementMap, vUv ).x * displacementScale + displacementBias );\\\\n#endif\\\\\\\",emissivemap_fragment:\\\\\\\"#ifdef USE_EMISSIVEMAP\\\\n\\\\tvec4 emissiveColor = texture2D( emissiveMap, vUv );\\\\n\\\\temissiveColor.rgb = emissiveMapTexelToLinear( emissiveColor ).rgb;\\\\n\\\\ttotalEmissiveRadiance *= emissiveColor.rgb;\\\\n#endif\\\\\\\",emissivemap_pars_fragment:\\\\\\\"#ifdef USE_EMISSIVEMAP\\\\n\\\\tuniform sampler2D emissiveMap;\\\\n#endif\\\\\\\",encodings_fragment:\\\\\\\"gl_FragColor = linearToOutputTexel( gl_FragColor );\\\\\\\",encodings_pars_fragment:\\\\\\\"\\\\nvec4 LinearToLinear( in vec4 value ) {\\\\n\\\\treturn value;\\\\n}\\\\nvec4 GammaToLinear( in vec4 value, in float gammaFactor ) {\\\\n\\\\treturn vec4( pow( value.rgb, vec3( gammaFactor ) ), value.a );\\\\n}\\\\nvec4 LinearToGamma( in vec4 value, in float gammaFactor ) {\\\\n\\\\treturn vec4( pow( value.rgb, vec3( 1.0 / gammaFactor ) ), value.a );\\\\n}\\\\nvec4 sRGBToLinear( in vec4 value ) {\\\\n\\\\treturn vec4( mix( pow( value.rgb * 0.9478672986 + vec3( 0.0521327014 ), vec3( 2.4 ) ), value.rgb * 0.0773993808, vec3( lessThanEqual( value.rgb, vec3( 0.04045 ) ) ) ), value.a );\\\\n}\\\\nvec4 LinearTosRGB( in vec4 value ) {\\\\n\\\\treturn vec4( mix( pow( value.rgb, vec3( 0.41666 ) ) * 1.055 - vec3( 0.055 ), value.rgb * 12.92, vec3( lessThanEqual( value.rgb, vec3( 0.0031308 ) ) ) ), value.a );\\\\n}\\\\nvec4 RGBEToLinear( in vec4 value ) {\\\\n\\\\treturn vec4( value.rgb * exp2( value.a * 255.0 - 128.0 ), 1.0 );\\\\n}\\\\nvec4 LinearToRGBE( in vec4 value ) {\\\\n\\\\tfloat maxComponent = max( max( value.r, value.g ), value.b );\\\\n\\\\tfloat fExp = clamp( ceil( log2( maxComponent ) ), -128.0, 127.0 );\\\\n\\\\treturn vec4( value.rgb / exp2( fExp ), ( fExp + 128.0 ) / 255.0 );\\\\n}\\\\nvec4 RGBMToLinear( in vec4 value, in float maxRange ) {\\\\n\\\\treturn vec4( value.rgb * value.a * maxRange, 1.0 );\\\\n}\\\\nvec4 LinearToRGBM( in vec4 value, in float maxRange ) {\\\\n\\\\tfloat maxRGB = max( value.r, max( value.g, value.b ) );\\\\n\\\\tfloat M = clamp( maxRGB / maxRange, 0.0, 1.0 );\\\\n\\\\tM = ceil( M * 255.0 ) / 255.0;\\\\n\\\\treturn vec4( value.rgb / ( M * maxRange ), M );\\\\n}\\\\nvec4 RGBDToLinear( in vec4 value, in float maxRange ) {\\\\n\\\\treturn vec4( value.rgb * ( ( maxRange / 255.0 ) / value.a ), 1.0 );\\\\n}\\\\nvec4 LinearToRGBD( in vec4 value, in float maxRange ) {\\\\n\\\\tfloat maxRGB = max( value.r, max( value.g, value.b ) );\\\\n\\\\tfloat D = max( maxRange / maxRGB, 1.0 );\\\\n\\\\tD = clamp( floor( D ) / 255.0, 0.0, 1.0 );\\\\n\\\\treturn vec4( value.rgb * ( D * ( 255.0 / maxRange ) ), D );\\\\n}\\\\nconst mat3 cLogLuvM = mat3( 0.2209, 0.3390, 0.4184, 0.1138, 0.6780, 0.7319, 0.0102, 0.1130, 0.2969 );\\\\nvec4 LinearToLogLuv( in vec4 value ) {\\\\n\\\\tvec3 Xp_Y_XYZp = cLogLuvM * value.rgb;\\\\n\\\\tXp_Y_XYZp = max( Xp_Y_XYZp, vec3( 1e-6, 1e-6, 1e-6 ) );\\\\n\\\\tvec4 vResult;\\\\n\\\\tvResult.xy = Xp_Y_XYZp.xy / Xp_Y_XYZp.z;\\\\n\\\\tfloat Le = 2.0 * log2(Xp_Y_XYZp.y) + 127.0;\\\\n\\\\tvResult.w = fract( Le );\\\\n\\\\tvResult.z = ( Le - ( floor( vResult.w * 255.0 ) ) / 255.0 ) / 255.0;\\\\n\\\\treturn vResult;\\\\n}\\\\nconst mat3 cLogLuvInverseM = mat3( 6.0014, -2.7008, -1.7996, -1.3320, 3.1029, -5.7721, 0.3008, -1.0882, 5.6268 );\\\\nvec4 LogLuvToLinear( in vec4 value ) {\\\\n\\\\tfloat Le = value.z * 255.0 + value.w;\\\\n\\\\tvec3 Xp_Y_XYZp;\\\\n\\\\tXp_Y_XYZp.y = exp2( ( Le - 127.0 ) / 2.0 );\\\\n\\\\tXp_Y_XYZp.z = Xp_Y_XYZp.y / value.y;\\\\n\\\\tXp_Y_XYZp.x = value.x * Xp_Y_XYZp.z;\\\\n\\\\tvec3 vRGB = cLogLuvInverseM * Xp_Y_XYZp.rgb;\\\\n\\\\treturn vec4( max( vRGB, 0.0 ), 1.0 );\\\\n}\\\\\\\",envmap_fragment:\\\\\\\"#ifdef USE_ENVMAP\\\\n\\\\t#ifdef ENV_WORLDPOS\\\\n\\\\t\\\\tvec3 cameraToFrag;\\\\n\\\\t\\\\tif ( isOrthographic ) {\\\\n\\\\t\\\\t\\\\tcameraToFrag = normalize( vec3( - viewMatrix[ 0 ][ 2 ], - viewMatrix[ 1 ][ 2 ], - viewMatrix[ 2 ][ 2 ] ) );\\\\n\\\\t\\\\t} else {\\\\n\\\\t\\\\t\\\\tcameraToFrag = normalize( vWorldPosition - cameraPosition );\\\\n\\\\t\\\\t}\\\\n\\\\t\\\\tvec3 worldNormal = inverseTransformDirection( normal, viewMatrix );\\\\n\\\\t\\\\t#ifdef ENVMAP_MODE_REFLECTION\\\\n\\\\t\\\\t\\\\tvec3 reflectVec = reflect( cameraToFrag, worldNormal );\\\\n\\\\t\\\\t#else\\\\n\\\\t\\\\t\\\\tvec3 reflectVec = refract( cameraToFrag, worldNormal, refractionRatio );\\\\n\\\\t\\\\t#endif\\\\n\\\\t#else\\\\n\\\\t\\\\tvec3 reflectVec = vReflect;\\\\n\\\\t#endif\\\\n\\\\t#ifdef ENVMAP_TYPE_CUBE\\\\n\\\\t\\\\tvec4 envColor = textureCube( envMap, vec3( flipEnvMap * reflectVec.x, reflectVec.yz ) );\\\\n\\\\t\\\\tenvColor = envMapTexelToLinear( envColor );\\\\n\\\\t#elif defined( ENVMAP_TYPE_CUBE_UV )\\\\n\\\\t\\\\tvec4 envColor = textureCubeUV( envMap, reflectVec, 0.0 );\\\\n\\\\t#else\\\\n\\\\t\\\\tvec4 envColor = vec4( 0.0 );\\\\n\\\\t#endif\\\\n\\\\t#ifdef ENVMAP_BLENDING_MULTIPLY\\\\n\\\\t\\\\toutgoingLight = mix( outgoingLight, outgoingLight * envColor.xyz, specularStrength * reflectivity );\\\\n\\\\t#elif defined( ENVMAP_BLENDING_MIX )\\\\n\\\\t\\\\toutgoingLight = mix( outgoingLight, envColor.xyz, specularStrength * reflectivity );\\\\n\\\\t#elif defined( ENVMAP_BLENDING_ADD )\\\\n\\\\t\\\\toutgoingLight += envColor.xyz * specularStrength * reflectivity;\\\\n\\\\t#endif\\\\n#endif\\\\\\\",envmap_common_pars_fragment:\\\\\\\"#ifdef USE_ENVMAP\\\\n\\\\tuniform float envMapIntensity;\\\\n\\\\tuniform float flipEnvMap;\\\\n\\\\tuniform int maxMipLevel;\\\\n\\\\t#ifdef ENVMAP_TYPE_CUBE\\\\n\\\\t\\\\tuniform samplerCube envMap;\\\\n\\\\t#else\\\\n\\\\t\\\\tuniform sampler2D envMap;\\\\n\\\\t#endif\\\\n\\\\t\\\\n#endif\\\\\\\",envmap_pars_fragment:\\\\\\\"#ifdef USE_ENVMAP\\\\n\\\\tuniform float reflectivity;\\\\n\\\\t#if defined( USE_BUMPMAP ) || defined( USE_NORMALMAP ) || defined( PHONG )\\\\n\\\\t\\\\t#define ENV_WORLDPOS\\\\n\\\\t#endif\\\\n\\\\t#ifdef ENV_WORLDPOS\\\\n\\\\t\\\\tvarying vec3 vWorldPosition;\\\\n\\\\t\\\\tuniform float refractionRatio;\\\\n\\\\t#else\\\\n\\\\t\\\\tvarying vec3 vReflect;\\\\n\\\\t#endif\\\\n#endif\\\\\\\",envmap_pars_vertex:\\\\\\\"#ifdef USE_ENVMAP\\\\n\\\\t#if defined( USE_BUMPMAP ) || defined( USE_NORMALMAP ) ||defined( PHONG )\\\\n\\\\t\\\\t#define ENV_WORLDPOS\\\\n\\\\t#endif\\\\n\\\\t#ifdef ENV_WORLDPOS\\\\n\\\\t\\\\t\\\\n\\\\t\\\\tvarying vec3 vWorldPosition;\\\\n\\\\t#else\\\\n\\\\t\\\\tvarying vec3 vReflect;\\\\n\\\\t\\\\tuniform float refractionRatio;\\\\n\\\\t#endif\\\\n#endif\\\\\\\",envmap_physical_pars_fragment:\\\\\\\"#if defined( USE_ENVMAP )\\\\n\\\\t#ifdef ENVMAP_MODE_REFRACTION\\\\n\\\\t\\\\tuniform float refractionRatio;\\\\n\\\\t#endif\\\\n\\\\tvec3 getIBLIrradiance( const in vec3 normal ) {\\\\n\\\\t\\\\t#if defined( ENVMAP_TYPE_CUBE_UV )\\\\n\\\\t\\\\t\\\\tvec3 worldNormal = inverseTransformDirection( normal, viewMatrix );\\\\n\\\\t\\\\t\\\\tvec4 envMapColor = textureCubeUV( envMap, worldNormal, 1.0 );\\\\n\\\\t\\\\t\\\\treturn PI * envMapColor.rgb * envMapIntensity;\\\\n\\\\t\\\\t#else\\\\n\\\\t\\\\t\\\\treturn vec3( 0.0 );\\\\n\\\\t\\\\t#endif\\\\n\\\\t}\\\\n\\\\tvec3 getIBLRadiance( const in vec3 viewDir, const in vec3 normal, const in float roughness ) {\\\\n\\\\t\\\\t#if defined( ENVMAP_TYPE_CUBE_UV )\\\\n\\\\t\\\\t\\\\tvec3 reflectVec;\\\\n\\\\t\\\\t\\\\t#ifdef ENVMAP_MODE_REFLECTION\\\\n\\\\t\\\\t\\\\t\\\\treflectVec = reflect( - viewDir, normal );\\\\n\\\\t\\\\t\\\\t\\\\treflectVec = normalize( mix( reflectVec, normal, roughness * roughness) );\\\\n\\\\t\\\\t\\\\t#else\\\\n\\\\t\\\\t\\\\t\\\\treflectVec = refract( - viewDir, normal, refractionRatio );\\\\n\\\\t\\\\t\\\\t#endif\\\\n\\\\t\\\\t\\\\treflectVec = inverseTransformDirection( reflectVec, viewMatrix );\\\\n\\\\t\\\\t\\\\tvec4 envMapColor = textureCubeUV( envMap, reflectVec, roughness );\\\\n\\\\t\\\\t\\\\treturn envMapColor.rgb * envMapIntensity;\\\\n\\\\t\\\\t#else\\\\n\\\\t\\\\t\\\\treturn vec3( 0.0 );\\\\n\\\\t\\\\t#endif\\\\n\\\\t}\\\\n#endif\\\\\\\",envmap_vertex:\\\\\\\"#ifdef USE_ENVMAP\\\\n\\\\t#ifdef ENV_WORLDPOS\\\\n\\\\t\\\\tvWorldPosition = worldPosition.xyz;\\\\n\\\\t#else\\\\n\\\\t\\\\tvec3 cameraToVertex;\\\\n\\\\t\\\\tif ( isOrthographic ) {\\\\n\\\\t\\\\t\\\\tcameraToVertex = normalize( vec3( - viewMatrix[ 0 ][ 2 ], - viewMatrix[ 1 ][ 2 ], - viewMatrix[ 2 ][ 2 ] ) );\\\\n\\\\t\\\\t} else {\\\\n\\\\t\\\\t\\\\tcameraToVertex = normalize( worldPosition.xyz - cameraPosition );\\\\n\\\\t\\\\t}\\\\n\\\\t\\\\tvec3 worldNormal = inverseTransformDirection( transformedNormal, viewMatrix );\\\\n\\\\t\\\\t#ifdef ENVMAP_MODE_REFLECTION\\\\n\\\\t\\\\t\\\\tvReflect = reflect( cameraToVertex, worldNormal );\\\\n\\\\t\\\\t#else\\\\n\\\\t\\\\t\\\\tvReflect = refract( cameraToVertex, worldNormal, refractionRatio );\\\\n\\\\t\\\\t#endif\\\\n\\\\t#endif\\\\n#endif\\\\\\\",fog_vertex:\\\\\\\"#ifdef USE_FOG\\\\n\\\\tvFogDepth = - mvPosition.z;\\\\n#endif\\\\\\\",fog_pars_vertex:\\\\\\\"#ifdef USE_FOG\\\\n\\\\tvarying float vFogDepth;\\\\n#endif\\\\\\\",fog_fragment:\\\\\\\"#ifdef USE_FOG\\\\n\\\\t#ifdef FOG_EXP2\\\\n\\\\t\\\\tfloat fogFactor = 1.0 - exp( - fogDensity * fogDensity * vFogDepth * vFogDepth );\\\\n\\\\t#else\\\\n\\\\t\\\\tfloat fogFactor = smoothstep( fogNear, fogFar, vFogDepth );\\\\n\\\\t#endif\\\\n\\\\tgl_FragColor.rgb = mix( gl_FragColor.rgb, fogColor, fogFactor );\\\\n#endif\\\\\\\",fog_pars_fragment:\\\\\\\"#ifdef USE_FOG\\\\n\\\\tuniform vec3 fogColor;\\\\n\\\\tvarying float vFogDepth;\\\\n\\\\t#ifdef FOG_EXP2\\\\n\\\\t\\\\tuniform float fogDensity;\\\\n\\\\t#else\\\\n\\\\t\\\\tuniform float fogNear;\\\\n\\\\t\\\\tuniform float fogFar;\\\\n\\\\t#endif\\\\n#endif\\\\\\\",gradientmap_pars_fragment:\\\\\\\"#ifdef USE_GRADIENTMAP\\\\n\\\\tuniform sampler2D gradientMap;\\\\n#endif\\\\nvec3 getGradientIrradiance( vec3 normal, vec3 lightDirection ) {\\\\n\\\\tfloat dotNL = dot( normal, lightDirection );\\\\n\\\\tvec2 coord = vec2( dotNL * 0.5 + 0.5, 0.0 );\\\\n\\\\t#ifdef USE_GRADIENTMAP\\\\n\\\\t\\\\treturn texture2D( gradientMap, coord ).rgb;\\\\n\\\\t#else\\\\n\\\\t\\\\treturn ( coord.x < 0.7 ) ? vec3( 0.7 ) : vec3( 1.0 );\\\\n\\\\t#endif\\\\n}\\\\\\\",lightmap_fragment:\\\\\\\"#ifdef USE_LIGHTMAP\\\\n\\\\tvec4 lightMapTexel = texture2D( lightMap, vUv2 );\\\\n\\\\tvec3 lightMapIrradiance = lightMapTexelToLinear( lightMapTexel ).rgb * lightMapIntensity;\\\\n\\\\t#ifndef PHYSICALLY_CORRECT_LIGHTS\\\\n\\\\t\\\\tlightMapIrradiance *= PI;\\\\n\\\\t#endif\\\\n\\\\treflectedLight.indirectDiffuse += lightMapIrradiance;\\\\n#endif\\\\\\\",lightmap_pars_fragment:\\\\\\\"#ifdef USE_LIGHTMAP\\\\n\\\\tuniform sampler2D lightMap;\\\\n\\\\tuniform float lightMapIntensity;\\\\n#endif\\\\\\\",lights_lambert_vertex:\\\\\\\"vec3 diffuse = vec3( 1.0 );\\\\nGeometricContext geometry;\\\\ngeometry.position = mvPosition.xyz;\\\\ngeometry.normal = normalize( transformedNormal );\\\\ngeometry.viewDir = ( isOrthographic ) ? vec3( 0, 0, 1 ) : normalize( -mvPosition.xyz );\\\\nGeometricContext backGeometry;\\\\nbackGeometry.position = geometry.position;\\\\nbackGeometry.normal = -geometry.normal;\\\\nbackGeometry.viewDir = geometry.viewDir;\\\\nvLightFront = vec3( 0.0 );\\\\nvIndirectFront = vec3( 0.0 );\\\\n#ifdef DOUBLE_SIDED\\\\n\\\\tvLightBack = vec3( 0.0 );\\\\n\\\\tvIndirectBack = vec3( 0.0 );\\\\n#endif\\\\nIncidentLight directLight;\\\\nfloat dotNL;\\\\nvec3 directLightColor_Diffuse;\\\\nvIndirectFront += getAmbientLightIrradiance( ambientLightColor );\\\\nvIndirectFront += getLightProbeIrradiance( lightProbe, geometry.normal );\\\\n#ifdef DOUBLE_SIDED\\\\n\\\\tvIndirectBack += getAmbientLightIrradiance( ambientLightColor );\\\\n\\\\tvIndirectBack += getLightProbeIrradiance( lightProbe, backGeometry.normal );\\\\n#endif\\\\n#if NUM_POINT_LIGHTS > 0\\\\n\\\\t#pragma unroll_loop_start\\\\n\\\\tfor ( int i = 0; i < NUM_POINT_LIGHTS; i ++ ) {\\\\n\\\\t\\\\tgetPointLightInfo( pointLights[ i ], geometry, directLight );\\\\n\\\\t\\\\tdotNL = dot( geometry.normal, directLight.direction );\\\\n\\\\t\\\\tdirectLightColor_Diffuse = directLight.color;\\\\n\\\\t\\\\tvLightFront += saturate( dotNL ) * directLightColor_Diffuse;\\\\n\\\\t\\\\t#ifdef DOUBLE_SIDED\\\\n\\\\t\\\\t\\\\tvLightBack += saturate( - dotNL ) * directLightColor_Diffuse;\\\\n\\\\t\\\\t#endif\\\\n\\\\t}\\\\n\\\\t#pragma unroll_loop_end\\\\n#endif\\\\n#if NUM_SPOT_LIGHTS > 0\\\\n\\\\t#pragma unroll_loop_start\\\\n\\\\tfor ( int i = 0; i < NUM_SPOT_LIGHTS; i ++ ) {\\\\n\\\\t\\\\tgetSpotLightInfo( spotLights[ i ], geometry, directLight );\\\\n\\\\t\\\\tdotNL = dot( geometry.normal, directLight.direction );\\\\n\\\\t\\\\tdirectLightColor_Diffuse = directLight.color;\\\\n\\\\t\\\\tvLightFront += saturate( dotNL ) * directLightColor_Diffuse;\\\\n\\\\t\\\\t#ifdef DOUBLE_SIDED\\\\n\\\\t\\\\t\\\\tvLightBack += saturate( - dotNL ) * directLightColor_Diffuse;\\\\n\\\\t\\\\t#endif\\\\n\\\\t}\\\\n\\\\t#pragma unroll_loop_end\\\\n#endif\\\\n#if NUM_DIR_LIGHTS > 0\\\\n\\\\t#pragma unroll_loop_start\\\\n\\\\tfor ( int i = 0; i < NUM_DIR_LIGHTS; i ++ ) {\\\\n\\\\t\\\\tgetDirectionalLightInfo( directionalLights[ i ], geometry, directLight );\\\\n\\\\t\\\\tdotNL = dot( geometry.normal, directLight.direction );\\\\n\\\\t\\\\tdirectLightColor_Diffuse = directLight.color;\\\\n\\\\t\\\\tvLightFront += saturate( dotNL ) * directLightColor_Diffuse;\\\\n\\\\t\\\\t#ifdef DOUBLE_SIDED\\\\n\\\\t\\\\t\\\\tvLightBack += saturate( - dotNL ) * directLightColor_Diffuse;\\\\n\\\\t\\\\t#endif\\\\n\\\\t}\\\\n\\\\t#pragma unroll_loop_end\\\\n#endif\\\\n#if NUM_HEMI_LIGHTS > 0\\\\n\\\\t#pragma unroll_loop_start\\\\n\\\\tfor ( int i = 0; i < NUM_HEMI_LIGHTS; i ++ ) {\\\\n\\\\t\\\\tvIndirectFront += getHemisphereLightIrradiance( hemisphereLights[ i ], geometry.normal );\\\\n\\\\t\\\\t#ifdef DOUBLE_SIDED\\\\n\\\\t\\\\t\\\\tvIndirectBack += getHemisphereLightIrradiance( hemisphereLights[ i ], backGeometry.normal );\\\\n\\\\t\\\\t#endif\\\\n\\\\t}\\\\n\\\\t#pragma unroll_loop_end\\\\n#endif\\\\\\\",lights_pars_begin:\\\\\\\"uniform bool receiveShadow;\\\\nuniform vec3 ambientLightColor;\\\\nuniform vec3 lightProbe[ 9 ];\\\\nvec3 shGetIrradianceAt( in vec3 normal, in vec3 shCoefficients[ 9 ] ) {\\\\n\\\\tfloat x = normal.x, y = normal.y, z = normal.z;\\\\n\\\\tvec3 result = shCoefficients[ 0 ] * 0.886227;\\\\n\\\\tresult += shCoefficients[ 1 ] * 2.0 * 0.511664 * y;\\\\n\\\\tresult += shCoefficients[ 2 ] * 2.0 * 0.511664 * z;\\\\n\\\\tresult += shCoefficients[ 3 ] * 2.0 * 0.511664 * x;\\\\n\\\\tresult += shCoefficients[ 4 ] * 2.0 * 0.429043 * x * y;\\\\n\\\\tresult += shCoefficients[ 5 ] * 2.0 * 0.429043 * y * z;\\\\n\\\\tresult += shCoefficients[ 6 ] * ( 0.743125 * z * z - 0.247708 );\\\\n\\\\tresult += shCoefficients[ 7 ] * 2.0 * 0.429043 * x * z;\\\\n\\\\tresult += shCoefficients[ 8 ] * 0.429043 * ( x * x - y * y );\\\\n\\\\treturn result;\\\\n}\\\\nvec3 getLightProbeIrradiance( const in vec3 lightProbe[ 9 ], const in vec3 normal ) {\\\\n\\\\tvec3 worldNormal = inverseTransformDirection( normal, viewMatrix );\\\\n\\\\tvec3 irradiance = shGetIrradianceAt( worldNormal, lightProbe );\\\\n\\\\treturn irradiance;\\\\n}\\\\nvec3 getAmbientLightIrradiance( const in vec3 ambientLightColor ) {\\\\n\\\\tvec3 irradiance = ambientLightColor;\\\\n\\\\treturn irradiance;\\\\n}\\\\nfloat getDistanceAttenuation( const in float lightDistance, const in float cutoffDistance, const in float decayExponent ) {\\\\n\\\\t#if defined ( PHYSICALLY_CORRECT_LIGHTS )\\\\n\\\\t\\\\tfloat distanceFalloff = 1.0 / max( pow( lightDistance, decayExponent ), 0.01 );\\\\n\\\\t\\\\tif ( cutoffDistance > 0.0 ) {\\\\n\\\\t\\\\t\\\\tdistanceFalloff *= pow2( saturate( 1.0 - pow4( lightDistance / cutoffDistance ) ) );\\\\n\\\\t\\\\t}\\\\n\\\\t\\\\treturn distanceFalloff;\\\\n\\\\t#else\\\\n\\\\t\\\\tif ( cutoffDistance > 0.0 && decayExponent > 0.0 ) {\\\\n\\\\t\\\\t\\\\treturn pow( saturate( - lightDistance / cutoffDistance + 1.0 ), decayExponent );\\\\n\\\\t\\\\t}\\\\n\\\\t\\\\treturn 1.0;\\\\n\\\\t#endif\\\\n}\\\\nfloat getSpotAttenuation( const in float coneCosine, const in float penumbraCosine, const in float angleCosine ) {\\\\n\\\\treturn smoothstep( coneCosine, penumbraCosine, angleCosine );\\\\n}\\\\n#if NUM_DIR_LIGHTS > 0\\\\n\\\\tstruct DirectionalLight {\\\\n\\\\t\\\\tvec3 direction;\\\\n\\\\t\\\\tvec3 color;\\\\n\\\\t};\\\\n\\\\tuniform DirectionalLight directionalLights[ NUM_DIR_LIGHTS ];\\\\n\\\\tvoid getDirectionalLightInfo( const in DirectionalLight directionalLight, const in GeometricContext geometry, out IncidentLight light ) {\\\\n\\\\t\\\\tlight.color = directionalLight.color;\\\\n\\\\t\\\\tlight.direction = directionalLight.direction;\\\\n\\\\t\\\\tlight.visible = true;\\\\n\\\\t}\\\\n#endif\\\\n#if NUM_POINT_LIGHTS > 0\\\\n\\\\tstruct PointLight {\\\\n\\\\t\\\\tvec3 position;\\\\n\\\\t\\\\tvec3 color;\\\\n\\\\t\\\\tfloat distance;\\\\n\\\\t\\\\tfloat decay;\\\\n\\\\t};\\\\n\\\\tuniform PointLight pointLights[ NUM_POINT_LIGHTS ];\\\\n\\\\tvoid getPointLightInfo( const in PointLight pointLight, const in GeometricContext geometry, out IncidentLight light ) {\\\\n\\\\t\\\\tvec3 lVector = pointLight.position - geometry.position;\\\\n\\\\t\\\\tlight.direction = normalize( lVector );\\\\n\\\\t\\\\tfloat lightDistance = length( lVector );\\\\n\\\\t\\\\tlight.color = pointLight.color;\\\\n\\\\t\\\\tlight.color *= getDistanceAttenuation( lightDistance, pointLight.distance, pointLight.decay );\\\\n\\\\t\\\\tlight.visible = ( light.color != vec3( 0.0 ) );\\\\n\\\\t}\\\\n#endif\\\\n#if NUM_SPOT_LIGHTS > 0\\\\n\\\\tstruct SpotLight {\\\\n\\\\t\\\\tvec3 position;\\\\n\\\\t\\\\tvec3 direction;\\\\n\\\\t\\\\tvec3 color;\\\\n\\\\t\\\\tfloat distance;\\\\n\\\\t\\\\tfloat decay;\\\\n\\\\t\\\\tfloat coneCos;\\\\n\\\\t\\\\tfloat penumbraCos;\\\\n\\\\t};\\\\n\\\\tuniform SpotLight spotLights[ NUM_SPOT_LIGHTS ];\\\\n\\\\tvoid getSpotLightInfo( const in SpotLight spotLight, const in GeometricContext geometry, out IncidentLight light ) {\\\\n\\\\t\\\\tvec3 lVector = spotLight.position - geometry.position;\\\\n\\\\t\\\\tlight.direction = normalize( lVector );\\\\n\\\\t\\\\tfloat angleCos = dot( light.direction, spotLight.direction );\\\\n\\\\t\\\\tfloat spotAttenuation = getSpotAttenuation( spotLight.coneCos, spotLight.penumbraCos, angleCos );\\\\n\\\\t\\\\tif ( spotAttenuation > 0.0 ) {\\\\n\\\\t\\\\t\\\\tfloat lightDistance = length( lVector );\\\\n\\\\t\\\\t\\\\tlight.color = spotLight.color * spotAttenuation;\\\\n\\\\t\\\\t\\\\tlight.color *= getDistanceAttenuation( lightDistance, spotLight.distance, spotLight.decay );\\\\n\\\\t\\\\t\\\\tlight.visible = ( light.color != vec3( 0.0 ) );\\\\n\\\\t\\\\t} else {\\\\n\\\\t\\\\t\\\\tlight.color = vec3( 0.0 );\\\\n\\\\t\\\\t\\\\tlight.visible = false;\\\\n\\\\t\\\\t}\\\\n\\\\t}\\\\n#endif\\\\n#if NUM_RECT_AREA_LIGHTS > 0\\\\n\\\\tstruct RectAreaLight {\\\\n\\\\t\\\\tvec3 color;\\\\n\\\\t\\\\tvec3 position;\\\\n\\\\t\\\\tvec3 halfWidth;\\\\n\\\\t\\\\tvec3 halfHeight;\\\\n\\\\t};\\\\n\\\\tuniform sampler2D ltc_1;\\\\tuniform sampler2D ltc_2;\\\\n\\\\tuniform RectAreaLight rectAreaLights[ NUM_RECT_AREA_LIGHTS ];\\\\n#endif\\\\n#if NUM_HEMI_LIGHTS > 0\\\\n\\\\tstruct HemisphereLight {\\\\n\\\\t\\\\tvec3 direction;\\\\n\\\\t\\\\tvec3 skyColor;\\\\n\\\\t\\\\tvec3 groundColor;\\\\n\\\\t};\\\\n\\\\tuniform HemisphereLight hemisphereLights[ NUM_HEMI_LIGHTS ];\\\\n\\\\tvec3 getHemisphereLightIrradiance( const in HemisphereLight hemiLight, const in vec3 normal ) {\\\\n\\\\t\\\\tfloat dotNL = dot( normal, hemiLight.direction );\\\\n\\\\t\\\\tfloat hemiDiffuseWeight = 0.5 * dotNL + 0.5;\\\\n\\\\t\\\\tvec3 irradiance = mix( hemiLight.groundColor, hemiLight.skyColor, hemiDiffuseWeight );\\\\n\\\\t\\\\treturn irradiance;\\\\n\\\\t}\\\\n#endif\\\\\\\",lights_toon_fragment:\\\\\\\"ToonMaterial material;\\\\nmaterial.diffuseColor = diffuseColor.rgb;\\\\\\\",lights_toon_pars_fragment:\\\\\\\"varying vec3 vViewPosition;\\\\nstruct ToonMaterial {\\\\n\\\\tvec3 diffuseColor;\\\\n};\\\\nvoid RE_Direct_Toon( const in IncidentLight directLight, const in GeometricContext geometry, const in ToonMaterial material, inout ReflectedLight reflectedLight ) {\\\\n\\\\tvec3 irradiance = getGradientIrradiance( geometry.normal, directLight.direction ) * directLight.color;\\\\n\\\\treflectedLight.directDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );\\\\n}\\\\nvoid RE_IndirectDiffuse_Toon( const in vec3 irradiance, const in GeometricContext geometry, const in ToonMaterial material, inout ReflectedLight reflectedLight ) {\\\\n\\\\treflectedLight.indirectDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );\\\\n}\\\\n#define RE_Direct\\\\t\\\\t\\\\t\\\\tRE_Direct_Toon\\\\n#define RE_IndirectDiffuse\\\\t\\\\tRE_IndirectDiffuse_Toon\\\\n#define Material_LightProbeLOD( material )\\\\t(0)\\\\\\\",lights_phong_fragment:\\\\\\\"BlinnPhongMaterial material;\\\\nmaterial.diffuseColor = diffuseColor.rgb;\\\\nmaterial.specularColor = specular;\\\\nmaterial.specularShininess = shininess;\\\\nmaterial.specularStrength = specularStrength;\\\\\\\",lights_phong_pars_fragment:\\\\\\\"varying vec3 vViewPosition;\\\\nstruct BlinnPhongMaterial {\\\\n\\\\tvec3 diffuseColor;\\\\n\\\\tvec3 specularColor;\\\\n\\\\tfloat specularShininess;\\\\n\\\\tfloat specularStrength;\\\\n};\\\\nvoid RE_Direct_BlinnPhong( const in IncidentLight directLight, const in GeometricContext geometry, const in BlinnPhongMaterial material, inout ReflectedLight reflectedLight ) {\\\\n\\\\tfloat dotNL = saturate( dot( geometry.normal, directLight.direction ) );\\\\n\\\\tvec3 irradiance = dotNL * directLight.color;\\\\n\\\\treflectedLight.directDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );\\\\n\\\\treflectedLight.directSpecular += irradiance * BRDF_BlinnPhong( directLight.direction, geometry.viewDir, geometry.normal, material.specularColor, material.specularShininess ) * material.specularStrength;\\\\n}\\\\nvoid RE_IndirectDiffuse_BlinnPhong( const in vec3 irradiance, const in GeometricContext geometry, const in BlinnPhongMaterial material, inout ReflectedLight reflectedLight ) {\\\\n\\\\treflectedLight.indirectDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );\\\\n}\\\\n#define RE_Direct\\\\t\\\\t\\\\t\\\\tRE_Direct_BlinnPhong\\\\n#define RE_IndirectDiffuse\\\\t\\\\tRE_IndirectDiffuse_BlinnPhong\\\\n#define Material_LightProbeLOD( material )\\\\t(0)\\\\\\\",lights_physical_fragment:\\\\\\\"PhysicalMaterial material;\\\\nmaterial.diffuseColor = diffuseColor.rgb * ( 1.0 - metalnessFactor );\\\\nvec3 dxy = max( abs( dFdx( geometryNormal ) ), abs( dFdy( geometryNormal ) ) );\\\\nfloat geometryRoughness = max( max( dxy.x, dxy.y ), dxy.z );\\\\nmaterial.roughness = max( roughnessFactor, 0.0525 );material.roughness += geometryRoughness;\\\\nmaterial.roughness = min( material.roughness, 1.0 );\\\\n#ifdef IOR\\\\n\\\\t#ifdef SPECULAR\\\\n\\\\t\\\\tfloat specularIntensityFactor = specularIntensity;\\\\n\\\\t\\\\tvec3 specularTintFactor = specularTint;\\\\n\\\\t\\\\t#ifdef USE_SPECULARINTENSITYMAP\\\\n\\\\t\\\\t\\\\tspecularIntensityFactor *= texture2D( specularIntensityMap, vUv ).a;\\\\n\\\\t\\\\t#endif\\\\n\\\\t\\\\t#ifdef USE_SPECULARTINTMAP\\\\n\\\\t\\\\t\\\\tspecularTintFactor *= specularTintMapTexelToLinear( texture2D( specularTintMap, vUv ) ).rgb;\\\\n\\\\t\\\\t#endif\\\\n\\\\t\\\\tmaterial.specularF90 = mix( specularIntensityFactor, 1.0, metalnessFactor );\\\\n\\\\t#else\\\\n\\\\t\\\\tfloat specularIntensityFactor = 1.0;\\\\n\\\\t\\\\tvec3 specularTintFactor = vec3( 1.0 );\\\\n\\\\t\\\\tmaterial.specularF90 = 1.0;\\\\n\\\\t#endif\\\\n\\\\tmaterial.specularColor = mix( min( pow2( ( ior - 1.0 ) / ( ior + 1.0 ) ) * specularTintFactor, vec3( 1.0 ) ) * specularIntensityFactor, diffuseColor.rgb, metalnessFactor );\\\\n#else\\\\n\\\\tmaterial.specularColor = mix( vec3( 0.04 ), diffuseColor.rgb, metalnessFactor );\\\\n\\\\tmaterial.specularF90 = 1.0;\\\\n#endif\\\\n#ifdef USE_CLEARCOAT\\\\n\\\\tmaterial.clearcoat = clearcoat;\\\\n\\\\tmaterial.clearcoatRoughness = clearcoatRoughness;\\\\n\\\\tmaterial.clearcoatF0 = vec3( 0.04 );\\\\n\\\\tmaterial.clearcoatF90 = 1.0;\\\\n\\\\t#ifdef USE_CLEARCOATMAP\\\\n\\\\t\\\\tmaterial.clearcoat *= texture2D( clearcoatMap, vUv ).x;\\\\n\\\\t#endif\\\\n\\\\t#ifdef USE_CLEARCOAT_ROUGHNESSMAP\\\\n\\\\t\\\\tmaterial.clearcoatRoughness *= texture2D( clearcoatRoughnessMap, vUv ).y;\\\\n\\\\t#endif\\\\n\\\\tmaterial.clearcoat = saturate( material.clearcoat );\\\\tmaterial.clearcoatRoughness = max( material.clearcoatRoughness, 0.0525 );\\\\n\\\\tmaterial.clearcoatRoughness += geometryRoughness;\\\\n\\\\tmaterial.clearcoatRoughness = min( material.clearcoatRoughness, 1.0 );\\\\n#endif\\\\n#ifdef USE_SHEEN\\\\n\\\\tmaterial.sheenTint = sheenTint;\\\\n\\\\tmaterial.sheenRoughness = clamp( sheenRoughness, 0.07, 1.0 );\\\\n#endif\\\\\\\",lights_physical_pars_fragment:\\\\\\\"struct PhysicalMaterial {\\\\n\\\\tvec3 diffuseColor;\\\\n\\\\tfloat roughness;\\\\n\\\\tvec3 specularColor;\\\\n\\\\tfloat specularF90;\\\\n\\\\t#ifdef USE_CLEARCOAT\\\\n\\\\t\\\\tfloat clearcoat;\\\\n\\\\t\\\\tfloat clearcoatRoughness;\\\\n\\\\t\\\\tvec3 clearcoatF0;\\\\n\\\\t\\\\tfloat clearcoatF90;\\\\n\\\\t#endif\\\\n\\\\t#ifdef USE_SHEEN\\\\n\\\\t\\\\tvec3 sheenTint;\\\\n\\\\t\\\\tfloat sheenRoughness;\\\\n\\\\t#endif\\\\n};\\\\nvec3 clearcoatSpecular = vec3( 0.0 );\\\\nvec2 DFGApprox( const in vec3 normal, const in vec3 viewDir, const in float roughness ) {\\\\n\\\\tfloat dotNV = saturate( dot( normal, viewDir ) );\\\\n\\\\tconst vec4 c0 = vec4( - 1, - 0.0275, - 0.572, 0.022 );\\\\n\\\\tconst vec4 c1 = vec4( 1, 0.0425, 1.04, - 0.04 );\\\\n\\\\tvec4 r = roughness * c0 + c1;\\\\n\\\\tfloat a004 = min( r.x * r.x, exp2( - 9.28 * dotNV ) ) * r.x + r.y;\\\\n\\\\tvec2 fab = vec2( - 1.04, 1.04 ) * a004 + r.zw;\\\\n\\\\treturn fab;\\\\n}\\\\nvec3 EnvironmentBRDF( const in vec3 normal, const in vec3 viewDir, const in vec3 specularColor, const in float specularF90, const in float roughness ) {\\\\n\\\\tvec2 fab = DFGApprox( normal, viewDir, roughness );\\\\n\\\\treturn specularColor * fab.x + specularF90 * fab.y;\\\\n}\\\\nvoid computeMultiscattering( const in vec3 normal, const in vec3 viewDir, const in vec3 specularColor, const in float specularF90, const in float roughness, inout vec3 singleScatter, inout vec3 multiScatter ) {\\\\n\\\\tvec2 fab = DFGApprox( normal, viewDir, roughness );\\\\n\\\\tvec3 FssEss = specularColor * fab.x + specularF90 * fab.y;\\\\n\\\\tfloat Ess = fab.x + fab.y;\\\\n\\\\tfloat Ems = 1.0 - Ess;\\\\n\\\\tvec3 Favg = specularColor + ( 1.0 - specularColor ) * 0.047619;\\\\tvec3 Fms = FssEss * Favg / ( 1.0 - Ems * Favg );\\\\n\\\\tsingleScatter += FssEss;\\\\n\\\\tmultiScatter += Fms * Ems;\\\\n}\\\\n#if NUM_RECT_AREA_LIGHTS > 0\\\\n\\\\tvoid RE_Direct_RectArea_Physical( const in RectAreaLight rectAreaLight, const in GeometricContext geometry, const in PhysicalMaterial material, inout ReflectedLight reflectedLight ) {\\\\n\\\\t\\\\tvec3 normal = geometry.normal;\\\\n\\\\t\\\\tvec3 viewDir = geometry.viewDir;\\\\n\\\\t\\\\tvec3 position = geometry.position;\\\\n\\\\t\\\\tvec3 lightPos = rectAreaLight.position;\\\\n\\\\t\\\\tvec3 halfWidth = rectAreaLight.halfWidth;\\\\n\\\\t\\\\tvec3 halfHeight = rectAreaLight.halfHeight;\\\\n\\\\t\\\\tvec3 lightColor = rectAreaLight.color;\\\\n\\\\t\\\\tfloat roughness = material.roughness;\\\\n\\\\t\\\\tvec3 rectCoords[ 4 ];\\\\n\\\\t\\\\trectCoords[ 0 ] = lightPos + halfWidth - halfHeight;\\\\t\\\\trectCoords[ 1 ] = lightPos - halfWidth - halfHeight;\\\\n\\\\t\\\\trectCoords[ 2 ] = lightPos - halfWidth + halfHeight;\\\\n\\\\t\\\\trectCoords[ 3 ] = lightPos + halfWidth + halfHeight;\\\\n\\\\t\\\\tvec2 uv = LTC_Uv( normal, viewDir, roughness );\\\\n\\\\t\\\\tvec4 t1 = texture2D( ltc_1, uv );\\\\n\\\\t\\\\tvec4 t2 = texture2D( ltc_2, uv );\\\\n\\\\t\\\\tmat3 mInv = mat3(\\\\n\\\\t\\\\t\\\\tvec3( t1.x, 0, t1.y ),\\\\n\\\\t\\\\t\\\\tvec3( 0, 1, 0 ),\\\\n\\\\t\\\\t\\\\tvec3( t1.z, 0, t1.w )\\\\n\\\\t\\\\t);\\\\n\\\\t\\\\tvec3 fresnel = ( material.specularColor * t2.x + ( vec3( 1.0 ) - material.specularColor ) * t2.y );\\\\n\\\\t\\\\treflectedLight.directSpecular += lightColor * fresnel * LTC_Evaluate( normal, viewDir, position, mInv, rectCoords );\\\\n\\\\t\\\\treflectedLight.directDiffuse += lightColor * material.diffuseColor * LTC_Evaluate( normal, viewDir, position, mat3( 1.0 ), rectCoords );\\\\n\\\\t}\\\\n#endif\\\\nvoid RE_Direct_Physical( const in IncidentLight directLight, const in GeometricContext geometry, const in PhysicalMaterial material, inout ReflectedLight reflectedLight ) {\\\\n\\\\tfloat dotNL = saturate( dot( geometry.normal, directLight.direction ) );\\\\n\\\\tvec3 irradiance = dotNL * directLight.color;\\\\n\\\\t#ifdef USE_CLEARCOAT\\\\n\\\\t\\\\tfloat dotNLcc = saturate( dot( geometry.clearcoatNormal, directLight.direction ) );\\\\n\\\\t\\\\tvec3 ccIrradiance = dotNLcc * directLight.color;\\\\n\\\\t\\\\tclearcoatSpecular += ccIrradiance * BRDF_GGX( directLight.direction, geometry.viewDir, geometry.clearcoatNormal, material.clearcoatF0, material.clearcoatF90, material.clearcoatRoughness );\\\\n\\\\t#endif\\\\n\\\\t#ifdef USE_SHEEN\\\\n\\\\t\\\\treflectedLight.directSpecular += irradiance * BRDF_Sheen( directLight.direction, geometry.viewDir, geometry.normal, material.sheenTint, material.sheenRoughness );\\\\n\\\\t#endif\\\\n\\\\treflectedLight.directSpecular += irradiance * BRDF_GGX( directLight.direction, geometry.viewDir, geometry.normal, material.specularColor, material.specularF90, material.roughness );\\\\n\\\\treflectedLight.directDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );\\\\n}\\\\nvoid RE_IndirectDiffuse_Physical( const in vec3 irradiance, const in GeometricContext geometry, const in PhysicalMaterial material, inout ReflectedLight reflectedLight ) {\\\\n\\\\treflectedLight.indirectDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );\\\\n}\\\\nvoid RE_IndirectSpecular_Physical( const in vec3 radiance, const in vec3 irradiance, const in vec3 clearcoatRadiance, const in GeometricContext geometry, const in PhysicalMaterial material, inout ReflectedLight reflectedLight) {\\\\n\\\\t#ifdef USE_CLEARCOAT\\\\n\\\\t\\\\tclearcoatSpecular += clearcoatRadiance * EnvironmentBRDF( geometry.clearcoatNormal, geometry.viewDir, material.clearcoatF0, material.clearcoatF90, material.clearcoatRoughness );\\\\n\\\\t#endif\\\\n\\\\tvec3 singleScattering = vec3( 0.0 );\\\\n\\\\tvec3 multiScattering = vec3( 0.0 );\\\\n\\\\tvec3 cosineWeightedIrradiance = irradiance * RECIPROCAL_PI;\\\\n\\\\tcomputeMultiscattering( geometry.normal, geometry.viewDir, material.specularColor, material.specularF90, material.roughness, singleScattering, multiScattering );\\\\n\\\\tvec3 diffuse = material.diffuseColor * ( 1.0 - ( singleScattering + multiScattering ) );\\\\n\\\\treflectedLight.indirectSpecular += radiance * singleScattering;\\\\n\\\\treflectedLight.indirectSpecular += multiScattering * cosineWeightedIrradiance;\\\\n\\\\treflectedLight.indirectDiffuse += diffuse * cosineWeightedIrradiance;\\\\n}\\\\n#define RE_Direct\\\\t\\\\t\\\\t\\\\tRE_Direct_Physical\\\\n#define RE_Direct_RectArea\\\\t\\\\tRE_Direct_RectArea_Physical\\\\n#define RE_IndirectDiffuse\\\\t\\\\tRE_IndirectDiffuse_Physical\\\\n#define RE_IndirectSpecular\\\\t\\\\tRE_IndirectSpecular_Physical\\\\nfloat computeSpecularOcclusion( const in float dotNV, const in float ambientOcclusion, const in float roughness ) {\\\\n\\\\treturn saturate( pow( dotNV + ambientOcclusion, exp2( - 16.0 * roughness - 1.0 ) ) - 1.0 + ambientOcclusion );\\\\n}\\\\\\\",lights_fragment_begin:\\\\\\\"\\\\nGeometricContext geometry;\\\\ngeometry.position = - vViewPosition;\\\\ngeometry.normal = normal;\\\\ngeometry.viewDir = ( isOrthographic ) ? vec3( 0, 0, 1 ) : normalize( vViewPosition );\\\\n#ifdef USE_CLEARCOAT\\\\n\\\\tgeometry.clearcoatNormal = clearcoatNormal;\\\\n#endif\\\\nIncidentLight directLight;\\\\n#if ( NUM_POINT_LIGHTS > 0 ) && defined( RE_Direct )\\\\n\\\\tPointLight pointLight;\\\\n\\\\t#if defined( USE_SHADOWMAP ) && NUM_POINT_LIGHT_SHADOWS > 0\\\\n\\\\tPointLightShadow pointLightShadow;\\\\n\\\\t#endif\\\\n\\\\t#pragma unroll_loop_start\\\\n\\\\tfor ( int i = 0; i < NUM_POINT_LIGHTS; i ++ ) {\\\\n\\\\t\\\\tpointLight = pointLights[ i ];\\\\n\\\\t\\\\tgetPointLightInfo( pointLight, geometry, directLight );\\\\n\\\\t\\\\t#if defined( USE_SHADOWMAP ) && ( UNROLLED_LOOP_INDEX < NUM_POINT_LIGHT_SHADOWS )\\\\n\\\\t\\\\tpointLightShadow = pointLightShadows[ i ];\\\\n\\\\t\\\\tdirectLight.color *= all( bvec2( directLight.visible, receiveShadow ) ) ? getPointShadow( pointShadowMap[ i ], pointLightShadow.shadowMapSize, pointLightShadow.shadowBias, pointLightShadow.shadowRadius, vPointShadowCoord[ i ], pointLightShadow.shadowCameraNear, pointLightShadow.shadowCameraFar ) : 1.0;\\\\n\\\\t\\\\t#endif\\\\n\\\\t\\\\tRE_Direct( directLight, geometry, material, reflectedLight );\\\\n\\\\t}\\\\n\\\\t#pragma unroll_loop_end\\\\n#endif\\\\n#if ( NUM_SPOT_LIGHTS > 0 ) && defined( RE_Direct )\\\\n\\\\tSpotLight spotLight;\\\\n\\\\t#if defined( USE_SHADOWMAP ) && NUM_SPOT_LIGHT_SHADOWS > 0\\\\n\\\\tSpotLightShadow spotLightShadow;\\\\n\\\\t#endif\\\\n\\\\t#pragma unroll_loop_start\\\\n\\\\tfor ( int i = 0; i < NUM_SPOT_LIGHTS; i ++ ) {\\\\n\\\\t\\\\tspotLight = spotLights[ i ];\\\\n\\\\t\\\\tgetSpotLightInfo( spotLight, geometry, directLight );\\\\n\\\\t\\\\t#if defined( USE_SHADOWMAP ) && ( UNROLLED_LOOP_INDEX < NUM_SPOT_LIGHT_SHADOWS )\\\\n\\\\t\\\\tspotLightShadow = spotLightShadows[ i ];\\\\n\\\\t\\\\tdirectLight.color *= all( bvec2( directLight.visible, receiveShadow ) ) ? getShadow( spotShadowMap[ i ], spotLightShadow.shadowMapSize, spotLightShadow.shadowBias, spotLightShadow.shadowRadius, vSpotShadowCoord[ i ] ) : 1.0;\\\\n\\\\t\\\\t#endif\\\\n\\\\t\\\\tRE_Direct( directLight, geometry, material, reflectedLight );\\\\n\\\\t}\\\\n\\\\t#pragma unroll_loop_end\\\\n#endif\\\\n#if ( NUM_DIR_LIGHTS > 0 ) && defined( RE_Direct )\\\\n\\\\tDirectionalLight directionalLight;\\\\n\\\\t#if defined( USE_SHADOWMAP ) && NUM_DIR_LIGHT_SHADOWS > 0\\\\n\\\\tDirectionalLightShadow directionalLightShadow;\\\\n\\\\t#endif\\\\n\\\\t#pragma unroll_loop_start\\\\n\\\\tfor ( int i = 0; i < NUM_DIR_LIGHTS; i ++ ) {\\\\n\\\\t\\\\tdirectionalLight = directionalLights[ i ];\\\\n\\\\t\\\\tgetDirectionalLightInfo( directionalLight, geometry, directLight );\\\\n\\\\t\\\\t#if defined( USE_SHADOWMAP ) && ( UNROLLED_LOOP_INDEX < NUM_DIR_LIGHT_SHADOWS )\\\\n\\\\t\\\\tdirectionalLightShadow = directionalLightShadows[ i ];\\\\n\\\\t\\\\tdirectLight.color *= all( bvec2( directLight.visible, receiveShadow ) ) ? getShadow( directionalShadowMap[ i ], directionalLightShadow.shadowMapSize, directionalLightShadow.shadowBias, directionalLightShadow.shadowRadius, vDirectionalShadowCoord[ i ] ) : 1.0;\\\\n\\\\t\\\\t#endif\\\\n\\\\t\\\\tRE_Direct( directLight, geometry, material, reflectedLight );\\\\n\\\\t}\\\\n\\\\t#pragma unroll_loop_end\\\\n#endif\\\\n#if ( NUM_RECT_AREA_LIGHTS > 0 ) && defined( RE_Direct_RectArea )\\\\n\\\\tRectAreaLight rectAreaLight;\\\\n\\\\t#pragma unroll_loop_start\\\\n\\\\tfor ( int i = 0; i < NUM_RECT_AREA_LIGHTS; i ++ ) {\\\\n\\\\t\\\\trectAreaLight = rectAreaLights[ i ];\\\\n\\\\t\\\\tRE_Direct_RectArea( rectAreaLight, geometry, material, reflectedLight );\\\\n\\\\t}\\\\n\\\\t#pragma unroll_loop_end\\\\n#endif\\\\n#if defined( RE_IndirectDiffuse )\\\\n\\\\tvec3 iblIrradiance = vec3( 0.0 );\\\\n\\\\tvec3 irradiance = getAmbientLightIrradiance( ambientLightColor );\\\\n\\\\tirradiance += getLightProbeIrradiance( lightProbe, geometry.normal );\\\\n\\\\t#if ( NUM_HEMI_LIGHTS > 0 )\\\\n\\\\t\\\\t#pragma unroll_loop_start\\\\n\\\\t\\\\tfor ( int i = 0; i < NUM_HEMI_LIGHTS; i ++ ) {\\\\n\\\\t\\\\t\\\\tirradiance += getHemisphereLightIrradiance( hemisphereLights[ i ], geometry.normal );\\\\n\\\\t\\\\t}\\\\n\\\\t\\\\t#pragma unroll_loop_end\\\\n\\\\t#endif\\\\n#endif\\\\n#if defined( RE_IndirectSpecular )\\\\n\\\\tvec3 radiance = vec3( 0.0 );\\\\n\\\\tvec3 clearcoatRadiance = vec3( 0.0 );\\\\n#endif\\\\\\\",lights_fragment_maps:\\\\\\\"#if defined( RE_IndirectDiffuse )\\\\n\\\\t#ifdef USE_LIGHTMAP\\\\n\\\\t\\\\tvec4 lightMapTexel = texture2D( lightMap, vUv2 );\\\\n\\\\t\\\\tvec3 lightMapIrradiance = lightMapTexelToLinear( lightMapTexel ).rgb * lightMapIntensity;\\\\n\\\\t\\\\t#ifndef PHYSICALLY_CORRECT_LIGHTS\\\\n\\\\t\\\\t\\\\tlightMapIrradiance *= PI;\\\\n\\\\t\\\\t#endif\\\\n\\\\t\\\\tirradiance += lightMapIrradiance;\\\\n\\\\t#endif\\\\n\\\\t#if defined( USE_ENVMAP ) && defined( STANDARD ) && defined( ENVMAP_TYPE_CUBE_UV )\\\\n\\\\t\\\\tiblIrradiance += getIBLIrradiance( geometry.normal );\\\\n\\\\t#endif\\\\n#endif\\\\n#if defined( USE_ENVMAP ) && defined( RE_IndirectSpecular )\\\\n\\\\tradiance += getIBLRadiance( geometry.viewDir, geometry.normal, material.roughness );\\\\n\\\\t#ifdef USE_CLEARCOAT\\\\n\\\\t\\\\tclearcoatRadiance += getIBLRadiance( geometry.viewDir, geometry.clearcoatNormal, material.clearcoatRoughness );\\\\n\\\\t#endif\\\\n#endif\\\\\\\",lights_fragment_end:\\\\\\\"#if defined( RE_IndirectDiffuse )\\\\n\\\\tRE_IndirectDiffuse( irradiance, geometry, material, reflectedLight );\\\\n#endif\\\\n#if defined( RE_IndirectSpecular )\\\\n\\\\tRE_IndirectSpecular( radiance, iblIrradiance, clearcoatRadiance, geometry, material, reflectedLight );\\\\n#endif\\\\\\\",logdepthbuf_fragment:\\\\\\\"#if defined( USE_LOGDEPTHBUF ) && defined( USE_LOGDEPTHBUF_EXT )\\\\n\\\\tgl_FragDepthEXT = vIsPerspective == 0.0 ? gl_FragCoord.z : log2( vFragDepth ) * logDepthBufFC * 0.5;\\\\n#endif\\\\\\\",logdepthbuf_pars_fragment:\\\\\\\"#if defined( USE_LOGDEPTHBUF ) && defined( USE_LOGDEPTHBUF_EXT )\\\\n\\\\tuniform float logDepthBufFC;\\\\n\\\\tvarying float vFragDepth;\\\\n\\\\tvarying float vIsPerspective;\\\\n#endif\\\\\\\",logdepthbuf_pars_vertex:\\\\\\\"#ifdef USE_LOGDEPTHBUF\\\\n\\\\t#ifdef USE_LOGDEPTHBUF_EXT\\\\n\\\\t\\\\tvarying float vFragDepth;\\\\n\\\\t\\\\tvarying float vIsPerspective;\\\\n\\\\t#else\\\\n\\\\t\\\\tuniform float logDepthBufFC;\\\\n\\\\t#endif\\\\n#endif\\\\\\\",logdepthbuf_vertex:\\\\\\\"#ifdef USE_LOGDEPTHBUF\\\\n\\\\t#ifdef USE_LOGDEPTHBUF_EXT\\\\n\\\\t\\\\tvFragDepth = 1.0 + gl_Position.w;\\\\n\\\\t\\\\tvIsPerspective = float( isPerspectiveMatrix( projectionMatrix ) );\\\\n\\\\t#else\\\\n\\\\t\\\\tif ( isPerspectiveMatrix( projectionMatrix ) ) {\\\\n\\\\t\\\\t\\\\tgl_Position.z = log2( max( EPSILON, gl_Position.w + 1.0 ) ) * logDepthBufFC - 1.0;\\\\n\\\\t\\\\t\\\\tgl_Position.z *= gl_Position.w;\\\\n\\\\t\\\\t}\\\\n\\\\t#endif\\\\n#endif\\\\\\\",map_fragment:\\\\\\\"#ifdef USE_MAP\\\\n\\\\tvec4 texelColor = texture2D( map, vUv );\\\\n\\\\ttexelColor = mapTexelToLinear( texelColor );\\\\n\\\\tdiffuseColor *= texelColor;\\\\n#endif\\\\\\\",map_pars_fragment:\\\\\\\"#ifdef USE_MAP\\\\n\\\\tuniform sampler2D map;\\\\n#endif\\\\\\\",map_particle_fragment:\\\\\\\"#if defined( USE_MAP ) || defined( USE_ALPHAMAP )\\\\n\\\\tvec2 uv = ( uvTransform * vec3( gl_PointCoord.x, 1.0 - gl_PointCoord.y, 1 ) ).xy;\\\\n#endif\\\\n#ifdef USE_MAP\\\\n\\\\tvec4 mapTexel = texture2D( map, uv );\\\\n\\\\tdiffuseColor *= mapTexelToLinear( mapTexel );\\\\n#endif\\\\n#ifdef USE_ALPHAMAP\\\\n\\\\tdiffuseColor.a *= texture2D( alphaMap, uv ).g;\\\\n#endif\\\\\\\",map_particle_pars_fragment:\\\\\\\"#if defined( USE_MAP ) || defined( USE_ALPHAMAP )\\\\n\\\\tuniform mat3 uvTransform;\\\\n#endif\\\\n#ifdef USE_MAP\\\\n\\\\tuniform sampler2D map;\\\\n#endif\\\\n#ifdef USE_ALPHAMAP\\\\n\\\\tuniform sampler2D alphaMap;\\\\n#endif\\\\\\\",metalnessmap_fragment:\\\\\\\"float metalnessFactor = metalness;\\\\n#ifdef USE_METALNESSMAP\\\\n\\\\tvec4 texelMetalness = texture2D( metalnessMap, vUv );\\\\n\\\\tmetalnessFactor *= texelMetalness.b;\\\\n#endif\\\\\\\",metalnessmap_pars_fragment:\\\\\\\"#ifdef USE_METALNESSMAP\\\\n\\\\tuniform sampler2D metalnessMap;\\\\n#endif\\\\\\\",morphnormal_vertex:\\\\\\\"#ifdef USE_MORPHNORMALS\\\\n\\\\tobjectNormal *= morphTargetBaseInfluence;\\\\n\\\\t#ifdef MORPHTARGETS_TEXTURE\\\\n\\\\t\\\\tfor ( int i = 0; i < MORPHTARGETS_COUNT; i ++ ) {\\\\n\\\\t\\\\t\\\\tif ( morphTargetInfluences[ i ] > 0.0 ) objectNormal += getMorph( gl_VertexID, i, 1, 2 ) * morphTargetInfluences[ i ];\\\\n\\\\t\\\\t}\\\\n\\\\t#else\\\\n\\\\t\\\\tobjectNormal += morphNormal0 * morphTargetInfluences[ 0 ];\\\\n\\\\t\\\\tobjectNormal += morphNormal1 * morphTargetInfluences[ 1 ];\\\\n\\\\t\\\\tobjectNormal += morphNormal2 * morphTargetInfluences[ 2 ];\\\\n\\\\t\\\\tobjectNormal += morphNormal3 * morphTargetInfluences[ 3 ];\\\\n\\\\t#endif\\\\n#endif\\\\\\\",morphtarget_pars_vertex:\\\\\\\"#ifdef USE_MORPHTARGETS\\\\n\\\\tuniform float morphTargetBaseInfluence;\\\\n\\\\t#ifdef MORPHTARGETS_TEXTURE\\\\n\\\\t\\\\tuniform float morphTargetInfluences[ MORPHTARGETS_COUNT ];\\\\n\\\\t\\\\tuniform sampler2DArray morphTargetsTexture;\\\\n\\\\t\\\\tuniform vec2 morphTargetsTextureSize;\\\\n\\\\t\\\\tvec3 getMorph( const in int vertexIndex, const in int morphTargetIndex, const in int offset, const in int stride ) {\\\\n\\\\t\\\\t\\\\tfloat texelIndex = float( vertexIndex * stride + offset );\\\\n\\\\t\\\\t\\\\tfloat y = floor( texelIndex / morphTargetsTextureSize.x );\\\\n\\\\t\\\\t\\\\tfloat x = texelIndex - y * morphTargetsTextureSize.x;\\\\n\\\\t\\\\t\\\\tvec3 morphUV = vec3( ( x + 0.5 ) / morphTargetsTextureSize.x, y / morphTargetsTextureSize.y, morphTargetIndex );\\\\n\\\\t\\\\t\\\\treturn texture( morphTargetsTexture, morphUV ).xyz;\\\\n\\\\t\\\\t}\\\\n\\\\t#else\\\\n\\\\t\\\\t#ifndef USE_MORPHNORMALS\\\\n\\\\t\\\\t\\\\tuniform float morphTargetInfluences[ 8 ];\\\\n\\\\t\\\\t#else\\\\n\\\\t\\\\t\\\\tuniform float morphTargetInfluences[ 4 ];\\\\n\\\\t\\\\t#endif\\\\n\\\\t#endif\\\\n#endif\\\\\\\",morphtarget_vertex:\\\\\\\"#ifdef USE_MORPHTARGETS\\\\n\\\\ttransformed *= morphTargetBaseInfluence;\\\\n\\\\t#ifdef MORPHTARGETS_TEXTURE\\\\n\\\\t\\\\tfor ( int i = 0; i < MORPHTARGETS_COUNT; i ++ ) {\\\\n\\\\t\\\\t\\\\t#ifndef USE_MORPHNORMALS\\\\n\\\\t\\\\t\\\\t\\\\tif ( morphTargetInfluences[ i ] > 0.0 ) transformed += getMorph( gl_VertexID, i, 0, 1 ) * morphTargetInfluences[ i ];\\\\n\\\\t\\\\t\\\\t#else\\\\n\\\\t\\\\t\\\\t\\\\tif ( morphTargetInfluences[ i ] > 0.0 ) transformed += getMorph( gl_VertexID, i, 0, 2 ) * morphTargetInfluences[ i ];\\\\n\\\\t\\\\t\\\\t#endif\\\\n\\\\t\\\\t}\\\\n\\\\t#else\\\\n\\\\t\\\\ttransformed += morphTarget0 * morphTargetInfluences[ 0 ];\\\\n\\\\t\\\\ttransformed += morphTarget1 * morphTargetInfluences[ 1 ];\\\\n\\\\t\\\\ttransformed += morphTarget2 * morphTargetInfluences[ 2 ];\\\\n\\\\t\\\\ttransformed += morphTarget3 * morphTargetInfluences[ 3 ];\\\\n\\\\t\\\\t#ifndef USE_MORPHNORMALS\\\\n\\\\t\\\\t\\\\ttransformed += morphTarget4 * morphTargetInfluences[ 4 ];\\\\n\\\\t\\\\t\\\\ttransformed += morphTarget5 * morphTargetInfluences[ 5 ];\\\\n\\\\t\\\\t\\\\ttransformed += morphTarget6 * morphTargetInfluences[ 6 ];\\\\n\\\\t\\\\t\\\\ttransformed += morphTarget7 * morphTargetInfluences[ 7 ];\\\\n\\\\t\\\\t#endif\\\\n\\\\t#endif\\\\n#endif\\\\\\\",normal_fragment_begin:\\\\\\\"float faceDirection = gl_FrontFacing ? 1.0 : - 1.0;\\\\n#ifdef FLAT_SHADED\\\\n\\\\tvec3 fdx = vec3( dFdx( vViewPosition.x ), dFdx( vViewPosition.y ), dFdx( vViewPosition.z ) );\\\\n\\\\tvec3 fdy = vec3( dFdy( vViewPosition.x ), dFdy( vViewPosition.y ), dFdy( vViewPosition.z ) );\\\\n\\\\tvec3 normal = normalize( cross( fdx, fdy ) );\\\\n#else\\\\n\\\\tvec3 normal = normalize( vNormal );\\\\n\\\\t#ifdef DOUBLE_SIDED\\\\n\\\\t\\\\tnormal = normal * faceDirection;\\\\n\\\\t#endif\\\\n\\\\t#ifdef USE_TANGENT\\\\n\\\\t\\\\tvec3 tangent = normalize( vTangent );\\\\n\\\\t\\\\tvec3 bitangent = normalize( vBitangent );\\\\n\\\\t\\\\t#ifdef DOUBLE_SIDED\\\\n\\\\t\\\\t\\\\ttangent = tangent * faceDirection;\\\\n\\\\t\\\\t\\\\tbitangent = bitangent * faceDirection;\\\\n\\\\t\\\\t#endif\\\\n\\\\t\\\\t#if defined( TANGENTSPACE_NORMALMAP ) || defined( USE_CLEARCOAT_NORMALMAP )\\\\n\\\\t\\\\t\\\\tmat3 vTBN = mat3( tangent, bitangent, normal );\\\\n\\\\t\\\\t#endif\\\\n\\\\t#endif\\\\n#endif\\\\nvec3 geometryNormal = normal;\\\\\\\",normal_fragment_maps:\\\\\\\"#ifdef OBJECTSPACE_NORMALMAP\\\\n\\\\tnormal = texture2D( normalMap, vUv ).xyz * 2.0 - 1.0;\\\\n\\\\t#ifdef FLIP_SIDED\\\\n\\\\t\\\\tnormal = - normal;\\\\n\\\\t#endif\\\\n\\\\t#ifdef DOUBLE_SIDED\\\\n\\\\t\\\\tnormal = normal * faceDirection;\\\\n\\\\t#endif\\\\n\\\\tnormal = normalize( normalMatrix * normal );\\\\n#elif defined( TANGENTSPACE_NORMALMAP )\\\\n\\\\tvec3 mapN = texture2D( normalMap, vUv ).xyz * 2.0 - 1.0;\\\\n\\\\tmapN.xy *= normalScale;\\\\n\\\\t#ifdef USE_TANGENT\\\\n\\\\t\\\\tnormal = normalize( vTBN * mapN );\\\\n\\\\t#else\\\\n\\\\t\\\\tnormal = perturbNormal2Arb( - vViewPosition, normal, mapN, faceDirection );\\\\n\\\\t#endif\\\\n#elif defined( USE_BUMPMAP )\\\\n\\\\tnormal = perturbNormalArb( - vViewPosition, normal, dHdxy_fwd(), faceDirection );\\\\n#endif\\\\\\\",normal_pars_fragment:\\\\\\\"#ifndef FLAT_SHADED\\\\n\\\\tvarying vec3 vNormal;\\\\n\\\\t#ifdef USE_TANGENT\\\\n\\\\t\\\\tvarying vec3 vTangent;\\\\n\\\\t\\\\tvarying vec3 vBitangent;\\\\n\\\\t#endif\\\\n#endif\\\\\\\",normal_pars_vertex:\\\\\\\"#ifndef FLAT_SHADED\\\\n\\\\tvarying vec3 vNormal;\\\\n\\\\t#ifdef USE_TANGENT\\\\n\\\\t\\\\tvarying vec3 vTangent;\\\\n\\\\t\\\\tvarying vec3 vBitangent;\\\\n\\\\t#endif\\\\n#endif\\\\\\\",normal_vertex:\\\\\\\"#ifndef FLAT_SHADED\\\\n\\\\tvNormal = normalize( transformedNormal );\\\\n\\\\t#ifdef USE_TANGENT\\\\n\\\\t\\\\tvTangent = normalize( transformedTangent );\\\\n\\\\t\\\\tvBitangent = normalize( cross( vNormal, vTangent ) * tangent.w );\\\\n\\\\t#endif\\\\n#endif\\\\\\\",normalmap_pars_fragment:\\\\\\\"#ifdef USE_NORMALMAP\\\\n\\\\tuniform sampler2D normalMap;\\\\n\\\\tuniform vec2 normalScale;\\\\n#endif\\\\n#ifdef OBJECTSPACE_NORMALMAP\\\\n\\\\tuniform mat3 normalMatrix;\\\\n#endif\\\\n#if ! defined ( USE_TANGENT ) && ( defined ( TANGENTSPACE_NORMALMAP ) || defined ( USE_CLEARCOAT_NORMALMAP ) )\\\\n\\\\tvec3 perturbNormal2Arb( vec3 eye_pos, vec3 surf_norm, vec3 mapN, float faceDirection ) {\\\\n\\\\t\\\\tvec3 q0 = vec3( dFdx( eye_pos.x ), dFdx( eye_pos.y ), dFdx( eye_pos.z ) );\\\\n\\\\t\\\\tvec3 q1 = vec3( dFdy( eye_pos.x ), dFdy( eye_pos.y ), dFdy( eye_pos.z ) );\\\\n\\\\t\\\\tvec2 st0 = dFdx( vUv.st );\\\\n\\\\t\\\\tvec2 st1 = dFdy( vUv.st );\\\\n\\\\t\\\\tvec3 N = surf_norm;\\\\n\\\\t\\\\tvec3 q1perp = cross( q1, N );\\\\n\\\\t\\\\tvec3 q0perp = cross( N, q0 );\\\\n\\\\t\\\\tvec3 T = q1perp * st0.x + q0perp * st1.x;\\\\n\\\\t\\\\tvec3 B = q1perp * st0.y + q0perp * st1.y;\\\\n\\\\t\\\\tfloat det = max( dot( T, T ), dot( B, B ) );\\\\n\\\\t\\\\tfloat scale = ( det == 0.0 ) ? 0.0 : faceDirection * inversesqrt( det );\\\\n\\\\t\\\\treturn normalize( T * ( mapN.x * scale ) + B * ( mapN.y * scale ) + N * mapN.z );\\\\n\\\\t}\\\\n#endif\\\\\\\",clearcoat_normal_fragment_begin:\\\\\\\"#ifdef USE_CLEARCOAT\\\\n\\\\tvec3 clearcoatNormal = geometryNormal;\\\\n#endif\\\\\\\",clearcoat_normal_fragment_maps:\\\\\\\"#ifdef USE_CLEARCOAT_NORMALMAP\\\\n\\\\tvec3 clearcoatMapN = texture2D( clearcoatNormalMap, vUv ).xyz * 2.0 - 1.0;\\\\n\\\\tclearcoatMapN.xy *= clearcoatNormalScale;\\\\n\\\\t#ifdef USE_TANGENT\\\\n\\\\t\\\\tclearcoatNormal = normalize( vTBN * clearcoatMapN );\\\\n\\\\t#else\\\\n\\\\t\\\\tclearcoatNormal = perturbNormal2Arb( - vViewPosition, clearcoatNormal, clearcoatMapN, faceDirection );\\\\n\\\\t#endif\\\\n#endif\\\\\\\",clearcoat_pars_fragment:\\\\\\\"#ifdef USE_CLEARCOATMAP\\\\n\\\\tuniform sampler2D clearcoatMap;\\\\n#endif\\\\n#ifdef USE_CLEARCOAT_ROUGHNESSMAP\\\\n\\\\tuniform sampler2D clearcoatRoughnessMap;\\\\n#endif\\\\n#ifdef USE_CLEARCOAT_NORMALMAP\\\\n\\\\tuniform sampler2D clearcoatNormalMap;\\\\n\\\\tuniform vec2 clearcoatNormalScale;\\\\n#endif\\\\\\\",output_fragment:\\\\\\\"#ifdef OPAQUE\\\\ndiffuseColor.a = 1.0;\\\\n#endif\\\\n#ifdef USE_TRANSMISSION\\\\ndiffuseColor.a *= transmissionAlpha + 0.1;\\\\n#endif\\\\ngl_FragColor = vec4( outgoingLight, diffuseColor.a );\\\\\\\",packing:\\\\\\\"vec3 packNormalToRGB( const in vec3 normal ) {\\\\n\\\\treturn normalize( normal ) * 0.5 + 0.5;\\\\n}\\\\nvec3 unpackRGBToNormal( const in vec3 rgb ) {\\\\n\\\\treturn 2.0 * rgb.xyz - 1.0;\\\\n}\\\\nconst float PackUpscale = 256. / 255.;const float UnpackDownscale = 255. / 256.;\\\\nconst vec3 PackFactors = vec3( 256. * 256. * 256., 256. * 256., 256. );\\\\nconst vec4 UnpackFactors = UnpackDownscale / vec4( PackFactors, 1. );\\\\nconst float ShiftRight8 = 1. / 256.;\\\\nvec4 packDepthToRGBA( const in float v ) {\\\\n\\\\tvec4 r = vec4( fract( v * PackFactors ), v );\\\\n\\\\tr.yzw -= r.xyz * ShiftRight8;\\\\treturn r * PackUpscale;\\\\n}\\\\nfloat unpackRGBAToDepth( const in vec4 v ) {\\\\n\\\\treturn dot( v, UnpackFactors );\\\\n}\\\\nvec4 pack2HalfToRGBA( vec2 v ) {\\\\n\\\\tvec4 r = vec4( v.x, fract( v.x * 255.0 ), v.y, fract( v.y * 255.0 ) );\\\\n\\\\treturn vec4( r.x - r.y / 255.0, r.y, r.z - r.w / 255.0, r.w );\\\\n}\\\\nvec2 unpackRGBATo2Half( vec4 v ) {\\\\n\\\\treturn vec2( v.x + ( v.y / 255.0 ), v.z + ( v.w / 255.0 ) );\\\\n}\\\\nfloat viewZToOrthographicDepth( const in float viewZ, const in float near, const in float far ) {\\\\n\\\\treturn ( viewZ + near ) / ( near - far );\\\\n}\\\\nfloat orthographicDepthToViewZ( const in float linearClipZ, const in float near, const in float far ) {\\\\n\\\\treturn linearClipZ * ( near - far ) - near;\\\\n}\\\\nfloat viewZToPerspectiveDepth( const in float viewZ, const in float near, const in float far ) {\\\\n\\\\treturn ( ( near + viewZ ) * far ) / ( ( far - near ) * viewZ );\\\\n}\\\\nfloat perspectiveDepthToViewZ( const in float invClipZ, const in float near, const in float far ) {\\\\n\\\\treturn ( near * far ) / ( ( far - near ) * invClipZ - far );\\\\n}\\\\\\\",premultiplied_alpha_fragment:\\\\\\\"#ifdef PREMULTIPLIED_ALPHA\\\\n\\\\tgl_FragColor.rgb *= gl_FragColor.a;\\\\n#endif\\\\\\\",project_vertex:\\\\\\\"vec4 mvPosition = vec4( transformed, 1.0 );\\\\n#ifdef USE_INSTANCING\\\\n\\\\tmvPosition = instanceMatrix * mvPosition;\\\\n#endif\\\\nmvPosition = modelViewMatrix * mvPosition;\\\\ngl_Position = projectionMatrix * mvPosition;\\\\\\\",dithering_fragment:\\\\\\\"#ifdef DITHERING\\\\n\\\\tgl_FragColor.rgb = dithering( gl_FragColor.rgb );\\\\n#endif\\\\\\\",dithering_pars_fragment:\\\\\\\"#ifdef DITHERING\\\\n\\\\tvec3 dithering( vec3 color ) {\\\\n\\\\t\\\\tfloat grid_position = rand( gl_FragCoord.xy );\\\\n\\\\t\\\\tvec3 dither_shift_RGB = vec3( 0.25 / 255.0, -0.25 / 255.0, 0.25 / 255.0 );\\\\n\\\\t\\\\tdither_shift_RGB = mix( 2.0 * dither_shift_RGB, -2.0 * dither_shift_RGB, grid_position );\\\\n\\\\t\\\\treturn color + dither_shift_RGB;\\\\n\\\\t}\\\\n#endif\\\\\\\",roughnessmap_fragment:\\\\\\\"float roughnessFactor = roughness;\\\\n#ifdef USE_ROUGHNESSMAP\\\\n\\\\tvec4 texelRoughness = texture2D( roughnessMap, vUv );\\\\n\\\\troughnessFactor *= texelRoughness.g;\\\\n#endif\\\\\\\",roughnessmap_pars_fragment:\\\\\\\"#ifdef USE_ROUGHNESSMAP\\\\n\\\\tuniform sampler2D roughnessMap;\\\\n#endif\\\\\\\",shadowmap_pars_fragment:\\\\\\\"#ifdef USE_SHADOWMAP\\\\n\\\\t#if NUM_DIR_LIGHT_SHADOWS > 0\\\\n\\\\t\\\\tuniform sampler2D directionalShadowMap[ NUM_DIR_LIGHT_SHADOWS ];\\\\n\\\\t\\\\tvarying vec4 vDirectionalShadowCoord[ NUM_DIR_LIGHT_SHADOWS ];\\\\n\\\\t\\\\tstruct DirectionalLightShadow {\\\\n\\\\t\\\\t\\\\tfloat shadowBias;\\\\n\\\\t\\\\t\\\\tfloat shadowNormalBias;\\\\n\\\\t\\\\t\\\\tfloat shadowRadius;\\\\n\\\\t\\\\t\\\\tvec2 shadowMapSize;\\\\n\\\\t\\\\t};\\\\n\\\\t\\\\tuniform DirectionalLightShadow directionalLightShadows[ NUM_DIR_LIGHT_SHADOWS ];\\\\n\\\\t#endif\\\\n\\\\t#if NUM_SPOT_LIGHT_SHADOWS > 0\\\\n\\\\t\\\\tuniform sampler2D spotShadowMap[ NUM_SPOT_LIGHT_SHADOWS ];\\\\n\\\\t\\\\tvarying vec4 vSpotShadowCoord[ NUM_SPOT_LIGHT_SHADOWS ];\\\\n\\\\t\\\\tstruct SpotLightShadow {\\\\n\\\\t\\\\t\\\\tfloat shadowBias;\\\\n\\\\t\\\\t\\\\tfloat shadowNormalBias;\\\\n\\\\t\\\\t\\\\tfloat shadowRadius;\\\\n\\\\t\\\\t\\\\tvec2 shadowMapSize;\\\\n\\\\t\\\\t};\\\\n\\\\t\\\\tuniform SpotLightShadow spotLightShadows[ NUM_SPOT_LIGHT_SHADOWS ];\\\\n\\\\t#endif\\\\n\\\\t#if NUM_POINT_LIGHT_SHADOWS > 0\\\\n\\\\t\\\\tuniform sampler2D pointShadowMap[ NUM_POINT_LIGHT_SHADOWS ];\\\\n\\\\t\\\\tvarying vec4 vPointShadowCoord[ NUM_POINT_LIGHT_SHADOWS ];\\\\n\\\\t\\\\tstruct PointLightShadow {\\\\n\\\\t\\\\t\\\\tfloat shadowBias;\\\\n\\\\t\\\\t\\\\tfloat shadowNormalBias;\\\\n\\\\t\\\\t\\\\tfloat shadowRadius;\\\\n\\\\t\\\\t\\\\tvec2 shadowMapSize;\\\\n\\\\t\\\\t\\\\tfloat shadowCameraNear;\\\\n\\\\t\\\\t\\\\tfloat shadowCameraFar;\\\\n\\\\t\\\\t};\\\\n\\\\t\\\\tuniform PointLightShadow pointLightShadows[ NUM_POINT_LIGHT_SHADOWS ];\\\\n\\\\t#endif\\\\n\\\\tfloat texture2DCompare( sampler2D depths, vec2 uv, float compare ) {\\\\n\\\\t\\\\treturn step( compare, unpackRGBAToDepth( texture2D( depths, uv ) ) );\\\\n\\\\t}\\\\n\\\\tvec2 texture2DDistribution( sampler2D shadow, vec2 uv ) {\\\\n\\\\t\\\\treturn unpackRGBATo2Half( texture2D( shadow, uv ) );\\\\n\\\\t}\\\\n\\\\tfloat VSMShadow (sampler2D shadow, vec2 uv, float compare ){\\\\n\\\\t\\\\tfloat occlusion = 1.0;\\\\n\\\\t\\\\tvec2 distribution = texture2DDistribution( shadow, uv );\\\\n\\\\t\\\\tfloat hard_shadow = step( compare , distribution.x );\\\\n\\\\t\\\\tif (hard_shadow != 1.0 ) {\\\\n\\\\t\\\\t\\\\tfloat distance = compare - distribution.x ;\\\\n\\\\t\\\\t\\\\tfloat variance = max( 0.00000, distribution.y * distribution.y );\\\\n\\\\t\\\\t\\\\tfloat softness_probability = variance / (variance + distance * distance );\\\\t\\\\t\\\\tsoftness_probability = clamp( ( softness_probability - 0.3 ) / ( 0.95 - 0.3 ), 0.0, 1.0 );\\\\t\\\\t\\\\tocclusion = clamp( max( hard_shadow, softness_probability ), 0.0, 1.0 );\\\\n\\\\t\\\\t}\\\\n\\\\t\\\\treturn occlusion;\\\\n\\\\t}\\\\n\\\\tfloat getShadow( sampler2D shadowMap, vec2 shadowMapSize, float shadowBias, float shadowRadius, vec4 shadowCoord ) {\\\\n\\\\t\\\\tfloat shadow = 1.0;\\\\n\\\\t\\\\tshadowCoord.xyz /= shadowCoord.w;\\\\n\\\\t\\\\tshadowCoord.z += shadowBias;\\\\n\\\\t\\\\tbvec4 inFrustumVec = bvec4 ( shadowCoord.x >= 0.0, shadowCoord.x <= 1.0, shadowCoord.y >= 0.0, shadowCoord.y <= 1.0 );\\\\n\\\\t\\\\tbool inFrustum = all( inFrustumVec );\\\\n\\\\t\\\\tbvec2 frustumTestVec = bvec2( inFrustum, shadowCoord.z <= 1.0 );\\\\n\\\\t\\\\tbool frustumTest = all( frustumTestVec );\\\\n\\\\t\\\\tif ( frustumTest ) {\\\\n\\\\t\\\\t#if defined( SHADOWMAP_TYPE_PCF )\\\\n\\\\t\\\\t\\\\tvec2 texelSize = vec2( 1.0 ) / shadowMapSize;\\\\n\\\\t\\\\t\\\\tfloat dx0 = - texelSize.x * shadowRadius;\\\\n\\\\t\\\\t\\\\tfloat dy0 = - texelSize.y * shadowRadius;\\\\n\\\\t\\\\t\\\\tfloat dx1 = + texelSize.x * shadowRadius;\\\\n\\\\t\\\\t\\\\tfloat dy1 = + texelSize.y * shadowRadius;\\\\n\\\\t\\\\t\\\\tfloat dx2 = dx0 / 2.0;\\\\n\\\\t\\\\t\\\\tfloat dy2 = dy0 / 2.0;\\\\n\\\\t\\\\t\\\\tfloat dx3 = dx1 / 2.0;\\\\n\\\\t\\\\t\\\\tfloat dy3 = dy1 / 2.0;\\\\n\\\\t\\\\t\\\\tshadow = (\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx0, dy0 ), shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( 0.0, dy0 ), shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx1, dy0 ), shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx2, dy2 ), shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( 0.0, dy2 ), shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx3, dy2 ), shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx0, 0.0 ), shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx2, 0.0 ), shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, shadowCoord.xy, shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx3, 0.0 ), shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx1, 0.0 ), shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx2, dy3 ), shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( 0.0, dy3 ), shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx3, dy3 ), shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx0, dy1 ), shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( 0.0, dy1 ), shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx1, dy1 ), shadowCoord.z )\\\\n\\\\t\\\\t\\\\t) * ( 1.0 / 17.0 );\\\\n\\\\t\\\\t#elif defined( SHADOWMAP_TYPE_PCF_SOFT )\\\\n\\\\t\\\\t\\\\tvec2 texelSize = vec2( 1.0 ) / shadowMapSize;\\\\n\\\\t\\\\t\\\\tfloat dx = texelSize.x;\\\\n\\\\t\\\\t\\\\tfloat dy = texelSize.y;\\\\n\\\\t\\\\t\\\\tvec2 uv = shadowCoord.xy;\\\\n\\\\t\\\\t\\\\tvec2 f = fract( uv * shadowMapSize + 0.5 );\\\\n\\\\t\\\\t\\\\tuv -= f * texelSize;\\\\n\\\\t\\\\t\\\\tshadow = (\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, uv, shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, uv + vec2( dx, 0.0 ), shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, uv + vec2( 0.0, dy ), shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, uv + texelSize, shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\tmix( texture2DCompare( shadowMap, uv + vec2( -dx, 0.0 ), shadowCoord.z ), \\\\n\\\\t\\\\t\\\\t\\\\t\\\\t texture2DCompare( shadowMap, uv + vec2( 2.0 * dx, 0.0 ), shadowCoord.z ),\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t f.x ) +\\\\n\\\\t\\\\t\\\\t\\\\tmix( texture2DCompare( shadowMap, uv + vec2( -dx, dy ), shadowCoord.z ), \\\\n\\\\t\\\\t\\\\t\\\\t\\\\t texture2DCompare( shadowMap, uv + vec2( 2.0 * dx, dy ), shadowCoord.z ),\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t f.x ) +\\\\n\\\\t\\\\t\\\\t\\\\tmix( texture2DCompare( shadowMap, uv + vec2( 0.0, -dy ), shadowCoord.z ), \\\\n\\\\t\\\\t\\\\t\\\\t\\\\t texture2DCompare( shadowMap, uv + vec2( 0.0, 2.0 * dy ), shadowCoord.z ),\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t f.y ) +\\\\n\\\\t\\\\t\\\\t\\\\tmix( texture2DCompare( shadowMap, uv + vec2( dx, -dy ), shadowCoord.z ), \\\\n\\\\t\\\\t\\\\t\\\\t\\\\t texture2DCompare( shadowMap, uv + vec2( dx, 2.0 * dy ), shadowCoord.z ),\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t f.y ) +\\\\n\\\\t\\\\t\\\\t\\\\tmix( mix( texture2DCompare( shadowMap, uv + vec2( -dx, -dy ), shadowCoord.z ), \\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t texture2DCompare( shadowMap, uv + vec2( 2.0 * dx, -dy ), shadowCoord.z ),\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t f.x ),\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t mix( texture2DCompare( shadowMap, uv + vec2( -dx, 2.0 * dy ), shadowCoord.z ), \\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t texture2DCompare( shadowMap, uv + vec2( 2.0 * dx, 2.0 * dy ), shadowCoord.z ),\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t f.x ),\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t f.y )\\\\n\\\\t\\\\t\\\\t) * ( 1.0 / 9.0 );\\\\n\\\\t\\\\t#elif defined( SHADOWMAP_TYPE_VSM )\\\\n\\\\t\\\\t\\\\tshadow = VSMShadow( shadowMap, shadowCoord.xy, shadowCoord.z );\\\\n\\\\t\\\\t#else\\\\n\\\\t\\\\t\\\\tshadow = texture2DCompare( shadowMap, shadowCoord.xy, shadowCoord.z );\\\\n\\\\t\\\\t#endif\\\\n\\\\t\\\\t}\\\\n\\\\t\\\\treturn shadow;\\\\n\\\\t}\\\\n\\\\tvec2 cubeToUV( vec3 v, float texelSizeY ) {\\\\n\\\\t\\\\tvec3 absV = abs( v );\\\\n\\\\t\\\\tfloat scaleToCube = 1.0 / max( absV.x, max( absV.y, absV.z ) );\\\\n\\\\t\\\\tabsV *= scaleToCube;\\\\n\\\\t\\\\tv *= scaleToCube * ( 1.0 - 2.0 * texelSizeY );\\\\n\\\\t\\\\tvec2 planar = v.xy;\\\\n\\\\t\\\\tfloat almostATexel = 1.5 * texelSizeY;\\\\n\\\\t\\\\tfloat almostOne = 1.0 - almostATexel;\\\\n\\\\t\\\\tif ( absV.z >= almostOne ) {\\\\n\\\\t\\\\t\\\\tif ( v.z > 0.0 )\\\\n\\\\t\\\\t\\\\t\\\\tplanar.x = 4.0 - v.x;\\\\n\\\\t\\\\t} else if ( absV.x >= almostOne ) {\\\\n\\\\t\\\\t\\\\tfloat signX = sign( v.x );\\\\n\\\\t\\\\t\\\\tplanar.x = v.z * signX + 2.0 * signX;\\\\n\\\\t\\\\t} else if ( absV.y >= almostOne ) {\\\\n\\\\t\\\\t\\\\tfloat signY = sign( v.y );\\\\n\\\\t\\\\t\\\\tplanar.x = v.x + 2.0 * signY + 2.0;\\\\n\\\\t\\\\t\\\\tplanar.y = v.z * signY - 2.0;\\\\n\\\\t\\\\t}\\\\n\\\\t\\\\treturn vec2( 0.125, 0.25 ) * planar + vec2( 0.375, 0.75 );\\\\n\\\\t}\\\\n\\\\tfloat getPointShadow( sampler2D shadowMap, vec2 shadowMapSize, float shadowBias, float shadowRadius, vec4 shadowCoord, float shadowCameraNear, float shadowCameraFar ) {\\\\n\\\\t\\\\tvec2 texelSize = vec2( 1.0 ) / ( shadowMapSize * vec2( 4.0, 2.0 ) );\\\\n\\\\t\\\\tvec3 lightToPosition = shadowCoord.xyz;\\\\n\\\\t\\\\tfloat dp = ( length( lightToPosition ) - shadowCameraNear ) / ( shadowCameraFar - shadowCameraNear );\\\\t\\\\tdp += shadowBias;\\\\n\\\\t\\\\tvec3 bd3D = normalize( lightToPosition );\\\\n\\\\t\\\\t#if defined( SHADOWMAP_TYPE_PCF ) || defined( SHADOWMAP_TYPE_PCF_SOFT ) || defined( SHADOWMAP_TYPE_VSM )\\\\n\\\\t\\\\t\\\\tvec2 offset = vec2( - 1, 1 ) * shadowRadius * texelSize.y;\\\\n\\\\t\\\\t\\\\treturn (\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.xyy, texelSize.y ), dp ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.yyy, texelSize.y ), dp ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.xyx, texelSize.y ), dp ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.yyx, texelSize.y ), dp ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, cubeToUV( bd3D, texelSize.y ), dp ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.xxy, texelSize.y ), dp ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.yxy, texelSize.y ), dp ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.xxx, texelSize.y ), dp ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.yxx, texelSize.y ), dp )\\\\n\\\\t\\\\t\\\\t) * ( 1.0 / 9.0 );\\\\n\\\\t\\\\t#else\\\\n\\\\t\\\\t\\\\treturn texture2DCompare( shadowMap, cubeToUV( bd3D, texelSize.y ), dp );\\\\n\\\\t\\\\t#endif\\\\n\\\\t}\\\\n#endif\\\\\\\",shadowmap_pars_vertex:\\\\\\\"#ifdef USE_SHADOWMAP\\\\n\\\\t#if NUM_DIR_LIGHT_SHADOWS > 0\\\\n\\\\t\\\\tuniform mat4 directionalShadowMatrix[ NUM_DIR_LIGHT_SHADOWS ];\\\\n\\\\t\\\\tvarying vec4 vDirectionalShadowCoord[ NUM_DIR_LIGHT_SHADOWS ];\\\\n\\\\t\\\\tstruct DirectionalLightShadow {\\\\n\\\\t\\\\t\\\\tfloat shadowBias;\\\\n\\\\t\\\\t\\\\tfloat shadowNormalBias;\\\\n\\\\t\\\\t\\\\tfloat shadowRadius;\\\\n\\\\t\\\\t\\\\tvec2 shadowMapSize;\\\\n\\\\t\\\\t};\\\\n\\\\t\\\\tuniform DirectionalLightShadow directionalLightShadows[ NUM_DIR_LIGHT_SHADOWS ];\\\\n\\\\t#endif\\\\n\\\\t#if NUM_SPOT_LIGHT_SHADOWS > 0\\\\n\\\\t\\\\tuniform mat4 spotShadowMatrix[ NUM_SPOT_LIGHT_SHADOWS ];\\\\n\\\\t\\\\tvarying vec4 vSpotShadowCoord[ NUM_SPOT_LIGHT_SHADOWS ];\\\\n\\\\t\\\\tstruct SpotLightShadow {\\\\n\\\\t\\\\t\\\\tfloat shadowBias;\\\\n\\\\t\\\\t\\\\tfloat shadowNormalBias;\\\\n\\\\t\\\\t\\\\tfloat shadowRadius;\\\\n\\\\t\\\\t\\\\tvec2 shadowMapSize;\\\\n\\\\t\\\\t};\\\\n\\\\t\\\\tuniform SpotLightShadow spotLightShadows[ NUM_SPOT_LIGHT_SHADOWS ];\\\\n\\\\t#endif\\\\n\\\\t#if NUM_POINT_LIGHT_SHADOWS > 0\\\\n\\\\t\\\\tuniform mat4 pointShadowMatrix[ NUM_POINT_LIGHT_SHADOWS ];\\\\n\\\\t\\\\tvarying vec4 vPointShadowCoord[ NUM_POINT_LIGHT_SHADOWS ];\\\\n\\\\t\\\\tstruct PointLightShadow {\\\\n\\\\t\\\\t\\\\tfloat shadowBias;\\\\n\\\\t\\\\t\\\\tfloat shadowNormalBias;\\\\n\\\\t\\\\t\\\\tfloat shadowRadius;\\\\n\\\\t\\\\t\\\\tvec2 shadowMapSize;\\\\n\\\\t\\\\t\\\\tfloat shadowCameraNear;\\\\n\\\\t\\\\t\\\\tfloat shadowCameraFar;\\\\n\\\\t\\\\t};\\\\n\\\\t\\\\tuniform PointLightShadow pointLightShadows[ NUM_POINT_LIGHT_SHADOWS ];\\\\n\\\\t#endif\\\\n#endif\\\\\\\",shadowmap_vertex:\\\\\\\"#ifdef USE_SHADOWMAP\\\\n\\\\t#if NUM_DIR_LIGHT_SHADOWS > 0 || NUM_SPOT_LIGHT_SHADOWS > 0 || NUM_POINT_LIGHT_SHADOWS > 0\\\\n\\\\t\\\\tvec3 shadowWorldNormal = inverseTransformDirection( transformedNormal, viewMatrix );\\\\n\\\\t\\\\tvec4 shadowWorldPosition;\\\\n\\\\t#endif\\\\n\\\\t#if NUM_DIR_LIGHT_SHADOWS > 0\\\\n\\\\t#pragma unroll_loop_start\\\\n\\\\tfor ( int i = 0; i < NUM_DIR_LIGHT_SHADOWS; i ++ ) {\\\\n\\\\t\\\\tshadowWorldPosition = worldPosition + vec4( shadowWorldNormal * directionalLightShadows[ i ].shadowNormalBias, 0 );\\\\n\\\\t\\\\tvDirectionalShadowCoord[ i ] = directionalShadowMatrix[ i ] * shadowWorldPosition;\\\\n\\\\t}\\\\n\\\\t#pragma unroll_loop_end\\\\n\\\\t#endif\\\\n\\\\t#if NUM_SPOT_LIGHT_SHADOWS > 0\\\\n\\\\t#pragma unroll_loop_start\\\\n\\\\tfor ( int i = 0; i < NUM_SPOT_LIGHT_SHADOWS; i ++ ) {\\\\n\\\\t\\\\tshadowWorldPosition = worldPosition + vec4( shadowWorldNormal * spotLightShadows[ i ].shadowNormalBias, 0 );\\\\n\\\\t\\\\tvSpotShadowCoord[ i ] = spotShadowMatrix[ i ] * shadowWorldPosition;\\\\n\\\\t}\\\\n\\\\t#pragma unroll_loop_end\\\\n\\\\t#endif\\\\n\\\\t#if NUM_POINT_LIGHT_SHADOWS > 0\\\\n\\\\t#pragma unroll_loop_start\\\\n\\\\tfor ( int i = 0; i < NUM_POINT_LIGHT_SHADOWS; i ++ ) {\\\\n\\\\t\\\\tshadowWorldPosition = worldPosition + vec4( shadowWorldNormal * pointLightShadows[ i ].shadowNormalBias, 0 );\\\\n\\\\t\\\\tvPointShadowCoord[ i ] = pointShadowMatrix[ i ] * shadowWorldPosition;\\\\n\\\\t}\\\\n\\\\t#pragma unroll_loop_end\\\\n\\\\t#endif\\\\n#endif\\\\\\\",shadowmask_pars_fragment:\\\\\\\"float getShadowMask() {\\\\n\\\\tfloat shadow = 1.0;\\\\n\\\\t#ifdef USE_SHADOWMAP\\\\n\\\\t#if NUM_DIR_LIGHT_SHADOWS > 0\\\\n\\\\tDirectionalLightShadow directionalLight;\\\\n\\\\t#pragma unroll_loop_start\\\\n\\\\tfor ( int i = 0; i < NUM_DIR_LIGHT_SHADOWS; i ++ ) {\\\\n\\\\t\\\\tdirectionalLight = directionalLightShadows[ i ];\\\\n\\\\t\\\\tshadow *= receiveShadow ? getShadow( directionalShadowMap[ i ], directionalLight.shadowMapSize, directionalLight.shadowBias, directionalLight.shadowRadius, vDirectionalShadowCoord[ i ] ) : 1.0;\\\\n\\\\t}\\\\n\\\\t#pragma unroll_loop_end\\\\n\\\\t#endif\\\\n\\\\t#if NUM_SPOT_LIGHT_SHADOWS > 0\\\\n\\\\tSpotLightShadow spotLight;\\\\n\\\\t#pragma unroll_loop_start\\\\n\\\\tfor ( int i = 0; i < NUM_SPOT_LIGHT_SHADOWS; i ++ ) {\\\\n\\\\t\\\\tspotLight = spotLightShadows[ i ];\\\\n\\\\t\\\\tshadow *= receiveShadow ? getShadow( spotShadowMap[ i ], spotLight.shadowMapSize, spotLight.shadowBias, spotLight.shadowRadius, vSpotShadowCoord[ i ] ) : 1.0;\\\\n\\\\t}\\\\n\\\\t#pragma unroll_loop_end\\\\n\\\\t#endif\\\\n\\\\t#if NUM_POINT_LIGHT_SHADOWS > 0\\\\n\\\\tPointLightShadow pointLight;\\\\n\\\\t#pragma unroll_loop_start\\\\n\\\\tfor ( int i = 0; i < NUM_POINT_LIGHT_SHADOWS; i ++ ) {\\\\n\\\\t\\\\tpointLight = pointLightShadows[ i ];\\\\n\\\\t\\\\tshadow *= receiveShadow ? getPointShadow( pointShadowMap[ i ], pointLight.shadowMapSize, pointLight.shadowBias, pointLight.shadowRadius, vPointShadowCoord[ i ], pointLight.shadowCameraNear, pointLight.shadowCameraFar ) : 1.0;\\\\n\\\\t}\\\\n\\\\t#pragma unroll_loop_end\\\\n\\\\t#endif\\\\n\\\\t#endif\\\\n\\\\treturn shadow;\\\\n}\\\\\\\",skinbase_vertex:\\\\\\\"#ifdef USE_SKINNING\\\\n\\\\tmat4 boneMatX = getBoneMatrix( skinIndex.x );\\\\n\\\\tmat4 boneMatY = getBoneMatrix( skinIndex.y );\\\\n\\\\tmat4 boneMatZ = getBoneMatrix( skinIndex.z );\\\\n\\\\tmat4 boneMatW = getBoneMatrix( skinIndex.w );\\\\n#endif\\\\\\\",skinning_pars_vertex:\\\\\\\"#ifdef USE_SKINNING\\\\n\\\\tuniform mat4 bindMatrix;\\\\n\\\\tuniform mat4 bindMatrixInverse;\\\\n\\\\t#ifdef BONE_TEXTURE\\\\n\\\\t\\\\tuniform highp sampler2D boneTexture;\\\\n\\\\t\\\\tuniform int boneTextureSize;\\\\n\\\\t\\\\tmat4 getBoneMatrix( const in float i ) {\\\\n\\\\t\\\\t\\\\tfloat j = i * 4.0;\\\\n\\\\t\\\\t\\\\tfloat x = mod( j, float( boneTextureSize ) );\\\\n\\\\t\\\\t\\\\tfloat y = floor( j / float( boneTextureSize ) );\\\\n\\\\t\\\\t\\\\tfloat dx = 1.0 / float( boneTextureSize );\\\\n\\\\t\\\\t\\\\tfloat dy = 1.0 / float( boneTextureSize );\\\\n\\\\t\\\\t\\\\ty = dy * ( y + 0.5 );\\\\n\\\\t\\\\t\\\\tvec4 v1 = texture2D( boneTexture, vec2( dx * ( x + 0.5 ), y ) );\\\\n\\\\t\\\\t\\\\tvec4 v2 = texture2D( boneTexture, vec2( dx * ( x + 1.5 ), y ) );\\\\n\\\\t\\\\t\\\\tvec4 v3 = texture2D( boneTexture, vec2( dx * ( x + 2.5 ), y ) );\\\\n\\\\t\\\\t\\\\tvec4 v4 = texture2D( boneTexture, vec2( dx * ( x + 3.5 ), y ) );\\\\n\\\\t\\\\t\\\\tmat4 bone = mat4( v1, v2, v3, v4 );\\\\n\\\\t\\\\t\\\\treturn bone;\\\\n\\\\t\\\\t}\\\\n\\\\t#else\\\\n\\\\t\\\\tuniform mat4 boneMatrices[ MAX_BONES ];\\\\n\\\\t\\\\tmat4 getBoneMatrix( const in float i ) {\\\\n\\\\t\\\\t\\\\tmat4 bone = boneMatrices[ int(i) ];\\\\n\\\\t\\\\t\\\\treturn bone;\\\\n\\\\t\\\\t}\\\\n\\\\t#endif\\\\n#endif\\\\\\\",skinning_vertex:\\\\\\\"#ifdef USE_SKINNING\\\\n\\\\tvec4 skinVertex = bindMatrix * vec4( transformed, 1.0 );\\\\n\\\\tvec4 skinned = vec4( 0.0 );\\\\n\\\\tskinned += boneMatX * skinVertex * skinWeight.x;\\\\n\\\\tskinned += boneMatY * skinVertex * skinWeight.y;\\\\n\\\\tskinned += boneMatZ * skinVertex * skinWeight.z;\\\\n\\\\tskinned += boneMatW * skinVertex * skinWeight.w;\\\\n\\\\ttransformed = ( bindMatrixInverse * skinned ).xyz;\\\\n#endif\\\\\\\",skinnormal_vertex:\\\\\\\"#ifdef USE_SKINNING\\\\n\\\\tmat4 skinMatrix = mat4( 0.0 );\\\\n\\\\tskinMatrix += skinWeight.x * boneMatX;\\\\n\\\\tskinMatrix += skinWeight.y * boneMatY;\\\\n\\\\tskinMatrix += skinWeight.z * boneMatZ;\\\\n\\\\tskinMatrix += skinWeight.w * boneMatW;\\\\n\\\\tskinMatrix = bindMatrixInverse * skinMatrix * bindMatrix;\\\\n\\\\tobjectNormal = vec4( skinMatrix * vec4( objectNormal, 0.0 ) ).xyz;\\\\n\\\\t#ifdef USE_TANGENT\\\\n\\\\t\\\\tobjectTangent = vec4( skinMatrix * vec4( objectTangent, 0.0 ) ).xyz;\\\\n\\\\t#endif\\\\n#endif\\\\\\\",specularmap_fragment:\\\\\\\"float specularStrength;\\\\n#ifdef USE_SPECULARMAP\\\\n\\\\tvec4 texelSpecular = texture2D( specularMap, vUv );\\\\n\\\\tspecularStrength = texelSpecular.r;\\\\n#else\\\\n\\\\tspecularStrength = 1.0;\\\\n#endif\\\\\\\",specularmap_pars_fragment:\\\\\\\"#ifdef USE_SPECULARMAP\\\\n\\\\tuniform sampler2D specularMap;\\\\n#endif\\\\\\\",tonemapping_fragment:\\\\\\\"#if defined( TONE_MAPPING )\\\\n\\\\tgl_FragColor.rgb = toneMapping( gl_FragColor.rgb );\\\\n#endif\\\\\\\",tonemapping_pars_fragment:\\\\\\\"#ifndef saturate\\\\n#define saturate( a ) clamp( a, 0.0, 1.0 )\\\\n#endif\\\\nuniform float toneMappingExposure;\\\\nvec3 LinearToneMapping( vec3 color ) {\\\\n\\\\treturn toneMappingExposure * color;\\\\n}\\\\nvec3 ReinhardToneMapping( vec3 color ) {\\\\n\\\\tcolor *= toneMappingExposure;\\\\n\\\\treturn saturate( color / ( vec3( 1.0 ) + color ) );\\\\n}\\\\nvec3 OptimizedCineonToneMapping( vec3 color ) {\\\\n\\\\tcolor *= toneMappingExposure;\\\\n\\\\tcolor = max( vec3( 0.0 ), color - 0.004 );\\\\n\\\\treturn pow( ( color * ( 6.2 * color + 0.5 ) ) / ( color * ( 6.2 * color + 1.7 ) + 0.06 ), vec3( 2.2 ) );\\\\n}\\\\nvec3 RRTAndODTFit( vec3 v ) {\\\\n\\\\tvec3 a = v * ( v + 0.0245786 ) - 0.000090537;\\\\n\\\\tvec3 b = v * ( 0.983729 * v + 0.4329510 ) + 0.238081;\\\\n\\\\treturn a / b;\\\\n}\\\\nvec3 ACESFilmicToneMapping( vec3 color ) {\\\\n\\\\tconst mat3 ACESInputMat = mat3(\\\\n\\\\t\\\\tvec3( 0.59719, 0.07600, 0.02840 ),\\\\t\\\\tvec3( 0.35458, 0.90834, 0.13383 ),\\\\n\\\\t\\\\tvec3( 0.04823, 0.01566, 0.83777 )\\\\n\\\\t);\\\\n\\\\tconst mat3 ACESOutputMat = mat3(\\\\n\\\\t\\\\tvec3( 1.60475, -0.10208, -0.00327 ),\\\\t\\\\tvec3( -0.53108, 1.10813, -0.07276 ),\\\\n\\\\t\\\\tvec3( -0.07367, -0.00605, 1.07602 )\\\\n\\\\t);\\\\n\\\\tcolor *= toneMappingExposure / 0.6;\\\\n\\\\tcolor = ACESInputMat * color;\\\\n\\\\tcolor = RRTAndODTFit( color );\\\\n\\\\tcolor = ACESOutputMat * color;\\\\n\\\\treturn saturate( color );\\\\n}\\\\nvec3 CustomToneMapping( vec3 color ) { return color; }\\\\\\\",transmission_fragment:\\\\\\\"#ifdef USE_TRANSMISSION\\\\n\\\\tfloat transmissionAlpha = 1.0;\\\\n\\\\tfloat transmissionFactor = transmission;\\\\n\\\\tfloat thicknessFactor = thickness;\\\\n\\\\t#ifdef USE_TRANSMISSIONMAP\\\\n\\\\t\\\\ttransmissionFactor *= texture2D( transmissionMap, vUv ).r;\\\\n\\\\t#endif\\\\n\\\\t#ifdef USE_THICKNESSMAP\\\\n\\\\t\\\\tthicknessFactor *= texture2D( thicknessMap, vUv ).g;\\\\n\\\\t#endif\\\\n\\\\tvec3 pos = vWorldPosition;\\\\n\\\\tvec3 v = normalize( cameraPosition - pos );\\\\n\\\\tvec3 n = inverseTransformDirection( normal, viewMatrix );\\\\n\\\\tvec4 transmission = getIBLVolumeRefraction(\\\\n\\\\t\\\\tn, v, roughnessFactor, material.diffuseColor, material.specularColor, material.specularF90,\\\\n\\\\t\\\\tpos, modelMatrix, viewMatrix, projectionMatrix, ior, thicknessFactor,\\\\n\\\\t\\\\tattenuationTint, attenuationDistance );\\\\n\\\\ttotalDiffuse = mix( totalDiffuse, transmission.rgb, transmissionFactor );\\\\n\\\\ttransmissionAlpha = mix( transmissionAlpha, transmission.a, transmissionFactor );\\\\n#endif\\\\\\\",transmission_pars_fragment:\\\\\\\"#ifdef USE_TRANSMISSION\\\\n\\\\tuniform float transmission;\\\\n\\\\tuniform float thickness;\\\\n\\\\tuniform float attenuationDistance;\\\\n\\\\tuniform vec3 attenuationTint;\\\\n\\\\t#ifdef USE_TRANSMISSIONMAP\\\\n\\\\t\\\\tuniform sampler2D transmissionMap;\\\\n\\\\t#endif\\\\n\\\\t#ifdef USE_THICKNESSMAP\\\\n\\\\t\\\\tuniform sampler2D thicknessMap;\\\\n\\\\t#endif\\\\n\\\\tuniform vec2 transmissionSamplerSize;\\\\n\\\\tuniform sampler2D transmissionSamplerMap;\\\\n\\\\tuniform mat4 modelMatrix;\\\\n\\\\tuniform mat4 projectionMatrix;\\\\n\\\\tvarying vec3 vWorldPosition;\\\\n\\\\tvec3 getVolumeTransmissionRay( vec3 n, vec3 v, float thickness, float ior, mat4 modelMatrix ) {\\\\n\\\\t\\\\tvec3 refractionVector = refract( - v, normalize( n ), 1.0 / ior );\\\\n\\\\t\\\\tvec3 modelScale;\\\\n\\\\t\\\\tmodelScale.x = length( vec3( modelMatrix[ 0 ].xyz ) );\\\\n\\\\t\\\\tmodelScale.y = length( vec3( modelMatrix[ 1 ].xyz ) );\\\\n\\\\t\\\\tmodelScale.z = length( vec3( modelMatrix[ 2 ].xyz ) );\\\\n\\\\t\\\\treturn normalize( refractionVector ) * thickness * modelScale;\\\\n\\\\t}\\\\n\\\\tfloat applyIorToRoughness( float roughness, float ior ) {\\\\n\\\\t\\\\treturn roughness * clamp( ior * 2.0 - 2.0, 0.0, 1.0 );\\\\n\\\\t}\\\\n\\\\tvec4 getTransmissionSample( vec2 fragCoord, float roughness, float ior ) {\\\\n\\\\t\\\\tfloat framebufferLod = log2( transmissionSamplerSize.x ) * applyIorToRoughness( roughness, ior );\\\\n\\\\t\\\\t#ifdef TEXTURE_LOD_EXT\\\\n\\\\t\\\\t\\\\treturn texture2DLodEXT( transmissionSamplerMap, fragCoord.xy, framebufferLod );\\\\n\\\\t\\\\t#else\\\\n\\\\t\\\\t\\\\treturn texture2D( transmissionSamplerMap, fragCoord.xy, framebufferLod );\\\\n\\\\t\\\\t#endif\\\\n\\\\t}\\\\n\\\\tvec3 applyVolumeAttenuation( vec3 radiance, float transmissionDistance, vec3 attenuationColor, float attenuationDistance ) {\\\\n\\\\t\\\\tif ( attenuationDistance == 0.0 ) {\\\\n\\\\t\\\\t\\\\treturn radiance;\\\\n\\\\t\\\\t} else {\\\\n\\\\t\\\\t\\\\tvec3 attenuationCoefficient = -log( attenuationColor ) / attenuationDistance;\\\\n\\\\t\\\\t\\\\tvec3 transmittance = exp( - attenuationCoefficient * transmissionDistance );\\\\t\\\\t\\\\treturn transmittance * radiance;\\\\n\\\\t\\\\t}\\\\n\\\\t}\\\\n\\\\tvec4 getIBLVolumeRefraction( vec3 n, vec3 v, float roughness, vec3 diffuseColor, vec3 specularColor, float specularF90,\\\\n\\\\t\\\\tvec3 position, mat4 modelMatrix, mat4 viewMatrix, mat4 projMatrix, float ior, float thickness,\\\\n\\\\t\\\\tvec3 attenuationColor, float attenuationDistance ) {\\\\n\\\\t\\\\tvec3 transmissionRay = getVolumeTransmissionRay( n, v, thickness, ior, modelMatrix );\\\\n\\\\t\\\\tvec3 refractedRayExit = position + transmissionRay;\\\\n\\\\t\\\\tvec4 ndcPos = projMatrix * viewMatrix * vec4( refractedRayExit, 1.0 );\\\\n\\\\t\\\\tvec2 refractionCoords = ndcPos.xy / ndcPos.w;\\\\n\\\\t\\\\trefractionCoords += 1.0;\\\\n\\\\t\\\\trefractionCoords /= 2.0;\\\\n\\\\t\\\\tvec4 transmittedLight = getTransmissionSample( refractionCoords, roughness, ior );\\\\n\\\\t\\\\tvec3 attenuatedColor = applyVolumeAttenuation( transmittedLight.rgb, length( transmissionRay ), attenuationColor, attenuationDistance );\\\\n\\\\t\\\\tvec3 F = EnvironmentBRDF( n, v, specularColor, specularF90, roughness );\\\\n\\\\t\\\\treturn vec4( ( 1.0 - F ) * attenuatedColor * diffuseColor, transmittedLight.a );\\\\n\\\\t}\\\\n#endif\\\\\\\",uv_pars_fragment:\\\\\\\"#if ( defined( USE_UV ) && ! defined( UVS_VERTEX_ONLY ) )\\\\n\\\\tvarying vec2 vUv;\\\\n#endif\\\\\\\",uv_pars_vertex:\\\\\\\"#ifdef USE_UV\\\\n\\\\t#ifdef UVS_VERTEX_ONLY\\\\n\\\\t\\\\tvec2 vUv;\\\\n\\\\t#else\\\\n\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\t#endif\\\\n\\\\tuniform mat3 uvTransform;\\\\n#endif\\\\\\\",uv_vertex:\\\\\\\"#ifdef USE_UV\\\\n\\\\tvUv = ( uvTransform * vec3( uv, 1 ) ).xy;\\\\n#endif\\\\\\\",uv2_pars_fragment:\\\\\\\"#if defined( USE_LIGHTMAP ) || defined( USE_AOMAP )\\\\n\\\\tvarying vec2 vUv2;\\\\n#endif\\\\\\\",uv2_pars_vertex:\\\\\\\"#if defined( USE_LIGHTMAP ) || defined( USE_AOMAP )\\\\n\\\\tattribute vec2 uv2;\\\\n\\\\tvarying vec2 vUv2;\\\\n\\\\tuniform mat3 uv2Transform;\\\\n#endif\\\\\\\",uv2_vertex:\\\\\\\"#if defined( USE_LIGHTMAP ) || defined( USE_AOMAP )\\\\n\\\\tvUv2 = ( uv2Transform * vec3( uv2, 1 ) ).xy;\\\\n#endif\\\\\\\",worldpos_vertex:\\\\\\\"#if defined( USE_ENVMAP ) || defined( DISTANCE ) || defined ( USE_SHADOWMAP ) || defined ( USE_TRANSMISSION )\\\\n\\\\tvec4 worldPosition = vec4( transformed, 1.0 );\\\\n\\\\t#ifdef USE_INSTANCING\\\\n\\\\t\\\\tworldPosition = instanceMatrix * worldPosition;\\\\n\\\\t#endif\\\\n\\\\tworldPosition = modelMatrix * worldPosition;\\\\n#endif\\\\\\\",background_vert:\\\\\\\"varying vec2 vUv;\\\\nuniform mat3 uvTransform;\\\\nvoid main() {\\\\n\\\\tvUv = ( uvTransform * vec3( uv, 1 ) ).xy;\\\\n\\\\tgl_Position = vec4( position.xy, 1.0, 1.0 );\\\\n}\\\\\\\",background_frag:\\\\\\\"uniform sampler2D t2D;\\\\nvarying vec2 vUv;\\\\nvoid main() {\\\\n\\\\tvec4 texColor = texture2D( t2D, vUv );\\\\n\\\\tgl_FragColor = mapTexelToLinear( texColor );\\\\n\\\\t#include \\\\n\\\\t#include \\\\n}\\\\\\\",cube_vert:\\\\\\\"varying vec3 vWorldDirection;\\\\n#include \\\\nvoid main() {\\\\n\\\\tvWorldDirection = transformDirection( position, modelMatrix );\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\tgl_Position.z = gl_Position.w;\\\\n}\\\\\\\",cube_frag:\\\\\\\"#include \\\\nuniform float opacity;\\\\nvarying vec3 vWorldDirection;\\\\n#include \\\\nvoid main() {\\\\n\\\\tvec3 vReflect = vWorldDirection;\\\\n\\\\t#include \\\\n\\\\tgl_FragColor = envColor;\\\\n\\\\tgl_FragColor.a *= opacity;\\\\n\\\\t#include \\\\n\\\\t#include \\\\n}\\\\\\\",depth_vert:\\\\\\\"#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\nvarying vec2 vHighPrecisionZW;\\\\nvoid main() {\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#ifdef USE_DISPLACEMENTMAP\\\\n\\\\t\\\\t#include \\\\n\\\\t\\\\t#include \\\\n\\\\t\\\\t#include \\\\n\\\\t#endif\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\tvHighPrecisionZW = gl_Position.zw;\\\\n}\\\\\\\",depth_frag:\\\\\\\"#if DEPTH_PACKING == 3200\\\\n\\\\tuniform float opacity;\\\\n#endif\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\nvarying vec2 vHighPrecisionZW;\\\\nvoid main() {\\\\n\\\\t#include \\\\n\\\\tvec4 diffuseColor = vec4( 1.0 );\\\\n\\\\t#if DEPTH_PACKING == 3200\\\\n\\\\t\\\\tdiffuseColor.a = opacity;\\\\n\\\\t#endif\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\tfloat fragCoordZ = 0.5 * vHighPrecisionZW[0] / vHighPrecisionZW[1] + 0.5;\\\\n\\\\t#if DEPTH_PACKING == 3200\\\\n\\\\t\\\\tgl_FragColor = vec4( vec3( 1.0 - fragCoordZ ), opacity );\\\\n\\\\t#elif DEPTH_PACKING == 3201\\\\n\\\\t\\\\tgl_FragColor = packDepthToRGBA( fragCoordZ );\\\\n\\\\t#endif\\\\n}\\\\\\\",distanceRGBA_vert:\\\\\\\"#define DISTANCE\\\\nvarying vec3 vWorldPosition;\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\nvoid main() {\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#ifdef USE_DISPLACEMENTMAP\\\\n\\\\t\\\\t#include \\\\n\\\\t\\\\t#include \\\\n\\\\t\\\\t#include \\\\n\\\\t#endif\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\tvWorldPosition = worldPosition.xyz;\\\\n}\\\\\\\",distanceRGBA_frag:\\\\\\\"#define DISTANCE\\\\nuniform vec3 referencePosition;\\\\nuniform float nearDistance;\\\\nuniform float farDistance;\\\\nvarying vec3 vWorldPosition;\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\nvoid main () {\\\\n\\\\t#include \\\\n\\\\tvec4 diffuseColor = vec4( 1.0 );\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\tfloat dist = length( vWorldPosition - referencePosition );\\\\n\\\\tdist = ( dist - nearDistance ) / ( farDistance - nearDistance );\\\\n\\\\tdist = saturate( dist );\\\\n\\\\tgl_FragColor = packDepthToRGBA( dist );\\\\n}\\\\\\\",equirect_vert:\\\\\\\"varying vec3 vWorldDirection;\\\\n#include \\\\nvoid main() {\\\\n\\\\tvWorldDirection = transformDirection( position, modelMatrix );\\\\n\\\\t#include \\\\n\\\\t#include \\\\n}\\\\\\\",equirect_frag:\\\\\\\"uniform sampler2D tEquirect;\\\\nvarying vec3 vWorldDirection;\\\\n#include \\\\nvoid main() {\\\\n\\\\tvec3 direction = normalize( vWorldDirection );\\\\n\\\\tvec2 sampleUV = equirectUv( direction );\\\\n\\\\tvec4 texColor = texture2D( tEquirect, sampleUV );\\\\n\\\\tgl_FragColor = mapTexelToLinear( texColor );\\\\n\\\\t#include \\\\n\\\\t#include \\\\n}\\\\\\\",linedashed_vert:\\\\\\\"uniform float scale;\\\\nattribute float lineDistance;\\\\nvarying float vLineDistance;\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\nvoid main() {\\\\n\\\\tvLineDistance = scale * lineDistance;\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n}\\\\\\\",linedashed_frag:\\\\\\\"uniform vec3 diffuse;\\\\nuniform float opacity;\\\\nuniform float dashSize;\\\\nuniform float totalSize;\\\\nvarying float vLineDistance;\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\nvoid main() {\\\\n\\\\t#include \\\\n\\\\tif ( mod( vLineDistance, totalSize ) > dashSize ) {\\\\n\\\\t\\\\tdiscard;\\\\n\\\\t}\\\\n\\\\tvec3 outgoingLight = vec3( 0.0 );\\\\n\\\\tvec4 diffuseColor = vec4( diffuse, opacity );\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\toutgoingLight = diffuseColor.rgb;\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n}\\\\\\\",meshbasic_vert:\\\\\\\"#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\nvoid main() {\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#if defined ( USE_ENVMAP ) || defined ( USE_SKINNING )\\\\n\\\\t\\\\t#include \\\\n\\\\t\\\\t#include \\\\n\\\\t\\\\t#include \\\\n\\\\t\\\\t#include \\\\n\\\\t\\\\t#include \\\\n\\\\t#endif\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n}\\\\\\\",meshbasic_frag:\\\\\\\"uniform vec3 diffuse;\\\\nuniform float opacity;\\\\n#ifndef FLAT_SHADED\\\\n\\\\tvarying vec3 vNormal;\\\\n#endif\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\nvoid main() {\\\\n\\\\t#include \\\\n\\\\tvec4 diffuseColor = vec4( diffuse, opacity );\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\tReflectedLight reflectedLight = ReflectedLight( vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ) );\\\\n\\\\t#ifdef USE_LIGHTMAP\\\\n\\\\t\\\\tvec4 lightMapTexel= texture2D( lightMap, vUv2 );\\\\n\\\\t\\\\treflectedLight.indirectDiffuse += lightMapTexelToLinear( lightMapTexel ).rgb * lightMapIntensity;\\\\n\\\\t#else\\\\n\\\\t\\\\treflectedLight.indirectDiffuse += vec3( 1.0 );\\\\n\\\\t#endif\\\\n\\\\t#include \\\\n\\\\treflectedLight.indirectDiffuse *= diffuseColor.rgb;\\\\n\\\\tvec3 outgoingLight = reflectedLight.indirectDiffuse;\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n}\\\\\\\",meshlambert_vert:\\\\\\\"#define LAMBERT\\\\nvarying vec3 vLightFront;\\\\nvarying vec3 vIndirectFront;\\\\n#ifdef DOUBLE_SIDED\\\\n\\\\tvarying vec3 vLightBack;\\\\n\\\\tvarying vec3 vIndirectBack;\\\\n#endif\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\nvoid main() {\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n}\\\\\\\",meshlambert_frag:\\\\\\\"uniform vec3 diffuse;\\\\nuniform vec3 emissive;\\\\nuniform float opacity;\\\\nvarying vec3 vLightFront;\\\\nvarying vec3 vIndirectFront;\\\\n#ifdef DOUBLE_SIDED\\\\n\\\\tvarying vec3 vLightBack;\\\\n\\\\tvarying vec3 vIndirectBack;\\\\n#endif\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\nvoid main() {\\\\n\\\\t#include \\\\n\\\\tvec4 diffuseColor = vec4( diffuse, opacity );\\\\n\\\\tReflectedLight reflectedLight = ReflectedLight( vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ) );\\\\n\\\\tvec3 totalEmissiveRadiance = emissive;\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#ifdef DOUBLE_SIDED\\\\n\\\\t\\\\treflectedLight.indirectDiffuse += ( gl_FrontFacing ) ? vIndirectFront : vIndirectBack;\\\\n\\\\t#else\\\\n\\\\t\\\\treflectedLight.indirectDiffuse += vIndirectFront;\\\\n\\\\t#endif\\\\n\\\\t#include \\\\n\\\\treflectedLight.indirectDiffuse *= BRDF_Lambert( diffuseColor.rgb );\\\\n\\\\t#ifdef DOUBLE_SIDED\\\\n\\\\t\\\\treflectedLight.directDiffuse = ( gl_FrontFacing ) ? vLightFront : vLightBack;\\\\n\\\\t#else\\\\n\\\\t\\\\treflectedLight.directDiffuse = vLightFront;\\\\n\\\\t#endif\\\\n\\\\treflectedLight.directDiffuse *= BRDF_Lambert( diffuseColor.rgb ) * getShadowMask();\\\\n\\\\t#include \\\\n\\\\tvec3 outgoingLight = reflectedLight.directDiffuse + reflectedLight.indirectDiffuse + totalEmissiveRadiance;\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n}\\\\\\\",meshmatcap_vert:\\\\\\\"#define MATCAP\\\\nvarying vec3 vViewPosition;\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\nvoid main() {\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\tvViewPosition = - mvPosition.xyz;\\\\n}\\\\\\\",meshmatcap_frag:\\\\\\\"#define MATCAP\\\\nuniform vec3 diffuse;\\\\nuniform float opacity;\\\\nuniform sampler2D matcap;\\\\nvarying vec3 vViewPosition;\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\nvoid main() {\\\\n\\\\t#include \\\\n\\\\tvec4 diffuseColor = vec4( diffuse, opacity );\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\tvec3 viewDir = normalize( vViewPosition );\\\\n\\\\tvec3 x = normalize( vec3( viewDir.z, 0.0, - viewDir.x ) );\\\\n\\\\tvec3 y = cross( viewDir, x );\\\\n\\\\tvec2 uv = vec2( dot( x, normal ), dot( y, normal ) ) * 0.495 + 0.5;\\\\n\\\\t#ifdef USE_MATCAP\\\\n\\\\t\\\\tvec4 matcapColor = texture2D( matcap, uv );\\\\n\\\\t\\\\tmatcapColor = matcapTexelToLinear( matcapColor );\\\\n\\\\t#else\\\\n\\\\t\\\\tvec4 matcapColor = vec4( 1.0 );\\\\n\\\\t#endif\\\\n\\\\tvec3 outgoingLight = diffuseColor.rgb * matcapColor.rgb;\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n}\\\\\\\",meshnormal_vert:\\\\\\\"#define NORMAL\\\\n#if defined( FLAT_SHADED ) || defined( USE_BUMPMAP ) || defined( TANGENTSPACE_NORMALMAP )\\\\n\\\\tvarying vec3 vViewPosition;\\\\n#endif\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\nvoid main() {\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n#if defined( FLAT_SHADED ) || defined( USE_BUMPMAP ) || defined( TANGENTSPACE_NORMALMAP )\\\\n\\\\tvViewPosition = - mvPosition.xyz;\\\\n#endif\\\\n}\\\\\\\",meshnormal_frag:\\\\\\\"#define NORMAL\\\\nuniform float opacity;\\\\n#if defined( FLAT_SHADED ) || defined( USE_BUMPMAP ) || defined( TANGENTSPACE_NORMALMAP )\\\\n\\\\tvarying vec3 vViewPosition;\\\\n#endif\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\nvoid main() {\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\tgl_FragColor = vec4( packNormalToRGB( normal ), opacity );\\\\n}\\\\\\\",meshphong_vert:\\\\\\\"#define PHONG\\\\nvarying vec3 vViewPosition;\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\nvoid main() {\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\tvViewPosition = - mvPosition.xyz;\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n}\\\\\\\",meshphong_frag:\\\\\\\"#define PHONG\\\\nuniform vec3 diffuse;\\\\nuniform vec3 emissive;\\\\nuniform vec3 specular;\\\\nuniform float shininess;\\\\nuniform float opacity;\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\nvoid main() {\\\\n\\\\t#include \\\\n\\\\tvec4 diffuseColor = vec4( diffuse, opacity );\\\\n\\\\tReflectedLight reflectedLight = ReflectedLight( vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ) );\\\\n\\\\tvec3 totalEmissiveRadiance = emissive;\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\tvec3 outgoingLight = reflectedLight.directDiffuse + reflectedLight.indirectDiffuse + reflectedLight.directSpecular + reflectedLight.indirectSpecular + totalEmissiveRadiance;\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n}\\\\\\\",meshphysical_vert:\\\\\\\"#define STANDARD\\\\nvarying vec3 vViewPosition;\\\\n#ifdef USE_TRANSMISSION\\\\n\\\\tvarying vec3 vWorldPosition;\\\\n#endif\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\nvoid main() {\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\tvViewPosition = - mvPosition.xyz;\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n#ifdef USE_TRANSMISSION\\\\n\\\\tvWorldPosition = worldPosition.xyz;\\\\n#endif\\\\n}\\\\\\\",meshphysical_frag:\\\\\\\"#define STANDARD\\\\n#ifdef PHYSICAL\\\\n\\\\t#define IOR\\\\n\\\\t#define SPECULAR\\\\n#endif\\\\nuniform vec3 diffuse;\\\\nuniform vec3 emissive;\\\\nuniform float roughness;\\\\nuniform float metalness;\\\\nuniform float opacity;\\\\n#ifdef IOR\\\\n\\\\tuniform float ior;\\\\n#endif\\\\n#ifdef SPECULAR\\\\n\\\\tuniform float specularIntensity;\\\\n\\\\tuniform vec3 specularTint;\\\\n\\\\t#ifdef USE_SPECULARINTENSITYMAP\\\\n\\\\t\\\\tuniform sampler2D specularIntensityMap;\\\\n\\\\t#endif\\\\n\\\\t#ifdef USE_SPECULARTINTMAP\\\\n\\\\t\\\\tuniform sampler2D specularTintMap;\\\\n\\\\t#endif\\\\n#endif\\\\n#ifdef USE_CLEARCOAT\\\\n\\\\tuniform float clearcoat;\\\\n\\\\tuniform float clearcoatRoughness;\\\\n#endif\\\\n#ifdef USE_SHEEN\\\\n\\\\tuniform vec3 sheenTint;\\\\n\\\\tuniform float sheenRoughness;\\\\n#endif\\\\nvarying vec3 vViewPosition;\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\nvoid main() {\\\\n\\\\t#include \\\\n\\\\tvec4 diffuseColor = vec4( diffuse, opacity );\\\\n\\\\tReflectedLight reflectedLight = ReflectedLight( vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ) );\\\\n\\\\tvec3 totalEmissiveRadiance = emissive;\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\tvec3 totalDiffuse = reflectedLight.directDiffuse + reflectedLight.indirectDiffuse;\\\\n\\\\tvec3 totalSpecular = reflectedLight.directSpecular + reflectedLight.indirectSpecular;\\\\n\\\\t#include \\\\n\\\\tvec3 outgoingLight = totalDiffuse + totalSpecular + totalEmissiveRadiance;\\\\n\\\\t#ifdef USE_CLEARCOAT\\\\n\\\\t\\\\tfloat dotNVcc = saturate( dot( geometry.clearcoatNormal, geometry.viewDir ) );\\\\n\\\\t\\\\tvec3 Fcc = F_Schlick( material.clearcoatF0, material.clearcoatF90, dotNVcc );\\\\n\\\\t\\\\toutgoingLight = outgoingLight * ( 1.0 - clearcoat * Fcc ) + clearcoatSpecular * clearcoat;\\\\n\\\\t#endif\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n}\\\\\\\",meshtoon_vert:\\\\\\\"#define TOON\\\\nvarying vec3 vViewPosition;\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\nvoid main() {\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\tvViewPosition = - mvPosition.xyz;\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n}\\\\\\\",meshtoon_frag:\\\\\\\"#define TOON\\\\nuniform vec3 diffuse;\\\\nuniform vec3 emissive;\\\\nuniform float opacity;\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\nvoid main() {\\\\n\\\\t#include \\\\n\\\\tvec4 diffuseColor = vec4( diffuse, opacity );\\\\n\\\\tReflectedLight reflectedLight = ReflectedLight( vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ) );\\\\n\\\\tvec3 totalEmissiveRadiance = emissive;\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\tvec3 outgoingLight = reflectedLight.directDiffuse + reflectedLight.indirectDiffuse + totalEmissiveRadiance;\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n}\\\\\\\",points_vert:\\\\\\\"uniform float size;\\\\nuniform float scale;\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\nvoid main() {\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\tgl_PointSize = size;\\\\n\\\\t#ifdef USE_SIZEATTENUATION\\\\n\\\\t\\\\tbool isPerspective = isPerspectiveMatrix( projectionMatrix );\\\\n\\\\t\\\\tif ( isPerspective ) gl_PointSize *= ( scale / - mvPosition.z );\\\\n\\\\t#endif\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n}\\\\\\\",points_frag:\\\\\\\"uniform vec3 diffuse;\\\\nuniform float opacity;\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\nvoid main() {\\\\n\\\\t#include \\\\n\\\\tvec3 outgoingLight = vec3( 0.0 );\\\\n\\\\tvec4 diffuseColor = vec4( diffuse, opacity );\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\toutgoingLight = diffuseColor.rgb;\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n}\\\\\\\",shadow_vert:\\\\\\\"#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\nvoid main() {\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n}\\\\\\\",shadow_frag:\\\\\\\"uniform vec3 color;\\\\nuniform float opacity;\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\nvoid main() {\\\\n\\\\tgl_FragColor = vec4( color, opacity * ( 1.0 - getShadowMask() ) );\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n}\\\\\\\",sprite_vert:\\\\\\\"uniform float rotation;\\\\nuniform vec2 center;\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\nvoid main() {\\\\n\\\\t#include \\\\n\\\\tvec4 mvPosition = modelViewMatrix * vec4( 0.0, 0.0, 0.0, 1.0 );\\\\n\\\\tvec2 scale;\\\\n\\\\tscale.x = length( vec3( modelMatrix[ 0 ].x, modelMatrix[ 0 ].y, modelMatrix[ 0 ].z ) );\\\\n\\\\tscale.y = length( vec3( modelMatrix[ 1 ].x, modelMatrix[ 1 ].y, modelMatrix[ 1 ].z ) );\\\\n\\\\t#ifndef USE_SIZEATTENUATION\\\\n\\\\t\\\\tbool isPerspective = isPerspectiveMatrix( projectionMatrix );\\\\n\\\\t\\\\tif ( isPerspective ) scale *= - mvPosition.z;\\\\n\\\\t#endif\\\\n\\\\tvec2 alignedPosition = ( position.xy - ( center - vec2( 0.5 ) ) ) * scale;\\\\n\\\\tvec2 rotatedPosition;\\\\n\\\\trotatedPosition.x = cos( rotation ) * alignedPosition.x - sin( rotation ) * alignedPosition.y;\\\\n\\\\trotatedPosition.y = sin( rotation ) * alignedPosition.x + cos( rotation ) * alignedPosition.y;\\\\n\\\\tmvPosition.xy += rotatedPosition;\\\\n\\\\tgl_Position = projectionMatrix * mvPosition;\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n}\\\\\\\",sprite_frag:\\\\\\\"uniform vec3 diffuse;\\\\nuniform float opacity;\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\nvoid main() {\\\\n\\\\t#include \\\\n\\\\tvec3 outgoingLight = vec3( 0.0 );\\\\n\\\\tvec4 diffuseColor = vec4( diffuse, opacity );\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\toutgoingLight = diffuseColor.rgb;\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n}\\\\\\\"},KT={common:{diffuse:{value:new $w(16777215)},opacity:{value:1},map:{value:null},uvTransform:{value:new mb},uv2Transform:{value:new mb},alphaMap:{value:null},alphaTest:{value:0}},specularmap:{specularMap:{value:null}},envmap:{envMap:{value:null},flipEnvMap:{value:-1},reflectivity:{value:1},ior:{value:1.5},refractionRatio:{value:.98},maxMipLevel:{value:0}},aomap:{aoMap:{value:null},aoMapIntensity:{value:1}},lightmap:{lightMap:{value:null},lightMapIntensity:{value:1}},emissivemap:{emissiveMap:{value:null}},bumpmap:{bumpMap:{value:null},bumpScale:{value:1}},normalmap:{normalMap:{value:null},normalScale:{value:new _b(1,1)}},displacementmap:{displacementMap:{value:null},displacementScale:{value:1},displacementBias:{value:0}},roughnessmap:{roughnessMap:{value:null}},metalnessmap:{metalnessMap:{value:null}},gradientmap:{gradientMap:{value:null}},fog:{fogDensity:{value:25e-5},fogNear:{value:1},fogFar:{value:2e3},fogColor:{value:new $w(16777215)}},lights:{ambientLightColor:{value:[]},lightProbe:{value:[]},directionalLights:{value:[],properties:{direction:{},color:{}}},directionalLightShadows:{value:[],properties:{shadowBias:{},shadowNormalBias:{},shadowRadius:{},shadowMapSize:{}}},directionalShadowMap:{value:[]},directionalShadowMatrix:{value:[]},spotLights:{value:[],properties:{color:{},position:{},direction:{},distance:{},coneCos:{},penumbraCos:{},decay:{}}},spotLightShadows:{value:[],properties:{shadowBias:{},shadowNormalBias:{},shadowRadius:{},shadowMapSize:{}}},spotShadowMap:{value:[]},spotShadowMatrix:{value:[]},pointLights:{value:[],properties:{color:{},position:{},decay:{},distance:{}}},pointLightShadows:{value:[],properties:{shadowBias:{},shadowNormalBias:{},shadowRadius:{},shadowMapSize:{},shadowCameraNear:{},shadowCameraFar:{}}},pointShadowMap:{value:[]},pointShadowMatrix:{value:[]},hemisphereLights:{value:[],properties:{direction:{},skyColor:{},groundColor:{}}},rectAreaLights:{value:[],properties:{color:{},position:{},width:{},height:{}}},ltc_1:{value:null},ltc_2:{value:null}},points:{diffuse:{value:new $w(16777215)},opacity:{value:1},size:{value:1},scale:{value:1},map:{value:null},alphaMap:{value:null},alphaTest:{value:0},uvTransform:{value:new mb}},sprite:{diffuse:{value:new $w(16777215)},opacity:{value:1},center:{value:new _b(.5,.5)},rotation:{value:0},map:{value:null},alphaMap:{value:null},alphaTest:{value:0},uvTransform:{value:new mb}}},QT={basic:{uniforms:PT([KT.common,KT.specularmap,KT.envmap,KT.aomap,KT.lightmap,KT.fog]),vertexShader:ZT.meshbasic_vert,fragmentShader:ZT.meshbasic_frag},lambert:{uniforms:PT([KT.common,KT.specularmap,KT.envmap,KT.aomap,KT.lightmap,KT.emissivemap,KT.fog,KT.lights,{emissive:{value:new $w(0)}}]),vertexShader:ZT.meshlambert_vert,fragmentShader:ZT.meshlambert_frag},phong:{uniforms:PT([KT.common,KT.specularmap,KT.envmap,KT.aomap,KT.lightmap,KT.emissivemap,KT.bumpmap,KT.normalmap,KT.displacementmap,KT.fog,KT.lights,{emissive:{value:new $w(0)},specular:{value:new 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c=l.buffer,h=l.type,u=l.bytesPerElement;if(r.isInterleavedBufferAttribute){const n=r.data,l=n.stride,d=r.offset;if(n&&n.isInstancedInterleavedBuffer){for(let t=0;t0&&t.getShaderPrecisionFormat(35632,36338).precision>0)return\\\\\\\"highp\\\\\\\";e=\\\\\\\"mediump\\\\\\\"}return\\\\\\\"mediump\\\\\\\"===e&&t.getShaderPrecisionFormat(35633,36337).precision>0&&t.getShaderPrecisionFormat(35632,36337).precision>0?\\\\\\\"mediump\\\\\\\":\\\\\\\"lowp\\\\\\\"}const r=\\\\\\\"undefined\\\\\\\"!=typeof WebGL2RenderingContext&&t instanceof WebGL2RenderingContext||\\\\\\\"undefined\\\\\\\"!=typeof WebGL2ComputeRenderingContext&&t instanceof WebGL2ComputeRenderingContext;let o=void 0!==n.precision?n.precision:\\\\\\\"highp\\\\\\\";const a=s(o);a!==o&&(console.warn(\\\\\\\"THREE.WebGLRenderer:\\\\\\\",o,\\\\\\\"not supported, using\\\\\\\",a,\\\\\\\"instead.\\\\\\\"),o=a);const l=r||e.has(\\\\\\\"WEBGL_draw_buffers\\\\\\\"),c=!0===n.logarithmicDepthBuffer,h=t.getParameter(34930),u=t.getParameter(35660),d=t.getParameter(3379),p=t.getParameter(34076),_=t.getParameter(34921),m=t.getParameter(36347),f=t.getParameter(36348),g=t.getParameter(36349),v=u>0,y=r||e.has(\\\\\\\"OES_texture_float\\\\\\\");return{isWebGL2:r,drawBuffers:l,getMaxAnisotropy:function(){if(void 0!==i)return i;if(!0===e.has(\\\\\\\"EXT_texture_filter_anisotropic\\\\\\\")){const n=e.get(\\\\\\\"EXT_texture_filter_anisotropic\\\\\\\");i=t.getParameter(n.MAX_TEXTURE_MAX_ANISOTROPY_EXT)}else i=0;return i},getMaxPrecision:s,precision:o,logarithmicDepthBuffer:c,maxTextures:h,maxVertexTextures:u,maxTextureSize:d,maxCubemapSize:p,maxAttributes:_,maxVertexUniforms:m,maxVaryings:f,maxFragmentUniforms:g,vertexTextures:v,floatFragmentTextures:y,floatVertexTextures:v&&y,maxSamples:r?t.getParameter(36183):0}}function sA(t){const e=this;let n=null,i=0,s=!1,r=!1;const o=new jT,a=new mb,l={value:null,needsUpdate:!1};function c(){l.value!==n&&(l.value=n,l.needsUpdate=i>0),e.numPlanes=i,e.numIntersection=0}function h(t,n,i,s){const r=null!==t?t.length:0;let c=null;if(0!==r){if(c=l.value,!0!==s||null===c){const e=i+4*r,s=n.matrixWorldInverse;a.getNormalMatrix(s),(null===c||c.length0){const o=t.getRenderTarget(),a=new UT(r.height/2);return a.fromEquirectangularTexture(t,s),e.set(s,a),t.setRenderTarget(o),s.addEventListener(\\\\\\\"dispose\\\\\\\",i),n(a.texture,s.mapping)}return null}}}return s},dispose:function(){e=new WeakMap}}}QT.physical={uniforms:PT([QT.standard.uniforms,{clearcoat:{value:0},clearcoatMap:{value:null},clearcoatRoughness:{value:0},clearcoatRoughnessMap:{value:null},clearcoatNormalScale:{value:new _b(1,1)},clearcoatNormalMap:{value:null},sheen:{value:0},sheenTint:{value:new $w(0)},sheenRoughness:{value:0},transmission:{value:0},transmissionMap:{value:null},transmissionSamplerSize:{value:new _b},transmissionSamplerMap:{value:null},thickness:{value:0},thicknessMap:{value:null},attenuationDistance:{value:0},attenuationTint:{value:new $w(0)},specularIntensity:{value:0},specularIntensityMap:{value:null},specularTint:{value:new $w(1,1,1)},specularTintMap:{value:null}}]),vertexShader:ZT.meshphysical_vert,fragmentShader:ZT.meshphysical_frag};class oA extends FT{constructor(t=-1,e=1,n=1,i=-1,s=.1,r=2e3){super(),this.type=\\\\\\\"OrthographicCamera\\\\\\\",this.zoom=1,this.view=null,this.left=t,this.right=e,this.top=n,this.bottom=i,this.near=s,this.far=r,this.updateProjectionMatrix()}copy(t,e){return super.copy(t,e),this.left=t.left,this.right=t.right,this.top=t.top,this.bottom=t.bottom,this.near=t.near,this.far=t.far,this.zoom=t.zoom,this.view=null===t.view?null:Object.assign({},t.view),this}setViewOffset(t,e,n,i,s,r){null===this.view&&(this.view={enabled:!0,fullWidth:1,fullHeight:1,offsetX:0,offsetY:0,width:1,height:1}),this.view.enabled=!0,this.view.fullWidth=t,this.view.fullHeight=e,this.view.offsetX=n,this.view.offsetY=i,this.view.width=s,this.view.height=r,this.updateProjectionMatrix()}clearViewOffset(){null!==this.view&&(this.view.enabled=!1),this.updateProjectionMatrix()}updateProjectionMatrix(){const t=(this.right-this.left)/(2*this.zoom),e=(this.top-this.bottom)/(2*this.zoom),n=(this.right+this.left)/2,i=(this.top+this.bottom)/2;let s=n-t,r=n+t,o=i+e,a=i-e;if(null!==this.view&&this.view.enabled){const t=(this.right-this.left)/this.view.fullWidth/this.zoom,e=(this.top-this.bottom)/this.view.fullHeight/this.zoom;s+=t*this.view.offsetX,r=s+t*this.view.width,o-=e*this.view.offsetY,a=o-e*this.view.height}this.projectionMatrix.makeOrthographic(s,r,o,a,this.near,this.far),this.projectionMatrixInverse.copy(this.projectionMatrix).invert()}toJSON(t){const e=super.toJSON(t);return e.object.zoom=this.zoom,e.object.left=this.left,e.object.right=this.right,e.object.top=this.top,e.object.bottom=this.bottom,e.object.near=this.near,e.object.far=this.far,null!==this.view&&(e.object.view=Object.assign({},this.view)),e}}oA.prototype.isOrthographicCamera=!0;class aA extends IT{constructor(t){super(t),this.type=\\\\\\\"RawShaderMaterial\\\\\\\"}}aA.prototype.isRawShaderMaterial=!0;const lA=Math.pow(2,8),cA=[.125,.215,.35,.446,.526,.582],hA=5+cA.length,uA=20,dA={[qx]:0,[Xx]:1,[$x]:2,3004:3,3005:4,3006:5,[Yx]:6},pA=new oA,{_lodPlanes:_A,_sizeLods:mA,_sigmas:fA}=AA(),gA=new $w;let vA=null;const yA=(1+Math.sqrt(5))/2,xA=1/yA,bA=[new Sb(1,1,1),new Sb(-1,1,1),new Sb(1,1,-1),new Sb(-1,1,-1),new Sb(0,yA,xA),new Sb(0,yA,-xA),new Sb(xA,0,yA),new Sb(-xA,0,yA),new Sb(yA,xA,0),new Sb(-yA,xA,0)];class wA{constructor(t){this._renderer=t,this._pingPongRenderTarget=null,this._blurMaterial=function(t){const e=new Float32Array(t),n=new Sb(0,1,0);return new aA({name:\\\\\\\"SphericalGaussianBlur\\\\\\\",defines:{n:t},uniforms:{envMap:{value:null},samples:{value:1},weights:{value:e},latitudinal:{value:!1},dTheta:{value:0},mipInt:{value:0},poleAxis:{value:n},inputEncoding:{value:dA[3e3]},outputEncoding:{value:dA[3e3]}},vertexShader:NA(),fragmentShader:`\\\\n\\\\n\\\\t\\\\t\\\\tprecision mediump float;\\\\n\\\\t\\\\t\\\\tprecision mediump int;\\\\n\\\\n\\\\t\\\\t\\\\tvarying vec3 vOutputDirection;\\\\n\\\\n\\\\t\\\\t\\\\tuniform sampler2D envMap;\\\\n\\\\t\\\\t\\\\tuniform int samples;\\\\n\\\\t\\\\t\\\\tuniform float weights[ n ];\\\\n\\\\t\\\\t\\\\tuniform bool latitudinal;\\\\n\\\\t\\\\t\\\\tuniform float dTheta;\\\\n\\\\t\\\\t\\\\tuniform float mipInt;\\\\n\\\\t\\\\t\\\\tuniform vec3 poleAxis;\\\\n\\\\n\\\\t\\\\t\\\\t${LA()}\\\\n\\\\n\\\\t\\\\t\\\\t#define ENVMAP_TYPE_CUBE_UV\\\\n\\\\t\\\\t\\\\t#include \\\\n\\\\n\\\\t\\\\t\\\\tvec3 getSample( float theta, vec3 axis ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tfloat cosTheta = cos( theta );\\\\n\\\\t\\\\t\\\\t\\\\t// Rodrigues' axis-angle rotation\\\\n\\\\t\\\\t\\\\t\\\\tvec3 sampleDirection = vOutputDirection * cosTheta\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t+ cross( axis, vOutputDirection ) * sin( theta )\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t+ axis * dot( axis, vOutputDirection ) * ( 1.0 - cosTheta );\\\\n\\\\n\\\\t\\\\t\\\\t\\\\treturn bilinearCubeUV( envMap, sampleDirection, mipInt );\\\\n\\\\n\\\\t\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tvec3 axis = latitudinal ? poleAxis : cross( poleAxis, vOutputDirection );\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tif ( all( equal( axis, vec3( 0.0 ) ) ) ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\t\\\\taxis = vec3( vOutputDirection.z, 0.0, - vOutputDirection.x );\\\\n\\\\n\\\\t\\\\t\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\t\\\\t\\\\taxis = normalize( axis );\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tgl_FragColor = vec4( 0.0, 0.0, 0.0, 1.0 );\\\\n\\\\t\\\\t\\\\t\\\\tgl_FragColor.rgb += weights[ 0 ] * getSample( 0.0, axis );\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tfor ( int i = 1; i < n; i++ ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tif ( i >= samples ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tbreak;\\\\n\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tfloat theta = dTheta * float( i );\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tgl_FragColor.rgb += weights[ i ] * getSample( -1.0 * theta, axis );\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tgl_FragColor.rgb += weights[ i ] * getSample( theta, axis );\\\\n\\\\n\\\\t\\\\t\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tgl_FragColor = linearToOutputTexel( gl_FragColor );\\\\n\\\\n\\\\t\\\\t\\\\t}\\\\n\\\\t\\\\t`,blending:0,depthTest:!1,depthWrite:!1})}(uA),this._equirectShader=null,this._cubemapShader=null,this._compileMaterial(this._blurMaterial)}fromScene(t,e=0,n=.1,i=100){vA=this._renderer.getRenderTarget();const s=this._allocateTargets();return this._sceneToCubeUV(t,n,i,s),e>0&&this._blur(s,0,0,e),this._applyPMREM(s),this._cleanup(s),s}fromEquirectangular(t){return this._fromTexture(t)}fromCubemap(t){return this._fromTexture(t)}compileCubemapShader(){null===this._cubemapShader&&(this._cubemapShader=CA(),this._compileMaterial(this._cubemapShader))}compileEquirectangularShader(){null===this._equirectShader&&(this._equirectShader=SA(),this._compileMaterial(this._equirectShader))}dispose(){this._blurMaterial.dispose(),null!==this._cubemapShader&&this._cubemapShader.dispose(),null!==this._equirectShader&&this._equirectShader.dispose();for(let t=0;t<_A.length;t++)_A[t].dispose()}_cleanup(t){this._pingPongRenderTarget.dispose(),this._renderer.setRenderTarget(vA),t.scissorTest=!1,EA(t,0,0,t.width,t.height)}_fromTexture(t){vA=this._renderer.getRenderTarget();const e=this._allocateTargets(t);return this._textureToCubeUV(t,e),this._applyPMREM(e),this._cleanup(e),e}_allocateTargets(t){const e={magFilter:Tx,minFilter:Tx,generateMipmaps:!1,type:Nx,format:1023,encoding:TA(t)?t.encoding:$x,depthBuffer:!1},n=MA(e);return n.depthBuffer=!t,this._pingPongRenderTarget=MA(e),n}_compileMaterial(t){const e=new CT(_A[0],t);this._renderer.compile(e,pA)}_sceneToCubeUV(t,e,n,i){const s=new DT(90,1,e,n),r=[1,-1,1,1,1,1],o=[1,1,1,-1,-1,-1],a=this._renderer,l=a.autoClear,c=a.outputEncoding,h=a.toneMapping;a.getClearColor(gA),a.toneMapping=0,a.outputEncoding=qx,a.autoClear=!1;const u=new Jw({name:\\\\\\\"PMREM.Background\\\\\\\",side:1,depthWrite:!1,depthTest:!1}),d=new CT(new LT,u);let p=!1;const _=t.background;_?_.isColor&&(u.color.copy(_),t.background=null,p=!0):(u.color.copy(gA),p=!0);for(let e=0;e<6;e++){const n=e%3;0==n?(s.up.set(0,r[e],0),s.lookAt(o[e],0,0)):1==n?(s.up.set(0,0,r[e]),s.lookAt(0,o[e],0)):(s.up.set(0,r[e],0),s.lookAt(0,0,o[e])),EA(i,n*lA,e>2?lA:0,lA,lA),a.setRenderTarget(i),p&&a.render(d,s),a.render(t,s)}d.geometry.dispose(),d.material.dispose(),a.toneMapping=h,a.outputEncoding=c,a.autoClear=l,t.background=_}_setEncoding(t,e){!0===this._renderer.capabilities.isWebGL2&&e.format===Dx&&e.type===Nx&&e.encoding===Xx?t.value=dA[3e3]:t.value=dA[e.encoding]}_textureToCubeUV(t,e){const n=this._renderer;t.isCubeTexture?null==this._cubemapShader&&(this._cubemapShader=CA()):null==this._equirectShader&&(this._equirectShader=SA());const i=t.isCubeTexture?this._cubemapShader:this._equirectShader,s=new CT(_A[0],i),r=i.uniforms;r.envMap.value=t,t.isCubeTexture||r.texelSize.value.set(1/t.image.width,1/t.image.height),this._setEncoding(r.inputEncoding,t),this._setEncoding(r.outputEncoding,e.texture),EA(e,0,0,3*lA,2*lA),n.setRenderTarget(e),n.render(s,pA)}_applyPMREM(t){const e=this._renderer,n=e.autoClear;e.autoClear=!1;for(let e=1;euA&&console.warn(`sigmaRadians, ${s}, is too large and will clip, as it requested ${_} samples when the maximum is set to 20`);const m=[];let f=0;for(let t=0;t4?i-8+4:0),3*g,2*g),a.setRenderTarget(e),a.render(c,pA)}}function TA(t){return void 0!==t&&t.type===Nx&&(t.encoding===qx||t.encoding===Xx||t.encoding===Yx)}function AA(){const t=[],e=[],n=[];let i=8;for(let s=0;s4?o=cA[s-8+4-1]:0==s&&(o=0),n.push(o);const a=1/(r-1),l=-a/2,c=1+a/2,h=[l,l,c,l,c,c,l,l,c,c,l,c],u=6,d=6,p=3,_=2,m=1,f=new Float32Array(p*d*u),g=new Float32Array(_*d*u),v=new Float32Array(m*d*u);for(let t=0;t2?0:-1,i=[e,n,0,e+2/3,n,0,e+2/3,n+1,0,e,n,0,e+2/3,n+1,0,e,n+1,0];f.set(i,p*d*t),g.set(h,_*d*t);const s=[t,t,t,t,t,t];v.set(s,m*d*t)}const y=new hT;y.setAttribute(\\\\\\\"position\\\\\\\",new Qw(f,p)),y.setAttribute(\\\\\\\"uv\\\\\\\",new Qw(g,_)),y.setAttribute(\\\\\\\"faceIndex\\\\\\\",new Qw(v,m)),t.push(y),i>4&&i--}return{_lodPlanes:t,_sizeLods:e,_sigmas:n}}function MA(t){const e=new Ab(3*lA,3*lA,t);return e.texture.mapping=vx,e.texture.name=\\\\\\\"PMREM.cubeUv\\\\\\\",e.scissorTest=!0,e}function EA(t,e,n,i,s){t.viewport.set(e,n,i,s),t.scissor.set(e,n,i,s)}function SA(){const t=new _b(1,1);return new aA({name:\\\\\\\"EquirectangularToCubeUV\\\\\\\",uniforms:{envMap:{value:null},texelSize:{value:t},inputEncoding:{value:dA[3e3]},outputEncoding:{value:dA[3e3]}},vertexShader:NA(),fragmentShader:`\\\\n\\\\n\\\\t\\\\t\\\\tprecision mediump float;\\\\n\\\\t\\\\t\\\\tprecision mediump int;\\\\n\\\\n\\\\t\\\\t\\\\tvarying vec3 vOutputDirection;\\\\n\\\\n\\\\t\\\\t\\\\tuniform sampler2D envMap;\\\\n\\\\t\\\\t\\\\tuniform vec2 texelSize;\\\\n\\\\n\\\\t\\\\t\\\\t${LA()}\\\\n\\\\n\\\\t\\\\t\\\\t#include \\\\n\\\\n\\\\t\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tgl_FragColor = vec4( 0.0, 0.0, 0.0, 1.0 );\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tvec3 outputDirection = normalize( vOutputDirection );\\\\n\\\\t\\\\t\\\\t\\\\tvec2 uv = equirectUv( outputDirection );\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tvec2 f = fract( uv / texelSize - 0.5 );\\\\n\\\\t\\\\t\\\\t\\\\tuv -= f * texelSize;\\\\n\\\\t\\\\t\\\\t\\\\tvec3 tl = envMapTexelToLinear( texture2D ( envMap, uv ) ).rgb;\\\\n\\\\t\\\\t\\\\t\\\\tuv.x += texelSize.x;\\\\n\\\\t\\\\t\\\\t\\\\tvec3 tr = envMapTexelToLinear( texture2D ( envMap, uv ) ).rgb;\\\\n\\\\t\\\\t\\\\t\\\\tuv.y += texelSize.y;\\\\n\\\\t\\\\t\\\\t\\\\tvec3 br = envMapTexelToLinear( texture2D ( envMap, uv ) ).rgb;\\\\n\\\\t\\\\t\\\\t\\\\tuv.x -= texelSize.x;\\\\n\\\\t\\\\t\\\\t\\\\tvec3 bl = envMapTexelToLinear( texture2D ( envMap, uv ) ).rgb;\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tvec3 tm = mix( tl, tr, f.x );\\\\n\\\\t\\\\t\\\\t\\\\tvec3 bm = mix( bl, br, f.x );\\\\n\\\\t\\\\t\\\\t\\\\tgl_FragColor.rgb = mix( tm, bm, f.y );\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tgl_FragColor = linearToOutputTexel( gl_FragColor );\\\\n\\\\n\\\\t\\\\t\\\\t}\\\\n\\\\t\\\\t`,blending:0,depthTest:!1,depthWrite:!1})}function CA(){return new aA({name:\\\\\\\"CubemapToCubeUV\\\\\\\",uniforms:{envMap:{value:null},inputEncoding:{value:dA[3e3]},outputEncoding:{value:dA[3e3]}},vertexShader:NA(),fragmentShader:`\\\\n\\\\n\\\\t\\\\t\\\\tprecision mediump float;\\\\n\\\\t\\\\t\\\\tprecision mediump int;\\\\n\\\\n\\\\t\\\\t\\\\tvarying vec3 vOutputDirection;\\\\n\\\\n\\\\t\\\\t\\\\tuniform samplerCube envMap;\\\\n\\\\n\\\\t\\\\t\\\\t${LA()}\\\\n\\\\n\\\\t\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tgl_FragColor = vec4( 0.0, 0.0, 0.0, 1.0 );\\\\n\\\\t\\\\t\\\\t\\\\tgl_FragColor.rgb = envMapTexelToLinear( textureCube( envMap, vec3( - vOutputDirection.x, vOutputDirection.yz ) ) ).rgb;\\\\n\\\\t\\\\t\\\\t\\\\tgl_FragColor = linearToOutputTexel( gl_FragColor );\\\\n\\\\n\\\\t\\\\t\\\\t}\\\\n\\\\t\\\\t`,blending:0,depthTest:!1,depthWrite:!1})}function NA(){return\\\\\\\"\\\\n\\\\n\\\\t\\\\tprecision mediump float;\\\\n\\\\t\\\\tprecision mediump int;\\\\n\\\\n\\\\t\\\\tattribute vec3 position;\\\\n\\\\t\\\\tattribute vec2 uv;\\\\n\\\\t\\\\tattribute float faceIndex;\\\\n\\\\n\\\\t\\\\tvarying vec3 vOutputDirection;\\\\n\\\\n\\\\t\\\\t// RH coordinate system; PMREM face-indexing convention\\\\n\\\\t\\\\tvec3 getDirection( vec2 uv, float face ) {\\\\n\\\\n\\\\t\\\\t\\\\tuv = 2.0 * uv - 1.0;\\\\n\\\\n\\\\t\\\\t\\\\tvec3 direction = vec3( uv, 1.0 );\\\\n\\\\n\\\\t\\\\t\\\\tif ( face == 0.0 ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tdirection = direction.zyx; // ( 1, v, u ) pos x\\\\n\\\\n\\\\t\\\\t\\\\t} else if ( face == 1.0 ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tdirection = direction.xzy;\\\\n\\\\t\\\\t\\\\t\\\\tdirection.xz *= -1.0; // ( -u, 1, -v ) pos y\\\\n\\\\n\\\\t\\\\t\\\\t} else if ( face == 2.0 ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tdirection.x *= -1.0; // ( -u, v, 1 ) pos z\\\\n\\\\n\\\\t\\\\t\\\\t} else if ( face == 3.0 ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tdirection = direction.zyx;\\\\n\\\\t\\\\t\\\\t\\\\tdirection.xz *= -1.0; // ( -1, v, -u ) neg x\\\\n\\\\n\\\\t\\\\t\\\\t} else if ( face == 4.0 ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tdirection = direction.xzy;\\\\n\\\\t\\\\t\\\\t\\\\tdirection.xy *= -1.0; // ( -u, -1, v ) neg y\\\\n\\\\n\\\\t\\\\t\\\\t} else if ( face == 5.0 ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tdirection.z *= -1.0; // ( u, v, -1 ) neg z\\\\n\\\\n\\\\t\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\t\\\\treturn direction;\\\\n\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\tvOutputDirection = getDirection( uv, faceIndex );\\\\n\\\\t\\\\t\\\\tgl_Position = vec4( position, 1.0 );\\\\n\\\\n\\\\t\\\\t}\\\\n\\\\t\\\\\\\"}function LA(){return\\\\\\\"\\\\n\\\\n\\\\t\\\\tuniform int inputEncoding;\\\\n\\\\t\\\\tuniform int outputEncoding;\\\\n\\\\n\\\\t\\\\t#include \\\\n\\\\n\\\\t\\\\tvec4 inputTexelToLinear( vec4 value ) {\\\\n\\\\n\\\\t\\\\t\\\\tif ( inputEncoding == 0 ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\treturn value;\\\\n\\\\n\\\\t\\\\t\\\\t} else if ( inputEncoding == 1 ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\treturn sRGBToLinear( value );\\\\n\\\\n\\\\t\\\\t\\\\t} else if ( inputEncoding == 2 ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\treturn RGBEToLinear( value );\\\\n\\\\n\\\\t\\\\t\\\\t} else if ( inputEncoding == 3 ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\treturn RGBMToLinear( value, 7.0 );\\\\n\\\\n\\\\t\\\\t\\\\t} else if ( inputEncoding == 4 ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\treturn RGBMToLinear( value, 16.0 );\\\\n\\\\n\\\\t\\\\t\\\\t} else if ( inputEncoding == 5 ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\treturn RGBDToLinear( value, 256.0 );\\\\n\\\\n\\\\t\\\\t\\\\t} else {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\treturn GammaToLinear( value, 2.2 );\\\\n\\\\n\\\\t\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\tvec4 linearToOutputTexel( vec4 value ) {\\\\n\\\\n\\\\t\\\\t\\\\tif ( outputEncoding == 0 ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\treturn value;\\\\n\\\\n\\\\t\\\\t\\\\t} else if ( outputEncoding == 1 ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\treturn LinearTosRGB( value );\\\\n\\\\n\\\\t\\\\t\\\\t} else if ( outputEncoding == 2 ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\treturn LinearToRGBE( value );\\\\n\\\\n\\\\t\\\\t\\\\t} else if ( outputEncoding == 3 ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\treturn LinearToRGBM( value, 7.0 );\\\\n\\\\n\\\\t\\\\t\\\\t} else if ( outputEncoding == 4 ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\treturn LinearToRGBM( value, 16.0 );\\\\n\\\\n\\\\t\\\\t\\\\t} else if ( outputEncoding == 5 ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\treturn LinearToRGBD( value, 256.0 );\\\\n\\\\n\\\\t\\\\t\\\\t} else {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\treturn LinearToGamma( value, 2.2 );\\\\n\\\\n\\\\t\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\tvec4 envMapTexelToLinear( vec4 color ) {\\\\n\\\\n\\\\t\\\\t\\\\treturn inputTexelToLinear( color );\\\\n\\\\n\\\\t\\\\t}\\\\n\\\\t\\\\\\\"}function OA(t){let e=new WeakMap,n=null;function i(t){const n=t.target;n.removeEventListener(\\\\\\\"dispose\\\\\\\",i);const s=e.get(n);void 0!==s&&(e.delete(n),s.dispose())}return{get:function(s){if(s&&s.isTexture&&!1===s.isRenderTargetTexture){const r=s.mapping,o=r===fx||r===gx,a=r===_x||r===mx;if(o||a){if(e.has(s))return e.get(s).texture;{const r=s.image;if(o&&r&&r.height>0||a&&r&&function(t){let e=0;const n=6;for(let i=0;i65535?eT:tT)(n,1);a.version=o;const l=r.get(t);l&&e.remove(l),r.set(t,a)}return{get:function(t,e){return!0===s[e.id]||(e.addEventListener(\\\\\\\"dispose\\\\\\\",o),s[e.id]=!0,n.memory.geometries++),e},update:function(t){const n=t.attributes;for(const t in n)e.update(n[t],34962);const i=t.morphAttributes;for(const t in i){const n=i[t];for(let t=0,i=n.length;te.maxTextureSize&&(u=Math.ceil(h/e.maxTextureSize),h=e.maxTextureSize);const d=new Float32Array(h*u*4*i),p=new DA(d,h,u,i);p.format=Dx,p.type=Px;const _=4*l;for(let 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0!==r.depthPacking&&r.depthPacking,index0AttributeName:r.index0AttributeName,extensionDerivatives:r.extensions&&r.extensions.derivatives,extensionFragDepth:r.extensions&&r.extensions.fragDepth,extensionDrawBuffers:r.extensions&&r.extensions.drawBuffers,extensionShaderTextureLOD:r.extensions&&r.extensions.shaderTextureLOD,rendererExtensionFragDepth:l||i.has(\\\\\\\"EXT_frag_depth\\\\\\\"),rendererExtensionDrawBuffers:l||i.has(\\\\\\\"WEBGL_draw_buffers\\\\\\\"),rendererExtensionShaderTextureLod:l||i.has(\\\\\\\"EXT_shader_texture_lod\\\\\\\"),customProgramCacheKey:r.customProgramCacheKey()}},getProgramCacheKey:function(e){const n=[];if(e.shaderID?n.push(e.shaderID):(n.push(e.fragmentShader),n.push(e.vertexShader)),void 0!==e.defines)for(const t in e.defines)n.push(t),n.push(e.defines[t]);if(!1===e.isRawShaderMaterial){for(let t=0;t0?s.push(h):!0===n.transparent?r.push(h):i.push(h)},unshift:function(t,e,n,o,l,c){const h=a(t,e,n,o,l,c);n.transmission>0?s.unshift(h):!0===n.transparent?r.unshift(h):i.unshift(h)},finish:function(){for(let t=n,i=e.length;t1&&i.sort(t||pE),s.length>1&&s.sort(e||_E),r.length>1&&r.sort(e||_E)}}}function fE(t){let e=new WeakMap;return{get:function(n,i){let s;return!1===e.has(n)?(s=new mE(t),e.set(n,[s])):i>=e.get(n).length?(s=new mE(t),e.get(n).push(s)):s=e.get(n)[i],s},dispose:function(){e=new WeakMap}}}function gE(){const t={};return{get:function(e){if(void 0!==t[e.id])return t[e.id];let n;switch(e.type){case\\\\\\\"DirectionalLight\\\\\\\":n={direction:new Sb,color:new $w};break;case\\\\\\\"SpotLight\\\\\\\":n={position:new Sb,direction:new Sb,color:new $w,distance:0,coneCos:0,penumbraCos:0,decay:0};break;case\\\\\\\"PointLight\\\\\\\":n={position:new Sb,color:new $w,distance:0,decay:0};break;case\\\\\\\"HemisphereLight\\\\\\\":n={direction:new Sb,skyColor:new $w,groundColor:new $w};break;case\\\\\\\"RectAreaLight\\\\\\\":n={color:new $w,position:new Sb,halfWidth:new Sb,halfHeight:new Sb}}return t[e.id]=n,n}}}let vE=0;function yE(t,e){return(e.castShadow?1:0)-(t.castShadow?1:0)}function xE(t,e){const n=new gE,i=function(){const t={};return{get:function(e){if(void 0!==t[e.id])return t[e.id];let n;switch(e.type){case\\\\\\\"DirectionalLight\\\\\\\":case\\\\\\\"SpotLight\\\\\\\":n={shadowBias:0,shadowNormalBias:0,shadowRadius:1,shadowMapSize:new _b};break;case\\\\\\\"PointLight\\\\\\\":n={shadowBias:0,shadowNormalBias:0,shadowRadius:1,shadowMapSize:new _b,shadowCameraNear:1,shadowCameraFar:1e3}}return t[e.id]=n,n}}}(),s={version:0,hash:{directionalLength:-1,pointLength:-1,spotLength:-1,rectAreaLength:-1,hemiLength:-1,numDirectionalShadows:-1,numPointShadows:-1,numSpotShadows:-1},ambient:[0,0,0],probe:[],directional:[],directionalShadow:[],directionalShadowMap:[],directionalShadowMatrix:[],spot:[],spotShadow:[],spotShadowMap:[],spotShadowMatrix:[],rectArea:[],rectAreaLTC1:null,rectAreaLTC2:null,point:[],pointShadow:[],pointShadowMap:[],pointShadowMatrix:[],hemi:[]};for(let t=0;t<9;t++)s.probe.push(new Sb);const r=new Sb,o=new sw,a=new sw;return{setup:function(r,o){let a=0,l=0,c=0;for(let t=0;t<9;t++)s.probe[t].set(0,0,0);let h=0,u=0,d=0,p=0,_=0,m=0,f=0,g=0;r.sort(yE);const v=!0!==o?Math.PI:1;for(let t=0,e=r.length;t0&&(e.isWebGL2||!0===t.has(\\\\\\\"OES_texture_float_linear\\\\\\\")?(s.rectAreaLTC1=KT.LTC_FLOAT_1,s.rectAreaLTC2=KT.LTC_FLOAT_2):!0===t.has(\\\\\\\"OES_texture_half_float_linear\\\\\\\")?(s.rectAreaLTC1=KT.LTC_HALF_1,s.rectAreaLTC2=KT.LTC_HALF_2):console.error(\\\\\\\"THREE.WebGLRenderer: Unable to use RectAreaLight. Missing WebGL extensions.\\\\\\\")),s.ambient[0]=a,s.ambient[1]=l,s.ambient[2]=c;const y=s.hash;y.directionalLength===h&&y.pointLength===u&&y.spotLength===d&&y.rectAreaLength===p&&y.hemiLength===_&&y.numDirectionalShadows===m&&y.numPointShadows===f&&y.numSpotShadows===g||(s.directional.length=h,s.spot.length=d,s.rectArea.length=p,s.point.length=u,s.hemi.length=_,s.directionalShadow.length=m,s.directionalShadowMap.length=m,s.pointShadow.length=f,s.pointShadowMap.length=f,s.spotShadow.length=g,s.spotShadowMap.length=g,s.directionalShadowMatrix.length=m,s.pointShadowMatrix.length=f,s.spotShadowMatrix.length=g,y.directionalLength=h,y.pointLength=u,y.spotLength=d,y.rectAreaLength=p,y.hemiLength=_,y.numDirectionalShadows=m,y.numPointShadows=f,y.numSpotShadows=g,s.version=vE++)},setupView:function(t,e){let n=0,i=0,l=0,c=0,h=0;const u=e.matrixWorldInverse;for(let e=0,d=t.length;e=n.get(i).length?(r=new bE(t,e),n.get(i).push(r)):r=n.get(i)[s],r},dispose:function(){n=new WeakMap}}}class TE extends Vw{constructor(t){super(),this.type=\\\\\\\"MeshDepthMaterial\\\\\\\",this.depthPacking=3200,this.map=null,this.alphaMap=null,this.displacementMap=null,this.displacementScale=1,this.displacementBias=0,this.wireframe=!1,this.wireframeLinewidth=1,this.fog=!1,this.setValues(t)}copy(t){return super.copy(t),this.depthPacking=t.depthPacking,this.map=t.map,this.alphaMap=t.alphaMap,this.displacementMap=t.displacementMap,this.displacementScale=t.displacementScale,this.displacementBias=t.displacementBias,this.wireframe=t.wireframe,this.wireframeLinewidth=t.wireframeLinewidth,this}}TE.prototype.isMeshDepthMaterial=!0;class AE extends Vw{constructor(t){super(),this.type=\\\\\\\"MeshDistanceMaterial\\\\\\\",this.referencePosition=new Sb,this.nearDistance=1,this.farDistance=1e3,this.map=null,this.alphaMap=null,this.displacementMap=null,this.displacementScale=1,this.displacementBias=0,this.fog=!1,this.setValues(t)}copy(t){return super.copy(t),this.referencePosition.copy(t.referencePosition),this.nearDistance=t.nearDistance,this.farDistance=t.farDistance,this.map=t.map,this.alphaMap=t.alphaMap,this.displacementMap=t.displacementMap,this.displacementScale=t.displacementScale,this.displacementBias=t.displacementBias,this}}AE.prototype.isMeshDistanceMaterial=!0;function ME(t,e,n){let i=new XT;const s=new _b,r=new _b,o=new Tb,a=new TE({depthPacking:3201}),l=new AE,c={},h=n.maxTextureSize,u={0:1,1:0,2:2},d=new IT({uniforms:{shadow_pass:{value:null},resolution:{value:new _b},radius:{value:4},samples:{value:8}},vertexShader:\\\\\\\"void main() {\\\\n\\\\tgl_Position = vec4( position, 1.0 );\\\\n}\\\\\\\",fragmentShader:\\\\\\\"uniform sampler2D shadow_pass;\\\\nuniform vec2 resolution;\\\\nuniform float radius;\\\\nuniform float samples;\\\\n#include \\\\nvoid main() {\\\\n\\\\tfloat mean = 0.0;\\\\n\\\\tfloat squared_mean = 0.0;\\\\n\\\\tfloat uvStride = samples <= 1.0 ? 0.0 : 2.0 / ( samples - 1.0 );\\\\n\\\\tfloat uvStart = samples <= 1.0 ? 0.0 : - 1.0;\\\\n\\\\tfor ( float i = 0.0; i < samples; i ++ ) {\\\\n\\\\t\\\\tfloat uvOffset = uvStart + i * uvStride;\\\\n\\\\t\\\\t#ifdef HORIZONTAL_PASS\\\\n\\\\t\\\\t\\\\tvec2 distribution = unpackRGBATo2Half( texture2D( shadow_pass, ( gl_FragCoord.xy + vec2( uvOffset, 0.0 ) * radius ) / resolution ) );\\\\n\\\\t\\\\t\\\\tmean += distribution.x;\\\\n\\\\t\\\\t\\\\tsquared_mean += distribution.y * distribution.y + distribution.x * distribution.x;\\\\n\\\\t\\\\t#else\\\\n\\\\t\\\\t\\\\tfloat depth = unpackRGBAToDepth( texture2D( shadow_pass, ( gl_FragCoord.xy + vec2( 0.0, uvOffset ) * radius ) / resolution ) );\\\\n\\\\t\\\\t\\\\tmean += depth;\\\\n\\\\t\\\\t\\\\tsquared_mean += depth * depth;\\\\n\\\\t\\\\t#endif\\\\n\\\\t}\\\\n\\\\tmean = mean / samples;\\\\n\\\\tsquared_mean = squared_mean / samples;\\\\n\\\\tfloat std_dev = sqrt( squared_mean - mean * mean );\\\\n\\\\tgl_FragColor = pack2HalfToRGBA( vec2( mean, std_dev ) );\\\\n}\\\\\\\"}),p=d.clone();p.defines.HORIZONTAL_PASS=1;const _=new hT;_.setAttribute(\\\\\\\"position\\\\\\\",new Qw(new Float32Array([-1,-1,.5,3,-1,.5,-1,3,.5]),3));const m=new CT(_,d),f=this;function g(n,i){const s=e.update(m);d.uniforms.shadow_pass.value=n.map.texture,d.uniforms.resolution.value=n.mapSize,d.uniforms.radius.value=n.radius,d.uniforms.samples.value=n.blurSamples,t.setRenderTarget(n.mapPass),t.clear(),t.renderBufferDirect(i,null,s,d,m,null),p.uniforms.shadow_pass.value=n.mapPass.texture,p.uniforms.resolution.value=n.mapSize,p.uniforms.radius.value=n.radius,p.uniforms.samples.value=n.blurSamples,t.setRenderTarget(n.map),t.clear(),t.renderBufferDirect(i,null,s,p,m,null)}function v(e,n,i,s,r,o,h){let d=null;const p=!0===s.isPointLight?e.customDistanceMaterial:e.customDepthMaterial;if(d=void 0!==p?p:!0===s.isPointLight?l:a,t.localClippingEnabled&&!0===i.clipShadows&&0!==i.clippingPlanes.length||i.displacementMap&&0!==i.displacementScale||i.alphaMap&&i.alphaTest>0){const t=d.uuid,e=i.uuid;let n=c[t];void 0===n&&(n={},c[t]=n);let s=n[e];void 0===s&&(s=d.clone(),n[e]=s),d=s}return d.visible=i.visible,d.wireframe=i.wireframe,d.side=3===h?null!==i.shadowSide?i.shadowSide:i.side:null!==i.shadowSide?i.shadowSide:u[i.side],d.alphaMap=i.alphaMap,d.alphaTest=i.alphaTest,d.clipShadows=i.clipShadows,d.clippingPlanes=i.clippingPlanes,d.clipIntersection=i.clipIntersection,d.displacementMap=i.displacementMap,d.displacementScale=i.displacementScale,d.displacementBias=i.displacementBias,d.wireframeLinewidth=i.wireframeLinewidth,d.linewidth=i.linewidth,!0===s.isPointLight&&!0===d.isMeshDistanceMaterial&&(d.referencePosition.setFromMatrixPosition(s.matrixWorld),d.nearDistance=r,d.farDistance=o),d}function y(n,s,r,o,a){if(!1===n.visible)return;if(n.layers.test(s.layers)&&(n.isMesh||n.isLine||n.isPoints)&&(n.castShadow||n.receiveShadow&&3===a)&&(!n.frustumCulled||i.intersectsObject(n))){n.modelViewMatrix.multiplyMatrices(r.matrixWorldInverse,n.matrixWorld);const i=e.update(n),s=n.material;if(Array.isArray(s)){const e=i.groups;for(let l=0,c=e.length;lh||s.y>h)&&(s.x>h&&(r.x=Math.floor(h/p.x),s.x=r.x*p.x,u.mapSize.x=r.x),s.y>h&&(r.y=Math.floor(h/p.y),s.y=r.y*p.y,u.mapSize.y=r.y)),null===u.map&&!u.isPointLightShadow&&3===this.type){const t={minFilter:Ex,magFilter:Ex,format:Dx};u.map=new Ab(s.x,s.y,t),u.map.texture.name=c.name+\\\\\\\".shadowMap\\\\\\\",u.mapPass=new Ab(s.x,s.y,t),u.camera.updateProjectionMatrix()}if(null===u.map){const t={minFilter:Tx,magFilter:Tx,format:Dx};u.map=new Ab(s.x,s.y,t),u.map.texture.name=c.name+\\\\\\\".shadowMap\\\\\\\",u.camera.updateProjectionMatrix()}t.setRenderTarget(u.map),t.clear();const _=u.getViewportCount();for(let t=0;t<_;t++){const e=u.getViewport(t);o.set(r.x*e.x,r.y*e.y,r.x*e.z,r.y*e.w),d.viewport(o),u.updateMatrices(c,t),i=u.getFrustum(),y(n,a,u.camera,c,this.type)}u.isPointLightShadow||3!==this.type||g(u,a),u.needsUpdate=!1}f.needsUpdate=!1,t.setRenderTarget(l,c,u)}}function EE(t,e,n){const i=n.isWebGL2;const s=new function(){let e=!1;const n=new Tb;let i=null;const s=new Tb(0,0,0,0);return{setMask:function(n){i===n||e||(t.colorMask(n,n,n,n),i=n)},setLocked:function(t){e=t},setClear:function(e,i,r,o,a){!0===a&&(e*=o,i*=o,r*=o),n.set(e,i,r,o),!1===s.equals(n)&&(t.clearColor(e,i,r,o),s.copy(n))},reset:function(){e=!1,i=null,s.set(-1,0,0,0)}}},r=new function(){let e=!1,n=null,i=null,s=null;return{setTest:function(t){t?B(2929):z(2929)},setMask:function(i){n===i||e||(t.depthMask(i),n=i)},setFunc:function(e){if(i!==e){if(e)switch(e){case 0:t.depthFunc(512);break;case 1:t.depthFunc(519);break;case 2:t.depthFunc(513);break;case 3:t.depthFunc(515);break;case 4:t.depthFunc(514);break;case 5:t.depthFunc(518);break;case 6:t.depthFunc(516);break;case 7:t.depthFunc(517);break;default:t.depthFunc(515)}else t.depthFunc(515);i=e}},setLocked:function(t){e=t},setClear:function(e){s!==e&&(t.clearDepth(e),s=e)},reset:function(){e=!1,n=null,i=null,s=null}}},o=new function(){let e=!1,n=null,i=null,s=null,r=null,o=null,a=null,l=null,c=null;return{setTest:function(t){e||(t?B(2960):z(2960))},setMask:function(i){n===i||e||(t.stencilMask(i),n=i)},setFunc:function(e,n,o){i===e&&s===n&&r===o||(t.stencilFunc(e,n,o),i=e,s=n,r=o)},setOp:function(e,n,i){o===e&&a===n&&l===i||(t.stencilOp(e,n,i),o=e,a=n,l=i)},setLocked:function(t){e=t},setClear:function(e){c!==e&&(t.clearStencil(e),c=e)},reset:function(){e=!1,n=null,i=null,s=null,r=null,o=null,a=null,l=null,c=null}}};let a={},l=null,c={},h=null,u=!1,d=null,p=null,_=null,m=null,f=null,g=null,v=null,y=!1,x=null,b=null,w=null,T=null,A=null;const M=t.getParameter(35661);let E=!1,S=0;const C=t.getParameter(7938);-1!==C.indexOf(\\\\\\\"WebGL\\\\\\\")?(S=parseFloat(/^WebGL (\\\\d)/.exec(C)[1]),E=S>=1):-1!==C.indexOf(\\\\\\\"OpenGL ES\\\\\\\")&&(S=parseFloat(/^OpenGL ES (\\\\d)/.exec(C)[1]),E=S>=2);let N=null,L={};const O=t.getParameter(3088),P=t.getParameter(2978),R=(new Tb).fromArray(O),I=(new Tb).fromArray(P);function F(e,n,i){const s=new Uint8Array(4),r=t.createTexture();t.bindTexture(e,r),t.texParameteri(e,10241,9728),t.texParameteri(e,10240,9728);for(let e=0;ei||t.height>i)&&(s=i/Math.max(t.width,t.height)),s<1||!0===e){if(\\\\\\\"undefined\\\\\\\"!=typeof HTMLImageElement&&t instanceof HTMLImageElement||\\\\\\\"undefined\\\\\\\"!=typeof HTMLCanvasElement&&t instanceof HTMLCanvasElement||\\\\\\\"undefined\\\\\\\"!=typeof ImageBitmap&&t instanceof ImageBitmap){const i=e?db:Math.floor,r=i(s*t.width),o=i(s*t.height);void 0===p&&(p=m(r,o));const a=n?m(r,o):p;a.width=r,a.height=o;return a.getContext(\\\\\\\"2d\\\\\\\").drawImage(t,0,0,r,o),console.warn(\\\\\\\"THREE.WebGLRenderer: Texture has been resized from (\\\\\\\"+t.width+\\\\\\\"x\\\\\\\"+t.height+\\\\\\\") to (\\\\\\\"+r+\\\\\\\"x\\\\\\\"+o+\\\\\\\").\\\\\\\"),a}return\\\\\\\"data\\\\\\\"in t&&console.warn(\\\\\\\"THREE.WebGLRenderer: Image in DataTexture is too big (\\\\\\\"+t.width+\\\\\\\"x\\\\\\\"+t.height+\\\\\\\").\\\\\\\"),t}return t}function g(t){return hb(t.width)&&hb(t.height)}function v(t,e){return t.generateMipmaps&&e&&t.minFilter!==Tx&&t.minFilter!==Ex}function y(e,n,s,r,o=1){t.generateMipmap(e);i.get(n).__maxMipLevel=Math.log2(Math.max(s,r,o))}function x(n,i,s,r){if(!1===a)return i;if(null!==n){if(void 0!==t[n])return t[n];console.warn(\\\\\\\"THREE.WebGLRenderer: Attempt to use non-existing WebGL internal format '\\\\\\\"+n+\\\\\\\"'\\\\\\\")}let o=i;return 6403===i&&(5126===s&&(o=33326),5131===s&&(o=33325),5121===s&&(o=33321)),6407===i&&(5126===s&&(o=34837),5131===s&&(o=34843),5121===s&&(o=32849)),6408===i&&(5126===s&&(o=34836),5131===s&&(o=34842),5121===s&&(o=r===Xx?35907:32856)),33325!==o&&33326!==o&&34842!==o&&34836!==o||e.get(\\\\\\\"EXT_color_buffer_float\\\\\\\"),o}function b(t){return t===Tx||t===Ax||t===Mx?9728:9729}function w(e){const n=e.target;n.removeEventListener(\\\\\\\"dispose\\\\\\\",w),function(e){const n=i.get(e);if(void 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e=0,s=n.length;e0&&s.__version!==t.version){const n=t.image;if(void 0===n)console.warn(\\\\\\\"THREE.WebGLRenderer: Texture marked for update but image is undefined\\\\\\\");else{if(!1!==n.complete)return void O(s,t,e);console.warn(\\\\\\\"THREE.WebGLRenderer: Texture marked for update but image is incomplete\\\\\\\")}}n.activeTexture(33984+e),n.bindTexture(3553,s.__webglTexture)}function E(e,s){const o=i.get(e);e.version>0&&o.__version!==e.version?function(e,i,s){if(6!==i.image.length)return;L(e,i),n.activeTexture(33984+s),n.bindTexture(34067,e.__webglTexture),t.pixelStorei(37440,i.flipY),t.pixelStorei(37441,i.premultiplyAlpha),t.pixelStorei(3317,i.unpackAlignment),t.pixelStorei(37443,0);const o=i&&(i.isCompressedTexture||i.image[0].isCompressedTexture),l=i.image[0]&&i.image[0].isDataTexture,h=[];for(let t=0;t<6;t++)h[t]=o||l?l?i.image[t].image:i.image[t]:f(i.image[t],!1,!0,c);const u=h[0],d=g(u)||a,p=r.convert(i.format),_=r.convert(i.type),m=x(i.internalFormat,p,_,i.encoding);let b;if(N(34067,i,d),o){for(let t=0;t<6;t++){b=h[t].mipmaps;for(let e=0;e1||i.get(r).__currentAnisotropy)&&(t.texParameterf(n,o.TEXTURE_MAX_ANISOTROPY_EXT,Math.min(r.anisotropy,s.getMaxAnisotropy())),i.get(r).__currentAnisotropy=r.anisotropy)}}function L(e,n){void 0===e.__webglInit&&(e.__webglInit=!0,n.addEventListener(\\\\\\\"dispose\\\\\\\",w),e.__webglTexture=t.createTexture(),o.memory.textures++)}function O(e,i,s){let o=3553;i.isDataTexture2DArray&&(o=35866),i.isDataTexture3D&&(o=32879),L(e,i),n.activeTexture(33984+s),n.bindTexture(o,e.__webglTexture),t.pixelStorei(37440,i.flipY),t.pixelStorei(37441,i.premultiplyAlpha),t.pixelStorei(3317,i.unpackAlignment),t.pixelStorei(37443,0);const l=function(t){return!a&&(t.wrapS!==bx||t.wrapT!==bx||t.minFilter!==Tx&&t.minFilter!==Ex)}(i)&&!1===g(i.image),c=f(i.image,l,!1,h),u=g(c)||a,d=r.convert(i.format);let p,_=r.convert(i.type),m=x(i.internalFormat,d,_,i.encoding);N(o,i,u);const 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s=i.get(t);t.version>0&&s.__version!==t.version?O(s,t,e):(n.activeTexture(33984+e),n.bindTexture(35866,s.__webglTexture))},this.setTexture3D=function(t,e){const s=i.get(t);t.version>0&&s.__version!==t.version?O(s,t,e):(n.activeTexture(33984+e),n.bindTexture(32879,s.__webglTexture))},this.setTextureCube=E,this.setupRenderTarget=function(e){const l=e.texture,c=i.get(e),h=i.get(l);e.addEventListener(\\\\\\\"dispose\\\\\\\",T),!0!==e.isWebGLMultipleRenderTargets&&(h.__webglTexture=t.createTexture(),h.__version=l.version,o.memory.textures++);const u=!0===e.isWebGLCubeRenderTarget,d=!0===e.isWebGLMultipleRenderTargets,p=!0===e.isWebGLMultisampleRenderTarget,_=l.isDataTexture3D||l.isDataTexture2DArray,m=g(e)||a;if(!a||l.format!==Fx||l.type!==Px&&l.type!==Rx||(l.format=Dx,console.warn(\\\\\\\"THREE.WebGLRenderer: Rendering to textures with RGB format is not supported. Using RGBA format instead.\\\\\\\")),u){c.__webglFramebuffer=[];for(let e=0;e<6;e++)c.__webglFramebuffer[e]=t.createFramebuffer()}else if(c.__webglFramebuffer=t.createFramebuffer(),d)if(s.drawBuffers){const n=e.texture;for(let e=0,s=n.length;ea+c?(l.inputState.pinching=!1,this.dispatchEvent({type:\\\\\\\"pinchend\\\\\\\",handedness:t.handedness,target:this})):!l.inputState.pinching&&o<=a-c&&(l.inputState.pinching=!0,this.dispatchEvent({type:\\\\\\\"pinchstart\\\\\\\",handedness:t.handedness,target:this}))}else null!==a&&t.gripSpace&&(s=e.getPose(t.gripSpace,n),null!==s&&(a.matrix.fromArray(s.transform.matrix),a.matrix.decompose(a.position,a.rotation,a.scale),s.linearVelocity?(a.hasLinearVelocity=!0,a.linearVelocity.copy(s.linearVelocity)):a.hasLinearVelocity=!1,s.angularVelocity?(a.hasAngularVelocity=!0,a.angularVelocity.copy(s.angularVelocity)):a.hasAngularVelocity=!1));return null!==o&&(o.visible=null!==i),null!==a&&(a.visible=null!==s),null!==l&&(l.visible=null!==r),this}}class RE extends tb{constructor(t,e){super();const n=this,i=t.state;let s=null,r=1,o=null,a=\\\\\\\"local-floor\\\\\\\",l=null,c=null,h=null,u=null,d=null,p=!1,_=null,m=null,f=null,g=null,v=null,y=null;const x=[],b=new Map,w=new DT;w.layers.enable(1),w.viewport=new Tb;const T=new DT;T.layers.enable(2),T.viewport=new Tb;const A=[w,T],M=new NE;M.layers.enable(1),M.layers.enable(2);let E=null,S=null;function C(t){const e=b.get(t.inputSource);e&&e.dispatchEvent({type:t.type,data:t.inputSource})}function N(){b.forEach((function(t,e){t.disconnect(e)})),b.clear(),E=null,S=null,i.bindXRFramebuffer(null),t.setRenderTarget(t.getRenderTarget()),h&&e.deleteFramebuffer(h),_&&e.deleteFramebuffer(_),m&&e.deleteRenderbuffer(m),f&&e.deleteRenderbuffer(f),h=null,_=null,m=null,f=null,d=null,u=null,c=null,s=null,F.stop(),n.isPresenting=!1,n.dispatchEvent({type:\\\\\\\"sessionend\\\\\\\"})}function L(t){const e=s.inputSources;for(let t=0;t0&&(e.alphaTest.value=n.alphaTest);const i=t.get(n).envMap;if(i){e.envMap.value=i,e.flipEnvMap.value=i.isCubeTexture&&!1===i.isRenderTargetTexture?-1:1,e.reflectivity.value=n.reflectivity,e.ior.value=n.ior,e.refractionRatio.value=n.refractionRatio;const s=t.get(i).__maxMipLevel;void 0!==s&&(e.maxMipLevel.value=s)}let s,r;n.lightMap&&(e.lightMap.value=n.lightMap,e.lightMapIntensity.value=n.lightMapIntensity),n.aoMap&&(e.aoMap.value=n.aoMap,e.aoMapIntensity.value=n.aoMapIntensity),n.map?s=n.map:n.specularMap?s=n.specularMap:n.displacementMap?s=n.displacementMap:n.normalMap?s=n.normalMap:n.bumpMap?s=n.bumpMap:n.roughnessMap?s=n.roughnessMap:n.metalnessMap?s=n.metalnessMap:n.alphaMap?s=n.alphaMap:n.emissiveMap?s=n.emissiveMap:n.clearcoatMap?s=n.clearcoatMap:n.clearcoatNormalMap?s=n.clearcoatNormalMap:n.clearcoatRoughnessMap?s=n.clearcoatRoughnessMap:n.specularIntensityMap?s=n.specularIntensityMap:n.specularTintMap?s=n.specularTintMap:n.transmissionMap?s=n.transmissionMap:n.thicknessMap&&(s=n.thicknessMap),void 0!==s&&(s.isWebGLRenderTarget&&(s=s.texture),!0===s.matrixAutoUpdate&&s.updateMatrix(),e.uvTransform.value.copy(s.matrix)),n.aoMap?r=n.aoMap:n.lightMap&&(r=n.lightMap),void 0!==r&&(r.isWebGLRenderTarget&&(r=r.texture),!0===r.matrixAutoUpdate&&r.updateMatrix(),e.uv2Transform.value.copy(r.matrix))}function n(e,n){e.roughness.value=n.roughness,e.metalness.value=n.metalness,n.roughnessMap&&(e.roughnessMap.value=n.roughnessMap),n.metalnessMap&&(e.metalnessMap.value=n.metalnessMap),n.emissiveMap&&(e.emissiveMap.value=n.emissiveMap),n.bumpMap&&(e.bumpMap.value=n.bumpMap,e.bumpScale.value=n.bumpScale,1===n.side&&(e.bumpScale.value*=-1)),n.normalMap&&(e.normalMap.value=n.normalMap,e.normalScale.value.copy(n.normalScale),1===n.side&&e.normalScale.value.negate()),n.displacementMap&&(e.displacementMap.value=n.displacementMap,e.displacementScale.value=n.displacementScale,e.displacementBias.value=n.displacementBias);t.get(n).envMap&&(e.envMapIntensity.value=n.envMapIntensity)}return{refreshFogUniforms:function(t,e){t.fogColor.value.copy(e.color),e.isFog?(t.fogNear.value=e.near,t.fogFar.value=e.far):e.isFogExp2&&(t.fogDensity.value=e.density)},refreshMaterialUniforms:function(t,i,s,r,o){i.isMeshBasicMaterial?e(t,i):i.isMeshLambertMaterial?(e(t,i),function(t,e){e.emissiveMap&&(t.emissiveMap.value=e.emissiveMap)}(t,i)):i.isMeshToonMaterial?(e(t,i),function(t,e){e.gradientMap&&(t.gradientMap.value=e.gradientMap);e.emissiveMap&&(t.emissiveMap.value=e.emissiveMap);e.bumpMap&&(t.bumpMap.value=e.bumpMap,t.bumpScale.value=e.bumpScale,1===e.side&&(t.bumpScale.value*=-1));e.normalMap&&(t.normalMap.value=e.normalMap,t.normalScale.value.copy(e.normalScale),1===e.side&&t.normalScale.value.negate());e.displacementMap&&(t.displacementMap.value=e.displacementMap,t.displacementScale.value=e.displacementScale,t.displacementBias.value=e.displacementBias)}(t,i)):i.isMeshPhongMaterial?(e(t,i),function(t,e){t.specular.value.copy(e.specular),t.shininess.value=Math.max(e.shininess,1e-4),e.emissiveMap&&(t.emissiveMap.value=e.emissiveMap);e.bumpMap&&(t.bumpMap.value=e.bumpMap,t.bumpScale.value=e.bumpScale,1===e.side&&(t.bumpScale.value*=-1));e.normalMap&&(t.normalMap.value=e.normalMap,t.normalScale.value.copy(e.normalScale),1===e.side&&t.normalScale.value.negate());e.displacementMap&&(t.displacementMap.value=e.displacementMap,t.displacementScale.value=e.displacementScale,t.displacementBias.value=e.displacementBias)}(t,i)):i.isMeshStandardMaterial?(e(t,i),i.isMeshPhysicalMaterial?function(t,e,i){n(t,e),t.ior.value=e.ior,e.sheen>0&&(t.sheenTint.value.copy(e.sheenTint).multiplyScalar(e.sheen),t.sheenRoughness.value=e.sheenRoughness);e.clearcoat>0&&(t.clearcoat.value=e.clearcoat,t.clearcoatRoughness.value=e.clearcoatRoughness,e.clearcoatMap&&(t.clearcoatMap.value=e.clearcoatMap),e.clearcoatRoughnessMap&&(t.clearcoatRoughnessMap.value=e.clearcoatRoughnessMap),e.clearcoatNormalMap&&(t.clearcoatNormalScale.value.copy(e.clearcoatNormalScale),t.clearcoatNormalMap.value=e.clearcoatNormalMap,1===e.side&&t.clearcoatNormalScale.value.negate()));e.transmission>0&&(t.transmission.value=e.transmission,t.transmissionSamplerMap.value=i.texture,t.transmissionSamplerSize.value.set(i.width,i.height),e.transmissionMap&&(t.transmissionMap.value=e.transmissionMap),t.thickness.value=e.thickness,e.thicknessMap&&(t.thicknessMap.value=e.thicknessMap),t.attenuationDistance.value=e.attenuationDistance,t.attenuationTint.value.copy(e.attenuationTint));t.specularIntensity.value=e.specularIntensity,t.specularTint.value.copy(e.specularTint),e.specularIntensityMap&&(t.specularIntensityMap.value=e.specularIntensityMap);e.specularTintMap&&(t.specularTintMap.value=e.specularTintMap)}(t,i,o):n(t,i)):i.isMeshMatcapMaterial?(e(t,i),function(t,e){e.matcap&&(t.matcap.value=e.matcap);e.bumpMap&&(t.bumpMap.value=e.bumpMap,t.bumpScale.value=e.bumpScale,1===e.side&&(t.bumpScale.value*=-1));e.normalMap&&(t.normalMap.value=e.normalMap,t.normalScale.value.copy(e.normalScale),1===e.side&&t.normalScale.value.negate());e.displacementMap&&(t.displacementMap.value=e.displacementMap,t.displacementScale.value=e.displacementScale,t.displacementBias.value=e.displacementBias)}(t,i)):i.isMeshDepthMaterial?(e(t,i),function(t,e){e.displacementMap&&(t.displacementMap.value=e.displacementMap,t.displacementScale.value=e.displacementScale,t.displacementBias.value=e.displacementBias)}(t,i)):i.isMeshDistanceMaterial?(e(t,i),function(t,e){e.displacementMap&&(t.displacementMap.value=e.displacementMap,t.displacementScale.value=e.displacementScale,t.displacementBias.value=e.displacementBias);t.referencePosition.value.copy(e.referencePosition),t.nearDistance.value=e.nearDistance,t.farDistance.value=e.farDistance}(t,i)):i.isMeshNormalMaterial?(e(t,i),function(t,e){e.bumpMap&&(t.bumpMap.value=e.bumpMap,t.bumpScale.value=e.bumpScale,1===e.side&&(t.bumpScale.value*=-1));e.normalMap&&(t.normalMap.value=e.normalMap,t.normalScale.value.copy(e.normalScale),1===e.side&&t.normalScale.value.negate());e.displacementMap&&(t.displacementMap.value=e.displacementMap,t.displacementScale.value=e.displacementScale,t.displacementBias.value=e.displacementBias)}(t,i)):i.isLineBasicMaterial?(function(t,e){t.diffuse.value.copy(e.color),t.opacity.value=e.opacity}(t,i),i.isLineDashedMaterial&&function(t,e){t.dashSize.value=e.dashSize,t.totalSize.value=e.dashSize+e.gapSize,t.scale.value=e.scale}(t,i)):i.isPointsMaterial?function(t,e,n,i){t.diffuse.value.copy(e.color),t.opacity.value=e.opacity,t.size.value=e.size*n,t.scale.value=.5*i,e.map&&(t.map.value=e.map);e.alphaMap&&(t.alphaMap.value=e.alphaMap);e.alphaTest>0&&(t.alphaTest.value=e.alphaTest);let s;e.map?s=e.map:e.alphaMap&&(s=e.alphaMap);void 0!==s&&(!0===s.matrixAutoUpdate&&s.updateMatrix(),t.uvTransform.value.copy(s.matrix))}(t,i,s,r):i.isSpriteMaterial?function(t,e){t.diffuse.value.copy(e.color),t.opacity.value=e.opacity,t.rotation.value=e.rotation,e.map&&(t.map.value=e.map);e.alphaMap&&(t.alphaMap.value=e.alphaMap);e.alphaTest>0&&(t.alphaTest.value=e.alphaTest);let n;e.map?n=e.map:e.alphaMap&&(n=e.alphaMap);void 0!==n&&(!0===n.matrixAutoUpdate&&n.updateMatrix(),t.uvTransform.value.copy(n.matrix))}(t,i):i.isShadowMaterial?(t.color.value.copy(i.color),t.opacity.value=i.opacity):i.isShaderMaterial&&(i.uniformsNeedUpdate=!1)}}}function FE(t={}){const e=void 0!==t.canvas?t.canvas:function(){const t=gb(\\\\\\\"canvas\\\\\\\");return t.style.display=\\\\\\\"block\\\\\\\",t}(),n=void 0!==t.context?t.context:null,i=void 0!==t.alpha&&t.alpha,s=void 0===t.depth||t.depth,r=void 0===t.stencil||t.stencil,o=void 0!==t.antialias&&t.antialias,a=void 0===t.premultipliedAlpha||t.premultipliedAlpha,l=void 0!==t.preserveDrawingBuffer&&t.preserveDrawingBuffer,c=void 0!==t.powerPreference?t.powerPreference:\\\\\\\"default\\\\\\\",h=void 0!==t.failIfMajorPerformanceCaveat&&t.failIfMajorPerformanceCaveat;let u=null,d=null;const p=[],_=[];this.domElement=e,this.debug={checkShaderErrors:!0},this.autoClear=!0,this.autoClearColor=!0,this.autoClearDepth=!0,this.autoClearStencil=!0,this.sortObjects=!0,this.clippingPlanes=[],this.localClippingEnabled=!1,this.gammaFactor=2,this.outputEncoding=qx,this.physicallyCorrectLights=!1,this.toneMapping=0,this.toneMappingExposure=1;const m=this;let f=!1,g=0,v=0,y=null,x=-1,b=null;const w=new Tb,T=new Tb;let A=null,M=e.width,E=e.height,S=1,C=null,N=null;const L=new Tb(0,0,M,E),O=new Tb(0,0,M,E);let P=!1;const R=[],I=new XT;let F=!1,D=!1,B=null;const z=new sw,k=new Sb,U={background:null,fog:null,environment:null,overrideMaterial:null,isScene:!0};function G(){return null===y?S:1}let V,H,j,W,q,X,Y,$,J,Z,K,Q,tt,et,nt,it,st,rt,ot,at,lt,ct,ht,ut=n;function dt(t,n){for(let i=0;i0&&function(t,e,n){if(null===B){const t=!0===o&&!0===H.isWebGL2;B=new(t?Mb:Ab)(1024,1024,{generateMipmaps:!0,type:null!==ct.convert(Rx)?Rx:Nx,minFilter:Cx,magFilter:Tx,wrapS:bx,wrapT:bx})}const i=m.getRenderTarget();m.setRenderTarget(B),m.clear();const s=m.toneMapping;m.toneMapping=0,At(t,e,n),m.toneMapping=s,X.updateMultisampleRenderTarget(B),X.updateRenderTargetMipmap(B),m.setRenderTarget(i)}(s,e,n),i&&j.viewport(w.copy(i)),s.length>0&&At(s,e,n),r.length>0&&At(r,e,n),a.length>0&&At(a,e,n)}function At(t,e,n){const i=!0===e.isScene?e.overrideMaterial:null;for(let s=0,r=t.length;s0?_[_.length-1]:null,p.pop(),u=p.length>0?p[p.length-1]:null},this.getActiveCubeFace=function(){return g},this.getActiveMipmapLevel=function(){return v},this.getRenderTarget=function(){return y},this.setRenderTarget=function(t,e=0,n=0){y=t,g=e,v=n,t&&void 0===q.get(t).__webglFramebuffer&&X.setupRenderTarget(t);let 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s=e.image.width,r=e.image.height,o=ct.convert(n.format),a=ct.convert(n.type);X.setTexture2D(n,0),ut.pixelStorei(37440,n.flipY),ut.pixelStorei(37441,n.premultiplyAlpha),ut.pixelStorei(3317,n.unpackAlignment),e.isDataTexture?ut.texSubImage2D(3553,i,t.x,t.y,s,r,o,a,e.image.data):e.isCompressedTexture?ut.compressedTexSubImage2D(3553,i,t.x,t.y,e.mipmaps[0].width,e.mipmaps[0].height,o,e.mipmaps[0].data):ut.texSubImage2D(3553,i,t.x,t.y,o,a,e.image),0===i&&n.generateMipmaps&&ut.generateMipmap(3553),j.unbindTexture()},this.copyTextureToTexture3D=function(t,e,n,i,s=0){if(m.isWebGL1Renderer)return void console.warn(\\\\\\\"THREE.WebGLRenderer.copyTextureToTexture3D: can only be used with WebGL2.\\\\\\\");const r=t.max.x-t.min.x+1,o=t.max.y-t.min.y+1,a=t.max.z-t.min.z+1,l=ct.convert(i.format),c=ct.convert(i.type);let h;if(i.isDataTexture3D)X.setTexture3D(i,0),h=32879;else{if(!i.isDataTexture2DArray)return void console.warn(\\\\\\\"THREE.WebGLRenderer.copyTextureToTexture3D: only supports 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srcTexture.\\\\\\\"),ut.compressedTexSubImage3D(h,s,e.x,e.y,e.z,r,o,a,l,g.data)):ut.texSubImage3D(h,s,e.x,e.y,e.z,r,o,a,l,c,g),ut.pixelStorei(3314,u),ut.pixelStorei(32878,d),ut.pixelStorei(3316,p),ut.pixelStorei(3315,_),ut.pixelStorei(32877,f),0===s&&i.generateMipmaps&&ut.generateMipmap(h),j.unbindTexture()},this.initTexture=function(t){X.setTexture2D(t,0),j.unbindTexture()},this.resetState=function(){g=0,v=0,y=null,j.reset(),ht.reset()},\\\\\\\"undefined\\\\\\\"!=typeof __THREE_DEVTOOLS__&&__THREE_DEVTOOLS__.dispatchEvent(new CustomEvent(\\\\\\\"observe\\\\\\\",{detail:this}))}(class extends FE{}).prototype.isWebGL1Renderer=!0;class DE{constructor(t,e=25e-5){this.name=\\\\\\\"\\\\\\\",this.color=new $w(t),this.density=e}clone(){return new DE(this.color,this.density)}toJSON(){return{type:\\\\\\\"FogExp2\\\\\\\",color:this.color.getHex(),density:this.density}}}DE.prototype.isFogExp2=!0;class BE{constructor(t,e=1,n=1e3){this.name=\\\\\\\"\\\\\\\",this.color=new $w(t),this.near=e,this.far=n}clone(){return new BE(this.color,this.near,this.far)}toJSON(){return{type:\\\\\\\"Fog\\\\\\\",color:this.color.getHex(),near:this.near,far:this.far}}}BE.prototype.isFog=!0;class zE extends Nw{constructor(){super(),this.type=\\\\\\\"Scene\\\\\\\",this.background=null,this.environment=null,this.fog=null,this.overrideMaterial=null,this.autoUpdate=!0,\\\\\\\"undefined\\\\\\\"!=typeof __THREE_DEVTOOLS__&&__THREE_DEVTOOLS__.dispatchEvent(new CustomEvent(\\\\\\\"observe\\\\\\\",{detail:this}))}copy(t,e){return super.copy(t,e),null!==t.background&&(this.background=t.background.clone()),null!==t.environment&&(this.environment=t.environment.clone()),null!==t.fog&&(this.fog=t.fog.clone()),null!==t.overrideMaterial&&(this.overrideMaterial=t.overrideMaterial.clone()),this.autoUpdate=t.autoUpdate,this.matrixAutoUpdate=t.matrixAutoUpdate,this}toJSON(t){const e=super.toJSON(t);return null!==this.fog&&(e.object.fog=this.fog.toJSON()),e}}zE.prototype.isScene=!0;class kE{constructor(t,e){this.array=t,this.stride=e,this.count=void 0!==t?t.length/e:0,this.usage=Zx,this.updateRange={offset:0,count:-1},this.version=0,this.uuid=ob()}onUploadCallback(){}set needsUpdate(t){!0===t&&this.version++}setUsage(t){return this.usage=t,this}copy(t){return this.array=new t.array.constructor(t.array),this.count=t.count,this.stride=t.stride,this.usage=t.usage,this}copyAt(t,e,n){t*=this.stride,n*=e.stride;for(let i=0,s=this.stride;it.far||e.push({distance:a,point:jE.clone(),uv:Uw.getUV(jE,JE,ZE,KE,QE,tS,eS,new _b),face:null,object:this})}copy(t){return super.copy(t),void 0!==t.center&&this.center.copy(t.center),this.material=t.material,this}}function iS(t,e,n,i,s,r){XE.subVectors(t,n).addScalar(.5).multiply(i),void 0!==s?(YE.x=r*XE.x-s*XE.y,YE.y=s*XE.x+r*XE.y):YE.copy(XE),t.copy(e),t.x+=YE.x,t.y+=YE.y,t.applyMatrix4($E)}nS.prototype.isSprite=!0;const sS=new Sb,rS=new Tb,oS=new Tb,aS=new Sb,lS=new sw;class cS extends CT{constructor(t,e){super(t,e),this.type=\\\\\\\"SkinnedMesh\\\\\\\",this.bindMode=\\\\\\\"attached\\\\\\\",this.bindMatrix=new sw,this.bindMatrixInverse=new sw}copy(t){return super.copy(t),this.bindMode=t.bindMode,this.bindMatrix.copy(t.bindMatrix),this.bindMatrixInverse.copy(t.bindMatrixInverse),this.skeleton=t.skeleton,this}bind(t,e){this.skeleton=t,void 0===e&&(this.updateMatrixWorld(!0),this.skeleton.calculateInverses(),e=this.matrixWorld),this.bindMatrix.copy(e),this.bindMatrixInverse.copy(e).invert()}pose(){this.skeleton.pose()}normalizeSkinWeights(){const t=new Tb,e=this.geometry.attributes.skinWeight;for(let n=0,i=e.count;na)continue;u.applyMatrix4(this.matrixWorld);const d=t.ray.origin.distanceTo(u);dt.far||e.push({distance:d,point:h.clone().applyMatrix4(this.matrixWorld),index:n,face:null,faceIndex:null,object:this})}}else{for(let n=Math.max(0,r.start),i=Math.min(s.count,r.start+r.count)-1;na)continue;u.applyMatrix4(this.matrixWorld);const i=t.ray.origin.distanceTo(u);it.far||e.push({distance:i,point:h.clone().applyMatrix4(this.matrixWorld),index:n,face:null,faceIndex:null,object:this})}}}else n.isGeometry&&console.error(\\\\\\\"THREE.Line.raycast() no longer supports THREE.Geometry. Use THREE.BufferGeometry instead.\\\\\\\")}updateMorphTargets(){const t=this.geometry;if(t.isBufferGeometry){const e=t.morphAttributes,n=Object.keys(e);if(n.length>0){const t=e[n[0]];if(void 0!==t){this.morphTargetInfluences=[],this.morphTargetDictionary={};for(let e=0,n=t.length;e0&&console.error(\\\\\\\"THREE.Line.updateMorphTargets() does not support THREE.Geometry. Use THREE.BufferGeometry instead.\\\\\\\")}}}AS.prototype.isLine=!0;const MS=new Sb,ES=new Sb;class SS extends AS{constructor(t,e){super(t,e),this.type=\\\\\\\"LineSegments\\\\\\\"}computeLineDistances(){const t=this.geometry;if(t.isBufferGeometry)if(null===t.index){const e=t.attributes.position,n=[];for(let t=0,i=e.count;t0){const t=e[n[0]];if(void 0!==t){this.morphTargetInfluences=[],this.morphTargetDictionary={};for(let e=0,n=t.length;e0&&console.error(\\\\\\\"THREE.Points.updateMorphTargets() does not support THREE.Geometry. Use THREE.BufferGeometry instead.\\\\\\\")}}}function FS(t,e,n,i,s,r,o){const a=OS.distanceSqToPoint(t);if(as.far)return;r.push({distance:l,distanceToRay:Math.sqrt(a),point:n,index:e,face:null,object:o})}}IS.prototype.isPoints=!0;(class extends bb{constructor(t,e,n,i,s,r,o,a,l){super(t,e,n,i,s,r,o,a,l),this.format=void 0!==o?o:Fx,this.minFilter=void 0!==r?r:Ex,this.magFilter=void 0!==s?s:Ex,this.generateMipmaps=!1;const c=this;\\\\\\\"requestVideoFrameCallback\\\\\\\"in t&&t.requestVideoFrameCallback((function e(){c.needsUpdate=!0,t.requestVideoFrameCallback(e)}))}clone(){return new this.constructor(this.image).copy(this)}update(){const t=this.image;!1===\\\\\\\"requestVideoFrameCallback\\\\\\\"in t&&t.readyState>=t.HAVE_CURRENT_DATA&&(this.needsUpdate=!0)}}).prototype.isVideoTexture=!0;class DS extends bb{constructor(t,e,n,i,s,r,o,a,l,c,h,u){super(null,r,o,a,l,c,i,s,h,u),this.image={width:e,height:n},this.mipmaps=t,this.flipY=!1,this.generateMipmaps=!1}}DS.prototype.isCompressedTexture=!0;(class extends bb{constructor(t,e,n,i,s,r,o,a,l){super(t,e,n,i,s,r,o,a,l),this.needsUpdate=!0}}).prototype.isCanvasTexture=!0;(class extends bb{constructor(t,e,n,i,s,r,o,a,l,c){if((c=void 0!==c?c:Bx)!==Bx&&c!==zx)throw new Error(\\\\\\\"DepthTexture format must be either THREE.DepthFormat or THREE.DepthStencilFormat\\\\\\\");void 0===n&&c===Bx&&(n=Lx),void 0===n&&c===zx&&(n=Ix),super(null,i,s,r,o,a,c,n,l),this.image={width:t,height:e},this.magFilter=void 0!==o?o:Tx,this.minFilter=void 0!==a?a:Tx,this.flipY=!1,this.generateMipmaps=!1}}).prototype.isDepthTexture=!0;new Sb,new Sb,new Sb,new Uw;class BS{constructor(){this.type=\\\\\\\"Curve\\\\\\\",this.arcLengthDivisions=200}getPoint(){return console.warn(\\\\\\\"THREE.Curve: .getPoint() not implemented.\\\\\\\"),null}getPointAt(t,e){const n=this.getUtoTmapping(t);return this.getPoint(n,e)}getPoints(t=5){const e=[];for(let n=0;n<=t;n++)e.push(this.getPoint(n/t));return e}getSpacedPoints(t=5){const e=[];for(let n=0;n<=t;n++)e.push(this.getPointAt(n/t));return e}getLength(){const t=this.getLengths();return t[t.length-1]}getLengths(t=this.arcLengthDivisions){if(this.cacheArcLengths&&this.cacheArcLengths.length===t+1&&!this.needsUpdate)return this.cacheArcLengths;this.needsUpdate=!1;const e=[];let n,i=this.getPoint(0),s=0;e.push(0);for(let r=1;r<=t;r++)n=this.getPoint(r/t),s+=n.distanceTo(i),e.push(s),i=n;return this.cacheArcLengths=e,e}updateArcLengths(){this.needsUpdate=!0,this.getLengths()}getUtoTmapping(t,e){const n=this.getLengths();let i=0;const s=n.length;let r;r=e||t*n[s-1];let o,a=0,l=s-1;for(;a<=l;)if(i=Math.floor(a+(l-a)/2),o=n[i]-r,o<0)a=i+1;else{if(!(o>0)){l=i;break}l=i-1}if(i=l,n[i]===r)return i/(s-1);const c=n[i];return(i+(r-c)/(n[i+1]-c))/(s-1)}getTangent(t,e){const n=1e-4;let i=t-n,s=t+n;i<0&&(i=0),s>1&&(s=1);const r=this.getPoint(i),o=this.getPoint(s),a=e||(r.isVector2?new _b:new Sb);return a.copy(o).sub(r).normalize(),a}getTangentAt(t,e){const n=this.getUtoTmapping(t);return this.getTangent(n,e)}computeFrenetFrames(t,e){const n=new Sb,i=[],s=[],r=[],o=new Sb,a=new sw;for(let e=0;e<=t;e++){const n=e/t;i[e]=this.getTangentAt(n,new Sb)}s[0]=new Sb,r[0]=new Sb;let l=Number.MAX_VALUE;const c=Math.abs(i[0].x),h=Math.abs(i[0].y),u=Math.abs(i[0].z);c<=l&&(l=c,n.set(1,0,0)),h<=l&&(l=h,n.set(0,1,0)),u<=l&&n.set(0,0,1),o.crossVectors(i[0],n).normalize(),s[0].crossVectors(i[0],o),r[0].crossVectors(i[0],s[0]);for(let e=1;e<=t;e++){if(s[e]=s[e-1].clone(),r[e]=r[e-1].clone(),o.crossVectors(i[e-1],i[e]),o.length()>Number.EPSILON){o.normalize();const t=Math.acos(ab(i[e-1].dot(i[e]),-1,1));s[e].applyMatrix4(a.makeRotationAxis(o,t))}r[e].crossVectors(i[e],s[e])}if(!0===e){let e=Math.acos(ab(s[0].dot(s[t]),-1,1));e/=t,i[0].dot(o.crossVectors(s[0],s[t]))>0&&(e=-e);for(let n=1;n<=t;n++)s[n].applyMatrix4(a.makeRotationAxis(i[n],e*n)),r[n].crossVectors(i[n],s[n])}return{tangents:i,normals:s,binormals:r}}clone(){return(new this.constructor).copy(this)}copy(t){return this.arcLengthDivisions=t.arcLengthDivisions,this}toJSON(){const t={metadata:{version:4.5,type:\\\\\\\"Curve\\\\\\\",generator:\\\\\\\"Curve.toJSON\\\\\\\"}};return t.arcLengthDivisions=this.arcLengthDivisions,t.type=this.type,t}fromJSON(t){return this.arcLengthDivisions=t.arcLengthDivisions,this}}class zS extends BS{constructor(t=0,e=0,n=1,i=1,s=0,r=2*Math.PI,o=!1,a=0){super(),this.type=\\\\\\\"EllipseCurve\\\\\\\",this.aX=t,this.aY=e,this.xRadius=n,this.yRadius=i,this.aStartAngle=s,this.aEndAngle=r,this.aClockwise=o,this.aRotation=a}getPoint(t,e){const n=e||new _b,i=2*Math.PI;let s=this.aEndAngle-this.aStartAngle;const r=Math.abs(s)i;)s-=i;s0?0:(Math.floor(Math.abs(l)/s)+1)*s:0===c&&l===s-1&&(l=s-2,c=1),this.closed||l>0?o=i[(l-1)%s]:(GS.subVectors(i[0],i[1]).add(i[0]),o=GS);const 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xC(t.prev,t,t.next)<0?xC(t,e,t.next)>=0&&xC(t,t.prev,e)>=0:xC(t,e,t.prev)<0||xC(t,t.next,e)<0}function EC(t,e){const n=new NC(t.i,t.x,t.y),i=new NC(e.i,e.x,e.y),s=t.next,r=e.prev;return t.next=e,e.prev=t,n.next=s,s.prev=n,i.next=n,n.prev=i,r.next=i,i.prev=r,i}function SC(t,e,n,i){const s=new NC(t,e,n);return i?(s.next=i.next,s.prev=i,i.next.prev=s,i.next=s):(s.prev=s,s.next=s),s}function CC(t){t.next.prev=t.prev,t.prev.next=t.next,t.prevZ&&(t.prevZ.nextZ=t.nextZ),t.nextZ&&(t.nextZ.prevZ=t.prevZ)}function NC(t,e,n){this.i=t,this.x=e,this.y=n,this.prev=null,this.next=null,this.z=null,this.prevZ=null,this.nextZ=null,this.steiner=!1}class LC{static area(t){const e=t.length;let n=0;for(let i=e-1,s=0;s2&&t[e-1].equals(t[0])&&t.pop()}function PC(t,e){for(let n=0;nNumber.EPSILON){const u=Math.sqrt(h),d=Math.sqrt(l*l+c*c),p=e.x-a/u,_=e.y+o/u,m=((n.x-c/d-p)*c-(n.y+l/d-_)*l)/(o*c-a*l);i=p+o*m-t.x,s=_+a*m-t.y;const f=i*i+s*s;if(f<=2)return new _b(i,s);r=Math.sqrt(f/2)}else{let t=!1;o>Number.EPSILON?l>Number.EPSILON&&(t=!0):o<-Number.EPSILON?l<-Number.EPSILON&&(t=!0):Math.sign(a)===Math.sign(c)&&(t=!0),t?(i=-a,s=o,r=Math.sqrt(h)):(i=o,s=a,r=Math.sqrt(h/2))}return new _b(i/r,s/r)}const O=[];for(let t=0,e=E.length,n=e-1,i=t+1;t=0;t--){const e=t/p,n=h*Math.cos(e*Math.PI/2),i=u*Math.sin(e*Math.PI/2)+d;for(let t=0,e=E.length;t=0;){const i=n;let s=n-1;s<0&&(s=t.length-1);for(let t=0,n=a+2*p;t0!=t>0&&this.version++,this._sheen=t}get clearcoat(){return this._clearcoat}set clearcoat(t){this._clearcoat>0!=t>0&&this.version++,this._clearcoat=t}get transmission(){return this._transmission}set transmission(t){this._transmission>0!=t>0&&this.version++,this._transmission=t}copy(t){return super.copy(t),this.defines={STANDARD:\\\\\\\"\\\\\\\",PHYSICAL:\\\\\\\"\\\\\\\"},this.clearcoat=t.clearcoat,this.clearcoatMap=t.clearcoatMap,this.clearcoatRoughness=t.clearcoatRoughness,this.clearcoatRoughnessMap=t.clearcoatRoughnessMap,this.clearcoatNormalMap=t.clearcoatNormalMap,this.clearcoatNormalScale.copy(t.clearcoatNormalScale),this.ior=t.ior,this.sheen=t.sheen,this.sheenTint.copy(t.sheenTint),this.sheenRoughness=t.sheenRoughness,this.transmission=t.transmission,this.transmissionMap=t.transmissionMap,this.thickness=t.thickness,this.thicknessMap=t.thicknessMap,this.attenuationDistance=t.attenuationDistance,this.attenuationTint.copy(t.attenuationTint),this.specularIntensity=t.specularIntensity,this.specularIntensityMap=t.specularIntensityMap,this.specularTint.copy(t.specularTint),this.specularTintMap=t.specularTintMap,this}}zC.prototype.isMeshPhysicalMaterial=!0;class kC extends Vw{constructor(t){super(),this.type=\\\\\\\"MeshPhongMaterial\\\\\\\",this.color=new $w(16777215),this.specular=new $w(1118481),this.shininess=30,this.map=null,this.lightMap=null,this.lightMapIntensity=1,this.aoMap=null,this.aoMapIntensity=1,this.emissive=new $w(0),this.emissiveIntensity=1,this.emissiveMap=null,this.bumpMap=null,this.bumpScale=1,this.normalMap=null,this.normalMapType=0,this.normalScale=new _b(1,1),this.displacementMap=null,this.displacementScale=1,this.displacementBias=0,this.specularMap=null,this.alphaMap=null,this.envMap=null,this.combine=0,this.reflectivity=1,this.refractionRatio=.98,this.wireframe=!1,this.wireframeLinewidth=1,this.wireframeLinecap=\\\\\\\"round\\\\\\\",this.wireframeLinejoin=\\\\\\\"round\\\\\\\",this.flatShading=!1,this.setValues(t)}copy(t){return super.copy(t),this.color.copy(t.color),this.specular.copy(t.specular),this.shininess=t.shininess,this.map=t.map,this.lightMap=t.lightMap,this.lightMapIntensity=t.lightMapIntensity,this.aoMap=t.aoMap,this.aoMapIntensity=t.aoMapIntensity,this.emissive.copy(t.emissive),this.emissiveMap=t.emissiveMap,this.emissiveIntensity=t.emissiveIntensity,this.bumpMap=t.bumpMap,this.bumpScale=t.bumpScale,this.normalMap=t.normalMap,this.normalMapType=t.normalMapType,this.normalScale.copy(t.normalScale),this.displacementMap=t.displacementMap,this.displacementScale=t.displacementScale,this.displacementBias=t.displacementBias,this.specularMap=t.specularMap,this.alphaMap=t.alphaMap,this.envMap=t.envMap,this.combine=t.combine,this.reflectivity=t.reflectivity,this.refractionRatio=t.refractionRatio,this.wireframe=t.wireframe,this.wireframeLinewidth=t.wireframeLinewidth,this.wireframeLinecap=t.wireframeLinecap,this.wireframeLinejoin=t.wireframeLinejoin,this.flatShading=t.flatShading,this}}kC.prototype.isMeshPhongMaterial=!0;class UC extends Vw{constructor(t){super(),this.defines={TOON:\\\\\\\"\\\\\\\"},this.type=\\\\\\\"MeshToonMaterial\\\\\\\",this.color=new $w(16777215),this.map=null,this.gradientMap=null,this.lightMap=null,this.lightMapIntensity=1,this.aoMap=null,this.aoMapIntensity=1,this.emissive=new $w(0),this.emissiveIntensity=1,this.emissiveMap=null,this.bumpMap=null,this.bumpScale=1,this.normalMap=null,this.normalMapType=0,this.normalScale=new _b(1,1),this.displacementMap=null,this.displacementScale=1,this.displacementBias=0,this.alphaMap=null,this.wireframe=!1,this.wireframeLinewidth=1,this.wireframeLinecap=\\\\\\\"round\\\\\\\",this.wireframeLinejoin=\\\\\\\"round\\\\\\\",this.setValues(t)}copy(t){return super.copy(t),this.color.copy(t.color),this.map=t.map,this.gradientMap=t.gradientMap,this.lightMap=t.lightMap,this.lightMapIntensity=t.lightMapIntensity,this.aoMap=t.aoMap,this.aoMapIntensity=t.aoMapIntensity,this.emissive.copy(t.emissive),this.emissiveMap=t.emissiveMap,this.emissiveIntensity=t.emissiveIntensity,this.bumpMap=t.bumpMap,this.bumpScale=t.bumpScale,this.normalMap=t.normalMap,this.normalMapType=t.normalMapType,this.normalScale.copy(t.normalScale),this.displacementMap=t.displacementMap,this.displacementScale=t.displacementScale,this.displacementBias=t.displacementBias,this.alphaMap=t.alphaMap,this.wireframe=t.wireframe,this.wireframeLinewidth=t.wireframeLinewidth,this.wireframeLinecap=t.wireframeLinecap,this.wireframeLinejoin=t.wireframeLinejoin,this}}UC.prototype.isMeshToonMaterial=!0;class GC extends Vw{constructor(t){super(),this.type=\\\\\\\"MeshNormalMaterial\\\\\\\",this.bumpMap=null,this.bumpScale=1,this.normalMap=null,this.normalMapType=0,this.normalScale=new _b(1,1),this.displacementMap=null,this.displacementScale=1,this.displacementBias=0,this.wireframe=!1,this.wireframeLinewidth=1,this.fog=!1,this.flatShading=!1,this.setValues(t)}copy(t){return super.copy(t),this.bumpMap=t.bumpMap,this.bumpScale=t.bumpScale,this.normalMap=t.normalMap,this.normalMapType=t.normalMapType,this.normalScale.copy(t.normalScale),this.displacementMap=t.displacementMap,this.displacementScale=t.displacementScale,this.displacementBias=t.displacementBias,this.wireframe=t.wireframe,this.wireframeLinewidth=t.wireframeLinewidth,this.flatShading=t.flatShading,this}}GC.prototype.isMeshNormalMaterial=!0;class VC extends Vw{constructor(t){super(),this.type=\\\\\\\"MeshLambertMaterial\\\\\\\",this.color=new $w(16777215),this.map=null,this.lightMap=null,this.lightMapIntensity=1,this.aoMap=null,this.aoMapIntensity=1,this.emissive=new $w(0),this.emissiveIntensity=1,this.emissiveMap=null,this.specularMap=null,this.alphaMap=null,this.envMap=null,this.combine=0,this.reflectivity=1,this.refractionRatio=.98,this.wireframe=!1,this.wireframeLinewidth=1,this.wireframeLinecap=\\\\\\\"round\\\\\\\",this.wireframeLinejoin=\\\\\\\"round\\\\\\\",this.setValues(t)}copy(t){return super.copy(t),this.color.copy(t.color),this.map=t.map,this.lightMap=t.lightMap,this.lightMapIntensity=t.lightMapIntensity,this.aoMap=t.aoMap,this.aoMapIntensity=t.aoMapIntensity,this.emissive.copy(t.emissive),this.emissiveMap=t.emissiveMap,this.emissiveIntensity=t.emissiveIntensity,this.specularMap=t.specularMap,this.alphaMap=t.alphaMap,this.envMap=t.envMap,this.combine=t.combine,this.reflectivity=t.reflectivity,this.refractionRatio=t.refractionRatio,this.wireframe=t.wireframe,this.wireframeLinewidth=t.wireframeLinewidth,this.wireframeLinecap=t.wireframeLinecap,this.wireframeLinejoin=t.wireframeLinejoin,this}}VC.prototype.isMeshLambertMaterial=!0;class HC extends Vw{constructor(t){super(),this.defines={MATCAP:\\\\\\\"\\\\\\\"},this.type=\\\\\\\"MeshMatcapMaterial\\\\\\\",this.color=new $w(16777215),this.matcap=null,this.map=null,this.bumpMap=null,this.bumpScale=1,this.normalMap=null,this.normalMapType=0,this.normalScale=new _b(1,1),this.displacementMap=null,this.displacementScale=1,this.displacementBias=0,this.alphaMap=null,this.flatShading=!1,this.setValues(t)}copy(t){return super.copy(t),this.defines={MATCAP:\\\\\\\"\\\\\\\"},this.color.copy(t.color),this.matcap=t.matcap,this.map=t.map,this.bumpMap=t.bumpMap,this.bumpScale=t.bumpScale,this.normalMap=t.normalMap,this.normalMapType=t.normalMapType,this.normalScale.copy(t.normalScale),this.displacementMap=t.displacementMap,this.displacementScale=t.displacementScale,this.displacementBias=t.displacementBias,this.alphaMap=t.alphaMap,this.flatShading=t.flatShading,this}}HC.prototype.isMeshMatcapMaterial=!0;class jC extends vS{constructor(t){super(),this.type=\\\\\\\"LineDashedMaterial\\\\\\\",this.scale=1,this.dashSize=3,this.gapSize=1,this.setValues(t)}copy(t){return super.copy(t),this.scale=t.scale,this.dashSize=t.dashSize,this.gapSize=t.gapSize,this}}jC.prototype.isLineDashedMaterial=!0;const WC={arraySlice:function(t,e,n){return WC.isTypedArray(t)?new t.constructor(t.subarray(e,void 0!==n?n:t.length)):t.slice(e,n)},convertArray:function(t,e,n){return!t||!n&&t.constructor===e?t:\\\\\\\"number\\\\\\\"==typeof e.BYTES_PER_ELEMENT?new e(t):Array.prototype.slice.call(t)},isTypedArray:function(t){return ArrayBuffer.isView(t)&&!(t instanceof DataView)},getKeyframeOrder:function(t){const e=t.length,n=new Array(e);for(let t=0;t!==e;++t)n[t]=t;return n.sort((function(e,n){return t[e]-t[n]})),n},sortedArray:function(t,e,n){const i=t.length,s=new t.constructor(i);for(let r=0,o=0;o!==i;++r){const i=n[r]*e;for(let n=0;n!==e;++n)s[o++]=t[i+n]}return s},flattenJSON:function(t,e,n,i){let s=1,r=t[0];for(;void 0!==r&&void 0===r[i];)r=t[s++];if(void 0===r)return;let o=r[i];if(void 0!==o)if(Array.isArray(o))do{o=r[i],void 0!==o&&(e.push(r.time),n.push.apply(n,o)),r=t[s++]}while(void 0!==r);else if(void 0!==o.toArray)do{o=r[i],void 0!==o&&(e.push(r.time),o.toArray(n,n.length)),r=t[s++]}while(void 0!==r);else do{o=r[i],void 0!==o&&(e.push(r.time),n.push(o)),r=t[s++]}while(void 0!==r)},subclip:function(t,e,n,i,s=30){const r=t.clone();r.name=e;const o=[];for(let t=0;t=i)){l.push(e.times[t]);for(let n=0;nr.tracks[t].times[0]&&(a=r.tracks[t].times[0]);for(let t=0;t=i.times[u]){const t=u*l+a,e=t+l-a;d=WC.arraySlice(i.values,t,e)}else{const t=i.createInterpolant(),e=a,n=l-a;t.evaluate(r),d=WC.arraySlice(t.resultBuffer,e,n)}if(\\\\\\\"quaternion\\\\\\\"===s){(new Eb).fromArray(d).normalize().conjugate().toArray(d)}const p=o.times.length;for(let t=0;t=s)break t;{const o=e[1];t=s)break e}r=n,n=0}}for(;n>>1;te;)--r;if(++r,0!==s||r!==i){s>=r&&(r=Math.max(r,1),s=r-1);const t=this.getValueSize();this.times=WC.arraySlice(n,s,r),this.values=WC.arraySlice(this.values,s*t,r*t)}return this}validate(){let t=!0;const e=this.getValueSize();e-Math.floor(e)!=0&&(console.error(\\\\\\\"THREE.KeyframeTrack: Invalid value size in track.\\\\\\\",this),t=!1);const n=this.times,i=this.values,s=n.length;0===s&&(console.error(\\\\\\\"THREE.KeyframeTrack: Track is empty.\\\\\\\",this),t=!1);let r=null;for(let e=0;e!==s;e++){const i=n[e];if(\\\\\\\"number\\\\\\\"==typeof i&&isNaN(i)){console.error(\\\\\\\"THREE.KeyframeTrack: Time is not a valid number.\\\\\\\",this,e,i),t=!1;break}if(null!==r&&r>i){console.error(\\\\\\\"THREE.KeyframeTrack: Out of order keys.\\\\\\\",this,e,i,r),t=!1;break}r=i}if(void 0!==i&&WC.isTypedArray(i))for(let e=0,n=i.length;e!==n;++e){const n=i[e];if(isNaN(n)){console.error(\\\\\\\"THREE.KeyframeTrack: Value is not a valid number.\\\\\\\",this,e,n),t=!1;break}}return t}optimize(){const t=WC.arraySlice(this.times),e=WC.arraySlice(this.values),n=this.getValueSize(),i=this.getInterpolation()===Gx,s=t.length-1;let r=1;for(let o=1;o0){t[r]=t[s];for(let t=s*n,i=r*n,o=0;o!==n;++o)e[i+o]=e[t+o];++r}return r!==t.length?(this.times=WC.arraySlice(t,0,r),this.values=WC.arraySlice(e,0,r*n)):(this.times=t,this.values=e),this}clone(){const t=WC.arraySlice(this.times,0),e=WC.arraySlice(this.values,0),n=new(0,this.constructor)(this.name,t,e);return n.createInterpolant=this.createInterpolant,n}}JC.prototype.TimeBufferType=Float32Array,JC.prototype.ValueBufferType=Float32Array,JC.prototype.DefaultInterpolation=Ux;class ZC extends JC{}ZC.prototype.ValueTypeName=\\\\\\\"bool\\\\\\\",ZC.prototype.ValueBufferType=Array,ZC.prototype.DefaultInterpolation=kx,ZC.prototype.InterpolantFactoryMethodLinear=void 0,ZC.prototype.InterpolantFactoryMethodSmooth=void 0;class KC extends JC{}KC.prototype.ValueTypeName=\\\\\\\"color\\\\\\\";class QC extends JC{}QC.prototype.ValueTypeName=\\\\\\\"number\\\\\\\";class tN extends qC{constructor(t,e,n,i){super(t,e,n,i)}interpolate_(t,e,n,i){const s=this.resultBuffer,r=this.sampleValues,o=this.valueSize,a=(n-e)/(i-e);let l=t*o;for(let t=l+o;l!==t;l+=4)Eb.slerpFlat(s,0,r,l-o,r,l,a);return s}}class eN extends JC{InterpolantFactoryMethodLinear(t){return new tN(this.times,this.values,this.getValueSize(),t)}}eN.prototype.ValueTypeName=\\\\\\\"quaternion\\\\\\\",eN.prototype.DefaultInterpolation=Ux,eN.prototype.InterpolantFactoryMethodSmooth=void 0;class nN extends JC{}nN.prototype.ValueTypeName=\\\\\\\"string\\\\\\\",nN.prototype.ValueBufferType=Array,nN.prototype.DefaultInterpolation=kx,nN.prototype.InterpolantFactoryMethodLinear=void 0,nN.prototype.InterpolantFactoryMethodSmooth=void 0;class iN extends JC{}iN.prototype.ValueTypeName=\\\\\\\"vector\\\\\\\";class sN{constructor(t,e=-1,n,i=2500){this.name=t,this.tracks=n,this.duration=e,this.blendMode=i,this.uuid=ob(),this.duration<0&&this.resetDuration()}static parse(t){const e=[],n=t.tracks,i=1/(t.fps||1);for(let t=0,s=n.length;t!==s;++t)e.push(rN(n[t]).scale(i));const s=new this(t.name,t.duration,e,t.blendMode);return s.uuid=t.uuid,s}static toJSON(t){const e=[],n=t.tracks,i={name:t.name,duration:t.duration,tracks:e,uuid:t.uuid,blendMode:t.blendMode};for(let t=0,i=n.length;t!==i;++t)e.push(JC.toJSON(n[t]));return i}static CreateFromMorphTargetSequence(t,e,n,i){const s=e.length,r=[];for(let t=0;t1){const t=r[1];let e=i[t];e||(i[t]=e=[]),e.push(n)}}const r=[];for(const t in i)r.push(this.CreateFromMorphTargetSequence(t,i[t],e,n));return r}static parseAnimation(t,e){if(!t)return console.error(\\\\\\\"THREE.AnimationClip: No animation in JSONLoader data.\\\\\\\"),null;const n=function(t,e,n,i,s){if(0!==n.length){const r=[],o=[];WC.flattenJSON(n,r,o,i),0!==r.length&&s.push(new t(e,r,o))}},i=[],s=t.name||\\\\\\\"default\\\\\\\",r=t.fps||30,o=t.blendMode;let a=t.length||-1;const l=t.hierarchy||[];for(let t=0;t0){this.source.connect(this.filters[0]);for(let t=1,e=this.filters.length;t0){this.source.disconnect(this.filters[0]);for(let t=1,e=this.filters.length;t0&&this._mixBufferRegionAdditive(n,i,this._addIndex*e,1,e);for(let t=e,s=e+e;t!==s;++t)if(n[t]!==n[t+e]){o.setValue(n,i);break}}saveOriginalState(){const t=this.binding,e=this.buffer,n=this.valueSize,i=n*this._origIndex;t.getValue(e,i);for(let t=n,s=i;t!==s;++t)e[t]=e[i+t%n];this._setIdentity(),this.cumulativeWeight=0,this.cumulativeWeightAdditive=0}restoreOriginalState(){const t=3*this.valueSize;this.binding.setValue(this.buffer,t)}_setAdditiveIdentityNumeric(){const t=this._addIndex*this.valueSize,e=t+this.valueSize;for(let n=t;n=.5)for(let i=0;i!==s;++i)t[e+i]=t[n+i]}_slerp(t,e,n,i){Eb.slerpFlat(t,e,t,e,t,n,i)}_slerpAdditive(t,e,n,i,s){const r=this._workIndex*s;Eb.multiplyQuaternionsFlat(t,r,t,e,t,n),Eb.slerpFlat(t,e,t,e,t,r,i)}_lerp(t,e,n,i,s){const r=1-i;for(let o=0;o!==s;++o){const s=e+o;t[s]=t[s]*r+t[n+o]*i}}_lerpAdditive(t,e,n,i,s){for(let r=0;r!==s;++r){const s=e+r;t[s]=t[s]+t[n+r]*i}}}const GN=\\\\\\\"\\\\\\\\[\\\\\\\\]\\\\\\\\.:\\\\\\\\/\\\\\\\",VN=new RegExp(\\\\\\\"[\\\\\\\\[\\\\\\\\]\\\\\\\\.:\\\\\\\\/]\\\\\\\",\\\\\\\"g\\\\\\\"),HN=\\\\\\\"[^\\\\\\\\[\\\\\\\\]\\\\\\\\.:\\\\\\\\/]\\\\\\\",jN=\\\\\\\"[^\\\\\\\"+GN.replace(\\\\\\\"\\\\\\\\.\\\\\\\",\\\\\\\"\\\\\\\")+\\\\\\\"]\\\\\\\",WN=/((?:WC+[\\\\/:])*)/.source.replace(\\\\\\\"WC\\\\\\\",HN),qN=/(WCOD+)?/.source.replace(\\\\\\\"WCOD\\\\\\\",jN),XN=/(?:\\\\.(WC+)(?:\\\\[(.+)\\\\])?)?/.source.replace(\\\\\\\"WC\\\\\\\",HN),YN=/\\\\.(WC+)(?:\\\\[(.+)\\\\])?/.source.replace(\\\\\\\"WC\\\\\\\",HN),$N=new RegExp(\\\\\\\"^\\\\\\\"+WN+qN+XN+YN+\\\\\\\"$\\\\\\\"),JN=[\\\\\\\"material\\\\\\\",\\\\\\\"materials\\\\\\\",\\\\\\\"bones\\\\\\\"];class ZN{constructor(t,e,n){this.path=e,this.parsedPath=n||ZN.parseTrackName(e),this.node=ZN.findNode(t,this.parsedPath.nodeName)||t,this.rootNode=t,this.getValue=this._getValue_unbound,this.setValue=this._setValue_unbound}static create(t,e,n){return t&&t.isAnimationObjectGroup?new ZN.Composite(t,e,n):new ZN(t,e,n)}static sanitizeNodeName(t){return t.replace(/\\\\s/g,\\\\\\\"_\\\\\\\").replace(VN,\\\\\\\"\\\\\\\")}static parseTrackName(t){const e=$N.exec(t);if(!e)throw new Error(\\\\\\\"PropertyBinding: Cannot parse trackName: \\\\\\\"+t);const n={nodeName:e[2],objectName:e[3],objectIndex:e[4],propertyName:e[5],propertyIndex:e[6]},i=n.nodeName&&n.nodeName.lastIndexOf(\\\\\\\".\\\\\\\");if(void 0!==i&&-1!==i){const t=n.nodeName.substring(i+1);-1!==JN.indexOf(t)&&(n.nodeName=n.nodeName.substring(0,i),n.objectName=t)}if(null===n.propertyName||0===n.propertyName.length)throw new Error(\\\\\\\"PropertyBinding: can not parse propertyName from trackName: \\\\\\\"+t);return n}static findNode(t,e){if(!e||\\\\\\\"\\\\\\\"===e||\\\\\\\".\\\\\\\"===e||-1===e||e===t.name||e===t.uuid)return t;if(t.skeleton){const n=t.skeleton.getBoneByName(e);if(void 0!==n)return n}if(t.children){const n=function(t){for(let i=0;i0){const t=this._interpolants,e=this._propertyBindings;switch(this.blendMode){case 2501:for(let n=0,i=t.length;n!==i;++n)t[n].evaluate(r),e[n].accumulateAdditive(o);break;case Wx:default:for(let n=0,s=t.length;n!==s;++n)t[n].evaluate(r),e[n].accumulate(i,o)}}}_updateWeight(t){let e=0;if(this.enabled){e=this.weight;const n=this._weightInterpolant;if(null!==n){const i=n.evaluate(t)[0];e*=i,t>n.parameterPositions[1]&&(this.stopFading(),0===i&&(this.enabled=!1))}}return this._effectiveWeight=e,e}_updateTimeScale(t){let e=0;if(!this.paused){e=this.timeScale;const n=this._timeScaleInterpolant;if(null!==n){e*=n.evaluate(t)[0],t>n.parameterPositions[1]&&(this.stopWarping(),0===e?this.paused=!0:this.timeScale=e)}}return this._effectiveTimeScale=e,e}_updateTime(t){const e=this._clip.duration,n=this.loop;let i=this.time+t,s=this._loopCount;const r=2202===n;if(0===t)return-1===s?i:r&&1==(1&s)?e-i:i;if(2200===n){-1===s&&(this._loopCount=0,this._setEndings(!0,!0,!1));t:{if(i>=e)i=e;else{if(!(i<0)){this.time=i;break t}i=0}this.clampWhenFinished?this.paused=!0:this.enabled=!1,this.time=i,this._mixer.dispatchEvent({type:\\\\\\\"finished\\\\\\\",action:this,direction:t<0?-1:1})}}else{if(-1===s&&(t>=0?(s=0,this._setEndings(!0,0===this.repetitions,r)):this._setEndings(0===this.repetitions,!0,r)),i>=e||i<0){const n=Math.floor(i/e);i-=e*n,s+=Math.abs(n);const o=this.repetitions-s;if(o<=0)this.clampWhenFinished?this.paused=!0:this.enabled=!1,i=t>0?e:0,this.time=i,this._mixer.dispatchEvent({type:\\\\\\\"finished\\\\\\\",action:this,direction:t>0?1:-1});else{if(1===o){const e=t<0;this._setEndings(e,!e,r)}else this._setEndings(!1,!1,r);this._loopCount=s,this.time=i,this._mixer.dispatchEvent({type:\\\\\\\"loop\\\\\\\",action:this,loopDelta:n})}}else this.time=i;if(r&&1==(1&s))return e-i}return i}_setEndings(t,e,n){const i=this._interpolantSettings;n?(i.endingStart=Hx,i.endingEnd=Hx):(i.endingStart=t?this.zeroSlopeAtStart?Hx:Vx:jx,i.endingEnd=e?this.zeroSlopeAtEnd?Hx:Vx:jx)}_scheduleFading(t,e,n){const i=this._mixer,s=i.time;let r=this._weightInterpolant;null===r&&(r=i._lendControlInterpolant(),this._weightInterpolant=r);const o=r.parameterPositions,a=r.sampleValues;return o[0]=s,a[0]=e,o[1]=s+t,a[1]=n,this}}(class extends tb{constructor(t){super(),this._root=t,this._initMemoryManager(),this._accuIndex=0,this.time=0,this.timeScale=1}_bindAction(t,e){const n=t._localRoot||this._root,i=t._clip.tracks,s=i.length,r=t._propertyBindings,o=t._interpolants,a=n.uuid,l=this._bindingsByRootAndName;let c=l[a];void 0===c&&(c={},l[a]=c);for(let t=0;t!==s;++t){const s=i[t],l=s.name;let h=c[l];if(void 0!==h)r[t]=h;else{if(h=r[t],void 0!==h){null===h._cacheIndex&&(++h.referenceCount,this._addInactiveBinding(h,a,l));continue}const i=e&&e._propertyBindings[t].binding.parsedPath;h=new UN(ZN.create(n,l,i),s.ValueTypeName,s.getValueSize()),++h.referenceCount,this._addInactiveBinding(h,a,l),r[t]=h}o[t].resultBuffer=h.buffer}}_activateAction(t){if(!this._isActiveAction(t)){if(null===t._cacheIndex){const e=(t._localRoot||this._root).uuid,n=t._clip.uuid,i=this._actionsByClip[n];this._bindAction(t,i&&i.knownActions[0]),this._addInactiveAction(t,n,e)}const e=t._propertyBindings;for(let t=0,n=e.length;t!==n;++t){const n=e[t];0==n.useCount++&&(this._lendBinding(n),n.saveOriginalState())}this._lendAction(t)}}_deactivateAction(t){if(this._isActiveAction(t)){const e=t._propertyBindings;for(let t=0,n=e.length;t!==n;++t){const n=e[t];0==--n.useCount&&(n.restoreOriginalState(),this._takeBackBinding(n))}this._takeBackAction(t)}}_initMemoryManager(){this._actions=[],this._nActiveActions=0,this._actionsByClip={},this._bindings=[],this._nActiveBindings=0,this._bindingsByRootAndName={},this._controlInterpolants=[],this._nActiveControlInterpolants=0;const t=this;this.stats={actions:{get total(){return t._actions.length},get inUse(){return t._nActiveActions}},bindings:{get total(){return t._bindings.length},get inUse(){return t._nActiveBindings}},controlInterpolants:{get total(){return t._controlInterpolants.length},get inUse(){return t._nActiveControlInterpolants}}}}_isActiveAction(t){const e=t._cacheIndex;return null!==e&&e=0;--e)t[e].stop();return this}update(t){t*=this.timeScale;const e=this._actions,n=this._nActiveActions,i=this.time+=t,s=Math.sign(t),r=this._accuIndex^=1;for(let o=0;o!==n;++o){e[o]._update(i,t,s,r)}const o=this._bindings,a=this._nActiveBindings;for(let t=0;t!==a;++t)o[t].apply(r);return this}setTime(t){this.time=0;for(let t=0;tthis.max.x||t.ythis.max.y)}containsBox(t){return this.min.x<=t.min.x&&t.max.x<=this.max.x&&this.min.y<=t.min.y&&t.max.y<=this.max.y}getParameter(t,e){return e.set((t.x-this.min.x)/(this.max.x-this.min.x),(t.y-this.min.y)/(this.max.y-this.min.y))}intersectsBox(t){return!(t.max.xthis.max.x||t.max.ythis.max.y)}clampPoint(t,e){return e.copy(t).clamp(this.min,this.max)}distanceToPoint(t){return tL.copy(t).clamp(this.min,this.max).sub(t).length()}intersect(t){return this.min.max(t.min),this.max.min(t.max),this}union(t){return this.min.min(t.min),this.max.max(t.max),this}translate(t){return this.min.add(t),this.max.add(t),this}equals(t){return t.min.equals(this.min)&&t.max.equals(this.max)}}eL.prototype.isBox2=!0;const nL=new Sb,iL=new Sb;class sL{constructor(t=new Sb,e=new Sb){this.start=t,this.end=e}set(t,e){return this.start.copy(t),this.end.copy(e),this}copy(t){return this.start.copy(t.start),this.end.copy(t.end),this}getCenter(t){return t.addVectors(this.start,this.end).multiplyScalar(.5)}delta(t){return t.subVectors(this.end,this.start)}distanceSq(){return this.start.distanceToSquared(this.end)}distance(){return this.start.distanceTo(this.end)}at(t,e){return this.delta(e).multiplyScalar(t).add(this.start)}closestPointToPointParameter(t,e){nL.subVectors(t,this.start),iL.subVectors(this.end,this.start);const n=iL.dot(iL);let i=iL.dot(nL)/n;return e&&(i=ab(i,0,1)),i}closestPointToPoint(t,e,n){const i=this.closestPointToPointParameter(t,e);return this.delta(n).multiplyScalar(i).add(this.start)}applyMatrix4(t){return this.start.applyMatrix4(t),this.end.applyMatrix4(t),this}equals(t){return t.start.equals(this.start)&&t.end.equals(this.end)}clone(){return(new this.constructor).copy(this)}}(class extends Nw{constructor(t){super(),this.material=t,this.render=function(){},this.hasPositions=!1,this.hasNormals=!1,this.hasColors=!1,this.hasUvs=!1,this.positionArray=null,this.normalArray=null,this.colorArray=null,this.uvArray=null,this.count=0}}).prototype.isImmediateRenderObject=!0;const rL=new Sb,oL=new sw,aL=new sw;function lL(t){const e=[];t&&t.isBone&&e.push(t);for(let n=0;n8&&t<16&&e[n].split(t+1),0!==i&&this.subTrees.push(e[n])}return this}build(){return this.calcBox(),this.split(0),this}getRayTriangles(t,e){for(let n=0;n0)for(let t=0;t0&&i>0||n<-t.radius&&i<-t.radius)return!1;const s=Math.abs(n/(Math.abs(n)+Math.abs(i))),r=_L.copy(t.start).lerp(t.end,s);if(e.containsPoint(r))return{normal:fL.normal.clone(),point:r.clone(),depth:Math.abs(Math.min(n,i))};const o=t.radius*t.radius,a=gL.set(t.start,t.end),l=[[e.a,e.b],[e.b,e.c],[e.c,e.a]];for(let e=0;e0)for(let t=0;t0)for(let t=0;ta&&(i=o.clone().add(t.origin),s=a,n=e[r])}}return s<1e100&&{distance:s,triangle:n,position:i}}fromGraphNode(t){return t.updateWorldMatrix(!0,!0),t.traverse((t=>{if(!0===t.isMesh){let e,n=!1;null!==t.geometry.index?(n=!0,e=t.geometry.toNonIndexed()):e=t.geometry;const i=e.getAttribute(\\\\\\\"position\\\\\\\");for(let e=0;e{if(!e){const n=t;n.geometry&&(e=n)}})),e?this._playerCollisionController=new wL(e):console.error(\\\\\\\"no geo found in\\\\\\\",t)}else this._playerCollisionController=void 0}setCollisionCapsule(t){var e;null===(e=this._playerCollisionController)||void 0===e||e.setCapsule(t)}setJumpParams(t){}setGravity(t){}setPlayerMass(t){}}const AL={rotateSpeed:1,rotationRange:{min:.25*-Math.PI,max:.25*Math.PI}},ML={type:\\\\\\\"change\\\\\\\"},EL=new p.a,SL=new uy;class CL extends TL{constructor(t,e,n){super(),this._camera=t,this.domElement=e,this.player=n,this.translationData={direction:new p.a},this.rotationData={direction:{x:0,y:0}},this._boundMethods={onRotateStart:this._onRotateStart.bind(this),onRotateMove:this._onRotateMove.bind(this),onRotateEnd:this._onRotateEnd.bind(this),onTranslateStart:this._onTranslateStart.bind(this),onTranslateMove:this._onTranslateMove.bind(this),onTranslateEnd:this._onTranslateEnd.bind(this),onJump:this._onJump.bind(this),onRunToggle:this._onRunToggle.bind(this)},this._startCameraRotation=new ny.a,this._rotationSpeed=AL.rotateSpeed,this._rotationRange={min:AL.rotationRange.min,max:AL.rotationRange.max},this._azimuthalAngle=0,this.vLeft=new p.a,this.vRight=new p.a,this.vTop=new p.a,this.vBottom=new p.a,this.angleY=0,this.angleX=0,this._rotationStartPosition=new d.a,this._rotationMovePosition=new d.a,this._rotationDelta=new d.a,this._startCameraPosition=new p.a,this._translationStartPosition=new d.a,this._translationMovePosition=new d.a,this._translationDelta=new d.a,this._camera.rotation.order=\\\\\\\"ZYX\\\\\\\",this._translateDomElement=this._createTranslateDomElement(),this._translateDomElementRect=this._translateDomElement.getBoundingClientRect(),this._runDomElement=this._createRunDomElement(),this._jumpDomElement=this._createJumpDomElement(),this._addElements(),this._addEvents()}dispose(){this._removeEvents(),this._removeElements(),this.updateElements()}_createTranslateDomElement(){const t=this.domElement.getBoundingClientRect(),e=Math.min(t.width,t.height),n=Math.round(.4*e),i=Math.round(.1*e),s=document.createElement(\\\\\\\"div\\\\\\\");return s.id=\\\\\\\"MobileJoystickControls-translate\\\\\\\",s.style.width=`${n}px`,s.style.height=s.style.width,s.style.border=\\\\\\\"1px solid black\\\\\\\",s.style.borderRadius=`${n}px`,s.style.position=\\\\\\\"absolute\\\\\\\",s.style.bottom=`${i}px`,s.style.left=`${i}px`,s}_jumpDomElementSize(){const t=this.domElement.getBoundingClientRect(),e=Math.min(t.width,t.height);return{size:Math.round(.2*e),margin:Math.round(.05*e)}}_createJumpDomElement(){const{size:t,margin:e}=this._jumpDomElementSize(),n=document.createElement(\\\\\\\"div\\\\\\\");n.id=\\\\\\\"MobileJoystickControls-jump\\\\\\\",n.style.width=`${t}px`;const i=Math.floor(t);return n.style.height=`${i}px`,n.style.border=\\\\\\\"1px solid black\\\\\\\",n.style.position=\\\\\\\"absolute\\\\\\\",n.style.bottom=`${2*e+parseInt(this._runDomElement.style.height)}px`,n.style.right=`${e}px`,n.style.borderRadius=`${i}px`,n}_createRunDomElement(){const t=document.createElement(\\\\\\\"div\\\\\\\"),e=this.domElement.getBoundingClientRect(),n=Math.min(e.width,e.height),i=Math.round(.2*n),s=Math.round(.05*n);return t.id=\\\\\\\"MobileJoystickControls-run\\\\\\\",t.style.width=`${i}px`,t.style.height=`${Math.floor(i)}px`,t.style.border=\\\\\\\"1px solid black\\\\\\\",t.style.position=\\\\\\\"absolute\\\\\\\",t.style.bottom=`${s}px`,t.style.right=`${s}px`,t.style.translate=\\\\\\\"-50%\\\\\\\",t}_addElements(){var t,e,n;null===(t=this.domElement.parentElement)||void 0===t||t.append(this._translateDomElement),null===(e=this.domElement.parentElement)||void 0===e||e.append(this._jumpDomElement),null===(n=this.domElement.parentElement)||void 0===n||n.append(this._runDomElement)}_removeElements(){var t;const e=[this._translateDomElement,this._jumpDomElement,this._runDomElement];for(let n of e)null===(t=n.parentElement)||void 0===t||t.removeChild(n)}updateElements(){this.player&&(this._jumpDomElement.style.display=this.player.jumpAllowed?\\\\\\\"block\\\\\\\":\\\\\\\"none\\\\\\\",this._runDomElement.style.display=this.player.runAllowed?\\\\\\\"block\\\\\\\":\\\\\\\"none\\\\\\\")}_addEvents(){xv.disableContextMenu(),this.domElement.addEventListener(\\\\\\\"touchstart\\\\\\\",this._boundMethods.onRotateStart),this.domElement.addEventListener(\\\\\\\"touchmove\\\\\\\",this._boundMethods.onRotateMove),this.domElement.addEventListener(\\\\\\\"touchend\\\\\\\",this._boundMethods.onRotateEnd),this._translateDomElement.addEventListener(\\\\\\\"touchstart\\\\\\\",this._boundMethods.onTranslateStart),this._translateDomElement.addEventListener(\\\\\\\"touchmove\\\\\\\",this._boundMethods.onTranslateMove),this._translateDomElement.addEventListener(\\\\\\\"touchend\\\\\\\",this._boundMethods.onTranslateEnd),this._jumpDomElement.addEventListener(\\\\\\\"pointerdown\\\\\\\",this._boundMethods.onJump),this._runDomElement.addEventListener(\\\\\\\"pointerdown\\\\\\\",this._boundMethods.onRunToggle)}_removeEvents(){xv.reEstablishContextMenu(),this.domElement.removeEventListener(\\\\\\\"touchstart\\\\\\\",this._boundMethods.onRotateStart),this.domElement.removeEventListener(\\\\\\\"touchmove\\\\\\\",this._boundMethods.onRotateMove),this.domElement.removeEventListener(\\\\\\\"touchend\\\\\\\",this._boundMethods.onRotateEnd),this._translateDomElement.removeEventListener(\\\\\\\"touchstart\\\\\\\",this._boundMethods.onTranslateStart),this._translateDomElement.removeEventListener(\\\\\\\"touchmove\\\\\\\",this._boundMethods.onTranslateMove),this._translateDomElement.removeEventListener(\\\\\\\"touchend\\\\\\\",this._boundMethods.onTranslateEnd),this._jumpDomElement.removeEventListener(\\\\\\\"pointerdown\\\\\\\",this._boundMethods.onJump),this._runDomElement.removeEventListener(\\\\\\\"pointerdown\\\\\\\",this._boundMethods.onRunToggle)}setRotationSpeed(t){this._rotationSpeed=t}setRotationRange(t){this._rotationRange.min=t.min,this._rotationRange.max=t.max}_onRotateStart(t){this._startCameraRotation.copy(this._camera.rotation);const e=this._getTouch(t,this.domElement);e&&(this._rotationStartPosition.set(e.clientX,e.clientY),this.vLeft.set(-1,0,.5),this.vRight.set(1,0,.5),[this.vLeft,this.vRight].forEach((t=>{t.unproject(this._camera),this._camera.worldToLocal(t)})),this.angleY=this.vLeft.angleTo(this.vRight),this.vTop.set(0,1,.5),this.vBottom.set(0,-1,.5),[this.vTop,this.vBottom].forEach((t=>{t.unproject(this._camera),this._camera.worldToLocal(t)})),this.angleX=this.vTop.angleTo(this.vBottom))}_onRotateMove(t){const e=this._getTouch(t,this.domElement);e&&(this._rotationMovePosition.set(e.clientX,e.clientY),this._rotationDelta.copy(this._rotationMovePosition).sub(this._rotationStartPosition),this.rotationData.direction.x=this._rotationDelta.x/this.domElement.clientWidth,this.rotationData.direction.y=this._rotationDelta.y/this.domElement.clientHeight,this._rotateCamera(this.rotationData))}_onRotateEnd(){this.rotationData.direction.x=0,this.rotationData.direction.y=0}_rotateCamera(t){let e=this.angleY*t.direction.x*this._rotationSpeed;this._camera.rotation.y=this._startCameraRotation.y+-e;let n=this.angleX*t.direction.y*this._rotationSpeed;this._camera.rotation.x=or.clamp(this._startCameraRotation.x+-n,this._rotationRange.min,this._rotationRange.max),this._computeAzimuthalAngle(),this.dispatchEvent(ML)}_computeAzimuthalAngle(){this._camera.updateMatrixWorld(),EL.set(0,0,1),this._camera.localToWorld(EL),EL.sub(this._camera.position),SL.setFromVector3(EL),this._azimuthalAngle=SL.theta}_onTranslateStart(t){this._startCameraPosition.copy(this._camera.position);if(!this._getTouch(t,this._translateDomElement))return;this._translateDomElementRect=this._translateDomElement.getBoundingClientRect();const e=this._translateDomElementRect.left+.5*this._translateDomElementRect.width,n=this._translateDomElementRect.top+.5*this._translateDomElementRect.height;this._translationStartPosition.set(e,n)}_onTranslateMove(t){const e=this._getTouch(t,this._translateDomElement);e&&(this._translationMovePosition.set(e.clientX,e.clientY),this._translationDelta.copy(this._translationMovePosition).sub(this._translationStartPosition),this.translationData.direction.x=this._translationDelta.x/this._translateDomElementRect.width*.5,this.translationData.direction.z=-this._translationDelta.y/this._translateDomElementRect.height*.5,this._updatePlayerTranslate(),this.dispatchEvent(ML))}_onTranslateEnd(){this.translationData.direction.x=0,this.translationData.direction.z=0,this._updatePlayerTranslate()}_updatePlayerTranslate(){if(!this.player)return;const t=this.translationData.direction;this.player.setForward(!1),this.player.setBackward(!1),this.player.setLeft(!1),this.player.setRight(!1);const e=Math.abs(t.x),n=Math.abs(t.z),i=n-e;function s(e){t.z>0&&e.setForward(!0),t.z<0&&e.setBackward(!0)}function r(e){t.x>0&&e.setRight(!0),t.x<0&&e.setLeft(!0)}i>0?(s(this.player),i<.5*n&&r(this.player)):(r(this.player),i<.5*e&&s(this.player))}_onJump(){var t;null===(t=this.player)||void 0===t||t.jump()}_onRunToggle(){if(!this.player)return;const t=this.player.running();this.player.setRun(!t);const e=this.player.running()?3:1;this._runDomElement.style.border=`${e}px solid black`}update(t){this.player&&(this.player.setAzimuthalAngle(this._azimuthalAngle),this.player.update(t))}_getTouch(t,e){for(let n=0;n{IL.PARAM_CALLBACK_updatePlayerParams(t)}}}const RL=new class extends ua{constructor(){super(...arguments),this.main=ha.FOLDER(),this.colliderObject=ha.NODE_PATH(\\\\\\\"\\\\\\\",{nodeSelection:{context:ts.SOP},dependentOnFoundNode:!1,callback:t=>{IL.PARAM_CALLBACK_updateCollider(t)}}),this.capsuleRadius=ha.FLOAT(.5,{range:[0,1],rangeLocked:[!0,!1],...PL()}),this.capsuleHeight=ha.FLOAT(1,{range:[0,2],rangeLocked:[!0,!1],...PL()}),this.physics=ha.FOLDER(),this.physicsSteps=ha.INTEGER(5,{range:[1,10],rangeLocked:[!0,!1],...PL()}),this.gravity=ha.VECTOR3([0,-30,0],{...PL()}),this.translateSpeed=ha.FLOAT(1),this.rotateSpeed=ha.FLOAT(AL.rotateSpeed),this.jumpAllowed=ha.BOOLEAN(!0,{...PL()}),this.jumpStrength=ha.FLOAT(10,{range:[0,100],rangeLocked:[!0,!1],...PL()}),this.runAllowed=ha.BOOLEAN(!0,{...PL()}),this.runSpeedMult=ha.FLOAT(2,{range:[0,10],rangeLocked:[!0,!1],...PL()}),this.updateCollider=ha.BUTTON(null,{callback:t=>{IL.PARAM_CALLBACK_updateCollider(t)}}),this.init=ha.FOLDER(),this.startPosition=ha.VECTOR3([0,2,0],{...PL()}),this.startRotation=ha.VECTOR3([0,0,0],{...PL()}),this.reset=ha.BUTTON(null,{callback:t=>{IL.PARAM_CALLBACK_resetPlayer(t)}}),this.minPolarAngle=ha.FLOAT(\\\\\\\"-$PI*0.5\\\\\\\",{range:[-Math.PI,Math.PI],rangeLocked:[!0,!0]}),this.maxPolarAngle=ha.FLOAT(\\\\\\\"$PI*0.5\\\\\\\",{range:[-Math.PI,Math.PI],rangeLocked:[!0,!0]})}};class IL extends ey{constructor(){super(...arguments),this.paramsConfig=RL,this._controls_by_element_id=new Map}static type(){return _s.MOBILE_JOYSTICK}endEventName(){return\\\\\\\"end\\\\\\\"}collisionController(){return this._collisionController=this._collisionController||new tx(this)}initializeNode(){this.io.inputs.setNamedInputConnectionPoints([new ta(IL.INPUT_UPDATE_COLLIDER,Qo.BASE,this._updateCollider.bind(this))]),this.io.outputs.setNamedOutputConnectionPoints([new ta(NL,Qo.BASE),new ta(LL,Qo.BASE),new ta(OL,Qo.BASE)])}async createControlsInstance(t,e){await this._initPlayer(t);const n=new CL(t,e,this._player);return this._controls_by_element_id.set(e.id,n),this._bind_listeners_to_controls_instance(n),n}async _initPlayer(t){this._player=this._player||await this._createPlayer(t),this._player&&(this._updatePlayerParams(),this._player.reset())}player(){return this._player}async _updatePlayerParams(){this._player&&(this._player.startPosition.copy(this.pv.startPosition),this._player.physicsSteps=this.pv.physicsSteps,this._player.jumpAllowed=this.pv.jumpAllowed,this._player.jumpStrength=this.pv.jumpStrength,this._player.runAllowed=this.pv.runAllowed,this._player.runSpeedMult=this.pv.runSpeedMult,this._player.gravity.copy(this.pv.gravity),this._player.speed=this.pv.translateSpeed,this._player.setCapsule({radius:this.pv.capsuleRadius,height:this.pv.capsuleHeight}),this._controls_by_element_id.forEach((t=>t.updateElements())))}async _createPlayer(t){const e=t,n=await this.collisionController().getCollider();if(!n)return void this.states.error.set(\\\\\\\"invalid collider\\\\\\\");return new $y({object:e,collider:n})}_resetPlayer(){var t;null===(t=this._player)||void 0===t||t.reset()}async _updateCollider(){await this.collisionController().updateCollider()}_bind_listeners_to_controls_instance(t){t.addEventListener(NL,(()=>{this.dispatchEventToOutput(NL,{})})),t.addEventListener(LL,(()=>{this.dispatchEventToOutput(LL,{})})),t.addEventListener(OL,(()=>{this.dispatchEventToOutput(OL,{})}))}updateRequired(){return!0}setupControls(t){t.setRotationSpeed(this.pv.rotateSpeed),t.setRotationRange({min:this.pv.minPolarAngle,max:this.pv.maxPolarAngle}),t.updateElements()}disposeControlsForHtmlElementId(t){this._controls_by_element_id.get(t)&&this._controls_by_element_id.delete(t)}static PARAM_CALLBACK_updateCollider(t){t._updateCollider()}static PARAM_CALLBACK_updatePlayerParams(t){t._updatePlayerParams()}static PARAM_CALLBACK_resetPlayer(t){t._resetPlayer()}}var FL;IL.INPUT_UPDATE_COLLIDER=\\\\\\\"updateCollider\\\\\\\",function(t){t.ALL_TOGETHER=\\\\\\\"all together\\\\\\\",t.BATCH=\\\\\\\"batch\\\\\\\"}(FL||(FL={}));const DL=[FL.ALL_TOGETHER,FL.BATCH];const BL=new class extends ua{constructor(){super(...arguments),this.mask=ha.STRING(\\\\\\\"/geo*\\\\\\\",{callback:t=>{zL.PARAM_CALLBACK_updateResolvedNodes(t)}}),this.force=ha.BOOLEAN(0),this.cookMode=ha.INTEGER(DL.indexOf(FL.ALL_TOGETHER),{menu:{entries:DL.map(((t,e)=>({name:t,value:e})))}}),this.batchSize=ha.INTEGER(1,{visibleIf:{cookMode:DL.indexOf(FL.BATCH)},separatorAfter:!0}),this.registerOnlyFirstCooks=ha.BOOLEAN(!0),this.updateResolve=ha.BUTTON(null,{callback:(t,e)=>{zL.PARAM_CALLBACK_updateResolve(t)}}),this.printResolve=ha.BUTTON(null,{callback:(t,e)=>{zL.PARAM_CALLBACK_printResolve(t)}})}};class zL extends Va{constructor(){super(...arguments),this.paramsConfig=BL,this._resolvedNodes=[],this._dispatchedFirstNodeCooked=!1,this._dispatchedAllNodesCooked=!1,this._cookStateByNodeId=new Map}static type(){return\\\\\\\"nodeCook\\\\\\\"}initializeNode(){this.io.inputs.setNamedInputConnectionPoints([new ta(zL.INPUT_TRIGGER,Qo.BASE,this.processEventTrigger.bind(this))]),this.io.outputs.setNamedOutputConnectionPoints([new ta(zL.OUTPUT_FIRST_NODE,Qo.BASE),new ta(zL.OUTPUT_EACH_NODE,Qo.BASE),new ta(zL.OUTPUT_ALL_NODES,Qo.BASE)])}trigger(){this.processEventTrigger({})}cook(){this._updateResolvedNodes(),this.cookController.endCook()}dispose(){super.dispose(),this._reset()}resolvedNodes(){return this._resolvedNodes}processEventTrigger(t){this._cook_nodes_with_mode()}_cook_nodes_with_mode(){this._updateResolvedNodes();const t=DL[this.pv.cookMode];switch(t){case FL.ALL_TOGETHER:return this._cookNodesAllTogether();case FL.BATCH:return this._cookNodesInBatch()}os.unreachable(t)}_cookNodesAllTogether(){this._cookNodes(this._resolvedNodes)}async _cookNodesInBatch(){const t=this.pv.batchSize,e=Math.ceil(this._resolvedNodes.length/t);for(let n=0;n{this._onNodeCookComplete(t)})),this._cookStateByNodeId.set(t.graphNodeId(),!1)}_callbackNameForNode(t){return`owner-${this.graphNodeId()}-target-${t.graphNodeId()}`}_reset(){this._dispatchedFirstNodeCooked=!1,this._cookStateByNodeId.clear();for(let t of this._resolvedNodes)t.cookController.deregisterOnCookEnd(this._callbackNameForNode(t));this._resolvedNodes=[]}_allNodesHaveCooked(){for(let t of this._resolvedNodes){if(!this._cookStateByNodeId.get(t.graphNodeId()))return!1}return!0}_onNodeCookComplete(t){const e={value:{node:t}};this._dispatchedFirstNodeCooked||(this._dispatchedFirstNodeCooked=!0,this.dispatchEventToOutput(zL.OUTPUT_FIRST_NODE,e));this._cookStateByNodeId.get(t.graphNodeId())&&this.pv.registerOnlyFirstCooks||this.dispatchEventToOutput(zL.OUTPUT_EACH_NODE,e),this._cookStateByNodeId.set(t.graphNodeId(),!0),this._dispatchedAllNodesCooked||this._allNodesHaveCooked()&&(this._dispatchedAllNodesCooked=!0,this.dispatchEventToOutput(zL.OUTPUT_ALL_NODES,{}))}static PARAM_CALLBACK_updateResolve(t){t._allNodesHaveCooked()}static PARAM_CALLBACK_printResolve(t){t.printResolve()}printResolve(){console.log(this._resolvedNodes)}}var kL,UL;zL.INPUT_TRIGGER=\\\\\\\"trigger\\\\\\\",zL.OUTPUT_FIRST_NODE=\\\\\\\"first\\\\\\\",zL.OUTPUT_EACH_NODE=\\\\\\\"each\\\\\\\",zL.OUTPUT_ALL_NODES=\\\\\\\"all\\\\\\\",function(t){t.TRIGGER=\\\\\\\"trigger\\\\\\\"}(kL||(kL={})),function(t){t.OUT=\\\\\\\"out\\\\\\\"}(UL||(UL={}));const GL=new class extends ua{};class VL extends Va{constructor(){super(...arguments),this.paramsConfig=GL}static type(){return\\\\\\\"null\\\\\\\"}initializeNode(){this.io.inputs.setNamedInputConnectionPoints([new ta(kL.TRIGGER,Qo.BASE,this.processEventTrigger.bind(this))]),this.io.outputs.setNamedOutputConnectionPoints([new ta(UL.OUT,Qo.BASE)])}processEvent(t){}processEventTrigger(t){this.dispatchEventToOutput(UL.OUT,t)}}const HL=\\\\\\\"init\\\\\\\",jL=\\\\\\\"dispose\\\\\\\",WL=\\\\\\\"reset\\\\\\\";function qL(){return{callback:t=>{ZL.PARAM_CALLBACK_updatePlayerParams(t)}}}const XL=new p.a,YL=new p.a,$L=new uy;const JL=new class extends ua{constructor(){super(...arguments),this.main=ha.FOLDER(),this.playerObject=ha.NODE_PATH(\\\\\\\"\\\\\\\",{nodeSelection:{context:ts.OBJ}}),this.colliderObject=ha.NODE_PATH(\\\\\\\"\\\\\\\",{nodeSelection:{context:ts.SOP},dependentOnFoundNode:!1,callback:t=>{ZL.PARAM_CALLBACK_updateCollider(t)}}),this.camera=ha.NODE_PATH(\\\\\\\"\\\\\\\",{nodeSelection:{types:[is.PERSPECTIVE,is.ORTHOGRAPHIC],context:ts.OBJ}}),this.initPlayer=ha.BUTTON(null,{callback:t=>{ZL.PARAM_CALLBACK_initPlayer(t)}}),this.capsuleRadius=ha.FLOAT(.5,{range:[0,1],rangeLocked:[!0,!1],...qL()}),this.capsuleHeight=ha.FLOAT(1,{range:[0,2],rangeLocked:[!0,!1],...qL()}),this.physics=ha.FOLDER(),this.physicsSteps=ha.INTEGER(5,{range:[1,10],rangeLocked:[!0,!1],...qL()}),this.gravity=ha.VECTOR3([0,-30,0],{...qL()}),this.speed=ha.FLOAT(1,{range:[0,10],rangeLocked:[!0,!1],...qL()}),this.jumpAllowed=ha.BOOLEAN(!0,{...qL()}),this.jumpStrength=ha.FLOAT(10,{range:[0,100],rangeLocked:[!0,!1],...qL()}),this.runAllowed=ha.BOOLEAN(!0,{...qL()}),this.runSpeedMult=ha.FLOAT(2,{range:[0,10],rangeLocked:[!0,!1],...qL()}),this.updateCollider=ha.BUTTON(null,{callback:t=>{ZL.PARAM_CALLBACK_updateCollider(t)}}),this.mesh=ha.FOLDER(),this.useMesh=ha.BOOLEAN(!0,{callback:t=>{ZL.PARAM_CALLBACK_updatePlayerMesh(t)}}),this.material=ha.NODE_PATH(\\\\\\\"\\\\\\\",{nodeSelection:{context:ts.MAT},callback:t=>{ZL.PARAM_CALLBACK_updatePlayerMaterial(t)}}),this.init=ha.FOLDER(),this.startPosition=ha.VECTOR3([0,5,0],{...qL()}),this.reset=ha.BUTTON(null,{callback:t=>{ZL.PARAM_CALLBACK_resetPlayer(t)}})}};class ZL extends Va{constructor(){super(...arguments),this.paramsConfig=JL}static type(){return _s.PLAYER}collisionController(){return this._collisionController=this._collisionController||new tx(this)}initializeNode(){this.io.inputs.setNamedInputConnectionPoints([new ta(HL,Qo.BASE,this._initPlayer.bind(this)),new ta(jL,Qo.BASE,this._disposePlayer.bind(this)),new ta(WL,Qo.BASE,this._resetPlayer.bind(this))]),this.io.outputs.setNamedOutputConnectionPoints([new ta(HL,Qo.BASE),new ta(jL,Qo.BASE),new ta(WL,Qo.BASE)])}async _initPlayer(){if(this._player=this._player||await this._createPlayer(),!this._player)return void this.states.error.set(\\\\\\\"could not create player\\\\\\\");this._updatePlayerMesh(),this._updatePlayerMaterial(),this._updatePlayerParams(),this._corePlayerKeyEvents=new Zy(this._player),this._corePlayerKeyEvents.addEvents(),this._player.reset();const t=this._player;this.scene().registerOnBeforeTick(this._callbackName(),(e=>{t.setAzimuthalAngle(this._getAzimuthalAngle()),t.update(e)})),this.dispatchEventToOutput(HL,{})}player(){return this._player}_callbackName(){return`event/PlayerControls-${this.graphNodeId()}`}_disposePlayer(){var t;this._player&&(null===(t=this._corePlayerKeyEvents)||void 0===t||t.removeEvents(),this.scene().unRegisterOnBeforeTick(this._callbackName())),this.dispatchEventToOutput(jL,{})}_resetPlayer(){this._player&&this._player.reset(),this.dispatchEventToOutput(WL,{})}async _updatePlayerParams(){this._player&&(this._player.startPosition.copy(this.pv.startPosition),this._player.physicsSteps=this.pv.physicsSteps,this._player.jumpAllowed=this.pv.jumpAllowed,this._player.jumpStrength=this.pv.jumpStrength,this._player.runAllowed=this.pv.runAllowed,this._player.runSpeedMult=this.pv.runSpeedMult,this._player.gravity.copy(this.pv.gravity),this._player.speed=this.pv.speed,this._player.setCapsule({radius:this.pv.capsuleRadius,height:this.pv.capsuleHeight}))}_updatePlayerMesh(){this._player&&this._player.setUsePlayerMesh(this.pv.useMesh)}async _updatePlayerMaterial(){if(!this._player)return;const t=this.pv.material.nodeWithContext(ts.MAT);if(!t)return void this.states.error.set(\\\\\\\"material node not found\\\\\\\");const e=(await t.compute()).material();this._player.setMaterial(e)}async _createPlayer(){const t=this.pv.playerObject.nodeWithContext(ts.OBJ);if(!t)return void this.states.error.set(\\\\\\\"player node not found\\\\\\\");const e=this.pv.camera.nodeWithContext(ts.OBJ);if(!e)return void this.states.error.set(\\\\\\\"invalid camera node\\\\\\\");this._cameraObject=e.object;const n=t.object,i=await this.collisionController().getCollider();if(!i)return void this.states.error.set(\\\\\\\"invalid collider\\\\\\\");return new $y({object:n,collider:i,meshName:this.path()})}async _updateCollider(){await this.collisionController().updateCollider()}_getAzimuthalAngle(){if(!this._cameraObject||!this._player)return 0;const t=this._cameraObject.position,e=this._player.object.position;return XL.copy(t),YL.copy(e),XL.sub(YL),$L.setFromVector3(XL),$L.theta}static PARAM_CALLBACK_initPlayer(t){t._initPlayer()}static PARAM_CALLBACK_updatePlayerParams(t){t._updatePlayerParams()}static PARAM_CALLBACK_updatePlayerMaterial(t){t._updatePlayerMaterial()}static PARAM_CALLBACK_updatePlayerMesh(t){t._updatePlayerMesh()}static PARAM_CALLBACK_updateCollider(t){t._updateCollider()}static PARAM_CALLBACK_resetPlayer(t){t._resetPlayer()}}var KL,QL=n(39),tO=n(36);class eO{constructor(t,e,n=0,i=1/0){this.ray=new QL.a(t,e),this.near=n,this.far=i,this.camera=null,this.layers=new tO.a,this.params={Mesh:{},Line:{threshold:1},LOD:{},Points:{threshold:1},Sprite:{}}}set(t,e){this.ray.set(t,e)}setFromCamera(t,e){e&&e.isPerspectiveCamera?(this.ray.origin.setFromMatrixPosition(e.matrixWorld),this.ray.direction.set(t.x,t.y,.5).unproject(e).sub(this.ray.origin).normalize(),this.camera=e):e&&e.isOrthographicCamera?(this.ray.origin.set(t.x,t.y,(e.near+e.far)/(e.near-e.far)).unproject(e),this.ray.direction.set(0,0,-1).transformDirection(e.matrixWorld),this.camera=e):console.error(\\\\\\\"THREE.Raycaster: Unsupported camera type: \\\\\\\"+e.type)}intersectObject(t,e=!0,n=[]){return iO(t,this,n,e),n.sort(nO),n}intersectObjects(t,e=!0,n=[]){for(let i=0,s=t.length;i{this._mouse.x=t.offsetX/n.offsetWidth*2-1,this._mouse.y=-t.offsetY/n.offsetHeight*2+1,this._mouse.toArray(this._mouse_array),this._node.p.mouse.set(this._mouse_array)})(this._offset),this._raycaster.setFromCamera(this._mouse,i.object)}processEvent(t){this._prepareRaycaster(t);const e=oO[this._node.pv.intersectWith];switch(e){case rO.GEOMETRY:return this._intersect_with_geometry(t);case rO.PLANE:return this._intersect_with_plane(t)}os.unreachable(e)}_intersect_with_plane(t){this._plane.normal.copy(this._node.pv.planeDirection),this._plane.constant=this._node.pv.planeOffset,this._raycaster.ray.intersectPlane(this._plane,this._plane_intersect_target),this._set_position_param(this._plane_intersect_target),this._node.trigger_hit(t)}_intersect_with_geometry(t){if(this._resolved_targets||this.update_target(),this._resolved_targets){this._intersections.length=0;const e=this._raycaster.intersectObjects(this._resolved_targets,this._node.pv.traverseChildren,this._intersections)[0];e?(this._set_position_param(e.point),this._node.pv.geoAttribute&&this._resolve_geometry_attribute(e),t.value={intersect:e},this._node.trigger_hit(t)):this._node.trigger_miss(t)}}_resolve_geometry_attribute(t){const e=ks[this._node.pv.geoAttributeType],n=lO.resolve_geometry_attribute(t,this._node.pv.geoAttributeName,e);if(null!=n){switch(e){case zs.NUMERIC:return void this._node.p.geoAttributeValue1.set(n);case zs.STRING:return void(m.isString(n)&&this._node.p.geoAttributeValues.set(n))}os.unreachable(e)}}static resolve_geometry_attribute(t,e,n){switch(Os(t.object.constructor)){case Ns.MESH:return this.resolve_geometry_attribute_for_mesh(t,e,n);case Ns.POINTS:return this.resolve_geometry_attribute_for_point(t,e,n)}}static resolve_geometry_attribute_for_mesh(t,e,n){const i=t.object.geometry;if(i){const s=i.getAttribute(e);if(s){switch(n){case zs.NUMERIC:{const e=i.getAttribute(\\\\\\\"position\\\\\\\");return t.face?(this._vA.fromBufferAttribute(e,t.face.a),this._vB.fromBufferAttribute(e,t.face.b),this._vC.fromBufferAttribute(e,t.face.c),this._uvA.fromBufferAttribute(s,t.face.a),this._uvB.fromBufferAttribute(s,t.face.b),this._uvC.fromBufferAttribute(s,t.face.c),t.uv=tr.a.getUV(t.point,this._vA,this._vB,this._vC,this._uvA,this._uvB,this._uvC,this._hitUV),this._hitUV.x):void 0}case zs.STRING:{const t=new fr(i).points()[0];return t?t.stringAttribValue(e):void 0}}os.unreachable(n)}}}static resolve_geometry_attribute_for_point(t,e,n){const i=t.object.geometry;if(i&&null!=t.index){switch(n){case zs.NUMERIC:{const n=i.getAttribute(e);return n?n.array[t.index]:void 0}case zs.STRING:{const n=new fr(i).points()[t.index];return n?n.stringAttribValue(e):void 0}}os.unreachable(n)}}_set_position_param(t){if(t.toArray(this._hit_position_array),this._node.pv.tpositionTarget){if(li.playerMode())this._found_position_target_param=this._found_position_target_param||this._node.pv.positionTarget.paramWithType(Cr.VECTOR3);else{const t=this._node.pv.positionTarget;this._found_position_target_param=t.paramWithType(Cr.VECTOR3)}this._found_position_target_param&&this._found_position_target_param.set(this._hit_position_array)}else this._node.p.position.set(this._hit_position_array);this.velocity_controller.process(t)}_prepareRaycaster(t){const e=this._raycaster.params.Points;e&&(e.threshold=this._node.pv.pointsThreshold);let n=t.cameraNode;if(this._node.pv.overrideCamera)if(this._node.pv.overrideRay)this._raycaster.ray.origin.copy(this._node.pv.rayOrigin),this._raycaster.ray.direction.copy(this._node.pv.rayDirection);else{const t=this._node.p.camera.found_node_with_context(ts.OBJ);t&&(n=t)}n&&!this._node.pv.overrideRay&&n.prepareRaycaster(this._mouse,this._raycaster)}update_target(){const t=vO[this._node.pv.targetType];switch(t){case gO.NODE:return this._update_target_from_node();case gO.SCENE_GRAPH:return this._update_target_from_scene_graph()}os.unreachable(t)}_update_target_from_node(){const t=this._node.p.targetNode.value.nodeWithContext(ts.OBJ);if(t){const e=this._node.pv.traverseChildren?t.object:t.childrenDisplayController.sopGroup();this._resolved_targets=e?[e]:void 0}else this._node.states.error.set(\\\\\\\"node is not an object\\\\\\\")}_update_target_from_scene_graph(){const t=this._node.scene().objectsByMask(this._node.pv.objectMask);t.length>0?this._resolved_targets=t:this._resolved_targets=void 0}async update_position_target(){this._node.p.positionTarget.isDirty()&&await this._node.p.positionTarget.compute()}static PARAM_CALLBACK_update_target(t){t.cpuController.update_target()}static PARAM_CALLBACK_print_resolve(t){t.cpuController.print_resolve()}print_resolve(){this.update_target(),console.log(this._resolved_targets)}}lO._vA=new p.a,lO._vB=new p.a,lO._vC=new p.a,lO._uvA=new d.a,lO._uvB=new d.a,lO._uvC=new d.a,lO._hitUV=new d.a;class cO{constructor(t){this._node=t,this._resolved_material=null,this._restore_context={scene:{overrideMaterial:null},renderer:{toneMapping:-1,outputEncoding:-1}},this._mouse=new d.a,this._mouse_array=[0,0],this._read=new Float32Array(4),this._param_read=[0,0,0,0]}updateMouse(t){var e;const n=null===(e=t.viewer)||void 0===e?void 0:e.canvas();n&&t.event&&(t.event instanceof MouseEvent||t.event instanceof DragEvent||t.event instanceof PointerEvent?(this._mouse.x=t.event.offsetX/n.offsetWidth,this._mouse.y=1-t.event.offsetY/n.offsetHeight,this._mouse.toArray(this._mouse_array),this._node.p.mouse.set(this._mouse_array)):console.warn(\\\\\\\"event type not implemented\\\\\\\"))}processEvent(t){var e;const n=null===(e=t.viewer)||void 0===e?void 0:e.canvas();if(!n||!t.cameraNode)return;const i=t.cameraNode,s=i.renderController;if(s){if(this._render_target=this._render_target||new K(n.offsetWidth,n.offsetHeight,{minFilter:w.V,magFilter:w.ob,format:w.Ib,type:w.G}),!this._resolved_material)return this.update_material(),void console.warn(\\\\\\\"no material found\\\\\\\");const e=i,r=s.resolved_scene||i.scene().threejsScene(),o=s.renderer(n);this._modify_scene_and_renderer(r,o),o.setRenderTarget(this._render_target),o.clear(),o.render(r,e.object),o.setRenderTarget(null),this._restore_scene_and_renderer(r,o),o.readRenderTargetPixels(this._render_target,Math.round(this._mouse.x*n.offsetWidth),Math.round(this._mouse.y*n.offsetHeight),1,1,this._read),this._param_read[0]=this._read[0],this._param_read[1]=this._read[1],this._param_read[2]=this._read[2],this._param_read[3]=this._read[3],this._node.p.pixelValue.set(this._param_read),this._node.pv.pixelValue.x>this._node.pv.hitThreshold?this._node.trigger_hit(t):this._node.trigger_miss(t)}}_modify_scene_and_renderer(t,e){this._restore_context.scene.overrideMaterial=t.overrideMaterial,this._restore_context.renderer.outputEncoding=e.outputEncoding,this._restore_context.renderer.toneMapping=e.toneMapping,t.overrideMaterial=this._resolved_material,e.toneMapping=w.vb,e.outputEncoding=w.U}_restore_scene_and_renderer(t,e){t.overrideMaterial=this._restore_context.scene.overrideMaterial,e.outputEncoding=this._restore_context.renderer.outputEncoding,e.toneMapping=this._restore_context.renderer.toneMapping}update_material(){const t=this._node.p.material.found_node();t?t.context()==ts.MAT?this._resolved_material=t.material:this._node.states.error.set(\\\\\\\"target is not an obj\\\\\\\"):this._node.states.error.set(\\\\\\\"no target found\\\\\\\")}static PARAM_CALLBACK_update_material(t){t.gpuController.update_material()}}const hO=1e3/60;var uO;!function(t){t.CPU=\\\\\\\"cpu\\\\\\\",t.GPU=\\\\\\\"gpu\\\\\\\"}(uO||(uO={}));const dO=[uO.CPU,uO.GPU];function pO(t={}){return t.mode=dO.indexOf(uO.CPU),{visibleIf:t}}function _O(t={}){return t.mode=dO.indexOf(uO.CPU),t.intersectWith=oO.indexOf(rO.GEOMETRY),{visibleIf:t}}function mO(t={}){return t.mode=dO.indexOf(uO.CPU),t.intersectWith=oO.indexOf(rO.PLANE),{visibleIf:t}}function fO(t={}){return t.mode=dO.indexOf(uO.GPU),{visibleIf:t}}var gO;!function(t){t.SCENE_GRAPH=\\\\\\\"scene graph\\\\\\\",t.NODE=\\\\\\\"node\\\\\\\"}(gO||(gO={}));const vO=[gO.SCENE_GRAPH,gO.NODE];const yO=new class extends ua{constructor(){super(...arguments),this.mode=ha.INTEGER(dO.indexOf(uO.CPU),{menu:{entries:dO.map(((t,e)=>({name:t,value:e})))}}),this.mouse=ha.VECTOR2([0,0],{cook:!1}),this.overrideCamera=ha.BOOLEAN(0),this.overrideRay=ha.BOOLEAN(0,{visibleIf:{mode:dO.indexOf(uO.CPU),overrideCamera:1}}),this.camera=ha.OPERATOR_PATH(\\\\\\\"/perspective_camera1\\\\\\\",{nodeSelection:{context:ts.OBJ},dependentOnFoundNode:!1,visibleIf:{overrideCamera:1,overrideRay:0}}),this.rayOrigin=ha.VECTOR3([0,0,0],{visibleIf:{overrideCamera:1,overrideRay:1}}),this.rayDirection=ha.VECTOR3([0,0,1],{visibleIf:{overrideCamera:1,overrideRay:1}}),this.material=ha.OPERATOR_PATH(\\\\\\\"/MAT/mesh_basic_builder1\\\\\\\",{nodeSelection:{context:ts.MAT},dependentOnFoundNode:!1,callback:(t,e)=>{cO.PARAM_CALLBACK_update_material(t)},...fO()}),this.pixelValue=ha.VECTOR4([0,0,0,0],{cook:!1,...fO()}),this.hitThreshold=ha.FLOAT(.5,{cook:!1,...fO()}),this.intersectWith=ha.INTEGER(oO.indexOf(rO.GEOMETRY),{menu:{entries:oO.map(((t,e)=>({name:t,value:e})))},...pO()}),this.pointsThreshold=ha.FLOAT(1,{range:[0,100],rangeLocked:[!0,!1],...pO()}),this.planeDirection=ha.VECTOR3([0,1,0],{...mO()}),this.planeOffset=ha.FLOAT(0,{...mO()}),this.targetType=ha.INTEGER(0,{menu:{entries:vO.map(((t,e)=>({name:t,value:e})))},..._O()}),this.targetNode=ha.NODE_PATH(\\\\\\\"\\\\\\\",{nodeSelection:{context:ts.OBJ},dependentOnFoundNode:!1,callback:(t,e)=>{lO.PARAM_CALLBACK_update_target(t)},..._O({targetType:vO.indexOf(gO.NODE)})}),this.objectMask=ha.STRING(\\\\\\\"*geo1*\\\\\\\",{callback:(t,e)=>{lO.PARAM_CALLBACK_update_target(t)},..._O({targetType:vO.indexOf(gO.SCENE_GRAPH)})}),this.printFoundObjectsFromMask=ha.BUTTON(null,{callback:(t,e)=>{lO.PARAM_CALLBACK_print_resolve(t)},..._O({targetType:vO.indexOf(gO.SCENE_GRAPH)})}),this.traverseChildren=ha.BOOLEAN(!0,{callback:(t,e)=>{lO.PARAM_CALLBACK_update_target(t)},..._O(),separatorAfter:!0}),this.tpositionTarget=ha.BOOLEAN(0,{cook:!1,...pO()}),this.position=ha.VECTOR3([0,0,0],{cook:!1,...pO({tpositionTarget:0})}),this.positionTarget=ha.PARAM_PATH(\\\\\\\"\\\\\\\",{cook:!1,...pO({tpositionTarget:1}),paramSelection:Cr.VECTOR3,computeOnDirty:!0}),this.tvelocity=ha.BOOLEAN(0,{cook:!1}),this.tvelocityTarget=ha.BOOLEAN(0,{cook:!1,...pO({tvelocity:1})}),this.velocity=ha.VECTOR3([0,0,0],{cook:!1,...pO({tvelocity:1,tvelocityTarget:0})}),this.velocityTarget=ha.PARAM_PATH(\\\\\\\"\\\\\\\",{cook:!1,...pO({tvelocity:1,tvelocityTarget:1}),paramSelection:Cr.VECTOR3,computeOnDirty:!0}),this.geoAttribute=ha.BOOLEAN(0,_O()),this.geoAttributeName=ha.STRING(\\\\\\\"id\\\\\\\",{cook:!1,..._O({geoAttribute:1})}),this.geoAttributeType=ha.INTEGER(ks.indexOf(zs.NUMERIC),{menu:{entries:Us},..._O({geoAttribute:1})}),this.geoAttributeValue1=ha.FLOAT(0,{cook:!1,..._O({geoAttribute:1,geoAttributeType:ks.indexOf(zs.NUMERIC)})}),this.geoAttributeValues=ha.STRING(\\\\\\\"\\\\\\\",{..._O({geoAttribute:1,geoAttributeType:ks.indexOf(zs.STRING)})})}};class xO extends Va{constructor(){super(...arguments),this.paramsConfig=yO,this.cpuController=new lO(this),this.gpuController=new cO(this),this._last_event_processed_at=-1}static type(){return\\\\\\\"raycast\\\\\\\"}initializeNode(){this.io.inputs.setNamedInputConnectionPoints([new ta(xO.INPUT_TRIGGER,Qo.BASE,this._process_trigger_event_throttled.bind(this)),new ta(xO.INPUT_MOUSE,Qo.MOUSE,this._process_mouse_event.bind(this)),new ta(xO.INPUT_UPDATE_OBJECTS,Qo.BASE,this._process_trigger_update_objects.bind(this)),new ta(xO.INPUT_TRIGGER_VEL_RESET,Qo.BASE,this._process_trigger_vel_reset.bind(this))]),this.io.outputs.setNamedOutputConnectionPoints([new ta(xO.OUTPUT_HIT,Qo.BASE),new ta(xO.OUTPUT_MISS,Qo.BASE)])}trigger_hit(t){this.dispatchEventToOutput(xO.OUTPUT_HIT,t)}trigger_miss(t){this.dispatchEventToOutput(xO.OUTPUT_MISS,t)}_process_mouse_event(t){this.pv.mode==dO.indexOf(uO.CPU)?this.cpuController.updateMouse(t):this.gpuController.updateMouse(t)}_process_trigger_event_throttled(t){const e=this._last_event_processed_at,n=li.performance.performanceManager().now();this._last_event_processed_at=n;const i=n-e;i{this._process_trigger_event(t)}),hO-i):this._process_trigger_event(t)}_process_trigger_event(t){this.pv.mode==dO.indexOf(uO.CPU)?this.cpuController.processEvent(t):this.gpuController.processEvent(t)}_process_trigger_update_objects(t){this.pv.mode==dO.indexOf(uO.CPU)&&this.cpuController.update_target()}_process_trigger_vel_reset(t){this.pv.mode==dO.indexOf(uO.CPU)&&this.cpuController.velocity_controller.reset()}}var bO;xO.INPUT_TRIGGER=\\\\\\\"trigger\\\\\\\",xO.INPUT_MOUSE=\\\\\\\"mouse\\\\\\\",xO.INPUT_UPDATE_OBJECTS=\\\\\\\"updateObjects\\\\\\\",xO.INPUT_TRIGGER_VEL_RESET=\\\\\\\"triggerVelReset\\\\\\\",xO.OUTPUT_HIT=\\\\\\\"hit\\\\\\\",xO.OUTPUT_MISS=\\\\\\\"miss\\\\\\\",function(t){t.SET=\\\\\\\"set\\\\\\\",t.TOGGLE=\\\\\\\"toggle\\\\\\\"}(bO||(bO={}));const wO=[bO.SET,bO.TOGGLE];const TO=new class extends ua{constructor(){super(...arguments),this.mask=ha.STRING(\\\\\\\"/geo*\\\\\\\",{separatorAfter:!0}),this.tdisplay=ha.BOOLEAN(0),this.displayMode=ha.INTEGER(wO.indexOf(bO.SET),{visibleIf:{tdisplay:1},menu:{entries:wO.map(((t,e)=>({name:t,value:e})))}}),this.display=ha.BOOLEAN(0,{visibleIf:{tdisplay:1,displayMode:wO.indexOf(bO.SET)},separatorAfter:!0}),this.tbypass=ha.BOOLEAN(0),this.bypassMode=ha.INTEGER(wO.indexOf(bO.SET),{visibleIf:{tbypass:1},menu:{entries:wO.map(((t,e)=>({name:t,value:e})))}}),this.bypass=ha.BOOLEAN(0,{visibleIf:{tbypass:1,displayMode:wO.indexOf(bO.SET)}}),this.execute=ha.BUTTON(null,{callback:t=>{AO.PARAM_CALLBACK_execute(t)}})}};class AO extends Va{constructor(){super(...arguments),this.paramsConfig=TO}static type(){return\\\\\\\"setFlag\\\\\\\"}initializeNode(){this.io.inputs.setNamedInputConnectionPoints([new ta(\\\\\\\"trigger\\\\\\\",Qo.BASE)])}async processEvent(t){let e=this.pv.mask;if(t.value){const n=t.value.node;if(n){const t=n.parent();t&&(e=`${t.path()}/${e}`)}}const n=this.scene().nodesController.nodesFromMask(e);for(let t of n)this._update_node_flags(t)}_update_node_flags(t){this._update_node_display_flag(t),this._update_node_bypass_flag(t)}_update_node_display_flag(t){var e;if(!this.pv.tdisplay)return;if(!(null===(e=t.flags)||void 0===e?void 0:e.hasDisplay()))return;const n=t.flags.display;if(!n)return;const i=wO[this.pv.displayMode];switch(i){case bO.SET:return void n.set(this.pv.display);case bO.TOGGLE:return void n.set(!n.active())}os.unreachable(i)}_update_node_bypass_flag(t){var e;if(!this.pv.tbypass)return;if(!(null===(e=t.flags)||void 0===e?void 0:e.hasBypass()))return;const n=t.flags.bypass;if(!n)return;const i=wO[this.pv.bypassMode];switch(i){case bO.SET:return void n.set(this.pv.bypass);case bO.TOGGLE:return void n.set(!n.active())}os.unreachable(i)}static PARAM_CALLBACK_execute(t){t.processEvent({})}}var MO;!function(t){t.BOOLEAN=\\\\\\\"boolean\\\\\\\",t.BUTTON=\\\\\\\"button\\\\\\\",t.NUMBER=\\\\\\\"number\\\\\\\",t.VECTOR2=\\\\\\\"vector2\\\\\\\",t.VECTOR3=\\\\\\\"vector3\\\\\\\",t.VECTOR4=\\\\\\\"vector4\\\\\\\",t.STRING=\\\\\\\"string\\\\\\\"}(MO||(MO={}));const EO=[MO.BOOLEAN,MO.BUTTON,MO.NUMBER,MO.VECTOR2,MO.VECTOR3,MO.VECTOR4,MO.STRING],SO=EO.indexOf(MO.BOOLEAN),CO=EO.indexOf(MO.NUMBER),NO=EO.indexOf(MO.VECTOR2),LO=EO.indexOf(MO.VECTOR3),OO=EO.indexOf(MO.VECTOR4),PO=EO.indexOf(MO.STRING),RO=\\\\\\\"output\\\\\\\";const IO=new class extends ua{constructor(){super(...arguments),this.param=ha.PARAM_PATH(\\\\\\\"\\\\\\\",{paramSelection:!0,computeOnDirty:!0}),this.type=ha.INTEGER(CO,{menu:{entries:EO.map(((t,e)=>({name:t,value:e})))}}),this.toggle=ha.BOOLEAN(0,{visibleIf:{type:SO}}),this.boolean=ha.BOOLEAN(0,{visibleIf:{type:SO,toggle:0}}),this.number=ha.FLOAT(0,{visibleIf:{type:CO}}),this.vector2=ha.VECTOR2([0,0],{visibleIf:{type:NO}}),this.vector3=ha.VECTOR3([0,0,0],{visibleIf:{type:LO}}),this.vector4=ha.VECTOR4([0,0,0,0],{visibleIf:{type:OO}}),this.increment=ha.BOOLEAN(0,{visibleIf:[{type:CO},{type:NO},{type:LO},{type:OO}]}),this.string=ha.STRING(\\\\\\\"\\\\\\\",{visibleIf:{type:PO}}),this.execute=ha.BUTTON(null,{callback:t=>{FO.PARAM_CALLBACK_execute(t)}})}};class FO extends Va{constructor(){super(...arguments),this.paramsConfig=IO,this._tmp_vector2=new d.a,this._tmp_vector3=new p.a,this._tmp_vector4=new _.a,this._tmp_array2=[0,0],this._tmp_array3=[0,0,0],this._tmp_array4=[0,0,0,0]}static type(){return\\\\\\\"setParam\\\\\\\"}initializeNode(){this.io.inputs.setNamedInputConnectionPoints([new ta(\\\\\\\"trigger\\\\\\\",Qo.BASE)]),this.io.outputs.setNamedOutputConnectionPoints([new ta(RO,Qo.BASE)]),this.scene().dispatchController.onAddListener((()=>{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{this.params.label.init([this.p.param])}))}))}async processEvent(t){this.p.param.isDirty()&&await this.p.param.compute();const e=this.p.param.value.param();if(e){const t=await this._new_param_value(e);null!=t&&e.set(t)}else this.states.error.set(\\\\\\\"target param not found\\\\\\\");this.dispatchEventToOutput(RO,t)}async _new_param_value(t){const e=EO[this.pv.type];switch(e){case MO.BOOLEAN:return await this._compute_params_if_dirty([this.p.toggle]),this.pv.toggle?t.value?0:1:this.pv.boolean?1:0;case MO.BUTTON:return t.options.executeCallback();case MO.NUMBER:return await this._compute_params_if_dirty([this.p.increment,this.p.number]),this.pv.increment?t.type()==Cr.FLOAT?t.value+this.pv.number:t.value:this.pv.number;case MO.VECTOR2:return await this._compute_params_if_dirty([this.p.increment,this.p.vector2]),this.pv.increment?t.type()==Cr.VECTOR2?(this._tmp_vector2.copy(t.value),this._tmp_vector2.add(this.pv.vector2),this._tmp_vector2.toArray(this._tmp_array2)):t.value.toArray(this._tmp_array2):this.pv.vector2.toArray(this._tmp_array2),this._tmp_array2;case MO.VECTOR3:return await this._compute_params_if_dirty([this.p.increment,this.p.vector3]),this.pv.increment?t.type()==Cr.VECTOR3?(this._tmp_vector3.copy(t.value),this._tmp_vector3.add(this.pv.vector3),this._tmp_vector3.toArray(this._tmp_array3)):t.value.toArray(this._tmp_array3):this.pv.vector3.toArray(this._tmp_array3),this._tmp_array3;case MO.VECTOR4:return await this._compute_params_if_dirty([this.p.increment,this.p.vector4]),this.pv.increment?t.type()==Cr.VECTOR4?(this._tmp_vector4.copy(t.value),this._tmp_vector4.add(this.pv.vector4),this._tmp_vector4.toArray(this._tmp_array4)):t.value.toArray(this._tmp_array4):this.pv.vector4.toArray(this._tmp_array4),this._tmp_array4;case MO.STRING:return await this._compute_params_if_dirty([this.p.string]),this.pv.string}os.unreachable(e)}static PARAM_CALLBACK_execute(t){t.processEvent({})}async _compute_params_if_dirty(t){const e=[];for(let n of t)n.isDirty()&&e.push(n);const n=[];for(let t of e)n.push(t.compute());return await Promise.all(n)}}const DO=new class extends ua{constructor(){super(...arguments),this.outputsCount=ha.INTEGER(5,{range:[1,10],rangeLocked:[!0,!1]})}};class BO extends Va{constructor(){super(...arguments),this.paramsConfig=DO}static type(){return\\\\\\\"sequence\\\\\\\"}initializeNode(){this.io.connection_points.set_input_name_function((()=>\\\\\\\"trigger\\\\\\\")),this.io.connection_points.set_expected_input_types_function((()=>[Qo.BASE])),this.io.connection_points.set_expected_output_types_function(this._expected_output_types.bind(this)),this.io.connection_points.set_output_name_function(this._output_name.bind(this))}_expected_output_types(){const t=new Array(this.pv.outputsCount);return t.fill(Qo.BASE),t}_output_name(t){return`out${t}`}processEvent(t){const e=this.pv.outputsCount;for(let n=0;n{this._timer_active&&(this.pv.count<=0||this._current_count{var e;null===(e=t.controlsController)||void 0===e||e.create_controls()}))}_process_trigger_disposeControls(t){this.scene().viewersRegister.traverseViewers((t=>{var e;null===(e=t.controlsController)||void 0===e||e.dispose_controls()}))}}class HO extends aa{static context(){return ts.EVENT}cook(){this.cookController.endCook()}}class jO extends HO{}class WO extends jO{constructor(){super(...arguments),this._children_controller_context=ts.ANIM}static type(){return es.ANIM}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}}class qO extends jO{constructor(){super(...arguments),this._children_controller_context=ts.COP}static type(){return es.COP}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}}class XO extends jO{constructor(){super(...arguments),this._children_controller_context=ts.EVENT}static type(){return es.EVENT}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}}class YO extends jO{constructor(){super(...arguments),this._children_controller_context=ts.MAT}static type(){return es.MAT}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}}class $O extends HO{constructor(){super(...arguments),this.paramsConfig=new ef,this.effectsComposerController=new nf(this),this.displayNodeController=new Fm(this,this.effectsComposerController.displayNodeControllerCallbacks()),this._children_controller_context=ts.POST}static type(){return es.POST}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}}class JO extends jO{constructor(){super(...arguments),this._children_controller_context=ts.ROP}static type(){return es.ROP}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}}const ZO=\\\\\\\"int\\\\\\\";const KO=new class extends ua{constructor(){super(...arguments),this.float=ha.FLOAT(0)}};class QO extends gf{constructor(){super(...arguments),this.paramsConfig=KO}static type(){return\\\\\\\"floatToInt\\\\\\\"}initializeNode(){this.io.outputs.setNamedOutputConnectionPoints([new qo(ZO,Uo.INT)])}setLines(t){const e=this.variableForInputParam(this.p.float),n=`int ${this.glVarName(ZO)} = int(${mf.float(e)})`;t.addBodyLines(this,[n])}}const tP=\\\\\\\"float\\\\\\\";const eP=new class extends ua{constructor(){super(...arguments),this.int=ha.INTEGER(0)}};class nP extends gf{constructor(){super(...arguments),this.paramsConfig=eP}static type(){return\\\\\\\"intToFloat\\\\\\\"}initializeNode(){this.io.outputs.setNamedOutputConnectionPoints([new qo(tP,Uo.FLOAT)])}setLines(t){const e=this.variableForInputParam(this.p.int),n=`float ${this.glVarName(tP)} = float(${mf.integer(e)})`;t.addBodyLines(this,[n])}}const iP=\\\\\\\"bool\\\\\\\";const sP=new class extends ua{constructor(){super(...arguments),this.int=ha.INTEGER(0)}};class rP extends gf{constructor(){super(...arguments),this.paramsConfig=sP}static type(){return\\\\\\\"intToBool\\\\\\\"}initializeNode(){this.io.outputs.setNamedOutputConnectionPoints([new qo(iP,Uo.BOOL)])}setLines(t){const e=this.variableForInputParam(this.p.int),n=`bool ${this.glVarName(iP)} = bool(${mf.integer(e)})`;t.addBodyLines(this,[n])}}const oP=new class extends ua{constructor(){super(...arguments),this.bool=ha.BOOLEAN(0)}};class aP extends gf{constructor(){super(...arguments),this.paramsConfig=oP}static type(){return\\\\\\\"boolToInt\\\\\\\"}initializeNode(){this.io.outputs.setNamedOutputConnectionPoints([new qo(ZO,Uo.INT)])}setLines(t){const e=this.variableForInputParam(this.p.bool),n=`int ${this.glVarName(ZO)} = int(${mf.bool(e)})`;t.addBodyLines(this,[n])}}const lP=new class extends ua{constructor(){super(...arguments),this.x=ha.FLOAT(0),this.y=ha.FLOAT(0)}};class cP extends gf{constructor(){super(...arguments),this.paramsConfig=lP}static type(){return\\\\\\\"floatToVec2\\\\\\\"}initializeNode(){this.io.outputs.setNamedOutputConnectionPoints([new qo(cP.OUTPUT_NAME,Uo.VEC2)])}setLines(t){const e=this.variableForInputParam(this.p.x),n=this.variableForInputParam(this.p.y),i=`vec2 ${this.glVarName(cP.OUTPUT_NAME)} = ${mf.float2(e,n)}`;t.addBodyLines(this,[i])}}cP.OUTPUT_NAME=\\\\\\\"vec2\\\\\\\";const hP=new class extends ua{constructor(){super(...arguments),this.x=ha.FLOAT(0),this.y=ha.FLOAT(0),this.z=ha.FLOAT(0)}};class uP extends gf{constructor(){super(...arguments),this.paramsConfig=hP}static type(){return\\\\\\\"floatToVec3\\\\\\\"}initializeNode(){this.io.outputs.setNamedOutputConnectionPoints([new qo(uP.OUTPUT_NAME,Uo.VEC3)])}setLines(t){const e=this.variableForInputParam(this.p.x),n=this.variableForInputParam(this.p.y),i=this.variableForInputParam(this.p.z),s=`vec3 ${this.glVarName(uP.OUTPUT_NAME)} = ${mf.float3(e,n,i)}`;t.addBodyLines(this,[s])}}uP.OUTPUT_NAME=\\\\\\\"vec3\\\\\\\";const dP=new class extends ua{constructor(){super(...arguments),this.x=ha.FLOAT(0),this.y=ha.FLOAT(0),this.z=ha.FLOAT(0),this.w=ha.FLOAT(0)}};class pP extends gf{constructor(){super(...arguments),this.paramsConfig=dP}static type(){return\\\\\\\"floatToVec4\\\\\\\"}initializeNode(){this.io.outputs.setNamedOutputConnectionPoints([new qo(pP.OUTPUT_NAME,Uo.VEC4)])}setLines(t){const e=this.variableForInputParam(this.p.x),n=this.variableForInputParam(this.p.y),i=this.variableForInputParam(this.p.z),s=this.variableForInputParam(this.p.w),r=`vec4 ${this.glVarName(pP.OUTPUT_NAME)} = ${mf.float4(e,n,i,s)}`;t.addBodyLines(this,[r])}}pP.OUTPUT_NAME=\\\\\\\"vec4\\\\\\\";const _P=new class extends ua{};class mP extends gf{constructor(){super(...arguments),this.paramsConfig=_P}}function fP(t,e){const n=e.components,i=e.param_type;return class extends mP{static type(){return t}initializeNode(){this.io.outputs.setNamedOutputConnectionPoints(n.map((t=>new qo(t,Uo.FLOAT))))}createParams(){this.addParam(i,\\\\\\\"vec\\\\\\\",n.map((t=>0)))}setLines(t){const e=[],n=this.variableForInput(\\\\\\\"vec\\\\\\\");this.io.outputs.used_output_names().forEach((t=>{const i=this.glVarName(t);e.push(`float ${i} = ${n}.${t}`)})),t.addBodyLines(this,e)}}}const gP=[\\\\\\\"x\\\\\\\",\\\\\\\"y\\\\\\\"],vP=[\\\\\\\"x\\\\\\\",\\\\\\\"y\\\\\\\",\\\\\\\"z\\\\\\\"],yP=[\\\\\\\"x\\\\\\\",\\\\\\\"y\\\\\\\",\\\\\\\"z\\\\\\\",\\\\\\\"w\\\\\\\"];class xP extends(fP(\\\\\\\"vec2ToFloat\\\\\\\",{components:[\\\\\\\"x\\\\\\\",\\\\\\\"y\\\\\\\"],param_type:Cr.VECTOR2})){}class bP extends(fP(\\\\\\\"vec3ToFloat\\\\\\\",{components:[\\\\\\\"x\\\\\\\",\\\\\\\"y\\\\\\\",\\\\\\\"z\\\\\\\"],param_type:Cr.VECTOR3})){}class wP extends(fP(\\\\\\\"vec4ToFloat\\\\\\\",{components:yP,param_type:Cr.VECTOR4})){}class TP extends mP{static type(){return\\\\\\\"vec4ToVec3\\\\\\\"}initializeNode(){this.io.outputs.setNamedOutputConnectionPoints([new qo(TP.OUTPUT_NAME_VEC3,Uo.VEC3),new qo(TP.OUTPUT_NAME_W,Uo.FLOAT)])}createParams(){this.addParam(Cr.VECTOR4,TP.INPUT_NAME_VEC4,yP.map((t=>0)))}setLines(t){const e=[],n=TP.INPUT_NAME_VEC4,i=TP.OUTPUT_NAME_VEC3,s=TP.OUTPUT_NAME_W,r=this.variableForInput(n),o=this.io.outputs.used_output_names();if(o.indexOf(i)>=0){const t=this.glVarName(i);e.push(`vec3 ${t} = ${r}.xyz`)}if(o.indexOf(s)>=0){const t=this.glVarName(s);e.push(`float ${t} = ${r}.w`)}t.addBodyLines(this,e)}}TP.INPUT_NAME_VEC4=\\\\\\\"vec4\\\\\\\",TP.OUTPUT_NAME_VEC3=\\\\\\\"vec3\\\\\\\",TP.OUTPUT_NAME_W=\\\\\\\"w\\\\\\\";class AP extends mP{static type(){return\\\\\\\"vec3ToVec2\\\\\\\"}initializeNode(){this.io.outputs.setNamedOutputConnectionPoints([new qo(AP.OUTPUT_NAME_VEC2,Uo.VEC2),new qo(AP.OUTPUT_NAME_Z,Uo.FLOAT)])}createParams(){this.addParam(Cr.VECTOR3,AP.INPUT_NAME_VEC3,vP.map((t=>0)))}setLines(t){const e=[],n=AP.INPUT_NAME_VEC3,i=AP.OUTPUT_NAME_VEC2,s=AP.OUTPUT_NAME_Z,r=this.variableForInput(n),o=this.io.outputs.used_output_names();if(o.indexOf(i)>=0){const t=this.glVarName(i);e.push(`vec2 ${t} = ${r}.xy`)}if(o.indexOf(s)>=0){const t=this.glVarName(s);e.push(`float ${t} = ${r}.z`)}t.addBodyLines(this,e)}}AP.INPUT_NAME_VEC3=\\\\\\\"vec3\\\\\\\",AP.OUTPUT_NAME_VEC2=\\\\\\\"vec2\\\\\\\",AP.OUTPUT_NAME_Z=\\\\\\\"z\\\\\\\";class MP extends mP{static type(){return\\\\\\\"vec2ToVec3\\\\\\\"}initializeNode(){this.io.outputs.setNamedOutputConnectionPoints([new qo(MP.OUTPUT_NAME_VEC3,Uo.VEC3)])}createParams(){this.addParam(Cr.VECTOR2,MP.INPUT_NAME_VEC2,gP.map((t=>0))),this.addParam(Cr.FLOAT,MP.INPUT_NAME_Z,0)}setLines(t){const e=[],n=MP.INPUT_NAME_VEC2,i=MP.INPUT_NAME_Z,s=MP.OUTPUT_NAME_VEC3,r=this.variableForInput(n),o=this.variableForInput(i),a=this.glVarName(s);e.push(`vec3 ${a} = vec3(${r}.xy, ${o})`),t.addBodyLines(this,e)}}MP.INPUT_NAME_VEC2=\\\\\\\"vec3\\\\\\\",MP.INPUT_NAME_Z=\\\\\\\"z\\\\\\\",MP.OUTPUT_NAME_VEC3=\\\\\\\"vec3\\\\\\\";class EP extends mP{static type(){return\\\\\\\"vec3ToVec4\\\\\\\"}initializeNode(){this.io.outputs.setNamedOutputConnectionPoints([new qo(EP.OUTPUT_NAME_VEC4,Uo.VEC4)])}createParams(){this.addParam(Cr.VECTOR3,EP.INPUT_NAME_VEC3,vP.map((t=>0))),this.addParam(Cr.FLOAT,EP.INPUT_NAME_W,0)}setLines(t){const e=[],n=EP.INPUT_NAME_VEC3,i=EP.INPUT_NAME_W,s=EP.OUTPUT_NAME_VEC4,r=this.variableForInput(n),o=this.variableForInput(i),a=this.glVarName(s);e.push(`vec4 ${a} = vec4(${r}.xyz, ${o})`),t.addBodyLines(this,e)}}EP.INPUT_NAME_VEC3=\\\\\\\"vec3\\\\\\\",EP.INPUT_NAME_W=\\\\\\\"w\\\\\\\",EP.OUTPUT_NAME_VEC4=\\\\\\\"vec4\\\\\\\";const SP=new class extends ua{};class CP extends gf{constructor(){super(...arguments),this.paramsConfig=SP}gl_method_name(){return\\\\\\\"\\\\\\\"}gl_function_definitions(){return[]}initializeNode(){super.initializeNode(),this.io.connection_points.set_expected_input_types_function(this._expected_input_types.bind(this)),this.io.connection_points.set_expected_output_types_function(this._expected_output_types.bind(this)),this.io.connection_points.set_input_name_function(this._gl_input_name.bind(this))}_expected_input_types(){const t=this.io.connection_points.first_input_connection_type()||Uo.FLOAT;if(this.io.connections.firstInputConnection()){const e=this.io.connections.inputConnections();if(e){let n=Math.max(f.compact(e).length+1,2);return f.range(n).map((e=>t))}return[]}return f.range(2).map((e=>t))}_expected_output_types(){return[this._expected_input_types()[0]]}_gl_input_name(t){return\\\\\\\"in\\\\\\\"}setLines(t){const e=this.io.outputs.namedOutputConnectionPoints()[0].type(),n=this.io.inputs.namedInputConnectionPoints().map(((t,e)=>{const n=t.name();return mf.any(this.variableForInput(n))})).join(\\\\\\\", \\\\\\\"),i=`${e} ${this.glVarName(this.io.connection_points.output_name(0))} = ${this.gl_method_name()}(${n})`;t.addBodyLines(this,[i]),t.addDefinitions(this,this.gl_function_definitions())}}class NP extends CP{_gl_input_name(t){return\\\\\\\"in\\\\\\\"}_expected_input_types(){return[this.io.connection_points.first_input_connection_type()||Uo.FLOAT]}}class LP extends CP{_expected_input_types(){const t=this.io.connection_points.first_input_connection_type()||Uo.FLOAT;return[t,t]}}class OP extends CP{_expected_input_types(){const t=this.io.connection_points.first_input_connection_type()||Uo.FLOAT;return[t,t,t]}}class PP extends CP{_expected_input_types(){const t=this.io.connection_points.first_input_connection_type()||Uo.FLOAT;return[t,t,t,t]}}class RP extends CP{_expected_input_types(){const t=this.io.connection_points.first_input_connection_type()||Uo.FLOAT;return[t,t,t,t,t]}}function IP(t,e={}){const n=e.method||t,i=e.out||\\\\\\\"val\\\\\\\",s=e.in||\\\\\\\"in\\\\\\\";return class extends NP{static type(){return t}initializeNode(){super.initializeNode(),this.io.connection_points.set_input_name_function(this._gl_input_name.bind(this)),this.io.connection_points.set_output_name_function(this._gl_output_name.bind(this))}_gl_input_name(t){return s}_gl_output_name(t){return i}gl_method_name(){return n}}}class FP extends(IP(\\\\\\\"abs\\\\\\\")){}class DP extends(IP(\\\\\\\"acos\\\\\\\",{out:\\\\\\\"radians\\\\\\\"})){}class BP extends(IP(\\\\\\\"asin\\\\\\\",{out:\\\\\\\"radians\\\\\\\"})){}class zP extends(IP(\\\\\\\"atan\\\\\\\",{out:\\\\\\\"radians\\\\\\\"})){}class kP extends(IP(\\\\\\\"ceil\\\\\\\")){}class UP extends(IP(\\\\\\\"cos\\\\\\\",{in:\\\\\\\"radians\\\\\\\"})){}class GP extends(IP(\\\\\\\"degrees\\\\\\\",{in:\\\\\\\"radians\\\\\\\",out:\\\\\\\"degrees\\\\\\\"})){}class VP extends(IP(\\\\\\\"exp\\\\\\\")){}class HP extends(IP(\\\\\\\"exp2\\\\\\\")){}class jP extends(IP(\\\\\\\"floor\\\\\\\")){}class WP extends(IP(\\\\\\\"fract\\\\\\\")){}class qP extends(IP(\\\\\\\"inverseSqrt\\\\\\\",{method:\\\\\\\"inversesqrt\\\\\\\"})){}class XP extends(IP(\\\\\\\"log\\\\\\\")){}class YP extends(IP(\\\\\\\"log2\\\\\\\")){}class $P extends(IP(\\\\\\\"normalize\\\\\\\",{out:\\\\\\\"normalized\\\\\\\"})){}class JP extends(IP(\\\\\\\"radians\\\\\\\",{in:\\\\\\\"degrees\\\\\\\",out:\\\\\\\"radians\\\\\\\"})){}class ZP extends(IP(\\\\\\\"sign\\\\\\\")){}class KP extends(IP(\\\\\\\"sin\\\\\\\",{in:\\\\\\\"radians\\\\\\\"})){}class QP extends(IP(\\\\\\\"sqrt\\\\\\\")){}class tR extends(IP(\\\\\\\"tan\\\\\\\")){}function eR(t,e={}){const n=e.method||t,i=e.out||\\\\\\\"val\\\\\\\",s=e.in||[\\\\\\\"in0\\\\\\\",\\\\\\\"in1\\\\\\\"],r=e.default_in_type,o=e.allowed_in_types,a=e.out_type,l=e.functions||[];return class extends LP{static type(){return t}initializeNode(){super.initializeNode(),this.io.connection_points.set_input_name_function(this._gl_input_name.bind(this)),this.io.connection_points.set_output_name_function(this._gl_output_name.bind(this)),this.io.connection_points.set_expected_input_types_function(this._expected_input_types.bind(this)),a&&this.io.connection_points.set_expected_output_types_function((()=>[a]))}_gl_input_name(t){return s[t]}_gl_output_name(t){return i}gl_method_name(){return n}gl_function_definitions(){return l?l.map((t=>new Cf(this,t))):[]}_expected_input_types(){let t=this.io.connection_points.first_input_connection_type();if(t&&o&&!o.includes(t)){const e=this.io.inputs.namedInputConnectionPoints()[0];t=e?e.type():r}const e=t||r||Uo.FLOAT;return[e,e]}}}class nR extends(eR(\\\\\\\"distance\\\\\\\",{in:[\\\\\\\"p0\\\\\\\",\\\\\\\"p1\\\\\\\"],default_in_type:Uo.VEC3,allowed_in_types:[Uo.VEC2,Uo.VEC3,Uo.VEC4],out_type:Uo.FLOAT})){}class iR extends(eR(\\\\\\\"dot\\\\\\\",{in:[\\\\\\\"vec0\\\\\\\",\\\\\\\"vec1\\\\\\\"],default_in_type:Uo.VEC3,allowed_in_types:[Uo.VEC2,Uo.VEC3,Uo.VEC4],out_type:Uo.FLOAT})){}class sR extends(eR(\\\\\\\"max\\\\\\\")){}class rR extends(eR(\\\\\\\"min\\\\\\\")){}class oR extends(eR(\\\\\\\"mod\\\\\\\")){paramDefaultValue(t){return{in1:1}[t]}_expected_input_types(){const t=Uo.FLOAT;return[t,t]}}class aR extends(eR(\\\\\\\"pow\\\\\\\",{in:[\\\\\\\"x\\\\\\\",\\\\\\\"y\\\\\\\"]})){}class lR extends(eR(\\\\\\\"reflect\\\\\\\",{in:[\\\\\\\"I\\\\\\\",\\\\\\\"N\\\\\\\"],default_in_type:Uo.VEC3})){}class cR extends(eR(\\\\\\\"step\\\\\\\",{in:[\\\\\\\"edge\\\\\\\",\\\\\\\"x\\\\\\\"]})){}function hR(t,e={}){const n=e.method||t,i=e.out||\\\\\\\"val\\\\\\\",s=e.in||[\\\\\\\"in0\\\\\\\",\\\\\\\"in1\\\\\\\",\\\\\\\"in2\\\\\\\"],r=e.default||{},o=e.out_type||Uo.FLOAT,a=e.functions||[];return class extends OP{static type(){return t}initializeNode(){super.initializeNode(),this.io.connection_points.set_input_name_function(this._gl_input_name.bind(this)),this.io.connection_points.set_output_name_function(this._gl_output_name.bind(this)),this.io.connection_points.set_expected_output_types_function(this._expected_output_types.bind(this))}_gl_input_name(t){return s[t]}_gl_output_name(t){return i}gl_method_name(){return n}_expected_output_types(){return[o]}paramDefaultValue(t){return r[t]}gl_function_definitions(){return a.map((t=>new Cf(this,t)))}}}class uR extends(hR(\\\\\\\"clamp\\\\\\\",{in:[\\\\\\\"value\\\\\\\",\\\\\\\"min\\\\\\\",\\\\\\\"max\\\\\\\"],default:{max:1}})){_expected_output_types(){return[this._expected_input_types()[0]]}}class dR extends(hR(\\\\\\\"faceForward\\\\\\\",{in:[\\\\\\\"N\\\\\\\",\\\\\\\"I\\\\\\\",\\\\\\\"Nref\\\\\\\"]})){}class pR extends(hR(\\\\\\\"smoothstep\\\\\\\",{in:[\\\\\\\"edge0\\\\\\\",\\\\\\\"edge1\\\\\\\",\\\\\\\"x\\\\\\\"],default:{edge1:1}})){_expected_output_types(){return[this._expected_input_types()[0]]}}function _R(t,e){const n=e.in_prefix||t,i=e.out||\\\\\\\"val\\\\\\\",s=e.operation,r=e.allowed_in_types;return class extends LP{static type(){return t}initializeNode(){super.initializeNode(),this.io.connection_points.set_input_name_function(this._gl_input_name.bind(this)),this.io.connection_points.set_output_name_function(this._gl_output_name.bind(this)),this.io.connection_points.set_expected_input_types_function(this._expected_input_types.bind(this)),this.io.connection_points.set_expected_output_types_function(this._expected_output_types.bind(this))}setLines(t){const e=this.io.outputs.namedOutputConnectionPoints()[0].type(),n=this.io.inputs.namedInputConnectionPoints().map(((t,e)=>{const n=t.name(),i=this.variableForInput(n);if(i)return mf.any(i)})).join(` ${this.gl_operation()} `),i=`${e} ${this.glVarName(this.io.connection_points.output_name(0))} = ${this.gl_method_name()}(${n})`;t.addBodyLines(this,[i])}_gl_input_name(t){return`${n}${t}`}_gl_output_name(t){return i}gl_operation(){return s}_expected_input_types(){let t=this.io.connection_points.first_input_connection_type();if(t&&r&&!r.includes(t)){const e=this.io.inputs.namedInputConnectionPoints()[0];e&&(t=e.type())}const e=t||Uo.FLOAT,n=this.io.connections.existingInputConnections(),i=n?Math.max(n.length+1,2):2,s=[];for(let t=0;t{const n=t.name();return mf.any(this.variableForInput(n))})).join(` ${this.boolean_operation()} `),n=`bool ${this.glVarName(this.io.connection_points.output_name(0))} = ${e}`;t.addBodyLines(this,[n])}}function xR(t,e){return class extends yR{static type(){return t}initializeNode(){super.initializeNode(),this.io.connection_points.set_input_name_function(this._gl_input_name.bind(this)),this.io.connection_points.set_output_name_function(this._gl_output_name.bind(this))}boolean_operation(){return e.op}_gl_output_name(e){return t}_gl_input_name(e=0){return`${t}${e}`}}}class bR extends(xR(\\\\\\\"and\\\\\\\",{op:\\\\\\\"&&\\\\\\\"})){}class wR extends(xR(\\\\\\\"or\\\\\\\",{op:\\\\\\\"||\\\\\\\"})){}var TR;!function(t){t.TIME=\\\\\\\"time\\\\\\\",t.DELTA_TIME=\\\\\\\"delta_time\\\\\\\"}(TR||(TR={}));var AR,MR;!function(t){t.POSITION=\\\\\\\"position\\\\\\\",t.VELOCITY=\\\\\\\"velocity\\\\\\\",t.MASS=\\\\\\\"mass\\\\\\\",t.FORCE=\\\\\\\"force\\\\\\\"}(AR||(AR={})),function(t){t.POSITION=\\\\\\\"position\\\\\\\",t.VELOCITY=\\\\\\\"velocity\\\\\\\"}(MR||(MR={}));const ER=[AR.POSITION,AR.VELOCITY,AR.MASS,AR.FORCE],SR=[MR.POSITION,MR.VELOCITY],CR={[AR.POSITION]:[0,0,0],[AR.VELOCITY]:[0,0,0],[AR.MASS]:1,[AR.FORCE]:[0,-9.8,0]};const NR=new class extends ua{};class LR extends gf{constructor(){super(...arguments),this.paramsConfig=NR}static type(){return\\\\\\\"acceleration\\\\\\\"}initializeNode(){super.initializeNode(),this.io.outputs.setNamedOutputConnectionPoints([new qo(MR.POSITION,Uo.VEC3),new qo(MR.VELOCITY,Uo.VEC3)]),this.io.connection_points.set_expected_input_types_function(this._expected_input_types.bind(this)),this.io.connection_points.set_expected_output_types_function(this._expected_output_types.bind(this)),this.io.connection_points.set_input_name_function(this._gl_input_name.bind(this)),this.io.connection_points.set_output_name_function(this._gl_output_name.bind(this))}_expected_input_types(){const t=this.io.connection_points.first_input_connection_type()||Uo.VEC3;return[t,t,Uo.FLOAT,t]}_expected_output_types(){const t=this._expected_input_types()[0];return[t,t]}_gl_input_name(t){return ER[t]}_gl_output_name(t){return SR[t]}paramDefaultValue(t){return CR[t]}setLines(t){const e=this.io.outputs.namedOutputConnectionPoints()[0].type(),n=new Nf(this,Uo.FLOAT,TR.DELTA_TIME),i=new Cf(this,\\\\\\\"float compute_velocity_from_acceleration(float vel, float force, float mass, float time_delta){\\\\n\\\\tfloat impulse = (force * mass) * time_delta;\\\\n\\\\treturn vel + impulse;\\\\n}\\\\nvec2 compute_velocity_from_acceleration(vec2 vel, vec2 force, float mass, float time_delta){\\\\n\\\\tvec2 impulse = (force * mass) * time_delta;\\\\n\\\\treturn vel + impulse;\\\\n}\\\\nvec3 compute_velocity_from_acceleration(vec3 vel, vec3 force, float mass, float time_delta){\\\\n\\\\tvec3 impulse = (force * mass) * time_delta;\\\\n\\\\treturn vel + impulse;\\\\n}\\\\nvec4 compute_velocity_from_acceleration(vec4 vel, vec4 force, float mass, float time_delta){\\\\n\\\\tvec4 impulse = (force * mass) * time_delta;\\\\n\\\\treturn vel + impulse;\\\\n}\\\\nfloat compute_position_from_velocity(float position, float velocity, float time_delta){\\\\n\\\\treturn position + (velocity * time_delta);\\\\n}\\\\nvec2 compute_position_from_velocity(vec2 position, vec2 velocity, float time_delta){\\\\n\\\\treturn position + (velocity * time_delta);\\\\n}\\\\nvec3 compute_position_from_velocity(vec3 position, vec3 velocity, float time_delta){\\\\n\\\\treturn position + (velocity * time_delta);\\\\n}\\\\nvec4 compute_position_from_velocity(vec4 position, vec4 velocity, float time_delta){\\\\n\\\\treturn position + (velocity * time_delta);\\\\n}\\\\\\\");t.addDefinitions(this,[n,i]);const s=mf.any(this.variableForInput(AR.POSITION)),r=mf.any(this.variableForInput(AR.VELOCITY)),o=mf.float(this.variableForInput(AR.MASS)),a=mf.any(this.variableForInput(AR.FORCE)),l=this.glVarName(MR.POSITION),c=this.glVarName(MR.VELOCITY),h=`${e} ${c} = compute_velocity_from_acceleration(${[r,a,o,TR.DELTA_TIME].join(\\\\\\\", \\\\\\\")})`,u=`${e} ${l} = compute_position_from_velocity(${[s,c,TR.DELTA_TIME].join(\\\\\\\", \\\\\\\")})`;t.addBodyLines(this,[h,u])}}var OR,PR=\\\\\\\"\\\\n\\\\n// https://github.com/mattatz/ShibuyaCrowd/blob/master/source/shaders/common/quaternion.glsl\\\\nvec4 quatMult(vec4 q1, vec4 q2)\\\\n{\\\\n\\\\treturn vec4(\\\\n\\\\tq1.w * q2.x + q1.x * q2.w + q1.z * q2.y - q1.y * q2.z,\\\\n\\\\tq1.w * q2.y + q1.y * q2.w + q1.x * q2.z - q1.z * q2.x,\\\\n\\\\tq1.w * q2.z + q1.z * q2.w + q1.y * q2.x - q1.x * q2.y,\\\\n\\\\tq1.w * q2.w - q1.x * q2.x - q1.y * q2.y - q1.z * q2.z\\\\n\\\\t);\\\\n}\\\\n// http://glmatrix.net/docs/quat.js.html#line97\\\\n// let ax = a[0], ay = a[1], az = a[2], aw = a[3];\\\\n\\\\n// let bx = b[0], by = b[1], bz = b[2], bw = b[3];\\\\n\\\\n// out[0] = ax * bw + aw * bx + ay * bz - az * by;\\\\n\\\\n// out[1] = ay * bw + aw * by + az * bx - ax * bz;\\\\n\\\\n// out[2] = az * bw + aw * bz + ax * by - ay * bx;\\\\n\\\\n// out[3] = aw * bw - ax * bx - ay * by - az * bz;\\\\n\\\\n// return out\\\\n\\\\n\\\\n\\\\n// http://www.neilmendoza.com/glsl-rotation-about-an-arbitrary-axis/\\\\nmat4 rotationMatrix(vec3 axis, float angle)\\\\n{\\\\n\\\\taxis = normalize(axis);\\\\n\\\\tfloat s = sin(angle);\\\\n\\\\tfloat c = cos(angle);\\\\n\\\\tfloat oc = 1.0 - c;\\\\n\\\\n \\\\treturn mat4(oc * axis.x * axis.x + c, oc * axis.x * axis.y - axis.z * s, oc * axis.z * axis.x + axis.y * s, 0.0, oc * axis.x * axis.y + axis.z * s, oc * axis.y * axis.y + c, oc * axis.y * axis.z - axis.x * s, 0.0, oc * axis.z * axis.x - axis.y * s, oc * axis.y * axis.z + axis.x * s, oc * axis.z * axis.z + c, 0.0, 0.0, 0.0, 0.0, 1.0);\\\\n}\\\\n\\\\n// https://www.geeks3d.com/20141201/how-to-rotate-a-vertex-by-a-quaternion-in-glsl/\\\\nvec4 quatFromAxisAngle(vec3 axis, float angle)\\\\n{\\\\n\\\\tvec4 qr;\\\\n\\\\tfloat half_angle = (angle * 0.5); // * 3.14159 / 180.0;\\\\n\\\\tfloat sin_half_angle = sin(half_angle);\\\\n\\\\tqr.x = axis.x * sin_half_angle;\\\\n\\\\tqr.y = axis.y * sin_half_angle;\\\\n\\\\tqr.z = axis.z * sin_half_angle;\\\\n\\\\tqr.w = cos(half_angle);\\\\n\\\\treturn qr;\\\\n}\\\\nvec3 rotateWithAxisAngle(vec3 position, vec3 axis, float angle)\\\\n{\\\\n\\\\tvec4 q = quatFromAxisAngle(axis, angle);\\\\n\\\\tvec3 v = position.xyz;\\\\n\\\\treturn v + 2.0 * cross(q.xyz, cross(q.xyz, v) + q.w * v);\\\\n}\\\\n// vec3 applyQuaternionToVector( vec4 q, vec3 v ){\\\\n// \\\\treturn v + 2.0 * cross( q.xyz, cross( q.xyz, v ) + q.w * v );\\\\n// }\\\\nvec3 rotateWithQuat( vec3 v, vec4 q )\\\\n{\\\\n\\\\t// vec4 qv = multQuat( quat, vec4(vec, 0.0) );\\\\n\\\\t// return multQuat( qv, vec4(-quat.x, -quat.y, -quat.z, quat.w) ).xyz;\\\\n\\\\treturn v + 2.0 * cross( q.xyz, cross( q.xyz, v ) + q.w * v );\\\\n}\\\\n// https://github.com/glslify/glsl-look-at/blob/gh-pages/index.glsl\\\\n// mat3 rotation_matrix(vec3 origin, vec3 target, float roll) {\\\\n// \\\\tvec3 rr = vec3(sin(roll), cos(roll), 0.0);\\\\n// \\\\tvec3 ww = normalize(target - origin);\\\\n// \\\\tvec3 uu = normalize(cross(ww, rr));\\\\n// \\\\tvec3 vv = normalize(cross(uu, ww));\\\\n\\\\n// \\\\treturn mat3(uu, vv, ww);\\\\n// }\\\\n// mat3 rotation_matrix(vec3 target, float roll) {\\\\n// \\\\tvec3 rr = vec3(sin(roll), cos(roll), 0.0);\\\\n// \\\\tvec3 ww = normalize(target);\\\\n// \\\\tvec3 uu = normalize(cross(ww, rr));\\\\n// \\\\tvec3 vv = normalize(cross(uu, ww));\\\\n\\\\n// \\\\treturn mat3(uu, vv, ww);\\\\n// }\\\\n\\\\nfloat vectorAngle(vec3 start, vec3 dest){\\\\n\\\\tstart = normalize(start);\\\\n\\\\tdest = normalize(dest);\\\\n\\\\n\\\\tfloat cosTheta = dot(start, dest);\\\\n\\\\tvec3 c1 = cross(start, dest);\\\\n\\\\t// We use the dot product of the cross with the Y axis.\\\\n\\\\t// This is a little arbitrary, but can still give a good sense of direction\\\\n\\\\tvec3 y_axis = vec3(0.0, 1.0, 0.0);\\\\n\\\\tfloat d1 = dot(c1, y_axis);\\\\n\\\\tfloat angle = acos(cosTheta) * sign(d1);\\\\n\\\\treturn angle;\\\\n}\\\\n\\\\n// http://www.opengl-tutorial.org/intermediate-tutorials/tutorial-17-quaternions/#i-need-an-equivalent-of-glulookat-how-do-i-orient-an-object-towards-a-point-\\\\nvec4 vectorAlign(vec3 start, vec3 dest){\\\\n\\\\tstart = normalize(start);\\\\n\\\\tdest = normalize(dest);\\\\n\\\\n\\\\tfloat cosTheta = dot(start, dest);\\\\n\\\\tvec3 axis;\\\\n\\\\n\\\\t// if (cosTheta < -1 + 0.001f){\\\\n\\\\t// \\\\t// special case when vectors in opposite directions:\\\\n\\\\t// \\\\t// there is no ideal rotation axis\\\\n\\\\t// \\\\t// So guess one; any will do as long as it's perpendicular to start\\\\n\\\\t// \\\\taxis = cross(vec3(0.0f, 0.0f, 1.0f), start);\\\\n\\\\t// \\\\tif (length2(axis) < 0.01 ) // bad luck, they were parallel, try again!\\\\n\\\\t// \\\\t\\\\taxis = cross(vec3(1.0f, 0.0f, 0.0f), start);\\\\n\\\\n\\\\t// \\\\taxis = normalize(axis);\\\\n\\\\t// \\\\treturn gtx::quaternion::angleAxis(glm::radians(180.0f), axis);\\\\n\\\\t// }\\\\n\\\\tif(cosTheta > (1.0 - 0.0001) || cosTheta < (-1.0 + 0.0001) ){\\\\n\\\\t\\\\taxis = normalize(cross(start, vec3(0.0, 1.0, 0.0)));\\\\n\\\\t\\\\tif (length(axis) < 0.001 ){ // bad luck, they were parallel, try again!\\\\n\\\\t\\\\t\\\\taxis = normalize(cross(start, vec3(1.0, 0.0, 0.0)));\\\\n\\\\t\\\\t}\\\\n\\\\t} else {\\\\n\\\\t\\\\taxis = normalize(cross(start, dest));\\\\n\\\\t}\\\\n\\\\n\\\\tfloat angle = acos(cosTheta);\\\\n\\\\n\\\\treturn quatFromAxisAngle(axis, angle);\\\\n}\\\\nvec4 vectorAlignWithUp(vec3 start, vec3 dest, vec3 up){\\\\n\\\\tvec4 rot1 = vectorAlign(start, dest);\\\\n\\\\tup = normalize(up);\\\\n\\\\n\\\\t// Recompute desiredUp so that it's perpendicular to the direction\\\\n\\\\t// You can skip that part if you really want to force desiredUp\\\\n\\\\t// vec3 right = normalize(cross(dest, up));\\\\n\\\\t// up = normalize(cross(right, dest));\\\\n\\\\n\\\\t// Because of the 1rst rotation, the up is probably completely screwed up.\\\\n\\\\t// Find the rotation between the up of the rotated object, and the desired up\\\\n\\\\tvec3 newUp = rotateWithQuat(vec3(0.0, 1.0, 0.0), rot1);//rot1 * vec3(0.0, 1.0, 0.0);\\\\n\\\\tvec4 rot2 = vectorAlign(up, newUp);\\\\n\\\\n\\\\t// return rot1;\\\\n\\\\treturn rot2;\\\\n\\\\t// return multQuat(rot1, rot2);\\\\n\\\\t// return rot2 * rot1;\\\\n\\\\n}\\\\n\\\\n// https://www.euclideanspace.com/maths/geometry/rotations/conversions/quaternionToAngle/index.htm\\\\nfloat quatToAngle(vec4 q){\\\\n\\\\treturn 2.0 * acos(q.w);\\\\n}\\\\nvec3 quatToAxis(vec4 q){\\\\n\\\\treturn vec3(\\\\n\\\\t\\\\tq.x / sqrt(1.0-q.w*q.w),\\\\n\\\\t\\\\tq.y / sqrt(1.0-q.w*q.w),\\\\n\\\\t\\\\tq.z / sqrt(1.0-q.w*q.w)\\\\n\\\\t);\\\\n}\\\\n\\\\nvec4 align(vec3 dir, vec3 up){\\\\n\\\\tvec3 start_dir = vec3(0.0, 0.0, 1.0);\\\\n\\\\tvec3 start_up = vec3(0.0, 1.0, 0.0);\\\\n\\\\tvec4 rot1 = vectorAlign(start_dir, dir);\\\\n\\\\tup = normalize(up);\\\\n\\\\n\\\\t// Recompute desiredUp so that it's perpendicular to the direction\\\\n\\\\t// You can skip that part if you really want to force desiredUp\\\\n\\\\tvec3 right = normalize(cross(dir, up));\\\\n\\\\tif(length(right)<0.001){\\\\n\\\\t\\\\tright = vec3(1.0, 0.0, 0.0);\\\\n\\\\t}\\\\n\\\\tup = normalize(cross(right, dir));\\\\n\\\\n\\\\t// Because of the 1rst rotation, the up is probably completely screwed up.\\\\n\\\\t// Find the rotation between the up of the rotated object, and the desired up\\\\n\\\\tvec3 newUp = rotateWithQuat(start_up, rot1);//rot1 * vec3(0.0, 1.0, 0.0);\\\\n\\\\tvec4 rot2 = vectorAlign(normalize(newUp), up);\\\\n\\\\n\\\\t// return rot1;\\\\n\\\\treturn quatMult(rot1, rot2);\\\\n\\\\t// return rot2 * rot1;\\\\n\\\\n}\\\\\\\";!function(t){t.DIR=\\\\\\\"dir\\\\\\\",t.UP=\\\\\\\"up\\\\\\\"}(OR||(OR={}));const RR=[OR.DIR,OR.UP],IR={[OR.DIR]:[0,0,1],[OR.UP]:[0,1,0]};class FR extends LP{static type(){return\\\\\\\"align\\\\\\\"}initializeNode(){super.initializeNode(),this.io.connection_points.set_input_name_function((t=>RR[t])),this.io.connection_points.set_expected_input_types_function((()=>[Uo.VEC3,Uo.VEC3])),this.io.connection_points.set_expected_output_types_function((()=>[Uo.VEC4]))}paramDefaultValue(t){return IR[t]}gl_method_name(){return\\\\\\\"align\\\\\\\"}gl_function_definitions(){return[new Cf(this,PR)]}}var DR;!function(t){t.LINEAR=\\\\\\\"Linear\\\\\\\",t.GAMMA=\\\\\\\"Gamma\\\\\\\",t.SRGB=\\\\\\\"sRGB\\\\\\\",t.RGBE=\\\\\\\"RGBE\\\\\\\",t.RGBM=\\\\\\\"RGBM\\\\\\\",t.RGBD=\\\\\\\"RGBD\\\\\\\",t.LogLuv=\\\\\\\"LogLuv\\\\\\\"}(DR||(DR={}));const BR=[DR.LINEAR,DR.GAMMA,DR.SRGB,DR.RGBE,DR.RGBM,DR.RGBD,DR.LogLuv];const zR=new class extends ua{constructor(){super(...arguments),this.color=ha.VECTOR4([1,1,1,1]),this.from=ha.INTEGER(BR.indexOf(DR.LINEAR),{menu:{entries:BR.map(((t,e)=>({name:t,value:e})))}}),this.to=ha.INTEGER(BR.indexOf(DR.GAMMA),{menu:{entries:BR.map(((t,e)=>({name:t,value:e})))}}),this.gammaFactor=ha.FLOAT(2.2)}};class kR extends gf{constructor(){super(...arguments),this.paramsConfig=zR}static type(){return\\\\\\\"colorCorrect\\\\\\\"}initializeNode(){this.io.connection_points.spare_params.set_inputless_param_names([\\\\\\\"to\\\\\\\",\\\\\\\"from\\\\\\\"]),this.io.outputs.setNamedOutputConnectionPoints([new qo(kR.OUTPUT_NAME,Uo.VEC4)])}setLines(t){const e=BR[this.pv.from],n=BR[this.pv.to],i=this.glVarName(kR.OUTPUT_NAME),s=mf.any(this.variableForInput(kR.INPUT_NAME)),r=[];if(e!=n){const t=`${e}To${n}`,o=[];if(o.push(s),e==DR.GAMMA||n==DR.GAMMA){const t=mf.any(this.variableForInputParam(this.p.gammaFactor));o.push(t)}r.push(`vec4 ${i} = ${t}(${o.join(\\\\\\\", \\\\\\\")})`)}else r.push(`vec4 ${i} = ${s}`);t.addBodyLines(this,r)}}var UR,GR;kR.INPUT_NAME=\\\\\\\"color\\\\\\\",kR.INPUT_GAMMA_FACTOR=\\\\\\\"gammaFactor\\\\\\\",kR.OUTPUT_NAME=\\\\\\\"out\\\\\\\",function(t){t.EQUAL=\\\\\\\"Equal\\\\\\\",t.LESS_THAN=\\\\\\\"Less Than\\\\\\\",t.GREATER_THAN=\\\\\\\"Greater Than\\\\\\\",t.LESS_THAN_OR_EQUAL=\\\\\\\"Less Than Or Equal\\\\\\\",t.GREATER_THAN_OR_EQUAL=\\\\\\\"Greater Than Or Equal\\\\\\\",t.NOT_EQUAL=\\\\\\\"Not Equal\\\\\\\"}(UR||(UR={})),function(t){t.EQUAL=\\\\\\\"==\\\\\\\",t.LESS_THAN=\\\\\\\"<\\\\\\\",t.GREATER_THAN=\\\\\\\">\\\\\\\",t.LESS_THAN_OR_EQUAL=\\\\\\\"<=\\\\\\\",t.GREATER_THAN_OR_EQUAL=\\\\\\\">=\\\\\\\",t.NOT_EQUAL=\\\\\\\"!=\\\\\\\"}(GR||(GR={}));const VR=[UR.EQUAL,UR.LESS_THAN,UR.GREATER_THAN,UR.LESS_THAN_OR_EQUAL,UR.GREATER_THAN_OR_EQUAL,UR.NOT_EQUAL],HR=[GR.EQUAL,GR.LESS_THAN,GR.GREATER_THAN,GR.LESS_THAN_OR_EQUAL,GR.GREATER_THAN_OR_EQUAL,GR.NOT_EQUAL],jR=[\\\\\\\"x\\\\\\\",\\\\\\\"y\\\\\\\",\\\\\\\"z\\\\\\\",\\\\\\\"w\\\\\\\"];const WR=new class extends ua{constructor(){super(...arguments),this.test=ha.INTEGER(0,{menu:{entries:VR.map(((t,e)=>({name:`${HR[e].padEnd(2,\\\\\\\" \\\\\\\")} (${t})`,value:e})))}})}};class qR extends gf{constructor(){super(...arguments),this.paramsConfig=WR}static type(){return\\\\\\\"compare\\\\\\\"}initializeNode(){super.initializeNode(),this.io.connection_points.spare_params.set_inputless_param_names([\\\\\\\"test\\\\\\\"]),this.io.connection_points.initializeNode(),this.io.connection_points.set_input_name_function(this._gl_input_name.bind(this)),this.io.connection_points.set_output_name_function((t=>\\\\\\\"val\\\\\\\")),this.io.connection_points.set_expected_input_types_function(this._expected_input_type.bind(this)),this.io.connection_points.set_expected_output_types_function((()=>[Uo.BOOL]))}set_test_name(t){this.p.test.set(VR.indexOf(t))}_gl_input_name(t){return[\\\\\\\"value0\\\\\\\",\\\\\\\"value1\\\\\\\"][t]}_expected_input_type(){const t=this.io.connection_points.first_input_connection_type()||Uo.FLOAT;return[t,t]}setLines(t){const e=[],n=this.glVarName(\\\\\\\"val\\\\\\\"),i=HR[this.pv.test],s=mf.any(this.variableForInput(this._gl_input_name(0))),r=mf.any(this.variableForInput(this._gl_input_name(1))),o=this.io.inputs.namedInputConnectionPoints()[0];let a=1;if(o&&(a=Wo[o.type()]||1),a>1){let t=[];for(let n=0;n({name:t,value:e})))}}),this.bool=ha.BOOLEAN(0,YR(Uo.BOOL)),this.int=ha.INTEGER(0,YR(Uo.INT)),this.float=ha.FLOAT(0,YR(Uo.FLOAT)),this.vec2=ha.VECTOR2([0,0],YR(Uo.VEC2)),this.vec3=ha.VECTOR3([0,0,0],YR(Uo.VEC3)),this.vec4=ha.VECTOR4([0,0,0,0],YR(Uo.VEC4))}};class JR extends gf{constructor(){super(...arguments),this.paramsConfig=$R,this._allow_inputs_created_from_params=!1}static type(){return\\\\\\\"constant\\\\\\\"}initializeNode(){this.io.connection_points.set_output_name_function((t=>JR.OUTPUT_NAME)),this.io.connection_points.set_expected_input_types_function((()=>[])),this.io.connection_points.set_expected_output_types_function((()=>[this._current_connection_type]))}setLines(t){const e=this._current_param;if(e){const n=this._current_connection_type;let i=mf.any(e.value);e.name()==this.p.int.name()&&m.isNumber(e.value)&&(i=mf.integer(e.value));const s=`${n} ${this._current_var_name} = ${i}`;t.addBodyLines(this,[s])}else console.warn(`no param found for constant node for type '${this.pv.type}'`)}get _current_connection_type(){null==this.pv.type&&console.warn(\\\\\\\"constant gl node type if not valid\\\\\\\");const t=Go[this.pv.type];return null==t&&console.warn(\\\\\\\"constant gl node type if not valid\\\\\\\"),t}get _current_param(){this._params_by_type=this._params_by_type||new Map([[Uo.BOOL,this.p.bool],[Uo.INT,this.p.int],[Uo.FLOAT,this.p.float],[Uo.VEC2,this.p.vec2],[Uo.VEC3,this.p.vec3],[Uo.VEC4,this.p.vec4]]);const t=Go[this.pv.type];return this._params_by_type.get(t)}get _current_var_name(){return this.glVarName(JR.OUTPUT_NAME)}set_gl_type(t){this.p.type.set(Go.indexOf(t))}}JR.OUTPUT_NAME=\\\\\\\"val\\\\\\\";const ZR=\\\\\\\"cross\\\\\\\";const KR=new class extends ua{constructor(){super(...arguments),this.x=ha.VECTOR3([0,0,1]),this.y=ha.VECTOR3([0,1,0])}};class QR extends gf{constructor(){super(...arguments),this.paramsConfig=KR}static type(){return\\\\\\\"cross\\\\\\\"}initializeNode(){super.initializeNode(),this.io.outputs.setNamedOutputConnectionPoints([new qo(ZR,Uo.VEC3)])}setLines(t){const e=mf.float(this.variableForInputParam(this.p.x)),n=mf.float(this.variableForInputParam(this.p.y)),i=`vec3 ${this.glVarName(ZR)} = cross(${e}, ${n})`;t.addBodyLines(this,[i])}}class tI extends(hR(\\\\\\\"cycle\\\\\\\",{in:[\\\\\\\"in\\\\\\\",\\\\\\\"min\\\\\\\",\\\\\\\"max\\\\\\\"],default:{max:1},functions:[\\\\\\\"float cycle(float val, float val_min, float val_max){\\\\n\\\\tif(val >= val_min && val < val_max){\\\\n\\\\t\\\\treturn val;\\\\n\\\\t} else {\\\\n\\\\t\\\\tfloat range = val_max - val_min;\\\\n\\\\t\\\\tif(val >= val_max){\\\\n\\\\t\\\\t\\\\tfloat delta = (val - val_max);\\\\n\\\\t\\\\t\\\\treturn val_min + mod(delta, range);\\\\n\\\\t\\\\t} else {\\\\n\\\\t\\\\t\\\\tfloat delta = (val_min - val);\\\\n\\\\t\\\\t\\\\treturn val_max - mod(delta, range);\\\\n\\\\t\\\\t}\\\\n\\\\t}\\\\n}\\\\\\\"]})){}var eI=\\\\\\\"float disk_feather(float dist, float radius, float feather){\\\\n\\\\tif(feather <= 0.0){\\\\n\\\\t\\\\tif(dist < radius){return 1.0;}else{return 0.0;}\\\\n\\\\t} else {\\\\n\\\\t\\\\tfloat half_feather = feather * 0.5;\\\\n\\\\t\\\\tif(dist < (radius - half_feather)){\\\\n\\\\t\\\\t\\\\treturn 1.0;\\\\n\\\\t\\\\t} else {\\\\n\\\\t\\\\t\\\\tif(dist > (radius + half_feather)){\\\\n\\\\t\\\\t\\\\t\\\\treturn 0.0;\\\\n\\\\t\\\\t\\\\t} else {\\\\n\\\\t\\\\t\\\\t\\\\tfloat feather_start = (radius - half_feather);\\\\n\\\\t\\\\t\\\\t\\\\tfloat blend = 1.0 - (dist - feather_start) / feather;\\\\n\\\\t\\\\t\\\\t\\\\treturn blend;\\\\n\\\\t\\\\t\\\\t}\\\\n\\\\t\\\\t}\\\\n\\\\t}\\\\n}\\\\n\\\\nfloat disk2d(vec2 pos, vec2 center, float radius, float feather){\\\\n\\\\tfloat dist = distance(pos, center);\\\\n\\\\treturn disk_feather(dist, radius, feather);\\\\n}\\\\n\\\\n// function could be called sphere, but is an overload of disk, and is the same\\\\nfloat disk3d(vec3 pos, vec3 center, float radius, float feather){\\\\n\\\\tfloat dist = distance(pos, center);\\\\n\\\\treturn disk_feather(dist, radius, feather);\\\\n}\\\\\\\";const nI=new class extends ua{constructor(){super(...arguments),this.position=ha.VECTOR2([0,0]),this.center=ha.VECTOR2([0,0]),this.radius=ha.FLOAT(1),this.feather=ha.FLOAT(.1)}};class iI extends gf{constructor(){super(...arguments),this.paramsConfig=nI}static type(){return\\\\\\\"disk\\\\\\\"}initializeNode(){super.initializeNode(),this.io.outputs.setNamedOutputConnectionPoints([new qo(\\\\\\\"float\\\\\\\",Uo.FLOAT)])}setLines(t){const e=mf.vector2(this.variableForInputParam(this.p.position)),n=mf.vector2(this.variableForInputParam(this.p.center)),i=mf.float(this.variableForInputParam(this.p.radius)),s=mf.float(this.variableForInputParam(this.p.feather)),r=`float ${this.glVarName(\\\\\\\"float\\\\\\\")} = disk2d(${e}, ${n}, ${i}, ${s})`;t.addBodyLines(this,[r]),t.addDefinitions(this,[new Cf(this,eI)])}}var sI=\\\\\\\"\\\\nfloat bounceOut(float t) {\\\\n const float a = 4.0 / 11.0;\\\\n const float b = 8.0 / 11.0;\\\\n const float c = 9.0 / 10.0;\\\\n\\\\n const float ca = 4356.0 / 361.0;\\\\n const float cb = 35442.0 / 1805.0;\\\\n const float cc = 16061.0 / 1805.0;\\\\n\\\\n float t2 = t * t;\\\\n\\\\n return t < a\\\\n ? 7.5625 * t2\\\\n : t < b\\\\n ? 9.075 * t2 - 9.9 * t + 3.4\\\\n : t < c\\\\n ? ca * t2 - cb * t + cc\\\\n : 10.8 * t * t - 20.52 * t + 10.72;\\\\n}\\\\n\\\\n\\\\\\\";const rI=[\\\\\\\"back-in-out\\\\\\\",\\\\\\\"back-in\\\\\\\",\\\\\\\"back-out\\\\\\\",\\\\\\\"bounce-in-out\\\\\\\",\\\\\\\"bounce-in\\\\\\\",\\\\\\\"bounce-out\\\\\\\",\\\\\\\"circular-in-out\\\\\\\",\\\\\\\"circular-in\\\\\\\",\\\\\\\"circular-out\\\\\\\",\\\\\\\"cubic-in-out\\\\\\\",\\\\\\\"cubic-in\\\\\\\",\\\\\\\"cubic-out\\\\\\\",\\\\\\\"elastic-in-out\\\\\\\",\\\\\\\"elastic-in\\\\\\\",\\\\\\\"elastic-out\\\\\\\",\\\\\\\"exponential-in-out\\\\\\\",\\\\\\\"exponential-in\\\\\\\",\\\\\\\"exponential-out\\\\\\\",\\\\\\\"linear\\\\\\\",\\\\\\\"quadratic-in-out\\\\\\\",\\\\\\\"quadratic-in\\\\\\\",\\\\\\\"quadratic-out\\\\\\\",\\\\\\\"sine-in-out\\\\\\\",\\\\\\\"sine-in\\\\\\\",\\\\\\\"sine-out\\\\\\\"],oI={\\\\\\\"circular-in-out\\\\\\\":\\\\\\\"float circularInOut(float t) {\\\\n return t < 0.5\\\\n ? 0.5 * (1.0 - sqrt(1.0 - 4.0 * t * t))\\\\n : 0.5 * (sqrt((3.0 - 2.0 * t) * (2.0 * t - 1.0)) + 1.0);\\\\n}\\\\n\\\\n\\\\\\\",\\\\\\\"exponential-in-out\\\\\\\":\\\\\\\"float exponentialInOut(float t) {\\\\n return t == 0.0 || t == 1.0\\\\n ? t\\\\n : t < 0.5\\\\n ? +0.5 * pow(2.0, (20.0 * t) - 10.0)\\\\n : -0.5 * pow(2.0, 10.0 - (t * 20.0)) + 1.0;\\\\n}\\\\n\\\\n\\\\\\\",\\\\\\\"circular-in\\\\\\\":\\\\\\\"float circularIn(float t) {\\\\n return 1.0 - sqrt(1.0 - t * t);\\\\n}\\\\n\\\\n\\\\\\\",\\\\\\\"elastic-out\\\\\\\":\\\\\\\"#ifndef HALF_PI\\\\n#define HALF_PI 1.5707963267948966\\\\n#endif\\\\n\\\\nfloat elasticOut(float t) {\\\\n return sin(-13.0 * (t + 1.0) * HALF_PI) * pow(2.0, -10.0 * t) + 1.0;\\\\n}\\\\n\\\\n\\\\\\\",\\\\\\\"cubic-in\\\\\\\":\\\\\\\"float cubicIn(float t) {\\\\n return t * t * t;\\\\n}\\\\n\\\\n\\\\\\\",\\\\\\\"exponential-out\\\\\\\":\\\\\\\"float exponentialOut(float t) {\\\\n return t == 1.0 ? t : 1.0 - pow(2.0, -10.0 * t);\\\\n}\\\\n\\\\n\\\\\\\",\\\\\\\"quintic-out\\\\\\\":\\\\\\\"float quinticOut(float t) {\\\\n return 1.0 - (pow(t - 1.0, 5.0));\\\\n}\\\\n\\\\n\\\\\\\",\\\\\\\"elastic-in-out\\\\\\\":\\\\\\\"#ifndef HALF_PI\\\\n#define HALF_PI 1.5707963267948966\\\\n#endif\\\\n\\\\nfloat elasticInOut(float t) {\\\\n return t < 0.5\\\\n ? 0.5 * sin(+13.0 * HALF_PI * 2.0 * t) * pow(2.0, 10.0 * (2.0 * t - 1.0))\\\\n : 0.5 * sin(-13.0 * HALF_PI * ((2.0 * t - 1.0) + 1.0)) * pow(2.0, -10.0 * (2.0 * t - 1.0)) + 1.0;\\\\n}\\\\n\\\\n\\\\\\\",linear:\\\\\\\"float linear(float t) {\\\\n return t;\\\\n}\\\\n\\\\n\\\\\\\",\\\\\\\"circular-out\\\\\\\":\\\\\\\"float circularOut(float t) {\\\\n return sqrt((2.0 - t) * t);\\\\n}\\\\n\\\\n\\\\\\\",\\\\\\\"back-in-out\\\\\\\":\\\\\\\"\\\\nfloat backInOut(float t) {\\\\n float f = t < 0.5\\\\n ? 2.0 * t\\\\n : 1.0 - (2.0 * t - 1.0);\\\\n\\\\n float g = pow(f, 3.0) - f * sin(f * PI);\\\\n\\\\n return t < 0.5\\\\n ? 0.5 * g\\\\n : 0.5 * (1.0 - g) + 0.5;\\\\n}\\\\n\\\\n\\\\\\\",\\\\\\\"back-in\\\\\\\":\\\\\\\"\\\\nfloat backIn(float t) {\\\\n return pow(t, 3.0) - t * sin(t * PI);\\\\n}\\\\n\\\\n\\\\\\\",\\\\\\\"sine-in\\\\\\\":\\\\\\\"#ifndef HALF_PI\\\\n#define HALF_PI 1.5707963267948966\\\\n#endif\\\\n\\\\nfloat sineIn(float t) {\\\\n return sin((t - 1.0) * HALF_PI) + 1.0;\\\\n}\\\\n\\\\n\\\\\\\",\\\\\\\"back-out\\\\\\\":\\\\\\\"\\\\nfloat backOut(float t) {\\\\n float f = 1.0 - t;\\\\n return 1.0 - (pow(f, 3.0) - f * sin(f * PI));\\\\n}\\\\n\\\\n\\\\\\\",\\\\\\\"quartic-in-out\\\\\\\":\\\\\\\"float quarticInOut(float t) {\\\\n return t < 0.5\\\\n ? +8.0 * pow(t, 4.0)\\\\n : -8.0 * pow(t - 1.0, 4.0) + 1.0;\\\\n}\\\\n\\\\n\\\\\\\",\\\\\\\"quadratic-in\\\\\\\":\\\\\\\"float quadraticIn(float t) {\\\\n return t * t;\\\\n}\\\\n\\\\n\\\\\\\",\\\\\\\"cubic-in-out\\\\\\\":\\\\\\\"float cubicInOut(float t) {\\\\n return t < 0.5\\\\n ? 4.0 * t * t * t\\\\n : 0.5 * pow(2.0 * t - 2.0, 3.0) + 1.0;\\\\n}\\\\n\\\\n\\\\\\\",\\\\\\\"elastic-in\\\\\\\":\\\\\\\"#ifndef HALF_PI\\\\n#define HALF_PI 1.5707963267948966\\\\n#endif\\\\n\\\\nfloat elasticIn(float t) {\\\\n return sin(13.0 * t * HALF_PI) * pow(2.0, 10.0 * (t - 1.0));\\\\n}\\\\n\\\\n\\\\\\\",\\\\\\\"bounce-out\\\\\\\":sI,\\\\\\\"quadratic-in-out\\\\\\\":\\\\\\\"float quadraticInOut(float t) {\\\\n float p = 2.0 * t * t;\\\\n return t < 0.5 ? p : -p + (4.0 * t) - 1.0;\\\\n}\\\\n\\\\n\\\\\\\",\\\\\\\"exponential-in\\\\\\\":\\\\\\\"float exponentialIn(float t) {\\\\n return t == 0.0 ? t : pow(2.0, 10.0 * (t - 1.0));\\\\n}\\\\n\\\\n\\\\\\\",\\\\\\\"quintic-in-out\\\\\\\":\\\\\\\"float quinticInOut(float t) {\\\\n return t < 0.5\\\\n ? +16.0 * pow(t, 5.0)\\\\n : -0.5 * pow(2.0 * t - 2.0, 5.0) + 1.0;\\\\n}\\\\n\\\\n\\\\\\\",\\\\\\\"sine-in-out\\\\\\\":\\\\\\\"\\\\nfloat sineInOut(float t) {\\\\n return -0.5 * (cos(PI * t) - 1.0);\\\\n}\\\\n\\\\n\\\\\\\",\\\\\\\"cubic-out\\\\\\\":\\\\\\\"float cubicOut(float t) {\\\\n float f = t - 1.0;\\\\n return f * f * f + 1.0;\\\\n}\\\\n\\\\n\\\\\\\",\\\\\\\"quadratic-out\\\\\\\":\\\\\\\"float quadraticOut(float t) {\\\\n return -t * (t - 2.0);\\\\n}\\\\n\\\\n\\\\\\\",\\\\\\\"bounce-in-out\\\\\\\":\\\\\\\"\\\\nfloat bounceInOut(float t) {\\\\n return t < 0.5\\\\n ? 0.5 * (1.0 - bounceOut(1.0 - t * 2.0))\\\\n : 0.5 * bounceOut(t * 2.0 - 1.0) + 0.5;\\\\n}\\\\n\\\\n\\\\n\\\\n\\\\\\\",\\\\\\\"quintic-in\\\\\\\":\\\\\\\"float quinticIn(float t) {\\\\n return pow(t, 5.0);\\\\n}\\\\n\\\\n\\\\\\\",\\\\\\\"quartic-in\\\\\\\":\\\\\\\"float quarticIn(float t) {\\\\n return pow(t, 4.0);\\\\n}\\\\n\\\\n\\\\\\\",\\\\\\\"quartic-out\\\\\\\":\\\\\\\"float quarticOut(float t) {\\\\n return pow(t - 1.0, 3.0) * (1.0 - t) + 1.0;\\\\n}\\\\n\\\\n\\\\\\\",\\\\\\\"bounce-in\\\\\\\":\\\\\\\"\\\\nfloat bounceIn(float t) {\\\\n return 1.0 - bounceOut(1.0 - t);\\\\n}\\\\n\\\\n\\\\\\\",\\\\\\\"sine-out\\\\\\\":\\\\\\\"#ifndef HALF_PI\\\\n#define HALF_PI 1.5707963267948966\\\\n#endif\\\\n\\\\nfloat sineOut(float t) {\\\\n return sin(t * HALF_PI);\\\\n}\\\\n\\\\n\\\\\\\"},aI={\\\\\\\"bounce-in\\\\\\\":[sI],\\\\\\\"bounce-in-out\\\\\\\":[sI]},lI={\\\\\\\"circular-in-out\\\\\\\":\\\\\\\"circularInOut\\\\\\\",\\\\\\\"exponential-in-out\\\\\\\":\\\\\\\"exponentialInOut\\\\\\\",\\\\\\\"circular-in\\\\\\\":\\\\\\\"circularIn\\\\\\\",\\\\\\\"elastic-out\\\\\\\":\\\\\\\"elasticOut\\\\\\\",\\\\\\\"cubic-in\\\\\\\":\\\\\\\"cubicIn\\\\\\\",\\\\\\\"exponential-out\\\\\\\":\\\\\\\"exponentialOut\\\\\\\",\\\\\\\"quintic-out\\\\\\\":\\\\\\\"quinticOut\\\\\\\",\\\\\\\"elastic-in-out\\\\\\\":\\\\\\\"elasticInOut\\\\\\\",linear:\\\\\\\"linear\\\\\\\",\\\\\\\"circular-out\\\\\\\":\\\\\\\"circularOut\\\\\\\",\\\\\\\"back-in-out\\\\\\\":\\\\\\\"backInOut\\\\\\\",\\\\\\\"back-in\\\\\\\":\\\\\\\"backIn\\\\\\\",\\\\\\\"sine-in\\\\\\\":\\\\\\\"sineIn\\\\\\\",\\\\\\\"back-out\\\\\\\":\\\\\\\"backOut\\\\\\\",\\\\\\\"quartic-in-out\\\\\\\":\\\\\\\"quarticInOut\\\\\\\",\\\\\\\"quadratic-in\\\\\\\":\\\\\\\"quadraticIn\\\\\\\",\\\\\\\"cubic-in-out\\\\\\\":\\\\\\\"cubicInOut\\\\\\\",\\\\\\\"elastic-in\\\\\\\":\\\\\\\"elasticIn\\\\\\\",\\\\\\\"bounce-out\\\\\\\":\\\\\\\"bounceOut\\\\\\\",\\\\\\\"quadratic-in-out\\\\\\\":\\\\\\\"quadraticInOut\\\\\\\",\\\\\\\"exponential-in\\\\\\\":\\\\\\\"exponentialIn\\\\\\\",\\\\\\\"quintic-in-out\\\\\\\":\\\\\\\"quinticInOut\\\\\\\",\\\\\\\"sine-in-out\\\\\\\":\\\\\\\"sineInOut\\\\\\\",\\\\\\\"cubic-out\\\\\\\":\\\\\\\"cubicOut\\\\\\\",\\\\\\\"quadratic-out\\\\\\\":\\\\\\\"quadraticOut\\\\\\\",\\\\\\\"bounce-in-out\\\\\\\":\\\\\\\"bounceInOut\\\\\\\",\\\\\\\"quintic-in\\\\\\\":\\\\\\\"quinticIn\\\\\\\",\\\\\\\"quartic-in\\\\\\\":\\\\\\\"quarticIn\\\\\\\",\\\\\\\"quartic-out\\\\\\\":\\\\\\\"quarticOut\\\\\\\",\\\\\\\"bounce-in\\\\\\\":\\\\\\\"bounceIn\\\\\\\",\\\\\\\"sine-out\\\\\\\":\\\\\\\"sineOut\\\\\\\"},cI=rI.indexOf(\\\\\\\"sine-in-out\\\\\\\");const hI=new class extends ua{constructor(){super(...arguments),this.type=ha.INTEGER(cI,{menu:{entries:rI.map(((t,e)=>({name:t,value:e})))}}),this.input=ha.FLOAT(0)}};class uI extends gf{constructor(){super(...arguments),this.paramsConfig=hI}static type(){return\\\\\\\"easing\\\\\\\"}initializeNode(){super.initializeNode(),this.io.connection_points.spare_params.set_inputless_param_names([\\\\\\\"type\\\\\\\"]),this.io.outputs.setNamedOutputConnectionPoints([new qo(\\\\\\\"out\\\\\\\",Uo.FLOAT)])}setLines(t){const e=rI[this.pv.type],n=lI[e];let i=[new Cf(this,oI[e])];const s=(aI[e]||[]).map((t=>new Cf(this,t)));s&&(i=s.concat(i));const r=mf.float(this.variableForInputParam(this.p.input)),o=`float ${this.glVarName(\\\\\\\"out\\\\\\\")} = ${n}(${r})`;t.addDefinitions(this,i),t.addBodyLines(this,[o])}}var dI=\\\\\\\"//\\\\n//\\\\n// FIT\\\\n//\\\\n//\\\\nfloat fit(float val, float srcMin, float srcMax, float destMin, float destMax){\\\\n\\\\tfloat src_range = srcMax - srcMin;\\\\n\\\\tfloat dest_range = destMax - destMin;\\\\n\\\\n\\\\tfloat r = (val - srcMin) / src_range;\\\\n\\\\treturn (r * dest_range) + destMin;\\\\n}\\\\nvec2 fit(vec2 val, vec2 srcMin, vec2 srcMax, vec2 destMin, vec2 destMax){\\\\n\\\\treturn vec2(\\\\n\\\\t\\\\tfit(val.x, srcMin.x, srcMax.x, destMin.x, destMax.x),\\\\n\\\\t\\\\tfit(val.y, srcMin.y, srcMax.y, destMin.y, destMax.y)\\\\n\\\\t);\\\\n}\\\\nvec3 fit(vec3 val, vec3 srcMin, vec3 srcMax, vec3 destMin, vec3 destMax){\\\\n\\\\treturn vec3(\\\\n\\\\t\\\\tfit(val.x, srcMin.x, srcMax.x, destMin.x, destMax.x),\\\\n\\\\t\\\\tfit(val.y, srcMin.y, srcMax.y, destMin.y, destMax.y),\\\\n\\\\t\\\\tfit(val.z, srcMin.z, srcMax.z, destMin.z, destMax.z)\\\\n\\\\t);\\\\n}\\\\nvec4 fit(vec4 val, vec4 srcMin, vec4 srcMax, vec4 destMin, vec4 destMax){\\\\n\\\\treturn vec4(\\\\n\\\\t\\\\tfit(val.x, srcMin.x, srcMax.x, destMin.x, destMax.x),\\\\n\\\\t\\\\tfit(val.y, srcMin.y, srcMax.y, destMin.y, destMax.y),\\\\n\\\\t\\\\tfit(val.z, srcMin.z, srcMax.z, destMin.z, destMax.z),\\\\n\\\\t\\\\tfit(val.w, srcMin.w, srcMax.w, destMin.w, destMax.w)\\\\n\\\\t);\\\\n}\\\\n\\\\n//\\\\n//\\\\n// FIT TO 01\\\\n// fits the range [srcMin, srcMax] to [0, 1]\\\\n//\\\\nfloat fitTo01(float val, float srcMin, float srcMax){\\\\n\\\\tfloat size = srcMax - srcMin;\\\\n\\\\treturn (val - srcMin) / size;\\\\n}\\\\nvec2 fitTo01(vec2 val, vec2 srcMin, vec2 srcMax){\\\\n\\\\treturn vec2(\\\\n\\\\t\\\\tfitTo01(val.x, srcMin.x, srcMax.x),\\\\n\\\\t\\\\tfitTo01(val.y, srcMin.y, srcMax.y)\\\\n\\\\t);\\\\n}\\\\nvec3 fitTo01(vec3 val, vec3 srcMin, vec3 srcMax){\\\\n\\\\treturn vec3(\\\\n\\\\t\\\\tfitTo01(val.x, srcMin.x, srcMax.x),\\\\n\\\\t\\\\tfitTo01(val.y, srcMin.y, srcMax.y),\\\\n\\\\t\\\\tfitTo01(val.z, srcMin.z, srcMax.z)\\\\n\\\\t);\\\\n}\\\\nvec4 fitTo01(vec4 val, vec4 srcMin, vec4 srcMax){\\\\n\\\\treturn vec4(\\\\n\\\\t\\\\tfitTo01(val.x, srcMin.x, srcMax.x),\\\\n\\\\t\\\\tfitTo01(val.y, srcMin.y, srcMax.y),\\\\n\\\\t\\\\tfitTo01(val.z, srcMin.z, srcMax.z),\\\\n\\\\t\\\\tfitTo01(val.w, srcMin.w, srcMax.w)\\\\n\\\\t);\\\\n}\\\\n\\\\n//\\\\n//\\\\n// FIT FROM 01\\\\n// fits the range [0, 1] to [destMin, destMax]\\\\n//\\\\nfloat fitFrom01(float val, float destMin, float destMax){\\\\n\\\\treturn fit(val, 0.0, 1.0, destMin, destMax);\\\\n}\\\\nvec2 fitFrom01(vec2 val, vec2 srcMin, vec2 srcMax){\\\\n\\\\treturn vec2(\\\\n\\\\t\\\\tfitFrom01(val.x, srcMin.x, srcMax.x),\\\\n\\\\t\\\\tfitFrom01(val.y, srcMin.y, srcMax.y)\\\\n\\\\t);\\\\n}\\\\nvec3 fitFrom01(vec3 val, vec3 srcMin, vec3 srcMax){\\\\n\\\\treturn vec3(\\\\n\\\\t\\\\tfitFrom01(val.x, srcMin.x, srcMax.x),\\\\n\\\\t\\\\tfitFrom01(val.y, srcMin.y, srcMax.y),\\\\n\\\\t\\\\tfitFrom01(val.z, srcMin.z, srcMax.z)\\\\n\\\\t);\\\\n}\\\\nvec4 fitFrom01(vec4 val, vec4 srcMin, vec4 srcMax){\\\\n\\\\treturn vec4(\\\\n\\\\t\\\\tfitFrom01(val.x, srcMin.x, srcMax.x),\\\\n\\\\t\\\\tfitFrom01(val.y, srcMin.y, srcMax.y),\\\\n\\\\t\\\\tfitFrom01(val.z, srcMin.z, srcMax.z),\\\\n\\\\t\\\\tfitFrom01(val.w, srcMin.w, srcMax.w)\\\\n\\\\t);\\\\n}\\\\n\\\\n//\\\\n//\\\\n// FIT FROM 01 TO VARIANCE\\\\n// fits the range [0, 1] to [center - variance, center + variance]\\\\n//\\\\nfloat fitFrom01ToVariance(float val, float center, float variance){\\\\n\\\\treturn fitFrom01(val, center - variance, center + variance);\\\\n}\\\\nvec2 fitFrom01ToVariance(vec2 val, vec2 center, vec2 variance){\\\\n\\\\treturn vec2(\\\\n\\\\t\\\\tfitFrom01ToVariance(val.x, center.x, variance.x),\\\\n\\\\t\\\\tfitFrom01ToVariance(val.y, center.y, variance.y)\\\\n\\\\t);\\\\n}\\\\nvec3 fitFrom01ToVariance(vec3 val, vec3 center, vec3 variance){\\\\n\\\\treturn vec3(\\\\n\\\\t\\\\tfitFrom01ToVariance(val.x, center.x, variance.x),\\\\n\\\\t\\\\tfitFrom01ToVariance(val.y, center.y, variance.y),\\\\n\\\\t\\\\tfitFrom01ToVariance(val.z, center.z, variance.z)\\\\n\\\\t);\\\\n}\\\\nvec4 fitFrom01ToVariance(vec4 val, vec4 center, vec4 variance){\\\\n\\\\treturn vec4(\\\\n\\\\t\\\\tfitFrom01ToVariance(val.x, center.x, variance.x),\\\\n\\\\t\\\\tfitFrom01ToVariance(val.y, center.y, variance.y),\\\\n\\\\t\\\\tfitFrom01ToVariance(val.z, center.z, variance.z),\\\\n\\\\t\\\\tfitFrom01ToVariance(val.w, center.w, variance.w)\\\\n\\\\t);\\\\n}\\\\\\\";const pI={srcMin:0,srcMax:1,destMin:0,destMax:1};class _I extends RP{static type(){return\\\\\\\"fit\\\\\\\"}_gl_input_name(t){return[\\\\\\\"val\\\\\\\",\\\\\\\"srcMin\\\\\\\",\\\\\\\"srcMax\\\\\\\",\\\\\\\"destMin\\\\\\\",\\\\\\\"destMax\\\\\\\"][t]}paramDefaultValue(t){return pI[t]}gl_method_name(){return\\\\\\\"fit\\\\\\\"}gl_function_definitions(){return[new Cf(this,dI)]}}const mI={srcMin:0,srcMax:1};class fI extends OP{static type(){return\\\\\\\"fitTo01\\\\\\\"}_gl_input_name(t){return[\\\\\\\"val\\\\\\\",\\\\\\\"srcMin\\\\\\\",\\\\\\\"srcMax\\\\\\\"][t]}paramDefaultValue(t){return mI[t]}gl_method_name(){return\\\\\\\"fitTo01\\\\\\\"}gl_function_definitions(){return[new Cf(this,dI)]}}const gI={destMin:0,destMax:1};class vI extends OP{static type(){return\\\\\\\"fitFrom01\\\\\\\"}_gl_input_name(t){return[\\\\\\\"val\\\\\\\",\\\\\\\"destMin\\\\\\\",\\\\\\\"destMax\\\\\\\"][t]}paramDefaultValue(t){return gI[t]}gl_method_name(){return\\\\\\\"fitFrom01\\\\\\\"}gl_function_definitions(){return[new Cf(this,dI)]}}const yI={center:.5,variance:.5};class xI extends OP{static type(){return\\\\\\\"fitFrom01ToVariance\\\\\\\"}_gl_input_name(t){return[\\\\\\\"val\\\\\\\",\\\\\\\"center\\\\\\\",\\\\\\\"variance\\\\\\\"][t]}paramDefaultValue(t){return yI[t]}gl_method_name(){return\\\\\\\"fitFrom01ToVariance\\\\\\\"}gl_function_definitions(){return[new Cf(this,dI)]}}const bI=\\\\\\\"color\\\\\\\";const wI=new class extends ua{constructor(){super(...arguments),this.mvPosition=ha.VECTOR4([0,0,0,0]),this.baseColor=ha.COLOR([0,0,0]),this.fogColor=ha.COLOR([1,1,1]),this.near=ha.FLOAT(0),this.far=ha.FLOAT(0)}};class TI extends gf{constructor(){super(...arguments),this.paramsConfig=wI}static type(){return\\\\\\\"fog\\\\\\\"}initializeNode(){super.initializeNode(),this.io.outputs.setNamedOutputConnectionPoints([new qo(bI,Uo.VEC3)])}setLines(t){if(t.current_shader_name==Mf.FRAGMENT){const e=this.glVarName(this.name()),n=new Lf(this,Uo.VEC4,e),i=`${e} = modelViewMatrix * vec4(position, 1.0)`;t.addDefinitions(this,[n],Mf.VERTEX),t.addBodyLines(this,[i],Mf.VERTEX);const s=new Cf(this,\\\\\\\"vec3 compute_fog(vec4 mvPosition, vec3 base_color, vec3 fog_color, float near, float far) {\\\\n\\\\tfloat blend = (-mvPosition.z - near) / (far - near);\\\\n\\\\tblend = clamp(blend, 0.0, 1.0);\\\\n\\\\treturn blend * fog_color + (1.0 - blend) * base_color;\\\\n}\\\\\\\"),r=mf.vector4(this.variableForInputParam(this.p.mvPosition)),o=mf.vector3(this.variableForInputParam(this.p.baseColor)),a=mf.vector3(this.variableForInputParam(this.p.fogColor)),l=mf.vector3(this.variableForInputParam(this.p.near)),c=mf.vector3(this.variableForInputParam(this.p.far)),h=`vec3 ${this.glVarName(bI)} = compute_fog(${[r,o,a,l,c].join(\\\\\\\", \\\\\\\")})`;t.addDefinitions(this,[n,s]),t.addBodyLines(this,[h])}}}const AI=new class extends ua{};class MI extends gf{constructor(){super(...arguments),this.paramsConfig=AI}static type(){return ns.OUTPUT}initializeNode(){this.io.connection_points.set_input_name_function(this._expected_input_name.bind(this)),this.io.connection_points.set_expected_output_types_function((()=>[])),this.io.connection_points.set_expected_input_types_function(this._expected_input_types.bind(this)),this.io.connection_points.set_create_spare_params_from_inputs(!1),this.addPostDirtyHook(\\\\\\\"setParentDirty\\\\\\\",(()=>{var t;null===(t=this.parent())||void 0===t||t.setDirty(this)}))}parent(){return super.parent()}_expected_input_name(t){const e=this.parent();return(null==e?void 0:e.child_expected_output_connection_point_name(t))||`in${t}`}_expected_input_types(){const t=this.parent();return(null==t?void 0:t.child_expected_output_connection_point_types())||[]}setLines(t){const e=this.parent();if(!e)return;const n=[],i=this.io.connections.inputConnections();if(i)for(let t of i)if(t){const i=t.dest_connection_point(),s=mf.any(this.variableForInput(i.name())),r=`\\\\t${e.glVarName(i.name())} = ${s}`;n.push(r)}t.addBodyLines(this,n),e.set_lines_block_end(t,this)}}class EI extends gf{constructor(){super(...arguments),this._children_controller_context=ts.GL}initializeNode(){var t;null===(t=this.childrenController)||void 0===t||t.set_output_node_find_method((()=>this.nodesByType(MI.type())[0])),this.io.connection_points.set_input_name_function(this._expected_input_name.bind(this)),this.io.connection_points.set_output_name_function(this._expected_output_name.bind(this)),this.io.connection_points.set_expected_input_types_function(this._expected_input_types.bind(this)),this.io.connection_points.set_expected_output_types_function(this._expected_output_types.bind(this))}_expected_inputs_count(){const t=this.io.connections.inputConnections();return t?t.length+1:1}_expected_input_types(){const t=[],e=Uo.FLOAT,n=this.io.connections.inputConnections(),i=this._expected_inputs_count();for(let s=0;s=0){const e=t.dest_connection_point(),i=mf.any(this.variableForInput(e.name())),s=`${e.type()} ${this.glVarName(e.name())} = ${i}`;n.push(s)}const r=this.pv.start,o=this.pv.max,a=this.pv.step,l=mf.float(r),c=mf.float(o),h=mf.float(a),u=this.glVarName(\\\\\\\"i\\\\\\\"),d=`for(float ${u} = ${l}; ${u} < ${c}; ${u}+= ${h}){`;n.push(d);const p=`\\\\tfloat ${e.glVarName(NI.START_INDEX)} = ${u}`;if(n.push(p),s)for(let t of s)if(t&&t.input_index>=0){const i=t.dest_connection_point(),s=this.glVarName(i.name()),r=`\\\\t${i.type()} ${e.glVarName(i.name())} = ${s}`;n.push(r)}t.addBodyLines(e,n)}setLines(t){}}const RI=new class extends ua{};class II extends gf{constructor(){super(...arguments),this.paramsConfig=RI}static type(){return\\\\\\\"globals\\\\\\\"}initializeNode(){super.initializeNode(),this.lifecycle.add_on_add_hook((()=>{var t,e;null===(e=null===(t=this.material_node)||void 0===t?void 0:t.assemblerController)||void 0===e||e.add_globals_outputs(this)}))}setLines(t){t.assembler().set_node_lines_globals(this,t)}}const FI=new class extends ua{constructor(){super(...arguments),this.hsluv=ha.VECTOR3([1,1,1])}};class DI extends gf{constructor(){super(...arguments),this.paramsConfig=FI}static type(){return\\\\\\\"hsluvToRgb\\\\\\\"}initializeNode(){super.initializeNode(),this.io.outputs.setNamedOutputConnectionPoints([new qo(\\\\\\\"rgb\\\\\\\",Uo.VEC3)])}setLines(t){const e=[],n=[];e.push(new Cf(this,\\\\\\\"// from https://github.com/williammalo/hsluv-glsl\\\\n/*\\\\nHSLUV-GLSL v4.2\\\\nHSLUV is a human-friendly alternative to HSL. ( http://www.hsluv.org )\\\\nGLSL port by William Malo ( https://github.com/williammalo )\\\\nPut this code in your fragment shader.\\\\n*/\\\\n\\\\nvec3 hsluv_intersectLineLine(vec3 line1x, vec3 line1y, vec3 line2x, vec3 line2y) {\\\\n\\\\treturn (line1y - line2y) / (line2x - line1x);\\\\n}\\\\n\\\\nvec3 hsluv_distanceFromPole(vec3 pointx,vec3 pointy) {\\\\n\\\\treturn sqrt(pointx*pointx + pointy*pointy);\\\\n}\\\\n\\\\nvec3 hsluv_lengthOfRayUntilIntersect(float theta, vec3 x, vec3 y) {\\\\n\\\\tvec3 len = y / (sin(theta) - x * cos(theta));\\\\n\\\\tif (len.r < 0.0) {len.r=1000.0;}\\\\n\\\\tif (len.g < 0.0) {len.g=1000.0;}\\\\n\\\\tif (len.b < 0.0) {len.b=1000.0;}\\\\n\\\\treturn len;\\\\n}\\\\n\\\\nfloat hsluv_maxSafeChromaForL(float L){\\\\n\\\\tmat3 m2 = mat3(\\\\n\\\\t\\\\t 3.2409699419045214 ,-0.96924363628087983 , 0.055630079696993609,\\\\n\\\\t\\\\t-1.5373831775700935 , 1.8759675015077207 ,-0.20397695888897657 ,\\\\n\\\\t\\\\t-0.49861076029300328 , 0.041555057407175613, 1.0569715142428786 \\\\n\\\\t);\\\\n\\\\tfloat sub0 = L + 16.0;\\\\n\\\\tfloat sub1 = sub0 * sub0 * sub0 * .000000641;\\\\n\\\\tfloat sub2 = sub1 > 0.0088564516790356308 ? sub1 : L / 903.2962962962963;\\\\n\\\\n\\\\tvec3 top1 = (284517.0 * m2[0] - 94839.0 * m2[2]) * sub2;\\\\n\\\\tvec3 bottom = (632260.0 * m2[2] - 126452.0 * m2[1]) * sub2;\\\\n\\\\tvec3 top2 = (838422.0 * m2[2] + 769860.0 * m2[1] + 731718.0 * m2[0]) * L * sub2;\\\\n\\\\n\\\\tvec3 bounds0x = top1 / bottom;\\\\n\\\\tvec3 bounds0y = top2 / bottom;\\\\n\\\\n\\\\tvec3 bounds1x = top1 / (bottom+126452.0);\\\\n\\\\tvec3 bounds1y = (top2-769860.0*L) / (bottom+126452.0);\\\\n\\\\n\\\\tvec3 xs0 = hsluv_intersectLineLine(bounds0x, bounds0y, -1.0/bounds0x, vec3(0.0) );\\\\n\\\\tvec3 xs1 = hsluv_intersectLineLine(bounds1x, bounds1y, -1.0/bounds1x, vec3(0.0) );\\\\n\\\\n\\\\tvec3 lengths0 = hsluv_distanceFromPole( xs0, bounds0y + xs0 * bounds0x );\\\\n\\\\tvec3 lengths1 = hsluv_distanceFromPole( xs1, bounds1y + xs1 * bounds1x );\\\\n\\\\n\\\\treturn min(lengths0.r,\\\\n\\\\t\\\\t\\\\tmin(lengths1.r,\\\\n\\\\t\\\\t\\\\tmin(lengths0.g,\\\\n\\\\t\\\\t\\\\tmin(lengths1.g,\\\\n\\\\t\\\\t\\\\tmin(lengths0.b,\\\\n\\\\t\\\\t\\\\t\\\\tlengths1.b)))));\\\\n}\\\\n\\\\nfloat hsluv_maxChromaForLH(float L, float H) {\\\\n\\\\n\\\\tfloat hrad = radians(H);\\\\n\\\\n\\\\tmat3 m2 = mat3(\\\\n\\\\t\\\\t 3.2409699419045214 ,-0.96924363628087983 , 0.055630079696993609,\\\\n\\\\t\\\\t-1.5373831775700935 , 1.8759675015077207 ,-0.20397695888897657 ,\\\\n\\\\t\\\\t-0.49861076029300328 , 0.041555057407175613, 1.0569715142428786 \\\\n\\\\t);\\\\n\\\\tfloat sub1 = pow(L + 16.0, 3.0) / 1560896.0;\\\\n\\\\tfloat sub2 = sub1 > 0.0088564516790356308 ? sub1 : L / 903.2962962962963;\\\\n\\\\n\\\\tvec3 top1 = (284517.0 * m2[0] - 94839.0 * m2[2]) * sub2;\\\\n\\\\tvec3 bottom = (632260.0 * m2[2] - 126452.0 * m2[1]) * sub2;\\\\n\\\\tvec3 top2 = (838422.0 * m2[2] + 769860.0 * m2[1] + 731718.0 * m2[0]) * L * sub2;\\\\n\\\\n\\\\tvec3 bound0x = top1 / bottom;\\\\n\\\\tvec3 bound0y = top2 / bottom;\\\\n\\\\n\\\\tvec3 bound1x = top1 / (bottom+126452.0);\\\\n\\\\tvec3 bound1y = (top2-769860.0*L) / (bottom+126452.0);\\\\n\\\\n\\\\tvec3 lengths0 = hsluv_lengthOfRayUntilIntersect(hrad, bound0x, bound0y );\\\\n\\\\tvec3 lengths1 = hsluv_lengthOfRayUntilIntersect(hrad, bound1x, bound1y );\\\\n\\\\n\\\\treturn min(lengths0.r,\\\\n\\\\t\\\\t\\\\tmin(lengths1.r,\\\\n\\\\t\\\\t\\\\tmin(lengths0.g,\\\\n\\\\t\\\\t\\\\tmin(lengths1.g,\\\\n\\\\t\\\\t\\\\tmin(lengths0.b,\\\\n\\\\t\\\\t\\\\t\\\\tlengths1.b)))));\\\\n}\\\\n\\\\nfloat hsluv_fromLinear(float c) {\\\\n\\\\treturn c <= 0.0031308 ? 12.92 * c : 1.055 * pow(c, 1.0 / 2.4) - 0.055;\\\\n}\\\\nvec3 hsluv_fromLinear(vec3 c) {\\\\n\\\\treturn vec3( hsluv_fromLinear(c.r), hsluv_fromLinear(c.g), hsluv_fromLinear(c.b) );\\\\n}\\\\n\\\\nfloat hsluv_toLinear(float c) {\\\\n\\\\treturn c > 0.04045 ? pow((c + 0.055) / (1.0 + 0.055), 2.4) : c / 12.92;\\\\n}\\\\n\\\\nvec3 hsluv_toLinear(vec3 c) {\\\\n\\\\treturn vec3( hsluv_toLinear(c.r), hsluv_toLinear(c.g), hsluv_toLinear(c.b) );\\\\n}\\\\n\\\\nfloat hsluv_yToL(float Y){\\\\n\\\\treturn Y <= 0.0088564516790356308 ? Y * 903.2962962962963 : 116.0 * pow(Y, 1.0 / 3.0) - 16.0;\\\\n}\\\\n\\\\nfloat hsluv_lToY(float L) {\\\\n\\\\treturn L <= 8.0 ? L / 903.2962962962963 : pow((L + 16.0) / 116.0, 3.0);\\\\n}\\\\n\\\\nvec3 xyzToRgb(vec3 tuple) {\\\\n\\\\tconst mat3 m = mat3( \\\\n\\\\t\\\\t3.2409699419045214 ,-1.5373831775700935 ,-0.49861076029300328 ,\\\\n\\\\t\\\\t-0.96924363628087983 , 1.8759675015077207 , 0.041555057407175613,\\\\n\\\\t\\\\t0.055630079696993609,-0.20397695888897657, 1.0569715142428786 );\\\\n\\\\t\\\\n\\\\treturn hsluv_fromLinear(tuple*m);\\\\n}\\\\n\\\\nvec3 rgbToXyz(vec3 tuple) {\\\\n\\\\tconst mat3 m = mat3(\\\\n\\\\t\\\\t0.41239079926595948 , 0.35758433938387796, 0.18048078840183429 ,\\\\n\\\\t\\\\t0.21263900587151036 , 0.71516867876775593, 0.072192315360733715,\\\\n\\\\t\\\\t0.019330818715591851, 0.11919477979462599, 0.95053215224966058 \\\\n\\\\t);\\\\n\\\\treturn hsluv_toLinear(tuple) * m;\\\\n}\\\\n\\\\nvec3 xyzToLuv(vec3 tuple){\\\\n\\\\tfloat X = tuple.x;\\\\n\\\\tfloat Y = tuple.y;\\\\n\\\\tfloat Z = tuple.z;\\\\n\\\\n\\\\tfloat L = hsluv_yToL(Y);\\\\n\\\\t\\\\n\\\\tfloat div = 1./dot(tuple,vec3(1,15,3)); \\\\n\\\\n\\\\treturn vec3(\\\\n\\\\t\\\\t1.,\\\\n\\\\t\\\\t(52. * (X*div) - 2.57179),\\\\n\\\\t\\\\t(117.* (Y*div) - 6.08816)\\\\n\\\\t) * L;\\\\n}\\\\n\\\\n\\\\nvec3 luvToXyz(vec3 tuple) {\\\\n\\\\tfloat L = tuple.x;\\\\n\\\\n\\\\tfloat U = tuple.y / (13.0 * L) + 0.19783000664283681;\\\\n\\\\tfloat V = tuple.z / (13.0 * L) + 0.468319994938791;\\\\n\\\\n\\\\tfloat Y = hsluv_lToY(L);\\\\n\\\\tfloat X = 2.25 * U * Y / V;\\\\n\\\\tfloat Z = (3./V - 5.)*Y - (X/3.);\\\\n\\\\n\\\\treturn vec3(X, Y, Z);\\\\n}\\\\n\\\\nvec3 luvToLch(vec3 tuple) {\\\\n\\\\tfloat L = tuple.x;\\\\n\\\\tfloat U = tuple.y;\\\\n\\\\tfloat V = tuple.z;\\\\n\\\\n\\\\tfloat C = length(tuple.yz);\\\\n\\\\tfloat H = degrees(atan(V,U));\\\\n\\\\tif (H < 0.0) {\\\\n\\\\t\\\\tH = 360.0 + H;\\\\n\\\\t}\\\\n\\\\t\\\\n\\\\treturn vec3(L, C, H);\\\\n}\\\\n\\\\nvec3 lchToLuv(vec3 tuple) {\\\\n\\\\tfloat hrad = radians(tuple.b);\\\\n\\\\treturn vec3(\\\\n\\\\t\\\\ttuple.r,\\\\n\\\\t\\\\tcos(hrad) * tuple.g,\\\\n\\\\t\\\\tsin(hrad) * tuple.g\\\\n\\\\t);\\\\n}\\\\n\\\\nvec3 hsluvToLch(vec3 tuple) {\\\\n\\\\ttuple.g *= hsluv_maxChromaForLH(tuple.b, tuple.r) * .01;\\\\n\\\\treturn tuple.bgr;\\\\n}\\\\n\\\\nvec3 lchToHsluv(vec3 tuple) {\\\\n\\\\ttuple.g /= hsluv_maxChromaForLH(tuple.r, tuple.b) * .01;\\\\n\\\\treturn tuple.bgr;\\\\n}\\\\n\\\\nvec3 hpluvToLch(vec3 tuple) {\\\\n\\\\ttuple.g *= hsluv_maxSafeChromaForL(tuple.b) * .01;\\\\n\\\\treturn tuple.bgr;\\\\n}\\\\n\\\\nvec3 lchToHpluv(vec3 tuple) {\\\\n\\\\ttuple.g /= hsluv_maxSafeChromaForL(tuple.r) * .01;\\\\n\\\\treturn tuple.bgr;\\\\n}\\\\n\\\\nvec3 lchToRgb(vec3 tuple) {\\\\n\\\\treturn xyzToRgb(luvToXyz(lchToLuv(tuple)));\\\\n}\\\\n\\\\nvec3 rgbToLch(vec3 tuple) {\\\\n\\\\treturn luvToLch(xyzToLuv(rgbToXyz(tuple)));\\\\n}\\\\n\\\\nvec3 hsluvToRgb(vec3 tuple) {\\\\n\\\\treturn lchToRgb(hsluvToLch(tuple));\\\\n}\\\\n\\\\nvec3 rgbToHsluv(vec3 tuple) {\\\\n\\\\treturn lchToHsluv(rgbToLch(tuple));\\\\n}\\\\n\\\\nvec3 hpluvToRgb(vec3 tuple) {\\\\n\\\\treturn lchToRgb(hpluvToLch(tuple));\\\\n}\\\\n\\\\nvec3 rgbToHpluv(vec3 tuple) {\\\\n\\\\treturn lchToHpluv(rgbToLch(tuple));\\\\n}\\\\n\\\\nvec3 luvToRgb(vec3 tuple){\\\\n\\\\treturn xyzToRgb(luvToXyz(tuple));\\\\n}\\\\n\\\\n// allow vec4's\\\\nvec4 xyzToRgb(vec4 c) {return vec4( xyzToRgb( vec3(c.x,c.y,c.z) ), c.a);}\\\\nvec4 rgbToXyz(vec4 c) {return vec4( rgbToXyz( vec3(c.x,c.y,c.z) ), c.a);}\\\\nvec4 xyzToLuv(vec4 c) {return vec4( xyzToLuv( vec3(c.x,c.y,c.z) ), c.a);}\\\\nvec4 luvToXyz(vec4 c) {return vec4( luvToXyz( vec3(c.x,c.y,c.z) ), c.a);}\\\\nvec4 luvToLch(vec4 c) {return vec4( luvToLch( vec3(c.x,c.y,c.z) ), c.a);}\\\\nvec4 lchToLuv(vec4 c) {return vec4( lchToLuv( vec3(c.x,c.y,c.z) ), c.a);}\\\\nvec4 hsluvToLch(vec4 c) {return vec4( hsluvToLch( vec3(c.x,c.y,c.z) ), c.a);}\\\\nvec4 lchToHsluv(vec4 c) {return vec4( lchToHsluv( vec3(c.x,c.y,c.z) ), c.a);}\\\\nvec4 hpluvToLch(vec4 c) {return vec4( hpluvToLch( vec3(c.x,c.y,c.z) ), c.a);}\\\\nvec4 lchToHpluv(vec4 c) {return vec4( lchToHpluv( vec3(c.x,c.y,c.z) ), c.a);}\\\\nvec4 lchToRgb(vec4 c) {return vec4( lchToRgb( vec3(c.x,c.y,c.z) ), c.a);}\\\\nvec4 rgbToLch(vec4 c) {return vec4( rgbToLch( vec3(c.x,c.y,c.z) ), c.a);}\\\\nvec4 hsluvToRgb(vec4 c) {return vec4( hsluvToRgb( vec3(c.x,c.y,c.z) ), c.a);}\\\\nvec4 rgbToHsluv(vec4 c) {return vec4( rgbToHsluv( vec3(c.x,c.y,c.z) ), c.a);}\\\\nvec4 hpluvToRgb(vec4 c) {return vec4( hpluvToRgb( vec3(c.x,c.y,c.z) ), c.a);}\\\\nvec4 rgbToHpluv(vec4 c) {return vec4( rgbToHpluv( vec3(c.x,c.y,c.z) ), c.a);}\\\\nvec4 luvToRgb(vec4 c) {return vec4( luvToRgb( vec3(c.x,c.y,c.z) ), c.a);}\\\\n// allow 3 floats\\\\nvec3 xyzToRgb(float x, float y, float z) {return xyzToRgb( vec3(x,y,z) );}\\\\nvec3 rgbToXyz(float x, float y, float z) {return rgbToXyz( vec3(x,y,z) );}\\\\nvec3 xyzToLuv(float x, float y, float z) {return xyzToLuv( vec3(x,y,z) );}\\\\nvec3 luvToXyz(float x, float y, float z) {return luvToXyz( vec3(x,y,z) );}\\\\nvec3 luvToLch(float x, float y, float z) {return luvToLch( vec3(x,y,z) );}\\\\nvec3 lchToLuv(float x, float y, float z) {return lchToLuv( vec3(x,y,z) );}\\\\nvec3 hsluvToLch(float x, float y, float z) {return hsluvToLch( vec3(x,y,z) );}\\\\nvec3 lchToHsluv(float x, float y, float z) {return lchToHsluv( vec3(x,y,z) );}\\\\nvec3 hpluvToLch(float x, float y, float z) {return hpluvToLch( vec3(x,y,z) );}\\\\nvec3 lchToHpluv(float x, float y, float z) {return lchToHpluv( vec3(x,y,z) );}\\\\nvec3 lchToRgb(float x, float y, float z) {return lchToRgb( vec3(x,y,z) );}\\\\nvec3 rgbToLch(float x, float y, float z) {return rgbToLch( vec3(x,y,z) );}\\\\nvec3 hsluvToRgb(float x, float y, float z) {return hsluvToRgb( vec3(x,y,z) );}\\\\nvec3 rgbToHsluv(float x, float y, float z) {return rgbToHsluv( vec3(x,y,z) );}\\\\nvec3 hpluvToRgb(float x, float y, float z) {return hpluvToRgb( vec3(x,y,z) );}\\\\nvec3 rgbToHpluv(float x, float y, float z) {return rgbToHpluv( vec3(x,y,z) );}\\\\nvec3 luvToRgb(float x, float y, float z) {return luvToRgb( vec3(x,y,z) );}\\\\n// allow 4 floats\\\\nvec4 xyzToRgb(float x, float y, float z, float a) {return xyzToRgb( vec4(x,y,z,a) );}\\\\nvec4 rgbToXyz(float x, float y, float z, float a) {return rgbToXyz( vec4(x,y,z,a) );}\\\\nvec4 xyzToLuv(float x, float y, float z, float a) {return xyzToLuv( vec4(x,y,z,a) );}\\\\nvec4 luvToXyz(float x, float y, float z, float a) {return luvToXyz( vec4(x,y,z,a) );}\\\\nvec4 luvToLch(float x, float y, float z, float a) {return luvToLch( vec4(x,y,z,a) );}\\\\nvec4 lchToLuv(float x, float y, float z, float a) {return lchToLuv( vec4(x,y,z,a) );}\\\\nvec4 hsluvToLch(float x, float y, float z, float a) {return hsluvToLch( vec4(x,y,z,a) );}\\\\nvec4 lchToHsluv(float x, float y, float z, float a) {return lchToHsluv( vec4(x,y,z,a) );}\\\\nvec4 hpluvToLch(float x, float y, float z, float a) {return hpluvToLch( vec4(x,y,z,a) );}\\\\nvec4 lchToHpluv(float x, float y, float z, float a) {return lchToHpluv( vec4(x,y,z,a) );}\\\\nvec4 lchToRgb(float x, float y, float z, float a) {return lchToRgb( vec4(x,y,z,a) );}\\\\nvec4 rgbToLch(float x, float y, float z, float a) {return rgbToLch( vec4(x,y,z,a) );}\\\\nvec4 hsluvToRgb(float x, float y, float z, float a) {return hsluvToRgb( vec4(x,y,z,a) );}\\\\nvec4 rgbToHslul(float x, float y, float z, float a) {return rgbToHsluv( vec4(x,y,z,a) );}\\\\nvec4 hpluvToRgb(float x, float y, float z, float a) {return hpluvToRgb( vec4(x,y,z,a) );}\\\\nvec4 rgbToHpluv(float x, float y, float z, float a) {return rgbToHpluv( vec4(x,y,z,a) );}\\\\nvec4 luvToRgb(float x, float y, float z, float a) {return luvToRgb( vec4(x,y,z,a) );}\\\\n\\\\n/*\\\\nEND HSLUV-GLSL\\\\n*/\\\\n\\\\n\\\\n// from https://gist.github.com/mattatz/44f081cac87e2f7c8980\\\\n// converted to glsl by gui@polygonjs.com\\\\n// and made function names consistent with the ones above\\\\n/*\\\\n * Conversion between RGB and LAB colorspace.\\\\n * Import from flowabs glsl program : https://code.google.com/p/flowabs/source/browse/glsl/?r=f36cbdcf7790a28d90f09e2cf89ec9a64911f138\\\\n */\\\\n\\\\n\\\\n\\\\nvec3 xyzToLab( vec3 c ) {\\\\n\\\\tvec3 n = c / vec3(95.047, 100, 108.883);\\\\n\\\\tvec3 v;\\\\n\\\\tv.x = ( n.x > 0.008856 ) ? pow( n.x, 1.0 / 3.0 ) : ( 7.787 * n.x ) + ( 16.0 / 116.0 );\\\\n\\\\tv.y = ( n.y > 0.008856 ) ? pow( n.y, 1.0 / 3.0 ) : ( 7.787 * n.y ) + ( 16.0 / 116.0 );\\\\n\\\\tv.z = ( n.z > 0.008856 ) ? pow( n.z, 1.0 / 3.0 ) : ( 7.787 * n.z ) + ( 16.0 / 116.0 );\\\\n\\\\treturn vec3(( 116.0 * v.y ) - 16.0, 500.0 * ( v.x - v.y ), 200.0 * ( v.y - v.z ));\\\\n}\\\\n\\\\nvec3 rgbToLab( vec3 c ) {\\\\n\\\\tvec3 lab = xyzToLab( rgbToXyz( c ) );\\\\n\\\\treturn vec3( lab.x / 100.0, 0.5 + 0.5 * ( lab.y / 127.0 ), 0.5 + 0.5 * ( lab.z / 127.0 ));\\\\n}\\\\n\\\\nvec3 labToXyz( vec3 c ) {\\\\n\\\\tfloat fy = ( c.x + 16.0 ) / 116.0;\\\\n\\\\tfloat fx = c.y / 500.0 + fy;\\\\n\\\\tfloat fz = fy - c.z / 200.0;\\\\n\\\\treturn vec3(\\\\n\\\\t\\\\t 95.047 * (( fx > 0.206897 ) ? fx * fx * fx : ( fx - 16.0 / 116.0 ) / 7.787),\\\\n\\\\t\\\\t100.000 * (( fy > 0.206897 ) ? fy * fy * fy : ( fy - 16.0 / 116.0 ) / 7.787),\\\\n\\\\t\\\\t108.883 * (( fz > 0.206897 ) ? fz * fz * fz : ( fz - 16.0 / 116.0 ) / 7.787)\\\\n\\\\t);\\\\n}\\\\n\\\\n\\\\n\\\\nvec3 labToRgb( vec3 c ) {\\\\n\\\\treturn xyzToRgb( labToXyz( vec3(100.0 * c.x, 2.0 * 127.0 * (c.y - 0.5), 2.0 * 127.0 * (c.z - 0.5)) ) );\\\\n}\\\\\\\"));const i=mf.vector3(this.variableForInputParam(this.p.hsluv)),s=this.glVarName(\\\\\\\"rgb\\\\\\\");n.push(`vec3 ${s} = hsluvToRgb(${i}.x * 360.0, ${i}.y * 100.0, ${i}.z * 100.0)`),t.addDefinitions(this,e),t.addBodyLines(this,n)}}const BI=new class extends ua{constructor(){super(...arguments),this.hsv=ha.VECTOR3([1,1,1])}};class zI extends gf{constructor(){super(...arguments),this.paramsConfig=BI}static type(){return\\\\\\\"hsvToRgb\\\\\\\"}initializeNode(){super.initializeNode(),this.io.outputs.setNamedOutputConnectionPoints([new qo(\\\\\\\"rgb\\\\\\\",Uo.VEC3)])}setLines(t){const e=[],n=[];e.push(new Cf(this,\\\\\\\"// https://github.com/hughsk/glsl-hsv2rgb\\\\n// https://stackoverflow.com/questions/15095909/from-rgb-to-hsv-in-opengl-glsl\\\\nvec3 hsv2rgb(vec3 c) {\\\\n\\\\tvec4 K = vec4(1.0, 2.0 / 3.0, 1.0 / 3.0, 3.0);\\\\n\\\\tvec3 p = abs(fract(c.xxx + K.xyz) * 6.0 - K.www);\\\\n\\\\treturn c.z * mix(K.xxx, clamp(p - K.xxx, 0.0, 1.0), c.y);\\\\n}\\\\\\\"));const i=mf.vector3(this.variableForInputParam(this.p.hsv)),s=this.glVarName(\\\\\\\"rgb\\\\\\\");n.push(`vec3 ${s} = hsv2rgb(${i})`),t.addDefinitions(this,e),t.addBodyLines(this,n)}}const kI=\\\\\\\"condition\\\\\\\";const UI=new class extends ua{};class GI extends CI{constructor(){super(...arguments),this.paramsConfig=UI}static type(){return\\\\\\\"ifThen\\\\\\\"}_expected_inputs_count(){const t=this.io.connections.inputConnections();return t?Math.max(t.length+1,2):2}_expected_input_types(){const t=[Uo.BOOL],e=Uo.FLOAT,n=this.io.connections.inputConnections(),i=this._expected_inputs_count();for(let s=1;s[\\\\\\\"value0\\\\\\\",\\\\\\\"value1\\\\\\\",\\\\\\\"blend\\\\\\\"][t])),this.io.connection_points.set_output_name_function(this._gl_output_name.bind(this)),this.io.connection_points.set_expected_input_types_function(this._expected_input_types.bind(this)),this.io.connection_points.set_expected_output_types_function(this._expected_output_types.bind(this))}_gl_output_name(){return\\\\\\\"mix\\\\\\\"}_expected_input_types(){const t=this.io.connection_points.first_input_connection_type()||Uo.FLOAT;return[t,t,Uo.FLOAT]}_expected_output_types(){return[this._expected_input_types()[0]]}}const sF=\\\\\\\"mvMult\\\\\\\";const rF=new class extends ua{constructor(){super(...arguments),this.vector=ha.VECTOR3([0,0,0])}};class oF extends gf{constructor(){super(...arguments),this.paramsConfig=rF}static type(){return\\\\\\\"modelViewMatrixMult\\\\\\\"}initializeNode(){super.initializeNode(),this.io.outputs.setNamedOutputConnectionPoints([new qo(sF,Uo.VEC4)])}setLines(t){if(t.current_shader_name==Mf.VERTEX){const e=mf.vector3(this.variableForInputParam(this.p.vector)),n=`vec4 ${this.glVarName(sF)} = modelViewMatrix * vec4(${e}, 1.0)`;t.addBodyLines(this,[n],Mf.VERTEX)}}}const aF={mult:1};var lF;!function(t){t.VALUE=\\\\\\\"value\\\\\\\",t.PRE_ADD=\\\\\\\"preAdd\\\\\\\",t.MULT=\\\\\\\"mult\\\\\\\",t.POST_ADD=\\\\\\\"postAdd\\\\\\\"}(lF||(lF={}));class cF extends PP{static type(){return\\\\\\\"multAdd\\\\\\\"}_gl_input_name(t){return[lF.VALUE,lF.PRE_ADD,lF.MULT,lF.POST_ADD][t]}paramDefaultValue(t){return aF[t]}setLines(t){const e=mf.any(this.variableForInput(lF.VALUE)),n=mf.any(this.variableForInput(lF.PRE_ADD)),i=mf.any(this.variableForInput(lF.MULT)),s=mf.any(this.variableForInput(lF.POST_ADD)),r=this._expected_output_types()[0],o=this.io.outputs.namedOutputConnectionPoints()[0].name(),a=`${r} ${this.glVarName(o)} = (${i}*(${e} + ${n})) + ${s}`;t.addBodyLines(this,[a])}}class hF extends NP{static type(){return\\\\\\\"negate\\\\\\\"}initializeNode(){super.initializeNode(),this.io.connection_points.set_input_name_function((t=>[\\\\\\\"in\\\\\\\"][t]))}_gl_input_name(t){return[\\\\\\\"in\\\\\\\"][t]}setLines(t){const e=mf.any(this.variableForInput(this._gl_input_name(0))),n=`${this.io.inputs.namedInputConnectionPoints()[0].type()} ${this.glVarName(this.io.connection_points.output_name(0))} = -1.0 * ${e}`;t.addBodyLines(this,[n])}}var uF;!function(t){t.CLASSIC_PERLIN_2D=\\\\\\\"Classic Perlin 2D\\\\\\\",t.CLASSIC_PERLIN_3D=\\\\\\\"Classic Perlin 3D\\\\\\\",t.CLASSIC_PERLIN_4D=\\\\\\\"Classic Perlin 4D\\\\\\\",t.NOISE_2D=\\\\\\\"noise2D\\\\\\\",t.NOISE_3D=\\\\\\\"noise3D\\\\\\\",t.NOISE_4D=\\\\\\\"noise4D\\\\\\\"}(uF||(uF={}));const dF=[uF.CLASSIC_PERLIN_2D,uF.CLASSIC_PERLIN_3D,uF.CLASSIC_PERLIN_4D,uF.NOISE_2D,uF.NOISE_3D,uF.NOISE_4D],pF={[uF.CLASSIC_PERLIN_2D]:'//\\\\n// GLSL textureless classic 2D noise \\\\\\\"cnoise\\\\\\\",\\\\n// with an RSL-style periodic variant \\\\\\\"pnoise\\\\\\\".\\\\n// Author: Stefan Gustavson (stefan.gustavson@liu.se)\\\\n// Version: 2011-08-22\\\\n//\\\\n// Many thanks to Ian McEwan of Ashima Arts for the\\\\n// ideas for permutation and gradient selection.\\\\n//\\\\n// Copyright (c) 2011 Stefan Gustavson. All rights reserved.\\\\n// Distributed under the MIT license. See LICENSE file.\\\\n// https://github.com/stegu/webgl-noise\\\\n//\\\\n\\\\n\\\\n// Classic Perlin noise\\\\nfloat cnoise(vec2 P)\\\\n{\\\\n vec4 Pi = floor(P.xyxy) + vec4(0.0, 0.0, 1.0, 1.0);\\\\n vec4 Pf = fract(P.xyxy) - vec4(0.0, 0.0, 1.0, 1.0);\\\\n Pi = mod289(Pi); // To avoid truncation effects in permutation\\\\n vec4 ix = Pi.xzxz;\\\\n vec4 iy = Pi.yyww;\\\\n vec4 fx = Pf.xzxz;\\\\n vec4 fy = Pf.yyww;\\\\n\\\\n vec4 i = permute(permute(ix) + iy);\\\\n\\\\n vec4 gx = fract(i * (1.0 / 41.0)) * 2.0 - 1.0 ;\\\\n vec4 gy = abs(gx) - 0.5 ;\\\\n vec4 tx = floor(gx + 0.5);\\\\n gx = gx - tx;\\\\n\\\\n vec2 g00 = vec2(gx.x,gy.x);\\\\n vec2 g10 = vec2(gx.y,gy.y);\\\\n vec2 g01 = vec2(gx.z,gy.z);\\\\n vec2 g11 = vec2(gx.w,gy.w);\\\\n\\\\n vec4 norm = taylorInvSqrt(vec4(dot(g00, g00), dot(g01, g01), dot(g10, g10), dot(g11, g11)));\\\\n g00 *= norm.x; \\\\n g01 *= norm.y; \\\\n g10 *= norm.z; \\\\n g11 *= norm.w; \\\\n\\\\n float n00 = dot(g00, vec2(fx.x, fy.x));\\\\n float n10 = dot(g10, vec2(fx.y, fy.y));\\\\n float n01 = dot(g01, vec2(fx.z, fy.z));\\\\n float n11 = dot(g11, vec2(fx.w, fy.w));\\\\n\\\\n vec2 fade_xy = fade(Pf.xy);\\\\n vec2 n_x = mix(vec2(n00, n01), vec2(n10, n11), fade_xy.x);\\\\n float n_xy = mix(n_x.x, n_x.y, fade_xy.y);\\\\n return 2.3 * n_xy;\\\\n}\\\\n\\\\n// Classic Perlin noise, periodic variant\\\\nfloat pnoise(vec2 P, vec2 rep)\\\\n{\\\\n vec4 Pi = floor(P.xyxy) + vec4(0.0, 0.0, 1.0, 1.0);\\\\n vec4 Pf = fract(P.xyxy) - vec4(0.0, 0.0, 1.0, 1.0);\\\\n Pi = mod(Pi, rep.xyxy); // To create noise with explicit period\\\\n Pi = mod289(Pi); // To avoid truncation effects in permutation\\\\n vec4 ix = Pi.xzxz;\\\\n vec4 iy = Pi.yyww;\\\\n vec4 fx = Pf.xzxz;\\\\n vec4 fy = Pf.yyww;\\\\n\\\\n vec4 i = permute(permute(ix) + iy);\\\\n\\\\n vec4 gx = fract(i * (1.0 / 41.0)) * 2.0 - 1.0 ;\\\\n vec4 gy = abs(gx) - 0.5 ;\\\\n vec4 tx = floor(gx + 0.5);\\\\n gx = gx - tx;\\\\n\\\\n vec2 g00 = vec2(gx.x,gy.x);\\\\n vec2 g10 = vec2(gx.y,gy.y);\\\\n vec2 g01 = vec2(gx.z,gy.z);\\\\n vec2 g11 = vec2(gx.w,gy.w);\\\\n\\\\n vec4 norm = taylorInvSqrt(vec4(dot(g00, g00), dot(g01, g01), dot(g10, g10), dot(g11, g11)));\\\\n g00 *= norm.x; \\\\n g01 *= norm.y; \\\\n g10 *= norm.z; \\\\n g11 *= norm.w; \\\\n\\\\n float n00 = dot(g00, vec2(fx.x, fy.x));\\\\n float n10 = dot(g10, vec2(fx.y, fy.y));\\\\n float n01 = dot(g01, vec2(fx.z, fy.z));\\\\n float n11 = dot(g11, vec2(fx.w, fy.w));\\\\n\\\\n vec2 fade_xy = fade(Pf.xy);\\\\n vec2 n_x = mix(vec2(n00, n01), vec2(n10, n11), fade_xy.x);\\\\n float n_xy = mix(n_x.x, n_x.y, fade_xy.y);\\\\n return 2.3 * n_xy;\\\\n}\\\\n',[uF.CLASSIC_PERLIN_3D]:'//\\\\n// GLSL textureless classic 3D noise \\\\\\\"cnoise\\\\\\\",\\\\n// with an RSL-style periodic variant \\\\\\\"pnoise\\\\\\\".\\\\n// Author: Stefan Gustavson (stefan.gustavson@liu.se)\\\\n// Version: 2011-10-11\\\\n//\\\\n// Many thanks to Ian McEwan of Ashima Arts for the\\\\n// ideas for permutation and gradient selection.\\\\n//\\\\n// Copyright (c) 2011 Stefan Gustavson. All rights reserved.\\\\n// Distributed under the MIT license. See LICENSE file.\\\\n// https://github.com/stegu/webgl-noise\\\\n//\\\\n\\\\n// Classic Perlin noise\\\\nfloat cnoise(vec3 P)\\\\n{\\\\n vec3 Pi0 = floor(P); // Integer part for indexing\\\\n vec3 Pi1 = Pi0 + vec3(1.0); // Integer part + 1\\\\n Pi0 = mod289(Pi0);\\\\n Pi1 = mod289(Pi1);\\\\n vec3 Pf0 = fract(P); // Fractional part for interpolation\\\\n vec3 Pf1 = Pf0 - vec3(1.0); // Fractional part - 1.0\\\\n vec4 ix = vec4(Pi0.x, Pi1.x, Pi0.x, Pi1.x);\\\\n vec4 iy = vec4(Pi0.yy, Pi1.yy);\\\\n vec4 iz0 = Pi0.zzzz;\\\\n vec4 iz1 = Pi1.zzzz;\\\\n\\\\n vec4 ixy = permute(permute(ix) + iy);\\\\n vec4 ixy0 = permute(ixy + iz0);\\\\n vec4 ixy1 = permute(ixy + iz1);\\\\n\\\\n vec4 gx0 = ixy0 * (1.0 / 7.0);\\\\n vec4 gy0 = fract(floor(gx0) * (1.0 / 7.0)) - 0.5;\\\\n gx0 = fract(gx0);\\\\n vec4 gz0 = vec4(0.5) - abs(gx0) - abs(gy0);\\\\n vec4 sz0 = step(gz0, vec4(0.0));\\\\n gx0 -= sz0 * (step(0.0, gx0) - 0.5);\\\\n gy0 -= sz0 * (step(0.0, gy0) - 0.5);\\\\n\\\\n vec4 gx1 = ixy1 * (1.0 / 7.0);\\\\n vec4 gy1 = fract(floor(gx1) * (1.0 / 7.0)) - 0.5;\\\\n gx1 = fract(gx1);\\\\n vec4 gz1 = vec4(0.5) - abs(gx1) - abs(gy1);\\\\n vec4 sz1 = step(gz1, vec4(0.0));\\\\n gx1 -= sz1 * (step(0.0, gx1) - 0.5);\\\\n gy1 -= sz1 * (step(0.0, gy1) - 0.5);\\\\n\\\\n vec3 g000 = vec3(gx0.x,gy0.x,gz0.x);\\\\n vec3 g100 = vec3(gx0.y,gy0.y,gz0.y);\\\\n vec3 g010 = vec3(gx0.z,gy0.z,gz0.z);\\\\n vec3 g110 = vec3(gx0.w,gy0.w,gz0.w);\\\\n vec3 g001 = vec3(gx1.x,gy1.x,gz1.x);\\\\n vec3 g101 = vec3(gx1.y,gy1.y,gz1.y);\\\\n vec3 g011 = vec3(gx1.z,gy1.z,gz1.z);\\\\n vec3 g111 = vec3(gx1.w,gy1.w,gz1.w);\\\\n\\\\n vec4 norm0 = taylorInvSqrt(vec4(dot(g000, g000), dot(g010, g010), dot(g100, g100), dot(g110, g110)));\\\\n g000 *= norm0.x;\\\\n g010 *= norm0.y;\\\\n g100 *= norm0.z;\\\\n g110 *= norm0.w;\\\\n vec4 norm1 = taylorInvSqrt(vec4(dot(g001, g001), dot(g011, g011), dot(g101, g101), dot(g111, g111)));\\\\n g001 *= norm1.x;\\\\n g011 *= norm1.y;\\\\n g101 *= norm1.z;\\\\n g111 *= norm1.w;\\\\n\\\\n float n000 = dot(g000, Pf0);\\\\n float n100 = dot(g100, vec3(Pf1.x, Pf0.yz));\\\\n float n010 = dot(g010, vec3(Pf0.x, Pf1.y, Pf0.z));\\\\n float n110 = dot(g110, vec3(Pf1.xy, Pf0.z));\\\\n float n001 = dot(g001, vec3(Pf0.xy, Pf1.z));\\\\n float n101 = dot(g101, vec3(Pf1.x, Pf0.y, Pf1.z));\\\\n float n011 = dot(g011, vec3(Pf0.x, Pf1.yz));\\\\n float n111 = dot(g111, Pf1);\\\\n\\\\n vec3 fade_xyz = fade(Pf0);\\\\n vec4 n_z = mix(vec4(n000, n100, n010, n110), vec4(n001, n101, n011, n111), fade_xyz.z);\\\\n vec2 n_yz = mix(n_z.xy, n_z.zw, fade_xyz.y);\\\\n float n_xyz = mix(n_yz.x, n_yz.y, fade_xyz.x); \\\\n return 2.2 * n_xyz;\\\\n}\\\\n\\\\n// Classic Perlin noise, periodic variant\\\\nfloat pnoise(vec3 P, vec3 rep)\\\\n{\\\\n vec3 Pi0 = mod(floor(P), rep); // Integer part, modulo period\\\\n vec3 Pi1 = mod(Pi0 + vec3(1.0), rep); // Integer part + 1, mod period\\\\n Pi0 = mod289(Pi0);\\\\n Pi1 = mod289(Pi1);\\\\n vec3 Pf0 = fract(P); // Fractional part for interpolation\\\\n vec3 Pf1 = Pf0 - vec3(1.0); // Fractional part - 1.0\\\\n vec4 ix = vec4(Pi0.x, Pi1.x, Pi0.x, Pi1.x);\\\\n vec4 iy = vec4(Pi0.yy, Pi1.yy);\\\\n vec4 iz0 = Pi0.zzzz;\\\\n vec4 iz1 = Pi1.zzzz;\\\\n\\\\n vec4 ixy = permute(permute(ix) + iy);\\\\n vec4 ixy0 = permute(ixy + iz0);\\\\n vec4 ixy1 = permute(ixy + iz1);\\\\n\\\\n vec4 gx0 = ixy0 * (1.0 / 7.0);\\\\n vec4 gy0 = fract(floor(gx0) * (1.0 / 7.0)) - 0.5;\\\\n gx0 = fract(gx0);\\\\n vec4 gz0 = vec4(0.5) - abs(gx0) - abs(gy0);\\\\n vec4 sz0 = step(gz0, vec4(0.0));\\\\n gx0 -= sz0 * (step(0.0, gx0) - 0.5);\\\\n gy0 -= sz0 * (step(0.0, gy0) - 0.5);\\\\n\\\\n vec4 gx1 = ixy1 * (1.0 / 7.0);\\\\n vec4 gy1 = fract(floor(gx1) * (1.0 / 7.0)) - 0.5;\\\\n gx1 = fract(gx1);\\\\n vec4 gz1 = vec4(0.5) - abs(gx1) - abs(gy1);\\\\n vec4 sz1 = step(gz1, vec4(0.0));\\\\n gx1 -= sz1 * (step(0.0, gx1) - 0.5);\\\\n gy1 -= sz1 * (step(0.0, gy1) - 0.5);\\\\n\\\\n vec3 g000 = vec3(gx0.x,gy0.x,gz0.x);\\\\n vec3 g100 = vec3(gx0.y,gy0.y,gz0.y);\\\\n vec3 g010 = vec3(gx0.z,gy0.z,gz0.z);\\\\n vec3 g110 = vec3(gx0.w,gy0.w,gz0.w);\\\\n vec3 g001 = vec3(gx1.x,gy1.x,gz1.x);\\\\n vec3 g101 = vec3(gx1.y,gy1.y,gz1.y);\\\\n vec3 g011 = vec3(gx1.z,gy1.z,gz1.z);\\\\n vec3 g111 = vec3(gx1.w,gy1.w,gz1.w);\\\\n\\\\n vec4 norm0 = taylorInvSqrt(vec4(dot(g000, g000), dot(g010, g010), dot(g100, g100), dot(g110, g110)));\\\\n g000 *= norm0.x;\\\\n g010 *= norm0.y;\\\\n g100 *= norm0.z;\\\\n g110 *= norm0.w;\\\\n vec4 norm1 = taylorInvSqrt(vec4(dot(g001, g001), dot(g011, g011), dot(g101, g101), dot(g111, g111)));\\\\n g001 *= norm1.x;\\\\n g011 *= norm1.y;\\\\n g101 *= norm1.z;\\\\n g111 *= norm1.w;\\\\n\\\\n float n000 = dot(g000, Pf0);\\\\n float n100 = dot(g100, vec3(Pf1.x, Pf0.yz));\\\\n float n010 = dot(g010, vec3(Pf0.x, Pf1.y, Pf0.z));\\\\n float n110 = dot(g110, vec3(Pf1.xy, Pf0.z));\\\\n float n001 = dot(g001, vec3(Pf0.xy, Pf1.z));\\\\n float n101 = dot(g101, vec3(Pf1.x, Pf0.y, Pf1.z));\\\\n float n011 = dot(g011, vec3(Pf0.x, Pf1.yz));\\\\n float n111 = dot(g111, Pf1);\\\\n\\\\n vec3 fade_xyz = fade(Pf0);\\\\n vec4 n_z = mix(vec4(n000, n100, n010, n110), vec4(n001, n101, n011, n111), fade_xyz.z);\\\\n vec2 n_yz = mix(n_z.xy, n_z.zw, fade_xyz.y);\\\\n float n_xyz = mix(n_yz.x, n_yz.y, fade_xyz.x); \\\\n return 2.2 * n_xyz;\\\\n}\\\\n',[uF.CLASSIC_PERLIN_4D]:'//\\\\n// GLSL textureless classic 4D noise \\\\\\\"cnoise\\\\\\\",\\\\n// with an RSL-style periodic variant \\\\\\\"pnoise\\\\\\\".\\\\n// Author: Stefan Gustavson (stefan.gustavson@liu.se)\\\\n// Version: 2011-08-22\\\\n//\\\\n// Many thanks to Ian McEwan of Ashima Arts for the\\\\n// ideas for permutation and gradient selection.\\\\n//\\\\n// Copyright (c) 2011 Stefan Gustavson. All rights reserved.\\\\n// Distributed under the MIT license. See LICENSE file.\\\\n// https://github.com/stegu/webgl-noise\\\\n//\\\\n\\\\n\\\\n\\\\n// Classic Perlin noise\\\\nfloat cnoise(vec4 P)\\\\n{\\\\n vec4 Pi0 = floor(P); // Integer part for indexing\\\\n vec4 Pi1 = Pi0 + 1.0; // Integer part + 1\\\\n Pi0 = mod289(Pi0);\\\\n Pi1 = mod289(Pi1);\\\\n vec4 Pf0 = fract(P); // Fractional part for interpolation\\\\n vec4 Pf1 = Pf0 - 1.0; // Fractional part - 1.0\\\\n vec4 ix = vec4(Pi0.x, Pi1.x, Pi0.x, Pi1.x);\\\\n vec4 iy = vec4(Pi0.yy, Pi1.yy);\\\\n vec4 iz0 = vec4(Pi0.zzzz);\\\\n vec4 iz1 = vec4(Pi1.zzzz);\\\\n vec4 iw0 = vec4(Pi0.wwww);\\\\n vec4 iw1 = vec4(Pi1.wwww);\\\\n\\\\n vec4 ixy = permute(permute(ix) + iy);\\\\n vec4 ixy0 = permute(ixy + iz0);\\\\n vec4 ixy1 = permute(ixy + iz1);\\\\n vec4 ixy00 = permute(ixy0 + iw0);\\\\n vec4 ixy01 = permute(ixy0 + iw1);\\\\n vec4 ixy10 = permute(ixy1 + iw0);\\\\n vec4 ixy11 = permute(ixy1 + iw1);\\\\n\\\\n vec4 gx00 = ixy00 * (1.0 / 7.0);\\\\n vec4 gy00 = floor(gx00) * (1.0 / 7.0);\\\\n vec4 gz00 = floor(gy00) * (1.0 / 6.0);\\\\n gx00 = fract(gx00) - 0.5;\\\\n gy00 = fract(gy00) - 0.5;\\\\n gz00 = fract(gz00) - 0.5;\\\\n vec4 gw00 = vec4(0.75) - abs(gx00) - abs(gy00) - abs(gz00);\\\\n vec4 sw00 = step(gw00, vec4(0.0));\\\\n gx00 -= sw00 * (step(0.0, gx00) - 0.5);\\\\n gy00 -= sw00 * (step(0.0, gy00) - 0.5);\\\\n\\\\n vec4 gx01 = ixy01 * (1.0 / 7.0);\\\\n vec4 gy01 = floor(gx01) * (1.0 / 7.0);\\\\n vec4 gz01 = floor(gy01) * (1.0 / 6.0);\\\\n gx01 = fract(gx01) - 0.5;\\\\n gy01 = fract(gy01) - 0.5;\\\\n gz01 = fract(gz01) - 0.5;\\\\n vec4 gw01 = vec4(0.75) - abs(gx01) - abs(gy01) - abs(gz01);\\\\n vec4 sw01 = step(gw01, vec4(0.0));\\\\n gx01 -= sw01 * (step(0.0, gx01) - 0.5);\\\\n gy01 -= sw01 * (step(0.0, gy01) - 0.5);\\\\n\\\\n vec4 gx10 = ixy10 * (1.0 / 7.0);\\\\n vec4 gy10 = floor(gx10) * (1.0 / 7.0);\\\\n vec4 gz10 = floor(gy10) * (1.0 / 6.0);\\\\n gx10 = fract(gx10) - 0.5;\\\\n gy10 = fract(gy10) - 0.5;\\\\n gz10 = fract(gz10) - 0.5;\\\\n vec4 gw10 = vec4(0.75) - abs(gx10) - abs(gy10) - abs(gz10);\\\\n vec4 sw10 = step(gw10, vec4(0.0));\\\\n gx10 -= sw10 * (step(0.0, gx10) - 0.5);\\\\n gy10 -= sw10 * (step(0.0, gy10) - 0.5);\\\\n\\\\n vec4 gx11 = ixy11 * (1.0 / 7.0);\\\\n vec4 gy11 = floor(gx11) * (1.0 / 7.0);\\\\n vec4 gz11 = floor(gy11) * (1.0 / 6.0);\\\\n gx11 = fract(gx11) - 0.5;\\\\n gy11 = fract(gy11) - 0.5;\\\\n gz11 = fract(gz11) - 0.5;\\\\n vec4 gw11 = vec4(0.75) - abs(gx11) - abs(gy11) - abs(gz11);\\\\n vec4 sw11 = step(gw11, vec4(0.0));\\\\n gx11 -= sw11 * (step(0.0, gx11) - 0.5);\\\\n gy11 -= sw11 * (step(0.0, gy11) - 0.5);\\\\n\\\\n vec4 g0000 = vec4(gx00.x,gy00.x,gz00.x,gw00.x);\\\\n vec4 g1000 = vec4(gx00.y,gy00.y,gz00.y,gw00.y);\\\\n vec4 g0100 = vec4(gx00.z,gy00.z,gz00.z,gw00.z);\\\\n vec4 g1100 = vec4(gx00.w,gy00.w,gz00.w,gw00.w);\\\\n vec4 g0010 = vec4(gx10.x,gy10.x,gz10.x,gw10.x);\\\\n vec4 g1010 = vec4(gx10.y,gy10.y,gz10.y,gw10.y);\\\\n vec4 g0110 = vec4(gx10.z,gy10.z,gz10.z,gw10.z);\\\\n vec4 g1110 = vec4(gx10.w,gy10.w,gz10.w,gw10.w);\\\\n vec4 g0001 = vec4(gx01.x,gy01.x,gz01.x,gw01.x);\\\\n vec4 g1001 = vec4(gx01.y,gy01.y,gz01.y,gw01.y);\\\\n vec4 g0101 = vec4(gx01.z,gy01.z,gz01.z,gw01.z);\\\\n vec4 g1101 = vec4(gx01.w,gy01.w,gz01.w,gw01.w);\\\\n vec4 g0011 = vec4(gx11.x,gy11.x,gz11.x,gw11.x);\\\\n vec4 g1011 = vec4(gx11.y,gy11.y,gz11.y,gw11.y);\\\\n vec4 g0111 = vec4(gx11.z,gy11.z,gz11.z,gw11.z);\\\\n vec4 g1111 = vec4(gx11.w,gy11.w,gz11.w,gw11.w);\\\\n\\\\n vec4 norm00 = taylorInvSqrt(vec4(dot(g0000, g0000), dot(g0100, g0100), dot(g1000, g1000), dot(g1100, g1100)));\\\\n g0000 *= norm00.x;\\\\n g0100 *= norm00.y;\\\\n g1000 *= norm00.z;\\\\n g1100 *= norm00.w;\\\\n\\\\n vec4 norm01 = taylorInvSqrt(vec4(dot(g0001, g0001), dot(g0101, g0101), dot(g1001, g1001), dot(g1101, g1101)));\\\\n g0001 *= norm01.x;\\\\n g0101 *= norm01.y;\\\\n g1001 *= norm01.z;\\\\n g1101 *= norm01.w;\\\\n\\\\n vec4 norm10 = taylorInvSqrt(vec4(dot(g0010, g0010), dot(g0110, g0110), dot(g1010, g1010), dot(g1110, g1110)));\\\\n g0010 *= norm10.x;\\\\n g0110 *= norm10.y;\\\\n g1010 *= norm10.z;\\\\n g1110 *= norm10.w;\\\\n\\\\n vec4 norm11 = taylorInvSqrt(vec4(dot(g0011, g0011), dot(g0111, g0111), dot(g1011, g1011), dot(g1111, g1111)));\\\\n g0011 *= norm11.x;\\\\n g0111 *= norm11.y;\\\\n g1011 *= norm11.z;\\\\n g1111 *= norm11.w;\\\\n\\\\n float n0000 = dot(g0000, Pf0);\\\\n float n1000 = dot(g1000, vec4(Pf1.x, Pf0.yzw));\\\\n float n0100 = dot(g0100, vec4(Pf0.x, Pf1.y, Pf0.zw));\\\\n float n1100 = dot(g1100, vec4(Pf1.xy, Pf0.zw));\\\\n float n0010 = dot(g0010, vec4(Pf0.xy, Pf1.z, Pf0.w));\\\\n float n1010 = dot(g1010, vec4(Pf1.x, Pf0.y, Pf1.z, Pf0.w));\\\\n float n0110 = dot(g0110, vec4(Pf0.x, Pf1.yz, Pf0.w));\\\\n float n1110 = dot(g1110, vec4(Pf1.xyz, Pf0.w));\\\\n float n0001 = dot(g0001, vec4(Pf0.xyz, Pf1.w));\\\\n float n1001 = dot(g1001, vec4(Pf1.x, Pf0.yz, Pf1.w));\\\\n float n0101 = dot(g0101, vec4(Pf0.x, Pf1.y, Pf0.z, Pf1.w));\\\\n float n1101 = dot(g1101, vec4(Pf1.xy, Pf0.z, Pf1.w));\\\\n float n0011 = dot(g0011, vec4(Pf0.xy, Pf1.zw));\\\\n float n1011 = dot(g1011, vec4(Pf1.x, Pf0.y, Pf1.zw));\\\\n float n0111 = dot(g0111, vec4(Pf0.x, Pf1.yzw));\\\\n float n1111 = dot(g1111, Pf1);\\\\n\\\\n vec4 fade_xyzw = fade(Pf0);\\\\n vec4 n_0w = mix(vec4(n0000, n1000, n0100, n1100), vec4(n0001, n1001, n0101, n1101), fade_xyzw.w);\\\\n vec4 n_1w = mix(vec4(n0010, n1010, n0110, n1110), vec4(n0011, n1011, n0111, n1111), fade_xyzw.w);\\\\n vec4 n_zw = mix(n_0w, n_1w, fade_xyzw.z);\\\\n vec2 n_yzw = mix(n_zw.xy, n_zw.zw, fade_xyzw.y);\\\\n float n_xyzw = mix(n_yzw.x, n_yzw.y, fade_xyzw.x);\\\\n return 2.2 * n_xyzw;\\\\n}\\\\n\\\\n// Classic Perlin noise, periodic version\\\\nfloat pnoise(vec4 P, vec4 rep)\\\\n{\\\\n vec4 Pi0 = mod(floor(P), rep); // Integer part modulo rep\\\\n vec4 Pi1 = mod(Pi0 + 1.0, rep); // Integer part + 1 mod rep\\\\n Pi0 = mod289(Pi0);\\\\n Pi1 = mod289(Pi1);\\\\n vec4 Pf0 = fract(P); // Fractional part for interpolation\\\\n vec4 Pf1 = Pf0 - 1.0; // Fractional part - 1.0\\\\n vec4 ix = vec4(Pi0.x, Pi1.x, Pi0.x, Pi1.x);\\\\n vec4 iy = vec4(Pi0.yy, Pi1.yy);\\\\n vec4 iz0 = vec4(Pi0.zzzz);\\\\n vec4 iz1 = vec4(Pi1.zzzz);\\\\n vec4 iw0 = vec4(Pi0.wwww);\\\\n vec4 iw1 = vec4(Pi1.wwww);\\\\n\\\\n vec4 ixy = permute(permute(ix) + iy);\\\\n vec4 ixy0 = permute(ixy + iz0);\\\\n vec4 ixy1 = permute(ixy + iz1);\\\\n vec4 ixy00 = permute(ixy0 + iw0);\\\\n vec4 ixy01 = permute(ixy0 + iw1);\\\\n vec4 ixy10 = permute(ixy1 + iw0);\\\\n vec4 ixy11 = permute(ixy1 + iw1);\\\\n\\\\n vec4 gx00 = ixy00 * (1.0 / 7.0);\\\\n vec4 gy00 = floor(gx00) * (1.0 / 7.0);\\\\n vec4 gz00 = floor(gy00) * (1.0 / 6.0);\\\\n gx00 = fract(gx00) - 0.5;\\\\n gy00 = fract(gy00) - 0.5;\\\\n gz00 = fract(gz00) - 0.5;\\\\n vec4 gw00 = vec4(0.75) - abs(gx00) - abs(gy00) - abs(gz00);\\\\n vec4 sw00 = step(gw00, vec4(0.0));\\\\n gx00 -= sw00 * (step(0.0, gx00) - 0.5);\\\\n gy00 -= sw00 * (step(0.0, gy00) - 0.5);\\\\n\\\\n vec4 gx01 = ixy01 * (1.0 / 7.0);\\\\n vec4 gy01 = floor(gx01) * (1.0 / 7.0);\\\\n vec4 gz01 = floor(gy01) * (1.0 / 6.0);\\\\n gx01 = fract(gx01) - 0.5;\\\\n gy01 = fract(gy01) - 0.5;\\\\n gz01 = fract(gz01) - 0.5;\\\\n vec4 gw01 = vec4(0.75) - abs(gx01) - abs(gy01) - abs(gz01);\\\\n vec4 sw01 = step(gw01, vec4(0.0));\\\\n gx01 -= sw01 * (step(0.0, gx01) - 0.5);\\\\n gy01 -= sw01 * (step(0.0, gy01) - 0.5);\\\\n\\\\n vec4 gx10 = ixy10 * (1.0 / 7.0);\\\\n vec4 gy10 = floor(gx10) * (1.0 / 7.0);\\\\n vec4 gz10 = floor(gy10) * (1.0 / 6.0);\\\\n gx10 = fract(gx10) - 0.5;\\\\n gy10 = fract(gy10) - 0.5;\\\\n gz10 = fract(gz10) - 0.5;\\\\n vec4 gw10 = vec4(0.75) - abs(gx10) - abs(gy10) - abs(gz10);\\\\n vec4 sw10 = step(gw10, vec4(0.0));\\\\n gx10 -= sw10 * (step(0.0, gx10) - 0.5);\\\\n gy10 -= sw10 * (step(0.0, gy10) - 0.5);\\\\n\\\\n vec4 gx11 = ixy11 * (1.0 / 7.0);\\\\n vec4 gy11 = floor(gx11) * (1.0 / 7.0);\\\\n vec4 gz11 = floor(gy11) * (1.0 / 6.0);\\\\n gx11 = fract(gx11) - 0.5;\\\\n gy11 = fract(gy11) - 0.5;\\\\n gz11 = fract(gz11) - 0.5;\\\\n vec4 gw11 = vec4(0.75) - abs(gx11) - abs(gy11) - abs(gz11);\\\\n vec4 sw11 = step(gw11, vec4(0.0));\\\\n gx11 -= sw11 * (step(0.0, gx11) - 0.5);\\\\n gy11 -= sw11 * (step(0.0, gy11) - 0.5);\\\\n\\\\n vec4 g0000 = vec4(gx00.x,gy00.x,gz00.x,gw00.x);\\\\n vec4 g1000 = vec4(gx00.y,gy00.y,gz00.y,gw00.y);\\\\n vec4 g0100 = vec4(gx00.z,gy00.z,gz00.z,gw00.z);\\\\n vec4 g1100 = vec4(gx00.w,gy00.w,gz00.w,gw00.w);\\\\n vec4 g0010 = vec4(gx10.x,gy10.x,gz10.x,gw10.x);\\\\n vec4 g1010 = vec4(gx10.y,gy10.y,gz10.y,gw10.y);\\\\n vec4 g0110 = vec4(gx10.z,gy10.z,gz10.z,gw10.z);\\\\n vec4 g1110 = vec4(gx10.w,gy10.w,gz10.w,gw10.w);\\\\n vec4 g0001 = vec4(gx01.x,gy01.x,gz01.x,gw01.x);\\\\n vec4 g1001 = vec4(gx01.y,gy01.y,gz01.y,gw01.y);\\\\n vec4 g0101 = vec4(gx01.z,gy01.z,gz01.z,gw01.z);\\\\n vec4 g1101 = vec4(gx01.w,gy01.w,gz01.w,gw01.w);\\\\n vec4 g0011 = vec4(gx11.x,gy11.x,gz11.x,gw11.x);\\\\n vec4 g1011 = vec4(gx11.y,gy11.y,gz11.y,gw11.y);\\\\n vec4 g0111 = vec4(gx11.z,gy11.z,gz11.z,gw11.z);\\\\n vec4 g1111 = vec4(gx11.w,gy11.w,gz11.w,gw11.w);\\\\n\\\\n vec4 norm00 = taylorInvSqrt(vec4(dot(g0000, g0000), dot(g0100, g0100), dot(g1000, g1000), dot(g1100, g1100)));\\\\n g0000 *= norm00.x;\\\\n g0100 *= norm00.y;\\\\n g1000 *= norm00.z;\\\\n g1100 *= norm00.w;\\\\n\\\\n vec4 norm01 = taylorInvSqrt(vec4(dot(g0001, g0001), dot(g0101, g0101), dot(g1001, g1001), dot(g1101, g1101)));\\\\n g0001 *= norm01.x;\\\\n g0101 *= norm01.y;\\\\n g1001 *= norm01.z;\\\\n g1101 *= norm01.w;\\\\n\\\\n vec4 norm10 = taylorInvSqrt(vec4(dot(g0010, g0010), dot(g0110, g0110), dot(g1010, g1010), dot(g1110, g1110)));\\\\n g0010 *= norm10.x;\\\\n g0110 *= norm10.y;\\\\n g1010 *= norm10.z;\\\\n g1110 *= norm10.w;\\\\n\\\\n vec4 norm11 = taylorInvSqrt(vec4(dot(g0011, g0011), dot(g0111, g0111), dot(g1011, g1011), dot(g1111, g1111)));\\\\n g0011 *= norm11.x;\\\\n g0111 *= norm11.y;\\\\n g1011 *= norm11.z;\\\\n g1111 *= norm11.w;\\\\n\\\\n float n0000 = dot(g0000, Pf0);\\\\n float n1000 = dot(g1000, vec4(Pf1.x, Pf0.yzw));\\\\n float n0100 = dot(g0100, vec4(Pf0.x, Pf1.y, Pf0.zw));\\\\n float n1100 = dot(g1100, vec4(Pf1.xy, Pf0.zw));\\\\n float n0010 = dot(g0010, vec4(Pf0.xy, Pf1.z, Pf0.w));\\\\n float n1010 = dot(g1010, vec4(Pf1.x, Pf0.y, Pf1.z, Pf0.w));\\\\n float n0110 = dot(g0110, vec4(Pf0.x, Pf1.yz, Pf0.w));\\\\n float n1110 = dot(g1110, vec4(Pf1.xyz, Pf0.w));\\\\n float n0001 = dot(g0001, vec4(Pf0.xyz, Pf1.w));\\\\n float n1001 = dot(g1001, vec4(Pf1.x, Pf0.yz, Pf1.w));\\\\n float n0101 = dot(g0101, vec4(Pf0.x, Pf1.y, Pf0.z, Pf1.w));\\\\n float n1101 = dot(g1101, vec4(Pf1.xy, Pf0.z, Pf1.w));\\\\n float n0011 = dot(g0011, vec4(Pf0.xy, Pf1.zw));\\\\n float n1011 = dot(g1011, vec4(Pf1.x, Pf0.y, Pf1.zw));\\\\n float n0111 = dot(g0111, vec4(Pf0.x, Pf1.yzw));\\\\n float n1111 = dot(g1111, Pf1);\\\\n\\\\n vec4 fade_xyzw = fade(Pf0);\\\\n vec4 n_0w = mix(vec4(n0000, n1000, n0100, n1100), vec4(n0001, n1001, n0101, n1101), fade_xyzw.w);\\\\n vec4 n_1w = mix(vec4(n0010, n1010, n0110, n1110), vec4(n0011, n1011, n0111, n1111), fade_xyzw.w);\\\\n vec4 n_zw = mix(n_0w, n_1w, fade_xyzw.z);\\\\n vec2 n_yzw = mix(n_zw.xy, n_zw.zw, fade_xyzw.y);\\\\n float n_xyzw = mix(n_yzw.x, n_yzw.y, fade_xyzw.x);\\\\n return 2.2 * n_xyzw;\\\\n}\\\\n',[uF.NOISE_2D]:\\\\\\\"//\\\\n// Description : Array and textureless GLSL 2D simplex noise function.\\\\n// Author : Ian McEwan, Ashima Arts.\\\\n// Maintainer : stegu\\\\n// Lastmod : 20110822 (ijm)\\\\n// License : Copyright (C) 2011 Ashima Arts. All rights reserved.\\\\n// Distributed under the MIT License. See LICENSE file.\\\\n// https://github.com/ashima/webgl-noise\\\\n// https://github.com/stegu/webgl-noise\\\\n// \\\\n\\\\n\\\\nfloat snoise(vec2 v)\\\\n {\\\\n const vec4 C = vec4(0.211324865405187, // (3.0-sqrt(3.0))/6.0\\\\n 0.366025403784439, // 0.5*(sqrt(3.0)-1.0)\\\\n -0.577350269189626, // -1.0 + 2.0 * C.x\\\\n 0.024390243902439); // 1.0 / 41.0\\\\n// First corner\\\\n vec2 i = floor(v + dot(v, C.yy) );\\\\n vec2 x0 = v - i + dot(i, C.xx);\\\\n\\\\n// Other corners\\\\n vec2 i1;\\\\n //i1.x = step( x0.y, x0.x ); // x0.x > x0.y ? 1.0 : 0.0\\\\n //i1.y = 1.0 - i1.x;\\\\n i1 = (x0.x > x0.y) ? vec2(1.0, 0.0) : vec2(0.0, 1.0);\\\\n // x0 = x0 - 0.0 + 0.0 * C.xx ;\\\\n // x1 = x0 - i1 + 1.0 * C.xx ;\\\\n // x2 = x0 - 1.0 + 2.0 * C.xx ;\\\\n vec4 x12 = x0.xyxy + C.xxzz;\\\\n x12.xy -= i1;\\\\n\\\\n// Permutations\\\\n i = mod289(i); // Avoid truncation effects in permutation\\\\n vec3 p = permute( permute( i.y + vec3(0.0, i1.y, 1.0 ))\\\\n\\\\t\\\\t+ i.x + vec3(0.0, i1.x, 1.0 ));\\\\n\\\\n vec3 m = max(0.5 - vec3(dot(x0,x0), dot(x12.xy,x12.xy), dot(x12.zw,x12.zw)), 0.0);\\\\n m = m*m ;\\\\n m = m*m ;\\\\n\\\\n// Gradients: 41 points uniformly over a line, mapped onto a diamond.\\\\n// The ring size 17*17 = 289 is close to a multiple of 41 (41*7 = 287)\\\\n\\\\n vec3 x = 2.0 * fract(p * C.www) - 1.0;\\\\n vec3 h = abs(x) - 0.5;\\\\n vec3 ox = floor(x + 0.5);\\\\n vec3 a0 = x - ox;\\\\n\\\\n// Normalise gradients implicitly by scaling m\\\\n// Approximation of: m *= inversesqrt( a0*a0 + h*h );\\\\n m *= 1.79284291400159 - 0.85373472095314 * ( a0*a0 + h*h );\\\\n\\\\n// Compute final noise value at P\\\\n vec3 g;\\\\n g.x = a0.x * x0.x + h.x * x0.y;\\\\n g.yz = a0.yz * x12.xz + h.yz * x12.yw;\\\\n return 130.0 * dot(m, g);\\\\n}\\\\n\\\\\\\",[uF.NOISE_3D]:\\\\\\\"//\\\\n// Description : Array and textureless GLSL 2D/3D/4D simplex \\\\n// noise functions.\\\\n// Author : Ian McEwan, Ashima Arts.\\\\n// Maintainer : stegu\\\\n// Lastmod : 20110822 (ijm)\\\\n// License : Copyright (C) 2011 Ashima Arts. All rights reserved.\\\\n// Distributed under the MIT License. See LICENSE file.\\\\n// https://github.com/ashima/webgl-noise\\\\n// https://github.com/stegu/webgl-noise\\\\n// \\\\n\\\\n\\\\n\\\\nfloat snoise(vec3 v)\\\\n { \\\\n const vec2 C = vec2(1.0/6.0, 1.0/3.0) ;\\\\n const vec4 D = vec4(0.0, 0.5, 1.0, 2.0);\\\\n\\\\n// First corner\\\\n vec3 i = floor(v + dot(v, C.yyy) );\\\\n vec3 x0 = v - i + dot(i, C.xxx) ;\\\\n\\\\n// Other corners\\\\n vec3 g = step(x0.yzx, x0.xyz);\\\\n vec3 l = 1.0 - g;\\\\n vec3 i1 = min( g.xyz, l.zxy );\\\\n vec3 i2 = max( g.xyz, l.zxy );\\\\n\\\\n // x0 = x0 - 0.0 + 0.0 * C.xxx;\\\\n // x1 = x0 - i1 + 1.0 * C.xxx;\\\\n // x2 = x0 - i2 + 2.0 * C.xxx;\\\\n // x3 = x0 - 1.0 + 3.0 * C.xxx;\\\\n vec3 x1 = x0 - i1 + C.xxx;\\\\n vec3 x2 = x0 - i2 + C.yyy; // 2.0*C.x = 1/3 = C.y\\\\n vec3 x3 = x0 - D.yyy; // -1.0+3.0*C.x = -0.5 = -D.y\\\\n\\\\n// Permutations\\\\n i = mod289(i); \\\\n vec4 p = permute( permute( permute( \\\\n i.z + vec4(0.0, i1.z, i2.z, 1.0 ))\\\\n + i.y + vec4(0.0, i1.y, i2.y, 1.0 )) \\\\n + i.x + vec4(0.0, i1.x, i2.x, 1.0 ));\\\\n\\\\n// Gradients: 7x7 points over a square, mapped onto an octahedron.\\\\n// The ring size 17*17 = 289 is close to a multiple of 49 (49*6 = 294)\\\\n float n_ = 0.142857142857; // 1.0/7.0\\\\n vec3 ns = n_ * D.wyz - D.xzx;\\\\n\\\\n vec4 j = p - 49.0 * floor(p * ns.z * ns.z); // mod(p,7*7)\\\\n\\\\n vec4 x_ = floor(j * ns.z);\\\\n vec4 y_ = floor(j - 7.0 * x_ ); // mod(j,N)\\\\n\\\\n vec4 x = x_ *ns.x + ns.yyyy;\\\\n vec4 y = y_ *ns.x + ns.yyyy;\\\\n vec4 h = 1.0 - abs(x) - abs(y);\\\\n\\\\n vec4 b0 = vec4( x.xy, y.xy );\\\\n vec4 b1 = vec4( x.zw, y.zw );\\\\n\\\\n //vec4 s0 = vec4(lessThan(b0,0.0))*2.0 - 1.0;\\\\n //vec4 s1 = vec4(lessThan(b1,0.0))*2.0 - 1.0;\\\\n vec4 s0 = floor(b0)*2.0 + 1.0;\\\\n vec4 s1 = floor(b1)*2.0 + 1.0;\\\\n vec4 sh = -step(h, vec4(0.0));\\\\n\\\\n vec4 a0 = b0.xzyw + s0.xzyw*sh.xxyy ;\\\\n vec4 a1 = b1.xzyw + s1.xzyw*sh.zzww ;\\\\n\\\\n vec3 p0 = vec3(a0.xy,h.x);\\\\n vec3 p1 = vec3(a0.zw,h.y);\\\\n vec3 p2 = vec3(a1.xy,h.z);\\\\n vec3 p3 = vec3(a1.zw,h.w);\\\\n\\\\n//Normalise gradients\\\\n vec4 norm = taylorInvSqrt(vec4(dot(p0,p0), dot(p1,p1), dot(p2, p2), dot(p3,p3)));\\\\n p0 *= norm.x;\\\\n p1 *= norm.y;\\\\n p2 *= norm.z;\\\\n p3 *= norm.w;\\\\n\\\\n// Mix final noise value\\\\n vec4 m = max(0.6 - vec4(dot(x0,x0), dot(x1,x1), dot(x2,x2), dot(x3,x3)), 0.0);\\\\n m = m * m;\\\\n return 42.0 * dot( m*m, vec4( dot(p0,x0), dot(p1,x1), \\\\n dot(p2,x2), dot(p3,x3) ) );\\\\n }\\\\n\\\\\\\",[uF.NOISE_4D]:\\\\\\\"//\\\\n// Description : Array and textureless GLSL 2D/3D/4D simplex \\\\n// noise functions.\\\\n// Author : Ian McEwan, Ashima Arts.\\\\n// Maintainer : stegu\\\\n// Lastmod : 20110822 (ijm)\\\\n// License : Copyright (C) 2011 Ashima Arts. All rights reserved.\\\\n// Distributed under the MIT License. See LICENSE file.\\\\n// https://github.com/ashima/webgl-noise\\\\n// https://github.com/stegu/webgl-noise\\\\n// \\\\n\\\\n\\\\n\\\\n\\\\n\\\\n\\\\n\\\\nvec4 grad4(float j, vec4 ip)\\\\n {\\\\n const vec4 ones = vec4(1.0, 1.0, 1.0, -1.0);\\\\n vec4 p,s;\\\\n\\\\n p.xyz = floor( fract (vec3(j) * ip.xyz) * 7.0) * ip.z - 1.0;\\\\n p.w = 1.5 - dot(abs(p.xyz), ones.xyz);\\\\n s = vec4(lessThan(p, vec4(0.0)));\\\\n p.xyz = p.xyz + (s.xyz*2.0 - 1.0) * s.www; \\\\n\\\\n return p;\\\\n }\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\n// (sqrt(5) - 1)/4 = F4, used once below\\\\n#define F4 0.309016994374947451\\\\n\\\\nfloat snoise(vec4 v)\\\\n {\\\\n const vec4 C = vec4( 0.138196601125011, // (5 - sqrt(5))/20 G4\\\\n 0.276393202250021, // 2 * G4\\\\n 0.414589803375032, // 3 * G4\\\\n -0.447213595499958); // -1 + 4 * G4\\\\n\\\\n// First corner\\\\n vec4 i = floor(v + dot(v, vec4(F4)) );\\\\n vec4 x0 = v - i + dot(i, C.xxxx);\\\\n\\\\n// Other corners\\\\n\\\\n// Rank sorting originally contributed by Bill Licea-Kane, AMD (formerly ATI)\\\\n vec4 i0;\\\\n vec3 isX = step( x0.yzw, x0.xxx );\\\\n vec3 isYZ = step( x0.zww, x0.yyz );\\\\n// i0.x = dot( isX, vec3( 1.0 ) );\\\\n i0.x = isX.x + isX.y + isX.z;\\\\n i0.yzw = 1.0 - isX;\\\\n// i0.y += dot( isYZ.xy, vec2( 1.0 ) );\\\\n i0.y += isYZ.x + isYZ.y;\\\\n i0.zw += 1.0 - isYZ.xy;\\\\n i0.z += isYZ.z;\\\\n i0.w += 1.0 - isYZ.z;\\\\n\\\\n // i0 now contains the unique values 0,1,2,3 in each channel\\\\n vec4 i3 = clamp( i0, 0.0, 1.0 );\\\\n vec4 i2 = clamp( i0-1.0, 0.0, 1.0 );\\\\n vec4 i1 = clamp( i0-2.0, 0.0, 1.0 );\\\\n\\\\n // x0 = x0 - 0.0 + 0.0 * C.xxxx\\\\n // x1 = x0 - i1 + 1.0 * C.xxxx\\\\n // x2 = x0 - i2 + 2.0 * C.xxxx\\\\n // x3 = x0 - i3 + 3.0 * C.xxxx\\\\n // x4 = x0 - 1.0 + 4.0 * C.xxxx\\\\n vec4 x1 = x0 - i1 + C.xxxx;\\\\n vec4 x2 = x0 - i2 + C.yyyy;\\\\n vec4 x3 = x0 - i3 + C.zzzz;\\\\n vec4 x4 = x0 + C.wwww;\\\\n\\\\n// Permutations\\\\n i = mod289(i); \\\\n float j0 = permute( permute( permute( permute(i.w) + i.z) + i.y) + i.x);\\\\n vec4 j1 = permute( permute( permute( permute (\\\\n i.w + vec4(i1.w, i2.w, i3.w, 1.0 ))\\\\n + i.z + vec4(i1.z, i2.z, i3.z, 1.0 ))\\\\n + i.y + vec4(i1.y, i2.y, i3.y, 1.0 ))\\\\n + i.x + vec4(i1.x, i2.x, i3.x, 1.0 ));\\\\n\\\\n// Gradients: 7x7x6 points over a cube, mapped onto a 4-cross polytope\\\\n// 7*7*6 = 294, which is close to the ring size 17*17 = 289.\\\\n vec4 ip = vec4(1.0/294.0, 1.0/49.0, 1.0/7.0, 0.0) ;\\\\n\\\\n vec4 p0 = grad4(j0, ip);\\\\n vec4 p1 = grad4(j1.x, ip);\\\\n vec4 p2 = grad4(j1.y, ip);\\\\n vec4 p3 = grad4(j1.z, ip);\\\\n vec4 p4 = grad4(j1.w, ip);\\\\n\\\\n// Normalise gradients\\\\n vec4 norm = taylorInvSqrt(vec4(dot(p0,p0), dot(p1,p1), dot(p2, p2), dot(p3,p3)));\\\\n p0 *= norm.x;\\\\n p1 *= norm.y;\\\\n p2 *= norm.z;\\\\n p3 *= norm.w;\\\\n p4 *= taylorInvSqrt(dot(p4,p4));\\\\n\\\\n// Mix contributions from the five corners\\\\n vec3 m0 = max(0.6 - vec3(dot(x0,x0), dot(x1,x1), dot(x2,x2)), 0.0);\\\\n vec2 m1 = max(0.6 - vec2(dot(x3,x3), dot(x4,x4) ), 0.0);\\\\n m0 = m0 * m0;\\\\n m1 = m1 * m1;\\\\n return 49.0 * ( dot(m0*m0, vec3( dot( p0, x0 ), dot( p1, x1 ), dot( p2, x2 )))\\\\n + dot(m1*m1, vec2( dot( p3, x3 ), dot( p4, x4 ) ) ) ) ;\\\\n\\\\n }\\\\n\\\\\\\"},_F={[uF.CLASSIC_PERLIN_2D]:Uo.VEC2,[uF.CLASSIC_PERLIN_3D]:Uo.VEC3,[uF.CLASSIC_PERLIN_4D]:Uo.VEC4,[uF.NOISE_2D]:Uo.VEC2,[uF.NOISE_3D]:Uo.VEC3,[uF.NOISE_4D]:Uo.VEC4},mF={[uF.CLASSIC_PERLIN_2D]:Uo.FLOAT,[uF.CLASSIC_PERLIN_3D]:Uo.FLOAT,[uF.CLASSIC_PERLIN_4D]:Uo.FLOAT,[uF.NOISE_2D]:Uo.FLOAT,[uF.NOISE_3D]:Uo.FLOAT,[uF.NOISE_4D]:Uo.FLOAT},fF={[uF.CLASSIC_PERLIN_2D]:\\\\\\\"cnoise\\\\\\\",[uF.CLASSIC_PERLIN_3D]:\\\\\\\"cnoise\\\\\\\",[uF.CLASSIC_PERLIN_4D]:\\\\\\\"cnoise\\\\\\\",[uF.NOISE_2D]:\\\\\\\"snoise\\\\\\\",[uF.NOISE_3D]:\\\\\\\"snoise\\\\\\\",[uF.NOISE_4D]:\\\\\\\"snoise\\\\\\\"};var gF;!function(t){t[t.NoChange=0]=\\\\\\\"NoChange\\\\\\\",t[t.Float=1]=\\\\\\\"Float\\\\\\\",t[t.Vec2=2]=\\\\\\\"Vec2\\\\\\\",t[t.Vec3=3]=\\\\\\\"Vec3\\\\\\\",t[t.Vec4=4]=\\\\\\\"Vec4\\\\\\\"}(gF||(gF={}));const vF=[gF.NoChange,gF.Float,gF.Vec2,gF.Vec3,gF.Vec4],yF={[gF.NoChange]:\\\\\\\"Same as noise\\\\\\\",[gF.Float]:\\\\\\\"Float\\\\\\\",[gF.Vec2]:\\\\\\\"Vec2\\\\\\\",[gF.Vec3]:\\\\\\\"Vec3\\\\\\\",[gF.Vec4]:\\\\\\\"Vec4\\\\\\\"},xF={[gF.NoChange]:Uo.FLOAT,[gF.Float]:Uo.FLOAT,[gF.Vec2]:Uo.VEC2,[gF.Vec3]:Uo.VEC3,[gF.Vec4]:Uo.VEC4},bF=[\\\\\\\"x\\\\\\\",\\\\\\\"y\\\\\\\",\\\\\\\"z\\\\\\\",\\\\\\\"w\\\\\\\"],wF=\\\\\\\"noise\\\\\\\",TF=dF.indexOf(uF.NOISE_3D),AF=gF.NoChange,MF={amp:1,freq:1};var EF;!function(t){t.AMP=\\\\\\\"amp\\\\\\\",t.POSITION=\\\\\\\"position\\\\\\\",t.FREQ=\\\\\\\"freq\\\\\\\",t.OFFSET=\\\\\\\"offset\\\\\\\"}(EF||(EF={}));const SF=new class extends ua{constructor(){super(...arguments),this.type=ha.INTEGER(TF,{menu:{entries:dF.map(((t,e)=>({name:`${t} (output: ${mF[t]})`,value:e})))}}),this.outputType=ha.INTEGER(AF,{menu:{entries:vF.map((t=>{const e=vF[t];return{name:yF[e],value:e}}))}}),this.octaves=ha.INTEGER(3,{range:[1,10],rangeLocked:[!0,!1]}),this.ampAttenuation=ha.FLOAT(.5,{range:[0,1]}),this.freqIncrease=ha.FLOAT(2,{range:[0,10],separatorAfter:!0})}};class CF extends gf{constructor(){super(...arguments),this.paramsConfig=SF}static type(){return\\\\\\\"noise\\\\\\\"}initializeNode(){super.initializeNode(),this.io.connection_points.initializeNode(),this.io.connection_points.spare_params.set_inputless_param_names([\\\\\\\"octaves\\\\\\\",\\\\\\\"ampAttenuation\\\\\\\",\\\\\\\"freqIncrease\\\\\\\"]),this.io.outputs.setNamedOutputConnectionPoints([new qo(wF,Uo.FLOAT)]),this.io.connection_points.set_expected_input_types_function(this._expected_input_types.bind(this)),this.io.connection_points.set_expected_output_types_function(this._expected_output_types.bind(this)),this.io.connection_points.set_input_name_function(this._gl_input_name.bind(this)),this.io.connection_points.set_output_name_function((()=>wF))}_gl_input_name(t){return[EF.AMP,EF.POSITION,EF.FREQ,EF.OFFSET][t]}paramDefaultValue(t){return MF[t]}_expected_input_types(){const t=dF[this.pv.type],e=this._expected_output_types()[0],n=_F[t];return[e,n,n,n]}_expected_output_types(){const t=dF[this.pv.type],e=vF[this.pv.outputType];return e==gF.NoChange?[_F[t]]:[xF[e]]}setLines(t){const e=[],n=[],i=dF[this.pv.type],s=pF[i],r=mF[i];e.push(new Cf(this,\\\\\\\"// Modulo 289 without a division (only multiplications)\\\\nfloat mod289(float x) {\\\\n return x - floor(x * (1.0 / 289.0)) * 289.0;\\\\n}\\\\nvec2 mod289(vec2 x) {\\\\n return x - floor(x * (1.0 / 289.0)) * 289.0;\\\\n}\\\\nvec3 mod289(vec3 x) {\\\\n return x - floor(x * (1.0 / 289.0)) * 289.0;\\\\n}\\\\nvec4 mod289(vec4 x) {\\\\n return x - floor(x * (1.0 / 289.0)) * 289.0;\\\\n}\\\\n// Modulo 7 without a division\\\\nvec3 mod7(vec3 x) {\\\\n return x - floor(x * (1.0 / 7.0)) * 7.0;\\\\n}\\\\n\\\\n// Permutation polynomial: (34x^2 + x) mod 289\\\\nfloat permute(float x) {\\\\n return mod289(((x*34.0)+1.0)*x);\\\\n}\\\\nvec3 permute(vec3 x) {\\\\n return mod289((34.0 * x + 1.0) * x);\\\\n}\\\\nvec4 permute(vec4 x) {\\\\n return mod289(((x*34.0)+1.0)*x);\\\\n}\\\\n\\\\nfloat taylorInvSqrt(float r)\\\\n{\\\\n return 1.79284291400159 - 0.85373472095314 * r;\\\\n}\\\\nvec4 taylorInvSqrt(vec4 r)\\\\n{\\\\n return 1.79284291400159 - 0.85373472095314 * r;\\\\n}\\\\n\\\\nvec2 fade(vec2 t) {\\\\n return t*t*t*(t*(t*6.0-15.0)+10.0);\\\\n}\\\\nvec3 fade(vec3 t) {\\\\n return t*t*t*(t*(t*6.0-15.0)+10.0);\\\\n}\\\\nvec4 fade(vec4 t) {\\\\n return t*t*t*(t*(t*6.0-15.0)+10.0);\\\\n}\\\\\\\")),e.push(new Cf(this,s)),e.push(new Cf(this,this.fbm_function()));const o=this._expected_output_types()[0];if(o==r){const t=this.single_noise_line();n.push(t)}else{const t=Wo[o],e=[],s=this.glVarName(\\\\\\\"noise\\\\\\\");for(let r=0;rmf.float(1e3*r))).join(\\\\\\\", \\\\\\\")})`,c=this.single_noise_line(t,t,l);n.push(c)}const r=`vec${t} ${s} = vec${t}(${e.join(\\\\\\\", \\\\\\\")})`;n.push(r)}t.addDefinitions(this,e),t.addBodyLines(this,n)}fbm_method_name(){const t=dF[this.pv.type];return`fbm_${fF[t]}_${this.name()}`}fbm_function(){const t=dF[this.pv.type],e=fF[t],n=_F[t];return`\\\\nfloat ${this.fbm_method_name()} (in ${n} st) {\\\\n\\\\tfloat value = 0.0;\\\\n\\\\tfloat amplitude = 1.0;\\\\n\\\\tfor (int i = 0; i < ${mf.integer(this.pv.octaves)}; i++) {\\\\n\\\\t\\\\tvalue += amplitude * ${e}(st);\\\\n\\\\t\\\\tst *= ${mf.float(this.pv.freqIncrease)};\\\\n\\\\t\\\\tamplitude *= ${mf.float(this.pv.ampAttenuation)};\\\\n\\\\t}\\\\n\\\\treturn value;\\\\n}\\\\n`}single_noise_line(t,e,n){const i=this.fbm_method_name(),s=mf.any(this.variableForInput(EF.AMP)),r=mf.any(this.variableForInput(EF.POSITION)),o=mf.any(this.variableForInput(EF.FREQ));let a=mf.any(this.variableForInput(EF.OFFSET));n&&(a=`(${a}+${n})`);const l=[`(${r}*${o})+${a}`].join(\\\\\\\", \\\\\\\"),c=this.glVarName(wF),h=`${s}*${i}(${l})`;if(e)return`float ${c}${t} = (${h}).${e}`;return`${this.io.outputs.namedOutputConnectionPoints()[0].type()} ${c} = ${h}`}}class NF extends NP{static type(){return\\\\\\\"null\\\\\\\"}setLines(t){const e=mf.any(this.variableForInput(this._gl_input_name(0))),n=this.io.outputs.namedOutputConnectionPoints()[0],i=`${n.type()} ${this.glVarName(n.name())} = ${e}`;t.addBodyLines(this,[i])}}const LF=new class extends ua{};class OF extends gf{constructor(){super(...arguments),this.paramsConfig=LF}static type(){return\\\\\\\"output\\\\\\\"}initializeNode(){super.initializeNode(),this.addPostDirtyHook(\\\\\\\"_set_mat_to_recompile\\\\\\\",this._set_mat_to_recompile.bind(this)),this.lifecycle.add_on_add_hook((()=>{var t,e;null===(e=null===(t=this.material_node)||void 0===t?void 0:t.assemblerController)||void 0===e||e.add_output_inputs(this)}))}setLines(t){t.assembler().set_node_lines_output(this,t)}}class PF{constructor(){this._param_configs=[]}reset(){this._param_configs=[]}push(t){this._param_configs.push(t)}list(){return this._param_configs}}const RF=new class extends ua{constructor(){super(...arguments),this.name=ha.STRING(\\\\\\\"\\\\\\\"),this.type=ha.INTEGER(Go.indexOf(Uo.FLOAT),{menu:{entries:Go.map(((t,e)=>({name:t,value:e})))}}),this.asColor=ha.BOOLEAN(0,{visibleIf:{type:Go.indexOf(Uo.VEC3)}})}};class IF extends gf{constructor(){super(...arguments),this.paramsConfig=RF,this._allow_inputs_created_from_params=!1,this._on_create_set_name_if_none_bound=this._on_create_set_name_if_none.bind(this)}static type(){return\\\\\\\"param\\\\\\\"}initializeNode(){this.addPostDirtyHook(\\\\\\\"_set_mat_to_recompile\\\\\\\",this._set_mat_to_recompile.bind(this)),this.lifecycle.add_on_create_hook(this._on_create_set_name_if_none_bound),this.io.connection_points.initializeNode(),this.io.connection_points.set_expected_input_types_function((()=>[])),this.io.connection_points.set_expected_output_types_function((()=>[Go[this.pv.type]])),this.scene().dispatchController.onAddListener((()=>{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{this.params.label.init([this.p.name])}))}))}setLines(t){const e=[],n=Go[this.pv.type],i=this.uniform_name();e.push(new Nf(this,n,i)),t.addDefinitions(this,e)}paramsGenerating(){return!0}setParamConfigs(){const t=Go[this.pv.type],e=jo[t];let n=Vo[t];if(this._param_configs_controller=this._param_configs_controller||new PF,this._param_configs_controller.reset(),n==Cr.VECTOR3&&this.p.asColor.value&&m.isArray(e)&&3==e.length){const t=new tg(Cr.COLOR,this.pv.name,e,this.uniform_name());this._param_configs_controller.push(t)}else{const t=new tg(n,this.pv.name,e,this.uniform_name());this._param_configs_controller.push(t)}}uniform_name(){const t=this.io.outputs.namedOutputConnectionPoints()[0];return this.glVarName(t.name())}set_gl_type(t){const e=Go.indexOf(t);this.p.type.set(e)}_on_create_set_name_if_none(){\\\\\\\"\\\\\\\"==this.pv.name&&this.p.name.set(this.name())}}class FF extends CP{static type(){return\\\\\\\"refract\\\\\\\"}initializeNode(){super.initializeNode(),this.io.connection_points.set_input_name_function((t=>[\\\\\\\"I\\\\\\\",\\\\\\\"N\\\\\\\",\\\\\\\"eta\\\\\\\"][t])),this.io.connection_points.set_output_name_function((t=>\\\\\\\"refract\\\\\\\")),this.io.connection_points.set_expected_input_types_function(this._expected_input_types.bind(this)),this.io.connection_points.set_expected_output_types_function(this._expected_output_types.bind(this))}gl_method_name(){return\\\\\\\"refract\\\\\\\"}_expected_input_types(){const t=this.io.connection_points.first_input_connection_type()||Uo.VEC3;return[t,t,Uo.FLOAT]}_expected_output_types(){return[this._expected_input_types()[0]]}}const DF=\\\\\\\"SSSModel\\\\\\\";const BF=new class extends ua{constructor(){super(...arguments),this.color=ha.COLOR([1,1,1]),this.thickness=ha.FLOAT(.1),this.power=ha.FLOAT(2),this.scale=ha.FLOAT(16),this.distortion=ha.FLOAT(.1),this.ambient=ha.FLOAT(.4),this.attenuation=ha.FLOAT(.8)}};class zF extends gf{constructor(){super(...arguments),this.paramsConfig=BF}static type(){return\\\\\\\"SSSModel\\\\\\\"}initializeNode(){this.io.outputs.setNamedOutputConnectionPoints([new qo(DF,Uo.SSS_MODEL)])}setLines(t){const e=[],n=this.glVarName(DF);e.push(`SSSModel ${n}`),e.push(`${n}.isActive = true;`),e.push(this._paramLineFloat(n,this.p.color)),e.push(this._paramLineFloat(n,this.p.thickness)),e.push(this._paramLineFloat(n,this.p.power)),e.push(this._paramLineFloat(n,this.p.scale)),e.push(this._paramLineFloat(n,this.p.distortion)),e.push(this._paramLineFloat(n,this.p.ambient)),e.push(this._paramLineFloat(n,this.p.attenuation)),t.addBodyLines(this,e)}_paramLineFloat(t,e){return`${t}.${e.name()} = ${mf.vector3(this.variableForInputParam(e))};`}}class kF extends NP{static type(){return\\\\\\\"quatMult\\\\\\\"}initializeNode(){super.initializeNode(),this.io.connection_points.set_input_name_function((t=>[\\\\\\\"quat0\\\\\\\",\\\\\\\"quat1\\\\\\\"][t])),this.io.connection_points.set_expected_input_types_function((()=>[Uo.VEC4,Uo.VEC4])),this.io.connection_points.set_expected_output_types_function((()=>[Uo.VEC4]))}gl_method_name(){return\\\\\\\"quatMult\\\\\\\"}gl_function_definitions(){return[new Cf(this,PR)]}}var UF;!function(t){t.AXIS=\\\\\\\"axis\\\\\\\",t.ANGLE=\\\\\\\"angle\\\\\\\"}(UF||(UF={}));const GF=[UF.AXIS,UF.ANGLE],VF={[UF.AXIS]:[0,0,1],[UF.ANGLE]:0};class HF extends LP{static type(){return\\\\\\\"quatFromAxisAngle\\\\\\\"}initializeNode(){super.initializeNode(),this.io.connection_points.set_input_name_function((t=>GF[t])),this.io.connection_points.set_expected_input_types_function((()=>[Uo.VEC3,Uo.FLOAT])),this.io.connection_points.set_expected_output_types_function((()=>[Uo.VEC4]))}paramDefaultValue(t){return VF[t]}gl_method_name(){return\\\\\\\"quatFromAxisAngle\\\\\\\"}gl_function_definitions(){return[new Cf(this,PR)]}}class jF extends NP{static type(){return\\\\\\\"quatToAngle\\\\\\\"}initializeNode(){super.initializeNode(),this.io.connection_points.set_input_name_function((t=>[\\\\\\\"quat\\\\\\\"][t])),this.io.connection_points.set_expected_input_types_function((()=>[Uo.VEC4])),this.io.connection_points.set_expected_output_types_function((()=>[Uo.FLOAT]))}gl_method_name(){return\\\\\\\"quatToAngle\\\\\\\"}gl_function_definitions(){return[new Cf(this,PR)]}}class WF extends NP{static type(){return\\\\\\\"quatToAxis\\\\\\\"}initializeNode(){super.initializeNode(),this.io.connection_points.set_input_name_function((t=>[\\\\\\\"quat\\\\\\\"][t])),this.io.connection_points.set_expected_input_types_function((()=>[Uo.VEC4])),this.io.connection_points.set_expected_output_types_function((()=>[Uo.VEC3]))}gl_method_name(){return\\\\\\\"quatToAxis\\\\\\\"}gl_function_definitions(){return[new Cf(this,PR)]}}const qF=\\\\\\\"val\\\\\\\";const XF=new class extends ua{constructor(){super(...arguments),this.name=ha.STRING(\\\\\\\"ramp\\\\\\\"),this.input=ha.FLOAT(0)}};class YF extends gf{constructor(){super(...arguments),this.paramsConfig=XF}static type(){return\\\\\\\"ramp\\\\\\\"}initializeNode(){super.initializeNode(),this.addPostDirtyHook(\\\\\\\"_set_mat_to_recompile\\\\\\\",this._set_mat_to_recompile.bind(this)),this.io.outputs.setNamedOutputConnectionPoints([new qo(qF,Uo.FLOAT)]),this.scene().dispatchController.onAddListener((()=>{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{this.params.label.init([this.p.name])}))}))}setLines(t){const e=Uo.VEC3,n=this.glVarName(\\\\\\\"tmpTexureVarName\\\\\\\"),i=Uo.FLOAT,s=this._uniform_name(),r=this.glVarName(qF),o=new Nf(this,Uo.SAMPLER_2D,s);t.addDefinitions(this,[o]);const a=this.variableForInputParam(this.p.input),l=[`${e} ${n} = texture2D(${this._uniform_name()}, vec2(${a}, 0.0)).xyz`,`${i} ${r} = -1.0 + ${n}.x + ${n}.y + ${n}.z`];t.addBodyLines(this,l)}paramsGenerating(){return!0}setParamConfigs(){this._param_configs_controller=this._param_configs_controller||new PF,this._param_configs_controller.reset();const t=new tg(Cr.RAMP,this.pv.name,Ao.DEFAULT_VALUE,this._uniform_name());this._param_configs_controller.push(t)}_uniform_name(){return\\\\\\\"ramp_texture_\\\\\\\"+this.glVarName(qF)}}const $F=\\\\\\\"rand\\\\\\\";const JF=new class extends ua{constructor(){super(...arguments),this.seed=ha.VECTOR2([1,1])}};class ZF extends gf{constructor(){super(...arguments),this.paramsConfig=JF}static type(){return\\\\\\\"random\\\\\\\"}initializeNode(){super.initializeNode(),this.io.outputs.setNamedOutputConnectionPoints([new qo($F,Uo.FLOAT)])}setLines(t){const e=this.io.inputs.namedInputConnectionPoints()[0].name(),n=mf.vector2(this.variableForInput(e)),i=`float ${this.glVarName($F)} = rand(${n})`;t.addBodyLines(this,[i])}}const KF=new class extends ua{constructor(){super(...arguments),this.rgb=ha.VECTOR3([1,1,1])}};class QF extends gf{constructor(){super(...arguments),this.paramsConfig=KF}static type(){return\\\\\\\"rgbToHsv\\\\\\\"}initializeNode(){this.io.outputs.setNamedOutputConnectionPoints([new qo(\\\\\\\"hsv\\\\\\\",Uo.VEC3)])}setLines(t){const e=[],n=[];e.push(new Cf(this,\\\\\\\"// https://stackoverflow.com/questions/15095909/from-rgb-to-hsv-in-opengl-glsl\\\\nvec3 rgb2hsv(vec3 c)\\\\n{\\\\n\\\\tvec4 K = vec4(0.0, -1.0 / 3.0, 2.0 / 3.0, -1.0);\\\\n\\\\tvec4 p = mix(vec4(c.bg, K.wz), vec4(c.gb, K.xy), step(c.b, c.g));\\\\n\\\\tvec4 q = mix(vec4(p.xyw, c.r), vec4(c.r, p.yzx), step(p.x, c.r));\\\\n\\\\n\\\\tfloat d = q.x - min(q.w, q.y);\\\\n\\\\tfloat e = 1.0e-10;\\\\n\\\\treturn vec3(abs(q.z + (q.w - q.y) / (6.0 * d + e)), d / (q.x + e), q.x);\\\\n}\\\\\\\"));const i=mf.vector3(this.variableForInputParam(this.p.rgb)),s=this.glVarName(\\\\\\\"hsv\\\\\\\");n.push(`vec3 ${s} = rgb2hsv(${i})`),t.addDefinitions(this,e),t.addBodyLines(this,n)}}var tD;!function(t){t[t.AXIS=0]=\\\\\\\"AXIS\\\\\\\",t[t.QUAT=1]=\\\\\\\"QUAT\\\\\\\"}(tD||(tD={}));const eD=[tD.AXIS,tD.QUAT],nD={[tD.AXIS]:\\\\\\\"from axis + angle\\\\\\\",[tD.QUAT]:\\\\\\\"from quaternion\\\\\\\"},iD={[tD.AXIS]:[\\\\\\\"vector\\\\\\\",\\\\\\\"axis\\\\\\\",\\\\\\\"angle\\\\\\\"],[tD.QUAT]:[\\\\\\\"vector\\\\\\\",\\\\\\\"quat\\\\\\\"]},sD={[tD.AXIS]:\\\\\\\"rotateWithAxisAngle\\\\\\\",[tD.QUAT]:\\\\\\\"rotateWithQuat\\\\\\\"},rD={[tD.AXIS]:[Uo.VEC3,Uo.VEC3,Uo.FLOAT],[tD.QUAT]:[Uo.VEC3,Uo.VEC4]},oD={vector:[0,0,1],axis:[0,1,0]};const aD=new class extends ua{constructor(){super(...arguments),this.signature=ha.INTEGER(tD.AXIS,{menu:{entries:eD.map(((t,e)=>({name:nD[t],value:e})))}})}};class lD extends gf{constructor(){super(...arguments),this.paramsConfig=aD}static type(){return\\\\\\\"rotate\\\\\\\"}initializeNode(){super.initializeNode(),this.io.connection_points.set_expected_input_types_function(this._expected_input_types.bind(this)),this.io.connection_points.set_expected_output_types_function(this._expected_output_types.bind(this)),this.io.connection_points.set_input_name_function(this._gl_input_name.bind(this))}set_signature(t){const e=eD.indexOf(t);this.p.signature.set(e)}_gl_input_name(t){const e=eD[this.pv.signature];return iD[e][t]}paramDefaultValue(t){return oD[t]}gl_method_name(){const t=eD[this.pv.signature];return sD[t]}_expected_input_types(){const t=eD[this.pv.signature];return rD[t]}_expected_output_types(){return[Uo.VEC3]}gl_function_definitions(){return[new Cf(this,PR)]}setLines(t){const e=this.io.outputs.namedOutputConnectionPoints()[0].type(),n=this.io.inputs.namedInputConnectionPoints().map(((t,e)=>{const n=t.name();return mf.any(this.variableForInput(n))})).join(\\\\\\\", \\\\\\\"),i=`${e} ${this.glVarName(this.io.connection_points.output_name(0))} = ${this.gl_method_name()}(${n})`;t.addBodyLines(this,[i]),t.addDefinitions(this,this.gl_function_definitions())}}const cD=[\\\\\\\"x\\\\\\\",\\\\\\\"y\\\\\\\",\\\\\\\"z\\\\\\\",\\\\\\\"w\\\\\\\"];class hD extends NP{static type(){return\\\\\\\"round\\\\\\\"}setLines(t){const e=this.io.inputs.namedInputConnectionPoints()[0],n=mf.vector2(this.variableForInput(e.name())),i=this.io.outputs.namedOutputConnectionPoints()[0],s=this.glVarName(i.name()),r=[];if(1==Wo[i.type()])r.push(`${i.type()} ${s} = ${this._simple_line(n)}`);else{const t=cD.map((t=>this._simple_line(`${n}.${t}`)));r.push(`${i.type()} ${s} = ${i.type()}(${t.join(\\\\\\\",\\\\\\\")})`)}t.addBodyLines(this,r)}_simple_line(t){return`sign(${t})*floor(abs(${t})+0.5)`}}const uD=new class extends ua{constructor(){super(...arguments),this.position=ha.VECTOR3([0,0,0]),this.center=ha.VECTOR3([0,0,0]),this.radius=ha.FLOAT(1),this.feather=ha.FLOAT(.1)}};class dD extends gf{constructor(){super(...arguments),this.paramsConfig=uD}static type(){return\\\\\\\"sphere\\\\\\\"}initializeNode(){super.initializeNode(),this.io.outputs.setNamedOutputConnectionPoints([new qo(\\\\\\\"float\\\\\\\",Uo.FLOAT)])}setLines(t){const e=mf.vector2(this.variableForInputParam(this.p.position)),n=mf.vector2(this.variableForInputParam(this.p.center)),i=mf.float(this.variableForInputParam(this.p.radius)),s=mf.float(this.variableForInputParam(this.p.feather)),r=`float ${this.glVarName(\\\\\\\"float\\\\\\\")} = disk3d(${e}, ${n}, ${i}, ${s})`;t.addBodyLines(this,[r]),t.addDefinitions(this,[new Cf(this,eI)])}}const pD=new class extends ua{};class _D extends gf{constructor(){super(...arguments),this.paramsConfig=pD}static type(){return ns.INPUT}initializeNode(){this.io.connection_points.set_output_name_function(this._expected_output_names.bind(this)),this.io.connection_points.set_expected_input_types_function((()=>[])),this.io.connection_points.set_expected_output_types_function(this._expected_output_types.bind(this))}parent(){return super.parent()}_expected_output_names(t){const e=this.parent();return(null==e?void 0:e.child_expected_input_connection_point_name(t))||`out${t}`}_expected_output_types(){const t=this.parent();return(null==t?void 0:t.child_expected_input_connection_point_types())||[]}setLines(t){const e=this.parent();e&&e.set_lines_block_start(t,this)}}const mD=new class extends ua{};class fD extends gf{constructor(){super(...arguments),this.paramsConfig=mD}static type(){return\\\\\\\"switch\\\\\\\"}initializeNode(){this.io.connection_points.set_input_name_function(this._gl_input_name.bind(this)),this.io.connection_points.set_expected_input_types_function(this._expected_input_types.bind(this)),this.io.connection_points.set_expected_output_types_function(this._expected_output_types.bind(this))}_gl_input_name(t){return 0==t?fD.INPUT_INDEX:\\\\\\\"in\\\\\\\"+(t-1)}_expected_input_types(){const t=this.io.connection_points.input_connection_type(1)||Uo.FLOAT,e=this.io.connections.inputConnections(),n=e?or.clamp(e.length,2,16):2,i=[Uo.INT];for(let e=0;e{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{this.params.label.init([this.p.paramName])}))}))}setLines(t){const e=mf.vector2(this.variableForInputParam(this.p.uv)),n=this.glVarName(vD.OUTPUT_NAME),i=this._uniform_name(),s=new Nf(this,Uo.SAMPLER_2D,i),r=`vec4 ${n} = texture2D(${i}, ${e})`;t.addDefinitions(this,[s]),t.addBodyLines(this,[r])}paramsGenerating(){return!0}setParamConfigs(){this._param_configs_controller=this._param_configs_controller||new PF,this._param_configs_controller.reset();const t=new tg(Cr.OPERATOR_PATH,this.pv.paramName,this.pv.defaultValue,this._uniform_name());this._param_configs_controller.push(t)}_uniform_name(){return this.glVarName(this.pv.paramName)}}var yD;vD.OUTPUT_NAME=\\\\\\\"rgba\\\\\\\",function(t){t.POSITION=\\\\\\\"position\\\\\\\",t.DIR_VEC=\\\\\\\"direction vector\\\\\\\"}(yD||(yD={}));const xD=[yD.POSITION,yD.DIR_VEC];const bD=new class extends ua{constructor(){super(...arguments),this.vec=ha.VECTOR3([0,0,0]),this.interpretation=ha.INTEGER(0,{menu:{entries:xD.map(((t,e)=>({name:t,value:e})))}})}};class wD extends gf{constructor(){super(...arguments),this.paramsConfig=bD}static type(){return\\\\\\\"toWorldSpace\\\\\\\"}initializeNode(){this.io.connection_points.spare_params.set_inputless_param_names([\\\\\\\"interpretation\\\\\\\"]),this.io.outputs.setNamedOutputConnectionPoints([new qo(\\\\\\\"out\\\\\\\",Uo.VEC3)])}setLines(t){const e=[],n=mf.vector3(this.variableForInputParam(this.p.vec)),i=this.glVarName(\\\\\\\"out\\\\\\\");switch(xD[this.pv.interpretation]){case yD.POSITION:e.push(`vec3 ${i} = (modelMatrix * vec4( ${n}, 1.0 )).xyz`);break;case yD.DIR_VEC:e.push(`vec3 ${i} = normalize( mat3( modelMatrix[0].xyz, modelMatrix[1].xyz, modelMatrix[2].xyz ) * ${n} )`)}t.addBodyLines(this,e)}}var TD;!function(t){t.CONDITION=\\\\\\\"condition\\\\\\\",t.IF_TRUE=\\\\\\\"ifTrue\\\\\\\",t.IF_FALSE=\\\\\\\"ifFalse\\\\\\\"}(TD||(TD={}));const AD=[TD.CONDITION,TD.IF_TRUE,TD.IF_FALSE];class MD extends yf{static type(){return\\\\\\\"twoWaySwitch\\\\\\\"}initializeNode(){super.initializeNode(),this.io.connection_points.initializeNode(),this.io.connection_points.set_expected_input_types_function(this._expected_input_types.bind(this)),this.io.connection_points.set_expected_output_types_function(this._expected_output_types.bind(this)),this.io.connection_points.set_input_name_function(this._gl_input_name.bind(this)),this.io.connection_points.set_output_name_function(this._gl_output_name.bind(this))}_gl_input_name(t){return AD[t]}_gl_output_name(){return\\\\\\\"val\\\\\\\"}_expected_input_types(){const t=this.io.connections.inputConnection(1)||this.io.connections.inputConnection(2),e=t?t.src_connection_point().type():Uo.FLOAT;return[Uo.BOOL,e,e]}_expected_output_types(){return[this._expected_input_types()[1]]}setLines(t){const e=[],n=this.glVarName(\\\\\\\"val\\\\\\\"),i=mf.bool(this.variableForInput(TD.CONDITION)),s=mf.any(this.variableForInput(TD.IF_TRUE)),r=mf.any(this.variableForInput(TD.IF_FALSE)),o=this._expected_output_types()[0];e.push(`${o} ${n}`),e.push(`if(${i}){`),e.push(`${n} = ${s}`),e.push(\\\\\\\"} else {\\\\\\\"),e.push(`${n} = ${r}`),e.push(\\\\\\\"}\\\\\\\"),t.addBodyLines(this,e)}}const ED=[Uo.FLOAT,Uo.VEC2,Uo.VEC3,Uo.VEC4];const SD=new class extends ua{constructor(){super(...arguments),this.name=ha.STRING(\\\\\\\"\\\\\\\"),this.type=ha.INTEGER(0,{menu:{entries:ED.map(((t,e)=>({name:t,value:e})))}})}};class CD extends gf{constructor(){super(...arguments),this.paramsConfig=SD,this._on_create_set_name_if_none_bound=this._on_create_set_name_if_none.bind(this)}static type(){return\\\\\\\"varyingRead\\\\\\\"}initializeNode(){this.addPostDirtyHook(\\\\\\\"_set_mat_to_recompile\\\\\\\",this._set_mat_to_recompile.bind(this)),this.lifecycle.add_on_create_hook(this._on_create_set_name_if_none_bound),this.io.connection_points.initializeNode(),this.io.connection_points.set_output_name_function((()=>this.output_name)),this.io.connection_points.set_expected_input_types_function((()=>[])),this.io.connection_points.set_expected_output_types_function((()=>[ED[this.pv.type]])),this.scene().dispatchController.onAddListener((()=>{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{this.params.label.init([this.p.name])}))}))}get output_name(){return CD.OUTPUT_NAME}setLines(t){if(t.current_shader_name==Mf.FRAGMENT){const e=this.pv.name,n=new Lf(this,this.gl_type(),e),i=this.glVarName(CD.OUTPUT_NAME),s=`${this.gl_type()} ${i} = ${e}`;t.addDefinitions(this,[n]),t.addBodyLines(this,[s])}}get attribute_name(){return this.pv.name.trim()}gl_type(){return this.io.outputs.namedOutputConnectionPoints()[0].type()}set_gl_type(t){this.p.type.set(ED.indexOf(t))}_on_create_set_name_if_none(){\\\\\\\"\\\\\\\"==this.pv.name&&this.p.name.set(this.name())}}CD.OUTPUT_NAME=\\\\\\\"fragment\\\\\\\";const ND={start:[0,0,1],end:[1,0,0],up:[0,1,0]};class LD extends(hR(\\\\\\\"vectorAlign\\\\\\\",{in:[\\\\\\\"start\\\\\\\",\\\\\\\"end\\\\\\\",\\\\\\\"up\\\\\\\"],method:\\\\\\\"vectorAlignWithUp\\\\\\\",functions:[PR]})){_expected_input_types(){const t=Uo.VEC3;return[t,t,t]}_expected_output_types(){return[Uo.VEC4]}paramDefaultValue(t){return ND[t]}}const OD={start:[0,0,1],end:[1,0,0]};class PD extends(eR(\\\\\\\"vectorAngle\\\\\\\",{in:[\\\\\\\"start\\\\\\\",\\\\\\\"end\\\\\\\"],method:\\\\\\\"vectorAngle\\\\\\\",functions:[PR]})){_expected_input_types(){const t=Uo.VEC3;return[t,t]}_expected_output_types(){return[Uo.FLOAT]}paramDefaultValue(t){return OD[t]}}const RD={only:[`${GI.context()}/${GI.type()}`,`${CI.context()}/${CI.type()}`,`${PI.context()}/${PI.type()}`]};class ID extends aa{static context(){return ts.JS}initializeBaseNode(){this.uiData.setLayoutHorizontal(),this.io.connection_points.initializeNode()}cook(){console.warn(\\\\\\\"js nodes should never cook\\\\\\\")}_set_function_node_to_recompile(){var t;null===(t=this.function_node)||void 0===t||t.assembler_controller.set_compilation_required_and_dirty(this)}get function_node(){var t;const e=this.parent();if(e)return e.type()==this.type()?null===(t=e)||void 0===t?void 0:t.function_node:e}js_var_name(t){return`v_POLY_${this.name()}_${t}`}variableForInput(t){const e=this.io.inputs.get_input_index(t),n=this.io.connections.inputConnection(e);if(n){const e=n.node_src,i=e.io.outputs.namedOutputConnectionPoints()[n.output_index];if(i){const t=i.name();return e.js_var_name(t)}throw console.warn(`no output called '${t}' for gl node ${e.path()}`),\\\\\\\"variable_for_input ERROR\\\\\\\"}return\\\\\\\"to debug...\\\\\\\"}setLines(t){}reset_code(){var t;null===(t=this._param_configs_controller)||void 0===t||t.reset()}setParamConfigs(){}param_configs(){var t;return null===(t=this._param_configs_controller)||void 0===t?void 0:t.list()}js_input_default_value(t){return null}}new class extends ua{};const FD=[Xo.FLOAT,Xo.VEC2,Xo.VEC3,Xo.VEC4];const DD=new class extends ua{constructor(){super(...arguments),this.name=ha.STRING(\\\\\\\"\\\\\\\"),this.type=ha.INTEGER(0,{menu:{entries:FD.map(((t,e)=>({name:t,value:e})))}})}};class BD extends ID{constructor(){super(...arguments),this.paramsConfig=DD,this._on_create_set_name_if_none_bound=this._on_create_set_name_if_none.bind(this)}static type(){return\\\\\\\"attribute\\\\\\\"}initializeNode(){this.lifecycle.add_on_create_hook(this._on_create_set_name_if_none_bound),this.io.connection_points.initializeNode(),this.io.connection_points.set_expected_input_types_function((()=>[])),this.io.connection_points.set_expected_output_types_function((()=>[FD[this.pv.type]]))}get input_name(){return BD.INPUT_NAME}get output_name(){return BD.OUTPUT_NAME}setLines(t){var e;null===(e=this.function_node)||void 0===e||e.assembler_controller.assembler.set_node_lines_attribute(this,t)}get attribute_name(){return this.pv.name.trim()}gl_type(){return this.io.outputs.namedOutputConnectionPoints()[0].type()}set_gl_type(t){this.p.type.set(FD.indexOf(t))}connected_input_node(){return this.io.inputs.named_input(BD.INPUT_NAME)}connected_input_connection_point(){return this.io.inputs.named_input_connection_point(BD.INPUT_NAME)}output_connection_point(){return this.io.outputs.namedOutputConnectionPointsByName(this.input_name)}get is_importing(){return this.io.outputs.used_output_names().length>0}_on_create_set_name_if_none(){\\\\\\\"\\\\\\\"==this.pv.name&&this.p.name.set(this.name())}}BD.INPUT_NAME=\\\\\\\"export\\\\\\\",BD.OUTPUT_NAME=\\\\\\\"val\\\\\\\";const zD=new class extends ua{};class kD extends ID{constructor(){super(...arguments),this.paramsConfig=zD}static type(){return\\\\\\\"globals\\\\\\\"}createParams(){var t;null===(t=this.function_node)||void 0===t||t.assembler_controller.add_globals_outputs(this)}setLines(t){var e,n;null===(n=null===(e=this.function_node)||void 0===e?void 0:e.assembler_controller)||void 0===n||n.assembler.set_node_lines_globals(this,t)}}const UD=new class extends ua{};class GD extends ID{constructor(){super(...arguments),this.paramsConfig=UD}static type(){return\\\\\\\"output\\\\\\\"}initializeNode(){super.initializeNode(),this.addPostDirtyHook(\\\\\\\"_set_mat_to_recompile\\\\\\\",this._set_function_node_to_recompile.bind(this))}createParams(){var t;null===(t=this.function_node)||void 0===t||t.assembler_controller.add_output_inputs(this)}setLines(t){var e;null===(e=this.function_node)||void 0===e||e.assembler_controller.assembler.set_node_lines_output(this,t)}}class VD{constructor(t=[]){this._definitions=t,this._errored=!1}get errored(){return this._errored}get error_message(){return this._error_message}uniq(){const t=new Map,e=[];for(let n of this._definitions)if(!this._errored){const i=n.name(),s=t.get(i);s?s.data_type!=n.data_type&&(this._errored=!0,this._error_message=`attempt to create '${n.name()}' with types '${n.data_type}' by node '${n.node.path()}', when there is already an existing with type ${s.data_type} from node '${s.node.path()}'`,console.warn(\\\\\\\"emitting error message:\\\\\\\",this._error_message)):(t.set(i,n),e.push(i))}const n=[];for(let i of e){const e=t.get(i);e&&n.push(e)}return n}}var HD;!function(t){t.ATTRIBUTE=\\\\\\\"attribute\\\\\\\",t.FUNCTION=\\\\\\\"function\\\\\\\",t.UNIFORM=\\\\\\\"uniform\\\\\\\"}(HD||(HD={}));class jD{constructor(t,e,n,i){this._definition_type=t,this._data_type=e,this._node=n,this._name=i}get definition_type(){return this._definition_type}get data_type(){return this._data_type}get node(){return this._node}name(){return this._name}collection_instance(){return new VD}}class WD extends jD{constructor(t,e,n){super(HD.UNIFORM,e,t,n),this._node=t,this._data_type=e,this._name=n}get line(){return`uniform ${this.data_type} ${this.name()}`}}class qD extends Qf{constructor(t,e,n,i){super(t,e,n),this._uniform_name=i}get uniform_name(){return this._uniform_name}static uniform_by_type(t){switch(t){case Cr.BOOLEAN:case Cr.BUTTON:return{value:0};case Cr.COLOR:return{value:new D.a(0,0,0)};case Cr.FLOAT:case Cr.FOLDER:case Cr.INTEGER:case Cr.OPERATOR_PATH:case Cr.NODE_PATH:case Cr.PARAM_PATH:return{value:0};case Cr.RAMP:case Cr.STRING:return{value:null};case Cr.VECTOR2:return{value:new d.a(0,0)};case Cr.VECTOR3:return{value:new p.a(0,0,0)};case Cr.VECTOR4:return{value:new _.a(0,0,0,0)}}os.unreachable(t)}}const XD=new class extends ua{constructor(){super(...arguments),this.name=ha.STRING(\\\\\\\"\\\\\\\"),this.type=ha.INTEGER(Yo.indexOf(Xo.FLOAT),{menu:{entries:Yo.map(((t,e)=>({name:t,value:e})))}}),this.asColor=ha.BOOLEAN(0,{visibleIf:{type:Yo.indexOf(Xo.VEC3)}})}};class YD extends ID{constructor(){super(...arguments),this.paramsConfig=XD,this._allow_inputs_created_from_params=!1,this._on_create_set_name_if_none_bound=this._on_create_set_name_if_none.bind(this)}static type(){return\\\\\\\"param\\\\\\\"}initializeNode(){this.addPostDirtyHook(\\\\\\\"_set_mat_to_recompile\\\\\\\",this._set_function_node_to_recompile.bind(this)),this.lifecycle.add_on_create_hook(this._on_create_set_name_if_none_bound),this.io.connection_points.initializeNode(),this.io.connection_points.set_expected_input_types_function((()=>[])),this.io.connection_points.set_expected_output_types_function((()=>[Yo[this.pv.type]]))}setLines(t){const e=[],n=Yo[this.pv.type],i=this.uniform_name();e.push(new WD(this,n,i)),t.addDefinitions(this,e)}setParamConfigs(){const t=Yo[this.pv.type],e=Zo[t];let n=$o[t];if(this._param_configs_controller=this._param_configs_controller||new PF,this._param_configs_controller.reset(),n==Cr.VECTOR3&&this.p.asColor.value&&m.isArray(e)&&3==e.length){const t=new qD(Cr.COLOR,this.pv.name,e,this.uniform_name());this._param_configs_controller.push(t)}else{const t=new qD(n,this.pv.name,e,this.uniform_name());this._param_configs_controller.push(t)}}uniform_name(){const t=this.io.outputs.namedOutputConnectionPoints()[0];return this.js_var_name(t.name())}set_gl_type(t){const e=Yo.indexOf(t);this.p.type.set(e)}_on_create_set_name_if_none(){\\\\\\\"\\\\\\\"==this.pv.name&&this.p.name.set(this.name())}}class $D extends aa{constructor(){super(...arguments),this._cook_main_without_inputs_when_dirty_bound=this._cook_main_without_inputs_when_dirty.bind(this)}static context(){return ts.MAT}initializeBaseNode(){super.initializeBaseNode(),this.nameController.add_post_set_fullPath_hook(this.set_material_name.bind(this)),this.addPostDirtyHook(\\\\\\\"_cook_main_without_inputs_when_dirty\\\\\\\",(()=>{setTimeout(this._cook_main_without_inputs_when_dirty_bound,0)}))}async _cook_main_without_inputs_when_dirty(){await this.cookController.cookMainWithoutInputs()}set_material_name(){this._material&&(this._material.name=this.path())}get material(){return this._material=this._material||this.createMaterial()}setMaterial(t){this._setContainer(t)}}class JD{constructor(t){this.node=t}add_params(){}update(){}get material(){return this.node.material}}const ZD={NoBlending:w.ub,NormalBlending:w.xb,AdditiveBlending:w.e,SubtractiveBlending:w.Sc,MultiplyBlending:w.mb},KD=Object.keys(ZD);function QD(t){return class extends t{constructor(){super(...arguments),this.doubleSided=ha.BOOLEAN(0),this.front=ha.BOOLEAN(1,{visibleIf:{doubleSided:!1}}),this.overrideShadowSide=ha.BOOLEAN(0),this.shadowDoubleSided=ha.BOOLEAN(0,{visibleIf:{overrideShadowSide:!0}}),this.shadowFront=ha.BOOLEAN(1,{visibleIf:{overrideShadowSide:!0,shadowDoubleSided:!1}}),this.colorWrite=ha.BOOLEAN(1,{separatorBefore:!0,cook:!1,callback:(t,e)=>{tB.update(t)}}),this.depthWrite=ha.BOOLEAN(1,{cook:!1,callback:(t,e)=>{tB.update(t)}}),this.depthTest=ha.BOOLEAN(1,{cook:!1,callback:(t,e)=>{tB.update(t)}}),this.premultipliedAlpha=ha.BOOLEAN(!1,{separatorAfter:!0}),this.blending=ha.INTEGER(w.xb,{menu:{entries:KD.map((t=>({name:t,value:ZD[t]})))}}),this.dithering=ha.BOOLEAN(0),this.polygonOffset=ha.BOOLEAN(!1,{separatorBefore:!0}),this.polygonOffsetFactor=ha.INTEGER(0,{range:[0,1e3],visibleIf:{polygonOffset:1}}),this.polygonOffsetUnits=ha.INTEGER(0,{range:[0,1e3],visibleIf:{polygonOffset:1}})}}}QD(ua);class tB extends JD{constructor(t){super(t),this.node=t}initializeNode(){}async update(){const t=this.node.material,e=this.node.pv;this._updateSides(t,e),t.colorWrite=e.colorWrite,t.depthWrite=e.depthWrite,t.depthTest=e.depthTest,t.blending=e.blending,t.premultipliedAlpha=e.premultipliedAlpha,t.dithering=e.dithering,t.polygonOffset=e.polygonOffset,t.polygonOffset&&(t.polygonOffsetFactor=e.polygonOffsetFactor,t.polygonOffsetUnits=e.polygonOffsetUnits,t.needsUpdate=!0)}_updateSides(t,e){const n=e.front?w.H:w.i,i=e.doubleSided?w.z:n;if(i!=t.side&&(t.side=i,t.needsUpdate=!0),e.overrideShadowSide){const t=e.shadowFront?w.H:w.i,n=e.shadowDoubleSided?w.z:t,i=this.node.material;n!=i.shadowSide&&(i.shadowSide=n,i.needsUpdate=!0)}else t.shadowSide=null;const s=t.customMaterials;if(s){const t=Object.keys(s);for(let n of t){const t=s[n];t&&this._updateSides(t,e)}}}static async update(t){t.controllers.advancedCommon.update()}}class eB extends(QD(ua)){constructor(){super(...arguments),this.color=ha.COLOR([1,1,1]),this.lineWidth=ha.FLOAT(1,{range:[1,10],rangeLocked:[!0,!1]})}}const nB=new eB;class iB extends $D{constructor(){super(...arguments),this.paramsConfig=nB,this.controllers={advancedCommon:new tB(this)},this.controllerNames=Object.keys(this.controllers)}static type(){return\\\\\\\"lineBasic\\\\\\\"}createMaterial(){return new As.a({color:16777215,linewidth:1})}initializeNode(){this.params.onParamsCreated(\\\\\\\"init controllers\\\\\\\",(()=>{for(let t of this.controllerNames)this.controllers[t].initializeNode()}))}async cook(){for(let t of this.controllerNames)this.controllers[t].update();this.material.color.copy(this.pv.color),this.material.linewidth=this.pv.lineWidth,this.setMaterial(this.material)}}function sB(t){return class extends t{constructor(){super(...arguments),this.transparent=ha.BOOLEAN(0),this.opacity=ha.FLOAT(1),this.alphaTest=ha.FLOAT(0)}}}sB(ua);class rB extends JD{constructor(t){super(t),this.node=t}static update(t){const e=t.material,n=t.pv;this._updateTransparency(e,n)}static _updateTransparency(t,e){t.transparent=e.transparent,this._updateCommon(t,e)}static _updateCommon(t,e){t.uniforms.opacity&&(t.uniforms.opacity.value=e.opacity),t.opacity=e.opacity,t.alphaTest=e.alphaTest;const n=t.customMaterials;if(n){const t=Object.keys(n);for(let i of t){const t=n[i];t&&this._updateCommon(t,e)}}}}class oB extends Kf{constructor(t){super(t),this.node=t}toJSON(){const t=this.node.assemblerController;if(!t)return;const e={},n=this.node.material.customMaterials;if(n){const t=Object.keys(n);for(let i of t){const t=n[i];if(t){const n=this._materialToJson(t,{node:this.node,suffix:i});n&&(e[i]=n)}}}const i=[],s=t.assembler.param_configs();for(let t of s)i.push([t.name(),t.uniform_name]);const r=this._materialToJson(this.node.material,{node:this.node,suffix:\\\\\\\"main\\\\\\\"});r||console.warn(\\\\\\\"failed to save material from node\\\\\\\",this.node.path());return{material:r||{},uniforms_time_dependent:t.assembler.uniformsTimeDependent(),uniforms_resolution_dependent:t.assembler.uniforms_resolution_dependent(),param_uniform_pairs:i,customMaterials:e}}load(t){if(this._material=this._loadMaterial(t.material),this._material){if(this._material.customMaterials=this._material.customMaterials||{},t.customMaterials){const e=Object.keys(t.customMaterials);for(let n of e){const e=t.customMaterials[n],i=this._loadMaterial(e);i&&(this._material.customMaterials[n]=i)}}if(t.uniforms_time_dependent&&this.node.scene().uniformsController.addTimeDependentUniformOwner(this._material.uuid,this._material.uniforms),t.uniforms_resolution_dependent&&this.node.scene().uniformsController.addResolutionDependentUniformOwner(this._material.uuid,this._material.uniforms),t.param_uniform_pairs)for(let e of t.param_uniform_pairs){const t=e[0],n=e[1],i=this.node.params.get(t),s=this._material.uniforms[n],r=Object.keys(this._material.customMaterials);let o;for(let t of r){const e=this._material.customMaterials[t],i=null==e?void 0:e.uniforms[n];i&&(o=o||[],o.push(i))}i&&(s||o)&&i.options.setOption(\\\\\\\"callback\\\\\\\",(()=>{if(s&&tg.callback(i,s),o)for(let t of o)tg.callback(i,t)}))}}}material(){if(li.playerMode())return this._material}}function aB(t){return class extends t{constructor(){super(...arguments),this.setBuilderNode=ha.BOOLEAN(0,{callback:t=>{lB.PARAM_CALLBACK_setCompileRequired(t)}}),this.builderNode=ha.NODE_PATH(\\\\\\\"\\\\\\\",{visibleIf:{setBuilderNode:!0},callback:t=>{lB.PARAM_CALLBACK_setCompileRequired(t)}})}}}aB(ua);class lB extends $D{constructor(){super(...arguments),this._children_controller_context=ts.GL,this.persisted_config=new oB(this)}createMaterial(){var t;let e;return this.persisted_config&&(e=this.persisted_config.material()),e||(e=null===(t=this.assemblerController)||void 0===t?void 0:t.assembler.createMaterial()),e}get assemblerController(){return this._assembler_controller=this._assembler_controller||this._create_assembler_controller()}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}childrenAllowed(){return this.assemblerController?super.childrenAllowed():(this.scene().markAsReadOnly(this),!1)}compileIfRequired(){var t;(null===(t=this.assemblerController)||void 0===t?void 0:t.compileRequired())&&this._compile()}_compile(){const t=this.assemblerController;this.material&&t&&(t.assembler.setGlParentNode(this),this._setAssemblerGlParentNode(t),t.assembler.compileMaterial(this.material),t.post_compile())}_setAssemblerGlParentNode(t){if(!this.pv.setBuilderNode)return;const e=this.pv.builderNode.nodeWithContext(ts.MAT);if(!e)return;const n=e;n.assemblerController?n.type()==this.type()?t.assembler.setGlParentNode(n):this.states.error.set(`resolved node '${e.path()}' does not have the same type '${e.type()}' as current node '${this.type()}'`):this.states.error.set(`resolved node '${e.path()}' is not a builder node`)}static PARAM_CALLBACK_setCompileRequired(t){t.PARAM_CALLBACK_setCompileRequired()}PARAM_CALLBACK_setCompileRequired(){var t;null===(t=this.assemblerController)||void 0===t||t.setCompilationRequired(!0)}}function cB(t){return class extends t{constructor(){super(...arguments),this.useFog=ha.BOOLEAN(0)}}}cB(ua);class hB extends JD{constructor(t){super(t),this.node=t}static update(t){const e=t.material,n=t.pv;e.fog=n.useFog}}function uB(t){return class extends t{constructor(){super(...arguments),this.default=ha.FOLDER(null)}}}function dB(t){return class extends t{constructor(){super(...arguments),this.advanced=ha.FOLDER(null)}}}class pB extends(cB(QD(aB(dB(sB(uB(ua))))))){constructor(){super(...arguments),this.linewidth=ha.FLOAT(1,{range:[0,10],rangeLocked:[!0,!1]})}}const _B=new pB;class mB extends lB{constructor(){super(...arguments),this.paramsConfig=_B,this.controllers={advancedCommon:new tB(this)},this.controllerNames=Object.keys(this.controllers)}static type(){return\\\\\\\"lineBasicBuilder\\\\\\\"}usedAssembler(){return jn.GL_LINE}_create_assembler_controller(){return li.assemblersRegister.assembler(this,this.usedAssembler())}initializeNode(){this.params.onParamsCreated(\\\\\\\"init controllers\\\\\\\",(()=>{for(let t of this.controllerNames)this.controllers[t].initializeNode()}))}async cook(){for(let t of this.controllerNames)this.controllers[t].update();rB.update(this),hB.update(this),this.compileIfRequired(),this.material.linewidth=this.pv.linewidth,this.setMaterial(this.material)}}function fB(t){return class extends t{constructor(){super(...arguments),this.color=ha.COLOR([1,1,1],{conversion:lo.SRGB_TO_LINEAR}),this.useVertexColors=ha.BOOLEAN(0,{separatorAfter:!0}),this.transparent=ha.BOOLEAN(0),this.opacity=ha.FLOAT(1),this.alphaTest=ha.FLOAT(0)}}}O.a;fB(ua);class gB extends JD{constructor(t){super(t),this.node=t}static update(t){const e=t.material,n=t.pv;e.color.copy(n.color);const i=n.useVertexColors;i!=e.vertexColors&&(e.vertexColors=i,e.needsUpdate=!0),e.opacity=n.opacity,e.transparent=n.transparent,e.alphaTest=n.alphaTest}}function vB(t){return class extends t{constructor(){super(...arguments),this.useFog=ha.BOOLEAN(0)}}}vB(ua);class yB extends JD{constructor(t){super(t),this.node=t}static update(t){const e=t.material,n=t.pv;e.fog=n.useFog}}function xB(t){return{cook:!1,callback:(e,n)=>{t.update(e)}}}function bB(t,e,n){return{visibleIf:{[e]:1},nodeSelection:{context:ts.COP,types:null==n?void 0:n.types},cook:!1,callback:(e,n)=>{t.update(e)}}}class wB extends JD{constructor(t,e){super(t),this.node=t,this._update_options=e}add_hooks(t,e){t.addPostDirtyHook(\\\\\\\"TextureController\\\\\\\",(()=>{this.update()})),e.addPostDirtyHook(\\\\\\\"TextureController\\\\\\\",(()=>{this.update()}))}static update(t){}async _update(t,e,n,i){if(this._update_options.uniforms){const s=t,r=e;await this._update_texture_on_uniforms(s,r,n,i)}if(this._update_options.directParams){const s=t,r=e;await this._update_texture_on_material(s,r,n,i)}}async _update_texture_on_uniforms(t,e,n,i){this._update_required_attribute(t,t.uniforms,e,n,i,this._apply_texture_on_uniforms.bind(this),this._remove_texture_from_uniforms.bind(this))}_apply_texture_on_uniforms(t,e,n,i){const s=null!=e[n]&&null!=e[n].value;let r=!1;if(s){e[n].value.uuid!=i.uuid&&(r=!0)}if(!s||r){e[n]&&(e[n].value=i),this._apply_texture_on_material(t,t,n,i),t.needsUpdate=!0;const s=t.customMaterials;if(s){const t=Object.keys(s);for(let e of t){const t=s[e];t&&this._apply_texture_on_uniforms(t,t.uniforms,n,i)}}}}_remove_texture_from_uniforms(t,e,n){if(e[n]){if(e[n].value){e[n].value=null,this._remove_texture_from_material(t,t,n),t.needsUpdate=!0;const i=t.customMaterials;if(i){const t=Object.keys(i);for(let e of t){const t=i[e];t&&this._remove_texture_from_uniforms(t,t.uniforms,n)}}}}else li.warn(`'${n}' uniform not found. existing uniforms are:`,Object.keys(e).sort())}async _update_texture_on_material(t,e,n,i){this._update_required_attribute(t,t,e,n,i,this._apply_texture_on_material.bind(this),this._remove_texture_from_material.bind(this))}_apply_texture_on_material(t,e,n,i){const s=null!=e[n];let r=!1;if(s){e[n].uuid!=i.uuid&&(r=!0)}s&&!r||(e[n]=i,t.needsUpdate=!0)}_remove_texture_from_material(t,e,n){e[n]&&(e[n]=null,t.needsUpdate=!0)}async _update_required_attribute(t,e,n,i,s,r,o){i.isDirty()&&await i.compute();if(i.value){s.isDirty()&&await s.compute();const i=s.value.nodeWithContext(ts.COP);if(i){const s=(await i.compute()).texture();if(s)return void r(t,e,n,s)}}o(t,e,n)}}function TB(t){return class extends t{constructor(){super(...arguments),this.useMap=ha.BOOLEAN(0,xB(AB)),this.map=ha.NODE_PATH(vi.EMPTY,bB(AB,\\\\\\\"useMap\\\\\\\"))}}}O.a;TB(ua);class AB extends wB{constructor(t,e){super(t,e),this.node=t}initializeNode(){this.add_hooks(this.node.p.useMap,this.node.p.map)}async update(){this._update(this.node.material,\\\\\\\"map\\\\\\\",this.node.p.useMap,this.node.p.map)}static async update(t){t.controllers.map.update()}}function MB(t){return class extends t{constructor(){super(...arguments),this.useAlphaMap=ha.BOOLEAN(0,{separatorBefore:!0,...xB(EB)}),this.alphaMap=ha.NODE_PATH(vi.EMPTY,bB(EB,\\\\\\\"useAlphaMap\\\\\\\"))}}}O.a;MB(ua);class EB extends wB{constructor(t,e){super(t,e),this.node=t}initializeNode(){this.add_hooks(this.node.p.useAlphaMap,this.node.p.alphaMap)}async update(){this._update(this.node.material,\\\\\\\"alphaMap\\\\\\\",this.node.p.useAlphaMap,this.node.p.alphaMap)}static async update(t){t.controllers.alphaMap.update()}}function SB(t){return class extends t{constructor(){super(...arguments),this.useAOMap=ha.BOOLEAN(0,{separatorBefore:!0,...xB(CB)}),this.aoMap=ha.NODE_PATH(vi.EMPTY,bB(CB,\\\\\\\"useAOMap\\\\\\\")),this.aoMapIntensity=ha.FLOAT(1,{range:[0,1],rangeLocked:[!1,!1],visibleIf:{useAOMap:1}})}}}O.a;SB(ua);class CB extends wB{constructor(t,e){super(t,e),this.node=t}initializeNode(){this.add_hooks(this.node.p.useAOMap,this.node.p.aoMap)}async update(){if(this._update(this.node.material,\\\\\\\"aoMap\\\\\\\",this.node.p.useAOMap,this.node.p.aoMap),this._update_options.uniforms){this.node.material.uniforms.aoMapIntensity.value=this.node.pv.aoMapIntensity}if(this._update_options.directParams){this.node.material.aoMapIntensity=this.node.pv.aoMapIntensity}}static async update(t){t.controllers.aoMap.update()}}var NB;!function(t){t.MULT=\\\\\\\"mult\\\\\\\",t.ADD=\\\\\\\"add\\\\\\\",t.MIX=\\\\\\\"mix\\\\\\\"}(NB||(NB={}));const LB=[NB.MULT,NB.ADD,NB.MIX],OB={[NB.MULT]:w.nb,[NB.ADD]:w.c,[NB.MIX]:w.lb};function PB(t){return class extends t{constructor(){super(...arguments),this.useEnvMap=ha.BOOLEAN(0,xB(RB)),this.envMap=ha.NODE_PATH(vi.EMPTY,bB(RB,\\\\\\\"useEnvMap\\\\\\\",{types:[Fg.CUBE_CAMERA]})),this.combine=ha.INTEGER(0,{visibleIf:{useEnvMap:1},menu:{entries:LB.map(((t,e)=>({name:t,value:e})))}}),this.reflectivity=ha.FLOAT(1,{visibleIf:{useEnvMap:1}}),this.refractionRatio=ha.FLOAT(.98,{range:[-1,1],rangeLocked:[!1,!1],visibleIf:{useEnvMap:1}})}}}PB(ua);class RB extends wB{constructor(t,e){super(t,e),this.node=t}initializeNode(){this.add_hooks(this.node.p.useEnvMap,this.node.p.envMap)}async update(){this._update(this.node.material,\\\\\\\"envMap\\\\\\\",this.node.p.useEnvMap,this.node.p.envMap);const t=OB[LB[this.node.pv.combine]];if(this._update_options.uniforms){const t=this.node.material;t.uniforms.reflectivity.value=this.node.pv.reflectivity,t.uniforms.refractionRatio.value=this.node.pv.refractionRatio}if(this._update_options.directParams){const e=this.node.material;e.combine=t,e.reflectivity=this.node.pv.reflectivity,e.refractionRatio=this.node.pv.refractionRatio}}static async update(t){t.controllers.envMap.update()}}function IB(t){return class extends t{constructor(){super(...arguments),this.useLightMap=ha.BOOLEAN(0,{separatorBefore:!0,...xB(FB)}),this.lightMap=ha.NODE_PATH(vi.EMPTY,bB(FB,\\\\\\\"useLightMap\\\\\\\")),this.lightMapIntensity=ha.FLOAT(1,{visibleIf:{useLightMap:1}})}}}O.a;IB(ua);class FB extends wB{constructor(t,e){super(t,e),this.node=t}initializeNode(){this.add_hooks(this.node.p.useLightMap,this.node.p.lightMap)}async update(){if(this._update(this.node.material,\\\\\\\"lightMap\\\\\\\",this.node.p.useLightMap,this.node.p.lightMap),this._update_options.uniforms){this.node.material.uniforms.lightMapIntensity.value=this.node.pv.lightMapIntensity}if(this._update_options.directParams){this.node.material.lightMapIntensity=this.node.pv.lightMapIntensity}}static async update(t){t.controllers.lightMap.update()}}var DB;!function(t){t.ROUND=\\\\\\\"round\\\\\\\",t.BUTT=\\\\\\\"butt\\\\\\\",t.SQUARE=\\\\\\\"square\\\\\\\"}(DB||(DB={}));const BB=[DB.ROUND,DB.BUTT,DB.SQUARE];var zB;!function(t){t.ROUND=\\\\\\\"round\\\\\\\",t.BEVEL=\\\\\\\"bevel\\\\\\\",t.MITER=\\\\\\\"miter\\\\\\\"}(zB||(zB={}));const kB=[zB.ROUND,zB.BEVEL,zB.MITER];function UB(t){return class extends t{constructor(){super(...arguments),this.wireframe=ha.BOOLEAN(0,{separatorBefore:!0}),this.wireframeLinecap=ha.INTEGER(0,{menu:{entries:BB.map(((t,e)=>({name:t,value:e})))},visibleIf:{wireframe:1}}),this.wireframeLinejoin=ha.INTEGER(0,{menu:{entries:kB.map(((t,e)=>({name:t,value:e})))},visibleIf:{wireframe:1}})}}}O.a;UB(ua);class GB extends JD{constructor(t){super(t),this.node=t}static update(t){const e=t.material,n=t.pv;e.wireframe=n.wireframe,e.wireframeLinecap=BB[n.wireframeLinecap],e.wireframeLinejoin=kB[n.wireframeLinejoin],e.needsUpdate=!0}}function VB(t){return class extends t{constructor(){super(...arguments),this.textures=ha.FOLDER(null)}}}const HB={directParams:!0};class jB extends(vB(UB(QD(dB(IB(PB(SB(MB(TB(VB(fB(uB(ua))))))))))))){}const WB=new jB;class qB extends $D{constructor(){super(...arguments),this.paramsConfig=WB,this.controllers={advancedCommon:new tB(this),alphaMap:new EB(this,HB),aoMap:new CB(this,HB),envMap:new RB(this,HB),lightMap:new FB(this,HB),map:new AB(this,HB)},this.controllerNames=Object.keys(this.controllers)}static type(){return\\\\\\\"meshBasic\\\\\\\"}createMaterial(){return new lt.a({vertexColors:!1,side:w.H,color:16777215,opacity:1})}initializeNode(){this.params.onParamsCreated(\\\\\\\"init controllers\\\\\\\",(()=>{for(let t of this.controllerNames)this.controllers[t].initializeNode()}))}async cook(){for(let t of this.controllerNames)this.controllers[t].update();gB.update(this),yB.update(this),GB.update(this),this.setMaterial(this.material)}}function XB(t){return class extends t{constructor(){super(...arguments),this.wireframe=ha.BOOLEAN(0)}}}XB(ua);class YB extends JD{constructor(t){super(t),this.node=t}static update(t){const e=t.material,n=t.pv;e.wireframe=n.wireframe,e.needsUpdate=!0}}const $B={uniforms:!0};class JB extends(cB(XB(QD(aB(dB(PB(SB(MB(TB(VB(sB(uB(ua))))))))))))){}const ZB=new JB;class KB extends lB{constructor(){super(...arguments),this.paramsConfig=ZB,this.controllers={advancedCommon:new tB(this),alphaMap:new EB(this,$B),aoMap:new CB(this,$B),envMap:new RB(this,$B),map:new AB(this,$B)},this.controllerNames=Object.keys(this.controllers)}static type(){return\\\\\\\"meshBasicBuilder\\\\\\\"}usedAssembler(){return jn.GL_MESH_BASIC}_create_assembler_controller(){return li.assemblersRegister.assembler(this,this.usedAssembler())}initializeNode(){this.params.onParamsCreated(\\\\\\\"init controllers\\\\\\\",(()=>{for(let t of this.controllerNames)this.controllers[t].initializeNode()}))}async cook(){for(let t of this.controllerNames)this.controllers[t].update();rB.update(this),hB.update(this),YB.update(this),this.compileIfRequired(),this.setMaterial(this.material)}}function QB(t){return class extends t{constructor(){super(...arguments),this.emissive=ha.COLOR([0,0,0],{separatorBefore:!0}),this.useEmissiveMap=ha.BOOLEAN(0,xB(tz)),this.emissiveMap=ha.NODE_PATH(vi.EMPTY,bB(tz,\\\\\\\"useEmissiveMap\\\\\\\")),this.emissiveIntensity=ha.FLOAT(1)}}}O.a;QB(ua);class tz extends wB{constructor(t,e){super(t,e),this.node=t}initializeNode(){this.add_hooks(this.node.p.useEmissiveMap,this.node.p.emissiveMap)}async update(){if(this._update(this.node.material,\\\\\\\"emissiveMap\\\\\\\",this.node.p.useEmissiveMap,this.node.p.emissiveMap),this._update_options.uniforms){this.node.material.uniforms.emissive.value.copy(this.node.pv.emissive)}if(this._update_options.directParams){const t=this.node.material;t.emissive.copy(this.node.pv.emissive),t.emissiveIntensity=this.node.pv.emissiveIntensity}}static async update(t){t.controllers.emissiveMap.update()}}const ez={directParams:!0};class nz extends(vB(UB(QD(dB(IB(PB(QB(SB(MB(TB(VB(fB(uB(ua)))))))))))))){}const iz=new nz;class sz extends $D{constructor(){super(...arguments),this.paramsConfig=iz,this.controllers={advancedCommon:new tB(this),alphaMap:new EB(this,ez),aoMap:new CB(this,ez),emissiveMap:new tz(this,ez),envMap:new RB(this,ez),lightMap:new FB(this,ez),map:new AB(this,ez)},this.controllerNames=Object.keys(this.controllers)}static type(){return\\\\\\\"meshLambert\\\\\\\"}createMaterial(){return new Ts.a({vertexColors:!1,side:w.H,color:16777215,opacity:1})}initializeNode(){this.params.onParamsCreated(\\\\\\\"init controllers\\\\\\\",(()=>{for(let t of this.controllerNames)this.controllers[t].initializeNode()}))}async cook(){for(let t of this.controllerNames)this.controllers[t].update();gB.update(this),yB.update(this),GB.update(this),this.setMaterial(this.material)}}function rz(t){return class extends t{constructor(){super(...arguments),this.shadowPCSS=ha.BOOLEAN(0,{callback:t=>{oz.PARAM_CALLBACK_setRecompileRequired(t)},separatorBefore:!0}),this.shadowPCSSSamplesCount=ha.INTEGER(16,{visibleIf:{shadowPCSS:1},range:[0,128],rangeLocked:[!0,!1]}),this.shadowPCSSFilterSize=ha.FLOAT(1,{visibleIf:{shadowPCSS:1},range:[0,10],rangeLocked:[!0,!1]})}}}rz(ua);class oz extends JD{constructor(t){super(t),this.node=t}initializeNode(){}static filterFragmentShader(t,e){const n=`\\\\n#define NUM_SAMPLES ${mf.integer(t.pv.shadowPCSSSamplesCount)}\\\\n#define PCSS_FILTER_SIZE ${mf.float(t.pv.shadowPCSSFilterSize)}\\\\n#define LIGHT_WORLD_SIZE 0.005\\\\n// #define LIGHT_FRUSTUM_WIDTH 1.0\\\\n// #define PCSS_FILTER_SIZE 1.0\\\\n#define LIGHT_SIZE_UV (PCSS_FILTER_SIZE * LIGHT_WORLD_SIZE)\\\\n#define NEAR_PLANE 9.5\\\\n\\\\n// #define NUM_SAMPLES 32\\\\n#define NUM_RINGS 11\\\\n#define BLOCKER_SEARCH_NUM_SAMPLES NUM_SAMPLES\\\\n#define PCF_NUM_SAMPLES NUM_SAMPLES\\\\n\\\\nvec2 poissonDisk[NUM_SAMPLES];\\\\n\\\\nvoid initPoissonSamples( const in vec2 randomSeed ) {\\\\n\\\\tfloat ANGLE_STEP = PI2 * float( NUM_RINGS ) / float( NUM_SAMPLES );\\\\n\\\\tfloat INV_NUM_SAMPLES = 1.0 / float( NUM_SAMPLES );\\\\n\\\\n\\\\t// jsfiddle that shows sample pattern: https://jsfiddle.net/a16ff1p7/\\\\n\\\\tfloat angle = rand( randomSeed ) * PI2;\\\\n\\\\tfloat radius = INV_NUM_SAMPLES;\\\\n\\\\tfloat radiusStep = radius;\\\\n\\\\n\\\\tfor( int i = 0; i < NUM_SAMPLES; i ++ ) {\\\\n\\\\t\\\\tpoissonDisk[i] = vec2( cos( angle ), sin( angle ) ) * pow( radius, 0.75 );\\\\n\\\\t\\\\tradius += radiusStep;\\\\n\\\\t\\\\tangle += ANGLE_STEP;\\\\n\\\\t}\\\\n}\\\\n\\\\nfloat penumbraSize( const in float zReceiver, const in float zBlocker ) { // Parallel plane estimation\\\\n\\\\treturn (zReceiver - zBlocker) / zBlocker;\\\\n}\\\\n\\\\nfloat findBlocker( sampler2D shadowMap, const in vec2 uv, const in float zReceiver ) {\\\\n\\\\t// This uses similar triangles to compute what\\\\n\\\\t// area of the shadow map we should search\\\\n\\\\tfloat searchRadius = LIGHT_SIZE_UV * ( zReceiver - NEAR_PLANE ) / zReceiver;\\\\n\\\\tfloat blockerDepthSum = 0.0;\\\\n\\\\tint numBlockers = 0;\\\\n\\\\n\\\\tfor( int i = 0; i < BLOCKER_SEARCH_NUM_SAMPLES; i++ ) {\\\\n\\\\t\\\\tfloat shadowMapDepth = unpackRGBAToDepth(texture2D(shadowMap, uv + poissonDisk[i] * searchRadius));\\\\n\\\\t\\\\tif ( shadowMapDepth < zReceiver ) {\\\\n\\\\t\\\\t\\\\tblockerDepthSum += shadowMapDepth;\\\\n\\\\t\\\\t\\\\tnumBlockers ++;\\\\n\\\\t\\\\t}\\\\n\\\\t}\\\\n\\\\n\\\\tif( numBlockers == 0 ) return -1.0;\\\\n\\\\n\\\\treturn blockerDepthSum / float( numBlockers );\\\\n}\\\\n\\\\nfloat PCF_Filter(sampler2D shadowMap, vec2 uv, float zReceiver, float filterRadius ) {\\\\n\\\\tfloat sum = 0.0;\\\\n\\\\tfor( int i = 0; i < PCF_NUM_SAMPLES; i ++ ) {\\\\n\\\\t\\\\tfloat depth = unpackRGBAToDepth( texture2D( shadowMap, uv + poissonDisk[ i ] * filterRadius ) );\\\\n\\\\t\\\\tif( zReceiver <= depth ) sum += 1.0;\\\\n\\\\t}\\\\n\\\\tfor( int i = 0; i < PCF_NUM_SAMPLES; i ++ ) {\\\\n\\\\t\\\\tfloat depth = unpackRGBAToDepth( texture2D( shadowMap, uv + -poissonDisk[ i ].yx * filterRadius ) );\\\\n\\\\t\\\\tif( zReceiver <= depth ) sum += 1.0;\\\\n\\\\t}\\\\n\\\\treturn sum / ( 2.0 * float( PCF_NUM_SAMPLES ) );\\\\n}\\\\n\\\\nfloat PCSS ( sampler2D shadowMap, vec4 coords ) {\\\\n\\\\tvec2 uv = coords.xy;\\\\n\\\\tfloat zReceiver = coords.z; // Assumed to be eye-space z in this code\\\\n\\\\n\\\\tinitPoissonSamples( uv );\\\\n\\\\t// STEP 1: blocker search\\\\n\\\\tfloat avgBlockerDepth = findBlocker( shadowMap, uv, zReceiver );\\\\n\\\\n\\\\t//There are no occluders so early out (this saves filtering)\\\\n\\\\tif( avgBlockerDepth == -1.0 ) return 1.0;\\\\n\\\\n\\\\t// STEP 2: penumbra size\\\\n\\\\tfloat penumbraRatio = penumbraSize( zReceiver, avgBlockerDepth );\\\\n\\\\tfloat filterRadius = penumbraRatio * LIGHT_SIZE_UV * NEAR_PLANE / zReceiver;\\\\n\\\\n\\\\t// STEP 3: filtering\\\\n\\\\t//return avgBlockerDepth;\\\\n\\\\treturn PCF_Filter( shadowMap, uv, zReceiver, filterRadius );\\\\n}\\\\n`;let i=z;return i=i.replace(\\\\\\\"#ifdef USE_SHADOWMAP\\\\\\\",`#ifdef USE_SHADOWMAP\\\\n${n}\\\\n\\\\t\\\\t\\\\t\\\\t`),i=i.replace(\\\\\\\"#if defined( SHADOWMAP_TYPE_PCF )\\\\\\\",\\\\\\\"\\\\n\\\\t\\\\t\\\\t\\\\treturn PCSS( shadowMap, shadowCoord );\\\\n\\\\t\\\\t\\\\t\\\\t#if defined( SHADOWMAP_TYPE_PCF )\\\\\\\"),e=e.replace(\\\\\\\"#include \\\\\\\",i)}async update(){const t=this.node;if(!t.assemblerController)return;const e=\\\\\\\"PCSS\\\\\\\";this.node.pv.shadowPCSS?t.assemblerController.addFilterFragmentShaderCallback(e,(t=>oz.filterFragmentShader(this.node,t))):t.assemblerController.removeFilterFragmentShaderCallback(e)}static async update(t){t.controllers.PCSS.update()}static PARAM_CALLBACK_setRecompileRequired(t){t.controllers.PCSS.update()}}const az={uniforms:!0};class lz extends(rz(cB(XB(QD(aB(dB(IB(PB(QB(SB(MB(TB(VB(sB(uB(ua)))))))))))))))){}const cz=new lz;class hz extends lB{constructor(){super(...arguments),this.paramsConfig=cz,this.controllers={advancedCommon:new tB(this),alphaMap:new EB(this,az),aoMap:new CB(this,az),emissiveMap:new tz(this,az),envMap:new RB(this,az),lightMap:new FB(this,az),map:new AB(this,az),PCSS:new oz(this)},this.controllerNames=Object.keys(this.controllers)}static type(){return\\\\\\\"meshLambertBuilder\\\\\\\"}usedAssembler(){return jn.GL_MESH_LAMBERT}_create_assembler_controller(){return li.assemblersRegister.assembler(this,this.usedAssembler())}initializeNode(){this.params.onParamsCreated(\\\\\\\"init controllers\\\\\\\",(()=>{for(let t of this.controllerNames)this.controllers[t].initializeNode()}))}async cook(){for(let t of this.controllerNames)this.controllers[t].update();rB.update(this),hB.update(this),YB.update(this),this.compileIfRequired(),this.setMaterial(this.material)}}function uz(t){return class extends t{constructor(){super(...arguments),this.useBumpMap=ha.BOOLEAN(0,{separatorBefore:!0,...xB(dz)}),this.bumpMap=ha.NODE_PATH(\\\\\\\"\\\\\\\",bB(dz,\\\\\\\"useBumpMap\\\\\\\")),this.bumpScale=ha.FLOAT(1,{range:[0,1],rangeLocked:[!1,!1],...bB(dz,\\\\\\\"useBumpMap\\\\\\\")}),this.bumpBias=ha.FLOAT(0,{range:[0,1],rangeLocked:[!1,!1],...bB(dz,\\\\\\\"useBumpMap\\\\\\\")})}}}O.a;uz(ua);class dz extends wB{constructor(t,e){super(t,e),this.node=t}initializeNode(){this.add_hooks(this.node.p.useBumpMap,this.node.p.bumpMap)}async update(){if(this._update(this.node.material,\\\\\\\"bumpMap\\\\\\\",this.node.p.useBumpMap,this.node.p.bumpMap),this._update_options.uniforms){this.node.material.uniforms.bumpScale.value=this.node.pv.bumpScale}if(this._update_options.directParams){this.node.material.bumpScale=this.node.pv.bumpScale}}static async update(t){t.controllers.bumpMap.update()}}var pz;!function(t){t.TANGENT=\\\\\\\"tangent\\\\\\\",t.OBJECT=\\\\\\\"object\\\\\\\"}(pz||(pz={}));const _z=[pz.TANGENT,pz.OBJECT],mz={[pz.TANGENT]:w.Uc,[pz.OBJECT]:w.zb};function fz(t){return class extends t{constructor(){super(...arguments),this.useNormalMap=ha.BOOLEAN(0,{separatorBefore:!0,...xB(gz)}),this.normalMap=ha.NODE_PATH(vi.EMPTY,bB(gz,\\\\\\\"useNormalMap\\\\\\\")),this.normalMapType=ha.INTEGER(0,{visibleIf:{useNormalMap:1},menu:{entries:_z.map(((t,e)=>({name:t,value:e})))}}),this.normalScale=ha.VECTOR2([1,1],{visibleIf:{useNormalMap:1}})}}}O.a;fz(ua);class gz extends wB{constructor(t,e){super(t,e),this.node=t}initializeNode(){this.add_hooks(this.node.p.useNormalMap,this.node.p.normalMap)}async update(){this._update(this.node.material,\\\\\\\"normalMap\\\\\\\",this.node.p.useNormalMap,this.node.p.normalMap);const t=mz[_z[this.node.pv.normalMapType]];if(this._update_options.uniforms){this.node.material.uniforms.normalScale.value.copy(this.node.pv.normalScale)}const e=this.node.material;e.normalMapType=t,this._update_options.directParams&&e.normalScale.copy(this.node.pv.normalScale)}static async update(t){t.controllers.normalMap.update()}}function vz(t){return class extends t{constructor(){super(...arguments),this.useDisplacementMap=ha.BOOLEAN(0,{separatorBefore:!0,...xB(yz)}),this.displacementMap=ha.NODE_PATH(\\\\\\\"\\\\\\\",bB(yz,\\\\\\\"useDisplacementMap\\\\\\\")),this.displacementScale=ha.FLOAT(1,{range:[0,1],rangeLocked:[!1,!1],...bB(yz,\\\\\\\"useDisplacementMap\\\\\\\")}),this.displacementBias=ha.FLOAT(0,{range:[0,1],rangeLocked:[!1,!1],...bB(yz,\\\\\\\"useDisplacementMap\\\\\\\")})}}}O.a;vz(ua);class yz extends wB{constructor(t,e){super(t,e),this.node=t}initializeNode(){this.add_hooks(this.node.p.useDisplacementMap,this.node.p.displacementMap)}async update(){if(this._update(this.node.material,\\\\\\\"displacementMap\\\\\\\",this.node.p.useDisplacementMap,this.node.p.displacementMap),this._update_options.uniforms){const t=this.node.material;t.uniforms.displacementScale.value=this.node.pv.displacementScale,t.uniforms.displacementBias.value=this.node.pv.displacementBias}if(this._update_options.directParams){const t=this.node.material;t.displacementScale=this.node.pv.displacementScale,t.displacementBias=this.node.pv.displacementBias}}static async update(t){t.controllers.displacementMap.update()}}function xz(t){return class extends t{constructor(){super(...arguments),this.useMatcapMap=ha.BOOLEAN(0,xB(bz)),this.matcapMap=ha.NODE_PATH(vi.EMPTY,bB(bz,\\\\\\\"useMatcapMap\\\\\\\"))}}}O.a;xz(ua);class bz extends wB{constructor(t,e){super(t,e),this.node=t}initializeNode(){this.add_hooks(this.node.p.useMatcapMap,this.node.p.matcapMap)}async update(){this._update(this.node.material,\\\\\\\"matcap\\\\\\\",this.node.p.useMatcapMap,this.node.p.matcapMap)}static async update(t){t.controllers.matcap.update()}}const wz={directParams:!0};class Tz extends(vB(QD(dB(fz(vz(uz(MB(TB(xz(VB(fB(uB(ua))))))))))))){}const Az=new Tz;class Mz extends $D{constructor(){super(...arguments),this.paramsConfig=Az,this.controllers={advancedCommon:new tB(this),alphaMap:new EB(this,wz),bumpMap:new dz(this,wz),displacementMap:new yz(this,wz),map:new AB(this,wz),matcap:new bz(this,wz),normalMap:new gz(this,wz)},this.controllerNames=Object.keys(this.controllers)}static type(){return\\\\\\\"meshMatcap\\\\\\\"}createMaterial(){return new $f({vertexColors:!1,side:w.H,color:16777215,opacity:1})}initializeNode(){this.params.onParamsCreated(\\\\\\\"init controllers\\\\\\\",(()=>{for(let t of this.controllerNames)this.controllers[t].initializeNode()}))}async cook(){for(let t of this.controllerNames)this.controllers[t].update();gB.update(this),yB.update(this),this.setMaterial(this.material)}}const Ez={directParams:!0};class Sz extends(vB(QD(fz(vz(uz(VB(uB(ua)))))))){}const Cz=new Sz;class Nz extends $D{constructor(){super(...arguments),this.paramsConfig=Cz,this.controllers={advancedCommon:new tB(this),bumpMap:new dz(this,Ez),displacementMap:new yz(this,Ez),normalMap:new gz(this,Ez)},this.controllerNames=Object.keys(this.controllers)}static type(){return\\\\\\\"meshNormal\\\\\\\"}createMaterial(){return new Yf({vertexColors:!1,side:w.H,opacity:1})}initializeNode(){this.params.onParamsCreated(\\\\\\\"init controllers\\\\\\\",(()=>{for(let t of this.controllerNames)this.controllers[t].initializeNode()}))}async cook(){for(let t of this.controllerNames)this.controllers[t].update();yB.update(this),this.setMaterial(this.material)}}function Lz(t){return class extends t{constructor(){super(...arguments),this.useSpecularMap=ha.BOOLEAN(0,xB(Oz)),this.specularMap=ha.NODE_PATH(vi.EMPTY,bB(Oz,\\\\\\\"useSpecularMap\\\\\\\"))}}}O.a;Lz(ua);class Oz extends wB{constructor(t,e){super(t,e),this.node=t}initializeNode(){this.add_hooks(this.node.p.useSpecularMap,this.node.p.specularMap)}async update(){this._update(this.node.material,\\\\\\\"specularMap\\\\\\\",this.node.p.useSpecularMap,this.node.p.specularMap)}static async update(t){t.controllers.specularMap.update()}}const Pz={directParams:!0};class Rz extends(vB(UB(QD(dB(Lz(fz(IB(PB(QB(vz(uz(SB(MB(TB(VB(fB(uB(ua)))))))))))))))))){constructor(){super(...arguments),this.flatShading=ha.BOOLEAN(0)}}const Iz=new Rz;class Fz extends $D{constructor(){super(...arguments),this.paramsConfig=Iz,this.controllers={advancedCommon:new tB(this),alphaMap:new EB(this,Pz),aoMap:new CB(this,Pz),bumpMap:new dz(this,Pz),displacementMap:new yz(this,Pz),emissiveMap:new tz(this,Pz),envMap:new RB(this,Pz),lightMap:new FB(this,Pz),map:new AB(this,Pz),normalMap:new gz(this,Pz),specularMap:new Oz(this,Pz)},this.controllerNames=Object.keys(this.controllers)}static type(){return\\\\\\\"meshPhong\\\\\\\"}createMaterial(){return new qf.a({vertexColors:!1,side:w.H,color:16777215,opacity:1})}initializeNode(){this.params.onParamsCreated(\\\\\\\"init controllers\\\\\\\",(()=>{for(let t of this.controllerNames)this.controllers[t].initializeNode()}))}async cook(){for(let t of this.controllerNames)this.controllers[t].update();gB.update(this),yB.update(this),GB.update(this),this.material.flatShading!=this.pv.flatShading&&(this.material.flatShading=this.pv.flatShading,this.material.needsUpdate=!0),this.setMaterial(this.material)}}const Dz={uniforms:!0};class Bz extends(rz(cB(XB(QD(aB(dB(Lz(fz(IB(PB(QB(vz(uz(SB(MB(TB(VB(sB(uB(ua)))))))))))))))))))){}const zz=new Bz;class kz extends lB{constructor(){super(...arguments),this.paramsConfig=zz,this.controllers={advancedCommon:new tB(this),alphaMap:new EB(this,Dz),aoMap:new CB(this,Dz),bumpMap:new dz(this,Dz),displacementMap:new yz(this,Dz),emissiveMap:new tz(this,Dz),envMap:new RB(this,Dz),lightMap:new FB(this,Dz),map:new AB(this,Dz),normalMap:new gz(this,Dz),specularMap:new Oz(this,Dz),PCSS:new oz(this)},this.controllerNames=Object.keys(this.controllers)}static type(){return\\\\\\\"meshPhongBuilder\\\\\\\"}usedAssembler(){return jn.GL_MESH_PHONG}_create_assembler_controller(){return li.assemblersRegister.assembler(this,this.usedAssembler())}initializeNode(){this.params.onParamsCreated(\\\\\\\"init controllers\\\\\\\",(()=>{for(let t of this.controllerNames)this.controllers[t].initializeNode()}))}async cook(){for(let t of this.controllerNames)this.controllers[t].update();rB.update(this),hB.update(this),YB.update(this),this.compileIfRequired(),this.setMaterial(this.material)}}function Uz(t){return class extends t{constructor(){super(...arguments),this.useEnvMap=ha.BOOLEAN(0,{separatorBefore:!0,...xB(Gz)}),this.envMap=ha.NODE_PATH(vi.EMPTY,bB(Gz,\\\\\\\"useEnvMap\\\\\\\")),this.envMapIntensity=ha.FLOAT(1,{visibleIf:{useEnvMap:1}}),this.refractionRatio=ha.FLOAT(.98,{range:[-1,1],rangeLocked:[!1,!1],visibleIf:{useEnvMap:1}})}}}Uz(ua);class Gz extends wB{constructor(t,e){super(t,e),this.node=t}initializeNode(){this.add_hooks(this.node.p.useEnvMap,this.node.p.envMap)}async update(){if(this._update(this.node.material,\\\\\\\"envMap\\\\\\\",this.node.p.useEnvMap,this.node.p.envMap),this._update_options.uniforms){const t=this.node.material;t.uniforms.envMapIntensity.value=this.node.pv.envMapIntensity,t.uniforms.refractionRatio.value=this.node.pv.refractionRatio}if(this._update_options.directParams){const t=this.node.material;t.envMapIntensity=this.node.pv.envMapIntensity,t.refractionRatio=this.node.pv.refractionRatio}}static async update(t){t.controllers.envMap.update()}}function Vz(t){return class extends t{constructor(){super(...arguments),this.useMetalnessMap=ha.BOOLEAN(0,{separatorBefore:!0,...xB(Hz)}),this.metalnessMap=ha.NODE_PATH(vi.EMPTY,bB(Hz,\\\\\\\"useMetalnessMap\\\\\\\")),this.metalness=ha.FLOAT(1),this.useRoughnessMap=ha.BOOLEAN(0,{separatorBefore:!0,...xB(Hz)}),this.roughnessMap=ha.NODE_PATH(vi.EMPTY,bB(Hz,\\\\\\\"useRoughnessMap\\\\\\\")),this.roughness=ha.FLOAT(.5)}}}O.a;Vz(ua);class Hz extends wB{constructor(t,e){super(t,e),this.node=t}initializeNode(){this.add_hooks(this.node.p.useMetalnessMap,this.node.p.metalnessMap)}async update(){if(this._update(this.node.material,\\\\\\\"metalnessMap\\\\\\\",this.node.p.useMetalnessMap,this.node.p.metalnessMap),this._update_options.uniforms){this.node.material.uniforms.metalness.value=this.node.pv.metalness}if(this._update_options.directParams){this.node.material.metalness=this.node.pv.metalness}if(this._update(this.node.material,\\\\\\\"roughnessMap\\\\\\\",this.node.p.useRoughnessMap,this.node.p.roughnessMap),this._update_options.uniforms){this.node.material.uniforms.roughness.value=this.node.pv.roughness}if(this._update_options.directParams){this.node.material.roughness=this.node.pv.roughness}}static async update(t){t.controllers.metalnessRoughnessMap.update()}}function jz(t){return class extends t{constructor(){super(...arguments),this.clearcoat=ha.FLOAT(0,{separatorBefore:!0}),this.useClearCoatMap=ha.BOOLEAN(0,xB(qz)),this.clearcoatMap=ha.NODE_PATH(vi.EMPTY,bB(qz,\\\\\\\"useClearCoatMap\\\\\\\")),this.useClearCoatNormalMap=ha.BOOLEAN(0,xB(qz)),this.clearcoatNormalMap=ha.NODE_PATH(vi.EMPTY,bB(qz,\\\\\\\"useClearCoatNormalMap\\\\\\\")),this.clearcoatNormalScale=ha.VECTOR2([1,1],{visibleIf:{useClearCoatNormalMap:1}}),this.clearcoatRoughness=ha.FLOAT(0),this.useClearCoatRoughnessMap=ha.BOOLEAN(0,xB(qz)),this.clearcoatRoughnessMap=ha.NODE_PATH(vi.EMPTY,bB(qz,\\\\\\\"useClearCoatRoughnessMap\\\\\\\")),this.useSheen=ha.BOOLEAN(0),this.sheen=ha.FLOAT(0,{range:[0,1],rangeLocked:[!0,!1],visibleIf:{useSheen:1}}),this.sheenRoughness=ha.FLOAT(1,{range:[0,1],rangeLocked:[!0,!1],visibleIf:{useSheen:1}}),this.sheenColor=ha.COLOR([1,1,1],{visibleIf:{useSheen:1}}),this.transmission=ha.FLOAT(0,{range:[0,1]}),this.useTransmissionMap=ha.BOOLEAN(0),this.transmissionMap=ha.NODE_PATH(vi.EMPTY,{visibleIf:{useTransmissionMap:1}}),this.ior=ha.FLOAT(1.5,{range:[1,2.3333],rangeLocked:[!0,!0]}),this.thickness=ha.FLOAT(.01,{range:[0,10],rangeLocked:[!0,!1]}),this.useThicknessMap=ha.BOOLEAN(0),this.thicknessMap=ha.NODE_PATH(vi.EMPTY,{visibleIf:{useThicknessMap:1}}),this.attenuationDistance=ha.FLOAT(0,{range:[0,10],rangeLocked:[!0,!1]}),this.attenuationColor=ha.COLOR([1,1,1])}}}jz(ua);const Wz=new Wf.a;class qz extends wB{constructor(t,e){super(t,e),this.node=t,this._sheenColorClone=new D.a}initializeNode(){this.add_hooks(this.node.p.useClearCoatMap,this.node.p.clearcoatMap),this.add_hooks(this.node.p.useClearCoatNormalMap,this.node.p.clearcoatNormalMap),this.add_hooks(this.node.p.useClearCoatRoughnessMap,this.node.p.clearcoatRoughnessMap),this.add_hooks(this.node.p.useTransmissionMap,this.node.p.transmissionMap),this.add_hooks(this.node.p.useThicknessMap,this.node.p.thicknessMap)}async update(){this._update(this.node.material,\\\\\\\"clearcoatMap\\\\\\\",this.node.p.useClearCoatMap,this.node.p.clearcoatMap),this._update(this.node.material,\\\\\\\"clearcoatNormalMap\\\\\\\",this.node.p.useClearCoatNormalMap,this.node.p.clearcoatNormalMap),this._update(this.node.material,\\\\\\\"clearcoatRoughnessMap\\\\\\\",this.node.p.useClearCoatRoughnessMap,this.node.p.clearcoatRoughnessMap),this._update(this.node.material,\\\\\\\"transmissionMap\\\\\\\",this.node.p.useTransmissionMap,this.node.p.transmissionMap),this._update(this.node.material,\\\\\\\"thicknessMap\\\\\\\",this.node.p.useThicknessMap,this.node.p.thicknessMap);const t=this.node.pv;Wz.ior=t.ior;const e=Wz.reflectivity;if(this._update_options.uniforms){const n=this.node.material;n.uniforms.clearcoat.value=t.clearcoat,n.uniforms.clearcoatNormalScale.value.copy(t.clearcoatNormalScale),n.uniforms.clearcoatRoughness.value=t.clearcoatRoughness,n.uniforms.reflectivity.value=e,n.uniforms.transmission.value=t.transmission,n.uniforms.thickness.value=t.thickness,n.uniforms.attenuationDistance.value=t.attenuationDistance,n.uniforms.attenuationTint.value=t.attenuationColor,t.useSheen?(this._sheenColorClone.copy(t.sheenColor),n.uniforms.sheen.value=t.sheen,n.uniforms.sheenRoughness.value=t.sheenRoughness,n.uniforms.sheenTint.value=this._sheenColorClone):n.uniforms.sheen.value=0,n.uniforms.ior.value=t.ior,n.specularTint=n.uniforms.specularTint.value,n.ior=n.uniforms.ior.value}if(this._update_options.directParams){const n=this.node.material;n.clearcoat=t.clearcoat,null!=n.clearcoatNormalScale&&n.clearcoatNormalScale.copy(t.clearcoatNormalScale),n.clearcoatRoughness=t.clearcoatRoughness,n.reflectivity=e,t.useSheen?(this._sheenColorClone.copy(t.sheenColor),n.sheen=t.sheen,n.sheenRoughness=t.sheenRoughness,n.sheenTint=this._sheenColorClone):n.sheen=0,n.transmission=t.transmission,n.thickness=t.thickness,n.attenuationDistance=t.attenuationDistance,n.attenuationTint=t.attenuationColor}}static async update(t){t.controllers.physical.update()}}const Xz={directParams:!0};class Yz extends(vB(UB(QD(dB(jz(Vz(fz(IB(Uz(QB(vz(uz(SB(MB(TB(VB(fB(uB(ua))))))))))))))))))){}const $z=new Yz;class Jz extends $D{constructor(){super(...arguments),this.paramsConfig=$z,this.controllers={advancedCommon:new tB(this),alphaMap:new EB(this,Xz),aoMap:new CB(this,Xz),bumpMap:new dz(this,Xz),displacementMap:new yz(this,Xz),emissiveMap:new tz(this,Xz),envMap:new Gz(this,Xz),lightMap:new FB(this,Xz),map:new AB(this,Xz),metalnessRoughnessMap:new Hz(this,Xz),normalMap:new gz(this,Xz),physical:new qz(this,Xz)},this.controllerNames=Object.keys(this.controllers)}static type(){return\\\\\\\"meshPhysical\\\\\\\"}createMaterial(){return new Wf.a({vertexColors:!1,side:w.H,color:16777215,opacity:1,metalness:1,roughness:0})}initializeNode(){this.params.onParamsCreated(\\\\\\\"init controllers\\\\\\\",(()=>{for(let t of this.controllerNames)this.controllers[t].initializeNode()}))}async cook(){for(let t of this.controllerNames)this.controllers[t].update();gB.update(this),yB.update(this),GB.update(this),this.setMaterial(this.material)}}const Zz={uniforms:!0};class Kz extends(function(t){return class extends(rz(cB(XB(QD(aB(t)))))){}}(dB(jz(Vz(fz(IB(Uz(QB(vz(uz(SB(MB(TB(VB(sB(uB(ua))))))))))))))))){}const Qz=new Kz;class tk extends lB{constructor(){super(...arguments),this.paramsConfig=Qz,this.controllers={advancedCommon:new tB(this),alphaMap:new EB(this,Zz),aoMap:new CB(this,Zz),bumpMap:new dz(this,Zz),displacementMap:new yz(this,Zz),emissiveMap:new tz(this,Zz),envMap:new Gz(this,{uniforms:!0,directParams:!0}),lightMap:new FB(this,Zz),map:new AB(this,Zz),metalnessRoughnessMap:new Hz(this,{uniforms:!0,directParams:!0}),normalMap:new gz(this,Zz),physical:new qz(this,{uniforms:!0,directParams:!0}),PCSS:new oz(this)},this.controllerNames=Object.keys(this.controllers)}static type(){return\\\\\\\"meshPhysicalBuilder\\\\\\\"}usedAssembler(){return jn.GL_MESH_PHYSICAL}_create_assembler_controller(){return li.assemblersRegister.assembler(this,this.usedAssembler())}initializeNode(){this.params.onParamsCreated(\\\\\\\"init controllers\\\\\\\",(()=>{for(let t of this.controllerNames)this.controllers[t].initializeNode()}))}createMaterial(){const t=super.createMaterial();return t.isMeshStandardMaterial=!0,t.isMeshPhysicalMaterial=!0,t}async cook(){for(let t of this.controllerNames)this.controllers[t].update();rB.update(this),hB.update(this),YB.update(this),this.compileIfRequired(),this.setMaterial(this.material)}}const ek={directParams:!0};class nk extends(vB(UB(QD(dB(Vz(fz(IB(Uz(QB(vz(uz(SB(MB(TB(VB(fB(uB(ua)))))))))))))))))){}const ik=new nk;class sk extends $D{constructor(){super(...arguments),this.paramsConfig=ik,this.controllers={advancedCommon:new tB(this),alphaMap:new EB(this,ek),aoMap:new CB(this,ek),bumpMap:new dz(this,ek),displacementMap:new yz(this,ek),emissiveMap:new tz(this,ek),envMap:new Gz(this,ek),lightMap:new FB(this,ek),map:new AB(this,ek),metalnessRoughnessMap:new Hz(this,ek),normalMap:new gz(this,ek)},this.controllerNames=Object.keys(this.controllers)}static type(){return\\\\\\\"meshStandard\\\\\\\"}createMaterial(){return new ws.a({vertexColors:!1,side:w.H,color:16777215,opacity:1,metalness:1,roughness:0})}initializeNode(){this.params.onParamsCreated(\\\\\\\"init controllers\\\\\\\",(()=>{for(let t of this.controllerNames)this.controllers[t].initializeNode()}))}async cook(){for(let t of this.controllerNames)this.controllers[t].update();gB.update(this),yB.update(this),GB.update(this),this.setMaterial(this.material)}}const rk={uniforms:!0};class ok extends(rz(cB(XB(QD(aB(dB(Vz(fz(IB(Uz(QB(vz(uz(SB(MB(TB(VB(sB(uB(ua)))))))))))))))))))){}const ak=new ok;class lk extends lB{constructor(){super(...arguments),this.paramsConfig=ak,this.controllers={advancedCommon:new tB(this),alphaMap:new EB(this,rk),aoMap:new CB(this,rk),bumpMap:new dz(this,rk),displacementMap:new yz(this,rk),emissiveMap:new tz(this,rk),envMap:new Gz(this,rk),lightMap:new FB(this,rk),map:new AB(this,rk),metalnessRoughnessMap:new Hz(this,rk),normalMap:new gz(this,rk),PCSS:new oz(this)},this.controllerNames=Object.keys(this.controllers)}static type(){return\\\\\\\"meshStandardBuilder\\\\\\\"}usedAssembler(){return jn.GL_MESH_STANDARD}_create_assembler_controller(){return li.assemblersRegister.assembler(this,this.usedAssembler())}initializeNode(){this.params.onParamsCreated(\\\\\\\"init controllers\\\\\\\",(()=>{for(let t of this.controllerNames)this.controllers[t].initializeNode()}))}async cook(){for(let t of this.controllerNames)this.controllers[t].update();rB.update(this),hB.update(this),YB.update(this),this.compileIfRequired(),this.setMaterial(this.material)}}const ck=U.meshphong_frag.slice(0,U.meshphong_frag.indexOf(\\\\\\\"void main() {\\\\\\\")),hk=U.meshphong_frag.slice(U.meshphong_frag.indexOf(\\\\\\\"void main() {\\\\\\\")),uk={uniforms:I.merge([H.phong.uniforms,{thicknessMap:{value:null},thicknessColor:{value:new D.a(16777215)},thicknessDistortion:{value:.1},thicknessAmbient:{value:0},thicknessAttenuation:{value:.1},thicknessPower:{value:2},thicknessScale:{value:10}}]),vertexShader:[\\\\\\\"#define USE_UV\\\\\\\",U.meshphong_vert].join(\\\\\\\"\\\\n\\\\\\\"),fragmentShader:[\\\\\\\"#define USE_UV\\\\\\\",\\\\\\\"#define SUBSURFACE\\\\\\\",ck,\\\\\\\"uniform sampler2D thicknessMap;\\\\\\\",\\\\\\\"uniform float thicknessPower;\\\\\\\",\\\\\\\"uniform float thicknessScale;\\\\\\\",\\\\\\\"uniform float thicknessDistortion;\\\\\\\",\\\\\\\"uniform float thicknessAmbient;\\\\\\\",\\\\\\\"uniform float thicknessAttenuation;\\\\\\\",\\\\\\\"uniform vec3 thicknessColor;\\\\\\\",\\\\\\\"void RE_Direct_Scattering(const in IncidentLight directLight, const in vec2 uv, const in GeometricContext geometry, inout ReflectedLight reflectedLight) {\\\\\\\",\\\\\\\"\\\\tvec3 thickness = thicknessColor * texture2D(thicknessMap, uv).r;\\\\\\\",\\\\\\\"\\\\tvec3 scatteringHalf = normalize(directLight.direction + (geometry.normal * thicknessDistortion));\\\\\\\",\\\\\\\"\\\\tfloat scatteringDot = pow(saturate(dot(geometry.viewDir, -scatteringHalf)), thicknessPower) * thicknessScale;\\\\\\\",\\\\\\\"\\\\tvec3 scatteringIllu = (scatteringDot + thicknessAmbient) * thickness;\\\\\\\",\\\\\\\"\\\\treflectedLight.directDiffuse += scatteringIllu * thicknessAttenuation * directLight.color;\\\\\\\",\\\\\\\"}\\\\\\\",hk.replace(\\\\\\\"#include \\\\\\\",(dk=U.lights_fragment_begin,pk=\\\\\\\"RE_Direct( directLight, geometry, material, reflectedLight );\\\\\\\",_k=[\\\\\\\"RE_Direct( directLight, geometry, material, reflectedLight );\\\\\\\",\\\\\\\"#if defined( SUBSURFACE ) && defined( USE_UV )\\\\\\\",\\\\\\\" RE_Direct_Scattering(directLight, vUv, geometry, reflectedLight);\\\\\\\",\\\\\\\"#endif\\\\\\\"].join(\\\\\\\"\\\\n\\\\\\\"),dk.split(pk).join(_k)))].join(\\\\\\\"\\\\n\\\\\\\")};var dk,pk,_k;function mk(t){return{cook:!1,callback:(e,n)=>{xk.PARAM_CALLBACK_update_uniformColor(e,n,t)}}}function fk(t){return{cook:!1,callback:(e,n)=>{xk.PARAM_CALLBACK_update_uniformN(e,n,t)}}}const gk={uniforms:!0};class vk extends(vB(XB(QD(dB(MB(TB(VB(function(t){return class extends t{constructor(){var t;super(...arguments),this.diffuse=ha.COLOR([1,1,1],{...mk(\\\\\\\"diffuse\\\\\\\")}),this.shininess=ha.FLOAT(1,{range:[0,1e3]}),this.thicknessMap=ha.NODE_PATH(vi.EMPTY,{nodeSelection:{context:ts.COP},...(t=\\\\\\\"thicknessMap\\\\\\\",{cook:!1,callback:(e,n)=>{xk.PARAM_CALLBACK_update_uniformTexture(e,n,t)}})}),this.thicknessColor=ha.COLOR([.5,.3,0],{...mk(\\\\\\\"thicknessColor\\\\\\\")}),this.thicknessDistortion=ha.FLOAT(.1,{...fk(\\\\\\\"thicknessDistortion\\\\\\\")}),this.thicknessAmbient=ha.FLOAT(.4,{...fk(\\\\\\\"thicknessAmbient\\\\\\\")}),this.thicknessAttenuation=ha.FLOAT(.8,{...fk(\\\\\\\"thicknessAttenuation\\\\\\\")}),this.thicknessPower=ha.FLOAT(2,{range:[0,10],...fk(\\\\\\\"thicknessPower\\\\\\\")}),this.thicknessScale=ha.FLOAT(16,{range:[0,100],...fk(\\\\\\\"thicknessScale\\\\\\\")})}}}(uB(ua)))))))))){}const yk=new vk;class xk extends $D{constructor(){super(...arguments),this.paramsConfig=yk,this.controllers={advancedCommon:new tB(this),alphaMap:new EB(this,gk),map:new AB(this,gk)},this.controllerNames=Object.keys(this.controllers)}static type(){return\\\\\\\"meshSubsurfaceScattering\\\\\\\"}createMaterial(){const t=I.clone(uk.uniforms),e=new F({uniforms:t,vertexShader:uk.vertexShader,fragmentShader:uk.fragmentShader,lights:!0});return e.extensions.derivatives=!0,e}initializeNode(){this.params.onParamsCreated(\\\\\\\"init controllers\\\\\\\",(()=>{for(let t of this.controllerNames)this.controllers[t].initializeNode()}))}async cook(){for(let t of this.controllerNames)this.controllers[t].update();yB.update(this),YB.update(this),this.update_map(this.p.thicknessMap,\\\\\\\"thicknessMap\\\\\\\"),this.material.uniforms.diffuse.value.copy(this.pv.diffuse),this.material.uniforms.shininess.value=this.pv.shininess,this.material.uniforms.thicknessColor.value.copy(this.pv.thicknessColor),this.material.uniforms.thicknessDistortion.value=this.pv.thicknessDistortion,this.material.uniforms.thicknessAmbient.value=this.pv.thicknessAmbient,this.material.uniforms.thicknessAttenuation.value=this.pv.thicknessAttenuation,this.material.uniforms.thicknessPower.value=this.pv.thicknessPower,this.material.uniforms.thicknessScale.value=this.pv.thicknessScale,this.setMaterial(this.material)}static PARAM_CALLBACK_update_uniformN(t,e,n){t.material.uniforms[n].value=e.value}static PARAM_CALLBACK_update_uniformColor(t,e,n){e.parent_param&&t.material.uniforms[n].value.copy(e.parent_param.value)}static PARAM_CALLBACK_update_uniformTexture(t,e,n){t.update_map(e,n)}async update_map(t,e){const n=t.value.nodeWithContext(ts.COP);n||(this.material.uniforms[e].value=null);const i=n,s=await i.compute();this.material.uniforms[e].value=s.texture()}}function bk(t){return class extends t{constructor(){super(...arguments),this.useGradientMap=ha.BOOLEAN(0,xB(wk)),this.gradientMap=ha.NODE_PATH(vi.EMPTY,bB(wk,\\\\\\\"useGradientMap\\\\\\\"))}}}O.a;bk(ua);class wk extends wB{constructor(t,e){super(t,e),this.node=t}initializeNode(){this.add_hooks(this.node.p.useGradientMap,this.node.p.gradientMap)}async update(){this._update(this.node.material,\\\\\\\"gradientMap\\\\\\\",this.node.p.useGradientMap,this.node.p.gradientMap)}static async update(t){t.controllers.gradientMap.update()}}const Tk={directParams:!0};class Ak extends(vB(UB(QD(dB(fz(IB(bk(QB(vz(uz(SB(MB(TB(VB(fB(uB(ua))))))))))))))))){}const Mk=new Ak;class Ek extends $D{constructor(){super(...arguments),this.paramsConfig=Mk,this.controllers={advancedCommon:new tB(this),alphaMap:new EB(this,Tk),aoMap:new CB(this,Tk),bumpMap:new dz(this,Tk),displacementMap:new yz(this,Tk),emissiveMap:new tz(this,Tk),gradientMap:new wk(this,Tk),lightMap:new FB(this,Tk),map:new AB(this,Tk),normalMap:new gz(this,Tk)},this.controllerNames=Object.keys(this.controllers)}static type(){return\\\\\\\"meshToon\\\\\\\"}createMaterial(){return new Xf({vertexColors:!1,side:w.H,color:16777215,opacity:1})}initializeNode(){this.params.onParamsCreated(\\\\\\\"init controllers\\\\\\\",(()=>{for(let t of this.controllerNames)this.controllers[t].initializeNode()}))}async cook(){for(let t of this.controllerNames)this.controllers[t].update();gB.update(this),yB.update(this),GB.update(this),this.setMaterial(this.material)}}const Sk={directParams:!0};class Ck extends(cB(QD(dB(MB(TB(VB(fB(function(t){return class extends t{constructor(){super(...arguments),this.size=ha.FLOAT(1),this.sizeAttenuation=ha.BOOLEAN(1)}}}(uB(ua)))))))))){}const Nk=new Ck;class Lk extends $D{constructor(){super(...arguments),this.paramsConfig=Nk,this.controllers={advancedCommon:new tB(this),alphaMap:new EB(this,Sk),map:new AB(this,Sk)},this.controllerNames=Object.keys(this.controllers)}static type(){return\\\\\\\"points\\\\\\\"}createMaterial(){return new bs.a({vertexColors:!1,side:w.H,color:16777215,opacity:1})}initializeNode(){this.params.onParamsCreated(\\\\\\\"init controllers\\\\\\\",(()=>{for(let t of this.controllerNames)this.controllers[t].initializeNode()}))}async cook(){for(let t of this.controllerNames)this.controllers[t].update();gB.update(this),hB.update(this),this.material.size=this.pv.size,this.material.sizeAttenuation=this.pv.sizeAttenuation,this.setMaterial(this.material)}}class Ok extends(cB(QD(aB(dB(sB(uB(ua))))))){}const Pk=new Ok;class Rk extends lB{constructor(){super(...arguments),this.paramsConfig=Pk,this.controllers={advancedCommon:new tB(this)},this.controllerNames=Object.keys(this.controllers)}static type(){return\\\\\\\"pointsBuilder\\\\\\\"}usedAssembler(){return jn.GL_POINTS}_create_assembler_controller(){return li.assemblersRegister.assembler(this,this.usedAssembler())}initializeNode(){this.params.onParamsCreated(\\\\\\\"init controllers\\\\\\\",(()=>{for(let t of this.controllerNames)this.controllers[t].initializeNode()}))}async cook(){for(let t of this.controllerNames)this.controllers[t].update();rB.update(this),hB.update(this),this.compileIfRequired(),this.setMaterial(this.material)}}class Ik extends(QD(fB(ua))){}const Fk=new Ik;class Dk extends $D{constructor(){super(...arguments),this.paramsConfig=Fk,this.controllers={advancedCommon:new tB(this)},this.controllerNames=Object.keys(this.controllers)}static type(){return\\\\\\\"shadow\\\\\\\"}createMaterial(){return new Hf({vertexColors:!1,side:w.H,color:16777215,opacity:1})}initializeNode(){this.params.onParamsCreated(\\\\\\\"init controllers\\\\\\\",(()=>{for(let t of this.controllerNames)this.controllers[t].initializeNode()}))}async cook(){for(let t of this.controllerNames)this.controllers[t].update();gB.update(this),this.setMaterial(this.material)}}class Bk extends B.a{constructor(){const t=Bk.SkyShader,e=new F({name:\\\\\\\"SkyShader\\\\\\\",fragmentShader:t.fragmentShader,vertexShader:t.vertexShader,uniforms:I.clone(t.uniforms),side:w.i,depthWrite:!1});super(new N(1,1,1),e)}}Bk.prototype.isSky=!0,Bk.SkyShader={uniforms:{turbidity:{value:2},rayleigh:{value:1},mieCoefficient:{value:.005},mieDirectionalG:{value:.8},sunPosition:{value:new p.a},up:{value:new p.a(0,1,0)}},vertexShader:\\\\\\\"\\\\n\\\\t\\\\tuniform vec3 sunPosition;\\\\n\\\\t\\\\tuniform float rayleigh;\\\\n\\\\t\\\\tuniform float turbidity;\\\\n\\\\t\\\\tuniform float mieCoefficient;\\\\n\\\\t\\\\tuniform vec3 up;\\\\n\\\\n\\\\t\\\\tvarying vec3 vWorldPosition;\\\\n\\\\t\\\\tvarying vec3 vSunDirection;\\\\n\\\\t\\\\tvarying float vSunfade;\\\\n\\\\t\\\\tvarying vec3 vBetaR;\\\\n\\\\t\\\\tvarying vec3 vBetaM;\\\\n\\\\t\\\\tvarying float vSunE;\\\\n\\\\n\\\\t\\\\t// constants for atmospheric scattering\\\\n\\\\t\\\\tconst float e = 2.71828182845904523536028747135266249775724709369995957;\\\\n\\\\t\\\\tconst float pi = 3.141592653589793238462643383279502884197169;\\\\n\\\\n\\\\t\\\\t// wavelength of used primaries, according to preetham\\\\n\\\\t\\\\tconst vec3 lambda = vec3( 680E-9, 550E-9, 450E-9 );\\\\n\\\\t\\\\t// this pre-calcuation replaces older TotalRayleigh(vec3 lambda) function:\\\\n\\\\t\\\\t// (8.0 * pow(pi, 3.0) * pow(pow(n, 2.0) - 1.0, 2.0) * (6.0 + 3.0 * pn)) / (3.0 * N * pow(lambda, vec3(4.0)) * (6.0 - 7.0 * pn))\\\\n\\\\t\\\\tconst vec3 totalRayleigh = vec3( 5.804542996261093E-6, 1.3562911419845635E-5, 3.0265902468824876E-5 );\\\\n\\\\n\\\\t\\\\t// mie stuff\\\\n\\\\t\\\\t// K coefficient for the primaries\\\\n\\\\t\\\\tconst float v = 4.0;\\\\n\\\\t\\\\tconst vec3 K = vec3( 0.686, 0.678, 0.666 );\\\\n\\\\t\\\\t// MieConst = pi * pow( ( 2.0 * pi ) / lambda, vec3( v - 2.0 ) ) * K\\\\n\\\\t\\\\tconst vec3 MieConst = vec3( 1.8399918514433978E14, 2.7798023919660528E14, 4.0790479543861094E14 );\\\\n\\\\n\\\\t\\\\t// earth shadow hack\\\\n\\\\t\\\\t// cutoffAngle = pi / 1.95;\\\\n\\\\t\\\\tconst float cutoffAngle = 1.6110731556870734;\\\\n\\\\t\\\\tconst float steepness = 1.5;\\\\n\\\\t\\\\tconst float EE = 1000.0;\\\\n\\\\n\\\\t\\\\tfloat sunIntensity( float zenithAngleCos ) {\\\\n\\\\t\\\\t\\\\tzenithAngleCos = clamp( zenithAngleCos, -1.0, 1.0 );\\\\n\\\\t\\\\t\\\\treturn EE * max( 0.0, 1.0 - pow( e, -( ( cutoffAngle - acos( zenithAngleCos ) ) / steepness ) ) );\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\tvec3 totalMie( float T ) {\\\\n\\\\t\\\\t\\\\tfloat c = ( 0.2 * T ) * 10E-18;\\\\n\\\\t\\\\t\\\\treturn 0.434 * c * MieConst;\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\tvec4 worldPosition = modelMatrix * vec4( position, 1.0 );\\\\n\\\\t\\\\t\\\\tvWorldPosition = worldPosition.xyz;\\\\n\\\\n\\\\t\\\\t\\\\tgl_Position = projectionMatrix * modelViewMatrix * vec4( position, 1.0 );\\\\n\\\\t\\\\t\\\\tgl_Position.z = gl_Position.w; // set z to camera.far\\\\n\\\\n\\\\t\\\\t\\\\tvSunDirection = normalize( sunPosition );\\\\n\\\\n\\\\t\\\\t\\\\tvSunE = sunIntensity( dot( vSunDirection, up ) );\\\\n\\\\n\\\\t\\\\t\\\\tvSunfade = 1.0 - clamp( 1.0 - exp( ( sunPosition.y / 450000.0 ) ), 0.0, 1.0 );\\\\n\\\\n\\\\t\\\\t\\\\tfloat rayleighCoefficient = rayleigh - ( 1.0 * ( 1.0 - vSunfade ) );\\\\n\\\\n\\\\t\\\\t\\\\t// extinction (absorbtion + out scattering)\\\\n\\\\t\\\\t\\\\t// rayleigh coefficients\\\\n\\\\t\\\\t\\\\tvBetaR = totalRayleigh * rayleighCoefficient;\\\\n\\\\n\\\\t\\\\t\\\\t// mie coefficients\\\\n\\\\t\\\\t\\\\tvBetaM = totalMie( turbidity ) * mieCoefficient;\\\\n\\\\n\\\\t\\\\t}\\\\\\\",fragmentShader:\\\\\\\"\\\\n\\\\t\\\\tvarying vec3 vWorldPosition;\\\\n\\\\t\\\\tvarying vec3 vSunDirection;\\\\n\\\\t\\\\tvarying float vSunfade;\\\\n\\\\t\\\\tvarying vec3 vBetaR;\\\\n\\\\t\\\\tvarying vec3 vBetaM;\\\\n\\\\t\\\\tvarying float vSunE;\\\\n\\\\n\\\\t\\\\tuniform float mieDirectionalG;\\\\n\\\\t\\\\tuniform vec3 up;\\\\n\\\\n\\\\t\\\\tconst vec3 cameraPos = vec3( 0.0, 0.0, 0.0 );\\\\n\\\\n\\\\t\\\\t// constants for atmospheric scattering\\\\n\\\\t\\\\tconst float pi = 3.141592653589793238462643383279502884197169;\\\\n\\\\n\\\\t\\\\tconst float n = 1.0003; // refractive index of air\\\\n\\\\t\\\\tconst float N = 2.545E25; // number of molecules per unit volume for air at 288.15K and 1013mb (sea level -45 celsius)\\\\n\\\\n\\\\t\\\\t// optical length at zenith for molecules\\\\n\\\\t\\\\tconst float rayleighZenithLength = 8.4E3;\\\\n\\\\t\\\\tconst float mieZenithLength = 1.25E3;\\\\n\\\\t\\\\t// 66 arc seconds -> degrees, and the cosine of that\\\\n\\\\t\\\\tconst float sunAngularDiameterCos = 0.999956676946448443553574619906976478926848692873900859324;\\\\n\\\\n\\\\t\\\\t// 3.0 / ( 16.0 * pi )\\\\n\\\\t\\\\tconst float THREE_OVER_SIXTEENPI = 0.05968310365946075;\\\\n\\\\t\\\\t// 1.0 / ( 4.0 * pi )\\\\n\\\\t\\\\tconst float ONE_OVER_FOURPI = 0.07957747154594767;\\\\n\\\\n\\\\t\\\\tfloat rayleighPhase( float cosTheta ) {\\\\n\\\\t\\\\t\\\\treturn THREE_OVER_SIXTEENPI * ( 1.0 + pow( cosTheta, 2.0 ) );\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\tfloat hgPhase( float cosTheta, float g ) {\\\\n\\\\t\\\\t\\\\tfloat g2 = pow( g, 2.0 );\\\\n\\\\t\\\\t\\\\tfloat inverse = 1.0 / pow( 1.0 - 2.0 * g * cosTheta + g2, 1.5 );\\\\n\\\\t\\\\t\\\\treturn ONE_OVER_FOURPI * ( ( 1.0 - g2 ) * inverse );\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\tvec3 direction = normalize( vWorldPosition - cameraPos );\\\\n\\\\n\\\\t\\\\t\\\\t// optical length\\\\n\\\\t\\\\t\\\\t// cutoff angle at 90 to avoid singularity in next formula.\\\\n\\\\t\\\\t\\\\tfloat zenithAngle = acos( max( 0.0, dot( up, direction ) ) );\\\\n\\\\t\\\\t\\\\tfloat inverse = 1.0 / ( cos( zenithAngle ) + 0.15 * pow( 93.885 - ( ( zenithAngle * 180.0 ) / pi ), -1.253 ) );\\\\n\\\\t\\\\t\\\\tfloat sR = rayleighZenithLength * inverse;\\\\n\\\\t\\\\t\\\\tfloat sM = mieZenithLength * inverse;\\\\n\\\\n\\\\t\\\\t\\\\t// combined extinction factor\\\\n\\\\t\\\\t\\\\tvec3 Fex = exp( -( vBetaR * sR + vBetaM * sM ) );\\\\n\\\\n\\\\t\\\\t\\\\t// in scattering\\\\n\\\\t\\\\t\\\\tfloat cosTheta = dot( direction, vSunDirection );\\\\n\\\\n\\\\t\\\\t\\\\tfloat rPhase = rayleighPhase( cosTheta * 0.5 + 0.5 );\\\\n\\\\t\\\\t\\\\tvec3 betaRTheta = vBetaR * rPhase;\\\\n\\\\n\\\\t\\\\t\\\\tfloat mPhase = hgPhase( cosTheta, mieDirectionalG );\\\\n\\\\t\\\\t\\\\tvec3 betaMTheta = vBetaM * mPhase;\\\\n\\\\n\\\\t\\\\t\\\\tvec3 Lin = pow( vSunE * ( ( betaRTheta + betaMTheta ) / ( vBetaR + vBetaM ) ) * ( 1.0 - Fex ), vec3( 1.5 ) );\\\\n\\\\t\\\\t\\\\tLin *= mix( vec3( 1.0 ), pow( vSunE * ( ( betaRTheta + betaMTheta ) / ( vBetaR + vBetaM ) ) * Fex, vec3( 1.0 / 2.0 ) ), clamp( pow( 1.0 - dot( up, vSunDirection ), 5.0 ), 0.0, 1.0 ) );\\\\n\\\\n\\\\t\\\\t\\\\t// nightsky\\\\n\\\\t\\\\t\\\\tfloat theta = acos( direction.y ); // elevation --\\\\x3e y-axis, [-pi/2, pi/2]\\\\n\\\\t\\\\t\\\\tfloat phi = atan( direction.z, direction.x ); // azimuth --\\\\x3e x-axis [-pi/2, pi/2]\\\\n\\\\t\\\\t\\\\tvec2 uv = vec2( phi, theta ) / vec2( 2.0 * pi, pi ) + vec2( 0.5, 0.0 );\\\\n\\\\t\\\\t\\\\tvec3 L0 = vec3( 0.1 ) * Fex;\\\\n\\\\n\\\\t\\\\t\\\\t// composition + solar disc\\\\n\\\\t\\\\t\\\\tfloat sundisk = smoothstep( sunAngularDiameterCos, sunAngularDiameterCos + 0.00002, cosTheta );\\\\n\\\\t\\\\t\\\\tL0 += ( vSunE * 19000.0 * Fex ) * sundisk;\\\\n\\\\n\\\\t\\\\t\\\\tvec3 texColor = ( Lin + L0 ) * 0.04 + vec3( 0.0, 0.0003, 0.00075 );\\\\n\\\\n\\\\t\\\\t\\\\tvec3 retColor = pow( texColor, vec3( 1.0 / ( 1.2 + ( 1.2 * vSunfade ) ) ) );\\\\n\\\\n\\\\t\\\\t\\\\tgl_FragColor = vec4( retColor, 1.0 );\\\\n\\\\n\\\\t\\\\t\\\\t#include \\\\n\\\\t\\\\t\\\\t#include \\\\n\\\\n\\\\t\\\\t}\\\\\\\"};const zk=new class extends ua{constructor(){super(...arguments),this.turbidity=ha.FLOAT(2,{range:[0,20]}),this.rayleigh=ha.FLOAT(1,{range:[0,4]}),this.mieCoefficient=ha.FLOAT(.005),this.mieDirectional=ha.FLOAT(.8),this.inclination=ha.FLOAT(.5),this.azimuth=ha.FLOAT(.25),this.up=ha.VECTOR3([0,1,0])}};class kk extends $D{constructor(){super(...arguments),this.paramsConfig=zk}static type(){return\\\\\\\"sky\\\\\\\"}createMaterial(){const t=(new Bk).material;return t.depthWrite=!0,t}async cook(){const t=this.material.uniforms;t.turbidity.value=this.pv.turbidity,t.rayleigh.value=this.pv.rayleigh,t.mieCoefficient.value=this.pv.mieCoefficient,t.mieDirectionalG.value=this.pv.mieDirectional,t.up.value.copy(this.pv.up);const e=Math.PI*(this.pv.inclination-.5),n=2*Math.PI*(this.pv.azimuth-.5);t.sunPosition.value.x=Math.cos(n),t.sunPosition.value.y=Math.sin(n)*Math.sin(e),t.sunPosition.value.z=Math.sin(n)*Math.cos(e),this.setMaterial(this.material)}}var Uk=\\\\\\\"precision highp float;\\\\nprecision highp int;\\\\n\\\\nvarying vec3 vPw;\\\\n\\\\n#include \\\\n\\\\nvoid main()\\\\t{\\\\n\\\\n\\\\t// start builder body code\\\\n\\\\n\\\\tvPw = position;\\\\n\\\\tgl_Position = projectionMatrix * modelViewMatrix * vec4( position, 1.0 );\\\\n\\\\n}\\\\\\\",Gk=\\\\\\\"precision highp float;\\\\nprecision highp int;\\\\n\\\\n#include \\\\n\\\\n#define DIR_LIGHTS_COUNT 1\\\\n#define MAX_STEPS_COUNT 4096\\\\n\\\\nuniform vec3 u_Color;\\\\nuniform float u_VolumeDensity;\\\\nuniform float u_ShadowDensity;\\\\nuniform float u_StepSize;\\\\nuniform vec3 u_BoundingBoxMin;\\\\nuniform vec3 u_BoundingBoxMax;\\\\n//const int u_PointsCount = 3;\\\\n//uniform vec3 u_Points[3];\\\\nuniform sampler2D u_Map;\\\\n\\\\n//const int u_DirectionalLightsCount = 1;\\\\nuniform vec3 u_DirectionalLightDirection; //[DIR_LIGHTS_COUNT];\\\\n\\\\nvarying vec3 vPw;\\\\n// varying vec3 vN;\\\\n// varying vec2 vUV;\\\\n//varying vec3 vPCameraSpace;\\\\n// varying vec4 vCd;\\\\n\\\\nvec3 normalize_in_bbox(vec3 point){\\\\n\\\\n\\\\tvec3 min = u_BoundingBoxMin;\\\\n\\\\tvec3 max = u_BoundingBoxMax;\\\\n\\\\n\\\\treturn vec3(\\\\n\\\\t\\\\t(point.x - min.x) / (max.x - min.x),\\\\n\\\\t\\\\t(point.y - min.y) / (max.y - min.y),\\\\n\\\\t\\\\t(point.z - min.z) / (max.z - min.z)\\\\n\\\\t);\\\\n}\\\\n\\\\nbool is_inside_bbox(vec3 Pw){\\\\n\\\\n\\\\tvec3 min = u_BoundingBoxMin;\\\\n\\\\tvec3 max = u_BoundingBoxMax;\\\\n\\\\n\\\\treturn (\\\\n\\\\t\\\\tPw.x > min.x &&\\\\n\\\\t\\\\tPw.y > min.y &&\\\\n\\\\t\\\\tPw.z > min.z &&\\\\n\\\\n\\\\t\\\\tPw.x < max.x &&\\\\n\\\\t\\\\tPw.y < max.y &&\\\\n\\\\t\\\\tPw.z < max.z\\\\n\\\\t\\\\t);\\\\n}\\\\n\\\\nfloat density_to_opacity(float density, float step_size){\\\\n\\\\tfloat curent_density = density;\\\\n\\\\tcurent_density = max(0.0, curent_density);\\\\n\\\\n\\\\tfloat opacity = (1.0-exp(-curent_density * step_size));\\\\n\\\\treturn max(opacity,0.0);\\\\n}\\\\n\\\\nfloat density_function(vec3 position_for_step){\\\\n\\\\tfloat density = 1.0;\\\\n\\\\t// start builder body code\\\\n\\\\n\\\\treturn density;\\\\n}\\\\n\\\\nvec4 raymarch_light(vec3 ray_dir, vec3 start_pos){\\\\n\\\\n\\\\tfloat step_size = u_StepSize;\\\\n\\\\tvec3 step_vector = ray_dir * step_size;\\\\n\\\\n\\\\tvec3 current_pos = start_pos + step_vector*rand(start_pos.x*ray_dir.xy);\\\\n\\\\tfloat opacity = 0.0;\\\\n\\\\tfor(int i=0; i= 0.99){ break; }\\\\n\\\\n\\\\t\\\\tif( is_inside_bbox(current_pos) ){\\\\n\\\\n\\\\t\\\\t\\\\tfloat density = density_function(current_pos) * u_ShadowDensity;\\\\n\\\\t\\\\t\\\\topacity += density_to_opacity(density, step_size);\\\\n\\\\t\\\\t\\\\tcurrent_pos += step_vector;\\\\n\\\\n\\\\t\\\\t}else{\\\\n\\\\t\\\\t\\\\tbreak;\\\\n\\\\t\\\\t}\\\\n\\\\t}\\\\n\\\\n\\\\tvec3 light_color = vec3(1.0, 1.0, 1.0) * u_Color;\\\\n\\\\tlight_color *= (1.0-opacity);\\\\n\\\\treturn vec4(light_color, 1.0-opacity);\\\\n}\\\\n\\\\nvec4 raymarch_bbox(vec3 start_pos, vec3 ray_dir){\\\\n\\\\n\\\\tfloat step_size = u_StepSize;\\\\n\\\\tvec3 step_vector = ray_dir * step_size;\\\\n\\\\n\\\\tvec3 current_pos = start_pos - step_vector*rand(ray_dir.xz);\\\\n\\\\tfloat opacity = 0.0;\\\\n\\\\tvec3 color = vec3(0.0, 0.0, 0.0);\\\\n\\\\tfloat steps_count = 0.0;\\\\n\\\\tbool was_inside_bbox = false;\\\\n\\\\tfor(int i=0; i= 0.99){ break; }\\\\n\\\\n\\\\t\\\\tif( i==0 || is_inside_bbox(current_pos) ){\\\\n\\\\t\\\\t\\\\twas_inside_bbox = true;\\\\n\\\\n\\\\t\\\\t\\\\tfloat density = density_function(current_pos) * u_VolumeDensity;\\\\n\\\\t\\\\t\\\\topacity += density_to_opacity(density, step_size);\\\\n\\\\n\\\\t\\\\t\\\\tvec4 light_color = vec4(0.0,0.0,0.0,1.0); //vec4(1.0,1.0,1.0,1.0);\\\\n\\\\t\\\\t\\\\t// vec3 directional_light_direction;\\\\n\\\\t\\\\t\\\\t// for ( int l = 0; l < DIR_LIGHTS_COUNT; l++ ) {\\\\n\\\\t\\\\t\\\\t// directional_light_direction = u_DirectionalLightsDirection[ l ];\\\\n\\\\t\\\\t\\\\tlight_color += raymarch_light(-u_DirectionalLightDirection, current_pos);\\\\n\\\\t\\\\t\\\\t// }\\\\n\\\\t\\\\t\\\\tfloat blend = 1.0-opacity;\\\\n\\\\t\\\\t\\\\tcolor = mix( color.xyz, light_color.xyz, vec3(blend, blend, blend) );\\\\n\\\\t\\\\t\\\\tsteps_count += 1.0;\\\\n\\\\n\\\\t\\\\t}else{\\\\n\\\\t\\\\t\\\\tif (was_inside_bbox) { break; }\\\\n\\\\t\\\\t}\\\\n\\\\t\\\\tcurrent_pos += step_vector;\\\\n\\\\t}\\\\n\\\\n\\\\treturn vec4(color, opacity);\\\\n\\\\t// steps_count = steps_count / 5.0;\\\\n\\\\t// return vec4(vec3(steps_count, steps_count, steps_count), 1.0);\\\\n}\\\\n\\\\nvoid main()\\\\t{\\\\n\\\\n\\\\tvec3 eye = normalize(vPw - cameraPosition);\\\\n\\\\t// we can start from the bbox, as we are front facing\\\\n\\\\tvec3 start_pos = vPw;\\\\n\\\\n\\\\tvec4 color = raymarch_bbox(start_pos, eye);\\\\n\\\\tgl_FragColor = color;\\\\n\\\\n}\\\\\\\";const Vk={u_Color:{value:new D.a(1,1,1)},u_VolumeDensity:{value:5},u_ShadowDensity:{value:2},u_StepSize:{value:.01},u_BoundingBoxMin:{value:new p.a(-1,-1,-1)},u_BoundingBoxMax:{value:new p.a(1,1,1)},u_DirectionalLightDirection:{value:new p.a(-1,-1,-1)}};function Hk(t){return class extends t{constructor(){super(...arguments),this.color=ha.COLOR([1,1,1]),this.stepSize=ha.FLOAT(.01),this.density=ha.FLOAT(1),this.shadowDensity=ha.FLOAT(1),this.lightDir=ha.VECTOR3([-1,-1,-1])}}}Hk(ua);class jk{constructor(t){this.node=t}static render_hook(t,e,n,i,s,r,o){if(o){this._object_bbox.setFromObject(o);const t=s;t.uniforms.u_BoundingBoxMin.value.copy(this._object_bbox.min),t.uniforms.u_BoundingBoxMax.value.copy(this._object_bbox.max)}}update_uniforms_from_params(){const t=this.node.material.uniforms;t.u_Color.value.copy(this.node.pv.color),t.u_StepSize.value=this.node.pv.stepSize,t.u_VolumeDensity.value=this.node.pv.density,t.u_ShadowDensity.value=this.node.pv.shadowDensity;const e=t.u_DirectionalLightDirection.value,n=this.node.pv.lightDir;e&&(e.x=n.x,e.y=n.y,e.z=n.z)}}jk._object_bbox=new Ry.a;class Wk extends(Hk(ua)){}const qk=new Wk;class Xk extends $D{constructor(){super(...arguments),this.paramsConfig=qk,this._volume_controller=new jk(this)}static type(){return\\\\\\\"volume\\\\\\\"}createMaterial(){const t=new F({vertexShader:Uk,fragmentShader:Gk,side:w.H,transparent:!0,depthTest:!0,uniforms:I.clone(Vk)});return yr.add_user_data_render_hook(t,jk.render_hook.bind(jk)),t}initializeNode(){}async cook(){this._volume_controller.update_uniforms_from_params(),this.setMaterial(this.material)}}class Yk extends(aB(Hk(ua))){}const $k=new Yk;class Jk extends lB{constructor(){super(...arguments),this.paramsConfig=$k,this._volume_controller=new jk(this)}static type(){return\\\\\\\"volumeBuilder\\\\\\\"}usedAssembler(){return jn.GL_VOLUME}_create_assembler_controller(){return li.assemblersRegister.assembler(this,this.usedAssembler())}initializeNode(){}async cook(){this._volume_controller.update_uniforms_from_params(),this.compileIfRequired(),this.setMaterial(this.material)}}class Zk extends aa{static context(){return ts.MAT}cook(){this.cookController.endCook()}}class Kk extends Zk{}class Qk extends Kk{constructor(){super(...arguments),this._children_controller_context=ts.ANIM}static type(){return es.ANIM}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}}class tU extends Kk{constructor(){super(...arguments),this._children_controller_context=ts.COP}static type(){return es.COP}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}}class eU extends Kk{constructor(){super(...arguments),this._children_controller_context=ts.EVENT}static type(){return es.EVENT}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}}class nU extends Kk{constructor(){super(...arguments),this._children_controller_context=ts.MAT}static type(){return es.MAT}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}}class iU extends Zk{constructor(){super(...arguments),this.paramsConfig=new ef,this.effectsComposerController=new nf(this),this.displayNodeController=new Fm(this,this.effectsComposerController.displayNodeControllerCallbacks()),this._children_controller_context=ts.POST}static type(){return es.POST}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}}class sU extends Kk{constructor(){super(...arguments),this._children_controller_context=ts.ROP}static type(){return es.ROP}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}}var rU=n(87);const oU=\\\\\\\"parent object\\\\\\\",aU=[oU,oU,oU,oU];var lU;!function(t){t[t.MANAGER=0]=\\\\\\\"MANAGER\\\\\\\",t[t.CAMERA=2]=\\\\\\\"CAMERA\\\\\\\",t[t.LIGHT=3]=\\\\\\\"LIGHT\\\\\\\"}(lU||(lU={}));class cU extends aa{constructor(){super(...arguments),this.renderOrder=lU.MANAGER,this._children_group=this._create_children_group(),this._attachableToHierarchy=!0,this._used_in_scene=!0}static context(){return ts.OBJ}static displayedInputNames(){return aU}_create_children_group(){const t=new Fn.a;return t.matrixAutoUpdate=!1,t}attachableToHierarchy(){return this._attachableToHierarchy}usedInScene(){return this._used_in_scene}addObjectToParent(t){this.attachableToHierarchy()&&t.add(this.object)}removeObjectFromParent(){if(this.attachableToHierarchy()){const t=this.object.parent;t&&t.remove(this.object)}}initializeBaseNode(){this._object=this._create_object_with_attributes(),this.nameController.add_post_set_fullPath_hook(this.set_object_name.bind(this)),this.set_object_name()}get children_group(){return this._children_group}get object(){return this._object}_create_object_with_attributes(){const t=this.createObject();return t.node=this,t.add(this._children_group),t}set_object_name(){this._object&&(this._object.name=this.path(),this._children_group.name=`${this.path()}:parented_outputs`)}createObject(){const t=new Q.a;return t.matrixAutoUpdate=!1,t}isDisplayNodeCooking(){if(this.displayNodeController){const t=this.displayNodeController.displayNode();if(t)return t.cookController.isCooking()}return!1}isDisplayed(){var t,e;return(null===(e=null===(t=this.flags)||void 0===t?void 0:t.display)||void 0===e?void 0:e.active())||!1}}class hU extends cU{constructor(){super(...arguments),this.flags=new Di(this),this.renderOrder=lU.LIGHT,this._color_with_intensity=new D.a(0),this._used_in_scene=!0,this._cook_main_without_inputs_when_dirty_bound=this._cook_main_without_inputs_when_dirty.bind(this)}get light(){return this._light}initializeBaseNode(){super.initializeBaseNode(),this._light=this.createLight(),this.object.add(this._light),this.flags.display.onUpdate((()=>{this._updateLightAttachment()})),this.dirtyController.addPostDirtyHook(\\\\\\\"_cook_main_without_inputs_when_dirty\\\\\\\",this._cook_main_without_inputs_when_dirty_bound)}async _cook_main_without_inputs_when_dirty(){await this.cookController.cookMainWithoutInputs()}set_object_name(){super.set_object_name(),this._light&&(this._light.name=`${this.path()}:light`)}_updateLightAttachment(){this.flags.display.active()?(this.object.add(this.light),this._cook_main_without_inputs_when_dirty()):this.object.remove(this.light)}cook(){this.updateLightParams(),this.updateShadowParams(),this.cookController.endCook()}updateLightParams(){}updateShadowParams(){}}const uU=new class extends ua{constructor(){super(...arguments),this.color=ha.COLOR([1,1,1],{conversion:lo.SRGB_TO_LINEAR}),this.intensity=ha.FLOAT(1)}};class dU extends hU{constructor(){super(...arguments),this.paramsConfig=uU}static type(){return\\\\\\\"ambientLight\\\\\\\"}createLight(){const t=new rU.a;return t.matrixAutoUpdate=!1,t}initializeNode(){this.io.inputs.setCount(0,1)}updateLightParams(){this.light.color=this.pv.color,this.light.intensity=this.pv.intensity}}class pU extends cv.a{constructor(t,e,n=10,i=10){super(t,e),this.type=\\\\\\\"RectAreaLight\\\\\\\",this.width=n,this.height=i}get power(){return this.intensity*this.width*this.height*Math.PI}set power(t){this.intensity=t/(this.width*this.height*Math.PI)}copy(t){return super.copy(t),this.width=t.width,this.height=t.height,this}toJSON(t){const e=super.toJSON(t);return e.object.width=this.width,e.object.height=this.height,e}}pU.prototype.isRectAreaLight=!0;var _U,mU=n(61);class fU{static init(){const 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Float32Array(t),i=new Float32Array(e);V.LTC_FLOAT_1=new vo.a(n,64,64,w.Ib,w.G,w.Yc,w.n,w.n,w.V,w.ob,1),V.LTC_FLOAT_2=new vo.a(i,64,64,w.Ib,w.G,w.Yc,w.n,w.n,w.V,w.ob,1);const s=new Uint16Array(t.length);t.forEach((function(t,e){s[e]=mU.a.toHalfFloat(t)}));const r=new Uint16Array(e.length);e.forEach((function(t,e){r[e]=mU.a.toHalfFloat(t)})),V.LTC_HALF_1=new vo.a(s,64,64,w.Ib,w.M,w.Yc,w.n,w.n,w.V,w.ob,1),V.LTC_HALF_2=new vo.a(r,64,64,w.Ib,w.M,w.Yc,w.n,w.n,w.V,w.ob,1)}}!function(t){t.OBJECTS=\\\\\\\"objects\\\\\\\",t.GEOMETRIES=\\\\\\\"geometries\\\\\\\"}(_U||(_U={}));const gU=[_U.GEOMETRIES,_U.OBJECTS];var vU;!function(t){t.XYZ=\\\\\\\"XYZ\\\\\\\",t.XZY=\\\\\\\"XZY\\\\\\\",t.YXZ=\\\\\\\"YXZ\\\\\\\",t.YZX=\\\\\\\"YZX\\\\\\\",t.ZYX=\\\\\\\"ZYX\\\\\\\",t.ZXY=\\\\\\\"ZXY\\\\\\\"}(vU||(vU={}));const yU=[vU.XYZ,vU.XZY,vU.YXZ,vU.YZX,vU.ZXY,vU.ZYX],xU=vU.XYZ;class bU{constructor(){this._translation_matrix=new A.a,this._translation_matrix_q=new hh.a,this._translation_matrix_s=new 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setParamsFromObject(t,e){t.position.toArray(this.set_params_from_object_position_array),t.rotation.toArray(this.set_params_from_object_rotation_array),this.set_params_from_object_rotation_deg.fromArray(this.set_params_from_object_rotation_array),this.set_params_from_object_rotation_deg.multiplyScalar(180/Math.PI),this.set_params_from_object_rotation_deg.toArray(this.set_params_from_object_rotation_array),e.scene().batchUpdates((()=>{e.params.set_vector3(\\\\\\\"t\\\\\\\",this.set_params_from_object_position_array),e.params.set_vector3(\\\\\\\"r\\\\\\\",this.set_params_from_object_rotation_array)}))}translationMatrix(t){return this._translation_matrix.compose(t,this._translation_matrix_q,this._translation_matrix_s),this._translation_matrix}matrix(t,e,n,i,s){return this._matrix_euler.set(Object(On.e)(e.x),Object(On.e)(e.y),Object(On.e)(e.z),s),this._matrix_q.setFromEuler(this._matrix_euler),this._matrix_s.copy(n).multiplyScalar(i),this._matrix.compose(t,this._matrix_q,this._matrix_s),this._matrix}rotateGeometry(t,e,n){this._rotate_geometry_vec_dest.copy(n),this._rotate_geometry_vec_dest.normalize(),this._rotate_geometry_q.setFromUnitVectors(e,this._rotate_geometry_vec_dest),this._rotate_geometry_m.makeRotationFromQuaternion(this._rotate_geometry_q),t.applyMatrix4(this._rotate_geometry_m)}static decomposeMatrix(t){t.matrix.decompose(t.position,t.quaternion,t.scale)}}function wU(t,e){const n=(null==e?void 0:e.matrixAutoUpdate)||!1;return class extends t{constructor(){super(...arguments),this.transform=ha.FOLDER(),this.keepPosWhenParenting=ha.BOOLEAN(0),this.rotationOrder=ha.INTEGER(yU.indexOf(vU.XYZ),{menu:{entries:yU.map(((t,e)=>({name:t,value:e})))}}),this.t=ha.VECTOR3([0,0,0]),this.r=ha.VECTOR3([0,0,0]),this.s=ha.VECTOR3([1,1,1]),this.scale=ha.FLOAT(1),this.matrixAutoUpdate=ha.BOOLEAN(n?1:0),this.updateTransformFromObject=ha.BUTTON(null,{callback:t=>{AU.PARAM_CALLBACK_update_transform_from_object(t)}})}}}bU.set_params_from_matrix_position=new p.a,bU.set_params_from_matrix_quaternion=new hh.a,bU.set_params_from_matrix_scale=new p.a,bU.set_params_from_matrix_euler=new ny.a,bU.set_params_from_matrix_rotation=new p.a,bU.set_params_from_matrix_t=[0,0,0],bU.set_params_from_matrix_r=[0,0,0],bU.set_params_from_matrix_s=[0,0,0],bU.set_params_from_object_position_array=[0,0,0],bU.set_params_from_object_rotation_deg=new p.a,bU.set_params_from_object_rotation_array=[0,0,0];wU(ua);const TU=\\\\\\\"_cook_main_without_inputs_when_dirty\\\\\\\";class AU{constructor(t){this.node=t,this._cook_main_without_inputs_when_dirty_bound=this._cook_main_without_inputs_when_dirty.bind(this),this._core_transform=new bU,this._keep_pos_when_parenting_m_object=new A.a,this._keep_pos_when_parenting_m_new_parent_inv=new A.a}initializeNode(){this.node.dirtyController.hasHook(TU)||this.node.dirtyController.addPostDirtyHook(TU,this._cook_main_without_inputs_when_dirty_bound)}async _cook_main_without_inputs_when_dirty(){await this.node.cookController.cookMainWithoutInputs()}update(){this.update_transform_with_matrix();this.node.object.matrixAutoUpdate=this.node.pv.matrixAutoUpdate}update_transform_with_matrix(t){const e=this.node.object;null==t||t.equals(e.matrix)?this._update_matrix_from_params_with_core_transform():(e.matrix.copy(t),e.dispatchEvent({type:\\\\\\\"change\\\\\\\"}))}_update_matrix_from_params_with_core_transform(){const t=this.node.object;let e=t.matrixAutoUpdate;e&&(t.matrixAutoUpdate=!1);const n=this._core_transform.matrix(this.node.pv.t,this.node.pv.r,this.node.pv.s,this.node.pv.scale,yU[this.node.pv.rotationOrder]);t.matrix.identity(),t.applyMatrix4(n),this._apply_look_at(),t.updateMatrix(),e&&(t.matrixAutoUpdate=!0),t.dispatchEvent({type:\\\\\\\"change\\\\\\\"})}_apply_look_at(){}set_params_from_matrix(t,e={}){bU.setParamsFromMatrix(t,this.node,e)}static update_node_transform_params_if_required(t,e){t.transformController.update_node_transform_params_if_required(e)}update_node_transform_params_if_required(t){if(!this.node.pv.keepPosWhenParenting)return;if(!this.node.scene().loadingController.loaded())return;if(t==this.node.object.parent)return;const e=this.node.object;e.updateMatrixWorld(!0),t.updateMatrixWorld(!0),this._keep_pos_when_parenting_m_object.copy(e.matrixWorld),this._keep_pos_when_parenting_m_new_parent_inv.copy(t.matrixWorld),this._keep_pos_when_parenting_m_new_parent_inv.invert(),this._keep_pos_when_parenting_m_object.premultiply(this._keep_pos_when_parenting_m_new_parent_inv),bU.setParamsFromMatrix(this._keep_pos_when_parenting_m_object,this.node,{scale:!0})}update_node_transform_params_from_object(t=!1){const e=this.node.object;t&&e.updateMatrix(),bU.setParamsFromMatrix(e.matrix,this.node,{scale:!0})}static PARAM_CALLBACK_update_transform_from_object(t){t.transformController.update_node_transform_params_from_object()}}class MU{constructor(t){this.node=t}initializeNode(){this.node.io.inputs.setCount(0,1),this.node.io.inputs.set_depends_on_inputs(!1),this.node.io.outputs.setHasOneOutput(),this.node.io.inputs.add_on_set_input_hook(\\\\\\\"on_input_updated:update_parent\\\\\\\",(()=>{this.on_input_updated()}))}static on_input_updated(t){const e=t.root().getParentForNode(t);t.transformController&&e&&AU.update_node_transform_params_if_required(t,e),null!=t.io.inputs.input(0)?t.root().addToParentTransform(t):t.root().removeFromParentTransform(t)}on_input_updated(){MU.on_input_updated(this.node)}}wU(ua);class EU extends hU{constructor(){super(...arguments),this.flags=new Di(this),this.hierarchyController=new MU(this),this.transformController=new AU(this)}initializeBaseNode(){super.initializeBaseNode(),this.hierarchyController.initializeNode(),this.transformController.initializeNode()}cook(){this.transformController.update(),this.updateLightParams(),this.updateShadowParams(),this.cookController.endCook()}}class SU{constructor(t,e,n){this.node=t,this._helperConstructor=e,this._name=n}initializeNode(){this.node.flags.display.onUpdate((()=>{this.update()}))}visible(){return this.node.flags.display.active()&&this.node.pv.showHelper}_createHelper(){const t=new this._helperConstructor(this.node,this._name);return t.build(),t}update(){this.visible()?(this._helper||(this._helper=this._createHelper()),this._helper&&(this.node.light.add(this._helper.object),this._helper.update())):this._helper&&this.node.light.remove(this._helper.object)}}var CU=n(41);class NU extends CU.a{constructor(t,e){const n=new S.a;n.setAttribute(\\\\\\\"position\\\\\\\",new C.c([1,1,0,-1,1,0,-1,-1,0,1,-1,0,1,1,0],3)),n.computeBoundingSphere();super(n,new As.a({fog:!1})),this.light=t,this.color=e,this.type=\\\\\\\"RectAreaLightHelper\\\\\\\";const i=new S.a;i.setAttribute(\\\\\\\"position\\\\\\\",new C.c([1,1,0,-1,1,0,-1,-1,0,1,1,0,-1,-1,0,1,-1,0],3)),i.computeBoundingSphere(),this.add(new B.a(i,new lt.a({side:w.i,fog:!1})))}updateMatrixWorld(){if(this.scale.set(.5*this.light.width,.5*this.light.height,1),void 0!==this.color)this.material.color.set(this.color),this.children[0].material.color.set(this.color);else{this.material.color.copy(this.light.color).multiplyScalar(this.light.intensity);const t=this.material.color,e=Math.max(t.r,t.g,t.b);e>1&&t.multiplyScalar(1/e),this.children[0].material.color.copy(this.material.color)}this.matrixWorld.extractRotation(this.light.matrixWorld).scale(this.scale).copyPosition(this.light.matrixWorld),this.children[0].matrixWorld.copy(this.matrixWorld)}dispose(){this.geometry.dispose(),this.material.dispose(),this.children[0].geometry.dispose(),this.children[0].material.dispose()}}class LU{constructor(t,e){this.node=t,this._name=e,this._object=this.createObject(),this._material=new lt.a({wireframe:!0,fog:!1})}build(){this._object.matrixAutoUpdate=!1,this._object.name=this._name,this.buildHelper()}get object(){return this._object}}class OU extends LU{createObject(){return new NU(this.node.light)}buildHelper(){}update(){this._object.updateMatrixWorld()}}class PU extends(function(t){return class extends t{constructor(){super(...arguments),this.light=ha.FOLDER(),this.color=ha.COLOR([1,1,1],{conversion:lo.SRGB_TO_LINEAR}),this.intensity=ha.FLOAT(1,{range:[0,10]}),this.width=ha.FLOAT(1,{range:[0,10]}),this.height=ha.FLOAT(1,{range:[0,10]}),this.showHelper=ha.BOOLEAN(0)}}}(wU(ua))){}const RU=new PU;class IU extends EU{constructor(){super(...arguments),this.paramsConfig=RU,this._helperController=new SU(this,OU,\\\\\\\"RectAreaLightObjNodeHelper\\\\\\\")}static type(){return\\\\\\\"areaLight\\\\\\\"}initializeNode(){this._helperController.initializeNode()}createLight(){const t=new pU(16777215,1,1,1);return t.matrixAutoUpdate=!1,fU.initialized||(fU.init(),fU.initialized=!0),t}updateLightParams(){this.light.color=this.pv.color,this.light.intensity=this.pv.intensity,this.light.width=this.pv.width,this.light.height=this.pv.height,this._helperController.update()}}var FU=n(72);const DU=new p.a,BU=new of.a;class zU extends Ms.a{constructor(t){const e=new S.a,n=new As.a({color:16777215,vertexColors:!0,toneMapped:!1}),i=[],s=[],r={},o=new D.a(16755200),a=new D.a(16711680),l=new D.a(43775),c=new D.a(16777215),h=new D.a(3355443);function u(t,e,n){d(t,n),d(e,n)}function d(t,e){i.push(0,0,0),s.push(e.r,e.g,e.b),void 0===r[t]&&(r[t]=[]),r[t].push(i.length/3-1)}u(\\\\\\\"n1\\\\\\\",\\\\\\\"n2\\\\\\\",o),u(\\\\\\\"n2\\\\\\\",\\\\\\\"n4\\\\\\\",o),u(\\\\\\\"n4\\\\\\\",\\\\\\\"n3\\\\\\\",o),u(\\\\\\\"n3\\\\\\\",\\\\\\\"n1\\\\\\\",o),u(\\\\\\\"f1\\\\\\\",\\\\\\\"f2\\\\\\\",o),u(\\\\\\\"f2\\\\\\\",\\\\\\\"f4\\\\\\\",o),u(\\\\\\\"f4\\\\\\\",\\\\\\\"f3\\\\\\\",o),u(\\\\\\\"f3\\\\\\\",\\\\\\\"f1\\\\\\\",o),u(\\\\\\\"n1\\\\\\\",\\\\\\\"f1\\\\\\\",o),u(\\\\\\\"n2\\\\\\\",\\\\\\\"f2\\\\\\\",o),u(\\\\\\\"n3\\\\\\\",\\\\\\\"f3\\\\\\\",o),u(\\\\\\\"n4\\\\\\\",\\\\\\\"f4\\\\\\\",o),u(\\\\\\\"p\\\\\\\",\\\\\\\"n1\\\\\\\",a),u(\\\\\\\"p\\\\\\\",\\\\\\\"n2\\\\\\\",a),u(\\\\\\\"p\\\\\\\",\\\\\\\"n3\\\\\\\",a),u(\\\\\\\"p\\\\\\\",\\\\\\\"n4\\\\\\\",a),u(\\\\\\\"u1\\\\\\\",\\\\\\\"u2\\\\\\\",l),u(\\\\\\\"u2\\\\\\\",\\\\\\\"u3\\\\\\\",l),u(\\\\\\\"u3\\\\\\\",\\\\\\\"u1\\\\\\\",l),u(\\\\\\\"c\\\\\\\",\\\\\\\"t\\\\\\\",c),u(\\\\\\\"p\\\\\\\",\\\\\\\"c\\\\\\\",h),u(\\\\\\\"cn1\\\\\\\",\\\\\\\"cn2\\\\\\\",h),u(\\\\\\\"cn3\\\\\\\",\\\\\\\"cn4\\\\\\\",h),u(\\\\\\\"cf1\\\\\\\",\\\\\\\"cf2\\\\\\\",h),u(\\\\\\\"cf3\\\\\\\",\\\\\\\"cf4\\\\\\\",h),e.setAttribute(\\\\\\\"position\\\\\\\",new C.c(i,3)),e.setAttribute(\\\\\\\"color\\\\\\\",new C.c(s,3)),super(e,n),this.type=\\\\\\\"CameraHelper\\\\\\\",this.camera=t,this.camera.updateProjectionMatrix&&this.camera.updateProjectionMatrix(),this.matrixAutoUpdate=!1,this.pointMap=r,this.update()}update(){const t=this.geometry,e=this.pointMap;BU.projectionMatrixInverse.copy(this.camera.projectionMatrixInverse),kU(\\\\\\\"c\\\\\\\",e,t,BU,0,0,-1),kU(\\\\\\\"t\\\\\\\",e,t,BU,0,0,1),kU(\\\\\\\"n1\\\\\\\",e,t,BU,-1,-1,-1),kU(\\\\\\\"n2\\\\\\\",e,t,BU,1,-1,-1),kU(\\\\\\\"n3\\\\\\\",e,t,BU,-1,1,-1),kU(\\\\\\\"n4\\\\\\\",e,t,BU,1,1,-1),kU(\\\\\\\"f1\\\\\\\",e,t,BU,-1,-1,1),kU(\\\\\\\"f2\\\\\\\",e,t,BU,1,-1,1),kU(\\\\\\\"f3\\\\\\\",e,t,BU,-1,1,1),kU(\\\\\\\"f4\\\\\\\",e,t,BU,1,1,1),kU(\\\\\\\"u1\\\\\\\",e,t,BU,.7,1.1,-1),kU(\\\\\\\"u2\\\\\\\",e,t,BU,-.7,1.1,-1),kU(\\\\\\\"u3\\\\\\\",e,t,BU,0,2,-1),kU(\\\\\\\"cf1\\\\\\\",e,t,BU,-1,0,1),kU(\\\\\\\"cf2\\\\\\\",e,t,BU,1,0,1),kU(\\\\\\\"cf3\\\\\\\",e,t,BU,0,-1,1),kU(\\\\\\\"cf4\\\\\\\",e,t,BU,0,1,1),kU(\\\\\\\"cn1\\\\\\\",e,t,BU,-1,0,-1),kU(\\\\\\\"cn2\\\\\\\",e,t,BU,1,0,-1),kU(\\\\\\\"cn3\\\\\\\",e,t,BU,0,-1,-1),kU(\\\\\\\"cn4\\\\\\\",e,t,BU,0,1,-1),t.getAttribute(\\\\\\\"position\\\\\\\").needsUpdate=!0}}function kU(t,e,n,i,s,r,o){DU.set(s,r,o).unproject(i);const a=e[t];if(void 0!==a){const t=n.getAttribute(\\\\\\\"position\\\\\\\");for(let e=0,n=a.length;e.9&&o<.1&&(e<.2&&(r[t+0]+=1),n<.2&&(r[t+2]+=1),i<.2&&(r[t+4]+=1))}}()}(),this.setAttribute(\\\\\\\"position\\\\\\\",new C.c(s,3)),this.setAttribute(\\\\\\\"normal\\\\\\\",new C.c(s.slice(),3)),this.setAttribute(\\\\\\\"uv\\\\\\\",new C.c(r,2)),0===i?this.computeVertexNormals():this.normalizeNormals()}static fromJSON(t){return new XU(t.vertices,t.indices,t.radius,t.details)}}class YU extends XU{constructor(t=1,e=0){super([1,0,0,-1,0,0,0,1,0,0,-1,0,0,0,1,0,0,-1],[0,2,4,0,4,3,0,3,5,0,5,2,1,2,5,1,5,3,1,3,4,1,4,2],t,e),this.type=\\\\\\\"OctahedronGeometry\\\\\\\",this.parameters={radius:t,detail:e}}static fromJSON(t){return new YU(t.radius,t.detail)}}class $U extends LU{constructor(){super(...arguments),this._geometry=new YU(1),this._quat=new hh.a,this._default_position=new p.a(0,1,0),this._color1=new D.a,this._color2=new D.a}createObject(){return new B.a}buildHelper(){this._geometry.rotateZ(.5*Math.PI),this._material.vertexColors=!0;const t=this._geometry.getAttribute(\\\\\\\"position\\\\\\\"),e=new Float32Array(3*t.count);this._geometry.setAttribute(\\\\\\\"color\\\\\\\",new C.a(e,3)),this._object.geometry=this._geometry,this._object.material=this._material,this._object.matrixAutoUpdate=!1}update(){if(!this.node.pv.position)return;this._object.position.copy(this.node.pv.position).multiplyScalar(-1),this._quat.setFromUnitVectors(this._default_position,this.node.pv.position),this._object.setRotationFromQuaternion(this._quat),this._object.scale.setScalar(this.node.pv.helperSize),this._object.updateMatrix();const t=this._geometry.getAttribute(\\\\\\\"color\\\\\\\");this._color1.copy(this.node.light.color),this._color2.copy(this.node.light.groundColor);for(let e=0,n=t.count;e0)&&d.push(e,s,l),(t!==n-1||a0&&y(!0),e>0&&y(!1)),this.setIndex(c),this.setAttribute(\\\\\\\"position\\\\\\\",new C.c(h,3)),this.setAttribute(\\\\\\\"normal\\\\\\\",new C.c(u,3)),this.setAttribute(\\\\\\\"uv\\\\\\\",new C.c(_,2))}static fromJSON(t){return new aG(t.radiusTop,t.radiusBottom,t.height,t.radialSegments,t.heightSegments,t.openEnded,t.thetaStart,t.thetaLength)}}class lG extends aG{constructor(t=1,e=1,n=8,i=1,s=!1,r=0,o=2*Math.PI){super(0,t,e,n,i,s,r,o),this.type=\\\\\\\"ConeGeometry\\\\\\\",this.parameters={radius:t,height:e,radialSegments:n,heightSegments:i,openEnded:s,thetaStart:r,thetaLength:o}}static fromJSON(t){return new lG(t.radius,t.height,t.radialSegments,t.heightSegments,t.openEnded,t.thetaStart,t.thetaLength)}}class cG{constructor(t){this.node=t}update(){const t=this.node.pv;if(t.tvolumetric){const e=this.object(),n=this.node.light;oG.updateConeObject(e,{sizeMult:t.helperSize,distance:n.distance,angle:n.angle});const i=e.material.uniforms;i.lightColor.value.copy(n.color),i.attenuation.value=t.volAttenuation,i.anglePower.value=t.volAnglePower,this.node.light.add(e)}else this._mesh&&this.node.light.remove(this._mesh)}object(){return this._mesh=this._mesh||this._createMesh()}_createMesh(){const t=new lG(1,1,256,1);t.applyMatrix4((new A.a).makeTranslation(0,-.5,0)),t.applyMatrix4((new A.a).makeRotationX(-Math.PI/2));const e=this._createMaterial(),n=new B.a(t,e);return n.matrixAutoUpdate=!1,n.name=\\\\\\\"Volumetric\\\\\\\",e.uniforms.lightColor.value.set(\\\\\\\"white\\\\\\\"),n}_createMaterial(){return new F({uniforms:{attenuation:{value:5},anglePower:{value:1.2},lightColor:{value:new D.a(\\\\\\\"cyan\\\\\\\")}},vertexShader:\\\\\\\"varying vec3 vNormal;\\\\nvarying vec3 vWorldPosition;\\\\nvarying vec3 vWorldOrigin;\\\\n\\\\nvoid main(){\\\\n\\\\t// compute intensity\\\\n\\\\tvNormal\\\\t\\\\t= normalize( normalMatrix * normal );\\\\n\\\\n\\\\tvec4 worldPosition\\\\t= modelMatrix * vec4( position, 1.0 );\\\\n\\\\tvWorldPosition\\\\t\\\\t= worldPosition.xyz;\\\\n\\\\n\\\\tvec4 worldOrigin\\\\t= modelMatrix * vec4( 0.0, 0.0, 0.0, 1.0 );\\\\n\\\\tvWorldOrigin\\\\t\\\\t= worldOrigin.xyz;\\\\n\\\\n\\\\t// set gl_Position\\\\n\\\\tgl_Position\\\\t= projectionMatrix * modelViewMatrix * vec4( position, 1.0 );\\\\n}\\\\\\\",fragmentShader:\\\\\\\"varying vec3 vNormal;\\\\nvarying vec3 vWorldPosition;\\\\nvarying vec3 vWorldOrigin;\\\\n\\\\nuniform vec3 lightColor;\\\\n\\\\n// uniform vec3 spotPosition;\\\\n\\\\nuniform float attenuation;\\\\nuniform float anglePower;\\\\n\\\\nvoid main(){\\\\n\\\\n\\\\t//////////////////////////////////////////////////////////\\\\n\\\\t// distance attenuation //\\\\n\\\\t//////////////////////////////////////////////////////////\\\\n\\\\tfloat intensity = distance(vWorldPosition, vWorldOrigin) / attenuation;\\\\n\\\\tintensity = 1.0 - clamp(intensity, 0.0, 1.0);\\\\n\\\\n\\\\t//////////////////////////////////////////////////////////\\\\n\\\\t// intensity on angle //\\\\n\\\\t//////////////////////////////////////////////////////////\\\\n\\\\tvec3 normal = vec3(vNormal.x, vNormal.y, abs(vNormal.z));\\\\n\\\\tfloat angleIntensity = pow( dot(normal, vec3(0.0, 0.0, 1.0)), anglePower );\\\\n\\\\tintensity = intensity * angleIntensity;\\\\n\\\\t// 'gl_FragColor = vec4( lightColor, intensity );\\\\n\\\\n\\\\t//////////////////////////////////////////////////////////\\\\n\\\\t// final color //\\\\n\\\\t//////////////////////////////////////////////////////////\\\\n\\\\n\\\\t// set the final color\\\\n\\\\tgl_FragColor = vec4( lightColor, intensity);\\\\n}\\\\\\\",transparent:!0,depthWrite:!1})}}class hG extends(wU(ua)){constructor(){super(...arguments),this.light=ha.FOLDER(),this.color=ha.COLOR([1,1,1],{conversion:lo.SRGB_TO_LINEAR}),this.intensity=ha.FLOAT(1),this.angle=ha.FLOAT(45,{range:[0,180]}),this.penumbra=ha.FLOAT(.1),this.decay=ha.FLOAT(.1,{range:[0,1]}),this.distance=ha.FLOAT(100,{range:[0,100]}),this.showHelper=ha.BOOLEAN(0),this.helperSize=ha.FLOAT(1,{visibleIf:{showHelper:1}}),this.shadow=ha.FOLDER(),this.castShadow=ha.BOOLEAN(1),this.shadowAutoUpdate=ha.BOOLEAN(1,{visibleIf:{castShadow:1}}),this.shadowUpdateOnNextRender=ha.BOOLEAN(0,{visibleIf:{castShadow:1,shadowAutoUpdate:0}}),this.shadowRes=ha.VECTOR2([256,256],{visibleIf:{castShadow:1}}),this.shadowBias=ha.FLOAT(.001,{visibleIf:{castShadow:1},range:[-.01,.01],rangeLocked:[!1,!1]}),this.shadowNear=ha.FLOAT(.1,{visibleIf:{castShadow:1},range:[0,100],rangeLocked:[!0,!1]}),this.shadowFar=ha.FLOAT(100,{visibleIf:{castShadow:1},range:[0,100],rangeLocked:[!0,!1]}),this.shadowRadius=ha.FLOAT(0,{visibleIf:{castShadow:1},range:[0,10],rangeLocked:[!0,!1]}),this.volumetric=ha.FOLDER(),this.tvolumetric=ha.BOOLEAN(0),this.volAttenuation=ha.FLOAT(5,{range:[0,10],rangeLocked:[!0,!1]}),this.volAnglePower=ha.FLOAT(10,{range:[0,20],rangeLocked:[!0,!1]})}}const uG=new hG;class dG extends EU{constructor(){super(...arguments),this.paramsConfig=uG,this._helperController=new SU(this,oG,\\\\\\\"SpotLightHelper\\\\\\\"),this._volumetricController=new cG(this)}static type(){return GU.SPOT}initializeNode(){this._helperController.initializeNode()}createLight(){const t=new rG.a;return t.matrixAutoUpdate=!1,t.castShadow=!0,t.shadow.bias=-.001,t.shadow.mapSize.x=256,t.shadow.mapSize.y=256,t.shadow.camera.near=.1,this._target_target=t.target,this._target_target.name=\\\\\\\"SpotLight Default Target\\\\\\\",this._target_target.matrixAutoUpdate=!1,this.object.add(this._target_target),t}updateLightParams(){this.light.color=this.pv.color,this.light.intensity=this.pv.intensity,this.light.angle=this.pv.angle*(Math.PI/180),this.light.penumbra=this.pv.penumbra,this.light.decay=this.pv.decay,this.light.distance=this.pv.distance,this._helperController.update(),this._volumetricController.update()}updateShadowParams(){this.light.castShadow=this.pv.castShadow,this.light.shadow.autoUpdate=this.pv.shadowAutoUpdate,this.light.shadow.needsUpdate=this.pv.shadowUpdateOnNextRender,this.light.shadow.mapSize.copy(this.pv.shadowRes),this.light.shadow.camera.near=this.pv.shadowNear,this.light.shadow.camera.far=this.pv.shadowFar,this.light.shadow.bias=this.pv.shadowBias,this.light.shadow.radius=this.pv.shadowRadius}}let pG;const _G=function(){return void 0===pG&&(pG=new(window.AudioContext||window.webkitAudioContext)),pG},mG=new p.a,fG=new hh.a,gG=new p.a,vG=new p.a;class yG extends Q.a{constructor(){super(),this.type=\\\\\\\"AudioListener\\\\\\\",this.context=_G(),this.gain=this.context.createGain(),this.gain.connect(this.context.destination),this.filter=null,this.timeDelta=0,this._clock=new Dm}getInput(){return this.gain}removeFilter(){return null!==this.filter&&(this.gain.disconnect(this.filter),this.filter.disconnect(this.context.destination),this.gain.connect(this.context.destination),this.filter=null),this}getFilter(){return this.filter}setFilter(t){return null!==this.filter?(this.gain.disconnect(this.filter),this.filter.disconnect(this.context.destination)):this.gain.disconnect(this.context.destination),this.filter=t,this.gain.connect(this.filter),this.filter.connect(this.context.destination),this}getMasterVolume(){return this.gain.gain.value}setMasterVolume(t){return this.gain.gain.setTargetAtTime(t,this.context.currentTime,.01),this}updateMatrixWorld(t){super.updateMatrixWorld(t);const e=this.context.listener,n=this.up;if(this.timeDelta=this._clock.getDelta(),this.matrixWorld.decompose(mG,fG,gG),vG.set(0,0,-1).applyQuaternion(fG),e.positionX){const t=this.context.currentTime+this.timeDelta;e.positionX.linearRampToValueAtTime(mG.x,t),e.positionY.linearRampToValueAtTime(mG.y,t),e.positionZ.linearRampToValueAtTime(mG.z,t),e.forwardX.linearRampToValueAtTime(vG.x,t),e.forwardY.linearRampToValueAtTime(vG.y,t),e.forwardZ.linearRampToValueAtTime(vG.z,t),e.upX.linearRampToValueAtTime(n.x,t),e.upY.linearRampToValueAtTime(n.y,t),e.upZ.linearRampToValueAtTime(n.z,t)}else e.setPosition(mG.x,mG.y,mG.z),e.setOrientation(vG.x,vG.y,vG.z,n.x,n.y,n.z)}}class xG extends(wU(ua)){constructor(){super(...arguments),this.audio=ha.FOLDER(),this.soundOn=ha.BOOLEAN(1),this.masterVolume=ha.FLOAT(1,{range:[0,1],rangeLocked:[!0,!1]})}}const bG=new xG;class wG extends cU{constructor(){super(...arguments),this.paramsConfig=bG,this.hierarchyController=new MU(this),this.transformController=new AU(this),this.flags=new Di(this)}static type(){return Ig.AUDIO_LISTENER}createObject(){const t=new yG;return t.matrixAutoUpdate=!1,t}initializeNode(){this.hierarchyController.initializeNode(),this.transformController.initializeNode(),this.scene().dispatchController.onAddListener((()=>{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{this.params.label.init([this.p.soundOn],(()=>this.pv.soundOn?\\\\\\\"on\\\\\\\":\\\\\\\"off\\\\\\\"))}))}))}cook(){this.transformController.update(),this._updatePositionalAudio(),this.cookController.endCook()}_updatePositionalAudio(){const t=this.pv.soundOn?this.pv.masterVolume:0;this.object.setMasterVolume(t)}}class TG extends Ms.a{constructor(t=1){const e=[0,0,0,t,0,0,0,0,0,0,t,0,0,0,0,0,0,t],n=new S.a;n.setAttribute(\\\\\\\"position\\\\\\\",new C.c(e,3)),n.setAttribute(\\\\\\\"color\\\\\\\",new C.c([1,0,0,1,.6,0,0,1,0,.6,1,0,0,0,1,0,.6,1],3));super(n,new As.a({vertexColors:!0,toneMapped:!1})),this.type=\\\\\\\"AxesHelper\\\\\\\"}setColors(t,e,n){const i=new D.a,s=this.geometry.attributes.color.array;return i.set(t),i.toArray(s,0),i.toArray(s,3),i.set(e),i.toArray(s,6),i.toArray(s,9),i.set(n),i.toArray(s,12),i.toArray(s,15),this.geometry.attributes.color.needsUpdate=!0,this}dispose(){this.geometry.dispose(),this.material.dispose()}}var AG;!function(t){t.TOGETHER=\\\\\\\"translate + rotate together\\\\\\\",t.SEPARATELY=\\\\\\\"translate + rotate separately\\\\\\\"}(AG||(AG={}));const MG=[AG.TOGETHER,AG.SEPARATELY];const EG=new class extends ua{constructor(){super(...arguments),this.object0=ha.OPERATOR_PATH(\\\\\\\"/geo1\\\\\\\",{nodeSelection:{context:ts.OBJ}}),this.object1=ha.OPERATOR_PATH(\\\\\\\"/geo2\\\\\\\",{nodeSelection:{context:ts.OBJ}}),this.mode=ha.INTEGER(MG.indexOf(AG.TOGETHER),{menu:{entries:MG.map(((t,e)=>({name:t,value:e})))}}),this.blend=ha.FLOAT(0,{visibleIf:{mode:MG.indexOf(AG.TOGETHER)},range:[0,1],rangeLocked:[!1,!1]}),this.blendT=ha.FLOAT(0,{visibleIf:{mode:MG.indexOf(AG.SEPARATELY)},range:[0,1],rangeLocked:[!1,!1]}),this.blendR=ha.FLOAT(0,{visibleIf:{mode:MG.indexOf(AG.SEPARATELY)},range:[0,1],rangeLocked:[!1,!1]})}};class SG extends cU{constructor(){super(...arguments),this.paramsConfig=EG,this.hierarchyController=new MU(this),this.flags=new Di(this),this._helper=new TG(1),this._t0=new p.a,this._q0=new hh.a,this._s0=new p.a,this._t1=new p.a,this._q1=new hh.a,this._s1=new p.a}static type(){return\\\\\\\"blend\\\\\\\"}createObject(){const t=new Fn.a;return t.matrixAutoUpdate=!1,t}initializeNode(){this.hierarchyController.initializeNode(),this.io.inputs.setCount(0),this.addPostDirtyHook(\\\\\\\"blend_on_dirty\\\\\\\",(()=>{this.cookController.cookMainWithoutInputs()})),this._updateHelperHierarchy(),this.flags.display.onUpdate((()=>{this._updateHelperHierarchy()}))}_updateHelperHierarchy(){this.flags.display.active()?this.object.add(this._helper):this.object.remove(this._helper)}cook(){const t=this.p.object0.found_node_with_context(ts.OBJ),e=this.p.object1.found_node_with_context(ts.OBJ);t&&e&&this._blend(t.object,e.object),this.cookController.endCook()}_blend(t,e){const n=MG[this.pv.mode];switch(n){case AG.TOGETHER:return this._blend_together(t,e);case AG.SEPARATELY:return this._blend_separately(t,e)}os.unreachable(n)}_blend_together(t,e){this._decompose_matrices(t,e),this._object.position.copy(this._t0).lerp(this._t1,this.pv.blend),this._object.quaternion.copy(this._q0).slerp(this._q1,this.pv.blend),this._object.matrixAutoUpdate||this._object.updateMatrix()}_blend_separately(t,e){this._decompose_matrices(t,e),this._object.position.copy(this._t0).lerp(this._t1,this.pv.blendT),this._object.quaternion.copy(this._q0).slerp(this._q1,this.pv.blendR),this._object.matrixAutoUpdate||this._object.updateMatrix()}_decompose_matrices(t,e){t.matrixWorld.decompose(this._t0,this._q0,this._s0),e.matrixWorld.decompose(this._t1,this._q1,this._s1)}}var CG={uniforms:{tDiffuse:{value:null},h:{value:1/512}},vertexShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\tvUv = uv;\\\\n\\\\t\\\\t\\\\tgl_Position = projectionMatrix * modelViewMatrix * vec4( position, 1.0 );\\\\n\\\\n\\\\t\\\\t}\\\\\\\",fragmentShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\tuniform sampler2D tDiffuse;\\\\n\\\\t\\\\tuniform float h;\\\\n\\\\n\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\tvec4 sum = vec4( 0.0 );\\\\n\\\\n\\\\t\\\\t\\\\tsum += texture2D( tDiffuse, vec2( vUv.x - 4.0 * h, vUv.y ) ) * 0.051;\\\\n\\\\t\\\\t\\\\tsum += texture2D( tDiffuse, vec2( vUv.x - 3.0 * h, vUv.y ) ) * 0.0918;\\\\n\\\\t\\\\t\\\\tsum += texture2D( tDiffuse, vec2( vUv.x - 2.0 * h, vUv.y ) ) * 0.12245;\\\\n\\\\t\\\\t\\\\tsum += texture2D( tDiffuse, vec2( vUv.x - 1.0 * h, vUv.y ) ) * 0.1531;\\\\n\\\\t\\\\t\\\\tsum += texture2D( tDiffuse, vec2( vUv.x, vUv.y ) ) * 0.1633;\\\\n\\\\t\\\\t\\\\tsum += texture2D( tDiffuse, vec2( vUv.x + 1.0 * h, vUv.y ) ) * 0.1531;\\\\n\\\\t\\\\t\\\\tsum += texture2D( tDiffuse, vec2( vUv.x + 2.0 * h, vUv.y ) ) * 0.12245;\\\\n\\\\t\\\\t\\\\tsum += texture2D( tDiffuse, vec2( vUv.x + 3.0 * h, vUv.y ) ) * 0.0918;\\\\n\\\\t\\\\t\\\\tsum += texture2D( tDiffuse, vec2( vUv.x + 4.0 * h, vUv.y ) ) * 0.051;\\\\n\\\\n\\\\t\\\\t\\\\tgl_FragColor = sum;\\\\n\\\\n\\\\t\\\\t}\\\\\\\"};const NG={uniforms:{tDiffuse:{value:null},v:{value:1/512}},vertexShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\tvUv = uv;\\\\n\\\\t\\\\t\\\\tgl_Position = projectionMatrix * modelViewMatrix * vec4( position, 1.0 );\\\\n\\\\n\\\\t\\\\t}\\\\\\\",fragmentShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\tuniform sampler2D tDiffuse;\\\\n\\\\t\\\\tuniform float v;\\\\n\\\\n\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\tvec4 sum = vec4( 0.0 );\\\\n\\\\n\\\\t\\\\t\\\\tsum += texture2D( tDiffuse, vec2( vUv.x, vUv.y - 4.0 * v ) ) * 0.051;\\\\n\\\\t\\\\t\\\\tsum += texture2D( tDiffuse, vec2( vUv.x, vUv.y - 3.0 * v ) ) * 0.0918;\\\\n\\\\t\\\\t\\\\tsum += texture2D( tDiffuse, vec2( vUv.x, vUv.y - 2.0 * v ) ) * 0.12245;\\\\n\\\\t\\\\t\\\\tsum += texture2D( tDiffuse, vec2( vUv.x, vUv.y - 1.0 * v ) ) * 0.1531;\\\\n\\\\t\\\\t\\\\tsum += texture2D( tDiffuse, vec2( vUv.x, vUv.y ) ) * 0.1633;\\\\n\\\\t\\\\t\\\\tsum += texture2D( tDiffuse, vec2( vUv.x, vUv.y + 1.0 * v ) ) * 0.1531;\\\\n\\\\t\\\\t\\\\tsum += texture2D( tDiffuse, vec2( vUv.x, vUv.y + 2.0 * v ) ) * 0.12245;\\\\n\\\\t\\\\t\\\\tsum += texture2D( tDiffuse, vec2( vUv.x, vUv.y + 3.0 * v ) ) * 0.0918;\\\\n\\\\t\\\\t\\\\tsum += texture2D( tDiffuse, vec2( vUv.x, vUv.y + 4.0 * v ) ) * 0.051;\\\\n\\\\n\\\\t\\\\t\\\\tgl_FragColor = sum;\\\\n\\\\n\\\\t\\\\t}\\\\\\\"},LG=1/256e3;class OG{constructor(t){this._renderTargetBlur=this._createRenderTarget(t),this._camera=this._createCamera(),this._blurPlane=this._createBlurPlane(),this._horizontalBlurMaterial=new F(CG),this._horizontalBlurMaterial.depthTest=!1,this._verticalBlurMaterial=new F(NG),this._verticalBlurMaterial.depthTest=!1}setSize(t,e){this._renderTargetBlur.setSize(t,e)}_createRenderTarget(t){const e=new K(t.x,t.y);return e.texture.generateMipmaps=!1,e}_createCamera(){const t=new ot.a(-.5,.5,.5,-.5,0,1);return t.position.z=.5,t}_createBlurPlane(){const t=new L(1,1);return new B.a(t)}applyBlur(t,e,n,i){const s=Math.max(this._renderTargetBlur.width,this._renderTargetBlur.height);this._horizontalBlurMaterial.uniforms.tDiffuse.value=t.texture,this._horizontalBlurMaterial.uniforms.h.value=n*s*LG,this._blurPlane.material=this._horizontalBlurMaterial,e.setRenderTarget(this._renderTargetBlur),e.render(this._blurPlane,this._camera),this._verticalBlurMaterial.uniforms.tDiffuse.value=this._renderTargetBlur.texture,this._verticalBlurMaterial.uniforms.v.value=i*s*LG,this._blurPlane.material=this._verticalBlurMaterial,e.setRenderTarget(t),e.render(this._blurPlane,this._camera)}}var PG;!function(t){t.ON_RENDER=\\\\\\\"On Every Render\\\\\\\",t.MANUAL=\\\\\\\"Manual\\\\\\\"}(PG||(PG={}));const RG=[PG.ON_RENDER,PG.MANUAL];class IG extends(wU(ua)){constructor(){super(...arguments),this.shadow=ha.FOLDER(),this.dist=ha.FLOAT(1,{range:[0,10],rangeLocked:[!0,!1]}),this.planeSize=ha.VECTOR2([1,1]),this.shadowRes=ha.VECTOR2([256,256]),this.blur=ha.FLOAT(1,{range:[0,10],rangeLocked:[!0,!1]}),this.tblur2=ha.BOOLEAN(1),this.blur2=ha.FLOAT(1,{range:[0,10],rangeLocked:[!0,!1],visibleIf:{tblur2:1}}),this.darkness=ha.FLOAT(1),this.opacity=ha.FLOAT(1),this.showHelper=ha.BOOLEAN(0),this.updateMode=ha.INTEGER(RG.indexOf(PG.ON_RENDER),{callback:t=>{BG.PARAM_CALLBACK_update_updateMode(t)},menu:{entries:RG.map(((t,e)=>({name:t,value:e})))}}),this.update=ha.BUTTON(null,{callback:t=>{BG.PARAM_CALLBACK_updateManual(t)},visibleIf:{updateMode:RG.indexOf(PG.MANUAL)}}),this.scene=ha.FOLDER(),this.include=ha.STRING(\\\\\\\"\\\\\\\"),this.exclude=ha.STRING(\\\\\\\"\\\\\\\"),this.updateObjectsList=ha.BUTTON(null,{callback:t=>{BG.PARAM_CALLBACK_updateObjectsList(t)}}),this.printResolveObjectsList=ha.BUTTON(null,{callback:t=>{BG.PARAM_CALLBACK_printResolveObjectsList(t)}})}}const FG=new IG,DG=new d.a(256,256);class BG extends cU{constructor(){super(...arguments),this.paramsConfig=FG,this.hierarchyController=new MU(this),this.flags=new Di(this),this._renderTarget=this._createRenderTarget(DG),this._coreRenderBlur=this._createCoreRenderBlur(DG),this._includedObjects=[],this._includedAncestors=[],this._excludedObjects=[],this.transformController=new AU(this),this._darknessUniform={value:1},this._emptyOnBeforeRender=()=>{},this._emptyRenderHook=()=>{},this._on_object_before_render_bound=this._update.bind(this),this._initialVisibilityState=new WeakMap}static type(){return\\\\\\\"contactShadow\\\\\\\"}_createRenderTarget(t){const e=new K(t.x,t.y);return e.texture.generateMipmaps=!1,e}_createCoreRenderBlur(t){return new OG(t)}createObject(){const t=new Fn.a;this._shadowGroup=new Fn.a,t.add(this._shadowGroup),this._shadowGroup.name=\\\\\\\"shadowGroup\\\\\\\";const e=new L(1,1).rotateX(-Math.PI/2),n=e.getAttribute(\\\\\\\"uv\\\\\\\").array;for(let t of[1,3,5,7])n[t]=1-n[t];return this._planeMaterial=new lt.a({map:this._renderTarget.texture,opacity:1,transparent:!0,depthWrite:!1}),this._plane=new B.a(e,this._planeMaterial),this._plane.renderOrder=1,this._plane.matrixAutoUpdate=!1,this._shadowGroup.add(this._plane),this._createDepthCamera(this._shadowGroup),this._createMaterials(),t}initializeNode(){this.hierarchyController.initializeNode(),this.transformController.initializeNode(),this._updateShadowGroupVisibility(),this._updateHelperVisibility(),this.flags.display.onUpdate((()=>{this._updateShadowGroupVisibility(),this._updateHelperVisibility()}))}async cook(){this.transformController.update(),this._updateRenderHook(),this._updateHelperVisibility(),this._updateObjectsList(),this._planeMaterial&&(this._planeMaterial.opacity=this.pv.opacity),this._darknessUniform.value=this.pv.darkness,this._plane&&this._shadowCamera&&this._helper&&(this._plane.scale.x=this.pv.planeSize.x,this._plane.scale.z=this.pv.planeSize.y,this._plane.updateMatrix(),this._shadowCamera.left=-this.pv.planeSize.x/2,this._shadowCamera.right=this.pv.planeSize.x/2,this._shadowCamera.bottom=-this.pv.planeSize.y/2,this._shadowCamera.top=this.pv.planeSize.y/2,this._shadowCamera.far=this.pv.dist,this._shadowCamera.updateProjectionMatrix(),this._helper.update()),this._renderTarget.width==this.pv.shadowRes.x&&this._renderTarget.height==this.pv.shadowRes.y||this._planeMaterial&&(this._renderTarget=this._createRenderTarget(this.pv.shadowRes),this._coreRenderBlur=this._createCoreRenderBlur(this.pv.shadowRes),this._planeMaterial.map=this._renderTarget.texture),this.cookController.endCook()}_createDepthCamera(t){this._shadowCamera=new ot.a(-.5,.5,.5,-.5,0,1),this._shadowCamera.rotation.x=Math.PI/2,t.add(this._shadowCamera),this._helper=new zU(this._shadowCamera),this._helper.visible=!1,this._shadowCamera.add(this._helper)}_createMaterials(){this._depthMaterial=new Sn,this._depthMaterial.onBeforeCompile=t=>{t.uniforms.darkness=this._darknessUniform,t.fragmentShader=`\\\\n\\\\t\\\\t\\\\tuniform float darkness;\\\\n\\\\t\\\\t\\\\t${t.fragmentShader.replace(\\\\\\\"gl_FragColor = vec4( vec3( 1.0 - fragCoordZ ), opacity );\\\\\\\",\\\\\\\"gl_FragColor = vec4( vec3( 0.0 ), ( 1.0 - fragCoordZ ) * darkness );\\\\\\\")}\\\\n\\\\t\\\\t`},this._depthMaterial.depthTest=!1,this._depthMaterial.depthWrite=!1}_renderShadow(t,e){if(!this._helper)return;if(!this._depthMaterial)return;if(!this._shadowCamera)return;if(!this._helper)return;if(!this._plane)return;const n=this._plane.onBeforeRender,i=e.background,s=this._helper.visible;e.background=null,this._plane.onBeforeRender=this._emptyOnBeforeRender,this._helper.visible=!1,e.overrideMaterial=this._depthMaterial,this._initVisibility(e),t.setRenderTarget(this._renderTarget),t.render(e,this._shadowCamera),this._coreRenderBlur.applyBlur(this._renderTarget,t,this.pv.blur,this.pv.blur),this.pv.tblur2&&this._coreRenderBlur.applyBlur(this._renderTarget,t,this.pv.blur2,this.pv.blur2),this._restoreVisibility(e),e.overrideMaterial=null,this._helper.visible=s,t.setRenderTarget(null),e.background=i,this._plane.onBeforeRender=n}_updateShadowGroupVisibility(){this._shadowGroup&&(this.flags.display.active()?this._shadowGroup.visible=!0:this._shadowGroup.visible=!1)}_updateHelperVisibility(){this._helper&&(this.flags.display.active()&&this.pv.showHelper?this._helper.visible=!0:this._helper.visible=!1)}_updateRenderHook(){const t=RG[this.pv.updateMode];switch(t){case PG.ON_RENDER:return this._addRenderHook();case PG.MANUAL:return this._removeRenderHook()}os.unreachable(t)}_addRenderHook(){this._plane&&this._plane.onBeforeRender!=this._on_object_before_render_bound&&(this._plane.onBeforeRender=this._on_object_before_render_bound)}_removeRenderHook(){this._plane&&this._plane.onBeforeRender!=this._emptyRenderHook&&(this._plane.onBeforeRender=this._emptyRenderHook)}_update(t,e,n,i,s,r){t&&e?this._renderShadow(t,e):console.log(\\\\\\\"no renderer or scene\\\\\\\")}_updateManual(){const t=li.renderersController.firstRenderer();if(!t)return void console.log(\\\\\\\"no renderer found\\\\\\\");const e=this.scene().threejsScene();this._renderShadow(t,e)}static PARAM_CALLBACK_update_updateMode(t){t._updateRenderHook()}static PARAM_CALLBACK_updateManual(t){t._updateManual()}static PARAM_CALLBACK_updateObjectsList(t){t._updateObjectsList()}_updateObjectsList(){\\\\\\\"\\\\\\\"!=this.pv.include?this._includedObjects=this.scene().objectsByMask(this.pv.include):this._includedObjects=[];const t=new Map;for(let e of this._includedObjects)e.traverseAncestors((e=>{t.set(e.uuid,e)}));this._includedAncestors=[],t.forEach(((t,e)=>{this._includedAncestors.push(t)})),\\\\\\\"\\\\\\\"!=this.pv.exclude?this._excludedObjects=this.scene().objectsByMask(this.pv.exclude):this._excludedObjects=[]}static PARAM_CALLBACK_printResolveObjectsList(t){t._printResolveObjectsList()}_printResolveObjectsList(){console.log(\\\\\\\"included objects:\\\\\\\"),console.log(this._includedObjects),console.log(\\\\\\\"included parents:\\\\\\\"),console.log(this._includedAncestors),console.log(\\\\\\\"excluded objects:\\\\\\\"),console.log(this._excludedObjects)}_initVisibility(t){this._includedObjects.length>0?t.traverse((t=>{this._initialVisibilityState.set(t,t.visible),t.visible=!1})):(this._storeObjectsVisibility(this._includedObjects),this._storeObjectsVisibility(this._includedAncestors),this._storeObjectsVisibility(this._excludedObjects)),this._setObjectsVisibility(this._includedObjects,!0),this._setObjectsVisibility(this._includedAncestors,!0),this._setObjectsVisibility(this._excludedObjects,!1)}_storeObjectsVisibility(t){for(let e of t)this._initialVisibilityState.set(e,e.visible)}_setObjectsVisibility(t,e){for(let n of t)n.visible=e}_restoreVisibility(t){this._includedObjects.length>0?t.traverse((t=>{const e=this._initialVisibilityState.get(t);e&&(t.visible=e)})):(this._restoreObjectsVisibility(this._includedObjects),this._restoreObjectsVisibility(this._includedAncestors),this._restoreObjectsVisibility(this._excludedObjects))}_restoreObjectsVisibility(t){for(let e of t){const t=this._initialVisibilityState.get(e);t&&(e.visible=t)}}}const zG=\\\\\\\"display\\\\\\\";class kG{constructor(t){this.node=t,this._children_uuids_dict=new Map,this._children_length=0,this._sop_group=this._create_sop_group()}_create_sop_group(){const t=new Fn.a;return t.matrixAutoUpdate=!1,t}sopGroup(){return this._sop_group}set_sop_group_name(){this._sop_group.name=`${this.node.name()}:sop_group`}displayNodeControllerCallbacks(){return{onDisplayNodeRemove:()=>{this.remove_children()},onDisplayNodeSet:()=>{setTimeout((()=>{this.request_display_node_container()}),0)},onDisplayNodeUpdate:()=>{this.request_display_node_container()}}}initializeNode(){var t;this.node.object.add(this.sopGroup()),this.node.nameController.add_post_set_fullPath_hook(this.set_sop_group_name.bind(this)),this._create_sop_group();const e=null===(t=this.node.flags)||void 0===t?void 0:t.display;e&&e.onUpdate((()=>{this._updateSopGroupHierarchy(),e.active()&&this.request_display_node_container()}))}_updateSopGroupHierarchy(){var t;if(null===(t=this.node.flags)||void 0===t?void 0:t.display){const t=this.sopGroup();this.usedInScene()?(t.visible=!0,this.node.object.add(t),t.updateMatrix()):(t.visible=!1,this.node.object.remove(t))}}usedInScene(){var t,e;const n=this.node.params.has(zG),i=this.node.params.boolean(zG),s=this.node.usedInScene(),r=(null===(e=null===(t=this.node.flags)||void 0===t?void 0:t.display)||void 0===e?void 0:e.active())||!1;return s&&r&&(!n||i)}async request_display_node_container(){this.node.scene().loadingController.loaded()&&this.usedInScene()&&await this._set_content_under_sop_group()}remove_children(){if(0==this._sop_group.children.length)return;let t;for(;t=this._sop_group.children[0];)this._sop_group.remove(t);this._children_uuids_dict.clear(),this._children_length=0}async _set_content_under_sop_group(){var t;const e=this.node.displayNodeController.displayNode();if(e&&(null===(t=e.parent())||void 0===t?void 0:t.graphNodeId())==this.node.graphNodeId()){const t=(await e.compute()).coreContent();if(t){const e=t.objects();let n=e.length!=this._children_length;if(!n)for(let t of e)this._children_uuids_dict.get(t.uuid)||(n=!0);if(n){this.remove_children();for(let t of e)this._sop_group.add(t),t.updateMatrix(),this._children_uuids_dict.set(t.uuid,!0);this._children_length=e.length}return}}this.remove_children()}}class UG extends(wU(ua)){constructor(){super(...arguments),this.display=ha.BOOLEAN(1),this.renderOrder=ha.INTEGER(0,{range:[0,10],rangeLocked:[!0,!1]})}}const GG=new UG;class VG extends cU{constructor(){super(...arguments),this.paramsConfig=GG,this.hierarchyController=new MU(this),this.transformController=new AU(this),this.flags=new Di(this),this.childrenDisplayController=new kG(this),this.displayNodeController=new Fm(this,this.childrenDisplayController.displayNodeControllerCallbacks()),this._children_controller_context=ts.SOP,this._onChildAddBound=this._onChildAdd.bind(this)}static type(){return Ig.GEO}createObject(){const t=new Fn.a;return t.matrixAutoUpdate=!1,t}initializeNode(){this.lifecycle.add_on_child_add_hook(this._onChildAddBound),this.hierarchyController.initializeNode(),this.transformController.initializeNode(),this.childrenDisplayController.initializeNode()}isDisplayNodeCooking(){if(this.flags.display.active()){const t=this.displayNodeController.displayNode();return!!t&&t.isDirty()}return!1}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}_onChildAdd(t){var e,n;this.scene().loadingController.loaded()&&1==this.children().length&&(null===(n=null===(e=t.flags)||void 0===e?void 0:e.display)||void 0===n||n.set(!0))}cook(){this.transformController.update(),this.object.visible=this.pv.display,this.object.renderOrder=this.pv.renderOrder,this.cookController.endCook()}}class HG extends(wU(ua)){}const jG=new HG;class WG extends cU{constructor(){super(...arguments),this.paramsConfig=jG,this.hierarchyController=new MU(this),this.transformController=new AU(this),this.flags=new Di(this),this._helper=new TG(1)}static type(){return\\\\\\\"null\\\\\\\"}createObject(){const t=new Fn.a;return t.matrixAutoUpdate=!1,t}initializeNode(){this.hierarchyController.initializeNode(),this.transformController.initializeNode(),this._updateHelperHierarchy(),this._helper.matrixAutoUpdate=!1,this.flags.display.onUpdate((()=>{this._updateHelperHierarchy()}))}_updateHelperHierarchy(){this.flags.display.active()?(this.object.add(this._helper),this._helper.updateMatrix()):this.object.remove(this._helper)}cook(){this.transformController.update(),this.cookController.endCook()}}const qG=new class extends ua{constructor(){super(...arguments),this.center=ha.VECTOR3([0,0,0]),this.longitude=ha.FLOAT(0,{range:[0,360]}),this.latitude=ha.FLOAT(0,{range:[-180,180]}),this.depth=ha.FLOAT(1,{range:[0,10]})}},XG=\\\\\\\"_cook_main_without_inputs_when_dirty\\\\\\\",YG=new p.a(0,1,0),$G=new p.a(-1,0,0);class JG extends cU{constructor(){super(...arguments),this.paramsConfig=qG,this.hierarchyController=new MU(this),this.flags=new Di(this),this._helper=new TG(1),this._cook_main_without_inputs_when_dirty_bound=this._cook_main_without_inputs_when_dirty.bind(this),this._centerMatrix=new A.a,this._longitudeMatrix=new A.a,this._latitudeMatrix=new A.a,this._depthMatrix=new A.a,this._fullMatrix=new A.a,this._decomposed={t:new p.a,q:new hh.a,s:new p.a}}static type(){return\\\\\\\"polarTransform\\\\\\\"}createObject(){const t=new Fn.a;return t.matrixAutoUpdate=!1,t}initializeNode(){this.hierarchyController.initializeNode(),this.dirtyController.hasHook(XG)||this.dirtyController.addPostDirtyHook(XG,this._cook_main_without_inputs_when_dirty_bound),this._updateHelperHierarchy(),this._helper.matrixAutoUpdate=!1,this.flags.display.onUpdate((()=>{this._updateHelperHierarchy()}))}_updateHelperHierarchy(){this.flags.display.active()?(this.object.add(this._helper),this._helper.updateMatrix()):this.object.remove(this._helper)}async _cook_main_without_inputs_when_dirty(){await this.cookController.cookMainWithoutInputs()}cook(){const t=this.object;this._centerMatrix.identity(),this._longitudeMatrix.identity(),this._latitudeMatrix.identity(),this._depthMatrix.identity(),this._centerMatrix.makeTranslation(this.pv.center.x,this.pv.center.y,this.pv.center.z),this._longitudeMatrix.makeRotationAxis(YG,Object(On.e)(this.pv.longitude)),this._latitudeMatrix.makeRotationAxis($G,Object(On.e)(this.pv.latitude)),this._depthMatrix.makeTranslation(0,0,this.pv.depth),this._fullMatrix.copy(this._centerMatrix).multiply(this._longitudeMatrix).multiply(this._latitudeMatrix).multiply(this._depthMatrix),this._fullMatrix.decompose(this._decomposed.t,this._decomposed.q,this._decomposed.s),t.position.copy(this._decomposed.t),t.quaternion.copy(this._decomposed.q),t.scale.copy(this._decomposed.s),t.updateMatrix(),this.cookController.endCook()}}class ZG{constructor(t){this._scene=t,this._data={}}data(t){this._scene.nodesController.reset_node_context_signatures();const e=rV.dispatch_node(this._scene.root()),n=e.data(),i=e.ui_data();return this._data={properties:{frame:this._scene.frame()||Nl.START_FRAME,maxFrame:this._scene.maxFrame(),maxFrameLocked:this._scene.timeController.maxFrameLocked(),realtimeState:this._scene.timeController.realtimeState(),mainCameraNodePath:this._scene.camerasController.mainCameraNodePath(),versions:t},root:n,ui:i},this._data}static sanitize_string(t){return t=t.replace(/'/g,\\\\\\\"'\\\\\\\"),t=ss.escapeLineBreaks(t)}}class KG{constructor(t){this._node=t}data(t={}){var e,n,i,s,r,o,a;this.is_root()||this._node.scene().nodesController.register_node_context_signature(this._node),this._data={type:this._node.type()};const l=this.nodes_data(t);Object.keys(l).length>0&&(this._data.nodes=l);const c=this.params_data();if(Object.keys(c).length>0&&(this._data.params=c),!this.is_root()){this._node.io.inputs.maxInputsCountOverriden()&&(this._data.maxInputsCount=this._node.io.inputs.maxInputsCount());const t=this.inputs_data();t.length>0&&(this._data.inputs=t);const e=this.connection_points_data();e&&(this._data.connection_points=e)}if(this._node.flags){const t={};(this._node.flags.hasBypass()||this._node.flags.hasDisplay()||this._node.flags.hasOptimize())&&(this._node.flags.hasBypass()&&(null===(e=this._node.flags.bypass)||void 0===e?void 0:e.active())&&(t.bypass=this._node.flags.bypass.active()),this._node.flags.hasDisplay()&&(!(null===(n=this._node.flags.display)||void 0===n?void 0:n.active())&&(null===(i=this._node.parent())||void 0===i?void 0:i.displayNodeController)||(t.display=null===(s=this._node.flags.display)||void 0===s?void 0:s.active())),this._node.flags.hasOptimize()&&(null===(r=this._node.flags.optimize)||void 0===r?void 0:r.active())&&(t.optimize=null===(o=this._node.flags.optimize)||void 0===o?void 0:o.active())),Object.keys(t).length>0&&(this._data.flags=t)}if(this._node.childrenAllowed()){const t=null===(a=this._node.childrenController)||void 0===a?void 0:a.selection;if(t&&this._node.children().length>0){const e=[],n={};for(let e of t.nodes())n[e.graphNodeId()]=!0;for(let t of this._node.children())t.graphNodeId()in n&&e.push(t);const i=e.map((t=>t.name()));i.length>0&&(this._data.selection=i)}}if(this._node.io.inputs.overrideClonedStateAllowed()){const t=this._node.io.inputs.clonedStateOverriden();t&&(this._data.cloned_state_overriden=t)}if(this._node.persisted_config){const t=this._node.persisted_config.toJSON();t&&(this._data.persisted_config=t)}return this.add_custom(),this._data}ui_data(t={}){const e=this.ui_data_without_children(),n=this._node.children();return n.length>0&&(e.nodes={},n.forEach((n=>{const i=rV.dispatch_node(n);e.nodes[n.name()]=i.ui_data(t)}))),e}ui_data_without_children(){const t={};if(!this.is_root()){const e=this._node.uiData;t.pos=e.position().toArray();const n=e.comment();n&&(t.comment=ZG.sanitize_string(n))}return t}is_root(){return null===this._node.parent()&&this._node.graphNodeId()==this._node.root().graphNodeId()}inputs_data(){const t=[];return this._node.io.inputs.inputs().forEach(((e,n)=>{var i;if(e){const s=this._node.io.connections.inputConnection(n);if(this._node.io.inputs.hasNamedInputs()){const r=s.output_index,o=null===(i=e.io.outputs.namedOutputConnectionPoints()[r])||void 0===i?void 0:i.name();o&&(t[n]={index:n,node:e.name(),output:o})}else t[n]=e.name()}})),t}connection_points_data(){if(this._node.io.has_connection_points_controller&&this._node.io.connection_points.initialized()&&(this._node.io.inputs.hasNamedInputs()||this._node.io.outputs.hasNamedOutputs())){const t={};if(this._node.io.inputs.hasNamedInputs()){t.in=[];for(let e of this._node.io.inputs.namedInputConnectionPoints())e&&t.in.push(e.toJSON())}if(this._node.io.outputs.hasNamedOutputs()){t.out=[];for(let e of this._node.io.outputs.namedOutputConnectionPoints())e&&t.out.push(e.toJSON())}return t}}params_data(){const t={};for(let e of this._node.params.names){const n=this._node.params.get(e);if(n&&!n.parent_param){const e=rV.dispatch_param(n);if(e.required()){const i=e.data();t[n.name()]=i}}}return t}nodes_data(t={}){const e={};for(let n of this._node.children()){const i=rV.dispatch_node(n);e[n.name()]=i.data(t)}return e}add_custom(){}}class QG{constructor(t){this._param=t,this._complex_data={}}required(){const t=this._param.options.isSpare()&&!this._param.parent_param,e=!this._param.isDefault();return t||e||this._param.options.hasOptionsOverridden()}data(){if(this._param.parent_param)throw console.warn(\\\\\\\"no component should be saved\\\\\\\"),\\\\\\\"no component should be saved\\\\\\\";return this._require_data_complex()?this._data_complex():this._data_simple()}_data_simple(){return this._param.rawInputSerialized()}_data_complex(){if(this._complex_data={},this._param.options.isSpare()&&!this._param.parent_param&&(this._complex_data.type=this._param.type(),this._complex_data.default_value=this._param.defaultValueSerialized(),this._complex_data.options=this._param.options.current()),this._param.isDefault()||(this._complex_data.raw_input=this._param.rawInputSerialized()),this._param.options.hasOptionsOverridden()){const t={},e=this._param.options.overriddenOptions();for(let n of Object.keys(e)){const i=e[n];m.isString(i)||m.isNumber(i)?t[n]=i:t[n]=JSON.stringify(i)}this._complex_data.overriden_options=t}return this._complex_data}_require_data_complex(){return!!this._param.options.isSpare()||!!this._param.options.hasOptionsOverridden()}add_main(){}}class tV extends QG{add_main(){if(!this._require_data_complex())return this._param.rawInputSerialized();this._complex_data.raw_input=this._param.rawInputSerialized()}}class eV extends QG{add_main(){let t=this._param.rawInput();if(t=ZG.sanitize_string(t),!this._require_data_complex())return t;this._complex_data.raw_input=t}}class nV extends QG{add_main(){let t=this._param.rawInput();if(t=ZG.sanitize_string(t),!this._require_data_complex())return t;this._complex_data.raw_input=t}}class iV extends QG{add_main(){if(!this._require_data_complex())return this._param.rawInputSerialized();this._complex_data.raw_input=this._param.rawInputSerialized()}}class sV extends KG{nodes_data(t={}){return t.showPolyNodesData?super.nodes_data(t):{}}ui_data(t={}){return t.showPolyNodesData?super.ui_data(t):this.ui_data_without_children()}}class rV{static dispatch_node(t){return t.polyNodeController?new sV(t):new KG(t)}static dispatch_param(t){return t instanceof ro?new tV(t):t instanceof fo?new eV(t):t instanceof Mo?new nV(t):t instanceof Ao?new iV(t):new QG(t)}}class oV{constructor(){this._objects=[],this._objects_with_geo=[],this.touch()}timestamp(){return this._timestamp}touch(){const t=li.performance.performanceManager();this._timestamp=t.now(),this.reset()}reset(){this._bounding_box=void 0,this._core_geometries=void 0,this._core_objects=void 0}clone(){const t=new oV;if(this._objects){const e=[];for(let t of this._objects)e.push(br.clone(t));t.setObjects(e)}return t}setObjects(t){this._objects=t,this._objects_with_geo=t.filter((t=>null!=t.geometry)),this.touch()}objects(){return this._objects}objectsWithGeo(){return this._objects_with_geo}coreObjects(){return this._core_objects=this._core_objects||this._create_core_objects()}_create_core_objects(){return this._objects?this._objects.map(((t,e)=>new br(t,e))):[]}objectsData(){return this._objects?this._objects.map((t=>this._objectData(t))):[]}_objectData(t){let e=0;return t.geometry&&(e=fr.pointsCount(t.geometry)),{type:Os(t.constructor),name:t.name,children_count:t.children.length,points_count:e}}geometries(){const t=[];for(let e of this.coreObjects()){const n=e.object().geometry;n&&t.push(n)}return t}coreGeometries(){return this._core_geometries=this._core_geometries||this._createCoreGeometries()}_createCoreGeometries(){const t=[];for(let e of this.geometries())t.push(new fr(e));return t}static geometryFromObject(t){return t.isMesh||t.isLine||t.isPoints?t.geometry:null}faces(){const t=[];for(let e of this.objectsWithGeo())if(e.geometry){const n=new fr(e.geometry).faces();for(let i of n)i.applyMatrix4(e.matrix),t.push(i)}return t}points(){return this.coreGeometries().map((t=>t.points())).flat()}pointsCount(){return f.sum(this.coreGeometries().map((t=>t.pointsCount())))}totalPointsCount(){if(this._objects){let t=0;for(let e of this._objects)e.traverse((e=>{const n=e.geometry;n&&(t+=fr.pointsCount(n))}));return t}return 0}pointsFromGroup(t){if(t){const e=ss.indices(t),n=this.points();return f.compact(e.map((t=>n[t])))}return this.points()}static _fromObjects(t){const e=new oV;return e.setObjects(t),e}objectsFromGroup(t){return this.coreObjectsFromGroup(t).map((t=>t.object()))}coreObjectsFromGroup(t){if(\\\\\\\"\\\\\\\"!==(t=t.trim())){const e=parseInt(t);return m.isNaN(e)?this.coreObjects().filter((e=>ss.matchMask(t,e.name()))):f.compact([this.coreObjects()[e]])}return this.coreObjects()}boundingBox(t=!1){return this._bounding_box=t?this._computeBoundingBox():this._bounding_box||this._computeBoundingBox()}center(){const t=new p.a;return this.boundingBox().getCenter(t),t}size(){const t=new p.a;return this.boundingBox().getSize(t),t}_computeBoundingBox(){let t;if(this._objects)for(let e of this._objects){const n=e.geometry;n&&(n.computeBoundingBox(),t?t.expandByObject(e):n.boundingBox&&(t=n.boundingBox.clone()))}return t=t||new Ry.a(new p.a(-1,-1,-1),new p.a(1,1,1)),t}computeVertexNormals(){for(let t of this.coreObjects())t.computeVertexNormals()}hasAttrib(t){let e;return null!=(e=this.coreGeometries()[0])&&e.hasAttrib(t)}attribType(t){const e=this.coreGeometries()[0];return null!=e?e.attribType(t):null}objectAttribType(t){const e=this.coreObjects()[0];return null!=e?e.attribType(t):null}renameAttrib(t,e,n){switch(n){case js.ATTRIB_CLASS.VERTEX:if(this.hasAttrib(t)&&this._objects)for(let n of this._objects)n.traverse((n=>{const i=oV.geometryFromObject(n);if(i){new fr(i).renameAttrib(t,e)}}));break;case js.ATTRIB_CLASS.OBJECT:if(this.hasAttrib(t)&&this._objects)for(let n of this._objects)n.traverse((n=>{new br(n,0).renameAttrib(t,e)}))}}attribNames(){let t;return null!=(t=this.coreGeometries()[0])?t.attribNames():[]}objectAttribNames(){let t;return null!=(t=this.coreObjects()[0])?t.attribNames():[]}attribNamesMatchingMask(t){const e=ss.attribNames(t),n=[];for(let t of this.attribNames())for(let i of e)if(ss.matchMask(t,i))n.push(t);else{t==Xs.remapName(i)&&n.push(t)}return f.uniq(n)}attribSizes(){let t;return null!=(t=this.coreGeometries()[0])?t.attribSizes():{}}objectAttribSizes(){let t;return null!=(t=this.coreObjects()[0])?t.attribSizes():{}}attribSize(t){let e;return null!=(e=this.coreGeometries()[0])?e.attribSize(t):0}addNumericVertexAttrib(t,e,n){null==n&&(n=Xs.default_value(e));for(let i of this.coreGeometries())i.addNumericAttrib(t,e,n)}static clone(t){const e=new Fn.a;return t.children.forEach((t=>{const n=br.clone(t);e.add(n)})),e}}class aV extends zl{static context(){return ts.SOP}cook(t,e){}createCoreGroupFromObjects(t){const e=new oV;return e.setObjects(t),e}createCoreGroupFromGeometry(t,e=Ns.MESH){const n=aV.createObject(t,e);return this.createCoreGroupFromObjects([n])}createObject(t,e,n){return aV.createObject(t,e,n)}static createObject(t,e,n){this.createIndexIfNone(t);const i=new(0,Ls[e])(t,n=n||js.MATERIALS[e].clone());return i.castShadow=!0,i.receiveShadow=!0,i.frustumCulled=!1,i.matrixAutoUpdate=!1,i}createIndexIfNone(t){aV.createIndexIfNone(t)}static createIndexIfNone(t){pr.createIndexIfNone(t)}}var lV;!function(t){t.FROM_SET_CORE_GROUP=\\\\\\\"from set_core_group\\\\\\\",t.FROM_SET_GROUP=\\\\\\\"from set_group\\\\\\\",t.FROM_SET_OBJECTS=\\\\\\\"from set_objects\\\\\\\",t.FROM_SET_OBJECT=\\\\\\\"from set_object\\\\\\\",t.FROM_SET_GEOMETRIES=\\\\\\\"from set_geometries\\\\\\\",t.FROM_SET_GEOMETRY=\\\\\\\"from set_geometry\\\\\\\"}(lV||(lV={}));const cV=\\\\\\\"input geometry\\\\\\\",hV=[cV,cV,cV,cV];class uV extends aa{constructor(){super(...arguments),this.flags=new Ui(this)}static context(){return ts.SOP}static displayedInputNames(){return hV}initializeBaseNode(){this.flags.display.set(!1),this.flags.display.onUpdate((()=>{if(this.flags.display.active()){const t=this.parent();t&&t.displayNodeController&&t.displayNodeController.setDisplayNode(this)}})),this.io.outputs.setHasOneOutput()}setCoreGroup(t){this._setContainer(t,lV.FROM_SET_CORE_GROUP)}setObject(t){this._setContainerObjects([t],lV.FROM_SET_OBJECT)}setObjects(t){this._setContainerObjects(t,lV.FROM_SET_OBJECTS)}setGeometry(t,e=Ns.MESH){const n=this.createObject(t,e);this._setContainerObjects([n],lV.FROM_SET_GEOMETRY)}setGeometries(t,e=Ns.MESH){const n=[];let i;for(let s of t)i=this.createObject(s,e),n.push(i);this._setContainerObjects(n,lV.FROM_SET_GEOMETRIES)}_setContainerObjects(t,e){const n=this.containerController.container().coreContent()||new oV;n.setObjects(t),n.touch(),this._setContainer(n)}static createObject(t,e,n){return aV.createObject(t,e,n)}createObject(t,e,n){return uV.createObject(t,e,n)}static createIndexIfNone(t){aV.createIndexIfNone(t)}_createIndexIfNone(t){uV.createIndexIfNone(t)}}const dV=new class extends ua{};class pV extends uV{constructor(){super(...arguments),this.paramsConfig=dV}static type(){return ns.OUTPUT}initializeNode(){this.io.inputs.setCount(1),this.io.outputs.setHasNoOutput(),this.io.inputs.initInputsClonedState(Qi.NEVER)}cook(t){this.setCoreGroup(t[0])}}class _V extends uV{constructor(){super(...arguments),this.childrenDisplayController=new fV(this),this.displayNodeController=new Fm(this,this.childrenDisplayController.displayNodeControllerCallbacks()),this._children_controller_context=ts.SOP}initializeBaseNode(){super.initializeBaseNode(),this.childrenDisplayController.initializeNode(),this.cookController.disallowInputsEvaluation()}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}async cook(t){const e=this.childrenDisplayController.output_node();if(e){const t=(await e.compute()).coreContent();t?this.setCoreGroup(t):e.states.error.active()?this.states.error.set(e.states.error.message()):this.setObjects([])}else this.states.error.set(\\\\\\\"no output node found inside subnet\\\\\\\")}}const mV={dependsOnDisplayNode:!0};class fV{constructor(t,e=mV){this.node=t,this.options=e,this._output_node_needs_update=!0}dispose(){var t;null===(t=this._graph_node)||void 0===t||t.dispose()}displayNodeControllerCallbacks(){return{onDisplayNodeRemove:()=>{this.node.setDirty()},onDisplayNodeSet:()=>{this.node.setDirty()},onDisplayNodeUpdate:()=>{this.node.setDirty()}}}output_node(){return this._output_node_needs_update&&this._update_output_node(),this._output_node}initializeNode(){var t;const e=null===(t=this.node.flags)||void 0===t?void 0:t.display;e&&e.onUpdate((()=>{e.active()&&this.node.setDirty()})),this.node.lifecycle.add_on_child_add_hook((()=>{this._output_node_needs_update=!0,this.node.setDirty()})),this.node.lifecycle.add_on_child_remove_hook((()=>{this._output_node_needs_update=!0,this.node.setDirty()}))}_update_output_node(){const t=this.node.nodesByType(pV.type())[0];null!=this._output_node&&null!=t&&this._output_node.graphNodeId()==t.graphNodeId()||(this._graph_node&&this._output_node&&this._graph_node.removeGraphInput(this._output_node),this._output_node=t,this._output_node&&this.options.dependsOnDisplayNode&&(this._graph_node=this._graph_node||this._create_graph_node(),this._graph_node.addGraphInput(this._output_node)))}_create_graph_node(){const t=new Mi(this.node.scene(),\\\\\\\"subnetChildrenDisplayController\\\\\\\");return t.addPostDirtyHook(\\\\\\\"subnetChildrenDisplayController\\\\\\\",(()=>{this.node.setDirty()})),t}}function gV(t,e){const n=new class extends ua{constructor(){super(...arguments),this.template=ha.OPERATOR_PATH(\\\\\\\"../template\\\\\\\"),this.debug=ha.BUTTON(null,{callback:t=>{i.PARAM_CALLBACK_debug(t)}})}};class i extends _V{constructor(){super(...arguments),this.paramsConfig=n,this.polyNodeController=new xV(this,e)}static type(){return t}static PARAM_CALLBACK_debug(t){t._debug()}_debug(){this.polyNodeController.debug(this.p.template)}}return i}const vV=gV(\\\\\\\"poly\\\\\\\",{nodeContext:ts.SOP,inputs:[0,4]});class yV extends vV{}class xV{constructor(t,e){this.node=t,this._definition=e}initializeNode(){this.init_inputs(),this.node.params.onParamsCreated(\\\\\\\"poly_node_init\\\\\\\",(()=>{this.create_params_from_definition()})),this.node.lifecycle.add_on_create_hook((()=>{this.create_params_from_definition(),this.createChildNodesFromDefinition()}))}init_inputs(){const t=this._definition.inputs;t&&this.node.io.inputs.setCount(t[0],t[1])}create_params_from_definition(){const t=this._definition.params;if(t){for(let e of t)e.options=e.options||{},e.options.spare=!0;this.node.params.updateParams({toAdd:t})}}createChildNodesFromDefinition(){const t=this._definition.nodes;if(!t)return;const e=this.node.scene().loadingController.loaded();e&&this.node.scene().loadingController.markAsLoading();const n=new Jl({}),i=new Vl(this.node);i.create_nodes(n,t);const s=this._definition.ui;s&&i.process_nodes_ui_data(n,s),e&&this.node.scene().loadingController.markAsLoaded()}debug(t){const e=t.found_node();if(e){const t=rV.dispatch_node(e),n=t.data({showPolyNodesData:!0}),i=t.ui_data({showPolyNodesData:!0}),s={nodeContext:e.context(),inputs:[0,0],params:[],nodes:n.nodes,ui:i.nodes};console.log(JSON.stringify(s))}}static createNodeClass(t,e,n){switch(e){case ts.SOP:return gV(t,n);case ts.OBJ:return bV(t,n)}}}function bV(t,e){const n=new class extends ua{constructor(){super(...arguments),this.display=ha.BOOLEAN(1),this.template=ha.OPERATOR_PATH(\\\\\\\"../template\\\\\\\"),this.debug=ha.BUTTON(null,{callback:t=>{i.PARAM_CALLBACK_debug(t)}})}};class i extends cU{constructor(){super(...arguments),this.paramsConfig=n,this.hierarchyController=new MU(this),this.flags=new Di(this),this.childrenDisplayController=new kG(this),this.displayNodeController=new Fm(this,this.childrenDisplayController.displayNodeControllerCallbacks()),this._children_controller_context=ts.SOP,this.polyNodeController=new xV(this,e)}static type(){return t}createObject(){const t=new Fn.a;return t.matrixAutoUpdate=!1,t}initializeNode(){this.hierarchyController.initializeNode(),this.childrenDisplayController.initializeNode()}isDisplayNodeCooking(){if(this.flags.display.active()){const t=this.displayNodeController.displayNode();return!!t&&t.isDirty()}return!1}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}cook(){this.object.visible=this.pv.display,this.cookController.endCook()}static PARAM_CALLBACK_debug(t){t._debug()}_debug(){this.polyNodeController.debug(this.p.template)}}return i}const wV=bV(\\\\\\\"poly\\\\\\\",{nodeContext:ts.OBJ});class TV extends wV{}class AV extends Q.a{constructor(t){super(),this.type=\\\\\\\"Audio\\\\\\\",this.listener=t,this.context=t.context,this.gain=this.context.createGain(),this.gain.connect(t.getInput()),this.autoplay=!1,this.buffer=null,this.detune=0,this.loop=!1,this.loopStart=0,this.loopEnd=0,this.offset=0,this.duration=void 0,this.playbackRate=1,this.isPlaying=!1,this.hasPlaybackControl=!0,this.source=null,this.sourceType=\\\\\\\"empty\\\\\\\",this._startedAt=0,this._progress=0,this._connected=!1,this.filters=[]}getOutput(){return this.gain}setNodeSource(t){return this.hasPlaybackControl=!1,this.sourceType=\\\\\\\"audioNode\\\\\\\",this.source=t,this.connect(),this}setMediaElementSource(t){return this.hasPlaybackControl=!1,this.sourceType=\\\\\\\"mediaNode\\\\\\\",this.source=this.context.createMediaElementSource(t),this.connect(),this}setMediaStreamSource(t){return this.hasPlaybackControl=!1,this.sourceType=\\\\\\\"mediaStreamNode\\\\\\\",this.source=this.context.createMediaStreamSource(t),this.connect(),this}setBuffer(t){return this.buffer=t,this.sourceType=\\\\\\\"buffer\\\\\\\",this.autoplay&&this.play(),this}play(t=0){if(!0===this.isPlaying)return void console.warn(\\\\\\\"THREE.Audio: Audio is already playing.\\\\\\\");if(!1===this.hasPlaybackControl)return void console.warn(\\\\\\\"THREE.Audio: this Audio has no playback control.\\\\\\\");this._startedAt=this.context.currentTime+t;const e=this.context.createBufferSource();return e.buffer=this.buffer,e.loop=this.loop,e.loopStart=this.loopStart,e.loopEnd=this.loopEnd,e.onended=this.onEnded.bind(this),e.start(this._startedAt,this._progress+this.offset,this.duration),this.isPlaying=!0,this.source=e,this.setDetune(this.detune),this.setPlaybackRate(this.playbackRate),this.connect()}pause(){if(!1!==this.hasPlaybackControl)return!0===this.isPlaying&&(this._progress+=Math.max(this.context.currentTime-this._startedAt,0)*this.playbackRate,!0===this.loop&&(this._progress=this._progress%(this.duration||this.buffer.duration)),this.source.stop(),this.source.onended=null,this.isPlaying=!1),this;console.warn(\\\\\\\"THREE.Audio: this Audio has no playback control.\\\\\\\")}stop(){if(!1!==this.hasPlaybackControl)return this._progress=0,this.source.stop(),this.source.onended=null,this.isPlaying=!1,this;console.warn(\\\\\\\"THREE.Audio: this Audio has no playback control.\\\\\\\")}connect(){if(this.filters.length>0){this.source.connect(this.filters[0]);for(let t=1,e=this.filters.length;t0){this.source.disconnect(this.filters[0]);for(let t=1,e=this.filters.length;t{t.load(e,(function(t){n(t)}))}))}}var IV;!function(t){t.LINEAR=\\\\\\\"linear\\\\\\\",t.INVERSE=\\\\\\\"inverse\\\\\\\",t.EXPONENTIAL=\\\\\\\"exponential\\\\\\\"}(IV||(IV={}));const FV=[IV.LINEAR,IV.INVERSE,IV.EXPONENTIAL];class DV extends(wU(ua)){constructor(){super(...arguments),this.audio=ha.FOLDER(),this.listener=ha.NODE_PATH(\\\\\\\"\\\\\\\",{nodeSelection:{context:ts.OBJ,types:[Ig.AUDIO_LISTENER]}}),this.url=ha.STRING(\\\\\\\"\\\\\\\",{fileBrowse:{type:[Rr.AUDIO]}}),this.volume=ha.FLOAT(1),this.loop=ha.BOOLEAN(1,{separatorBefore:!0}),this.loopStart=ha.FLOAT(0,{visibleIf:{loop:1}}),this.loopEnd=ha.FLOAT(0,{visibleIf:{loop:1},separatorAfter:!0}),this.refDistance=ha.FLOAT(10,{range:[0,10],rangeLocked:[!0,!1]}),this.rolloffFactor=ha.FLOAT(10,{range:[0,10],rangeLocked:[!0,!1]}),this.maxDistance=ha.FLOAT(100,{range:[.001,100],rangeLocked:[!0,!1]}),this.distanceModel=ha.INTEGER(FV.indexOf(IV.LINEAR),{menu:{entries:FV.map(((t,e)=>({name:t,value:e})))}}),this.coneInnerAngle=ha.FLOAT(180,{range:[0,360],rangeLocked:[!0,!0]}),this.coneOuterAngle=ha.FLOAT(230,{range:[0,360],rangeLocked:[!0,!0]}),this.coneOuterGain=ha.FLOAT(.1,{range:[0,1],rangeLocked:[!0,!0]}),this.autoplay=ha.BOOLEAN(1),this.showHelper=ha.BOOLEAN(0),this.helperSize=ha.FLOAT(1,{range:[0,10],rangeLocked:[!0,!1],visibleIf:{showHelper:!0}}),this.play=ha.BUTTON(null,{callback:t=>{zV.PARAM_CALLBACK_play(t)}}),this.pause=ha.BUTTON(null,{callback:t=>{zV.PARAM_CALLBACK_pause(t)}})}}const BV=new DV;class zV extends cU{constructor(){super(...arguments),this.paramsConfig=BV,this.hierarchyController=new MU(this),this.transformController=new AU(this),this.flags=new Di(this)}static type(){return Ig.POSITIONAL_AUDIO}createObject(){const t=new Fn.a;return t.matrixAutoUpdate=!1,t}initializeNode(){this.hierarchyController.initializeNode(),this.transformController.initializeNode(),this._updateHelperHierarchy(),this.flags.display.onUpdate((()=>{this._updateHelperHierarchy()})),this.scene().dispatchController.onAddListener((()=>{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{this.params.label.init([this.p.url],(()=>{const t=this.p.url.rawInput();if(t){const e=t.split(\\\\\\\"/\\\\\\\");return e[e.length-1]}return\\\\\\\"\\\\\\\"}))}))}))}_updateHelperHierarchy(){this._helper&&(this.flags.display.active()?this.object.add(this._helper):this.object.remove(this._helper))}cook(){this.transformController.update(),this._updatePositionalAudio(),this.cookController.endCook()}async _updatePositionalAudio(){this.p.listener.isDirty()&&await this.p.listener.compute();const t=this.pv.url;if(this._loadedUrl!=t)try{await this._createPositionalAudio()}catch(t){this.states.error.set(`error when creating audio: ${t}`)}this._positionalAudio&&(this._positionalAudio.setVolume(this.pv.volume),this._positionalAudio.setLoop(this.pv.loop),this._positionalAudio.setLoopStart(this.pv.loopStart),this._positionalAudio.setLoopEnd(this.pv.loopEnd),this._positionalAudio.setRefDistance(this.pv.refDistance),this._positionalAudio.setRolloffFactor(this.pv.rolloffFactor),this._positionalAudio.setMaxDistance(this.pv.maxDistance),this._positionalAudio.setDistanceModel(FV[this.pv.distanceModel]),this._positionalAudio.setDirectionalCone(this.pv.coneInnerAngle,this.pv.coneOuterAngle,this.pv.coneOuterGain),this.pv.showHelper&&(this._helper=this._helper||this._createHelper(this._positionalAudio),this.object.add(this._helper)),this._helper&&(this._helper.visible=this.pv.showHelper,this._helper.range=this.pv.helperSize,this._helper.update()))}_createHelper(t){const e=new LV(t);return e.matrixAutoUpdate=!1,e}async _createPositionalAudio(){const t=this.pv.listener.nodeWithContext(ts.OBJ);if(!t)return;const e=t.object;this._positionalAudio&&(this._positionalAudio.source&&(this._positionalAudio.stop(),this._positionalAudio.disconnect()),this.object.remove(this._positionalAudio),this._positionalAudio=void 0),this._helper&&(this._helper.dispose(),this._helper=void 0),this._positionalAudio=new NV(e),this._positionalAudio.matrixAutoUpdate=!1;const n=new RV(this.pv.url,this.scene(),this),i=await n.load();this._loadedUrl=this.pv.url,this._positionalAudio.autoplay=this.pv.autoplay,this._positionalAudio.setBuffer(i),this.object.add(this._positionalAudio)}isPlaying(){return!!this._positionalAudio&&this._positionalAudio.isPlaying}static PARAM_CALLBACK_play(t){t.PARAM_CALLBACK_play()}static PARAM_CALLBACK_pause(t){t.PARAM_CALLBACK_pause()}PARAM_CALLBACK_play(){this._positionalAudio&&(this.isPlaying()||this._positionalAudio.play())}PARAM_CALLBACK_pause(){this._positionalAudio&&this.isPlaying()&&this._positionalAudio.pause()}}var kV;!function(t){t.ON_RENDER=\\\\\\\"On Every Render\\\\\\\",t.MANUAL=\\\\\\\"Manual\\\\\\\"}(kV||(kV={}));const UV=[kV.ON_RENDER,kV.MANUAL];const GV=new class extends ua{constructor(){super(...arguments),this.object=ha.OPERATOR_PATH(\\\\\\\"\\\\\\\",{nodeSelection:{context:ts.OBJ},dependentOnFoundNode:!1,computeOnDirty:!0,callback:t=>{VV.PARAM_CALLBACK_update_resolved_object(t)}}),this.pointIndex=ha.INTEGER(0,{range:[0,100]}),this.updateMode=ha.INTEGER(UV.indexOf(kV.ON_RENDER),{callback:t=>{VV.PARAM_CALLBACK_update_updateMode(t)},menu:{entries:UV.map(((t,e)=>({name:t,value:e})))}}),this.update=ha.BUTTON(null,{callback:t=>{VV.PARAM_CALLBACK_update(t)},visibleIf:{updateMode:UV.indexOf(kV.MANUAL)}})}};class VV extends cU{constructor(){super(...arguments),this.paramsConfig=GV,this.hierarchyController=new MU(this),this.flags=new Di(this),this._helper=new TG(1),this._found_point_post=new p.a,this._on_object_before_render_bound=this._update.bind(this)}static type(){return\\\\\\\"rivet\\\\\\\"}createObject(){const t=new B.a;return t.matrixAutoUpdate=!1,t}initializeNode(){this.hierarchyController.initializeNode(),this.addPostDirtyHook(\\\\\\\"rivet_on_dirty\\\\\\\",(()=>{this.cookController.cookMainWithoutInputs()})),this._updateHelperHierarchy(),this.flags.display.onUpdate((()=>{this._updateHelperHierarchy()}))}_updateHelperHierarchy(){this.flags.display.active()?this.object.add(this._helper):this.object.remove(this._helper)}async cook(){await this._update_resolved_object(),this._update_render_hook(),this.cookController.endCook()}_update_render_hook(){const t=UV[this.pv.updateMode];switch(t){case kV.ON_RENDER:return this._add_render_hook();case kV.MANUAL:return this._remove_render_hook()}os.unreachable(t)}_add_render_hook(){this.object.onBeforeRender=this._on_object_before_render_bound,this.object.frustumCulled=!1}_remove_render_hook(){this.object.onBeforeRender=()=>{}}_update(t,e,n,i,s,r){const o=this._resolved_object();if(o){const t=o.geometry;if(t){const e=t.attributes.position;if(e){const t=e.array;this._found_point_post.fromArray(t,3*this.pv.pointIndex),o.updateWorldMatrix(!0,!1),o.localToWorld(this._found_point_post),this.object.matrix.makeTranslation(this._found_point_post.x,this._found_point_post.y,this._found_point_post.z)}}}}static PARAM_CALLBACK_update_resolved_object(t){t._update_resolved_object()}async _update_resolved_object(){this.p.object.isDirty()&&await this.p.object.compute();const t=this.p.object.found_node();if(t)if(t.context()==ts.OBJ&&t.type()==VG.type()){const e=t;this._resolved_sop_group=e.childrenDisplayController.sopGroup()}else this.states.error.set(\\\\\\\"found node is not a geo node\\\\\\\")}_resolved_object(){if(!this._resolved_sop_group)return;const t=this._resolved_sop_group.children[0];return t||void 0}static PARAM_CALLBACK_update_updateMode(t){t._update_render_hook()}static PARAM_CALLBACK_update(t){t._update()}}class HV extends(Pa(Na(wa(ya(_a(ua)))))){}const jV=new HV;class WV extends cU{constructor(){super(...arguments),this.paramsConfig=jV,this.hierarchyController=new MU(this),this.SceneAutoUpdateController=new ma(this),this.sceneBackgroundController=new xa(this),this.SceneEnvController=new Ta(this),this.sceneFogController=new La(this),this.sceneMaterialOverrideController=new Ra(this)}static type(){return\\\\\\\"scene\\\\\\\"}createObject(){const t=new vs;return t.matrixAutoUpdate=!1,t}initializeNode(){this.hierarchyController.initializeNode()}cook(){this.SceneAutoUpdateController.update(),this.sceneBackgroundController.update(),this.SceneEnvController.update(),this.sceneFogController.update(),this.sceneMaterialOverrideController.update(),this.cookController.endCook()}}class qV{constructor(t,e,n){this._camera_node_id=t,this._controls_node=e,this._controls=n,this._updateRequired=this._controls_node.updateRequired()}updateRequired(){return this._updateRequired}get camera_node_id(){return this._camera_node_id}get controls(){return this._controls}get controls_node(){return this._controls_node}is_equal(t){return t.camera_node_id==this._camera_node_id&&t.controls_node.graphNodeId()==this._controls_node.graphNodeId()}}const XV=\\\\\\\"controls\\\\\\\";class YV{constructor(t){this.node=t,this._applied_controls_by_element_id=new Map,this._controls_node=null}controls_param(){return this.node.params.has(XV)?this.node.params.get(XV):null}async controls_node(){const t=this.node.p.controls,e=t.rawInput();if(e&&\\\\\\\"\\\\\\\"!=e){t.isDirty()&&await t.compute();const e=t.value.node();if(e){if(ms.includes(e.type()))return e;this.node.states.error.set(\\\\\\\"found node is not of a camera control type\\\\\\\")}else this.node.states.error.set(\\\\\\\"no node has been found\\\\\\\")}return null}async update_controls(){const t=await this.controls_node();t&&this._controls_node!=t&&this._dispose_control_refs(),this._controls_node=t}async apply_controls(t){const e=t.canvas();if(!e)return;const n=await this.controls_node();if(n){this._controlsEndEventName=n.endEventName();const i=n.controls_id();let s=!1,r=this._applied_controls_by_element_id.get(e.id);if(r&&r.get(i)&&(s=!0),!s){r=new Map,this._applied_controls_by_element_id.set(e.id,r),r.set(i,n);const s=await n.apply_controls(this.node.object,t);if(!s)return;const o=new qV(this.node.graphNodeId(),n,s);return this.set_controls_events(s),o}}}_dispose_control_refs(){this._applied_controls_by_element_id.forEach(((t,e)=>{this._dispose_controls_for_element_id(e)})),this._applied_controls_by_element_id.clear(),this._controlsEndEventName=void 0}_dispose_controls_for_element_id(t){const e=this._applied_controls_by_element_id.get(t);e&&e.forEach(((e,n)=>{e.disposeControlsForHtmlElementId(t)})),this._applied_controls_by_element_id.delete(t)}async dispose_controls(t){this._dispose_controls_for_element_id(t.id)}set_controls_events(t){const e=UH[this.node.pv.updateFromControlsMode];switch(e){case kH.ON_END:return this._set_controls_events_to_update_on_end(t);case kH.ALWAYS:return this._set_controls_events_to_update_always(t);case kH.NEVER:return this._reset(t)}os.unreachable(e)}_reset(t){this.controls_change_listener&&(t.removeEventListener(\\\\\\\"change\\\\\\\",this.controls_change_listener),this.controls_change_listener=void 0),this.controls_end_listener&&this._controlsEndEventName&&(t.removeEventListener(this._controlsEndEventName,this.controls_end_listener),this.controls_end_listener=void 0)}_set_controls_events_to_update_on_end(t){this._reset(t),this._controlsEndEventName&&(this.controls_end_listener=()=>{this.node.update_transform_params_from_object()},t.addEventListener(this._controlsEndEventName,this.controls_end_listener))}_set_controls_events_to_update_always(t){this._reset(t),this.controls_change_listener=()=>{this.node.update_transform_params_from_object()},t.addEventListener(\\\\\\\"change\\\\\\\",this.controls_change_listener)}}function $V(t){return class extends t{constructor(){super(...arguments),this.layer=ha.INTEGER(0,{range:[0,31],rangeLocked:[!0,!0]})}}}class JV{constructor(t){this.node=t}update(){const t=this.node.object;t.layers.set(0),t.layers.enable(this.node.params.integer(\\\\\\\"layer\\\\\\\"))}}const ZV={callback:t=>{$H.PARAM_CALLBACK_reset_effects_composer(t)}};function KV(t){return class extends t{constructor(){super(...arguments),this.doPostProcess=ha.BOOLEAN(0),this.postProcessNode=ha.NODE_PATH(\\\\\\\"\\\\\\\",{visibleIf:{doPostProcess:1},nodeSelection:{types:[es.POST]},...ZV})}}}class QV{constructor(t){this.node=t,this._composers_by_canvas_id={},this.node.p.postProcessNode?this._add_param_dirty_hook():this.node.params.onParamsCreated(\\\\\\\"post process add param dirty hook\\\\\\\",(()=>{this._add_param_dirty_hook()}))}_add_param_dirty_hook(){this.node.p.postProcessNode.addPostDirtyHook(\\\\\\\"on_post_node_dirty\\\\\\\",(()=>{this.reset()}))}render(t,e){const n=this.composer(t);n&&(e&&n.setSize(e.x,e.y),n.render())}reset(){const t=Object.keys(this._composers_by_canvas_id);for(let e of t)delete this._composers_by_canvas_id[e]}composer(t){return this._composers_by_canvas_id[t.id]=this._composers_by_canvas_id[t.id]||this._create_composer(t)}_create_composer(t){const e=this.node.renderController.renderer(t);if(e){const n=this.node.renderController.resolved_scene||this.node.scene().threejsScene(),i=this.node.object,s=this.node.p.postProcessNode.value.node();if(s){if(s.type()==es.POST){const r=s,o=this.node.renderController.canvas_resolution(t);return r.effectsComposerController.createEffectsComposer({renderer:e,scene:n,camera:i,resolution:o,requester:this.node,camera_node:this.node})}this.node.states.error.set(\\\\\\\"found node is not a post process node\\\\\\\")}else this.node.states.error.set(\\\\\\\"no post node found\\\\\\\")}}}class tH extends aa{constructor(){super(...arguments),this.flags=new Pi(this)}static context(){return ts.ROP}initializeBaseNode(){this.dirtyController.addPostDirtyHook(\\\\\\\"cook_immediately\\\\\\\",(()=>{this.cookController.cookMainWithoutInputs()}))}cook(){this.cookController.endCook()}}var eH,nH,iH,sH;!function(t){t.CSS2D=\\\\\\\"CSS2DRenderer\\\\\\\",t.CSS3D=\\\\\\\"CSS3DRenderer\\\\\\\",t.WEBGL=\\\\\\\"WebGLRenderer\\\\\\\"}(eH||(eH={})),function(t){t.Linear=\\\\\\\"Linear\\\\\\\",t.sRGB=\\\\\\\"sRGB\\\\\\\",t.Gamma=\\\\\\\"Gamma\\\\\\\",t.RGBE=\\\\\\\"RGBE\\\\\\\",t.LogLuv=\\\\\\\"LogLuv\\\\\\\",t.RGBM7=\\\\\\\"RGBM7\\\\\\\",t.RGBM16=\\\\\\\"RGBM16\\\\\\\",t.RGBD=\\\\\\\"RGBD\\\\\\\"}(nH||(nH={})),(sH=iH||(iH={}))[sH.Linear=w.U]=\\\\\\\"Linear\\\\\\\",sH[sH.sRGB=w.ld]=\\\\\\\"sRGB\\\\\\\",sH[sH.Gamma=w.J]=\\\\\\\"Gamma\\\\\\\",sH[sH.RGBE=w.gc]=\\\\\\\"RGBE\\\\\\\",sH[sH.LogLuv=w.bb]=\\\\\\\"LogLuv\\\\\\\",sH[sH.RGBM7=w.lc]=\\\\\\\"RGBM7\\\\\\\",sH[sH.RGBM16=w.kc]=\\\\\\\"RGBM16\\\\\\\",sH[sH.RGBD=w.fc]=\\\\\\\"RGBD\\\\\\\";const rH=[nH.Linear,nH.sRGB,nH.Gamma,nH.RGBE,nH.LogLuv,nH.RGBM7,nH.RGBM16,nH.RGBD],oH=[iH.Linear,iH.sRGB,iH.Gamma,iH.RGBE,iH.LogLuv,iH.RGBM7,iH.RGBM16,iH.RGBD],aH=iH.sRGB;var lH,cH,hH;!function(t){t.No=\\\\\\\"No\\\\\\\",t.Linear=\\\\\\\"Linear\\\\\\\",t.Reinhard=\\\\\\\"Reinhard\\\\\\\",t.Cineon=\\\\\\\"Cineon\\\\\\\",t.ACESFilmic=\\\\\\\"ACESFilmic\\\\\\\"}(lH||(lH={})),(hH=cH||(cH={}))[hH.No=w.vb]=\\\\\\\"No\\\\\\\",hH[hH.Linear=w.ab]=\\\\\\\"Linear\\\\\\\",hH[hH.Reinhard=w.vc]=\\\\\\\"Reinhard\\\\\\\",hH[hH.Cineon=w.m]=\\\\\\\"Cineon\\\\\\\",hH[hH.ACESFilmic=w.a]=\\\\\\\"ACESFilmic\\\\\\\";const uH=[lH.No,lH.Linear,lH.Reinhard,lH.Cineon,lH.ACESFilmic],dH=[cH.No,cH.Linear,cH.Reinhard,cH.Cineon,cH.ACESFilmic],pH=cH.ACESFilmic,_H=uH.map(((t,e)=>({name:t,value:dH[e]})));var mH;!function(t){t.HIGH=\\\\\\\"highp\\\\\\\",t.MEDIUM=\\\\\\\"mediump\\\\\\\",t.LOW=\\\\\\\"lowp\\\\\\\"}(mH||(mH={}));const fH=[mH.HIGH,mH.MEDIUM,mH.LOW];var gH;!function(t){t.HIGH=\\\\\\\"high-performance\\\\\\\",t.LOW=\\\\\\\"low-power\\\\\\\",t.DEFAULT=\\\\\\\"default\\\\\\\"}(gH||(gH={}));const vH=[gH.HIGH,gH.LOW,gH.DEFAULT];var yH,xH,bH;!function(t){t.Basic=\\\\\\\"Basic\\\\\\\",t.PCF=\\\\\\\"PCF\\\\\\\",t.PCFSoft=\\\\\\\"PCFSoft\\\\\\\",t.VSM=\\\\\\\"VSM\\\\\\\"}(yH||(yH={})),(bH=xH||(xH={}))[bH.Basic=w.k]=\\\\\\\"Basic\\\\\\\",bH[bH.PCF=w.Fb]=\\\\\\\"PCF\\\\\\\",bH[bH.PCFSoft=w.Gb]=\\\\\\\"PCFSoft\\\\\\\",bH[bH.VSM=w.gd]=\\\\\\\"VSM\\\\\\\";const wH=[yH.Basic,yH.PCF,yH.PCFSoft,yH.VSM],TH=[xH.Basic,xH.PCF,xH.PCFSoft,xH.VSM],AH=(w.k,w.Fb,w.Gb,w.gd,xH.PCFSoft),MH={alpha:!1,precision:mH.HIGH,premultipliedAlpha:!0,antialias:!1,stencil:!0,preserveDrawingBuffer:!1,powerPreference:gH.DEFAULT,depth:!0,logarithmicDepthBuffer:!1};const EH=new class extends ua{constructor(){super(...arguments),this.tprecision=ha.BOOLEAN(0),this.precision=ha.INTEGER(fH.indexOf(mH.HIGH),{visibleIf:{tprecision:1},menu:{entries:fH.map(((t,e)=>({value:e,name:t})))}}),this.tpowerPreference=ha.BOOLEAN(0),this.powerPreference=ha.INTEGER(vH.indexOf(gH.DEFAULT),{visibleIf:{tpowerPreference:1},menu:{entries:vH.map(((t,e)=>({value:e,name:t})))}}),this.alpha=ha.BOOLEAN(1),this.premultipliedAlpha=ha.BOOLEAN(1),this.antialias=ha.BOOLEAN(1),this.stencil=ha.BOOLEAN(1),this.depth=ha.BOOLEAN(1),this.logarithmicDepthBuffer=ha.BOOLEAN(0),this.toneMapping=ha.INTEGER(pH,{menu:{entries:_H}}),this.toneMappingExposure=ha.FLOAT(1,{range:[0,2]}),this.outputEncoding=ha.INTEGER(aH,{menu:{entries:rH.map(((t,e)=>({name:t,value:oH[e]})))}}),this.physicallyCorrectLights=ha.BOOLEAN(1),this.sortObjects=ha.BOOLEAN(1),this.tpixelRatio=ha.BOOLEAN(0),this.pixelRatio=ha.INTEGER(2,{visibleIf:{tpixelRatio:!0},range:[1,4],rangeLocked:[!0,!1]}),this.tshadowMap=ha.BOOLEAN(1),this.shadowMapAutoUpdate=ha.BOOLEAN(1,{visibleIf:{tshadowMap:1}}),this.shadowMapNeedsUpdate=ha.BOOLEAN(0,{visibleIf:{tshadowMap:1}}),this.shadowMapType=ha.INTEGER(AH,{visibleIf:{tshadowMap:1},menu:{entries:wH.map(((t,e)=>({name:t,value:TH[e]})))}})}};class SH extends tH{constructor(){super(...arguments),this.paramsConfig=EH,this._renderers_by_canvas_id={}}static type(){return eH.WEBGL}createRenderer(t,e){const n={},i=Object.keys(MH);let s;for(s of i)n[s]=MH[s];if(this.pv.tprecision){const t=fH[this.pv.precision];n.precision=t}if(this.pv.tpowerPreference){const t=vH[this.pv.powerPreference];n.powerPreference=t}n.antialias=this.pv.antialias,n.antialias=this.pv.antialias,n.alpha=this.pv.alpha,n.premultipliedAlpha=this.pv.premultipliedAlpha,n.depth=this.pv.depth,n.stencil=this.pv.stencil,n.logarithmicDepthBuffer=this.pv.logarithmicDepthBuffer,n.canvas=t,n.context=e;const r=li.renderersController.createWebGLRenderer(n);return li.renderersController.printDebug()&&(li.renderersController.printDebugMessage(`create renderer from node '${this.path()}'`),li.renderersController.printDebugMessage({params:n})),this._update_renderer(r),this._renderers_by_canvas_id[t.id]=r,r}cook(){const t=Object.keys(this._renderers_by_canvas_id);for(let e of t){const t=this._renderers_by_canvas_id[e];this._update_renderer(t)}this._traverse_scene_and_update_materials(),this.cookController.endCook()}_update_renderer(t){t.physicallyCorrectLights=this.pv.physicallyCorrectLights,t.outputEncoding=this.pv.outputEncoding,t.toneMapping=this.pv.toneMapping,t.toneMappingExposure=this.pv.toneMappingExposure,t.shadowMap.enabled=this.pv.tshadowMap,t.shadowMap.autoUpdate=this.pv.shadowMapAutoUpdate,t.shadowMap.needsUpdate=this.pv.shadowMapNeedsUpdate,t.shadowMap.type=this.pv.shadowMapType,t.sortObjects=this.pv.sortObjects;const e=this.pv.tpixelRatio?this.pv.pixelRatio:NH.defaultPixelRatio();li.renderersController.printDebug()&&(li.renderersController.printDebugMessage(`set renderer pixelRatio from '${this.path()}'`),li.renderersController.printDebugMessage({pixelRatio:e})),t.setPixelRatio(e)}_traverse_scene_and_update_materials(){this.scene().threejsScene().traverse((t=>{const e=t.material;if(e)if(m.isArray(e))for(let t of e)t.needsUpdate=!0;else e.needsUpdate=!0}))}}function CH(t){return class extends t{constructor(){super(...arguments),this.render=ha.FOLDER(),this.setScene=ha.BOOLEAN(0),this.scene=ha.OPERATOR_PATH(\\\\\\\"\\\\\\\",{visibleIf:{setScene:1},nodeSelection:{context:ts.OBJ,types:[WV.type()]}}),this.setRenderer=ha.BOOLEAN(0),this.renderer=ha.OPERATOR_PATH(\\\\\\\"\\\\\\\",{visibleIf:{setRenderer:1},nodeSelection:{context:ts.ROP,types:[SH.type()]}}),this.setCSSRenderer=ha.BOOLEAN(0),this.CSSRenderer=ha.OPERATOR_PATH(\\\\\\\"\\\\\\\",{visibleIf:{setCSSRenderer:1},nodeSelection:{context:ts.ROP,types:[eH.CSS2D,eH.CSS3D]}})}}}class NH{constructor(t){this.node=t,this._renderers_by_canvas_id={},this._resolution_by_canvas_id={},this._super_sampling_size=new d.a}render(t,e,n,i){if(this.node.pv.doPostProcess?this.node.postProcessController.render(t,e):this.renderWithRenderer(t,i),this._resolved_cssRenderer_rop&&this._resolved_scene&&this.node.pv.setCSSRenderer){const e=this.cssRenderer(t);e&&e.render(this._resolved_scene,this.node.object)}}renderWithRenderer(t,e){const n=this.renderer(t);if(n){const t=this._resolved_scene;t&&n.render(t,this.node.object)}}async update(){this.update_scene(),this.update_renderer(),this.update_cssRenderer()}get resolved_scene(){return this._resolved_scene}update_scene(){if(this.node.pv.setScene){const t=this.node.p.scene;t.isDirty()&&t.find_target();const e=t.found_node_with_context_and_type(ts.OBJ,WV.type());e&&(e.isDirty()&&e.cookController.cookMainWithoutInputs(),this._resolved_scene=e.object)}else this._resolved_scene=this.node.scene().threejsScene()}update_renderer(){if(this.node.pv.setRenderer){const t=this.node.p.renderer;t.isDirty()&&t.find_target(),this._resolved_renderer_rop=t.found_node_with_context_and_type(ts.ROP,eH.WEBGL)}else this._resolved_renderer_rop=void 0}update_cssRenderer(){if(this.node.pv.setCSSRenderer){const t=this.node.p.CSSRenderer;t.isDirty()&&t.find_target(),this._resolved_cssRenderer_rop=t.found_node_with_context_and_type(ts.ROP,[eH.CSS2D,eH.CSS3D])}else this._resolved_cssRenderer_rop,this._resolved_cssRenderer_rop=void 0}renderer(t){return this._renderers_by_canvas_id[t.id]}cssRenderer(t){if(this._resolved_cssRenderer_rop&&this.node.pv.setCSSRenderer)return this._resolved_cssRenderer_rop.renderer(t)}createRenderer(t,e){const n=li.renderersController.createRenderingContext(t);if(!n)return void console.error(\\\\\\\"failed to create webgl context\\\\\\\");let i;return this.node.pv.setRenderer&&(this.update_renderer(),this._resolved_renderer_rop&&(i=this._resolved_renderer_rop.createRenderer(t,n))),i||(i=NH._createDefaultRenderer(t,n)),li.renderersController.registerRenderer(i),this._renderers_by_canvas_id[t.id]=i,this._super_sampling_size.copy(e),this.set_renderer_size(t,this._super_sampling_size),i}static defaultPixelRatio(){return ng.isMobile()?1:Math.max(2,window.devicePixelRatio)}static _createDefaultRenderer(t,e){const n={canvas:t,antialias:!1,alpha:!1,context:e},i=li.renderersController.createWebGLRenderer(n),s=this.defaultPixelRatio();return i.setPixelRatio(s),i.shadowMap.enabled=!0,i.shadowMap.type=AH,i.physicallyCorrectLights=!0,i.toneMapping=pH,i.toneMappingExposure=1,i.outputEncoding=aH,li.renderersController.printDebug()&&(li.renderersController.printDebugMessage(\\\\\\\"create default renderer\\\\\\\"),li.renderersController.printDebugMessage({params:n,pixelRatio:s})),i}deleteRenderer(t){const e=this.renderer(t);e&&li.renderersController.deregisterRenderer(e)}canvas_resolution(t){return this._resolution_by_canvas_id[t.id]}set_renderer_size(t,e){this._resolution_by_canvas_id[t.id]=this._resolution_by_canvas_id[t.id]||new d.a,this._resolution_by_canvas_id[t.id].copy(e);const n=this.renderer(t);if(n){const t=!1;n.setSize(e.x,e.y,t)}if(this._resolved_cssRenderer_rop){const n=this.cssRenderer(t);n&&n.setSize(e.x,e.y)}}}class LH{constructor(t){this.viewer=t,this._active=!1,this._controls=null,this._bound_on_controls_start=this._on_controls_start.bind(this),this._bound_on_controls_end=this._on_controls_end.bind(this),this._update_graph_node()}controls(){return this._controls}async create_controls(){var t;this.dispose_controls();this.viewer.canvas()&&(this._config=await(null===(t=this.viewer.cameraControlsController)||void 0===t?void 0:t.apply_controls(this.viewer)),this._config&&(this._controls=this._config.controls,this._controls&&(this.viewer.active()?(this._controls.addEventListener(\\\\\\\"start\\\\\\\",this._bound_on_controls_start),this._controls.addEventListener(\\\\\\\"end\\\\\\\",this._bound_on_controls_end)):this.dispose_controls())))}update(t){this._config&&this._controls&&this._config.updateRequired()&&this._controls.update(t)}dispose(){var t;null===(t=this._graph_node)||void 0===t||t.graphDisconnectPredecessors(),this.dispose_controls()}dispose_controls(){var t;if(this._controls){const e=this.viewer.canvas();e&&(null===(t=this.viewer)||void 0===t||t.cameraControlsController.dispose_controls(e)),this._bound_on_controls_start&&this._controls.removeEventListener(\\\\\\\"start\\\\\\\",this._bound_on_controls_start),this._bound_on_controls_end&&this._controls.removeEventListener(\\\\\\\"end\\\\\\\",this._bound_on_controls_end),this._controls.dispose(),this._controls=null}}_on_controls_start(){this._active=!0}_on_controls_end(){this._active=!1}_update_graph_node(){const t=this.viewer.cameraNode().p.controls;this._graph_node=this._graph_node||this._create_graph_node(),this._graph_node&&(this._graph_node.graphDisconnectPredecessors(),this._graph_node.addGraphInput(t))}_create_graph_node(){const t=new Mi(this.viewer.cameraNode().scene(),\\\\\\\"viewer-controls\\\\\\\");return t.addPostDirtyHook(\\\\\\\"this.viewer.controls_controller\\\\\\\",(async()=>{await this.create_controls()})),t}}class OH{constructor(t){this._viewer=t,this._size=new d.a(100,100),this._aspect=1}cameraNode(){return this._viewer.cameraNode()}get size(){return this._size}get aspect(){return this._aspect}computeSizeAndAspect(){this._updateSize(),this.cameraNode().scene().uniformsController.updateResolutionDependentUniformOwners(this._size),this._aspect=this._getAspect()}_updateSize(){this._size.x=this._viewer.domElement().offsetWidth,this._size.y=this._viewer.domElement().offsetHeight}_getAspect(){return this._size.x/this._size.y}updateCameraAspect(){this.cameraNode().setupForAspectRatio(this._aspect)}async prepareCurrentCamera(){await this.cameraNode().compute(),await this._updateFromCameraContainer()}async _updateFromCameraContainer(){var t;this.updateCameraAspect(),await(null===(t=this._viewer.controlsController)||void 0===t?void 0:t.create_controls())}}class PH{constructor(t){this.viewer=t}init(){const t=this.viewer.canvas();t&&(t.onwebglcontextlost=this._on_webglcontextlost.bind(this),t.onwebglcontextrestored=this._on_webglcontextrestored.bind(this))}_on_webglcontextlost(){console.warn(\\\\\\\"context lost at frame\\\\\\\",this.viewer.scene().frame()),this.request_animation_frame_id?cancelAnimationFrame(this.request_animation_frame_id):console.warn(\\\\\\\"request_animation_frame_id not initialized\\\\\\\"),console.warn(\\\\\\\"not canceled\\\\\\\",this.request_animation_frame_id)}_on_webglcontextrestored(){console.log(\\\\\\\"context restored\\\\\\\")}}const RH=\\\\\\\"hovered\\\\\\\";class IH{constructor(t,e,n){this._container=t,this._scene=e,this._camera_node=n,this._active=!1,this._id=IH._next_viewer_id++,this._scene.viewersRegister.registerViewer(this)}setRenderObjectOverride(t){console.log(\\\\\\\"setRenderObjectOverride\\\\\\\",t),this._renderObjectOverride=t||void 0}active(){return this._active}activate(){this._active=!0}deactivate(){this._active=!1}get camerasController(){return this._cameras_controller=this._cameras_controller||new OH(this)}get controlsController(){return this._controls_controller}get eventsController(){return this._events_controller=this._events_controller||new Wa(this)}get webglController(){return this._webgl_controller=this._webgl_controller||new PH(this)}domElement(){return this._container}scene(){return this._scene}canvas(){return this._canvas}cameraNode(){return this._camera_node}get cameraControlsController(){}id(){return this._id}dispose(){let t;for(this._scene.viewersRegister.unregisterViewer(this),this.eventsController.dispose();t=this._container.children[0];)this._container.removeChild(t)}resetContainerClass(){this.domElement().classList.remove(RH)}setContainerClassHovered(){this.domElement().classList.add(RH)}registerOnBeforeTick(t,e){this._registerCallback(t,e,this.registeredBeforeTickCallbacks())}unRegisterOnBeforeTick(t){this._unregisterCallback(t,this._onBeforeTickCallbacks)}registeredBeforeTickCallbacks(){return this._onBeforeTickCallbacks=this._onBeforeTickCallbacks||new Map}registerOnAfterTick(t,e){this._registerCallback(t,e,this.registeredAfterTickCallbacks())}unRegisterOnAfterTick(t){this._unregisterCallback(t,this._onAfterTickCallbacks)}registeredAfterTickCallbacks(){return this._onAfterTickCallbacks=this._onAfterTickCallbacks||new Map}registerOnBeforeRender(t,e){this._registerCallback(t,e,this.registeredBeforeRenderCallbacks())}unRegisterOnBeforeRender(t){this._unregisterCallback(t,this._onBeforeRenderCallbacks)}registeredBeforeRenderCallbacks(){return this._onBeforeRenderCallbacks=this._onBeforeRenderCallbacks||new Map}registerOnAfterRender(t,e){this._registerCallback(t,e,this.registeredAfterRenderCallbacks())}unRegisterOnAfterRender(t){this._unregisterCallback(t,this._onAfterRenderCallbacks)}registeredAfterRenderCallbacks(){return this._onAfterRenderCallbacks=this._onAfterRenderCallbacks||new Map}_registerCallback(t,e,n){n.has(t)?console.warn(`callback ${t} already registered`):n.set(t,e)}_unregisterCallback(t,e){e&&e.delete(t)}}IH._next_viewer_id=0;class FH extends IH{constructor(t,e,n,i){super(t,e,n),this._scene=e,this._camera_node=n,this._properties=i,this._do_render=!0,this._clock=new Dm,this._delta=0,this._animate_method=this.animate.bind(this),this._onResizeBound=this.onResize.bind(this),this._do_render=null==this._properties||this._properties.autoRender,this._canvas=document.createElement(\\\\\\\"canvas\\\\\\\"),this._canvas.id=`canvas_id_${Math.random()}`.replace(\\\\\\\".\\\\\\\",\\\\\\\"_\\\\\\\"),this._canvas.style.display=\\\\\\\"block\\\\\\\",this._canvas.style.outline=\\\\\\\"none\\\\\\\",this._container.appendChild(this._canvas),this._container.classList.add(\\\\\\\"CoreThreejsViewer\\\\\\\"),this._build(),this._setEvents()}get controlsController(){return this._controls_controller=this._controls_controller||new LH(this)}_build(){this._init_display(),this.activate()}dispose(){this._cancel_animate(),this.controlsController.dispose(),this._disposeEvents(),super.dispose()}get cameraControlsController(){return this._camera_node.controls_controller}_setEvents(){this.eventsController.init(),this.webglController.init(),window.addEventListener(\\\\\\\"resize\\\\\\\",this._onResizeBound.bind(this),!1)}_disposeEvents(){window.removeEventListener(\\\\\\\"resize\\\\\\\",this._onResizeBound.bind(this),!1)}onResize(){const t=this.canvas();t&&(this.camerasController.computeSizeAndAspect(),this._camera_node.renderController.set_renderer_size(t,this.camerasController.size),this.camerasController.updateCameraAspect())}_init_display(){if(!this._canvas)return void console.warn(\\\\\\\"no canvas found for viewer\\\\\\\");this.camerasController.computeSizeAndAspect();const t=this.camerasController.size;this._camera_node.renderController.createRenderer(this._canvas,t),this.camerasController.prepareCurrentCamera(),this.animate()}setAutoRender(t=!0){this._do_render=t,this._do_render&&this.animate()}animate(){var t,e,n;this._do_render&&(this._delta=this._clock.getDelta(),this._request_animation_frame_id=requestAnimationFrame(this._animate_method),null===(t=this._onBeforeTickCallbacks)||void 0===t||t.forEach((t=>t(this._delta))),this._scene.timeController.incrementTimeIfPlaying(this._delta),null===(e=this._onAfterTickCallbacks)||void 0===e||e.forEach((t=>t(this._delta))),this.render(this._delta),null===(n=this._controls_controller)||void 0===n||n.update(this._delta))}_cancel_animate(){this._do_render=!1,this._request_animation_frame_id&&cancelAnimationFrame(this._request_animation_frame_id),this._canvas&&this._camera_node.renderController.deleteRenderer(this._canvas)}render(t){var e,n;if(this.camerasController.cameraNode()&&this._canvas){null===(e=this._onBeforeRenderCallbacks)||void 0===e||e.forEach((e=>e(t)));const i=this.camerasController.size,s=this.camerasController.aspect;this._camera_node.renderController.render(this._canvas,i,s,this._renderObjectOverride),null===(n=this._onAfterRenderCallbacks)||void 0===n||n.forEach((e=>e(t)))}else console.warn(\\\\\\\"no camera to render with\\\\\\\")}renderer(){if(this._canvas)return this._camera_node.renderController.renderer(this._canvas)}}const DH={type:\\\\\\\"change\\\\\\\"},BH=1,zH=100;var kH;!function(t){t.ON_END=\\\\\\\"on move end\\\\\\\",t.ALWAYS=\\\\\\\"always\\\\\\\",t.NEVER=\\\\\\\"never\\\\\\\"}(kH||(kH={}));const UH=[kH.ON_END,kH.ALWAYS,kH.NEVER];function GH(t){return class extends t{constructor(){super(...arguments),this.setMainCamera=ha.BUTTON(null,{callback:(t,e)=>{YH.PARAM_CALLBACK_setMasterCamera(t)}})}}}function VH(t){return class extends t{constructor(){super(...arguments),this.camera=ha.FOLDER(),this.controls=ha.NODE_PATH(\\\\\\\"\\\\\\\",{nodeSelection:{context:ts.EVENT}}),this.updateFromControlsMode=ha.INTEGER(UH.indexOf(kH.ON_END),{menu:{entries:UH.map(((t,e)=>({name:t,value:e})))}}),this.near=ha.FLOAT(BH,{range:[0,100],cook:!1,computeOnDirty:!0,callback:(t,e)=>{$H.PARAM_CALLBACK_update_near_far_from_param(t,e)}}),this.far=ha.FLOAT(zH,{range:[0,100],cook:!1,computeOnDirty:!0,callback:(t,e)=>{$H.PARAM_CALLBACK_update_near_far_from_param(t,e)}}),this.display=ha.BOOLEAN(1),this.showHelper=ha.BOOLEAN(0)}}}var HH;!function(t){t.DEFAULT=\\\\\\\"default\\\\\\\",t.COVER=\\\\\\\"cover\\\\\\\",t.CONTAIN=\\\\\\\"contain\\\\\\\"}(HH||(HH={}));const jH=[HH.DEFAULT,HH.COVER,HH.CONTAIN];function WH(t){return class extends t{constructor(){super(...arguments),this.fovAdjustMode=ha.INTEGER(jH.indexOf(HH.DEFAULT),{menu:{entries:jH.map(((t,e)=>({name:t,value:e})))}}),this.expectedAspectRatio=ha.FLOAT(\\\\\\\"16/9\\\\\\\",{visibleIf:[{fovAdjustMode:jH.indexOf(HH.COVER)},{fovAdjustMode:jH.indexOf(HH.CONTAIN)}],range:[0,2],rangeLocked:[!0,!1]})}}}GH(ua);KV(CH(wU($V(VH(GH(ua))))));class qH extends cU{constructor(){super(...arguments),this.renderOrder=lU.CAMERA,this._aspect=-1}get object(){return this._object}async cook(){this.updateCamera(),this._object.dispatchEvent(DH),this.cookController.endCook()}on_create(){}on_delete(){}prepareRaycaster(t,e){}camera(){return this._object}updateCamera(){}static PARAM_CALLBACK_setMasterCamera(t){t.set_as_master_camera()}set_as_master_camera(){this.scene().camerasController.setMainCameraNodePath(this.path())}setupForAspectRatio(t){}_updateForAspectRatio(){}update_transform_params_from_object(){bU.setParamsFromObject(this._object,this)}static PARAM_CALLBACK_update_from_param(t,e){t.object[e.name()]=t.pv[e.name()]}}class XH extends qH{constructor(){super(...arguments),this.flags=new Di(this),this.hierarchyController=new MU(this),this.transformController=new AU(this),this.childrenDisplayController=new kG(this),this.displayNodeController=new Fm(this,this.childrenDisplayController.displayNodeControllerCallbacks()),this._children_controller_context=ts.SOP}get controls_controller(){return this._controls_controller=this._controls_controller||new YV(this)}get layers_controller(){return this._layers_controller=this._layers_controller||new JV(this)}get renderController(){return this._render_controller=this._render_controller||new NH(this)}get postProcessController(){return this._post_process_controller=this._post_process_controller||new QV(this)}initializeBaseNode(){super.initializeBaseNode(),this.io.outputs.setHasOneOutput(),this.hierarchyController.initializeNode(),this.transformController.initializeNode(),this.childrenDisplayController.initializeNode(),this.initHelperHook()}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}prepareRaycaster(t,e){e.setFromCamera(t,this._object)}async cook(){this.transformController.update(),this.layers_controller.update(),this.updateNearFar(),this.renderController.update(),this.updateCamera(),this._updateHelper(),this.controls_controller.update_controls(),this._object.dispatchEvent(DH),this.cookController.endCook()}static PARAM_CALLBACK_update_near_far_from_param(t,e){t.updateNearFar()}updateNearFar(){this._object.near==this.pv.near&&this._object.far==this.pv.far||(this._object.near=this.pv.near,this._object.far=this.pv.far,this._object.updateProjectionMatrix(),this._updateHelper())}setupForAspectRatio(t){m.isNaN(t)||t&&this._aspect!=t&&(this._aspect=t,this._updateForAspectRatio())}createViewer(t,e){return new FH(t,this.scene(),this,e)}static PARAM_CALLBACK_reset_effects_composer(t){t.postProcessController.reset()}initHelperHook(){this.flags.display.onUpdate((()=>{this._updateHelper()}))}helperVisible(){return this.flags.display.active()&&this.pv.showHelper}_createHelper(){const t=new zU(this.object);return t.update(),t}_updateHelper(){this.helperVisible()?(this._helper||(this._helper=this._createHelper()),this._helper&&(this.object.add(this._helper),this._helper.update())):this._helper&&this.object.remove(this._helper)}}class YH extends qH{}class $H extends XH{PARAM_CALLBACK_update_effects_composer(t){}}const JH=-.5,ZH=.5,KH=.5,QH=-.5;class tj extends(KV(CH($V(GH(WH(function(t){return class extends t{constructor(){super(...arguments),this.size=ha.FLOAT(1)}}}(VH(wU(ua,{matrixAutoUpdate:!0}))))))))){}const ej=new tj;class nj extends XH{constructor(){super(...arguments),this.paramsConfig=ej}static type(){return is.ORTHOGRAPHIC}createObject(){return new ot.a(2*JH,2*ZH,2*KH,2*QH,BH,zH)}updateCamera(){this._updateForAspectRatio()}_updateForAspectRatio(){this._aspect&&(this._adjustFOVFromMode(),this._object.updateProjectionMatrix())}_adjustFOVFromMode(){const t=jH[this.pv.fovAdjustMode];switch(t){case HH.DEFAULT:return this._adjustFOVFromModeDefault();case HH.COVER:return this._adjustFOVFromModeCover();case HH.CONTAIN:return this._adjustFOVFromModeContain()}os.unreachable(t)}_adjustFOVFromModeDefault(){this._adjustFOVFromSize(this.pv.size||1)}_adjustFOVFromModeCover(){const t=this.pv.size||1;this._aspect>this.pv.expectedAspectRatio?this._adjustFOVFromSize(this.pv.expectedAspectRatio*t/this._aspect):this._adjustFOVFromSize(t)}_adjustFOVFromModeContain(){const t=this.pv.size||1;this._aspect>this.pv.expectedAspectRatio?this._adjustFOVFromSize(t):this._adjustFOVFromSize(this.pv.expectedAspectRatio*t/this._aspect)}_adjustFOVFromSize(t){const e=t*this._aspect;this._object.left=JH*e*1,this._object.right=ZH*e*1,this._object.top=KH*t*1,this._object.bottom=QH*t*1}}const ij=50;class sj extends(KV(CH($V(GH(WH(function(t){return class extends t{constructor(){super(...arguments),this.fov=ha.FLOAT(ij,{range:[0,100]})}}}(VH(wU(ua,{matrixAutoUpdate:!0}))))))))){}const rj=new sj;class oj extends XH{constructor(){super(...arguments),this.paramsConfig=rj}static type(){return is.PERSPECTIVE}createObject(){return new tt.a(ij,1,BH,zH)}updateCamera(){this._object.fov!=this.pv.fov&&(this._object.fov=this.pv.fov,this._object.updateProjectionMatrix()),this._updateForAspectRatio()}_updateForAspectRatio(){this._aspect&&(this._object.aspect=this._aspect,this._adjustFOVFromMode(),this._object.updateProjectionMatrix())}_adjustFOVFromMode(){const t=jH[this.pv.fovAdjustMode];switch(t){case HH.DEFAULT:return this._adjustFOVFromModeDefault();case HH.COVER:return this._adjustFOVFromModeCover();case HH.CONTAIN:return this._adjustFOVFromModeContain()}os.unreachable(t)}_adjustFOVFromModeDefault(){this._object.fov=this.pv.fov}_adjustFOVFromModeCover(){if(this._object.aspect>this.pv.expectedAspectRatio){const t=Math.tan(Object(On.e)(this.pv.fov/2))/(this._object.aspect/this.pv.expectedAspectRatio);this._object.fov=2*Object(On.k)(Math.atan(t))}else this._object.fov=this.pv.fov}_adjustFOVFromModeContain(){if(this._object.aspect>this.pv.expectedAspectRatio)this._object.fov=this.pv.fov;else{const t=Math.tan(Object(On.e)(this.pv.fov/2))/(this._object.aspect/this.pv.expectedAspectRatio);this._object.fov=2*Object(On.k)(Math.atan(t))}}}class aj extends(function(t){return class extends t{constructor(){super(...arguments),this.main=ha.FOLDER(),this.resolution=ha.INTEGER(256),this.excludedObjects=ha.STRING(\\\\\\\"*`$OS`\\\\\\\"),this.printResolve=ha.BUTTON(null,{callback:t=>{cj.PARAM_CALLBACK_printResolve(t)}}),this.near=ha.FLOAT(1),this.far=ha.FLOAT(100),this.render=ha.BUTTON(null,{callback:t=>{cj.PARAM_CALLBACK_render(t)}}),this.renderTarget=ha.FOLDER(),this.tencoding=ha.BOOLEAN(0),this.encoding=ha.INTEGER(w.ld,{visibleIf:{tencoding:1},menu:{entries:og.map((t=>({name:Object.keys(t)[0],value:Object.values(t)[0]})))}}),this.tminFilter=ha.BOOLEAN(0),this.minFilter=ha.INTEGER(Km,{visibleIf:{tminFilter:1},menu:{entries:tf}}),this.tmagFilter=ha.BOOLEAN(0),this.magFilter=ha.INTEGER(Zm,{visibleIf:{tmagFilter:1},menu:{entries:Qm}})}}}(wU(ua))){}const lj=new aj;class cj extends cU{constructor(){super(...arguments),this.paramsConfig=lj,this.hierarchyController=new MU(this),this.transformController=new AU(this),this.flags=new Di(this),this._excludedObjects=[],this._previousVisibleStateByUuid=new Map,this._helper=new TG(1)}static type(){return Ig.CUBE_CAMERA}initializeNode(){this.hierarchyController.initializeNode(),this.transformController.initializeNode(),this._updateHelperHierarchy(),this._helper.matrixAutoUpdate=!1,this.flags.display.onUpdate((()=>{this._updateHelperHierarchy()})),this.io.inputs.setCount(0,1)}createObject(){const t=new Fn.a;return t.matrixAutoUpdate=!0,t}cook(){this.transformController.update(),this._resolveObjects();const t=this._setupCubeCamera();this._cubeCamera&&!t||this._createCubeCamera(),this.cookController.endCook()}_updateHelperHierarchy(){this.flags.display.active()?this.object.add(this._helper):this.object.remove(this._helper)}_setupCubeCamera(){let t=!1;if(this._cubeCamera){const e=this._cubeCamera.children[0],n=e.near,i=e.far,s=this._cubeCamera.renderTarget.width;n==this.pv.near&&i==this.pv.far&&s==this.pv.resolution||(t=!0),t&&this.object.remove(this._cubeCamera)}return t}_createCubeCamera(){const t=new st(this.pv.resolution,{encoding:this.pv.tencoding?this.pv.encoding:w.ld,minFilter:this.pv.tminFilter?this.pv.minFilter:void 0,magFilter:this.pv.tmagFilter?this.pv.magFilter:void 0});this._cubeCamera=new nt(this.pv.near,this.pv.far,t),this._cubeCamera.matrixAutoUpdate=!0,this.object.add(this._cubeCamera)}renderTarget(){if(this._cubeCamera)return this._cubeCamera.renderTarget}render(){const t=li.renderersController.firstRenderer();if(t)if(this._cubeCamera){for(let t of this._excludedObjects)this._previousVisibleStateByUuid.set(t.uuid,t.visible),t.visible=!1;this._cubeCamera.update(t,this.scene().threejsScene());for(let t of this._excludedObjects){const e=this._previousVisibleStateByUuid.get(t.uuid);e&&(t.visible=e)}this._previousVisibleStateByUuid.clear()}else console.warn(`no cubeCamera for ${this.path()}`);else console.warn(`no renderer found for ${this.path()}`)}_resolveObjects(){const t=this.scene().objectsByMask(this.pv.excludedObjects),e=new Map;for(let n of t)e.set(n.uuid,n);this._excludedObjects=[];for(let n of t){const t=n.parent;t&&(e.get(t.uuid)||this._excludedObjects.push(n))}}static PARAM_CALLBACK_printResolve(t){t.param_callback_printResolve()}param_callback_printResolve(){this._resolveObjects(),console.log(this._excludedObjects)}static PARAM_CALLBACK_render(t){t.param_callback_render()}param_callback_render(){this.render()}}class hj extends cU{constructor(){super(...arguments),this._attachableToHierarchy=!1}createObject(){const t=new Fn.a;return t.matrixAutoUpdate=!1,t}cook(){this.cookController.endCook()}}class uj extends hj{}class dj extends uj{constructor(){super(...arguments),this._children_controller_context=ts.ANIM}static type(){return es.ANIM}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}}class pj extends dj{constructor(){super(...arguments),this.renderOrder=lU.MANAGER}}class _j extends uj{constructor(){super(...arguments),this._children_controller_context=ts.COP}static type(){return es.COP}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}}class mj extends uj{constructor(){super(...arguments),this.renderOrder=lU.MANAGER,this._children_controller_context=ts.EVENT}static type(){return es.EVENT}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}}class fj extends uj{constructor(){super(...arguments),this.renderOrder=lU.MANAGER,this._children_controller_context=ts.MAT}static type(){return es.MAT}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}}class gj extends hj{constructor(){super(...arguments),this.paramsConfig=new ef,this.effectsComposerController=new nf(this),this.displayNodeController=new Fm(this,this.effectsComposerController.displayNodeControllerCallbacks()),this._children_controller_context=ts.POST}static type(){return es.POST}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}}class vj extends uj{constructor(){super(...arguments),this.renderOrder=lU.MANAGER,this._children_controller_context=ts.ROP}static type(){return es.ROP}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}}const yj=[\\\\\\\"input pass\\\\\\\"];const xj={cook:!1,callback:function(t,e){bj.PARAM_CALLBACK_updatePasses(t)},computeOnDirty:!0};class bj extends aa{constructor(){super(...arguments),this.flags=new zi(this),this._passes_by_requester_id=new Map,this._update_pass_bound=this.updatePass.bind(this)}static context(){return ts.POST}static displayedInputNames(){return yj}initializeNode(){this.flags.display.set(!1),this.flags.display.onUpdate((()=>{if(this.flags.display.active()){const t=this.parent();t&&t.displayNodeController&&t.displayNodeController.setDisplayNode(this)}})),this.io.inputs.setCount(0,1),this.io.outputs.setHasOneOutput()}cook(){this.cookController.endCook()}setupComposer(t){if(this._addPassFromInput(0,t),!this.flags.bypass.active()){let e=this._passes_by_requester_id.get(t.requester.graphNodeId());e||(e=this._createPass(t),e&&this._passes_by_requester_id.set(t.requester.graphNodeId(),e)),e&&t.composer.addPass(e)}}_addPassFromInput(t,e){const n=this.io.inputs.input(t);n&&n.setupComposer(e)}_createPass(t){}static PARAM_CALLBACK_updatePasses(t){t._updatePasses()}_updatePasses(){this._passes_by_requester_id.forEach(this._update_pass_bound)}updatePass(t){}}const wj={uniforms:{tDiffuse:{value:null}},vertexShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\tvUv = uv;\\\\n\\\\n\\\\t\\\\t\\\\tgl_Position = projectionMatrix * modelViewMatrix * vec4( position, 1.0 );\\\\n\\\\n\\\\t\\\\t}\\\\\\\",fragmentShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\t#include \\\\n\\\\n\\\\t\\\\tuniform sampler2D tDiffuse;\\\\n\\\\n\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\tvec4 texel = texture2D( tDiffuse, vUv );\\\\n\\\\n\\\\t\\\\t\\\\tfloat l = linearToRelativeLuminance( texel.rgb );\\\\n\\\\n\\\\t\\\\t\\\\tgl_FragColor = vec4( l, l, l, texel.w );\\\\n\\\\n\\\\t\\\\t}\\\\\\\"};var Tj={uniforms:{tDiffuse:{value:null},averageLuminance:{value:1},luminanceMap:{value:null},maxLuminance:{value:16},minLuminance:{value:.01},middleGrey:{value:.6}},vertexShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\tvUv = uv;\\\\n\\\\t\\\\t\\\\tgl_Position = projectionMatrix * modelViewMatrix * vec4( position, 1.0 );\\\\n\\\\n\\\\t\\\\t}\\\\\\\",fragmentShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\t#include \\\\n\\\\n\\\\t\\\\tuniform sampler2D tDiffuse;\\\\n\\\\n\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\n\\\\t\\\\tuniform float middleGrey;\\\\n\\\\t\\\\tuniform float minLuminance;\\\\n\\\\t\\\\tuniform float maxLuminance;\\\\n\\\\t\\\\t#ifdef ADAPTED_LUMINANCE\\\\n\\\\t\\\\t\\\\tuniform sampler2D luminanceMap;\\\\n\\\\t\\\\t#else\\\\n\\\\t\\\\t\\\\tuniform float averageLuminance;\\\\n\\\\t\\\\t#endif\\\\n\\\\n\\\\t\\\\tvec3 ToneMap( vec3 vColor ) {\\\\n\\\\t\\\\t\\\\t#ifdef ADAPTED_LUMINANCE\\\\n\\\\t\\\\t\\\\t\\\\t// Get the calculated average luminance\\\\n\\\\t\\\\t\\\\t\\\\tfloat fLumAvg = texture2D(luminanceMap, vec2(0.5, 0.5)).r;\\\\n\\\\t\\\\t\\\\t#else\\\\n\\\\t\\\\t\\\\t\\\\tfloat fLumAvg = averageLuminance;\\\\n\\\\t\\\\t\\\\t#endif\\\\n\\\\n\\\\t\\\\t\\\\t// Calculate the luminance of the current pixel\\\\n\\\\t\\\\t\\\\tfloat fLumPixel = linearToRelativeLuminance( vColor );\\\\n\\\\n\\\\t\\\\t\\\\t// Apply the modified operator (Eq. 4)\\\\n\\\\t\\\\t\\\\tfloat fLumScaled = (fLumPixel * middleGrey) / max( minLuminance, fLumAvg );\\\\n\\\\n\\\\t\\\\t\\\\tfloat fLumCompressed = (fLumScaled * (1.0 + (fLumScaled / (maxLuminance * maxLuminance)))) / (1.0 + fLumScaled);\\\\n\\\\t\\\\t\\\\treturn fLumCompressed * vColor;\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\tvec4 texel = texture2D( tDiffuse, vUv );\\\\n\\\\n\\\\t\\\\t\\\\tgl_FragColor = vec4( ToneMap( texel.xyz ), texel.w );\\\\n\\\\n\\\\t\\\\t}\\\\\\\"};class Aj extends km{constructor(t,e){super(),this.resolution=void 0!==e?e:256,this.needsInit=!0,this.adaptive=void 0===t||!!t,this.luminanceRT=null,this.previousLuminanceRT=null,this.currentLuminanceRT=null,void 0===zm&&console.error(\\\\\\\"THREE.AdaptiveToneMappingPass relies on CopyShader\\\\\\\");const n=zm;this.copyUniforms=I.clone(n.uniforms),this.materialCopy=new F({uniforms:this.copyUniforms,vertexShader:n.vertexShader,fragmentShader:n.fragmentShader,blending:w.ub,depthTest:!1}),void 0===wj&&console.error(\\\\\\\"THREE.AdaptiveToneMappingPass relies on LuminosityShader\\\\\\\"),this.materialLuminance=new F({uniforms:I.clone(wj.uniforms),vertexShader:wj.vertexShader,fragmentShader:wj.fragmentShader,blending:w.ub}),this.adaptLuminanceShader={defines:{MIP_LEVEL_1X1:(Math.log(this.resolution)/Math.log(2)).toFixed(1)},uniforms:{lastLum:{value:null},currentLum:{value:null},minLuminance:{value:.01},delta:{value:.016},tau:{value:1}},vertexShader:\\\\\\\"varying vec2 vUv;\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tvUv = uv;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tgl_Position = projectionMatrix * modelViewMatrix * vec4( position, 1.0 );\\\\n\\\\n\\\\t\\\\t\\\\t\\\\t}\\\\\\\",fragmentShader:\\\\\\\"varying vec2 vUv;\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tuniform sampler2D lastLum;\\\\n\\\\t\\\\t\\\\t\\\\tuniform sampler2D currentLum;\\\\n\\\\t\\\\t\\\\t\\\\tuniform float minLuminance;\\\\n\\\\t\\\\t\\\\t\\\\tuniform float delta;\\\\n\\\\t\\\\t\\\\t\\\\tuniform float tau;\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tvec4 lastLum = texture2D( lastLum, vUv, MIP_LEVEL_1X1 );\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tvec4 currentLum = texture2D( currentLum, vUv, MIP_LEVEL_1X1 );\\\\n\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tfloat fLastLum = max( minLuminance, lastLum.r );\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tfloat fCurrentLum = max( minLuminance, currentLum.r );\\\\n\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t//The adaption seems to work better in extreme lighting differences\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t//if the input luminance is squared.\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tfCurrentLum *= fCurrentLum;\\\\n\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t// Adapt the luminance using Pattanaik's technique\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tfloat fAdaptedLum = fLastLum + (fCurrentLum - fLastLum) * (1.0 - exp(-delta * tau));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t// \\\\\\\\\\\"fAdaptedLum = sqrt(fAdaptedLum);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tgl_FragColor.r = fAdaptedLum;\\\\n\\\\t\\\\t\\\\t\\\\t}\\\\\\\"},this.materialAdaptiveLum=new F({uniforms:I.clone(this.adaptLuminanceShader.uniforms),vertexShader:this.adaptLuminanceShader.vertexShader,fragmentShader:this.adaptLuminanceShader.fragmentShader,defines:Object.assign({},this.adaptLuminanceShader.defines),blending:w.ub}),void 0===Tj&&console.error(\\\\\\\"THREE.AdaptiveToneMappingPass relies on ToneMapShader\\\\\\\"),this.materialToneMap=new F({uniforms:I.clone(Tj.uniforms),vertexShader:Tj.vertexShader,fragmentShader:Tj.fragmentShader,blending:w.ub}),this.fsQuad=new Vm(null)}render(t,e,n,i){this.needsInit&&(this.reset(t),this.luminanceRT.texture.type=n.texture.type,this.previousLuminanceRT.texture.type=n.texture.type,this.currentLuminanceRT.texture.type=n.texture.type,this.needsInit=!1),this.adaptive&&(this.fsQuad.material=this.materialLuminance,this.materialLuminance.uniforms.tDiffuse.value=n.texture,t.setRenderTarget(this.currentLuminanceRT),this.fsQuad.render(t),this.fsQuad.material=this.materialAdaptiveLum,this.materialAdaptiveLum.uniforms.delta.value=i,this.materialAdaptiveLum.uniforms.lastLum.value=this.previousLuminanceRT.texture,this.materialAdaptiveLum.uniforms.currentLum.value=this.currentLuminanceRT.texture,t.setRenderTarget(this.luminanceRT),this.fsQuad.render(t),this.fsQuad.material=this.materialCopy,this.copyUniforms.tDiffuse.value=this.luminanceRT.texture,t.setRenderTarget(this.previousLuminanceRT),this.fsQuad.render(t)),this.fsQuad.material=this.materialToneMap,this.materialToneMap.uniforms.tDiffuse.value=n.texture,this.renderToScreen?(t.setRenderTarget(null),this.fsQuad.render(t)):(t.setRenderTarget(e),this.clear&&t.clear(),this.fsQuad.render(t))}reset(){this.luminanceRT&&this.luminanceRT.dispose(),this.currentLuminanceRT&&this.currentLuminanceRT.dispose(),this.previousLuminanceRT&&this.previousLuminanceRT.dispose();const t={minFilter:w.V,magFilter:w.V,format:w.Ib};this.luminanceRT=new K(this.resolution,this.resolution,t),this.luminanceRT.texture.name=\\\\\\\"AdaptiveToneMappingPass.l\\\\\\\",this.luminanceRT.texture.generateMipmaps=!1,this.previousLuminanceRT=new K(this.resolution,this.resolution,t),this.previousLuminanceRT.texture.name=\\\\\\\"AdaptiveToneMappingPass.pl\\\\\\\",this.previousLuminanceRT.texture.generateMipmaps=!1,t.minFilter=w.Y,t.generateMipmaps=!0,this.currentLuminanceRT=new K(this.resolution,this.resolution,t),this.currentLuminanceRT.texture.name=\\\\\\\"AdaptiveToneMappingPass.cl\\\\\\\",this.adaptive&&(this.materialToneMap.defines.ADAPTED_LUMINANCE=\\\\\\\"\\\\\\\",this.materialToneMap.uniforms.luminanceMap.value=this.luminanceRT.texture),this.fsQuad.material=new lt.a({color:7829367}),this.materialLuminance.needsUpdate=!0,this.materialAdaptiveLum.needsUpdate=!0,this.materialToneMap.needsUpdate=!0}setAdaptive(t){t?(this.adaptive=!0,this.materialToneMap.defines.ADAPTED_LUMINANCE=\\\\\\\"\\\\\\\",this.materialToneMap.uniforms.luminanceMap.value=this.luminanceRT.texture):(this.adaptive=!1,delete this.materialToneMap.defines.ADAPTED_LUMINANCE,this.materialToneMap.uniforms.luminanceMap.value=null),this.materialToneMap.needsUpdate=!0}setAdaptionRate(t){t&&(this.materialAdaptiveLum.uniforms.tau.value=Math.abs(t))}setMinLuminance(t){t&&(this.materialToneMap.uniforms.minLuminance.value=t,this.materialAdaptiveLum.uniforms.minLuminance.value=t)}setMaxLuminance(t){t&&(this.materialToneMap.uniforms.maxLuminance.value=t)}setAverageLuminance(t){t&&(this.materialToneMap.uniforms.averageLuminance.value=t)}setMiddleGrey(t){t&&(this.materialToneMap.uniforms.middleGrey.value=t)}dispose(){this.luminanceRT&&this.luminanceRT.dispose(),this.previousLuminanceRT&&this.previousLuminanceRT.dispose(),this.currentLuminanceRT&&this.currentLuminanceRT.dispose(),this.materialLuminance&&this.materialLuminance.dispose(),this.materialAdaptiveLum&&this.materialAdaptiveLum.dispose(),this.materialCopy&&this.materialCopy.dispose(),this.materialToneMap&&this.materialToneMap.dispose()}}const Mj=new class extends ua{constructor(){super(...arguments),this.adaptive=ha.BOOLEAN(1,{...xj}),this.averageLuminance=ha.FLOAT(.7,{...xj}),this.midGrey=ha.FLOAT(.04,{...xj}),this.maxLuminance=ha.FLOAT(16,{range:[0,20],...xj}),this.adaptiveRange=ha.FLOAT(2,{range:[0,10],...xj})}};class Ej extends bj{constructor(){super(...arguments),this.paramsConfig=Mj}static type(){return\\\\\\\"adaptiveToneMapping\\\\\\\"}_createPass(t){const e=new Aj(this.pv.adaptive,t.resolution.x);return this.updatePass(e),e}updatePass(t){t.setMaxLuminance(this.pv.maxLuminance),t.setMiddleGrey(this.pv.midGrey),t.setAverageLuminance(this.pv.averageLuminance)}}const Sj={uniforms:{damp:{value:.96},tOld:{value:null},tNew:{value:null}},vertexShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\tvUv = uv;\\\\n\\\\t\\\\t\\\\tgl_Position = projectionMatrix * modelViewMatrix * vec4( position, 1.0 );\\\\n\\\\n\\\\t\\\\t}\\\\\\\",fragmentShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\tuniform float damp;\\\\n\\\\n\\\\t\\\\tuniform sampler2D tOld;\\\\n\\\\t\\\\tuniform sampler2D tNew;\\\\n\\\\n\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\n\\\\t\\\\tvec4 when_gt( vec4 x, float y ) {\\\\n\\\\n\\\\t\\\\t\\\\treturn max( sign( x - y ), 0.0 );\\\\n\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\tvec4 texelOld = texture2D( tOld, vUv );\\\\n\\\\t\\\\t\\\\tvec4 texelNew = texture2D( tNew, vUv );\\\\n\\\\n\\\\t\\\\t\\\\ttexelOld *= damp * when_gt( texelOld, 0.1 );\\\\n\\\\n\\\\t\\\\t\\\\tgl_FragColor = max(texelNew, texelOld);\\\\n\\\\n\\\\t\\\\t}\\\\\\\"};class Cj extends km{constructor(t=.96){super(),void 0===Sj&&console.error(\\\\\\\"THREE.AfterimagePass relies on AfterimageShader\\\\\\\"),this.shader=Sj,this.uniforms=I.clone(this.shader.uniforms),this.uniforms.damp.value=t,this.textureComp=new K(window.innerWidth,window.innerHeight,{minFilter:w.V,magFilter:w.ob,format:w.Ib}),this.textureOld=new K(window.innerWidth,window.innerHeight,{minFilter:w.V,magFilter:w.ob,format:w.Ib}),this.shaderMaterial=new F({uniforms:this.uniforms,vertexShader:this.shader.vertexShader,fragmentShader:this.shader.fragmentShader}),this.compFsQuad=new Vm(this.shaderMaterial);const e=new lt.a;this.copyFsQuad=new Vm(e)}render(t,e,n){this.uniforms.tOld.value=this.textureOld.texture,this.uniforms.tNew.value=n.texture,t.setRenderTarget(this.textureComp),this.compFsQuad.render(t),this.copyFsQuad.material.map=this.textureComp.texture,this.renderToScreen?(t.setRenderTarget(null),this.copyFsQuad.render(t)):(t.setRenderTarget(e),this.clear&&t.clear(),this.copyFsQuad.render(t));const i=this.textureOld;this.textureOld=this.textureComp,this.textureComp=i}setSize(t,e){this.textureComp.setSize(t,e),this.textureOld.setSize(t,e)}}const Nj=new class extends ua{constructor(){super(...arguments),this.damp=ha.FLOAT(.96,{range:[0,1],rangeLocked:[!0,!0],...xj})}};class Lj extends bj{constructor(){super(...arguments),this.paramsConfig=Nj}static type(){return\\\\\\\"afterImage\\\\\\\"}_createPass(t){const e=new Cj;return this.updatePass(e),e}updatePass(t){t.uniforms.damp.value=this.pv.damp}}const Oj={uniforms:{tDiffuse:{value:null},opacity:{value:1}},vertexShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\tvUv = uv;\\\\n\\\\t\\\\t\\\\tgl_Position = projectionMatrix * modelViewMatrix * vec4( position, 1.0 );\\\\n\\\\n\\\\t\\\\t}\\\\\\\",fragmentShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\tuniform float opacity;\\\\n\\\\n\\\\t\\\\tuniform sampler2D tDiffuse;\\\\n\\\\n\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\tvec4 base = texture2D( tDiffuse, vUv );\\\\n\\\\n\\\\t\\\\t\\\\tvec3 lumCoeff = vec3( 0.25, 0.65, 0.1 );\\\\n\\\\t\\\\t\\\\tfloat lum = dot( lumCoeff, base.rgb );\\\\n\\\\t\\\\t\\\\tvec3 blend = vec3( lum );\\\\n\\\\n\\\\t\\\\t\\\\tfloat L = min( 1.0, max( 0.0, 10.0 * ( lum - 0.45 ) ) );\\\\n\\\\n\\\\t\\\\t\\\\tvec3 result1 = 2.0 * base.rgb * blend;\\\\n\\\\t\\\\t\\\\tvec3 result2 = 1.0 - 2.0 * ( 1.0 - blend ) * ( 1.0 - base.rgb );\\\\n\\\\n\\\\t\\\\t\\\\tvec3 newColor = mix( result1, result2, L );\\\\n\\\\n\\\\t\\\\t\\\\tfloat A2 = opacity * base.a;\\\\n\\\\t\\\\t\\\\tvec3 mixRGB = A2 * newColor.rgb;\\\\n\\\\t\\\\t\\\\tmixRGB += ( ( 1.0 - A2 ) * base.rgb );\\\\n\\\\n\\\\t\\\\t\\\\tgl_FragColor = vec4( mixRGB, base.a );\\\\n\\\\n\\\\t\\\\t}\\\\\\\"};const Pj=new class extends ua{constructor(){super(...arguments),this.opacity=ha.FLOAT(.95,{range:[-5,5],rangeLocked:[!0,!0],...xj})}};class Rj extends bj{constructor(){super(...arguments),this.paramsConfig=Pj}static type(){return\\\\\\\"bleach\\\\\\\"}_createPass(t){const e=new Hm(Oj);return this.updatePass(e),e}updatePass(t){t.uniforms.opacity.value=this.pv.opacity}}const Ij={uniforms:{tDiffuse:{value:null},brightness:{value:0},contrast:{value:0}},vertexShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\tvUv = uv;\\\\n\\\\n\\\\t\\\\t\\\\tgl_Position = projectionMatrix * modelViewMatrix * vec4( position, 1.0 );\\\\n\\\\n\\\\t\\\\t}\\\\\\\",fragmentShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\tuniform sampler2D tDiffuse;\\\\n\\\\t\\\\tuniform float brightness;\\\\n\\\\t\\\\tuniform float contrast;\\\\n\\\\n\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\tgl_FragColor = texture2D( tDiffuse, vUv );\\\\n\\\\n\\\\t\\\\t\\\\tgl_FragColor.rgb += brightness;\\\\n\\\\n\\\\t\\\\t\\\\tif (contrast > 0.0) {\\\\n\\\\t\\\\t\\\\t\\\\tgl_FragColor.rgb = (gl_FragColor.rgb - 0.5) / (1.0 - contrast) + 0.5;\\\\n\\\\t\\\\t\\\\t} else {\\\\n\\\\t\\\\t\\\\t\\\\tgl_FragColor.rgb = (gl_FragColor.rgb - 0.5) * (1.0 + contrast) + 0.5;\\\\n\\\\t\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\t}\\\\\\\"};const Fj=new class extends ua{constructor(){super(...arguments),this.brightness=ha.FLOAT(0,{range:[-1,1],rangeLocked:[!1,!1],...xj}),this.contrast=ha.FLOAT(0,{range:[-1,1],rangeLocked:[!1,!1],...xj}),this.transparent=ha.BOOLEAN(1,xj)}};class Dj extends bj{constructor(){super(...arguments),this.paramsConfig=Fj}static type(){return\\\\\\\"brightnessContrast\\\\\\\"}_createPass(t){const e=new Hm(Ij);return e.fsQuad.material.transparent=!0,this.updatePass(e),e}updatePass(t){t.uniforms.brightness.value=this.pv.brightness,t.uniforms.contrast.value=this.pv.contrast,t.material.transparent=this.pv.transparent}}class Bj extends km{constructor(t,e){super(),this.needsSwap=!1,this.clearColor=void 0!==t?t:0,this.clearAlpha=void 0!==e?e:0,this._oldClearColor=new D.a}render(t,e,n){let i;this.clearColor&&(t.getClearColor(this._oldClearColor),i=t.getClearAlpha(),t.setClearColor(this.clearColor,this.clearAlpha)),t.setRenderTarget(this.renderToScreen?null:n),t.clear(),this.clearColor&&t.setClearColor(this._oldClearColor,i)}}const zj=new class extends ua{};class kj extends bj{constructor(){super(...arguments),this.paramsConfig=zj}static type(){return\\\\\\\"clear\\\\\\\"}_createPass(t){const e=new Bj;return this.updatePass(e),e}updatePass(t){}}const Uj=new class extends ua{};class Gj extends bj{constructor(){super(...arguments),this.paramsConfig=Uj}static type(){return\\\\\\\"clearMask\\\\\\\"}_createPass(t){const e=new Wm;return this.updatePass(e),e}updatePass(t){}}const Vj={uniforms:{tDiffuse:{value:null},powRGB:{value:new p.a(2,2,2)},mulRGB:{value:new p.a(1,1,1)},addRGB:{value:new p.a(0,0,0)}},vertexShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\tvUv = uv;\\\\n\\\\n\\\\t\\\\t\\\\tgl_Position = projectionMatrix * modelViewMatrix * vec4( position, 1.0 );\\\\n\\\\n\\\\t\\\\t}\\\\\\\",fragmentShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\tuniform sampler2D tDiffuse;\\\\n\\\\t\\\\tuniform vec3 powRGB;\\\\n\\\\t\\\\tuniform vec3 mulRGB;\\\\n\\\\t\\\\tuniform vec3 addRGB;\\\\n\\\\n\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\tgl_FragColor = texture2D( tDiffuse, vUv );\\\\n\\\\t\\\\t\\\\tgl_FragColor.rgb = mulRGB * pow( ( gl_FragColor.rgb + addRGB ), powRGB );\\\\n\\\\n\\\\t\\\\t}\\\\\\\"};const Hj=new class extends ua{constructor(){super(...arguments),this.pow=ha.VECTOR3([2,2,2],{...xj}),this.mult=ha.COLOR([1,1,1],{...xj}),this.add=ha.COLOR([0,0,0],{...xj})}};class jj extends bj{constructor(){super(...arguments),this.paramsConfig=Hj}static type(){return\\\\\\\"colorCorrection\\\\\\\"}_createPass(t){const e=new Hm(Vj);return this.updatePass(e),e}updatePass(t){t.uniforms.powRGB.value.copy(this.pv.pow),t.uniforms.mulRGB.value.set(this.pv.mult.r,this.pv.mult.g,this.pv.mult.b),t.uniforms.addRGB.value.set(this.pv.add.r,this.pv.add.g,this.pv.add.b)}}const Wj=new class extends ua{constructor(){super(...arguments),this.opacity=ha.FLOAT(1,{range:[0,1],rangeLocked:[!0,!0],...xj}),this.transparent=ha.BOOLEAN(1,xj)}};class qj extends bj{constructor(){super(...arguments),this.paramsConfig=Wj}static type(){return\\\\\\\"copy\\\\\\\"}_createPass(t){const e=new Hm(zm);return this.updatePass(e),e}updatePass(t){t.uniforms.opacity.value=this.pv.opacity,t.material.transparent=this.pv.transparent}}const Xj={uniforms:{textureWidth:{value:1},textureHeight:{value:1},focalDepth:{value:1},focalLength:{value:24},fstop:{value:.9},tColor:{value:null},tDepth:{value:null},maxblur:{value:1},showFocus:{value:0},manualdof:{value:0},vignetting:{value:0},depthblur:{value:0},threshold:{value:.5},gain:{value:2},bias:{value:.5},fringe:{value:.7},znear:{value:.1},zfar:{value:100},noise:{value:1},dithering:{value:1e-4},pentagon:{value:0},shaderFocus:{value:1},focusCoords:{value:new d.a}},vertexShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\tvUv = uv;\\\\n\\\\t\\\\t\\\\tgl_Position = projectionMatrix * modelViewMatrix * vec4( position, 1.0 );\\\\n\\\\n\\\\t\\\\t}\\\\\\\",fragmentShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\t#include \\\\n\\\\n\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\n\\\\t\\\\tuniform sampler2D tColor;\\\\n\\\\t\\\\tuniform sampler2D tDepth;\\\\n\\\\t\\\\tuniform float textureWidth;\\\\n\\\\t\\\\tuniform float textureHeight;\\\\n\\\\n\\\\t\\\\tuniform float focalDepth; //focal distance value in meters, but you may use autofocus option below\\\\n\\\\t\\\\tuniform float focalLength; //focal length in mm\\\\n\\\\t\\\\tuniform float fstop; //f-stop value\\\\n\\\\t\\\\tuniform bool showFocus; //show debug focus point and focal range (red = focal point, green = focal range)\\\\n\\\\n\\\\t\\\\t/*\\\\n\\\\t\\\\tmake sure that these two values are the same for your camera, otherwise distances will be wrong.\\\\n\\\\t\\\\t*/\\\\n\\\\n\\\\t\\\\tuniform float znear; // camera clipping start\\\\n\\\\t\\\\tuniform float zfar; // camera clipping end\\\\n\\\\n\\\\t\\\\t//------------------------------------------\\\\n\\\\t\\\\t//user variables\\\\n\\\\n\\\\t\\\\tconst int samples = SAMPLES; //samples on the first ring\\\\n\\\\t\\\\tconst int rings = RINGS; //ring count\\\\n\\\\n\\\\t\\\\tconst int maxringsamples = rings * samples;\\\\n\\\\n\\\\t\\\\tuniform bool manualdof; // manual dof calculation\\\\n\\\\t\\\\tfloat ndofstart = 1.0; // near dof blur start\\\\n\\\\t\\\\tfloat ndofdist = 2.0; // near dof blur falloff distance\\\\n\\\\t\\\\tfloat fdofstart = 1.0; // far dof blur start\\\\n\\\\t\\\\tfloat fdofdist = 3.0; // far dof blur falloff distance\\\\n\\\\n\\\\t\\\\tfloat CoC = 0.03; //circle of confusion size in mm (35mm film = 0.03mm)\\\\n\\\\n\\\\t\\\\tuniform bool vignetting; // use optical lens vignetting\\\\n\\\\n\\\\t\\\\tfloat vignout = 1.3; // vignetting outer border\\\\n\\\\t\\\\tfloat vignin = 0.0; // vignetting inner border\\\\n\\\\t\\\\tfloat vignfade = 22.0; // f-stops till vignete fades\\\\n\\\\n\\\\t\\\\tuniform bool shaderFocus;\\\\n\\\\t\\\\t// disable if you use external focalDepth value\\\\n\\\\n\\\\t\\\\tuniform vec2 focusCoords;\\\\n\\\\t\\\\t// autofocus point on screen (0.0,0.0 - left lower corner, 1.0,1.0 - upper right)\\\\n\\\\t\\\\t// if center of screen use vec2(0.5, 0.5);\\\\n\\\\n\\\\t\\\\tuniform float maxblur;\\\\n\\\\t\\\\t//clamp value of max blur (0.0 = no blur, 1.0 default)\\\\n\\\\n\\\\t\\\\tuniform float threshold; // highlight threshold;\\\\n\\\\t\\\\tuniform float gain; // highlight gain;\\\\n\\\\n\\\\t\\\\tuniform float bias; // bokeh edge bias\\\\n\\\\t\\\\tuniform float fringe; // bokeh chromatic aberration / fringing\\\\n\\\\n\\\\t\\\\tuniform bool noise; //use noise instead of pattern for sample dithering\\\\n\\\\n\\\\t\\\\tuniform float dithering;\\\\n\\\\n\\\\t\\\\tuniform bool depthblur; // blur the depth buffer\\\\n\\\\t\\\\tfloat dbsize = 1.25; // depth blur size\\\\n\\\\n\\\\t\\\\t/*\\\\n\\\\t\\\\tnext part is experimental\\\\n\\\\t\\\\tnot looking good with small sample and ring count\\\\n\\\\t\\\\tlooks okay starting from samples = 4, rings = 4\\\\n\\\\t\\\\t*/\\\\n\\\\n\\\\t\\\\tuniform bool pentagon; //use pentagon as bokeh shape?\\\\n\\\\t\\\\tfloat feather = 0.4; //pentagon shape feather\\\\n\\\\n\\\\t\\\\t//------------------------------------------\\\\n\\\\n\\\\t\\\\tfloat penta(vec2 coords) {\\\\n\\\\t\\\\t\\\\t//pentagonal shape\\\\n\\\\t\\\\t\\\\tfloat scale = float(rings) - 1.3;\\\\n\\\\t\\\\t\\\\tvec4 HS0 = vec4( 1.0, 0.0, 0.0, 1.0);\\\\n\\\\t\\\\t\\\\tvec4 HS1 = vec4( 0.309016994, 0.951056516, 0.0, 1.0);\\\\n\\\\t\\\\t\\\\tvec4 HS2 = vec4(-0.809016994, 0.587785252, 0.0, 1.0);\\\\n\\\\t\\\\t\\\\tvec4 HS3 = vec4(-0.809016994,-0.587785252, 0.0, 1.0);\\\\n\\\\t\\\\t\\\\tvec4 HS4 = vec4( 0.309016994,-0.951056516, 0.0, 1.0);\\\\n\\\\t\\\\t\\\\tvec4 HS5 = vec4( 0.0 ,0.0 , 1.0, 1.0);\\\\n\\\\n\\\\t\\\\t\\\\tvec4 one = vec4( 1.0 );\\\\n\\\\n\\\\t\\\\t\\\\tvec4 P = vec4((coords),vec2(scale, scale));\\\\n\\\\n\\\\t\\\\t\\\\tvec4 dist = vec4(0.0);\\\\n\\\\t\\\\t\\\\tfloat inorout = -4.0;\\\\n\\\\n\\\\t\\\\t\\\\tdist.x = dot( P, HS0 );\\\\n\\\\t\\\\t\\\\tdist.y = dot( P, HS1 );\\\\n\\\\t\\\\t\\\\tdist.z = dot( P, HS2 );\\\\n\\\\t\\\\t\\\\tdist.w = dot( P, HS3 );\\\\n\\\\n\\\\t\\\\t\\\\tdist = smoothstep( -feather, feather, dist );\\\\n\\\\n\\\\t\\\\t\\\\tinorout += dot( dist, one );\\\\n\\\\n\\\\t\\\\t\\\\tdist.x = dot( P, HS4 );\\\\n\\\\t\\\\t\\\\tdist.y = HS5.w - abs( P.z );\\\\n\\\\n\\\\t\\\\t\\\\tdist = smoothstep( -feather, feather, dist );\\\\n\\\\t\\\\t\\\\tinorout += dist.x;\\\\n\\\\n\\\\t\\\\t\\\\treturn clamp( inorout, 0.0, 1.0 );\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\tfloat bdepth(vec2 coords) {\\\\n\\\\t\\\\t\\\\t// Depth buffer blur\\\\n\\\\t\\\\t\\\\tfloat d = 0.0;\\\\n\\\\t\\\\t\\\\tfloat kernel[9];\\\\n\\\\t\\\\t\\\\tvec2 offset[9];\\\\n\\\\n\\\\t\\\\t\\\\tvec2 wh = vec2(1.0/textureWidth,1.0/textureHeight) * dbsize;\\\\n\\\\n\\\\t\\\\t\\\\toffset[0] = vec2(-wh.x,-wh.y);\\\\n\\\\t\\\\t\\\\toffset[1] = vec2( 0.0, -wh.y);\\\\n\\\\t\\\\t\\\\toffset[2] = vec2( wh.x -wh.y);\\\\n\\\\n\\\\t\\\\t\\\\toffset[3] = vec2(-wh.x, 0.0);\\\\n\\\\t\\\\t\\\\toffset[4] = vec2( 0.0, 0.0);\\\\n\\\\t\\\\t\\\\toffset[5] = vec2( wh.x, 0.0);\\\\n\\\\n\\\\t\\\\t\\\\toffset[6] = vec2(-wh.x, wh.y);\\\\n\\\\t\\\\t\\\\toffset[7] = vec2( 0.0, wh.y);\\\\n\\\\t\\\\t\\\\toffset[8] = vec2( wh.x, wh.y);\\\\n\\\\n\\\\t\\\\t\\\\tkernel[0] = 1.0/16.0; kernel[1] = 2.0/16.0; kernel[2] = 1.0/16.0;\\\\n\\\\t\\\\t\\\\tkernel[3] = 2.0/16.0; kernel[4] = 4.0/16.0; kernel[5] = 2.0/16.0;\\\\n\\\\t\\\\t\\\\tkernel[6] = 1.0/16.0; kernel[7] = 2.0/16.0; kernel[8] = 1.0/16.0;\\\\n\\\\n\\\\n\\\\t\\\\t\\\\tfor( int i=0; i<9; i++ ) {\\\\n\\\\t\\\\t\\\\t\\\\tfloat tmp = texture2D(tDepth, coords + offset[i]).r;\\\\n\\\\t\\\\t\\\\t\\\\td += tmp * kernel[i];\\\\n\\\\t\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\t\\\\treturn d;\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\n\\\\t\\\\tvec3 color(vec2 coords,float blur) {\\\\n\\\\t\\\\t\\\\t//processing the sample\\\\n\\\\n\\\\t\\\\t\\\\tvec3 col = vec3(0.0);\\\\n\\\\t\\\\t\\\\tvec2 texel = vec2(1.0/textureWidth,1.0/textureHeight);\\\\n\\\\n\\\\t\\\\t\\\\tcol.r = texture2D(tColor,coords + vec2(0.0,1.0)*texel*fringe*blur).r;\\\\n\\\\t\\\\t\\\\tcol.g = texture2D(tColor,coords + vec2(-0.866,-0.5)*texel*fringe*blur).g;\\\\n\\\\t\\\\t\\\\tcol.b = texture2D(tColor,coords + vec2(0.866,-0.5)*texel*fringe*blur).b;\\\\n\\\\n\\\\t\\\\t\\\\tvec3 lumcoeff = vec3(0.299,0.587,0.114);\\\\n\\\\t\\\\t\\\\tfloat lum = dot(col.rgb, lumcoeff);\\\\n\\\\t\\\\t\\\\tfloat thresh = max((lum-threshold)*gain, 0.0);\\\\n\\\\t\\\\t\\\\treturn col+mix(vec3(0.0),col,thresh*blur);\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\tvec3 debugFocus(vec3 col, float blur, float depth) {\\\\n\\\\t\\\\t\\\\tfloat edge = 0.002*depth; //distance based edge smoothing\\\\n\\\\t\\\\t\\\\tfloat m = clamp(smoothstep(0.0,edge,blur),0.0,1.0);\\\\n\\\\t\\\\t\\\\tfloat e = clamp(smoothstep(1.0-edge,1.0,blur),0.0,1.0);\\\\n\\\\n\\\\t\\\\t\\\\tcol = mix(col,vec3(1.0,0.5,0.0),(1.0-m)*0.6);\\\\n\\\\t\\\\t\\\\tcol = mix(col,vec3(0.0,0.5,1.0),((1.0-e)-(1.0-m))*0.2);\\\\n\\\\n\\\\t\\\\t\\\\treturn col;\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\tfloat linearize(float depth) {\\\\n\\\\t\\\\t\\\\treturn -zfar * znear / (depth * (zfar - znear) - zfar);\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\tfloat vignette() {\\\\n\\\\t\\\\t\\\\tfloat dist = distance(vUv.xy, vec2(0.5,0.5));\\\\n\\\\t\\\\t\\\\tdist = smoothstep(vignout+(fstop/vignfade), vignin+(fstop/vignfade), dist);\\\\n\\\\t\\\\t\\\\treturn clamp(dist,0.0,1.0);\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\tfloat gather(float i, float j, int ringsamples, inout vec3 col, float w, float h, float blur) {\\\\n\\\\t\\\\t\\\\tfloat rings2 = float(rings);\\\\n\\\\t\\\\t\\\\tfloat step = PI*2.0 / float(ringsamples);\\\\n\\\\t\\\\t\\\\tfloat pw = cos(j*step)*i;\\\\n\\\\t\\\\t\\\\tfloat ph = sin(j*step)*i;\\\\n\\\\t\\\\t\\\\tfloat p = 1.0;\\\\n\\\\t\\\\t\\\\tif (pentagon) {\\\\n\\\\t\\\\t\\\\t\\\\tp = penta(vec2(pw,ph));\\\\n\\\\t\\\\t\\\\t}\\\\n\\\\t\\\\t\\\\tcol += color(vUv.xy + vec2(pw*w,ph*h), blur) * mix(1.0, i/rings2, bias) * p;\\\\n\\\\t\\\\t\\\\treturn 1.0 * mix(1.0, i /rings2, bias) * p;\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\t\\\\t\\\\t//scene depth calculation\\\\n\\\\n\\\\t\\\\t\\\\tfloat depth = linearize(texture2D(tDepth,vUv.xy).x);\\\\n\\\\n\\\\t\\\\t\\\\t// Blur depth?\\\\n\\\\t\\\\t\\\\tif ( depthblur ) {\\\\n\\\\t\\\\t\\\\t\\\\tdepth = linearize(bdepth(vUv.xy));\\\\n\\\\t\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\t\\\\t//focal plane calculation\\\\n\\\\n\\\\t\\\\t\\\\tfloat fDepth = focalDepth;\\\\n\\\\n\\\\t\\\\t\\\\tif (shaderFocus) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tfDepth = linearize(texture2D(tDepth,focusCoords).x);\\\\n\\\\n\\\\t\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\t\\\\t// dof blur factor calculation\\\\n\\\\n\\\\t\\\\t\\\\tfloat blur = 0.0;\\\\n\\\\n\\\\t\\\\t\\\\tif (manualdof) {\\\\n\\\\t\\\\t\\\\t\\\\tfloat a = depth-fDepth; // Focal plane\\\\n\\\\t\\\\t\\\\t\\\\tfloat b = (a-fdofstart)/fdofdist; // Far DoF\\\\n\\\\t\\\\t\\\\t\\\\tfloat c = (-a-ndofstart)/ndofdist; // Near Dof\\\\n\\\\t\\\\t\\\\t\\\\tblur = (a>0.0) ? b : c;\\\\n\\\\t\\\\t\\\\t} else {\\\\n\\\\t\\\\t\\\\t\\\\tfloat f = focalLength; // focal length in mm\\\\n\\\\t\\\\t\\\\t\\\\tfloat d = fDepth*1000.0; // focal plane in mm\\\\n\\\\t\\\\t\\\\t\\\\tfloat o = depth*1000.0; // depth in mm\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tfloat a = (o*f)/(o-f);\\\\n\\\\t\\\\t\\\\t\\\\tfloat b = (d*f)/(d-f);\\\\n\\\\t\\\\t\\\\t\\\\tfloat c = (d-f)/(d*fstop*CoC);\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tblur = abs(a-b)*c;\\\\n\\\\t\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\t\\\\tblur = clamp(blur,0.0,1.0);\\\\n\\\\n\\\\t\\\\t\\\\t// calculation of pattern for dithering\\\\n\\\\n\\\\t\\\\t\\\\tvec2 noise = vec2(rand(vUv.xy), rand( vUv.xy + vec2( 0.4, 0.6 ) ) )*dithering*blur;\\\\n\\\\n\\\\t\\\\t\\\\t// getting blur x and y step factor\\\\n\\\\n\\\\t\\\\t\\\\tfloat w = (1.0/textureWidth)*blur*maxblur+noise.x;\\\\n\\\\t\\\\t\\\\tfloat h = (1.0/textureHeight)*blur*maxblur+noise.y;\\\\n\\\\n\\\\t\\\\t\\\\t// calculation of final color\\\\n\\\\n\\\\t\\\\t\\\\tvec3 col = vec3(0.0);\\\\n\\\\n\\\\t\\\\t\\\\tif(blur < 0.05) {\\\\n\\\\t\\\\t\\\\t\\\\t//some optimization thingy\\\\n\\\\t\\\\t\\\\t\\\\tcol = texture2D(tColor, vUv.xy).rgb;\\\\n\\\\t\\\\t\\\\t} else {\\\\n\\\\t\\\\t\\\\t\\\\tcol = texture2D(tColor, vUv.xy).rgb;\\\\n\\\\t\\\\t\\\\t\\\\tfloat s = 1.0;\\\\n\\\\t\\\\t\\\\t\\\\tint ringsamples;\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tfor (int i = 1; i <= rings; i++) {\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t/*unboxstart*/\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tringsamples = i * samples;\\\\n\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tfor (int j = 0 ; j < maxringsamples ; j++) {\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif (j >= ringsamples) break;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\ts += gather(float(i), float(j), ringsamples, col, w, h, blur);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t}\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t/*unboxend*/\\\\n\\\\t\\\\t\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tcol /= s; //divide by sample count\\\\n\\\\t\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\t\\\\tif (showFocus) {\\\\n\\\\t\\\\t\\\\t\\\\tcol = debugFocus(col, blur, depth);\\\\n\\\\t\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\t\\\\tif (vignetting) {\\\\n\\\\t\\\\t\\\\t\\\\tcol *= vignette();\\\\n\\\\t\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\t\\\\tgl_FragColor.rgb = col;\\\\n\\\\t\\\\t\\\\tgl_FragColor.a = 1.0;\\\\n\\\\t\\\\t}\\\\\\\"},Yj={uniforms:{mNear:{value:1},mFar:{value:1e3}},vertexShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\tvarying float vViewZDepth;\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\t#include \\\\n\\\\t\\\\t\\\\t#include \\\\n\\\\n\\\\t\\\\t\\\\tvViewZDepth = - mvPosition.z;\\\\n\\\\n\\\\t\\\\t}\\\\\\\",fragmentShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\tuniform float mNear;\\\\n\\\\t\\\\tuniform float mFar;\\\\n\\\\n\\\\t\\\\tvarying float vViewZDepth;\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\tfloat color = 1.0 - smoothstep( mNear, mFar, vViewZDepth );\\\\n\\\\t\\\\t\\\\tgl_FragColor = vec4( vec3( color ), 1.0 );\\\\n\\\\n\\\\t\\\\t}\\\\\\\"};class $j{constructor(t){this._scene=t}scene(){return this._scene}with_overriden_material(t,e,n,i){const s={};let r;this._scene.traverse((i=>{const o=i;if(o.material){const i=o.geometry;if(i){const a=o.customDepthDOFMaterial;if(a){if(r=a,r.uniforms)for(let t of Object.keys(n))r.uniforms[t].value=n[t].value}else r=fr.markedAsInstance(i)?e:t;r&&(s[o.uuid]=o.material,o.material=r)}}})),i(),this._scene.traverse((t=>{const e=t;if(e.material){e.geometry&&(e.material=s[e.uuid])}}));for(let t of Object.keys(s))delete s[t]}}class Jj{constructor(t,e,n,i){this._depth_of_field_node=t,this._scene=e,this._camera=n,this._resolution=i,this._camera_uniforms={mNear:{value:0},mFar:{value:0}},this.enabled=!0,this.needsSwap=!0,this.clear=!0,this.renderToScreen=!0,this._processing_scene=new vs,this.clear_color=new D.a(1,1,1),this._prev_clear_color=new D.a,this._core_scene=new $j(this._scene);const s=3,r=4;this._processing_camera=new ot.a(this._resolution.x/-2,this._resolution.x/2,this._resolution.y/2,this._resolution.y/-2,-1e4,1e4),this._processing_camera.position.z=100,this._processing_scene.add(this._processing_camera);var o={minFilter:w.V,magFilter:w.V,format:w.ic};this._rtTextureDepth=new K(this._resolution.x,this._resolution.y,o),this._rtTextureColor=new K(this._resolution.x,this._resolution.y,o);var a=Xj;a||console.error(\\\\\\\"BokehPass relies on BokehShader\\\\\\\"),this.bokeh_uniforms=I.clone(a.uniforms),this.bokeh_uniforms.tColor.value=this._rtTextureColor.texture,this.bokeh_uniforms.tDepth.value=this._rtTextureDepth.texture,this.bokeh_uniforms.textureWidth.value=this._resolution.x,this.bokeh_uniforms.textureHeight.value=this._resolution.y,this.bokeh_material=new F({uniforms:this.bokeh_uniforms,vertexShader:a.vertexShader,fragmentShader:a.fragmentShader,defines:{RINGS:s,SAMPLES:r}}),this._quad=new B.a(new L(this._resolution.x,this._resolution.y),this.bokeh_material),this._quad.position.z=-500,this._processing_scene.add(this._quad);var l=Yj;l||console.error(\\\\\\\"BokehPass relies on BokehDepthShader\\\\\\\"),this.materialDepth=new F({uniforms:l.uniforms,vertexShader:l.vertexShader,fragmentShader:l.fragmentShader}),this.materialDepthInstance=new F({uniforms:l.uniforms,vertexShader:\\\\\\\"#include \\\\n\\\\nvec3 rotate_with_quat( vec3 v, vec4 q )\\\\n{\\\\n\\\\treturn v + 2.0 * cross( q.xyz, cross( q.xyz, v ) + q.w * v );\\\\n}\\\\n\\\\n\\\\nattribute vec4 instanceOrientation;\\\\nattribute vec3 instancePosition;\\\\nattribute vec3 instanceScale;\\\\nvarying float vViewZDepth;\\\\n\\\\n\\\\n\\\\nvoid main() {\\\\n\\\\n\\\\tvec3 v_POLYGON_instance_transform1_position = vec3(position);\\\\n\\\\tv_POLYGON_instance_transform1_position *= instanceScale;\\\\n\\\\tv_POLYGON_instance_transform1_position = rotate_with_quat( v_POLYGON_instance_transform1_position, instanceOrientation );\\\\n\\\\tv_POLYGON_instance_transform1_position += instancePosition;\\\\n\\\\t\\\\n\\\\t// replaces #include \\\\n\\\\tvec3 transformed = v_POLYGON_instance_transform1_position;\\\\n\\\\n\\\\n\\\\t#include \\\\n\\\\n\\\\tvViewZDepth = - mvPosition.z;\\\\n}\\\\\\\",fragmentShader:l.fragmentShader}),this.update_camera_uniforms_with_node(this._depth_of_field_node,this._camera)}setSize(t,e){this._rtTextureDepth.setSize(t,e),this._rtTextureColor.setSize(t,e),this.bokeh_uniforms.textureWidth.value=t,this.bokeh_uniforms.textureHeight.value=e}dispose(){this._rtTextureDepth.dispose(),this._rtTextureColor.dispose()}render(t,e,n){t.getClearColor(this._prev_clear_color),t.setClearColor(this.clear_color),t.clear(),t.setRenderTarget(this._rtTextureColor),t.clear(),t.render(this._scene,this._camera),t.setClearColor(0),this._core_scene.with_overriden_material(this.materialDepth,this.materialDepthInstance,this._camera_uniforms,(()=>{t.setRenderTarget(this._rtTextureDepth),t.clear(),t.render(this._scene,this._camera)})),t.setRenderTarget(null),t.clear(),t.render(this._processing_scene,this._processing_camera),t.setClearColor(this._prev_clear_color)}update_camera_uniforms_with_node(t,e){this.bokeh_uniforms.focalLength.value=e.getFocalLength(),this.bokeh_uniforms.znear.value=e.near,this.bokeh_uniforms.zfar.value=e.far;var n=Kj.smoothstep(e.near,e.far,t.pv.focalDepth),i=Kj.linearize(1-n,e.near,e.far);this.bokeh_uniforms.focalDepth.value=i,this._camera_uniforms={mNear:{value:e.near},mFar:{value:e.far}};for(let t of[this.materialDepth,this.materialDepthInstance])t.uniforms.mNear.value=this._camera_uniforms.mNear.value,t.uniforms.mFar.value=this._camera_uniforms.mFar.value}}const Zj=new class extends ua{constructor(){super(...arguments),this.focalDepth=ha.FLOAT(10,{range:[0,50],rangeLocked:[!0,!1],step:.001,...xj}),this.fStep=ha.FLOAT(10,{range:[.1,22],rangeLocked:[!0,!0],...xj}),this.maxBlur=ha.FLOAT(2,{range:[0,10],rangeLocked:[!0,!1],...xj}),this.vignetting=ha.BOOLEAN(0,{...xj}),this.depthBlur=ha.BOOLEAN(0,{...xj}),this.threshold=ha.FLOAT(.5,{range:[0,1],rangeLocked:[!0,!0],step:.001,...xj}),this.gain=ha.FLOAT(1,{range:[0,100],rangeLocked:[!0,!0],step:.001,...xj}),this.bias=ha.FLOAT(1,{range:[0,3],rangeLocked:[!0,!0],step:.001,...xj}),this.fringe=ha.FLOAT(.7,{range:[0,5],rangeLocked:[!0,!1],step:.001,...xj}),this.noise=ha.BOOLEAN(0,{...xj}),this.dithering=ha.FLOAT(0,{range:[0,.001],rangeLocked:[!0,!0],step:1e-4,...xj}),this.pentagon=ha.BOOLEAN(0,{...xj}),this.rings=ha.INTEGER(3,{range:[1,8],rangeLocked:[!0,!0],...xj}),this.samples=ha.INTEGER(4,{range:[1,13],rangeLocked:[!0,!0],...xj}),this.clearColor=ha.COLOR([1,1,1],{...xj})}};class Kj extends bj{constructor(){super(...arguments),this.paramsConfig=Zj}static type(){return\\\\\\\"depthOfField\\\\\\\"}static saturate(t){return Math.max(0,Math.min(1,t))}static linearize(t,e,n){return-n*e/(t*(n-e)-n)}static smoothstep(t,e,n){var i=this.saturate((n-t)/(e-t));return i*i*(3-2*i)}_createPass(t){if(t.camera.isPerspectiveCamera){const e=t.camera_node;if(e){const n=new Jj(this,t.scene,e.object,t.resolution);this.updatePass(n);const i=new Mi(this.scene(),\\\\\\\"DOF\\\\\\\");return i.addGraphInput(e.p.near),i.addGraphInput(e.p.far),i.addGraphInput(e.p.fov),i.addGraphInput(this.p.focalDepth),i.addPostDirtyHook(\\\\\\\"post/DOF\\\\\\\",(()=>{this.update_pass_from_camera_node(n,e)})),n}}}update_pass_from_camera_node(t,e){t.update_camera_uniforms_with_node(this,e.object)}updatePass(t){t.bokeh_uniforms.fstop.value=this.pv.fStep,t.bokeh_uniforms.maxblur.value=this.pv.maxBlur,t.bokeh_uniforms.threshold.value=this.pv.threshold,t.bokeh_uniforms.gain.value=this.pv.gain,t.bokeh_uniforms.bias.value=this.pv.bias,t.bokeh_uniforms.fringe.value=this.pv.fringe,t.bokeh_uniforms.dithering.value=this.pv.dithering,t.bokeh_uniforms.noise.value=this.pv.noise?1:0,t.bokeh_uniforms.pentagon.value=this.pv.pentagon?1:0,t.bokeh_uniforms.vignetting.value=this.pv.vignetting?1:0,t.bokeh_uniforms.depthblur.value=this.pv.depthBlur?1:0,t.bokeh_uniforms.shaderFocus.value=0,t.bokeh_uniforms.showFocus.value=0,t.bokeh_uniforms.manualdof.value=0,t.bokeh_uniforms.focusCoords.value.set(.5,.5),t.bokeh_material.defines.RINGS=this.pv.rings,t.bokeh_material.defines.SAMPLES=this.pv.samples,t.bokeh_material.needsUpdate=!0,t.clear_color.copy(this.pv.clearColor)}}const Qj={uniforms:{tDiffuse:{value:null},tSize:{value:new d.a(256,256)},center:{value:new d.a(.5,.5)},angle:{value:1.57},scale:{value:1}},vertexShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\tvUv = uv;\\\\n\\\\t\\\\t\\\\tgl_Position = projectionMatrix * modelViewMatrix * vec4( position, 1.0 );\\\\n\\\\n\\\\t\\\\t}\\\\\\\",fragmentShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\tuniform vec2 center;\\\\n\\\\t\\\\tuniform float angle;\\\\n\\\\t\\\\tuniform float scale;\\\\n\\\\t\\\\tuniform vec2 tSize;\\\\n\\\\n\\\\t\\\\tuniform sampler2D tDiffuse;\\\\n\\\\n\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\n\\\\t\\\\tfloat pattern() {\\\\n\\\\n\\\\t\\\\t\\\\tfloat s = sin( angle ), c = cos( angle );\\\\n\\\\n\\\\t\\\\t\\\\tvec2 tex = vUv * tSize - center;\\\\n\\\\t\\\\t\\\\tvec2 point = vec2( c * tex.x - s * tex.y, s * tex.x + c * tex.y ) * scale;\\\\n\\\\n\\\\t\\\\t\\\\treturn ( sin( point.x ) * sin( point.y ) ) * 4.0;\\\\n\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\tvec4 color = texture2D( tDiffuse, vUv );\\\\n\\\\n\\\\t\\\\t\\\\tfloat average = ( color.r + color.g + color.b ) / 3.0;\\\\n\\\\n\\\\t\\\\t\\\\tgl_FragColor = vec4( vec3( average * 10.0 - 5.0 + pattern() ), color.a );\\\\n\\\\n\\\\t\\\\t}\\\\\\\"};const tW=new class extends ua{constructor(){super(...arguments),this.center=ha.VECTOR2([.5,.5],{...xj}),this.angle=ha.FLOAT(\\\\\\\"$PI*0.5\\\\\\\",{range:[0,10],rangeLocked:[!1,!1],...xj}),this.scale=ha.FLOAT(1,{range:[0,1],rangeLocked:[!1,!1],...xj})}};class eW extends bj{constructor(){super(...arguments),this.paramsConfig=tW}static type(){return\\\\\\\"dotScreen\\\\\\\"}_createPass(t){const e=new Hm(Qj);return this.updatePass(e),e}updatePass(t){t.uniforms.center.value=this.pv.center,t.uniforms.angle.value=this.pv.angle,t.uniforms.scale.value=this.pv.scale}}const nW={uniforms:{tDiffuse:{value:null},time:{value:0},nIntensity:{value:.5},sIntensity:{value:.05},sCount:{value:4096},grayscale:{value:1}},vertexShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\tvUv = uv;\\\\n\\\\t\\\\t\\\\tgl_Position = projectionMatrix * modelViewMatrix * vec4( position, 1.0 );\\\\n\\\\n\\\\t\\\\t}\\\\\\\",fragmentShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\t#include \\\\n\\\\n\\\\t\\\\t// control parameter\\\\n\\\\t\\\\tuniform float time;\\\\n\\\\n\\\\t\\\\tuniform bool grayscale;\\\\n\\\\n\\\\t\\\\t// noise effect intensity value (0 = no effect, 1 = full effect)\\\\n\\\\t\\\\tuniform float nIntensity;\\\\n\\\\n\\\\t\\\\t// scanlines effect intensity value (0 = no effect, 1 = full effect)\\\\n\\\\t\\\\tuniform float sIntensity;\\\\n\\\\n\\\\t\\\\t// scanlines effect count value (0 = no effect, 4096 = full effect)\\\\n\\\\t\\\\tuniform float sCount;\\\\n\\\\n\\\\t\\\\tuniform sampler2D tDiffuse;\\\\n\\\\n\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t// sample the source\\\\n\\\\t\\\\t\\\\tvec4 cTextureScreen = texture2D( tDiffuse, vUv );\\\\n\\\\n\\\\t\\\\t// make some noise\\\\n\\\\t\\\\t\\\\tfloat dx = rand( vUv + time );\\\\n\\\\n\\\\t\\\\t// add noise\\\\n\\\\t\\\\t\\\\tvec3 cResult = cTextureScreen.rgb + cTextureScreen.rgb * clamp( 0.1 + dx, 0.0, 1.0 );\\\\n\\\\n\\\\t\\\\t// get us a sine and cosine\\\\n\\\\t\\\\t\\\\tvec2 sc = vec2( sin( vUv.y * sCount ), cos( vUv.y * sCount ) );\\\\n\\\\n\\\\t\\\\t// add scanlines\\\\n\\\\t\\\\t\\\\tcResult += cTextureScreen.rgb * vec3( sc.x, sc.y, sc.x ) * sIntensity;\\\\n\\\\n\\\\t\\\\t// interpolate between source and result by intensity\\\\n\\\\t\\\\t\\\\tcResult = cTextureScreen.rgb + clamp( nIntensity, 0.0,1.0 ) * ( cResult - cTextureScreen.rgb );\\\\n\\\\n\\\\t\\\\t// convert to grayscale if desired\\\\n\\\\t\\\\t\\\\tif( grayscale ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tcResult = vec3( cResult.r * 0.3 + cResult.g * 0.59 + cResult.b * 0.11 );\\\\n\\\\n\\\\t\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\t\\\\tgl_FragColor = vec4( cResult, cTextureScreen.a );\\\\n\\\\n\\\\t\\\\t}\\\\\\\"};class iW extends km{constructor(t,e,n,i){super(),void 0===nW&&console.error(\\\\\\\"THREE.FilmPass relies on FilmShader\\\\\\\");const s=nW;this.uniforms=I.clone(s.uniforms),this.material=new F({uniforms:this.uniforms,vertexShader:s.vertexShader,fragmentShader:s.fragmentShader}),void 0!==i&&(this.uniforms.grayscale.value=i),void 0!==t&&(this.uniforms.nIntensity.value=t),void 0!==e&&(this.uniforms.sIntensity.value=e),void 0!==n&&(this.uniforms.sCount.value=n),this.fsQuad=new Vm(this.material)}render(t,e,n,i){this.uniforms.tDiffuse.value=n.texture,this.uniforms.time.value+=i,this.renderToScreen?(t.setRenderTarget(null),this.fsQuad.render(t)):(t.setRenderTarget(e),this.clear&&t.clear(),this.fsQuad.render(t))}}const sW=new class extends ua{constructor(){super(...arguments),this.noiseIntensity=ha.FLOAT(.5,{range:[0,1],rangeLocked:[!1,!1],...xj}),this.scanlinesIntensity=ha.FLOAT(.05,{range:[0,1],rangeLocked:[!0,!1],...xj}),this.scanlinesCount=ha.FLOAT(4096,{range:[0,4096],rangeLocked:[!0,!1],...xj}),this.grayscale=ha.BOOLEAN(1,{...xj})}};class rW extends bj{constructor(){super(...arguments),this.paramsConfig=sW}static type(){return\\\\\\\"film\\\\\\\"}_createPass(t){const e=new iW(this.pv.noiseIntensity,this.pv.scanlinesIntensity,this.pv.scanlinesCount,this.pv.grayscale?1:0);return this.updatePass(e),e}updatePass(t){t.uniforms.nIntensity.value=this.pv.noiseIntensity,t.uniforms.sIntensity.value=this.pv.scanlinesIntensity,t.uniforms.sCount.value=this.pv.scanlinesCount,t.uniforms.grayscale.value=this.pv.grayscale?1:0}}const oW={uniforms:{tDiffuse:{value:null},resolution:{value:new d.a(1/1024,1/512)}},vertexShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\tvUv = uv;\\\\n\\\\t\\\\t\\\\tgl_Position = projectionMatrix * modelViewMatrix * vec4( position, 1.0 );\\\\n\\\\n\\\\t\\\\t}\\\\\\\",fragmentShader:'\\\\n\\\\n\\\\t\\\\tprecision highp float;\\\\n\\\\n\\\\t\\\\tuniform sampler2D tDiffuse;\\\\n\\\\n\\\\t\\\\tuniform vec2 resolution;\\\\n\\\\n\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\n\\\\t\\\\t#define FXAA_PC 1\\\\n\\\\t\\\\t#define FXAA_GLSL_100 1\\\\n\\\\t\\\\t#define FXAA_QUALITY_PRESET 12\\\\n\\\\n\\\\t\\\\t#define FXAA_GREEN_AS_LUMA 1\\\\n\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t#ifndef FXAA_PC_CONSOLE\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\n\\\\t\\\\t\\\\t\\\\t// The console algorithm for PC is included\\\\n\\\\t\\\\t\\\\t\\\\t// for developers targeting really low spec machines.\\\\n\\\\t\\\\t\\\\t\\\\t// Likely better to just run FXAA_PC, and use a really low preset.\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_PC_CONSOLE 0\\\\n\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t#ifndef FXAA_GLSL_120\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_GLSL_120 0\\\\n\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t#ifndef FXAA_GLSL_130\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_GLSL_130 0\\\\n\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t#ifndef FXAA_HLSL_3\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_HLSL_3 0\\\\n\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t#ifndef FXAA_HLSL_4\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_HLSL_4 0\\\\n\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t#ifndef FXAA_HLSL_5\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_HLSL_5 0\\\\n\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*==========================================================================*/\\\\n\\\\t\\\\t#ifndef FXAA_GREEN_AS_LUMA\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\n\\\\t\\\\t\\\\t\\\\t// For those using non-linear color,\\\\n\\\\t\\\\t\\\\t\\\\t// and either not able to get luma in alpha, or not wanting to,\\\\n\\\\t\\\\t\\\\t\\\\t// this enables FXAA to run using green as a proxy for luma.\\\\n\\\\t\\\\t\\\\t\\\\t// So with this enabled, no need to pack luma in alpha.\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\n\\\\t\\\\t\\\\t\\\\t// This will turn off AA on anything which lacks some amount of green.\\\\n\\\\t\\\\t\\\\t\\\\t// Pure red and blue or combination of only R and B, will get no AA.\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\n\\\\t\\\\t\\\\t\\\\t// Might want to lower the settings for both,\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t\\\\tfxaaConsoleEdgeThresholdMin\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t\\\\tfxaaQualityEdgeThresholdMin\\\\n\\\\t\\\\t\\\\t\\\\t// In order to insure AA does not get turned off on colors\\\\n\\\\t\\\\t\\\\t\\\\t// which contain a minor amount of green.\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\n\\\\t\\\\t\\\\t\\\\t// 1 = On.\\\\n\\\\t\\\\t\\\\t\\\\t// 0 = Off.\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_GREEN_AS_LUMA 0\\\\n\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t#ifndef FXAA_EARLY_EXIT\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\n\\\\t\\\\t\\\\t\\\\t// Controls algorithm\\\\'s early exit path.\\\\n\\\\t\\\\t\\\\t\\\\t// On PS3 turning this ON adds 2 cycles to the shader.\\\\n\\\\t\\\\t\\\\t\\\\t// On 360 turning this OFF adds 10ths of a millisecond to the shader.\\\\n\\\\t\\\\t\\\\t\\\\t// Turning this off on console will result in a more blurry image.\\\\n\\\\t\\\\t\\\\t\\\\t// So this defaults to on.\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\n\\\\t\\\\t\\\\t\\\\t// 1 = On.\\\\n\\\\t\\\\t\\\\t\\\\t// 0 = Off.\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_EARLY_EXIT 1\\\\n\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t#ifndef FXAA_DISCARD\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\n\\\\t\\\\t\\\\t\\\\t// Only valid for PC OpenGL currently.\\\\n\\\\t\\\\t\\\\t\\\\t// Probably will not work when FXAA_GREEN_AS_LUMA = 1.\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\n\\\\t\\\\t\\\\t\\\\t// 1 = Use discard on pixels which don\\\\'t need AA.\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t\\\\t For APIs which enable concurrent TEX+ROP from same surface.\\\\n\\\\t\\\\t\\\\t\\\\t// 0 = Return unchanged color on pixels which don\\\\'t need AA.\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_DISCARD 0\\\\n\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t#ifndef FXAA_FAST_PIXEL_OFFSET\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\n\\\\t\\\\t\\\\t\\\\t// Used for GLSL 120 only.\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\n\\\\t\\\\t\\\\t\\\\t// 1 = GL API supports fast pixel offsets\\\\n\\\\t\\\\t\\\\t\\\\t// 0 = do not use fast pixel offsets\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\n\\\\t\\\\t\\\\t\\\\t#ifdef GL_EXT_gpu_shader4\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#define FXAA_FAST_PIXEL_OFFSET 1\\\\n\\\\t\\\\t\\\\t\\\\t#endif\\\\n\\\\t\\\\t\\\\t\\\\t#ifdef GL_NV_gpu_shader5\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#define FXAA_FAST_PIXEL_OFFSET 1\\\\n\\\\t\\\\t\\\\t\\\\t#endif\\\\n\\\\t\\\\t\\\\t\\\\t#ifdef GL_ARB_gpu_shader5\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#define FXAA_FAST_PIXEL_OFFSET 1\\\\n\\\\t\\\\t\\\\t\\\\t#endif\\\\n\\\\t\\\\t\\\\t\\\\t#ifndef FXAA_FAST_PIXEL_OFFSET\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#define FXAA_FAST_PIXEL_OFFSET 0\\\\n\\\\t\\\\t\\\\t\\\\t#endif\\\\n\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t#ifndef FXAA_GATHER4_ALPHA\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\n\\\\t\\\\t\\\\t\\\\t// 1 = API supports gather4 on alpha channel.\\\\n\\\\t\\\\t\\\\t\\\\t// 0 = API does not support gather4 on alpha channel.\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\n\\\\t\\\\t\\\\t\\\\t#if (FXAA_HLSL_5 == 1)\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#define FXAA_GATHER4_ALPHA 1\\\\n\\\\t\\\\t\\\\t\\\\t#endif\\\\n\\\\t\\\\t\\\\t\\\\t#ifdef GL_ARB_gpu_shader5\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#define FXAA_GATHER4_ALPHA 1\\\\n\\\\t\\\\t\\\\t\\\\t#endif\\\\n\\\\t\\\\t\\\\t\\\\t#ifdef GL_NV_gpu_shader5\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#define FXAA_GATHER4_ALPHA 1\\\\n\\\\t\\\\t\\\\t\\\\t#endif\\\\n\\\\t\\\\t\\\\t\\\\t#ifndef FXAA_GATHER4_ALPHA\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#define FXAA_GATHER4_ALPHA 0\\\\n\\\\t\\\\t\\\\t\\\\t#endif\\\\n\\\\t\\\\t#endif\\\\n\\\\n\\\\n\\\\t\\\\t/*============================================================================\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tFXAA QUALITY - TUNING KNOBS\\\\n\\\\t\\\\t------------------------------------------------------------------------------\\\\n\\\\t\\\\tNOTE the other tuning knobs are now in the shader function inputs!\\\\n\\\\t\\\\t============================================================================*/\\\\n\\\\t\\\\t#ifndef FXAA_QUALITY_PRESET\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\n\\\\t\\\\t\\\\t\\\\t// Choose the quality preset.\\\\n\\\\t\\\\t\\\\t\\\\t// This needs to be compiled into the shader as it effects code.\\\\n\\\\t\\\\t\\\\t\\\\t// Best option to include multiple presets is to\\\\n\\\\t\\\\t\\\\t\\\\t// in each shader define the preset, then include this file.\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\n\\\\t\\\\t\\\\t\\\\t// OPTIONS\\\\n\\\\t\\\\t\\\\t\\\\t// -----------------------------------------------------------------------\\\\n\\\\t\\\\t\\\\t\\\\t// 10 to 15 - default medium dither (10=fastest, 15=highest quality)\\\\n\\\\t\\\\t\\\\t\\\\t// 20 to 29 - less dither, more expensive (20=fastest, 29=highest quality)\\\\n\\\\t\\\\t\\\\t\\\\t// 39\\\\t\\\\t\\\\t - no dither, very expensive\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\n\\\\t\\\\t\\\\t\\\\t// NOTES\\\\n\\\\t\\\\t\\\\t\\\\t// -----------------------------------------------------------------------\\\\n\\\\t\\\\t\\\\t\\\\t// 12 = slightly faster then FXAA 3.9 and higher edge quality (default)\\\\n\\\\t\\\\t\\\\t\\\\t// 13 = about same speed as FXAA 3.9 and better than 12\\\\n\\\\t\\\\t\\\\t\\\\t// 23 = closest to FXAA 3.9 visually and performance wise\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t_ = the lowest digit is directly related to performance\\\\n\\\\t\\\\t\\\\t\\\\t// _\\\\t= the highest digit is directly related to style\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_PRESET 12\\\\n\\\\t\\\\t#endif\\\\n\\\\n\\\\n\\\\t\\\\t/*============================================================================\\\\n\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t FXAA QUALITY - PRESETS\\\\n\\\\n\\\\t\\\\t============================================================================*/\\\\n\\\\n\\\\t\\\\t/*============================================================================\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t FXAA QUALITY - MEDIUM DITHER PRESETS\\\\n\\\\t\\\\t============================================================================*/\\\\n\\\\t\\\\t#if (FXAA_QUALITY_PRESET == 10)\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_PS 3\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P0 1.5\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P1 3.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P2 12.0\\\\n\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t#if (FXAA_QUALITY_PRESET == 11)\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_PS 4\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P0 1.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P1 1.5\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P2 3.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P3 12.0\\\\n\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t#if (FXAA_QUALITY_PRESET == 12)\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_PS 5\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P0 1.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P1 1.5\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P2 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P3 4.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P4 12.0\\\\n\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t#if (FXAA_QUALITY_PRESET == 13)\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_PS 6\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P0 1.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P1 1.5\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P2 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P3 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P4 4.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P5 12.0\\\\n\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t#if (FXAA_QUALITY_PRESET == 14)\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_PS 7\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P0 1.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P1 1.5\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P2 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P3 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P4 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P5 4.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P6 12.0\\\\n\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t#if (FXAA_QUALITY_PRESET == 15)\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_PS 8\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P0 1.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P1 1.5\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P2 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P3 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P4 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P5 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P6 4.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P7 12.0\\\\n\\\\t\\\\t#endif\\\\n\\\\n\\\\t\\\\t/*============================================================================\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t FXAA QUALITY - LOW DITHER PRESETS\\\\n\\\\t\\\\t============================================================================*/\\\\n\\\\t\\\\t#if (FXAA_QUALITY_PRESET == 20)\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_PS 3\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P0 1.5\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P1 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P2 8.0\\\\n\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t#if (FXAA_QUALITY_PRESET == 21)\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_PS 4\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P0 1.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P1 1.5\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P2 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P3 8.0\\\\n\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t#if (FXAA_QUALITY_PRESET == 22)\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_PS 5\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P0 1.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P1 1.5\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P2 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P3 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P4 8.0\\\\n\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t#if (FXAA_QUALITY_PRESET == 23)\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_PS 6\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P0 1.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P1 1.5\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P2 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P3 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P4 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P5 8.0\\\\n\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t#if (FXAA_QUALITY_PRESET == 24)\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_PS 7\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P0 1.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P1 1.5\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P2 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P3 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P4 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P5 3.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P6 8.0\\\\n\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t#if (FXAA_QUALITY_PRESET == 25)\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_PS 8\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P0 1.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P1 1.5\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P2 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P3 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P4 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P5 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P6 4.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P7 8.0\\\\n\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t#if (FXAA_QUALITY_PRESET == 26)\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_PS 9\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P0 1.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P1 1.5\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P2 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P3 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P4 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P5 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P6 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P7 4.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P8 8.0\\\\n\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t#if (FXAA_QUALITY_PRESET == 27)\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_PS 10\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P0 1.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P1 1.5\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P2 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P3 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P4 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P5 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P6 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P7 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P8 4.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P9 8.0\\\\n\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t#if (FXAA_QUALITY_PRESET == 28)\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_PS 11\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P0 1.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P1 1.5\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P2 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P3 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P4 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P5 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P6 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P7 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P8 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P9 4.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P10 8.0\\\\n\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t#if (FXAA_QUALITY_PRESET == 29)\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_PS 12\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P0 1.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P1 1.5\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P2 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P3 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P4 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P5 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P6 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P7 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P8 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P9 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P10 4.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P11 8.0\\\\n\\\\t\\\\t#endif\\\\n\\\\n\\\\t\\\\t/*============================================================================\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t FXAA QUALITY - EXTREME QUALITY\\\\n\\\\t\\\\t============================================================================*/\\\\n\\\\t\\\\t#if (FXAA_QUALITY_PRESET == 39)\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_PS 12\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P0 1.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P1 1.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P2 1.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P3 1.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P4 1.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P5 1.5\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P6 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P7 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P8 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P9 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P10 4.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P11 8.0\\\\n\\\\t\\\\t#endif\\\\n\\\\n\\\\n\\\\n\\\\t\\\\t/*============================================================================\\\\n\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tAPI PORTING\\\\n\\\\n\\\\t\\\\t============================================================================*/\\\\n\\\\t\\\\t#if (FXAA_GLSL_100 == 1) || (FXAA_GLSL_120 == 1) || (FXAA_GLSL_130 == 1)\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaBool bool\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaDiscard discard\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaFloat float\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaFloat2 vec2\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaFloat3 vec3\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaFloat4 vec4\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaHalf float\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaHalf2 vec2\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaHalf3 vec3\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaHalf4 vec4\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaInt2 ivec2\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaSat(x) clamp(x, 0.0, 1.0)\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaTex sampler2D\\\\n\\\\t\\\\t#else\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaBool bool\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaDiscard clip(-1)\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaFloat float\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaFloat2 float2\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaFloat3 float3\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaFloat4 float4\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaHalf half\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaHalf2 half2\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaHalf3 half3\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaHalf4 half4\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaSat(x) saturate(x)\\\\n\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t#if (FXAA_GLSL_100 == 1)\\\\n\\\\t\\\\t\\\\t#define FxaaTexTop(t, p) texture2D(t, p, 0.0)\\\\n\\\\t\\\\t\\\\t#define FxaaTexOff(t, p, o, r) texture2D(t, p + (o * r), 0.0)\\\\n\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t#if (FXAA_GLSL_120 == 1)\\\\n\\\\t\\\\t\\\\t\\\\t// Requires,\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t#version 120\\\\n\\\\t\\\\t\\\\t\\\\t// And at least,\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t#extension GL_EXT_gpu_shader4 : enable\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t(or set FXAA_FAST_PIXEL_OFFSET 1 to work like DX9)\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaTexTop(t, p) texture2DLod(t, p, 0.0)\\\\n\\\\t\\\\t\\\\t\\\\t#if (FXAA_FAST_PIXEL_OFFSET == 1)\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#define FxaaTexOff(t, p, o, r) texture2DLodOffset(t, p, 0.0, o)\\\\n\\\\t\\\\t\\\\t\\\\t#else\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#define FxaaTexOff(t, p, o, r) texture2DLod(t, p + (o * r), 0.0)\\\\n\\\\t\\\\t\\\\t\\\\t#endif\\\\n\\\\t\\\\t\\\\t\\\\t#if (FXAA_GATHER4_ALPHA == 1)\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t// use #extension GL_ARB_gpu_shader5 : enable\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#define FxaaTexAlpha4(t, p) textureGather(t, p, 3)\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#define FxaaTexOffAlpha4(t, p, o) textureGatherOffset(t, p, o, 3)\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#define FxaaTexGreen4(t, p) textureGather(t, p, 1)\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#define FxaaTexOffGreen4(t, p, o) textureGatherOffset(t, p, o, 1)\\\\n\\\\t\\\\t\\\\t\\\\t#endif\\\\n\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t#if (FXAA_GLSL_130 == 1)\\\\n\\\\t\\\\t\\\\t\\\\t// Requires \\\\\\\"#version 130\\\\\\\" or better\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaTexTop(t, p) textureLod(t, p, 0.0)\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaTexOff(t, p, o, r) textureLodOffset(t, p, 0.0, o)\\\\n\\\\t\\\\t\\\\t\\\\t#if (FXAA_GATHER4_ALPHA == 1)\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t// use #extension GL_ARB_gpu_shader5 : enable\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#define FxaaTexAlpha4(t, p) textureGather(t, p, 3)\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#define FxaaTexOffAlpha4(t, p, o) textureGatherOffset(t, p, o, 3)\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#define FxaaTexGreen4(t, p) textureGather(t, p, 1)\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#define FxaaTexOffGreen4(t, p, o) textureGatherOffset(t, p, o, 1)\\\\n\\\\t\\\\t\\\\t\\\\t#endif\\\\n\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t#if (FXAA_HLSL_3 == 1)\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaInt2 float2\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaTex sampler2D\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaTexTop(t, p) tex2Dlod(t, float4(p, 0.0, 0.0))\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaTexOff(t, p, o, r) tex2Dlod(t, float4(p + (o * r), 0, 0))\\\\n\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t#if (FXAA_HLSL_4 == 1)\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaInt2 int2\\\\n\\\\t\\\\t\\\\t\\\\tstruct FxaaTex { SamplerState smpl; Texture2D tex; };\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaTexTop(t, p) t.tex.SampleLevel(t.smpl, p, 0.0)\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaTexOff(t, p, o, r) t.tex.SampleLevel(t.smpl, p, 0.0, o)\\\\n\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t#if (FXAA_HLSL_5 == 1)\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaInt2 int2\\\\n\\\\t\\\\t\\\\t\\\\tstruct FxaaTex { SamplerState smpl; Texture2D tex; };\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaTexTop(t, p) t.tex.SampleLevel(t.smpl, p, 0.0)\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaTexOff(t, p, o, r) t.tex.SampleLevel(t.smpl, p, 0.0, o)\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaTexAlpha4(t, p) t.tex.GatherAlpha(t.smpl, p)\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaTexOffAlpha4(t, p, o) t.tex.GatherAlpha(t.smpl, p, o)\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaTexGreen4(t, p) t.tex.GatherGreen(t.smpl, p)\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaTexOffGreen4(t, p, o) t.tex.GatherGreen(t.smpl, p, o)\\\\n\\\\t\\\\t#endif\\\\n\\\\n\\\\n\\\\t\\\\t/*============================================================================\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t GREEN AS LUMA OPTION SUPPORT FUNCTION\\\\n\\\\t\\\\t============================================================================*/\\\\n\\\\t\\\\t#if (FXAA_GREEN_AS_LUMA == 0)\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat FxaaLuma(FxaaFloat4 rgba) { return rgba.w; }\\\\n\\\\t\\\\t#else\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat FxaaLuma(FxaaFloat4 rgba) { return rgba.y; }\\\\n\\\\t\\\\t#endif\\\\n\\\\n\\\\n\\\\n\\\\n\\\\t\\\\t/*============================================================================\\\\n\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t FXAA3 QUALITY - PC\\\\n\\\\n\\\\t\\\\t============================================================================*/\\\\n\\\\t\\\\t#if (FXAA_PC == 1)\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\tFxaaFloat4 FxaaPixelShader(\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\n\\\\t\\\\t\\\\t\\\\t// Use noperspective interpolation here (turn off perspective interpolation).\\\\n\\\\t\\\\t\\\\t\\\\t// {xy} = center of pixel\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat2 pos,\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\n\\\\t\\\\t\\\\t\\\\t// Used only for FXAA Console, and not used on the 360 version.\\\\n\\\\t\\\\t\\\\t\\\\t// Use noperspective interpolation here (turn off perspective interpolation).\\\\n\\\\t\\\\t\\\\t\\\\t// {xy_} = upper left of pixel\\\\n\\\\t\\\\t\\\\t\\\\t// {_zw} = lower right of pixel\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat4 fxaaConsolePosPos,\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\n\\\\t\\\\t\\\\t\\\\t// Input color texture.\\\\n\\\\t\\\\t\\\\t\\\\t// {rgb_} = color in linear or perceptual color space\\\\n\\\\t\\\\t\\\\t\\\\t// if (FXAA_GREEN_AS_LUMA == 0)\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t\\\\t {__a} = luma in perceptual color space (not linear)\\\\n\\\\t\\\\t\\\\t\\\\tFxaaTex tex,\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\n\\\\t\\\\t\\\\t\\\\t// Only used on the optimized 360 version of FXAA Console.\\\\n\\\\t\\\\t\\\\t\\\\t// For everything but 360, just use the same input here as for \\\\\\\"tex\\\\\\\".\\\\n\\\\t\\\\t\\\\t\\\\t// For 360, same texture, just alias with a 2nd sampler.\\\\n\\\\t\\\\t\\\\t\\\\t// This sampler needs to have an exponent bias of -1.\\\\n\\\\t\\\\t\\\\t\\\\tFxaaTex fxaaConsole360TexExpBiasNegOne,\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\n\\\\t\\\\t\\\\t\\\\t// Only used on the optimized 360 version of FXAA Console.\\\\n\\\\t\\\\t\\\\t\\\\t// For everything but 360, just use the same input here as for \\\\\\\"tex\\\\\\\".\\\\n\\\\t\\\\t\\\\t\\\\t// For 360, same texture, just alias with a 3nd sampler.\\\\n\\\\t\\\\t\\\\t\\\\t// This sampler needs to have an exponent bias of -2.\\\\n\\\\t\\\\t\\\\t\\\\tFxaaTex fxaaConsole360TexExpBiasNegTwo,\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\n\\\\t\\\\t\\\\t\\\\t// Only used on FXAA Quality.\\\\n\\\\t\\\\t\\\\t\\\\t// This must be from a constant/uniform.\\\\n\\\\t\\\\t\\\\t\\\\t// {x_} = 1.0/screenWidthInPixels\\\\n\\\\t\\\\t\\\\t\\\\t// {_y} = 1.0/screenHeightInPixels\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat2 fxaaQualityRcpFrame,\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\n\\\\t\\\\t\\\\t\\\\t// Only used on FXAA Console.\\\\n\\\\t\\\\t\\\\t\\\\t// This must be from a constant/uniform.\\\\n\\\\t\\\\t\\\\t\\\\t// This effects sub-pixel AA quality and inversely sharpness.\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t Where N ranges between,\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t\\\\t N = 0.50 (default)\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t\\\\t N = 0.33 (sharper)\\\\n\\\\t\\\\t\\\\t\\\\t// {x__} = -N/screenWidthInPixels\\\\n\\\\t\\\\t\\\\t\\\\t// {_y_} = -N/screenHeightInPixels\\\\n\\\\t\\\\t\\\\t\\\\t// {_z_} =\\\\tN/screenWidthInPixels\\\\n\\\\t\\\\t\\\\t\\\\t// {__w} =\\\\tN/screenHeightInPixels\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat4 fxaaConsoleRcpFrameOpt,\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\n\\\\t\\\\t\\\\t\\\\t// Only used on FXAA Console.\\\\n\\\\t\\\\t\\\\t\\\\t// Not used on 360, but used on PS3 and PC.\\\\n\\\\t\\\\t\\\\t\\\\t// This must be from a constant/uniform.\\\\n\\\\t\\\\t\\\\t\\\\t// {x__} = -2.0/screenWidthInPixels\\\\n\\\\t\\\\t\\\\t\\\\t// {_y_} = -2.0/screenHeightInPixels\\\\n\\\\t\\\\t\\\\t\\\\t// {_z_} =\\\\t2.0/screenWidthInPixels\\\\n\\\\t\\\\t\\\\t\\\\t// {__w} =\\\\t2.0/screenHeightInPixels\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat4 fxaaConsoleRcpFrameOpt2,\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\n\\\\t\\\\t\\\\t\\\\t// Only used on FXAA Console.\\\\n\\\\t\\\\t\\\\t\\\\t// Only used on 360 in place of fxaaConsoleRcpFrameOpt2.\\\\n\\\\t\\\\t\\\\t\\\\t// This must be from a constant/uniform.\\\\n\\\\t\\\\t\\\\t\\\\t// {x__} =\\\\t8.0/screenWidthInPixels\\\\n\\\\t\\\\t\\\\t\\\\t// {_y_} =\\\\t8.0/screenHeightInPixels\\\\n\\\\t\\\\t\\\\t\\\\t// {_z_} = -4.0/screenWidthInPixels\\\\n\\\\t\\\\t\\\\t\\\\t// {__w} = -4.0/screenHeightInPixels\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat4 fxaaConsole360RcpFrameOpt2,\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\n\\\\t\\\\t\\\\t\\\\t// Only used on FXAA Quality.\\\\n\\\\t\\\\t\\\\t\\\\t// This used to be the FXAA_QUALITY_SUBPIX define.\\\\n\\\\t\\\\t\\\\t\\\\t// It is here now to allow easier tuning.\\\\n\\\\t\\\\t\\\\t\\\\t// Choose the amount of sub-pixel aliasing removal.\\\\n\\\\t\\\\t\\\\t\\\\t// This can effect sharpness.\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t 1.00 - upper limit (softer)\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t 0.75 - default amount of filtering\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t 0.50 - lower limit (sharper, less sub-pixel aliasing removal)\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t 0.25 - almost off\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t 0.00 - completely off\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat fxaaQualitySubpix,\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\n\\\\t\\\\t\\\\t\\\\t// Only used on FXAA Quality.\\\\n\\\\t\\\\t\\\\t\\\\t// This used to be the FXAA_QUALITY_EDGE_THRESHOLD define.\\\\n\\\\t\\\\t\\\\t\\\\t// It is here now to allow easier tuning.\\\\n\\\\t\\\\t\\\\t\\\\t// The minimum amount of local contrast required to apply algorithm.\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t 0.333 - too little (faster)\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t 0.250 - low quality\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t 0.166 - default\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t 0.125 - high quality\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t 0.063 - overkill (slower)\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat fxaaQualityEdgeThreshold,\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\n\\\\t\\\\t\\\\t\\\\t// Only used on FXAA Quality.\\\\n\\\\t\\\\t\\\\t\\\\t// This used to be the FXAA_QUALITY_EDGE_THRESHOLD_MIN define.\\\\n\\\\t\\\\t\\\\t\\\\t// It is here now to allow easier tuning.\\\\n\\\\t\\\\t\\\\t\\\\t// Trims the algorithm from processing darks.\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t 0.0833 - upper limit (default, the start of visible unfiltered edges)\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t 0.0625 - high quality (faster)\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t 0.0312 - visible limit (slower)\\\\n\\\\t\\\\t\\\\t\\\\t// Special notes when using FXAA_GREEN_AS_LUMA,\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t Likely want to set this to zero.\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t As colors that are mostly not-green\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t will appear very dark in the green channel!\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t Tune by looking at mostly non-green content,\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t then start at zero and increase until aliasing is a problem.\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat fxaaQualityEdgeThresholdMin,\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\n\\\\t\\\\t\\\\t\\\\t// Only used on FXAA Console.\\\\n\\\\t\\\\t\\\\t\\\\t// This used to be the FXAA_CONSOLE_EDGE_SHARPNESS define.\\\\n\\\\t\\\\t\\\\t\\\\t// It is here now to allow easier tuning.\\\\n\\\\t\\\\t\\\\t\\\\t// This does not effect PS3, as this needs to be compiled in.\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t Use FXAA_CONSOLE_PS3_EDGE_SHARPNESS for PS3.\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t Due to the PS3 being ALU bound,\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t there are only three safe values here: 2 and 4 and 8.\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t These options use the shaders ability to a free *|/ by 2|4|8.\\\\n\\\\t\\\\t\\\\t\\\\t// For all other platforms can be a non-power of two.\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t 8.0 is sharper (default!!!)\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t 4.0 is softer\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t 2.0 is really soft (good only for vector graphics inputs)\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat fxaaConsoleEdgeSharpness,\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\n\\\\t\\\\t\\\\t\\\\t// Only used on FXAA Console.\\\\n\\\\t\\\\t\\\\t\\\\t// This used to be the FXAA_CONSOLE_EDGE_THRESHOLD define.\\\\n\\\\t\\\\t\\\\t\\\\t// It is here now to allow easier tuning.\\\\n\\\\t\\\\t\\\\t\\\\t// This does not effect PS3, as this needs to be compiled in.\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t Use FXAA_CONSOLE_PS3_EDGE_THRESHOLD for PS3.\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t Due to the PS3 being ALU bound,\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t there are only two safe values here: 1/4 and 1/8.\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t These options use the shaders ability to a free *|/ by 2|4|8.\\\\n\\\\t\\\\t\\\\t\\\\t// The console setting has a different mapping than the quality setting.\\\\n\\\\t\\\\t\\\\t\\\\t// Other platforms can use other values.\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t 0.125 leaves less aliasing, but is softer (default!!!)\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t 0.25 leaves more aliasing, and is sharper\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat fxaaConsoleEdgeThreshold,\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\n\\\\t\\\\t\\\\t\\\\t// Only used on FXAA Console.\\\\n\\\\t\\\\t\\\\t\\\\t// This used to be the FXAA_CONSOLE_EDGE_THRESHOLD_MIN define.\\\\n\\\\t\\\\t\\\\t\\\\t// It is here now to allow easier tuning.\\\\n\\\\t\\\\t\\\\t\\\\t// Trims the algorithm from processing darks.\\\\n\\\\t\\\\t\\\\t\\\\t// The console setting has a different mapping than the quality setting.\\\\n\\\\t\\\\t\\\\t\\\\t// This only applies when FXAA_EARLY_EXIT is 1.\\\\n\\\\t\\\\t\\\\t\\\\t// This does not apply to PS3,\\\\n\\\\t\\\\t\\\\t\\\\t// PS3 was simplified to avoid more shader instructions.\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t 0.06 - faster but more aliasing in darks\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t 0.05 - default\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t 0.04 - slower and less aliasing in darks\\\\n\\\\t\\\\t\\\\t\\\\t// Special notes when using FXAA_GREEN_AS_LUMA,\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t Likely want to set this to zero.\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t As colors that are mostly not-green\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t will appear very dark in the green channel!\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t Tune by looking at mostly non-green content,\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t then start at zero and increase until aliasing is a problem.\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat fxaaConsoleEdgeThresholdMin,\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\n\\\\t\\\\t\\\\t\\\\t// Extra constants for 360 FXAA Console only.\\\\n\\\\t\\\\t\\\\t\\\\t// Use zeros or anything else for other platforms.\\\\n\\\\t\\\\t\\\\t\\\\t// These must be in physical constant registers and NOT immediates.\\\\n\\\\t\\\\t\\\\t\\\\t// Immediates will result in compiler un-optimizing.\\\\n\\\\t\\\\t\\\\t\\\\t// {xyzw} = float4(1.0, -1.0, 0.25, -0.25)\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat4 fxaaConsole360ConstDir\\\\n\\\\t\\\\t) {\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat2 posM;\\\\n\\\\t\\\\t\\\\t\\\\tposM.x = pos.x;\\\\n\\\\t\\\\t\\\\t\\\\tposM.y = pos.y;\\\\n\\\\t\\\\t\\\\t\\\\t#if (FXAA_GATHER4_ALPHA == 1)\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#if (FXAA_DISCARD == 0)\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tFxaaFloat4 rgbyM = FxaaTexTop(tex, posM);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#if (FXAA_GREEN_AS_LUMA == 0)\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#define lumaM rgbyM.w\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#else\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#define lumaM rgbyM.y\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#endif\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#endif\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#if (FXAA_GREEN_AS_LUMA == 0)\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tFxaaFloat4 luma4A = FxaaTexAlpha4(tex, posM);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tFxaaFloat4 luma4B = FxaaTexOffAlpha4(tex, posM, FxaaInt2(-1, -1));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#else\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tFxaaFloat4 luma4A = FxaaTexGreen4(tex, posM);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tFxaaFloat4 luma4B = FxaaTexOffGreen4(tex, posM, FxaaInt2(-1, -1));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#endif\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#if (FXAA_DISCARD == 1)\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#define lumaM luma4A.w\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#endif\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#define lumaE luma4A.z\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#define lumaS luma4A.x\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#define lumaSE luma4A.y\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#define lumaNW luma4B.w\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#define lumaN luma4B.z\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#define lumaW luma4B.x\\\\n\\\\t\\\\t\\\\t\\\\t#else\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tFxaaFloat4 rgbyM = FxaaTexTop(tex, posM);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#if (FXAA_GREEN_AS_LUMA == 0)\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#define lumaM rgbyM.w\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#else\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#define lumaM rgbyM.y\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#endif\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#if (FXAA_GLSL_100 == 1)\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tFxaaFloat lumaS = FxaaLuma(FxaaTexOff(tex, posM, FxaaFloat2( 0.0, 1.0), fxaaQualityRcpFrame.xy));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tFxaaFloat lumaE = FxaaLuma(FxaaTexOff(tex, posM, FxaaFloat2( 1.0, 0.0), fxaaQualityRcpFrame.xy));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tFxaaFloat lumaN = FxaaLuma(FxaaTexOff(tex, posM, FxaaFloat2( 0.0,-1.0), fxaaQualityRcpFrame.xy));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tFxaaFloat lumaW = FxaaLuma(FxaaTexOff(tex, posM, FxaaFloat2(-1.0, 0.0), fxaaQualityRcpFrame.xy));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#else\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tFxaaFloat lumaS = FxaaLuma(FxaaTexOff(tex, posM, FxaaInt2( 0, 1), fxaaQualityRcpFrame.xy));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tFxaaFloat lumaE = FxaaLuma(FxaaTexOff(tex, posM, FxaaInt2( 1, 0), fxaaQualityRcpFrame.xy));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tFxaaFloat lumaN = FxaaLuma(FxaaTexOff(tex, posM, FxaaInt2( 0,-1), fxaaQualityRcpFrame.xy));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tFxaaFloat lumaW = FxaaLuma(FxaaTexOff(tex, posM, FxaaInt2(-1, 0), fxaaQualityRcpFrame.xy));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#endif\\\\n\\\\t\\\\t\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat maxSM = max(lumaS, lumaM);\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat minSM = min(lumaS, lumaM);\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat maxESM = max(lumaE, maxSM);\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat minESM = min(lumaE, minSM);\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat maxWN = max(lumaN, lumaW);\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat minWN = min(lumaN, lumaW);\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat rangeMax = max(maxWN, maxESM);\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat rangeMin = min(minWN, minESM);\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat rangeMaxScaled = rangeMax * fxaaQualityEdgeThreshold;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat range = rangeMax - rangeMin;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat rangeMaxClamped = max(fxaaQualityEdgeThresholdMin, rangeMaxScaled);\\\\n\\\\t\\\\t\\\\t\\\\tFxaaBool earlyExit = range < rangeMaxClamped;\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\tif(earlyExit)\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#if (FXAA_DISCARD == 1)\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tFxaaDiscard;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#else\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\treturn rgbyM;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\t#if (FXAA_GATHER4_ALPHA == 0)\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#if (FXAA_GLSL_100 == 1)\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tFxaaFloat lumaNW = FxaaLuma(FxaaTexOff(tex, posM, FxaaFloat2(-1.0,-1.0), fxaaQualityRcpFrame.xy));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tFxaaFloat lumaSE = FxaaLuma(FxaaTexOff(tex, posM, FxaaFloat2( 1.0, 1.0), fxaaQualityRcpFrame.xy));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tFxaaFloat lumaNE = FxaaLuma(FxaaTexOff(tex, posM, FxaaFloat2( 1.0,-1.0), fxaaQualityRcpFrame.xy));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tFxaaFloat lumaSW = FxaaLuma(FxaaTexOff(tex, posM, FxaaFloat2(-1.0, 1.0), fxaaQualityRcpFrame.xy));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#else\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tFxaaFloat lumaNW = FxaaLuma(FxaaTexOff(tex, posM, FxaaInt2(-1,-1), fxaaQualityRcpFrame.xy));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tFxaaFloat lumaSE = FxaaLuma(FxaaTexOff(tex, posM, FxaaInt2( 1, 1), fxaaQualityRcpFrame.xy));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tFxaaFloat lumaNE = FxaaLuma(FxaaTexOff(tex, posM, FxaaInt2( 1,-1), fxaaQualityRcpFrame.xy));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tFxaaFloat lumaSW = FxaaLuma(FxaaTexOff(tex, posM, FxaaInt2(-1, 1), fxaaQualityRcpFrame.xy));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#endif\\\\n\\\\t\\\\t\\\\t\\\\t#else\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tFxaaFloat lumaNE = FxaaLuma(FxaaTexOff(tex, posM, FxaaInt2(1, -1), fxaaQualityRcpFrame.xy));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tFxaaFloat lumaSW = FxaaLuma(FxaaTexOff(tex, posM, FxaaInt2(-1, 1), fxaaQualityRcpFrame.xy));\\\\n\\\\t\\\\t\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat lumaNS = lumaN + lumaS;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat lumaWE = lumaW + lumaE;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat subpixRcpRange = 1.0/range;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat subpixNSWE = lumaNS + lumaWE;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat edgeHorz1 = (-2.0 * lumaM) + lumaNS;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat edgeVert1 = (-2.0 * lumaM) + lumaWE;\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat lumaNESE = lumaNE + lumaSE;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat lumaNWNE = lumaNW + lumaNE;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat edgeHorz2 = (-2.0 * lumaE) + lumaNESE;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat edgeVert2 = (-2.0 * lumaN) + lumaNWNE;\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat lumaNWSW = lumaNW + lumaSW;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat lumaSWSE = lumaSW + lumaSE;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat edgeHorz4 = (abs(edgeHorz1) * 2.0) + abs(edgeHorz2);\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat edgeVert4 = (abs(edgeVert1) * 2.0) + abs(edgeVert2);\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat edgeHorz3 = (-2.0 * lumaW) + lumaNWSW;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat edgeVert3 = (-2.0 * lumaS) + lumaSWSE;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat edgeHorz = abs(edgeHorz3) + edgeHorz4;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat edgeVert = abs(edgeVert3) + edgeVert4;\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat subpixNWSWNESE = lumaNWSW + lumaNESE;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat lengthSign = fxaaQualityRcpFrame.x;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaBool horzSpan = edgeHorz >= edgeVert;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat subpixA = subpixNSWE * 2.0 + subpixNWSWNESE;\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\tif(!horzSpan) lumaN = lumaW;\\\\n\\\\t\\\\t\\\\t\\\\tif(!horzSpan) lumaS = lumaE;\\\\n\\\\t\\\\t\\\\t\\\\tif(horzSpan) lengthSign = fxaaQualityRcpFrame.y;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat subpixB = (subpixA * (1.0/12.0)) - lumaM;\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat gradientN = lumaN - lumaM;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat gradientS = lumaS - lumaM;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat lumaNN = lumaN + lumaM;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat lumaSS = lumaS + lumaM;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaBool pairN = abs(gradientN) >= abs(gradientS);\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat gradient = max(abs(gradientN), abs(gradientS));\\\\n\\\\t\\\\t\\\\t\\\\tif(pairN) lengthSign = -lengthSign;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat subpixC = FxaaSat(abs(subpixB) * subpixRcpRange);\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat2 posB;\\\\n\\\\t\\\\t\\\\t\\\\tposB.x = posM.x;\\\\n\\\\t\\\\t\\\\t\\\\tposB.y = posM.y;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat2 offNP;\\\\n\\\\t\\\\t\\\\t\\\\toffNP.x = (!horzSpan) ? 0.0 : fxaaQualityRcpFrame.x;\\\\n\\\\t\\\\t\\\\t\\\\toffNP.y = ( horzSpan) ? 0.0 : fxaaQualityRcpFrame.y;\\\\n\\\\t\\\\t\\\\t\\\\tif(!horzSpan) posB.x += lengthSign * 0.5;\\\\n\\\\t\\\\t\\\\t\\\\tif( horzSpan) posB.y += lengthSign * 0.5;\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat2 posN;\\\\n\\\\t\\\\t\\\\t\\\\tposN.x = posB.x - offNP.x * FXAA_QUALITY_P0;\\\\n\\\\t\\\\t\\\\t\\\\tposN.y = posB.y - offNP.y * FXAA_QUALITY_P0;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat2 posP;\\\\n\\\\t\\\\t\\\\t\\\\tposP.x = posB.x + offNP.x * FXAA_QUALITY_P0;\\\\n\\\\t\\\\t\\\\t\\\\tposP.y = posB.y + offNP.y * FXAA_QUALITY_P0;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat subpixD = ((-2.0)*subpixC) + 3.0;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat lumaEndN = FxaaLuma(FxaaTexTop(tex, posN));\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat subpixE = subpixC * subpixC;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat lumaEndP = FxaaLuma(FxaaTexTop(tex, posP));\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\tif(!pairN) lumaNN = lumaSS;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat gradientScaled = gradient * 1.0/4.0;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat lumaMM = lumaM - lumaNN * 0.5;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat subpixF = subpixD * subpixE;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaBool lumaMLTZero = lumaMM < 0.0;\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\tlumaEndN -= lumaNN * 0.5;\\\\n\\\\t\\\\t\\\\t\\\\tlumaEndP -= lumaNN * 0.5;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaBool doneN = abs(lumaEndN) >= gradientScaled;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaBool doneP = abs(lumaEndP) >= gradientScaled;\\\\n\\\\t\\\\t\\\\t\\\\tif(!doneN) posN.x -= offNP.x * FXAA_QUALITY_P1;\\\\n\\\\t\\\\t\\\\t\\\\tif(!doneN) posN.y -= offNP.y * FXAA_QUALITY_P1;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaBool doneNP = (!doneN) || (!doneP);\\\\n\\\\t\\\\t\\\\t\\\\tif(!doneP) posP.x += offNP.x * FXAA_QUALITY_P1;\\\\n\\\\t\\\\t\\\\t\\\\tif(!doneP) posP.y += offNP.y * FXAA_QUALITY_P1;\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\tif(doneNP) {\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) lumaEndN = FxaaLuma(FxaaTexTop(tex, posN.xy));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) lumaEndP = FxaaLuma(FxaaTexTop(tex, posP.xy));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) lumaEndN = lumaEndN - lumaNN * 0.5;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) lumaEndP = lumaEndP - lumaNN * 0.5;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tdoneN = abs(lumaEndN) >= gradientScaled;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tdoneP = abs(lumaEndP) >= gradientScaled;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) posN.x -= offNP.x * FXAA_QUALITY_P2;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) posN.y -= offNP.y * FXAA_QUALITY_P2;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tdoneNP = (!doneN) || (!doneP);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) posP.x += offNP.x * FXAA_QUALITY_P2;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) posP.y += offNP.y * FXAA_QUALITY_P2;\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#if (FXAA_QUALITY_PS > 3)\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(doneNP) {\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) lumaEndN = FxaaLuma(FxaaTexTop(tex, posN.xy));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) lumaEndP = FxaaLuma(FxaaTexTop(tex, posP.xy));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) lumaEndN = lumaEndN - lumaNN * 0.5;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) lumaEndP = lumaEndP - lumaNN * 0.5;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tdoneN = abs(lumaEndN) >= gradientScaled;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tdoneP = abs(lumaEndP) >= gradientScaled;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) posN.x -= offNP.x * FXAA_QUALITY_P3;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) posN.y -= offNP.y * FXAA_QUALITY_P3;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tdoneNP = (!doneN) || (!doneP);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) posP.x += offNP.x * FXAA_QUALITY_P3;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) posP.y += offNP.y * FXAA_QUALITY_P3;\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#if (FXAA_QUALITY_PS > 4)\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(doneNP) {\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) lumaEndN = FxaaLuma(FxaaTexTop(tex, posN.xy));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) lumaEndP = FxaaLuma(FxaaTexTop(tex, posP.xy));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) lumaEndN = lumaEndN - lumaNN * 0.5;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) lumaEndP = lumaEndP - lumaNN * 0.5;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tdoneN = abs(lumaEndN) >= gradientScaled;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tdoneP = abs(lumaEndP) >= gradientScaled;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) posN.x -= offNP.x * FXAA_QUALITY_P4;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) posN.y -= offNP.y * FXAA_QUALITY_P4;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tdoneNP = (!doneN) || (!doneP);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) posP.x += offNP.x * FXAA_QUALITY_P4;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) posP.y += offNP.y * FXAA_QUALITY_P4;\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#if (FXAA_QUALITY_PS > 5)\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(doneNP) {\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) lumaEndN = FxaaLuma(FxaaTexTop(tex, posN.xy));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) lumaEndP = FxaaLuma(FxaaTexTop(tex, posP.xy));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) lumaEndN = lumaEndN - lumaNN * 0.5;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) lumaEndP = lumaEndP - lumaNN * 0.5;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tdoneN = abs(lumaEndN) >= gradientScaled;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tdoneP = abs(lumaEndP) >= gradientScaled;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) posN.x -= offNP.x * FXAA_QUALITY_P5;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) posN.y -= offNP.y * FXAA_QUALITY_P5;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tdoneNP = (!doneN) || (!doneP);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) posP.x += offNP.x * FXAA_QUALITY_P5;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) posP.y += offNP.y * FXAA_QUALITY_P5;\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#if (FXAA_QUALITY_PS > 6)\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(doneNP) {\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) lumaEndN = FxaaLuma(FxaaTexTop(tex, posN.xy));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) lumaEndP = FxaaLuma(FxaaTexTop(tex, posP.xy));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) lumaEndN = lumaEndN - lumaNN * 0.5;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) lumaEndP = lumaEndP - lumaNN * 0.5;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tdoneN = abs(lumaEndN) >= gradientScaled;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tdoneP = abs(lumaEndP) >= gradientScaled;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) posN.x -= offNP.x * FXAA_QUALITY_P6;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) posN.y -= offNP.y * FXAA_QUALITY_P6;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tdoneNP = (!doneN) || (!doneP);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) posP.x += offNP.x * FXAA_QUALITY_P6;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) posP.y += offNP.y * FXAA_QUALITY_P6;\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#if (FXAA_QUALITY_PS > 7)\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(doneNP) {\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) lumaEndN = FxaaLuma(FxaaTexTop(tex, posN.xy));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) lumaEndP = FxaaLuma(FxaaTexTop(tex, posP.xy));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) lumaEndN = lumaEndN - lumaNN * 0.5;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) lumaEndP = lumaEndP - lumaNN * 0.5;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tdoneN = abs(lumaEndN) >= gradientScaled;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tdoneP = abs(lumaEndP) >= gradientScaled;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) posN.x -= offNP.x * FXAA_QUALITY_P7;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) posN.y -= offNP.y * FXAA_QUALITY_P7;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tdoneNP = (!doneN) || (!doneP);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) posP.x += offNP.x * FXAA_QUALITY_P7;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) posP.y += offNP.y * FXAA_QUALITY_P7;\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\t#if (FXAA_QUALITY_PS > 8)\\\\n\\\\t\\\\t\\\\t\\\\tif(doneNP) {\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) lumaEndN = FxaaLuma(FxaaTexTop(tex, posN.xy));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) lumaEndP = FxaaLuma(FxaaTexTop(tex, posP.xy));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) lumaEndN = lumaEndN - lumaNN * 0.5;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) lumaEndP = lumaEndP - lumaNN * 0.5;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tdoneN = abs(lumaEndN) >= gradientScaled;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tdoneP = abs(lumaEndP) >= gradientScaled;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) posN.x -= offNP.x * FXAA_QUALITY_P8;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) posN.y -= offNP.y * FXAA_QUALITY_P8;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tdoneNP = (!doneN) || (!doneP);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) posP.x += offNP.x * FXAA_QUALITY_P8;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) posP.y += offNP.y * FXAA_QUALITY_P8;\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#if (FXAA_QUALITY_PS > 9)\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(doneNP) {\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) lumaEndN = FxaaLuma(FxaaTexTop(tex, posN.xy));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) lumaEndP = FxaaLuma(FxaaTexTop(tex, posP.xy));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) lumaEndN = lumaEndN - lumaNN * 0.5;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) lumaEndP = lumaEndP - lumaNN * 0.5;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tdoneN = abs(lumaEndN) >= gradientScaled;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tdoneP = abs(lumaEndP) >= gradientScaled;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) posN.x -= offNP.x * FXAA_QUALITY_P9;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) posN.y -= offNP.y * FXAA_QUALITY_P9;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tdoneNP = (!doneN) || (!doneP);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) posP.x += offNP.x * FXAA_QUALITY_P9;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) posP.y += offNP.y * FXAA_QUALITY_P9;\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#if (FXAA_QUALITY_PS > 10)\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(doneNP) {\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) lumaEndN = FxaaLuma(FxaaTexTop(tex, posN.xy));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) lumaEndP = FxaaLuma(FxaaTexTop(tex, posP.xy));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) lumaEndN = lumaEndN - lumaNN * 0.5;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) lumaEndP = lumaEndP - lumaNN * 0.5;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tdoneN = abs(lumaEndN) >= gradientScaled;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tdoneP = abs(lumaEndP) >= gradientScaled;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) posN.x -= offNP.x * FXAA_QUALITY_P10;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) posN.y -= offNP.y * FXAA_QUALITY_P10;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tdoneNP = (!doneN) || (!doneP);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) posP.x += offNP.x * FXAA_QUALITY_P10;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) posP.y += offNP.y * FXAA_QUALITY_P10;\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#if (FXAA_QUALITY_PS > 11)\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(doneNP) {\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) lumaEndN = FxaaLuma(FxaaTexTop(tex, posN.xy));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) lumaEndP = FxaaLuma(FxaaTexTop(tex, posP.xy));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) lumaEndN = lumaEndN - lumaNN * 0.5;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) lumaEndP = lumaEndP - lumaNN * 0.5;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tdoneN = abs(lumaEndN) >= gradientScaled;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tdoneP = abs(lumaEndP) >= gradientScaled;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) posN.x -= offNP.x * FXAA_QUALITY_P11;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) posN.y -= offNP.y * FXAA_QUALITY_P11;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tdoneNP = (!doneN) || (!doneP);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) posP.x += offNP.x * FXAA_QUALITY_P11;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) posP.y += offNP.y * FXAA_QUALITY_P11;\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#if (FXAA_QUALITY_PS > 12)\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(doneNP) {\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) lumaEndN = FxaaLuma(FxaaTexTop(tex, posN.xy));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) lumaEndP = FxaaLuma(FxaaTexTop(tex, posP.xy));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) lumaEndN = lumaEndN - lumaNN * 0.5;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) lumaEndP = lumaEndP - lumaNN * 0.5;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tdoneN = abs(lumaEndN) >= gradientScaled;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tdoneP = abs(lumaEndP) >= gradientScaled;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) posN.x -= offNP.x * FXAA_QUALITY_P12;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) posN.y -= offNP.y * FXAA_QUALITY_P12;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tdoneNP = (!doneN) || (!doneP);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) posP.x += offNP.x * FXAA_QUALITY_P12;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) posP.y += offNP.y * FXAA_QUALITY_P12;\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t}\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t}\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t}\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t}\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\t}\\\\n\\\\t\\\\t\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t}\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t}\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t}\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t}\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t}\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\t}\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat dstN = posM.x - posN.x;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat dstP = posP.x - posM.x;\\\\n\\\\t\\\\t\\\\t\\\\tif(!horzSpan) dstN = posM.y - posN.y;\\\\n\\\\t\\\\t\\\\t\\\\tif(!horzSpan) dstP = posP.y - posM.y;\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\tFxaaBool goodSpanN = (lumaEndN < 0.0) != lumaMLTZero;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat spanLength = (dstP + dstN);\\\\n\\\\t\\\\t\\\\t\\\\tFxaaBool goodSpanP = (lumaEndP < 0.0) != lumaMLTZero;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat spanLengthRcp = 1.0/spanLength;\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\tFxaaBool directionN = dstN < dstP;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat dst = min(dstN, dstP);\\\\n\\\\t\\\\t\\\\t\\\\tFxaaBool goodSpan = directionN ? goodSpanN : goodSpanP;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat subpixG = subpixF * subpixF;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat pixelOffset = (dst * (-spanLengthRcp)) + 0.5;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat subpixH = subpixG * fxaaQualitySubpix;\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat pixelOffsetGood = goodSpan ? pixelOffset : 0.0;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat pixelOffsetSubpix = max(pixelOffsetGood, subpixH);\\\\n\\\\t\\\\t\\\\t\\\\tif(!horzSpan) posM.x += pixelOffsetSubpix * lengthSign;\\\\n\\\\t\\\\t\\\\t\\\\tif( horzSpan) posM.y += pixelOffsetSubpix * lengthSign;\\\\n\\\\t\\\\t\\\\t\\\\t#if (FXAA_DISCARD == 1)\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\treturn FxaaTexTop(tex, posM);\\\\n\\\\t\\\\t\\\\t\\\\t#else\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\treturn FxaaFloat4(FxaaTexTop(tex, posM).xyz, lumaM);\\\\n\\\\t\\\\t\\\\t\\\\t#endif\\\\n\\\\t\\\\t}\\\\n\\\\t\\\\t/*==========================================================================*/\\\\n\\\\t\\\\t#endif\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\t\\\\t\\\\tgl_FragColor = FxaaPixelShader(\\\\n\\\\t\\\\t\\\\t\\\\tvUv,\\\\n\\\\t\\\\t\\\\t\\\\tvec4(0.0),\\\\n\\\\t\\\\t\\\\t\\\\ttDiffuse,\\\\n\\\\t\\\\t\\\\t\\\\ttDiffuse,\\\\n\\\\t\\\\t\\\\t\\\\ttDiffuse,\\\\n\\\\t\\\\t\\\\t\\\\tresolution,\\\\n\\\\t\\\\t\\\\t\\\\tvec4(0.0),\\\\n\\\\t\\\\t\\\\t\\\\tvec4(0.0),\\\\n\\\\t\\\\t\\\\t\\\\tvec4(0.0),\\\\n\\\\t\\\\t\\\\t\\\\t0.75,\\\\n\\\\t\\\\t\\\\t\\\\t0.166,\\\\n\\\\t\\\\t\\\\t\\\\t0.0833,\\\\n\\\\t\\\\t\\\\t\\\\t0.0,\\\\n\\\\t\\\\t\\\\t\\\\t0.0,\\\\n\\\\t\\\\t\\\\t\\\\t0.0,\\\\n\\\\t\\\\t\\\\t\\\\tvec4(0.0)\\\\n\\\\t\\\\t\\\\t);\\\\n\\\\n\\\\t\\\\t\\\\t// TODO avoid querying texture twice for same texel\\\\n\\\\t\\\\t\\\\tgl_FragColor.a = texture2D(tDiffuse, vUv).a;\\\\n\\\\t\\\\t}'};const aW=new class extends ua{constructor(){super(...arguments),this.transparent=ha.BOOLEAN(1,xj)}};class lW extends bj{constructor(){super(...arguments),this.paramsConfig=aW}static type(){return\\\\\\\"FXAA\\\\\\\"}_createPass(t){const e=new Hm(oW);return e.uniforms.resolution.value.set(1/t.resolution.x,1/t.resolution.y),e.material.transparent=!0,this.updatePass(e),e}updatePass(t){t.material.transparent=this.pv.transparent}}const cW={uniforms:{tDiffuse:{value:null}},vertexShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\tvUv = uv;\\\\n\\\\t\\\\t\\\\tgl_Position = projectionMatrix * modelViewMatrix * vec4( position, 1.0 );\\\\n\\\\n\\\\t\\\\t}\\\\\\\",fragmentShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\tuniform sampler2D tDiffuse;\\\\n\\\\n\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\tvec4 tex = texture2D( tDiffuse, vUv );\\\\n\\\\n\\\\t\\\\t\\\\tgl_FragColor = LinearTosRGB( tex ); // optional: LinearToGamma( tex, float( GAMMA_FACTOR ) );\\\\n\\\\n\\\\t\\\\t}\\\\\\\"};const hW=new class extends ua{};class uW extends bj{constructor(){super(...arguments),this.paramsConfig=hW}static type(){return\\\\\\\"gammaCorrection\\\\\\\"}_createPass(t){const e=new Hm(cW);return this.updatePass(e),e}updatePass(t){}}const dW=new class extends ua{constructor(){super(...arguments),this.amount=ha.FLOAT(2,{range:[0,10],rangeLocked:[!0,!1],step:.01,...xj}),this.transparent=ha.BOOLEAN(1,xj)}};class pW extends bj{constructor(){super(...arguments),this.paramsConfig=dW}static type(){return\\\\\\\"horizontalBlur\\\\\\\"}_createPass(t){const e=new Hm(CG);return e.resolution_x=t.resolution.x,this.updatePass(e),e}updatePass(t){t.uniforms.h.value=this.pv.amount/(t.resolution_x*window.devicePixelRatio),t.material.transparent=this.pv.transparent}}const _W=new class extends ua{constructor(){super(...arguments),this.map=ha.OPERATOR_PATH(vi.UV,{nodeSelection:{context:ts.COP},...xj}),this.darkness=ha.FLOAT(0,{range:[0,2],rangeLocked:[!0,!1],...xj}),this.offset=ha.FLOAT(0,{range:[0,2],rangeLocked:[!0,!1],...xj})}};class mW extends bj{constructor(){super(...arguments),this.paramsConfig=_W}static type(){return\\\\\\\"image\\\\\\\"}static _create_shader(){return{uniforms:{tDiffuse:{value:null},map:{value:null},offset:{value:1},darkness:{value:1}},vertexShader:\\\\\\\"varying vec2 vUv;\\\\nvoid main() {\\\\n\\\\tvUv = uv;\\\\n\\\\tgl_Position = projectionMatrix * modelViewMatrix * vec4( position, 1.0 );\\\\n}\\\\\\\",fragmentShader:\\\\\\\"uniform float offset;\\\\nuniform float darkness;\\\\nuniform sampler2D tDiffuse;\\\\nuniform sampler2D map;\\\\nvarying vec2 vUv;\\\\n\\\\nvoid main() {\\\\n\\\\n\\\\tvec4 texel = texture2D( tDiffuse, vUv );\\\\n\\\\tvec4 map_val = texture2D( map, vUv );\\\\n\\\\tvec2 uv = ( vUv - vec2( 0.5 ) ) * vec2( offset );\\\\n\\\\t// gl_FragColor = vec4( mix( texel.rgb, vec3( 1.0 - darkness ), dot( uv, uv ) ), texel.a );\\\\n\\\\tgl_FragColor = vec4( mix( texel.rgb, map_val.rgb, map_val.a ), texel.a );\\\\n\\\\n}\\\\n\\\\\\\"}}_createPass(t){const e=new Hm(mW._create_shader());return this.updatePass(e),e}updatePass(t){t.uniforms.darkness.value=this.pv.darkness,t.uniforms.offset.value=this.pv.offset,this._update_map(t)}async _update_map(t){this.p.map.isDirty()&&await this.p.map.compute();const e=this.p.map.found_node();if(e)if(e.context()==ts.COP){const n=e,i=(await n.compute()).coreContent();t.uniforms.map.value=i}else this.states.error.set(\\\\\\\"node is not COP\\\\\\\");else this.states.error.set(\\\\\\\"no map found\\\\\\\")}}const fW={tDiffuse:{value:null},texture1:{value:null},texture2:{value:null},h:{value:1/512}},gW=\\\\\\\"varying vec2 vUv;\\\\n\\\\nvoid main() {\\\\n\\\\n\\\\tvUv = uv;\\\\n\\\\tgl_Position = projectionMatrix * modelViewMatrix * vec4( position, 1.0 );\\\\n\\\\n}\\\\\\\",vW=\\\\\\\"uniform sampler2D texture1;\\\\nuniform sampler2D texture2;\\\\nvarying vec2 vUv;\\\\n\\\\nvoid main() {\\\\n\\\\n\\\\tvec4 t1 = texture2D( texture1, vUv);\\\\n\\\\tvec4 t2 = texture2D( texture2, vUv);\\\\n\\\\n\\\\tvec3 c1 = t1.rgb * t1.a * (1.0-t2.a);\\\\n\\\\tvec3 c2 = t2.rgb * t2.a;\\\\n\\\\tfloat a = t2.a + t1.a;\\\\n\\\\tvec3 c = max(c1,c2);\\\\n\\\\n\\\\tgl_FragColor = vec4(c,a);\\\\n\\\\n}\\\\\\\";class yW extends km{constructor(t,e){super(),this._composer1=t,this._composer2=e,this.uniforms=I.clone(fW),this.material=new F({uniforms:this.uniforms,vertexShader:gW,fragmentShader:vW,transparent:!0}),this.fsQuad=new Vm(this.material)}render(t,e){this._composer1.render(),this._composer2.render(),this.uniforms.texture1.value=this._composer1.readBuffer.texture,this.uniforms.texture2.value=this._composer2.readBuffer.texture,this.renderToScreen?(t.setRenderTarget(null),this.fsQuad.render(t)):(t.setRenderTarget(e),this.clear&&t.clear(t.autoClearColor,t.autoClearDepth,t.autoClearStencil),this.fsQuad.render(t))}}const xW=new class extends ua{};class bW extends bj{constructor(){super(...arguments),this.paramsConfig=xW}static type(){return\\\\\\\"layer\\\\\\\"}initializeNode(){super.initializeNode(),this.io.inputs.setCount(2)}setupComposer(t){const e=t.composer.renderer,n={minFilter:w.V,magFilter:w.V,format:w.Ib,stencilBuffer:!0},i=li.renderersController.renderTarget(e.domElement.offsetWidth,e.domElement.offsetHeight,n),s=li.renderersController.renderTarget(e.domElement.offsetWidth,e.domElement.offsetHeight,n),r=new qm(e,i),o=new qm(e,s);r.renderToScreen=!1,o.renderToScreen=!1;const a={...t},l={...t};a.composer=r,l.composer=o,this._addPassFromInput(0,a),this._addPassFromInput(1,l);const c=new yW(r,o);this.updatePass(c),t.composer.addPass(c)}updatePass(t){}}const wW=new class extends ua{constructor(){super(...arguments),this.overrideScene=ha.BOOLEAN(0,xj),this.scene=ha.OPERATOR_PATH(\\\\\\\"/scene1\\\\\\\",{visibleIf:{overrideScene:1},nodeSelection:{context:ts.OBJ,types:[WV.type()]},...xj}),this.overrideCamera=ha.BOOLEAN(0,xj),this.camera=ha.OPERATOR_PATH(\\\\\\\"/perspective_camera1\\\\\\\",{visibleIf:{overrideCamera:1},nodeSelection:{context:ts.OBJ},...xj}),this.inverse=ha.BOOLEAN(0,xj)}};class TW extends bj{constructor(){super(...arguments),this.paramsConfig=wW}static type(){return\\\\\\\"mask\\\\\\\"}_createPass(t){const e=new jm(t.scene,t.camera);return e.context={scene:t.scene,camera:t.camera},this.updatePass(e),e}updatePass(t){t.inverse=this.pv.inverse,this._update_scene(t),this._updateCamera(t)}async _update_scene(t){if(this.pv.overrideScene){this.p.scene.isDirty()&&await this.p.scene.compute();const e=this.p.scene.found_node_with_expected_type();if(e)return void(t.scene=e.object)}t.scene=t.context.scene}async _updateCamera(t){if(this.pv.overrideCamera){this.p.camera.isDirty()&&await this.p.camera.compute();const e=this.p.camera.found_node_with_expected_type();if(e)return void(t.camera=e.object)}t.camera=t.context.camera}}const AW=new class extends ua{};class MW extends bj{constructor(){super(...arguments),this.paramsConfig=AW}static type(){return\\\\\\\"null\\\\\\\"}}class EW extends km{constructor(t,e,n,i){super(),this.renderScene=e,this.renderCamera=n,this.selectedObjects=void 0!==i?i:[],this.visibleEdgeColor=new D.a(1,1,1),this.hiddenEdgeColor=new D.a(.1,.04,.02),this.edgeGlow=0,this.usePatternTexture=!1,this.edgeThickness=1,this.edgeStrength=3,this.downSampleRatio=2,this.pulsePeriod=0,this._visibilityCache=new Map,this.resolution=void 0!==t?new d.a(t.x,t.y):new d.a(256,256);const s={minFilter:w.V,magFilter:w.V,format:w.Ib},r=Math.round(this.resolution.x/this.downSampleRatio),o=Math.round(this.resolution.y/this.downSampleRatio);this.maskBufferMaterial=new lt.a({color:16777215}),this.maskBufferMaterial.side=w.z,this.renderTargetMaskBuffer=new K(this.resolution.x,this.resolution.y,s),this.renderTargetMaskBuffer.texture.name=\\\\\\\"OutlinePass.mask\\\\\\\",this.renderTargetMaskBuffer.texture.generateMipmaps=!1,this.depthMaterial=new Sn,this.depthMaterial.side=w.z,this.depthMaterial.depthPacking=w.Hb,this.depthMaterial.blending=w.ub,this.prepareMaskMaterial=this.getPrepareMaskMaterial(),this.prepareMaskMaterial.side=w.z,this.prepareMaskMaterial.fragmentShader=function(t,e){var n=e.isPerspectiveCamera?\\\\\\\"perspective\\\\\\\":\\\\\\\"orthographic\\\\\\\";return t.replace(/DEPTH_TO_VIEW_Z/g,n+\\\\\\\"DepthToViewZ\\\\\\\")}(this.prepareMaskMaterial.fragmentShader,this.renderCamera),this.renderTargetDepthBuffer=new K(this.resolution.x,this.resolution.y,s),this.renderTargetDepthBuffer.texture.name=\\\\\\\"OutlinePass.depth\\\\\\\",this.renderTargetDepthBuffer.texture.generateMipmaps=!1,this.renderTargetMaskDownSampleBuffer=new K(r,o,s),this.renderTargetMaskDownSampleBuffer.texture.name=\\\\\\\"OutlinePass.depthDownSample\\\\\\\",this.renderTargetMaskDownSampleBuffer.texture.generateMipmaps=!1,this.renderTargetBlurBuffer1=new K(r,o,s),this.renderTargetBlurBuffer1.texture.name=\\\\\\\"OutlinePass.blur1\\\\\\\",this.renderTargetBlurBuffer1.texture.generateMipmaps=!1,this.renderTargetBlurBuffer2=new K(Math.round(r/2),Math.round(o/2),s),this.renderTargetBlurBuffer2.texture.name=\\\\\\\"OutlinePass.blur2\\\\\\\",this.renderTargetBlurBuffer2.texture.generateMipmaps=!1,this.edgeDetectionMaterial=this.getEdgeDetectionMaterial(),this.renderTargetEdgeBuffer1=new K(r,o,s),this.renderTargetEdgeBuffer1.texture.name=\\\\\\\"OutlinePass.edge1\\\\\\\",this.renderTargetEdgeBuffer1.texture.generateMipmaps=!1,this.renderTargetEdgeBuffer2=new K(Math.round(r/2),Math.round(o/2),s),this.renderTargetEdgeBuffer2.texture.name=\\\\\\\"OutlinePass.edge2\\\\\\\",this.renderTargetEdgeBuffer2.texture.generateMipmaps=!1;this.separableBlurMaterial1=this.getSeperableBlurMaterial(4),this.separableBlurMaterial1.uniforms.texSize.value.set(r,o),this.separableBlurMaterial1.uniforms.kernelRadius.value=1,this.separableBlurMaterial2=this.getSeperableBlurMaterial(4),this.separableBlurMaterial2.uniforms.texSize.value.set(Math.round(r/2),Math.round(o/2)),this.separableBlurMaterial2.uniforms.kernelRadius.value=4,this.overlayMaterial=this.getOverlayMaterial(),void 0===zm&&console.error(\\\\\\\"THREE.OutlinePass relies on CopyShader\\\\\\\");const a=zm;this.copyUniforms=I.clone(a.uniforms),this.copyUniforms.opacity.value=1,this.materialCopy=new F({uniforms:this.copyUniforms,vertexShader:a.vertexShader,fragmentShader:a.fragmentShader,blending:w.ub,depthTest:!1,depthWrite:!1,transparent:!0}),this.enabled=!0,this.needsSwap=!1,this._oldClearColor=new D.a,this.oldClearAlpha=1,this.fsQuad=new Vm(null),this.tempPulseColor1=new D.a,this.tempPulseColor2=new D.a,this.textureMatrix=new A.a}dispose(){this.renderTargetMaskBuffer.dispose(),this.renderTargetDepthBuffer.dispose(),this.renderTargetMaskDownSampleBuffer.dispose(),this.renderTargetBlurBuffer1.dispose(),this.renderTargetBlurBuffer2.dispose(),this.renderTargetEdgeBuffer1.dispose(),this.renderTargetEdgeBuffer2.dispose()}setSize(t,e){this.renderTargetMaskBuffer.setSize(t,e),this.renderTargetDepthBuffer.setSize(t,e);let n=Math.round(t/this.downSampleRatio),i=Math.round(e/this.downSampleRatio);this.renderTargetMaskDownSampleBuffer.setSize(n,i),this.renderTargetBlurBuffer1.setSize(n,i),this.renderTargetEdgeBuffer1.setSize(n,i),this.separableBlurMaterial1.uniforms.texSize.value.set(n,i),n=Math.round(n/2),i=Math.round(i/2),this.renderTargetBlurBuffer2.setSize(n,i),this.renderTargetEdgeBuffer2.setSize(n,i),this.separableBlurMaterial2.uniforms.texSize.value.set(n,i)}changeVisibilityOfSelectedObjects(t){const e=this._visibilityCache;function n(n){n.isMesh&&(!0===t?n.visible=e.get(n):(e.set(n,n.visible),n.visible=t))}for(let t=0;t0){t.getClearColor(this._oldClearColor),this.oldClearAlpha=t.getClearAlpha();const e=t.autoClear;t.autoClear=!1,s&&t.state.buffers.stencil.setTest(!1),t.setClearColor(16777215,1),this.changeVisibilityOfSelectedObjects(!1);const i=this.renderScene.background;if(this.renderScene.background=null,this.renderScene.overrideMaterial=this.depthMaterial,t.setRenderTarget(this.renderTargetDepthBuffer),t.clear(),t.render(this.renderScene,this.renderCamera),this.changeVisibilityOfSelectedObjects(!0),this._visibilityCache.clear(),this.updateTextureMatrix(),this.changeVisibilityOfNonSelectedObjects(!1),this.renderScene.overrideMaterial=this.prepareMaskMaterial,this.prepareMaskMaterial.uniforms.cameraNearFar.value.set(this.renderCamera.near,this.renderCamera.far),this.prepareMaskMaterial.uniforms.depthTexture.value=this.renderTargetDepthBuffer.texture,this.prepareMaskMaterial.uniforms.textureMatrix.value=this.textureMatrix,t.setRenderTarget(this.renderTargetMaskBuffer),t.clear(),t.render(this.renderScene,this.renderCamera),this.renderScene.overrideMaterial=null,this.changeVisibilityOfNonSelectedObjects(!0),this._visibilityCache.clear(),this.renderScene.background=i,this.fsQuad.material=this.materialCopy,this.copyUniforms.tDiffuse.value=this.renderTargetMaskBuffer.texture,t.setRenderTarget(this.renderTargetMaskDownSampleBuffer),t.clear(),this.fsQuad.render(t),this.tempPulseColor1.copy(this.visibleEdgeColor),this.tempPulseColor2.copy(this.hiddenEdgeColor),this.pulsePeriod>0){const t=.625+.75*Math.cos(.01*performance.now()/this.pulsePeriod)/2;this.tempPulseColor1.multiplyScalar(t),this.tempPulseColor2.multiplyScalar(t)}this.fsQuad.material=this.edgeDetectionMaterial,this.edgeDetectionMaterial.uniforms.maskTexture.value=this.renderTargetMaskDownSampleBuffer.texture,this.edgeDetectionMaterial.uniforms.texSize.value.set(this.renderTargetMaskDownSampleBuffer.width,this.renderTargetMaskDownSampleBuffer.height),this.edgeDetectionMaterial.uniforms.visibleEdgeColor.value=this.tempPulseColor1,this.edgeDetectionMaterial.uniforms.hiddenEdgeColor.value=this.tempPulseColor2,t.setRenderTarget(this.renderTargetEdgeBuffer1),t.clear(),this.fsQuad.render(t),this.fsQuad.material=this.separableBlurMaterial1,this.separableBlurMaterial1.uniforms.colorTexture.value=this.renderTargetEdgeBuffer1.texture,this.separableBlurMaterial1.uniforms.direction.value=EW.BlurDirectionX,this.separableBlurMaterial1.uniforms.kernelRadius.value=this.edgeThickness,t.setRenderTarget(this.renderTargetBlurBuffer1),t.clear(),this.fsQuad.render(t),this.separableBlurMaterial1.uniforms.colorTexture.value=this.renderTargetBlurBuffer1.texture,this.separableBlurMaterial1.uniforms.direction.value=EW.BlurDirectionY,t.setRenderTarget(this.renderTargetEdgeBuffer1),t.clear(),this.fsQuad.render(t),this.fsQuad.material=this.separableBlurMaterial2,this.separableBlurMaterial2.uniforms.colorTexture.value=this.renderTargetEdgeBuffer1.texture,this.separableBlurMaterial2.uniforms.direction.value=EW.BlurDirectionX,t.setRenderTarget(this.renderTargetBlurBuffer2),t.clear(),this.fsQuad.render(t),this.separableBlurMaterial2.uniforms.colorTexture.value=this.renderTargetBlurBuffer2.texture,this.separableBlurMaterial2.uniforms.direction.value=EW.BlurDirectionY,t.setRenderTarget(this.renderTargetEdgeBuffer2),t.clear(),this.fsQuad.render(t),this.fsQuad.material=this.overlayMaterial,this.overlayMaterial.uniforms.maskTexture.value=this.renderTargetMaskBuffer.texture,this.overlayMaterial.uniforms.edgeTexture1.value=this.renderTargetEdgeBuffer1.texture,this.overlayMaterial.uniforms.edgeTexture2.value=this.renderTargetEdgeBuffer2.texture,this.overlayMaterial.uniforms.patternTexture.value=this.patternTexture,this.overlayMaterial.uniforms.edgeStrength.value=this.edgeStrength,this.overlayMaterial.uniforms.edgeGlow.value=this.edgeGlow,this.overlayMaterial.uniforms.usePatternTexture.value=this.usePatternTexture,s&&t.state.buffers.stencil.setTest(!0),t.setRenderTarget(n),this.fsQuad.render(t),t.setClearColor(this._oldClearColor,this.oldClearAlpha),t.autoClear=e}this.renderToScreen&&(this.fsQuad.material=this.materialCopy,this.copyUniforms.tDiffuse.value=n.texture,t.setRenderTarget(null),this.fsQuad.render(t))}getPrepareMaskMaterial(){return new F({uniforms:{depthTexture:{value:null},cameraNearFar:{value:new d.a(.5,.5)},textureMatrix:{value:null}},vertexShader:\\\\\\\"#include \\\\n\\\\t\\\\t\\\\t\\\\t#include \\\\n\\\\n\\\\t\\\\t\\\\t\\\\tvarying vec4 projTexCoord;\\\\n\\\\t\\\\t\\\\t\\\\tvarying vec4 vPosition;\\\\n\\\\t\\\\t\\\\t\\\\tuniform mat4 textureMatrix;\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t#include \\\\n\\\\t\\\\t\\\\t\\\\t\\\\t#include \\\\n\\\\t\\\\t\\\\t\\\\t\\\\t#include \\\\n\\\\t\\\\t\\\\t\\\\t\\\\t#include \\\\n\\\\t\\\\t\\\\t\\\\t\\\\t#include \\\\n\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tvPosition = mvPosition;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tvec4 worldPosition = modelMatrix * vec4( transformed, 1.0 );\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tprojTexCoord = textureMatrix * worldPosition;\\\\n\\\\n\\\\t\\\\t\\\\t\\\\t}\\\\\\\",fragmentShader:\\\\\\\"#include \\\\n\\\\t\\\\t\\\\t\\\\tvarying vec4 vPosition;\\\\n\\\\t\\\\t\\\\t\\\\tvarying vec4 projTexCoord;\\\\n\\\\t\\\\t\\\\t\\\\tuniform sampler2D depthTexture;\\\\n\\\\t\\\\t\\\\t\\\\tuniform vec2 cameraNearFar;\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tfloat depth = unpackRGBAToDepth(texture2DProj( depthTexture, projTexCoord ));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tfloat viewZ = - DEPTH_TO_VIEW_Z( depth, cameraNearFar.x, cameraNearFar.y );\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tfloat depthTest = (-vPosition.z > viewZ) ? 1.0 : 0.0;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tgl_FragColor = vec4(0.0, depthTest, 1.0, 1.0);\\\\n\\\\n\\\\t\\\\t\\\\t\\\\t}\\\\\\\"})}getEdgeDetectionMaterial(){return new F({uniforms:{maskTexture:{value:null},texSize:{value:new d.a(.5,.5)},visibleEdgeColor:{value:new p.a(1,1,1)},hiddenEdgeColor:{value:new p.a(1,1,1)}},vertexShader:\\\\\\\"varying vec2 vUv;\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tvoid main() {\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tvUv = uv;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tgl_Position = projectionMatrix * modelViewMatrix * vec4( position, 1.0 );\\\\n\\\\t\\\\t\\\\t\\\\t}\\\\\\\",fragmentShader:\\\\\\\"varying vec2 vUv;\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tuniform sampler2D maskTexture;\\\\n\\\\t\\\\t\\\\t\\\\tuniform vec2 texSize;\\\\n\\\\t\\\\t\\\\t\\\\tuniform vec3 visibleEdgeColor;\\\\n\\\\t\\\\t\\\\t\\\\tuniform vec3 hiddenEdgeColor;\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tvoid main() {\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tvec2 invSize = 1.0 / texSize;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tvec4 uvOffset = vec4(1.0, 0.0, 0.0, 1.0) * vec4(invSize, invSize);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tvec4 c1 = texture2D( maskTexture, vUv + uvOffset.xy);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tvec4 c2 = texture2D( maskTexture, vUv - uvOffset.xy);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tvec4 c3 = texture2D( maskTexture, vUv + uvOffset.yw);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tvec4 c4 = texture2D( maskTexture, vUv - uvOffset.yw);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tfloat diff1 = (c1.r - c2.r)*0.5;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tfloat diff2 = (c3.r - c4.r)*0.5;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tfloat d = length( vec2(diff1, diff2) );\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tfloat a1 = min(c1.g, c2.g);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tfloat a2 = min(c3.g, c4.g);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tfloat visibilityFactor = min(a1, a2);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tvec3 edgeColor = 1.0 - visibilityFactor > 0.001 ? visibleEdgeColor : hiddenEdgeColor;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tgl_FragColor = vec4(edgeColor, 1.0) * vec4(d);\\\\n\\\\t\\\\t\\\\t\\\\t}\\\\\\\"})}getSeperableBlurMaterial(t){return new F({defines:{MAX_RADIUS:t},uniforms:{colorTexture:{value:null},texSize:{value:new d.a(.5,.5)},direction:{value:new d.a(.5,.5)},kernelRadius:{value:1}},vertexShader:\\\\\\\"varying vec2 vUv;\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tvoid main() {\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tvUv = uv;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tgl_Position = projectionMatrix * modelViewMatrix * vec4( position, 1.0 );\\\\n\\\\t\\\\t\\\\t\\\\t}\\\\\\\",fragmentShader:\\\\\\\"#include \\\\n\\\\t\\\\t\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\t\\\\t\\\\t\\\\tuniform sampler2D colorTexture;\\\\n\\\\t\\\\t\\\\t\\\\tuniform vec2 texSize;\\\\n\\\\t\\\\t\\\\t\\\\tuniform vec2 direction;\\\\n\\\\t\\\\t\\\\t\\\\tuniform float kernelRadius;\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tfloat gaussianPdf(in float x, in float sigma) {\\\\n\\\\t\\\\t\\\\t\\\\t\\\\treturn 0.39894 * exp( -0.5 * x * x/( sigma * sigma))/sigma;\\\\n\\\\t\\\\t\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tvoid main() {\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tvec2 invSize = 1.0 / texSize;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tfloat weightSum = gaussianPdf(0.0, kernelRadius);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tvec4 diffuseSum = texture2D( colorTexture, vUv) * weightSum;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tvec2 delta = direction * invSize * kernelRadius/float(MAX_RADIUS);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tvec2 uvOffset = delta;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tfor( int i = 1; i <= MAX_RADIUS; i ++ ) {\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tfloat w = gaussianPdf(uvOffset.x, kernelRadius);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tvec4 sample1 = texture2D( colorTexture, vUv + uvOffset);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tvec4 sample2 = texture2D( colorTexture, vUv - uvOffset);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tdiffuseSum += ((sample1 + sample2) * w);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tweightSum += (2.0 * w);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tuvOffset += delta;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t}\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tgl_FragColor = diffuseSum/weightSum;\\\\n\\\\t\\\\t\\\\t\\\\t}\\\\\\\"})}getOverlayMaterial(){return new F({uniforms:{maskTexture:{value:null},edgeTexture1:{value:null},edgeTexture2:{value:null},patternTexture:{value:null},edgeStrength:{value:1},edgeGlow:{value:1},usePatternTexture:{value:0}},vertexShader:\\\\\\\"varying vec2 vUv;\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tvoid main() {\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tvUv = uv;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tgl_Position = projectionMatrix * modelViewMatrix * vec4( position, 1.0 );\\\\n\\\\t\\\\t\\\\t\\\\t}\\\\\\\",fragmentShader:\\\\\\\"varying vec2 vUv;\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tuniform sampler2D maskTexture;\\\\n\\\\t\\\\t\\\\t\\\\tuniform sampler2D edgeTexture1;\\\\n\\\\t\\\\t\\\\t\\\\tuniform sampler2D edgeTexture2;\\\\n\\\\t\\\\t\\\\t\\\\tuniform sampler2D patternTexture;\\\\n\\\\t\\\\t\\\\t\\\\tuniform float edgeStrength;\\\\n\\\\t\\\\t\\\\t\\\\tuniform float edgeGlow;\\\\n\\\\t\\\\t\\\\t\\\\tuniform bool usePatternTexture;\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tvoid main() {\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tvec4 edgeValue1 = texture2D(edgeTexture1, vUv);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tvec4 edgeValue2 = texture2D(edgeTexture2, vUv);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tvec4 maskColor = texture2D(maskTexture, vUv);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tvec4 patternColor = texture2D(patternTexture, 6.0 * vUv);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tfloat visibilityFactor = 1.0 - maskColor.g > 0.0 ? 1.0 : 0.5;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tvec4 edgeValue = edgeValue1 + edgeValue2 * edgeGlow;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tvec4 finalColor = edgeStrength * maskColor.r * edgeValue;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tif(usePatternTexture)\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tfinalColor += + visibilityFactor * (1.0 - maskColor.r) * (1.0 - patternColor.r);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tgl_FragColor = finalColor;\\\\n\\\\t\\\\t\\\\t\\\\t}\\\\\\\",blending:w.e,depthTest:!1,depthWrite:!1,transparent:!0})}}EW.BlurDirectionX=new d.a(1,0),EW.BlurDirectionY=new d.a(0,1);const SW=new class extends ua{constructor(){super(...arguments),this.objectsMask=ha.STRING(\\\\\\\"*outlined*\\\\\\\",{...xj}),this.refreshObjects=ha.BUTTON(null,{...xj}),this.printObjects=ha.BUTTON(null,{cook:!1,callback:t=>{CW.PARAM_CALLBACK_printResolve(t)}}),this.edgeStrength=ha.FLOAT(3,{range:[0,10],rangeLocked:[!0,!1],...xj}),this.edgeThickness=ha.FLOAT(1,{range:[0,4],rangeLocked:[!0,!1],...xj}),this.edgeGlow=ha.FLOAT(0,{range:[0,1],rangeLocked:[!0,!1],...xj}),this.pulsePeriod=ha.FLOAT(0,{range:[0,5],rangeLocked:[!0,!1],...xj}),this.visibleEdgeColor=ha.COLOR([1,1,1],{...xj}),this.hiddenEdgeColor=ha.COLOR([.2,.1,.4],{...xj})}};class CW extends bj{constructor(){super(...arguments),this.paramsConfig=SW,this._resolvedObjects=[],this._map=new Map}static type(){return\\\\\\\"outline\\\\\\\"}_createPass(t){const e=new EW(new d.a(t.resolution.x,t.resolution.y),t.scene,t.camera,t.scene.children);return this.updatePass(e),e}updatePass(t){t.edgeStrength=this.pv.edgeStrength,t.edgeThickness=this.pv.edgeThickness,t.edgeGlow=this.pv.edgeGlow,t.pulsePeriod=this.pv.pulsePeriod,t.visibleEdgeColor=this.pv.visibleEdgeColor,t.hiddenEdgeColor=this.pv.hiddenEdgeColor,this._setSelectedObjects(t)}_setSelectedObjects(t){const e=this.scene().objectsByMask(this.pv.objectsMask);this._map.clear();for(let t of e)this._map.set(t.uuid,t);this._resolvedObjects=e.filter((t=>{let e=!1;return t.traverseAncestors((t=>{this._map.has(t.uuid)&&(e=!0)})),!e})),t.selectedObjects=this._resolvedObjects}static PARAM_CALLBACK_printResolve(t){t.printResolve()}printResolve(){console.log(this._resolvedObjects)}}const NW={uniforms:{tDiffuse:{value:null},resolution:{value:null},pixelSize:{value:1}},vertexShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\tvarying highp vec2 vUv;\\\\n\\\\n\\\\t\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tvUv = uv;\\\\n\\\\t\\\\t\\\\t\\\\tgl_Position = projectionMatrix * modelViewMatrix * vec4( position, 1.0 );\\\\n\\\\n\\\\t\\\\t}\\\\\\\",fragmentShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\tuniform sampler2D tDiffuse;\\\\n\\\\t\\\\tuniform float pixelSize;\\\\n\\\\t\\\\tuniform vec2 resolution;\\\\n\\\\n\\\\t\\\\tvarying highp vec2 vUv;\\\\n\\\\n\\\\t\\\\tvoid main(){\\\\n\\\\n\\\\t\\\\t\\\\tvec2 dxy = pixelSize / resolution;\\\\n\\\\t\\\\t\\\\tvec2 coord = dxy * floor( vUv / dxy );\\\\n\\\\t\\\\t\\\\tgl_FragColor = texture2D(tDiffuse, coord);\\\\n\\\\n\\\\t\\\\t}\\\\\\\"};const LW=new class extends ua{constructor(){super(...arguments),this.pixelSize=ha.INTEGER(16,{range:[1,50],rangeLocked:[!0,!1],...xj})}};class OW extends bj{constructor(){super(...arguments),this.paramsConfig=LW}static type(){return\\\\\\\"pixel\\\\\\\"}_createPass(t){const e=new Hm(NW);return e.uniforms.resolution.value=t.resolution,e.uniforms.resolution.value.multiplyScalar(window.devicePixelRatio),this.updatePass(e),e}updatePass(t){t.uniforms.pixelSize.value=this.pv.pixelSize}}const PW=new class extends ua{constructor(){super(...arguments),this.overrideScene=ha.BOOLEAN(0,xj),this.scene=ha.OPERATOR_PATH(\\\\\\\"/scene1\\\\\\\",{visibleIf:{overrideScene:1},nodeSelection:{context:ts.OBJ,types:[WV.type()]},...xj}),this.overrideCamera=ha.BOOLEAN(0,xj),this.camera=ha.OPERATOR_PATH(\\\\\\\"/perspective_camera1\\\\\\\",{visibleIf:{overrideCamera:1},nodeSelection:{context:ts.OBJ},...xj})}};class RW extends bj{constructor(){super(...arguments),this.paramsConfig=PW}static type(){return\\\\\\\"render\\\\\\\"}_createPass(t){const e=new Ym(t.scene,t.camera);return e.context={camera:t.camera,scene:t.scene},this.updatePass(e),e}updatePass(t){this._updateCamera(t),this._update_scene(t)}async _updateCamera(t){if(this.pv.overrideCamera){this.p.camera.isDirty()&&await this.p.camera.compute();const e=this.p.camera.found_node_with_context(ts.OBJ);if(e&&(e.type()==is.PERSPECTIVE||e.type()==is.ORTHOGRAPHIC)){const n=e.object;t.camera=n}}else t.camera=t.context.camera}async _update_scene(t){if(this.pv.overrideScene){this.p.camera.isDirty()&&await this.p.scene.compute();const e=this.p.scene.found_node_with_context(ts.OBJ);if(e&&e.type()==WV.type()){const n=e.object;t.scene=n}}else t.scene=t.context.scene}}const IW={uniforms:{tDiffuse:{value:null},amount:{value:.005},angle:{value:0}},vertexShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\tvUv = uv;\\\\n\\\\t\\\\t\\\\tgl_Position = projectionMatrix * modelViewMatrix * vec4( position, 1.0 );\\\\n\\\\n\\\\t\\\\t}\\\\\\\",fragmentShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\tuniform sampler2D tDiffuse;\\\\n\\\\t\\\\tuniform float amount;\\\\n\\\\t\\\\tuniform float angle;\\\\n\\\\n\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\tvec2 offset = amount * vec2( cos(angle), sin(angle));\\\\n\\\\t\\\\t\\\\tvec4 cr = texture2D(tDiffuse, vUv + offset);\\\\n\\\\t\\\\t\\\\tvec4 cga = texture2D(tDiffuse, vUv);\\\\n\\\\t\\\\t\\\\tvec4 cb = texture2D(tDiffuse, vUv - offset);\\\\n\\\\t\\\\t\\\\tgl_FragColor = vec4(cr.r, cga.g, cb.b, cga.a);\\\\n\\\\n\\\\t\\\\t}\\\\\\\"};const FW=new class extends ua{constructor(){super(...arguments),this.amount=ha.FLOAT(.005,{range:[0,1],rangeLocked:[!0,!1],...xj}),this.angle=ha.FLOAT(0,{range:[0,10],rangeLocked:[!0,!1],...xj})}};class DW extends bj{constructor(){super(...arguments),this.paramsConfig=FW}static type(){return\\\\\\\"RGBShift\\\\\\\"}_createPass(t){const e=new Hm(IW);return this.updatePass(e),e}updatePass(t){t.uniforms.amount.value=this.pv.amount,t.uniforms.angle.value=this.pv.angle}}const BW={uniforms:{tDiffuse:{value:null},amount:{value:1}},vertexShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\tvUv = uv;\\\\n\\\\t\\\\t\\\\tgl_Position = projectionMatrix * modelViewMatrix * vec4( position, 1.0 );\\\\n\\\\n\\\\t\\\\t}\\\\\\\",fragmentShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\tuniform float amount;\\\\n\\\\n\\\\t\\\\tuniform sampler2D tDiffuse;\\\\n\\\\n\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\tvec4 color = texture2D( tDiffuse, vUv );\\\\n\\\\t\\\\t\\\\tvec3 c = color.rgb;\\\\n\\\\n\\\\t\\\\t\\\\tcolor.r = dot( c, vec3( 1.0 - 0.607 * amount, 0.769 * amount, 0.189 * amount ) );\\\\n\\\\t\\\\t\\\\tcolor.g = dot( c, vec3( 0.349 * amount, 1.0 - 0.314 * amount, 0.168 * amount ) );\\\\n\\\\t\\\\t\\\\tcolor.b = dot( c, vec3( 0.272 * amount, 0.534 * amount, 1.0 - 0.869 * amount ) );\\\\n\\\\n\\\\t\\\\t\\\\tgl_FragColor = vec4( min( vec3( 1.0 ), color.rgb ), color.a );\\\\n\\\\n\\\\t\\\\t}\\\\\\\"};const zW=new class extends ua{constructor(){super(...arguments),this.amount=ha.FLOAT(.5,{range:[0,2],rangeLocked:[!1,!1],...xj})}};class kW extends bj{constructor(){super(...arguments),this.paramsConfig=zW}static type(){return\\\\\\\"sepia\\\\\\\"}_createPass(t){const e=new Hm(BW);return this.updatePass(e),e}updatePass(t){t.uniforms.amount.value=this.pv.amount}}const UW=new class extends ua{};class GW extends bj{constructor(){super(...arguments),this.paramsConfig=UW}static type(){return\\\\\\\"sequence\\\\\\\"}initializeNode(){super.initializeNode(),this.io.inputs.setCount(0,4)}setupComposer(t){this._addPassFromInput(0,t),this._addPassFromInput(1,t),this._addPassFromInput(2,t),this._addPassFromInput(3,t)}}const VW=I.clone(CG.uniforms);VW.delta={value:new d.a};const HW={uniforms:VW,vertexShader:CG.vertexShader,fragmentShader:\\\\\\\"\\\\n#include \\\\n#define ITERATIONS 10.0\\\\nuniform sampler2D tDiffuse;\\\\nuniform vec2 delta;\\\\nvarying vec2 vUv;\\\\nvoid main() {\\\\n\\\\tvec4 color = vec4( 0.0 );\\\\n\\\\tfloat total = 0.0;\\\\n\\\\tfloat offset = rand( vUv );\\\\n\\\\tfor ( float t = -ITERATIONS; t <= ITERATIONS; t ++ ) {\\\\n\\\\t\\\\tfloat percent = ( t + offset - 0.5 ) / ITERATIONS;\\\\n\\\\t\\\\tfloat weight = 1.0 - abs( percent );\\\\n\\\\t\\\\tcolor += texture2D( tDiffuse, vUv + delta * percent ) * weight;\\\\n\\\\t\\\\ttotal += weight;\\\\n\\\\t}\\\\n\\\\tgl_FragColor = color / total;\\\\n}\\\\\\\"};const jW=new class extends ua{constructor(){super(...arguments),this.delta=ha.VECTOR2([2,2],{...xj})}};class WW extends bj{constructor(){super(...arguments),this.paramsConfig=jW}static type(){return\\\\\\\"triangleBlur\\\\\\\"}_createPass(t){const e=new Hm(HW);return e.resolution=t.resolution.clone(),this.updatePass(e),e}updatePass(t){t.uniforms.delta.value.copy(this.pv.delta).divide(t.resolution).multiplyScalar(window.devicePixelRatio)}}const qW={shaderID:\\\\\\\"luminosityHighPass\\\\\\\",uniforms:{tDiffuse:{value:null},luminosityThreshold:{value:1},smoothWidth:{value:1},defaultColor:{value:new D.a(0)},defaultOpacity:{value:0}},vertexShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\tvUv = uv;\\\\n\\\\n\\\\t\\\\t\\\\tgl_Position = projectionMatrix * modelViewMatrix * vec4( position, 1.0 );\\\\n\\\\n\\\\t\\\\t}\\\\\\\",fragmentShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\tuniform sampler2D tDiffuse;\\\\n\\\\t\\\\tuniform vec3 defaultColor;\\\\n\\\\t\\\\tuniform float defaultOpacity;\\\\n\\\\t\\\\tuniform float luminosityThreshold;\\\\n\\\\t\\\\tuniform float smoothWidth;\\\\n\\\\n\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\tvec4 texel = texture2D( tDiffuse, vUv );\\\\n\\\\n\\\\t\\\\t\\\\tvec3 luma = vec3( 0.299, 0.587, 0.114 );\\\\n\\\\n\\\\t\\\\t\\\\tfloat v = dot( texel.xyz, luma );\\\\n\\\\n\\\\t\\\\t\\\\tvec4 outputColor = vec4( defaultColor.rgb, defaultOpacity );\\\\n\\\\n\\\\t\\\\t\\\\tfloat alpha = smoothstep( luminosityThreshold, luminosityThreshold + smoothWidth, v );\\\\n\\\\n\\\\t\\\\t\\\\tgl_FragColor = mix( outputColor, texel, alpha );\\\\n\\\\n\\\\t\\\\t}\\\\\\\"};class XW extends km{constructor(t,e,n,i){super(),this.strength=void 0!==e?e:1,this.radius=n,this.threshold=i,this.resolution=void 0!==t?new d.a(t.x,t.y):new d.a(256,256),this.clearColor=new D.a(0,0,0);const s={minFilter:w.V,magFilter:w.V,format:w.Ib};this.renderTargetsHorizontal=[],this.renderTargetsVertical=[],this.nMips=5;let r=Math.round(this.resolution.x/2),o=Math.round(this.resolution.y/2);this.renderTargetBright=new K(r,o,s),this.renderTargetBright.texture.name=\\\\\\\"UnrealBloomPass.bright\\\\\\\",this.renderTargetBright.texture.generateMipmaps=!1;for(let t=0;t\\\\n\\\\t\\\\t\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\t\\\\t\\\\t\\\\tuniform sampler2D colorTexture;\\\\n\\\\t\\\\t\\\\t\\\\tuniform vec2 texSize;\\\\n\\\\t\\\\t\\\\t\\\\tuniform vec2 direction;\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tfloat gaussianPdf(in float x, in float sigma) {\\\\n\\\\t\\\\t\\\\t\\\\t\\\\treturn 0.39894 * exp( -0.5 * x * x/( sigma * sigma))/sigma;\\\\n\\\\t\\\\t\\\\t\\\\t}\\\\n\\\\t\\\\t\\\\t\\\\tvoid main() {\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tvec2 invSize = 1.0 / texSize;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tfloat fSigma = float(SIGMA);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tfloat weightSum = gaussianPdf(0.0, fSigma);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tvec3 diffuseSum = texture2D( colorTexture, vUv).rgb * weightSum;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tfor( int i = 1; i < KERNEL_RADIUS; i ++ ) {\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tfloat x = float(i);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tfloat w = gaussianPdf(x, fSigma);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tvec2 uvOffset = direction * invSize * x;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tvec3 sample1 = texture2D( colorTexture, vUv + uvOffset).rgb;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tvec3 sample2 = texture2D( colorTexture, vUv - uvOffset).rgb;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tdiffuseSum += (sample1 + sample2) * w;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tweightSum += 2.0 * w;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t}\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tgl_FragColor = vec4(diffuseSum/weightSum, 1.0);\\\\n\\\\t\\\\t\\\\t\\\\t}\\\\\\\"})}getCompositeMaterial(t){return new F({defines:{NUM_MIPS:t},uniforms:{blurTexture1:{value:null},blurTexture2:{value:null},blurTexture3:{value:null},blurTexture4:{value:null},blurTexture5:{value:null},dirtTexture:{value:null},bloomStrength:{value:1},bloomFactors:{value:null},bloomTintColors:{value:null},bloomRadius:{value:0}},vertexShader:\\\\\\\"varying vec2 vUv;\\\\n\\\\t\\\\t\\\\t\\\\tvoid main() {\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tvUv = uv;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tgl_Position = projectionMatrix * modelViewMatrix * vec4( position, 1.0 );\\\\n\\\\t\\\\t\\\\t\\\\t}\\\\\\\",fragmentShader:\\\\\\\"varying vec2 vUv;\\\\n\\\\t\\\\t\\\\t\\\\tuniform sampler2D blurTexture1;\\\\n\\\\t\\\\t\\\\t\\\\tuniform sampler2D blurTexture2;\\\\n\\\\t\\\\t\\\\t\\\\tuniform sampler2D blurTexture3;\\\\n\\\\t\\\\t\\\\t\\\\tuniform sampler2D blurTexture4;\\\\n\\\\t\\\\t\\\\t\\\\tuniform sampler2D blurTexture5;\\\\n\\\\t\\\\t\\\\t\\\\tuniform sampler2D dirtTexture;\\\\n\\\\t\\\\t\\\\t\\\\tuniform float bloomStrength;\\\\n\\\\t\\\\t\\\\t\\\\tuniform float bloomRadius;\\\\n\\\\t\\\\t\\\\t\\\\tuniform float bloomFactors[NUM_MIPS];\\\\n\\\\t\\\\t\\\\t\\\\tuniform vec3 bloomTintColors[NUM_MIPS];\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tfloat lerpBloomFactor(const in float factor) {\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tfloat mirrorFactor = 1.2 - factor;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\treturn mix(factor, mirrorFactor, bloomRadius);\\\\n\\\\t\\\\t\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tvoid main() {\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tgl_FragColor = bloomStrength * ( lerpBloomFactor(bloomFactors[0]) * vec4(bloomTintColors[0], 1.0) * texture2D(blurTexture1, vUv) +\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tlerpBloomFactor(bloomFactors[1]) * vec4(bloomTintColors[1], 1.0) * texture2D(blurTexture2, vUv) +\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tlerpBloomFactor(bloomFactors[2]) * vec4(bloomTintColors[2], 1.0) * texture2D(blurTexture3, vUv) +\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tlerpBloomFactor(bloomFactors[3]) * vec4(bloomTintColors[3], 1.0) * texture2D(blurTexture4, vUv) +\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tlerpBloomFactor(bloomFactors[4]) * vec4(bloomTintColors[4], 1.0) * texture2D(blurTexture5, vUv) );\\\\n\\\\t\\\\t\\\\t\\\\t}\\\\\\\"})}}XW.BlurDirectionX=new d.a(1,0),XW.BlurDirectionY=new d.a(0,1);const YW=new class extends ua{constructor(){super(...arguments),this.strength=ha.FLOAT(1.5,{range:[0,3],rangeLocked:[!0,!1],...xj}),this.radius=ha.FLOAT(1,{...xj}),this.threshold=ha.FLOAT(0,{...xj})}};class $W extends bj{constructor(){super(...arguments),this.paramsConfig=YW}static type(){return\\\\\\\"unrealBloom\\\\\\\"}_createPass(t){return new XW(new d.a(t.resolution.x,t.resolution.y),this.pv.strength,this.pv.radius,this.pv.threshold)}updatePass(t){t.strength=this.pv.strength,t.radius=this.pv.radius,t.threshold=this.pv.threshold}}const JW=new class extends ua{constructor(){super(...arguments),this.amount=ha.FLOAT(2,{range:[0,10],rangeLocked:[!0,!1],step:.01,...xj}),this.transparent=ha.BOOLEAN(1,xj)}};class ZW extends bj{constructor(){super(...arguments),this.paramsConfig=JW}static type(){return\\\\\\\"verticalBlur\\\\\\\"}_createPass(t){const e=new Hm(NG);return e.resolution_y=t.resolution.y,this.updatePass(e),e}updatePass(t){t.uniforms.v.value=this.pv.amount/(t.resolution_y*window.devicePixelRatio),t.material.transparent=this.pv.transparent}}const KW={uniforms:{tDiffuse:{value:null},offset:{value:1},darkness:{value:1}},vertexShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\tvUv = uv;\\\\n\\\\t\\\\t\\\\tgl_Position = projectionMatrix * modelViewMatrix * vec4( position, 1.0 );\\\\n\\\\n\\\\t\\\\t}\\\\\\\",fragmentShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\tuniform float offset;\\\\n\\\\t\\\\tuniform float darkness;\\\\n\\\\n\\\\t\\\\tuniform sampler2D tDiffuse;\\\\n\\\\n\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\t// Eskil's vignette\\\\n\\\\n\\\\t\\\\t\\\\tvec4 texel = texture2D( tDiffuse, vUv );\\\\n\\\\t\\\\t\\\\tvec2 uv = ( vUv - vec2( 0.5 ) ) * vec2( offset );\\\\n\\\\t\\\\t\\\\tgl_FragColor = vec4( mix( texel.rgb, vec3( 1.0 - darkness ), dot( uv, uv ) ), texel.a );\\\\n\\\\n\\\\t\\\\t}\\\\\\\"};const QW=new class extends ua{constructor(){super(...arguments),this.offset=ha.FLOAT(1,{range:[0,1],rangeLocked:[!1,!1],...xj}),this.darkness=ha.FLOAT(1,{range:[0,2],rangeLocked:[!0,!1],...xj})}};class tq extends bj{constructor(){super(...arguments),this.paramsConfig=QW}static type(){return\\\\\\\"vignette\\\\\\\"}_createPass(t){const e=new Hm(KW);return this.updatePass(e),e}updatePass(t){t.uniforms.offset.value=this.pv.offset,t.uniforms.darkness.value=this.pv.darkness}}class eq extends aa{static context(){return ts.POST}cook(){this.cookController.endCook()}}class nq extends eq{}class iq extends nq{constructor(){super(...arguments),this._children_controller_context=ts.ANIM}static type(){return es.ANIM}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}}class sq extends nq{constructor(){super(...arguments),this._children_controller_context=ts.COP}static type(){return es.COP}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}}class rq extends nq{constructor(){super(...arguments),this._children_controller_context=ts.EVENT}static type(){return es.EVENT}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}}class oq extends nq{constructor(){super(...arguments),this._children_controller_context=ts.MAT}static type(){return es.MAT}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}}class aq extends eq{constructor(){super(...arguments),this.paramsConfig=new ef,this.effectsComposerController=new nf(this),this.displayNodeController=new Fm(this,this.effectsComposerController.displayNodeControllerCallbacks()),this._children_controller_context=ts.POST}static type(){return es.POST}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}}class lq extends nq{constructor(){super(...arguments),this._children_controller_context=ts.ROP}static type(){return es.ROP}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}}class cq extends aa{static context(){return ts.ROP}cook(){this.cookController.endCook()}}class hq extends cq{}class uq extends hq{constructor(){super(...arguments),this._children_controller_context=ts.COP}static type(){return es.COP}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}}class dq extends Q.a{constructor(t){super(),this._element=t,this._element.style.position=\\\\\\\"absolute\\\\\\\",this.addEventListener(\\\\\\\"removed\\\\\\\",this._on_removed.bind(this))}_on_removed(){this.traverse((function(t){t instanceof dq&&t.element instanceof Element&&null!==t.element.parentNode&&t.element.parentNode.removeChild(t.element)}))}get element(){return this._element}clone(t){const e=this._element.cloneNode(!0);return new dq(e).copy(this,t)}copy(t,e){return Q.a.prototype.copy.call(this,t,e),this._element=t.element.cloneNode(!0),this.matrixAutoUpdate=t.matrixAutoUpdate,this}}class pq{constructor(){this._width=0,this._height=0,this._widthHalf=0,this._heightHalf=0,this.vector=new p.a,this.viewMatrix=new A.a,this.viewProjectionMatrix=new A.a,this.cache_distanceToCameraSquared=new WeakMap,this.domElement=document.createElement(\\\\\\\"div\\\\\\\"),this._sort_objects=!1,this._use_fog=!1,this._fog_near=1,this._fog_far=100,this.a=new p.a,this.b=new p.a,this.domElement.classList.add(\\\\\\\"polygonjs-CSS2DRenderer\\\\\\\")}getSize(){return{width:this._width,height:this._height}}setSize(t,e){this._width=t,this._height=e,this._widthHalf=this._width/2,this._heightHalf=this._height/2,this.domElement.style.width=t+\\\\\\\"px\\\\\\\",this.domElement.style.height=e+\\\\\\\"px\\\\\\\"}renderObject(t,e,n){if(t instanceof dq){this.vector.setFromMatrixPosition(t.matrixWorld),this.vector.applyMatrix4(this.viewProjectionMatrix);var i=t.element,s=\\\\\\\"translate(-50%,-50%) translate(\\\\\\\"+(this.vector.x*this._widthHalf+this._widthHalf)+\\\\\\\"px,\\\\\\\"+(-this.vector.y*this._heightHalf+this._heightHalf)+\\\\\\\"px)\\\\\\\";if(i.style.webkitTransform=s,i.style.transform=s,i.style.display=t.visible&&this.vector.z>=-1&&this.vector.z<=1?\\\\\\\"\\\\\\\":\\\\\\\"none\\\\\\\",this._sort_objects||this._use_fog){const e=this.getDistanceToSquared(n,t);if(this._use_fog){const t=Math.sqrt(e),n=or.fit(t,this._fog_near,this._fog_far,0,1),s=or.clamp(1-n,0,1);i.style.opacity=`${s}`,0==s&&(i.style.display=\\\\\\\"none\\\\\\\")}this.cache_distanceToCameraSquared.set(t,e)}i.parentNode!==this.domElement&&this.domElement.appendChild(i)}for(var r=0,o=t.children.length;r{const n=this.cache_distanceToCameraSquared.get(t),i=this.cache_distanceToCameraSquared.get(e);return null!=n&&null!=i?n-i:0})),n=e.length;for(let t=0,i=e.length;t{this._update_renderer(t)})),this.cookController.endCook()}_update_renderer(t){t.set_sorting(this.pv.sortObjects),t.set_use_fog(this.pv.useFog),t.set_fog_range(this.pv.fogNear,this.pv.fogFar)}_update_css(){this.css_element().innerHTML=this.pv.css}css_element(){return this._css_element=this._css_element||this._find_element()||this._create_element()}_find_element(){return document.getElementById(this._css_element_id())}_create_element(){const t=document.createElement(\\\\\\\"style\\\\\\\");return t.appendChild(document.createTextNode(\\\\\\\"\\\\\\\")),document.head.appendChild(t),t.id=this._css_element_id(),t}_css_element_id(){return`css_2d_renderer-${this.graphNodeId()}`}}class fq extends hq{constructor(){super(...arguments),this._children_controller_context=ts.ANIM}static type(){return es.ANIM}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}}class gq extends hq{constructor(){super(...arguments),this._children_controller_context=ts.EVENT}static type(){return es.EVENT}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}}class vq extends hq{constructor(){super(...arguments),this._children_controller_context=ts.MAT}static type(){return es.MAT}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}}class yq extends cq{constructor(){super(...arguments),this.paramsConfig=new ef,this.effectsComposerController=new nf(this),this.displayNodeController=new Fm(this,this.effectsComposerController.displayNodeControllerCallbacks()),this._children_controller_context=ts.POST}static type(){return es.POST}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}}class xq extends hq{constructor(){super(...arguments),this._children_controller_context=ts.ROP}static type(){return es.ROP}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}}class bq extends aV{static type(){return\\\\\\\"add\\\\\\\"}cook(t,e){const n=[];return this._create_point(n,e),this._create_polygon(t[0],n,e),this.createCoreGroupFromObjects(n)}_create_point(t,e){if(!e.createPoint)return;const n=new S.a,i=[];for(let t=0;t0&&this._create_polygon_open(t,e,n)}_create_polygon_open(t,e,n){const i=t.points();let s=[];const r=[];let o;for(let t=0;t0&&(r.push(t-1),r.push(t));if(i.length>2&&n.connectToLastPoint){i[0].position().toArray(s,s.length);const t=r[r.length-1];r.push(t),r.push(0)}const a=new S.a;a.setAttribute(\\\\\\\"position\\\\\\\",new C.c(s,3)),a.setIndex(r);const l=this.createObject(a,Ns.LINE_SEGMENTS);e.push(l)}}bq.DEFAULT_PARAMS={createPoint:!0,pointsCount:1,position:new p.a(0,0,0),connectInputPoints:!1,connectToLastPoint:!1};const wq=bq.DEFAULT_PARAMS;const Tq=new class extends ua{constructor(){super(...arguments),this.createPoint=ha.BOOLEAN(wq.createPoint),this.pointsCount=ha.INTEGER(wq.pointsCount,{range:[1,100],rangeLocked:[!0,!1],visibleIf:{createPoint:!0}}),this.position=ha.VECTOR3(wq.position,{visibleIf:{createPoint:!0}}),this.connectInputPoints=ha.BOOLEAN(wq.connectInputPoints),this.connectToLastPoint=ha.BOOLEAN(wq.connectToLastPoint)}};class Aq extends uV{constructor(){super(...arguments),this.paramsConfig=Tq}static type(){return\\\\\\\"add\\\\\\\"}static displayedInputNames(){return[\\\\\\\"geometry to create polygons from (optional)\\\\\\\"]}initializeNode(){this.io.inputs.setCount(0,1)}cook(t){this._operation=this._operation||new bq(this.scene(),this.states);const e=this._operation.cook(t,this.pv);this.setCoreGroup(e)}}const Mq=new class extends ua{};class Eq extends uV{constructor(){super(...arguments),this.paramsConfig=Mq}static type(){return\\\\\\\"animationCopy\\\\\\\"}static displayedInputNames(){return[\\\\\\\"geometry to copy animation to\\\\\\\",\\\\\\\"geometry to copy animation from\\\\\\\"]}initializeNode(){this.io.inputs.setCount(2),this.io.inputs.initInputsClonedState([Qi.FROM_NODE,Qi.NEVER])}cook(t){const e=t[0],n=t[1].objects()[0],i=e.objects()[0],s=n.animations;s?(i.animations=s.map((t=>t.clone())),this.setCoreGroup(e)):this.states.error.set(\\\\\\\"no animation found\\\\\\\")}}class Sq{constructor(t,e,n=null,i=e.blendMode){this._mixer=t,this._clip=e,this._localRoot=n,this.blendMode=i;const s=e.tracks,r=s.length,o=new Array(r),a={endingStart:w.id,endingEnd:w.id};for(let t=0;t!==r;++t){const e=s[t].createInterpolant(null);o[t]=e,e.settings=a}this._interpolantSettings=a,this._interpolants=o,this._propertyBindings=new Array(r),this._cacheIndex=null,this._byClipCacheIndex=null,this._timeScaleInterpolant=null,this._weightInterpolant=null,this.loop=w.eb,this._loopCount=-1,this._startTime=null,this.time=0,this.timeScale=1,this._effectiveTimeScale=1,this.weight=1,this._effectiveWeight=1,this.repetitions=1/0,this.paused=!1,this.enabled=!0,this.clampWhenFinished=!1,this.zeroSlopeAtStart=!0,this.zeroSlopeAtEnd=!0}play(){return this._mixer._activateAction(this),this}stop(){return this._mixer._deactivateAction(this),this.reset()}reset(){return this.paused=!1,this.enabled=!0,this.time=0,this._loopCount=-1,this._startTime=null,this.stopFading().stopWarping()}isRunning(){return this.enabled&&!this.paused&&0!==this.timeScale&&null===this._startTime&&this._mixer._isActiveAction(this)}isScheduled(){return this._mixer._isActiveAction(this)}startAt(t){return this._startTime=t,this}setLoop(t,e){return this.loop=t,this.repetitions=e,this}setEffectiveWeight(t){return this.weight=t,this._effectiveWeight=this.enabled?t:0,this.stopFading()}getEffectiveWeight(){return this._effectiveWeight}fadeIn(t){return this._scheduleFading(t,0,1)}fadeOut(t){return this._scheduleFading(t,1,0)}crossFadeFrom(t,e,n){if(t.fadeOut(e),this.fadeIn(e),n){const n=this._clip.duration,i=t._clip.duration,s=i/n,r=n/i;t.warp(1,s,e),this.warp(r,1,e)}return this}crossFadeTo(t,e,n){return t.crossFadeFrom(this,e,n)}stopFading(){const t=this._weightInterpolant;return null!==t&&(this._weightInterpolant=null,this._mixer._takeBackControlInterpolant(t)),this}setEffectiveTimeScale(t){return this.timeScale=t,this._effectiveTimeScale=this.paused?0:t,this.stopWarping()}getEffectiveTimeScale(){return this._effectiveTimeScale}setDuration(t){return this.timeScale=this._clip.duration/t,this.stopWarping()}syncWith(t){return this.time=t.time,this.timeScale=t.timeScale,this.stopWarping()}halt(t){return this.warp(this._effectiveTimeScale,0,t)}warp(t,e,n){const i=this._mixer,s=i.time,r=this.timeScale;let o=this._timeScaleInterpolant;null===o&&(o=i._lendControlInterpolant(),this._timeScaleInterpolant=o);const a=o.parameterPositions,l=o.sampleValues;return a[0]=s,a[1]=s+n,l[0]=t/r,l[1]=e/r,this}stopWarping(){const t=this._timeScaleInterpolant;return null!==t&&(this._timeScaleInterpolant=null,this._mixer._takeBackControlInterpolant(t)),this}getMixer(){return this._mixer}getClip(){return this._clip}getRoot(){return this._localRoot||this._mixer._root}_update(t,e,n,i){if(!this.enabled)return void this._updateWeight(t);const s=this._startTime;if(null!==s){const i=(t-s)*n;if(i<0||0===n)return;this._startTime=null,e=n*i}e*=this._updateTimeScale(t);const r=this._updateTime(e),o=this._updateWeight(t);if(o>0){const t=this._interpolants,e=this._propertyBindings;switch(this.blendMode){case w.d:for(let n=0,i=t.length;n!==i;++n)t[n].evaluate(r),e[n].accumulateAdditive(o);break;case w.wb:default:for(let n=0,s=t.length;n!==s;++n)t[n].evaluate(r),e[n].accumulate(i,o)}}}_updateWeight(t){let e=0;if(this.enabled){e=this.weight;const n=this._weightInterpolant;if(null!==n){const i=n.evaluate(t)[0];e*=i,t>n.parameterPositions[1]&&(this.stopFading(),0===i&&(this.enabled=!1))}}return this._effectiveWeight=e,e}_updateTimeScale(t){let e=0;if(!this.paused){e=this.timeScale;const n=this._timeScaleInterpolant;if(null!==n){e*=n.evaluate(t)[0],t>n.parameterPositions[1]&&(this.stopWarping(),0===e?this.paused=!0:this.timeScale=e)}}return this._effectiveTimeScale=e,e}_updateTime(t){const e=this._clip.duration,n=this.loop;let i=this.time+t,s=this._loopCount;const r=n===w.db;if(0===t)return-1===s?i:r&&1==(1&s)?e-i:i;if(n===w.cb){-1===s&&(this._loopCount=0,this._setEndings(!0,!0,!1));t:{if(i>=e)i=e;else{if(!(i<0)){this.time=i;break t}i=0}this.clampWhenFinished?this.paused=!0:this.enabled=!1,this.time=i,this._mixer.dispatchEvent({type:\\\\\\\"finished\\\\\\\",action:this,direction:t<0?-1:1})}}else{if(-1===s&&(t>=0?(s=0,this._setEndings(!0,0===this.repetitions,r)):this._setEndings(0===this.repetitions,!0,r)),i>=e||i<0){const n=Math.floor(i/e);i-=e*n,s+=Math.abs(n);const o=this.repetitions-s;if(o<=0)this.clampWhenFinished?this.paused=!0:this.enabled=!1,i=t>0?e:0,this.time=i,this._mixer.dispatchEvent({type:\\\\\\\"finished\\\\\\\",action:this,direction:t>0?1:-1});else{if(1===o){const e=t<0;this._setEndings(e,!e,r)}else this._setEndings(!1,!1,r);this._loopCount=s,this.time=i,this._mixer.dispatchEvent({type:\\\\\\\"loop\\\\\\\",action:this,loopDelta:n})}}else this.time=i;if(r&&1==(1&s))return e-i}return i}_setEndings(t,e,n){const i=this._interpolantSettings;n?(i.endingStart=w.kd,i.endingEnd=w.kd):(i.endingStart=t?this.zeroSlopeAtStart?w.kd:w.id:w.hd,i.endingEnd=e?this.zeroSlopeAtEnd?w.kd:w.id:w.hd)}_scheduleFading(t,e,n){const i=this._mixer,s=i.time;let r=this._weightInterpolant;null===r&&(r=i._lendControlInterpolant(),this._weightInterpolant=r);const o=r.parameterPositions,a=r.sampleValues;return o[0]=s,a[0]=e,o[1]=s+t,a[1]=n,this}}var Cq=n(71),Nq=n(66);class Lq{constructor(t,e,n){let i,s,r;switch(this.binding=t,this.valueSize=n,e){case\\\\\\\"quaternion\\\\\\\":i=this._slerp,s=this._slerpAdditive,r=this._setAdditiveIdentityQuaternion,this.buffer=new Float64Array(6*n),this._workIndex=5;break;case\\\\\\\"string\\\\\\\":case\\\\\\\"bool\\\\\\\":i=this._select,s=this._select,r=this._setAdditiveIdentityOther,this.buffer=new Array(5*n);break;default:i=this._lerp,s=this._lerpAdditive,r=this._setAdditiveIdentityNumeric,this.buffer=new Float64Array(5*n)}this._mixBufferRegion=i,this._mixBufferRegionAdditive=s,this._setIdentity=r,this._origIndex=3,this._addIndex=4,this.cumulativeWeight=0,this.cumulativeWeightAdditive=0,this.useCount=0,this.referenceCount=0}accumulate(t,e){const n=this.buffer,i=this.valueSize,s=t*i+i;let r=this.cumulativeWeight;if(0===r){for(let t=0;t!==i;++t)n[s+t]=n[t];r=e}else{r+=e;const t=e/r;this._mixBufferRegion(n,s,0,t,i)}this.cumulativeWeight=r}accumulateAdditive(t){const e=this.buffer,n=this.valueSize,i=n*this._addIndex;0===this.cumulativeWeightAdditive&&this._setIdentity(),this._mixBufferRegionAdditive(e,i,0,t,n),this.cumulativeWeightAdditive+=t}apply(t){const e=this.valueSize,n=this.buffer,i=t*e+e,s=this.cumulativeWeight,r=this.cumulativeWeightAdditive,o=this.binding;if(this.cumulativeWeight=0,this.cumulativeWeightAdditive=0,s<1){const t=e*this._origIndex;this._mixBufferRegion(n,i,t,1-s,e)}r>0&&this._mixBufferRegionAdditive(n,i,this._addIndex*e,1,e);for(let t=e,s=e+e;t!==s;++t)if(n[t]!==n[t+e]){o.setValue(n,i);break}}saveOriginalState(){const t=this.binding,e=this.buffer,n=this.valueSize,i=n*this._origIndex;t.getValue(e,i);for(let t=n,s=i;t!==s;++t)e[t]=e[i+t%n];this._setIdentity(),this.cumulativeWeight=0,this.cumulativeWeightAdditive=0}restoreOriginalState(){const t=3*this.valueSize;this.binding.setValue(this.buffer,t)}_setAdditiveIdentityNumeric(){const t=this._addIndex*this.valueSize,e=t+this.valueSize;for(let n=t;n=.5)for(let i=0;i!==s;++i)t[e+i]=t[n+i]}_slerp(t,e,n,i){hh.a.slerpFlat(t,e,t,e,t,n,i)}_slerpAdditive(t,e,n,i,s){const r=this._workIndex*s;hh.a.multiplyQuaternionsFlat(t,r,t,e,t,n),hh.a.slerpFlat(t,e,t,e,t,r,i)}_lerp(t,e,n,i,s){const r=1-i;for(let o=0;o!==s;++o){const s=e+o;t[s]=t[s]*r+t[n+o]*i}}_lerpAdditive(t,e,n,i,s){for(let r=0;r!==s;++r){const s=e+r;t[s]=t[s]+t[n+r]*i}}}var Oq=n(64);class Pq extends J.a{constructor(t){super(),this._root=t,this._initMemoryManager(),this._accuIndex=0,this.time=0,this.timeScale=1}_bindAction(t,e){const n=t._localRoot||this._root,i=t._clip.tracks,s=i.length,r=t._propertyBindings,o=t._interpolants,a=n.uuid,l=this._bindingsByRootAndName;let c=l[a];void 0===c&&(c={},l[a]=c);for(let t=0;t!==s;++t){const s=i[t],l=s.name;let h=c[l];if(void 0!==h)r[t]=h;else{if(h=r[t],void 0!==h){null===h._cacheIndex&&(++h.referenceCount,this._addInactiveBinding(h,a,l));continue}const i=e&&e._propertyBindings[t].binding.parsedPath;h=new Lq(Nq.a.create(n,l,i),s.ValueTypeName,s.getValueSize()),++h.referenceCount,this._addInactiveBinding(h,a,l),r[t]=h}o[t].resultBuffer=h.buffer}}_activateAction(t){if(!this._isActiveAction(t)){if(null===t._cacheIndex){const e=(t._localRoot||this._root).uuid,n=t._clip.uuid,i=this._actionsByClip[n];this._bindAction(t,i&&i.knownActions[0]),this._addInactiveAction(t,n,e)}const e=t._propertyBindings;for(let t=0,n=e.length;t!==n;++t){const n=e[t];0==n.useCount++&&(this._lendBinding(n),n.saveOriginalState())}this._lendAction(t)}}_deactivateAction(t){if(this._isActiveAction(t)){const e=t._propertyBindings;for(let t=0,n=e.length;t!==n;++t){const n=e[t];0==--n.useCount&&(n.restoreOriginalState(),this._takeBackBinding(n))}this._takeBackAction(t)}}_initMemoryManager(){this._actions=[],this._nActiveActions=0,this._actionsByClip={},this._bindings=[],this._nActiveBindings=0,this._bindingsByRootAndName={},this._controlInterpolants=[],this._nActiveControlInterpolants=0;const t=this;this.stats={actions:{get total(){return t._actions.length},get inUse(){return t._nActiveActions}},bindings:{get total(){return t._bindings.length},get inUse(){return t._nActiveBindings}},controlInterpolants:{get total(){return t._controlInterpolants.length},get inUse(){return t._nActiveControlInterpolants}}}}_isActiveAction(t){const e=t._cacheIndex;return null!==e&&e=0;--e)t[e].stop();return this}update(t){t*=this.timeScale;const e=this._actions,n=this._nActiveActions,i=this.time+=t,s=Math.sign(t),r=this._accuIndex^=1;for(let o=0;o!==n;++o){e[o]._update(i,t,s,r)}const o=this._bindings,a=this._nActiveBindings;for(let t=0;t!==a;++t)o[t].apply(r);return this}setTime(t){this.time=0;for(let t=0;t{Iq.PARAM_CALLBACK_reset(t,e)}})}};class Iq extends uV{constructor(){super(...arguments),this.paramsConfig=Rq}static type(){return\\\\\\\"animationMixer\\\\\\\"}static displayedInputNames(){return[\\\\\\\"geometry to be animated\\\\\\\"]}initializeNode(){this.io.inputs.setCount(1),this.io.inputs.initInputsClonedState(Qi.NEVER)}async cook(t){const e=t[0].objects()[0];e&&(await this.create_mixer_if_required(e),this._update_mixer()),this.setObjects([e])}async create_mixer_if_required(t){if(!this._mixer){const e=await this._create_mixer(t);e&&(this._mixer=e)}}async _create_mixer(t){this.p.clip.isDirty()&&await this.p.clip.compute();if(this.p.clip.found_node_with_context(ts.ANIM)){return new Pq(t)}}_update_mixer(){this._set_mixer_time()}_set_mixer_time(){this.pv.time!=this._previous_time&&(this._mixer&&this._mixer.setTime(this.pv.time),this._previous_time=this.pv.time)}static PARAM_CALLBACK_reset(t,e){e.setDirty(),t.reset_animation_mixer()}async reset_animation_mixer(){this._mixer=void 0,this._previous_time=void 0,this.setDirty()}}class Fq extends aV{static type(){return\\\\\\\"attribAddMult\\\\\\\"}cook(t,e){const n=t[0],i=n.attribNamesMatchingMask(e.name);for(let t of i){const i=n.geometries();for(let n of i)this._update_attrib(t,n,e)}return n}_update_attrib(t,e,n){const i=e.getAttribute(t);if(i){const t=i.array,e=n.preAdd,s=n.mult,r=n.postAdd;for(let n=0;n({name:t,value:e})))}})}};class qq extends uV{constructor(){super(...arguments),this.paramsConfig=Wq}static type(){return\\\\\\\"attribCast\\\\\\\"}initializeNode(){this.io.inputs.setCount(1),this.io.inputs.initInputsClonedState(Hq.INPUT_CLONED_STATE),this.scene().dispatchController.onAddListener((()=>{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{this.params.label.init([this.p.type],(()=>Uq[this.pv.type]))}))}))}cook(t){this._operation=this._operation||new Hq(this.scene(),this.states);const e=this._operation.cook(t,this.pv);this.setCoreGroup(e)}}class Xq extends aV{static type(){return\\\\\\\"attribCopy\\\\\\\"}cook(t,e){const n=t[0],i=t[1]||n,s=i.attribNamesMatchingMask(e.name);for(let t of s)this.copy_vertex_attribute_between_core_groups(n,i,t,e);return n}copy_vertex_attribute_between_core_groups(t,e,n,i){var s;const r=e.objectsWithGeo(),o=t.objectsWithGeo();if(o.length>r.length)null===(s=this.states)||void 0===s||s.error.set(\\\\\\\"second input does not have enough objects to copy attributes from\\\\\\\");else for(let t=0;ta&&(null===(s=this.states)||void 0===s||s.error.set(\\\\\\\"not enough points in second input\\\\\\\"));const c=i.tnewName?i.newName:n;let h=t.getAttribute(c);if(h)this._fill_dest_array(h,o,i),h.needsUpdate=!0;else{const e=o.array.slice(0,l*r);t.setAttribute(c,new C.c(e,r))}}else null===(r=this.states)||void 0===r||r.error.set(`attribute '${n}' does not exist on second input`)}_fill_dest_array(t,e,n){const i=t.array,s=e.array,r=i.length,o=t.itemSize,a=e.itemSize,l=n.srcOffset,c=n.destOffset;if(t.itemSize==e.itemSize){t.copyArray(e.array);for(let t=0;t{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{this.params.label.init([this.p.name,this.p.tnewName,this.p.newName],(()=>this.pv.tnewName?`${this.pv.name} -> ${this.pv.newName}`:this.pv.name))}))}))}cook(t){this._operation=this._operation||new Xq(this.scene(),this.states);const e=this._operation.cook(t,this.pv);this.setCoreGroup(e)}}class Zq extends aV{static type(){return\\\\\\\"attribCreate\\\\\\\"}cook(t,e){var n;const i=t[0];return e.name&&\\\\\\\"\\\\\\\"!=e.name.trim()?this._add_attribute(Ds[e.class],i,e):null===(n=this.states)||void 0===n||n.error.set(\\\\\\\"attribute name is not valid\\\\\\\"),i}async _add_attribute(t,e,n){const i=ks[n.type];switch(t){case Fs.VERTEX:return void await this.add_point_attribute(i,e,n);case Fs.OBJECT:return void await this.add_object_attribute(i,e,n)}os.unreachable(t)}async add_point_attribute(t,e,n){const i=e.coreObjects();switch(t){case zs.NUMERIC:for(let t=0;t{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{this.params.label.init([this.p.name])}))}))}cook(t){if(this._is_using_expression())this.pv.name&&\\\\\\\"\\\\\\\"!=this.pv.name.trim()?this._addAttribute(Ds[this.pv.class],t[0]):this.states.error.set(\\\\\\\"attribute name is not valid\\\\\\\");else{this._operation=this._operation||new Zq(this.scene(),this.states);const e=this._operation.cook(t,this.pv);this.setCoreGroup(e)}}async _addAttribute(t,e){const n=ks[this.pv.type];switch(t){case Fs.VERTEX:return await this._addPointAttribute(n,e),this.setCoreGroup(e);case Fs.OBJECT:return await this._addObjectAttribute(n,e),this.setCoreGroup(e)}os.unreachable(t)}async _addPointAttribute(t,e){const n=e.coreObjects();switch(t){case zs.NUMERIC:for(let t=0;t{s[t.index()*this.pv.size+0]=e}));else{let e=[this.p.value2,this.p.value3,this.p.value4][this.pv.size-2].components;const i=new Array(e.length);let r;const o=[this._x_arrays_by_geometry_uuid,this._y_arrays_by_geometry_uuid,this._z_arrays_by_geometry_uuid,this._w_arrays_by_geometry_uuid];for(let a=0;a{i[a][t.index()]=e}));else{const t=r.value;for(let e of n)s[e.index()*this.pv.size+a]=t}for(let t=0;t{t.setAttribValue(this.pv.name,e)}));else{let e=[this.p.value2,this.p.value3,this.p.value4][this.pv.size-2].components,n={};const i=this._vector_by_attrib_size(this.pv.size);if(i){for(let e of t)n[e.index()]=i;for(let i=0;i{n[t.index()][r]=e}));else for(let e of t){n[e.index()][r]=s.value}}for(let e=0;e{i[t.index()]=e}));const s=Xs.arrayToIndexedArrays(i),r=t.coreGeometry();r&&r.setIndexedAttribute(this.pv.name,s.values,s.indices)}async add_string_attribute_to_object(t){const e=this.p.string;e.hasExpression()&&e.expressionController&&await e.expressionController.computeExpressionForObjects(t,((t,e)=>{t.setAttribValue(this.pv.name,e)}))}_init_array_if_required(t,e,n){const i=t.uuid,s=e[i];return s?s.length{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{this.params.label.init([this.p.name])}))}))}cook(t){const e=t[0],n=e.attribNamesMatchingMask(this.pv.name);for(let t of n)switch(this.pv.class){case Fs.VERTEX:this.delete_vertex_attribute(e,t);case Fs.OBJECT:this.delete_object_attribute(e,t)}this.setCoreGroup(e)}delete_vertex_attribute(t,e){for(let n of t.objects())n.traverse((t=>{const n=t;if(n.geometry){new fr(n.geometry).deleteAttribute(e)}}))}delete_object_attribute(t,e){for(let n of t.objects()){let t=0;n.traverse((n=>{new br(n,t).deleteAttribute(e),t++}))}}}class sX{set_attrib(t){const e=t.geometry,n=t.targetAttribSize;if(n<1||n>4)return;const i=t.add,s=t.mult,r=this._data_from_texture(t.texture);if(!r)return;const{data:o,resx:a,resy:l}=r,c=o.length/(a*l),h=e.getAttribute(t.uvAttribName).array,u=h.length/2,d=new Array(u*n);let p,_,m,f,g,v,y,x,b;const w=or.clamp;for(v=0;v{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{this.params.label.init([this.p.attrib])}))}))}async cook(t){this._operation=this._operation||new rX(this.scene(),this.states);const e=await this._operation.cook(t,this.pv);this.setCoreGroup(e)}}var cX;!function(t){t.MIN_MAX_TO_01=\\\\\\\"min/max to 0/1\\\\\\\",t.VECTOR_TO_LENGTH_1=\\\\\\\"vectors to length 1\\\\\\\"}(cX||(cX={}));const hX=[cX.MIN_MAX_TO_01,cX.VECTOR_TO_LENGTH_1];class uX extends aV{constructor(){super(...arguments),this.min3=new p.a,this.max3=new p.a,this._vec=new p.a}static type(){return\\\\\\\"attribNormalize\\\\\\\"}cook(t,e){const n=t[0],i=t[0].objectsWithGeo(),s=ss.attribNames(e.name);for(let t of i){const n=t.geometry;for(let t of s){const i=n.getAttribute(t);if(i){let t=i;e.changeName&&\\\\\\\"\\\\\\\"!=e.newName&&(t=n.getAttribute(e.newName),t&&(t.needsUpdate=!0),t=t||i.clone()),this._normalize_attribute(i,t,e)}}}return n}_normalize_attribute(t,e,n){switch(hX[n.mode]){case cX.MIN_MAX_TO_01:return this._normalize_from_min_max_to_01(t,e);case cX.VECTOR_TO_LENGTH_1:return this._normalize_vectors(t,e)}}_normalize_from_min_max_to_01(t,e){const n=t.itemSize,i=t.array,s=e.array;switch(n){case 1:{const t=Math.min(...i),e=Math.max(...i);for(let n=0;n({name:t,value:e})))}}),this.name=ha.STRING(dX.name),this.changeName=ha.BOOLEAN(dX.changeName),this.newName=ha.STRING(dX.newName,{visibleIf:{changeName:1}})}};class _X extends uV{constructor(){super(...arguments),this.paramsConfig=pX}static type(){return\\\\\\\"attribNormalize\\\\\\\"}initializeNode(){this.io.inputs.setCount(1),this.io.inputs.initInputsClonedState(uX.INPUT_CLONED_STATE),this.scene().dispatchController.onAddListener((()=>{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{this.params.label.init([this.p.name])}))}))}set_mode(t){this.p.mode.set(hX.indexOf(t))}cook(t){this._operation=this._operation||new uX(this.scene(),this.states);const e=this._operation.cook(t,this.pv);this.setCoreGroup(e)}}var mX;!function(t){t[t.MIN=0]=\\\\\\\"MIN\\\\\\\",t[t.MAX=1]=\\\\\\\"MAX\\\\\\\",t[t.FIRST_FOUND=2]=\\\\\\\"FIRST_FOUND\\\\\\\"}(mX||(mX={}));class fX extends aV{constructor(){super(...arguments),this._values_per_attrib_name={},this._filtered_values_per_attrib_name={}}static type(){return\\\\\\\"attribPromote\\\\\\\"}cook(t,e){this._core_group=t[0],this._values_per_attrib_name={},this._filtered_values_per_attrib_name={};for(let t of this._core_group.coreObjects())this._core_object=t,this.find_values(e),this.filter_values(e),this.set_values(e);return this._core_group}find_values(t){const e=ss.attribNames(t.name);for(let n of e)this._find_values_for_attrib_name(n,t)}_find_values_for_attrib_name(t,e){switch(e.classFrom){case Fs.VERTEX:return this.find_values_from_points(t,e);case Fs.OBJECT:return this.find_values_from_object(t,e)}}find_values_from_points(t,e){if(this._core_object){const e=this._core_object.points(),n=e[0];if(n&&!n.isAttribIndexed(t)){const n=new Array(e.length);let i;for(let s=0;s{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{this.params.label.init([this.p.name,this.p.classFrom,this.p.classTo],(()=>{if(\\\\\\\"\\\\\\\"!=this.pv.name){const t=Bs.filter((t=>t.value==this.pv.classFrom))[0].name,e=Bs.filter((t=>t.value==this.pv.classTo))[0].name;return`${this.pv.name} (${t} -> ${e})`}return\\\\\\\"\\\\\\\"}))}))}))}cook(t){this._operation=this._operation||new fX(this.scene(),this.states);const e=this._operation.cook(t,this.pv);this.setCoreGroup(e)}}const bX=new class extends ua{constructor(){super(...arguments),this.name=ha.STRING(),this.ramp=ha.RAMP(),this.changeName=ha.BOOLEAN(0),this.newName=ha.STRING(\\\\\\\"\\\\\\\",{visibleIf:{changeName:1}})}};class wX extends uV{constructor(){super(...arguments),this.paramsConfig=bX}static type(){return\\\\\\\"attribRemap\\\\\\\"}initializeNode(){this.io.inputs.setCount(1)}cook(t){const e=t[0];this._remap_attribute(e),this.setCoreGroup(e)}_remap_attribute(t){const e=t.points();if(0===e.length)return;if(\\\\\\\"\\\\\\\"===this.pv.name)return;const n=e[0].attribSize(this.pv.name),i=e.map((t=>t.attribValue(this.pv.name)));let s=new Array(e.length);this._get_remaped_values(n,i,s);let r=this.pv.name;this.pv.changeName&&(r=this.pv.newName,t.hasAttrib(r)||t.addNumericVertexAttrib(r,n,0));let o=0;for(let t of s){e[o].setAttribValue(r,t),o++}}_get_remaped_values(t,e,n){switch(t){case Gs.FLOAT:return this._get_normalized_float(e,n);case Gs.VECTOR2:return this._get_normalized_vector2(e,n);case Gs.VECTOR3:return this._get_normalized_vector3(e,n);case Gs.VECTOR4:return this._get_normalized_vector4(e,n)}os.unreachable(t)}_get_normalized_float(t,e){const n=t,i=this.p.ramp;for(let t=0;t{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{this.params.label.init([this.p.oldName,this.p.newName],(()=>\\\\\\\"\\\\\\\"!=this.pv.oldName&&\\\\\\\"\\\\\\\"!=this.pv.newName?`${this.pv.oldName} -> ${this.pv.newName}`:\\\\\\\"\\\\\\\"))}))}))}cook(t){const e=t[0];e.renameAttrib(this.pv.oldName,this.pv.newName,this.pv.class),this.setCoreGroup(e)}}var MX=n(18);class EX{constructor(t,e=0){this._bbox=t,this._level=e,this._leaves_by_octant={},this._points_by_octant_id={},this._leaves=[],this._bounding_boxes_by_octant={},this._bounding_boxes_by_octant_prepared=!1,this._center=this._bbox.max.clone().add(this._bbox.min).multiplyScalar(.5)}level(){return this._level}traverse(t){t(this);Object.values(this._leaves_by_octant).forEach((e=>{e.traverse(t)}))}intersects_sphere(t){return!!this._bbox&&this._bbox.intersectsSphere(t)}points_in_sphere(t,e){if(0==this._leaves.length){Object.values(this._points_by_octant_id).flat().filter((e=>t.containsPoint(e.position()))).forEach((t=>{e.push(t)}))}else{this._leaves.filter((e=>e.intersects_sphere(t))).forEach((n=>n.points_in_sphere(t,e)))}}bounding_box(){return this._bbox}set_points(t){this._points_by_octant_id={};for(let e of t)this.add_point(e);const e=Object.keys(this._points_by_octant_id);e.length>1&&e.forEach((t=>{this.create_leaf(t)}))}create_leaf(t){const e=this._leaf_bbox(t),n=new EX(e,this._level+1);this._leaves_by_octant[t]=n,this._leaves.push(n),n.set_points(this._points_by_octant_id[t])}add_point(t){const e=this._octant_id(t.position());null==this._points_by_octant_id[e]&&(this._points_by_octant_id[e]=[]),this._points_by_octant_id[e].push(t)}_octant_id(t){return`${t.x>this._center.x?1:0}${t.y>this._center.y?1:0}${t.z>this._center.z?1:0}`}_leaf_bbox(t){return this._bounding_boxes_by_octant_prepared||(this._prepare_leaves_bboxes(),this._bounding_boxes_by_octant_prepared=!0),this._bounding_boxes_by_octant[t]}_bbox_center(t,e,n){const i=this._bbox.min.clone();return t&&(i.x=this._bbox.max.x),e&&(i.y=this._bbox.max.y),n&&(i.z=this._bbox.max.z),i.clone().add(this._center).multiplyScalar(.5)}_prepare_leaves_bboxes(){const t=[];t.push(this._bbox_center(0,0,0)),t.push(this._bbox_center(0,0,1)),t.push(this._bbox_center(0,1,0)),t.push(this._bbox_center(0,1,1)),t.push(this._bbox_center(1,0,0)),t.push(this._bbox_center(1,0,1)),t.push(this._bbox_center(1,1,0)),t.push(this._bbox_center(1,1,1));const e=this._bbox.max.clone().sub(this._bbox.min).multiplyScalar(.25);for(let n of t){const t=this._octant_id(n),i=new Ry.a(n.clone().sub(e),n.clone().add(e));this._bounding_boxes_by_octant[t]=i}}}class SX{constructor(t){this._root=new EX(t)}set_points(t){this._root.set_points(t)}traverse(t){this._root.traverse(t)}find_points(t,e,n){const i=new MX.a(t,e);let s=[];return this._root.intersects_sphere(i)&&this._root.points_in_sphere(i,s),null==n||s.length>n&&(s=f.sortBy(s,(e=>e.position().distanceTo(t))),s=s.slice(0,n)),s}}class CX{constructor(t={}){this._array_index=0,this._count=0,this._current_count_index=0,this._resolve=null,this._max_time_per_chunk=t.max_time_per_chunk||10,this._check_every_interations=t.check_every_interations||100}async startWithCount(t,e){if(this._count=t,this._current_count_index=0,this._iteratee_method_count=e,this._bound_next_with_count=this.nextWithCount.bind(this),this._resolve)throw\\\\\\\"an iterator cannot be started twice\\\\\\\";return new Promise(((t,e)=>{this._resolve=t,this.nextWithCount()}))}nextWithCount(){const t=li.performance.performanceManager(),e=t.now();if(this._iteratee_method_count&&this._bound_next_with_count)for(;this._current_count_indexthis._max_time_per_chunk){setTimeout(this._bound_next_with_count,1);break}this._current_count_index>=this._count&&this._resolve&&this._resolve()}async startWithArray(t,e){if(this._array=t,this._array_index=0,this._iteratee_method_array=e,this._bound_next_with_array=this.nextWithArray.bind(this),this._resolve)throw\\\\\\\"an iterator cannot be started twice\\\\\\\";return new Promise(((t,e)=>{this._resolve=t,this.nextWithArray()}))}nextWithArray(){const t=li.performance.performanceManager(),e=t.now();if(this._iteratee_method_array&&this._bound_next_with_array&&this._array)for(;this._current_array_element=this._array[this._array_index];)if(this._iteratee_method_array(this._current_array_element,this._array_index),this._array_index++,this._array_index%this._check_every_interations==0&&t.now()-e>this._max_time_per_chunk){setTimeout(this._bound_next_with_array,1);break}void 0===this._current_array_element&&this._resolve&&this._resolve()}}const NX=new class extends ua{constructor(){super(...arguments),this.srcGroup=ha.STRING(),this.destGroup=ha.STRING(),this.name=ha.STRING(),this.maxSamplesCount=ha.INTEGER(1,{range:[1,10],rangeLocked:[!0,!1]}),this.distanceThreshold=ha.FLOAT(1),this.blendWidth=ha.FLOAT(0)}};class LX extends uV{constructor(){super(...arguments),this.paramsConfig=NX}static type(){return\\\\\\\"attribTransfer\\\\\\\"}static displayedInputNames(){return[\\\\\\\"geometry to transfer attributes to\\\\\\\",\\\\\\\"geometry to transfer attributes from\\\\\\\"]}initializeNode(){this.io.inputs.setCount(2),this.io.inputs.initInputsClonedState([Qi.FROM_NODE,Qi.NEVER])}async cook(t){this._core_group_dest=t[0];const e=this._core_group_dest.pointsFromGroup(this.pv.destGroup);this._core_group_src=t[1],this._attrib_names=this._core_group_src.attribNamesMatchingMask(this.pv.name),this._error_if_attribute_not_found_on_second_input(),this._build_octree_if_required(this._core_group_src),this._add_attribute_if_required(),await this._transfer_attributes(e),this.setCoreGroup(this._core_group_dest)}_error_if_attribute_not_found_on_second_input(){for(let t of this._attrib_names)this._core_group_src.hasAttrib(t)||this.states.error.set(`attribute '${t}' not found on second input`)}_build_octree_if_required(t){const e=null==this._octree_timestamp||this._octree_timestamp!==t.timestamp();if(this._prev_param_srcGroup!==this.pv.srcGroup||e){this._octree_timestamp=t.timestamp(),this._prev_param_srcGroup=this.pv.srcGroup;const e=this._core_group_src.pointsFromGroup(this.pv.srcGroup);this._octree=new SX(this._core_group_src.boundingBox()),this._octree.set_points(e)}}_add_attribute_if_required(){for(let t of this._attrib_names)if(!this._core_group_dest.hasAttrib(t)){const e=this._core_group_src.attribSize(t);this._core_group_dest.addNumericVertexAttrib(t,e,0)}}async _transfer_attributes(t){const e=new CX;await e.startWithArray(t,this._transfer_attributes_for_point.bind(this))}_transfer_attributes_for_point(t){var e;const n=this.pv.distanceThreshold+this.pv.blendWidth,i=(null===(e=this._octree)||void 0===e?void 0:e.find_points(t.position(),n,this.pv.maxSamplesCount))||[];for(let e of this._attrib_names)this._interpolate_points(t,i,e)}_interpolate_points(t,e,n){let i;i=class{static perform(t,e,n,i,s){switch(e.length){case 0:return t.attribValue(n);case 1:return this._interpolate_with_1_point(t,e[0],n,i,s);default:return this._interpolate_with_multiple_points(t,e,n,i,s)}}static _interpolate_with_1_point(t,e,n,i,s){const r=t.position(),o=e.position(),a=r.distanceTo(o),l=e.attribValue(n);return m.isNumber(l)?this._weighted_value_from_distance(t,l,n,a,i,s):(console.warn(\\\\\\\"value is not a number\\\\\\\",l),0)}static _weight_from_distance(t,e,n){return(t-e)/n}static _weighted_value_from_distance(t,e,n,i,s,r){if(i<=s)return e;{const o=t.attribValue(n);if(m.isNumber(o)){const t=this._weight_from_distance(i,s,r);return t*o+(1-t)*e}return console.warn(\\\\\\\"value is not a number\\\\\\\",o),0}}static _interpolate_with_multiple_points(t,e,n,i,s){const r=e.map((e=>this._interpolate_with_1_point(t,e,n,i,s)));return f.max(r)||0}static weights(t,e){switch(e.length){case 1:return 1;case 2:return this._weights_from_2(t,e);default:return e=e.slice(0,3),this._weights_from_3(t,e)}}static _weights_from_2(t,e){const n=e.map((e=>t.distanceTo(e))),i=f.sum(n);return[n[1]/i,n[0]/i]}static _weights_from_3(t,e){const n=e.map((e=>t.distanceTo(e))),i=f.sum([n[0]*n[1],n[0]*n[2],n[1]*n[2]]);return[n[1]*n[2]/i,n[0]*n[2]/i,n[0]*n[1]/i]}}.perform(t,e,n,this.pv.distanceThreshold,this.pv.blendWidth),null!=i&&t.setAttribValue(n,i)}}const OX=new class extends ua{constructor(){super(...arguments),this.stepSize=ha.FLOAT(.1)}};class PX extends uV{constructor(){super(...arguments),this.paramsConfig=OX}static type(){return\\\\\\\"bboxScatter\\\\\\\"}static displayedInputNames(){return[\\\\\\\"geometry to create points from\\\\\\\"]}initializeNode(){this.io.inputs.setCount(1)}cook(t){const e=t[0],n=this.pv.stepSize,i=e.boundingBox(),s=i.min,r=i.max,o=[];for(let t=s.x;t<=r.x;t+=n)for(let e=s.y;e<=r.y;e+=n)for(let i=s.z;i<=r.z;i+=n)o.push(t),o.push(e),o.push(i);const a=new S.a;a.setAttribute(\\\\\\\"position\\\\\\\",new C.a(new Float32Array(o),3)),this.setGeometry(a,Ns.POINTS)}}const RX=new class extends ua{constructor(){super(...arguments),this.attribName=ha.STRING(\\\\\\\"position\\\\\\\"),this.blend=ha.FLOAT(.5,{range:[0,1],rangeLocked:[!0,!0]})}};class IX extends uV{constructor(){super(...arguments),this.paramsConfig=RX}static type(){return\\\\\\\"blend\\\\\\\"}static displayedInputNames(){return[\\\\\\\"geometry to blend from\\\\\\\",\\\\\\\"geometry to blend to\\\\\\\"]}initializeNode(){this.io.inputs.setCount(2),this.io.inputs.initInputsClonedState([Qi.FROM_NODE,Qi.NEVER])}cook(t){const e=t[0],n=t[1],i=e.objects(),s=n.objects();let r,o;for(let t=0;tt.flip())),t}}FX.fromPolygons=function(t){let e=new FX;return e.polygons=t,e};class DX{constructor(t=0,e=0,n=0){this.x=t,this.y=e,this.z=n}copy(t){return this.x=t.x,this.y=t.y,this.z=t.z,this}clone(){return new DX(this.x,this.y,this.z)}negate(){return this.x*=-1,this.y*=-1,this.z*=-1,this}add(t){return this.x+=t.x,this.y+=t.y,this.z+=t.z,this}sub(t){return this.x-=t.x,this.y-=t.y,this.z-=t.z,this}times(t){return this.x*=t,this.y*=t,this.z*=t,this}dividedBy(t){return this.x/=t,this.y/=t,this.z/=t,this}lerp(t,e){return this.add(BX.copy(t).sub(this).times(e))}unit(){return this.dividedBy(this.length())}length(){return Math.sqrt(this.x**2+this.y**2+this.z**2)}normalize(){return this.unit()}cross(t){let e=this;const n=e.x,i=e.y,s=e.z,r=t.x,o=t.y,a=t.z;return this.x=i*a-s*o,this.y=s*r-n*a,this.z=n*o-i*r,this}dot(t){return this.x*t.x+this.y*t.y+this.z*t.z}}let BX=new DX,zX=new DX;class kX{constructor(t,e,n,i){this.pos=(new DX).copy(t),this.normal=(new DX).copy(e),this.uv=(new DX).copy(n),this.uv.z=0,i&&(this.color=(new DX).copy(i))}clone(){return new kX(this.pos,this.normal,this.uv,this.color)}flip(){this.normal.negate()}interpolate(t,e){return new kX(this.pos.clone().lerp(t.pos,e),this.normal.clone().lerp(t.normal,e),this.uv.clone().lerp(t.uv,e),this.color&&t.color&&this.color.clone().lerp(t.color,e))}}class UX{constructor(t,e){this.normal=t,this.w=e}clone(){return new UX(this.normal.clone(),this.w)}flip(){this.normal.negate(),this.w=-this.w}splitPolygon(t,e,n,i,s){let r=0,o=[];for(let e=0;eUX.EPSILON?1:0;r|=i,o.push(i)}switch(r){case 0:(this.normal.dot(t.plane.normal)>0?e:n).push(t);break;case 1:i.push(t);break;case 2:s.push(t);break;case 3:let r=[],a=[];for(let e=0;e=3&&i.push(new GX(r,t.shared)),a.length>=3&&s.push(new GX(a,t.shared))}}}UX.EPSILON=1e-5,UX.fromPoints=function(t,e,n){let i=BX.copy(e).sub(t).cross(zX.copy(n).sub(t)).normalize();return new UX(i.clone(),i.dot(t))};class GX{constructor(t,e){this.vertices=t,this.shared=e,this.plane=UX.fromPoints(t[0].pos,t[1].pos,t[2].pos)}clone(){return new GX(this.vertices.map((t=>t.clone())),this.shared)}flip(){this.vertices.reverse().map((t=>t.flip())),this.plane.flip()}}class VX{constructor(t){this.plane=null,this.front=null,this.back=null,this.polygons=[],t&&this.build(t)}clone(){let t=new VX;return t.plane=this.plane&&this.plane.clone(),t.front=this.front&&this.front.clone(),t.back=this.back&&this.back.clone(),t.polygons=this.polygons.map((t=>t.clone())),t}invert(){for(let t=0;tnew GX(t.vertices.map((t=>new kX(t.pos,t.normal,t.uv))),t.shared))))},FX.fromGeometry=function(t,e){let n=[];if(t.isGeometry){let i=t.faces,s=t.vertices,r=[\\\\\\\"a\\\\\\\",\\\\\\\"b\\\\\\\",\\\\\\\"c\\\\\\\"];for(let o=0;o({top:0,array:new Float32Array(t),write:function(t){this.array[this.top++]=t.x,this.array[this.top++]=t.y,this.array[this.top++]=t.z}}),qX=t=>({top:0,array:new Float32Array(t),write:function(t){this.array[this.top++]=t.x,this.array[this.top++]=t.y}});var XX;FX.toMesh=function(t,e,n){let i,s,r=t.polygons;{let t=0;r.forEach((e=>t+=e.vertices.length-2)),i=new S.a;let e,n=WX(3*t*3),o=WX(3*t*3),a=qX(2*t*3),l=[];if(r.forEach((i=>{let s=i.vertices,r=s.length;void 0!==i.shared&&(l[i.shared]||(l[i.shared]=[])),r&&void 0!==s[0].color&&(e||(e=WX(3*t*3)));for(let t=3;t<=r;t++)void 0!==i.shared&&l[i.shared].push(n.top/3,n.top/3+1,n.top/3+2),n.write(s[0].pos),n.write(s[t-2].pos),n.write(s[t-1].pos),o.write(s[0].normal),o.write(s[t-2].normal),o.write(s[t-1].normal),a.write(s[0].uv),a.write(s[t-2].uv),a.write(s[t-1].uv),e&&(e.write(s[0].color)||e.write(s[t-2].color)||e.write(s[t-1].color))})),i.setAttribute(\\\\\\\"position\\\\\\\",new C.a(n.array,3)),i.setAttribute(\\\\\\\"normal\\\\\\\",new C.a(o.array,3)),i.setAttribute(\\\\\\\"uv\\\\\\\",new C.a(a.array,2)),e&&i.setAttribute(\\\\\\\"color\\\\\\\",new C.a(e.array,3)),l.length){let t=[],e=0;for(let n=0;n({name:t,value:e})))}}),this.useBothMaterials=ha.BOOLEAN(JX.useBothMaterials)}};class KX extends uV{constructor(){super(...arguments),this.paramsConfig=ZX}static type(){return\\\\\\\"boolean\\\\\\\"}initializeNode(){super.initializeNode(),this.io.inputs.setCount(2),this.io.inputs.initInputsClonedState($X.INPUT_CLONED_STATE),this.scene().dispatchController.onAddListener((()=>{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{this.params.label.init([this.p.operation],(()=>YX[this.pv.operation]))}))}))}setOperation(t){this.p.operation.set(YX.indexOf(t))}async cook(t){this._operation=this._operation||new $X(this.scene(),this.states,this);const e=await this._operation.cook(t,this.pv);this.setCoreGroup(e)}}class QX extends aV{constructor(){super(...arguments),this._core_transform=new bU}static type(){return\\\\\\\"box\\\\\\\"}cook(t,e){const n=t[0],i=n?this._cookWithInput(n,e):this._cookWithoutInput(e);return this.createCoreGroupFromGeometry(i)}_cookWithoutInput(t){const e=t.divisions,n=t.size,i=new N(n,n,n,e,e,e);return i.translate(t.center.x,t.center.y,t.center.z),i.computeVertexNormals(),i}_cookWithInput(t,e){const n=e.divisions,i=t.boundingBox(),s=i.max.clone().sub(i.min),r=i.max.clone().add(i.min).multiplyScalar(.5),o=new N(s.x,s.y,s.z,n,n,n),a=this._core_transform.translationMatrix(r);return o.applyMatrix4(a),o}}QX.DEFAULT_PARAMS={size:1,divisions:1,center:new p.a(0,0,0)},QX.INPUT_CLONED_STATE=Qi.NEVER;const tY=QX.DEFAULT_PARAMS;const eY=new class extends ua{constructor(){super(...arguments),this.size=ha.FLOAT(tY.size),this.divisions=ha.INTEGER(tY.divisions,{range:[1,10],rangeLocked:[!0,!1]}),this.center=ha.VECTOR3(tY.center)}};class nY extends uV{constructor(){super(...arguments),this.paramsConfig=eY}static type(){return\\\\\\\"box\\\\\\\"}static displayedInputNames(){return[\\\\\\\"geometry to create bounding box from (optional)\\\\\\\"]}initializeNode(){this.io.inputs.setCount(0,1),this.io.inputs.initInputsClonedState(QX.INPUT_CLONED_STATE)}cook(t){this._operation=this._operation||new QX(this._scene,this.states);const e=this._operation.cook(t,this.pv);this.setCoreGroup(e)}}class iY{constructor(){}}function sY(t,e,n){return n.min.x=e[t],n.min.y=e[t+1],n.min.z=e[t+2],n.max.x=e[t+3],n.max.y=e[t+4],n.max.z=e[t+5],n}function rY(t){let e=-1,n=-1/0;for(let i=0;i<3;i++){const s=t[i+3]-t[i];s>n&&(n=s,e=i)}return e}function oY(t,e){e.set(t)}function aY(t,e,n){let i,s;for(let r=0;r<3;r++){const o=r+3;i=t[r],s=e[r],n[r]=is?i:s}}function lY(t){const e=t[3]-t[0],n=t[4]-t[1],i=t[5]-t[2];return 2*(e*n+n*i+i*e)}const cY=Math.pow(2,-24);function hY(t,e,n,i,s=null){let r=1/0,o=1/0,a=1/0,l=-1/0,c=-1/0,h=-1/0,u=1/0,d=1/0,p=1/0,_=-1/0,m=-1/0,f=-1/0;const g=null!==s;for(let i=6*e,s=6*(e+n);il&&(l=v),g&&e_&&(_=e);const y=t[i+2],x=t[i+3],b=y-x,w=y+x;bc&&(c=w),g&&ym&&(m=y);const T=t[i+4],A=t[i+5],M=T-A,E=T+A;Mh&&(h=E),g&&Tf&&(f=T)}i[0]=r,i[1]=o,i[2]=a,i[3]=l,i[4]=c,i[5]=h,g&&(s[0]=u,s[1]=d,s[2]=p,s[3]=_,s[4]=m,s[5]=f)}const uY=32,dY=new Array(uY).fill().map((()=>({count:0,bounds:new Float32Array(6),rightCacheBounds:new Float32Array(6),candidate:0}))),pY=new Float32Array(6);function _Y(t,e){function n(e,i,d,p=null,_=0){if(!u&&_>=a&&(u=!0,l&&(console.warn(`MeshBVH: Max depth of ${a} reached when generating BVH. Consider increasing maxDepth.`),console.warn(t))),d<=c||_>=a)return e.offset=i,e.count=d,e;const m=function(t,e,n,i,s,r){let o=-1,a=0;if(0===r)o=rY(e),-1!==o&&(a=(e[o]+e[o+3])/2);else if(1===r)o=rY(t),-1!==o&&(a=function(t,e,n,i){let s=0;for(let r=e,o=e+n;r=uY&&(s=31);const r=dY[s];r.count++;const o=r.bounds;for(let t=0;t<3;t++){const i=n[e+2*t],s=n[e+2*t+1],r=i-s,a=i+s;ro[t+3]&&(o[t+3]=a)}}const d=dY[31];oY(d.bounds,d.rightCacheBounds);for(let t=30;t>=0;t--){const e=dY[t],n=dY[t+1];aY(e.bounds,n.rightCacheBounds,e.rightCacheBounds)}let p=0;for(let e=0;e<31;e++){const n=dY[e],i=n.count,c=n.bounds,h=dY[e+1].rightCacheBounds;0!==i&&(0===p?oY(c,pY):aY(c,pY,pY)),p+=i;let u=0,d=0;0!==p&&(u=lY(pY)/r);const _=s-p;0!==_&&(d=lY(h)/r);const m=1+1.25*(u*p+d*_);m=a;)o--;if(!(r65535?new Uint32Array(new i(4*n)):new Uint16Array(new i(2*n)),t.setIndex(new Qw(s,1));for(let t=0;td&&(d=s),a>d&&(d=a);const p=(d-l)/2,_=2*t;o[r+_+0]=l+p,o[r+_+1]=p+(Math.abs(l)+p)*cY,le[t+3]&&(e[t+3]=d)}}return o}(t,i),o=t.index.array,a=e.maxDepth,l=e.verbose,c=e.maxLeafTris,h=e.strategy;let u=!1;const d=[],p=function(t){if(!t.groups||!t.groups.length)return[{offset:0,count:t.index.count/3}];const e=[],n=new Set;for(const e of t.groups)n.add(e.start),n.add(e.start+e.count);const i=Array.from(n.values()).sort(((t,e)=>t-e));for(let t=0;ta&&(a=e);const n=t[i+2];nl&&(l=n);const h=t[i+4];hc&&(c=h)}i[0]=s,i[1]=r,i[2]=o,i[3]=a,i[4]=l,i[5]=c}(r,t.offset,t.count,s),n(e,t.offset,t.count,s),d.push(e)}else for(let t of p){const e=new iY;e.boundingData=new Float32Array(6),hY(r,t.offset,t.count,e.boundingData,s),n(e,t.offset,t.count,s),d.push(e)}return d}const mY=65535;class fY{constructor(){this.min=1/0,this.max=-1/0}setFromPointsField(t,e){let n=1/0,i=-1/0;for(let s=0,r=t.length;si?r:i}this.min=n,this.max=i}setFromPoints(t,e){let n=1/0,i=-1/0;for(let s=0,r=e.length;si?o:i}this.min=n,this.max=i}isSeparated(t){return this.min>t.max||t.min>this.max}}fY.prototype.setFromBox=function(){const t=new Sb;return function(e,n){const i=n.min,s=n.max;let r=1/0,o=-1/0;for(let n=0;n<=1;n++)for(let a=0;a<=1;a++)for(let l=0;l<=1;l++){t.x=i.x*n+s.x*(1-n),t.y=i.y*a+s.y*(1-a),t.z=i.z*l+s.z*(1-l);const c=e.dot(t);r=Math.min(c,r),o=Math.max(c,o)}this.min=r,this.max=o}}();!function(){const t=new fY}();const gY=function(){const t=new Sb,e=new Sb,n=new Sb;return function(i,s,r){const o=i.start,a=t,l=s.start,c=e;n.subVectors(o,l),t.subVectors(i.end,s.start),e.subVectors(s.end,s.start);const h=n.dot(c),u=c.dot(a),d=c.dot(c),p=n.dot(a),_=a.dot(a)*d-u*u;let m,f;m=0!==_?(h*u-p*d)/_:0,f=(h+m*u)/d,r.x=m,r.y=f}}(),vY=function(){const t=new _b,e=new Sb,n=new Sb;return function(i,s,r,o){gY(i,s,t);let a=t.x,l=t.y;if(a>=0&&a<=1&&l>=0&&l<=1)return i.at(a,r),void s.at(l,o);if(a>=0&&a<=1)return l<0?s.at(0,o):s.at(1,o),void i.closestPointToPoint(o,!0,r);if(l>=0&&l<=1)return a<0?i.at(0,r):i.at(1,r),void s.closestPointToPoint(r,!0,o);{let t,c;t=a<0?i.start:i.end,c=l<0?s.start:s.end;const h=e,u=n;return i.closestPointToPoint(c,!0,e),s.closestPointToPoint(t,!0,n),h.distanceToSquared(c)<=u.distanceToSquared(t)?(r.copy(h),void o.copy(c)):(r.copy(t),void o.copy(u))}}}(),yY=function(){const t=new Sb,e=new Sb,n=new jT,i=new sL;return function(s,r){const{radius:o,center:a}=s,{a:l,b:c,c:h}=r;i.start=l,i.end=c;if(i.closestPointToPoint(a,!0,t).distanceTo(a)<=o)return!0;i.start=l,i.end=h;if(i.closestPointToPoint(a,!0,t).distanceTo(a)<=o)return!0;i.start=c,i.end=h;if(i.closestPointToPoint(a,!0,t).distanceTo(a)<=o)return!0;const u=r.getPlane(n);if(Math.abs(u.distanceToPoint(a))<=o){const t=u.projectPoint(a,e);if(r.containsPoint(t))return!0}return!1}}();class xY extends Uw{constructor(...t){super(...t),this.isSeparatingAxisTriangle=!0,this.satAxes=new Array(4).fill().map((()=>new Sb)),this.satBounds=new Array(4).fill().map((()=>new fY)),this.points=[this.a,this.b,this.c],this.sphere=new $b,this.plane=new jT,this.needsUpdate=!1}intersectsSphere(t){return yY(t,this)}update(){const t=this.a,e=this.b,n=this.c,i=this.points,s=this.satAxes,r=this.satBounds,o=s[0],a=r[0];this.getNormal(o),a.setFromPoints(o,i);const l=s[1],c=r[1];l.subVectors(t,e),c.setFromPoints(l,i);const h=s[2],u=r[2];h.subVectors(e,n),u.setFromPoints(h,i);const d=s[3],p=r[3];d.subVectors(n,t),p.setFromPoints(d,i),this.sphere.setFromPoints(this.points),this.plane.setFromNormalAndCoplanarPoint(o,t),this.needsUpdate=!1}}xY.prototype.closestPointToSegment=function(){const t=new Sb,e=new Sb,n=new sL;return function(i,s=null,r=null){const{start:o,end:a}=i,l=this.points;let c,h=1/0;for(let o=0;o<3;o++){const a=(o+1)%3;n.start.copy(l[o]),n.end.copy(l[a]),vY(n,i,t,e),c=t.distanceToSquared(e),c1-1e-10)console.warn(\\\\\\\"SeparatingAxisTriangle.intersectsTriangle: Triangles are coplanar which does not support an output edge. Setting edge to 0, 0, 0.\\\\\\\"),p.start.set(0,0,0),p.end.set(0,0,0);else{const n=this.points;let i=!1;for(let t=0;t<3;t++){const s=n[t],r=n[(t+1)%3];if(c.start.copy(s),c.end.copy(r),e.intersectLine(c,i?h.start:h.end)){if(i)break;i=!0}}const s=d.points;let r=!1;for(let e=0;e<3;e++){const n=s[e],i=s[(e+1)%3];if(c.start.copy(n),c.end.copy(i),t.intersectLine(c,r?u.start:u.end)){if(r)break;r=!0}}if(h.delta(o),u.delta(a),o.dot(a)<0){let t=u.start;u.start=u.end,u.end=t}l.subVectors(h.start,u.start),l.dot(o)>0?p.start.copy(h.start):p.start.copy(u.start),l.subVectors(h.end,u.end),l.dot(o)<0?p.end.copy(h.end):p.end.copy(u.end)}}return!0}}(),xY.prototype.distanceToPoint=function(){const t=new Sb;return function(e){return this.closestPointToPoint(e,t),e.distanceTo(t)}}(),xY.prototype.distanceToTriangle=function(){const t=new Sb,e=new Sb,n=[\\\\\\\"a\\\\\\\",\\\\\\\"b\\\\\\\",\\\\\\\"c\\\\\\\"],i=new sL,s=new sL;return function(r,o=null,a=null){const l=o||a?i:null;if(this.intersectsTriangle(r,l))return(o||a)&&(o&&l.getCenter(o),a&&l.getCenter(a)),0;let c=1/0;for(let e=0;e<3;e++){let i;const s=n[e],l=r[s];this.closestPointToPoint(l,t),i=l.distanceToSquared(t),inew Sb)),this.satAxes=new Array(3).fill().map((()=>new Sb)),this.satBounds=new Array(3).fill().map((()=>new fY)),this.alignedSatBounds=new Array(3).fill().map((()=>new fY)),this.needsUpdate=!1}set(t,e,n){super.set(t,e),this.matrix=n,this.needsUpdate=!0}copy(t){super.copy(t),this.matrix.copy(t.matrix),this.needsUpdate=!0}}bY.prototype.update=function(){const t=this.matrix,e=this.min,n=this.max,i=this.points;for(let s=0;s<=1;s++)for(let r=0;r<=1;r++)for(let o=0;o<=1;o++){const a=i[1*s|2*r|4*o];a.x=s?n.x:e.x,a.y=r?n.y:e.y,a.z=o?n.z:e.z,a.applyMatrix4(t)}const s=this.satBounds,r=this.satAxes,o=i[0];for(let t=0;t<3;t++){const e=r[t],n=s[t],a=i[1<new sL)),n=new Array(12).fill().map((()=>new sL)),i=new Sb,s=new Sb;return function(r,o=0,a=null,l=null){if(this.needsUpdate&&this.update(),this.intersectsBox(r))return(a||l)&&(r.getCenter(s),this.closestPointToPoint(s,i),r.closestPointToPoint(i,s),a&&a.copy(i),l&&l.copy(s)),0;const c=o*o,h=r.min,u=r.max,d=this.points;let p=1/0;for(let t=0;t<8;t++){const e=d[t];s.copy(e).clamp(h,u);const n=e.distanceToSquared(s);if(nn.far?null:t)}function OY(t,e,n,i){const s=t.a,r=t.b,o=t.c;let a=e,l=e+1,c=e+2;n&&(a=n.getX(e),l=n.getX(e+1),c=n.getX(e+2)),s.x=i.getX(a),s.y=i.getY(a),s.z=i.getZ(a),r.x=i.getX(l),r.y=i.getY(l),r.z=i.getZ(l),o.x=i.getX(c),o.y=i.getY(c),o.z=i.getZ(c)}function PY(t,e,n,i,s,r,o){const a=n.index,l=n.attributes.position;for(let n=t,c=e+t;n=0;let c,h;l?(c=BY(t),h=zY(t,a)):(c=zY(t,a),h=BY(t));const u=qY(c,r,i,UY)?HY(c,e,n,i):null;if(u){const t=u.point[o];if(l?t<=r[h+s]:t>=r[h+s+3])return u}const d=qY(h,r,i,UY)?HY(h,e,n,i):null;return u&&d?u.distance<=d.distance?u:d:u||d||null}}const jY=function(){let t,e;const n=[],i=new RY((()=>new Lb));return function(...r){t=i.getPrimitive(),e=i.getPrimitive(),n.push(t,e);const o=s(...r);i.releasePrimitive(t),i.releasePrimitive(e),n.pop(),n.pop();const a=n.length;return a>0&&(e=n[a-1],t=n[a-2]),o};function s(n,i,r,o,a=null,l=0,c=0){function h(t){let e=2*t,n=JY,i=ZY;for(;!IY(e,n);)e=2*(t=BY(t));return FY(t,i)}function u(t){let e=2*t,n=JY,i=ZY;for(;!IY(e,n);)e=2*(t=zY(t,i));return FY(t,i)+DY(e,n)}let d=2*n,p=$Y,_=JY,m=ZY;if(IY(d,_)){const e=FY(n,m),i=DY(d,_);return sY(n,p,t),o(e,i,!1,c,l+n,t)}{const d=BY(n),f=zY(n,m);let g,v,y,x,b=d,w=f;if(a&&(y=t,x=e,sY(b,p,y),sY(w,p,x),g=a(y),v=a(x),vs.intersectsBox(t),intersectsTriangle:t=>{t.a.applyMatrix4(c),t.b.applyMatrix4(c),t.c.applyMatrix4(c),t.needsUpdate=!0;for(let n=3*g,i=3*(v+g);nnew xY));class p${static serialize(t,e={}){if(e.isBufferGeometry)return console.warn(\\\\\\\"MeshBVH.serialize: The arguments for the function have changed. 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See documentation for new signature.\\\\\\\"),p$.deserialize(arguments[0],arguments[1],{setIndex:void 0===arguments[2]||arguments[2]});n={setIndex:!0,...n};const{index:i,roots:s}=t,r=new p$(e,{...n,[t$]:!0});if(r._roots=s,n.setIndex){const n=e.getIndex();if(null===n){const n=new Qw(t.index,1,!1);e.setIndex(n)}else n.array!==i&&(n.array.set(i),n.needsUpdate=!0)}return r}constructor(t,e={}){if(!t.isBufferGeometry)throw new Error(\\\\\\\"MeshBVH: Only BufferGeometries are supported.\\\\\\\");if(t.index&&t.index.isInterleavedBufferAttribute)throw new Error(\\\\\\\"MeshBVH: InterleavedBufferAttribute is not supported for the index attribute.\\\\\\\");if((e=Object.assign({strategy:0,maxDepth:40,maxLeafTris:10,verbose:!0,useSharedArrayBuffer:!1,setBoundingBox:!0,[t$]:!1},e)).useSharedArrayBuffer&&\\\\\\\"undefined\\\\\\\"==typeof SharedArrayBuffer)throw new Error(\\\\\\\"MeshBVH: SharedArrayBuffer is not available.\\\\\\\");this._roots=null,e[t$]||(this._roots=function(t,e){const n=_Y(t,e);let i,s,r;const o=[],a=e.useSharedArrayBuffer?SharedArrayBuffer:ArrayBuffer;for(let t=0;tMath.pow(2,32))throw new Error(\\\\\\\"MeshBVH: Cannot store child pointer greater than 32 bits.\\\\\\\");return s[n+6]=a/4,a=c(a,r),s[n+7]=o,a}}}(t,e),!t.boundingBox&&e.setBoundingBox&&(t.boundingBox=this.getBoundingBox(new Lb))),this.geometry=t}refit(t=null){t&&Array.isArray(t)&&(t=new Set(t));const e=this.geometry,n=e.index.array,i=e.attributes.position,s=i.array,r=i.offset||0;let o,a,l,c,h=3;i.isInterleavedBufferAttribute&&(h=i.data.stride);let u=0;const d=this._roots;for(let t=0,e=d.length;tp&&(p=a),l_&&(_=l),cm&&(m=c)}return(c[e+0]!==i||c[e+1]!==o||c[e+2]!==d||c[e+3]!==p||c[e+4]!==_||c[e+5]!==m)&&(c[e+0]=i,c[e+1]=o,c[e+2]=d,c[e+3]=p,c[e+4]=_,c[e+5]=m,!0)}{const n=e+8,s=a[e+6],r=n+i,l=s+i;let h=o,u=!1,d=!1;t?h||(u=t.has(r),d=t.has(l),h=!u&&!d):(u=!0,d=!0);const _=h||d;let m=!1;(h||u)&&(m=p(n,i,h));let f=!1;_&&(f=p(s,i,h));const g=m||f;if(g)for(let t=0;t<3;t++){const i=n+t,r=s+t,o=c[i],a=c[i+3],l=c[r],h=c[r+3];c[e+t]=oh?a:h}return g}}}traverse(t,e=0){const n=this._roots[e],i=new Uint32Array(n),s=new Uint16Array(n);!function e(r,o=0){const a=2*r,l=s[a+15]===mY;if(l){const e=i[r+6],c=s[a+14];t(o,l,new Float32Array(n,4*r,6),e,c)}else{const s=r+8,a=i[r+6],c=i[r+7];t(o,l,new Float32Array(n,4*r,6),c)||(e(s,o+1),e(a,o+1))}}(0)}raycast(t,e=0){const n=this._roots,i=this.geometry,s=[],r=e.isMaterial,o=Array.isArray(e),a=i.groups,l=r?e.side:e;for(let r=0,c=n.length;r{const r=3*n;return t(e,r,r+1,r+2,i,s)}}t={boundsTraverseOrder:n,intersectsBounds:t,intersectsTriangle:e,intersectsRange:null},console.warn(\\\\\\\"MeshBVH: Shapecast function signature has changed and now takes an object of callbacks as a second argument. See docs for new signature.\\\\\\\")}const s=d$.getPrimitive();let{boundsTraverseOrder:r,intersectsBounds:o,intersectsRange:a,intersectsTriangle:l}=t;if(a&&l){const t=a;a=(e,n,r,o,a)=>!!t(e,n,r,o,a)||PY(e,n,i,l,r,o,s)}else a||(a=l?(t,e,n,r)=>PY(t,e,i,l,n,r,s):(t,e,n)=>n);let c=!1,h=0;for(const t of this._roots){if(KY(t),c=jY(0,i,o,a,r,h),QY(),c)break;h+=t.byteLength}return d$.releasePrimitive(s),c}bvhcast(t,e,n){let{intersectsRanges:i,intersectsTriangles:s}=n;const r=t.geometry,o=r.index,a=r.attributes.position;i$.copy(e).invert();const l=d$.getPrimitive(),c=d$.getPrimitive();if(s){function h(t,n,i,r,h,u,d,p){for(let _=i,m=i+r;_n$.intersectsBox(t),intersectsRange:(e,n,s,r,o,a)=>(e$.copy(a),e$.applyMatrix4(i$),t.shapecast({intersectsBounds:t=>e$.intersectsBox(t),intersectsRange:(t,s,a,l,c)=>i(e,n,t,s,r,o,l,c)}))});return d$.releasePrimitive(l),d$.releasePrimitive(c),u}intersectsBox(t,e){return s$.set(t.min,t.max,e),s$.needsUpdate=!0,this.shapecast({intersectsBounds:t=>s$.intersectsBox(t),intersectsTriangle:t=>s$.intersectsTriangle(t)})}intersectsSphere(t){return this.shapecast({intersectsBounds:e=>t.intersectsBox(e),intersectsTriangle:e=>e.intersectsSphere(t)})}closestPointToGeometry(t,e,n={},i={},s=0,r=1/0){t.boundingBox||t.computeBoundingBox(),s$.set(t.boundingBox.min,t.boundingBox.max,e),s$.needsUpdate=!0;const o=this.geometry,a=o.attributes.position,l=o.index,c=t.attributes.position,h=t.index,u=d$.getPrimitive(),d=d$.getPrimitive();let p=a$,_=l$,m=null,f=null;i&&(m=c$,f=h$);let g=1/0,v=null,y=null;return i$.copy(e).invert(),r$.matrix.copy(i$),this.shapecast({boundsTraverseOrder:t=>s$.distanceToBox(t,Math.min(g,r)),intersectsBounds:(t,e,n)=>n{if(t.boundsTree)return t.boundsTree.shapecast({boundsTraverseOrder:t=>r$.distanceToBox(t,Math.min(g,r)),intersectsBounds:(t,e,n)=>n{for(let o=3*t,x=3*(t+r);o(o$.copy(t).clamp(e.min,e.max),o$.distanceToSquared(t)),intersectsBounds:(t,e,n)=>n{e.closestPointToPoint(t,o$);const i=t.distanceToSquared(o$);return i{sY(0,new Float32Array(e),u$),t.union(u$)})),t}}const _$=p$.prototype.raycast;p$.prototype.raycast=function(...t){if(t[0].isMesh){console.warn('MeshBVH: The function signature and results frame for \\\\\\\"raycast\\\\\\\" has changed. See docs for new signature.');const[e,n,i,s]=t;return _$.call(this,i,e.material).forEach((t=>{(t=LY(t,e,n))&&s.push(t)})),s}return _$.apply(this,t)};const m$=p$.prototype.raycastFirst;p$.prototype.raycastFirst=function(...t){if(t[0].isMesh){console.warn('MeshBVH: The function signature and results frame for \\\\\\\"raycastFirst\\\\\\\" has changed. See docs for new signature.');const[e,n,i]=t;return LY(m$.call(this,i,e.material),e,n)}return m$.apply(this,t)};const f$=p$.prototype.closestPointToPoint;p$.prototype.closestPointToPoint=function(...t){if(t[0].isMesh){console.warn('MeshBVH: The function signature and results frame for \\\\\\\"closestPointToPoint\\\\\\\" has changed. See docs for new signature.'),t.unshift();const e=t[1],n={};return t[1]=n,f$.apply(this,t),e&&e.copy(n.point),n.distance}return f$.apply(this,t)};const g$=p$.prototype.closestPointToGeometry;p$.prototype.closestPointToGeometry=function(...t){const e=t[2],n=t[3];if(e&&e.isVector3||n&&n.isVector3){console.warn('MeshBVH: The function signature and results frame for \\\\\\\"closestPointToGeometry\\\\\\\" has changed. See docs for new signature.');const i={},s={},r=t[1];return t[2]=i,t[3]=s,g$.apply(this,t),e&&e.copy(i.point),n&&n.copy(s.point).applyMatrix4(r),i.distance}return g$.apply(this,t)};const v$=p$.prototype.refit;p$.prototype.refit=function(...t){const e=t[0],n=t[1];if(n&&(n instanceof Set||Array.isArray(n))){console.warn('MeshBVH: The function signature for \\\\\\\"refit\\\\\\\" has changed. See docs for new signature.');const t=new Set;n.forEach((e=>t.add(e))),e&&e.forEach((e=>t.add(e))),v$.call(this,t)}else v$.apply(this,t)},[\\\\\\\"intersectsGeometry\\\\\\\",\\\\\\\"shapecast\\\\\\\",\\\\\\\"intersectsBox\\\\\\\",\\\\\\\"intersectsSphere\\\\\\\"].forEach((t=>{const e=p$.prototype[t];p$.prototype[t]=function(...n){return(null===n[0]||n[0].isMesh)&&(n.shift(),console.warn(`MeshBVH: The function signature for \\\\\\\"${t}\\\\\\\" has changed and no longer takes Mesh. See docs for new signature.`)),e.apply(this,n)}}));const y$=new iw,x$=new sw,b$=CT.prototype.raycast;function w$(t,e){if(this.geometry.boundsTree){if(void 0===this.material)return;x$.copy(this.matrixWorld).invert(),y$.copy(t.ray).applyMatrix4(x$);const n=this.geometry.boundsTree;if(!0===t.firstHitOnly){const i=LY(n.raycastFirst(y$,this.material),this,t);i&&e.push(i)}else{const i=n.raycast(y$,this.material);for(let n=0,s=i.length;n{if(t===i||e)return r++,!0;s&&r++}),n);let o=0;const a=new Float32Array(24*r);let l,c;e.traverse(((t,e,n)=>{const r=t===i||e;if(r||s){sY(0,n,T$);const{min:t,max:e}=T$;for(let n=-1;n<=1;n+=2){const i=n<0?t.x:e.x;for(let n=-1;n<=1;n+=2){const s=n<0?t.y:e.y;for(let n=-1;n<=1;n+=2){const r=n<0?t.z:e.z;a[o+0]=i,a[o+1]=s,a[o+2]=r,o+=3}}}return r}}),n),c=this.displayEdges?new Uint8Array([0,4,1,5,2,6,3,7,0,2,1,3,4,6,5,7,0,1,2,3,4,5,6,7]):new Uint8Array([0,1,2,2,1,3,4,6,5,6,7,5,1,4,5,0,4,1,2,3,6,3,7,6,0,2,4,2,6,4,1,5,3,3,5,7]),l=a.length>65535?new Uint32Array(c.length*r):new Uint16Array(c.length*r);const h=c.length;for(let t=0;te;)this._roots.pop();for(let t=0;t=this._roots.length){const e=new A$(this.mesh,this.edgeMaterial,this.depth,t);this.add(e),this._roots.push(e)}const e=this._roots[t];e.depth=this.depth,e.mesh=this.mesh,e.displayParents=this.displayParents,e.displayEdges=this.displayEdges,e.material=this.displayEdges?this.edgeMaterial:this.meshMaterial,e.update()}}updateMatrixWorld(...t){this.position.copy(this.mesh.position),this.rotation.copy(this.mesh.rotation),this.scale.copy(this.mesh.scale),super.updateMatrixWorld(...t)}copy(t){this.depth=t.depth,this.mesh=t.mesh}clone(){return new M$(this.mesh,this.depth)}dispose(){this.edgeMaterial.dispose(),this.meshMaterial.dispose();const t=this.children;for(let e=0,n=t.length;e{const i=t;if(i.isMesh){if(e.keepOnlyPosition){const t=i.geometry;for(const e in t.attributes)\\\\\\\"position\\\\\\\"!==e&&t.deleteAttribute(e)}n.push(i)}}))}const i=this._makeCompact(n);if(i){i.matrixAutoUpdate=!1,i.raycast=w$;const t=new p$(i.geometry,{verbose:!1});return i.geometry.boundsTree=t,this.createCoreGroupFromObjects([i])}return this.createCoreGroupFromObjects([])}_makeCompact(t){var e,n;const i=[];let s;for(let e of t){s=s||e.material;const t=e.geometry;t.applyMatrix4(e.matrix),i.push(t)}try{const t=fr.mergeGeometries(i);if(t){return this.createObject(t,Ns.MESH,s)}null===(e=this.states)||void 0===e||e.error.set(\\\\\\\"merge failed, check that input geometries have the same attributes\\\\\\\")}catch(t){null===(n=this.states)||void 0===n||n.error.set(t.message)}}}E$.DEFAULT_PARAMS={keepOnlyPosition:!1},E$.INPUT_CLONED_STATE=Qi.ALWAYS;const S$=E$.DEFAULT_PARAMS;const C$=new class extends ua{constructor(){super(...arguments),this.keepOnlyPosition=ha.BOOLEAN(S$.keepOnlyPosition)}};class N$ extends uV{constructor(){super(...arguments),this.paramsConfig=C$}static type(){return\\\\\\\"BVH\\\\\\\"}static displayedInputNames(){return[\\\\\\\"geometry to create BVH from\\\\\\\"]}initializeNode(){this.io.inputs.setCount(1),this.io.inputs.initInputsClonedState(E$.INPUT_CLONED_STATE)}cook(t){this._operation=this._operation||new E$(this._scene,this.states);const e=this._operation.cook(t,this.pv);this.setCoreGroup(e)}}class L$ extends aV{static type(){return\\\\\\\"BVHVisualizer\\\\\\\"}cook(t,e){const n=t[0].objects()[0],i=new M$(n,e.depth);return i.opacity=1,i.update(),this.createCoreGroupFromObjects([i])}}L$.DEFAULT_PARAMS={depth:0},L$.INPUT_CLONED_STATE=Qi.NEVER;const O$=L$.DEFAULT_PARAMS;const P$=new class extends ua{constructor(){super(...arguments),this.depth=ha.INTEGER(O$.depth,{range:[0,20],rangeLocked:[!0,!1]})}};class R$ extends uV{constructor(){super(...arguments),this.paramsConfig=P$}static type(){return\\\\\\\"BVHVisualizer\\\\\\\"}static displayedInputNames(){return[\\\\\\\"geometry with bvh\\\\\\\"]}initializeNode(){this.io.inputs.setCount(1),this.io.inputs.initInputsClonedState(L$.INPUT_CLONED_STATE)}cook(t){this._operation=this._operation||new L$(this._scene,this.states);const e=this._operation.cook(t,this.pv);this.setCoreGroup(e)}}class I$ extends C.a{constructor(t,e,n,i=1){\\\\\\\"number\\\\\\\"==typeof n&&(i=n,n=!1,console.error(\\\\\\\"THREE.InstancedBufferAttribute: The constructor now expects normalized as the third argument.\\\\\\\")),super(t,e,n),this.meshPerAttribute=i}copy(t){return super.copy(t),this.meshPerAttribute=t.meshPerAttribute,this}toJSON(){const t=super.toJSON();return t.meshPerAttribute=this.meshPerAttribute,t.isInstancedBufferAttribute=!0,t}}I$.prototype.isInstancedBufferAttribute=!0;const F$=new A.a,D$=new A.a,B$=[],z$=new B.a;class k$ extends B.a{constructor(t,e,n){super(t,e),this.instanceMatrix=new I$(new Float32Array(16*n),16),this.instanceColor=null,this.count=n,this.frustumCulled=!1}copy(t){return super.copy(t),this.instanceMatrix.copy(t.instanceMatrix),null!==t.instanceColor&&(this.instanceColor=t.instanceColor.clone()),this.count=t.count,this}getColorAt(t,e){e.fromArray(this.instanceColor.array,3*t)}getMatrixAt(t,e){e.fromArray(this.instanceMatrix.array,16*t)}raycast(t,e){const n=this.matrixWorld,i=this.count;if(z$.geometry=this.geometry,z$.material=this.material,void 0!==z$.material)for(let s=0;st.far||e.push({distance:a,point:G$.clone(),uv:tr.a.getUV(G$,X$,Y$,$$,J$,Z$,K$,new d.a),face:null,object:this})}copy(t){return super.copy(t),void 0!==t.center&&this.center.copy(t.center),this.material=t.material,this}}function tJ(t,e,n,i,s,r){j$.subVectors(t,n).addScalar(.5).multiply(i),void 0!==s?(W$.x=r*j$.x-s*j$.y,W$.y=s*j$.x+r*j$.y):W$.copy(j$),t.copy(e),t.x+=W$.x,t.y+=W$.y,t.applyMatrix4(q$)}Q$.prototype.isSprite=!0;var eJ=n(92),nJ=n(81),iJ=n(46);class sJ{constructor(){this.coefficients=[];for(let t=0;t<9;t++)this.coefficients.push(new p.a)}set(t){for(let e=0;e<9;e++)this.coefficients[e].copy(t[e]);return this}zero(){for(let t=0;t<9;t++)this.coefficients[t].set(0,0,0);return this}getAt(t,e){const n=t.x,i=t.y,s=t.z,r=this.coefficients;return e.copy(r[0]).multiplyScalar(.282095),e.addScaledVector(r[1],.488603*i),e.addScaledVector(r[2],.488603*s),e.addScaledVector(r[3],.488603*n),e.addScaledVector(r[4],n*i*1.092548),e.addScaledVector(r[5],i*s*1.092548),e.addScaledVector(r[6],.315392*(3*s*s-1)),e.addScaledVector(r[7],n*s*1.092548),e.addScaledVector(r[8],.546274*(n*n-i*i)),e}getIrradianceAt(t,e){const n=t.x,i=t.y,s=t.z,r=this.coefficients;return e.copy(r[0]).multiplyScalar(.886227),e.addScaledVector(r[1],1.023328*i),e.addScaledVector(r[2],1.023328*s),e.addScaledVector(r[3],1.023328*n),e.addScaledVector(r[4],.858086*n*i),e.addScaledVector(r[5],.858086*i*s),e.addScaledVector(r[6],.743125*s*s-.247708),e.addScaledVector(r[7],.858086*n*s),e.addScaledVector(r[8],.429043*(n*n-i*i)),e}add(t){for(let e=0;e<9;e++)this.coefficients[e].add(t.coefficients[e]);return this}addScaledSH(t,e){for(let n=0;n<9;n++)this.coefficients[n].addScaledVector(t.coefficients[n],e);return this}scale(t){for(let e=0;e<9;e++)this.coefficients[e].multiplyScalar(t);return this}lerp(t,e){for(let n=0;n<9;n++)this.coefficients[n].lerp(t.coefficients[n],e);return this}equals(t){for(let e=0;e<9;e++)if(!this.coefficients[e].equals(t.coefficients[e]))return!1;return!0}copy(t){return this.set(t.coefficients)}clone(){return(new this.constructor).copy(this)}fromArray(t,e=0){const n=this.coefficients;for(let i=0;i<9;i++)n[i].fromArray(t,e+3*i);return this}toArray(t=[],e=0){const n=this.coefficients;for(let i=0;i<9;i++)n[i].toArray(t,e+3*i);return t}static getBasisAt(t,e){const n=t.x,i=t.y,s=t.z;e[0]=.282095,e[1]=.488603*i,e[2]=.488603*s,e[3]=.488603*n,e[4]=1.092548*n*i,e[5]=1.092548*i*s,e[6]=.315392*(3*s*s-1),e[7]=1.092548*n*s,e[8]=.546274*(n*n-i*i)}}sJ.prototype.isSphericalHarmonics3=!0;class rJ extends cv.a{constructor(t=new sJ,e=1){super(void 0,e),this.sh=t}copy(t){return super.copy(t),this.sh.copy(t.sh),this}fromJSON(t){return this.intensity=t.intensity,this.sh.fromArray(t.sh),this}toJSON(t){const e=super.toJSON(t);return e.object.sh=this.sh.toArray(),e}}rJ.prototype.isLightProbe=!0;var oJ=n(63),aJ=n(43);class lJ extends S.a{constructor(){super(),this.type=\\\\\\\"InstancedBufferGeometry\\\\\\\",this.instanceCount=1/0}copy(t){return super.copy(t),this.instanceCount=t.instanceCount,this}clone(){return(new this.constructor).copy(this)}toJSON(){const t=super.toJSON(this);return t.instanceCount=this.instanceCount,t.isInstancedBufferGeometry=!0,t}}lJ.prototype.isInstancedBufferGeometry=!0;class cJ extends Vf.a{constructor(t){super(t)}load(t,e,n,i){const s=this,r=new Gf.a(s.manager);r.setPath(s.path),r.setRequestHeader(s.requestHeader),r.setWithCredentials(s.withCredentials),r.load(t,(function(n){try{e(s.parse(JSON.parse(n)))}catch(e){i?i(e):console.error(e),s.manager.itemError(t)}}),n,i)}parse(t){const e={},n={};function i(t,i){if(void 0!==e[i])return e[i];const s=t.interleavedBuffers[i],r=function(t,e){if(void 0!==n[e])return n[e];const i=t.arrayBuffers[e],s=new Uint32Array(i).buffer;return n[e]=s,s}(t,s.buffer),o=Object(It.c)(s.type,r),a=new cr.a(o,s.stride);return a.uuid=s.uuid,e[i]=a,a}const s=t.isInstancedBufferGeometry?new lJ:new S.a,r=t.data.index;if(void 0!==r){const t=Object(It.c)(r.type,r.array);s.setIndex(new C.a(t,1))}const o=t.data.attributes;for(const e in o){const n=o[e];let r;if(n.isInterleavedBufferAttribute){const e=i(t.data,n.data);r=new hr.a(e,n.itemSize,n.offset,n.normalized)}else{const t=Object(It.c)(n.type,n.array);r=new(n.isInstancedBufferAttribute?I$:C.a)(t,n.itemSize,n.normalized)}void 0!==n.name&&(r.name=n.name),void 0!==n.usage&&r.setUsage(n.usage),void 0!==n.updateRange&&(r.updateRange.offset=n.updateRange.offset,r.updateRange.count=n.updateRange.count),s.setAttribute(e,r)}const a=t.data.morphAttributes;if(a)for(const e in a){const n=a[e],r=[];for(let e=0,s=n.length;eNumber.EPSILON){const u=Math.sqrt(h),p=Math.sqrt(l*l+c*c),_=e.x-a/u,m=e.y+o/u,f=((n.x-c/p-_)*c-(n.y+l/p-m)*l)/(o*c-a*l);i=_+o*f-t.x,s=m+a*f-t.y;const g=i*i+s*s;if(g<=2)return new d.a(i,s);r=Math.sqrt(g/2)}else{let t=!1;o>Number.EPSILON?l>Number.EPSILON&&(t=!0):o<-Number.EPSILON?l<-Number.EPSILON&&(t=!0):Math.sign(a)===Math.sign(c)&&(t=!0),t?(i=-a,s=o,r=Math.sqrt(h)):(i=o,s=a,r=Math.sqrt(h/2))}return new d.a(i/r,s/r)}const R=[];for(let t=0,e=C.length,n=e-1,i=t+1;t=0;t--){const e=t/m,n=h*Math.cos(e*Math.PI/2),i=u*Math.sin(e*Math.PI/2)+_;for(let t=0,e=C.length;t=0;){const i=n;let s=n-1;s<0&&(s=t.length-1);for(let t=0,n=a+2*m;t0){const n=new Xg.b(e);s=new oJ.a(n),s.setCrossOrigin(this.crossOrigin);for(let e=0,n=t.length;e0){i=new oJ.a(this.manager),i.setCrossOrigin(this.crossOrigin);for(let e=0,i=t.length;e{BJ.PARAM_CALLBACK_reset(t,e)}})}};class BJ extends uV{constructor(){super(...arguments),this.paramsConfig=DJ}static type(){return\\\\\\\"cache\\\\\\\"}static displayedInputNames(){return[\\\\\\\"geometry to cache\\\\\\\"]}initializeNode(){this.io.inputs.setCount(0,1)}cook(t){const e=\\\\\\\"\\\\\\\"==this.pv.cache||null==this.pv.cache,n=t[0];if(e&&n){const t=[];for(let e of n.objects())t.push(e.toJSON());this.setCoreGroup(n),this.p.cache.set(JSON.stringify(t))}else if(this.pv.cache){const t=new PJ,e=JSON.parse(this.pv.cache),n=[];for(let i of e){const e=t.parse(i);n.push(e)}this.setObjects(n)}else this.setObjects([])}static PARAM_CALLBACK_reset(t,e){t.param_callback_PARAM_CALLBACK_reset()}async param_callback_PARAM_CALLBACK_reset(){this.p.cache.set(\\\\\\\"\\\\\\\"),this.compute()}}const zJ={direction:new p.a(0,1,0)},kJ=[new d.a(-1,-1),new d.a(-1,1),new d.a(1,1),new d.a(1,-1)],UJ=new p.a(0,0,1);const GJ=new class extends ua{constructor(){super(...arguments),this.camera=ha.NODE_PATH(\\\\\\\"\\\\\\\",{nodeSelection:{context:ts.OBJ,types:ds}}),this.direction=ha.VECTOR3(zJ.direction),this.offset=ha.FLOAT(0,{range:[-10,10],rangeLocked:[!1,!1]}),this.useSegmentsCount=ha.BOOLEAN(!0),this.stepSize=ha.FLOAT(1,{range:[.001,1],rangeLocked:[!1,!1],visibleIf:{useSegmentsCount:0}}),this.segments=ha.VECTOR2([10,10],{visibleIf:{useSegmentsCount:1}}),this.sizeMult=ha.FLOAT(1,{range:[0,2],rangeLocked:[!0,!1]}),this.updateOnWindowResize=ha.BOOLEAN(1),this.update=ha.BUTTON(null,{callback:t=>{VJ.PARAM_CALLBACK_update(t)}})}};class VJ extends uV{constructor(){super(...arguments),this.paramsConfig=GJ,this._plane=new Y.a,this._raycaster=new eO,this._planeCorners=[new p.a,new p.a,new p.a,new p.a],this._planeCenter=new p.a,this._core_transform=new bU,this.segments_count=new d.a(1,1),this.planeSize=new d.a}static type(){return\\\\\\\"cameraPlane\\\\\\\"}cook(){this._updateWindowControllerDependency();const t=this.pv.camera.nodeWithContext(ts.OBJ);if(!t)return this.states.error.set(\\\\\\\"no camera found\\\\\\\"),void this.cookController.endCook();if(!ds.includes(t.type()))return this.states.error.set(\\\\\\\"node found is not a camera\\\\\\\"),void this.cookController.endCook();const e=t.object;this._computePlaneParams(e)}_updateWindowControllerDependency(){this.pv.updateOnWindowResize?this.addGraphInput(this.scene().windowController.graphNode()):this.removeGraphInput(this.scene().windowController.graphNode())}_computePlaneParams(t){this._plane.normal.copy(this.pv.direction),this._plane.constant=this.pv.offset;let e=0;this._planeCenter.set(0,0,0);for(let n of kJ){this._raycaster.setFromCamera(n,t);const i=this._planeCorners[e];this._raycaster.ray.intersectPlane(this._plane,i),this._planeCenter.add(i),e++}this._planeCenter.multiplyScalar(.25);const n=this._planeCorners[1].distanceTo(this._planeCorners[2]),i=this._planeCorners[0].distanceTo(this._planeCorners[3]),s=this._planeCorners[0].distanceTo(this._planeCorners[1]),r=this._planeCorners[2].distanceTo(this._planeCorners[3]),o=Math.max(n,i)*this.pv.sizeMult,a=Math.max(s,r)*this.pv.sizeMult;this.planeSize.set(o,a);const l=this._createPlane(this.planeSize);this._core_transform.rotateGeometry(l,UJ,this.pv.direction);const c=this._core_transform.translationMatrix(this._planeCenter);l.applyMatrix4(c),this.setGeometry(l)}_createPlane(t){return t=t.clone(),this.pv.useSegmentsCount?(this.segments_count.x=Math.floor(this.pv.segments.x),this.segments_count.y=Math.floor(this.pv.segments.y)):this.pv.stepSize>0&&(this.segments_count.x=Math.floor(t.x/this.pv.stepSize),this.segments_count.y=Math.floor(t.y/this.pv.stepSize),t.x=this.segments_count.x*this.pv.stepSize,t.y=this.segments_count.y*this.pv.stepSize),new L(t.x,t.y,this.segments_count.x,this.segments_count.y)}static PARAM_CALLBACK_update(t){t._paramCallbackUpdate()}_paramCallbackUpdate(){this.setDirty()}}class HJ extends aV{constructor(){super(...arguments),this._pointPosition=new p.a}static type(){return\\\\\\\"cameraProject\\\\\\\"}cook(t,e){var n,i;const s=t[0],r=e.camera.nodeWithContext(ts.OBJ,null===(n=this.states)||void 0===n?void 0:n.error);if(r){const t=r.object;for(let n of s.points())n.getPosition(this._pointPosition),e.unproject?this._pointPosition.unproject(t):this._pointPosition.project(t),n.setPosition(this._pointPosition)}else null===(i=this.states)||void 0===i||i.error.set(\\\\\\\"cameraNode invalid.\\\\\\\");return s}}HJ.DEFAULT_PARAMS={camera:new yi(\\\\\\\"\\\\\\\"),unproject:!1},HJ.INPUT_CLONED_STATE=Qi.FROM_NODE;const jJ=HJ.DEFAULT_PARAMS;const WJ=new class extends ua{constructor(){super(...arguments),this.camera=ha.NODE_PATH(jJ.camera.path(),{nodeSelection:{context:ts.OBJ,types:ds}}),this.unproject=ha.BOOLEAN(jJ.unproject)}};class qJ extends uV{constructor(){super(...arguments),this.paramsConfig=WJ}static type(){return\\\\\\\"cameraProject\\\\\\\"}static displayedInputNames(){return[\\\\\\\"points to project/unproject\\\\\\\"]}initializeNode(){this.io.inputs.setCount(1),this.io.inputs.initInputsClonedState(HJ.INPUT_CLONED_STATE)}cook(t){this._operation=this._operation||new HJ(this._scene,this.states);const e=this._operation.cook(t,this.pv);this.setCoreGroup(e)}}class XJ extends aV{constructor(){super(...arguments),this._geo_center=new p.a}static type(){return\\\\\\\"center\\\\\\\"}cook(t,e){var n;const i=t[0].objectsWithGeo(),s=new Array(3*i.length);s.fill(0);for(let t=0;t0&&(r.push(t-1),r.push(t));r.push(e-1),r.push(0);const a=new S.a;return a.setAttribute(\\\\\\\"position\\\\\\\",new C.c(s,3)),a.setIndex(r),a}}const ZJ=new p.a(0,0,1);class KJ extends aV{constructor(){super(...arguments),this._core_transform=new bU}static type(){return\\\\\\\"circle\\\\\\\"}cook(t,e){return e.open?this._create_circle(e):this._create_disk(e)}_create_circle(t){const e=JJ.create(t.radius,t.segments,t.arcAngle);return this._core_transform.rotateGeometry(e,ZJ,t.direction),this.createCoreGroupFromGeometry(e,Ns.LINE_SEGMENTS)}_create_disk(t){const e=new hJ(t.radius,t.segments);return this._core_transform.rotateGeometry(e,ZJ,t.direction),this.createCoreGroupFromGeometry(e)}}KJ.DEFAULT_PARAMS={radius:1,segments:12,open:!0,arcAngle:360,direction:new p.a(0,1,0)};const QJ=KJ.DEFAULT_PARAMS;const tZ=new class extends ua{constructor(){super(...arguments),this.radius=ha.FLOAT(QJ.radius),this.segments=ha.INTEGER(QJ.segments,{range:[1,50],rangeLocked:[!0,!1]}),this.open=ha.BOOLEAN(QJ.open),this.arcAngle=ha.FLOAT(QJ.arcAngle,{range:[0,360],rangeLocked:[!1,!1],visibleIf:{open:1}}),this.direction=ha.VECTOR3(QJ.direction)}};class eZ extends uV{constructor(){super(...arguments),this.paramsConfig=tZ}static type(){return\\\\\\\"circle\\\\\\\"}initializeNode(){}cook(){this._operation=this._operation||new KJ(this._scene,this.states);const t=this._operation.cook([],this.pv);this.setCoreGroup(t)}}var nZ;!function(t){t.SEGMENTS_COUNT=\\\\\\\"segments count\\\\\\\",t.SEGMENTS_LENGTH=\\\\\\\"segments length\\\\\\\"}(nZ||(nZ={}));const iZ=[nZ.SEGMENTS_COUNT,nZ.SEGMENTS_LENGTH];var sZ;!function(t){t.ABC=\\\\\\\"abc\\\\\\\",t.ACB=\\\\\\\"acb\\\\\\\",t.AB=\\\\\\\"ab\\\\\\\",t.BC=\\\\\\\"bc\\\\\\\",t.AC=\\\\\\\"ac\\\\\\\"}(sZ||(sZ={}));const rZ=[sZ.ABC,sZ.ACB,sZ.AB,sZ.AC,sZ.BC];class oZ{constructor(t){this.params=t,this.a=new p.a,this.b=new p.a,this.c=new p.a,this.an=new p.a,this.bn=new p.a,this.cn=new p.a,this.ac=new p.a,this.ab=new p.a,this.ab_x_ac=new p.a,this.part0=new p.a,this.part1=new p.a,this.divider=1,this.a_center=new p.a,this.center=new p.a,this.normal=new p.a,this.radius=1,this.x=new p.a,this.y=new p.a,this.z=new p.a,this.angle_ab=1,this.angle_ac=1,this.angle_bc=1,this.angle=2*Math.PI,this.x_rotated=new p.a,this._created_geometries={}}created_geometries(){return this._created_geometries}create(t,e,n){this.a.copy(t),this.b.copy(e),this.c.copy(n),this._compute_axis(),this._create_arc(),this._create_center()}_create_arc(){this._compute_angle();const t=this._points_count(),e=new Array(3*t),n=new Array(t),i=this.angle/(t-1);this.x_rotated.copy(this.x).multiplyScalar(this.radius);let s=0;for(s=0;s0&&(n[2*(s-1)]=s-1,n[2*(s-1)+1]=s);this.params.full&&(n.push(s-1),n.push(0));const r=new S.a;if(r.setAttribute(\\\\\\\"position\\\\\\\",new C.a(new Float32Array(e),3)),r.setIndex(n),this.params.addIdAttribute||this.params.addIdnAttribute){const e=new Array(t);for(let t=0;te/(t-1)));this.params.addIdnAttribute&&r.setAttribute(\\\\\\\"idn\\\\\\\",new C.a(new Float32Array(n),1))}this._created_geometries.arc=r}_create_center(){if(!this.params.center)return;const t=new S.a,e=[this.center.x,this.center.y,this.center.z];t.setAttribute(\\\\\\\"position\\\\\\\",new C.a(new Float32Array(e),3)),this._created_geometries.center=t}_compute_axis(){this.ac.copy(this.c).sub(this.a),this.ab.copy(this.b).sub(this.a),this.ab_x_ac.copy(this.ab).cross(this.ac),this.divider=2*this.ab_x_ac.lengthSq(),this.part0.copy(this.ab_x_ac).cross(this.ab).multiplyScalar(this.ac.lengthSq()),this.part1.copy(this.ac).cross(this.ab_x_ac).multiplyScalar(this.ab.lengthSq()),this.a_center.copy(this.part0).add(this.part1).divideScalar(this.divider),this.radius=this.a_center.length(),this.normal.copy(this.ab_x_ac).normalize(),this.center.copy(this.a).add(this.a_center)}_compute_angle(){this.params.arc&&(this.params.full?(this.x.copy(this.a).sub(this.center).normalize(),this.angle=2*Math.PI):(this.an.copy(this.a).sub(this.center).normalize(),this.bn.copy(this.b).sub(this.center).normalize(),this.cn.copy(this.c).sub(this.center).normalize(),this._set_x_from_joinMode(),this.y.copy(this.normal),this.z.copy(this.x).cross(this.y).normalize(),this.angle_ab=this.an.angleTo(this.bn),this.angle_ac=this.an.angleTo(this.cn),this.angle_bc=this.bn.angleTo(this.cn),this._set_angle_from_joinMode()))}_points_count(){const t=this.params.pointsCountMode;switch(t){case nZ.SEGMENTS_COUNT:return this.params.segmentsCount+1;case nZ.SEGMENTS_LENGTH:{let t=Math.PI*this.radius*this.radius;return this.params.full||(t*=Math.abs(this.angle)/(2*Math.PI)),Math.ceil(t/this.params.segmentsLength)}}os.unreachable(t)}_set_x_from_joinMode(){const t=this.params.joinMode;switch(this.x.copy(this.a).sub(this.center).normalize(),t){case sZ.ABC:case sZ.ACB:case sZ.AB:case sZ.AC:return this.x.copy(this.an);case sZ.BC:return this.x.copy(this.bn)}os.unreachable(t)}_set_angle_from_joinMode(){const t=this.params.joinMode;switch(t){case sZ.ABC:return void(this.angle=this.angle_ab+this.angle_bc);case sZ.ACB:return this.angle=this.angle_ac+this.angle_bc,void(this.angle*=-1);case sZ.AB:return void(this.angle=this.angle_ab);case sZ.AC:return this.angle=this.angle_ac,void(this.angle*=-1);case sZ.BC:return void(this.angle=this.angle_bc)}os.unreachable(t)}}const aZ=new class extends ua{constructor(){super(...arguments),this.arc=ha.BOOLEAN(1),this.pointsCountMode=ha.INTEGER(iZ.indexOf(nZ.SEGMENTS_COUNT),{visibleIf:{arc:1},menu:{entries:iZ.map(((t,e)=>({value:e,name:t})))}}),this.segmentsLength=ha.FLOAT(.1,{visibleIf:{arc:1,pointsCountMode:iZ.indexOf(nZ.SEGMENTS_LENGTH)},range:[0,1],rangeLocked:[!0,!1]}),this.segmentsCount=ha.INTEGER(100,{visibleIf:{arc:1,pointsCountMode:iZ.indexOf(nZ.SEGMENTS_COUNT)},range:[1,100],rangeLocked:[!0,!1]}),this.full=ha.BOOLEAN(1,{visibleIf:{arc:1}}),this.joinMode=ha.INTEGER(rZ.indexOf(sZ.ABC),{visibleIf:{arc:1,full:0},menu:{entries:rZ.map(((t,e)=>({value:e,name:t})))}}),this.addIdAttribute=ha.BOOLEAN(1),this.addIdnAttribute=ha.BOOLEAN(1),this.center=ha.BOOLEAN(0)}};class lZ extends uV{constructor(){super(...arguments),this.paramsConfig=aZ,this.a=new p.a,this.b=new p.a,this.c=new p.a}static type(){return\\\\\\\"circle3Points\\\\\\\"}initializeNode(){this.io.inputs.setCount(1),this.io.inputs.initInputsClonedState([Qi.NEVER])}cook(t){const e=t[0].points();e.length<3?this.states.error.set(`only ${e.length} points found, when 3 are required`):this._create_circle(e)}_create_circle(t){const e=new oZ({arc:this.pv.arc,center:this.pv.center,pointsCountMode:iZ[this.pv.pointsCountMode],segmentsLength:this.pv.segmentsLength,segmentsCount:this.pv.segmentsCount,full:this.pv.full,joinMode:rZ[this.pv.joinMode],addIdAttribute:this.pv.addIdAttribute,addIdnAttribute:this.pv.addIdnAttribute});t[0].getPosition(this.a),t[1].getPosition(this.b),t[2].getPosition(this.c),e.create(this.a,this.b,this.c);const n=[],i=e.created_geometries();i.arc&&n.push(this.createObject(i.arc,Ns.LINE_SEGMENTS)),i.center&&n.push(this.createObject(i.center,Ns.POINTS)),this.setObjects(n)}}const cZ=new p.a,hZ=new Dy;class uZ extends aV{constructor(){super(...arguments),this._plane=new Y.a}static type(){return\\\\\\\"clip\\\\\\\"}cook(t,e){const n=t[0].objectsWithGeo()[0];this._plane.set(e.direction,-e.distance),this._plane.translate(e.origin);const i=this._createClipGeo(n);return i?this.createCoreGroupFromObjects([i]):this.createCoreGroupFromObjects([])}_createClipGeo(t){var e;const n=t;if(!n.geometry.boundsTree)return void(null===(e=this.states)||void 0===e||e.error.set(\\\\\\\"no BVH found on input geo, make sure to use a BVH SOP node\\\\\\\"));const i=n.geometry.boundsTree,s=t=>{let e=0;return i.shapecast({intersectsBounds:t=>this._plane.intersectsBox(t),intersectsTriangle:n=>{let i=0;hZ.start.copy(n.a),hZ.end.copy(n.b),this._plane.intersectLine(hZ,cZ)&&(null==t||t.setXYZ(e,cZ.x,cZ.y,cZ.z),e++,i++),hZ.start.copy(n.b),hZ.end.copy(n.c),this._plane.intersectLine(hZ,cZ)&&(null==t||t.setXYZ(e,cZ.x,cZ.y,cZ.z),i++,e++),hZ.start.copy(n.c),hZ.end.copy(n.a),this._plane.intersectLine(hZ,cZ)&&(null==t||t.setXYZ(e,cZ.x,cZ.y,cZ.z),i++,e++),2!==i&&(e-=i)}}),{index:e}},{index:r}=s(),o=new S.a,a=new C.a(new Float32Array(3*r),3,!1);o.setAttribute(\\\\\\\"position\\\\\\\",a);const l=new Ms.a(o,js.MATERIALS[Ns.LINE_SEGMENTS]);l.frustumCulled=!1;return s(l.geometry.attributes.position),l}}uZ.DEFAULT_PARAMS={origin:new p.a(0,0,0),distance:0,direction:new p.a(0,1,0)},uZ.INPUT_CLONED_STATE=Qi.NEVER;const dZ=uZ.DEFAULT_PARAMS;const pZ=new class extends ua{constructor(){super(...arguments),this.origin=ha.VECTOR3(dZ.origin),this.distance=ha.FLOAT(dZ.distance,{range:[-10,10],rangeLocked:[!1,!1]}),this.direction=ha.VECTOR3(dZ.direction)}};class _Z extends uV{constructor(){super(...arguments),this.paramsConfig=pZ}static type(){return\\\\\\\"clip\\\\\\\"}initializeNode(){this.io.inputs.setCount(1),this.io.inputs.initInputsClonedState(uZ.INPUT_CLONED_STATE)}cook(t){this._operation=this._operation||new uZ(this._scene,this.states);const e=this._operation.cook(t,this.pv);this.setCoreGroup(e)}}class mZ extends aV{static type(){return\\\\\\\"color\\\\\\\"}cook(t,e){}}mZ.DEFAULT_PARAMS={fromAttribute:!1,attribName:\\\\\\\"\\\\\\\",color:new D.a(1,1,1),asHsv:!1};const fZ=new D.a(1,1,1),gZ=\\\\\\\"color\\\\\\\",vZ=mZ.DEFAULT_PARAMS;const yZ=new class extends ua{constructor(){super(...arguments),this.fromAttribute=ha.BOOLEAN(vZ.fromAttribute),this.attribName=ha.STRING(vZ.attribName,{visibleIf:{fromAttribute:1}}),this.color=ha.COLOR(vZ.color,{visibleIf:{fromAttribute:0},expression:{forEntities:!0}}),this.asHsv=ha.BOOLEAN(vZ.asHsv,{visibleIf:{fromAttribute:0}})}};class xZ extends uV{constructor(){super(...arguments),this.paramsConfig=yZ,this._r_arrays_by_geometry_uuid={},this._g_arrays_by_geometry_uuid={},this._b_arrays_by_geometry_uuid={}}static type(){return\\\\\\\"color\\\\\\\"}static displayedInputNames(){return[\\\\\\\"geometry to update color of\\\\\\\"]}initializeNode(){this.io.inputs.setCount(1),this.io.inputs.initInputsClonedState(Qi.FROM_NODE)}async cook(t){const e=t[0],n=e.coreObjects();for(let t of n)if(this.pv.fromAttribute)this._set_fromAttribute(t);else{this.p.color.hasExpression()?await this._eval_expressions(t):this._eval_simple_values(t)}if(!this.io.inputs.cloneRequired(0)){const t=e.geometries();for(let e of t)e.getAttribute(gZ).needsUpdate=!0}this.setCoreGroup(e)}_set_fromAttribute(t){const e=t.coreGeometry();if(!e)return;this._create_init_color(e,fZ);const n=e.points(),i=e.attribSize(this.pv.attribName),s=e.geometry(),r=s.getAttribute(this.pv.attribName).array,o=s.getAttribute(gZ).array;switch(i){case 1:for(let t=0;t{a[t.index()]=e}));else for(let t of n)e[3*t.index()+i]=r;return a}_init_array_if_required(t,e,n){const i=t.uuid,s=e[i];return s?s.length{const n=e.attribSize(t),o=new Float32Array(r*n);i.forEach(((e,i)=>{const s=e.attribValue(t);m.isNumber(s)?o[i]=s:s.toArray(o,i*n)})),s.setAttribute(t,new I$(o,n))}));return new fr(s).markAsInstance(),s}}LZ.transformAttributeNames=[CZ.POSITION,CZ.ORIENTATION,CZ.SCALE],LZ._point_color=new p.a,LZ._point_uv=new d.a,LZ._position=new p.a(0,0,0),LZ._quaternion=new hh.a,LZ._scale=new p.a(1,1,1),LZ._tmpMatrix=new A.a;class OZ extends ah{set_point(t){this._point=t,this.setDirty(),this.removeDirtyState()}value(t){return this._point?t?this._point.attribValue(t):this._point.index():this._global_index}}var PZ;!function(t){t[t.OBJECT=0]=\\\\\\\"OBJECT\\\\\\\",t[t.GEOMETRY=1]=\\\\\\\"GEOMETRY\\\\\\\"}(PZ||(PZ={}));const RZ=[PZ.OBJECT,PZ.GEOMETRY],IZ=[{name:\\\\\\\"object\\\\\\\",value:PZ.OBJECT},{name:\\\\\\\"geometry\\\\\\\",value:PZ.GEOMETRY}];const FZ=new class extends ua{constructor(){super(...arguments),this.count=ha.INTEGER(1,{range:[1,20],rangeLocked:[!0,!1]}),this.transformOnly=ha.BOOLEAN(0),this.transformMode=ha.INTEGER(0,{menu:{entries:IZ}}),this.copyAttributes=ha.BOOLEAN(0),this.attributesToCopy=ha.STRING(\\\\\\\"\\\\\\\",{visibleIf:{copyAttributes:!0}}),this.useCopyExpr=ha.BOOLEAN(0)}};class DZ extends uV{constructor(){super(...arguments),this.paramsConfig=FZ,this._attribute_names_to_copy=[],this._objects=[],this._instancer=new LZ,this._instanceMatrix=new A.a,this._object_position=new p.a}static type(){return\\\\\\\"copy\\\\\\\"}static displayedInputNames(){return[\\\\\\\"geometry to be copied\\\\\\\",\\\\\\\"points to copy to\\\\\\\"]}initializeNode(){this.io.inputs.setCount(1,2),this.io.inputs.initInputsClonedState([Qi.ALWAYS,Qi.NEVER])}async cook(t){const e=t[0];if(!this.io.inputs.has_input(1))return void await this.cook_without_template(e);const n=t[1];n?await this.cook_with_template(e,n):this.states.error.set(\\\\\\\"second input invalid\\\\\\\")}async cook_with_template(t,e){this._objects=[];const n=e.points();this._instancer.setCoreGroup(e),this._attribute_names_to_copy=ss.attribNames(this.pv.attributesToCopy).filter((t=>e.hasAttrib(t))),await this._copy_moved_objects_on_template_points(t,n),this.setObjects(this._objects)}async _copy_moved_objects_on_template_points(t,e){for(let n=0;n{const e=br.clone(t);this._objects.push(e)}))}async cook_without_template(t){this._objects=[],await this._copy_moved_objects_for_each_instance(t),this.setObjects(this._objects)}_copyAttributes_from_template(t,e){this._attribute_names_to_copy.forEach(((n,i)=>{const s=e.attribValue(n);new br(t,i).addAttribute(n,s)}))}stamp_value(t){return this.stamp_node.value(t)}get stamp_node(){return this._stamp_node=this._stamp_node||this.create_stamp_node()}create_stamp_node(){const t=new OZ(this.scene());return this.dirtyController.setForbiddenTriggerNodes([t]),t}dispose(){super.dispose(),this._stamp_node&&this._stamp_node.dispose()}}const BZ=\\\\\\\"id\\\\\\\",zZ=\\\\\\\"class\\\\\\\",kZ=\\\\\\\"html\\\\\\\";class UZ extends aV{static type(){return\\\\\\\"CSS2DObject\\\\\\\"}cook(t,e){const n=t[0];if(n){const t=this._create_objects_from_input_points(n,e);return this.createCoreGroupFromObjects(t)}{const t=this._create_object_from_scratch(e);return this.createCoreGroupFromObjects([t])}}_create_objects_from_input_points(t,e){const n=t.points(),i=[];for(let t of n){const n=e.useIdAttrib?t.attribValue(BZ):e.id,s=e.useClassAttrib?t.attribValue(zZ):e.className,r=e.useHTMLAttrib?t.attribValue(kZ):e.html,o=UZ.create_css_object({id:n,className:s,html:r}),a=o.element;if(e.copyAttributes){const n=ss.attribNames(e.attributesToCopy);for(let e of n){const n=t.attribValue(e);m.isString(n)?a.setAttribute(e,n):m.isNumber(n)&&a.setAttribute(e,`${n}`)}}o.position.copy(t.position()),o.updateMatrix(),i.push(o)}return i}_create_object_from_scratch(t){return UZ.create_css_object({id:t.id,className:t.className,html:t.html})}static create_css_object(t){const e=document.createElement(\\\\\\\"div\\\\\\\");e.id=t.id,e.className=t.className,e.innerHTML=t.html;const n=new dq(e);return n.matrixAutoUpdate=!1,n}}UZ.DEFAULT_PARAMS={useIdAttrib:!1,id:\\\\\\\"myCSSObject\\\\\\\",useClassAttrib:!1,className:\\\\\\\"CSS2DObject\\\\\\\",useHTMLAttrib:!1,html:\\\\\\\"
default html
\\\\\\\",copyAttributes:!1,attributesToCopy:\\\\\\\"\\\\\\\"},UZ.INPUT_CLONED_STATE=Qi.NEVER;const GZ=UZ.DEFAULT_PARAMS;const VZ=new class extends ua{constructor(){super(...arguments),this.useIdAttrib=ha.BOOLEAN(GZ.useIdAttrib),this.id=ha.STRING(GZ.id,{visibleIf:{useIdAttrib:0}}),this.useClassAttrib=ha.BOOLEAN(GZ.useClassAttrib),this.className=ha.STRING(GZ.className,{visibleIf:{useClassAttrib:0}}),this.useHTMLAttrib=ha.BOOLEAN(GZ.useHTMLAttrib),this.html=ha.STRING(GZ.html,{visibleIf:{useHTMLAttrib:0},multiline:!0}),this.copyAttributes=ha.BOOLEAN(GZ.copyAttributes),this.attributesToCopy=ha.STRING(GZ.attributesToCopy,{visibleIf:{copyAttributes:!0}})}};class HZ extends uV{constructor(){super(...arguments),this.paramsConfig=VZ}static type(){return\\\\\\\"CSS2DObject\\\\\\\"}initializeNode(){this.io.inputs.setCount(0,1),this.io.inputs.initInputsClonedState(UZ.INPUT_CLONED_STATE)}cook(t){this._operation=this._operation||new UZ(this.scene(),this.states);const e=this._operation.cook(t,this.pv);this.setCoreGroup(e)}}class jZ{constructor(t,e){this._size=t,this._type=e}size(){return this._size}type(){return this._type}static from_value(t){const e=m.isString(t)?zs.STRING:zs.NUMERIC;return new this(m.isArray(t)?t.length:1,e)}}class WZ{constructor(t={}){this._attribute_datas_by_name={},this._options={},this._options.dataKeysPrefix=t.dataKeysPrefix,this._options.skipEntries=t.skipEntries,this._options.doConvert=t.doConvert||!1,this._options.convertToNumeric=t.convertToNumeric}dataKeysPrefix(){return this._options.dataKeysPrefix}get_prefixed_json(t,e){if(0==e.length)return t;{const n=e.shift();if(n)return this.get_prefixed_json(t[n],e)}return[]}setJSON(t){return this._json=t}createObject(){const t=new S.a,e=new fr(t);if(null!=this._json){const n=this._json.length;e.initPositionAttribute(n),this._find_attributes();const i=ss.attribNames(this._options.convertToNumeric||\\\\\\\"\\\\\\\");for(let n of Object.keys(this._attribute_datas_by_name)){const s=Xs.remapName(n);let r=this._attribute_values_for_name(n).flat();const o=this._attribute_datas_by_name[n],a=o.size();if(o.type()===zs.STRING)if(this._options.doConvert&&ss.matchesOneMask(n,i)){const e=r.map((t=>m.isString(t)?parseFloat(t)||0:t));t.setAttribute(s,new C.c(e,a))}else{const t=Xs.arrayToIndexedArrays(r);e.setIndexedAttribute(s,t.values,t.indices)}else{const e=r;t.setAttribute(s,new C.c(e,a))}}}return t}_find_attributes(){let t;const e=ss.attribNames(this._options.skipEntries||\\\\\\\"\\\\\\\");if(this._json&&null!=(t=this._json[0]))for(let n of Object.keys(t)){const i=t[n];if(this._value_has_subentries(i))for(let t of Object.keys(i)){const s=[n,t].join(\\\\\\\":\\\\\\\"),r=i[n];ss.matchesOneMask(s,e)||(this._attribute_datas_by_name[s]=jZ.from_value(r))}else ss.matchesOneMask(n,e)||(this._attribute_datas_by_name[n]=jZ.from_value(i))}}_attribute_values_for_name(t){return this._json?this._json.map((e=>{const n=t.split(\\\\\\\":\\\\\\\")[0],i=e[n];if(this._value_has_subentries(i)){return i[t.substring(n.length+1)]||0}return i||0})):[]}_value_has_subentries(t){return m.isObject(t)&&!m.isArray(t)}}const qZ=JSON.stringify([{value:-40},{value:-30},{value:-20},{value:-10},{value:0},{value:10},{value:20},{value:30},{value:40},{value:50},{value:60},{value:70},{value:80}]);const XZ=new class extends ua{constructor(){super(...arguments),this.data=ha.STRING(qZ)}};class YZ extends uV{constructor(){super(...arguments),this.paramsConfig=XZ}static type(){return\\\\\\\"data\\\\\\\"}cook(){let t=null;try{t=JSON.parse(this.pv.data)}catch(t){this.states.error.set(\\\\\\\"could not parse json\\\\\\\")}if(t)try{const e=new WZ;e.setJSON(t);const n=e.createObject();this.setGeometry(n,Ns.POINTS)}catch(t){this.states.error.set(\\\\\\\"could not build geometry from json\\\\\\\")}else this.cookController.endCook()}}class $Z extends $g{constructor(t,e,n={},i){super(t,e,i),this._node=i,this._parser=new WZ(n)}async load(t,e,n){const i=await this._urlToLoad();fetch(i).then((async e=>{let n=await e.json();const i=this._parser.dataKeysPrefix();null!=i&&\\\\\\\"\\\\\\\"!=i&&(n=this._parser.get_prefixed_json(n,i.split(\\\\\\\".\\\\\\\"))),this._parser.setJSON(n);const s=this._parser.createObject();t(s)})).catch((t=>{li.error(\\\\\\\"error\\\\\\\",t),n(t)}))}}const JZ=\\\\\\\"position\\\\\\\";class ZZ extends $g{constructor(t,e,n,i){super(t,e,i),this.attribute_names=n,this._node=i,this.attribute_names_from_first_line=!1,this.lines=[],this.points_count=0,this.attribute_values_by_name={},this.attribute_data_by_name={},this._loading=!1,this.attribute_names||(this.attribute_names_from_first_line=!0)}async load(){if(this._loading)return void console.warn(\\\\\\\"is already loading\\\\\\\");this._loading=!0,this.points_count=0,await this.loadData(),this.infer_types(),this.read_values();return this.create_points()}async loadData(){const t=await this._urlToLoad(),e=await fetch(t),n=await e.text();this.lines=n.split(\\\\\\\"\\\\n\\\\\\\"),this.attribute_names||(this.attribute_names=this.lines[0].split(ZZ.SEPARATOR)),this.attribute_names=this.attribute_names.map((t=>Xs.remapName(t)));for(let t of this.attribute_names)this.attribute_values_by_name[t]=[]}infer_types(){const t=this.attribute_names_from_first_line?1:0;let e=this.lines[t].split(ZZ.SEPARATOR);for(let t=0;tparseFloat(t)))}return t}return t}read_values(){if(!this.attribute_names)return;let t;for(let e=this.attribute_names_from_first_line?1:0;e=this.attribute_names.length){for(let t=0;t({name:t,value:e})))}}),this.url=ha.STRING(tK,{fileBrowse:{type:[Rr.JSON]}}),this.jsonDataKeysPrefix=ha.STRING(\\\\\\\"\\\\\\\",{visibleIf:{dataType:QZ.indexOf(KZ.JSON)}}),this.skipEntries=ha.STRING(\\\\\\\"\\\\\\\",{visibleIf:{dataType:QZ.indexOf(KZ.JSON)}}),this.convert=ha.BOOLEAN(0,{visibleIf:{dataType:QZ.indexOf(KZ.JSON)}}),this.convertToNumeric=ha.STRING(\\\\\\\"\\\\\\\",{visibleIf:{dataType:QZ.indexOf(KZ.JSON),convert:1}}),this.readAttribNamesFromFile=ha.BOOLEAN(1,{visibleIf:{dataType:QZ.indexOf(KZ.CSV)}}),this.attribNames=ha.STRING(\\\\\\\"height scale\\\\\\\",{visibleIf:{dataType:QZ.indexOf(KZ.CSV),readAttribNamesFromFile:0}}),this.reload=ha.BUTTON(null,{callback:(t,e)=>{nK.PARAM_CALLBACK_reload(t,e)}})}};class nK extends uV{constructor(){super(...arguments),this.paramsConfig=eK}static type(){return\\\\\\\"dataUrl\\\\\\\"}initializeNode(){this.scene().dispatchController.onAddListener((()=>{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{this.params.label.init([this.p.url],(()=>{const t=this.p.url.rawInput();if(t){const e=t.split(\\\\\\\"/\\\\\\\");return e[e.length-1]}return\\\\\\\"\\\\\\\"}))}))}))}async cook(){this._load()}_load(){switch(QZ[this.pv.dataType]){case KZ.JSON:return this._loadJSON();case KZ.CSV:return this._loadCSV()}}_clearLoadedBlob(){switch(QZ[this.pv.dataType]){case KZ.JSON:return this._resetJSON();case KZ.CSV:return this._resetCSV()}}_url(){const t=this.scene().assets.root();return t?`${t}${this.pv.url}`:this.pv.url}_loadJSON(){new $Z(this._url(),this.scene(),{dataKeysPrefix:this.pv.jsonDataKeysPrefix,skipEntries:this.pv.skipEntries,doConvert:this.pv.convert,convertToNumeric:this.pv.convertToNumeric},this).load(this._onLoad.bind(this),void 0,this._onError.bind(this))}_resetJSON(){new $Z(this._url(),this.scene()).deregisterUrl()}_onLoad(t){this.setGeometry(t,Ns.POINTS)}_onError(t){this.states.error.set(`could not load geometry from ${this._url()} (${t})`),this.cookController.endCook()}async _loadCSV(){const t=this.pv.readAttribNamesFromFile?void 0:this.pv.attribNames.split(\\\\\\\" \\\\\\\"),e=new ZZ(this._url(),this.scene(),t,this),n=await e.load();n?this.setGeometry(n,Ns.POINTS):this.states.error.set(\\\\\\\"could not generate points\\\\\\\")}_resetCSV(){new ZZ(this._url(),this.scene(),[],this).deregisterUrl()}static PARAM_CALLBACK_reload(t,e){t.param_callback_reload()}param_callback_reload(){this._clearLoadedBlob(),this.p.url.setDirty()}}class iK extends S.a{constructor(t,e,n,i){super();const s=[],r=[],o=[],a=new p.a,l=new A.a;l.makeRotationFromEuler(n),l.setPosition(e);const c=new A.a;function h(e,n,i){n.applyMatrix4(t.matrixWorld),n.applyMatrix4(c),i.transformDirection(t.matrixWorld),e.push(new sK(n.clone(),i.clone()))}function u(t,e){const n=[],s=.5*Math.abs(i.dot(e));for(let i=0;i0,u=t[i+1].position.dot(e)-s>0,p=t[i+2].position.dot(e)-s>0;switch(c=(h?1:0)+(u?1:0)+(p?1:0),c){case 0:n.push(t[i]),n.push(t[i+1]),n.push(t[i+2]);break;case 1:if(h&&(r=t[i+1],o=t[i+2],a=d(t[i],r,e,s),l=d(t[i],o,e,s)),u){r=t[i],o=t[i+2],a=d(t[i+1],r,e,s),l=d(t[i+1],o,e,s),n.push(a),n.push(o.clone()),n.push(r.clone()),n.push(o.clone()),n.push(a.clone()),n.push(l);break}p&&(r=t[i],o=t[i+1],a=d(t[i+2],r,e,s),l=d(t[i+2],o,e,s)),n.push(r.clone()),n.push(o.clone()),n.push(a),n.push(l),n.push(a.clone()),n.push(o.clone());break;case 2:h||(r=t[i].clone(),o=d(r,t[i+1],e,s),a=d(r,t[i+2],e,s),n.push(r),n.push(o),n.push(a)),u||(r=t[i+1].clone(),o=d(r,t[i+2],e,s),a=d(r,t[i],e,s),n.push(r),n.push(o),n.push(a)),p||(r=t[i+2].clone(),o=d(r,t[i],e,s),a=d(r,t[i+1],e,s),n.push(r),n.push(o),n.push(a))}}return n}function d(t,e,n,i){const s=t.position.dot(n)-i,r=s/(s-(e.position.dot(n)-i));return new sK(new p.a(t.position.x+r*(e.position.x-t.position.x),t.position.y+r*(e.position.y-t.position.y),t.position.z+r*(e.position.z-t.position.z)),new p.a(t.normal.x+r*(e.normal.x-t.normal.x),t.normal.y+r*(e.normal.y-t.normal.y),t.normal.z+r*(e.normal.z-t.normal.z)))}c.copy(l).invert(),function(){let e=[];const n=new p.a,c=new p.a;if(!0===t.geometry.isGeometry)return void console.error(\\\\\\\"THREE.DecalGeometry no longer supports THREE.Geometry. Use BufferGeometry instead.\\\\\\\");const d=t.geometry,_=d.attributes.position,m=d.attributes.normal;if(null!==d.index){const t=d.index;for(let i=0;i{this.setCoreGroup(e)}),Math.max(this.pv.duration,0))}}class uK{constructor(t){this.node=t,this.selected_state=new Map,this._entities_count=0,this._selected_entities_count=0}init(t){this.selected_state.clear();for(let e of t)this.selected_state.set(e,!1);this._entities_count=t.length,this._selected_entities_count=0}select(t){const e=this.selected_state.get(t);null!=e&&0==e&&(this.selected_state.set(t,!0),this._selected_entities_count++)}entities_to_keep(){return this._entities_for_state(this.node.pv.invert)}entities_to_delete(){return this._entities_for_state(!this.node.pv.invert)}_entities_for_state(t){const e=!!t,n=t?this._selected_entities_count:this._entities_count-this._selected_entities_count;if(0==n)return[];{const t=new Array(n);let i=0;return this.selected_state.forEach(((n,s)=>{n==e&&(t[i]=s,i++)})),t}}}var dK;!function(t){t.EQUAL=\\\\\\\"==\\\\\\\",t.LESS_THAN=\\\\\\\"<\\\\\\\",t.EQUAL_OR_LESS_THAN=\\\\\\\"<=\\\\\\\",t.EQUAL_OR_GREATER_THAN=\\\\\\\">=\\\\\\\",t.GREATER_THAN=\\\\\\\">\\\\\\\",t.DIFFERENT=\\\\\\\"!=\\\\\\\"}(dK||(dK={}));const pK=[dK.EQUAL,dK.LESS_THAN,dK.EQUAL_OR_LESS_THAN,dK.EQUAL_OR_GREATER_THAN,dK.GREATER_THAN,dK.DIFFERENT],_K={[dK.EQUAL]:(t,e)=>t==e,[dK.LESS_THAN]:(t,e)=>tt<=e,[dK.EQUAL_OR_GREATER_THAN]:(t,e)=>t>=e,[dK.GREATER_THAN]:(t,e)=>t>e,[dK.DIFFERENT]:(t,e)=>t!=e},mK=pK.map(((t,e)=>({name:t,value:e})));class fK{constructor(t){this.node=t}evalForEntities(t){const e=ks[this.node.pv.attribType];switch(e){case zs.NUMERIC:return void this._eval_for_numeric(t);case zs.STRING:return void this._eval_for_string(t)}os.unreachable(e)}_eval_for_string(t){let e;for(let n of t)e=n.stringAttribValue(this.node.pv.attribName),e==this.node.pv.attribString&&this.node.entitySelectionHelper.select(n)}_eval_for_numeric(t){const e=Vs[this.node.pv.attribSize-1];switch(e){case Gs.FLOAT:return this._eval_for_points_numeric_float(t);case Gs.VECTOR2:return this._eval_for_points_numeric_vector2(t);case Gs.VECTOR3:return this._eval_for_points_numeric_vector3(t);case Gs.VECTOR4:return this._eval_for_points_numeric_vector4(t)}os.unreachable(e)}_eval_for_points_numeric_float(t){let e=this.node.pv.attribName;const n=this.node.pv.attribValue1;let i;const s=pK[this.node.pv.attribComparisonOperator],r=_K[s];for(let s of t)i=s.attribValue(e),r(i,n)&&this.node.entitySelectionHelper.select(s)}_eval_for_points_numeric_vector2(t){let e=this.node.pv.attribName;const n=this.node.pv.attribValue2;let i=new d.a;for(let s of t){const t=s.attribValue(e,i);n.equals(t)&&this.node.entitySelectionHelper.select(s)}}_eval_for_points_numeric_vector3(t){let e=this.node.pv.attribName;const n=this.node.pv.attribValue3;let i=new p.a;for(let s of t){const t=s.attribValue(e,i);n.equals(t)&&this.node.entitySelectionHelper.select(s)}}_eval_for_points_numeric_vector4(t){let e=this.node.pv.attribName;const n=this.node.pv.attribValue4;let i=new _.a;for(let s of t){const t=s.attribValue(e,i);n.equals(t)&&this.node.entitySelectionHelper.select(s)}}}class gK{constructor(t){this.node=t}async evalForEntities(t){const e=this.node.p.expression;this.node.p.expression.hasExpression()&&e.expressionController?await this.eval_expressions_for_points_with_expression(t):this.eval_expressions_without_expression(t)}async eval_expressions_for_points_with_expression(t){const e=this.node.p.expression;e.expressionController&&await e.expressionController.computeExpressionForEntities(t,((t,e)=>{e&&this.node.entitySelectionHelper.select(t)}))}eval_expressions_without_expression(t){if(this.node.pv.expression)for(let e of t)this.node.entitySelectionHelper.select(e)}}class vK{constructor(t){this.node=t,this._point_position=new p.a}evalForPoints(t){const e=this._createBbox();for(let n of t){e.containsPoint(n.getPosition(this._point_position))&&this.node.entitySelectionHelper.select(n)}}_createBbox(){return new Ry.a(this.node.pv.bboxCenter.clone().sub(this.node.pv.bboxSize.clone().multiplyScalar(.5)),this.node.pv.bboxCenter.clone().add(this.node.pv.bboxSize.clone().multiplyScalar(.5)))}}class yK{constructor(t){this.node=t}eval_for_objects(t){const e=Ps[this.node.pv.objectType];for(let n of t){Os(n.object().constructor)==e&&this.node.entitySelectionHelper.select(n)}}}class xK{constructor(){this._sidePropertyByMaterial=new WeakMap,this._bound_setMat=this._setObjectMaterialDoubleSided.bind(this),this._bound_restoreMat=this._restoreObjectMaterialSide.bind(this)}setCoreGroupMaterialDoubleSided(t){const e=t.objects();for(let t of e)t.traverse(this._bound_setMat)}restoreMaterialSideProperty(t){const e=t.objects();for(let t of e)t.traverse(this._bound_restoreMat)}_setObjectMaterialDoubleSided(t){const e=t.material;if(e)if(m.isArray(e))for(let t of e)this._setMaterialDoubleSided(t);else this._setMaterialDoubleSided(e)}_restoreObjectMaterialSide(t){const e=t.material;if(e)if(m.isArray(e))for(let t of e)this._restoreMaterialDoubleSided(t);else this._restoreMaterialDoubleSided(e)}_setMaterialDoubleSided(t){this._sidePropertyByMaterial.set(t,t.side),t.side=w.z}_restoreMaterialDoubleSided(t){t.side=this._sidePropertyByMaterial.get(t)||w.z}}const bK=new p.a(0,1,0),wK=new p.a(0,-1,0);class TK{constructor(t){this.node=t,this._matDoubleSideTmpSetter=new xK,this._point_position=new p.a,this._raycaster=new eO,this._intersections=[]}evalForPoints(t,e){if(!e)return;const n=null==e?void 0:e.objectsWithGeo()[0];if(!n)return;const i=n;if(!i.isMesh)return;this._matDoubleSideTmpSetter.setCoreGroupMaterialDoubleSided(e);const s=n.geometry;s.computeBoundingBox();const r=s.boundingBox;for(let e of t)e.getPosition(this._point_position),r.containsPoint(this._point_position)?this._isPositionInObject(this._point_position,i,bK)&&this._isPositionInObject(this._point_position,i,wK)&&this.node.entitySelectionHelper.select(e):this.node.entitySelectionHelper.select(e);this._matDoubleSideTmpSetter.restoreMaterialSideProperty(e)}_isPositionInObject(t,e,n){var i;this._raycaster.ray.direction.copy(n),this._raycaster.ray.origin.copy(t),this._intersections.length=0;const s=this._raycaster.intersectObject(e,!1,this._intersections);if(!s)return!1;if(0==s.length)return!1;const r=null===(i=s[0].face)||void 0===i?void 0:i.normal;if(!r)return!1;return this._raycaster.ray.direction.dot(r)>=0}}const AK=new class extends ua{constructor(){super(...arguments),this.class=ha.INTEGER(Ds.indexOf(Fs.VERTEX),{menu:{entries:Bs}}),this.invert=ha.BOOLEAN(0),this.byObjectType=ha.BOOLEAN(0,{visibleIf:{class:Ds.indexOf(Fs.OBJECT)}}),this.objectType=ha.INTEGER(Ps.indexOf(Ns.MESH),{menu:{entries:Rs},visibleIf:{class:Ds.indexOf(Fs.OBJECT),byObjectType:!0},separatorAfter:!0}),this.byExpression=ha.BOOLEAN(0),this.expression=ha.BOOLEAN(\\\\\\\"@ptnum==0\\\\\\\",{visibleIf:{byExpression:!0},expression:{forEntities:!0},separatorAfter:!0}),this.byAttrib=ha.BOOLEAN(0),this.attribType=ha.INTEGER(ks.indexOf(zs.NUMERIC),{menu:{entries:Us},visibleIf:{byAttrib:1}}),this.attribName=ha.STRING(\\\\\\\"\\\\\\\",{visibleIf:{byAttrib:1}}),this.attribSize=ha.INTEGER(1,{range:Hs,rangeLocked:[!0,!0],visibleIf:{byAttrib:1,attribType:ks.indexOf(zs.NUMERIC)}}),this.attribComparisonOperator=ha.INTEGER(pK.indexOf(dK.EQUAL),{menu:{entries:mK},visibleIf:{byAttrib:!0,attribType:ks.indexOf(zs.NUMERIC),attribSize:Gs.FLOAT}}),this.attribValue1=ha.FLOAT(0,{visibleIf:{byAttrib:1,attribType:ks.indexOf(zs.NUMERIC),attribSize:1}}),this.attribValue2=ha.VECTOR2([0,0],{visibleIf:{byAttrib:1,attribType:ks.indexOf(zs.NUMERIC),attribSize:2}}),this.attribValue3=ha.VECTOR3([0,0,0],{visibleIf:{byAttrib:1,attribType:ks.indexOf(zs.NUMERIC),attribSize:3}}),this.attribValue4=ha.VECTOR4([0,0,0,0],{visibleIf:{byAttrib:1,attribType:ks.indexOf(zs.NUMERIC),attribSize:4}}),this.attribString=ha.STRING(\\\\\\\"\\\\\\\",{visibleIf:{byAttrib:1,attribType:ks.indexOf(zs.STRING)},separatorAfter:!0}),this.byBbox=ha.BOOLEAN(0,{visibleIf:{class:Ds.indexOf(Fs.VERTEX)}}),this.bboxSize=ha.VECTOR3([1,1,1],{visibleIf:{class:Ds.indexOf(Fs.VERTEX),byBbox:!0}}),this.bboxCenter=ha.VECTOR3([0,0,0],{visibleIf:{class:Ds.indexOf(Fs.VERTEX),byBbox:!0},separatorAfter:!0}),this.byBoundingObject=ha.BOOLEAN(0,{visibleIf:{class:Ds.indexOf(Fs.VERTEX)}}),this.keepPoints=ha.BOOLEAN(0,{visibleIf:{class:Ds.indexOf(Fs.OBJECT)}})}};class MK extends uV{constructor(){super(...arguments),this.paramsConfig=AK,this._marked_for_deletion_per_object_index=new Map,this.entitySelectionHelper=new uK(this),this.byExpressionHelper=new gK(this),this.byAttributeHelper=new fK(this),this.byObjectTypeHelper=new yK(this),this.byBboxHelper=new vK(this),this.byBoundingObjectHelper=new TK(this)}static type(){return\\\\\\\"delete\\\\\\\"}static displayedInputNames(){return[\\\\\\\"geometry to delete from\\\\\\\",\\\\\\\"points inside this geometry will be deleted (optional)\\\\\\\"]}initializeNode(){this.io.inputs.setCount(1,2),this.io.inputs.initInputsClonedState(Qi.FROM_NODE)}async cook(t){const e=t[0],n=t[1];switch(this.pv.class){case Fs.VERTEX:await this._eval_for_points(e,n);break;case Fs.OBJECT:await this._eval_for_objects(e)}}set_class(t){this.p.class.set(t)}async _eval_for_objects(t){const e=t.coreObjects();this.entitySelectionHelper.init(e),this._marked_for_deletion_per_object_index=new Map;for(let t of e)this._marked_for_deletion_per_object_index.set(t.index(),!1);this.pv.byExpression&&await this.byExpressionHelper.evalForEntities(e),this.pv.byObjectType&&this.byObjectTypeHelper.eval_for_objects(e),this.pv.byAttrib&&\\\\\\\"\\\\\\\"!=this.pv.attribName&&this.byAttributeHelper.evalForEntities(e);const n=this.entitySelectionHelper.entities_to_keep().map((t=>t.object()));if(this.pv.keepPoints){const t=this.entitySelectionHelper.entities_to_delete();for(let e of t){const t=this._point_object(e);t&&n.push(t)}}this.setObjects(n)}async _eval_for_points(t,e){const n=t.coreObjects();let i,s=[];for(let t=0;t0){const e=fr.geometryFromPoints(a,Os(t.constructor));e&&(t.geometry=e,s.push(t))}}}this.setObjects(s)}_point_object(t){const e=t.points(),n=fr.geometryFromPoints(e,Ns.POINTS);if(n)return this.createObject(n,Ns.POINTS)}}const EK=new class extends ua{constructor(){super(...arguments),this.start=ha.INTEGER(0,{range:[0,100],rangeLocked:[!0,!1]}),this.useCount=ha.BOOLEAN(0),this.count=ha.INTEGER(0,{range:[0,100],rangeLocked:[!0,!1],visibleIf:{useCount:1}})}};class SK extends uV{constructor(){super(...arguments),this.paramsConfig=EK}static type(){return\\\\\\\"drawRange\\\\\\\"}initializeNode(){this.io.inputs.setCount(0,1),this.io.inputs.initInputsClonedState(Qi.FROM_NODE)}cook(t){const e=t[0],n=e.objects();for(let t of n){const e=t.geometry;if(e){const t=e.drawRange;t.start=this.pv.start,this.pv.useCount?t.count=this.pv.count:t.count=1/0}}this.setCoreGroup(e)}}class CK{constructor(){this.pluginCallbacks=[],this.register((function(t){return new nQ(t)})),this.register((function(t){return new iQ(t)})),this.register((function(t){return new sQ(t)})),this.register((function(t){return new rQ(t)})),this.register((function(t){return new oQ(t)}))}register(t){return-1===this.pluginCallbacks.indexOf(t)&&this.pluginCallbacks.push(t),this}unregister(t){return-1!==this.pluginCallbacks.indexOf(t)&&this.pluginCallbacks.splice(this.pluginCallbacks.indexOf(t),1),this}parse(t,e,n){const i=new eQ,s=[];for(let t=0,e=this.pluginCallbacks.length;t0&&(this.options.trs=!0),this.processInput(t);const i=this;Promise.all(this.pending).then((function(){const t=i.buffers,n=i.json,s=i.options,r=i.extensionsUsed,o=new Blob(t,{type:\\\\\\\"application/octet-stream\\\\\\\"}),a=Object.keys(r);if(a.length>0&&(n.extensionsUsed=a),n.buffers&&n.buffers.length>0&&(n.buffers[0].byteLength=o.size),!0===s.binary){const t=new window.FileReader;t.readAsArrayBuffer(o),t.onloadend=function(){const i=QK(t.result),s=new DataView(new ArrayBuffer(8));s.setUint32(0,i.byteLength,!0),s.setUint32(4,5130562,!0);const r=QK(function(t){if(void 0!==window.TextEncoder)return(new TextEncoder).encode(t).buffer;const e=new Uint8Array(new ArrayBuffer(t.length));for(let n=0,i=t.length;n255?32:i}return e.buffer}(JSON.stringify(n)),32),o=new DataView(new ArrayBuffer(8));o.setUint32(0,r.byteLength,!0),o.setUint32(4,1313821514,!0);const a=new ArrayBuffer(12),l=new DataView(a);l.setUint32(0,1179937895,!0),l.setUint32(4,2,!0);const c=12+o.byteLength+r.byteLength+s.byteLength+i.byteLength;l.setUint32(8,c,!0);const h=new Blob([a,o,r,s,i],{type:\\\\\\\"application/octet-stream\\\\\\\"}),u=new window.FileReader;u.readAsArrayBuffer(h),u.onloadend=function(){e(u.result)}}}else if(n.buffers&&n.buffers.length>0){const t=new window.FileReader;t.readAsDataURL(o),t.onloadend=function(){const i=t.result;n.buffers[0].uri=i,e(n)}}else e(n)}))}serializeUserData(t,e){if(0===Object.keys(t.userData).length)return;const n=this.options,i=this.extensionsUsed;try{const s=JSON.parse(JSON.stringify(t.userData));if(n.includeCustomExtensions&&s.gltfExtensions){void 0===e.extensions&&(e.extensions={});for(const t in s.gltfExtensions)e.extensions[t]=s.gltfExtensions[t],i[t]=!0;delete s.gltfExtensions}Object.keys(s).length>0&&(e.extras=s)}catch(e){console.warn(\\\\\\\"THREE.GLTFExporter: userData of '\\\\\\\"+t.name+\\\\\\\"' won't be serialized because of JSON.stringify error - \\\\\\\"+e.message)}}getUID(t){return this.uids.has(t)||this.uids.set(t,this.uid++),this.uids.get(t)}isNormalizedNormalAttribute(t){if(this.cache.attributesNormalized.has(t))return!1;const e=new Sb;for(let n=0,i=t.count;n5e-4)return!1;return!0}createNormalizedNormalAttribute(t){const e=this.cache;if(e.attributesNormalized.has(t))return e.attributesNormalized.get(t);const n=t.clone(),i=new Sb;for(let t=0,e=n.count;t4?i=t.array[s*t.itemSize+n]:0===n?i=t.getX(s):1===n?i=t.getY(s):2===n?i=t.getZ(s):3===n&&(i=t.getW(s)),e===DK?l.setFloat32(c,i,!0):e===BK?l.setUint32(c,i,!0):e===FK?l.setUint16(c,i,!0):e===IK&&l.setUint8(c,i),c+=o}const h={buffer:this.processBuffer(l.buffer),byteOffset:this.byteOffset,byteLength:a};void 0!==s&&(h.target=s),s===zK&&(h.byteStride=t.itemSize*o),this.byteOffset+=a,r.bufferViews.push(h);return{id:r.bufferViews.length-1,byteLength:0}}processBufferViewImage(t){const e=this,n=e.json;return n.bufferViews||(n.bufferViews=[]),new Promise((function(i){const s=new window.FileReader;s.readAsArrayBuffer(t),s.onloadend=function(){const t=QK(s.result),r={buffer:e.processBuffer(t),byteOffset:e.byteOffset,byteLength:t.byteLength};e.byteOffset+=t.byteLength,i(n.bufferViews.push(r)-1)}}))}processAccessor(t,e,n,i){const s=this.options,r=this.json;let o;if(t.array.constructor===Float32Array)o=DK;else if(t.array.constructor===Uint32Array)o=BK;else if(t.array.constructor===Uint16Array)o=FK;else{if(t.array.constructor!==Uint8Array)throw new Error(\\\\\\\"THREE.GLTFExporter: Unsupported bufferAttribute component type.\\\\\\\");o=IK}if(void 0===n&&(n=0),void 0===i&&(i=t.count),s.truncateDrawRange&&void 0!==e&&null===e.index){const s=n+i,r=e.drawRange.count===1/0?t.count:e.drawRange.start+e.drawRange.count;n=Math.max(n,e.drawRange.start),(i=Math.min(s,r)-n)<0&&(i=0)}if(0===i)return null;const a=function(t,e,n){const i={min:new Array(t.itemSize).fill(Number.POSITIVE_INFINITY),max:new Array(t.itemSize).fill(Number.NEGATIVE_INFINITY)};for(let s=e;s4?n=t.array[s*t.itemSize+e]:0===e?n=t.getX(s):1===e?n=t.getY(s):2===e?n=t.getZ(s):3===e&&(n=t.getW(s)),i.min[e]=Math.min(i.min[e],n),i.max[e]=Math.max(i.max[e],n)}return i}(t,n,i);let l;void 0!==e&&(l=t===e.index?kK:zK);const c=this.processBufferView(t,o,n,i,l),h={bufferView:c.id,byteOffset:c.byteOffset,componentType:o,count:i,max:a.max,min:a.min,type:{1:\\\\\\\"SCALAR\\\\\\\",2:\\\\\\\"VEC2\\\\\\\",3:\\\\\\\"VEC3\\\\\\\",4:\\\\\\\"VEC4\\\\\\\",16:\\\\\\\"MAT4\\\\\\\"}[t.itemSize]};return!0===t.normalized&&(h.normalized=!0),r.accessors||(r.accessors=[]),r.accessors.push(h)-1}processImage(t,e,n){const i=this,s=i.cache,r=i.json,o=i.options,a=i.pending;s.images.has(t)||s.images.set(t,{});const l=s.images.get(t),c=e===Dx?\\\\\\\"image/png\\\\\\\":\\\\\\\"image/jpeg\\\\\\\",h=c+\\\\\\\":flipY/\\\\\\\"+n.toString();if(void 0!==l[h])return l[h];r.images||(r.images=[]);const u={mimeType:c};if(o.embedImages){const s=tQ=tQ||document.createElement(\\\\\\\"canvas\\\\\\\");s.width=Math.min(t.width,o.maxTextureSize),s.height=Math.min(t.height,o.maxTextureSize);const r=s.getContext(\\\\\\\"2d\\\\\\\");if(!0===n&&(r.translate(0,s.height),r.scale(1,-1)),\\\\\\\"undefined\\\\\\\"!=typeof HTMLImageElement&&t instanceof HTMLImageElement||\\\\\\\"undefined\\\\\\\"!=typeof HTMLCanvasElement&&t instanceof HTMLCanvasElement||\\\\\\\"undefined\\\\\\\"!=typeof OffscreenCanvas&&t instanceof OffscreenCanvas||\\\\\\\"undefined\\\\\\\"!=typeof ImageBitmap&&t instanceof ImageBitmap)r.drawImage(t,0,0,s.width,s.height);else{e!==Dx&&e!==Fx&&console.error(\\\\\\\"GLTFExporter: Only RGB and RGBA formats are supported.\\\\\\\"),(t.width>o.maxTextureSize||t.height>o.maxTextureSize)&&console.warn(\\\\\\\"GLTFExporter: Image size is bigger than maxTextureSize\\\\\\\",t);const n=new Uint8ClampedArray(t.height*t.width*4);if(e===Dx)for(let e=0;e1&&(e.multiplyScalar(1/n),console.warn(\\\\\\\"THREE.GLTFExporter: Some emissive components exceed 1; emissive has been limited\\\\\\\")),n>0&&(i.emissiveFactor=e.toArray()),t.emissiveMap){const e={index:this.processTexture(t.emissiveMap)};this.applyTextureTransform(e,t.emissiveMap),i.emissiveTexture=e}}if(t.normalMap){const e={index:this.processTexture(t.normalMap)};t.normalScale&&1!==t.normalScale.x&&(e.scale=t.normalScale.x),this.applyTextureTransform(e,t.normalMap),i.normalTexture=e}if(t.aoMap){const e={index:this.processTexture(t.aoMap),texCoord:1};1!==t.aoMapIntensity&&(e.strength=t.aoMapIntensity),this.applyTextureTransform(e,t.aoMap),i.occlusionTexture=e}t.transparent?i.alphaMode=\\\\\\\"BLEND\\\\\\\":t.alphaTest>0&&(i.alphaMode=\\\\\\\"MASK\\\\\\\",i.alphaCutoff=t.alphaTest),2===t.side&&(i.doubleSided=!0),\\\\\\\"\\\\\\\"!==t.name&&(i.name=t.name),this.serializeUserData(t,i),this._invokeAll((function(e){e.writeMaterial&&e.writeMaterial(t,i)}));const r=n.materials.push(i)-1;return e.materials.set(t,r),r}processMesh(t){const e=this.cache,n=this.json,i=[t.geometry.uuid];if(Array.isArray(t.material))for(let e=0,n=t.material.length;e0){const n=[],i=[],s={};if(void 0!==t.morphTargetDictionary)for(const e in t.morphTargetDictionary)s[t.morphTargetDictionary[e]]=e;for(let o=0;o0&&(a.extras={},a.extras.targetNames=i)}const _=Array.isArray(t.material);if(_&&0===r.groups.length)return null;const m=_?t.material:[t.material],f=_?r.groups:[{materialIndex:0,start:void 0,count:void 0}];for(let t=0,n=f.length;t0&&(n.targets=h),null!==r.index){let i=this.getUID(r.index);void 0===f[t].start&&void 0===f[t].count||(i+=\\\\\\\":\\\\\\\"+f[t].start+\\\\\\\":\\\\\\\"+f[t].count),e.attributes.has(i)?n.indices=e.attributes.get(i):(n.indices=this.processAccessor(r.index,r,f[t].start,f[t].count),e.attributes.set(i,n.indices)),null===n.indices&&delete n.indices}const i=this.processMaterial(m[f[t].materialIndex]);null!==i&&(n.material=i),c.push(n)}a.primitives=c,n.meshes||(n.meshes=[]),this._invokeAll((function(e){e.writeMesh&&e.writeMesh(t,a)}));const g=n.meshes.push(a)-1;return e.meshes.set(s,g),g}processCamera(t){const e=this.json;e.cameras||(e.cameras=[]);const n=t.isOrthographicCamera,i={type:n?\\\\\\\"orthographic\\\\\\\":\\\\\\\"perspective\\\\\\\"};return n?i.orthographic={xmag:2*t.right,ymag:2*t.top,zfar:t.far<=0?.001:t.far,znear:t.near<0?0:t.near}:i.perspective={aspectRatio:t.aspect,yfov:pb.degToRad(t.fov),zfar:t.far<=0?.001:t.far,znear:t.near<0?0:t.near},\\\\\\\"\\\\\\\"!==t.name&&(i.name=t.type),e.cameras.push(i)-1}processAnimation(t,e){const n=this.json,i=this.nodeMap;n.animations||(n.animations=[]);const s=(t=CK.Utils.mergeMorphTargetTracks(t.clone(),e)).tracks,r=[],o=[];for(let t=0;t0){const e=[];for(let i=0,s=t.children.length;i0&&(s.children=e)}this._invokeAll((function(e){e.writeNode&&e.writeNode(t,s)}));const r=e.nodes.push(s)-1;return i.set(t,r),r}processScene(t){const e=this.json,n=this.options;e.scenes||(e.scenes=[],e.scene=0);const i={};\\\\\\\"\\\\\\\"!==t.name&&(i.name=t.name),e.scenes.push(i);const s=[];for(let e=0,i=t.children.length;e0&&(i.nodes=s),this.serializeUserData(t,i)}processObjects(t){const e=new zE;e.name=\\\\\\\"AuxScene\\\\\\\";for(let n=0;n0&&this.processObjects(n);for(let t=0;t0&&(r.range=t.distance)):t.isSpotLight&&(r.type=\\\\\\\"spot\\\\\\\",t.distance>0&&(r.range=t.distance),r.spot={},r.spot.innerConeAngle=(t.penumbra-1)*t.angle*-1,r.spot.outerConeAngle=t.angle),void 0!==t.decay&&2!==t.decay&&console.warn(\\\\\\\"THREE.GLTFExporter: Light decay may be lost. glTF is physically-based, and expects light.decay=2.\\\\\\\"),!t.target||t.target.parent===t&&0===t.target.position.x&&0===t.target.position.y&&-1===t.target.position.z||console.warn(\\\\\\\"THREE.GLTFExporter: Light direction may be lost. For best results, make light.target a child of the light with position 0,0,-1.\\\\\\\"),s[this.name]||(i.extensions=i.extensions||{},i.extensions[this.name]={lights:[]},s[this.name]=!0);const o=i.extensions[this.name].lights;o.push(r),e.extensions=e.extensions||{},e.extensions[this.name]={light:o.length-1}}}class iQ{constructor(t){this.writer=t,this.name=\\\\\\\"KHR_materials_unlit\\\\\\\"}writeMaterial(t,e){if(!t.isMeshBasicMaterial)return;const n=this.writer.extensionsUsed;e.extensions=e.extensions||{},e.extensions[this.name]={},n[this.name]=!0,e.pbrMetallicRoughness.metallicFactor=0,e.pbrMetallicRoughness.roughnessFactor=.9}}class sQ{constructor(t){this.writer=t,this.name=\\\\\\\"KHR_materials_pbrSpecularGlossiness\\\\\\\"}writeMaterial(t,e){if(!t.isGLTFSpecularGlossinessMaterial)return;const n=this.writer,i=n.extensionsUsed,s={};e.pbrMetallicRoughness.baseColorFactor&&(s.diffuseFactor=e.pbrMetallicRoughness.baseColorFactor);const r=[1,1,1];if(t.specular.toArray(r,0),s.specularFactor=r,s.glossinessFactor=t.glossiness,e.pbrMetallicRoughness.baseColorTexture&&(s.diffuseTexture=e.pbrMetallicRoughness.baseColorTexture),t.specularMap){const e={index:n.processTexture(t.specularMap)};n.applyTextureTransform(e,t.specularMap),s.specularGlossinessTexture=e}e.extensions=e.extensions||{},e.extensions[this.name]=s,i[this.name]=!0}}class rQ{constructor(t){this.writer=t,this.name=\\\\\\\"KHR_materials_transmission\\\\\\\"}writeMaterial(t,e){if(!t.isMeshPhysicalMaterial||0===t.transmission)return;const n=this.writer,i=n.extensionsUsed,s={};if(s.transmissionFactor=t.transmission,t.transmissionMap){const e={index:n.processTexture(t.transmissionMap)};n.applyTextureTransform(e,t.transmissionMap),s.transmissionTexture=e}e.extensions=e.extensions||{},e.extensions[this.name]=s,i[this.name]=!0}}class oQ{constructor(t){this.writer=t,this.name=\\\\\\\"KHR_materials_volume\\\\\\\"}writeMaterial(t,e){if(!t.isMeshPhysicalMaterial||0===t.thickness)return;const n=this.writer,i=n.extensionsUsed,s={};if(s.thicknessFactor=t.thickness,t.thicknessMap){const e={index:n.processTexture(t.thicknessMap)};n.applyTextureTransform(e,t.thicknessMap),s.thicknessTexture=e}s.attenuationDistance=t.attenuationDistance,s.attenuationColor=t.attenuationTint.toArray(),e.extensions=e.extensions||{},e.extensions[this.name]=s,i[this.name]=!0}}function aQ(t,e){const n=document.createElement(\\\\\\\"a\\\\\\\");n.style.display=\\\\\\\"none\\\\\\\",document.body.appendChild(n),n.href=URL.createObjectURL(t),n.download=e,n.click(),setTimeout((()=>{document.body.removeChild(n)}),10)}CK.Utils={insertKeyframe:function(t,e){const n=.001,i=t.getValueSize(),s=new t.TimeBufferType(t.times.length+1),r=new t.ValueBufferType(t.values.length+i),o=t.createInterpolant(new t.ValueBufferType(i));let a;if(0===t.times.length){s[0]=e;for(let t=0;tt.times[t.times.length-1]){if(Math.abs(t.times[t.times.length-1]-e)e){s.set(t.times.slice(0,l+1),0),s[l+1]=e,s.set(t.times.slice(l+1),l+2),r.set(t.values.slice(0,(l+1)*i),0),r.set(o.evaluate(e),(l+1)*i),r.set(t.values.slice((l+1)*i),(l+2)*i),a=l+1;break}}return t.times=s,t.values=r,a},mergeMorphTargetTracks:function(t,e){const n=[],i={},s=t.tracks;for(let t=0;t{cQ.PARAM_CALLBACK_export(t)}})}};class cQ extends uV{constructor(){super(...arguments),this.paramsConfig=lQ}static type(){return\\\\\\\"exporter\\\\\\\"}initializeNode(){this.io.inputs.setCount(1),this.io.inputs.initInputsClonedState(Qi.NEVER)}async cook(t){this.setCoreGroup(t[0])}static PARAM_CALLBACK_export(t){t._paramCallbackExport()}async _paramCallbackExport(){const t=(await this.compute()).coreContent();if(!t)return void console.error(\\\\\\\"input invalid\\\\\\\");const e=new WeakMap,n=t.objects();for(let t of n)e.set(t,t.parent);const i=new vs;for(let t of n)i.add(t);(new CK).parse(i,(t=>{if(t instanceof ArrayBuffer)i=\\\\\\\"scene.glb\\\\\\\",aQ(new Blob([t],{type:\\\\\\\"application/octet-stream\\\\\\\"}),i);else{!function(t,e){aQ(new Blob([t],{type:\\\\\\\"text/plain\\\\\\\"}),e)}(JSON.stringify(t,null,2),\\\\\\\"scene.gltf\\\\\\\")}var i;for(let t of n){const n=e.get(t);n&&n.add(t)}}),{embedImages:!0})}}const hQ=new class extends ua{constructor(){super(...arguments),this.makeFacesUnique=ha.BOOLEAN(0),this.addFaceCenterAttribute=ha.BOOLEAN(0,{visibleIf:{makeFacesUnique:1}}),this.addFaceId=ha.BOOLEAN(0,{visibleIf:{makeFacesUnique:1}}),this.transform=ha.BOOLEAN(0,{visibleIf:{makeFacesUnique:1}}),this.scale=ha.FLOAT(1,{visibleIf:{makeFacesUnique:1,transform:1}})}};class uQ extends uV{constructor(){super(...arguments),this.paramsConfig=hQ}static type(){return\\\\\\\"face\\\\\\\"}initializeNode(){this.io.inputs.setCount(1),this.io.inputs.initInputsClonedState(Qi.FROM_NODE)}cook(t){const e=t[0];this.pv.makeFacesUnique&&(this._makeFacesUnique(e),this.pv.addFaceCenterAttribute&&this._addFaceCenterAttribute(e),this.pv.addFaceId&&this._addFaceId(e),this.pv.transform&&this._transform_faces(e)),this.setCoreGroup(e)}_makeFacesUnique(t){var e;for(let n of t.objects())if(n.isMesh){const t=n.geometry,i=f.chunk((null===(e=t.index)||void 0===e?void 0:e.array)||[],3),s=3*i.length;for(let e of Object.keys(t.attributes)){const n=t.attributes[e],r=n.itemSize,o=new Float32Array(s*r);let a=0;i.forEach((t=>{t.forEach((t=>{for(let e=0;e{const a=t.object(),l=t.coreGeometry();if(a.isMesh&&l){i=l.faces(),l.hasAttrib(e)||l.addNumericAttrib(e,3,-1);for(let t=0;t{const n=t.object(),i=t.coreGeometry();if(n.isMesh&&i){const t=i.faces();i.hasAttrib(e)||i.addNumericAttrib(e,1,-1);for(let n=0;n{const c=t.object(),h=t.coreGeometry();if(c.isMesh&&h){r=h.faces(),h.hasAttrib(e)||h.addNumericAttrib(e,3,-1);for(let t=0;t{t(e)})).catch((t=>{e(t)}))}_load(){return new Promise((async(t,e)=>{const n=await this._urlToLoad(),i=this.extension();if(i==dQ.JSON&&this._options.format==dQ.AUTO)mQ.increment_in_progress_loads_count(),await mQ.wait_for_max_concurrent_loads_queue_freed(),fetch(n).then((async e=>{const n=await e.json();new PJ(this.loadingManager).parse(n,(e=>{mQ.decrement_in_progress_loads_count(),t(this.on_load_success(e.children[0]))}))})).catch((t=>{mQ.decrement_in_progress_loads_count(),e(t)}));else{const s=await this._loaderForFormat();if(s)mQ.increment_in_progress_loads_count(),await mQ.wait_for_max_concurrent_loads_queue_freed(),s.load(n,(e=>{this.on_load_success(e).then((e=>{mQ.decrement_in_progress_loads_count(),t(e)}))}),void 0,(t=>{li.warn(\\\\\\\"error loading\\\\\\\",n,t),mQ.decrement_in_progress_loads_count(),e(t)}));else{e(`format not supported (${i})`)}}}))}async on_load_success(t){const e=this.extension();if(e==dQ.JSON)return[t];const n=t;if(n.isObject3D)switch(e){case _Q.PDB:return this.on_load_succes_pdb(t);case _Q.OBJ:default:return[n]}const i=t;if(i.isBufferGeometry)switch(e){case _Q.DRC:return this.on_load_succes_drc(i);default:return[new B.a(i)]}const s=t;if(null!=s.scene)switch(e){case _Q.GLTF:case _Q.GLB:return this.on_load_succes_gltf(s);default:return[n]}const r=t;if(r.geometryAtoms||r.geometryBonds)switch(e){case _Q.PDB:return this.on_load_succes_pdb(r);default:return[]}return[]}on_load_succes_drc(t){return[new B.a(t,mQ._default_mat_mesh)]}on_load_succes_gltf(t){const e=t.scene;return e.animations=t.animations,[e]}on_load_succes_pdb(t){return[new ys.a(t.geometryAtoms,mQ._default_mat_point),new Ms.a(t.geometryBonds,mQ._default_mat_line)]}static moduleNamesFromFormat(t,e){switch(t){case dQ.AUTO:return this.moduleNamesFromExt(e);case dQ.DRC:return[Hn.DRACOLoader];case dQ.FBX:return[Hn.FBXLoader];case dQ.JSON:return[];case dQ.GLTF:return[Hn.GLTFLoader];case dQ.GLTF_WITH_DRACO:return[Hn.GLTFLoader,Hn.DRACOLoader];case dQ.OBJ:return[Hn.OBJLoader];case dQ.PDB:return[Hn.PDBLoader];case dQ.PLY:return[Hn.PLYLoader];case dQ.STL:return[Hn.STLLoader]}os.unreachable(t)}static moduleNamesFromExt(t){switch(t){case _Q.DRC:return[Hn.DRACOLoader];case _Q.FBX:return[Hn.FBXLoader];case _Q.GLTF:return[Hn.GLTFLoader];case _Q.GLB:return[Hn.GLTFLoader,Hn.DRACOLoader];case _Q.OBJ:return[Hn.OBJLoader];case _Q.PDB:return[Hn.PDBLoader];case _Q.PLY:return[Hn.PLYLoader];case _Q.STL:return[Hn.STLLoader]}}async _loaderForFormat(){const t=this._options.format;switch(t){case dQ.AUTO:return this._loaderForExt();case dQ.DRC:return this.loader_for_drc(this._node);case dQ.FBX:return this.loader_for_fbx();case dQ.JSON:return;case dQ.GLTF:return this.loader_for_gltf();case dQ.GLTF_WITH_DRACO:return this.loader_for_glb(this._node);case dQ.OBJ:return this.loader_for_obj();case dQ.PDB:return this.loader_for_pdb();case dQ.PLY:return this.loader_for_ply();case dQ.STL:return this.loader_for_stl()}os.unreachable(t)}async _loaderForExt(){switch(this.extension().toLowerCase()){case _Q.DRC:return this.loader_for_drc(this._node);case _Q.FBX:return this.loader_for_fbx();case _Q.GLTF:return this.loader_for_gltf();case _Q.GLB:return this.loader_for_glb(this._node);case _Q.OBJ:return this.loader_for_obj();case _Q.PDB:return this.loader_for_pdb();case _Q.PLY:return this.loader_for_ply();case _Q.STL:return this.loader_for_stl()}}loader_for_fbx(){const t=li.modulesRegister.module(Hn.FBXLoader);if(t)return new t(this.loadingManager)}loader_for_gltf(){const t=li.modulesRegister.module(Hn.GLTFLoader);if(t)return new t(this.loadingManager)}static async loader_for_drc(t){const e=li.modulesRegister.module(Hn.DRACOLoader);if(e){const n=new e(this.loadingManager),i=li.libs.root(),s=li.libs.DRACOPath();if(i||s){const e=`${i||\\\\\\\"\\\\\\\"}${s||\\\\\\\"\\\\\\\"}/`;if(t){const n=[\\\\\\\"draco_decoder.js\\\\\\\",\\\\\\\"draco_decoder.wasm\\\\\\\",\\\\\\\"draco_wasm_wrapper.js\\\\\\\"];await this._loadMultipleBlobGlobal({files:n.map((t=>({storedUrl:`${s}/${t}`,fullUrl:`${e}${t}`}))),node:t,error:\\\\\\\"failed to load draco libraries. Make sure to install them to load .glb files\\\\\\\"})}n.setDecoderPath(e)}else n.setDecoderPath(void 0);return n.setDecoderConfig({type:\\\\\\\"js\\\\\\\"}),n}}loader_for_drc(t){return mQ.loader_for_drc(t)}static async loader_for_glb(t){const e=li.modulesRegister.module(Hn.GLTFLoader),n=li.modulesRegister.module(Hn.DRACOLoader);if(e&&n){this.gltf_loader=this.gltf_loader||new e(this.loadingManager),this.draco_loader=this.draco_loader||new n(this.loadingManager);const i=li.libs.root(),s=li.libs.DRACOGLTFPath();if(i||s){const e=`${i||\\\\\\\"\\\\\\\"}${s||\\\\\\\"\\\\\\\"}/`;if(t){const n=[\\\\\\\"draco_decoder.js\\\\\\\",\\\\\\\"draco_decoder.wasm\\\\\\\",\\\\\\\"draco_wasm_wrapper.js\\\\\\\"];await this._loadMultipleBlobGlobal({files:n.map((t=>({storedUrl:`${s}/${t}`,fullUrl:`${e}${t}`}))),node:t,error:\\\\\\\"failed to load draco libraries. Make sure to install them to load .glb files\\\\\\\"})}this.draco_loader.setDecoderPath(e)}else this.draco_loader.setDecoderPath(void 0);return this.gltf_loader.setDRACOLoader(this.draco_loader),this.gltf_loader}}loader_for_glb(t){return mQ.loader_for_glb(t)}loader_for_obj(){const t=li.modulesRegister.module(Hn.OBJLoader);if(t)return new t(this.loadingManager)}loader_for_pdb(){const t=li.modulesRegister.module(Hn.PDBLoader);if(t)return new t(this.loadingManager)}loader_for_ply(){const t=li.modulesRegister.module(Hn.PLYLoader);if(t)return new t(this.loadingManager)}loader_for_stl(){const t=li.modulesRegister.module(Hn.STLLoader);if(t)return new t(this.loadingManager)}static setMaxConcurrentLoadsCount(t){this._maxConcurrentLoadsCountMethod=t}static _init_max_concurrent_loads_count(){return this._maxConcurrentLoadsCountMethod?this._maxConcurrentLoadsCountMethod():ng.isChrome()?4:1}static _init_concurrent_loads_delay(){return ng.isChrome()?1:10}static increment_in_progress_loads_count(){this.in_progress_loads_count++}static decrement_in_progress_loads_count(){this.in_progress_loads_count--;const t=this._queue.pop();if(t){const e=this.CONCURRENT_LOADS_DELAY;setTimeout((()=>{t()}),e)}}static async wait_for_max_concurrent_loads_queue_freed(){return this.in_progress_loads_count<=this.MAX_CONCURRENT_LOADS_COUNT?void 0:new Promise((t=>{this._queue.push(t)}))}}mQ._default_mat_mesh=new Ts.a,mQ._default_mat_point=new bs.a,mQ._default_mat_line=new As.a,mQ.MAX_CONCURRENT_LOADS_COUNT=mQ._init_max_concurrent_loads_count(),mQ.CONCURRENT_LOADS_DELAY=mQ._init_concurrent_loads_delay(),mQ.in_progress_loads_count=0,mQ._queue=[];class fQ extends aV{static type(){return\\\\\\\"file\\\\\\\"}static loader(t,e,n){return new mQ({url:t.url,format:t.format},e,n)}cook(t,e){const n=fQ.loader(e,this.scene(),this._node);return new Promise((t=>{n.load((e=>{const n=this._onLoad(e);t(this.createCoreGroupFromObjects(n))}),(t=>{this._onError(t,e)}))}))}clearLoadedBlob(t){fQ.loader(t,this.scene(),this._node).deregisterUrl()}_onLoad(t){t=t.flat();for(let e of t)e.traverse((t=>{this._ensureGeometryHasIndex(t),t.matrixAutoUpdate=!1}));return t}_onError(t,e){var n;null===(n=this.states)||void 0===n||n.error.set(`could not load geometry from ${e.url} (${t})`)}_ensureGeometryHasIndex(t){const e=t.geometry;e&&this.createIndexIfNone(e)}}fQ.DEFAULT_PARAMS={url:`${qg}/models/wolf.obj`,format:dQ.AUTO};const gQ=fQ.DEFAULT_PARAMS;const vQ=new class extends ua{constructor(){super(...arguments),this.url=ha.STRING(gQ.url,{fileBrowse:{type:[Rr.GEOMETRY]}}),this.format=ha.STRING(gQ.format,{menuString:{entries:pQ.map((t=>({name:t,value:t})))}}),this.reload=ha.BUTTON(null,{callback:t=>{yQ.PARAM_CALLBACK_reload(t)}})}};class yQ extends uV{constructor(){super(...arguments),this.paramsConfig=vQ}static type(){return\\\\\\\"file\\\\\\\"}async requiredModules(){for(let t of[this.p.url,this.p.format])t.isDirty()&&await t.compute();const t=$g.extension(this.pv.url||\\\\\\\"\\\\\\\"),e=this.pv.format;return mQ.moduleNamesFromFormat(e,t)}initializeNode(){this.scene().dispatchController.onAddListener((()=>{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{this.params.label.init([this.p.url],(()=>{const t=this.p.url.rawInput();if(t){const e=t.split(\\\\\\\"/\\\\\\\");return e[e.length-1]}return\\\\\\\"\\\\\\\"}))}))}))}operation(){return this._operation=this._operation||new fQ(this.scene(),this.states,this)}async cook(t){const e=await this.operation().cook(t,this.pv);this.setCoreGroup(e)}static PARAM_CALLBACK_reload(t){t._paramCallbackReload()}_paramCallbackReload(){this.operation().clearLoadedBlob(this.pv),this.p.url.setDirty()}}const xQ=new class extends ua{constructor(){super(...arguments),this.url=ha.STRING(`${qg}/models/\\\\`@name\\\\`.obj`,{fileBrowse:{type:[Rr.GEOMETRY]},expression:{forEntities:!0}}),this.format=ha.STRING(dQ.AUTO,{menuString:{entries:pQ.map((t=>({name:t,value:t})))}}),this.reload=ha.BUTTON(null,{callback:t=>{bQ.PARAM_CALLBACK_reload(t)}})}};class bQ extends uV{constructor(){super(...arguments),this.paramsConfig=xQ,this._instancer=new LZ,this._instanceMatrix=new A.a}static type(){return\\\\\\\"fileMulti\\\\\\\"}async requiredModules(){const t=$g.extension(this.p.url.rawInput()||\\\\\\\"\\\\\\\"),e=this.pv.format;return mQ.moduleNamesFromFormat(e,t)}initializeNode(){this.io.inputs.setCount(1),this.io.inputs.initInputsClonedState(Qi.NEVER),this.scene().dispatchController.onAddListener((()=>{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{this.params.label.init([this.p.url],(()=>this.p.url.rawInput()))}))}))}async cook(t){const e=t[0],n=e.points(),i=[],s=new Map,r=new Map,o=new Map,a=this.p.url;if(a.hasExpression()&&a.expressionController){const t=new Set;await a.expressionController.computeExpressionForPoints(n,((e,n)=>{const i=e.index();s.has(i)?this.states.error.set(\\\\\\\"input points have duplicate indices. Make sure to merge inputs together.\\\\\\\"):(s.set(i,n),t.add(n),bQ._incrementUrlUsageCount(n,o))})),t.forEach((t=>{i.push(t)}))}else{const t=this.pv.url;i.push(t),bQ._incrementUrlUsageCount(t,o)}const l=[],c=i.map((t=>this._loadFromUrlPromises(t,r)));await Promise.all(c),this._instancer.setCoreGroup(e);for(let t of n){const e=t.index(),n=s.get(e)||this.pv.url;this._instancer.matrixFromPoint(t,this._instanceMatrix);const i=o.get(n)||1;let a=r.get(n);a&&(i>1&&(a=a.clone()),a.applyMatrix4(this._instanceMatrix),l.push(a))}this.setObjects(l)}static _incrementUrlUsageCount(t,e){const n=e.get(t);null!=n?e.set(t,n+1):e.set(t,1)}async _loadFromUrlPromises(t,e){const n=await this._loadObject(t),i=new Fn.a;i.matrixAutoUpdate=!1,i.name=t;for(let t of n)i.add(t);e.set(t,i)}_loadObject(t){const e=new mQ({url:t,format:this.pv.format},this.scene(),this);return new Promise((n=>{e.load((t=>{const e=this._onLoad(t);n(e)}),(e=>{this._onError(e,t)}))}))}_onLoad(t){t=t.flat();for(let e of t)e.traverse((t=>{this._ensureGeometryHasIndex(t),t.matrixAutoUpdate=!1}));return t}_onError(t,e){var n;null===(n=this.states)||void 0===n||n.error.set(`could not load geometry from ${e} (${t})`)}_ensureGeometryHasIndex(t){const e=t.geometry;e&&pr.createIndexIfNone(e)}static PARAM_CALLBACK_reload(t){t._paramCallbackReload()}_paramCallbackReload(){this.p.url.setDirty()}}const wQ=new class extends ua{constructor(){super(...arguments),this.dist=ha.FLOAT(.1,{range:[0,1],rangeLocked:[!0,!1]})}};class TQ extends uV{constructor(){super(...arguments),this.paramsConfig=wQ}static type(){return\\\\\\\"fuse\\\\\\\"}static displayedInputNames(){return[\\\\\\\"points to fuse together\\\\\\\"]}initializeNode(){this.io.inputs.setCount(1),this.io.inputs.initInputsClonedState(Qi.FROM_NODE)}cook(t){const e=t[0],n=[];let i;for(let t of e.coreObjects())i=this._fuse_core_object(t),i&&n.push(i);this.setObjects(n)}_fuse_core_object(t){const e=t.object();if(!e)return;const n=t.points(),i=this.pv.dist,s={};for(let t of n){const e=t.position(),n=new p.a(Math.round(e.x/i),Math.round(e.y/i),Math.round(e.z/i)).toArray().join(\\\\\\\"-\\\\\\\");s[n]=s[n]||[],s[n].push(t)}const r=[];if(Object.keys(s).forEach((t=>{r.push(s[t][0])})),e.geometry.dispose(),r.length>0){const t=fr.geometryFromPoints(r,Os(e.constructor));return t&&(e.geometry=t),e}}}class AQ{constructor(t,e,n){this._param_size=t,this._param_hexagon_radius=e,this._param_points_only=n}process(){const t=this._param_hexagon_radius,e=.5*t,n=t,i=Math.cos(Math.PI/6)*this._param_hexagon_radius,s=Math.floor(this._param_size.x/n),r=Math.floor(this._param_size.y/i);let o=[],a=[];for(let t=0;t=1&&(0==r||r==s-1?0==r?a.push([r+1+(t-1)*s,r+(t-1)*s,r+t*s]):a.push([r+t*s,r+(t-1)*s,r-1+t*s]):(a.push([r+t*s,r+(t-1)*s,r-1+t*s]),a.push([r+t*s,r+1+(t-1)*s,r+(t-1)*s])));const l=new S.a;return l.setAttribute(\\\\\\\"position\\\\\\\",new C.a(new Float32Array(o.flat()),3)),this._param_points_only||(l.setIndex(a.flat()),l.computeVertexNormals()),l}}const MQ=new p.a(0,1,0);const EQ=new class extends ua{constructor(){super(...arguments),this.size=ha.VECTOR2([1,1]),this.hexagonRadius=ha.FLOAT(.1,{range:[.001,1],rangeLocked:[!1,!1]}),this.direction=ha.VECTOR3([0,1,0]),this.pointsOnly=ha.BOOLEAN(0)}};class SQ extends uV{constructor(){super(...arguments),this.paramsConfig=EQ,this._coreTransform=new bU}static type(){return\\\\\\\"hexagons\\\\\\\"}cook(){if(this.pv.hexagonRadius>0){const t=new AQ(this.pv.size,this.pv.hexagonRadius,this.pv.pointsOnly).process();this._coreTransform.rotateGeometry(t,MQ,this.pv.direction),this.pv.pointsOnly?this.setGeometry(t,Ns.POINTS):this.setGeometry(t)}else this.setObjects([])}}var CQ;!function(t){t.ADD_PARENT=\\\\\\\"add_parent\\\\\\\",t.REMOVE_PARENT=\\\\\\\"remove_parent\\\\\\\",t.ADD_CHILD=\\\\\\\"add_child\\\\\\\"}(CQ||(CQ={}));const NQ=[CQ.ADD_PARENT,CQ.REMOVE_PARENT,CQ.ADD_CHILD];class LQ extends aV{static type(){return\\\\\\\"hierarchy\\\\\\\"}cook(t,e){const n=t[0],i=NQ[e.mode];switch(i){case CQ.ADD_PARENT:{const t=this._add_parent_to_core_group(n,e);return this.createCoreGroupFromObjects(t)}case CQ.REMOVE_PARENT:{const t=this._remove_parent_from_core_group(n,e);return this.createCoreGroupFromObjects(t)}case CQ.ADD_CHILD:{const i=this._add_child_to_core_group(n,t[1],e);return this.createCoreGroupFromObjects(i)}}os.unreachable(i)}_add_parent_to_core_group(t,e){if(0==e.levels)return t.objects();return[this._add_parent_to_object(t.objects(),e)]}_add_parent_to_object(t,e){let n=new Fn.a;if(n.matrixAutoUpdate=!1,n.add(...t),e.levels>0)for(let t=0;t({name:t,value:e})))}}),this.levels=ha.INTEGER(PQ.levels,{range:[0,5],visibleIf:[{mode:NQ.indexOf(CQ.ADD_PARENT)},{mode:NQ.indexOf(CQ.REMOVE_PARENT)}]}),this.objectMask=ha.STRING(\\\\\\\"\\\\\\\",{visibleIf:{mode:NQ.indexOf(CQ.ADD_CHILD)}}),this.debugObjectMask=ha.BOOLEAN(0,{visibleIf:{mode:NQ.indexOf(CQ.ADD_CHILD)}})}};class IQ extends uV{constructor(){super(...arguments),this.paramsConfig=RQ}static type(){return\\\\\\\"hierarchy\\\\\\\"}static displayedInputNames(){return[\\\\\\\"geometry to add or remove parents to/from\\\\\\\",\\\\\\\"objects to use as parent or children (optional)\\\\\\\"]}initializeNode(){this.io.inputs.setCount(1,2),this.io.inputs.initInputsClonedState(LQ.INPUT_CLONED_STATE),this.scene().dispatchController.onAddListener((()=>{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{this.params.label.init([this.p.mode,this.p.levels,this.p.objectMask],(()=>{const t=NQ[this.pv.mode];return OQ.includes(t)?`${t} ${this.pv.levels}`:`${t} (with mask: ${this.pv.objectMask})`}))}))}))}cook(t){this._operation=this._operation||new LQ(this._scene,this.states);const e=this._operation.cook(t,this.pv);this.setCoreGroup(e)}}const FQ=new class extends ua{constructor(){super(...arguments),this.texture=ha.OPERATOR_PATH(vi.UV,{nodeSelection:{context:ts.COP}}),this.mult=ha.FLOAT(1)}};class DQ extends uV{constructor(){super(...arguments),this.paramsConfig=FQ}static type(){return\\\\\\\"heightMap\\\\\\\"}initializeNode(){this.io.inputs.setCount(1),this.io.inputs.initInputsClonedState(Qi.FROM_NODE)}async cook(t){const e=t[0],n=this.p.texture.found_node();if(n){if(n.context()==ts.COP){const t=n,i=(await t.compute()).texture();for(let t of e.coreObjects())this._set_position_from_data_texture(t,i)}else this.states.error.set(\\\\\\\"found node is not a texture\\\\\\\")}e.computeVertexNormals(),this.setCoreGroup(e)}_set_position_from_data_texture(t,e){var n;const i=this._data_from_texture(e);if(!i)return;const{data:s,resx:r,resy:o}=i,a=s.length/(r*o),l=null===(n=t.coreGeometry())||void 0===n?void 0:n.geometry();if(!l)return;const c=l.getAttribute(\\\\\\\"position\\\\\\\").array,h=l.getAttribute(\\\\\\\"uv\\\\\\\"),u=l.getAttribute(\\\\\\\"normal\\\\\\\");if(null==h)return void this.states.error.set(\\\\\\\"uvs are required\\\\\\\");if(null==u)return void this.states.error.set(\\\\\\\"normals are required\\\\\\\");const d=h.array,p=u.array,_=c.length/3;let m,f,g,v,y,x,b,w=0;for(let t=0;t<_;t++)m=2*t,f=d[m],g=d[m+1],v=Math.floor((r-1)*f),y=Math.floor((o-1)*(1-g)),x=y*r+v,b=s[a*x],w=3*t,c[w+0]+=p[w+0]*b*this.pv.mult,c[w+1]+=p[w+1]*b*this.pv.mult,c[w+2]+=p[w+2]*b*this.pv.mult}_data_from_texture(t){if(t.image)return t.image.data?this._data_from_data_texture(t):this._data_from_default_texture(t)}_data_from_default_texture(t){const e=t.image.width,n=t.image.height;return{data:Bf.data_from_image(t.image).data,resx:e,resy:n}}_data_from_data_texture(t){return{data:t.image.data,resx:t.image.width,resy:t.image.height}}}function BQ(t){return Math.atan2(-t.y,Math.sqrt(t.x*t.x+t.z*t.z))}class zQ extends S.a{constructor(t,e,n,i,s){super(),this.type=\\\\\\\"PolyhedronBufferGeometry\\\\\\\",this.parameters={vertices:t,indices:e,radius:n,detail:i},n=n||1,i=i||0;const r=[],o=[],a=new Map;function l(t,e,n,i){const s=i+1,r=[];for(let i=0;i<=s;i++){r[i]=[];const o=t.clone().lerp(n,i/s),a=e.clone().lerp(n,i/s),l=s-i;for(let t=0;t<=l;t++)r[i][t]=0===t&&i===s?o:o.clone().lerp(a,t/l)}for(let t=0;tLZ.remapName(t)));let o=!1;for(let t of r)LZ.transformAttributeNames.includes(t)&&(o=!0);const a=s.points();if(o){LZ.updateTransformInstanceAttributes(a,s,i);for(let t of LZ.transformAttributeNames){const e=i.getAttribute(t);e&&(e.needsUpdate=!0)}}}}JQ.DEFAULT_PARAMS={mode:$Q.indexOf(YQ.GEO),geoAttributes:\\\\\\\"P N\\\\\\\",pointAttributes:\\\\\\\"P\\\\\\\"},JQ.INPUT_CLONED_STATE=[Qi.FROM_NODE,Qi.NEVER];const ZQ=JQ.DEFAULT_PARAMS;const KQ=new class extends ua{constructor(){super(...arguments),this.mode=ha.INTEGER(ZQ.mode,{menu:{entries:$Q.map(((t,e)=>({value:e,name:t})))}}),this.geoAttributes=ha.STRING(ZQ.geoAttributes,{visibleIf:{mode:$Q.indexOf(YQ.GEO)}}),this.pointAttributes=ha.STRING(ZQ.pointAttributes,{visibleIf:{mode:$Q.indexOf(YQ.POINTS)}})}};class QQ extends uV{constructor(){super(...arguments),this.paramsConfig=KQ}static type(){return\\\\\\\"instanceUpdate\\\\\\\"}static displayedInputNames(){return[\\\\\\\"instance to update\\\\\\\",\\\\\\\"geometry to copy attributes from\\\\\\\"]}initializeNode(){super.initializeNode(),this.io.inputs.setCount(2),this.io.inputs.initInputsClonedState(JQ.INPUT_CLONED_STATE)}setMode(t){this.p.mode.set($Q.indexOf(t))}async cook(t){this._operation=this._operation||new JQ(this.scene(),this.states);const e=await this._operation.cook(t,this.pv);this.setCoreGroup(e)}}const t0=new class extends ua{constructor(){super(...arguments),this.useMax=ha.BOOLEAN(0),this.max=ha.INTEGER(1,{range:[0,100],rangeLocked:[!0,!1],visibleIf:{useMax:1}})}};class e0 extends uV{constructor(){super(...arguments),this.paramsConfig=t0}static type(){return\\\\\\\"instancesCount\\\\\\\"}initializeNode(){this.io.inputs.setCount(1),this.io.inputs.initInputsClonedState(Qi.FROM_NODE)}async cook(t){const e=t[0],n=e.objectsWithGeo();for(let t of n){const e=t.geometry;e&&e instanceof lJ&&(this.pv.useMax?e.instanceCount=this.pv.max:e.instanceCount=1/0)}this.setCoreGroup(e)}}class n0 extends aV{static type(){return\\\\\\\"jitter\\\\\\\"}cook(t,e){const n=t[0],i=n.points();let s;for(let t=0;t{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{this.params.label.init([this.p.layer])}))}))}cook(t){const e=t[0];for(let t of e.objects())t.layers.set(this.pv.layer);this.setCoreGroup(e)}}const l0=new class extends ua{constructor(){super(...arguments),this.length=ha.FLOAT(1,{range:[0,10]}),this.pointsCount=ha.INTEGER(1,{range:[2,100],rangeLocked:[!0,!1]}),this.origin=ha.VECTOR3([0,0,0]),this.direction=ha.VECTOR3([0,1,0])}};class c0 extends uV{constructor(){super(...arguments),this.paramsConfig=l0}static type(){return\\\\\\\"line\\\\\\\"}initializeNode(){}cook(){const t=Math.max(2,this.pv.pointsCount),e=new Array(3*t),n=new Array(t),i=this.pv.direction.clone().normalize().multiplyScalar(this.pv.length);for(let s=0;s0&&(n[2*(s-1)]=s-1,n[2*(s-1)+1]=s)}const s=new S.a;s.setAttribute(\\\\\\\"position\\\\\\\",new C.c(e,3)),s.setIndex(n),this.setGeometry(s,Ns.LINE_SEGMENTS)}}const h0=new class extends ua{constructor(){super(...arguments),this.distance0=ha.FLOAT(1),this.distance1=ha.FLOAT(2),this.autoUpdate=ha.BOOLEAN(1),this.update=ha.BUTTON(null,{callback:t=>{u0.PARAM_CALLBACK_update(t)}}),this.camera=ha.OPERATOR_PATH(\\\\\\\"/perspective_camera1\\\\\\\",{visibleIf:{autoUpdate:0},dependentOnFoundNode:!1})}};class u0 extends uV{constructor(){super(...arguments),this.paramsConfig=h0,this._lod=this._create_LOD()}static type(){return\\\\\\\"lod\\\\\\\"}static displayedInputNames(){return[\\\\\\\"high res\\\\\\\",\\\\\\\"mid res\\\\\\\",\\\\\\\"low res\\\\\\\"]}initializeNode(){this.io.inputs.setCount(1,3),this.io.inputs.initInputsClonedState(Qi.FROM_NODE)}_create_LOD(){const t=new Cs;return t.matrixAutoUpdate=!1,t}cook(t){this._clear_lod(),this._add_level(t[0],0),this._add_level(t[1],this.pv.distance0),this._add_level(t[2],this.pv.distance1),this._lod.autoUpdate=this.pv.autoUpdate,this.setObject(this._lod)}_add_level(t,e){if(t){const n=t.objects();let i;for(let t=0;t{this._apply_material(t,n,e)}));else for(let i of t.objectsFromGroup(e.group))this._apply_material(i,n,e);return t}null===(i=this.states)||void 0===i||i.error.set(`material invalid. (error: '${r.states.error.message()}')`)}else null===(s=this.states)||void 0===s||s.error.set(\\\\\\\"no material node found\\\\\\\")}_swap_textures(t,e){if(e.swapCurrentTex){this._materials_by_uuid.clear();for(let n of t.objectsFromGroup(e.group))if(e.applyToChildren)n.traverse((t=>{const e=n.material;this._materials_by_uuid.set(e.uuid,e)}));else{const t=n.material;this._materials_by_uuid.set(t.uuid,t)}this._materials_by_uuid.forEach(((t,n)=>{this._swap_texture(t,e)}))}}_apply_material(t,e,n){if(n.group&&!br.isInGroup(n.group,t))return;const i=n.cloneMat?yr.clone(e):e;if(e instanceof F&&i instanceof F)for(let t in e.uniforms)i.uniforms[t]=e.uniforms[t];const s=t;this._old_mat_by_old_new_id.set(i.uuid,s.material),s.material=i,yr.apply_render_hook(t,i),yr.applyCustomMaterials(t,i)}_swap_texture(t,e){if(\\\\\\\"\\\\\\\"==e.texSrc0||\\\\\\\"\\\\\\\"==e.texDest0)return;let n=this._old_mat_by_old_new_id.get(t.uuid);n=n||t;const i=n[e.texSrc0];if(i){t[e.texDest0]=i;const n=t.uniforms;if(n){n[e.texDest0]&&(n[e.texDest0]={value:i})}}}}d0.DEFAULT_PARAMS={group:\\\\\\\"\\\\\\\",assignMat:!0,material:new yi(\\\\\\\"\\\\\\\"),applyToChildren:!0,cloneMat:!1,shareUniforms:!0,swapCurrentTex:!1,texSrc0:\\\\\\\"emissiveMap\\\\\\\",texDest0:\\\\\\\"map\\\\\\\"},d0.INPUT_CLONED_STATE=Qi.FROM_NODE;const p0=d0.DEFAULT_PARAMS;const _0=new class extends ua{constructor(){super(...arguments),this.group=ha.STRING(p0.group),this.assignMat=ha.BOOLEAN(p0.assignMat),this.material=ha.NODE_PATH(p0.material.path(),{nodeSelection:{context:ts.MAT},dependentOnFoundNode:!1,visibleIf:{assignMat:1}}),this.applyToChildren=ha.BOOLEAN(p0.applyToChildren,{visibleIf:{assignMat:1}}),this.cloneMat=ha.BOOLEAN(p0.cloneMat,{visibleIf:{assignMat:1}}),this.shareUniforms=ha.BOOLEAN(p0.shareUniforms,{visibleIf:{assignMat:1,cloneMat:1}}),this.swapCurrentTex=ha.BOOLEAN(p0.swapCurrentTex),this.texSrc0=ha.STRING(p0.texSrc0,{visibleIf:{swapCurrentTex:1}}),this.texDest0=ha.STRING(p0.texDest0,{visibleIf:{swapCurrentTex:1}})}};class m0 extends uV{constructor(){super(...arguments),this.paramsConfig=_0}static type(){return\\\\\\\"material\\\\\\\"}static displayedInputNames(){return[\\\\\\\"objects to assign material to\\\\\\\"]}initializeNode(){this.io.inputs.setCount(1),this.io.inputs.initInputsClonedState(d0.INPUT_CLONED_STATE),this.scene().dispatchController.onAddListener((()=>{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{this.params.label.init([this.p.material],(()=>this.p.material.rawInput()))}))}))}async cook(t){this._operation=this._operation||new d0(this._scene,this.states);const e=await this._operation.cook(t,this.pv);this.setCoreGroup(e)}}class f0 extends aV{static type(){return\\\\\\\"merge\\\\\\\"}cook(t,e){let n=[];for(let i of t)if(i){const t=i.objects();if(e.compact)for(let e of t)e.traverse((t=>{n.push(t)}));else for(let t of i.objects())n.push(t)}e.compact&&(n=this._makeCompact(n));for(let t of n)t.traverse((t=>{t.matrixAutoUpdate=!1}));return this.createCoreGroupFromObjects(n)}_makeCompact(t){const e=new Map,n=new Map,i=[];for(let s of t)s.traverse((t=>{if(t instanceof Fn.a)return;const s=t;if(s.geometry){const t=Os(s.constructor);if(i.includes(t)||i.push(t),t){e.get(t)||e.set(t,s.material),h.pushOnArrayAtEntry(n,t,s)}}}));const s=[];return i.forEach((t=>{var i,r;const o=n.get(t);if(o){const n=[];for(let t of o){const e=t.geometry;e.applyMatrix4(t.matrix),n.push(e)}try{const r=fr.mergeGeometries(n);if(r){const n=e.get(t),i=this.createObject(r,t,n);s.push(i)}else null===(i=this.states)||void 0===i||i.error.set(\\\\\\\"merge failed, check that input geometries have the same attributes\\\\\\\")}catch(t){null===(r=this.states)||void 0===r||r.error.set(t.message)}}})),s}}f0.DEFAULT_PARAMS={compact:!1},f0.INPUT_CLONED_STATE=Qi.FROM_NODE;const g0=\\\\\\\"geometry to merge\\\\\\\",v0=f0.DEFAULT_PARAMS;const y0=new class extends ua{constructor(){super(...arguments),this.compact=ha.BOOLEAN(v0.compact),this.inputsCount=ha.INTEGER(4,{range:[1,32],rangeLocked:[!0,!1],callback:t=>{x0.PARAM_CALLBACK_setInputsCount(t)}})}};class x0 extends uV{constructor(){super(...arguments),this.paramsConfig=y0}static type(){return\\\\\\\"merge\\\\\\\"}static displayedInputNames(){return[g0,g0,g0,g0]}setCompactMode(t){this.p.compact.set(t)}initializeNode(){this.io.inputs.setCount(1,4),this.io.inputs.initInputsClonedState(f0.INPUT_CLONED_STATE),this.scene().dispatchController.onAddListener((()=>{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{this.params.label.init([this.p.compact],(()=>this.pv.compact?\\\\\\\"compact\\\\\\\":\\\\\\\"separate objects\\\\\\\"))})),this.params.addOnSceneLoadHook(\\\\\\\"update inputs\\\\\\\",(()=>{this._callbackUpdateInputsCount()}))}))}cook(t){this._operation=this._operation||new f0(this.scene(),this.states);const e=this._operation.cook(t,this.pv);this.setCoreGroup(e)}_callbackUpdateInputsCount(){this.io.inputs.setCount(1,this.pv.inputsCount),this.emit(Ei.INPUTS_UPDATED)}static PARAM_CALLBACK_setInputsCount(t){t._callbackUpdateInputsCount()}}const b0=new Float32Array(36),w0=new Float32Array(36),T0=new Float32Array(36);function A0(t,e,n){return t+(e-t)*n}class M0 extends S.a{constructor(t,e,n){super(),this.resolution=t,this.isMarchingCubes=!0,this.isolation=80,this.size=-1,this.size2=-1,this.size3=-1,this.halfsize=-1,this.delta=-1,this.yd=-1,this.zd=-1,this.count=-1,this.maxCount=-1,this.enableUvs=void 0!==e&&e,this.enableColors=void 0!==n&&n,this.size=this.resolution,this.size2=this.size*this.size,this.size3=this.size2*this.size,this.halfsize=this.size/2,this.delta=2/this.size,this.yd=this.size,this.zd=this.size2,this.field=new Float32Array(this.size3),this.normal_cache=new Float32Array(3*this.size3),this.palette=new Float32Array(3*this.size3),this.maxCount=this.size3,this.count=0,this.positionArray=new Float32Array(3*this.maxCount),this.setAttribute(\\\\\\\"position\\\\\\\",new C.a(this.positionArray,3)),this.normalArray=new Float32Array(3*this.maxCount),this.setAttribute(\\\\\\\"normal\\\\\\\",new C.a(this.normalArray,3)),this.enableUvs&&(this.uvArray=new Float32Array(2*this.maxCount),this.setAttribute(\\\\\\\"uv\\\\\\\",new C.a(this.uvArray,2))),this.enableColors&&(this.colorArray=new Float32Array(3*this.maxCount),this.setAttribute(\\\\\\\"color\\\\\\\",new C.a(this.colorArray,3)));const i=(t,e,n,i,c)=>{const h=i+1,u=i+this.yd,d=i+this.zd,p=h+this.yd,_=h+this.zd,m=i+this.yd+this.zd,f=h+this.yd+this.zd;let g=0;const v=this.field[i],y=this.field[h],x=this.field[u],b=this.field[p],w=this.field[d],T=this.field[_],A=this.field[m],M=this.field[f];v{const t=this.size-2;for(let e=1;e{const h=(n-o)/(a-o),u=this.normal_cache;b0[e+0]=i+h*this.delta,b0[e+1]=s,b0[e+2]=r,w0[e+0]=A0(u[t+0],u[t+3],h),w0[e+1]=A0(u[t+1],u[t+4],h),w0[e+2]=A0(u[t+2],u[t+5],h),T0[e+0]=A0(this.palette[3*l+0],this.palette[3*c+0],h),T0[e+1]=A0(this.palette[3*l+1],this.palette[3*c+1],h),T0[e+2]=A0(this.palette[3*l+2],this.palette[3*c+2],h)},r=(t,e,n,i,s,r,o,a,l,c)=>{const h=(n-o)/(a-o),u=this.normal_cache;b0[e+0]=i,b0[e+1]=s+h*this.delta,b0[e+2]=r;const d=t+3*this.yd;w0[e+0]=A0(u[t+0],u[d+0],h),w0[e+1]=A0(u[t+1],u[d+1],h),w0[e+2]=A0(u[t+2],u[d+2],h),T0[e+0]=A0(this.palette[3*l+0],this.palette[3*c+0],h),T0[e+1]=A0(this.palette[3*l+1],this.palette[3*c+1],h),T0[e+2]=A0(this.palette[3*l+2],this.palette[3*c+2],h)},o=(t,e,n,i,s,r,o,a,l,c)=>{const h=(n-o)/(a-o),u=this.normal_cache;b0[e+0]=i,b0[e+1]=s,b0[e+2]=r+h*this.delta;const d=t+3*this.zd;w0[e+0]=A0(u[t+0],u[d+0],h),w0[e+1]=A0(u[t+1],u[d+1],h),w0[e+2]=A0(u[t+2],u[d+2],h),T0[e+0]=A0(this.palette[3*l+0],this.palette[3*c+0],h),T0[e+1]=A0(this.palette[3*l+1],this.palette[3*c+1],h),T0[e+2]=A0(this.palette[3*l+2],this.palette[3*c+2],h)},a=t=>{const e=3*t;0===this.normal_cache[e]&&(this.normal_cache[e+0]=this.field[t-1]-this.field[t+1],this.normal_cache[e+1]=this.field[t-this.yd]-this.field[t+this.yd],this.normal_cache[e+2]=this.field[t-this.zd]-this.field[t+this.zd])},l=(t,e,n,i,s,r)=>{const o=3*this.count;if(this.positionArray&&this.normalArray){if(this.positionArray[o+0]=t[i],this.positionArray[o+1]=t[i+1],this.positionArray[o+2]=t[i+2],this.positionArray[o+3]=t[s],this.positionArray[o+4]=t[s+1],this.positionArray[o+5]=t[s+2],this.positionArray[o+6]=t[r],this.positionArray[o+7]=t[r+1],this.positionArray[o+8]=t[r+2],this.normalArray[o+0]=e[i+0],this.normalArray[o+1]=e[i+1],this.normalArray[o+2]=e[i+2],this.normalArray[o+3]=e[s+0],this.normalArray[o+4]=e[s+1],this.normalArray[o+5]=e[s+2],this.normalArray[o+6]=e[r+0],this.normalArray[o+7]=e[r+1],this.normalArray[o+8]=e[r+2],this.enableUvs&&this.uvArray){const e=2*this.count;this.uvArray[e+0]=t[i+0],this.uvArray[e+1]=t[i+2],this.uvArray[e+2]=t[s+0],this.uvArray[e+3]=t[s+2],this.uvArray[e+4]=t[r+0],this.uvArray[e+5]=t[r+2]}this.enableColors&&this.colorArray&&(this.colorArray[o+0]=n[i+0],this.colorArray[o+1]=n[i+1],this.colorArray[o+2]=n[i+2],this.colorArray[o+3]=n[s+0],this.colorArray[o+4]=n[s+1],this.colorArray[o+5]=n[s+2],this.colorArray[o+6]=n[r+0],this.colorArray[o+7]=n[r+1],this.colorArray[o+8]=n[r+2]),this.count+=3}}}createPolygons(){this._createPolygons()}addBall(t,e,n,i,s,r){const o=Math.sign(i);i=Math.abs(i);const a=!(null==r);let l=new D.a(t,e,n);if(a)try{r&&(l=r)}catch(i){l=new D.a(t,e,n)}const c=this.size*Math.sqrt(i/s),h=n*this.size,u=e*this.size,d=t*this.size;let p=Math.floor(h-c);p<1&&(p=1);let _=Math.floor(h+c);_>this.size-1&&(_=this.size-1);let m=Math.floor(u-c);m<1&&(m=1);let f=Math.floor(u+c);f>this.size-1&&(f=this.size-1);let g=Math.floor(d-c);g<1&&(g=1);let v,y,x,b,w,T,A,M,E,S,C,N=Math.floor(d+c);for(N>this.size-1&&(N=this.size-1),x=p;x<_;x++)for(w=this.size2*x,M=x/this.size-n,E=M*M,y=m;y0){this.field[b+v]+=C*o;const t=Math.sqrt((v-d)*(v-d)+(y-u)*(y-u)+(x-h)*(x-h))/c,e=1-t*t*t*(t*(6*t-15)+10);this.palette[3*(b+v)+0]+=l.r*e,this.palette[3*(b+v)+1]+=l.g*e,this.palette[3*(b+v)+2]+=l.b*e}}}const E0=new 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-1,-1,-1,-1,1,10,2,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,1,3,8,9,1,8,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,0,9,1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,0,3,8,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1]),C0=new p.a;class N0 extends aV{static type(){return\\\\\\\"metaball\\\\\\\"}cook(t,e){const n=t[0],i=new M0(e.resolution,e.enableUVs,e.enableColors);i.isolation=e.isolation;const s=n.points();for(let t of s){t.getPosition(C0),C0.multiplyScalar(.5).addScalar(.5);let n=e.metaStrength;if(e.useMetaStrengthAttrib){let e=t.attribValue(\\\\\\\"metaStrength\\\\\\\");m.isNumber(e)&&(n*=e)}let s=e.metaSubstract;if(e.useMetaSubstractAttrib){let e=t.attribValue(\\\\\\\"metaSubstract\\\\\\\");m.isNumber(e)&&(s*=e)}i.addBall(C0.x,C0.y,C0.z,n,s,void 0)}return i.createPolygons(),this.createCoreGroupFromGeometry(i)}}N0.DEFAULT_PARAMS={resolution:40,isolation:30,useMetaStrengthAttrib:!1,metaStrength:1,useMetaSubstractAttrib:!1,metaSubstract:1,enableUVs:!1,enableColors:!1},N0.INPUT_CLONED_STATE=Qi.NEVER;const L0=N0.DEFAULT_PARAMS;const O0=new class extends ua{constructor(){super(...arguments),this.resolution=ha.FLOAT(L0.resolution,{range:[0,100],rangeLocked:[!0,!1]}),this.isolation=ha.FLOAT(L0.isolation,{range:[0,100],rangeLocked:[!0,!1]}),this.useMetaStrengthAttrib=ha.BOOLEAN(L0.useMetaStrengthAttrib),this.metaStrength=ha.FLOAT(L0.metaStrength,{range:[0,10],rangeLocked:[!0,!1]}),this.useMetaSubstractAttrib=ha.BOOLEAN(L0.useMetaSubstractAttrib),this.metaSubstract=ha.FLOAT(L0.metaSubstract,{range:[0,10],rangeLocked:[!0,!1]}),this.enableUVs=ha.BOOLEAN(L0.enableUVs),this.enableColors=ha.BOOLEAN(L0.enableColors)}};class P0 extends uV{constructor(){super(...arguments),this.paramsConfig=O0}static type(){return\\\\\\\"metaball\\\\\\\"}static displayedInputNames(){return[\\\\\\\"points to create metaballs from\\\\\\\"]}initializeNode(){this.io.inputs.setCount(1),this.io.inputs.initInputsClonedState(N0.INPUT_CLONED_STATE)}cook(t){this._operation=this._operation||new N0(this._scene,this.states);const e=this._operation.cook(t,this.pv);this.setCoreGroup(e)}}class R0{constructor(t=Math){this.grad3=[[1,1,0],[-1,1,0],[1,-1,0],[-1,-1,0],[1,0,1],[-1,0,1],[1,0,-1],[-1,0,-1],[0,1,1],[0,-1,1],[0,1,-1],[0,-1,-1]],this.grad4=[[0,1,1,1],[0,1,1,-1],[0,1,-1,1],[0,1,-1,-1],[0,-1,1,1],[0,-1,1,-1],[0,-1,-1,1],[0,-1,-1,-1],[1,0,1,1],[1,0,1,-1],[1,0,-1,1],[1,0,-1,-1],[-1,0,1,1],[-1,0,1,-1],[-1,0,-1,1],[-1,0,-1,-1],[1,1,0,1],[1,1,0,-1],[1,-1,0,1],[1,-1,0,-1],[-1,1,0,1],[-1,1,0,-1],[-1,-1,0,1],[-1,-1,0,-1],[1,1,1,0],[1,1,-1,0],[1,-1,1,0],[1,-1,-1,0],[-1,1,1,0],[-1,1,-1,0],[-1,-1,1,0],[-1,-1,-1,0]],this.p=[];for(let e=0;e<256;e++)this.p[e]=Math.floor(256*t.random());this.perm=[];for(let t=0;t<512;t++)this.perm[t]=this.p[255&t];this.simplex=[[0,1,2,3],[0,1,3,2],[0,0,0,0],[0,2,3,1],[0,0,0,0],[0,0,0,0],[0,0,0,0],[1,2,3,0],[0,2,1,3],[0,0,0,0],[0,3,1,2],[0,3,2,1],[0,0,0,0],[0,0,0,0],[0,0,0,0],[1,3,2,0],[0,0,0,0],[0,0,0,0],[0,0,0,0],[0,0,0,0],[0,0,0,0],[0,0,0,0],[0,0,0,0],[0,0,0,0],[1,2,0,3],[0,0,0,0],[1,3,0,2],[0,0,0,0],[0,0,0,0],[0,0,0,0],[2,3,0,1],[2,3,1,0],[1,0,2,3],[1,0,3,2],[0,0,0,0],[0,0,0,0],[0,0,0,0],[2,0,3,1],[0,0,0,0],[2,1,3,0],[0,0,0,0],[0,0,0,0],[0,0,0,0],[0,0,0,0],[0,0,0,0],[0,0,0,0],[0,0,0,0],[0,0,0,0],[2,0,1,3],[0,0,0,0],[0,0,0,0],[0,0,0,0],[3,0,1,2],[3,0,2,1],[0,0,0,0],[3,1,2,0],[2,1,0,3],[0,0,0,0],[0,0,0,0],[0,0,0,0],[3,1,0,2],[0,0,0,0],[3,2,0,1],[3,2,1,0]]}dot(t,e,n){return t[0]*e+t[1]*n}dot3(t,e,n,i){return t[0]*e+t[1]*n+t[2]*i}dot4(t,e,n,i,s){return t[0]*e+t[1]*n+t[2]*i+t[3]*s}noise(t,e){let n,i,s;const r=(t+e)*(.5*(Math.sqrt(3)-1)),o=Math.floor(t+r),a=Math.floor(e+r),l=(3-Math.sqrt(3))/6,c=(o+a)*l,h=t-(o-c),u=e-(a-c);let d,p;h>u?(d=1,p=0):(d=0,p=1);const _=h-d+l,m=u-p+l,f=h-1+2*l,g=u-1+2*l,v=255&o,y=255&a,x=this.perm[v+this.perm[y]]%12,b=this.perm[v+d+this.perm[y+p]]%12,w=this.perm[v+1+this.perm[y+1]]%12;let T=.5-h*h-u*u;T<0?n=0:(T*=T,n=T*T*this.dot(this.grad3[x],h,u));let A=.5-_*_-m*m;A<0?i=0:(A*=A,i=A*A*this.dot(this.grad3[b],_,m));let M=.5-f*f-g*g;return M<0?s=0:(M*=M,s=M*M*this.dot(this.grad3[w],f,g)),70*(n+i+s)}noise3d(t,e,n){let i,s,r,o;const a=(t+e+n)*(1/3),l=Math.floor(t+a),c=Math.floor(e+a),h=Math.floor(n+a),u=1/6,d=(l+c+h)*u,p=t-(l-d),_=e-(c-d),m=n-(h-d);let f,g,v,y,x,b;p>=_?_>=m?(f=1,g=0,v=0,y=1,x=1,b=0):p>=m?(f=1,g=0,v=0,y=1,x=0,b=1):(f=0,g=0,v=1,y=1,x=0,b=1):_b?32:0)+(x>w?16:0)+(b>w?8:0)+(x>T?4:0)+(b>T?2:0)+(w>T?1:0),M=r[A][0]>=3?1:0,E=r[A][1]>=3?1:0,S=r[A][2]>=3?1:0,C=r[A][3]>=3?1:0,N=r[A][0]>=2?1:0,L=r[A][1]>=2?1:0,O=r[A][2]>=2?1:0,P=r[A][3]>=2?1:0,R=r[A][0]>=1?1:0,I=r[A][1]>=1?1:0,F=r[A][2]>=1?1:0,D=r[A][3]>=1?1:0,B=x-M+l,z=b-E+l,k=w-S+l,U=T-C+l,G=x-N+2*l,V=b-L+2*l,H=w-O+2*l,j=T-P+2*l,W=x-R+3*l,q=b-I+3*l,X=w-F+3*l,Y=T-D+3*l,$=x-1+4*l,J=b-1+4*l,Z=w-1+4*l,K=T-1+4*l,Q=255&m,tt=255&f,et=255&g,nt=255&v,it=o[Q+o[tt+o[et+o[nt]]]]%32,st=o[Q+M+o[tt+E+o[et+S+o[nt+C]]]]%32,rt=o[Q+N+o[tt+L+o[et+O+o[nt+P]]]]%32,ot=o[Q+R+o[tt+I+o[et+F+o[nt+D]]]]%32,at=o[Q+1+o[tt+1+o[et+1+o[nt+1]]]]%32;let lt=.6-x*x-b*b-w*w-T*T;lt<0?c=0:(lt*=lt,c=lt*lt*this.dot4(s[it],x,b,w,T));let ct=.6-B*B-z*z-k*k-U*U;ct<0?h=0:(ct*=ct,h=ct*ct*this.dot4(s[st],B,z,k,U));let ht=.6-G*G-V*V-H*H-j*j;ht<0?u=0:(ht*=ht,u=ht*ht*this.dot4(s[rt],G,V,H,j));let ut=.6-W*W-q*q-X*X-Y*Y;ut<0?d=0:(ut*=ut,d=ut*ut*this.dot4(s[ot],W,q,X,Y));let dt=.6-$*$-J*J-Z*Z-K*K;return dt<0?p=0:(dt*=dt,p=dt*dt*this.dot4(s[at],$,J,Z,K)),27*(c+h+u+d+p)}}var I0;!function(t){t.ADD=\\\\\\\"add\\\\\\\",t.SET=\\\\\\\"set\\\\\\\",t.MULT=\\\\\\\"mult\\\\\\\",t.SUBSTRACT=\\\\\\\"substract\\\\\\\",t.DIVIDE=\\\\\\\"divide\\\\\\\"}(I0||(I0={}));const F0=[I0.ADD,I0.SET,I0.MULT,I0.SUBSTRACT,I0.DIVIDE];const D0=new class extends ua{constructor(){super(...arguments),this.amplitude=ha.FLOAT(1),this.tamplitudeAttrib=ha.BOOLEAN(0),this.amplitudeAttrib=ha.STRING(\\\\\\\"amp\\\\\\\",{visibleIf:{tamplitudeAttrib:!0}}),this.freq=ha.VECTOR3([1,1,1]),this.offset=ha.VECTOR3([0,0,0]),this.octaves=ha.INTEGER(3,{range:[1,8],rangeLocked:[!0,!1]}),this.ampAttenuation=ha.FLOAT(.5,{range:[0,1]}),this.freqIncrease=ha.FLOAT(2,{range:[0,10]}),this.seed=ha.INTEGER(0,{range:[0,100],separatorAfter:!0}),this.useNormals=ha.BOOLEAN(0),this.attribName=ha.STRING(\\\\\\\"position\\\\\\\"),this.useRestAttributes=ha.BOOLEAN(0),this.restP=ha.STRING(\\\\\\\"restP\\\\\\\",{visibleIf:{useRestAttributes:!0}}),this.restN=ha.STRING(\\\\\\\"restN\\\\\\\",{visibleIf:{useRestAttributes:!0}}),this.operation=ha.INTEGER(F0.indexOf(I0.ADD),{menu:{entries:F0.map((t=>({name:t,value:F0.indexOf(t)})))}}),this.computeNormals=ha.BOOLEAN(1)}},B0=new p.a,z0=new p.a;class k0 extends uV{constructor(){super(...arguments),this.paramsConfig=D0,this._simplexBySeed=new Map,this._restPos=new p.a,this._restValue2=new d.a,this._restValue4=new _.a,this._noiseValueV=new p.a,this._currentAttribValueF=0,this._currentAttribValueV2=new d.a,this._currentAttribValueV3=new p.a,this._currentAttribValueV4=new _.a}static type(){return\\\\\\\"noise\\\\\\\"}static displayedInputNames(){return[\\\\\\\"geometry to add noise to\\\\\\\"]}initializeNode(){this.io.inputs.setCount(1),this.io.inputs.initInputsClonedState([Qi.FROM_NODE])}setOperation(t){this.p.operation.set(F0.indexOf(t))}async cook(t){const e=t[0],n=e.points(),i=this.pv.attribName;if(!e.hasAttrib(i))return this.states.error.set(`attribute ${i} not found`),void this.cookController.endCook();if(e.attribType(i)!=zs.NUMERIC)return this.states.error.set(`attribute ${i} is not a numeric attribute`),void this.cookController.endCook();const s=e.attribSize(this.pv.attribName),r=n[0];if(!r)return void this.setCoreGroup(e);const o=r.attribValue(i);if(m.isString(o))return void this.states.error.set(\\\\\\\"cannot add noise to a string attribute\\\\\\\");const a={octaves:this.pv.octaves,ampAttenuation:this.pv.ampAttenuation,freqIncrease:this.pv.freqIncrease};try{switch(s){case 1:this._cookForFloat(n,a);break;case 2:this._cookForV2(n,a);break;case 3:this._cookForV3(n,a);break;case 4:this._cookForV4(n,a)}}catch(t){console.error(\\\\\\\"sop/noise error\\\\\\\",t),this.states.error.set(`cook failed for (${this.path()}). make sure the required attributes are present`)}if(!this.io.inputs.cloneRequired(0))for(let t of e.geometries())t.getAttribute(i).needsUpdate=!0;this.pv.computeNormals&&e.computeVertexNormals(),this.setCoreGroup(e)}_cookForFloat(t,e){const n=this._getSimplex(),i=this.pv.useRestAttributes,s=this.pv.useNormals,r=this.pv.tamplitudeAttrib,o=this.pv.amplitude,a=F0[this.pv.operation],l=this.pv.attribName;for(let c of t){i?(c.attribValueVector3(this.pv.restP,B0),s&&c.attribValueVector3(this.pv.restN,z0),this._currentAttribValueF=B0.x):(c.getPosition(B0),s&&c.attribValueVector3(Ws.NORMAL,z0),this._currentAttribValueF=c.attribValueNumber(l));const t=r?this._amplitudeFromAttrib(c,o):o,h=this._noiseValue(s,n,t,e,B0,z0).x,u=k0._newAttribValueFromFloat(a,this._currentAttribValueF,h);c.setAttribValueFromNumber(l,u)}}_cookForV2(t,e){const n=this._getSimplex(),i=this.pv.useRestAttributes,s=this.pv.useNormals,r=this.pv.tamplitudeAttrib,o=this.pv.amplitude,a=F0[this.pv.operation],l=this.pv.attribName;for(let c of t){i?(c.attribValueVector3(this.pv.restP,B0),s&&c.attribValueVector3(this.pv.restN,z0),this._currentAttribValueV2.set(B0.x,B0.y)):(c.getPosition(B0),s&&c.attribValueVector3(Ws.NORMAL,z0),c.attribValueVector2(l,this._currentAttribValueV2));const t=r?this._amplitudeFromAttrib(c,o):o,h=this._noiseValue(s,n,t,e,B0,z0);this._restValue2.set(h.x,h.y);const u=this._restValue2,d=k0._newAttribValueFromVector2(a,this._currentAttribValueV2,u);c.setAttribValueFromVector2(l,d)}}_cookForV3(t,e){const n=this._getSimplex(),i=this.pv.useRestAttributes,s=this.pv.useNormals,r=this.pv.tamplitudeAttrib,o=this.pv.amplitude,a=F0[this.pv.operation],l=this.pv.attribName;for(let c of t){i?(c.attribValueVector3(this.pv.restP,B0),s&&c.attribValueVector3(this.pv.restN,z0),this._currentAttribValueV3.copy(B0)):(c.getPosition(B0),s&&c.attribValueVector3(Ws.NORMAL,z0),c.attribValueVector3(l,this._currentAttribValueV3));const t=r?this._amplitudeFromAttrib(c,o):o,h=this._noiseValue(s,n,t,e,B0,z0),u=k0._newAttribValueFromVector3(a,this._currentAttribValueV3,h);c.setAttribValueFromVector3(l,u)}}_cookForV4(t,e){const n=this._getSimplex(),i=this.pv.useRestAttributes,s=this.pv.useNormals,r=this.pv.tamplitudeAttrib,o=this.pv.amplitude,a=F0[this.pv.operation],l=this.pv.attribName;for(let c of t){i?(c.attribValueVector3(this.pv.restP,B0),s&&c.attribValueVector3(this.pv.restN,z0),this._currentAttribValueV4.set(B0.x,B0.y,B0.z,0)):(c.getPosition(B0),s&&c.attribValueVector3(Ws.NORMAL,z0),c.attribValueVector4(l,this._currentAttribValueV4));const t=r?this._amplitudeFromAttrib(c,o):o,h=this._noiseValue(s,n,t,e,B0,z0);this._restValue4.set(h.x,h.y,h.z,0);const u=this._restValue4,d=k0._newAttribValueFromVector4(a,this._currentAttribValueV4,u);c.setAttribValueFromVector4(l,d)}}_noiseValue(t,e,n,i,s,r){if(this._restPos.copy(s).add(this.pv.offset).multiply(this.pv.freq),t&&r){const t=n*this._fbm(e,i,this._restPos.x,this._restPos.y,this._restPos.z);return this._noiseValueV.copy(r),this._noiseValueV.multiplyScalar(t)}return this._noiseValueV.set(n*this._fbm(e,i,this._restPos.x+545,this._restPos.y+125454,this._restPos.z+2142),n*this._fbm(e,i,this._restPos.x-425,this._restPos.y-25746,this._restPos.z+95242),n*this._fbm(e,i,this._restPos.x+765132,this._restPos.y+21,this._restPos.z-9245)),this._noiseValueV}static _newAttribValueFromFloat(t,e,n){switch(t){case I0.ADD:return e+n;case I0.SET:return n;case I0.MULT:return e*n;case I0.DIVIDE:return e/n;case I0.SUBSTRACT:return e-n}os.unreachable(t)}static _newAttribValueFromVector2(t,e,n){switch(t){case I0.ADD:return e.add(n);case I0.SET:return n;case I0.MULT:return e.multiply(n);case I0.DIVIDE:return e.divide(n);case I0.SUBSTRACT:return e.sub(n)}os.unreachable(t)}static _newAttribValueFromVector3(t,e,n){switch(t){case I0.ADD:return e.add(n);case I0.SET:return n;case I0.MULT:return e.multiply(n);case I0.DIVIDE:return e.divide(n);case I0.SUBSTRACT:return e.sub(n)}os.unreachable(t)}static _newAttribValueFromVector4(t,e,n){switch(t){case I0.ADD:return e.add(n);case I0.SET:return n;case I0.MULT:return e.multiplyScalar(n.x);case I0.DIVIDE:return e.divideScalar(n.x);case I0.SUBSTRACT:return e.sub(n)}os.unreachable(t)}_amplitudeFromAttrib(t,e){const n=t.attribValue(this.pv.amplitudeAttrib);return m.isNumber(n)?n*e:n instanceof d.a||n instanceof p.a||n instanceof _.a?n.x*e:1}_fbm(t,e,n,i,s){let r=0,o=1;for(let a=0;a{s[3*t.index()+0]=e}));else{let t;for(let e=0;e{s[3*t.index()+1]=e}));else{let t;for(let e=0;e{s[3*t.index()+2]=e}));else{let t;for(let e=0;e{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{this.params.label.init([this.p.geometry],(()=>this.p.geometry.rawInput()))}))}))}async cook(t){const e=this.p.geometry.found_node();if(e)if(e.context()==ts.SOP){const t=await e.compute();this.import_input(e,t)}else this.states.error.set(\\\\\\\"found node is not a geometry\\\\\\\");else this.states.error.set(`node not found at path '${this.pv.geometry}'`)}import_input(t,e){let n;null!=(n=e.coreContentCloned())?this.setCoreGroup(n):this.states.error.set(\\\\\\\"invalid target\\\\\\\")}}class X0 extends aV{static type(){return\\\\\\\"objectProperties\\\\\\\"}cook(t,e){const n=t[0];for(let t of n.objects())e.applyToChildren?t.traverse((t=>{this._update_object(t,e)})):this._update_object(t,e);return n}_update_object(t,e){e.tname&&(t.name=e.name),e.trenderOrder&&(t.renderOrder=e.renderOrder),e.tfrustumCulled&&(t.frustumCulled=e.frustumCulled),e.tmatrixAutoUpdate&&(t.matrixAutoUpdate=e.matrixAutoUpdate),e.tvisible&&(t.visible=e.visible),e.tcastShadow&&(t.castShadow=e.castShadow),e.treceiveShadow&&(t.receiveShadow=e.receiveShadow)}}X0.DEFAULT_PARAMS={applyToChildren:!0,tname:!1,name:\\\\\\\"\\\\\\\",trenderOrder:!1,renderOrder:0,tfrustumCulled:!1,frustumCulled:!0,tmatrixAutoUpdate:!1,matrixAutoUpdate:!1,tvisible:!1,visible:!0,tcastShadow:!1,castShadow:!0,treceiveShadow:!1,receiveShadow:!0},X0.INPUT_CLONED_STATE=Qi.FROM_NODE;const Y0=X0.DEFAULT_PARAMS;const $0=new class extends ua{constructor(){super(...arguments),this.applyToChildren=ha.BOOLEAN(Y0.applyToChildren,{separatorAfter:!0}),this.tname=ha.BOOLEAN(Y0.tname),this.name=ha.STRING(Y0.name,{visibleIf:{tname:!0},separatorAfter:!0}),this.trenderOrder=ha.BOOLEAN(Y0.trenderOrder),this.renderOrder=ha.INTEGER(Y0.renderOrder,{visibleIf:{trenderOrder:!0},range:[0,10],rangeLocked:[!1,!1],separatorAfter:!0}),this.tfrustumCulled=ha.BOOLEAN(Y0.tfrustumCulled),this.frustumCulled=ha.BOOLEAN(Y0.frustumCulled,{visibleIf:{tfrustumCulled:!0},separatorAfter:!0}),this.tmatrixAutoUpdate=ha.BOOLEAN(Y0.tmatrixAutoUpdate),this.matrixAutoUpdate=ha.BOOLEAN(Y0.matrixAutoUpdate,{visibleIf:{tmatrixAutoUpdate:!0},separatorAfter:!0}),this.tvisible=ha.BOOLEAN(Y0.tvisible),this.visible=ha.BOOLEAN(Y0.visible,{visibleIf:{tvisible:!0},separatorAfter:!0}),this.tcastShadow=ha.BOOLEAN(Y0.tcastShadow),this.castShadow=ha.BOOLEAN(Y0.castShadow,{visibleIf:{tcastShadow:!0},separatorAfter:!0}),this.treceiveShadow=ha.BOOLEAN(Y0.treceiveShadow),this.receiveShadow=ha.BOOLEAN(Y0.receiveShadow,{visibleIf:{treceiveShadow:!0}})}};class J0 extends uV{constructor(){super(...arguments),this.paramsConfig=$0}static type(){return\\\\\\\"objectProperties\\\\\\\"}static displayedInputNames(){return[\\\\\\\"objects to change properties of\\\\\\\"]}initializeNode(){this.io.inputs.setCount(1),this.io.inputs.initInputsClonedState(X0.INPUT_CLONED_STATE)}async cook(t){this._operation=this._operation||new X0(this.scene(),this.states);const e=this._operation.cook(t,this.pv);this.setCoreGroup(e)}}const Z0=new class extends ua{};class K0 extends uV{constructor(){super(...arguments),this.paramsConfig=Z0,this._input_configs_by_operation_container=new WeakMap}static type(){return Bl}initializeNode(){this.io.inputs.initInputsClonedState(Qi.FROM_NODE)}set_output_operation_container(t){this._output_operation_container=t}output_operation_container(){return this._output_operation_container}add_input_config(t,e){let n=this._input_configs_by_operation_container.get(t);n||(n=new Map,this._input_configs_by_operation_container.set(t,n)),n.set(e.operation_input_index,e.node_input_index)}add_operation_container_with_path_param_resolve_required(t){this._operation_containers_requiring_resolve||(this._operation_containers_requiring_resolve=[]),this._operation_containers_requiring_resolve.push(t)}resolve_operation_containers_path_params(){if(this._operation_containers_requiring_resolve)for(let t of this._operation_containers_requiring_resolve)t.resolve_path_params(this)}async cook(t){if(this._output_operation_container){this._output_operation_container.setDirty();const e=await this._output_operation_container.compute(t,this._input_configs_by_operation_container);e&&this.setCoreGroup(e)}}}class Q0 extends _f{constructor(t){super(),this._uv_name=t}set_texture_allocations_controller(t){this._texture_allocations_controller=t}handle_globals_node(t,e,n){if(!this._texture_allocations_controller)return;const i=t.io.outputs.namedOutputConnectionPointsByName(e),s=t.glVarName(e);if(this._texture_allocations_controller.variable(e)&&i){const r=i.type(),o=`${r} ${s} = ${this.read_attribute(t,r,e,n)}`;n.addBodyLines(t,[o])}else this.globals_geometry_handler=this.globals_geometry_handler||new Pf,this.globals_geometry_handler.handle_globals_node(t,e,n)}read_attribute(t,e,n,i){if(!this._texture_allocations_controller)return;const s=this._texture_allocations_controller.variable(n);if(!s)return Pf.read_attribute(t,e,n,i);{this.add_particles_sim_uv_attribute(t,i);const e=s.component(),n=s.allocation();if(n){const s=n.textureName(),r=new Nf(t,Uo.SAMPLER_2D,s);i.addDefinitions(t,[r]);return`texture2D( ${s}, ${this._uv_name} ).${e}`}}}add_particles_sim_uv_attribute(t,e){const n=new Sf(t,Uo.VEC2,Q0.UV_ATTRIB),i=new Lf(t,Uo.VEC2,Q0.UV_VARYING);e.addDefinitions(t,[n,i],Mf.VERTEX),e.addDefinitions(t,[i],Mf.FRAGMENT),e.addBodyLines(t,[`${Q0.UV_VARYING} = ${Q0.UV_ATTRIB}`],Mf.VERTEX)}}Q0.UV_ATTRIB=\\\\\\\"particles_sim_uv_attrib\\\\\\\",Q0.UV_VARYING=\\\\\\\"particles_sim_uv_varying\\\\\\\",Q0.PARTICLE_SIM_UV=\\\\\\\"particleUV\\\\\\\";class t1{constructor(t){this.node=t,this._particles_group_objects=[],this._all_shader_names=[],this._all_uniform_names=[],this.globals_handler=new Q0(Q0.UV_VARYING)}setShadersByName(t){this._shaders_by_name=t,this._all_shader_names=[],this._all_uniform_names=[],this._shaders_by_name.forEach(((t,e)=>{this._all_shader_names.push(e),this._all_uniform_names.push(`texture_${e}`)})),this.reset_render_material()}assign_render_material(){if(this._render_material){for(let t of this._particles_group_objects){const e=t;e.geometry&&(e.material=this._render_material,yr.applyCustomMaterials(e,this._render_material),e.matrixAutoUpdate=!1,e.updateMatrix())}this._render_material.needsUpdate=!0,this.update_render_material_uniforms()}}update_render_material_uniforms(){var t;if(!this._render_material)return;let e,n;for(let i=0;i=e&&(null==this._lastSimulatedFrame&&(this._lastSimulatedFrame=e-1),null==this._lastSimulatedTime&&(this._lastSimulatedTime=this.node.scene().time()),t>this._lastSimulatedFrame&&this._computeSimulation(t-this._lastSimulatedFrame))}_computeSimulation(t=1){if(!this._gpuCompute||null==this._lastSimulatedTime)return;this._updateSimulationMaterialUniforms();for(let e=0;et)return void this.node.states.error.set(`max particles is set to (${this.node.pv.texturesSize.x}x${this.node.pv.texturesSize.y}=) ${t}`);this._usedTexturesSize.copy(this.node.pv.texturesSize)}this._forceTimeDependent(),this._initParticlesUVs(),this.node.renderController.reset_render_material();const n=await li.renderersController.waitForRenderer();if(n?this._renderer=n:this.node.states.error.set(\\\\\\\"no renderer found\\\\\\\"),!this._renderer)return;const i=new n1(this._usedTexturesSize.x,this._usedTexturesSize.y,this._renderer);if(i.setDataType(this._dataType()),this._gpuCompute=i,this._gpuCompute){this._lastSimulatedFrame=void 0,this._variablesByName.forEach(((t,e)=>{t.renderTargets[0].dispose(),t.renderTargets[1].dispose(),this._variablesByName.delete(e)})),this._allVariables=[],null===(t=this._shadersByName)||void 0===t||t.forEach(((t,e)=>{if(this._gpuCompute){const n=this._gpuCompute.addVariable(this._textureNameForShaderName(e),t,this._createdTexturesByName.get(e));this._variablesByName.set(e,n),this._allVariables.push(n)}})),null===(e=this._variablesByName)||void 0===e||e.forEach(((t,e)=>{this._gpuCompute&&this._gpuCompute.setVariableDependencies(t,this._allVariables)})),this._createTextureRenderTargets(),this._fillTextures(),this._createSimulationMaterialUniforms();var s=this._gpuCompute.init();null!==s&&(console.error(s),this.node.states.error.set(s))}else this.node.states.error.set(\\\\\\\"failed to create the GPUComputationRenderer\\\\\\\")}_forceTimeDependent(){this._graph_node||(this._graph_node=new Mi(this.node.scene(),\\\\\\\"gpu_compute\\\\\\\"),this._graph_node.addGraphInput(this.node.scene().timeController.graphNode),this._graph_node.addPostDirtyHook(\\\\\\\"on_time_change\\\\\\\",this._onGraphNodeDirty.bind(this)))}_onGraphNodeDirty(){this.node.isOnStartFrame()?this.node.setDirty():this.computeSimilationIfRequired()}materials(){const t=[];return this._variablesByName.forEach(((e,n)=>{t.push(e.material)})),t}_createSimulationMaterialUniforms(){const t=this.node.assemblerController,e=null==t?void 0:t.assembler;if(!e&&!this._persistedTextureAllocationsController)return;const n=[];this._variablesByName.forEach(((t,e)=>{n.push(t.material)}));const i=this._readonlyAllocations();for(let t of n)t.uniforms[TR.TIME]={value:this.node.scene().time()},t.uniforms[TR.DELTA_TIME]={value:this.node.scene().time()},i&&this._assignReadonlyTextures(t,i);if(e)for(let t of n)for(let n of e.param_configs())t.uniforms[n.uniform_name]=n.uniform;else{const t=this.node.persisted_config.loaded_data();if(t){const e=this.node.persisted_config.uniforms();if(e){const s=t.param_uniform_pairs;for(let t of s){const s=t[0],r=t[1],o=this.node.params.get(s),a=e[r];for(let t of n)t.uniforms[r]=a,i&&this._assignReadonlyTextures(t,i);o&&a&&o.options.setOption(\\\\\\\"callback\\\\\\\",(()=>{for(let t of n)tg.callback(o,t.uniforms[r])}))}}}}}_assignReadonlyTextures(t,e){for(let n of e){const e=n.shaderName(),i=this._createdTexturesByName.get(e);if(i){const n=this._textureNameForShaderName(e);t.uniforms[n]={value:i}}}}_updateSimulationMaterialUniforms(){for(let t of this._allVariables)t.material.uniforms[TR.TIME].value=this.node.scene().time(),t.material.uniforms[TR.DELTA_TIME].value=this._deltaTime}_initParticlesUVs(){var t=new Float32Array(2*this._points.length);let e=0;for(var n=0,i=0;i=t.length));s++);const r=Q0.UV_ATTRIB;if(this._particlesCoreGroup)for(let e of this._particlesCoreGroup.coreGeometries()){const n=e.geometry(),i=e.markedAsInstance()?I$:C.a;n.setAttribute(r,new i(t,2))}}createdTexturesByName(){return this._createdTexturesByName}_fillTextures(){const t=this._textureAllocationsController();t&&this._createdTexturesByName.forEach(((e,n)=>{const i=t.allocationForShaderName(n);if(!i)return void console.warn(`no allocation found for shader ${n}`);const s=i.variables();if(!s)return void console.warn(\\\\\\\"allocation has no variables\\\\\\\");const r=e.image.data;for(let t of s){const e=t.position();let n=t.name();const i=this._points[0];if(i){if(i.hasAttrib(n)){const t=i.attribSize(n);let s=e;for(let e of this._points){if(1==t){const t=e.attribValue(n);r[s]=t}else e.attribValue(n).toArray(r,s);s+=4}}}}}))}resetGpuCompute(){this._gpuCompute=void 0,this._simulationRestartRequired=!0}setRestartNotRequired(){this._simulationRestartRequired=!1}resetGpuComputeAndSetDirty(){this.resetGpuCompute(),this.node.setDirty()}resetParticleGroups(){this._particlesCoreGroup=void 0}initialized(){return null!=this._particlesCoreGroup&&null!=this._gpuCompute}_createTextureRenderTargets(){this._createdTexturesByName.forEach(((t,e)=>{t.dispose()})),this._createdTexturesByName.clear(),this._variablesByName.forEach(((t,e)=>{this._gpuCompute&&this._createdTexturesByName.set(e,this._gpuCompute.createTexture())}));const t=this._readonlyAllocations();if(t&&this._gpuCompute)for(let e of t)this._createdTexturesByName.set(e.shaderName(),this._gpuCompute.createTexture())}_textureAllocationsController(){var t;return(null===(t=this.node.assemblerController)||void 0===t?void 0:t.assembler.textureAllocationsController())||this._persistedTextureAllocationsController}_readonlyAllocations(){var t;return null===(t=this._textureAllocationsController())||void 0===t?void 0:t.readonlyAllocations()}restartSimulationIfRequired(){this._simulationRestartRequired&&this._restartSimulation()}_restartSimulation(){this._lastSimulatedTime=void 0,this._createTextureRenderTargets();this._getPoints()&&(this._fillTextures(),this._variablesByName.forEach(((t,e)=>{const n=this._createdTexturesByName.get(e);this._gpuCompute&&n&&(this._gpuCompute.renderTexture(n,t.renderTargets[0]),this._gpuCompute.renderTexture(n,t.renderTargets[1]))})))}_getPoints(){if(!this._particlesCoreGroup)return;let t=this._particlesCoreGroup.coreGeometries();const e=t[0];if(e){const n=e.markedAsInstance(),i=[];for(let e of t)e.markedAsInstance()==n&&i.push(e);const s=[];for(let t of i)for(let e of t.points())s.push(e);return s}return[]}}class o1{constructor(t,e){if(this._name=t,this._size=e,this._position=-1,this._readonly=!1,!t)throw\\\\\\\"TextureVariable requires a name\\\\\\\"}merge(t){var e;t.readonly()||this.setReadonly(!1),null===(e=t.graphNodeIds())||void 0===e||e.forEach(((t,e)=>{this.addGraphNodeId(e)}))}setReadonly(t){this._readonly=t}readonly(){return this._readonly}setAllocation(t){this._allocation=t}allocation(){return this._allocation}graphNodeIds(){return this._graph_node_ids}addGraphNodeId(t){this._graph_node_ids=this._graph_node_ids||new Map,this._graph_node_ids.set(t,!0)}name(){return this._name}size(){return this._size}setPosition(t){this._position=t}position(){return this._position}component(){return\\\\\\\"xyzw\\\\\\\".split(\\\\\\\"\\\\\\\").splice(this._position,this._size).join(\\\\\\\"\\\\\\\")}static fromJSON(t){return new o1(t.name,t.size)}toJSON(t){const e=[];return this._graph_node_ids&&this._graph_node_ids.forEach(((n,i)=>{const s=t.graph.nodeFromId(i);if(s){const t=s.path();t&&e.push(t)}})),{name:this.name(),size:this.size(),nodes:e}}}class a1{constructor(){this._size=0}addVariable(t){this._variables=this._variables||[],this._variables.push(t),t.setPosition(this._size),t.setAllocation(this),this._size+=t.size()}hasSpaceForVariable(t){return this._size+t.size()<=4}shaderName(){var t;return((null===(t=this.variables())||void 0===t?void 0:t.map((t=>t.name())))||[\\\\\\\"no_variables_allocated\\\\\\\"]).join(\\\\\\\"_SEPARATOR_\\\\\\\")}textureName(){return`texture_${this.shaderName()}`}variables(){return this._variables}variablesForInputNode(t){var e;return null===(e=this._variables)||void 0===e?void 0:e.filter((e=>{var n;return(null===(n=e.graphNodeIds())||void 0===n?void 0:n.has(t.graphNodeId()))||!1}))}inputNamesForNode(t){const e=this.variablesForInputNode(t);if(e)return t.type()==ps.ATTRIBUTE?[wf.INPUT_NAME]:e.map((t=>t.name()))}variable(t){if(this._variables)for(let e of this._variables)if(e.name()==t)return e}static fromJSON(t){const e=new a1;for(let n of t){const t=o1.fromJSON(n);e.addVariable(t)}return e}toJSON(t){return this._variables?this._variables.map((e=>e.toJSON(t))):[]}}const l1=[\\\\\\\"position\\\\\\\",\\\\\\\"normal\\\\\\\",\\\\\\\"color\\\\\\\",\\\\\\\"uv\\\\\\\"];class c1{constructor(){this._writableAllocations=[],this._readonlyAllocations=[]}static _sortNodes(t){const e=t.filter((t=>t.type()==OF.type())),n=t.filter((t=>t.type()!=OF.type())),i=n.map((t=>t.name())).sort(),s=new Map;for(let t of n)s.set(t.name(),t);for(let t of i){const n=s.get(t);n&&e.push(n)}return e}allocateConnectionsFromRootNodes(t,e){const n=[];t=c1._sortNodes(t),e=c1._sortNodes(e);for(let e of t){const t=e.graphNodeId();switch(e.type()){case OF.type():for(let i of e.io.inputs.namedInputConnectionPoints()){if(e.io.inputs.named_input(i.name())){const e=new o1(i.name(),Wo[i.type()]);e.addGraphNodeId(t),n.push(e)}}break;case wf.type():{const i=e,s=i.connected_input_node(),r=i.connected_input_connection_point();if(s&&r){const e=new o1(i.attribute_name,Wo[r.type()]);e.addGraphNodeId(t),n.push(e)}break}}}for(let t of e){const e=t.graphNodeId();switch(t.type()){case II.type():{const i=t;for(let t of i.io.outputs.used_output_names()){if(l1.includes(t)){const s=i.io.outputs.namedOutputConnectionPointsByName(t);if(s){const i=s.type(),r=new o1(t,Wo[i]);r.addGraphNodeId(e),n.push(r)}}}break}case wf.type():{const i=t,s=i.output_connection_point();if(s){const t=new o1(i.attribute_name,Wo[s.type()]);i.isExporting()||t.setReadonly(!0),t.addGraphNodeId(e),n.push(t)}break}}}this._allocateVariables(n)}_allocateVariables(t){const e=f.sortBy(t,(t=>-t.size())),n=this._ensureVariablesAreUnique(e);for(let t of n)t.readonly()?this._allocateVariable(t,this._readonlyAllocations):this._allocateVariable(t,this._writableAllocations)}_ensureVariablesAreUnique(t){const e=new Map;for(let n of t)h.pushOnArrayAtEntry(e,n.name(),n);const n=[];return e.forEach(((t,e)=>{const i=t[0];n.push(i);for(let e=1;et.shaderName()));return f.uniq(t)}createShaderConfigs(){return[]}allocationForShaderName(t){const e=this._writableAllocations.filter((e=>e.shaderName()==t))[0];return e||this._readonlyAllocations.filter((e=>e.shaderName()==t))[0]}inputNamesForShaderName(t,e){const n=this.allocationForShaderName(e);if(n)return n.inputNamesForNode(t)}variable(t){for(let e of this._writableAllocations){const n=e.variable(t);if(n)return n}for(let e of this._readonlyAllocations){const n=e.variable(t);if(n)return n}}variables(){const t=this._writableAllocations.map((t=>t.variables()||[])).flat(),e=this._writableAllocations.map((t=>t.variables()||[])).flat();return t.concat(e)}hasVariable(t){return this.variables().map((t=>t.name())).includes(t)}static fromJSON(t){const e=new c1;for(let n of t.writable){const t=n[Object.keys(n)[0]],i=a1.fromJSON(t);e._addWritableAllocation(i)}for(let n of t.readonly){const t=n[Object.keys(n)[0]],i=a1.fromJSON(t);e._addReadonlyAllocation(i)}return e}toJSON(t){return{writable:this._writableAllocations.map((e=>({[e.shaderName()]:e.toJSON(t)}))),readonly:this._readonlyAllocations.map((e=>({[e.shaderName()]:e.toJSON(t)})))}}print(t){console.warn(JSON.stringify(this.toJSON(t),[\\\\\\\"\\\\\\\"],2))}}class h1 extends Kf{constructor(t){super(t),this.node=t}toJSON(){const t=this.node.assemblerController;if(!t)return;const e={};this.node.shaders_by_name().forEach(((t,n)=>{e[n]=t}));const n=t.assembler.textureAllocationsController().toJSON(this.node.scene()),i=[],s=new F,r=t.assembler.param_configs();for(let t of r)i.push([t.name(),t.uniform_name]),s.uniforms[t.uniform_name]=t.uniform;const o=this._materialToJson(s,{node:this.node,suffix:\\\\\\\"main\\\\\\\"});return{shaders_by_name:e,texture_allocations:n,param_uniform_pairs:i,uniforms_owner:o||{}}}load(t){li.playerMode()&&(this._loaded_data=t,this.node.init_with_persisted_config())}loaded_data(){return this._loaded_data}shaders_by_name(){if(this._loaded_data){const t=new Map,e=Object.keys(this._loaded_data.shaders_by_name);for(let n of e)t.set(n,this._loaded_data.shaders_by_name[n]);return t}}texture_allocations_controller(){if(this._loaded_data)return c1.fromJSON(this._loaded_data.texture_allocations)}uniforms(){if(this._loaded_data){const t=this._loadMaterial(this._loaded_data.uniforms_owner);return(null==t?void 0:t.uniforms)||{}}}}const u1=new class extends ua{constructor(){super(...arguments),this.startFrame=ha.FLOAT(Nl.START_FRAME,{range:[0,1e3],rangeLocked:[!0,!1]}),this.autoTexturesSize=ha.BOOLEAN(1),this.maxTexturesSize=ha.VECTOR2([1024,1024],{visibleIf:{autoTexturesSize:1}}),this.texturesSize=ha.VECTOR2([64,64],{visibleIf:{autoTexturesSize:0}}),this.dataType=ha.INTEGER(0,{menu:{entries:i1.map(((t,e)=>({value:e,name:t})))}}),this.reset=ha.BUTTON(null,{callback:(t,e)=>{d1.PARAM_CALLBACK_reset(t)}}),this.material=ha.OPERATOR_PATH(\\\\\\\"\\\\\\\",{nodeSelection:{context:ts.MAT},dependentOnFoundNode:!1})}};class d1 extends uV{constructor(){super(...arguments),this.paramsConfig=u1,this._assembler_controller=this._create_assembler_controller(),this.persisted_config=new h1(this),this.globals_handler=new Q0(Q0.PARTICLE_SIM_UV),this._shaders_by_name=new Map,this.gpuController=new r1(this),this.renderController=new t1(this),this._reset_material_if_dirty_bound=this._reset_material_if_dirty.bind(this),this._children_controller_context=ts.GL}static type(){return\\\\\\\"particlesSystemGpu\\\\\\\"}dispose(){super.dispose(),this.gpuController.dispose()}get assemblerController(){return this._assembler_controller}usedAssembler(){return jn.GL_PARTICLES}_create_assembler_controller(){return li.assemblersRegister.assembler(this,this.usedAssembler())}shaders_by_name(){return this._shaders_by_name}static require_webgl2(){return!0}static PARAM_CALLBACK_reset(t){t.PARAM_CALLBACK_reset()}PARAM_CALLBACK_reset(){this.gpuController.resetGpuComputeAndSetDirty()}static displayedInputNames(){return[\\\\\\\"points to emit particles from\\\\\\\"]}initializeNode(){this.io.inputs.setCount(1),this.io.inputs.initInputsClonedState(Qi.NEVER),this.addPostDirtyHook(\\\\\\\"_reset_material_if_dirty\\\\\\\",this._reset_material_if_dirty_bound)}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}childrenAllowed(){return this.assemblerController?super.childrenAllowed():(this.scene().markAsReadOnly(this),!1)}async _reset_material_if_dirty(){this.p.material.isDirty()&&(this.renderController.reset_render_material(),this.isOnStartFrame()||await this.renderController.init_render_material())}isOnStartFrame(){return this.scene().frame()==this.pv.startFrame}async cook(t){this.gpuController.setRestartNotRequired();const e=t[0];this.compileIfRequired();const n=this.isOnStartFrame();n&&this.gpuController.resetParticleGroups(),this.gpuController.initialized()||await this.gpuController.init(e),this.renderController.initialized()||(this.renderController.init_core_group(e),await this.renderController.init_render_material()),this.gpuController.restartSimulationIfRequired(),this.gpuController.computeSimilationIfRequired(),n?this.setCoreGroup(e):this.cookController.endCook()}async compileIfRequired(){var t;(null===(t=this.assemblerController)||void 0===t?void 0:t.compileRequired())&&await this.run_assembler()}async run_assembler(){const t=this.assemblerController;if(!t)return;const e=this._find_export_nodes();if(e.length>0){const n=e;t.set_assembler_globals_handler(this.globals_handler),t.assembler.set_root_nodes(n),t.assembler.compile(),t.post_compile()}const n=t.assembler.shaders_by_name();this._setShaderNames(n)}_setShaderNames(t){this._shaders_by_name=t,this.gpuController.setShadersByName(this._shaders_by_name),this.renderController.setShadersByName(this._shaders_by_name),this.gpuController.resetGpuCompute(),this.gpuController.resetParticleGroups()}init_with_persisted_config(){const t=this.persisted_config.shaders_by_name(),e=this.persisted_config.texture_allocations_controller();t&&e&&(this._setShaderNames(t),this.gpuController.setPersistedTextureAllocationController(e))}_find_export_nodes(){const t=Df.findAttributeExportNodes(this),e=Df.findOutputNodes(this);if(e.length>1)return this.states.error.set(\\\\\\\"only one output node is allowed\\\\\\\"),[];const n=e[0];return n&&t.push(n),t}}class p1 extends aV{static type(){return\\\\\\\"peak\\\\\\\"}cook(t,e){const n=t[0];let i,s;for(let t of n.objects())t.traverse((t=>{let n;if(null!=(n=t.geometry)){for(s of(i=new fr(n),i.points())){const t=s.normal(),n=s.position().clone().add(t.multiplyScalar(e.amount));s.setPosition(n)}i.geometry().getAttribute(\\\\\\\"position\\\\\\\").needsUpdate=!0}}));return t[0]}}p1.DEFAULT_PARAMS={amount:0};const _1=p1.DEFAULT_PARAMS;const m1=new class extends ua{constructor(){super(...arguments),this.amount=ha.FLOAT(_1.amount,{range:[-1,1]})}};class f1 extends uV{constructor(){super(...arguments),this.paramsConfig=m1}static type(){return\\\\\\\"peak\\\\\\\"}initializeNode(){this.io.inputs.setCount(1),this.io.inputs.initInputsClonedState(Qi.FROM_NODE)}cook(t){this._operation=this._operation||new p1(this.scene(),this.states);const e=this._operation.cook(t,this.pv);this.setCoreGroup(e)}}const g1=new p.a(0,0,1),v1=new p.a(0,0,1),y1=new p.a(0,1,0);class x1 extends aV{constructor(){super(...arguments),this._core_transform=new bU,this._size=new p.a,this._center=new p.a,this._segmentsCount=new d.a(1,1)}static type(){return\\\\\\\"plane\\\\\\\"}cook(t,e){const n=t[0];return n?this._cook_with_input(n,e):this._cook_without_input(e)}_cook_without_input(t){const e=this._create_plane(t.size,t);this._core_transform.rotateGeometry(e,g1,t.direction);const n=this._core_transform.translationMatrix(t.center);return e.applyMatrix4(n),this.createCoreGroupFromGeometry(e)}_cook_with_input(t,e){const n=t.boundingBox();n.getSize(this._size),n.getCenter(this._center);const i=new d.a(this._size.x,this._size.z),s=this._create_plane(i,e);this._core_transform.rotateGeometry(s,v1,y1);const r=this._core_transform.translationMatrix(this._center);return s.applyMatrix4(r),this.createCoreGroupFromGeometry(s)}_create_plane(t,e){return t=t.clone(),e.useSegmentsCount?(this._segmentsCount.x=Math.floor(e.segments.x),this._segmentsCount.y=Math.floor(e.segments.y)):e.stepSize>0&&(this._segmentsCount.x=Math.floor(t.x/e.stepSize),this._segmentsCount.y=Math.floor(t.y/e.stepSize),t.x=this._segmentsCount.x*e.stepSize,t.y=this._segmentsCount.y*e.stepSize),new L(t.x,t.y,this._segmentsCount.x,this._segmentsCount.y)}}x1.DEFAULT_PARAMS={size:new d.a(1,1),useSegmentsCount:!1,stepSize:1,segments:new d.a(1,1),direction:new p.a(0,1,0),center:new p.a(0,0,0)},x1.INPUT_CLONED_STATE=Qi.NEVER;const b1=x1.DEFAULT_PARAMS;const w1=new class extends ua{constructor(){super(...arguments),this.size=ha.VECTOR2(b1.size),this.useSegmentsCount=ha.BOOLEAN(b1.useSegmentsCount),this.stepSize=ha.FLOAT(b1.stepSize,{range:[.001,1],rangeLocked:[!1,!1],visibleIf:{useSegmentsCount:0}}),this.segments=ha.VECTOR2(b1.segments,{visibleIf:{useSegmentsCount:1}}),this.direction=ha.VECTOR3(b1.direction),this.center=ha.VECTOR3(b1.center)}};class T1 extends uV{constructor(){super(...arguments),this.paramsConfig=w1}static type(){return\\\\\\\"plane\\\\\\\"}static displayedInputNames(){return[\\\\\\\"geometry to create plane from (optional)\\\\\\\"]}initializeNode(){this.io.inputs.setCount(0,1),this.io.inputs.initInputsClonedState(x1.INPUT_CLONED_STATE)}cook(t){this._operation=this._operation||new x1(this.scene(),this.states);const e=this._operation.cook(t,this.pv);this.setCoreGroup(e)}}class A1 extends aV{static type(){return\\\\\\\"playerCapsule\\\\\\\"}cook(t,e){return this.createCoreGroupFromGeometry(Uy(e))}}A1.DEFAULT_PARAMS={radius:.5,height:1};const M1=A1.DEFAULT_PARAMS;const E1=new class extends ua{constructor(){super(...arguments),this.radius=ha.FLOAT(M1.radius,{range:[0,1],rangeLocked:[!0,!1]}),this.height=ha.FLOAT(M1.height,{range:[0,1],rangeLocked:[!0,!1]})}};class S1 extends uV{constructor(){super(...arguments),this.paramsConfig=E1}static type(){return\\\\\\\"playerCapsule\\\\\\\"}initializeNode(){this.io.inputs.setCount(0)}cook(t){this._operation=this._operation||new A1(this._scene,this.states);const e=this._operation.cook(t,this.pv);this.setCoreGroup(e)}}const C1=\\\\\\\"position\\\\\\\";const N1=new class extends ua{constructor(){super(...arguments),this.updateX=ha.BOOLEAN(0),this.x=ha.FLOAT(\\\\\\\"@P.x\\\\\\\",{visibleIf:{updateX:1},expression:{forEntities:!0}}),this.updateY=ha.BOOLEAN(0),this.y=ha.FLOAT(\\\\\\\"@P.y\\\\\\\",{visibleIf:{updateY:1},expression:{forEntities:!0}}),this.updateZ=ha.BOOLEAN(0),this.z=ha.FLOAT(\\\\\\\"@P.z\\\\\\\",{visibleIf:{updateZ:1},expression:{forEntities:!0}}),this.updateNormals=ha.BOOLEAN(1)}};class L1 extends uV{constructor(){super(...arguments),this.paramsConfig=N1,this._x_arrays_by_geometry_uuid=new Map,this._y_arrays_by_geometry_uuid=new Map,this._z_arrays_by_geometry_uuid=new Map}static type(){return\\\\\\\"point\\\\\\\"}static displayedInputNames(){return[\\\\\\\"points to move\\\\\\\"]}initializeNode(){this.io.inputs.setCount(1),this.io.inputs.initInputsClonedState(Qi.FROM_NODE)}async cook(t){const e=t[0];await this._eval_expressions_for_core_group(e)}async _eval_expressions_for_core_group(t){const e=t.coreObjects();for(let t=0;t{h[t.index()]=e}));else{let t;for(let e=0;e({name:t,value:e})))}}),this.center=ha.VECTOR3(z1.center.toArray()),this.longitude=ha.FLOAT(z1.longitude,{range:[0,360]}),this.latitude=ha.FLOAT(z1.latitude,{range:[-180,180]}),this.depth=ha.FLOAT(z1.depth,{range:[0,10]})}};class U1 extends uV{constructor(){super(...arguments),this.paramsConfig=k1}static type(){return\\\\\\\"polarTransform\\\\\\\"}static displayedInputNames(){return[\\\\\\\"geometries or objects to transform\\\\\\\"]}initializeNode(){this.io.inputs.setCount(1),this.io.inputs.initInputsClonedState(B1.INPUT_CLONED_STATE)}cook(t){this._operation=this._operation||new B1(this.scene(),this.states);const e=this._operation.cook(t,this.pv);this.setCoreGroup(e)}}class G1{static accumulated_curve_point_indices(t){let e=[];const n=[];let i,s=null;for(let r=0;r{r[t]=[]})),e.forEach(((e,o)=>{const a=t[e];n.forEach((t=>{const e=a.attribValue(t);let n;n=i[t]>1?e.toArray():[e],n.forEach((e=>{r[t].push(e)}))})),o>0&&(s.push(o-1),s.push(o))}));const o=new S.a;return n.forEach((t=>{const e=i[t],n=r[t];o.setAttribute(t,new C.c(n,e))})),o.setIndex(s),o}static line_segment_to_geometries(t){var e;const n=[],i=new fr(t),s=i.attribNames(),r=i.points(),o=(null===(e=t.getIndex())||void 0===e?void 0:e.array)||[],a=this.accumulated_curve_point_indices(o);if(a.length>0){const e=i.attribSizes();a.forEach(((i,o)=>{t=this.create_line_segment_geometry(r,i,s,e),n.push(t)}))}return n}}class V1{constructor(t,e,n){this.geometry=t,this.geometry1=e,this.geometry0=n}process(){const t=new fr(this.geometry0),e=new fr(this.geometry1),n=t.segments(),i=e.segments();if(0===n.length||0===i.length)return;const s=n.length{const n=l[e];p.push(t[0]),p.push(t[1]),p.push(n[0]+u),p.push(t[1]),p.push(n[1]+u),p.push(n[0]+u)}));f.intersection(r.attribNames(),o.attribNames()).forEach((t=>{const e=r.attribSize(t);let n,i=d.map((e=>e.attribValue(t)));n=1==e?i:i.map((t=>t.toArray())).flat(),this.geometry.setAttribute(t,new C.c(n,e))})),this.geometry.setIndex(p),this.geometry.computeVertexNormals()}}const H1=new p.a(0,0,0),j1=new p.a(1,1,1);const W1=new class extends ua{constructor(){super(...arguments),this.radius=ha.FLOAT(1),this.segmentsRadial=ha.INTEGER(8,{range:[3,20],rangeLocked:[!0,!1]}),this.closed=ha.BOOLEAN(0)}};class q1 extends uV{constructor(){super(...arguments),this.paramsConfig=W1,this._core_transform=new bU,this._geometries=[]}static type(){return\\\\\\\"polywire\\\\\\\"}static displayedInputNames(){return[\\\\\\\"lines to create tubes from\\\\\\\"]}initializeNode(){this.io.inputs.setCount(1),this.io.inputs.initInputsClonedState(Qi.NEVER)}cook(t){const e=t[0];this._geometries=[];for(let t of e.objects())t instanceof Ms.a&&this._create_tube(t);const n=fr.mergeGeometries(this._geometries);for(let t of this._geometries)t.dispose();if(n){const t=this.createObject(n,Ns.MESH);this.setObject(t)}else this.setObjects([])}_create_tube(t){var e;const n=t.geometry,i=new fr(n).points(),s=null===(e=n.getIndex())||void 0===e?void 0:e.array,r=G1.accumulated_curve_point_indices(s);for(let t of r){const e=t.map((t=>i[t]));this._create_tube_from_points(e)}}_create_tube_from_points(t){if(t.length<=1)return;const e=t.map((t=>t.attribValue(\\\\\\\"position\\\\\\\"))),n=JJ.create(this.pv.radius,this.pv.segmentsRadial),i=[];for(let t of e){const e=t,s=this._core_transform.matrix(e,H1,j1,1,xU),r=n.clone();r.applyMatrix4(s),i.push(r)}for(let t=0;t0){const e=i[t],n=i[t-1],s=this._skin(n,e);this._geometries.push(s)}}_skin(t,e){const n=new S.a;return new V1(n,t,e).process(),n}}const X1=\\\\\\\"dist\\\\\\\";class Y1 extends aV{constructor(){super(...arguments),this._matDoubleSideTmpSetter=new xK,this._raycaster=function(){const t=new eO;return t.firstHitOnly=!0,t}(),this._pointPos=new p.a,this._pointNormal=new p.a}static type(){return\\\\\\\"ray\\\\\\\"}cook(t,e){const n=t[0],i=t[1];return this._ray(n,i,e)}_ray(t,e,n){let i,s;this._matDoubleSideTmpSetter.setCoreGroupMaterialDoubleSided(e),n.addDistAttribute&&(t.hasAttrib(X1)||t.addNumericVertexAttrib(X1,1,-1));const r=t.points();for(let t of r)if(t.getPosition(this._pointPos),i=n.direction,n.useNormals&&(t.getNormal(this._pointNormal),i=this._pointNormal),this._raycaster.set(this._pointPos,i),s=this._raycaster.intersectObjects(e.objects(),!0)[0],s){if(n.transformPoints&&t.setPosition(s.point),n.addDistAttribute){const e=this._pointPos.distanceTo(s.point);console.log(e),t.setAttribValue(X1,e)}n.transferFaceNormals&&s.face&&t.setNormal(s.face.normal)}return this._matDoubleSideTmpSetter.restoreMaterialSideProperty(e),t}}Y1.DEFAULT_PARAMS={useNormals:!0,direction:new p.a(0,-1,0),transformPoints:!0,transferFaceNormals:!0,addDistAttribute:!1},Y1.INPUT_CLONED_STATE=[Qi.FROM_NODE,Qi.NEVER];const $1=Y1.DEFAULT_PARAMS;const J1=new class extends ua{constructor(){super(...arguments),this.useNormals=ha.BOOLEAN($1.useNormals),this.direction=ha.VECTOR3($1.direction.toArray(),{visibleIf:{useNormals:0}}),this.transformPoints=ha.BOOLEAN($1.transformPoints),this.transferFaceNormals=ha.BOOLEAN($1.transferFaceNormals),this.addDistAttribute=ha.BOOLEAN($1.addDistAttribute)}};class Z1 extends uV{constructor(){super(...arguments),this.paramsConfig=J1}static type(){return\\\\\\\"ray\\\\\\\"}static displayedInputNames(){return[\\\\\\\"geometry to move\\\\\\\",\\\\\\\"geometry to ray onto\\\\\\\"]}initializeNode(){this.io.inputs.setCount(2),this.io.inputs.initInputsClonedState(Y1.INPUT_CLONED_STATE)}cook(t){this._operation=this._operation||new Y1(this._scene,this.states);const e=this._operation.cook(t,this.pv);this.setCoreGroup(e)}}const K1={color:{value:null},tDiffuse:{value:null},textureMatrix:{value:null},opacity:{value:.5}},Q1=\\\\\\\"uniform mat4 textureMatrix;\\\\nvarying vec4 vUv;\\\\n\\\\nvoid main() {\\\\n\\\\n\\\\tvUv = textureMatrix * vec4( position, 1.0 );\\\\n\\\\tgl_Position = projectionMatrix * modelViewMatrix * vec4( position, 1.0 );\\\\n\\\\n}\\\\\\\",t2=\\\\\\\"uniform vec3 color;\\\\nuniform sampler2D tDiffuse;\\\\nvarying vec4 vUv;\\\\nuniform float opacity;\\\\n\\\\nfloat blendOverlay( float base, float blend ) {\\\\n\\\\n\\\\treturn( base < 0.5 ? ( 2.0 * base * blend ) : ( 1.0 - 2.0 * ( 1.0 - base ) * ( 1.0 - blend ) ) );\\\\n\\\\n}\\\\n\\\\nvec3 blendOverlay( vec3 base, vec3 blend ) {\\\\n\\\\n\\\\treturn vec3( blendOverlay( base.r, blend.r ), blendOverlay( base.g, blend.g ), blendOverlay( base.b, blend.b ) );\\\\n\\\\n}\\\\n\\\\nvoid main() {\\\\n\\\\n\\\\tvec4 base = texture2DProj( tDiffuse, vUv );\\\\n\\\\tgl_FragColor = vec4( blendOverlay( base.rgb, color ), opacity );\\\\n\\\\n}\\\\\\\",e2={minFilter:w.V,magFilter:w.V,format:w.ic};class n2 extends B.a{constructor(t,e){super(),this.geometry=t,this._options=e,this.type=\\\\\\\"Reflector\\\\\\\",this.reflectorPlane=new Y.a,this.normal=new p.a,this.reflectorWorldPosition=new p.a,this.cameraWorldPosition=new p.a,this.rotationMatrix=new A.a,this.lookAtPosition=new p.a(0,0,-1),this.clipPlane=new _.a,this.view=new p.a,this.target=new p.a,this.q=new _.a,this.textureMatrix=new A.a,this.virtualCamera=new tt.a,this.onBeforeRender=this._onBeforeRender.bind(this),this._onWindowResizeBound=this._onWindowResize.bind(this);const{width:n,height:i}=this._getRendererSize(this._options.renderer);this.renderTarget=new K(n,i,e2),Object(On.i)(n)&&Object(On.i)(i)||(this.renderTarget.texture.generateMipmaps=!1),this._coreRenderBlur=new OG(new d.a(n,i)),this.material=new F({uniforms:I.clone(K1),fragmentShader:t2,vertexShader:Q1}),this.material.uniforms.tDiffuse.value=this.renderTarget.texture,this.material.uniforms.color.value=this._options.color,this.material.uniforms.textureMatrix.value=this.textureMatrix,this.material.uniforms.opacity.value=this._options.opacity,this.material.transparent=this._options.opacity<1,this._addWindowResizeEvent()}_addWindowResizeEvent(){window.addEventListener(\\\\\\\"resize\\\\\\\",this._onWindowResizeBound.bind(this),!1)}_removeWindowResizeEvent(){window.removeEventListener(\\\\\\\"resize\\\\\\\",this._onWindowResizeBound.bind(this),!1)}_onWindowResize(){this.traverseAncestors((t=>{t.parent||t.uuid!=this._options.scene.uuid&&this._removeWindowResizeEvent()}));const{width:t,height:e}=this._getRendererSize(this._options.renderer);this.renderTarget.setSize(t,e),this._coreRenderBlur.setSize(t,e)}_getRendererSize(t){const e=t.domElement;return{width:e.width*this._options.pixelRatio,height:e.height*this._options.pixelRatio}}_onBeforeRender(t,e,n,i,s,r){if(!this._options.active)return;const o=n;if(this.reflectorWorldPosition.setFromMatrixPosition(this.matrixWorld),this.cameraWorldPosition.setFromMatrixPosition(o.matrixWorld),this.rotationMatrix.extractRotation(this.matrixWorld),this.normal.set(0,0,1),this.normal.applyMatrix4(this.rotationMatrix),this.view.subVectors(this.reflectorWorldPosition,this.cameraWorldPosition),!(this.view.dot(this.normal)>0)){this.view.reflect(this.normal).negate(),this.view.add(this.reflectorWorldPosition),this.rotationMatrix.extractRotation(o.matrixWorld),this.lookAtPosition.set(0,0,-1),this.lookAtPosition.applyMatrix4(this.rotationMatrix),this.lookAtPosition.add(this.cameraWorldPosition),this.target.subVectors(this.reflectorWorldPosition,this.lookAtPosition),this.target.reflect(this.normal).negate(),this.target.add(this.reflectorWorldPosition),this.virtualCamera.position.copy(this.view),this.virtualCamera.up.set(0,1,0),this.virtualCamera.up.applyMatrix4(this.rotationMatrix),this.virtualCamera.up.reflect(this.normal),this.virtualCamera.lookAt(this.target),this.virtualCamera.far=o.far,this.virtualCamera.updateMatrixWorld(),this.virtualCamera.projectionMatrix.copy(o.projectionMatrix),this.textureMatrix.set(.5,0,0,.5,0,.5,0,.5,0,0,.5,.5,0,0,0,1),this.textureMatrix.multiply(this.virtualCamera.projectionMatrix),this.textureMatrix.multiply(this.virtualCamera.matrixWorldInverse),this.textureMatrix.multiply(this.matrixWorld),this.reflectorPlane.setFromNormalAndCoplanarPoint(this.normal,this.reflectorWorldPosition),this.reflectorPlane.applyMatrix4(this.virtualCamera.matrixWorldInverse),this.clipPlane.set(this.reflectorPlane.normal.x,this.reflectorPlane.normal.y,this.reflectorPlane.normal.z,this.reflectorPlane.constant);var a=this.virtualCamera.projectionMatrix;this.q.x=(Math.sign(this.clipPlane.x)+a.elements[8])/a.elements[0],this.q.y=(Math.sign(this.clipPlane.y)+a.elements[9])/a.elements[5],this.q.z=-1,this.q.w=(1+a.elements[10])/a.elements[14],this.clipPlane.multiplyScalar(2/this.clipPlane.dot(this.q)),a.elements[2]=this.clipPlane.x,a.elements[6]=this.clipPlane.y,a.elements[10]=this.clipPlane.z+1-this._options.clipBias,a.elements[14]=this.clipPlane.w,this.renderTarget.texture.encoding=t.outputEncoding,this.visible=!1;var l=t.getRenderTarget(),c=t.xr.enabled,h=t.shadowMap.autoUpdate;if(t.xr.enabled=!1,t.shadowMap.autoUpdate=!1,t.setRenderTarget(this.renderTarget),t.state.buffers.depth.setMask(!0),!1===t.autoClear&&t.clear(),t.render(e,this.virtualCamera),this._options.tblur){const e=this._options.blur*this._options.pixelRatio,n=e*this._options.verticalBlurMult;if(this._coreRenderBlur.applyBlur(this.renderTarget,t,e,n),this._options.tblur2){const e=this._options.blur2*this._options.pixelRatio,n=e*this._options.verticalBlur2Mult;this._coreRenderBlur.applyBlur(this.renderTarget,t,e,n)}}t.xr.enabled=c,t.shadowMap.autoUpdate=h,t.setRenderTarget(l);var u=o.viewport;void 0!==u&&t.state.viewport(u),this.visible=!0}}}class i2 extends aV{static type(){return\\\\\\\"reflector\\\\\\\"}async cook(t,e){const n=t[0],i=[],s=await li.renderersController.firstRenderer();if(!s)return this.createCoreGroupFromObjects(i);const r=n.objectsWithGeo();for(let t of r){const n=new n2(t.geometry,{clipBias:e.clipBias,renderer:s,scene:this.scene().threejsScene(),pixelRatio:e.pixelRatio,color:e.color,opacity:e.opacity,active:e.active,tblur:e.tblur,blur:e.blur,verticalBlurMult:e.verticalBlurMult,tblur2:e.tblur2,blur2:e.blur2,verticalBlur2Mult:e.verticalBlur2Mult});n.position.copy(t.position),n.rotation.copy(t.rotation),n.scale.copy(t.scale),n.updateMatrix(),i.push(n)}return this.createCoreGroupFromObjects(i)}}i2.DEFAULT_PARAMS={active:!0,clipBias:.003,color:new D.a(1,1,1),opacity:1,pixelRatio:1,tblur:!1,blur:1,verticalBlurMult:1,tblur2:!1,blur2:1,verticalBlur2Mult:1},i2.INPUT_CLONED_STATE=Qi.NEVER;const s2=i2.DEFAULT_PARAMS;const r2=new class extends ua{constructor(){super(...arguments),this.active=ha.BOOLEAN(s2.active),this.clipBias=ha.FLOAT(s2.clipBias),this.color=ha.COLOR(s2.color.toArray()),this.opacity=ha.FLOAT(s2.opacity),this.pixelRatio=ha.INTEGER(s2.pixelRatio,{range:[1,4],rangeLocked:[!0,!1]}),this.tblur=ha.BOOLEAN(s2.tblur),this.blur=ha.FLOAT(s2.blur,{visibleIf:{tblur:1}}),this.verticalBlurMult=ha.FLOAT(s2.verticalBlurMult,{visibleIf:{tblur:1}}),this.tblur2=ha.BOOLEAN(s2.tblur2,{visibleIf:{tblur:1}}),this.blur2=ha.FLOAT(s2.blur2,{visibleIf:{tblur:1,tblur2:1}}),this.verticalBlur2Mult=ha.FLOAT(s2.verticalBlur2Mult,{visibleIf:{tblur:1,tblur2:1}})}};class o2 extends uV{constructor(){super(...arguments),this.paramsConfig=r2}static type(){return\\\\\\\"reflector\\\\\\\"}static displayedInputNames(){return[\\\\\\\"geometry to create a reflector from\\\\\\\"]}initializeNode(){this.io.inputs.setCount(0,1),this.io.inputs.initInputsClonedState(i2.INPUT_CLONED_STATE)}async cook(t){this._operation=this._operation||new i2(this._scene,this.states);const e=await this._operation.cook(t,this.pv);this.setCoreGroup(e)}}var a2=n(85);var l2;!function(t){t.POINTS_COUNT=\\\\\\\"pointsCount\\\\\\\",t.SEGMENT_LENGTH=\\\\\\\"segmentLength\\\\\\\"}(l2||(l2={}));const c2=[l2.POINTS_COUNT,l2.SEGMENT_LENGTH];var h2;!function(t){t.CENTRIPETAL=\\\\\\\"centripetal\\\\\\\",t.CHORDAL=\\\\\\\"chordal\\\\\\\",t.CATMULLROM=\\\\\\\"catmullrom\\\\\\\"}(h2||(h2={}));const u2=[h2.CENTRIPETAL,h2.CHORDAL,h2.CATMULLROM];const d2=new class extends ua{constructor(){super(...arguments),this.method=ha.INTEGER(c2.indexOf(l2.POINTS_COUNT),{menu:{entries:c2.map(((t,e)=>({name:t,value:e})))}}),this.curveType=ha.INTEGER(u2.indexOf(h2.CATMULLROM),{range:[0,2],rangeLocked:[!0,!0],menu:{entries:u2.map(((t,e)=>({name:t,value:e})))}}),this.tension=ha.FLOAT(.01,{range:[0,1],rangeLocked:[!0,!0]}),this.pointsCount=ha.INTEGER(100,{visibleIf:{method:c2.indexOf(l2.POINTS_COUNT)},range:[1,1e3],rangeLocked:[!0,!1]}),this.segmentLength=ha.FLOAT(1,{visibleIf:{method:c2.indexOf(l2.SEGMENT_LENGTH)}})}};class p2 extends uV{constructor(){super(...arguments),this.paramsConfig=d2}static type(){return\\\\\\\"resample\\\\\\\"}initializeNode(){this.io.inputs.setCount(1)}cook(t){const e=t[0],n=[];if(this.pv.pointsCount>=2){const t=e.coreObjects();for(let e=0;ei[t])),n=this._create_curve_from_points(e);n&&o.push(n)}const a=ur(o);return this.createObject(a,Ns.LINE_SEGMENTS)}_create_curve_from_points(t){if(t.length<=1)return;const e=t.map((t=>t.attribValue(\\\\\\\"position\\\\\\\"))),n=u2[this.pv.curveType],i=this.pv.tension,s=new a2.a(e,!1,n,i),r=this._get_points_from_curve(s);let o=[];const a=[];for(let t=0;t0&&(a.push(t-1),a.push(t))}const l=new S.a;return l.setAttribute(\\\\\\\"position\\\\\\\",new C.c(o.flat(),3)),l.setIndex(a),l}_get_points_from_curve(t){const e=c2[this.pv.method];switch(e){case l2.POINTS_COUNT:return t.getSpacedPoints(Math.max(2,this.pv.pointsCount));case l2.SEGMENT_LENGTH:var n=t.getLength(),i=0!==this.pv.segmentLength?1+n/this.pv.segmentLength:2;return i=Math.max(2,i),t.getSpacedPoints(i)}os.unreachable(e)}}class _2 extends aV{static type(){return\\\\\\\"restAttributes\\\\\\\"}cook(t,e){const n=t[0].objectsWithGeo();return e.tposition&&this._create_rest_attribute(n,e.position,e.restP),e.tnormal&&this._create_rest_attribute(n,e.normal,e.restN),this.createCoreGroupFromObjects(n)}_create_rest_attribute(t,e,n){for(let i of t){const t=i.geometry;if(t){const i=t.getAttribute(e);i&&t.setAttribute(n,i.clone())}}}}_2.DEFAULT_PARAMS={tposition:!0,position:\\\\\\\"position\\\\\\\",restP:\\\\\\\"restP\\\\\\\",tnormal:!0,normal:\\\\\\\"normal\\\\\\\",restN:\\\\\\\"restN\\\\\\\"};const m2=_2.DEFAULT_PARAMS;const f2=new class extends ua{constructor(){super(...arguments),this.tposition=ha.BOOLEAN(m2.tposition),this.position=ha.STRING(m2.position,{visibleIf:{tposition:!0}}),this.restP=ha.STRING(m2.restP,{visibleIf:{tposition:!0}}),this.tnormal=ha.BOOLEAN(m2.tnormal),this.normal=ha.STRING(m2.normal,{visibleIf:{tnormal:!0}}),this.restN=ha.STRING(m2.restN,{visibleIf:{tnormal:!0}})}};class g2 extends uV{constructor(){super(...arguments),this.paramsConfig=f2}static type(){return\\\\\\\"restAttributes\\\\\\\"}initializeNode(){this.io.inputs.setCount(1),this.io.inputs.initInputsClonedState([Qi.FROM_NODE])}cook(t){this._operation=this._operation||new _2(this.scene(),this.states);const e=this._operation.cook(t,this.pv);this.setCoreGroup(e)}}class v2 extends aV{constructor(){super(...arguments),this._core_transform=new bU}static type(){return\\\\\\\"roundedBox\\\\\\\"}cook(t,e){const n=t[0],i=n?this._cook_with_input(n,e):this._cook_without_input(e);return this.createCoreGroupFromGeometry(i)}_cook_without_input(t){const e=t.size,n=new ky(e.x,e.y,e.z,t.divisions,t.bevel);return n.translate(t.center.x,t.center.y,t.center.z),n.computeVertexNormals(),n}_cook_with_input(t,e){const n=e.divisions,i=t.boundingBox(),s=i.max.clone().sub(i.min),r=i.max.clone().add(i.min).multiplyScalar(.5),o=new ky(s.x,s.y,s.z,n,e.bevel),a=this._core_transform.translationMatrix(r);return o.applyMatrix4(a),o}}v2.DEFAULT_PARAMS={size:new p.a(1,1,1),divisions:2,bevel:.1,center:new p.a(0,0,0)},v2.INPUT_CLONED_STATE=Qi.NEVER;const y2=v2.DEFAULT_PARAMS;const x2=new class extends ua{constructor(){super(...arguments),this.size=ha.VECTOR3(y2.size),this.divisions=ha.INTEGER(y2.divisions,{range:[1,10],rangeLocked:[!0,!1]}),this.bevel=ha.FLOAT(y2.bevel,{range:[0,1],rangeLocked:[!0,!1]}),this.center=ha.VECTOR3(y2.center)}};class b2 extends uV{constructor(){super(...arguments),this.paramsConfig=x2}static type(){return\\\\\\\"roundedBox\\\\\\\"}static displayedInputNames(){return[\\\\\\\"geometry to create bounding box from (optional)\\\\\\\"]}initializeNode(){this.io.inputs.setCount(0,1),this.io.inputs.initInputsClonedState(v2.INPUT_CLONED_STATE)}cook(t){this._operation=this._operation||new v2(this._scene,this.states);const e=this._operation.cook(t,this.pv);this.setCoreGroup(e)}}class w2 extends aV{static type(){return\\\\\\\"scatter\\\\\\\"}async cook(t,e){const n=t[0];let i=n.faces();const s=[];let r=0;const o=new Map;for(let t of i){const e=t.area();o.set(t.index(),e)}const a=f.sortBy(i,(t=>o.get(t.index())||-1));let l=0;for(let t of a)r+=o.get(t.index()),s[l]=r,l++;const c=[];let h=[];e.transferAttributes&&(h=n.attribNamesMatchingMask(e.attributesToTransfer));const u=new Map,d=new Map;for(let t of h)u.set(t,[]),d.set(t,n.attribSize(t));const p=new CX,_=2454*e.seed%Number.MAX_SAFE_INTEGER;await p.startWithCount(e.pointsCount,(t=>{const e=or.randFloat(_+t)*r;for(let t=0;te/(t-1)));e.addIdnAttribute&&g.setAttribute(\\\\\\\"idn\\\\\\\",new C.a(new Float32Array(i),1))}const v=this.createObject(g,Ns.POINTS);return this.createCoreGroupFromObjects([v])}}w2.DEFAULT_PARAMS={pointsCount:100,seed:0,transferAttributes:!0,attributesToTransfer:\\\\\\\"normal\\\\\\\",addIdAttribute:!0,addIdnAttribute:!0},w2.INPUT_CLONED_STATE=Qi.FROM_NODE;const T2=w2.DEFAULT_PARAMS;const A2=new class extends ua{constructor(){super(...arguments),this.pointsCount=ha.INTEGER(T2.pointsCount,{range:[0,100],rangeLocked:[!0,!1]}),this.seed=ha.INTEGER(T2.seed,{range:[0,100],rangeLocked:[!1,!1]}),this.transferAttributes=ha.BOOLEAN(T2.transferAttributes),this.attributesToTransfer=ha.STRING(T2.attributesToTransfer,{visibleIf:{transferAttributes:1}}),this.addIdAttribute=ha.BOOLEAN(T2.addIdAttribute),this.addIdnAttribute=ha.BOOLEAN(T2.addIdnAttribute)}};class M2 extends uV{constructor(){super(...arguments),this.paramsConfig=A2}static type(){return\\\\\\\"scatter\\\\\\\"}static displayedInputNames(){return[\\\\\\\"geometry to scatter points onto\\\\\\\"]}initializeNode(){this.io.inputs.setCount(1),this.io.inputs.initInputsClonedState(Qi.NEVER)}async cook(t){this._operation=this._operation||new w2(this.scene(),this.states);const e=await this._operation.cook(t,this.pv);this.setCoreGroup(e)}}var E2;!function(t){t.MATRIX=\\\\\\\"matrix\\\\\\\",t.AXIS=\\\\\\\"axis\\\\\\\"}(E2||(E2={}));const S2=[E2.MATRIX,E2.AXIS];var C2;!function(t){t.BBOX_CENTER=\\\\\\\"bbox center\\\\\\\",t.BBOX_CENTER_OFFSET=\\\\\\\"bbox center offset\\\\\\\",t.CUSTOM=\\\\\\\"custom\\\\\\\"}(C2||(C2={}));const N2=[C2.BBOX_CENTER,C2.BBOX_CENTER_OFFSET,C2.CUSTOM];class L2 extends aV{constructor(){super(...arguments),this._m4=new A.a,this._axisNormalized=new p.a,this._center=new p.a,this._pointPos=new p.a,this._axisPlane=new Y.a,this._pointOnPlane=new p.a,this._delta=new p.a,this._deltaNormalized=new p.a,this._offset=new p.a}static type(){return\\\\\\\"shear\\\\\\\"}cook(t,e){const n=t[0].objects();return this._applyShear(n,e),t[0]}_applyShear(t,e){const n=S2[e.mode];switch(n){case E2.MATRIX:return this._applyMatrixShear(t,e);case E2.AXIS:return this._applyAxisShear(t,e)}os.unreachable(n)}_applyMatrixShear(t,e){this._m4.makeShear(e.xy,e.xz,e.yx,e.yz,e.zx,e.zy);for(let e of t){const t=e.geometry;t&&t.applyMatrix4(this._m4)}}_applyAxisShear(t,e){this._axisNormalized.copy(e.axis),this._axisNormalized.normalize();for(let n of t){const t=n.geometry;if(t){this._getAxisModeCenter(t,e),this._axisPlane.setFromNormalAndCoplanarPoint(e.planeAxis,this._center);const n=new fr(t).points();for(let t of n){t.getPosition(this._pointPos),this._axisPlane.projectPoint(this._pointPos,this._pointOnPlane),this._delta.copy(this._pointOnPlane).sub(this._pointPos);const n=this._delta.length();this._deltaNormalized.copy(this._delta).normalize(),this._offset.copy(this._axisNormalized).multiplyScalar(e.axisAmount*n),this._delta.dot(e.planeAxis)>0&&this._offset.multiplyScalar(-1),this._pointPos.add(this._offset),t.setPosition(this._pointPos)}}}}_getAxisModeCenter(t,e){const n=N2[e.centerMode];switch(n){case C2.BBOX_CENTER:return this._getAxisModeCenterBbox(t,e);case C2.BBOX_CENTER_OFFSET:return this._getAxisModeCenterBboxOffset(t,e);case C2.CUSTOM:return this._getAxisModeCenterCustom(e)}os.unreachable(n)}_getAxisModeCenterBbox(t,e){t.computeBoundingBox();const n=t.boundingBox;n?n.getCenter(this._center):this._center.set(0,0,0)}_getAxisModeCenterBboxOffset(t,e){this._getAxisModeCenterBbox(t,e),this._center.add(e.centerOffset)}_getAxisModeCenterCustom(t){return this._center.copy(t.center)}}var O2;L2.DEFAULT_PARAMS={mode:S2.indexOf(E2.AXIS),xy:0,xz:0,yx:0,yz:0,zx:0,zy:0,centerMode:N2.indexOf(C2.BBOX_CENTER),centerOffset:new p.a(0,0,0),center:new p.a(0,0,0),planeAxis:new p.a(0,0,1),axis:new p.a(0,1,0),axisAmount:0},L2.INPUT_CLONED_STATE=Qi.FROM_NODE,function(t){t.SHEAR=\\\\\\\"shear\\\\\\\",t.TRANSFORM=\\\\\\\"transform\\\\\\\",t.UV_LAYOUT=\\\\\\\"uvLayout\\\\\\\",t.UV_TRANSFORM=\\\\\\\"uvTransform\\\\\\\",t.UV_UNWRAP=\\\\\\\"uvUnwrap\\\\\\\"}(O2||(O2={}));const P2=L2.DEFAULT_PARAMS;const R2=new class extends ua{constructor(){super(...arguments),this.mode=ha.INTEGER(P2.mode,{menu:{entries:S2.map(((t,e)=>({name:t,value:e})))}}),this.xy=ha.FLOAT(P2.xy,{visibleIf:{mode:S2.indexOf(E2.MATRIX)}}),this.xz=ha.FLOAT(P2.xz,{visibleIf:{mode:S2.indexOf(E2.MATRIX)}}),this.yx=ha.FLOAT(P2.yx,{visibleIf:{mode:S2.indexOf(E2.MATRIX)}}),this.yz=ha.FLOAT(P2.yz,{visibleIf:{mode:S2.indexOf(E2.MATRIX)}}),this.zx=ha.FLOAT(P2.zx,{visibleIf:{mode:S2.indexOf(E2.MATRIX)}}),this.zy=ha.FLOAT(P2.zy,{visibleIf:{mode:S2.indexOf(E2.MATRIX)}}),this.centerMode=ha.INTEGER(P2.centerMode,{visibleIf:{mode:S2.indexOf(E2.AXIS)},menu:{entries:N2.map(((t,e)=>({name:t,value:e})))}}),this.centerOffset=ha.VECTOR3(P2.centerOffset.toArray(),{visibleIf:{mode:S2.indexOf(E2.AXIS),centerMode:N2.indexOf(C2.BBOX_CENTER_OFFSET)}}),this.center=ha.VECTOR3(P2.center.toArray(),{visibleIf:{mode:S2.indexOf(E2.AXIS),centerMode:N2.indexOf(C2.CUSTOM)}}),this.planeAxis=ha.VECTOR3(P2.planeAxis.toArray(),{visibleIf:{mode:S2.indexOf(E2.AXIS)}}),this.axis=ha.VECTOR3(P2.axis.toArray(),{visibleIf:{mode:S2.indexOf(E2.AXIS)}}),this.axisAmount=ha.FLOAT(P2.axisAmount,{range:[-1,1],visibleIf:{mode:S2.indexOf(E2.AXIS)}})}};class I2 extends uV{constructor(){super(...arguments),this.paramsConfig=R2}static type(){return O2.SHEAR}static displayedInputNames(){return[\\\\\\\"geometries or objects to transform\\\\\\\"]}initializeNode(){this.io.inputs.setCount(1),this.io.inputs.initInputsClonedState(L2.INPUT_CLONED_STATE)}setMode(t){this.p.mode.set(S2.indexOf(t))}cook(t){this._operation=this._operation||new L2(this.scene(),this.states);const e=this._operation.cook(t,this.pv);this.setCoreGroup(e)}}const F2=new class extends ua{};class D2 extends uV{constructor(){super(...arguments),this.paramsConfig=F2}static type(){return\\\\\\\"skin\\\\\\\"}static displayedInputNames(){return[\\\\\\\"lines to create polygons from\\\\\\\",\\\\\\\"if used, lines from both inputs will be used\\\\\\\"]}initializeNode(){this.io.inputs.setCount(1,2)}cook(t){switch(f.compact(this.io.inputs.inputs()).length){case 1:return this.process_one_input(t);case 2:return this.process_two_inputs(t);default:return this.states.error.set(\\\\\\\"inputs count not valid\\\\\\\")}}process_one_input(t){const e=t[0],n=this._get_line_segments(e),i=[];if(n){const t=n[0];if(t){const e=G1.line_segment_to_geometries(t.geometry);e.forEach(((t,n)=>{if(n>0){const s=e[n-1],r=this._skin(s,t);i.push(r)}}))}}this.setGeometries(i)}process_two_inputs(t){const e=t[0],n=t[1],i=this._get_line_segments(e),s=this._get_line_segments(n),r=f.sortBy([i,s],(t=>-t.length)),o=r[0],a=r[1],l=[];o.forEach(((t,e)=>{const n=a[e];if(null!=t&&null!=n){const e=t.geometry,i=n.geometry,s=this._skin(e,i);l.push(s)}})),this.setGeometries(l)}_get_line_segments(t){return t.objects().filter((t=>t.isLineSegments))}_skin(t,e){const n=new S.a;return new V1(n,t,e).process(),n}}var B2;!function(t){t.X=\\\\\\\"x\\\\\\\",t.Y=\\\\\\\"y\\\\\\\",t.Z=\\\\\\\"z\\\\\\\"}(B2||(B2={}));const z2=[B2.X,B2.Y,B2.Z];class k2 extends aV{constructor(){super(...arguments),this._pointPos=new p.a,this._positions=[],this._indicesByPos=new Map,this._indexDest=new Map,this._debugActive=!1}static type(){return\\\\\\\"sort\\\\\\\"}cook(t,e){const n=t[0],i=n.objectsWithGeo();for(let t of i)this._sortObject(t,e);return n}_debug(t){this._debugActive}_sortObject(t,e){const n=new br(t,0).points(),i=t.geometry.getIndex();if(!i)return void console.warn(\\\\\\\"geometry cannot be sorted since it has no index\\\\\\\");const s=i.array;this._positions=new Array(n.length),this._indicesByPos.clear(),this._indexDest.clear();const r=z2[e.axis];let o=0,a=0;for(let t of n){switch(t.getPosition(this._pointPos),r){case B2.X:o=this._pointPos.x;break;case B2.Y:o=this._pointPos.y;break;case B2.Z:o=this._pointPos.z}this._positions[a]=o,h.pushOnArrayAtEntry(this._indicesByPos,o,t.index()),a++}let l=this._positions.sort(((t,e)=>t-e));e.invert&&l.reverse();const c=new Array(n.length);a=0;const u=f.uniq(l);for(let t of u){const e=this._indicesByPos.get(t);if(e)for(let t of e)c[a]=t,this._indexDest.set(t,a),a++}const d=new Array(s.length);for(let t=0;t ${e}`),null!=e)for(let n=0;n({name:t,value:e})))}}),this.invert=ha.BOOLEAN(U2.invert)}};class V2 extends uV{constructor(){super(...arguments),this.paramsConfig=G2}static type(){return\\\\\\\"sort\\\\\\\"}static displayedInputNames(){return[\\\\\\\"geometry to sort\\\\\\\"]}initializeNode(){this.io.inputs.setCount(1),this.io.inputs.initInputsClonedState([Qi.FROM_NODE])}cook(t){this._operation=this._operation||new k2(this._scene,this.states);const e=this._operation.cook(t,this.pv);this.setCoreGroup(e)}}const H2=new class extends ua{constructor(){super(...arguments),this.startFrame=ha.INTEGER(Nl.START_FRAME)}};class j2 extends _V{constructor(){super(...arguments),this.paramsConfig=H2,this._last_simulated_frame=null,this.childrenDisplayController=new fV(this,{dependsOnDisplayNode:!1}),this.displayNodeController=new Fm(this,{onDisplayNodeRemove:()=>{},onDisplayNodeSet:()=>{},onDisplayNodeUpdate:()=>{}},{dependsOnDisplayNode:!1})}static type(){return\\\\\\\"solver\\\\\\\"}initializeNode(){this.io.inputs.setCount(0,4),this.io.inputs.initInputsClonedState(Qi.NEVER),this.addGraphInput(this.scene().timeController.graphNode)}previousFrameCoreGroup(){return this._previousFrameCoreGroup}async cook(t){this.pv.startFrame==this.scene().frame()&&this._reset(),this.computeSolverIfRequired()}_reset(){this._previousFrameCoreGroup=void 0,this._last_simulated_frame=null}computeSolverIfRequired(){const t=this.scene().frame(),e=this.pv.startFrame;t>=e&&(null==this._last_simulated_frame&&(this._last_simulated_frame=e-1),t>this._last_simulated_frame&&this._computeSolverMultipleTimes(t-this._last_simulated_frame))}_computeSolverMultipleTimes(t=1){for(let e=0;e({name:t,value:Y2[t]})))}}),this.radius=ha.FLOAT(Z2.radius,{visibleIf:{type:Y2.default}}),this.resolution=ha.VECTOR2(Z2.resolution,{visibleIf:{type:Y2.default}}),this.open=ha.BOOLEAN(Z2.open,{visibleIf:{type:Y2.default}}),this.phiStart=ha.FLOAT(Z2.phiStart,{range:[0,2*Math.PI],visibleIf:{type:Y2.default,open:!0}}),this.phiLength=ha.FLOAT(\\\\\\\"$PI*2\\\\\\\",{range:[0,2*Math.PI],visibleIf:{type:Y2.default,open:!0}}),this.thetaStart=ha.FLOAT(Z2.thetaStart,{range:[0,Math.PI],visibleIf:{type:Y2.default,open:!0}}),this.thetaLength=ha.FLOAT(\\\\\\\"$PI\\\\\\\",{range:[0,Math.PI],visibleIf:{type:Y2.default,open:!0}}),this.detail=ha.INTEGER(Z2.detail,{range:[0,5],rangeLocked:[!0,!1],visibleIf:{type:Y2.isocahedron}}),this.center=ha.VECTOR3(Z2.center)}};class Q2 extends uV{constructor(){super(...arguments),this.paramsConfig=K2}static type(){return\\\\\\\"sphere\\\\\\\"}initializeNode(){this.io.inputs.setCount(0,1),this.io.inputs.initInputsClonedState(J2.INPUT_CLONED_STATE)}cook(t){this._operation=this._operation||new J2(this.scene(),this.states);const e=this._operation.cook(t,this.pv);this.setCoreGroup(e)}}const t9=new class extends ua{constructor(){super(...arguments),this.attribType=ha.INTEGER(ks.indexOf(zs.NUMERIC),{menu:{entries:Us}}),this.attribName=ha.STRING(\\\\\\\"\\\\\\\")}};class e9 extends uV{constructor(){super(...arguments),this.paramsConfig=t9,this._new_objects=[]}static type(){return\\\\\\\"split\\\\\\\"}static displayedInputNames(){return[\\\\\\\"geometry to split in multiple objects\\\\\\\"]}initializeNode(){this.io.inputs.setCount(1)}async cook(t){const e=t[0];this._new_objects=[],\\\\\\\"\\\\\\\"!=this.pv.attribName&&this._split_core_group(e),this.setObjects(this._new_objects)}async _split_core_group(t){const e=t.coreObjects();for(let t of e)this._split_core_object(t)}_split_core_object(t){let e=t.coreGeometry(),n=this.pv.attribName,i=new Map;if(e){const s=t.object(),r=e.pointsFromGeometry(),o=r[0];if(o){if(o.attribSize(n)!=Gs.FLOAT&&!o.isAttribIndexed(n))return void this.states.error.set(`attrib '${n}' must be a float or a string`);let t;if(o.isAttribIndexed(n))for(let e of r)t=e.indexedAttribValue(n),h.pushOnArrayAtEntry(i,t,e);else for(let e of r)t=e.attribValue(n),h.pushOnArrayAtEntry(i,t,e)}const a=Os(s.constructor);i.forEach(((t,e)=>{const i=fr.geometryFromPoints(t,a);if(i){const t=this.createObject(i,a);br.addAttribute(t,n,e),this._new_objects.push(t)}}))}}}const n9=new A.a,i9=new Q.a,s9=new p.a;class r9 extends J.a{constructor(){super(),this.uuid=On.h(),this.name=\\\\\\\"\\\\\\\",this.type=\\\\\\\"Geometry\\\\\\\",this.vertices=[],this.colors=[],this.faces=[],this.faceVertexUvs=[[]],this.morphTargets=[],this.morphNormals=[],this.skinWeights=[],this.skinIndices=[],this.lineDistances=[],this.boundingBox=null,this.boundingSphere=null,this.elementsNeedUpdate=!1,this.verticesNeedUpdate=!1,this.uvsNeedUpdate=!1,this.normalsNeedUpdate=!1,this.colorsNeedUpdate=!1,this.lineDistancesNeedUpdate=!1,this.groupsNeedUpdate=!1}applyMatrix4(t){const e=(new G.a).getNormalMatrix(t);for(let e=0,n=this.vertices.length;e0)for(let t=0;t0&&(this.normalsNeedUpdate=!0)}computeFlatVertexNormals(){this.computeFaceNormals();for(let t=0,e=this.faces.length;t0&&(this.normalsNeedUpdate=!0)}computeMorphNormals(){for(let t=0,e=this.faces.length;t=0;t--){const e=r[t];this.faces.splice(e,1);for(let t=0,n=this.faceVertexUvs.length;t0,a=e.vertexNormals.length>0,l=1!==e.color.r||1!==e.color.g||1!==e.color.b,p=e.vertexColors.length>0;let _=0;if(_=c(_,0,0),_=c(_,1,i),_=c(_,2,s),_=c(_,3,r),_=c(_,4,o),_=c(_,5,a),_=c(_,6,l),_=c(_,7,p),n.push(_),n.push(e.a,e.b,e.c),n.push(e.materialIndex),r){const e=this.faceVertexUvs[0][t];n.push(d(e[0]),d(e[1]),d(e[2]))}if(o&&n.push(h(e.normal)),a){const t=e.vertexNormals;n.push(h(t[0]),h(t[1]),h(t[2]))}if(l&&n.push(u(e.color)),p){const t=e.vertexColors;n.push(u(t[0]),u(t[1]),u(t[2]))}}function c(t,e,n){return n?t|1<0&&(t.data.colors=r),a.length>0&&(t.data.uvs=[a]),t.data.faces=n,t}clone(){return(new r9).copy(this)}copy(t){this.vertices=[],this.colors=[],this.faces=[],this.faceVertexUvs=[[]],this.morphTargets=[],this.morphNormals=[],this.skinWeights=[],this.skinIndices=[],this.lineDistances=[],this.boundingBox=null,this.boundingSphere=null,this.name=t.name;const e=t.vertices;for(let t=0,n=e.length;t0){const n=new Float32Array(3*t.normals.length);e.setAttribute(\\\\\\\"normal\\\\\\\",new C.a(n,3).copyVector3sArray(t.normals))}if(t.colors.length>0){const n=new Float32Array(3*t.colors.length);e.setAttribute(\\\\\\\"color\\\\\\\",new C.a(n,3).copyColorsArray(t.colors))}if(t.uvs.length>0){const n=new Float32Array(2*t.uvs.length);e.setAttribute(\\\\\\\"uv\\\\\\\",new C.a(n,2).copyVector2sArray(t.uvs))}if(t.uvs2.length>0){const n=new Float32Array(2*t.uvs2.length);e.setAttribute(\\\\\\\"uv2\\\\\\\",new C.a(n,2).copyVector2sArray(t.uvs2))}e.groups=t.groups;for(const n in t.morphTargets){const i=[],s=t.morphTargets[n];for(let t=0,e=s.length;t0){const n=new C.c(4*t.skinIndices.length,4);e.setAttribute(\\\\\\\"skinIndex\\\\\\\",n.copyVector4sArray(t.skinIndices))}if(t.skinWeights.length>0){const n=new C.c(4*t.skinWeights.length,4);e.setAttribute(\\\\\\\"skinWeight\\\\\\\",n.copyVector4sArray(t.skinWeights))}return null!==t.boundingSphere&&(e.boundingSphere=t.boundingSphere.clone()),null!==t.boundingBox&&(e.boundingBox=t.boundingBox.clone()),e}computeTangents(){console.error(\\\\\\\"THREE.Geometry: .computeTangents() has been removed.\\\\\\\")}computeLineDistances(){console.error(\\\\\\\"THREE.Geometry: .computeLineDistances() has been removed. Use THREE.Line.computeLineDistances() instead.\\\\\\\")}applyMatrix(t){return console.warn(\\\\\\\"THREE.Geometry: .applyMatrix() has been renamed to .applyMatrix4().\\\\\\\"),this.applyMatrix4(t)}dispose(){this.dispatchEvent({type:\\\\\\\"dispose\\\\\\\"})}static createBufferGeometryFromObject(t){let e=new S.a;const n=t.geometry;if(t.isPoints||t.isLine){const t=new C.c(3*n.vertices.length,3),i=new C.c(3*n.colors.length,3);if(e.setAttribute(\\\\\\\"position\\\\\\\",t.copyVector3sArray(n.vertices)),e.setAttribute(\\\\\\\"color\\\\\\\",i.copyColorsArray(n.colors)),n.lineDistances&&n.lineDistances.length===n.vertices.length){const t=new C.c(n.lineDistances.length,1);e.setAttribute(\\\\\\\"lineDistance\\\\\\\",t.copyArray(n.lineDistances))}null!==n.boundingSphere&&(e.boundingSphere=n.boundingSphere.clone()),null!==n.boundingBox&&(e.boundingBox=n.boundingBox.clone())}else t.isMesh&&(e=n.toBufferGeometry());return e}}r9.prototype.isGeometry=!0;class o9{constructor(){this.vertices=[],this.normals=[],this.colors=[],this.uvs=[],this.uvs2=[],this.groups=[],this.morphTargets={},this.skinWeights=[],this.skinIndices=[],this.boundingBox=null,this.boundingSphere=null,this.verticesNeedUpdate=!1,this.normalsNeedUpdate=!1,this.colorsNeedUpdate=!1,this.uvsNeedUpdate=!1,this.groupsNeedUpdate=!1}computeGroups(t){const e=[];let n,i,s;const r=t.faces;for(i=0;i0,r=i[1]&&i[1].length>0,o=t.morphTargets,a=o.length;let l;if(a>0){l=[];for(let t=0;t0){u=[];for(let t=0;t0&&0===e.length&&console.error(\\\\\\\"THREE.DirectGeometry: Faceless geometries are not supported.\\\\\\\");for(let t=0;t0;)this.smooth(t);return t.computeFaceNormals(),t.computeVertexNormals(),e?t.toBufferGeometry():t},function(){var t=[\\\\\\\"a\\\\\\\",\\\\\\\"b\\\\\\\",\\\\\\\"c\\\\\\\"];function e(t,e,n){return n[Math.min(t,e)+\\\\\\\"_\\\\\\\"+Math.max(t,e)]}function n(t,e,n,i,s,r){var o,a=Math.min(t,e),l=Math.max(t,e),c=a+\\\\\\\"_\\\\\\\"+l;c in i?o=i[c]:(o={a:n[a],b:n[l],newEdge:null,faces:[]},i[c]=o);o.faces.push(s),r[t].edges.push(o),r[e].edges.push(o)}function i(t,e,n,i,s){t.push(new a9(e,n,i,void 0,void 0,s))}function s(t,e){return Math.abs(e-t)/2+Math.min(t,e)}function r(t,e,n,i){t.push([e.clone(),n.clone(),i.clone()])}l9.prototype.smooth=function(o){var a,l,c,h,u,_,m,f,g,v,y,x,b,w=new p.a,T=[];a=o.vertices,l=o.faces;var A,M,E,S,C,N,L,O,P,R,I,F,D,B,z=void 0!==(c=o.faceVertexUvs)[0]&&c[0].length>0;if(z)for(var k=0;k3&&(O=3/(8*_)),P=1-_*O,R=O,_<=2&&2==_&&(P=3/4,R=1/8),B=D.clone().multiplyScalar(P),w.set(0,0,0),k=0;k<_;k++)A=(I=F[k]).a!==D?I.a:I.b,w.add(A);w.multiplyScalar(R),B.add(w),b.push(B)}h=b.concat(x);var U,G,V,H,j,W,q,X=b.length;u=[];var Y=new d.a,$=new d.a,J=new d.a;for(m=0,f=l.length;m{f9.PARAM_CALLBACK_reset(t)}})}};class f9 extends uV{constructor(){super(...arguments),this.paramsConfig=m9}static type(){return ns.INPUT}initializeNode(){this.io.inputs.setCount(0),this.lifecycle.add_on_add_hook((()=>{this.set_parent_input_dependency()}))}async cook(){const t=this.pv.input,e=this.parent();if(e){if(e.io.inputs.has_input(t)){const n=await e.containerController.requestInputContainer(t);if(n){const t=n.coreContent();if(t)return void this.setCoreGroup(t)}}else this.states.error.set(`parent has no input ${t}`);this.cookController.endCook()}else this.states.error.set(\\\\\\\"subnet input has no parent\\\\\\\")}static PARAM_CALLBACK_reset(t){t.set_parent_input_dependency()}set_parent_input_dependency(){this._current_parent_input_graph_node&&this.removeGraphInput(this._current_parent_input_graph_node);const t=this.parent();t&&(this._current_parent_input_graph_node=t.io.inputs.inputGraphNode(this.pv.input),this.addGraphInput(this._current_parent_input_graph_node))}}var g9=n(82);class v9 extends $g{constructor(t,e,n){super(t,e,n)}load(t){return new Promise((async(e,n)=>{const i=new g9.a(this.loadingManager),s=await this._urlToLoad();i.load(s,(i=>{try{const n=this._onLoaded(i,t);e(n)}catch(t){n([])}}))}))}parse(t,e){const n=new g9.a(this.loadingManager).parse(t);return this._onLoaded(n,e)}_onLoaded(t,e){const n=t.paths,i=new Fn.a;for(let t=0;t{const i=await n.load(e);for(let t of i.children)this._ensure_geometry_has_index(t);t(this.createCoreGroupFromObjects(i.children))}))}_ensure_geometry_has_index(t){const e=t.geometry;e&&this.createIndexIfNone(e)}}x9.DEFAULT_PARAMS={url:y9,drawFillShapes:!0,fillShapesWireframe:!1,drawStrokes:!0,strokesWireframe:!1};const b9=x9.DEFAULT_PARAMS;const w9=new class extends ua{constructor(){super(...arguments),this.url=ha.STRING(b9.url,{fileBrowse:{type:[Rr.SVG]}}),this.reload=ha.BUTTON(null,{callback:(t,e)=>{T9.PARAM_CALLBACK_reload(t)}}),this.drawFillShapes=ha.BOOLEAN(b9.drawFillShapes),this.fillShapesWireframe=ha.BOOLEAN(b9.fillShapesWireframe),this.drawStrokes=ha.BOOLEAN(b9.drawStrokes),this.strokesWireframe=ha.BOOLEAN(b9.strokesWireframe)}};class T9 extends uV{constructor(){super(...arguments),this.paramsConfig=w9}static type(){return\\\\\\\"svg\\\\\\\"}async requiredModules(){return[Hn.SVGLoader]}initializeNode(){this.scene().dispatchController.onAddListener((()=>{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{this.params.label.init([this.p.url],(()=>{const t=this.pv.url;if(t){const e=t.split(\\\\\\\"/\\\\\\\");return e[e.length-1]}return\\\\\\\"\\\\\\\"}))}))}))}async cook(t){this._operation=this._operation||new x9(this.scene(),this.states,this);const e=await this._operation.cook(t,this.pv);this.setCoreGroup(e)}static PARAM_CALLBACK_reload(t){t.param_callback_reload()}param_callback_reload(){this.p.url.setDirty()}}const A9=\\\\\\\"geometry to switch to\\\\\\\";const M9=new class extends ua{constructor(){super(...arguments),this.input=ha.INTEGER(0,{range:[0,3],rangeLocked:[!0,!0]})}};class E9 extends uV{constructor(){super(...arguments),this.paramsConfig=M9}static type(){return\\\\\\\"switch\\\\\\\"}static displayedInputNames(){return[A9,A9,A9,A9]}initializeNode(){this.io.inputs.setCount(0,4),this.io.inputs.initInputsClonedState(Qi.NEVER),this.cookController.disallowInputsEvaluation()}async cook(){const t=this.pv.input;if(this.io.inputs.has_input(t)){const e=await this.containerController.requestInputContainer(t);if(e){const t=e.coreContent();if(t)return void this.setCoreGroup(t)}}else this.states.error.set(`no input ${t}`);this.cookController.endCook()}}class S9 extends zQ{constructor(t,e,n){super([1,1,1,-1,-1,1,-1,1,-1,1,-1,-1],[2,1,0,0,3,2,1,3,0,2,3,1],t,e,n),this.type=\\\\\\\"TetrahedronBufferGeometry\\\\\\\",this.parameters={radius:t,detail:e}}}const C9=new class extends ua{constructor(){super(...arguments),this.radius=ha.FLOAT(1),this.detail=ha.INTEGER(0,{range:[0,10],rangeLocked:[!0,!1]}),this.pointsOnly=ha.BOOLEAN(0),this.center=ha.VECTOR3([0,0,0])}};class N9 extends uV{constructor(){super(...arguments),this.paramsConfig=C9}static type(){return\\\\\\\"tetrahedron\\\\\\\"}cook(){const t=this.pv.pointsOnly,e=new S9(this.pv.radius,this.pv.detail,t);if(e.translate(this.pv.center.x,this.pv.center.y,this.pv.center.z),t){const t=this.createObject(e,Ns.POINTS);this.setObject(t)}else e.computeVertexNormals(),this.setGeometry(e)}}class L9 extends yJ{constructor(t,e={}){const n=e.font;if(!n||!n.isFont)return new S.a;const i=n.generateShapes(t,e.size);e.depth=void 0!==e.height?e.height:50,void 0===e.bevelThickness&&(e.bevelThickness=10),void 0===e.bevelSize&&(e.bevelSize=8),void 0===e.bevelEnabled&&(e.bevelEnabled=!1),super(i,e),this.type=\\\\\\\"TextGeometry\\\\\\\"}}var O9=n(48);class P9 extends Vf.a{constructor(t){super(t)}load(t,e,n,i){const s=this,r=new Gf.a(this.manager);r.setPath(this.path),r.setRequestHeader(this.requestHeader),r.setWithCredentials(s.withCredentials),r.load(t,(function(t){let n;try{n=JSON.parse(t)}catch(e){console.warn(\\\\\\\"THREE.FontLoader: typeface.js support is being deprecated. Use typeface.json instead.\\\\\\\"),n=JSON.parse(t.substring(65,t.length-2))}const i=s.parse(n);e&&e(i)}),n,i)}parse(t){return new R9(t)}}class R9{constructor(t){this.type=\\\\\\\"Font\\\\\\\",this.data=t}generateShapes(t,e=100){const n=[],i=function(t,e,n){const i=Array.from(t),s=e/n.resolution,r=(n.boundingBox.yMax-n.boundingBox.yMin+n.underlineThickness)*s,o=[];let a=0,l=0;for(let t=0;t{const i=await this._loadTTFLoader();i&&i.load(t,(t=>{const n=this._font_loader.parse(t);e(n)}),void 0,(()=>{n()}))}))}_loadJSON(t){return new Promise(((e,n)=>{this._font_loader.load(t,(t=>{e(t)}),void 0,(()=>{n()}))}))}async _loadTTFLoader(){const t=await li.modulesRegister.module(Hn.TTFLoader);if(t)return new t(this.loadingManager)}static async loadSVGLoader(){const t=await li.modulesRegister.module(Hn.SVGLoader);if(t)return t}}var D9;!function(t){t.MESH=\\\\\\\"mesh\\\\\\\",t.FLAT=\\\\\\\"flat\\\\\\\",t.LINE=\\\\\\\"line\\\\\\\",t.STROKE=\\\\\\\"stroke\\\\\\\"}(D9||(D9={}));const B9=[D9.MESH,D9.FLAT,D9.LINE,D9.STROKE],z9=\\\\\\\"failed to generate geometry. Try to remove some characters\\\\\\\";const k9=new class extends ua{constructor(){super(...arguments),this.font=ha.STRING(\\\\\\\"https://raw.githubusercontent.com/polygonjs/polygonjs-assets/master/fonts/droid_sans_regular.typeface.json\\\\\\\",{fileBrowse:{type:[Rr.FONT]}}),this.text=ha.STRING(\\\\\\\"polygonjs\\\\\\\",{multiline:!0}),this.type=ha.INTEGER(0,{menu:{entries:B9.map(((t,e)=>({name:t,value:e})))}}),this.size=ha.FLOAT(1,{range:[0,1],rangeLocked:[!0,!1]}),this.extrude=ha.FLOAT(.1,{visibleIf:{type:B9.indexOf(D9.MESH)}}),this.segments=ha.INTEGER(1,{range:[1,20],rangeLocked:[!0,!1],visibleIf:{type:B9.indexOf(D9.MESH)}}),this.strokeWidth=ha.FLOAT(.02,{visibleIf:{type:B9.indexOf(D9.STROKE)}})}};class U9 extends uV{constructor(){super(...arguments),this.paramsConfig=k9,this._loaded_fonts={}}static type(){return\\\\\\\"text\\\\\\\"}initializeNode(){this.scene().dispatchController.onAddListener((()=>{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{this.params.label.init([this.p.text],(()=>this.p.text.rawInput()))}))}))}async cook(){try{this._loaded_fonts[this.pv.font]=this._loaded_fonts[this.pv.font]||await this._loadFont()}catch(t){return void this.states.error.set(`count not load font (${this.pv.font})`)}const t=this._loaded_fonts[this.pv.font];if(t)switch(B9[this.pv.type]){case D9.MESH:return this._create_geometry_from_type_mesh(t);case D9.FLAT:return this._create_geometry_from_type_flat(t);case D9.LINE:return this._create_geometry_from_type_line(t);case D9.STROKE:return this._create_geometry_from_type_stroke(t);default:console.warn(\\\\\\\"type is not valid\\\\\\\")}}_create_geometry_from_type_mesh(t){const e=this.displayed_text(),n={font:t,size:this.pv.size,height:this.pv.extrude,curveSegments:this.pv.segments};try{const t=new L9(e,n);if(!t.index){const e=t.getAttribute(\\\\\\\"position\\\\\\\").array;t.setIndex(f.range(e.length/3))}this.setGeometry(t)}catch(t){this.states.error.set(z9)}}_create_geometry_from_type_flat(t){const e=this._get_shapes(t);if(e){var n=new AJ(e);this.setGeometry(n)}}_create_geometry_from_type_line(t){const e=this.shapes_from_font(t);if(e){const t=[],n=[];let i=0;for(let s=0;s0&&e0)for(let e=0;e{const n=t.material;n&&(m.isArray(n)||s||(s=n[e.textureName]))}));if(s)for(let t of n.objects())t.traverse((t=>{const n=t.material;if(n&&!m.isArray(n)){n[e.textureName]=s;const t=n.uniforms;if(t){const n=t[e.textureName];n&&(n.value=s)}n.needsUpdate=!0}}));return n}}G9.DEFAULT_PARAMS={textureName:\\\\\\\"map\\\\\\\"},G9.INPUT_CLONED_STATE=[Qi.FROM_NODE,Qi.NEVER];const V9=G9.DEFAULT_PARAMS;const H9=new class extends ua{constructor(){super(...arguments),this.textureName=ha.STRING(V9.textureName)}};class j9 extends uV{constructor(){super(...arguments),this.paramsConfig=H9}static type(){return\\\\\\\"TextureCopy\\\\\\\"}static displayedInputNames(){return[\\\\\\\"objects to copy textures to\\\\\\\",\\\\\\\"objects to copy textures from\\\\\\\"]}initializeNode(){this.io.inputs.setCount(2),this.io.inputs.initInputsClonedState(G9.INPUT_CLONED_STATE)}async cook(t){this._operation=this._operation||new G9(this.scene(),this.states);const e=await this._operation.cook(t,this.pv);this.setCoreGroup(e)}}class W9 extends aV{static type(){return\\\\\\\"textureProperties\\\\\\\"}async cook(t,e){const n=t[0],i=[];for(let t of n.objects())e.applyToChildren?t.traverse((t=>{i.push(t)})):i.push(t);const s=i.map((t=>this._update_object(t,e)));return await Promise.all(s),n}async _update_object(t,e){const n=t.material;n&&await this._update_material(n,e)}async _update_material(t,e){let n=t.map;n&&await this._update_texture(n,e)}async _update_texture(t,e){this._updateEncoding(t,e),this._updateMapping(t,e),this._updateWrap(t,e),await this._updateAnisotropy(t,e),this._updateFilter(t,e)}_updateEncoding(t,e){e.tencoding&&(t.encoding=e.encoding,t.needsUpdate=!0)}_updateMapping(t,e){e.tmapping&&(t.mapping=e.mapping)}_updateWrap(t,e){e.twrap&&(t.wrapS=e.wrapS,t.wrapT=e.wrapT)}async _updateAnisotropy(t,e){if(e.tanisotropy)if(e.useRendererMaxAnisotropy){const e=await li.renderersController.firstRenderer();e&&(t.anisotropy=e.capabilities.getMaxAnisotropy())}else t.anisotropy=e.anisotropy}_updateFilter(t,e){e.tminFilter&&(t.minFilter=e.minFilter),e.tmagFilter&&(t.magFilter=e.magFilter)}}W9.DEFAULT_PARAMS={applyToChildren:!1,tencoding:!1,encoding:w.U,tmapping:!1,mapping:w.Yc,twrap:!1,wrapS:w.wc,wrapT:w.wc,tanisotropy:!1,useRendererMaxAnisotropy:!1,anisotropy:2,tminFilter:!1,minFilter:Km,tmagFilter:!1,magFilter:Zm},W9.INPUT_CLONED_STATE=Qi.FROM_NODE;const q9=W9.DEFAULT_PARAMS;const X9=new class extends ua{constructor(){super(...arguments),this.applyToChildren=ha.BOOLEAN(q9.applyToChildren,{separatorAfter:!0}),this.tencoding=ha.BOOLEAN(q9.tencoding),this.encoding=ha.INTEGER(q9.encoding,{visibleIf:{tencoding:1},menu:{entries:og.map((t=>({name:Object.keys(t)[0],value:Object.values(t)[0]})))}}),this.tmapping=ha.BOOLEAN(q9.tmapping),this.mapping=ha.INTEGER(q9.mapping,{visibleIf:{tmapping:1},menu:{entries:lg.map((t=>({name:Object.keys(t)[0],value:Object.values(t)[0]})))}}),this.twrap=ha.BOOLEAN(q9.twrap),this.wrapS=ha.INTEGER(q9.wrapS,{visibleIf:{twrap:1},menu:{entries:ag.map((t=>({name:Object.keys(t)[0],value:Object.values(t)[0]})))}}),this.wrapT=ha.INTEGER(q9.wrapT,{visibleIf:{twrap:1},menu:{entries:ag.map((t=>({name:Object.keys(t)[0],value:Object.values(t)[0]})))},separatorAfter:!0}),this.tanisotropy=ha.BOOLEAN(q9.tanisotropy),this.useRendererMaxAnisotropy=ha.BOOLEAN(q9.useRendererMaxAnisotropy,{visibleIf:{tanisotropy:1}}),this.anisotropy=ha.INTEGER(q9.anisotropy,{visibleIf:{tanisotropy:1,useRendererMaxAnisotropy:0},range:[0,32],rangeLocked:[!0,!1]}),this.tminFilter=ha.BOOLEAN(0),this.minFilter=ha.INTEGER(q9.minFilter,{visibleIf:{tminFilter:1},menu:{entries:tf}}),this.tmagFilter=ha.BOOLEAN(0),this.magFilter=ha.INTEGER(q9.magFilter,{visibleIf:{tmagFilter:1},menu:{entries:Qm}})}};class Y9 extends uV{constructor(){super(...arguments),this.paramsConfig=X9}static type(){return\\\\\\\"textureProperties\\\\\\\"}static displayedInputNames(){return[\\\\\\\"objects with textures to change properties of\\\\\\\"]}initializeNode(){this.io.inputs.setCount(1),this.io.inputs.initInputsClonedState(W9.INPUT_CLONED_STATE)}async cook(t){this._operation=this._operation||new W9(this.scene(),this.states);const e=await this._operation.cook(t,this.pv);this.setCoreGroup(e)}}const $9=new p.a(0,0,1);class J9 extends aV{constructor(){super(...arguments),this._core_transform=new bU}static type(){return\\\\\\\"torus\\\\\\\"}cook(t,e){const n=e.radius,i=e.radiusTube,s=e.segmentsRadial,r=e.segmentsTube,o=new EJ(n,i,s,r);return o.translate(e.center.x,e.center.y,e.center.z),this._core_transform.rotateGeometry(o,$9,e.direction),this.createCoreGroupFromGeometry(o)}}J9.DEFAULT_PARAMS={radius:1,radiusTube:1,segmentsRadial:20,segmentsTube:12,direction:new p.a(0,1,0),center:new p.a(0,0,0)},J9.INPUT_CLONED_STATE=Qi.FROM_NODE;const Z9=J9.DEFAULT_PARAMS;const K9=new class extends ua{constructor(){super(...arguments),this.radius=ha.FLOAT(Z9.radius,{range:[0,1]}),this.radiusTube=ha.FLOAT(Z9.radiusTube,{range:[0,1]}),this.segmentsRadial=ha.INTEGER(Z9.segmentsRadial,{range:[1,50],rangeLocked:[!0,!1]}),this.segmentsTube=ha.INTEGER(Z9.segmentsTube,{range:[1,50],rangeLocked:[!0,!1]}),this.direction=ha.VECTOR3(Z9.direction),this.center=ha.VECTOR3(Z9.center)}};class Q9 extends uV{constructor(){super(...arguments),this.paramsConfig=K9}static type(){return\\\\\\\"torus\\\\\\\"}cook(t){this._operation=this._operation||new J9(this.scene(),this.states);const e=this._operation.cook(t,this.pv);this.setCoreGroup(e)}}class t3 extends aV{static type(){return\\\\\\\"torusKnot\\\\\\\"}cook(t,e){const n=e.radius,i=e.radiusTube,s=e.segmentsRadial,r=e.segmentsTube,o=e.p,a=e.q,l=new SJ(n,i,s,r,o,a);return l.translate(e.center.x,e.center.y,e.center.z),this.createCoreGroupFromGeometry(l)}}t3.DEFAULT_PARAMS={radius:1,radiusTube:1,segmentsRadial:64,segmentsTube:8,p:2,q:3,center:new p.a(0,0,0)},t3.INPUT_CLONED_STATE=Qi.FROM_NODE;const e3=t3.DEFAULT_PARAMS;const n3=new class extends ua{constructor(){super(...arguments),this.radius=ha.FLOAT(e3.radius),this.radiusTube=ha.FLOAT(e3.radiusTube),this.segmentsRadial=ha.INTEGER(e3.segmentsRadial,{range:[1,128]}),this.segmentsTube=ha.INTEGER(e3.segmentsTube,{range:[1,32]}),this.p=ha.INTEGER(e3.p,{range:[1,10]}),this.q=ha.INTEGER(e3.q,{range:[1,10]}),this.center=ha.VECTOR3(e3.center)}};class i3 extends uV{constructor(){super(...arguments),this.paramsConfig=n3}static type(){return\\\\\\\"torusKnot\\\\\\\"}initializeNode(){}cook(t){this._operation=this._operation||new t3(this.scene(),this.states);const e=this._operation.cook(t,this.pv);this.setCoreGroup(e)}}var s3;!function(t){t.SET_PARAMS=\\\\\\\"set params\\\\\\\",t.UPDATE_MATRIX=\\\\\\\"update matrix\\\\\\\"}(s3||(s3={}));const r3=[s3.SET_PARAMS,s3.UPDATE_MATRIX];class o3 extends aV{constructor(){super(...arguments),this._core_transform=new bU,this._point_pos=new p.a,this._object_scale=new p.a,this._r=new p.a,this._object_position=new p.a}static type(){return\\\\\\\"transform\\\\\\\"}cook(t,e){const n=t[0].objects();return this._apply_transform(n,e),t[0]}_apply_transform(t,e){const n=gU[e.applyOn];switch(n){case _U.GEOMETRIES:return this._update_geometries(t,e);case _U.OBJECTS:return this._update_objects(t,e)}os.unreachable(n)}_update_geometries(t,e){const n=this._matrix(e);if(\\\\\\\"\\\\\\\"===e.group.trim())for(let i of t){const t=i.geometry;t&&(t.translate(-e.pivot.x,-e.pivot.y,-e.pivot.z),t.applyMatrix4(n),t.translate(e.pivot.x,e.pivot.y,e.pivot.z))}else{const i=oV._fromObjects(t).pointsFromGroup(e.group);for(let t of i){const i=t.getPosition(this._point_pos).sub(e.pivot);i.applyMatrix4(n),t.setPosition(i.add(e.pivot))}}}_update_objects(t,e){const n=r3[e.objectMode];switch(n){case s3.SET_PARAMS:return this._update_objects_params(t,e);case s3.UPDATE_MATRIX:return this._update_objects_matrix(t,e)}os.unreachable(n)}_update_objects_params(t,e){for(let n of t){n.position.copy(e.t);const t=yU[e.rotationOrder];this._r.copy(e.r).multiplyScalar(On.a),n.rotation.set(this._r.x,this._r.y,this._r.z,t),this._object_scale.copy(e.s).multiplyScalar(e.scale),n.scale.copy(this._object_scale),n.updateMatrix()}}_update_objects_matrix(t,e){const n=this._matrix(e);for(let e of t)this._object_position.copy(e.position),e.position.multiplyScalar(0),e.updateMatrix(),e.applyMatrix4(n),e.position.add(this._object_position),e.updateMatrix()}_matrix(t){return this._core_transform.matrix(t.t,t.r,t.s,t.scale,yU[t.rotationOrder])}}o3.DEFAULT_PARAMS={applyOn:gU.indexOf(_U.GEOMETRIES),objectMode:r3.indexOf(s3.SET_PARAMS),group:\\\\\\\"\\\\\\\",rotationOrder:yU.indexOf(vU.XYZ),t:new p.a(0,0,0),r:new p.a(0,0,0),s:new p.a(1,1,1),scale:1,pivot:new p.a(0,0,0)},o3.INPUT_CLONED_STATE=Qi.FROM_NODE;const a3=o3.DEFAULT_PARAMS;const l3=new class extends ua{constructor(){super(...arguments),this.applyOn=ha.INTEGER(a3.applyOn,{menu:{entries:gU.map(((t,e)=>({name:t,value:e})))}}),this.objectMode=ha.INTEGER(a3.objectMode,{visibleIf:{applyOn:gU.indexOf(_U.OBJECTS)},menu:{entries:r3.map(((t,e)=>({name:t,value:e})))}}),this.group=ha.STRING(a3.group,{visibleIf:{applyOn:gU.indexOf(_U.GEOMETRIES)}}),this.rotationOrder=ha.INTEGER(a3.rotationOrder,{menu:{entries:yU.map(((t,e)=>({name:t,value:e})))}}),this.t=ha.VECTOR3(a3.t),this.r=ha.VECTOR3(a3.r),this.s=ha.VECTOR3(a3.s),this.scale=ha.FLOAT(a3.scale,{range:[0,10]}),this.pivot=ha.VECTOR3(a3.pivot,{visibleIf:{applyOn:gU.indexOf(_U.GEOMETRIES)}})}};class c3 extends uV{constructor(){super(...arguments),this.paramsConfig=l3}static type(){return O2.TRANSFORM}static displayedInputNames(){return[\\\\\\\"geometries or objects to transform\\\\\\\"]}initializeNode(){this.io.inputs.setCount(1),this.io.inputs.initInputsClonedState(o3.INPUT_CLONED_STATE),this.scene().dispatchController.onAddListener((()=>{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{this.params.label.init([this.p.applyOn],(()=>gU[this.pv.applyOn]))}))}))}setApplyOn(t){this.p.applyOn.set(gU.indexOf(t))}setObjectMode(t){this.p.objectMode.set(r3.indexOf(t))}cook(t){this._operation=this._operation||new o3(this.scene(),this.states);const e=this._operation.cook(t,this.pv);this.setCoreGroup(e)}}const h3=new class extends ua{constructor(){super(...arguments),this.useSecondInput=ha.BOOLEAN(1),this.reference=ha.OPERATOR_PATH(\\\\\\\"\\\\\\\",{nodeSelection:{context:ts.SOP},visibleIf:{useSecondInput:0}})}};class u3 extends uV{constructor(){super(...arguments),this.paramsConfig=h3}static type(){return\\\\\\\"transformCopy\\\\\\\"}static displayedInputNames(){return[\\\\\\\"objects to transform\\\\\\\",\\\\\\\"objects to copy transform from\\\\\\\"]}initializeNode(){this.io.inputs.setCount(1,2),this.io.inputs.initInputsClonedState([Qi.FROM_NODE,Qi.NEVER])}cook(t){this.pv.useSecondInput&&t[1]?this._copy_from_src_objects(t[0].objects(),t[1].objects()):this._copy_from_found_node(t[0].objects())}_copy_from_src_objects(t,e){let n,i;for(let s=0;s({name:t,value:e})))}};function _3(t){const e=[];for(let n=t+1;n<=6;n++)e.push({count:n});return{visibleIf:e}}const m3=new class extends ua{constructor(){super(...arguments),this.applyOn=ha.INTEGER(gU.indexOf(_U.GEOMETRIES),{menu:{entries:gU.map(((t,e)=>({name:t,value:e})))}}),this.count=ha.INTEGER(2,{range:[0,6],rangeLocked:[!0,!0]}),this.rotationOrder0=ha.INTEGER(d3,{separatorBefore:!0,...p3,..._3(0)}),this.r0=ha.VECTOR3([0,0,0],{..._3(0)}),this.rotationOrder1=ha.INTEGER(d3,{separatorBefore:!0,...p3,..._3(1)}),this.r1=ha.VECTOR3([0,0,0],{..._3(1)}),this.rotationOrder2=ha.INTEGER(d3,{separatorBefore:!0,...p3,..._3(2)}),this.r2=ha.VECTOR3([0,0,0],{..._3(2)}),this.rotationOrder3=ha.INTEGER(d3,{separatorBefore:!0,...p3,..._3(3)}),this.r3=ha.VECTOR3([0,0,0],{..._3(3)}),this.rotationOrder4=ha.INTEGER(d3,{separatorBefore:!0,...p3,..._3(4)}),this.r4=ha.VECTOR3([0,0,0],{..._3(4)}),this.rotationOrder5=ha.INTEGER(d3,{separatorBefore:!0,...p3,..._3(5)}),this.r5=ha.VECTOR3([0,0,0],{..._3(5)})}};class f3 extends uV{constructor(){super(...arguments),this.paramsConfig=m3,this._core_transform=new bU,this._t=new p.a(0,0,0),this._s=new p.a(1,1,1),this._scale=1}static type(){return\\\\\\\"transformMulti\\\\\\\"}static displayedInputNames(){return[\\\\\\\"objects to transform\\\\\\\",\\\\\\\"objects to copy initial transform from\\\\\\\"]}initializeNode(){this.io.inputs.setCount(1,2),this.io.inputs.initInputsClonedState([Qi.FROM_NODE,Qi.NEVER]),this.scene().dispatchController.onAddListener((()=>{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{this.params.label.init([this.p.applyOn],(()=>gU[this.pv.applyOn]))}))})),this.params.onParamsCreated(\\\\\\\"cache param pairs\\\\\\\",(()=>{this._rot_and_index_pairs=[[this.p.r0,this.p.rotationOrder0],[this.p.r1,this.p.rotationOrder1],[this.p.r2,this.p.rotationOrder2],[this.p.r3,this.p.rotationOrder3],[this.p.r4,this.p.rotationOrder4],[this.p.r5,this.p.rotationOrder5]]}))}cook(t){const e=t[0].objectsWithGeo(),n=t[1]?t[1].objectsWithGeo()[0]:void 0;this._apply_transforms(e,n),this.setObjects(e)}_apply_transforms(t,e){const n=gU[this.pv.applyOn];switch(n){case _U.GEOMETRIES:return this._apply_matrix_to_geometries(t,e);case _U.OBJECTS:return this._apply_matrix_to_objects(t,e)}os.unreachable(n)}_apply_matrix_to_geometries(t,e){if(!this._rot_and_index_pairs)return;if(e){const n=e.geometry;if(n){const e=[Ws.POSITION,Ws.NORMAL,Ws.TANGENT];for(let i of e){const e=n.attributes[i];for(let n of t){const t=n.geometry.attributes[i];e&&t&&Xs.copy(e,t)}}}}let n;for(let e=0;e({name:t,value:e})))}})}};class x3 extends uV{constructor(){super(...arguments),this.paramsConfig=y3,this._bbox_center=new p.a,this._translate_matrix=new A.a}static type(){return\\\\\\\"transformReset\\\\\\\"}static displayedInputNames(){return[\\\\\\\"objects to reset transform\\\\\\\",\\\\\\\"optional reference for center\\\\\\\"]}initializeNode(){this.io.inputs.setCount(1,2),this.io.inputs.initInputsClonedState(Qi.FROM_NODE)}setMode(t){this.p.mode.set(v3.indexOf(t))}cook(t){const e=v3[this.pv.mode];this._select_mode(e,t)}_select_mode(t,e){switch(t){case g3.RESET_OBJECT:return this._reset_objects(e);case g3.CENTER_GEO:return this._center_geos(e,!1);case g3.PROMOTE_GEO_TO_OBJECT:return this._center_geos(e,!0)}os.unreachable(t)}_reset_objects(t){const e=t[0],n=e.objects();for(let t of n)t.matrix.identity(),bU.decomposeMatrix(t);this.setCoreGroup(e)}_center_geos(t,e){const n=t[0],i=n.objectsWithGeo();let s=i;const r=t[1];r&&(s=r.objectsWithGeo());for(let t=0;te.h-t.h));const i=[{x:0,y:0,w:Math.max(Math.ceil(Math.sqrt(e/.95)),n),h:1/0}];let s=0,r=0;for(const e of t)for(let t=i.length-1;t>=0;t--){const n=i[t];if(!(e.w>n.w||e.h>n.h)){if(e.x=n.x,e.y=n.y,r=Math.max(r,e.y+e.h),s=Math.max(s,e.x+e.w),e.w===n.w&&e.h===n.h){const e=i.pop();t=this.minAllowedArgumentsCount()&&t<=this.maxAllowedArgumentsCount()}processArguments(t){throw\\\\\\\"Expression.Method._Base.process_arguments virtual method call. Please override\\\\\\\"}async getReferencedNodeContainer(t){const e=this.getReferencedNode(t);if(e){let t;if(t=e.isDirty()?await e.compute():e.containerController.container(),t){if(t.coreContent())return t}throw`referenced node invalid: ${e.path()}`}throw`invalid input (${t})`}getReferencedParam(t,e){const n=this.node();return n?bi.findParam(n,t,e):null}findReferencedGraphNode(t,e){if(!m.isNumber(t)){const n=t;return this.getReferencedNode(n,e)}{const e=t,n=this.node();if(n){return n.io.inputs.inputGraphNode(e)}}return null}getReferencedNode(t,e){let n=null;const i=this.node();if(m.isString(t)){if(i){const s=t;n=bi.findNode(i,s,e)}}else if(i){const e=t;n=i.io.inputs.input(e)}return n||null}findDependency(t){return null}createDependencyFromIndexOrPath(t){const e=new po,n=this.findReferencedGraphNode(t,e);return n?this.createDependency(n,t,e):(li.warn(\\\\\\\"node not found for path\\\\\\\",t),null)}createDependency(t,e,n){return Ur.create(this.param,e,t,n)}}class Y3 extends X3{constructor(){super(...arguments),this._require_dependency=!0}static requiredArguments(){return[[\\\\\\\"string\\\\\\\",\\\\\\\"arguments list\\\\\\\"],[\\\\\\\"number\\\\\\\",\\\\\\\"index\\\\\\\"]]}processArguments(t){return new Promise(((e,n)=>{if(2==t.length){const n=t[0],i=t[1];e(n.split(\\\\\\\" \\\\\\\")[i])}else e(0)}))}}class $3 extends X3{constructor(){super(...arguments),this._require_dependency=!0}static requiredArguments(){return[[\\\\\\\"string\\\\\\\",\\\\\\\"arguments list\\\\\\\"]]}processArguments(t){return new Promise(((e,n)=>{if(1==t.length){e(t[0].split(\\\\\\\" \\\\\\\").length)}else e(0)}))}}const J3=[\\\\\\\"min\\\\\\\",\\\\\\\"max\\\\\\\",\\\\\\\"size\\\\\\\",\\\\\\\"center\\\\\\\"],Z3=[\\\\\\\"x\\\\\\\",\\\\\\\"y\\\\\\\",\\\\\\\"z\\\\\\\"];class K3 extends X3{constructor(){super(...arguments),this._require_dependency=!0}static requiredArguments(){return[[\\\\\\\"string\\\\\\\",\\\\\\\"path to node\\\\\\\"],[\\\\\\\"string\\\\\\\",\\\\\\\"vector name, min, max, size or center\\\\\\\"],[\\\\\\\"string\\\\\\\",\\\\\\\"component_name, x,y or z\\\\\\\"]]}findDependency(t){return this.createDependencyFromIndexOrPath(t)}processArguments(t){let e=0;return new Promise((async(n,i)=>{if(t.length>=1){const s=t[0],r=t[1],o=t[2];let a=null;try{a=await this.getReferencedNodeContainer(s)}catch(t){i(t)}a&&(e=this._get_value_from_container(a,r,o),n(e))}else n(0)}))}_get_value_from_container(t,e,n){const i=t.boundingBox();if(!e)return i;if(J3.indexOf(e)>=0){let t=new p.a;switch(e){case\\\\\\\"size\\\\\\\":i.getSize(t);break;case\\\\\\\"center\\\\\\\":i.getCenter(t);break;default:t=i[e]}return n?Z3.indexOf(n)>=0?t[n]:-1:t}return-1}}class Q3 extends X3{constructor(){super(...arguments),this._require_dependency=!0}static requiredArguments(){return[[\\\\\\\"string\\\\\\\",\\\\\\\"path to node\\\\\\\"],[\\\\\\\"string\\\\\\\",\\\\\\\"component_name, x,y or z\\\\\\\"]]}findDependency(t){return this.createDependencyFromIndexOrPath(t)}processArguments(t){return new Promise((async(e,n)=>{if(t.length>=1){const i=t[0],s=t[1];let r=null;try{r=await this.getReferencedNodeContainer(i)}catch(t){n(t)}if(r){const t=r.boundingBox(),n=t.min.clone().add(t.max).multiplyScalar(.5);if(s){const t=n[s];e(null!=t?t:0)}else e(n)}}else e(0)}))}}class t4 extends X3{constructor(){super(...arguments),this._require_dependency=!0}static requiredArguments(){return[[\\\\\\\"string\\\\\\\",\\\\\\\"path to param\\\\\\\"]]}findDependency(t){const e=new po,n=this.getReferencedParam(t,e);return n?this.createDependency(n,t,e):null}async processArguments(t){return new Promise((async(e,n)=>{let i=0;if(1==t.length){const s=t[0],r=this.getReferencedParam(s);if(r){r.isDirty()&&await r.compute();const t=r.value;null!=t&&(i=t,e(i))}else n(0)}}))}}class e4 extends X3{constructor(){super(...arguments),this._require_dependency=!0}static requiredArguments(){return[[\\\\\\\"string\\\\\\\",\\\\\\\"path to copy\\\\\\\"],[\\\\\\\"integer\\\\\\\",\\\\\\\"default value\\\\\\\"]]}static optionalArguments(){return[[\\\\\\\"string\\\\\\\",\\\\\\\"attribute name (optional)\\\\\\\"]]}findDependency(t){const e=this.findReferencedGraphNode(t);if(e&&\\\\\\\"copy\\\\\\\"==e.type()){const n=e.stamp_node;return this.createDependency(n,t)}return null}processArguments(t){return new Promise(((e,n)=>{if(2==t.length||3==t.length){const n=t[0],i=t[1],s=t[2],r=this.node(),o=r?bi.findNode(r,n):null;let a;o&&o.type()==DZ.type()&&(a=o.stamp_value(s)),null==a&&(a=i),e(a)}else e(0)}))}}class n4 extends X3{constructor(){super(...arguments),this._require_dependency=!0,this._resolution=new d.a}static requiredArguments(){return[[\\\\\\\"string\\\\\\\",\\\\\\\"path to node\\\\\\\"],[\\\\\\\"string\\\\\\\",\\\\\\\"component_name: x or y\\\\\\\"]]}findDependency(t){return this.createDependencyFromIndexOrPath(t)}async processArguments(t){if(1==t.length||2==t.length){const e=t[0],n=t[1],i=await this.getReferencedNodeContainer(e);if(i){const t=i.resolution();if(!n)return this._resolution.set(t[0],t[1]),this._resolution;if([0,\\\\\\\"0\\\\\\\",\\\\\\\"x\\\\\\\"].includes(n))return t[0];if([1,\\\\\\\"1\\\\\\\",\\\\\\\"y\\\\\\\"].includes(n))return t[1]}}return-1}}class i4 extends X3{constructor(){super(...arguments),this._require_dependency=!0}static requiredArguments(){return[]}async processArguments(t){return new Promise((async(t,e)=>{t(ng.isMobile())}))}}class s4 extends X3{constructor(){super(...arguments),this._require_dependency=!0}static requiredArguments(){return[]}async processArguments(t){return new Promise((async(t,e)=>{t(ng.isTouchDevice())}))}}class r4 extends X3{static requiredArguments(){return[[\\\\\\\"string\\\\\\\",\\\\\\\"javascript expression\\\\\\\"]]}async processArguments(t){let e=0;if(1==t.length){const n=t[0];if(this._function=this._function||this._create_function(n),this._function)try{e=this._function(this.param.scene(),this.param.node,this.param)}catch(t){console.warn(\\\\\\\"expression error\\\\\\\"),console.warn(t)}}return e}_create_function(t){return new Function(\\\\\\\"scene\\\\\\\",\\\\\\\"node\\\\\\\",\\\\\\\"param\\\\\\\",`return ${t}`)}}class o4 extends X3{constructor(){super(...arguments),this._require_dependency=!0}static requiredArguments(){return[[\\\\\\\"string\\\\\\\",\\\\\\\"path to node\\\\\\\"],[\\\\\\\"string\\\\\\\",\\\\\\\"attribute name\\\\\\\"],[\\\\\\\"index\\\\\\\",\\\\\\\"object index\\\\\\\"]]}findDependency(t){return this.createDependencyFromIndexOrPath(t)}processArguments(t){return new Promise((async(e,n)=>{if(3==t.length){const i=t[0],s=t[1],r=t[2];let o=null;try{o=await this.getReferencedNodeContainer(i)}catch(t){n(t)}if(o){e(this._get_value_from_container(o,s,r))}}else console.warn(`${t.length} given when expected 3`),e(0)}))}_get_value_from_container(t,e,n){const i=t.coreContent();if(i){const t=i.coreObjects()[n];return t?t.attribValue(e):0}return null}}class a4 extends X3{constructor(){super(...arguments),this._require_dependency=!0}static requiredArguments(){return[[\\\\\\\"string\\\\\\\",\\\\\\\"path to node\\\\\\\"]]}findDependency(t){return this.createDependencyFromIndexOrPath(t)}processArguments(t){return new Promise((async(e,n)=>{if(1==t.length){const i=t[0];let s;try{s=await this.getReferencedNodeContainer(i)}catch(t){return void n(t)}if(s){e(s.objectsCount())}}else e(0)}))}}class l4 extends X3{constructor(){super(...arguments),this._require_dependency=!0}static requiredArguments(){return[[\\\\\\\"string\\\\\\\",\\\\\\\"path to node\\\\\\\"]]}findDependency(t){const e=this.findReferencedGraphNode(t);if(e){const n=e;if(n.nameController){const e=n.nameController.graph_node;return this.createDependency(e,t)}}return null}processArguments(t){return new Promise(((e,n)=>{if(1==t.length){const n=t[0],i=this.getReferencedNode(n);if(i){const t=i.name();e(ss.tailDigits(t))}else e(0)}else e(0)}))}}class c4 extends X3{constructor(){super(...arguments),this._require_dependency=!0}static requiredArguments(){return[[\\\\\\\"string\\\\\\\",\\\\\\\"path to node\\\\\\\"]]}findDependency(t){const e=this.findReferencedGraphNode(t);if(e){const n=e;if(n.nameController){const e=n.nameController.graph_node;return this.createDependency(e,t)}}return null}processArguments(t){return new Promise(((e,n)=>{if(1==t.length){const n=t[0],i=this.getReferencedNode(n);if(i){e(i.name())}else e(0)}else e(0)}))}}class h4 extends X3{static requiredArguments(){return[[\\\\\\\"string\\\\\\\",\\\\\\\"number\\\\\\\"]]}processArguments(t){return new Promise((e=>{const n=t[0]||2;e(`${t[1]||0}`.padStart(n,\\\\\\\"0\\\\\\\"))}))}}class u4 extends X3{constructor(){super(...arguments),this._require_dependency=!0}static requiredArguments(){return[[\\\\\\\"string\\\\\\\",\\\\\\\"path to node\\\\\\\"],[\\\\\\\"string\\\\\\\",\\\\\\\"attribute name\\\\\\\"],[\\\\\\\"index\\\\\\\",\\\\\\\"point index\\\\\\\"]]}findDependency(t){return this.createDependencyFromIndexOrPath(t)}processArguments(t){return new Promise((async(e,n)=>{if(3==t.length){const i=t[0],s=t[1],r=t[2];let o=null;try{o=await this.getReferencedNodeContainer(i)}catch(t){n(t)}if(o){e(this._get_value_from_container(o,s,r))}}else console.warn(`${t.length} given when expected 3`),e(0)}))}_get_value_from_container(t,e,n){const i=t.coreContent();if(i){const t=i.points()[n];return t?t.attribValue(e):0}return null}}class d4 extends X3{constructor(){super(...arguments),this._require_dependency=!0}static requiredArguments(){return[[\\\\\\\"string\\\\\\\",\\\\\\\"path to node\\\\\\\"]]}findDependency(t){return this.createDependencyFromIndexOrPath(t)}processArguments(t){return new Promise((async(e,n)=>{if(1==t.length){const i=t[0];let s;try{s=await this.getReferencedNodeContainer(i)}catch(t){return void n(t)}if(s){e(s.pointsCount())}}else e(0)}))}}class p4 extends X3{static requiredArguments(){return[[\\\\\\\"string\\\\\\\",\\\\\\\"string to count characters of\\\\\\\"]]}async processArguments(t){let e=0;if(1==t.length){e=t[0].length}return e}}class _4 extends X3{static requiredArguments(){return[]}async processArguments(t){let e=\\\\\\\"\\\\\\\";for(let n of t)null==n&&(n=\\\\\\\"\\\\\\\"),e+=`${n}`;return e}}class m4 extends X3{static requiredArguments(){return[[\\\\\\\"string\\\\\\\",\\\\\\\"string to get index from\\\\\\\"],[\\\\\\\"string\\\\\\\",\\\\\\\"char to find index of\\\\\\\"]]}async processArguments(t){let e=-1;if(2==t.length){const n=t[0],i=t[1];e=n.indexOf(i)}return e}}class f4 extends X3{static requiredArguments(){return[[\\\\\\\"string\\\\\\\",\\\\\\\"string to get range from\\\\\\\"],[\\\\\\\"integer\\\\\\\",\\\\\\\"range start\\\\\\\"],[\\\\\\\"integer\\\\\\\",\\\\\\\"range size\\\\\\\"]]}async processArguments(t){let e=\\\\\\\"\\\\\\\";const n=t[0],i=t[1]||0;let s=t[2]||1;return n&&(e=n.substr(i,s)),e}}class g4 extends X3{constructor(){super(...arguments),this._require_dependency=!0,this._windowSize=new d.a}static requiredArguments(){return[[]]}findDependency(t){return this.param.addGraphInput(this.param.scene().windowController.graphNode()),null}processArguments(t){return new Promise((t=>{this._windowSize.set(window.innerWidth,window.innerHeight),t(this._windowSize)}))}}class v4{constructor(t,e){this._controller=t,this._node=e,this._deleted_params_data=new Map,this._created_spare_param_names=[],this._raw_input_serialized_by_param_name=new Map,this._init_value_serialized_by_param_name=new Map}get assembler(){return this._controller.assembler}createSpareParameters(){var t;const e={},n=this.assembler.param_configs(),i=n.map((t=>t.name())),s=b.clone(i);if(0==this._validateNames(s))return;b.clone(this._created_spare_param_names).concat(s).forEach((t=>{const n=this._node.params.get(t);if(n){this._raw_input_serialized_by_param_name.set(n.name(),n.rawInputSerialized()),this._init_value_serialized_by_param_name.set(n.name(),n.defaultValueSerialized());const t=rV.dispatch_param(n);if(t.required()){const e=t.data();this._deleted_params_data.set(n.name(),e)}}e.namesToDelete=e.namesToDelete||[],e.namesToDelete.push(t)}));for(let t of n)if(s.indexOf(t.name())>=0){const n=b.clone(t.param_options),i={spare:!0,computeOnDirty:!0,cook:!1},s=b.merge(n,i);let r=this._init_value_serialized_by_param_name.get(t.name());null==r&&(r=t.default_value);let o=this._raw_input_serialized_by_param_name.get(t.name());null==o&&(o=t.default_value),e.toAdd=e.toAdd||[],e.toAdd.push({name:t.name(),type:t.type(),init_value:r,raw_input:o,options:s})}this._node.params.updateParams(e),this._created_spare_param_names=(null===(t=e.toAdd)||void 0===t?void 0:t.map((t=>t.name)))||[];for(let t of n){const e=this._node.params.get(t.name());e&&(t.execute_callback(this._node,e),e.type()==Cr.OPERATOR_PATH&&setTimeout((async()=>{e.isDirty()&&await e.compute(),e.options.executeCallback()}),200))}}_validateNames(t){const e=b.clone(this._node.params.non_spare_names),n=f.intersection(t,e);if(n.length>0){const t=`${this._node.path()} attempts to create spare params called '${n.join(\\\\\\\", \\\\\\\")}' with same name as params`;return this._node.states.error.set(t),!1}return!0}}class y4{constructor(t,e){this.node=t,this._globals_handler=new Pf,this._compile_required=!0,this._assembler=new e(this.node),this._spare_params_controller=new v4(this,this.node)}set_assembler_globals_handler(t){(this._globals_handler?this._globals_handler.id():null)!=(t?t.id():null)&&(this._globals_handler=t,this.set_compilation_required_and_dirty(),this._assembler.reset_configs())}get assembler(){return this._assembler}get globals_handler(){return this._globals_handler}add_output_inputs(t){this._assembler.add_output_inputs(t)}add_globals_outputs(t){this._assembler.add_globals_outputs(t)}allow_attribute_exports(){return this._assembler.allow_attribute_exports()}setCompilationRequired(t=!0){this._compile_required=t}set_compilation_required_and_dirty(t){this.setCompilationRequired(),this.node.setDirty(t)}compileRequired(){return this._compile_required}post_compile(){this.createSpareParameters(),this.setCompilationRequired(!1)}createSpareParameters(){this._spare_params_controller.createSpareParameters()}addFilterFragmentShaderCallback(t,e){this.assembler._addFilterFragmentShaderCallback(t,e),this.setCompilationRequired()}removeFilterFragmentShaderCallback(t){this.assembler._removeFilterFragmentShaderCallback(t),this.setCompilationRequired()}}var x4;!function(t){t.FUNCTION_DECLARATION=\\\\\\\"function_declaration\\\\\\\",t.DEFINE=\\\\\\\"define\\\\\\\",t.BODY=\\\\\\\"body\\\\\\\"}(x4||(x4={}));class b4{constructor(t,e,n){this._name=t,this._input_names=e,this._dependencies=n}name(){return this._name}input_names(){return this._input_names}dependencies(){return this._dependencies}}class w4{constructor(t,e={}){this._name=t,this._options=e}name(){return this._name}default_from_attribute(){return this._options.default_from_attribute||!1}default(){return this._options.default}if_condition(){return this._options.if}prefix(){return this._options.prefix||\\\\\\\"\\\\\\\"}suffix(){return this._options.suffix||\\\\\\\"\\\\\\\"}postLines(){return this._options.postLines}}class T4{constructor(t){this._shader_name=t,this._definitions_by_node_id=new Map,this._body_lines_by_node_id=new Map}get shader_name(){return this._shader_name}addDefinitions(t,e){for(let n of e)h.pushOnArrayAtEntry(this._definitions_by_node_id,t.graphNodeId(),n)}definitions(t){return this._definitions_by_node_id.get(t.graphNodeId())}addBodyLines(t,e){for(let n of e)h.pushOnArrayAtEntry(this._body_lines_by_node_id,t.graphNodeId(),n)}body_lines(t){return this._body_lines_by_node_id.get(t.graphNodeId())}}class A4{constructor(t,e,n){this._shader_names=t,this._current_shader_name=e,this._assembler=n,this._lines_controller_by_shader_name=new Map;for(let t of this._shader_names)this._lines_controller_by_shader_name.set(t,new T4(t))}assembler(){return this._assembler}shaderNames(){return this._shader_names}set_current_shader_name(t){this._current_shader_name=t}get current_shader_name(){return this._current_shader_name}addDefinitions(t,e,n){if(0==e.length)return;n=n||this._current_shader_name;const i=this._lines_controller_by_shader_name.get(n);i&&i.addDefinitions(t,e)}definitions(t,e){const n=this._lines_controller_by_shader_name.get(t);if(n)return n.definitions(e)}addBodyLines(t,e,n){if(0==e.length)return;n=n||this._current_shader_name;const i=this._lines_controller_by_shader_name.get(n);i&&i.addBodyLines(t,e)}body_lines(t,e){const n=this._lines_controller_by_shader_name.get(t);if(n)return n.body_lines(e)}}const M4={[x4.FUNCTION_DECLARATION]:\\\\\\\"\\\\\\\",[x4.DEFINE]:\\\\\\\";\\\\\\\",[x4.BODY]:\\\\\\\";\\\\\\\"},E4={[x4.FUNCTION_DECLARATION]:\\\\\\\"\\\\\\\",[x4.DEFINE]:\\\\\\\"\\\\\\\",[x4.BODY]:\\\\\\\"\\\\t\\\\\\\"};class S4{static node_comment(t,e){let n=`// ${t.path()}`,i=E4[e];if(e==x4.BODY){let e=this.node_distance_to_material(t);t.type()==ns.OUTPUT&&(e+=1),i=i.repeat(e)}return e==x4.BODY&&(n=`${i}${n}`),n}static line_wrap(t,e,n){let i=!0;0!=e.indexOf(\\\\\\\"#if\\\\\\\")&&0!=e.indexOf(\\\\\\\"#endif\\\\\\\")||(i=!1);let s=E4[n];if(n==x4.BODY&&(s=s.repeat(this.node_distance_to_material(t))),e=`${s}${e}`,i){const t=e[e.length-1],i=M4[n];t!=i&&\\\\\\\"{\\\\\\\"!=t&&\\\\\\\"}\\\\\\\"!=t&&(e+=i)}return e}static post_line_separator(t){return t==x4.BODY?\\\\\\\"\\\\t\\\\\\\":\\\\\\\"\\\\\\\"}static node_distance_to_material(t){const e=t.parent();if(!e)return 0;if(e.context()!=t.context())return 1;{let n=1;return t.type()!=ns.INPUT&&t.type()!=ns.OUTPUT||(n=0),n+this.node_distance_to_material(e)}}}class C4{constructor(t,e,n){this._node_traverser=t,this._root_nodes_for_shader_method=e,this._assembler=n,this._param_configs_controller=new PF,this._param_configs_set_allowed=!0,this._lines=new Map}shaderNames(){return this._node_traverser.shaderNames()}buildFromNodes(t,e){this._node_traverser.traverse(t);const n=new Map;for(let t of this.shaderNames()){const e=this._node_traverser.nodes_for_shader_name(t);n.set(t,e)}const i=this._node_traverser.sorted_nodes();for(let t of this.shaderNames()){const e=this._root_nodes_for_shader_method(t);for(let i of e)h.pushOnArrayAtEntry(n,t,i)}const s=new Map;for(let t of i)s.set(t.graphNodeId(),!0);for(let e of t)s.get(e.graphNodeId())||(i.push(e),s.set(e.graphNodeId(),!0));for(let t of i)t.reset_code();for(let t of e)t.reset_code();this._shaders_collection_controller=new A4(this.shaderNames(),this.shaderNames()[0],this._assembler),this.reset();for(let t of this.shaderNames()){let e=n.get(t)||[];if(e=f.uniq(e),this._shaders_collection_controller.set_current_shader_name(t),e)for(let t of e)t.setLines(this._shaders_collection_controller)}if(this._param_configs_set_allowed){for(let t of e)t.setParamConfigs();this.setParamConfigs(e)}this.set_code_lines(i)}shaders_collection_controller(){return this._shaders_collection_controller}disallow_new_param_configs(){this._param_configs_set_allowed=!1}allow_new_param_configs(){this._param_configs_set_allowed=!0}reset(){for(let t of this.shaderNames()){const e=new Map;this._lines.set(t,e)}}param_configs(){return this._param_configs_controller.list()||[]}lines(t,e){var n;return(null===(n=this._lines.get(t))||void 0===n?void 0:n.get(e))||[]}all_lines(){return this._lines}setParamConfigs(t){this._param_configs_controller.reset();for(let e of t){const t=e.param_configs();if(t)for(let e of t)this._param_configs_controller.push(e)}}set_code_lines(t){for(let e of this.shaderNames())this.add_code_lines(t,e)}add_code_lines(t,e){this.addDefinitions(t,e,Af.FUNCTION,x4.FUNCTION_DECLARATION),this.addDefinitions(t,e,Af.UNIFORM,x4.DEFINE),this.addDefinitions(t,e,Af.VARYING,x4.DEFINE),this.addDefinitions(t,e,Af.ATTRIBUTE,x4.DEFINE),this.add_code_line_for_nodes_and_line_type(t,e,x4.BODY)}addDefinitions(t,e,n,i){if(!this._shaders_collection_controller)return;const s=[];for(let i of t){let t=this._shaders_collection_controller.definitions(e,i);if(t){t=t.filter((t=>t.definition_type==n));for(let e of t)s.push(e)}}if(s.length>0){const t=new Tf(s),n=t.uniq();if(t.errored)throw`code builder error: ${t.error_message}`;const r=new Map,o=new Map;for(let t of n){const e=t.node.graphNodeId();o.has(e)||o.set(e,!0),h.pushOnArrayAtEntry(r,e,t)}const a=this._lines.get(e);o.forEach(((t,e)=>{const n=r.get(e);if(n){const t=n[0];if(t){const e=S4.node_comment(t.node,i);h.pushOnArrayAtEntry(a,i,e);for(let e of n){const n=S4.line_wrap(t.node,e.line,i);h.pushOnArrayAtEntry(a,i,n)}const s=S4.post_line_separator(i);h.pushOnArrayAtEntry(a,i,s)}}}))}}add_code_line_for_nodes_and_line_type(t,e,n){var i=(t=t.filter((t=>{if(this._shaders_collection_controller){const n=this._shaders_collection_controller.body_lines(e,t);return n&&n.length>0}}))).length;for(let s=0;s0){const r=this._lines.get(e),o=S4.node_comment(t,n);if(h.pushOnArrayAtEntry(r,n,o),f.uniq(s).forEach((e=>{e=S4.line_wrap(t,e,n),h.pushOnArrayAtEntry(r,n,e)})),n!=x4.BODY||!i){const t=S4.post_line_separator(n);h.pushOnArrayAtEntry(r,n,t)}}}}class N4{constructor(t,e,n){this._parent_node=t,this._shader_names=e,this._input_names_for_shader_name_method=n,this._leaves_graph_id=new Map,this._graph_ids_by_shader_name=new Map,this._outputs_by_graph_id=new Map,this._depth_by_graph_id=new Map,this._graph_id_by_depth=new Map,this._graph=this._parent_node.scene().graph}reset(){this._leaves_graph_id.clear(),this._graph_ids_by_shader_name.clear(),this._outputs_by_graph_id.clear(),this._depth_by_graph_id.clear(),this._graph_id_by_depth.clear(),this._shader_names.forEach((t=>{this._graph_ids_by_shader_name.set(t,new Map)}))}shaderNames(){return this._shader_names}input_names_for_shader_name(t,e){return this._input_names_for_shader_name_method(t,e)}traverse(t){this.reset();for(let t of this.shaderNames())this._leaves_graph_id.set(t,new Map);for(let e of this.shaderNames()){this._shader_name=e;for(let e of t)this.find_leaves_from_root_node(e),this.set_nodes_depth()}this._depth_by_graph_id.forEach(((t,e)=>{null!=t&&h.pushOnArrayAtEntry(this._graph_id_by_depth,t,e)}))}leaves_from_nodes(t){var e;this._shader_name=Mf.LEAVES_FROM_NODES_SHADER,this._graph_ids_by_shader_name.set(this._shader_name,new Map),this._leaves_graph_id.set(this._shader_name,new Map);for(let e of t)this.find_leaves(e);const n=[];return null===(e=this._leaves_graph_id.get(this._shader_name))||void 0===e||e.forEach(((t,e)=>{n.push(e)})),this._graph.nodesFromIds(n)}nodes_for_shader_name(t){const e=[];this._graph_id_by_depth.forEach(((t,n)=>{e.push(n)})),e.sort(((t,e)=>t-e));const n=[],i=new Map;return e.forEach((e=>{const s=this._graph_id_by_depth.get(e);s&&s.forEach((e=>{var s;if(null===(s=this._graph_ids_by_shader_name.get(t))||void 0===s?void 0:s.get(e)){const s=this._graph.nodeFromId(e);this.add_nodes_with_children(s,i,n,t)}}))})),n}sorted_nodes(){const t=[];this._graph_id_by_depth.forEach(((e,n)=>{t.push(n)})),t.sort(((t,e)=>t-e));const e=[],n=new Map;return t.forEach((t=>{const i=this._graph_id_by_depth.get(t);if(i)for(let t of i){const i=this._graph.nodeFromId(t);i&&this.add_nodes_with_children(i,n,e)}})),e}add_nodes_with_children(t,e,n,i){if(e.get(t.graphNodeId())||(n.push(t),e.set(t.graphNodeId(),!0)),t.type()==ns.INPUT){const s=t.parent();if(s){const r=this.sorted_nodes_for_shader_name_for_parent(s,i);for(let s of r)s.graphNodeId()!=t.graphNodeId()&&this.add_nodes_with_children(s,e,n,i)}}}sorted_nodes_for_shader_name_for_parent(t,e){const n=[];this._graph_id_by_depth.forEach(((t,e)=>{n.push(e)})),n.sort(((t,e)=>t-e));const i=[];n.forEach((n=>{const s=this._graph_id_by_depth.get(n);s&&s.forEach((n=>{var s;if(!e||(null===(s=this._graph_ids_by_shader_name.get(e))||void 0===s?void 0:s.get(n))){const e=this._graph.nodeFromId(n);e.parent()==t&&i.push(e)}}))}));const s=i[0];return t.context()==s.context()&&i.push(t),i}find_leaves_from_root_node(t){var e;null===(e=this._graph_ids_by_shader_name.get(this._shader_name))||void 0===e||e.set(t.graphNodeId(),!0);const n=this.input_names_for_shader_name(t,this._shader_name);if(n)for(let e of n){const n=t.io.inputs.named_input(e);n&&(h.pushOnArrayAtEntry(this._outputs_by_graph_id,n.graphNodeId(),t.graphNodeId()),this.find_leaves(n))}this._outputs_by_graph_id.forEach(((t,e)=>{this._outputs_by_graph_id.set(e,f.uniq(t))}))}find_leaves(t){var e;null===(e=this._graph_ids_by_shader_name.get(this._shader_name))||void 0===e||e.set(t.graphNodeId(),!0);const n=this._find_inputs_or_children(t),i=f.compact(n),s=f.uniq(i.map((t=>t.graphNodeId()))).map((t=>this._graph.nodeFromId(t)));if(s.length>0)for(let e of s)h.pushOnArrayAtEntry(this._outputs_by_graph_id,e.graphNodeId(),t.graphNodeId()),this.find_leaves(e);else this._leaves_graph_id.get(this._shader_name).set(t.graphNodeId(),!0)}_find_inputs_or_children(t){var e,n;if(t.type()==ns.INPUT)return(null===(e=t.parent())||void 0===e?void 0:e.io.inputs.inputs())||[];if(t.childrenAllowed()){return[null===(n=t.childrenController)||void 0===n?void 0:n.output_node()]}return t.io.inputs.inputs()}set_nodes_depth(){this._leaves_graph_id.forEach(((t,e)=>{t.forEach(((t,e)=>{this.set_node_depth(e)}))}))}set_node_depth(t,e=0){const n=this._depth_by_graph_id.get(t);null!=n?this._depth_by_graph_id.set(t,Math.max(n,e)):this._depth_by_graph_id.set(t,e);const i=this._outputs_by_graph_id.get(t);i&&i.forEach((t=>{this.set_node_depth(t,e+1)}))}}const L4=new Map([[Mf.VERTEX,\\\\\\\"#include \\\\\\\"],[Mf.FRAGMENT,\\\\\\\"#include \\\\\\\"]]),O4=new Map([[Mf.VERTEX,\\\\\\\"#include \\\\\\\"],[Mf.FRAGMENT,\\\\\\\"vec4 diffuseColor = vec4( diffuse, opacity );\\\\\\\"]]),P4=new Map([[Mf.VERTEX,[\\\\\\\"#include \\\\\\\",\\\\\\\"#include \\\\\\\"]],[Mf.FRAGMENT,[]]]);class R4 extends class{}{constructor(t){super(),this._gl_parent_node=t,this._shaders_by_name=new Map,this._lines=new Map,this._root_nodes=[],this._leaf_nodes=[],this._uniforms_time_dependent=!1,this._uniforms_resolution_dependent=!1}setGlParentNode(t){this._overriden_gl_parent_node=t}currentGlParentNode(){return this._overriden_gl_parent_node||this._gl_parent_node}compile(){}_template_shader_for_shader_name(t){var e,n;switch(t){case Mf.VERTEX:return null===(e=this.templateShader())||void 0===e?void 0:e.vertexShader;case Mf.FRAGMENT:return null===(n=this.templateShader())||void 0===n?void 0:n.fragmentShader}}get globals_handler(){var t;return null===(t=this.currentGlParentNode().assemblerController)||void 0===t?void 0:t.globals_handler}compileAllowed(){var t;return null!=(null===(t=this.currentGlParentNode().assemblerController)||void 0===t?void 0:t.globals_handler)}shaders_by_name(){return this._shaders_by_name}_build_lines(){for(let t of this.shaderNames()){const e=this._template_shader_for_shader_name(t);e&&this._replace_template(e,t)}}set_root_nodes(t){this._root_nodes=t}templateShader(){}addUniforms(t){for(let e of this.param_configs())t[e.uniform_name]=e.uniform;this.uniformsTimeDependent()&&(t.time={value:this.currentGlParentNode().scene().time()}),this.uniforms_resolution_dependent()&&(t.resolution={value:new d.a(1e3,1e3)})}root_nodes_by_shader_name(t){const e=[];for(let t of this._root_nodes)switch(t.type()){case OF.type():case IF.type():e.push(t);break;case wf.type():case Ff.type():e.push(t)}return e}leaf_nodes_by_shader_name(t){const e=[];for(let t of this._leaf_nodes)switch(t.type()){case II.type():e.push(t);break;case wf.type():}return e}set_node_lines_globals(t,e){}set_node_lines_output(t,e){}set_node_lines_attribute(t,e){}codeBuilder(){return this._code_builder=this._code_builder||this._create_code_builder()}_resetCodeBuilder(){this._code_builder=void 0}_create_code_builder(){const t=new N4(this.currentGlParentNode(),this.shaderNames(),((t,e)=>this.input_names_for_shader_name(t,e)));return new C4(t,(t=>this.root_nodes_by_shader_name(t)),this)}build_code_from_nodes(t){const e=Df.findParamGeneratingNodes(this.currentGlParentNode());this.codeBuilder().buildFromNodes(t,e)}allow_new_param_configs(){this.codeBuilder().allow_new_param_configs()}disallow_new_param_configs(){this.codeBuilder().disallow_new_param_configs()}builder_param_configs(){return this.codeBuilder().param_configs()}builder_lines(t,e){return this.codeBuilder().lines(t,e)}all_builder_lines(){return this.codeBuilder().all_lines()}param_configs(){return(this._param_config_owner||this.codeBuilder()).param_configs()}set_param_configs_owner(t){this._param_config_owner=t,this._param_config_owner?this.codeBuilder().disallow_new_param_configs():this.codeBuilder().allow_new_param_configs()}static output_input_connection_points(){return[new qo(\\\\\\\"position\\\\\\\",Uo.VEC3),new qo(\\\\\\\"normal\\\\\\\",Uo.VEC3),new qo(\\\\\\\"color\\\\\\\",Uo.VEC3),new qo(\\\\\\\"alpha\\\\\\\",Uo.FLOAT),new qo(\\\\\\\"uv\\\\\\\",Uo.VEC2)]}add_output_inputs(t){t.io.inputs.setNamedInputConnectionPoints(R4.output_input_connection_points())}static create_globals_node_output_connections(){return[new qo(\\\\\\\"position\\\\\\\",Uo.VEC3),new qo(\\\\\\\"normal\\\\\\\",Uo.VEC3),new qo(\\\\\\\"color\\\\\\\",Uo.VEC3),new qo(\\\\\\\"uv\\\\\\\",Uo.VEC2),new qo(\\\\\\\"mvPosition\\\\\\\",Uo.VEC4),new qo(\\\\\\\"worldPosition\\\\\\\",Uo.VEC4),new qo(\\\\\\\"worldNormal\\\\\\\",Uo.VEC3),new qo(\\\\\\\"gl_Position\\\\\\\",Uo.VEC4),new qo(\\\\\\\"gl_FragCoord\\\\\\\",Uo.VEC4),new qo(\\\\\\\"cameraPosition\\\\\\\",Uo.VEC3),new qo(\\\\\\\"resolution\\\\\\\",Uo.VEC2),new qo(\\\\\\\"time\\\\\\\",Uo.FLOAT)]}create_globals_node_output_connections(){return R4.create_globals_node_output_connections()}add_globals_outputs(t){t.io.outputs.setNamedOutputConnectionPoints(this.create_globals_node_output_connections())}allow_attribute_exports(){return!1}reset_configs(){this._reset_shader_configs(),this._reset_variable_configs(),this._resetUniformsTimeDependency(),this._reset_uniforms_resolution_dependency()}shaderConfigs(){return this._shader_configs=this._shader_configs||this.create_shader_configs()}set_shader_configs(t){this._shader_configs=t}shaderNames(){var t;return(null===(t=this.shaderConfigs())||void 0===t?void 0:t.map((t=>t.name())))||[]}_reset_shader_configs(){this._shader_configs=void 0}create_shader_configs(){return[new b4(Mf.VERTEX,[\\\\\\\"position\\\\\\\",\\\\\\\"normal\\\\\\\",\\\\\\\"uv\\\\\\\",Ff.INPUT_NAME],[]),new b4(Mf.FRAGMENT,[\\\\\\\"color\\\\\\\",\\\\\\\"alpha\\\\\\\"],[Mf.VERTEX])]}shader_config(t){var e;return null===(e=this.shaderConfigs())||void 0===e?void 0:e.filter((e=>e.name()==t))[0]}variable_configs(){return this._variable_configs=this._variable_configs||this.create_variable_configs()}set_variable_configs(t){this._variable_configs=t}variable_config(t){return this.variable_configs().filter((e=>e.name()==t))[0]}static create_variable_configs(){return[new w4(\\\\\\\"position\\\\\\\",{default_from_attribute:!0,prefix:\\\\\\\"vec3 transformed = \\\\\\\"}),new w4(\\\\\\\"normal\\\\\\\",{default_from_attribute:!0,prefix:\\\\\\\"vec3 objectNormal = \\\\\\\",postLines:[\\\\\\\"#ifdef USE_TANGENT\\\\\\\",\\\\\\\"\\\\tvec3 objectTangent = vec3( tangent.xyz );\\\\\\\",\\\\\\\"#endif\\\\\\\"]}),new w4(\\\\\\\"color\\\\\\\",{prefix:\\\\\\\"diffuseColor.xyz = \\\\\\\"}),new w4(\\\\\\\"alpha\\\\\\\",{prefix:\\\\\\\"diffuseColor.a = \\\\\\\"}),new w4(\\\\\\\"uv\\\\\\\",{prefix:\\\\\\\"vUv = \\\\\\\",if:Pf.IF_RULE.uv})]}create_variable_configs(){return R4.create_variable_configs()}_reset_variable_configs(){this._variable_configs=void 0,this.variable_configs()}input_names_for_shader_name(t,e){var n;return(null===(n=this.shader_config(e))||void 0===n?void 0:n.input_names())||[]}_resetUniformsTimeDependency(){this._uniforms_time_dependent=!1}setUniformsTimeDependent(){this._uniforms_time_dependent=!0}uniformsTimeDependent(){return this._uniforms_time_dependent}_reset_uniforms_resolution_dependency(){this._uniforms_resolution_dependent=!1}set_uniforms_resolution_dependent(){this._uniforms_resolution_dependent=!0}uniforms_resolution_dependent(){return this._uniforms_resolution_dependent}insert_define_after(t){return L4.get(t)}insert_body_after(t){return O4.get(t)}lines_to_remove(t){return P4.get(t)}_replace_template(t,e){const n=this.builder_lines(e,x4.FUNCTION_DECLARATION),i=this.builder_lines(e,x4.DEFINE),s=this.builder_lines(e,x4.BODY);let r=t.split(\\\\\\\"\\\\n\\\\\\\");const o=[],a=this.insert_define_after(e),l=this.insert_body_after(e),c=this.lines_to_remove(e);let h=!1,u=!1;for(let t of r){1==h&&(n&&this._insert_lines(o,n),i&&this._insert_lines(o,i),h=!1),1==u&&(s&&this._insert_lines(o,s),u=!1);let e=!1;if(c)for(let n of c)t.indexOf(n)>=0&&(e=!0);e?(o.push(\\\\\\\"// removed:\\\\\\\"),o.push(`//${t}`)):o.push(t),a&&t.indexOf(a)>=0&&(h=!0),l&&t.indexOf(l)>=0&&(u=!0)}this._lines.set(e,o)}_insert_lines(t,e){if(e.length>0){for(let e=0;e<3;e++)t.push(\\\\\\\"\\\\\\\");for(let n of e)t.push(n);for(let e=0;e<3;e++)t.push(\\\\\\\"\\\\\\\")}}_addFilterFragmentShaderCallback(t,e){}_removeFilterFragmentShaderCallback(t){}getCustomMaterials(){return new Map}static expandShader(t){return function t(e){return e.replace(/^[ \\\\t]*#include +<([\\\\w\\\\d./]+)>/gm,(function(e,n){var i=U[n];if(void 0===i)throw new Error(\\\\\\\"Can not resolve #include <\\\\\\\"+n+\\\\\\\">\\\\\\\");return t(i)}))}(t)}}var I4,F4;!function(t){t.DISTANCE=\\\\\\\"customDistanceMaterial\\\\\\\",t.DEPTH=\\\\\\\"customDepthMaterial\\\\\\\",t.DEPTH_DOF=\\\\\\\"customDepthDOFMaterial\\\\\\\"}(I4||(I4={})),function(t){t.TIME=\\\\\\\"time\\\\\\\",t.RESOLUTION=\\\\\\\"resolution\\\\\\\",t.MV_POSITION=\\\\\\\"mvPosition\\\\\\\",t.GL_POSITION=\\\\\\\"gl_Position\\\\\\\",t.GL_FRAGCOORD=\\\\\\\"gl_FragCoord\\\\\\\",t.GL_POINTCOORD=\\\\\\\"gl_PointCoord\\\\\\\"}(F4||(F4={}));const D4=[F4.GL_FRAGCOORD,F4.GL_POINTCOORD];class B4 extends R4{constructor(){super(...arguments),this._assemblers_by_custom_name=new Map,this._filterFragmentShaderCallbacks=new Map}createMaterial(){return new F}custom_assembler_class_by_custom_name(){}_addCustomMaterials(t){const e=this.custom_assembler_class_by_custom_name();e&&e.forEach(((e,n)=>{this._add_custom_material(t,n,e)}))}_add_custom_material(t,e,n){let i=this._assemblers_by_custom_name.get(e);i||(i=new n(this.currentGlParentNode()),this._assemblers_by_custom_name.set(e,i)),t.customMaterials=t.customMaterials||{};const s=i.createMaterial();s.name=e,t.customMaterials[e]=s}compileCustomMaterials(t){const e=this.custom_assembler_class_by_custom_name();e&&e.forEach(((e,n)=>{if(this._code_builder){let i=this._assemblers_by_custom_name.get(n);i||(i=new e(this.currentGlParentNode()),this._assemblers_by_custom_name.set(n,i)),i.set_root_nodes(this._root_nodes),i.set_param_configs_owner(this._code_builder),i.set_shader_configs(this.shaderConfigs()),i.set_variable_configs(this.variable_configs());const s=t.customMaterials[n];s&&(i.setFilterFragmentShaderMethodOwner(this),i.compileMaterial(s),i.setFilterFragmentShaderMethodOwner(void 0))}}))}_resetFilterFragmentShaderCallbacks(){this._filterFragmentShaderCallbacks.clear()}_addFilterFragmentShaderCallback(t,e){this._filterFragmentShaderCallbacks.set(t,e)}_removeFilterFragmentShaderCallback(t){this._filterFragmentShaderCallbacks.delete(t)}setFilterFragmentShaderMethodOwner(t){this._filterFragmentShaderMethodOwner=t}filterFragmentShader(t){return this._filterFragmentShaderCallbacks.forEach(((e,n)=>{t=e(t)})),t}processFilterFragmentShader(t){return this._filterFragmentShaderMethodOwner?this._filterFragmentShaderMethodOwner.filterFragmentShader(t):this.filterFragmentShader(t)}compileMaterial(t){if(!this.compileAllowed())return;const e=Df.findOutputNodes(this.currentGlParentNode());e.length>1&&this.currentGlParentNode().states.error.set(\\\\\\\"only one output node allowed\\\\\\\");const n=Df.findVaryingNodes(this.currentGlParentNode()),i=e.concat(n);this.set_root_nodes(i),this._update_shaders();const s=this._shaders_by_name.get(Mf.VERTEX),r=this._shaders_by_name.get(Mf.FRAGMENT);s&&r&&(t.vertexShader=s,t.fragmentShader=this.processFilterFragmentShader(r),this.addUniforms(t.uniforms),t.needsUpdate=!0);const o=this.currentGlParentNode().scene();this.uniformsTimeDependent()?o.uniformsController.addTimeDependentUniformOwner(t.uuid,t.uniforms):o.uniformsController.removeTimeDependentUniformOwner(t.uuid),this.uniforms_resolution_dependent()?o.uniformsController.addResolutionDependentUniformOwner(t.uuid,t.uniforms):o.uniformsController.removeResolutionDependentUniformOwner(t.uuid),t.customMaterials&&this.compileCustomMaterials(t)}_update_shaders(){this._shaders_by_name=new Map,this._lines=new Map;for(let t of this.shaderNames()){const e=this._template_shader_for_shader_name(t);e&&this._lines.set(t,e.split(\\\\\\\"\\\\n\\\\\\\"))}this._root_nodes.length>0&&(this.build_code_from_nodes(this._root_nodes),this._build_lines());for(let t of this.shaderNames()){const e=this._lines.get(t);e&&this._shaders_by_name.set(t,e.join(\\\\\\\"\\\\n\\\\\\\"))}}shadow_assembler_class_by_custom_name(){return{}}add_output_body_line(t,e,n){var i;const s=t.io.inputs.named_input(n),r=t.variableForInput(n),o=this.variable_config(n);let a=null;if(s)a=mf.vector3(r);else if(o.default_from_attribute()){const s=t.io.inputs.namedInputConnectionPointsByName(n);if(s){const r=s.type(),o=null===(i=this.globals_handler)||void 0===i?void 0:i.read_attribute(t,r,n,e);o&&(a=o)}}else{const t=o.default();t&&(a=t)}if(a){const n=o.prefix(),i=o.suffix(),s=o.if_condition();s&&e.addBodyLines(t,[`#if ${s}`]),e.addBodyLines(t,[`${n}${a}${i}`]);const r=o.postLines();r&&e.addBodyLines(t,r),s&&e.addBodyLines(t,[\\\\\\\"#endif\\\\\\\"])}}set_node_lines_output(t,e){var n;const i=e.current_shader_name,s=null===(n=this.shader_config(i))||void 0===n?void 0:n.input_names();if(s)for(let n of s)t.io.inputs.has_named_input(n)&&this.add_output_body_line(t,e,n)}set_node_lines_attribute(t,e){var n;const i=t.gl_type(),s=null===(n=this.globals_handler)||void 0===n?void 0:n.read_attribute(t,i,t.attribute_name,e),r=t.glVarName(t.output_name);e.addBodyLines(t,[`${i} ${r} = ${s}`])}handle_globals_output_name(t){var e;switch(t.output_name){case F4.TIME:return void this.handleTime(t);case F4.RESOLUTION:return void this.handle_resolution(t);case F4.MV_POSITION:return void this.handle_mvPosition(t);case F4.GL_POSITION:return void this.handle_gl_Position(t);case F4.GL_FRAGCOORD:return void this.handle_gl_FragCoord(t);case F4.GL_POINTCOORD:return void this.handle_gl_PointCoord(t);default:null===(e=this.globals_handler)||void 0===e||e.handle_globals_node(t.globals_node,t.output_name,t.shaders_collection_controller)}}handleTime(t){const e=new Nf(t.globals_node,Uo.FLOAT,t.output_name);t.globals_shader_name&&h.pushOnArrayAtEntry(t.definitions_by_shader_name,t.globals_shader_name,e);const n=`float ${t.var_name} = ${t.output_name}`;for(let i of t.dependencies)h.pushOnArrayAtEntry(t.definitions_by_shader_name,i,e),h.pushOnArrayAtEntry(t.body_lines_by_shader_name,i,n);t.body_lines.push(n),this.setUniformsTimeDependent()}handle_resolution(t){t.body_lines.push(`vec2 ${t.var_name} = resolution`);const e=new Nf(t.globals_node,Uo.VEC2,t.output_name);t.globals_shader_name&&h.pushOnArrayAtEntry(t.definitions_by_shader_name,t.globals_shader_name,e);for(let n of t.dependencies)h.pushOnArrayAtEntry(t.definitions_by_shader_name,n,e);this.set_uniforms_resolution_dependent()}handle_mvPosition(t){if(t.shader_name==Mf.FRAGMENT){const e=t.globals_node,n=t.shaders_collection_controller,i=new Lf(e,Uo.VEC4,t.var_name),s=`${t.var_name} = modelViewMatrix * vec4(position, 1.0)`;n.addDefinitions(e,[i],Mf.VERTEX),n.addBodyLines(e,[s],Mf.VERTEX),n.addDefinitions(e,[i])}}handle_gl_Position(t){if(t.shader_name==Mf.FRAGMENT){const e=t.globals_node,n=t.shaders_collection_controller,i=new Lf(e,Uo.VEC4,t.var_name),s=`${t.var_name} = projectionMatrix * modelViewMatrix * vec4(position, 1.0)`;n.addDefinitions(e,[i],Mf.VERTEX),n.addBodyLines(e,[s],Mf.VERTEX),n.addDefinitions(e,[i])}}handle_gl_FragCoord(t){t.shader_name==Mf.FRAGMENT&&t.body_lines.push(`vec4 ${t.var_name} = gl_FragCoord`)}handle_gl_PointCoord(t){t.shader_name==Mf.FRAGMENT?t.body_lines.push(`vec2 ${t.var_name} = gl_PointCoord`):t.body_lines.push(`vec2 ${t.var_name} = vec2(0.0, 0.0)`)}set_node_lines_globals(t,e){const n=[],i=e.current_shader_name,s=this.shader_config(i);if(!s)return;const r=s.dependencies(),o=new Map,a=new Map,l=this.used_output_names_for_shader(t,i);for(let s of l){const l=t.glVarName(s),c=e.current_shader_name,h={globals_node:t,shaders_collection_controller:e,output_name:s,globals_shader_name:c,definitions_by_shader_name:o,body_lines:n,var_name:l,shader_name:i,dependencies:r,body_lines_by_shader_name:a};this.handle_globals_output_name(h)}o.forEach(((n,i)=>{e.addDefinitions(t,n,i)})),a.forEach(((n,i)=>{e.addBodyLines(t,n,i)})),e.addBodyLines(t,n)}used_output_names_for_shader(t,e){const n=t.io.outputs.used_output_names(),i=[];for(let t of n)e==Mf.VERTEX&&D4.includes(t)||i.push(t);return i}}const z4=new Map([[Mf.VERTEX,\\\\\\\"#include \\\\\\\"],[Mf.FRAGMENT,\\\\\\\"vec4 diffuseColor = vec4( 1.0 );\\\\\\\"]]);const k4=new Map([[Mf.VERTEX,\\\\\\\"#include \\\\\\\"],[Mf.FRAGMENT,\\\\\\\"vec4 diffuseColor = vec4( 1.0 );\\\\\\\"]]);var U4=\\\\\\\"uniform float mNear;\\\\nuniform float mFar;\\\\n\\\\nvarying float vViewZDepth;\\\\n\\\\nvoid main() {\\\\n\\\\n\\\\tfloat color = 1.0 - smoothstep( mNear, mFar, vViewZDepth );\\\\n\\\\tgl_FragColor = vec4( vec3( color ), 1.0 );\\\\n\\\\n}\\\\n\\\\\\\";const G4=new Map([[Mf.VERTEX,\\\\\\\"// INSERT DEFINES\\\\\\\"]]),V4=new Map([[Mf.VERTEX,\\\\\\\"// INSERT BODY\\\\\\\"]]);const H4=new Map([]);H4.set(I4.DISTANCE,class extends B4{templateShader(){const t=H.distanceRGBA;return{vertexShader:t.vertexShader,fragmentShader:t.fragmentShader,uniforms:t.uniforms}}insert_body_after(t){return z4.get(t)}createMaterial(){const t=this.templateShader();return new F({defines:{DEPTH_PACKING:[w.Hb,w.j][0]},uniforms:I.clone(t.uniforms),vertexShader:t.vertexShader,fragmentShader:t.fragmentShader})}}),H4.set(I4.DEPTH,class extends B4{templateShader(){const t=H.depth;return{vertexShader:t.vertexShader,fragmentShader:t.fragmentShader,uniforms:t.uniforms}}insert_body_after(t){return k4.get(t)}createMaterial(){const t=this.templateShader();return new F({defines:{DEPTH_PACKING:[w.Hb,w.j][0]},uniforms:I.clone(t.uniforms),vertexShader:t.vertexShader,fragmentShader:t.fragmentShader})}}),H4.set(I4.DEPTH_DOF,class extends B4{templateShader(){return{vertexShader:\\\\\\\"#include \\\\n\\\\nvarying float vViewZDepth;\\\\n\\\\n// INSERT DEFINES\\\\n\\\\n\\\\n\\\\nvoid main() {\\\\n\\\\n\\\\t// INSERT BODY\\\\n\\\\n\\\\n\\\\t#include \\\\n\\\\n\\\\tvViewZDepth = - mvPosition.z;\\\\n}\\\\\\\",fragmentShader:U4,uniforms:{mNear:{value:0},mFar:{value:10}}}}insert_define_after(t){return G4.get(t)}insert_body_after(t){return V4.get(t)}createMaterial(){const t=this.templateShader();return new F({uniforms:I.clone(t.uniforms),vertexShader:t.vertexShader,fragmentShader:t.fragmentShader})}});class j4 extends B4{custom_assembler_class_by_custom_name(){return H4}}class W4 extends j4{templateShader(){const t=H.basic;return{vertexShader:t.vertexShader,fragmentShader:t.fragmentShader,uniforms:t.uniforms}}createMaterial(){const t=this.templateShader(),e=new F({lights:!1,uniforms:I.clone(t.uniforms),vertexShader:t.vertexShader,fragmentShader:t.fragmentShader});return this._addCustomMaterials(e),e}}class q4 extends j4{templateShader(){const t=H.lambert;return{vertexShader:t.vertexShader,fragmentShader:t.fragmentShader,uniforms:t.uniforms}}createMaterial(){const t=this.templateShader(),e=new F({lights:!0,uniforms:I.clone(t.uniforms),vertexShader:t.vertexShader,fragmentShader:t.fragmentShader});return this._addCustomMaterials(e),e}}class X4 extends j4{templateShader(){const t=H.phong;return{vertexShader:t.vertexShader,fragmentShader:t.fragmentShader,uniforms:t.uniforms}}createMaterial(){const t=this.templateShader(),e=new F({lights:!0,uniforms:I.clone(t.uniforms),vertexShader:t.vertexShader,fragmentShader:t.fragmentShader});return this._addCustomMaterials(e),e}}var Y4=\\\\\\\"SSSModel(/*isActive*/false,/*color*/vec3(1.0, 1.0, 1.0), /*thickness*/0.1, /*power*/2.0, /*scale*/16.0, /*distortion*/0.1,/*ambient*/0.4,/*attenuation*/0.8 )\\\\\\\";class $4 extends j4{constructor(t){super(t),this._gl_parent_node=t,this._addFilterFragmentShaderCallback(\\\\\\\"MeshStandardBuilderMatNode\\\\\\\",$4.filterFragmentShader)}isPhysical(){return!1}templateShader(){const t=this.isPhysical()?H.physical:H.standard;return{vertexShader:t.vertexShader,fragmentShader:t.fragmentShader,uniforms:t.uniforms}}static filterFragmentShader(t){return t=(t=(t=t.replace(\\\\\\\"#include \\\\\\\",\\\\\\\"float metalnessFactor = metalness * POLY_metalness;\\\\n\\\\n#ifdef USE_METALNESSMAP\\\\n\\\\n\\\\tvec4 texelMetalness = texture2D( metalnessMap, vUv );\\\\n\\\\n\\\\t// reads channel B, compatible with a combined OcclusionRoughnessMetallic (RGB) texture\\\\n\\\\tmetalnessFactor *= texelMetalness.b;\\\\n\\\\n#endif\\\\n\\\\\\\")).replace(\\\\\\\"#include \\\\\\\",\\\\\\\"float roughnessFactor = roughness * POLY_roughness;\\\\n\\\\n#ifdef USE_ROUGHNESSMAP\\\\n\\\\n\\\\tvec4 texelRoughness = texture2D( roughnessMap, vUv );\\\\n\\\\n\\\\t// reads channel G, compatible with a combined OcclusionRoughnessMetallic (RGB) texture\\\\n\\\\troughnessFactor *= texelRoughness.g;\\\\n\\\\n#endif\\\\n\\\\\\\")).replace(\\\\\\\"vec3 totalEmissiveRadiance = emissive;\\\\\\\",\\\\\\\"vec3 totalEmissiveRadiance = emissive * POLY_emissive;\\\\\\\"),$4.USE_SSS&&(t=(t=t.replace(/void main\\\\s?\\\\(\\\\) {/,\\\\\\\"struct SSSModel {\\\\n\\\\tbool isActive;\\\\n\\\\tvec3 color;\\\\n\\\\tfloat thickness;\\\\n\\\\tfloat power;\\\\n\\\\tfloat scale;\\\\n\\\\tfloat distortion;\\\\n\\\\tfloat ambient;\\\\n\\\\tfloat attenuation;\\\\n};\\\\n\\\\nvoid RE_Direct_Scattering(\\\\n\\\\tconst in IncidentLight directLight,\\\\n\\\\tconst in GeometricContext geometry,\\\\n\\\\tconst in SSSModel sssModel,\\\\n\\\\tinout ReflectedLight reflectedLight\\\\n\\\\t){\\\\n\\\\tvec3 scatteringHalf = normalize(directLight.direction + (geometry.normal * sssModel.distortion));\\\\n\\\\tfloat scatteringDot = pow(saturate(dot(geometry.viewDir, -scatteringHalf)), sssModel.power) * sssModel.scale;\\\\n\\\\tvec3 scatteringIllu = (scatteringDot + sssModel.ambient) * (sssModel.color * (1.0-sssModel.thickness));\\\\n\\\\treflectedLight.directDiffuse += scatteringIllu * sssModel.attenuation * directLight.color;\\\\n}\\\\n\\\\nvoid main() {\\\\\\\")).replace(\\\\\\\"#include \\\\\\\",\\\\\\\"#include \\\\nif(POLY_SSSModel.isActive){\\\\n\\\\tRE_Direct_Scattering(directLight, geometry, POLY_SSSModel, reflectedLight);\\\\n}\\\\n\\\\n\\\\\\\")),t}createMaterial(){const t=this.templateShader(),e={lights:!0,extensions:{derivatives:!0},uniforms:I.clone(t.uniforms),vertexShader:t.vertexShader,fragmentShader:t.fragmentShader},n=new F(e);return this.isPhysical()&&(n.defines.PHYSICAL=!0),this._addCustomMaterials(n),n}add_output_inputs(t){const e=R4.output_input_connection_points();e.push(new qo(\\\\\\\"metalness\\\\\\\",Uo.FLOAT,1)),e.push(new qo(\\\\\\\"roughness\\\\\\\",Uo.FLOAT,1)),e.push(new qo(\\\\\\\"emissive\\\\\\\",Uo.VEC3,[1,1,1])),$4.USE_SSS&&e.push(new qo(\\\\\\\"SSSModel\\\\\\\",Uo.SSS_MODEL,Y4)),this.isPhysical()&&(e.push(new qo(\\\\\\\"transmission\\\\\\\",Uo.FLOAT,1)),e.push(new qo(\\\\\\\"thickness\\\\\\\",Uo.FLOAT,1))),t.io.inputs.setNamedInputConnectionPoints(e)}create_shader_configs(){const t=[\\\\\\\"color\\\\\\\",\\\\\\\"alpha\\\\\\\",\\\\\\\"metalness\\\\\\\",\\\\\\\"roughness\\\\\\\",\\\\\\\"emissive\\\\\\\",\\\\\\\"SSSModel\\\\\\\"];return this.isPhysical()&&(t.push(\\\\\\\"transmission\\\\\\\"),t.push(\\\\\\\"thickness\\\\\\\")),[new b4(Mf.VERTEX,[\\\\\\\"position\\\\\\\",\\\\\\\"normal\\\\\\\",\\\\\\\"uv\\\\\\\"],[]),new b4(Mf.FRAGMENT,t,[Mf.VERTEX])]}create_variable_configs(){const t=R4.create_variable_configs();return t.push(new w4(\\\\\\\"metalness\\\\\\\",{default:\\\\\\\"1.0\\\\\\\",prefix:\\\\\\\"float POLY_metalness = \\\\\\\"})),t.push(new w4(\\\\\\\"roughness\\\\\\\",{default:\\\\\\\"1.0\\\\\\\",prefix:\\\\\\\"float POLY_roughness = \\\\\\\"})),t.push(new w4(\\\\\\\"emissive\\\\\\\",{default:\\\\\\\"vec3(1.0, 1.0, 1.0)\\\\\\\",prefix:\\\\\\\"vec3 POLY_emissive = \\\\\\\"})),$4.USE_SSS&&t.push(new w4(\\\\\\\"SSSModel\\\\\\\",{default:Y4,prefix:\\\\\\\"SSSModel POLY_SSSModel = \\\\\\\"})),this.isPhysical()&&(t.push(new w4(\\\\\\\"transmission\\\\\\\",{default:\\\\\\\"1.0\\\\\\\",prefix:\\\\\\\"float POLY_transmission = \\\\\\\"})),t.push(new w4(\\\\\\\"thickness\\\\\\\",{default:\\\\\\\"1.0\\\\\\\",prefix:\\\\\\\"float POLY_thickness = \\\\\\\"}))),t}}$4.USE_SSS=!0;class J4 extends $4{constructor(t){super(t),this._gl_parent_node=t,this._addFilterFragmentShaderCallback(\\\\\\\"MeshPhysicalBuilderMatNode\\\\\\\",J4.filterFragmentShader)}isPhysical(){return!0}static filterFragmentShader(t){return t=t.replace(\\\\\\\"#include \\\\\\\",function(t){const e=t.split(\\\\\\\"\\\\n\\\\\\\");let n=0;for(let t of e)t.includes(\\\\\\\"float transmissionFactor = transmission;\\\\\\\")&&(t=\\\\\\\"float transmissionFactor = transmission * POLY_transmission;\\\\\\\",e[n]=t),t.includes(\\\\\\\"float thicknessFactor = thickness;\\\\\\\")&&(t=\\\\\\\"float thicknessFactor = thickness * POLY_thickness;\\\\\\\",e[n]=t),n++;return e.join(\\\\\\\"\\\\n\\\\\\\")}(k))}}const Z4=new Map([[Mf.VERTEX,\\\\\\\"// INSERT DEFINES\\\\\\\"]]),K4=new Map([[Mf.VERTEX,\\\\\\\"// INSERT BODY\\\\\\\"]]);const Q4=new Map([[Mf.VERTEX,\\\\\\\"// INSERT DEFINES\\\\\\\"]]),t5=new Map([[Mf.VERTEX,\\\\\\\"// INSERT BODY\\\\\\\"]]);const e5=new Map([[Mf.VERTEX,[\\\\\\\"#include \\\\\\\",\\\\\\\"gl_PointSize = size;\\\\\\\"]],[Mf.FRAGMENT,[]]]),n5=new Map;n5.set(I4.DISTANCE,class extends B4{templateShader(){const t=H.distanceRGBA,e=I.clone(t.uniforms);return e.size={value:1},e.scale={value:1},{vertexShader:\\\\\\\"uniform float size;\\\\nuniform float scale;\\\\n#define DISTANCE\\\\nvarying vec3 vWorldPosition;\\\\n#include \\\\n#include \\\\nvarying float vViewZDepth;\\\\n\\\\n// INSERT DEFINES\\\\n\\\\n\\\\n\\\\nvoid main() {\\\\n\\\\n\\\\t// INSERT BODY\\\\n\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\t#ifdef USE_SIZEATTENUATION\\\\n\\\\t\\\\tbool isPerspective = ( projectionMatrix[ 2 ][ 3 ] == - 1.0 );\\\\n\\\\t\\\\tif ( isPerspective ) gl_PointSize *= ( scale / - mvPosition.z );\\\\n\\\\t#endif\\\\n\\\\tvWorldPosition = worldPosition.xyz;\\\\n}\\\\n\\\\n// #define DISTANCE\\\\n// varying vec3 vWorldPosition;\\\\n// #include \\\\n// #include \\\\n// #include \\\\n// #include \\\\n// #include \\\\n// #include \\\\n// void main() {\\\\n// \\\\t#include \\\\n// \\\\t#include \\\\n// \\\\t#ifdef USE_DISPLACEMENTMAP\\\\n// \\\\t\\\\t#include \\\\n// \\\\t\\\\t#include \\\\n// \\\\t\\\\t#include \\\\n// \\\\t#endif\\\\n// \\\\t#include \\\\n// \\\\t#include \\\\n// \\\\t#include \\\\n// \\\\t#include \\\\n// \\\\t#include \\\\n// \\\\t#include \\\\n// \\\\t#include \\\\n// \\\\tvWorldPosition = worldPosition.xyz;\\\\n// }\\\\n\\\\n\\\\n\\\\\\\",fragmentShader:t.fragmentShader,uniforms:e}}insert_define_after(t){return Z4.get(t)}insert_body_after(t){return K4.get(t)}createMaterial(){const t=this.templateShader();return new F({defines:{USE_SIZEATTENUATION:1,DEPTH_PACKING:[w.Hb,w.j][0]},uniforms:I.clone(t.uniforms),vertexShader:t.vertexShader,fragmentShader:t.fragmentShader})}}),n5.set(I4.DEPTH_DOF,class extends B4{templateShader(){return{vertexShader:\\\\\\\"uniform float size;\\\\nuniform float scale;\\\\n#include \\\\n\\\\nvarying float vViewZDepth;\\\\n\\\\n// INSERT DEFINES\\\\n\\\\n\\\\n\\\\nvoid main() {\\\\n\\\\n\\\\t// INSERT BODY\\\\n\\\\n\\\\n\\\\t#include \\\\n\\\\n\\\\tvViewZDepth = - mvPosition.z;\\\\n\\\\t#ifdef USE_SIZEATTENUATION\\\\n\\\\t\\\\tbool isPerspective = ( projectionMatrix[ 2 ][ 3 ] == - 1.0 );\\\\n\\\\t\\\\tif ( isPerspective ) gl_PointSize *= ( scale / - mvPosition.z );\\\\n\\\\t#endif\\\\n\\\\n}\\\\n\\\\n\\\\\\\",fragmentShader:U4,uniforms:{size:{value:1},scale:{value:1},mNear:{value:0},mFar:{value:10}}}}insert_define_after(t){return Q4.get(t)}insert_body_after(t){return t5.get(t)}createMaterial(){const t=this.templateShader();return new F({depthTest:!0,defines:{USE_SIZEATTENUATION:1},uniforms:I.clone(t.uniforms),vertexShader:t.vertexShader,fragmentShader:t.fragmentShader})}});class i5 extends B4{custom_assembler_class_by_custom_name(){return n5}templateShader(){const t=H.points;return{vertexShader:t.vertexShader,fragmentShader:t.fragmentShader,uniforms:t.uniforms}}createMaterial(){const t=this.templateShader(),e=new F({transparent:!0,fog:!0,defines:{USE_SIZEATTENUATION:1},uniforms:I.clone(t.uniforms),vertexShader:t.vertexShader,fragmentShader:t.fragmentShader});return this._addCustomMaterials(e),e}add_output_inputs(t){const e=R4.output_input_connection_points();e.push(new qo(\\\\\\\"gl_PointSize\\\\\\\",Uo.FLOAT)),t.io.inputs.setNamedInputConnectionPoints(e)}create_globals_node_output_connections(){return R4.create_globals_node_output_connections().concat([new qo(F4.GL_POINTCOORD,Uo.VEC2)])}create_shader_configs(){return[new b4(Mf.VERTEX,[\\\\\\\"position\\\\\\\",\\\\\\\"normal\\\\\\\",\\\\\\\"uv\\\\\\\",\\\\\\\"gl_PointSize\\\\\\\"],[]),new b4(Mf.FRAGMENT,[\\\\\\\"color\\\\\\\",\\\\\\\"alpha\\\\\\\"],[Mf.VERTEX])]}create_variable_configs(){return R4.create_variable_configs().concat([new w4(\\\\\\\"gl_PointSize\\\\\\\",{default:\\\\\\\"1.0\\\\\\\",prefix:\\\\\\\"gl_PointSize = \\\\\\\",suffix:\\\\\\\" * size * 10.0\\\\\\\"})])}lines_to_remove(t){return e5.get(t)}}const s5=new Map([[Mf.VERTEX,\\\\\\\"// INSERT DEFINES\\\\\\\"]]),r5=new Map([[Mf.VERTEX,\\\\\\\"// INSERT BODY\\\\\\\"]]);const o5=new Map([]);o5.set(I4.DEPTH_DOF,class extends B4{templateShader(){return{vertexShader:\\\\\\\"uniform float scale;\\\\nattribute float lineDistance;\\\\nvarying float vLineDistance;\\\\n#include \\\\n\\\\nvarying float vViewZDepth;\\\\n\\\\n// INSERT DEFINES\\\\n\\\\n\\\\n\\\\nvoid main() {\\\\n\\\\n\\\\t// INSERT BODY\\\\n\\\\n\\\\n\\\\tvLineDistance = scale * lineDistance;\\\\n\\\\tgl_Position = projectionMatrix * mvPosition;\\\\n\\\\n\\\\tvViewZDepth = - mvPosition.z;\\\\n\\\\n\\\\n}\\\\n\\\\n\\\\n\\\\n\\\\\\\",fragmentShader:U4,uniforms:{scale:{value:1},mNear:{value:0},mFar:{value:10}}}}insert_define_after(t){return s5.get(t)}insert_body_after(t){return r5.get(t)}createMaterial(){const t=this.templateShader();return new F({depthTest:!0,linewidth:100,uniforms:I.clone(t.uniforms),vertexShader:t.vertexShader,fragmentShader:t.fragmentShader})}});const a5=new Map([[Mf.VERTEX,[\\\\\\\"#include \\\\\\\",\\\\\\\"#include \\\\\\\"]],[Mf.FRAGMENT,[]]]);class l5 extends B4{templateShader(){const t=H.dashed;return{vertexShader:t.vertexShader,fragmentShader:t.fragmentShader,uniforms:t.uniforms}}createMaterial(){const t=this.templateShader(),e=new F({depthTest:!0,alphaTest:.5,linewidth:1,uniforms:I.clone(t.uniforms),vertexShader:t.vertexShader,fragmentShader:t.fragmentShader});return this._addCustomMaterials(e),e}custom_assembler_class_by_custom_name(){return o5}create_shader_configs(){return[new b4(Mf.VERTEX,[\\\\\\\"position\\\\\\\",\\\\\\\"uv\\\\\\\"],[]),new b4(Mf.FRAGMENT,[\\\\\\\"color\\\\\\\",\\\\\\\"alpha\\\\\\\"],[Mf.VERTEX])]}static output_input_connection_points(){return[new qo(\\\\\\\"position\\\\\\\",Uo.VEC3),new qo(\\\\\\\"color\\\\\\\",Uo.VEC3),new qo(\\\\\\\"alpha\\\\\\\",Uo.FLOAT),new qo(\\\\\\\"uv\\\\\\\",Uo.VEC2)]}add_output_inputs(t){t.io.inputs.setNamedInputConnectionPoints(l5.output_input_connection_points())}static create_globals_node_output_connections(){return[new qo(\\\\\\\"position\\\\\\\",Uo.VEC3),new qo(\\\\\\\"color\\\\\\\",Uo.VEC3),new qo(\\\\\\\"uv\\\\\\\",Uo.VEC2),new qo(\\\\\\\"gl_FragCoord\\\\\\\",Uo.VEC4),new qo(\\\\\\\"resolution\\\\\\\",Uo.VEC2),new qo(\\\\\\\"time\\\\\\\",Uo.FLOAT)]}create_globals_node_output_connections(){return l5.create_globals_node_output_connections()}create_variable_configs(){return[new w4(\\\\\\\"position\\\\\\\",{default:\\\\\\\"vec3( position )\\\\\\\",prefix:\\\\\\\"vec3 transformed = \\\\\\\",suffix:\\\\\\\";vec4 mvPosition = vec4( transformed, 1.0 ); gl_Position = projectionMatrix * modelViewMatrix * mvPosition;\\\\\\\"}),new w4(\\\\\\\"color\\\\\\\",{prefix:\\\\\\\"diffuseColor.xyz = \\\\\\\"}),new w4(\\\\\\\"alpha\\\\\\\",{prefix:\\\\\\\"diffuseColor.w = \\\\\\\"}),new w4(\\\\\\\"uv\\\\\\\",{prefix:\\\\\\\"vUv = \\\\\\\",if:Pf.IF_RULE.uv})]}lines_to_remove(t){return a5.get(t)}}class c5 extends R4{templateShader(){}_template_shader_for_shader_name(t){return\\\\\\\"#include \\\\n\\\\n// INSERT DEFINE\\\\n\\\\nvoid main() {\\\\n\\\\n\\\\tvec2 particleUV = (gl_FragCoord.xy / resolution.xy);\\\\n\\\\n\\\\t// INSERT BODY\\\\n\\\\n}\\\\\\\"}compile(){this.setup_shader_names_and_variables(),this.update_shaders()}root_nodes_by_shader_name(t){var e,n;const i=[];for(let s of this._root_nodes)switch(s.type()){case OF.type():i.push(s);break;case wf.type():{const r=s.attribute_name,o=null===(e=this._texture_allocations_controller)||void 0===e?void 0:e.variable(r);if(o&&o.allocation()){(null===(n=o.allocation())||void 0===n?void 0:n.shaderName())==t&&i.push(s)}break}}return i}leaf_nodes_by_shader_name(t){var e,n;const i=[];for(let s of this._leaf_nodes)switch(s.type()){case II.type():i.push(s);break;case wf.type():{const r=s.attribute_name,o=null===(e=this._texture_allocations_controller)||void 0===e?void 0:e.variable(r);if(o&&o.allocation()){(null===(n=o.allocation())||void 0===n?void 0:n.shaderName())==t&&i.push(s)}break}}return i}setup_shader_names_and_variables(){var t;const e=new N4(this.currentGlParentNode(),this.shaderNames(),((t,e)=>this.input_names_for_shader_name(t,e)));this._leaf_nodes=e.leaves_from_nodes(this._root_nodes),this._texture_allocations_controller=new c1,this._texture_allocations_controller.allocateConnectionsFromRootNodes(this._root_nodes,this._leaf_nodes),this.globals_handler&&(null===(t=this.globals_handler)||void 0===t||t.set_texture_allocations_controller(this._texture_allocations_controller)),this._reset_shader_configs()}update_shaders(){this._shaders_by_name.clear(),this._lines.clear();for(let t of this.shaderNames()){const e=this._template_shader_for_shader_name(t);this._lines.set(t,e.split(\\\\\\\"\\\\n\\\\\\\"))}this._root_nodes.length>0&&(this._resetCodeBuilder(),this.build_code_from_nodes(this._root_nodes),this._build_lines());for(let t of this.shaderNames()){const e=this._lines.get(t);e&&this._shaders_by_name.set(t,e.join(\\\\\\\"\\\\n\\\\\\\"))}}add_output_inputs(t){t.io.inputs.setNamedInputConnectionPoints([new qo(\\\\\\\"position\\\\\\\",Uo.VEC3),new qo(\\\\\\\"velocity\\\\\\\",Uo.VEC3)])}add_globals_outputs(t){t.io.outputs.setNamedOutputConnectionPoints([new qo(\\\\\\\"position\\\\\\\",Uo.VEC3),new qo(\\\\\\\"velocity\\\\\\\",Uo.VEC3),new qo(\\\\\\\"time\\\\\\\",Uo.FLOAT)])}allow_attribute_exports(){return!0}textureAllocationsController(){return this._texture_allocations_controller=this._texture_allocations_controller||new c1}create_shader_configs(){var t;return(null===(t=this._texture_allocations_controller)||void 0===t?void 0:t.createShaderConfigs())||[]}create_variable_configs(){return[]}shaderNames(){return this.textureAllocationsController().shaderNames()||[]}input_names_for_shader_name(t,e){return this.textureAllocationsController().inputNamesForShaderName(t,e)||[]}insert_define_after(t){return\\\\\\\"// INSERT DEFINE\\\\\\\"}insert_body_after(t){return\\\\\\\"// INSERT BODY\\\\\\\"}lines_to_remove(t){return[\\\\\\\"// INSERT DEFINE\\\\\\\",\\\\\\\"// INSERT BODY\\\\\\\"]}add_export_body_line(t,e,n,i,s){var r;if(n){const n=t.variableForInput(e),o=mf.vector3(n);if(o){const e=this.textureAllocationsController().variable(i),n=s.current_shader_name;if(e&&(null===(r=e.allocation())||void 0===r?void 0:r.shaderName())==n){const i=`gl_FragColor.${e.component()} = ${o}`;s.addBodyLines(t,[i],n)}}}}set_node_lines_output(t,e){const n=e.current_shader_name,i=this.textureAllocationsController().inputNamesForShaderName(t,n);if(i)for(let n of i){const i=t.io.inputs.named_input(n);if(i){const s=n;this.add_export_body_line(t,n,i,s,e)}}}set_node_lines_attribute(t,e){var n,i;if(t.isImporting()){const s=t.gl_type(),r=t.attribute_name,o=null===(n=this.globals_handler)||void 0===n?void 0:n.read_attribute(t,s,r,e),a=t.glVarName(t.output_name),l=`${s} ${a} = ${o}`;e.addBodyLines(t,[l]);const c=this.textureAllocationsController().variable(r),h=e.current_shader_name;if(c&&(null===(i=c.allocation())||void 0===i?void 0:i.shaderName())==h){const n=this.textureAllocationsController().variable(r);if(n){const i=`gl_FragColor.${n.component()} = ${a}`;e.addBodyLines(t,[i])}}}if(t.isExporting()){const n=t.connected_input_node();if(n){const i=t.attribute_name;this.add_export_body_line(t,t.input_name,n,i,e)}}}set_node_lines_globals(t,e){for(let n of t.io.outputs.used_output_names())switch(n){case\\\\\\\"time\\\\\\\":this._handle_globals_time(t,n,e);break;default:this._handle_globals_default(t,n,e)}}_handle_globals_time(t,e,n){const i=new Nf(t,Uo.FLOAT,e);n.addDefinitions(t,[i]);const s=`float ${t.glVarName(e)} = ${e}`;n.addBodyLines(t,[s]),this.setUniformsTimeDependent()}_handle_globals_default(t,e,n){var i;const s=t.io.outputs.namedOutputConnectionPointsByName(e);if(s){const r=s.type(),o=null===(i=this.globals_handler)||void 0===i?void 0:i.read_attribute(t,r,e,n);if(o){const i=`${r} ${t.glVarName(e)} = ${o}`;n.addBodyLines(t,[i])}}}}class h5 extends R4{templateShader(){return{fragmentShader:\\\\\\\"#include \\\\n\\\\nuniform vec2 resolution;\\\\n\\\\n// INSERT DEFINE\\\\n\\\\nvoid main() {\\\\n\\\\n\\\\tvec4 diffuseColor = vec4(0.0,0.0,0.0,1.0);\\\\n\\\\n\\\\n\\\\t// INSERT BODY\\\\n\\\\n\\\\tgl_FragColor = vec4( diffuseColor );\\\\n}\\\\\\\",vertexShader:void 0,uniforms:void 0}}fragment_shader(){return this._shaders_by_name.get(Mf.FRAGMENT)}uniforms(){return this._uniforms}update_fragment_shader(){this._lines=new Map,this._shaders_by_name=new Map;for(let t of this.shaderNames())if(t==Mf.FRAGMENT){const e=this.templateShader().fragmentShader;this._lines.set(t,e.split(\\\\\\\"\\\\n\\\\\\\"))}this._root_nodes.length>0&&(this.build_code_from_nodes(this._root_nodes),this._build_lines()),this._uniforms=this._uniforms||{},this.addUniforms(this._uniforms);for(let t of this.shaderNames()){const e=this._lines.get(t);e&&this._shaders_by_name.set(t,e.join(\\\\\\\"\\\\n\\\\\\\"))}rg.handleDependencies(this.currentGlParentNode(),this.uniformsTimeDependent(),this._uniforms)}add_output_inputs(t){t.io.inputs.setNamedInputConnectionPoints([new qo(\\\\\\\"color\\\\\\\",Uo.VEC3),new qo(\\\\\\\"alpha\\\\\\\",Uo.FLOAT)])}add_globals_outputs(t){t.io.outputs.setNamedOutputConnectionPoints([new qo(\\\\\\\"gl_FragCoord\\\\\\\",Uo.VEC2),new qo(\\\\\\\"time\\\\\\\",Uo.FLOAT)])}create_shader_configs(){return[new b4(Mf.FRAGMENT,[\\\\\\\"color\\\\\\\",\\\\\\\"alpha\\\\\\\"],[])]}create_variable_configs(){return[new w4(\\\\\\\"color\\\\\\\",{prefix:\\\\\\\"diffuseColor.xyz = \\\\\\\"}),new w4(\\\\\\\"alpha\\\\\\\",{prefix:\\\\\\\"diffuseColor.a = \\\\\\\",default:\\\\\\\"1.0\\\\\\\"})]}insert_define_after(t){return\\\\\\\"// INSERT DEFINE\\\\\\\"}insert_body_after(t){return\\\\\\\"// INSERT BODY\\\\\\\"}lines_to_remove(t){return[\\\\\\\"// INSERT DEFINE\\\\\\\",\\\\\\\"// INSERT BODY\\\\\\\"]}handle_gl_FragCoord(t,e,n){\\\\\\\"fragment\\\\\\\"==e&&t.push(`vec2 ${n} = vec2(gl_FragCoord.x / resolution.x, gl_FragCoord.y / resolution.y)`)}set_node_lines_output(t,e){const n=this.input_names_for_shader_name(t,e.current_shader_name);if(n)for(let i of n){if(t.io.inputs.named_input(i)){const n=t.variableForInput(i);let s;\\\\\\\"color\\\\\\\"==i&&(s=`diffuseColor.xyz = ${mf.any(n)}`),\\\\\\\"alpha\\\\\\\"==i&&(s=`diffuseColor.a = ${mf.any(n)}`),s&&e.addBodyLines(t,[s])}}}set_node_lines_globals(t,e){const n=e.current_shader_name;if(!this.shader_config(n))return;const i=[],s=[];for(let e of t.io.outputs.used_output_names()){const r=t.glVarName(e);switch(e){case\\\\\\\"time\\\\\\\":s.push(new Nf(t,Uo.FLOAT,e)),i.push(`float ${r} = ${e}`),this.setUniformsTimeDependent();break;case\\\\\\\"gl_FragCoord\\\\\\\":this.handle_gl_FragCoord(i,n,r)}}e.addDefinitions(t,s,n),e.addBodyLines(t,i)}}const u5=new Map([]);class d5 extends B4{custom_assembler_class_by_custom_name(){return u5}}const p5=new Map([[Mf.VERTEX,\\\\\\\"// start builder body code\\\\\\\"],[Mf.FRAGMENT,\\\\\\\"// start builder body code\\\\\\\"]]),_5=new Map([[Mf.FRAGMENT,[]]]);class m5 extends d5{templateShader(){return{vertexShader:Uk,fragmentShader:Gk,uniforms:I.clone(Vk)}}createMaterial(){const t=this.templateShader(),e=new F({vertexShader:t.vertexShader,fragmentShader:t.fragmentShader,side:w.H,transparent:!0,depthTest:!0,uniforms:I.clone(t.uniforms)});return yr.add_user_data_render_hook(e,jk.render_hook.bind(jk)),this._addCustomMaterials(e),e}add_output_inputs(t){t.io.inputs.setNamedInputConnectionPoints([new qo(\\\\\\\"density\\\\\\\",Uo.FLOAT,1)])}static create_globals_node_output_connections(){return[new qo(\\\\\\\"position\\\\\\\",Uo.VEC3),new qo(\\\\\\\"pos_normalized\\\\\\\",Uo.VEC3),new qo(\\\\\\\"time\\\\\\\",Uo.FLOAT)]}create_globals_node_output_connections(){return m5.create_globals_node_output_connections()}insert_body_after(t){return p5.get(t)}lines_to_remove(t){return _5.get(t)}create_shader_configs(){return[new b4(Mf.VERTEX,[],[]),new b4(Mf.FRAGMENT,[\\\\\\\"density\\\\\\\"],[Mf.VERTEX])]}static create_variable_configs(){return[new w4(\\\\\\\"position\\\\\\\",{}),new w4(\\\\\\\"density\\\\\\\",{prefix:\\\\\\\"density *= \\\\\\\"})]}create_variable_configs(){return m5.create_variable_configs()}set_node_lines_globals(t,e){const n=[],i=e.current_shader_name,s=this.shader_config(i);if(!s)return;const r=s.dependencies(),o=new Map,a=new Map;let l,c;for(let s of t.io.outputs.used_output_names()){const u=t.glVarName(s),d=e.current_shader_name;switch(s){case\\\\\\\"time\\\\\\\":l=new Nf(t,Uo.FLOAT,s),d&&h.pushOnArrayAtEntry(o,d,l),c=`float ${u} = ${s}`;for(let t of r)h.pushOnArrayAtEntry(o,t,l),h.pushOnArrayAtEntry(a,t,c);n.push(c),this.setUniformsTimeDependent();break;case\\\\\\\"position\\\\\\\":i==Mf.FRAGMENT&&n.push(`vec3 ${u} = position_for_step`);break;case\\\\\\\"pos_normalized\\\\\\\":i==Mf.FRAGMENT&&n.push(`vec3 ${u} = (position_for_step - u_BoundingBoxMax) / (u_BoundingBoxMax - u_BoundingBoxMin)`)}}o.forEach(((n,i)=>{e.addDefinitions(t,n,i)})),a.forEach(((n,i)=>{e.addBodyLines(t,n,i)})),e.addBodyLines(t,n)}}class f5{static async run(){this._started||(this._started=!0,class{static async run(t){(class{static run(t){t.registerNode(k_,ec),t.registerNode(G_,sc),t.registerNode(H_,ec),t.registerNode(W_,ec),t.registerNode(tm,ec),t.registerNode(nm,tc),t.registerNode(sm,ec),t.registerNode(om,sc),t.registerNode(lm,ic),t.registerNode(mm,ic),t.registerNode(gm,ec),t.registerNode(ym,tc),t.registerNode(Sm,ic),t.registerNode(Lm,nc),t.registerNode(Om,nc),t.registerNode(Pm,nc),t.registerNode(Rm,nc),t.registerNode(sf,nc),t.registerNode(rf,nc)}}).run(t),class{static run(t){t.registerNode(rg,rc),t.registerNode(Og,oc),t.registerNode(Rg,oc),t.registerNode(kg,oc),t.registerNode(Hg,oc),t.registerNode(sv,oc),t.registerNode(lv,oc),t.registerNode(pv,ac),t.registerNode(mv,ac),t.registerNode(vv,ac),t.registerNode(Tv,ac),t.registerNode(Mv,ac),t.registerNode(Cv,rc),t.registerNode(Ov,oc),t.registerNode(Iv,rc),t.registerNode(Bv,lc),t.registerNode(kv,lc),t.registerNode(zv,lc),t.registerNode(Uv,lc),t.registerNode(Gv,lc),t.registerNode(Vv,lc)}}.run(t),class{static run(t){t.registerNode(qv,dc),t.registerNode($v,uc),t.registerNode(Zv,uc),t.registerNode(ty,uc),t.registerNode(hy,cc),t.registerNode(Ty,cc),t.registerNode(wy,cc),t.registerNode(My,uc),t.registerNode(Tl,hc),t.registerNode(ox,cc),t.registerNode(hl,hc),t.registerNode(hx,uc),t.registerNode(dx,uc),t.registerNode(IL,cc),t.registerNode(Ja,hc),t.registerNode(zL,dc),t.registerNode(VL,uc),t.registerNode(ZL,hc),t.registerNode(el,hc),t.registerNode(xO,uc),t.registerNode(rl,dc),t.registerNode(AO,dc),t.registerNode(FO,dc),t.registerNode(BO,uc),t.registerNode(UO,uc),t.registerNode(Ml,hc),t.registerNode(VO,uc),t.registerNode(ml,hc),t.registerNode(WO,pc),t.registerNode(qO,pc),t.registerNode(XO,pc),t.registerNode(YO,pc),t.registerNode($O,pc),t.registerNode(JO,pc)}}.run(t),class{static run(t){t.registerNode(FP,xc),t.registerNode(LR,bc),t.registerNode(DP,Tc),t.registerNode(mR,xc),t.registerNode(FR,Tc),t.registerNode(bR,yc),t.registerNode(BP,Tc),t.registerNode(zP,Tc),t.registerNode(wf,gc,{except:[`${ts.COP}/builder`]}),t.registerNode(aP,mc),t.registerNode(kP,xc),t.registerNode(uR,xc),t.registerNode(kR,_c),t.registerNode(qR,yc),t.registerNode(XR,xc),t.registerNode(JR,gc),t.registerNode(UP,Tc),t.registerNode(QR,fc),t.registerNode(tI,xc),t.registerNode(GP,mc),t.registerNode(iI,fc),t.registerNode(nR,fc),t.registerNode(fR,xc),t.registerNode(iR,fc),t.registerNode(uI,xc),t.registerNode(VP,xc),t.registerNode(HP,xc),t.registerNode(dR,fc),t.registerNode(_I,xc),t.registerNode(fI,xc),t.registerNode(vI,xc),t.registerNode(xI,xc),t.registerNode(QO,mc),t.registerNode(cP,mc),t.registerNode(uP,mc),t.registerNode(pP,mc),t.registerNode(jP,xc),t.registerNode(TI,_c),t.registerNode(PI,yc),t.registerNode(WP,xc),t.registerNode(II,gc),t.registerNode(DI,_c),t.registerNode(zI,_c),t.registerNode(GI,yc),t.registerNode(HI,Ac),t.registerNode(rP,mc),t.registerNode(nP,mc),t.registerNode(qP,xc),t.registerNode(JI,fc),t.registerNode(ZI,fc),t.registerNode(QI,_c),t.registerNode(XP,xc),t.registerNode(YP,xc),t.registerNode(sR,xc),t.registerNode(eF,xc),t.registerNode(rR,xc),t.registerNode(oR,xc),t.registerNode(oF,xc),t.registerNode(iF,xc),t.registerNode(vR,xc),t.registerNode(cF,xc),t.registerNode(hF,xc),t.registerNode(NF,Ac),t.registerNode(CF,fc),t.registerNode($P,xc),t.registerNode(wR,yc),t.registerNode(OF,gc),t.registerNode(IF,gc),t.registerNode(aR,xc),t.registerNode(kF,wc),t.registerNode(HF,wc),t.registerNode(jF,wc),t.registerNode(WF,wc),t.registerNode(YF,gc),t.registerNode(ZF,gc),t.registerNode(JP,mc),t.registerNode(lR,fc),t.registerNode(FF,fc),t.registerNode(QF,_c),t.registerNode(lD,fc),t.registerNode(hD,xc),t.registerNode(ZP,xc),t.registerNode(KP,Tc),t.registerNode(pR,xc),t.registerNode(dD,fc),t.registerNode(QP,xc),t.registerNode(zF,vc),t.registerNode(cR,fc),t.registerNode(CI,yc),t.registerNode(_D,yc,RD),t.registerNode(MI,yc,RD),t.registerNode(gR,xc),t.registerNode(fD,yc),t.registerNode(tR,Tc),t.registerNode(vD,_c),t.registerNode(wD,gc),t.registerNode(MD,yc),t.registerNode(Ff,gc),t.registerNode(CD,gc),t.registerNode(xP,mc),t.registerNode(MP,mc),t.registerNode(bP,mc),t.registerNode(AP,mc),t.registerNode(EP,mc),t.registerNode(wP,mc),t.registerNode(TP,mc),t.registerNode(LD,fc),t.registerNode(PD,fc)}}.run(t),class{static run(t){t.registerNode(BD,Mc),t.registerNode(kD,Mc),t.registerNode(GD,Mc),t.registerNode(YD,Mc)}}.run(t),class{static run(t){t.registerNode(iB,Sc),t.registerNode(mB,Sc),t.registerNode(qB,Cc),t.registerNode(KB,Ec),t.registerNode(sz,Cc),t.registerNode(hz,Ec),t.registerNode(Mz,Cc),t.registerNode(Nz,Cc),t.registerNode(Fz,Cc),t.registerNode(kz,Ec),t.registerNode(Jz,Cc),t.registerNode(tk,Ec),t.registerNode(sk,Cc),t.registerNode(lk,Ec),t.registerNode(xk,Cc),t.registerNode(Ek,Cc),t.registerNode(Lk,Lc),t.registerNode(Rk,Ec),t.registerNode(Dk,Ec),t.registerNode(kk,Cc),t.registerNode(Xk,Oc),t.registerNode(Jk,Oc),t.registerNode(Qk,Nc),t.registerNode(tU,Nc),t.registerNode(eU,Nc),t.registerNode(nU,Nc),t.registerNode(iU,Nc),t.registerNode(sU,Nc)}}.run(t),class{static run(t){t.registerNode(dU,Dc),t.registerNode(IU,Dc),t.registerNode(WU,Dc),t.registerNode(KU,Dc),t.registerNode(sG,Dc),t.registerNode(dG,Dc),t.registerNode(wG,Rc),t.registerNode(SG,zc),t.registerNode(BG,Pc),t.registerNode(VG,Fc),t.registerNode(WG,zc),t.registerNode(JG,zc),t.registerNode(TV,Pc),t.registerNode(zV,Rc),t.registerNode(VV,zc),t.registerNode(WV,Pc),t.registerNode(nj,Ic),t.registerNode(oj,Ic),t.registerNode(cj,Ic),t.registerNode(pj,Bc),t.registerNode(_j,Bc),t.registerNode(mj,Bc),t.registerNode(fj,Bc),t.registerNode(gj,Bc),t.registerNode(vj,Bc)}}.run(t),class{static run(t){t.registerNode(Ej,eh),t.registerNode(Lj,eh),t.registerNode(Rj,th),t.registerNode(Dj,th),t.registerNode(kj,nh),t.registerNode(Gj,nh),t.registerNode(jj,nh),t.registerNode(qj,nh),t.registerNode(eW,eh),t.registerNode(Kj,eh),t.registerNode(rW,eh),t.registerNode(lW,nh),t.registerNode(uW,th),t.registerNode(pW,Qc),t.registerNode(mW,nh),t.registerNode(bW,nh),t.registerNode(TW,nh),t.registerNode(MW,nh),t.registerNode(CW,eh),t.registerNode(OW,eh),t.registerNode(RW,nh),t.registerNode(DW,eh),t.registerNode(kW,th),t.registerNode(GW,nh),t.registerNode(WW,Qc),t.registerNode($W,eh),t.registerNode(ZW,Qc),t.registerNode(tq,eh),t.registerNode(iq,ih),t.registerNode(sq,ih),t.registerNode(rq,ih),t.registerNode(oq,ih),t.registerNode(aq,ih),t.registerNode(lq,ih)}}.run(t),class{static run(t){t.registerNode(mq,kc),t.registerNode(SH,Gc),t.registerNode(fq,Uc),t.registerNode(uq,Uc),t.registerNode(gq,Uc),t.registerNode(vq,Uc),t.registerNode(yq,Uc),t.registerNode(xq,Uc)}}.run(t),class{static run(t){t.registerOperation(bq),t.registerOperation(Fq),t.registerOperation(Hq),t.registerOperation(Xq),t.registerOperation(Zq),t.registerOperation(uX),t.registerOperation(rX),t.registerOperation(fX),t.registerOperation($X),t.registerOperation(QX),t.registerOperation(E$),t.registerOperation(L$),t.registerOperation(HJ),t.registerOperation(XJ),t.registerOperation(KJ),t.registerOperation(uZ),t.registerOperation(UZ),t.registerOperation(rK),t.registerOperation(fQ),t.registerOperation(LQ),t.registerOperation(UQ),t.registerOperation(jQ),t.registerOperation(JQ),t.registerOperation(n0),t.registerOperation(f0),t.registerOperation(N0),t.registerOperation(d0),t.registerOperation(V0),t.registerOperation(X0),t.registerOperation(p1),t.registerOperation(x1),t.registerOperation(A1),t.registerOperation(O1),t.registerOperation(B1),t.registerOperation(Y1),t.registerOperation(i2),t.registerOperation(_2),t.registerOperation(v2),t.registerOperation(w2),t.registerOperation(L2),t.registerOperation(k2),t.registerOperation(J2),t.registerOperation(c9),t.registerOperation(x9),t.registerOperation(G9),t.registerOperation(W9),t.registerOperation(J9),t.registerOperation(t3),t.registerOperation(o3),t.registerOperation(M3),t.registerOperation(P3),t.registerOperation(D3),t.registerNode(Aq,qc),t.registerNode(Eq,Hc),t.registerNode(Iq,Hc),t.registerNode(zq,jc),t.registerNode(qq,jc),t.registerNode(Jq,jc),t.registerNode(eX,jc),t.registerNode(iX,jc),t.registerNode(lX,jc),t.registerNode(_X,jc),t.registerNode(xX,jc),t.registerNode(wX,jc),t.registerNode(AX,jc),t.registerNode(LX,jc),t.registerNode(PX,$c),t.registerNode(IX,$c),t.registerNode(KX,$c),t.registerNode(nY,Zc),t.registerNode(N$,Vc),t.registerNode(R$,Vc),t.registerNode(BJ,Yc),t.registerNode(VJ,Zc),t.registerNode(qJ,$c),t.registerNode($J,Zc),t.registerNode(eZ,Zc),t.registerNode(lZ,Zc),t.registerNode(_Z,$c),t.registerNode(xZ,$c),t.registerNode(TZ,Zc),t.registerNode(DZ,$c),t.registerNode(HZ,Zc),t.registerNode(YZ,qc),t.registerNode(nK,qc),t.registerNode(lK,Yc),t.registerNode(hK,Yc),t.registerNode(MK,$c),t.registerNode(SK,$c),t.registerNode(cQ,Vc),t.registerNode(uQ,$c),t.registerNode(yQ,qc),t.registerNode(bQ,qc),t.registerNode(TQ,$c),t.registerNode(SQ,Zc),t.registerNode(DQ,$c),t.registerNode(IQ,Yc),t.registerNode(HQ,Zc),t.registerNode(XQ,Kc),t.registerNode(QQ,$c),t.registerNode(e0,Kc),t.registerNode(r0,$c),t.registerNode(a0,$c),t.registerNode(c0,Zc),t.registerNode(u0,Vc),t.registerNode(m0,Kc),t.registerNode(x0,Yc),t.registerNode(P0,Zc),t.registerNode(k0,Yc),t.registerNode(G0,$c),t.registerNode(j0,Yc),t.registerNode(q0,qc),t.registerNode(J0,$c),t.registerNode(K0,Vc,{userAllowed:!1}),t.registerNode(d1,Wc),t.registerNode(f1,$c),t.registerNode(T1,Zc),t.registerNode(S1,$c),t.registerNode(U1,$c),t.registerNode(L1,$c),t.registerNode(I1,Xc),t.registerNode(yV,Vc),t.registerNode(q1,$c),t.registerNode(Z1,$c),t.registerNode(o2,Kc),t.registerNode(p2,$c),t.registerNode(g2,jc),t.registerNode(b2,qc),t.registerNode(M2,$c),t.registerNode(D2,$c),t.registerNode(I2,$c),t.registerNode(j2,Vc),t.registerNode(q2,Vc),t.registerNode(V2,$c),t.registerNode(Q2,Zc),t.registerNode(e9,$c),t.registerNode(d9,$c),t.registerNode(_9,Yc),t.registerNode(f9,Yc),t.registerNode(pV,Yc),t.registerNode(T9,qc),t.registerNode(E9,Yc),t.registerNode(N9,Zc),t.registerNode(U9,Zc),t.registerNode(j9,$c),t.registerNode(Y9,$c),t.registerNode(Q9,Zc),t.registerNode(i3,Zc),t.registerNode(c3,$c),t.registerNode(u3,$c),t.registerNode(f3,$c),t.registerNode(x3,$c),t.registerNode(T3,Zc),t.registerNode(S3,$c),t.registerNode(O3,$c),t.registerNode(F3,$c),t.registerNode(z3,$c),t.registerNode(G3,Jc),t.registerNode(V3,Jc),t.registerNode(H3,Jc),t.registerNode(j3,Jc),t.registerNode(W3,Jc),t.registerNode(q3,Jc)}}.run(t)}}.run(li),class{static run(t){t.registerCamera(nj),t.registerCamera(oj)}}.run(li),class{static run(t){t.expressionsRegister.register(Y3,\\\\\\\"arg\\\\\\\"),t.expressionsRegister.register($3,\\\\\\\"argc\\\\\\\"),t.expressionsRegister.register(K3,\\\\\\\"bbox\\\\\\\"),t.expressionsRegister.register(Q3,\\\\\\\"centroid\\\\\\\"),t.expressionsRegister.register(t4,\\\\\\\"ch\\\\\\\"),t.expressionsRegister.register(e4,\\\\\\\"copy\\\\\\\"),t.expressionsRegister.register(n4,\\\\\\\"copRes\\\\\\\"),t.expressionsRegister.register(i4,\\\\\\\"isDeviceMobile\\\\\\\"),t.expressionsRegister.register(s4,\\\\\\\"isDeviceTouch\\\\\\\"),t.expressionsRegister.register(r4,\\\\\\\"js\\\\\\\"),t.expressionsRegister.register(o4,\\\\\\\"object\\\\\\\"),t.expressionsRegister.register(a4,\\\\\\\"objectsCount\\\\\\\"),t.expressionsRegister.register(l4,\\\\\\\"opdigits\\\\\\\"),t.expressionsRegister.register(c4,\\\\\\\"opname\\\\\\\"),t.expressionsRegister.register(h4,\\\\\\\"padzero\\\\\\\"),t.expressionsRegister.register(u4,\\\\\\\"point\\\\\\\"),t.expressionsRegister.register(d4,\\\\\\\"pointsCount\\\\\\\"),t.expressionsRegister.register(p4,\\\\\\\"strCharsCount\\\\\\\"),t.expressionsRegister.register(_4,\\\\\\\"strConcat\\\\\\\"),t.expressionsRegister.register(m4,\\\\\\\"strIndex\\\\\\\"),t.expressionsRegister.register(f4,\\\\\\\"strSub\\\\\\\"),t.expressionsRegister.register(g4,\\\\\\\"windowSize\\\\\\\")}}.run(li),class{static run(t){t.assemblersRegister.register(jn.GL_MESH_BASIC,y4,W4),t.assemblersRegister.register(jn.GL_MESH_LAMBERT,y4,q4),t.assemblersRegister.register(jn.GL_MESH_PHONG,y4,X4),t.assemblersRegister.register(jn.GL_MESH_STANDARD,y4,$4),t.assemblersRegister.register(jn.GL_MESH_PHYSICAL,y4,J4),t.assemblersRegister.register(jn.GL_PARTICLES,y4,c5),t.assemblersRegister.register(jn.GL_POINTS,y4,i5),t.assemblersRegister.register(jn.GL_LINE,y4,l5),t.assemblersRegister.register(jn.GL_TEXTURE,y4,h5),t.assemblersRegister.register(jn.GL_VOLUME,y4,m5)}}.run(li))}}f5._started=!1,f5.run()}]);void 0===POLY&&console.error(\\\\\\\"esm-webpack-plugin: nothing exported!\\\\\\\");const _POLY$PolyScene=POLY.PolyScene,_POLY$Poly=POLY.Poly,_POLY$SceneJsonImporter=POLY.SceneJsonImporter,_POLY$SceneDataManifestImporter=POLY.SceneDataManifestImporter,_POLY$mountScene=POLY.mountScene;export{_POLY$PolyScene as PolyScene,_POLY$Poly as Poly,_POLY$SceneJsonImporter as SceneJsonImporter,_POLY$SceneDataManifestImporter as SceneDataManifestImporter,_POLY$mountScene as mountScene};\\n//# sourceMappingURL=all.js.map\"","status":200,"headers":{"content-type":"application/javascript","content-length":"2831720"}},"type":2,"external":true,"timestamp":1723920076473},{"data":{"url":"blob:https://ipfs.arkivo.art/d79b34d4-43cb-4c8f-9cce-38586d2b57de","host":"","path":"https://ipfs.arkivo.art/d79b34d4-43cb-4c8f-9cce-38586d2b57de","type":"http","query":"","method":"GET","headers":{"origin":"https://ipfs.arkivo.art","referer":"","user-agent":"Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) HeadlessChrome/119.0.6045.9 Safari/537.36"},"fragment":"","postData":null,"protocol":"blob:"},"type":1,"external":false,"timestamp":1723920076474},{"data":{"url":"blob:https://ipfs.arkivo.art/7d38cb90-62ae-41eb-9cf9-63411d155abd","host":"","path":"https://ipfs.arkivo.art/7d38cb90-62ae-41eb-9cf9-63411d155abd","type":"http","query":"","method":"GET","headers":{"referer":"","user-agent":"Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) HeadlessChrome/119.0.6045.9 Safari/537.36"},"fragment":"","postData":null,"protocol":"blob:"},"type":1,"external":false,"timestamp":1723920077414},{"data":{"url":"blob:https://ipfs.arkivo.art/c715dc52-c1c7-45c7-bd92-45ce5c7c3049","host":"","path":"https://ipfs.arkivo.art/c715dc52-c1c7-45c7-bd92-45ce5c7c3049","type":"http","query":"","method":"GET","headers":{"origin":"https://ipfs.arkivo.art","referer":"","user-agent":"Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) HeadlessChrome/119.0.6045.9 Safari/537.36"},"fragment":"","postData":null,"protocol":"blob:"},"type":1,"external":false,"timestamp":1723920077414},{"data":{"url":"blob:https://ipfs.arkivo.art/d79b34d4-43cb-4c8f-9cce-38586d2b57de","body":"\"var __create = Object.create;\\nvar __defProp = Object.defineProperty;\\nvar __getProtoOf = Object.getPrototypeOf;\\nvar __hasOwnProp = Object.prototype.hasOwnProperty;\\nvar __getOwnPropNames = Object.getOwnPropertyNames;\\nvar __getOwnPropDesc = Object.getOwnPropertyDescriptor;\\nvar __markAsModule = (target) => __defProp(target, \\\\\\\"__esModule\\\\\\\", {value: true});\\nvar __commonJS = (callback, module) => () => {\\n if (!module) {\\n module = {exports: {}};\\n callback(module.exports, module);\\n }\\n return module.exports;\\n};\\nvar __exportStar = (target, module, desc) => {\\n __markAsModule(target);\\n if (module && typeof module === \\\\\\\"object\\\\\\\" || typeof module === \\\\\\\"function\\\\\\\") {\\n for (let key of __getOwnPropNames(module))\\n if (!__hasOwnProp.call(target, key) && key !== \\\\\\\"default\\\\\\\")\\n __defProp(target, key, {get: () => module[key], enumerable: !(desc = __getOwnPropDesc(module, key)) || desc.enumerable});\\n }\\n return target;\\n};\\nvar __toModule = (module) => {\\n if (module && module.__esModule)\\n return module;\\n return __exportStar(__defProp(module != null ? __create(__getProtoOf(module)) : {}, \\\\\\\"default\\\\\\\", {value: module, enumerable: true}), module);\\n};\\n\\n// ../../../node_modules/lodash/_listCacheClear.js\\nvar require_listCacheClear = __commonJS((exports, module) => {\\n function listCacheClear() {\\n this.__data__ = [];\\n this.size = 0;\\n }\\n module.exports = listCacheClear;\\n});\\n\\n// ../../../node_modules/lodash/eq.js\\nvar require_eq = __commonJS((exports, module) => {\\n function eq(value, other) {\\n return value === other || value !== value && other !== other;\\n }\\n module.exports = eq;\\n});\\n\\n// ../../../node_modules/lodash/_assocIndexOf.js\\nvar require_assocIndexOf = __commonJS((exports, module) => {\\n var eq = require_eq();\\n function assocIndexOf(array, key) {\\n var length = array.length;\\n while (length--) {\\n if (eq(array[length][0], key)) {\\n return length;\\n }\\n }\\n return -1;\\n }\\n module.exports = assocIndexOf;\\n});\\n\\n// ../../../node_modules/lodash/_listCacheDelete.js\\nvar require_listCacheDelete = __commonJS((exports, module) => {\\n var assocIndexOf = require_assocIndexOf();\\n var arrayProto = Array.prototype;\\n var splice = arrayProto.splice;\\n function listCacheDelete(key) {\\n var data = this.__data__, index = assocIndexOf(data, key);\\n if (index < 0) {\\n return false;\\n }\\n var lastIndex = data.length - 1;\\n if (index == lastIndex) {\\n data.pop();\\n } else {\\n splice.call(data, index, 1);\\n }\\n --this.size;\\n return true;\\n }\\n module.exports = listCacheDelete;\\n});\\n\\n// ../../../node_modules/lodash/_listCacheGet.js\\nvar require_listCacheGet = __commonJS((exports, module) => {\\n var assocIndexOf = require_assocIndexOf();\\n function listCacheGet(key) {\\n var data = this.__data__, index = assocIndexOf(data, key);\\n return index < 0 ? void 0 : data[index][1];\\n }\\n module.exports = listCacheGet;\\n});\\n\\n// ../../../node_modules/lodash/_listCacheHas.js\\nvar require_listCacheHas = __commonJS((exports, module) => {\\n var assocIndexOf = require_assocIndexOf();\\n function listCacheHas(key) {\\n return assocIndexOf(this.__data__, key) > -1;\\n }\\n module.exports = listCacheHas;\\n});\\n\\n// ../../../node_modules/lodash/_listCacheSet.js\\nvar require_listCacheSet = __commonJS((exports, module) => {\\n var assocIndexOf = require_assocIndexOf();\\n function listCacheSet(key, value) {\\n var data = this.__data__, index = assocIndexOf(data, key);\\n if (index < 0) {\\n ++this.size;\\n data.push([key, value]);\\n } else {\\n data[index][1] = value;\\n }\\n return this;\\n }\\n module.exports = listCacheSet;\\n});\\n\\n// ../../../node_modules/lodash/_ListCache.js\\nvar require_ListCache = __commonJS((exports, module) => {\\n var listCacheClear = require_listCacheClear();\\n var listCacheDelete = require_listCacheDelete();\\n var listCacheGet = require_listCacheGet();\\n var listCacheHas = require_listCacheHas();\\n var listCacheSet = require_listCacheSet();\\n function ListCache(entries) {\\n var index = -1, length = entries == null ? 0 : entries.length;\\n this.clear();\\n while (++index < length) {\\n var entry = entries[index];\\n this.set(entry[0], entry[1]);\\n }\\n }\\n ListCache.prototype.clear = listCacheClear;\\n ListCache.prototype[\\\\\\\"delete\\\\\\\"] = listCacheDelete;\\n ListCache.prototype.get = listCacheGet;\\n ListCache.prototype.has = listCacheHas;\\n ListCache.prototype.set = listCacheSet;\\n module.exports = ListCache;\\n});\\n\\n// ../../../node_modules/lodash/_stackClear.js\\nvar require_stackClear = __commonJS((exports, module) => {\\n var ListCache = require_ListCache();\\n function stackClear() {\\n this.__data__ = new ListCache();\\n this.size = 0;\\n }\\n module.exports = stackClear;\\n});\\n\\n// ../../../node_modules/lodash/_stackDelete.js\\nvar require_stackDelete = __commonJS((exports, module) => {\\n function stackDelete(key) {\\n var data = this.__data__, result = data[\\\\\\\"delete\\\\\\\"](key);\\n this.size = data.size;\\n return result;\\n }\\n module.exports = stackDelete;\\n});\\n\\n// ../../../node_modules/lodash/_stackGet.js\\nvar require_stackGet = __commonJS((exports, module) => {\\n function stackGet(key) {\\n return this.__data__.get(key);\\n }\\n module.exports = stackGet;\\n});\\n\\n// ../../../node_modules/lodash/_stackHas.js\\nvar require_stackHas = __commonJS((exports, module) => {\\n function stackHas(key) {\\n return this.__data__.has(key);\\n }\\n module.exports = stackHas;\\n});\\n\\n// ../../../node_modules/lodash/_freeGlobal.js\\nvar require_freeGlobal = __commonJS((exports, module) => {\\n var freeGlobal = typeof global == \\\\\\\"object\\\\\\\" && global && global.Object === Object && global;\\n module.exports = freeGlobal;\\n});\\n\\n// ../../../node_modules/lodash/_root.js\\nvar require_root = __commonJS((exports, module) => {\\n var freeGlobal = require_freeGlobal();\\n var freeSelf = typeof self == \\\\\\\"object\\\\\\\" && self && self.Object === Object && self;\\n var root = freeGlobal || freeSelf || Function(\\\\\\\"return this\\\\\\\")();\\n module.exports = root;\\n});\\n\\n// ../../../node_modules/lodash/_Symbol.js\\nvar require_Symbol = __commonJS((exports, module) => {\\n var root = require_root();\\n var Symbol2 = root.Symbol;\\n module.exports = Symbol2;\\n});\\n\\n// ../../../node_modules/lodash/_getRawTag.js\\nvar require_getRawTag = __commonJS((exports, module) => {\\n var Symbol2 = require_Symbol();\\n var objectProto = Object.prototype;\\n var hasOwnProperty = objectProto.hasOwnProperty;\\n var nativeObjectToString = objectProto.toString;\\n var symToStringTag = Symbol2 ? Symbol2.toStringTag : void 0;\\n function getRawTag(value) {\\n var isOwn = hasOwnProperty.call(value, symToStringTag), tag = value[symToStringTag];\\n try {\\n value[symToStringTag] = void 0;\\n var unmasked = true;\\n } catch (e) {\\n }\\n var result = nativeObjectToString.call(value);\\n if (unmasked) {\\n if (isOwn) {\\n value[symToStringTag] = tag;\\n } else {\\n delete value[symToStringTag];\\n }\\n }\\n return result;\\n }\\n module.exports = getRawTag;\\n});\\n\\n// ../../../node_modules/lodash/_objectToString.js\\nvar require_objectToString = __commonJS((exports, module) => {\\n var objectProto = Object.prototype;\\n var nativeObjectToString = objectProto.toString;\\n function objectToString(value) {\\n return nativeObjectToString.call(value);\\n }\\n module.exports = objectToString;\\n});\\n\\n// ../../../node_modules/lodash/_baseGetTag.js\\nvar require_baseGetTag = __commonJS((exports, module) => {\\n var Symbol2 = require_Symbol();\\n var getRawTag = require_getRawTag();\\n var objectToString = require_objectToString();\\n var nullTag = \\\\\\\"[object Null]\\\\\\\";\\n var undefinedTag = \\\\\\\"[object Undefined]\\\\\\\";\\n var symToStringTag = Symbol2 ? Symbol2.toStringTag : void 0;\\n function baseGetTag(value) {\\n if (value == null) {\\n return value === void 0 ? undefinedTag : nullTag;\\n }\\n return symToStringTag && symToStringTag in Object(value) ? getRawTag(value) : objectToString(value);\\n }\\n module.exports = baseGetTag;\\n});\\n\\n// ../../../node_modules/lodash/isObject.js\\nvar require_isObject = __commonJS((exports, module) => {\\n function isObject(value) {\\n var type = typeof value;\\n return value != null && (type == \\\\\\\"object\\\\\\\" || type == \\\\\\\"function\\\\\\\");\\n }\\n module.exports = isObject;\\n});\\n\\n// ../../../node_modules/lodash/isFunction.js\\nvar require_isFunction = __commonJS((exports, module) => {\\n var baseGetTag = require_baseGetTag();\\n var isObject = require_isObject();\\n var asyncTag = \\\\\\\"[object AsyncFunction]\\\\\\\";\\n var funcTag = \\\\\\\"[object Function]\\\\\\\";\\n var genTag = \\\\\\\"[object GeneratorFunction]\\\\\\\";\\n var proxyTag = \\\\\\\"[object Proxy]\\\\\\\";\\n function isFunction(value) {\\n if (!isObject(value)) {\\n return false;\\n }\\n var tag = baseGetTag(value);\\n return tag == funcTag || tag == genTag || tag == asyncTag || tag == proxyTag;\\n }\\n module.exports = isFunction;\\n});\\n\\n// ../../../node_modules/lodash/_coreJsData.js\\nvar require_coreJsData = __commonJS((exports, module) => {\\n var root = require_root();\\n var coreJsData = root[\\\\\\\"__core-js_shared__\\\\\\\"];\\n module.exports = coreJsData;\\n});\\n\\n// ../../../node_modules/lodash/_isMasked.js\\nvar require_isMasked = __commonJS((exports, module) => {\\n var coreJsData = require_coreJsData();\\n var maskSrcKey = function() {\\n var uid = /[^.]+$/.exec(coreJsData && coreJsData.keys && coreJsData.keys.IE_PROTO || \\\\\\\"\\\\\\\");\\n return uid ? \\\\\\\"Symbol(src)_1.\\\\\\\" + uid : \\\\\\\"\\\\\\\";\\n }();\\n function isMasked(func) {\\n return !!maskSrcKey && maskSrcKey in func;\\n }\\n module.exports = isMasked;\\n});\\n\\n// ../../../node_modules/lodash/_toSource.js\\nvar require_toSource = __commonJS((exports, module) => {\\n var funcProto = Function.prototype;\\n var funcToString = funcProto.toString;\\n function toSource(func) {\\n if (func != null) {\\n try {\\n return funcToString.call(func);\\n } catch (e) {\\n }\\n try {\\n return func + \\\\\\\"\\\\\\\";\\n } catch (e) {\\n }\\n }\\n return \\\\\\\"\\\\\\\";\\n }\\n module.exports = toSource;\\n});\\n\\n// ../../../node_modules/lodash/_baseIsNative.js\\nvar require_baseIsNative = __commonJS((exports, module) => {\\n var isFunction = require_isFunction();\\n var isMasked = require_isMasked();\\n var isObject = require_isObject();\\n var toSource = require_toSource();\\n var reRegExpChar = /[\\\\\\\\^$.*+?()[\\\\]{}|]/g;\\n var reIsHostCtor = /^\\\\[object .+?Constructor\\\\]$/;\\n var funcProto = Function.prototype;\\n var objectProto = Object.prototype;\\n var funcToString = funcProto.toString;\\n var hasOwnProperty = objectProto.hasOwnProperty;\\n var reIsNative = RegExp(\\\\\\\"^\\\\\\\" + funcToString.call(hasOwnProperty).replace(reRegExpChar, \\\\\\\"\\\\\\\\$&\\\\\\\").replace(/hasOwnProperty|(function).*?(?=\\\\\\\\\\\\()| for .+?(?=\\\\\\\\\\\\])/g, \\\\\\\"$1.*?\\\\\\\") + \\\\\\\"$\\\\\\\");\\n function baseIsNative(value) {\\n if (!isObject(value) || isMasked(value)) {\\n return false;\\n }\\n var pattern = isFunction(value) ? reIsNative : reIsHostCtor;\\n return pattern.test(toSource(value));\\n }\\n module.exports = baseIsNative;\\n});\\n\\n// ../../../node_modules/lodash/_getValue.js\\nvar require_getValue = __commonJS((exports, module) => {\\n function getValue(object, key) {\\n return object == null ? void 0 : object[key];\\n }\\n module.exports = getValue;\\n});\\n\\n// ../../../node_modules/lodash/_getNative.js\\nvar require_getNative = __commonJS((exports, module) => {\\n var baseIsNative = require_baseIsNative();\\n var getValue = require_getValue();\\n function getNative(object, key) {\\n var value = getValue(object, key);\\n return baseIsNative(value) ? value : void 0;\\n }\\n module.exports = getNative;\\n});\\n\\n// ../../../node_modules/lodash/_Map.js\\nvar require_Map = __commonJS((exports, module) => {\\n var getNative = require_getNative();\\n var root = require_root();\\n var Map2 = getNative(root, \\\\\\\"Map\\\\\\\");\\n module.exports = Map2;\\n});\\n\\n// ../../../node_modules/lodash/_nativeCreate.js\\nvar require_nativeCreate = __commonJS((exports, module) => {\\n var getNative = require_getNative();\\n var nativeCreate = getNative(Object, \\\\\\\"create\\\\\\\");\\n module.exports = nativeCreate;\\n});\\n\\n// ../../../node_modules/lodash/_hashClear.js\\nvar require_hashClear = __commonJS((exports, module) => {\\n var nativeCreate = require_nativeCreate();\\n function hashClear() {\\n this.__data__ = nativeCreate ? nativeCreate(null) : {};\\n this.size = 0;\\n }\\n module.exports = hashClear;\\n});\\n\\n// ../../../node_modules/lodash/_hashDelete.js\\nvar require_hashDelete = __commonJS((exports, module) => {\\n function hashDelete(key) {\\n var result = this.has(key) && delete this.__data__[key];\\n this.size -= result ? 1 : 0;\\n return result;\\n }\\n module.exports = hashDelete;\\n});\\n\\n// ../../../node_modules/lodash/_hashGet.js\\nvar require_hashGet = __commonJS((exports, module) => {\\n var nativeCreate = require_nativeCreate();\\n var HASH_UNDEFINED = \\\\\\\"__lodash_hash_undefined__\\\\\\\";\\n var objectProto = Object.prototype;\\n var hasOwnProperty = objectProto.hasOwnProperty;\\n function hashGet(key) {\\n var data = this.__data__;\\n if (nativeCreate) {\\n var result = data[key];\\n return result === HASH_UNDEFINED ? void 0 : result;\\n }\\n return hasOwnProperty.call(data, key) ? data[key] : void 0;\\n }\\n module.exports = hashGet;\\n});\\n\\n// ../../../node_modules/lodash/_hashHas.js\\nvar require_hashHas = __commonJS((exports, module) => {\\n var nativeCreate = require_nativeCreate();\\n var objectProto = Object.prototype;\\n var hasOwnProperty = objectProto.hasOwnProperty;\\n function hashHas(key) {\\n var data = this.__data__;\\n return nativeCreate ? data[key] !== void 0 : hasOwnProperty.call(data, key);\\n }\\n module.exports = hashHas;\\n});\\n\\n// ../../../node_modules/lodash/_hashSet.js\\nvar require_hashSet = __commonJS((exports, module) => {\\n var nativeCreate = require_nativeCreate();\\n var HASH_UNDEFINED = \\\\\\\"__lodash_hash_undefined__\\\\\\\";\\n function hashSet(key, value) {\\n var data = this.__data__;\\n this.size += this.has(key) ? 0 : 1;\\n data[key] = nativeCreate && value === void 0 ? HASH_UNDEFINED : value;\\n return this;\\n }\\n module.exports = hashSet;\\n});\\n\\n// ../../../node_modules/lodash/_Hash.js\\nvar require_Hash = __commonJS((exports, module) => {\\n var hashClear = require_hashClear();\\n var hashDelete = require_hashDelete();\\n var hashGet = require_hashGet();\\n var hashHas = require_hashHas();\\n var hashSet = require_hashSet();\\n function Hash(entries) {\\n var index = -1, length = entries == null ? 0 : entries.length;\\n this.clear();\\n while (++index < length) {\\n var entry = entries[index];\\n this.set(entry[0], entry[1]);\\n }\\n }\\n Hash.prototype.clear = hashClear;\\n Hash.prototype[\\\\\\\"delete\\\\\\\"] = hashDelete;\\n Hash.prototype.get = hashGet;\\n Hash.prototype.has = hashHas;\\n Hash.prototype.set = hashSet;\\n module.exports = Hash;\\n});\\n\\n// ../../../node_modules/lodash/_mapCacheClear.js\\nvar require_mapCacheClear = __commonJS((exports, module) => {\\n var Hash = require_Hash();\\n var ListCache = require_ListCache();\\n var Map2 = require_Map();\\n function mapCacheClear() {\\n this.size = 0;\\n this.__data__ = {\\n hash: new Hash(),\\n map: new (Map2 || ListCache)(),\\n string: new Hash()\\n };\\n }\\n module.exports = mapCacheClear;\\n});\\n\\n// ../../../node_modules/lodash/_isKeyable.js\\nvar require_isKeyable = __commonJS((exports, module) => {\\n function isKeyable(value) {\\n var type = typeof value;\\n return type == \\\\\\\"string\\\\\\\" || type == \\\\\\\"number\\\\\\\" || type == \\\\\\\"symbol\\\\\\\" || type == \\\\\\\"boolean\\\\\\\" ? value !== \\\\\\\"__proto__\\\\\\\" : value === null;\\n }\\n module.exports = isKeyable;\\n});\\n\\n// ../../../node_modules/lodash/_getMapData.js\\nvar require_getMapData = __commonJS((exports, module) => {\\n var isKeyable = require_isKeyable();\\n function getMapData(map, key) {\\n var data = map.__data__;\\n return isKeyable(key) ? data[typeof key == \\\\\\\"string\\\\\\\" ? \\\\\\\"string\\\\\\\" : \\\\\\\"hash\\\\\\\"] : data.map;\\n }\\n module.exports = getMapData;\\n});\\n\\n// ../../../node_modules/lodash/_mapCacheDelete.js\\nvar require_mapCacheDelete = __commonJS((exports, module) => {\\n var getMapData = require_getMapData();\\n function mapCacheDelete(key) {\\n var result = getMapData(this, key)[\\\\\\\"delete\\\\\\\"](key);\\n this.size -= result ? 1 : 0;\\n return result;\\n }\\n module.exports = mapCacheDelete;\\n});\\n\\n// ../../../node_modules/lodash/_mapCacheGet.js\\nvar require_mapCacheGet = __commonJS((exports, module) => {\\n var getMapData = require_getMapData();\\n function mapCacheGet(key) {\\n return getMapData(this, key).get(key);\\n }\\n module.exports = mapCacheGet;\\n});\\n\\n// ../../../node_modules/lodash/_mapCacheHas.js\\nvar require_mapCacheHas = __commonJS((exports, module) => {\\n var getMapData = require_getMapData();\\n function mapCacheHas(key) {\\n return getMapData(this, key).has(key);\\n }\\n module.exports = mapCacheHas;\\n});\\n\\n// ../../../node_modules/lodash/_mapCacheSet.js\\nvar require_mapCacheSet = __commonJS((exports, module) => {\\n var getMapData = require_getMapData();\\n function mapCacheSet(key, value) {\\n var data = getMapData(this, key), size = data.size;\\n data.set(key, value);\\n this.size += data.size == size ? 0 : 1;\\n return this;\\n }\\n module.exports = mapCacheSet;\\n});\\n\\n// ../../../node_modules/lodash/_MapCache.js\\nvar require_MapCache = __commonJS((exports, module) => {\\n var mapCacheClear = require_mapCacheClear();\\n var mapCacheDelete = require_mapCacheDelete();\\n var mapCacheGet = require_mapCacheGet();\\n var mapCacheHas = require_mapCacheHas();\\n var mapCacheSet = require_mapCacheSet();\\n function MapCache(entries) {\\n var index = -1, length = entries == null ? 0 : entries.length;\\n this.clear();\\n while (++index < length) {\\n var entry = entries[index];\\n this.set(entry[0], entry[1]);\\n }\\n }\\n MapCache.prototype.clear = mapCacheClear;\\n MapCache.prototype[\\\\\\\"delete\\\\\\\"] = mapCacheDelete;\\n MapCache.prototype.get = mapCacheGet;\\n MapCache.prototype.has = mapCacheHas;\\n MapCache.prototype.set = mapCacheSet;\\n module.exports = MapCache;\\n});\\n\\n// ../../../node_modules/lodash/_stackSet.js\\nvar require_stackSet = __commonJS((exports, module) => {\\n var ListCache = require_ListCache();\\n var Map2 = require_Map();\\n var MapCache = require_MapCache();\\n var LARGE_ARRAY_SIZE = 200;\\n function stackSet(key, value) {\\n var data = this.__data__;\\n if (data instanceof ListCache) {\\n var pairs = data.__data__;\\n if (!Map2 || pairs.length < LARGE_ARRAY_SIZE - 1) {\\n pairs.push([key, value]);\\n this.size = ++data.size;\\n return this;\\n }\\n data = this.__data__ = new MapCache(pairs);\\n }\\n data.set(key, value);\\n this.size = data.size;\\n return this;\\n }\\n module.exports = stackSet;\\n});\\n\\n// ../../../node_modules/lodash/_Stack.js\\nvar require_Stack = __commonJS((exports, module) => {\\n var ListCache = require_ListCache();\\n var stackClear = require_stackClear();\\n var stackDelete = require_stackDelete();\\n var stackGet = require_stackGet();\\n var stackHas = require_stackHas();\\n var stackSet = require_stackSet();\\n function Stack(entries) {\\n var data = this.__data__ = new ListCache(entries);\\n this.size = data.size;\\n }\\n Stack.prototype.clear = stackClear;\\n Stack.prototype[\\\\\\\"delete\\\\\\\"] = stackDelete;\\n Stack.prototype.get = stackGet;\\n Stack.prototype.has = stackHas;\\n Stack.prototype.set = stackSet;\\n module.exports = Stack;\\n});\\n\\n// ../../../node_modules/lodash/_arrayEach.js\\nvar require_arrayEach = __commonJS((exports, module) => {\\n function arrayEach(array, iteratee) {\\n var index = -1, length = array == null ? 0 : array.length;\\n while (++index < length) {\\n if (iteratee(array[index], index, array) === false) {\\n break;\\n }\\n }\\n return array;\\n }\\n module.exports = arrayEach;\\n});\\n\\n// ../../../node_modules/lodash/_defineProperty.js\\nvar require_defineProperty = __commonJS((exports, module) => {\\n var getNative = require_getNative();\\n var defineProperty = function() {\\n try {\\n var func = getNative(Object, \\\\\\\"defineProperty\\\\\\\");\\n func({}, \\\\\\\"\\\\\\\", {});\\n return func;\\n } catch (e) {\\n }\\n }();\\n module.exports = defineProperty;\\n});\\n\\n// ../../../node_modules/lodash/_baseAssignValue.js\\nvar require_baseAssignValue = __commonJS((exports, module) => {\\n var defineProperty = require_defineProperty();\\n function baseAssignValue(object, key, value) {\\n if (key == \\\\\\\"__proto__\\\\\\\" && defineProperty) {\\n defineProperty(object, key, {\\n configurable: true,\\n enumerable: true,\\n value,\\n writable: true\\n });\\n } else {\\n object[key] = value;\\n }\\n }\\n module.exports = baseAssignValue;\\n});\\n\\n// ../../../node_modules/lodash/_assignValue.js\\nvar require_assignValue = __commonJS((exports, module) => {\\n var baseAssignValue = require_baseAssignValue();\\n var eq = require_eq();\\n var objectProto = Object.prototype;\\n var hasOwnProperty = objectProto.hasOwnProperty;\\n function assignValue(object, key, value) {\\n var objValue = object[key];\\n if (!(hasOwnProperty.call(object, key) && eq(objValue, value)) || value === void 0 && !(key in object)) {\\n baseAssignValue(object, key, value);\\n }\\n }\\n module.exports = assignValue;\\n});\\n\\n// ../../../node_modules/lodash/_copyObject.js\\nvar require_copyObject = __commonJS((exports, module) => {\\n var assignValue = require_assignValue();\\n var baseAssignValue = require_baseAssignValue();\\n function copyObject(source, props, object, customizer) {\\n var isNew = !object;\\n object || (object = {});\\n var index = -1, length = props.length;\\n while (++index < length) {\\n var key = props[index];\\n var newValue = customizer ? customizer(object[key], source[key], key, object, source) : void 0;\\n if (newValue === void 0) {\\n newValue = source[key];\\n }\\n if (isNew) {\\n baseAssignValue(object, key, newValue);\\n } else {\\n assignValue(object, key, newValue);\\n }\\n }\\n return object;\\n }\\n module.exports = copyObject;\\n});\\n\\n// ../../../node_modules/lodash/_baseTimes.js\\nvar require_baseTimes = __commonJS((exports, module) => {\\n function baseTimes(n, iteratee) {\\n var index = -1, result = Array(n);\\n while (++index < n) {\\n result[index] = iteratee(index);\\n }\\n return result;\\n }\\n module.exports = baseTimes;\\n});\\n\\n// ../../../node_modules/lodash/isObjectLike.js\\nvar require_isObjectLike = __commonJS((exports, module) => {\\n function isObjectLike(value) {\\n return value != null && typeof value == \\\\\\\"object\\\\\\\";\\n }\\n module.exports = isObjectLike;\\n});\\n\\n// ../../../node_modules/lodash/_baseIsArguments.js\\nvar require_baseIsArguments = __commonJS((exports, module) => {\\n var baseGetTag = require_baseGetTag();\\n var isObjectLike = require_isObjectLike();\\n var argsTag = \\\\\\\"[object Arguments]\\\\\\\";\\n function baseIsArguments(value) {\\n return isObjectLike(value) && baseGetTag(value) == argsTag;\\n }\\n module.exports = baseIsArguments;\\n});\\n\\n// ../../../node_modules/lodash/isArguments.js\\nvar require_isArguments = __commonJS((exports, module) => {\\n var baseIsArguments = require_baseIsArguments();\\n var isObjectLike = require_isObjectLike();\\n var objectProto = Object.prototype;\\n var hasOwnProperty = objectProto.hasOwnProperty;\\n var propertyIsEnumerable = objectProto.propertyIsEnumerable;\\n var isArguments = baseIsArguments(function() {\\n return arguments;\\n }()) ? baseIsArguments : function(value) {\\n return isObjectLike(value) && hasOwnProperty.call(value, \\\\\\\"callee\\\\\\\") && !propertyIsEnumerable.call(value, \\\\\\\"callee\\\\\\\");\\n };\\n module.exports = isArguments;\\n});\\n\\n// ../../../node_modules/lodash/isArray.js\\nvar require_isArray = __commonJS((exports, module) => {\\n var isArray = Array.isArray;\\n module.exports = isArray;\\n});\\n\\n// ../../../node_modules/lodash/stubFalse.js\\nvar require_stubFalse = __commonJS((exports, module) => {\\n function stubFalse() {\\n return false;\\n }\\n module.exports = stubFalse;\\n});\\n\\n// ../../../node_modules/lodash/isBuffer.js\\nvar require_isBuffer = __commonJS((exports, module) => {\\n var root = require_root();\\n var stubFalse = require_stubFalse();\\n var freeExports = typeof exports == \\\\\\\"object\\\\\\\" && exports && !exports.nodeType && exports;\\n var freeModule = freeExports && typeof module == \\\\\\\"object\\\\\\\" && module && !module.nodeType && module;\\n var moduleExports = freeModule && freeModule.exports === freeExports;\\n var Buffer2 = moduleExports ? root.Buffer : void 0;\\n var nativeIsBuffer = Buffer2 ? Buffer2.isBuffer : void 0;\\n var isBuffer = nativeIsBuffer || stubFalse;\\n module.exports = isBuffer;\\n});\\n\\n// ../../../node_modules/lodash/_isIndex.js\\nvar require_isIndex = __commonJS((exports, module) => {\\n var MAX_SAFE_INTEGER = 9007199254740991;\\n var reIsUint = /^(?:0|[1-9]\\\\d*)$/;\\n function isIndex(value, length) {\\n var type = typeof value;\\n length = length == null ? MAX_SAFE_INTEGER : length;\\n return !!length && (type == \\\\\\\"number\\\\\\\" || type != \\\\\\\"symbol\\\\\\\" && reIsUint.test(value)) && (value > -1 && value % 1 == 0 && value < length);\\n }\\n module.exports = isIndex;\\n});\\n\\n// ../../../node_modules/lodash/isLength.js\\nvar require_isLength = __commonJS((exports, module) => {\\n var MAX_SAFE_INTEGER = 9007199254740991;\\n function isLength(value) {\\n return typeof value == \\\\\\\"number\\\\\\\" && value > -1 && value % 1 == 0 && value <= MAX_SAFE_INTEGER;\\n }\\n module.exports = isLength;\\n});\\n\\n// ../../../node_modules/lodash/_baseIsTypedArray.js\\nvar require_baseIsTypedArray = __commonJS((exports, module) => {\\n var baseGetTag = require_baseGetTag();\\n var isLength = require_isLength();\\n var isObjectLike = require_isObjectLike();\\n var argsTag = \\\\\\\"[object Arguments]\\\\\\\";\\n var arrayTag = \\\\\\\"[object Array]\\\\\\\";\\n var boolTag = \\\\\\\"[object Boolean]\\\\\\\";\\n var dateTag = \\\\\\\"[object Date]\\\\\\\";\\n var errorTag = \\\\\\\"[object Error]\\\\\\\";\\n var funcTag = \\\\\\\"[object Function]\\\\\\\";\\n var mapTag = \\\\\\\"[object Map]\\\\\\\";\\n var numberTag = \\\\\\\"[object Number]\\\\\\\";\\n var objectTag = \\\\\\\"[object Object]\\\\\\\";\\n var regexpTag = \\\\\\\"[object RegExp]\\\\\\\";\\n var setTag = \\\\\\\"[object Set]\\\\\\\";\\n var stringTag = \\\\\\\"[object String]\\\\\\\";\\n var weakMapTag = \\\\\\\"[object WeakMap]\\\\\\\";\\n var arrayBufferTag = \\\\\\\"[object ArrayBuffer]\\\\\\\";\\n var dataViewTag = \\\\\\\"[object DataView]\\\\\\\";\\n var float32Tag = \\\\\\\"[object Float32Array]\\\\\\\";\\n var float64Tag = \\\\\\\"[object Float64Array]\\\\\\\";\\n var int8Tag = \\\\\\\"[object Int8Array]\\\\\\\";\\n var int16Tag = \\\\\\\"[object Int16Array]\\\\\\\";\\n var int32Tag = \\\\\\\"[object Int32Array]\\\\\\\";\\n var uint8Tag = \\\\\\\"[object Uint8Array]\\\\\\\";\\n var uint8ClampedTag = \\\\\\\"[object Uint8ClampedArray]\\\\\\\";\\n var uint16Tag = \\\\\\\"[object Uint16Array]\\\\\\\";\\n var uint32Tag = \\\\\\\"[object Uint32Array]\\\\\\\";\\n var typedArrayTags = {};\\n typedArrayTags[float32Tag] = typedArrayTags[float64Tag] = typedArrayTags[int8Tag] = typedArrayTags[int16Tag] = typedArrayTags[int32Tag] = typedArrayTags[uint8Tag] = typedArrayTags[uint8ClampedTag] = typedArrayTags[uint16Tag] = typedArrayTags[uint32Tag] = true;\\n typedArrayTags[argsTag] = typedArrayTags[arrayTag] = typedArrayTags[arrayBufferTag] = typedArrayTags[boolTag] = typedArrayTags[dataViewTag] = typedArrayTags[dateTag] = typedArrayTags[errorTag] = typedArrayTags[funcTag] = typedArrayTags[mapTag] = typedArrayTags[numberTag] = typedArrayTags[objectTag] = typedArrayTags[regexpTag] = typedArrayTags[setTag] = typedArrayTags[stringTag] = typedArrayTags[weakMapTag] = false;\\n function baseIsTypedArray(value) {\\n return isObjectLike(value) && isLength(value.length) && !!typedArrayTags[baseGetTag(value)];\\n }\\n module.exports = baseIsTypedArray;\\n});\\n\\n// ../../../node_modules/lodash/_baseUnary.js\\nvar require_baseUnary = __commonJS((exports, module) => {\\n function baseUnary(func) {\\n return function(value) {\\n return func(value);\\n };\\n }\\n module.exports = baseUnary;\\n});\\n\\n// ../../../node_modules/lodash/_nodeUtil.js\\nvar require_nodeUtil = __commonJS((exports, module) => {\\n var freeGlobal = require_freeGlobal();\\n var freeExports = typeof exports == \\\\\\\"object\\\\\\\" && exports && !exports.nodeType && exports;\\n var freeModule = freeExports && typeof module == \\\\\\\"object\\\\\\\" && module && !module.nodeType && module;\\n var moduleExports = freeModule && freeModule.exports === freeExports;\\n var freeProcess = moduleExports && freeGlobal.process;\\n var nodeUtil = function() {\\n try {\\n var types = freeModule && freeModule.require && freeModule.require(\\\\\\\"util\\\\\\\").types;\\n if (types) {\\n return types;\\n }\\n return freeProcess && freeProcess.binding && freeProcess.binding(\\\\\\\"util\\\\\\\");\\n } catch (e) {\\n }\\n }();\\n module.exports = nodeUtil;\\n});\\n\\n// ../../../node_modules/lodash/isTypedArray.js\\nvar require_isTypedArray = __commonJS((exports, module) => {\\n var baseIsTypedArray = require_baseIsTypedArray();\\n var baseUnary = require_baseUnary();\\n var nodeUtil = require_nodeUtil();\\n var nodeIsTypedArray = nodeUtil && nodeUtil.isTypedArray;\\n var isTypedArray = nodeIsTypedArray ? baseUnary(nodeIsTypedArray) : baseIsTypedArray;\\n module.exports = isTypedArray;\\n});\\n\\n// ../../../node_modules/lodash/_arrayLikeKeys.js\\nvar require_arrayLikeKeys = __commonJS((exports, module) => {\\n var baseTimes = require_baseTimes();\\n var isArguments = require_isArguments();\\n var isArray = require_isArray();\\n var isBuffer = require_isBuffer();\\n var isIndex = require_isIndex();\\n var isTypedArray = require_isTypedArray();\\n var objectProto = Object.prototype;\\n var hasOwnProperty = objectProto.hasOwnProperty;\\n function arrayLikeKeys(value, inherited) {\\n var isArr = isArray(value), isArg = !isArr && isArguments(value), isBuff = !isArr && !isArg && isBuffer(value), isType = !isArr && !isArg && !isBuff && isTypedArray(value), skipIndexes = isArr || isArg || isBuff || isType, result = skipIndexes ? baseTimes(value.length, String) : [], length = result.length;\\n for (var key in value) {\\n if ((inherited || hasOwnProperty.call(value, key)) && !(skipIndexes && (key == \\\\\\\"length\\\\\\\" || isBuff && (key == \\\\\\\"offset\\\\\\\" || key == \\\\\\\"parent\\\\\\\") || isType && (key == \\\\\\\"buffer\\\\\\\" || key == \\\\\\\"byteLength\\\\\\\" || key == \\\\\\\"byteOffset\\\\\\\") || isIndex(key, length)))) {\\n result.push(key);\\n }\\n }\\n return result;\\n }\\n module.exports = arrayLikeKeys;\\n});\\n\\n// ../../../node_modules/lodash/_isPrototype.js\\nvar require_isPrototype = __commonJS((exports, module) => {\\n var objectProto = Object.prototype;\\n function isPrototype(value) {\\n var Ctor = value && value.constructor, proto = typeof Ctor == \\\\\\\"function\\\\\\\" && Ctor.prototype || objectProto;\\n return value === proto;\\n }\\n module.exports = isPrototype;\\n});\\n\\n// ../../../node_modules/lodash/_overArg.js\\nvar require_overArg = __commonJS((exports, module) => {\\n function overArg(func, transform) {\\n return function(arg) {\\n return func(transform(arg));\\n };\\n }\\n module.exports = overArg;\\n});\\n\\n// ../../../node_modules/lodash/_nativeKeys.js\\nvar require_nativeKeys = __commonJS((exports, module) => {\\n var overArg = require_overArg();\\n var nativeKeys = overArg(Object.keys, Object);\\n module.exports = nativeKeys;\\n});\\n\\n// ../../../node_modules/lodash/_baseKeys.js\\nvar require_baseKeys = __commonJS((exports, module) => {\\n var isPrototype = require_isPrototype();\\n var nativeKeys = require_nativeKeys();\\n var objectProto = Object.prototype;\\n var hasOwnProperty = objectProto.hasOwnProperty;\\n function baseKeys(object) {\\n if (!isPrototype(object)) {\\n return nativeKeys(object);\\n }\\n var result = [];\\n for (var key in Object(object)) {\\n if (hasOwnProperty.call(object, key) && key != \\\\\\\"constructor\\\\\\\") {\\n result.push(key);\\n }\\n }\\n return result;\\n }\\n module.exports = baseKeys;\\n});\\n\\n// ../../../node_modules/lodash/isArrayLike.js\\nvar require_isArrayLike = __commonJS((exports, module) => {\\n var isFunction = require_isFunction();\\n var isLength = require_isLength();\\n function isArrayLike(value) {\\n return value != null && isLength(value.length) && !isFunction(value);\\n }\\n module.exports = isArrayLike;\\n});\\n\\n// ../../../node_modules/lodash/keys.js\\nvar require_keys = __commonJS((exports, module) => {\\n var arrayLikeKeys = require_arrayLikeKeys();\\n var baseKeys = require_baseKeys();\\n var isArrayLike = require_isArrayLike();\\n function keys(object) {\\n return isArrayLike(object) ? arrayLikeKeys(object) : baseKeys(object);\\n }\\n module.exports = keys;\\n});\\n\\n// ../../../node_modules/lodash/_baseAssign.js\\nvar require_baseAssign = __commonJS((exports, module) => {\\n var copyObject = require_copyObject();\\n var keys = require_keys();\\n function baseAssign(object, source) {\\n return object && copyObject(source, keys(source), object);\\n }\\n module.exports = baseAssign;\\n});\\n\\n// ../../../node_modules/lodash/_nativeKeysIn.js\\nvar require_nativeKeysIn = __commonJS((exports, module) => {\\n function nativeKeysIn(object) {\\n var result = [];\\n if (object != null) {\\n for (var key in Object(object)) {\\n result.push(key);\\n }\\n }\\n return result;\\n }\\n module.exports = nativeKeysIn;\\n});\\n\\n// ../../../node_modules/lodash/_baseKeysIn.js\\nvar require_baseKeysIn = __commonJS((exports, module) => {\\n var isObject = require_isObject();\\n var isPrototype = require_isPrototype();\\n var nativeKeysIn = require_nativeKeysIn();\\n var objectProto = Object.prototype;\\n var hasOwnProperty = objectProto.hasOwnProperty;\\n function baseKeysIn(object) {\\n if (!isObject(object)) {\\n return nativeKeysIn(object);\\n }\\n var isProto = isPrototype(object), result = [];\\n for (var key in object) {\\n if (!(key == \\\\\\\"constructor\\\\\\\" && (isProto || !hasOwnProperty.call(object, key)))) {\\n result.push(key);\\n }\\n }\\n return result;\\n }\\n module.exports = baseKeysIn;\\n});\\n\\n// ../../../node_modules/lodash/keysIn.js\\nvar require_keysIn = __commonJS((exports, module) => {\\n var arrayLikeKeys = require_arrayLikeKeys();\\n var baseKeysIn = require_baseKeysIn();\\n var isArrayLike = require_isArrayLike();\\n function keysIn(object) {\\n return isArrayLike(object) ? arrayLikeKeys(object, true) : baseKeysIn(object);\\n }\\n module.exports = keysIn;\\n});\\n\\n// ../../../node_modules/lodash/_baseAssignIn.js\\nvar require_baseAssignIn = __commonJS((exports, module) => {\\n var copyObject = require_copyObject();\\n var keysIn = require_keysIn();\\n function baseAssignIn(object, source) {\\n return object && copyObject(source, keysIn(source), object);\\n }\\n module.exports = baseAssignIn;\\n});\\n\\n// ../../../node_modules/lodash/_cloneBuffer.js\\nvar require_cloneBuffer = __commonJS((exports, module) => {\\n var root = require_root();\\n var freeExports = typeof exports == \\\\\\\"object\\\\\\\" && exports && !exports.nodeType && exports;\\n var freeModule = freeExports && typeof module == \\\\\\\"object\\\\\\\" && module && !module.nodeType && module;\\n var moduleExports = freeModule && freeModule.exports === freeExports;\\n var Buffer2 = moduleExports ? root.Buffer : void 0;\\n var allocUnsafe = Buffer2 ? Buffer2.allocUnsafe : void 0;\\n function cloneBuffer(buffer, isDeep) {\\n if (isDeep) {\\n return buffer.slice();\\n }\\n var length = buffer.length, result = allocUnsafe ? allocUnsafe(length) : new buffer.constructor(length);\\n buffer.copy(result);\\n return result;\\n }\\n module.exports = cloneBuffer;\\n});\\n\\n// ../../../node_modules/lodash/_copyArray.js\\nvar require_copyArray = __commonJS((exports, module) => {\\n function copyArray2(source, array) {\\n var index = -1, length = source.length;\\n array || (array = Array(length));\\n while (++index < length) {\\n array[index] = source[index];\\n }\\n return array;\\n }\\n module.exports = copyArray2;\\n});\\n\\n// ../../../node_modules/lodash/_arrayFilter.js\\nvar require_arrayFilter = __commonJS((exports, module) => {\\n function arrayFilter(array, predicate) {\\n var index = -1, length = array == null ? 0 : array.length, resIndex = 0, result = [];\\n while (++index < length) {\\n var value = array[index];\\n if (predicate(value, index, array)) {\\n result[resIndex++] = value;\\n }\\n }\\n return result;\\n }\\n module.exports = arrayFilter;\\n});\\n\\n// ../../../node_modules/lodash/stubArray.js\\nvar require_stubArray = __commonJS((exports, module) => {\\n function stubArray() {\\n return [];\\n }\\n module.exports = stubArray;\\n});\\n\\n// ../../../node_modules/lodash/_getSymbols.js\\nvar require_getSymbols = __commonJS((exports, module) => {\\n var arrayFilter = require_arrayFilter();\\n var stubArray = require_stubArray();\\n var objectProto = Object.prototype;\\n var propertyIsEnumerable = objectProto.propertyIsEnumerable;\\n var nativeGetSymbols = Object.getOwnPropertySymbols;\\n var getSymbols = !nativeGetSymbols ? stubArray : function(object) {\\n if (object == null) {\\n return [];\\n }\\n object = Object(object);\\n return arrayFilter(nativeGetSymbols(object), function(symbol) {\\n return propertyIsEnumerable.call(object, symbol);\\n });\\n };\\n module.exports = getSymbols;\\n});\\n\\n// ../../../node_modules/lodash/_copySymbols.js\\nvar require_copySymbols = __commonJS((exports, module) => {\\n var copyObject = require_copyObject();\\n var getSymbols = require_getSymbols();\\n function copySymbols(source, object) {\\n return copyObject(source, getSymbols(source), object);\\n }\\n module.exports = copySymbols;\\n});\\n\\n// ../../../node_modules/lodash/_arrayPush.js\\nvar require_arrayPush = __commonJS((exports, module) => {\\n function arrayPush(array, values) {\\n var index = -1, length = values.length, offset = array.length;\\n while (++index < length) {\\n array[offset + index] = values[index];\\n }\\n return array;\\n }\\n module.exports = arrayPush;\\n});\\n\\n// ../../../node_modules/lodash/_getPrototype.js\\nvar require_getPrototype = __commonJS((exports, module) => {\\n var overArg = require_overArg();\\n var getPrototype = overArg(Object.getPrototypeOf, Object);\\n module.exports = getPrototype;\\n});\\n\\n// ../../../node_modules/lodash/_getSymbolsIn.js\\nvar require_getSymbolsIn = __commonJS((exports, module) => {\\n var arrayPush = require_arrayPush();\\n var getPrototype = require_getPrototype();\\n var getSymbols = require_getSymbols();\\n var stubArray = require_stubArray();\\n var nativeGetSymbols = Object.getOwnPropertySymbols;\\n var getSymbolsIn = !nativeGetSymbols ? stubArray : function(object) {\\n var result = [];\\n while (object) {\\n arrayPush(result, getSymbols(object));\\n object = getPrototype(object);\\n }\\n return result;\\n };\\n module.exports = getSymbolsIn;\\n});\\n\\n// ../../../node_modules/lodash/_copySymbolsIn.js\\nvar require_copySymbolsIn = __commonJS((exports, module) => {\\n var copyObject = require_copyObject();\\n var getSymbolsIn = require_getSymbolsIn();\\n function copySymbolsIn(source, object) {\\n return copyObject(source, getSymbolsIn(source), object);\\n }\\n module.exports = copySymbolsIn;\\n});\\n\\n// ../../../node_modules/lodash/_baseGetAllKeys.js\\nvar require_baseGetAllKeys = __commonJS((exports, module) => {\\n var arrayPush = require_arrayPush();\\n var isArray = require_isArray();\\n function baseGetAllKeys(object, keysFunc, symbolsFunc) {\\n var result = keysFunc(object);\\n return isArray(object) ? result : arrayPush(result, symbolsFunc(object));\\n }\\n module.exports = baseGetAllKeys;\\n});\\n\\n// ../../../node_modules/lodash/_getAllKeys.js\\nvar require_getAllKeys = __commonJS((exports, module) => {\\n var baseGetAllKeys = require_baseGetAllKeys();\\n var getSymbols = require_getSymbols();\\n var keys = require_keys();\\n function getAllKeys(object) {\\n return baseGetAllKeys(object, keys, getSymbols);\\n }\\n module.exports = getAllKeys;\\n});\\n\\n// ../../../node_modules/lodash/_getAllKeysIn.js\\nvar require_getAllKeysIn = __commonJS((exports, module) => {\\n var baseGetAllKeys = require_baseGetAllKeys();\\n var getSymbolsIn = require_getSymbolsIn();\\n var keysIn = require_keysIn();\\n function getAllKeysIn(object) {\\n return baseGetAllKeys(object, keysIn, getSymbolsIn);\\n }\\n module.exports = getAllKeysIn;\\n});\\n\\n// ../../../node_modules/lodash/_DataView.js\\nvar require_DataView = __commonJS((exports, module) => {\\n var getNative = require_getNative();\\n var root = require_root();\\n var DataView = getNative(root, \\\\\\\"DataView\\\\\\\");\\n module.exports = DataView;\\n});\\n\\n// ../../../node_modules/lodash/_Promise.js\\nvar require_Promise = __commonJS((exports, module) => {\\n var getNative = require_getNative();\\n var root = require_root();\\n var Promise2 = getNative(root, \\\\\\\"Promise\\\\\\\");\\n module.exports = Promise2;\\n});\\n\\n// ../../../node_modules/lodash/_Set.js\\nvar require_Set = __commonJS((exports, module) => {\\n var getNative = require_getNative();\\n var root = require_root();\\n var Set2 = getNative(root, \\\\\\\"Set\\\\\\\");\\n module.exports = Set2;\\n});\\n\\n// ../../../node_modules/lodash/_WeakMap.js\\nvar require_WeakMap = __commonJS((exports, module) => {\\n var getNative = require_getNative();\\n var root = require_root();\\n var WeakMap2 = getNative(root, \\\\\\\"WeakMap\\\\\\\");\\n module.exports = WeakMap2;\\n});\\n\\n// ../../../node_modules/lodash/_getTag.js\\nvar require_getTag = __commonJS((exports, module) => {\\n var DataView = require_DataView();\\n var Map2 = require_Map();\\n var Promise2 = require_Promise();\\n var Set2 = require_Set();\\n var WeakMap2 = require_WeakMap();\\n var baseGetTag = require_baseGetTag();\\n var toSource = require_toSource();\\n var mapTag = \\\\\\\"[object Map]\\\\\\\";\\n var objectTag = \\\\\\\"[object Object]\\\\\\\";\\n var promiseTag = \\\\\\\"[object Promise]\\\\\\\";\\n var setTag = \\\\\\\"[object Set]\\\\\\\";\\n var weakMapTag = \\\\\\\"[object WeakMap]\\\\\\\";\\n var dataViewTag = \\\\\\\"[object DataView]\\\\\\\";\\n var dataViewCtorString = toSource(DataView);\\n var mapCtorString = toSource(Map2);\\n var promiseCtorString = toSource(Promise2);\\n var setCtorString = toSource(Set2);\\n var weakMapCtorString = toSource(WeakMap2);\\n var getTag = baseGetTag;\\n if (DataView && getTag(new DataView(new ArrayBuffer(1))) != dataViewTag || Map2 && getTag(new Map2()) != mapTag || Promise2 && getTag(Promise2.resolve()) != promiseTag || Set2 && getTag(new Set2()) != setTag || WeakMap2 && getTag(new WeakMap2()) != weakMapTag) {\\n getTag = function(value) {\\n var result = baseGetTag(value), Ctor = result == objectTag ? value.constructor : void 0, ctorString = Ctor ? toSource(Ctor) : \\\\\\\"\\\\\\\";\\n if (ctorString) {\\n switch (ctorString) {\\n case dataViewCtorString:\\n return dataViewTag;\\n case mapCtorString:\\n return mapTag;\\n case promiseCtorString:\\n return promiseTag;\\n case setCtorString:\\n return setTag;\\n case weakMapCtorString:\\n return weakMapTag;\\n }\\n }\\n return result;\\n };\\n }\\n module.exports = getTag;\\n});\\n\\n// ../../../node_modules/lodash/_initCloneArray.js\\nvar require_initCloneArray = __commonJS((exports, module) => {\\n var objectProto = Object.prototype;\\n var hasOwnProperty = objectProto.hasOwnProperty;\\n function initCloneArray(array) {\\n var length = array.length, result = new array.constructor(length);\\n if (length && typeof array[0] == \\\\\\\"string\\\\\\\" && hasOwnProperty.call(array, \\\\\\\"index\\\\\\\")) {\\n result.index = array.index;\\n result.input = array.input;\\n }\\n return result;\\n }\\n module.exports = initCloneArray;\\n});\\n\\n// ../../../node_modules/lodash/_Uint8Array.js\\nvar require_Uint8Array = __commonJS((exports, module) => {\\n var root = require_root();\\n var Uint8Array2 = root.Uint8Array;\\n module.exports = Uint8Array2;\\n});\\n\\n// ../../../node_modules/lodash/_cloneArrayBuffer.js\\nvar require_cloneArrayBuffer = __commonJS((exports, module) => {\\n var Uint8Array2 = require_Uint8Array();\\n function cloneArrayBuffer(arrayBuffer) {\\n var result = new arrayBuffer.constructor(arrayBuffer.byteLength);\\n new Uint8Array2(result).set(new Uint8Array2(arrayBuffer));\\n return result;\\n }\\n module.exports = cloneArrayBuffer;\\n});\\n\\n// ../../../node_modules/lodash/_cloneDataView.js\\nvar require_cloneDataView = __commonJS((exports, module) => {\\n var cloneArrayBuffer = require_cloneArrayBuffer();\\n function cloneDataView(dataView, isDeep) {\\n var buffer = isDeep ? cloneArrayBuffer(dataView.buffer) : dataView.buffer;\\n return new dataView.constructor(buffer, dataView.byteOffset, dataView.byteLength);\\n }\\n module.exports = cloneDataView;\\n});\\n\\n// ../../../node_modules/lodash/_cloneRegExp.js\\nvar require_cloneRegExp = __commonJS((exports, module) => {\\n var reFlags = /\\\\w*$/;\\n function cloneRegExp(regexp) {\\n var result = new regexp.constructor(regexp.source, reFlags.exec(regexp));\\n result.lastIndex = regexp.lastIndex;\\n return result;\\n }\\n module.exports = cloneRegExp;\\n});\\n\\n// ../../../node_modules/lodash/_cloneSymbol.js\\nvar require_cloneSymbol = __commonJS((exports, module) => {\\n var Symbol2 = require_Symbol();\\n var symbolProto = Symbol2 ? Symbol2.prototype : void 0;\\n var symbolValueOf = symbolProto ? symbolProto.valueOf : void 0;\\n function cloneSymbol(symbol) {\\n return symbolValueOf ? Object(symbolValueOf.call(symbol)) : {};\\n }\\n module.exports = cloneSymbol;\\n});\\n\\n// ../../../node_modules/lodash/_cloneTypedArray.js\\nvar require_cloneTypedArray = __commonJS((exports, module) => {\\n var cloneArrayBuffer = require_cloneArrayBuffer();\\n function cloneTypedArray(typedArray, isDeep) {\\n var buffer = isDeep ? cloneArrayBuffer(typedArray.buffer) : typedArray.buffer;\\n return new typedArray.constructor(buffer, typedArray.byteOffset, typedArray.length);\\n }\\n module.exports = cloneTypedArray;\\n});\\n\\n// ../../../node_modules/lodash/_initCloneByTag.js\\nvar require_initCloneByTag = __commonJS((exports, module) => {\\n var cloneArrayBuffer = require_cloneArrayBuffer();\\n var cloneDataView = require_cloneDataView();\\n var cloneRegExp = require_cloneRegExp();\\n var cloneSymbol = require_cloneSymbol();\\n var cloneTypedArray = require_cloneTypedArray();\\n var boolTag = \\\\\\\"[object Boolean]\\\\\\\";\\n var dateTag = \\\\\\\"[object Date]\\\\\\\";\\n var mapTag = \\\\\\\"[object Map]\\\\\\\";\\n var numberTag = \\\\\\\"[object Number]\\\\\\\";\\n var regexpTag = \\\\\\\"[object RegExp]\\\\\\\";\\n var setTag = \\\\\\\"[object Set]\\\\\\\";\\n var stringTag = \\\\\\\"[object String]\\\\\\\";\\n var symbolTag = \\\\\\\"[object Symbol]\\\\\\\";\\n var arrayBufferTag = \\\\\\\"[object ArrayBuffer]\\\\\\\";\\n var dataViewTag = \\\\\\\"[object DataView]\\\\\\\";\\n var float32Tag = \\\\\\\"[object Float32Array]\\\\\\\";\\n var float64Tag = \\\\\\\"[object Float64Array]\\\\\\\";\\n var int8Tag = \\\\\\\"[object Int8Array]\\\\\\\";\\n var int16Tag = \\\\\\\"[object Int16Array]\\\\\\\";\\n var int32Tag = \\\\\\\"[object Int32Array]\\\\\\\";\\n var uint8Tag = \\\\\\\"[object Uint8Array]\\\\\\\";\\n var uint8ClampedTag = \\\\\\\"[object Uint8ClampedArray]\\\\\\\";\\n var uint16Tag = \\\\\\\"[object Uint16Array]\\\\\\\";\\n var uint32Tag = \\\\\\\"[object Uint32Array]\\\\\\\";\\n function initCloneByTag(object, tag, isDeep) {\\n var Ctor = object.constructor;\\n switch (tag) {\\n case arrayBufferTag:\\n return cloneArrayBuffer(object);\\n case boolTag:\\n case dateTag:\\n return new Ctor(+object);\\n case dataViewTag:\\n return cloneDataView(object, isDeep);\\n case float32Tag:\\n case float64Tag:\\n case int8Tag:\\n case int16Tag:\\n case int32Tag:\\n case uint8Tag:\\n case uint8ClampedTag:\\n case uint16Tag:\\n case uint32Tag:\\n return cloneTypedArray(object, isDeep);\\n case mapTag:\\n return new Ctor();\\n case numberTag:\\n case stringTag:\\n return new Ctor(object);\\n case regexpTag:\\n return cloneRegExp(object);\\n case setTag:\\n return new Ctor();\\n case symbolTag:\\n return cloneSymbol(object);\\n }\\n }\\n module.exports = initCloneByTag;\\n});\\n\\n// ../../../node_modules/lodash/_baseCreate.js\\nvar require_baseCreate = __commonJS((exports, module) => {\\n var isObject = require_isObject();\\n var objectCreate = Object.create;\\n var baseCreate = function() {\\n function object() {\\n }\\n return function(proto) {\\n if (!isObject(proto)) {\\n return {};\\n }\\n if (objectCreate) {\\n return objectCreate(proto);\\n }\\n object.prototype = proto;\\n var result = new object();\\n object.prototype = void 0;\\n return result;\\n };\\n }();\\n module.exports = baseCreate;\\n});\\n\\n// ../../../node_modules/lodash/_initCloneObject.js\\nvar require_initCloneObject = __commonJS((exports, module) => {\\n var baseCreate = require_baseCreate();\\n var getPrototype = require_getPrototype();\\n var isPrototype = require_isPrototype();\\n function initCloneObject(object) {\\n return typeof object.constructor == \\\\\\\"function\\\\\\\" && !isPrototype(object) ? baseCreate(getPrototype(object)) : {};\\n }\\n module.exports = initCloneObject;\\n});\\n\\n// ../../../node_modules/lodash/_baseIsMap.js\\nvar require_baseIsMap = __commonJS((exports, module) => {\\n var getTag = require_getTag();\\n var isObjectLike = require_isObjectLike();\\n var mapTag = \\\\\\\"[object Map]\\\\\\\";\\n function baseIsMap(value) {\\n return isObjectLike(value) && getTag(value) == mapTag;\\n }\\n module.exports = baseIsMap;\\n});\\n\\n// ../../../node_modules/lodash/isMap.js\\nvar require_isMap = __commonJS((exports, module) => {\\n var baseIsMap = require_baseIsMap();\\n var baseUnary = require_baseUnary();\\n var nodeUtil = require_nodeUtil();\\n var nodeIsMap = nodeUtil && nodeUtil.isMap;\\n var isMap = nodeIsMap ? baseUnary(nodeIsMap) : baseIsMap;\\n module.exports = isMap;\\n});\\n\\n// ../../../node_modules/lodash/_baseIsSet.js\\nvar require_baseIsSet = __commonJS((exports, module) => {\\n var getTag = require_getTag();\\n var isObjectLike = require_isObjectLike();\\n var setTag = \\\\\\\"[object Set]\\\\\\\";\\n function baseIsSet(value) {\\n return isObjectLike(value) && getTag(value) == setTag;\\n }\\n module.exports = baseIsSet;\\n});\\n\\n// ../../../node_modules/lodash/isSet.js\\nvar require_isSet = __commonJS((exports, module) => {\\n var baseIsSet = require_baseIsSet();\\n var baseUnary = require_baseUnary();\\n var nodeUtil = require_nodeUtil();\\n var nodeIsSet = nodeUtil && nodeUtil.isSet;\\n var isSet = nodeIsSet ? baseUnary(nodeIsSet) : baseIsSet;\\n module.exports = isSet;\\n});\\n\\n// ../../../node_modules/lodash/_baseClone.js\\nvar require_baseClone = __commonJS((exports, module) => {\\n var Stack = require_Stack();\\n var arrayEach = require_arrayEach();\\n var assignValue = require_assignValue();\\n var baseAssign = require_baseAssign();\\n var baseAssignIn = require_baseAssignIn();\\n var cloneBuffer = require_cloneBuffer();\\n var copyArray2 = require_copyArray();\\n var copySymbols = require_copySymbols();\\n var copySymbolsIn = require_copySymbolsIn();\\n var getAllKeys = require_getAllKeys();\\n var getAllKeysIn = require_getAllKeysIn();\\n var getTag = require_getTag();\\n var initCloneArray = require_initCloneArray();\\n var initCloneByTag = require_initCloneByTag();\\n var initCloneObject = require_initCloneObject();\\n var isArray = require_isArray();\\n var isBuffer = require_isBuffer();\\n var isMap = require_isMap();\\n var isObject = require_isObject();\\n var isSet = require_isSet();\\n var keys = require_keys();\\n var keysIn = require_keysIn();\\n var CLONE_DEEP_FLAG = 1;\\n var CLONE_FLAT_FLAG = 2;\\n var CLONE_SYMBOLS_FLAG = 4;\\n var argsTag = \\\\\\\"[object Arguments]\\\\\\\";\\n var arrayTag = \\\\\\\"[object Array]\\\\\\\";\\n var boolTag = \\\\\\\"[object Boolean]\\\\\\\";\\n var dateTag = \\\\\\\"[object Date]\\\\\\\";\\n var errorTag = \\\\\\\"[object Error]\\\\\\\";\\n var funcTag = \\\\\\\"[object Function]\\\\\\\";\\n var genTag = \\\\\\\"[object GeneratorFunction]\\\\\\\";\\n var mapTag = \\\\\\\"[object Map]\\\\\\\";\\n var numberTag = \\\\\\\"[object Number]\\\\\\\";\\n var objectTag = \\\\\\\"[object Object]\\\\\\\";\\n var regexpTag = \\\\\\\"[object RegExp]\\\\\\\";\\n var setTag = \\\\\\\"[object Set]\\\\\\\";\\n var stringTag = \\\\\\\"[object String]\\\\\\\";\\n var symbolTag = \\\\\\\"[object Symbol]\\\\\\\";\\n var weakMapTag = \\\\\\\"[object WeakMap]\\\\\\\";\\n var arrayBufferTag = \\\\\\\"[object ArrayBuffer]\\\\\\\";\\n var dataViewTag = \\\\\\\"[object DataView]\\\\\\\";\\n var float32Tag = \\\\\\\"[object Float32Array]\\\\\\\";\\n var float64Tag = \\\\\\\"[object Float64Array]\\\\\\\";\\n var int8Tag = \\\\\\\"[object Int8Array]\\\\\\\";\\n var int16Tag = \\\\\\\"[object Int16Array]\\\\\\\";\\n var int32Tag = \\\\\\\"[object Int32Array]\\\\\\\";\\n var uint8Tag = \\\\\\\"[object Uint8Array]\\\\\\\";\\n var uint8ClampedTag = \\\\\\\"[object Uint8ClampedArray]\\\\\\\";\\n var uint16Tag = \\\\\\\"[object Uint16Array]\\\\\\\";\\n var uint32Tag = \\\\\\\"[object Uint32Array]\\\\\\\";\\n var cloneableTags = {};\\n cloneableTags[argsTag] = cloneableTags[arrayTag] = cloneableTags[arrayBufferTag] = cloneableTags[dataViewTag] = cloneableTags[boolTag] = cloneableTags[dateTag] = cloneableTags[float32Tag] = cloneableTags[float64Tag] = cloneableTags[int8Tag] = cloneableTags[int16Tag] = cloneableTags[int32Tag] = cloneableTags[mapTag] = cloneableTags[numberTag] = cloneableTags[objectTag] = cloneableTags[regexpTag] = cloneableTags[setTag] = cloneableTags[stringTag] = cloneableTags[symbolTag] = cloneableTags[uint8Tag] = cloneableTags[uint8ClampedTag] = cloneableTags[uint16Tag] = cloneableTags[uint32Tag] = true;\\n cloneableTags[errorTag] = cloneableTags[funcTag] = cloneableTags[weakMapTag] = false;\\n function baseClone(value, bitmask, customizer, key, object, stack) {\\n var result, isDeep = bitmask & CLONE_DEEP_FLAG, isFlat = bitmask & CLONE_FLAT_FLAG, isFull = bitmask & CLONE_SYMBOLS_FLAG;\\n if (customizer) {\\n result = object ? customizer(value, key, object, stack) : customizer(value);\\n }\\n if (result !== void 0) {\\n return result;\\n }\\n if (!isObject(value)) {\\n return value;\\n }\\n var isArr = isArray(value);\\n if (isArr) {\\n result = initCloneArray(value);\\n if (!isDeep) {\\n return copyArray2(value, result);\\n }\\n } else {\\n var tag = getTag(value), isFunc = tag == funcTag || tag == genTag;\\n if (isBuffer(value)) {\\n return cloneBuffer(value, isDeep);\\n }\\n if (tag == objectTag || tag == argsTag || isFunc && !object) {\\n result = isFlat || isFunc ? {} : initCloneObject(value);\\n if (!isDeep) {\\n return isFlat ? copySymbolsIn(value, baseAssignIn(result, value)) : copySymbols(value, baseAssign(result, value));\\n }\\n } else {\\n if (!cloneableTags[tag]) {\\n return object ? value : {};\\n }\\n result = initCloneByTag(value, tag, isDeep);\\n }\\n }\\n stack || (stack = new Stack());\\n var stacked = stack.get(value);\\n if (stacked) {\\n return stacked;\\n }\\n stack.set(value, result);\\n if (isSet(value)) {\\n value.forEach(function(subValue) {\\n result.add(baseClone(subValue, bitmask, customizer, subValue, value, stack));\\n });\\n } else if (isMap(value)) {\\n value.forEach(function(subValue, key2) {\\n result.set(key2, baseClone(subValue, bitmask, customizer, key2, value, stack));\\n });\\n }\\n var keysFunc = isFull ? isFlat ? getAllKeysIn : getAllKeys : isFlat ? keysIn : keys;\\n var props = isArr ? void 0 : keysFunc(value);\\n arrayEach(props || value, function(subValue, key2) {\\n if (props) {\\n key2 = subValue;\\n subValue = value[key2];\\n }\\n assignValue(result, key2, baseClone(subValue, bitmask, customizer, key2, value, stack));\\n });\\n return result;\\n }\\n module.exports = baseClone;\\n});\\n\\n// ../../../node_modules/lodash/cloneDeep.js\\nvar require_cloneDeep = __commonJS((exports, module) => {\\n var baseClone = require_baseClone();\\n var CLONE_DEEP_FLAG = 1;\\n var CLONE_SYMBOLS_FLAG = 4;\\n function cloneDeep(value) {\\n return baseClone(value, CLONE_DEEP_FLAG | CLONE_SYMBOLS_FLAG);\\n }\\n module.exports = cloneDeep;\\n});\\n\\n// ../../../node_modules/lodash/clone.js\\nvar require_clone = __commonJS((exports, module) => {\\n var baseClone = require_baseClone();\\n var CLONE_SYMBOLS_FLAG = 4;\\n function clone(value) {\\n return baseClone(value, CLONE_SYMBOLS_FLAG);\\n }\\n module.exports = clone;\\n});\\n\\n// ../../../node_modules/jsep/build/jsep.js\\nvar require_jsep = __commonJS((exports, module) => {\\n (function(root) {\\n \\\\\\\"use strict\\\\\\\";\\n var COMPOUND = \\\\\\\"Compound\\\\\\\", IDENTIFIER = \\\\\\\"Identifier\\\\\\\", MEMBER_EXP = \\\\\\\"MemberExpression\\\\\\\", LITERAL = \\\\\\\"Literal\\\\\\\", THIS_EXP = \\\\\\\"ThisExpression\\\\\\\", CALL_EXP = \\\\\\\"CallExpression\\\\\\\", UNARY_EXP = \\\\\\\"UnaryExpression\\\\\\\", BINARY_EXP = \\\\\\\"BinaryExpression\\\\\\\", LOGICAL_EXP = \\\\\\\"LogicalExpression\\\\\\\", CONDITIONAL_EXP = \\\\\\\"ConditionalExpression\\\\\\\", ARRAY_EXP = \\\\\\\"ArrayExpression\\\\\\\", PERIOD_CODE = 46, COMMA_CODE = 44, SQUOTE_CODE = 39, DQUOTE_CODE = 34, OPAREN_CODE = 40, CPAREN_CODE = 41, OBRACK_CODE = 91, CBRACK_CODE = 93, QUMARK_CODE = 63, SEMCOL_CODE = 59, COLON_CODE = 58, throwError = function(message, index) {\\n var error = new Error(message + \\\\\\\" at character \\\\\\\" + index);\\n error.index = index;\\n error.description = message;\\n throw error;\\n }, t = true, unary_ops = {\\\\\\\"-\\\\\\\": t, \\\\\\\"!\\\\\\\": t, \\\\\\\"~\\\\\\\": t, \\\\\\\"+\\\\\\\": t}, binary_ops = {\\n \\\\\\\"||\\\\\\\": 1,\\n \\\\\\\"&&\\\\\\\": 2,\\n \\\\\\\"|\\\\\\\": 3,\\n \\\\\\\"^\\\\\\\": 4,\\n \\\\\\\"&\\\\\\\": 5,\\n \\\\\\\"==\\\\\\\": 6,\\n \\\\\\\"!=\\\\\\\": 6,\\n \\\\\\\"===\\\\\\\": 6,\\n \\\\\\\"!==\\\\\\\": 6,\\n \\\\\\\"<\\\\\\\": 7,\\n \\\\\\\">\\\\\\\": 7,\\n \\\\\\\"<=\\\\\\\": 7,\\n \\\\\\\">=\\\\\\\": 7,\\n \\\\\\\"<<\\\\\\\": 8,\\n \\\\\\\">>\\\\\\\": 8,\\n \\\\\\\">>>\\\\\\\": 8,\\n \\\\\\\"+\\\\\\\": 9,\\n \\\\\\\"-\\\\\\\": 9,\\n \\\\\\\"*\\\\\\\": 10,\\n \\\\\\\"/\\\\\\\": 10,\\n \\\\\\\"%\\\\\\\": 10\\n }, getMaxKeyLen = function(obj) {\\n var max_len = 0, len;\\n for (var key in obj) {\\n if ((len = key.length) > max_len && obj.hasOwnProperty(key)) {\\n max_len = len;\\n }\\n }\\n return max_len;\\n }, max_unop_len = getMaxKeyLen(unary_ops), max_binop_len = getMaxKeyLen(binary_ops), literals = {\\n true: true,\\n false: false,\\n null: null\\n }, this_str = \\\\\\\"this\\\\\\\", binaryPrecedence = function(op_val) {\\n return binary_ops[op_val] || 0;\\n }, createBinaryExpression = function(operator, left, right) {\\n var type = operator === \\\\\\\"||\\\\\\\" || operator === \\\\\\\"&&\\\\\\\" ? LOGICAL_EXP : BINARY_EXP;\\n return {\\n type,\\n operator,\\n left,\\n right\\n };\\n }, isDecimalDigit = function(ch) {\\n return ch >= 48 && ch <= 57;\\n }, isIdentifierStart = function(ch) {\\n return ch === 36 || ch === 95 || ch >= 65 && ch <= 90 || ch >= 97 && ch <= 122 || ch >= 128 && !binary_ops[String.fromCharCode(ch)];\\n }, isIdentifierPart = function(ch) {\\n return ch === 36 || ch === 95 || ch >= 65 && ch <= 90 || ch >= 97 && ch <= 122 || ch >= 48 && ch <= 57 || ch >= 128 && !binary_ops[String.fromCharCode(ch)];\\n }, jsep2 = function(expr) {\\n var index = 0, charAtFunc = expr.charAt, charCodeAtFunc = expr.charCodeAt, exprI = function(i) {\\n return charAtFunc.call(expr, i);\\n }, exprICode = function(i) {\\n return charCodeAtFunc.call(expr, i);\\n }, length = expr.length, gobbleSpaces = function() {\\n var ch = exprICode(index);\\n while (ch === 32 || ch === 9 || ch === 10 || ch === 13) {\\n ch = exprICode(++index);\\n }\\n }, gobbleExpression = function() {\\n var test = gobbleBinaryExpression(), consequent, alternate;\\n gobbleSpaces();\\n if (exprICode(index) === QUMARK_CODE) {\\n index++;\\n consequent = gobbleExpression();\\n if (!consequent) {\\n throwError(\\\\\\\"Expected expression\\\\\\\", index);\\n }\\n gobbleSpaces();\\n if (exprICode(index) === COLON_CODE) {\\n index++;\\n alternate = gobbleExpression();\\n if (!alternate) {\\n throwError(\\\\\\\"Expected expression\\\\\\\", index);\\n }\\n return {\\n type: CONDITIONAL_EXP,\\n test,\\n consequent,\\n alternate\\n };\\n } else {\\n throwError(\\\\\\\"Expected :\\\\\\\", index);\\n }\\n } else {\\n return test;\\n }\\n }, gobbleBinaryOp = function() {\\n gobbleSpaces();\\n var biop, to_check = expr.substr(index, max_binop_len), tc_len = to_check.length;\\n while (tc_len > 0) {\\n if (binary_ops.hasOwnProperty(to_check) && (!isIdentifierStart(exprICode(index)) || index + to_check.length < expr.length && !isIdentifierPart(exprICode(index + to_check.length)))) {\\n index += tc_len;\\n return to_check;\\n }\\n to_check = to_check.substr(0, --tc_len);\\n }\\n return false;\\n }, gobbleBinaryExpression = function() {\\n var ch_i2, node2, biop, prec, stack, biop_info, left, right, i, cur_biop;\\n left = gobbleToken();\\n biop = gobbleBinaryOp();\\n if (!biop) {\\n return left;\\n }\\n biop_info = {value: biop, prec: binaryPrecedence(biop)};\\n right = gobbleToken();\\n if (!right) {\\n throwError(\\\\\\\"Expected expression after \\\\\\\" + biop, index);\\n }\\n stack = [left, biop_info, right];\\n while (biop = gobbleBinaryOp()) {\\n prec = binaryPrecedence(biop);\\n if (prec === 0) {\\n break;\\n }\\n biop_info = {value: biop, prec};\\n cur_biop = biop;\\n while (stack.length > 2 && prec <= stack[stack.length - 2].prec) {\\n right = stack.pop();\\n biop = stack.pop().value;\\n left = stack.pop();\\n node2 = createBinaryExpression(biop, left, right);\\n stack.push(node2);\\n }\\n node2 = gobbleToken();\\n if (!node2) {\\n throwError(\\\\\\\"Expected expression after \\\\\\\" + cur_biop, index);\\n }\\n stack.push(biop_info, node2);\\n }\\n i = stack.length - 1;\\n node2 = stack[i];\\n while (i > 1) {\\n node2 = createBinaryExpression(stack[i - 1].value, stack[i - 2], node2);\\n i -= 2;\\n }\\n return node2;\\n }, gobbleToken = function() {\\n var ch, to_check, tc_len;\\n gobbleSpaces();\\n ch = exprICode(index);\\n if (isDecimalDigit(ch) || ch === PERIOD_CODE) {\\n return gobbleNumericLiteral();\\n } else if (ch === SQUOTE_CODE || ch === DQUOTE_CODE) {\\n return gobbleStringLiteral();\\n } else if (ch === OBRACK_CODE) {\\n return gobbleArray();\\n } else {\\n to_check = expr.substr(index, max_unop_len);\\n tc_len = to_check.length;\\n while (tc_len > 0) {\\n if (unary_ops.hasOwnProperty(to_check) && (!isIdentifierStart(exprICode(index)) || index + to_check.length < expr.length && !isIdentifierPart(exprICode(index + to_check.length)))) {\\n index += tc_len;\\n return {\\n type: UNARY_EXP,\\n operator: to_check,\\n argument: gobbleToken(),\\n prefix: true\\n };\\n }\\n to_check = to_check.substr(0, --tc_len);\\n }\\n if (isIdentifierStart(ch) || ch === OPAREN_CODE) {\\n return gobbleVariable();\\n }\\n }\\n return false;\\n }, gobbleNumericLiteral = function() {\\n var number = \\\\\\\"\\\\\\\", ch, chCode;\\n while (isDecimalDigit(exprICode(index))) {\\n number += exprI(index++);\\n }\\n if (exprICode(index) === PERIOD_CODE) {\\n number += exprI(index++);\\n while (isDecimalDigit(exprICode(index))) {\\n number += exprI(index++);\\n }\\n }\\n ch = exprI(index);\\n if (ch === \\\\\\\"e\\\\\\\" || ch === \\\\\\\"E\\\\\\\") {\\n number += exprI(index++);\\n ch = exprI(index);\\n if (ch === \\\\\\\"+\\\\\\\" || ch === \\\\\\\"-\\\\\\\") {\\n number += exprI(index++);\\n }\\n while (isDecimalDigit(exprICode(index))) {\\n number += exprI(index++);\\n }\\n if (!isDecimalDigit(exprICode(index - 1))) {\\n throwError(\\\\\\\"Expected exponent (\\\\\\\" + number + exprI(index) + \\\\\\\")\\\\\\\", index);\\n }\\n }\\n chCode = exprICode(index);\\n if (isIdentifierStart(chCode)) {\\n throwError(\\\\\\\"Variable names cannot start with a number (\\\\\\\" + number + exprI(index) + \\\\\\\")\\\\\\\", index);\\n } else if (chCode === PERIOD_CODE) {\\n throwError(\\\\\\\"Unexpected period\\\\\\\", index);\\n }\\n return {\\n type: LITERAL,\\n value: parseFloat(number),\\n raw: number\\n };\\n }, gobbleStringLiteral = function() {\\n var str = \\\\\\\"\\\\\\\", quote = exprI(index++), closed = false, ch;\\n while (index < length) {\\n ch = exprI(index++);\\n if (ch === quote) {\\n closed = true;\\n break;\\n } else if (ch === \\\\\\\"\\\\\\\\\\\\\\\") {\\n ch = exprI(index++);\\n switch (ch) {\\n case \\\\\\\"n\\\\\\\":\\n str += \\\\\\\"\\\\n\\\\\\\";\\n break;\\n case \\\\\\\"r\\\\\\\":\\n str += \\\\\\\"\\\\r\\\\\\\";\\n break;\\n case \\\\\\\"t\\\\\\\":\\n str += \\\\\\\"\\t\\\\\\\";\\n break;\\n case \\\\\\\"b\\\\\\\":\\n str += \\\\\\\"\\\\b\\\\\\\";\\n break;\\n case \\\\\\\"f\\\\\\\":\\n str += \\\\\\\"\\\\f\\\\\\\";\\n break;\\n case \\\\\\\"v\\\\\\\":\\n str += \\\\\\\"\\\\v\\\\\\\";\\n break;\\n default:\\n str += ch;\\n }\\n } else {\\n str += ch;\\n }\\n }\\n if (!closed) {\\n throwError('Unclosed quote after \\\\\\\"' + str + '\\\\\\\"', index);\\n }\\n return {\\n type: LITERAL,\\n value: str,\\n raw: quote + str + quote\\n };\\n }, gobbleIdentifier = function() {\\n var ch = exprICode(index), start = index, identifier;\\n if (isIdentifierStart(ch)) {\\n index++;\\n } else {\\n throwError(\\\\\\\"Unexpected \\\\\\\" + exprI(index), index);\\n }\\n while (index < length) {\\n ch = exprICode(index);\\n if (isIdentifierPart(ch)) {\\n index++;\\n } else {\\n break;\\n }\\n }\\n identifier = expr.slice(start, index);\\n if (literals.hasOwnProperty(identifier)) {\\n return {\\n type: LITERAL,\\n value: literals[identifier],\\n raw: identifier\\n };\\n } else if (identifier === this_str) {\\n return {type: THIS_EXP};\\n } else {\\n return {\\n type: IDENTIFIER,\\n name: identifier\\n };\\n }\\n }, gobbleArguments = function(termination) {\\n var ch_i2, args = [], node2, closed = false;\\n var separator_count = 0;\\n while (index < length) {\\n gobbleSpaces();\\n ch_i2 = exprICode(index);\\n if (ch_i2 === termination) {\\n closed = true;\\n index++;\\n if (termination === CPAREN_CODE && separator_count && separator_count >= args.length) {\\n throwError(\\\\\\\"Unexpected token \\\\\\\" + String.fromCharCode(termination), index);\\n }\\n break;\\n } else if (ch_i2 === COMMA_CODE) {\\n index++;\\n separator_count++;\\n if (separator_count !== args.length) {\\n if (termination === CPAREN_CODE) {\\n throwError(\\\\\\\"Unexpected token ,\\\\\\\", index);\\n } else if (termination === CBRACK_CODE) {\\n for (var arg = args.length; arg < separator_count; arg++) {\\n args.push(null);\\n }\\n }\\n }\\n } else {\\n node2 = gobbleExpression();\\n if (!node2 || node2.type === COMPOUND) {\\n throwError(\\\\\\\"Expected comma\\\\\\\", index);\\n }\\n args.push(node2);\\n }\\n }\\n if (!closed) {\\n throwError(\\\\\\\"Expected \\\\\\\" + String.fromCharCode(termination), index);\\n }\\n return args;\\n }, gobbleVariable = function() {\\n var ch_i2, node2;\\n ch_i2 = exprICode(index);\\n if (ch_i2 === OPAREN_CODE) {\\n node2 = gobbleGroup();\\n } else {\\n node2 = gobbleIdentifier();\\n }\\n gobbleSpaces();\\n ch_i2 = exprICode(index);\\n while (ch_i2 === PERIOD_CODE || ch_i2 === OBRACK_CODE || ch_i2 === OPAREN_CODE) {\\n index++;\\n if (ch_i2 === PERIOD_CODE) {\\n gobbleSpaces();\\n node2 = {\\n type: MEMBER_EXP,\\n computed: false,\\n object: node2,\\n property: gobbleIdentifier()\\n };\\n } else if (ch_i2 === OBRACK_CODE) {\\n node2 = {\\n type: MEMBER_EXP,\\n computed: true,\\n object: node2,\\n property: gobbleExpression()\\n };\\n gobbleSpaces();\\n ch_i2 = exprICode(index);\\n if (ch_i2 !== CBRACK_CODE) {\\n throwError(\\\\\\\"Unclosed [\\\\\\\", index);\\n }\\n index++;\\n } else if (ch_i2 === OPAREN_CODE) {\\n node2 = {\\n type: CALL_EXP,\\n arguments: gobbleArguments(CPAREN_CODE),\\n callee: node2\\n };\\n }\\n gobbleSpaces();\\n ch_i2 = exprICode(index);\\n }\\n return node2;\\n }, gobbleGroup = function() {\\n index++;\\n var node2 = gobbleExpression();\\n gobbleSpaces();\\n if (exprICode(index) === CPAREN_CODE) {\\n index++;\\n return node2;\\n } else {\\n throwError(\\\\\\\"Unclosed (\\\\\\\", index);\\n }\\n }, gobbleArray = function() {\\n index++;\\n return {\\n type: ARRAY_EXP,\\n elements: gobbleArguments(CBRACK_CODE)\\n };\\n }, nodes = [], ch_i, node;\\n while (index < length) {\\n ch_i = exprICode(index);\\n if (ch_i === SEMCOL_CODE || ch_i === COMMA_CODE) {\\n index++;\\n } else {\\n if (node = gobbleExpression()) {\\n nodes.push(node);\\n } else if (index < length) {\\n throwError('Unexpected \\\\\\\"' + exprI(index) + '\\\\\\\"', index);\\n }\\n }\\n }\\n if (nodes.length === 1) {\\n return nodes[0];\\n } else {\\n return {\\n type: COMPOUND,\\n body: nodes\\n };\\n }\\n };\\n jsep2.version = \\\\\\\"0.3.5\\\\\\\";\\n jsep2.toString = function() {\\n return \\\\\\\"JavaScript Expression Parser (JSEP) v\\\\\\\" + jsep2.version;\\n };\\n jsep2.addUnaryOp = function(op_name) {\\n max_unop_len = Math.max(op_name.length, max_unop_len);\\n unary_ops[op_name] = t;\\n return this;\\n };\\n jsep2.addBinaryOp = function(op_name, precedence2) {\\n max_binop_len = Math.max(op_name.length, max_binop_len);\\n binary_ops[op_name] = precedence2;\\n return this;\\n };\\n jsep2.addLiteral = function(literal_name, literal_value) {\\n literals[literal_name] = literal_value;\\n return this;\\n };\\n jsep2.removeUnaryOp = function(op_name) {\\n delete unary_ops[op_name];\\n if (op_name.length === max_unop_len) {\\n max_unop_len = getMaxKeyLen(unary_ops);\\n }\\n return this;\\n };\\n jsep2.removeAllUnaryOps = function() {\\n unary_ops = {};\\n max_unop_len = 0;\\n return this;\\n };\\n jsep2.removeBinaryOp = function(op_name) {\\n delete binary_ops[op_name];\\n if (op_name.length === max_binop_len) {\\n max_binop_len = getMaxKeyLen(binary_ops);\\n }\\n return this;\\n };\\n jsep2.removeAllBinaryOps = function() {\\n binary_ops = {};\\n max_binop_len = 0;\\n return this;\\n };\\n jsep2.removeLiteral = function(literal_name) {\\n delete literals[literal_name];\\n return this;\\n };\\n jsep2.removeAllLiterals = function() {\\n literals = {};\\n return this;\\n };\\n if (typeof exports === \\\\\\\"undefined\\\\\\\") {\\n var old_jsep = root.jsep;\\n root.jsep = jsep2;\\n jsep2.noConflict = function() {\\n if (root.jsep === jsep2) {\\n root.jsep = old_jsep;\\n }\\n return jsep2;\\n };\\n } else {\\n if (typeof module !== \\\\\\\"undefined\\\\\\\" && module.exports) {\\n exports = module.exports = jsep2;\\n } else {\\n exports.parse = jsep2;\\n }\\n }\\n })(exports);\\n});\\n\\n// ../../../node_modules/three/src/math/MathUtils.js\\nvar DEG2RAD = Math.PI / 180;\\nvar RAD2DEG = 180 / Math.PI;\\nvar _lut = [];\\nfor (let i = 0; i < 256; i++) {\\n _lut[i] = (i < 16 ? \\\\\\\"0\\\\\\\" : \\\\\\\"\\\\\\\") + i.toString(16);\\n}\\nvar hasRandomUUID = typeof crypto !== \\\\\\\"undefined\\\\\\\" && \\\\\\\"randomUUID\\\\\\\" in crypto;\\nfunction generateUUID() {\\n if (hasRandomUUID) {\\n return crypto.randomUUID().toUpperCase();\\n }\\n const d0 = Math.random() * 4294967295 | 0;\\n const d1 = Math.random() * 4294967295 | 0;\\n const d2 = Math.random() * 4294967295 | 0;\\n const d3 = Math.random() * 4294967295 | 0;\\n const uuid = _lut[d0 & 255] + _lut[d0 >> 8 & 255] + _lut[d0 >> 16 & 255] + _lut[d0 >> 24 & 255] + \\\\\\\"-\\\\\\\" + _lut[d1 & 255] + _lut[d1 >> 8 & 255] + \\\\\\\"-\\\\\\\" + _lut[d1 >> 16 & 15 | 64] + _lut[d1 >> 24 & 255] + \\\\\\\"-\\\\\\\" + _lut[d2 & 63 | 128] + _lut[d2 >> 8 & 255] + \\\\\\\"-\\\\\\\" + _lut[d2 >> 16 & 255] + _lut[d2 >> 24 & 255] + _lut[d3 & 255] + _lut[d3 >> 8 & 255] + _lut[d3 >> 16 & 255] + _lut[d3 >> 24 & 255];\\n return uuid.toUpperCase();\\n}\\nfunction clamp(value, min, max) {\\n return Math.max(min, Math.min(max, value));\\n}\\nfunction euclideanModulo(n, m) {\\n return (n % m + m) % m;\\n}\\nfunction lerp(x, y, t) {\\n return (1 - t) * x + t * y;\\n}\\nfunction degToRad(degrees) {\\n return degrees * DEG2RAD;\\n}\\nfunction isPowerOfTwo(value) {\\n return (value & value - 1) === 0 && value !== 0;\\n}\\nfunction floorPowerOfTwo(value) {\\n return Math.pow(2, Math.floor(Math.log(value) / Math.LN2));\\n}\\n\\n// ../../../node_modules/three/src/math/Quaternion.js\\nvar Quaternion = class {\\n constructor(x = 0, y = 0, z = 0, w = 1) {\\n this._x = x;\\n this._y = y;\\n this._z = z;\\n this._w = w;\\n }\\n static slerp(qa, qb, qm, t) {\\n console.warn(\\\\\\\"THREE.Quaternion: Static .slerp() has been deprecated. Use qm.slerpQuaternions( qa, qb, t ) instead.\\\\\\\");\\n return qm.slerpQuaternions(qa, qb, t);\\n }\\n static slerpFlat(dst, dstOffset, src0, srcOffset0, src1, srcOffset1, t) {\\n let x0 = src0[srcOffset0 + 0], y0 = src0[srcOffset0 + 1], z0 = src0[srcOffset0 + 2], w0 = src0[srcOffset0 + 3];\\n const x1 = src1[srcOffset1 + 0], y1 = src1[srcOffset1 + 1], z1 = src1[srcOffset1 + 2], w1 = src1[srcOffset1 + 3];\\n if (t === 0) {\\n dst[dstOffset + 0] = x0;\\n dst[dstOffset + 1] = y0;\\n dst[dstOffset + 2] = z0;\\n dst[dstOffset + 3] = w0;\\n return;\\n }\\n if (t === 1) {\\n dst[dstOffset + 0] = x1;\\n dst[dstOffset + 1] = y1;\\n dst[dstOffset + 2] = z1;\\n dst[dstOffset + 3] = w1;\\n return;\\n }\\n if (w0 !== w1 || x0 !== x1 || y0 !== y1 || z0 !== z1) {\\n let s = 1 - t;\\n const cos = x0 * x1 + y0 * y1 + z0 * z1 + w0 * w1, dir = cos >= 0 ? 1 : -1, sqrSin = 1 - cos * cos;\\n if (sqrSin > Number.EPSILON) {\\n const sin = Math.sqrt(sqrSin), len = Math.atan2(sin, cos * dir);\\n s = Math.sin(s * len) / sin;\\n t = Math.sin(t * len) / sin;\\n }\\n const tDir = t * dir;\\n x0 = x0 * s + x1 * tDir;\\n y0 = y0 * s + y1 * tDir;\\n z0 = z0 * s + z1 * tDir;\\n w0 = w0 * s + w1 * tDir;\\n if (s === 1 - t) {\\n const f = 1 / Math.sqrt(x0 * x0 + y0 * y0 + z0 * z0 + w0 * w0);\\n x0 *= f;\\n y0 *= f;\\n z0 *= f;\\n w0 *= f;\\n }\\n }\\n dst[dstOffset] = x0;\\n dst[dstOffset + 1] = y0;\\n dst[dstOffset + 2] = z0;\\n dst[dstOffset + 3] = w0;\\n }\\n static multiplyQuaternionsFlat(dst, dstOffset, src0, srcOffset0, src1, srcOffset1) {\\n const x0 = src0[srcOffset0];\\n const y0 = src0[srcOffset0 + 1];\\n const z0 = src0[srcOffset0 + 2];\\n const w0 = src0[srcOffset0 + 3];\\n const x1 = src1[srcOffset1];\\n const y1 = src1[srcOffset1 + 1];\\n const z1 = src1[srcOffset1 + 2];\\n const w1 = src1[srcOffset1 + 3];\\n dst[dstOffset] = x0 * w1 + w0 * x1 + y0 * z1 - z0 * y1;\\n dst[dstOffset + 1] = y0 * w1 + w0 * y1 + z0 * x1 - x0 * z1;\\n dst[dstOffset + 2] = z0 * w1 + w0 * z1 + x0 * y1 - y0 * x1;\\n dst[dstOffset + 3] = w0 * w1 - x0 * x1 - y0 * y1 - z0 * z1;\\n return dst;\\n }\\n get x() {\\n return this._x;\\n }\\n set x(value) {\\n this._x = value;\\n this._onChangeCallback();\\n }\\n get y() {\\n return this._y;\\n }\\n set y(value) {\\n this._y = value;\\n this._onChangeCallback();\\n }\\n get z() {\\n return this._z;\\n }\\n set z(value) {\\n this._z = value;\\n this._onChangeCallback();\\n }\\n get w() {\\n return this._w;\\n }\\n set w(value) {\\n this._w = value;\\n this._onChangeCallback();\\n }\\n set(x, y, z, w) {\\n this._x = x;\\n this._y = y;\\n this._z = z;\\n this._w = w;\\n this._onChangeCallback();\\n return this;\\n }\\n clone() {\\n return new this.constructor(this._x, this._y, this._z, this._w);\\n }\\n copy(quaternion) {\\n this._x = quaternion.x;\\n this._y = quaternion.y;\\n this._z = quaternion.z;\\n this._w = quaternion.w;\\n this._onChangeCallback();\\n return this;\\n }\\n setFromEuler(euler, update) {\\n if (!(euler && euler.isEuler)) {\\n throw new Error(\\\\\\\"THREE.Quaternion: .setFromEuler() now expects an Euler rotation rather than a Vector3 and order.\\\\\\\");\\n }\\n const x = euler._x, y = euler._y, z = euler._z, order = euler._order;\\n const cos = Math.cos;\\n const sin = Math.sin;\\n const c1 = cos(x / 2);\\n const c2 = cos(y / 2);\\n const c3 = cos(z / 2);\\n const s1 = sin(x / 2);\\n const s2 = sin(y / 2);\\n const s3 = sin(z / 2);\\n switch (order) {\\n case \\\\\\\"XYZ\\\\\\\":\\n this._x = s1 * c2 * c3 + c1 * s2 * s3;\\n this._y = c1 * s2 * c3 - s1 * c2 * s3;\\n this._z = c1 * c2 * s3 + s1 * s2 * c3;\\n this._w = c1 * c2 * c3 - s1 * s2 * s3;\\n break;\\n case \\\\\\\"YXZ\\\\\\\":\\n this._x = s1 * c2 * c3 + c1 * s2 * s3;\\n this._y = c1 * s2 * c3 - s1 * c2 * s3;\\n this._z = c1 * c2 * s3 - s1 * s2 * c3;\\n this._w = c1 * c2 * c3 + s1 * s2 * s3;\\n break;\\n case \\\\\\\"ZXY\\\\\\\":\\n this._x = s1 * c2 * c3 - c1 * s2 * s3;\\n this._y = c1 * s2 * c3 + s1 * c2 * s3;\\n this._z = c1 * c2 * s3 + s1 * s2 * c3;\\n this._w = c1 * c2 * c3 - s1 * s2 * s3;\\n break;\\n case \\\\\\\"ZYX\\\\\\\":\\n this._x = s1 * c2 * c3 - c1 * s2 * s3;\\n this._y = c1 * s2 * c3 + s1 * c2 * s3;\\n this._z = c1 * c2 * s3 - s1 * s2 * c3;\\n this._w = c1 * c2 * c3 + s1 * s2 * s3;\\n break;\\n case \\\\\\\"YZX\\\\\\\":\\n this._x = s1 * c2 * c3 + c1 * s2 * s3;\\n this._y = c1 * s2 * c3 + s1 * c2 * s3;\\n this._z = c1 * c2 * s3 - s1 * s2 * c3;\\n this._w = c1 * c2 * c3 - s1 * s2 * s3;\\n break;\\n case \\\\\\\"XZY\\\\\\\":\\n this._x = s1 * c2 * c3 - c1 * s2 * s3;\\n this._y = c1 * s2 * c3 - s1 * c2 * s3;\\n this._z = c1 * c2 * s3 + s1 * s2 * c3;\\n this._w = c1 * c2 * c3 + s1 * s2 * s3;\\n break;\\n default:\\n console.warn(\\\\\\\"THREE.Quaternion: .setFromEuler() encountered an unknown order: \\\\\\\" + order);\\n }\\n if (update !== false)\\n this._onChangeCallback();\\n return this;\\n }\\n setFromAxisAngle(axis, angle) {\\n const halfAngle = angle / 2, s = Math.sin(halfAngle);\\n this._x = axis.x * s;\\n this._y = axis.y * s;\\n this._z = axis.z * s;\\n this._w = Math.cos(halfAngle);\\n this._onChangeCallback();\\n return this;\\n }\\n setFromRotationMatrix(m) {\\n const te = m.elements, m11 = te[0], m12 = te[4], m13 = te[8], m21 = te[1], m22 = te[5], m23 = te[9], m31 = te[2], m32 = te[6], m33 = te[10], trace = m11 + m22 + m33;\\n if (trace > 0) {\\n const s = 0.5 / Math.sqrt(trace + 1);\\n this._w = 0.25 / s;\\n this._x = (m32 - m23) * s;\\n this._y = (m13 - m31) * s;\\n this._z = (m21 - m12) * s;\\n } else if (m11 > m22 && m11 > m33) {\\n const s = 2 * Math.sqrt(1 + m11 - m22 - m33);\\n this._w = (m32 - m23) / s;\\n this._x = 0.25 * s;\\n this._y = (m12 + m21) / s;\\n this._z = (m13 + m31) / s;\\n } else if (m22 > m33) {\\n const s = 2 * Math.sqrt(1 + m22 - m11 - m33);\\n this._w = (m13 - m31) / s;\\n this._x = (m12 + m21) / s;\\n this._y = 0.25 * s;\\n this._z = (m23 + m32) / s;\\n } else {\\n const s = 2 * Math.sqrt(1 + m33 - m11 - m22);\\n this._w = (m21 - m12) / s;\\n this._x = (m13 + m31) / s;\\n this._y = (m23 + m32) / s;\\n this._z = 0.25 * s;\\n }\\n this._onChangeCallback();\\n return this;\\n }\\n setFromUnitVectors(vFrom, vTo) {\\n let r = vFrom.dot(vTo) + 1;\\n if (r < Number.EPSILON) {\\n r = 0;\\n if (Math.abs(vFrom.x) > Math.abs(vFrom.z)) {\\n this._x = -vFrom.y;\\n this._y = vFrom.x;\\n this._z = 0;\\n this._w = r;\\n } else {\\n this._x = 0;\\n this._y = -vFrom.z;\\n this._z = vFrom.y;\\n this._w = r;\\n }\\n } else {\\n this._x = vFrom.y * vTo.z - vFrom.z * vTo.y;\\n this._y = vFrom.z * vTo.x - vFrom.x * vTo.z;\\n this._z = vFrom.x * vTo.y - vFrom.y * vTo.x;\\n this._w = r;\\n }\\n return this.normalize();\\n }\\n angleTo(q) {\\n return 2 * Math.acos(Math.abs(clamp(this.dot(q), -1, 1)));\\n }\\n rotateTowards(q, step) {\\n const angle = this.angleTo(q);\\n if (angle === 0)\\n return this;\\n const t = Math.min(1, step / angle);\\n this.slerp(q, t);\\n return this;\\n }\\n identity() {\\n return this.set(0, 0, 0, 1);\\n }\\n invert() {\\n return this.conjugate();\\n }\\n conjugate() {\\n this._x *= -1;\\n this._y *= -1;\\n this._z *= -1;\\n this._onChangeCallback();\\n return this;\\n }\\n dot(v) {\\n return this._x * v._x + this._y * v._y + this._z * v._z + this._w * v._w;\\n }\\n lengthSq() {\\n return this._x * this._x + this._y * this._y + this._z * this._z + this._w * this._w;\\n }\\n length() {\\n return Math.sqrt(this._x * this._x + this._y * this._y + this._z * this._z + this._w * this._w);\\n }\\n normalize() {\\n let l = this.length();\\n if (l === 0) {\\n this._x = 0;\\n this._y = 0;\\n this._z = 0;\\n this._w = 1;\\n } else {\\n l = 1 / l;\\n this._x = this._x * l;\\n this._y = this._y * l;\\n this._z = this._z * l;\\n this._w = this._w * l;\\n }\\n this._onChangeCallback();\\n return this;\\n }\\n multiply(q, p) {\\n if (p !== void 0) {\\n console.warn(\\\\\\\"THREE.Quaternion: .multiply() now only accepts one argument. Use .multiplyQuaternions( a, b ) instead.\\\\\\\");\\n return this.multiplyQuaternions(q, p);\\n }\\n return this.multiplyQuaternions(this, q);\\n }\\n premultiply(q) {\\n return this.multiplyQuaternions(q, this);\\n }\\n multiplyQuaternions(a, b) {\\n const qax = a._x, qay = a._y, qaz = a._z, qaw = a._w;\\n const qbx = b._x, qby = b._y, qbz = b._z, qbw = b._w;\\n this._x = qax * qbw + qaw * qbx + qay * qbz - qaz * qby;\\n this._y = qay * qbw + qaw * qby + qaz * qbx - qax * qbz;\\n this._z = qaz * qbw + qaw * qbz + qax * qby - qay * qbx;\\n this._w = qaw * qbw - qax * qbx - qay * qby - qaz * qbz;\\n this._onChangeCallback();\\n return this;\\n }\\n slerp(qb, t) {\\n if (t === 0)\\n return this;\\n if (t === 1)\\n return this.copy(qb);\\n const x = this._x, y = this._y, z = this._z, w = this._w;\\n let cosHalfTheta = w * qb._w + x * qb._x + y * qb._y + z * qb._z;\\n if (cosHalfTheta < 0) {\\n this._w = -qb._w;\\n this._x = -qb._x;\\n this._y = -qb._y;\\n this._z = -qb._z;\\n cosHalfTheta = -cosHalfTheta;\\n } else {\\n this.copy(qb);\\n }\\n if (cosHalfTheta >= 1) {\\n this._w = w;\\n this._x = x;\\n this._y = y;\\n this._z = z;\\n return this;\\n }\\n const sqrSinHalfTheta = 1 - cosHalfTheta * cosHalfTheta;\\n if (sqrSinHalfTheta <= Number.EPSILON) {\\n const s = 1 - t;\\n this._w = s * w + t * this._w;\\n this._x = s * x + t * this._x;\\n this._y = s * y + t * this._y;\\n this._z = s * z + t * this._z;\\n this.normalize();\\n this._onChangeCallback();\\n return this;\\n }\\n const sinHalfTheta = Math.sqrt(sqrSinHalfTheta);\\n const halfTheta = Math.atan2(sinHalfTheta, cosHalfTheta);\\n const ratioA = Math.sin((1 - t) * halfTheta) / sinHalfTheta, ratioB = Math.sin(t * halfTheta) / sinHalfTheta;\\n this._w = w * ratioA + this._w * ratioB;\\n this._x = x * ratioA + this._x * ratioB;\\n this._y = y * ratioA + this._y * ratioB;\\n this._z = z * ratioA + this._z * ratioB;\\n this._onChangeCallback();\\n return this;\\n }\\n slerpQuaternions(qa, qb, t) {\\n this.copy(qa).slerp(qb, t);\\n }\\n random() {\\n const u1 = Math.random();\\n const sqrt1u1 = Math.sqrt(1 - u1);\\n const sqrtu1 = Math.sqrt(u1);\\n const u2 = 2 * Math.PI * Math.random();\\n const u3 = 2 * Math.PI * Math.random();\\n return this.set(sqrt1u1 * Math.cos(u2), sqrtu1 * Math.sin(u3), sqrtu1 * Math.cos(u3), sqrt1u1 * Math.sin(u2));\\n }\\n equals(quaternion) {\\n return quaternion._x === this._x && quaternion._y === this._y && quaternion._z === this._z && quaternion._w === this._w;\\n }\\n fromArray(array, offset = 0) {\\n this._x = array[offset];\\n this._y = array[offset + 1];\\n this._z = array[offset + 2];\\n this._w = array[offset + 3];\\n this._onChangeCallback();\\n return this;\\n }\\n toArray(array = [], offset = 0) {\\n array[offset] = this._x;\\n array[offset + 1] = this._y;\\n array[offset + 2] = this._z;\\n array[offset + 3] = this._w;\\n return array;\\n }\\n fromBufferAttribute(attribute, index) {\\n this._x = attribute.getX(index);\\n this._y = attribute.getY(index);\\n this._z = attribute.getZ(index);\\n this._w = attribute.getW(index);\\n return this;\\n }\\n _onChange(callback) {\\n this._onChangeCallback = callback;\\n return this;\\n }\\n _onChangeCallback() {\\n }\\n};\\nQuaternion.prototype.isQuaternion = true;\\n\\n// ../../../node_modules/three/src/math/Vector3.js\\nvar Vector3 = class {\\n constructor(x = 0, y = 0, z = 0) {\\n this.x = x;\\n this.y = y;\\n this.z = z;\\n }\\n set(x, y, z) {\\n if (z === void 0)\\n z = this.z;\\n this.x = x;\\n this.y = y;\\n this.z = z;\\n return this;\\n }\\n setScalar(scalar) {\\n this.x = scalar;\\n this.y = scalar;\\n this.z = scalar;\\n return this;\\n }\\n setX(x) {\\n this.x = x;\\n return this;\\n }\\n setY(y) {\\n this.y = y;\\n return this;\\n }\\n setZ(z) {\\n this.z = z;\\n return this;\\n }\\n setComponent(index, value) {\\n switch (index) {\\n case 0:\\n this.x = value;\\n break;\\n case 1:\\n this.y = value;\\n break;\\n case 2:\\n this.z = value;\\n break;\\n default:\\n throw new Error(\\\\\\\"index is out of range: \\\\\\\" + index);\\n }\\n return this;\\n }\\n getComponent(index) {\\n switch (index) {\\n case 0:\\n return this.x;\\n case 1:\\n return this.y;\\n case 2:\\n return this.z;\\n default:\\n throw new Error(\\\\\\\"index is out of range: \\\\\\\" + index);\\n }\\n }\\n clone() {\\n return new this.constructor(this.x, this.y, this.z);\\n }\\n copy(v) {\\n this.x = v.x;\\n this.y = v.y;\\n this.z = v.z;\\n return this;\\n }\\n add(v, w) {\\n if (w !== void 0) {\\n console.warn(\\\\\\\"THREE.Vector3: .add() now only accepts one argument. Use .addVectors( a, b ) instead.\\\\\\\");\\n return this.addVectors(v, w);\\n }\\n this.x += v.x;\\n this.y += v.y;\\n this.z += v.z;\\n return this;\\n }\\n addScalar(s) {\\n this.x += s;\\n this.y += s;\\n this.z += s;\\n return this;\\n }\\n addVectors(a, b) {\\n this.x = a.x + b.x;\\n this.y = a.y + b.y;\\n this.z = a.z + b.z;\\n return this;\\n }\\n addScaledVector(v, s) {\\n this.x += v.x * s;\\n this.y += v.y * s;\\n this.z += v.z * s;\\n return this;\\n }\\n sub(v, w) {\\n if (w !== void 0) {\\n console.warn(\\\\\\\"THREE.Vector3: .sub() now only accepts one argument. Use .subVectors( a, b ) instead.\\\\\\\");\\n return this.subVectors(v, w);\\n }\\n this.x -= v.x;\\n this.y -= v.y;\\n this.z -= v.z;\\n return this;\\n }\\n subScalar(s) {\\n this.x -= s;\\n this.y -= s;\\n this.z -= s;\\n return this;\\n }\\n subVectors(a, b) {\\n this.x = a.x - b.x;\\n this.y = a.y - b.y;\\n this.z = a.z - b.z;\\n return this;\\n }\\n multiply(v, w) {\\n if (w !== void 0) {\\n console.warn(\\\\\\\"THREE.Vector3: .multiply() now only accepts one argument. Use .multiplyVectors( a, b ) instead.\\\\\\\");\\n return this.multiplyVectors(v, w);\\n }\\n this.x *= v.x;\\n this.y *= v.y;\\n this.z *= v.z;\\n return this;\\n }\\n multiplyScalar(scalar) {\\n this.x *= scalar;\\n this.y *= scalar;\\n this.z *= scalar;\\n return this;\\n }\\n multiplyVectors(a, b) {\\n this.x = a.x * b.x;\\n this.y = a.y * b.y;\\n this.z = a.z * b.z;\\n return this;\\n }\\n applyEuler(euler) {\\n if (!(euler && euler.isEuler)) {\\n console.error(\\\\\\\"THREE.Vector3: .applyEuler() now expects an Euler rotation rather than a Vector3 and order.\\\\\\\");\\n }\\n return this.applyQuaternion(_quaternion.setFromEuler(euler));\\n }\\n applyAxisAngle(axis, angle) {\\n return this.applyQuaternion(_quaternion.setFromAxisAngle(axis, angle));\\n }\\n applyMatrix3(m) {\\n const x = this.x, y = this.y, z = this.z;\\n const e = m.elements;\\n this.x = e[0] * x + e[3] * y + e[6] * z;\\n this.y = e[1] * x + e[4] * y + e[7] * z;\\n this.z = e[2] * x + e[5] * y + e[8] * z;\\n return this;\\n }\\n applyNormalMatrix(m) {\\n return this.applyMatrix3(m).normalize();\\n }\\n applyMatrix4(m) {\\n const x = this.x, y = this.y, z = this.z;\\n const e = m.elements;\\n const w = 1 / (e[3] * x + e[7] * y + e[11] * z + e[15]);\\n this.x = (e[0] * x + e[4] * y + e[8] * z + e[12]) * w;\\n this.y = (e[1] * x + e[5] * y + e[9] * z + e[13]) * w;\\n this.z = (e[2] * x + e[6] * y + e[10] * z + e[14]) * w;\\n return this;\\n }\\n applyQuaternion(q) {\\n const x = this.x, y = this.y, z = this.z;\\n const qx = q.x, qy = q.y, qz = q.z, qw = q.w;\\n const ix = qw * x + qy * z - qz * y;\\n const iy = qw * y + qz * x - qx * z;\\n const iz = qw * z + qx * y - qy * x;\\n const iw = -qx * x - qy * y - qz * z;\\n this.x = ix * qw + iw * -qx + iy * -qz - iz * -qy;\\n this.y = iy * qw + iw * -qy + iz * -qx - ix * -qz;\\n this.z = iz * qw + iw * -qz + ix * -qy - iy * -qx;\\n return this;\\n }\\n project(camera) {\\n return this.applyMatrix4(camera.matrixWorldInverse).applyMatrix4(camera.projectionMatrix);\\n }\\n unproject(camera) {\\n return this.applyMatrix4(camera.projectionMatrixInverse).applyMatrix4(camera.matrixWorld);\\n }\\n transformDirection(m) {\\n const x = this.x, y = this.y, z = this.z;\\n const e = m.elements;\\n this.x = e[0] * x + e[4] * y + e[8] * z;\\n this.y = e[1] * x + e[5] * y + e[9] * z;\\n this.z = e[2] * x + e[6] * y + e[10] * z;\\n return this.normalize();\\n }\\n divide(v) {\\n this.x /= v.x;\\n this.y /= v.y;\\n this.z /= v.z;\\n return this;\\n }\\n divideScalar(scalar) {\\n return this.multiplyScalar(1 / scalar);\\n }\\n min(v) {\\n this.x = Math.min(this.x, v.x);\\n this.y = Math.min(this.y, v.y);\\n this.z = Math.min(this.z, v.z);\\n return this;\\n }\\n max(v) {\\n this.x = Math.max(this.x, v.x);\\n this.y = Math.max(this.y, v.y);\\n this.z = Math.max(this.z, v.z);\\n return this;\\n }\\n clamp(min, max) {\\n this.x = Math.max(min.x, Math.min(max.x, this.x));\\n this.y = Math.max(min.y, Math.min(max.y, this.y));\\n this.z = Math.max(min.z, Math.min(max.z, this.z));\\n return this;\\n }\\n clampScalar(minVal, maxVal) {\\n this.x = Math.max(minVal, Math.min(maxVal, this.x));\\n this.y = Math.max(minVal, Math.min(maxVal, this.y));\\n this.z = Math.max(minVal, Math.min(maxVal, this.z));\\n return this;\\n }\\n clampLength(min, max) {\\n const length = this.length();\\n return this.divideScalar(length || 1).multiplyScalar(Math.max(min, Math.min(max, length)));\\n }\\n floor() {\\n this.x = Math.floor(this.x);\\n this.y = Math.floor(this.y);\\n this.z = Math.floor(this.z);\\n return this;\\n }\\n ceil() {\\n this.x = Math.ceil(this.x);\\n this.y = Math.ceil(this.y);\\n this.z = Math.ceil(this.z);\\n return this;\\n }\\n round() {\\n this.x = Math.round(this.x);\\n this.y = Math.round(this.y);\\n this.z = Math.round(this.z);\\n return this;\\n }\\n roundToZero() {\\n this.x = this.x < 0 ? Math.ceil(this.x) : Math.floor(this.x);\\n this.y = this.y < 0 ? Math.ceil(this.y) : Math.floor(this.y);\\n this.z = this.z < 0 ? Math.ceil(this.z) : Math.floor(this.z);\\n return this;\\n }\\n negate() {\\n this.x = -this.x;\\n this.y = -this.y;\\n this.z = -this.z;\\n return this;\\n }\\n dot(v) {\\n return this.x * v.x + this.y * v.y + this.z * v.z;\\n }\\n lengthSq() {\\n return this.x * this.x + this.y * this.y + this.z * this.z;\\n }\\n length() {\\n return Math.sqrt(this.x * this.x + this.y * this.y + this.z * this.z);\\n }\\n manhattanLength() {\\n return Math.abs(this.x) + Math.abs(this.y) + Math.abs(this.z);\\n }\\n normalize() {\\n return this.divideScalar(this.length() || 1);\\n }\\n setLength(length) {\\n return this.normalize().multiplyScalar(length);\\n }\\n lerp(v, alpha) {\\n this.x += (v.x - this.x) * alpha;\\n this.y += (v.y - this.y) * alpha;\\n this.z += (v.z - this.z) * alpha;\\n return this;\\n }\\n lerpVectors(v1, v2, alpha) {\\n this.x = v1.x + (v2.x - v1.x) * alpha;\\n this.y = v1.y + (v2.y - v1.y) * alpha;\\n this.z = v1.z + (v2.z - v1.z) * alpha;\\n return this;\\n }\\n cross(v, w) {\\n if (w !== void 0) {\\n console.warn(\\\\\\\"THREE.Vector3: .cross() now only accepts one argument. Use .crossVectors( a, b ) instead.\\\\\\\");\\n return this.crossVectors(v, w);\\n }\\n return this.crossVectors(this, v);\\n }\\n crossVectors(a, b) {\\n const ax = a.x, ay = a.y, az = a.z;\\n const bx = b.x, by = b.y, bz = b.z;\\n this.x = ay * bz - az * by;\\n this.y = az * bx - ax * bz;\\n this.z = ax * by - ay * bx;\\n return this;\\n }\\n projectOnVector(v) {\\n const denominator = v.lengthSq();\\n if (denominator === 0)\\n return this.set(0, 0, 0);\\n const scalar = v.dot(this) / denominator;\\n return this.copy(v).multiplyScalar(scalar);\\n }\\n projectOnPlane(planeNormal) {\\n _vector.copy(this).projectOnVector(planeNormal);\\n return this.sub(_vector);\\n }\\n reflect(normal) {\\n return this.sub(_vector.copy(normal).multiplyScalar(2 * this.dot(normal)));\\n }\\n angleTo(v) {\\n const denominator = Math.sqrt(this.lengthSq() * v.lengthSq());\\n if (denominator === 0)\\n return Math.PI / 2;\\n const theta = this.dot(v) / denominator;\\n return Math.acos(clamp(theta, -1, 1));\\n }\\n distanceTo(v) {\\n return Math.sqrt(this.distanceToSquared(v));\\n }\\n distanceToSquared(v) {\\n const dx = this.x - v.x, dy = this.y - v.y, dz = this.z - v.z;\\n return dx * dx + dy * dy + dz * dz;\\n }\\n manhattanDistanceTo(v) {\\n return Math.abs(this.x - v.x) + Math.abs(this.y - v.y) + Math.abs(this.z - v.z);\\n }\\n setFromSpherical(s) {\\n return this.setFromSphericalCoords(s.radius, s.phi, s.theta);\\n }\\n setFromSphericalCoords(radius, phi, theta) {\\n const sinPhiRadius = Math.sin(phi) * radius;\\n this.x = sinPhiRadius * Math.sin(theta);\\n this.y = Math.cos(phi) * radius;\\n this.z = sinPhiRadius * Math.cos(theta);\\n return this;\\n }\\n setFromCylindrical(c) {\\n return this.setFromCylindricalCoords(c.radius, c.theta, c.y);\\n }\\n setFromCylindricalCoords(radius, theta, y) {\\n this.x = radius * Math.sin(theta);\\n this.y = y;\\n this.z = radius * Math.cos(theta);\\n return this;\\n }\\n setFromMatrixPosition(m) {\\n const e = m.elements;\\n this.x = e[12];\\n this.y = e[13];\\n this.z = e[14];\\n return this;\\n }\\n setFromMatrixScale(m) {\\n const sx = this.setFromMatrixColumn(m, 0).length();\\n const sy = this.setFromMatrixColumn(m, 1).length();\\n const sz = this.setFromMatrixColumn(m, 2).length();\\n this.x = sx;\\n this.y = sy;\\n this.z = sz;\\n return this;\\n }\\n setFromMatrixColumn(m, index) {\\n return this.fromArray(m.elements, index * 4);\\n }\\n setFromMatrix3Column(m, index) {\\n return this.fromArray(m.elements, index * 3);\\n }\\n equals(v) {\\n return v.x === this.x && v.y === this.y && v.z === this.z;\\n }\\n fromArray(array, offset = 0) {\\n this.x = array[offset];\\n this.y = array[offset + 1];\\n this.z = array[offset + 2];\\n return this;\\n }\\n toArray(array = [], offset = 0) {\\n array[offset] = this.x;\\n array[offset + 1] = this.y;\\n array[offset + 2] = this.z;\\n return array;\\n }\\n fromBufferAttribute(attribute, index, offset) {\\n if (offset !== void 0) {\\n console.warn(\\\\\\\"THREE.Vector3: offset has been removed from .fromBufferAttribute().\\\\\\\");\\n }\\n this.x = attribute.getX(index);\\n this.y = attribute.getY(index);\\n this.z = attribute.getZ(index);\\n return this;\\n }\\n random() {\\n this.x = Math.random();\\n this.y = Math.random();\\n this.z = Math.random();\\n return this;\\n }\\n randomDirection() {\\n const u = (Math.random() - 0.5) * 2;\\n const t = Math.random() * Math.PI * 2;\\n const f = Math.sqrt(1 - u ** 2);\\n this.x = f * Math.cos(t);\\n this.y = f * Math.sin(t);\\n this.z = u;\\n return this;\\n }\\n *[Symbol.iterator]() {\\n yield this.x;\\n yield this.y;\\n yield this.z;\\n }\\n};\\nVector3.prototype.isVector3 = true;\\nvar _vector = /* @__PURE__ */ new Vector3();\\nvar _quaternion = /* @__PURE__ */ new Quaternion();\\n\\n// ../../../node_modules/three/src/math/Matrix4.js\\nvar Matrix4 = class {\\n constructor() {\\n this.elements = [\\n 1,\\n 0,\\n 0,\\n 0,\\n 0,\\n 1,\\n 0,\\n 0,\\n 0,\\n 0,\\n 1,\\n 0,\\n 0,\\n 0,\\n 0,\\n 1\\n ];\\n if (arguments.length > 0) {\\n console.error(\\\\\\\"THREE.Matrix4: the constructor no longer reads arguments. use .set() instead.\\\\\\\");\\n }\\n }\\n set(n11, n12, n13, n14, n21, n22, n23, n24, n31, n32, n33, n34, n41, n42, n43, n44) {\\n const te = this.elements;\\n te[0] = n11;\\n te[4] = n12;\\n te[8] = n13;\\n te[12] = n14;\\n te[1] = n21;\\n te[5] = n22;\\n te[9] = n23;\\n te[13] = n24;\\n te[2] = n31;\\n te[6] = n32;\\n te[10] = n33;\\n te[14] = n34;\\n te[3] = n41;\\n te[7] = n42;\\n te[11] = n43;\\n te[15] = n44;\\n return this;\\n }\\n identity() {\\n this.set(1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1);\\n return this;\\n }\\n clone() {\\n return new Matrix4().fromArray(this.elements);\\n }\\n copy(m) {\\n const te = this.elements;\\n const me = m.elements;\\n te[0] = me[0];\\n te[1] = me[1];\\n te[2] = me[2];\\n te[3] = me[3];\\n te[4] = me[4];\\n te[5] = me[5];\\n te[6] = me[6];\\n te[7] = me[7];\\n te[8] = me[8];\\n te[9] = me[9];\\n te[10] = me[10];\\n te[11] = me[11];\\n te[12] = me[12];\\n te[13] = me[13];\\n te[14] = me[14];\\n te[15] = me[15];\\n return this;\\n }\\n copyPosition(m) {\\n const te = this.elements, me = m.elements;\\n te[12] = me[12];\\n te[13] = me[13];\\n te[14] = me[14];\\n return this;\\n }\\n setFromMatrix3(m) {\\n const me = m.elements;\\n this.set(me[0], me[3], me[6], 0, me[1], me[4], me[7], 0, me[2], me[5], me[8], 0, 0, 0, 0, 1);\\n return this;\\n }\\n extractBasis(xAxis, yAxis, zAxis) {\\n xAxis.setFromMatrixColumn(this, 0);\\n yAxis.setFromMatrixColumn(this, 1);\\n zAxis.setFromMatrixColumn(this, 2);\\n return this;\\n }\\n makeBasis(xAxis, yAxis, zAxis) {\\n this.set(xAxis.x, yAxis.x, zAxis.x, 0, xAxis.y, yAxis.y, zAxis.y, 0, xAxis.z, yAxis.z, zAxis.z, 0, 0, 0, 0, 1);\\n return this;\\n }\\n extractRotation(m) {\\n const te = this.elements;\\n const me = m.elements;\\n const scaleX = 1 / _v1.setFromMatrixColumn(m, 0).length();\\n const scaleY = 1 / _v1.setFromMatrixColumn(m, 1).length();\\n const scaleZ = 1 / _v1.setFromMatrixColumn(m, 2).length();\\n te[0] = me[0] * scaleX;\\n te[1] = me[1] * scaleX;\\n te[2] = me[2] * scaleX;\\n te[3] = 0;\\n te[4] = me[4] * scaleY;\\n te[5] = me[5] * scaleY;\\n te[6] = me[6] * scaleY;\\n te[7] = 0;\\n te[8] = me[8] * scaleZ;\\n te[9] = me[9] * scaleZ;\\n te[10] = me[10] * scaleZ;\\n te[11] = 0;\\n te[12] = 0;\\n te[13] = 0;\\n te[14] = 0;\\n te[15] = 1;\\n return this;\\n }\\n makeRotationFromEuler(euler) {\\n if (!(euler && euler.isEuler)) {\\n console.error(\\\\\\\"THREE.Matrix4: .makeRotationFromEuler() now expects a Euler rotation rather than a Vector3 and order.\\\\\\\");\\n }\\n const te = this.elements;\\n const x = euler.x, y = euler.y, z = euler.z;\\n const a = Math.cos(x), b = Math.sin(x);\\n const c = Math.cos(y), d = Math.sin(y);\\n const e = Math.cos(z), f = Math.sin(z);\\n if (euler.order === \\\\\\\"XYZ\\\\\\\") {\\n const ae = a * e, af = a * f, be = b * e, bf = b * f;\\n te[0] = c * e;\\n te[4] = -c * f;\\n te[8] = d;\\n te[1] = af + be * d;\\n te[5] = ae - bf * d;\\n te[9] = -b * c;\\n te[2] = bf - ae * d;\\n te[6] = be + af * d;\\n te[10] = a * c;\\n } else if (euler.order === \\\\\\\"YXZ\\\\\\\") {\\n const ce = c * e, cf = c * f, de = d * e, df = d * f;\\n te[0] = ce + df * b;\\n te[4] = de * b - cf;\\n te[8] = a * d;\\n te[1] = a * f;\\n te[5] = a * e;\\n te[9] = -b;\\n te[2] = cf * b - de;\\n te[6] = df + ce * b;\\n te[10] = a * c;\\n } else if (euler.order === \\\\\\\"ZXY\\\\\\\") {\\n const ce = c * e, cf = c * f, de = d * e, df = d * f;\\n te[0] = ce - df * b;\\n te[4] = -a * f;\\n te[8] = de + cf * b;\\n te[1] = cf + de * b;\\n te[5] = a * e;\\n te[9] = df - ce * b;\\n te[2] = -a * d;\\n te[6] = b;\\n te[10] = a * c;\\n } else if (euler.order === \\\\\\\"ZYX\\\\\\\") {\\n const ae = a * e, af = a * f, be = b * e, bf = b * f;\\n te[0] = c * e;\\n te[4] = be * d - af;\\n te[8] = ae * d + bf;\\n te[1] = c * f;\\n te[5] = bf * d + ae;\\n te[9] = af * d - be;\\n te[2] = -d;\\n te[6] = b * c;\\n te[10] = a * c;\\n } else if (euler.order === \\\\\\\"YZX\\\\\\\") {\\n const ac = a * c, ad = a * d, bc = b * c, bd = b * d;\\n te[0] = c * e;\\n te[4] = bd - ac * f;\\n te[8] = bc * f + ad;\\n te[1] = f;\\n te[5] = a * e;\\n te[9] = -b * e;\\n te[2] = -d * e;\\n te[6] = ad * f + bc;\\n te[10] = ac - bd * f;\\n } else if (euler.order === \\\\\\\"XZY\\\\\\\") {\\n const ac = a * c, ad = a * d, bc = b * c, bd = b * d;\\n te[0] = c * e;\\n te[4] = -f;\\n te[8] = d * e;\\n te[1] = ac * f + bd;\\n te[5] = a * e;\\n te[9] = ad * f - bc;\\n te[2] = bc * f - ad;\\n te[6] = b * e;\\n te[10] = bd * f + ac;\\n }\\n te[3] = 0;\\n te[7] = 0;\\n te[11] = 0;\\n te[12] = 0;\\n te[13] = 0;\\n te[14] = 0;\\n te[15] = 1;\\n return this;\\n }\\n makeRotationFromQuaternion(q) {\\n return this.compose(_zero, q, _one);\\n }\\n lookAt(eye, target, up) {\\n const te = this.elements;\\n _z.subVectors(eye, target);\\n if (_z.lengthSq() === 0) {\\n _z.z = 1;\\n }\\n _z.normalize();\\n _x.crossVectors(up, _z);\\n if (_x.lengthSq() === 0) {\\n if (Math.abs(up.z) === 1) {\\n _z.x += 1e-4;\\n } else {\\n _z.z += 1e-4;\\n }\\n _z.normalize();\\n _x.crossVectors(up, _z);\\n }\\n _x.normalize();\\n _y.crossVectors(_z, _x);\\n te[0] = _x.x;\\n te[4] = _y.x;\\n te[8] = _z.x;\\n te[1] = _x.y;\\n te[5] = _y.y;\\n te[9] = _z.y;\\n te[2] = _x.z;\\n te[6] = _y.z;\\n te[10] = _z.z;\\n return this;\\n }\\n multiply(m, n) {\\n if (n !== void 0) {\\n console.warn(\\\\\\\"THREE.Matrix4: .multiply() now only accepts one argument. Use .multiplyMatrices( a, b ) instead.\\\\\\\");\\n return this.multiplyMatrices(m, n);\\n }\\n return this.multiplyMatrices(this, m);\\n }\\n premultiply(m) {\\n return this.multiplyMatrices(m, this);\\n }\\n multiplyMatrices(a, b) {\\n const ae = a.elements;\\n const be = b.elements;\\n const te = this.elements;\\n const a11 = ae[0], a12 = ae[4], a13 = ae[8], a14 = ae[12];\\n const a21 = ae[1], a22 = ae[5], a23 = ae[9], a24 = ae[13];\\n const a31 = ae[2], a32 = ae[6], a33 = ae[10], a34 = ae[14];\\n const a41 = ae[3], a42 = ae[7], a43 = ae[11], a44 = ae[15];\\n const b11 = be[0], b12 = be[4], b13 = be[8], b14 = be[12];\\n const b21 = be[1], b22 = be[5], b23 = be[9], b24 = be[13];\\n const b31 = be[2], b32 = be[6], b33 = be[10], b34 = be[14];\\n const b41 = be[3], b42 = be[7], b43 = be[11], b44 = be[15];\\n te[0] = a11 * b11 + a12 * b21 + a13 * b31 + a14 * b41;\\n te[4] = a11 * b12 + a12 * b22 + a13 * b32 + a14 * b42;\\n te[8] = a11 * b13 + a12 * b23 + a13 * b33 + a14 * b43;\\n te[12] = a11 * b14 + a12 * b24 + a13 * b34 + a14 * b44;\\n te[1] = a21 * b11 + a22 * b21 + a23 * b31 + a24 * b41;\\n te[5] = a21 * b12 + a22 * b22 + a23 * b32 + a24 * b42;\\n te[9] = a21 * b13 + a22 * b23 + a23 * b33 + a24 * b43;\\n te[13] = a21 * b14 + a22 * b24 + a23 * b34 + a24 * b44;\\n te[2] = a31 * b11 + a32 * b21 + a33 * b31 + a34 * b41;\\n te[6] = a31 * b12 + a32 * b22 + a33 * b32 + a34 * b42;\\n te[10] = a31 * b13 + a32 * b23 + a33 * b33 + a34 * b43;\\n te[14] = a31 * b14 + a32 * b24 + a33 * b34 + a34 * b44;\\n te[3] = a41 * b11 + a42 * b21 + a43 * b31 + a44 * b41;\\n te[7] = a41 * b12 + a42 * b22 + a43 * b32 + a44 * b42;\\n te[11] = a41 * b13 + a42 * b23 + a43 * b33 + a44 * b43;\\n te[15] = a41 * b14 + a42 * b24 + a43 * b34 + a44 * b44;\\n return this;\\n }\\n multiplyScalar(s) {\\n const te = this.elements;\\n te[0] *= s;\\n te[4] *= s;\\n te[8] *= s;\\n te[12] *= s;\\n te[1] *= s;\\n te[5] *= s;\\n te[9] *= s;\\n te[13] *= s;\\n te[2] *= s;\\n te[6] *= s;\\n te[10] *= s;\\n te[14] *= s;\\n te[3] *= s;\\n te[7] *= s;\\n te[11] *= s;\\n te[15] *= s;\\n return this;\\n }\\n determinant() {\\n const te = this.elements;\\n const n11 = te[0], n12 = te[4], n13 = te[8], n14 = te[12];\\n const n21 = te[1], n22 = te[5], n23 = te[9], n24 = te[13];\\n const n31 = te[2], n32 = te[6], n33 = te[10], n34 = te[14];\\n const n41 = te[3], n42 = te[7], n43 = te[11], n44 = te[15];\\n return n41 * (+n14 * n23 * n32 - n13 * n24 * n32 - n14 * n22 * n33 + n12 * n24 * n33 + n13 * n22 * n34 - n12 * n23 * n34) + n42 * (+n11 * n23 * n34 - n11 * n24 * n33 + n14 * n21 * n33 - n13 * n21 * n34 + n13 * n24 * n31 - n14 * n23 * n31) + n43 * (+n11 * n24 * n32 - n11 * n22 * n34 - n14 * n21 * n32 + n12 * n21 * n34 + n14 * n22 * n31 - n12 * n24 * n31) + n44 * (-n13 * n22 * n31 - n11 * n23 * n32 + n11 * n22 * n33 + n13 * n21 * n32 - n12 * n21 * n33 + n12 * n23 * n31);\\n }\\n transpose() {\\n const te = this.elements;\\n let tmp;\\n tmp = te[1];\\n te[1] = te[4];\\n te[4] = tmp;\\n tmp = te[2];\\n te[2] = te[8];\\n te[8] = tmp;\\n tmp = te[6];\\n te[6] = te[9];\\n te[9] = tmp;\\n tmp = te[3];\\n te[3] = te[12];\\n te[12] = tmp;\\n tmp = te[7];\\n te[7] = te[13];\\n te[13] = tmp;\\n tmp = te[11];\\n te[11] = te[14];\\n te[14] = tmp;\\n return this;\\n }\\n setPosition(x, y, z) {\\n const te = this.elements;\\n if (x.isVector3) {\\n te[12] = x.x;\\n te[13] = x.y;\\n te[14] = x.z;\\n } else {\\n te[12] = x;\\n te[13] = y;\\n te[14] = z;\\n }\\n return this;\\n }\\n invert() {\\n const te = this.elements, n11 = te[0], n21 = te[1], n31 = te[2], n41 = te[3], n12 = te[4], n22 = te[5], n32 = te[6], n42 = te[7], n13 = te[8], n23 = te[9], n33 = te[10], n43 = te[11], n14 = te[12], n24 = te[13], n34 = te[14], n44 = te[15], t11 = n23 * n34 * n42 - n24 * n33 * n42 + n24 * n32 * n43 - n22 * n34 * n43 - n23 * n32 * n44 + n22 * n33 * n44, t12 = n14 * n33 * n42 - n13 * n34 * n42 - n14 * n32 * n43 + n12 * n34 * n43 + n13 * n32 * n44 - n12 * n33 * n44, t13 = n13 * n24 * n42 - n14 * n23 * n42 + n14 * n22 * n43 - n12 * n24 * n43 - n13 * n22 * n44 + n12 * n23 * n44, t14 = n14 * n23 * n32 - n13 * n24 * n32 - n14 * n22 * n33 + n12 * n24 * n33 + n13 * n22 * n34 - n12 * n23 * n34;\\n const det = n11 * t11 + n21 * t12 + n31 * t13 + n41 * t14;\\n if (det === 0)\\n return this.set(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0);\\n const detInv = 1 / det;\\n te[0] = t11 * detInv;\\n te[1] = (n24 * n33 * n41 - n23 * n34 * n41 - n24 * n31 * n43 + n21 * n34 * n43 + n23 * n31 * n44 - n21 * n33 * n44) * detInv;\\n te[2] = (n22 * n34 * n41 - n24 * n32 * n41 + n24 * n31 * n42 - n21 * n34 * n42 - n22 * n31 * n44 + n21 * n32 * n44) * detInv;\\n te[3] = (n23 * n32 * n41 - n22 * n33 * n41 - n23 * n31 * n42 + n21 * n33 * n42 + n22 * n31 * n43 - n21 * n32 * n43) * detInv;\\n te[4] = t12 * detInv;\\n te[5] = (n13 * n34 * n41 - n14 * n33 * n41 + n14 * n31 * n43 - n11 * n34 * n43 - n13 * n31 * n44 + n11 * n33 * n44) * detInv;\\n te[6] = (n14 * n32 * n41 - n12 * n34 * n41 - n14 * n31 * n42 + n11 * n34 * n42 + n12 * n31 * n44 - n11 * n32 * n44) * detInv;\\n te[7] = (n12 * n33 * n41 - n13 * n32 * n41 + n13 * n31 * n42 - n11 * n33 * n42 - n12 * n31 * n43 + n11 * n32 * n43) * detInv;\\n te[8] = t13 * detInv;\\n te[9] = (n14 * n23 * n41 - n13 * n24 * n41 - n14 * n21 * n43 + n11 * n24 * n43 + n13 * n21 * n44 - n11 * n23 * n44) * detInv;\\n te[10] = (n12 * n24 * n41 - n14 * n22 * n41 + n14 * n21 * n42 - n11 * n24 * n42 - n12 * n21 * n44 + n11 * n22 * n44) * detInv;\\n te[11] = (n13 * n22 * n41 - n12 * n23 * n41 - n13 * n21 * n42 + n11 * n23 * n42 + n12 * n21 * n43 - n11 * n22 * n43) * detInv;\\n te[12] = t14 * detInv;\\n te[13] = (n13 * n24 * n31 - n14 * n23 * n31 + n14 * n21 * n33 - n11 * n24 * n33 - n13 * n21 * n34 + n11 * n23 * n34) * detInv;\\n te[14] = (n14 * n22 * n31 - n12 * n24 * n31 - n14 * n21 * n32 + n11 * n24 * n32 + n12 * n21 * n34 - n11 * n22 * n34) * detInv;\\n te[15] = (n12 * n23 * n31 - n13 * n22 * n31 + n13 * n21 * n32 - n11 * n23 * n32 - n12 * n21 * n33 + n11 * n22 * n33) * detInv;\\n return this;\\n }\\n scale(v) {\\n const te = this.elements;\\n const x = v.x, y = v.y, z = v.z;\\n te[0] *= x;\\n te[4] *= y;\\n te[8] *= z;\\n te[1] *= x;\\n te[5] *= y;\\n te[9] *= z;\\n te[2] *= x;\\n te[6] *= y;\\n te[10] *= z;\\n te[3] *= x;\\n te[7] *= y;\\n te[11] *= z;\\n return this;\\n }\\n getMaxScaleOnAxis() {\\n const te = this.elements;\\n const scaleXSq = te[0] * te[0] + te[1] * te[1] + te[2] * te[2];\\n const scaleYSq = te[4] * te[4] + te[5] * te[5] + te[6] * te[6];\\n const scaleZSq = te[8] * te[8] + te[9] * te[9] + te[10] * te[10];\\n return Math.sqrt(Math.max(scaleXSq, scaleYSq, scaleZSq));\\n }\\n makeTranslation(x, y, z) {\\n this.set(1, 0, 0, x, 0, 1, 0, y, 0, 0, 1, z, 0, 0, 0, 1);\\n return this;\\n }\\n makeRotationX(theta) {\\n const c = Math.cos(theta), s = Math.sin(theta);\\n this.set(1, 0, 0, 0, 0, c, -s, 0, 0, s, c, 0, 0, 0, 0, 1);\\n return this;\\n }\\n makeRotationY(theta) {\\n const c = Math.cos(theta), s = Math.sin(theta);\\n this.set(c, 0, s, 0, 0, 1, 0, 0, -s, 0, c, 0, 0, 0, 0, 1);\\n return this;\\n }\\n makeRotationZ(theta) {\\n const c = Math.cos(theta), s = Math.sin(theta);\\n this.set(c, -s, 0, 0, s, c, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1);\\n return this;\\n }\\n makeRotationAxis(axis, angle) {\\n const c = Math.cos(angle);\\n const s = Math.sin(angle);\\n const t = 1 - c;\\n const x = axis.x, y = axis.y, z = axis.z;\\n const tx = t * x, ty = t * y;\\n this.set(tx * x + c, tx * y - s * z, tx * z + s * y, 0, tx * y + s * z, ty * y + c, ty * z - s * x, 0, tx * z - s * y, ty * z + s * x, t * z * z + c, 0, 0, 0, 0, 1);\\n return this;\\n }\\n makeScale(x, y, z) {\\n this.set(x, 0, 0, 0, 0, y, 0, 0, 0, 0, z, 0, 0, 0, 0, 1);\\n return this;\\n }\\n makeShear(xy, xz, yx, yz, zx, zy) {\\n this.set(1, yx, zx, 0, xy, 1, zy, 0, xz, yz, 1, 0, 0, 0, 0, 1);\\n return this;\\n }\\n compose(position, quaternion, scale) {\\n const te = this.elements;\\n const x = quaternion._x, y = quaternion._y, z = quaternion._z, w = quaternion._w;\\n const x2 = x + x, y2 = y + y, z2 = z + z;\\n const xx = x * x2, xy = x * y2, xz = x * z2;\\n const yy = y * y2, yz = y * z2, zz = z * z2;\\n const wx = w * x2, wy = w * y2, wz = w * z2;\\n const sx = scale.x, sy = scale.y, sz = scale.z;\\n te[0] = (1 - (yy + zz)) * sx;\\n te[1] = (xy + wz) * sx;\\n te[2] = (xz - wy) * sx;\\n te[3] = 0;\\n te[4] = (xy - wz) * sy;\\n te[5] = (1 - (xx + zz)) * sy;\\n te[6] = (yz + wx) * sy;\\n te[7] = 0;\\n te[8] = (xz + wy) * sz;\\n te[9] = (yz - wx) * sz;\\n te[10] = (1 - (xx + yy)) * sz;\\n te[11] = 0;\\n te[12] = position.x;\\n te[13] = position.y;\\n te[14] = position.z;\\n te[15] = 1;\\n return this;\\n }\\n decompose(position, quaternion, scale) {\\n const te = this.elements;\\n let sx = _v1.set(te[0], te[1], te[2]).length();\\n const sy = _v1.set(te[4], te[5], te[6]).length();\\n const sz = _v1.set(te[8], te[9], te[10]).length();\\n const det = this.determinant();\\n if (det < 0)\\n sx = -sx;\\n position.x = te[12];\\n position.y = te[13];\\n position.z = te[14];\\n _m1.copy(this);\\n const invSX = 1 / sx;\\n const invSY = 1 / sy;\\n const invSZ = 1 / sz;\\n _m1.elements[0] *= invSX;\\n _m1.elements[1] *= invSX;\\n _m1.elements[2] *= invSX;\\n _m1.elements[4] *= invSY;\\n _m1.elements[5] *= invSY;\\n _m1.elements[6] *= invSY;\\n _m1.elements[8] *= invSZ;\\n _m1.elements[9] *= invSZ;\\n _m1.elements[10] *= invSZ;\\n quaternion.setFromRotationMatrix(_m1);\\n scale.x = sx;\\n scale.y = sy;\\n scale.z = sz;\\n return this;\\n }\\n makePerspective(left, right, top, bottom, near, far) {\\n if (far === void 0) {\\n console.warn(\\\\\\\"THREE.Matrix4: .makePerspective() has been redefined and has a new signature. Please check the docs.\\\\\\\");\\n }\\n const te = this.elements;\\n const x = 2 * near / (right - left);\\n const y = 2 * near / (top - bottom);\\n const a = (right + left) / (right - left);\\n const b = (top + bottom) / (top - bottom);\\n const c = -(far + near) / (far - near);\\n const d = -2 * far * near / (far - near);\\n te[0] = x;\\n te[4] = 0;\\n te[8] = a;\\n te[12] = 0;\\n te[1] = 0;\\n te[5] = y;\\n te[9] = b;\\n te[13] = 0;\\n te[2] = 0;\\n te[6] = 0;\\n te[10] = c;\\n te[14] = d;\\n te[3] = 0;\\n te[7] = 0;\\n te[11] = -1;\\n te[15] = 0;\\n return this;\\n }\\n makeOrthographic(left, right, top, bottom, near, far) {\\n const te = this.elements;\\n const w = 1 / (right - left);\\n const h = 1 / (top - bottom);\\n const p = 1 / (far - near);\\n const x = (right + left) * w;\\n const y = (top + bottom) * h;\\n const z = (far + near) * p;\\n te[0] = 2 * w;\\n te[4] = 0;\\n te[8] = 0;\\n te[12] = -x;\\n te[1] = 0;\\n te[5] = 2 * h;\\n te[9] = 0;\\n te[13] = -y;\\n te[2] = 0;\\n te[6] = 0;\\n te[10] = -2 * p;\\n te[14] = -z;\\n te[3] = 0;\\n te[7] = 0;\\n te[11] = 0;\\n te[15] = 1;\\n return this;\\n }\\n equals(matrix) {\\n const te = this.elements;\\n const me = matrix.elements;\\n for (let i = 0; i < 16; i++) {\\n if (te[i] !== me[i])\\n return false;\\n }\\n return true;\\n }\\n fromArray(array, offset = 0) {\\n for (let i = 0; i < 16; i++) {\\n this.elements[i] = array[i + offset];\\n }\\n return this;\\n }\\n toArray(array = [], offset = 0) {\\n const te = this.elements;\\n array[offset] = te[0];\\n array[offset + 1] = te[1];\\n array[offset + 2] = te[2];\\n array[offset + 3] = te[3];\\n array[offset + 4] = te[4];\\n array[offset + 5] = te[5];\\n array[offset + 6] = te[6];\\n array[offset + 7] = te[7];\\n array[offset + 8] = te[8];\\n array[offset + 9] = te[9];\\n array[offset + 10] = te[10];\\n array[offset + 11] = te[11];\\n array[offset + 12] = te[12];\\n array[offset + 13] = te[13];\\n array[offset + 14] = te[14];\\n array[offset + 15] = te[15];\\n return array;\\n }\\n};\\nMatrix4.prototype.isMatrix4 = true;\\nvar _v1 = /* @__PURE__ */ new Vector3();\\nvar _m1 = /* @__PURE__ */ new Matrix4();\\nvar _zero = /* @__PURE__ */ new Vector3(0, 0, 0);\\nvar _one = /* @__PURE__ */ new Vector3(1, 1, 1);\\nvar _x = /* @__PURE__ */ new Vector3();\\nvar _y = /* @__PURE__ */ new Vector3();\\nvar _z = /* @__PURE__ */ new Vector3();\\n\\n// ../../../node_modules/three/src/core/EventDispatcher.js\\nvar EventDispatcher = class {\\n addEventListener(type, listener) {\\n if (this._listeners === void 0)\\n this._listeners = {};\\n const listeners = this._listeners;\\n if (listeners[type] === void 0) {\\n listeners[type] = [];\\n }\\n if (listeners[type].indexOf(listener) === -1) {\\n listeners[type].push(listener);\\n }\\n }\\n hasEventListener(type, listener) {\\n if (this._listeners === void 0)\\n return false;\\n const listeners = this._listeners;\\n return listeners[type] !== void 0 && listeners[type].indexOf(listener) !== -1;\\n }\\n removeEventListener(type, listener) {\\n if (this._listeners === void 0)\\n return;\\n const listeners = this._listeners;\\n const listenerArray = listeners[type];\\n if (listenerArray !== void 0) {\\n const index = listenerArray.indexOf(listener);\\n if (index !== -1) {\\n listenerArray.splice(index, 1);\\n }\\n }\\n }\\n dispatchEvent(event) {\\n if (this._listeners === void 0)\\n return;\\n const listeners = this._listeners;\\n const listenerArray = listeners[event.type];\\n if (listenerArray !== void 0) {\\n event.target = this;\\n const array = listenerArray.slice(0);\\n for (let i = 0, l = array.length; i < l; i++) {\\n array[i].call(this, event);\\n }\\n event.target = null;\\n }\\n }\\n};\\n\\n// ../../../node_modules/three/src/math/Euler.js\\nvar _matrix = /* @__PURE__ */ new Matrix4();\\nvar _quaternion2 = /* @__PURE__ */ new Quaternion();\\nvar Euler = class {\\n constructor(x = 0, y = 0, z = 0, order = Euler.DefaultOrder) {\\n this._x = x;\\n this._y = y;\\n this._z = z;\\n this._order = order;\\n }\\n get x() {\\n return this._x;\\n }\\n set x(value) {\\n this._x = value;\\n this._onChangeCallback();\\n }\\n get y() {\\n return this._y;\\n }\\n set y(value) {\\n this._y = value;\\n this._onChangeCallback();\\n }\\n get z() {\\n return this._z;\\n }\\n set z(value) {\\n this._z = value;\\n this._onChangeCallback();\\n }\\n get order() {\\n return this._order;\\n }\\n set order(value) {\\n this._order = value;\\n this._onChangeCallback();\\n }\\n set(x, y, z, order = this._order) {\\n this._x = x;\\n this._y = y;\\n this._z = z;\\n this._order = order;\\n this._onChangeCallback();\\n return this;\\n }\\n clone() {\\n return new this.constructor(this._x, this._y, this._z, this._order);\\n }\\n copy(euler) {\\n this._x = euler._x;\\n this._y = euler._y;\\n this._z = euler._z;\\n this._order = euler._order;\\n this._onChangeCallback();\\n return this;\\n }\\n setFromRotationMatrix(m, order = this._order, update = true) {\\n const te = m.elements;\\n const m11 = te[0], m12 = te[4], m13 = te[8];\\n const m21 = te[1], m22 = te[5], m23 = te[9];\\n const m31 = te[2], m32 = te[6], m33 = te[10];\\n switch (order) {\\n case \\\\\\\"XYZ\\\\\\\":\\n this._y = Math.asin(clamp(m13, -1, 1));\\n if (Math.abs(m13) < 0.9999999) {\\n this._x = Math.atan2(-m23, m33);\\n this._z = Math.atan2(-m12, m11);\\n } else {\\n this._x = Math.atan2(m32, m22);\\n this._z = 0;\\n }\\n break;\\n case \\\\\\\"YXZ\\\\\\\":\\n this._x = Math.asin(-clamp(m23, -1, 1));\\n if (Math.abs(m23) < 0.9999999) {\\n this._y = Math.atan2(m13, m33);\\n this._z = Math.atan2(m21, m22);\\n } else {\\n this._y = Math.atan2(-m31, m11);\\n this._z = 0;\\n }\\n break;\\n case \\\\\\\"ZXY\\\\\\\":\\n this._x = Math.asin(clamp(m32, -1, 1));\\n if (Math.abs(m32) < 0.9999999) {\\n this._y = Math.atan2(-m31, m33);\\n this._z = Math.atan2(-m12, m22);\\n } else {\\n this._y = 0;\\n this._z = Math.atan2(m21, m11);\\n }\\n break;\\n case \\\\\\\"ZYX\\\\\\\":\\n this._y = Math.asin(-clamp(m31, -1, 1));\\n if (Math.abs(m31) < 0.9999999) {\\n this._x = Math.atan2(m32, m33);\\n this._z = Math.atan2(m21, m11);\\n } else {\\n this._x = 0;\\n this._z = Math.atan2(-m12, m22);\\n }\\n break;\\n case \\\\\\\"YZX\\\\\\\":\\n this._z = Math.asin(clamp(m21, -1, 1));\\n if (Math.abs(m21) < 0.9999999) {\\n this._x = Math.atan2(-m23, m22);\\n this._y = Math.atan2(-m31, m11);\\n } else {\\n this._x = 0;\\n this._y = Math.atan2(m13, m33);\\n }\\n break;\\n case \\\\\\\"XZY\\\\\\\":\\n this._z = Math.asin(-clamp(m12, -1, 1));\\n if (Math.abs(m12) < 0.9999999) {\\n this._x = Math.atan2(m32, m22);\\n this._y = Math.atan2(m13, m11);\\n } else {\\n this._x = Math.atan2(-m23, m33);\\n this._y = 0;\\n }\\n break;\\n default:\\n console.warn(\\\\\\\"THREE.Euler: .setFromRotationMatrix() encountered an unknown order: \\\\\\\" + order);\\n }\\n this._order = order;\\n if (update === true)\\n this._onChangeCallback();\\n return this;\\n }\\n setFromQuaternion(q, order, update) {\\n _matrix.makeRotationFromQuaternion(q);\\n return this.setFromRotationMatrix(_matrix, order, update);\\n }\\n setFromVector3(v, order = this._order) {\\n return this.set(v.x, v.y, v.z, order);\\n }\\n reorder(newOrder) {\\n _quaternion2.setFromEuler(this);\\n return this.setFromQuaternion(_quaternion2, newOrder);\\n }\\n equals(euler) {\\n return euler._x === this._x && euler._y === this._y && euler._z === this._z && euler._order === this._order;\\n }\\n fromArray(array) {\\n this._x = array[0];\\n this._y = array[1];\\n this._z = array[2];\\n if (array[3] !== void 0)\\n this._order = array[3];\\n this._onChangeCallback();\\n return this;\\n }\\n toArray(array = [], offset = 0) {\\n array[offset] = this._x;\\n array[offset + 1] = this._y;\\n array[offset + 2] = this._z;\\n array[offset + 3] = this._order;\\n return array;\\n }\\n toVector3(optionalResult) {\\n if (optionalResult) {\\n return optionalResult.set(this._x, this._y, this._z);\\n } else {\\n return new Vector3(this._x, this._y, this._z);\\n }\\n }\\n _onChange(callback) {\\n this._onChangeCallback = callback;\\n return this;\\n }\\n _onChangeCallback() {\\n }\\n};\\nEuler.prototype.isEuler = true;\\nEuler.DefaultOrder = \\\\\\\"XYZ\\\\\\\";\\nEuler.RotationOrders = [\\\\\\\"XYZ\\\\\\\", \\\\\\\"YZX\\\\\\\", \\\\\\\"ZXY\\\\\\\", \\\\\\\"XZY\\\\\\\", \\\\\\\"YXZ\\\\\\\", \\\\\\\"ZYX\\\\\\\"];\\n\\n// ../../../node_modules/three/src/core/Layers.js\\nvar Layers = class {\\n constructor() {\\n this.mask = 1 | 0;\\n }\\n set(channel) {\\n this.mask = 1 << channel | 0;\\n }\\n enable(channel) {\\n this.mask |= 1 << channel | 0;\\n }\\n enableAll() {\\n this.mask = 4294967295 | 0;\\n }\\n toggle(channel) {\\n this.mask ^= 1 << channel | 0;\\n }\\n disable(channel) {\\n this.mask &= ~(1 << channel | 0);\\n }\\n disableAll() {\\n this.mask = 0;\\n }\\n test(layers) {\\n return (this.mask & layers.mask) !== 0;\\n }\\n};\\n\\n// ../../../node_modules/three/src/math/Matrix3.js\\nvar Matrix3 = class {\\n constructor() {\\n this.elements = [\\n 1,\\n 0,\\n 0,\\n 0,\\n 1,\\n 0,\\n 0,\\n 0,\\n 1\\n ];\\n if (arguments.length > 0) {\\n console.error(\\\\\\\"THREE.Matrix3: the constructor no longer reads arguments. use .set() instead.\\\\\\\");\\n }\\n }\\n set(n11, n12, n13, n21, n22, n23, n31, n32, n33) {\\n const te = this.elements;\\n te[0] = n11;\\n te[1] = n21;\\n te[2] = n31;\\n te[3] = n12;\\n te[4] = n22;\\n te[5] = n32;\\n te[6] = n13;\\n te[7] = n23;\\n te[8] = n33;\\n return this;\\n }\\n identity() {\\n this.set(1, 0, 0, 0, 1, 0, 0, 0, 1);\\n return this;\\n }\\n copy(m) {\\n const te = this.elements;\\n const me = m.elements;\\n te[0] = me[0];\\n te[1] = me[1];\\n te[2] = me[2];\\n te[3] = me[3];\\n te[4] = me[4];\\n te[5] = me[5];\\n te[6] = me[6];\\n te[7] = me[7];\\n te[8] = me[8];\\n return this;\\n }\\n extractBasis(xAxis, yAxis, zAxis) {\\n xAxis.setFromMatrix3Column(this, 0);\\n yAxis.setFromMatrix3Column(this, 1);\\n zAxis.setFromMatrix3Column(this, 2);\\n return this;\\n }\\n setFromMatrix4(m) {\\n const me = m.elements;\\n this.set(me[0], me[4], me[8], me[1], me[5], me[9], me[2], me[6], me[10]);\\n return this;\\n }\\n multiply(m) {\\n return this.multiplyMatrices(this, m);\\n }\\n premultiply(m) {\\n return this.multiplyMatrices(m, this);\\n }\\n multiplyMatrices(a, b) {\\n const ae = a.elements;\\n const be = b.elements;\\n const te = this.elements;\\n const a11 = ae[0], a12 = ae[3], a13 = ae[6];\\n const a21 = ae[1], a22 = ae[4], a23 = ae[7];\\n const a31 = ae[2], a32 = ae[5], a33 = ae[8];\\n const b11 = be[0], b12 = be[3], b13 = be[6];\\n const b21 = be[1], b22 = be[4], b23 = be[7];\\n const b31 = be[2], b32 = be[5], b33 = be[8];\\n te[0] = a11 * b11 + a12 * b21 + a13 * b31;\\n te[3] = a11 * b12 + a12 * b22 + a13 * b32;\\n te[6] = a11 * b13 + a12 * b23 + a13 * b33;\\n te[1] = a21 * b11 + a22 * b21 + a23 * b31;\\n te[4] = a21 * b12 + a22 * b22 + a23 * b32;\\n te[7] = a21 * b13 + a22 * b23 + a23 * b33;\\n te[2] = a31 * b11 + a32 * b21 + a33 * b31;\\n te[5] = a31 * b12 + a32 * b22 + a33 * b32;\\n te[8] = a31 * b13 + a32 * b23 + a33 * b33;\\n return this;\\n }\\n multiplyScalar(s) {\\n const te = this.elements;\\n te[0] *= s;\\n te[3] *= s;\\n te[6] *= s;\\n te[1] *= s;\\n te[4] *= s;\\n te[7] *= s;\\n te[2] *= s;\\n te[5] *= s;\\n te[8] *= s;\\n return this;\\n }\\n determinant() {\\n const te = this.elements;\\n const a = te[0], b = te[1], c = te[2], d = te[3], e = te[4], f = te[5], g = te[6], h = te[7], i = te[8];\\n return a * e * i - a * f * h - b * d * i + b * f * g + c * d * h - c * e * g;\\n }\\n invert() {\\n const te = this.elements, n11 = te[0], n21 = te[1], n31 = te[2], n12 = te[3], n22 = te[4], n32 = te[5], n13 = te[6], n23 = te[7], n33 = te[8], t11 = n33 * n22 - n32 * n23, t12 = n32 * n13 - n33 * n12, t13 = n23 * n12 - n22 * n13, det = n11 * t11 + n21 * t12 + n31 * t13;\\n if (det === 0)\\n return this.set(0, 0, 0, 0, 0, 0, 0, 0, 0);\\n const detInv = 1 / det;\\n te[0] = t11 * detInv;\\n te[1] = (n31 * n23 - n33 * n21) * detInv;\\n te[2] = (n32 * n21 - n31 * n22) * detInv;\\n te[3] = t12 * detInv;\\n te[4] = (n33 * n11 - n31 * n13) * detInv;\\n te[5] = (n31 * n12 - n32 * n11) * detInv;\\n te[6] = t13 * detInv;\\n te[7] = (n21 * n13 - n23 * n11) * detInv;\\n te[8] = (n22 * n11 - n21 * n12) * detInv;\\n return this;\\n }\\n transpose() {\\n let tmp;\\n const m = this.elements;\\n tmp = m[1];\\n m[1] = m[3];\\n m[3] = tmp;\\n tmp = m[2];\\n m[2] = m[6];\\n m[6] = tmp;\\n tmp = m[5];\\n m[5] = m[7];\\n m[7] = tmp;\\n return this;\\n }\\n getNormalMatrix(matrix4) {\\n return this.setFromMatrix4(matrix4).invert().transpose();\\n }\\n transposeIntoArray(r) {\\n const m = this.elements;\\n r[0] = m[0];\\n r[1] = m[3];\\n r[2] = m[6];\\n r[3] = m[1];\\n r[4] = m[4];\\n r[5] = m[7];\\n r[6] = m[2];\\n r[7] = m[5];\\n r[8] = m[8];\\n return this;\\n }\\n setUvTransform(tx, ty, sx, sy, rotation, cx, cy) {\\n const c = Math.cos(rotation);\\n const s = Math.sin(rotation);\\n this.set(sx * c, sx * s, -sx * (c * cx + s * cy) + cx + tx, -sy * s, sy * c, -sy * (-s * cx + c * cy) + cy + ty, 0, 0, 1);\\n return this;\\n }\\n scale(sx, sy) {\\n const te = this.elements;\\n te[0] *= sx;\\n te[3] *= sx;\\n te[6] *= sx;\\n te[1] *= sy;\\n te[4] *= sy;\\n te[7] *= sy;\\n return this;\\n }\\n rotate(theta) {\\n const c = Math.cos(theta);\\n const s = Math.sin(theta);\\n const te = this.elements;\\n const a11 = te[0], a12 = te[3], a13 = te[6];\\n const a21 = te[1], a22 = te[4], a23 = te[7];\\n te[0] = c * a11 + s * a21;\\n te[3] = c * a12 + s * a22;\\n te[6] = c * a13 + s * a23;\\n te[1] = -s * a11 + c * a21;\\n te[4] = -s * a12 + c * a22;\\n te[7] = -s * a13 + c * a23;\\n return this;\\n }\\n translate(tx, ty) {\\n const te = this.elements;\\n te[0] += tx * te[2];\\n te[3] += tx * te[5];\\n te[6] += tx * te[8];\\n te[1] += ty * te[2];\\n te[4] += ty * te[5];\\n te[7] += ty * te[8];\\n return this;\\n }\\n equals(matrix) {\\n const te = this.elements;\\n const me = matrix.elements;\\n for (let i = 0; i < 9; i++) {\\n if (te[i] !== me[i])\\n return false;\\n }\\n return true;\\n }\\n fromArray(array, offset = 0) {\\n for (let i = 0; i < 9; i++) {\\n this.elements[i] = array[i + offset];\\n }\\n return this;\\n }\\n toArray(array = [], offset = 0) {\\n const te = this.elements;\\n array[offset] = te[0];\\n array[offset + 1] = te[1];\\n array[offset + 2] = te[2];\\n array[offset + 3] = te[3];\\n array[offset + 4] = te[4];\\n array[offset + 5] = te[5];\\n array[offset + 6] = te[6];\\n array[offset + 7] = te[7];\\n array[offset + 8] = te[8];\\n return array;\\n }\\n clone() {\\n return new this.constructor().fromArray(this.elements);\\n }\\n};\\nMatrix3.prototype.isMatrix3 = true;\\n\\n// ../../../node_modules/three/src/core/Object3D.js\\nvar _object3DId = 0;\\nvar _v12 = /* @__PURE__ */ new Vector3();\\nvar _q1 = /* @__PURE__ */ new Quaternion();\\nvar _m12 = /* @__PURE__ */ new Matrix4();\\nvar _target = /* @__PURE__ */ new Vector3();\\nvar _position = /* @__PURE__ */ new Vector3();\\nvar _scale = /* @__PURE__ */ new Vector3();\\nvar _quaternion3 = /* @__PURE__ */ new Quaternion();\\nvar _xAxis = /* @__PURE__ */ new Vector3(1, 0, 0);\\nvar _yAxis = /* @__PURE__ */ new Vector3(0, 1, 0);\\nvar _zAxis = /* @__PURE__ */ new Vector3(0, 0, 1);\\nvar _addedEvent = {type: \\\\\\\"added\\\\\\\"};\\nvar _removedEvent = {type: \\\\\\\"removed\\\\\\\"};\\nvar Object3D = class extends EventDispatcher {\\n constructor() {\\n super();\\n Object.defineProperty(this, \\\\\\\"id\\\\\\\", {value: _object3DId++});\\n this.uuid = generateUUID();\\n this.name = \\\\\\\"\\\\\\\";\\n this.type = \\\\\\\"Object3D\\\\\\\";\\n this.parent = null;\\n this.children = [];\\n this.up = Object3D.DefaultUp.clone();\\n const position = new Vector3();\\n const rotation = new Euler();\\n const quaternion = new Quaternion();\\n const scale = new Vector3(1, 1, 1);\\n function onRotationChange() {\\n quaternion.setFromEuler(rotation, false);\\n }\\n function onQuaternionChange() {\\n rotation.setFromQuaternion(quaternion, void 0, false);\\n }\\n rotation._onChange(onRotationChange);\\n quaternion._onChange(onQuaternionChange);\\n Object.defineProperties(this, {\\n position: {\\n configurable: true,\\n enumerable: true,\\n value: position\\n },\\n rotation: {\\n configurable: true,\\n enumerable: true,\\n value: rotation\\n },\\n quaternion: {\\n configurable: true,\\n enumerable: true,\\n value: quaternion\\n },\\n scale: {\\n configurable: true,\\n enumerable: true,\\n value: scale\\n },\\n modelViewMatrix: {\\n value: new Matrix4()\\n },\\n normalMatrix: {\\n value: new Matrix3()\\n }\\n });\\n this.matrix = new Matrix4();\\n this.matrixWorld = new Matrix4();\\n this.matrixAutoUpdate = Object3D.DefaultMatrixAutoUpdate;\\n this.matrixWorldNeedsUpdate = false;\\n this.layers = new Layers();\\n this.visible = true;\\n this.castShadow = false;\\n this.receiveShadow = false;\\n this.frustumCulled = true;\\n this.renderOrder = 0;\\n this.animations = [];\\n this.userData = {};\\n }\\n onBeforeRender() {\\n }\\n onAfterRender() {\\n }\\n applyMatrix4(matrix) {\\n if (this.matrixAutoUpdate)\\n this.updateMatrix();\\n this.matrix.premultiply(matrix);\\n this.matrix.decompose(this.position, this.quaternion, this.scale);\\n }\\n applyQuaternion(q) {\\n this.quaternion.premultiply(q);\\n return this;\\n }\\n setRotationFromAxisAngle(axis, angle) {\\n this.quaternion.setFromAxisAngle(axis, angle);\\n }\\n setRotationFromEuler(euler) {\\n this.quaternion.setFromEuler(euler, true);\\n }\\n setRotationFromMatrix(m) {\\n this.quaternion.setFromRotationMatrix(m);\\n }\\n setRotationFromQuaternion(q) {\\n this.quaternion.copy(q);\\n }\\n rotateOnAxis(axis, angle) {\\n _q1.setFromAxisAngle(axis, angle);\\n this.quaternion.multiply(_q1);\\n return this;\\n }\\n rotateOnWorldAxis(axis, angle) {\\n _q1.setFromAxisAngle(axis, angle);\\n this.quaternion.premultiply(_q1);\\n return this;\\n }\\n rotateX(angle) {\\n return this.rotateOnAxis(_xAxis, angle);\\n }\\n rotateY(angle) {\\n return this.rotateOnAxis(_yAxis, angle);\\n }\\n rotateZ(angle) {\\n return this.rotateOnAxis(_zAxis, angle);\\n }\\n translateOnAxis(axis, distance) {\\n _v12.copy(axis).applyQuaternion(this.quaternion);\\n this.position.add(_v12.multiplyScalar(distance));\\n return this;\\n }\\n translateX(distance) {\\n return this.translateOnAxis(_xAxis, distance);\\n }\\n translateY(distance) {\\n return this.translateOnAxis(_yAxis, distance);\\n }\\n translateZ(distance) {\\n return this.translateOnAxis(_zAxis, distance);\\n }\\n localToWorld(vector) {\\n return vector.applyMatrix4(this.matrixWorld);\\n }\\n worldToLocal(vector) {\\n return vector.applyMatrix4(_m12.copy(this.matrixWorld).invert());\\n }\\n lookAt(x, y, z) {\\n if (x.isVector3) {\\n _target.copy(x);\\n } else {\\n _target.set(x, y, z);\\n }\\n const parent = this.parent;\\n this.updateWorldMatrix(true, false);\\n _position.setFromMatrixPosition(this.matrixWorld);\\n if (this.isCamera || this.isLight) {\\n _m12.lookAt(_position, _target, this.up);\\n } else {\\n _m12.lookAt(_target, _position, this.up);\\n }\\n this.quaternion.setFromRotationMatrix(_m12);\\n if (parent) {\\n _m12.extractRotation(parent.matrixWorld);\\n _q1.setFromRotationMatrix(_m12);\\n this.quaternion.premultiply(_q1.invert());\\n }\\n }\\n add(object) {\\n if (arguments.length > 1) {\\n for (let i = 0; i < arguments.length; i++) {\\n this.add(arguments[i]);\\n }\\n return this;\\n }\\n if (object === this) {\\n console.error(\\\\\\\"THREE.Object3D.add: object can't be added as a child of itself.\\\\\\\", object);\\n return this;\\n }\\n if (object && object.isObject3D) {\\n if (object.parent !== null) {\\n object.parent.remove(object);\\n }\\n object.parent = this;\\n this.children.push(object);\\n object.dispatchEvent(_addedEvent);\\n } else {\\n console.error(\\\\\\\"THREE.Object3D.add: object not an instance of THREE.Object3D.\\\\\\\", object);\\n }\\n return this;\\n }\\n remove(object) {\\n if (arguments.length > 1) {\\n for (let i = 0; i < arguments.length; i++) {\\n this.remove(arguments[i]);\\n }\\n return this;\\n }\\n const index = this.children.indexOf(object);\\n if (index !== -1) {\\n object.parent = null;\\n this.children.splice(index, 1);\\n object.dispatchEvent(_removedEvent);\\n }\\n return this;\\n }\\n removeFromParent() {\\n const parent = this.parent;\\n if (parent !== null) {\\n parent.remove(this);\\n }\\n return this;\\n }\\n clear() {\\n for (let i = 0; i < this.children.length; i++) {\\n const object = this.children[i];\\n object.parent = null;\\n object.dispatchEvent(_removedEvent);\\n }\\n this.children.length = 0;\\n return this;\\n }\\n attach(object) {\\n this.updateWorldMatrix(true, false);\\n _m12.copy(this.matrixWorld).invert();\\n if (object.parent !== null) {\\n object.parent.updateWorldMatrix(true, false);\\n _m12.multiply(object.parent.matrixWorld);\\n }\\n object.applyMatrix4(_m12);\\n this.add(object);\\n object.updateWorldMatrix(false, true);\\n return this;\\n }\\n getObjectById(id) {\\n return this.getObjectByProperty(\\\\\\\"id\\\\\\\", id);\\n }\\n getObjectByName(name) {\\n return this.getObjectByProperty(\\\\\\\"name\\\\\\\", name);\\n }\\n getObjectByProperty(name, value) {\\n if (this[name] === value)\\n return this;\\n for (let i = 0, l = this.children.length; i < l; i++) {\\n const child = this.children[i];\\n const object = child.getObjectByProperty(name, value);\\n if (object !== void 0) {\\n return object;\\n }\\n }\\n return void 0;\\n }\\n getWorldPosition(target) {\\n this.updateWorldMatrix(true, false);\\n return target.setFromMatrixPosition(this.matrixWorld);\\n }\\n getWorldQuaternion(target) {\\n this.updateWorldMatrix(true, false);\\n this.matrixWorld.decompose(_position, target, _scale);\\n return target;\\n }\\n getWorldScale(target) {\\n this.updateWorldMatrix(true, false);\\n this.matrixWorld.decompose(_position, _quaternion3, target);\\n return target;\\n }\\n getWorldDirection(target) {\\n this.updateWorldMatrix(true, false);\\n const e = this.matrixWorld.elements;\\n return target.set(e[8], e[9], e[10]).normalize();\\n }\\n raycast() {\\n }\\n traverse(callback) {\\n callback(this);\\n const children = this.children;\\n for (let i = 0, l = children.length; i < l; i++) {\\n children[i].traverse(callback);\\n }\\n }\\n traverseVisible(callback) {\\n if (this.visible === false)\\n return;\\n callback(this);\\n const children = this.children;\\n for (let i = 0, l = children.length; i < l; i++) {\\n children[i].traverseVisible(callback);\\n }\\n }\\n traverseAncestors(callback) {\\n const parent = this.parent;\\n if (parent !== null) {\\n callback(parent);\\n parent.traverseAncestors(callback);\\n }\\n }\\n updateMatrix() {\\n this.matrix.compose(this.position, this.quaternion, this.scale);\\n this.matrixWorldNeedsUpdate = true;\\n }\\n updateMatrixWorld(force) {\\n if (this.matrixAutoUpdate)\\n this.updateMatrix();\\n if (this.matrixWorldNeedsUpdate || force) {\\n if (this.parent === null) {\\n this.matrixWorld.copy(this.matrix);\\n } else {\\n this.matrixWorld.multiplyMatrices(this.parent.matrixWorld, this.matrix);\\n }\\n this.matrixWorldNeedsUpdate = false;\\n force = true;\\n }\\n const children = this.children;\\n for (let i = 0, l = children.length; i < l; i++) {\\n children[i].updateMatrixWorld(force);\\n }\\n }\\n updateWorldMatrix(updateParents, updateChildren) {\\n const parent = this.parent;\\n if (updateParents === true && parent !== null) {\\n parent.updateWorldMatrix(true, false);\\n }\\n if (this.matrixAutoUpdate)\\n this.updateMatrix();\\n if (this.parent === null) {\\n this.matrixWorld.copy(this.matrix);\\n } else {\\n this.matrixWorld.multiplyMatrices(this.parent.matrixWorld, this.matrix);\\n }\\n if (updateChildren === true) {\\n const children = this.children;\\n for (let i = 0, l = children.length; i < l; i++) {\\n children[i].updateWorldMatrix(false, true);\\n }\\n }\\n }\\n toJSON(meta) {\\n const isRootObject = meta === void 0 || typeof meta === \\\\\\\"string\\\\\\\";\\n const output = {};\\n if (isRootObject) {\\n meta = {\\n geometries: {},\\n materials: {},\\n textures: {},\\n images: {},\\n shapes: {},\\n skeletons: {},\\n animations: {}\\n };\\n output.metadata = {\\n version: 4.5,\\n type: \\\\\\\"Object\\\\\\\",\\n generator: \\\\\\\"Object3D.toJSON\\\\\\\"\\n };\\n }\\n const object = {};\\n object.uuid = this.uuid;\\n object.type = this.type;\\n if (this.name !== \\\\\\\"\\\\\\\")\\n object.name = this.name;\\n if (this.castShadow === true)\\n object.castShadow = true;\\n if (this.receiveShadow === true)\\n object.receiveShadow = true;\\n if (this.visible === false)\\n object.visible = false;\\n if (this.frustumCulled === false)\\n object.frustumCulled = false;\\n if (this.renderOrder !== 0)\\n object.renderOrder = this.renderOrder;\\n if (JSON.stringify(this.userData) !== \\\\\\\"{}\\\\\\\")\\n object.userData = this.userData;\\n object.layers = this.layers.mask;\\n object.matrix = this.matrix.toArray();\\n if (this.matrixAutoUpdate === false)\\n object.matrixAutoUpdate = false;\\n if (this.isInstancedMesh) {\\n object.type = \\\\\\\"InstancedMesh\\\\\\\";\\n object.count = this.count;\\n object.instanceMatrix = this.instanceMatrix.toJSON();\\n if (this.instanceColor !== null)\\n object.instanceColor = this.instanceColor.toJSON();\\n }\\n function serialize(library, element) {\\n if (library[element.uuid] === void 0) {\\n library[element.uuid] = element.toJSON(meta);\\n }\\n return element.uuid;\\n }\\n if (this.isScene) {\\n if (this.background) {\\n if (this.background.isColor) {\\n object.background = this.background.toJSON();\\n } else if (this.background.isTexture) {\\n object.background = this.background.toJSON(meta).uuid;\\n }\\n }\\n if (this.environment && this.environment.isTexture) {\\n object.environment = this.environment.toJSON(meta).uuid;\\n }\\n } else if (this.isMesh || this.isLine || this.isPoints) {\\n object.geometry = serialize(meta.geometries, this.geometry);\\n const parameters = this.geometry.parameters;\\n if (parameters !== void 0 && parameters.shapes !== void 0) {\\n const shapes = parameters.shapes;\\n if (Array.isArray(shapes)) {\\n for (let i = 0, l = shapes.length; i < l; i++) {\\n const shape = shapes[i];\\n serialize(meta.shapes, shape);\\n }\\n } else {\\n serialize(meta.shapes, shapes);\\n }\\n }\\n }\\n if (this.isSkinnedMesh) {\\n object.bindMode = this.bindMode;\\n object.bindMatrix = this.bindMatrix.toArray();\\n if (this.skeleton !== void 0) {\\n serialize(meta.skeletons, this.skeleton);\\n object.skeleton = this.skeleton.uuid;\\n }\\n }\\n if (this.material !== void 0) {\\n if (Array.isArray(this.material)) {\\n const uuids = [];\\n for (let i = 0, l = this.material.length; i < l; i++) {\\n uuids.push(serialize(meta.materials, this.material[i]));\\n }\\n object.material = uuids;\\n } else {\\n object.material = serialize(meta.materials, this.material);\\n }\\n }\\n if (this.children.length > 0) {\\n object.children = [];\\n for (let i = 0; i < this.children.length; i++) {\\n object.children.push(this.children[i].toJSON(meta).object);\\n }\\n }\\n if (this.animations.length > 0) {\\n object.animations = [];\\n for (let i = 0; i < this.animations.length; i++) {\\n const animation = this.animations[i];\\n object.animations.push(serialize(meta.animations, animation));\\n }\\n }\\n if (isRootObject) {\\n const geometries = extractFromCache(meta.geometries);\\n const materials2 = extractFromCache(meta.materials);\\n const textures = extractFromCache(meta.textures);\\n const images = extractFromCache(meta.images);\\n const shapes = extractFromCache(meta.shapes);\\n const skeletons = extractFromCache(meta.skeletons);\\n const animations = extractFromCache(meta.animations);\\n if (geometries.length > 0)\\n output.geometries = geometries;\\n if (materials2.length > 0)\\n output.materials = materials2;\\n if (textures.length > 0)\\n output.textures = textures;\\n if (images.length > 0)\\n output.images = images;\\n if (shapes.length > 0)\\n output.shapes = shapes;\\n if (skeletons.length > 0)\\n output.skeletons = skeletons;\\n if (animations.length > 0)\\n output.animations = animations;\\n }\\n output.object = object;\\n return output;\\n function extractFromCache(cache) {\\n const values = [];\\n for (const key in cache) {\\n const data = cache[key];\\n delete data.metadata;\\n values.push(data);\\n }\\n return values;\\n }\\n }\\n clone(recursive) {\\n return new this.constructor().copy(this, recursive);\\n }\\n copy(source, recursive = true) {\\n this.name = source.name;\\n this.up.copy(source.up);\\n this.position.copy(source.position);\\n this.rotation.order = source.rotation.order;\\n this.quaternion.copy(source.quaternion);\\n this.scale.copy(source.scale);\\n this.matrix.copy(source.matrix);\\n this.matrixWorld.copy(source.matrixWorld);\\n this.matrixAutoUpdate = source.matrixAutoUpdate;\\n this.matrixWorldNeedsUpdate = source.matrixWorldNeedsUpdate;\\n this.layers.mask = source.layers.mask;\\n this.visible = source.visible;\\n this.castShadow = source.castShadow;\\n this.receiveShadow = source.receiveShadow;\\n this.frustumCulled = source.frustumCulled;\\n this.renderOrder = source.renderOrder;\\n this.userData = JSON.parse(JSON.stringify(source.userData));\\n if (recursive === true) {\\n for (let i = 0; i < source.children.length; i++) {\\n const child = source.children[i];\\n this.add(child.clone());\\n }\\n }\\n return this;\\n }\\n};\\nObject3D.DefaultUp = new Vector3(0, 1, 0);\\nObject3D.DefaultMatrixAutoUpdate = true;\\nObject3D.prototype.isObject3D = true;\\n\\n// ../../../node_modules/three/src/constants.js\\nvar CullFaceNone = 0;\\nvar CullFaceBack = 1;\\nvar CullFaceFront = 2;\\nvar PCFShadowMap = 1;\\nvar PCFSoftShadowMap = 2;\\nvar VSMShadowMap = 3;\\nvar FrontSide = 0;\\nvar BackSide = 1;\\nvar DoubleSide = 2;\\nvar FlatShading = 1;\\nvar NoBlending = 0;\\nvar NormalBlending = 1;\\nvar AdditiveBlending = 2;\\nvar SubtractiveBlending = 3;\\nvar MultiplyBlending = 4;\\nvar CustomBlending = 5;\\nvar AddEquation = 100;\\nvar SubtractEquation = 101;\\nvar ReverseSubtractEquation = 102;\\nvar MinEquation = 103;\\nvar MaxEquation = 104;\\nvar ZeroFactor = 200;\\nvar OneFactor = 201;\\nvar SrcColorFactor = 202;\\nvar OneMinusSrcColorFactor = 203;\\nvar SrcAlphaFactor = 204;\\nvar OneMinusSrcAlphaFactor = 205;\\nvar DstAlphaFactor = 206;\\nvar OneMinusDstAlphaFactor = 207;\\nvar DstColorFactor = 208;\\nvar OneMinusDstColorFactor = 209;\\nvar SrcAlphaSaturateFactor = 210;\\nvar NeverDepth = 0;\\nvar AlwaysDepth = 1;\\nvar LessDepth = 2;\\nvar LessEqualDepth = 3;\\nvar EqualDepth = 4;\\nvar GreaterEqualDepth = 5;\\nvar GreaterDepth = 6;\\nvar NotEqualDepth = 7;\\nvar MultiplyOperation = 0;\\nvar MixOperation = 1;\\nvar AddOperation = 2;\\nvar NoToneMapping = 0;\\nvar LinearToneMapping = 1;\\nvar ReinhardToneMapping = 2;\\nvar CineonToneMapping = 3;\\nvar ACESFilmicToneMapping = 4;\\nvar CustomToneMapping = 5;\\nvar UVMapping = 300;\\nvar CubeReflectionMapping = 301;\\nvar CubeRefractionMapping = 302;\\nvar EquirectangularReflectionMapping = 303;\\nvar EquirectangularRefractionMapping = 304;\\nvar CubeUVReflectionMapping = 306;\\nvar CubeUVRefractionMapping = 307;\\nvar RepeatWrapping = 1e3;\\nvar ClampToEdgeWrapping = 1001;\\nvar MirroredRepeatWrapping = 1002;\\nvar NearestFilter = 1003;\\nvar NearestMipmapNearestFilter = 1004;\\nvar NearestMipmapLinearFilter = 1005;\\nvar LinearFilter = 1006;\\nvar LinearMipmapNearestFilter = 1007;\\nvar LinearMipmapLinearFilter = 1008;\\nvar UnsignedByteType = 1009;\\nvar ByteType = 1010;\\nvar ShortType = 1011;\\nvar UnsignedShortType = 1012;\\nvar IntType = 1013;\\nvar UnsignedIntType = 1014;\\nvar FloatType = 1015;\\nvar HalfFloatType = 1016;\\nvar UnsignedShort4444Type = 1017;\\nvar UnsignedShort5551Type = 1018;\\nvar UnsignedShort565Type = 1019;\\nvar UnsignedInt248Type = 1020;\\nvar AlphaFormat = 1021;\\nvar RGBFormat = 1022;\\nvar RGBAFormat = 1023;\\nvar LuminanceFormat = 1024;\\nvar LuminanceAlphaFormat = 1025;\\nvar RGBEFormat = RGBAFormat;\\nvar DepthFormat = 1026;\\nvar DepthStencilFormat = 1027;\\nvar RedFormat = 1028;\\nvar RedIntegerFormat = 1029;\\nvar RGFormat = 1030;\\nvar RGIntegerFormat = 1031;\\nvar RGBIntegerFormat = 1032;\\nvar RGBAIntegerFormat = 1033;\\nvar RGB_S3TC_DXT1_Format = 33776;\\nvar RGBA_S3TC_DXT1_Format = 33777;\\nvar RGBA_S3TC_DXT3_Format = 33778;\\nvar RGBA_S3TC_DXT5_Format = 33779;\\nvar RGB_PVRTC_4BPPV1_Format = 35840;\\nvar RGB_PVRTC_2BPPV1_Format = 35841;\\nvar RGBA_PVRTC_4BPPV1_Format = 35842;\\nvar RGBA_PVRTC_2BPPV1_Format = 35843;\\nvar RGB_ETC1_Format = 36196;\\nvar RGB_ETC2_Format = 37492;\\nvar RGBA_ETC2_EAC_Format = 37496;\\nvar RGBA_ASTC_4x4_Format = 37808;\\nvar RGBA_ASTC_5x4_Format = 37809;\\nvar RGBA_ASTC_5x5_Format = 37810;\\nvar RGBA_ASTC_6x5_Format = 37811;\\nvar RGBA_ASTC_6x6_Format = 37812;\\nvar RGBA_ASTC_8x5_Format = 37813;\\nvar RGBA_ASTC_8x6_Format = 37814;\\nvar RGBA_ASTC_8x8_Format = 37815;\\nvar RGBA_ASTC_10x5_Format = 37816;\\nvar RGBA_ASTC_10x6_Format = 37817;\\nvar RGBA_ASTC_10x8_Format = 37818;\\nvar RGBA_ASTC_10x10_Format = 37819;\\nvar RGBA_ASTC_12x10_Format = 37820;\\nvar RGBA_ASTC_12x12_Format = 37821;\\nvar RGBA_BPTC_Format = 36492;\\nvar SRGB8_ALPHA8_ASTC_4x4_Format = 37840;\\nvar SRGB8_ALPHA8_ASTC_5x4_Format = 37841;\\nvar SRGB8_ALPHA8_ASTC_5x5_Format = 37842;\\nvar SRGB8_ALPHA8_ASTC_6x5_Format = 37843;\\nvar SRGB8_ALPHA8_ASTC_6x6_Format = 37844;\\nvar SRGB8_ALPHA8_ASTC_8x5_Format = 37845;\\nvar SRGB8_ALPHA8_ASTC_8x6_Format = 37846;\\nvar SRGB8_ALPHA8_ASTC_8x8_Format = 37847;\\nvar SRGB8_ALPHA8_ASTC_10x5_Format = 37848;\\nvar SRGB8_ALPHA8_ASTC_10x6_Format = 37849;\\nvar SRGB8_ALPHA8_ASTC_10x8_Format = 37850;\\nvar SRGB8_ALPHA8_ASTC_10x10_Format = 37851;\\nvar SRGB8_ALPHA8_ASTC_12x10_Format = 37852;\\nvar SRGB8_ALPHA8_ASTC_12x12_Format = 37853;\\nvar ZeroCurvatureEnding = 2400;\\nvar ZeroSlopeEnding = 2401;\\nvar WrapAroundEnding = 2402;\\nvar LinearEncoding = 3e3;\\nvar sRGBEncoding = 3001;\\nvar GammaEncoding = 3007;\\nvar RGBEEncoding = 3002;\\nvar LogLuvEncoding = 3003;\\nvar RGBM7Encoding = 3004;\\nvar RGBM16Encoding = 3005;\\nvar RGBDEncoding = 3006;\\nvar BasicDepthPacking = 3200;\\nvar RGBADepthPacking = 3201;\\nvar TangentSpaceNormalMap = 0;\\nvar ObjectSpaceNormalMap = 1;\\nvar KeepStencilOp = 7680;\\nvar AlwaysStencilFunc = 519;\\nvar StaticDrawUsage = 35044;\\nvar GLSL3 = \\\\\\\"300 es\\\\\\\";\\n\\n// ../../../node_modules/three/src/math/Box3.js\\nvar Box3 = class {\\n constructor(min = new Vector3(Infinity, Infinity, Infinity), max = new Vector3(-Infinity, -Infinity, -Infinity)) {\\n this.min = min;\\n this.max = max;\\n }\\n set(min, max) {\\n this.min.copy(min);\\n this.max.copy(max);\\n return this;\\n }\\n setFromArray(array) {\\n let minX = Infinity;\\n let minY = Infinity;\\n let minZ = Infinity;\\n let maxX = -Infinity;\\n let maxY = -Infinity;\\n let maxZ = -Infinity;\\n for (let i = 0, l = array.length; i < l; i += 3) {\\n const x = array[i];\\n const y = array[i + 1];\\n const z = array[i + 2];\\n if (x < minX)\\n minX = x;\\n if (y < minY)\\n minY = y;\\n if (z < minZ)\\n minZ = z;\\n if (x > maxX)\\n maxX = x;\\n if (y > maxY)\\n maxY = y;\\n if (z > maxZ)\\n maxZ = z;\\n }\\n this.min.set(minX, minY, minZ);\\n this.max.set(maxX, maxY, maxZ);\\n return this;\\n }\\n setFromBufferAttribute(attribute) {\\n let minX = Infinity;\\n let minY = Infinity;\\n let minZ = Infinity;\\n let maxX = -Infinity;\\n let maxY = -Infinity;\\n let maxZ = -Infinity;\\n for (let i = 0, l = attribute.count; i < l; i++) {\\n const x = attribute.getX(i);\\n const y = attribute.getY(i);\\n const z = attribute.getZ(i);\\n if (x < minX)\\n minX = x;\\n if (y < minY)\\n minY = y;\\n if (z < minZ)\\n minZ = z;\\n if (x > maxX)\\n maxX = x;\\n if (y > maxY)\\n maxY = y;\\n if (z > maxZ)\\n maxZ = z;\\n }\\n this.min.set(minX, minY, minZ);\\n this.max.set(maxX, maxY, maxZ);\\n return this;\\n }\\n setFromPoints(points2) {\\n this.makeEmpty();\\n for (let i = 0, il = points2.length; i < il; i++) {\\n this.expandByPoint(points2[i]);\\n }\\n return this;\\n }\\n setFromCenterAndSize(center, size) {\\n const halfSize = _vector2.copy(size).multiplyScalar(0.5);\\n this.min.copy(center).sub(halfSize);\\n this.max.copy(center).add(halfSize);\\n return this;\\n }\\n setFromObject(object) {\\n this.makeEmpty();\\n return this.expandByObject(object);\\n }\\n clone() {\\n return new this.constructor().copy(this);\\n }\\n copy(box) {\\n this.min.copy(box.min);\\n this.max.copy(box.max);\\n return this;\\n }\\n makeEmpty() {\\n this.min.x = this.min.y = this.min.z = Infinity;\\n this.max.x = this.max.y = this.max.z = -Infinity;\\n return this;\\n }\\n isEmpty() {\\n return this.max.x < this.min.x || this.max.y < this.min.y || this.max.z < this.min.z;\\n }\\n getCenter(target) {\\n return this.isEmpty() ? target.set(0, 0, 0) : target.addVectors(this.min, this.max).multiplyScalar(0.5);\\n }\\n getSize(target) {\\n return this.isEmpty() ? target.set(0, 0, 0) : target.subVectors(this.max, this.min);\\n }\\n expandByPoint(point) {\\n this.min.min(point);\\n this.max.max(point);\\n return this;\\n }\\n expandByVector(vector) {\\n this.min.sub(vector);\\n this.max.add(vector);\\n return this;\\n }\\n expandByScalar(scalar) {\\n this.min.addScalar(-scalar);\\n this.max.addScalar(scalar);\\n return this;\\n }\\n expandByObject(object) {\\n object.updateWorldMatrix(false, false);\\n const geometry = object.geometry;\\n if (geometry !== void 0) {\\n if (geometry.boundingBox === null) {\\n geometry.computeBoundingBox();\\n }\\n _box.copy(geometry.boundingBox);\\n _box.applyMatrix4(object.matrixWorld);\\n this.union(_box);\\n }\\n const children = object.children;\\n for (let i = 0, l = children.length; i < l; i++) {\\n this.expandByObject(children[i]);\\n }\\n return this;\\n }\\n containsPoint(point) {\\n return point.x < this.min.x || point.x > this.max.x || point.y < this.min.y || point.y > this.max.y || point.z < this.min.z || point.z > this.max.z ? false : true;\\n }\\n containsBox(box) {\\n return this.min.x <= box.min.x && box.max.x <= this.max.x && this.min.y <= box.min.y && box.max.y <= this.max.y && this.min.z <= box.min.z && box.max.z <= this.max.z;\\n }\\n getParameter(point, target) {\\n return target.set((point.x - this.min.x) / (this.max.x - this.min.x), (point.y - this.min.y) / (this.max.y - this.min.y), (point.z - this.min.z) / (this.max.z - this.min.z));\\n }\\n intersectsBox(box) {\\n return box.max.x < this.min.x || box.min.x > this.max.x || box.max.y < this.min.y || box.min.y > this.max.y || box.max.z < this.min.z || box.min.z > this.max.z ? false : true;\\n }\\n intersectsSphere(sphere) {\\n this.clampPoint(sphere.center, _vector2);\\n return _vector2.distanceToSquared(sphere.center) <= sphere.radius * sphere.radius;\\n }\\n intersectsPlane(plane) {\\n let min, max;\\n if (plane.normal.x > 0) {\\n min = plane.normal.x * this.min.x;\\n max = plane.normal.x * this.max.x;\\n } else {\\n min = plane.normal.x * this.max.x;\\n max = plane.normal.x * this.min.x;\\n }\\n if (plane.normal.y > 0) {\\n min += plane.normal.y * this.min.y;\\n max += plane.normal.y * this.max.y;\\n } else {\\n min += plane.normal.y * this.max.y;\\n max += plane.normal.y * this.min.y;\\n }\\n if (plane.normal.z > 0) {\\n min += plane.normal.z * this.min.z;\\n max += plane.normal.z * this.max.z;\\n } else {\\n min += plane.normal.z * this.max.z;\\n max += plane.normal.z * this.min.z;\\n }\\n return min <= -plane.constant && max >= -plane.constant;\\n }\\n intersectsTriangle(triangle) {\\n if (this.isEmpty()) {\\n return false;\\n }\\n this.getCenter(_center);\\n _extents.subVectors(this.max, _center);\\n _v0.subVectors(triangle.a, _center);\\n _v13.subVectors(triangle.b, _center);\\n _v2.subVectors(triangle.c, _center);\\n _f0.subVectors(_v13, _v0);\\n _f1.subVectors(_v2, _v13);\\n _f2.subVectors(_v0, _v2);\\n let axes = [\\n 0,\\n -_f0.z,\\n _f0.y,\\n 0,\\n -_f1.z,\\n _f1.y,\\n 0,\\n -_f2.z,\\n _f2.y,\\n _f0.z,\\n 0,\\n -_f0.x,\\n _f1.z,\\n 0,\\n -_f1.x,\\n _f2.z,\\n 0,\\n -_f2.x,\\n -_f0.y,\\n _f0.x,\\n 0,\\n -_f1.y,\\n _f1.x,\\n 0,\\n -_f2.y,\\n _f2.x,\\n 0\\n ];\\n if (!satForAxes(axes, _v0, _v13, _v2, _extents)) {\\n return false;\\n }\\n axes = [1, 0, 0, 0, 1, 0, 0, 0, 1];\\n if (!satForAxes(axes, _v0, _v13, _v2, _extents)) {\\n return false;\\n }\\n _triangleNormal.crossVectors(_f0, _f1);\\n axes = [_triangleNormal.x, _triangleNormal.y, _triangleNormal.z];\\n return satForAxes(axes, _v0, _v13, _v2, _extents);\\n }\\n clampPoint(point, target) {\\n return target.copy(point).clamp(this.min, this.max);\\n }\\n distanceToPoint(point) {\\n const clampedPoint = _vector2.copy(point).clamp(this.min, this.max);\\n return clampedPoint.sub(point).length();\\n }\\n getBoundingSphere(target) {\\n this.getCenter(target.center);\\n target.radius = this.getSize(_vector2).length() * 0.5;\\n return target;\\n }\\n intersect(box) {\\n this.min.max(box.min);\\n this.max.min(box.max);\\n if (this.isEmpty())\\n this.makeEmpty();\\n return this;\\n }\\n union(box) {\\n this.min.min(box.min);\\n this.max.max(box.max);\\n return this;\\n }\\n applyMatrix4(matrix) {\\n if (this.isEmpty())\\n return this;\\n _points[0].set(this.min.x, this.min.y, this.min.z).applyMatrix4(matrix);\\n _points[1].set(this.min.x, this.min.y, this.max.z).applyMatrix4(matrix);\\n _points[2].set(this.min.x, this.max.y, this.min.z).applyMatrix4(matrix);\\n _points[3].set(this.min.x, this.max.y, this.max.z).applyMatrix4(matrix);\\n _points[4].set(this.max.x, this.min.y, this.min.z).applyMatrix4(matrix);\\n _points[5].set(this.max.x, this.min.y, this.max.z).applyMatrix4(matrix);\\n _points[6].set(this.max.x, this.max.y, this.min.z).applyMatrix4(matrix);\\n _points[7].set(this.max.x, this.max.y, this.max.z).applyMatrix4(matrix);\\n this.setFromPoints(_points);\\n return this;\\n }\\n translate(offset) {\\n this.min.add(offset);\\n this.max.add(offset);\\n return this;\\n }\\n equals(box) {\\n return box.min.equals(this.min) && box.max.equals(this.max);\\n }\\n};\\nBox3.prototype.isBox3 = true;\\nvar _points = [\\n /* @__PURE__ */ new Vector3(),\\n /* @__PURE__ */ new Vector3(),\\n /* @__PURE__ */ new Vector3(),\\n /* @__PURE__ */ new Vector3(),\\n /* @__PURE__ */ new Vector3(),\\n /* @__PURE__ */ new Vector3(),\\n /* @__PURE__ */ new Vector3(),\\n /* @__PURE__ */ new Vector3()\\n];\\nvar _vector2 = /* @__PURE__ */ new Vector3();\\nvar _box = /* @__PURE__ */ new Box3();\\nvar _v0 = /* @__PURE__ */ new Vector3();\\nvar _v13 = /* @__PURE__ */ new Vector3();\\nvar _v2 = /* @__PURE__ */ new Vector3();\\nvar _f0 = /* @__PURE__ */ new Vector3();\\nvar _f1 = /* @__PURE__ */ new Vector3();\\nvar _f2 = /* @__PURE__ */ new Vector3();\\nvar _center = /* @__PURE__ */ new Vector3();\\nvar _extents = /* @__PURE__ */ new Vector3();\\nvar _triangleNormal = /* @__PURE__ */ new Vector3();\\nvar _testAxis = /* @__PURE__ */ new Vector3();\\nfunction satForAxes(axes, v0, v1, v2, extents) {\\n for (let i = 0, j = axes.length - 3; i <= j; i += 3) {\\n _testAxis.fromArray(axes, i);\\n const r = extents.x * Math.abs(_testAxis.x) + extents.y * Math.abs(_testAxis.y) + extents.z * Math.abs(_testAxis.z);\\n const p0 = v0.dot(_testAxis);\\n const p1 = v1.dot(_testAxis);\\n const p2 = v2.dot(_testAxis);\\n if (Math.max(-Math.max(p0, p1, p2), Math.min(p0, p1, p2)) > r) {\\n return false;\\n }\\n }\\n return true;\\n}\\n\\n// ../../../node_modules/three/src/math/Sphere.js\\nvar _box2 = /* @__PURE__ */ new Box3();\\nvar _v14 = /* @__PURE__ */ new Vector3();\\nvar _toFarthestPoint = /* @__PURE__ */ new Vector3();\\nvar _toPoint = /* @__PURE__ */ new Vector3();\\nvar Sphere = class {\\n constructor(center = new Vector3(), radius = -1) {\\n this.center = center;\\n this.radius = radius;\\n }\\n set(center, radius) {\\n this.center.copy(center);\\n this.radius = radius;\\n return this;\\n }\\n setFromPoints(points2, optionalCenter) {\\n const center = this.center;\\n if (optionalCenter !== void 0) {\\n center.copy(optionalCenter);\\n } else {\\n _box2.setFromPoints(points2).getCenter(center);\\n }\\n let maxRadiusSq = 0;\\n for (let i = 0, il = points2.length; i < il; i++) {\\n maxRadiusSq = Math.max(maxRadiusSq, center.distanceToSquared(points2[i]));\\n }\\n this.radius = Math.sqrt(maxRadiusSq);\\n return this;\\n }\\n copy(sphere) {\\n this.center.copy(sphere.center);\\n this.radius = sphere.radius;\\n return this;\\n }\\n isEmpty() {\\n return this.radius < 0;\\n }\\n makeEmpty() {\\n this.center.set(0, 0, 0);\\n this.radius = -1;\\n return this;\\n }\\n containsPoint(point) {\\n return point.distanceToSquared(this.center) <= this.radius * this.radius;\\n }\\n distanceToPoint(point) {\\n return point.distanceTo(this.center) - this.radius;\\n }\\n intersectsSphere(sphere) {\\n const radiusSum = this.radius + sphere.radius;\\n return sphere.center.distanceToSquared(this.center) <= radiusSum * radiusSum;\\n }\\n intersectsBox(box) {\\n return box.intersectsSphere(this);\\n }\\n intersectsPlane(plane) {\\n return Math.abs(plane.distanceToPoint(this.center)) <= this.radius;\\n }\\n clampPoint(point, target) {\\n const deltaLengthSq = this.center.distanceToSquared(point);\\n target.copy(point);\\n if (deltaLengthSq > this.radius * this.radius) {\\n target.sub(this.center).normalize();\\n target.multiplyScalar(this.radius).add(this.center);\\n }\\n return target;\\n }\\n getBoundingBox(target) {\\n if (this.isEmpty()) {\\n target.makeEmpty();\\n return target;\\n }\\n target.set(this.center, this.center);\\n target.expandByScalar(this.radius);\\n return target;\\n }\\n applyMatrix4(matrix) {\\n this.center.applyMatrix4(matrix);\\n this.radius = this.radius * matrix.getMaxScaleOnAxis();\\n return this;\\n }\\n translate(offset) {\\n this.center.add(offset);\\n return this;\\n }\\n expandByPoint(point) {\\n _toPoint.subVectors(point, this.center);\\n const lengthSq = _toPoint.lengthSq();\\n if (lengthSq > this.radius * this.radius) {\\n const length = Math.sqrt(lengthSq);\\n const missingRadiusHalf = (length - this.radius) * 0.5;\\n this.center.add(_toPoint.multiplyScalar(missingRadiusHalf / length));\\n this.radius += missingRadiusHalf;\\n }\\n return this;\\n }\\n union(sphere) {\\n _toFarthestPoint.subVectors(sphere.center, this.center).normalize().multiplyScalar(sphere.radius);\\n this.expandByPoint(_v14.copy(sphere.center).add(_toFarthestPoint));\\n this.expandByPoint(_v14.copy(sphere.center).sub(_toFarthestPoint));\\n return this;\\n }\\n equals(sphere) {\\n return sphere.center.equals(this.center) && sphere.radius === this.radius;\\n }\\n clone() {\\n return new this.constructor().copy(this);\\n }\\n};\\n\\n// ../../../node_modules/three/src/math/Plane.js\\nvar _vector1 = /* @__PURE__ */ new Vector3();\\nvar _vector22 = /* @__PURE__ */ new Vector3();\\nvar _normalMatrix = /* @__PURE__ */ new Matrix3();\\nvar Plane = class {\\n constructor(normal = new Vector3(1, 0, 0), constant = 0) {\\n this.normal = normal;\\n this.constant = constant;\\n }\\n set(normal, constant) {\\n this.normal.copy(normal);\\n this.constant = constant;\\n return this;\\n }\\n setComponents(x, y, z, w) {\\n this.normal.set(x, y, z);\\n this.constant = w;\\n return this;\\n }\\n setFromNormalAndCoplanarPoint(normal, point) {\\n this.normal.copy(normal);\\n this.constant = -point.dot(this.normal);\\n return this;\\n }\\n setFromCoplanarPoints(a, b, c) {\\n const normal = _vector1.subVectors(c, b).cross(_vector22.subVectors(a, b)).normalize();\\n this.setFromNormalAndCoplanarPoint(normal, a);\\n return this;\\n }\\n copy(plane) {\\n this.normal.copy(plane.normal);\\n this.constant = plane.constant;\\n return this;\\n }\\n normalize() {\\n const inverseNormalLength = 1 / this.normal.length();\\n this.normal.multiplyScalar(inverseNormalLength);\\n this.constant *= inverseNormalLength;\\n return this;\\n }\\n negate() {\\n this.constant *= -1;\\n this.normal.negate();\\n return this;\\n }\\n distanceToPoint(point) {\\n return this.normal.dot(point) + this.constant;\\n }\\n distanceToSphere(sphere) {\\n return this.distanceToPoint(sphere.center) - sphere.radius;\\n }\\n projectPoint(point, target) {\\n return target.copy(this.normal).multiplyScalar(-this.distanceToPoint(point)).add(point);\\n }\\n intersectLine(line, target) {\\n const direction = line.delta(_vector1);\\n const denominator = this.normal.dot(direction);\\n if (denominator === 0) {\\n if (this.distanceToPoint(line.start) === 0) {\\n return target.copy(line.start);\\n }\\n return null;\\n }\\n const t = -(line.start.dot(this.normal) + this.constant) / denominator;\\n if (t < 0 || t > 1) {\\n return null;\\n }\\n return target.copy(direction).multiplyScalar(t).add(line.start);\\n }\\n intersectsLine(line) {\\n const startSign = this.distanceToPoint(line.start);\\n const endSign = this.distanceToPoint(line.end);\\n return startSign < 0 && endSign > 0 || endSign < 0 && startSign > 0;\\n }\\n intersectsBox(box) {\\n return box.intersectsPlane(this);\\n }\\n intersectsSphere(sphere) {\\n return sphere.intersectsPlane(this);\\n }\\n coplanarPoint(target) {\\n return target.copy(this.normal).multiplyScalar(-this.constant);\\n }\\n applyMatrix4(matrix, optionalNormalMatrix) {\\n const normalMatrix = optionalNormalMatrix || _normalMatrix.getNormalMatrix(matrix);\\n const referencePoint = this.coplanarPoint(_vector1).applyMatrix4(matrix);\\n const normal = this.normal.applyMatrix3(normalMatrix).normalize();\\n this.constant = -referencePoint.dot(normal);\\n return this;\\n }\\n translate(offset) {\\n this.constant -= offset.dot(this.normal);\\n return this;\\n }\\n equals(plane) {\\n return plane.normal.equals(this.normal) && plane.constant === this.constant;\\n }\\n clone() {\\n return new this.constructor().copy(this);\\n }\\n};\\nPlane.prototype.isPlane = true;\\n\\n// ../../../node_modules/three/src/math/Frustum.js\\nvar _sphere = /* @__PURE__ */ new Sphere();\\nvar _vector3 = /* @__PURE__ */ new Vector3();\\nvar Frustum = class {\\n constructor(p0 = new Plane(), p1 = new Plane(), p2 = new Plane(), p3 = new Plane(), p4 = new Plane(), p5 = new Plane()) {\\n this.planes = [p0, p1, p2, p3, p4, p5];\\n }\\n set(p0, p1, p2, p3, p4, p5) {\\n const planes = this.planes;\\n planes[0].copy(p0);\\n planes[1].copy(p1);\\n planes[2].copy(p2);\\n planes[3].copy(p3);\\n planes[4].copy(p4);\\n planes[5].copy(p5);\\n return this;\\n }\\n copy(frustum) {\\n const planes = this.planes;\\n for (let i = 0; i < 6; i++) {\\n planes[i].copy(frustum.planes[i]);\\n }\\n return this;\\n }\\n setFromProjectionMatrix(m) {\\n const planes = this.planes;\\n const me = m.elements;\\n const me0 = me[0], me1 = me[1], me2 = me[2], me3 = me[3];\\n const me4 = me[4], me5 = me[5], me6 = me[6], me7 = me[7];\\n const me8 = me[8], me9 = me[9], me10 = me[10], me11 = me[11];\\n const me12 = me[12], me13 = me[13], me14 = me[14], me15 = me[15];\\n planes[0].setComponents(me3 - me0, me7 - me4, me11 - me8, me15 - me12).normalize();\\n planes[1].setComponents(me3 + me0, me7 + me4, me11 + me8, me15 + me12).normalize();\\n planes[2].setComponents(me3 + me1, me7 + me5, me11 + me9, me15 + me13).normalize();\\n planes[3].setComponents(me3 - me1, me7 - me5, me11 - me9, me15 - me13).normalize();\\n planes[4].setComponents(me3 - me2, me7 - me6, me11 - me10, me15 - me14).normalize();\\n planes[5].setComponents(me3 + me2, me7 + me6, me11 + me10, me15 + me14).normalize();\\n return this;\\n }\\n intersectsObject(object) {\\n const geometry = object.geometry;\\n if (geometry.boundingSphere === null)\\n geometry.computeBoundingSphere();\\n _sphere.copy(geometry.boundingSphere).applyMatrix4(object.matrixWorld);\\n return this.intersectsSphere(_sphere);\\n }\\n intersectsSprite(sprite2) {\\n _sphere.center.set(0, 0, 0);\\n _sphere.radius = 0.7071067811865476;\\n _sphere.applyMatrix4(sprite2.matrixWorld);\\n return this.intersectsSphere(_sphere);\\n }\\n intersectsSphere(sphere) {\\n const planes = this.planes;\\n const center = sphere.center;\\n const negRadius = -sphere.radius;\\n for (let i = 0; i < 6; i++) {\\n const distance = planes[i].distanceToPoint(center);\\n if (distance < negRadius) {\\n return false;\\n }\\n }\\n return true;\\n }\\n intersectsBox(box) {\\n const planes = this.planes;\\n for (let i = 0; i < 6; i++) {\\n const plane = planes[i];\\n _vector3.x = plane.normal.x > 0 ? box.max.x : box.min.x;\\n _vector3.y = plane.normal.y > 0 ? box.max.y : box.min.y;\\n _vector3.z = plane.normal.z > 0 ? box.max.z : box.min.z;\\n if (plane.distanceToPoint(_vector3) < 0) {\\n return false;\\n }\\n }\\n return true;\\n }\\n containsPoint(point) {\\n const planes = this.planes;\\n for (let i = 0; i < 6; i++) {\\n if (planes[i].distanceToPoint(point) < 0) {\\n return false;\\n }\\n }\\n return true;\\n }\\n clone() {\\n return new this.constructor().copy(this);\\n }\\n};\\n\\n// ../../../node_modules/three/src/math/Vector4.js\\nvar Vector4 = class {\\n constructor(x = 0, y = 0, z = 0, w = 1) {\\n this.x = x;\\n this.y = y;\\n this.z = z;\\n this.w = w;\\n }\\n get width() {\\n return this.z;\\n }\\n set width(value) {\\n this.z = value;\\n }\\n get height() {\\n return this.w;\\n }\\n set height(value) {\\n this.w = value;\\n }\\n set(x, y, z, w) {\\n this.x = x;\\n this.y = y;\\n this.z = z;\\n this.w = w;\\n return this;\\n }\\n setScalar(scalar) {\\n this.x = scalar;\\n this.y = scalar;\\n this.z = scalar;\\n this.w = scalar;\\n return this;\\n }\\n setX(x) {\\n this.x = x;\\n return this;\\n }\\n setY(y) {\\n this.y = y;\\n return this;\\n }\\n setZ(z) {\\n this.z = z;\\n return this;\\n }\\n setW(w) {\\n this.w = w;\\n return this;\\n }\\n setComponent(index, value) {\\n switch (index) {\\n case 0:\\n this.x = value;\\n break;\\n case 1:\\n this.y = value;\\n break;\\n case 2:\\n this.z = value;\\n break;\\n case 3:\\n this.w = value;\\n break;\\n default:\\n throw new Error(\\\\\\\"index is out of range: \\\\\\\" + index);\\n }\\n return this;\\n }\\n getComponent(index) {\\n switch (index) {\\n case 0:\\n return this.x;\\n case 1:\\n return this.y;\\n case 2:\\n return this.z;\\n case 3:\\n return this.w;\\n default:\\n throw new Error(\\\\\\\"index is out of range: \\\\\\\" + index);\\n }\\n }\\n clone() {\\n return new this.constructor(this.x, this.y, this.z, this.w);\\n }\\n copy(v) {\\n this.x = v.x;\\n this.y = v.y;\\n this.z = v.z;\\n this.w = v.w !== void 0 ? v.w : 1;\\n return this;\\n }\\n add(v, w) {\\n if (w !== void 0) {\\n console.warn(\\\\\\\"THREE.Vector4: .add() now only accepts one argument. Use .addVectors( a, b ) instead.\\\\\\\");\\n return this.addVectors(v, w);\\n }\\n this.x += v.x;\\n this.y += v.y;\\n this.z += v.z;\\n this.w += v.w;\\n return this;\\n }\\n addScalar(s) {\\n this.x += s;\\n this.y += s;\\n this.z += s;\\n this.w += s;\\n return this;\\n }\\n addVectors(a, b) {\\n this.x = a.x + b.x;\\n this.y = a.y + b.y;\\n this.z = a.z + b.z;\\n this.w = a.w + b.w;\\n return this;\\n }\\n addScaledVector(v, s) {\\n this.x += v.x * s;\\n this.y += v.y * s;\\n this.z += v.z * s;\\n this.w += v.w * s;\\n return this;\\n }\\n sub(v, w) {\\n if (w !== void 0) {\\n console.warn(\\\\\\\"THREE.Vector4: .sub() now only accepts one argument. Use .subVectors( a, b ) instead.\\\\\\\");\\n return this.subVectors(v, w);\\n }\\n this.x -= v.x;\\n this.y -= v.y;\\n this.z -= v.z;\\n this.w -= v.w;\\n return this;\\n }\\n subScalar(s) {\\n this.x -= s;\\n this.y -= s;\\n this.z -= s;\\n this.w -= s;\\n return this;\\n }\\n subVectors(a, b) {\\n this.x = a.x - b.x;\\n this.y = a.y - b.y;\\n this.z = a.z - b.z;\\n this.w = a.w - b.w;\\n return this;\\n }\\n multiply(v) {\\n this.x *= v.x;\\n this.y *= v.y;\\n this.z *= v.z;\\n this.w *= v.w;\\n return this;\\n }\\n multiplyScalar(scalar) {\\n this.x *= scalar;\\n this.y *= scalar;\\n this.z *= scalar;\\n this.w *= scalar;\\n return this;\\n }\\n applyMatrix4(m) {\\n const x = this.x, y = this.y, z = this.z, w = this.w;\\n const e = m.elements;\\n this.x = e[0] * x + e[4] * y + e[8] * z + e[12] * w;\\n this.y = e[1] * x + e[5] * y + e[9] * z + e[13] * w;\\n this.z = e[2] * x + e[6] * y + e[10] * z + e[14] * w;\\n this.w = e[3] * x + e[7] * y + e[11] * z + e[15] * w;\\n return this;\\n }\\n divideScalar(scalar) {\\n return this.multiplyScalar(1 / scalar);\\n }\\n setAxisAngleFromQuaternion(q) {\\n this.w = 2 * Math.acos(q.w);\\n const s = Math.sqrt(1 - q.w * q.w);\\n if (s < 1e-4) {\\n this.x = 1;\\n this.y = 0;\\n this.z = 0;\\n } else {\\n this.x = q.x / s;\\n this.y = q.y / s;\\n this.z = q.z / s;\\n }\\n return this;\\n }\\n setAxisAngleFromRotationMatrix(m) {\\n let angle, x, y, z;\\n const epsilon = 0.01, epsilon2 = 0.1, te = m.elements, m11 = te[0], m12 = te[4], m13 = te[8], m21 = te[1], m22 = te[5], m23 = te[9], m31 = te[2], m32 = te[6], m33 = te[10];\\n if (Math.abs(m12 - m21) < epsilon && Math.abs(m13 - m31) < epsilon && Math.abs(m23 - m32) < epsilon) {\\n if (Math.abs(m12 + m21) < epsilon2 && Math.abs(m13 + m31) < epsilon2 && Math.abs(m23 + m32) < epsilon2 && Math.abs(m11 + m22 + m33 - 3) < epsilon2) {\\n this.set(1, 0, 0, 0);\\n return this;\\n }\\n angle = Math.PI;\\n const xx = (m11 + 1) / 2;\\n const yy = (m22 + 1) / 2;\\n const zz = (m33 + 1) / 2;\\n const xy = (m12 + m21) / 4;\\n const xz = (m13 + m31) / 4;\\n const yz = (m23 + m32) / 4;\\n if (xx > yy && xx > zz) {\\n if (xx < epsilon) {\\n x = 0;\\n y = 0.707106781;\\n z = 0.707106781;\\n } else {\\n x = Math.sqrt(xx);\\n y = xy / x;\\n z = xz / x;\\n }\\n } else if (yy > zz) {\\n if (yy < epsilon) {\\n x = 0.707106781;\\n y = 0;\\n z = 0.707106781;\\n } else {\\n y = Math.sqrt(yy);\\n x = xy / y;\\n z = yz / y;\\n }\\n } else {\\n if (zz < epsilon) {\\n x = 0.707106781;\\n y = 0.707106781;\\n z = 0;\\n } else {\\n z = Math.sqrt(zz);\\n x = xz / z;\\n y = yz / z;\\n }\\n }\\n this.set(x, y, z, angle);\\n return this;\\n }\\n let s = Math.sqrt((m32 - m23) * (m32 - m23) + (m13 - m31) * (m13 - m31) + (m21 - m12) * (m21 - m12));\\n if (Math.abs(s) < 1e-3)\\n s = 1;\\n this.x = (m32 - m23) / s;\\n this.y = (m13 - m31) / s;\\n this.z = (m21 - m12) / s;\\n this.w = Math.acos((m11 + m22 + m33 - 1) / 2);\\n return this;\\n }\\n min(v) {\\n this.x = Math.min(this.x, v.x);\\n this.y = Math.min(this.y, v.y);\\n this.z = Math.min(this.z, v.z);\\n this.w = Math.min(this.w, v.w);\\n return this;\\n }\\n max(v) {\\n this.x = Math.max(this.x, v.x);\\n this.y = Math.max(this.y, v.y);\\n this.z = Math.max(this.z, v.z);\\n this.w = Math.max(this.w, v.w);\\n return this;\\n }\\n clamp(min, max) {\\n this.x = Math.max(min.x, Math.min(max.x, this.x));\\n this.y = Math.max(min.y, Math.min(max.y, this.y));\\n this.z = Math.max(min.z, Math.min(max.z, this.z));\\n this.w = Math.max(min.w, Math.min(max.w, this.w));\\n return this;\\n }\\n clampScalar(minVal, maxVal) {\\n this.x = Math.max(minVal, Math.min(maxVal, this.x));\\n this.y = Math.max(minVal, Math.min(maxVal, this.y));\\n this.z = Math.max(minVal, Math.min(maxVal, this.z));\\n this.w = Math.max(minVal, Math.min(maxVal, this.w));\\n return this;\\n }\\n clampLength(min, max) {\\n const length = this.length();\\n return this.divideScalar(length || 1).multiplyScalar(Math.max(min, Math.min(max, length)));\\n }\\n floor() {\\n this.x = Math.floor(this.x);\\n this.y = Math.floor(this.y);\\n this.z = Math.floor(this.z);\\n this.w = Math.floor(this.w);\\n return this;\\n }\\n ceil() {\\n this.x = Math.ceil(this.x);\\n this.y = Math.ceil(this.y);\\n this.z = Math.ceil(this.z);\\n this.w = Math.ceil(this.w);\\n return this;\\n }\\n round() {\\n this.x = Math.round(this.x);\\n this.y = Math.round(this.y);\\n this.z = Math.round(this.z);\\n this.w = Math.round(this.w);\\n return this;\\n }\\n roundToZero() {\\n this.x = this.x < 0 ? Math.ceil(this.x) : Math.floor(this.x);\\n this.y = this.y < 0 ? Math.ceil(this.y) : Math.floor(this.y);\\n this.z = this.z < 0 ? Math.ceil(this.z) : Math.floor(this.z);\\n this.w = this.w < 0 ? Math.ceil(this.w) : Math.floor(this.w);\\n return this;\\n }\\n negate() {\\n this.x = -this.x;\\n this.y = -this.y;\\n this.z = -this.z;\\n this.w = -this.w;\\n return this;\\n }\\n dot(v) {\\n return this.x * v.x + this.y * v.y + this.z * v.z + this.w * v.w;\\n }\\n lengthSq() {\\n return this.x * this.x + this.y * this.y + this.z * this.z + this.w * this.w;\\n }\\n length() {\\n return Math.sqrt(this.x * this.x + this.y * this.y + this.z * this.z + this.w * this.w);\\n }\\n manhattanLength() {\\n return Math.abs(this.x) + Math.abs(this.y) + Math.abs(this.z) + Math.abs(this.w);\\n }\\n normalize() {\\n return this.divideScalar(this.length() || 1);\\n }\\n setLength(length) {\\n return this.normalize().multiplyScalar(length);\\n }\\n lerp(v, alpha) {\\n this.x += (v.x - this.x) * alpha;\\n this.y += (v.y - this.y) * alpha;\\n this.z += (v.z - this.z) * alpha;\\n this.w += (v.w - this.w) * alpha;\\n return this;\\n }\\n lerpVectors(v1, v2, alpha) {\\n this.x = v1.x + (v2.x - v1.x) * alpha;\\n this.y = v1.y + (v2.y - v1.y) * alpha;\\n this.z = v1.z + (v2.z - v1.z) * alpha;\\n this.w = v1.w + (v2.w - v1.w) * alpha;\\n return this;\\n }\\n equals(v) {\\n return v.x === this.x && v.y === this.y && v.z === this.z && v.w === this.w;\\n }\\n fromArray(array, offset = 0) {\\n this.x = array[offset];\\n this.y = array[offset + 1];\\n this.z = array[offset + 2];\\n this.w = array[offset + 3];\\n return this;\\n }\\n toArray(array = [], offset = 0) {\\n array[offset] = this.x;\\n array[offset + 1] = this.y;\\n array[offset + 2] = this.z;\\n array[offset + 3] = this.w;\\n return array;\\n }\\n fromBufferAttribute(attribute, index, offset) {\\n if (offset !== void 0) {\\n console.warn(\\\\\\\"THREE.Vector4: offset has been removed from .fromBufferAttribute().\\\\\\\");\\n }\\n this.x = attribute.getX(index);\\n this.y = attribute.getY(index);\\n this.z = attribute.getZ(index);\\n this.w = attribute.getW(index);\\n return this;\\n }\\n random() {\\n this.x = Math.random();\\n this.y = Math.random();\\n this.z = Math.random();\\n this.w = Math.random();\\n return this;\\n }\\n *[Symbol.iterator]() {\\n yield this.x;\\n yield this.y;\\n yield this.z;\\n yield this.w;\\n }\\n};\\nVector4.prototype.isVector4 = true;\\n\\n// ../../../node_modules/three/src/renderers/webgl/WebGLAnimation.js\\nfunction WebGLAnimation() {\\n let context = null;\\n let isAnimating = false;\\n let animationLoop = null;\\n let requestId = null;\\n function onAnimationFrame(time, frame) {\\n animationLoop(time, frame);\\n requestId = context.requestAnimationFrame(onAnimationFrame);\\n }\\n return {\\n start: function() {\\n if (isAnimating === true)\\n return;\\n if (animationLoop === null)\\n return;\\n requestId = context.requestAnimationFrame(onAnimationFrame);\\n isAnimating = true;\\n },\\n stop: function() {\\n context.cancelAnimationFrame(requestId);\\n isAnimating = false;\\n },\\n setAnimationLoop: function(callback) {\\n animationLoop = callback;\\n },\\n setContext: function(value) {\\n context = value;\\n }\\n };\\n}\\n\\n// ../../../node_modules/three/src/renderers/webgl/WebGLAttributes.js\\nfunction WebGLAttributes(gl, capabilities) {\\n const isWebGL2 = capabilities.isWebGL2;\\n const buffers = new WeakMap();\\n function createBuffer(attribute, bufferType) {\\n const array = attribute.array;\\n const usage = attribute.usage;\\n const buffer = gl.createBuffer();\\n gl.bindBuffer(bufferType, buffer);\\n gl.bufferData(bufferType, array, usage);\\n attribute.onUploadCallback();\\n let type = gl.FLOAT;\\n if (array instanceof Float32Array) {\\n type = gl.FLOAT;\\n } else if (array instanceof Float64Array) {\\n console.warn(\\\\\\\"THREE.WebGLAttributes: Unsupported data buffer format: Float64Array.\\\\\\\");\\n } else if (array instanceof Uint16Array) {\\n if (attribute.isFloat16BufferAttribute) {\\n if (isWebGL2) {\\n type = gl.HALF_FLOAT;\\n } else {\\n console.warn(\\\\\\\"THREE.WebGLAttributes: Usage of Float16BufferAttribute requires WebGL2.\\\\\\\");\\n }\\n } else {\\n type = gl.UNSIGNED_SHORT;\\n }\\n } else if (array instanceof Int16Array) {\\n type = gl.SHORT;\\n } else if (array instanceof Uint32Array) {\\n type = gl.UNSIGNED_INT;\\n } else if (array instanceof Int32Array) {\\n type = gl.INT;\\n } else if (array instanceof Int8Array) {\\n type = gl.BYTE;\\n } else if (array instanceof Uint8Array) {\\n type = gl.UNSIGNED_BYTE;\\n } else if (array instanceof Uint8ClampedArray) {\\n type = gl.UNSIGNED_BYTE;\\n }\\n return {\\n buffer,\\n type,\\n bytesPerElement: array.BYTES_PER_ELEMENT,\\n version: attribute.version\\n };\\n }\\n function updateBuffer(buffer, attribute, bufferType) {\\n const array = attribute.array;\\n const updateRange = attribute.updateRange;\\n gl.bindBuffer(bufferType, buffer);\\n if (updateRange.count === -1) {\\n gl.bufferSubData(bufferType, 0, array);\\n } else {\\n if (isWebGL2) {\\n gl.bufferSubData(bufferType, updateRange.offset * array.BYTES_PER_ELEMENT, array, updateRange.offset, updateRange.count);\\n } else {\\n gl.bufferSubData(bufferType, updateRange.offset * array.BYTES_PER_ELEMENT, array.subarray(updateRange.offset, updateRange.offset + updateRange.count));\\n }\\n updateRange.count = -1;\\n }\\n }\\n function get(attribute) {\\n if (attribute.isInterleavedBufferAttribute)\\n attribute = attribute.data;\\n return buffers.get(attribute);\\n }\\n function remove(attribute) {\\n if (attribute.isInterleavedBufferAttribute)\\n attribute = attribute.data;\\n const data = buffers.get(attribute);\\n if (data) {\\n gl.deleteBuffer(data.buffer);\\n buffers.delete(attribute);\\n }\\n }\\n function update(attribute, bufferType) {\\n if (attribute.isGLBufferAttribute) {\\n const cached = buffers.get(attribute);\\n if (!cached || cached.version < attribute.version) {\\n buffers.set(attribute, {\\n buffer: attribute.buffer,\\n type: attribute.type,\\n bytesPerElement: attribute.elementSize,\\n version: attribute.version\\n });\\n }\\n return;\\n }\\n if (attribute.isInterleavedBufferAttribute)\\n attribute = attribute.data;\\n const data = buffers.get(attribute);\\n if (data === void 0) {\\n buffers.set(attribute, createBuffer(attribute, bufferType));\\n } else if (data.version < attribute.version) {\\n updateBuffer(data.buffer, attribute, bufferType);\\n data.version = attribute.version;\\n }\\n }\\n return {\\n get,\\n remove,\\n update\\n };\\n}\\n\\n// ../../../node_modules/three/src/math/Vector2.js\\nvar Vector2 = class {\\n constructor(x = 0, y = 0) {\\n this.x = x;\\n this.y = y;\\n }\\n get width() {\\n return this.x;\\n }\\n set width(value) {\\n this.x = value;\\n }\\n get height() {\\n return this.y;\\n }\\n set height(value) {\\n this.y = value;\\n }\\n set(x, y) {\\n this.x = x;\\n this.y = y;\\n return this;\\n }\\n setScalar(scalar) {\\n this.x = scalar;\\n this.y = scalar;\\n return this;\\n }\\n setX(x) {\\n this.x = x;\\n return this;\\n }\\n setY(y) {\\n this.y = y;\\n return this;\\n }\\n setComponent(index, value) {\\n switch (index) {\\n case 0:\\n this.x = value;\\n break;\\n case 1:\\n this.y = value;\\n break;\\n default:\\n throw new Error(\\\\\\\"index is out of range: \\\\\\\" + index);\\n }\\n return this;\\n }\\n getComponent(index) {\\n switch (index) {\\n case 0:\\n return this.x;\\n case 1:\\n return this.y;\\n default:\\n throw new Error(\\\\\\\"index is out of range: \\\\\\\" + index);\\n }\\n }\\n clone() {\\n return new this.constructor(this.x, this.y);\\n }\\n copy(v) {\\n this.x = v.x;\\n this.y = v.y;\\n return this;\\n }\\n add(v, w) {\\n if (w !== void 0) {\\n console.warn(\\\\\\\"THREE.Vector2: .add() now only accepts one argument. Use .addVectors( a, b ) instead.\\\\\\\");\\n return this.addVectors(v, w);\\n }\\n this.x += v.x;\\n this.y += v.y;\\n return this;\\n }\\n addScalar(s) {\\n this.x += s;\\n this.y += s;\\n return this;\\n }\\n addVectors(a, b) {\\n this.x = a.x + b.x;\\n this.y = a.y + b.y;\\n return this;\\n }\\n addScaledVector(v, s) {\\n this.x += v.x * s;\\n this.y += v.y * s;\\n return this;\\n }\\n sub(v, w) {\\n if (w !== void 0) {\\n console.warn(\\\\\\\"THREE.Vector2: .sub() now only accepts one argument. Use .subVectors( a, b ) instead.\\\\\\\");\\n return this.subVectors(v, w);\\n }\\n this.x -= v.x;\\n this.y -= v.y;\\n return this;\\n }\\n subScalar(s) {\\n this.x -= s;\\n this.y -= s;\\n return this;\\n }\\n subVectors(a, b) {\\n this.x = a.x - b.x;\\n this.y = a.y - b.y;\\n return this;\\n }\\n multiply(v) {\\n this.x *= v.x;\\n this.y *= v.y;\\n return this;\\n }\\n multiplyScalar(scalar) {\\n this.x *= scalar;\\n this.y *= scalar;\\n return this;\\n }\\n divide(v) {\\n this.x /= v.x;\\n this.y /= v.y;\\n return this;\\n }\\n divideScalar(scalar) {\\n return this.multiplyScalar(1 / scalar);\\n }\\n applyMatrix3(m) {\\n const x = this.x, y = this.y;\\n const e = m.elements;\\n this.x = e[0] * x + e[3] * y + e[6];\\n this.y = e[1] * x + e[4] * y + e[7];\\n return this;\\n }\\n min(v) {\\n this.x = Math.min(this.x, v.x);\\n this.y = Math.min(this.y, v.y);\\n return this;\\n }\\n max(v) {\\n this.x = Math.max(this.x, v.x);\\n this.y = Math.max(this.y, v.y);\\n return this;\\n }\\n clamp(min, max) {\\n this.x = Math.max(min.x, Math.min(max.x, this.x));\\n this.y = Math.max(min.y, Math.min(max.y, this.y));\\n return this;\\n }\\n clampScalar(minVal, maxVal) {\\n this.x = Math.max(minVal, Math.min(maxVal, this.x));\\n this.y = Math.max(minVal, Math.min(maxVal, this.y));\\n return this;\\n }\\n clampLength(min, max) {\\n const length = this.length();\\n return this.divideScalar(length || 1).multiplyScalar(Math.max(min, Math.min(max, length)));\\n }\\n floor() {\\n this.x = Math.floor(this.x);\\n this.y = Math.floor(this.y);\\n return this;\\n }\\n ceil() {\\n this.x = Math.ceil(this.x);\\n this.y = Math.ceil(this.y);\\n return this;\\n }\\n round() {\\n this.x = Math.round(this.x);\\n this.y = Math.round(this.y);\\n return this;\\n }\\n roundToZero() {\\n this.x = this.x < 0 ? Math.ceil(this.x) : Math.floor(this.x);\\n this.y = this.y < 0 ? Math.ceil(this.y) : Math.floor(this.y);\\n return this;\\n }\\n negate() {\\n this.x = -this.x;\\n this.y = -this.y;\\n return this;\\n }\\n dot(v) {\\n return this.x * v.x + this.y * v.y;\\n }\\n cross(v) {\\n return this.x * v.y - this.y * v.x;\\n }\\n lengthSq() {\\n return this.x * this.x + this.y * this.y;\\n }\\n length() {\\n return Math.sqrt(this.x * this.x + this.y * this.y);\\n }\\n manhattanLength() {\\n return Math.abs(this.x) + Math.abs(this.y);\\n }\\n normalize() {\\n return this.divideScalar(this.length() || 1);\\n }\\n angle() {\\n const angle = Math.atan2(-this.y, -this.x) + Math.PI;\\n return angle;\\n }\\n distanceTo(v) {\\n return Math.sqrt(this.distanceToSquared(v));\\n }\\n distanceToSquared(v) {\\n const dx = this.x - v.x, dy = this.y - v.y;\\n return dx * dx + dy * dy;\\n }\\n manhattanDistanceTo(v) {\\n return Math.abs(this.x - v.x) + Math.abs(this.y - v.y);\\n }\\n setLength(length) {\\n return this.normalize().multiplyScalar(length);\\n }\\n lerp(v, alpha) {\\n this.x += (v.x - this.x) * alpha;\\n this.y += (v.y - this.y) * alpha;\\n return this;\\n }\\n lerpVectors(v1, v2, alpha) {\\n this.x = v1.x + (v2.x - v1.x) * alpha;\\n this.y = v1.y + (v2.y - v1.y) * alpha;\\n return this;\\n }\\n equals(v) {\\n return v.x === this.x && v.y === this.y;\\n }\\n fromArray(array, offset = 0) {\\n this.x = array[offset];\\n this.y = array[offset + 1];\\n return this;\\n }\\n toArray(array = [], offset = 0) {\\n array[offset] = this.x;\\n array[offset + 1] = this.y;\\n return array;\\n }\\n fromBufferAttribute(attribute, index, offset) {\\n if (offset !== void 0) {\\n console.warn(\\\\\\\"THREE.Vector2: offset has been removed from .fromBufferAttribute().\\\\\\\");\\n }\\n this.x = attribute.getX(index);\\n this.y = attribute.getY(index);\\n return this;\\n }\\n rotateAround(center, angle) {\\n const c = Math.cos(angle), s = Math.sin(angle);\\n const x = this.x - center.x;\\n const y = this.y - center.y;\\n this.x = x * c - y * s + center.x;\\n this.y = x * s + y * c + center.y;\\n return this;\\n }\\n random() {\\n this.x = Math.random();\\n this.y = Math.random();\\n return this;\\n }\\n *[Symbol.iterator]() {\\n yield this.x;\\n yield this.y;\\n }\\n};\\nVector2.prototype.isVector2 = true;\\n\\n// ../../../node_modules/three/src/math/Color.js\\nvar _colorKeywords = {\\n aliceblue: 15792383,\\n antiquewhite: 16444375,\\n aqua: 65535,\\n aquamarine: 8388564,\\n azure: 15794175,\\n beige: 16119260,\\n bisque: 16770244,\\n black: 0,\\n blanchedalmond: 16772045,\\n blue: 255,\\n blueviolet: 9055202,\\n brown: 10824234,\\n burlywood: 14596231,\\n cadetblue: 6266528,\\n chartreuse: 8388352,\\n chocolate: 13789470,\\n coral: 16744272,\\n cornflowerblue: 6591981,\\n cornsilk: 16775388,\\n crimson: 14423100,\\n cyan: 65535,\\n darkblue: 139,\\n darkcyan: 35723,\\n darkgoldenrod: 12092939,\\n darkgray: 11119017,\\n darkgreen: 25600,\\n darkgrey: 11119017,\\n darkkhaki: 12433259,\\n darkmagenta: 9109643,\\n darkolivegreen: 5597999,\\n darkorange: 16747520,\\n darkorchid: 10040012,\\n darkred: 9109504,\\n darksalmon: 15308410,\\n darkseagreen: 9419919,\\n darkslateblue: 4734347,\\n darkslategray: 3100495,\\n darkslategrey: 3100495,\\n darkturquoise: 52945,\\n darkviolet: 9699539,\\n deeppink: 16716947,\\n deepskyblue: 49151,\\n dimgray: 6908265,\\n dimgrey: 6908265,\\n dodgerblue: 2003199,\\n firebrick: 11674146,\\n floralwhite: 16775920,\\n forestgreen: 2263842,\\n fuchsia: 16711935,\\n gainsboro: 14474460,\\n ghostwhite: 16316671,\\n gold: 16766720,\\n goldenrod: 14329120,\\n gray: 8421504,\\n green: 32768,\\n greenyellow: 11403055,\\n grey: 8421504,\\n honeydew: 15794160,\\n hotpink: 16738740,\\n indianred: 13458524,\\n indigo: 4915330,\\n ivory: 16777200,\\n khaki: 15787660,\\n lavender: 15132410,\\n lavenderblush: 16773365,\\n lawngreen: 8190976,\\n lemonchiffon: 16775885,\\n lightblue: 11393254,\\n lightcoral: 15761536,\\n lightcyan: 14745599,\\n lightgoldenrodyellow: 16448210,\\n lightgray: 13882323,\\n lightgreen: 9498256,\\n lightgrey: 13882323,\\n lightpink: 16758465,\\n lightsalmon: 16752762,\\n lightseagreen: 2142890,\\n lightskyblue: 8900346,\\n lightslategray: 7833753,\\n lightslategrey: 7833753,\\n lightsteelblue: 11584734,\\n lightyellow: 16777184,\\n lime: 65280,\\n limegreen: 3329330,\\n linen: 16445670,\\n magenta: 16711935,\\n maroon: 8388608,\\n mediumaquamarine: 6737322,\\n mediumblue: 205,\\n mediumorchid: 12211667,\\n mediumpurple: 9662683,\\n mediumseagreen: 3978097,\\n mediumslateblue: 8087790,\\n mediumspringgreen: 64154,\\n mediumturquoise: 4772300,\\n mediumvioletred: 13047173,\\n midnightblue: 1644912,\\n mintcream: 16121850,\\n mistyrose: 16770273,\\n moccasin: 16770229,\\n navajowhite: 16768685,\\n navy: 128,\\n oldlace: 16643558,\\n olive: 8421376,\\n olivedrab: 7048739,\\n orange: 16753920,\\n orangered: 16729344,\\n orchid: 14315734,\\n palegoldenrod: 15657130,\\n palegreen: 10025880,\\n paleturquoise: 11529966,\\n palevioletred: 14381203,\\n papayawhip: 16773077,\\n peachpuff: 16767673,\\n peru: 13468991,\\n pink: 16761035,\\n plum: 14524637,\\n powderblue: 11591910,\\n purple: 8388736,\\n rebeccapurple: 6697881,\\n red: 16711680,\\n rosybrown: 12357519,\\n royalblue: 4286945,\\n saddlebrown: 9127187,\\n salmon: 16416882,\\n sandybrown: 16032864,\\n seagreen: 3050327,\\n seashell: 16774638,\\n sienna: 10506797,\\n silver: 12632256,\\n skyblue: 8900331,\\n slateblue: 6970061,\\n slategray: 7372944,\\n slategrey: 7372944,\\n snow: 16775930,\\n springgreen: 65407,\\n steelblue: 4620980,\\n tan: 13808780,\\n teal: 32896,\\n thistle: 14204888,\\n tomato: 16737095,\\n turquoise: 4251856,\\n violet: 15631086,\\n wheat: 16113331,\\n white: 16777215,\\n whitesmoke: 16119285,\\n yellow: 16776960,\\n yellowgreen: 10145074\\n};\\nvar _hslA = {h: 0, s: 0, l: 0};\\nvar _hslB = {h: 0, s: 0, l: 0};\\nfunction hue2rgb(p, q, t) {\\n if (t < 0)\\n t += 1;\\n if (t > 1)\\n t -= 1;\\n if (t < 1 / 6)\\n return p + (q - p) * 6 * t;\\n if (t < 1 / 2)\\n return q;\\n if (t < 2 / 3)\\n return p + (q - p) * 6 * (2 / 3 - t);\\n return p;\\n}\\nfunction SRGBToLinear(c) {\\n return c < 0.04045 ? c * 0.0773993808 : Math.pow(c * 0.9478672986 + 0.0521327014, 2.4);\\n}\\nfunction LinearToSRGB(c) {\\n return c < 31308e-7 ? c * 12.92 : 1.055 * Math.pow(c, 0.41666) - 0.055;\\n}\\nvar Color = class {\\n constructor(r, g, b) {\\n if (g === void 0 && b === void 0) {\\n return this.set(r);\\n }\\n return this.setRGB(r, g, b);\\n }\\n set(value) {\\n if (value && value.isColor) {\\n this.copy(value);\\n } else if (typeof value === \\\\\\\"number\\\\\\\") {\\n this.setHex(value);\\n } else if (typeof value === \\\\\\\"string\\\\\\\") {\\n this.setStyle(value);\\n }\\n return this;\\n }\\n setScalar(scalar) {\\n this.r = scalar;\\n this.g = scalar;\\n this.b = scalar;\\n return this;\\n }\\n setHex(hex) {\\n hex = Math.floor(hex);\\n this.r = (hex >> 16 & 255) / 255;\\n this.g = (hex >> 8 & 255) / 255;\\n this.b = (hex & 255) / 255;\\n return this;\\n }\\n setRGB(r, g, b) {\\n this.r = r;\\n this.g = g;\\n this.b = b;\\n return this;\\n }\\n setHSL(h, s, l) {\\n h = euclideanModulo(h, 1);\\n s = clamp(s, 0, 1);\\n l = clamp(l, 0, 1);\\n if (s === 0) {\\n this.r = this.g = this.b = l;\\n } else {\\n const p = l <= 0.5 ? l * (1 + s) : l + s - l * s;\\n const q = 2 * l - p;\\n this.r = hue2rgb(q, p, h + 1 / 3);\\n this.g = hue2rgb(q, p, h);\\n this.b = hue2rgb(q, p, h - 1 / 3);\\n }\\n return this;\\n }\\n setStyle(style) {\\n function handleAlpha(string) {\\n if (string === void 0)\\n return;\\n if (parseFloat(string) < 1) {\\n console.warn(\\\\\\\"THREE.Color: Alpha component of \\\\\\\" + style + \\\\\\\" will be ignored.\\\\\\\");\\n }\\n }\\n let m;\\n if (m = /^((?:rgb|hsl)a?)\\\\(([^\\\\)]*)\\\\)/.exec(style)) {\\n let color;\\n const name = m[1];\\n const components = m[2];\\n switch (name) {\\n case \\\\\\\"rgb\\\\\\\":\\n case \\\\\\\"rgba\\\\\\\":\\n if (color = /^\\\\s*(\\\\d+)\\\\s*,\\\\s*(\\\\d+)\\\\s*,\\\\s*(\\\\d+)\\\\s*(?:,\\\\s*(\\\\d*\\\\.?\\\\d+)\\\\s*)?$/.exec(components)) {\\n this.r = Math.min(255, parseInt(color[1], 10)) / 255;\\n this.g = Math.min(255, parseInt(color[2], 10)) / 255;\\n this.b = Math.min(255, parseInt(color[3], 10)) / 255;\\n handleAlpha(color[4]);\\n return this;\\n }\\n if (color = /^\\\\s*(\\\\d+)\\\\%\\\\s*,\\\\s*(\\\\d+)\\\\%\\\\s*,\\\\s*(\\\\d+)\\\\%\\\\s*(?:,\\\\s*(\\\\d*\\\\.?\\\\d+)\\\\s*)?$/.exec(components)) {\\n this.r = Math.min(100, parseInt(color[1], 10)) / 100;\\n this.g = Math.min(100, parseInt(color[2], 10)) / 100;\\n this.b = Math.min(100, parseInt(color[3], 10)) / 100;\\n handleAlpha(color[4]);\\n return this;\\n }\\n break;\\n case \\\\\\\"hsl\\\\\\\":\\n case \\\\\\\"hsla\\\\\\\":\\n if (color = /^\\\\s*(\\\\d*\\\\.?\\\\d+)\\\\s*,\\\\s*(\\\\d+)\\\\%\\\\s*,\\\\s*(\\\\d+)\\\\%\\\\s*(?:,\\\\s*(\\\\d*\\\\.?\\\\d+)\\\\s*)?$/.exec(components)) {\\n const h = parseFloat(color[1]) / 360;\\n const s = parseInt(color[2], 10) / 100;\\n const l = parseInt(color[3], 10) / 100;\\n handleAlpha(color[4]);\\n return this.setHSL(h, s, l);\\n }\\n break;\\n }\\n } else if (m = /^\\\\#([A-Fa-f\\\\d]+)$/.exec(style)) {\\n const hex = m[1];\\n const size = hex.length;\\n if (size === 3) {\\n this.r = parseInt(hex.charAt(0) + hex.charAt(0), 16) / 255;\\n this.g = parseInt(hex.charAt(1) + hex.charAt(1), 16) / 255;\\n this.b = parseInt(hex.charAt(2) + hex.charAt(2), 16) / 255;\\n return this;\\n } else if (size === 6) {\\n this.r = parseInt(hex.charAt(0) + hex.charAt(1), 16) / 255;\\n this.g = parseInt(hex.charAt(2) + hex.charAt(3), 16) / 255;\\n this.b = parseInt(hex.charAt(4) + hex.charAt(5), 16) / 255;\\n return this;\\n }\\n }\\n if (style && style.length > 0) {\\n return this.setColorName(style);\\n }\\n return this;\\n }\\n setColorName(style) {\\n const hex = _colorKeywords[style.toLowerCase()];\\n if (hex !== void 0) {\\n this.setHex(hex);\\n } else {\\n console.warn(\\\\\\\"THREE.Color: Unknown color \\\\\\\" + style);\\n }\\n return this;\\n }\\n clone() {\\n return new this.constructor(this.r, this.g, this.b);\\n }\\n copy(color) {\\n this.r = color.r;\\n this.g = color.g;\\n this.b = color.b;\\n return this;\\n }\\n copyGammaToLinear(color, gammaFactor = 2) {\\n this.r = Math.pow(color.r, gammaFactor);\\n this.g = Math.pow(color.g, gammaFactor);\\n this.b = Math.pow(color.b, gammaFactor);\\n return this;\\n }\\n copyLinearToGamma(color, gammaFactor = 2) {\\n const safeInverse = gammaFactor > 0 ? 1 / gammaFactor : 1;\\n this.r = Math.pow(color.r, safeInverse);\\n this.g = Math.pow(color.g, safeInverse);\\n this.b = Math.pow(color.b, safeInverse);\\n return this;\\n }\\n convertGammaToLinear(gammaFactor) {\\n this.copyGammaToLinear(this, gammaFactor);\\n return this;\\n }\\n convertLinearToGamma(gammaFactor) {\\n this.copyLinearToGamma(this, gammaFactor);\\n return this;\\n }\\n copySRGBToLinear(color) {\\n this.r = SRGBToLinear(color.r);\\n this.g = SRGBToLinear(color.g);\\n this.b = SRGBToLinear(color.b);\\n return this;\\n }\\n copyLinearToSRGB(color) {\\n this.r = LinearToSRGB(color.r);\\n this.g = LinearToSRGB(color.g);\\n this.b = LinearToSRGB(color.b);\\n return this;\\n }\\n convertSRGBToLinear() {\\n this.copySRGBToLinear(this);\\n return this;\\n }\\n convertLinearToSRGB() {\\n this.copyLinearToSRGB(this);\\n return this;\\n }\\n getHex() {\\n return this.r * 255 << 16 ^ this.g * 255 << 8 ^ this.b * 255 << 0;\\n }\\n getHexString() {\\n return (\\\\\\\"000000\\\\\\\" + this.getHex().toString(16)).slice(-6);\\n }\\n getHSL(target) {\\n const r = this.r, g = this.g, b = this.b;\\n const max = Math.max(r, g, b);\\n const min = Math.min(r, g, b);\\n let hue, saturation;\\n const lightness = (min + max) / 2;\\n if (min === max) {\\n hue = 0;\\n saturation = 0;\\n } else {\\n const delta = max - min;\\n saturation = lightness <= 0.5 ? delta / (max + min) : delta / (2 - max - min);\\n switch (max) {\\n case r:\\n hue = (g - b) / delta + (g < b ? 6 : 0);\\n break;\\n case g:\\n hue = (b - r) / delta + 2;\\n break;\\n case b:\\n hue = (r - g) / delta + 4;\\n break;\\n }\\n hue /= 6;\\n }\\n target.h = hue;\\n target.s = saturation;\\n target.l = lightness;\\n return target;\\n }\\n getStyle() {\\n return \\\\\\\"rgb(\\\\\\\" + (this.r * 255 | 0) + \\\\\\\",\\\\\\\" + (this.g * 255 | 0) + \\\\\\\",\\\\\\\" + (this.b * 255 | 0) + \\\\\\\")\\\\\\\";\\n }\\n offsetHSL(h, s, l) {\\n this.getHSL(_hslA);\\n _hslA.h += h;\\n _hslA.s += s;\\n _hslA.l += l;\\n this.setHSL(_hslA.h, _hslA.s, _hslA.l);\\n return this;\\n }\\n add(color) {\\n this.r += color.r;\\n this.g += color.g;\\n this.b += color.b;\\n return this;\\n }\\n addColors(color1, color2) {\\n this.r = color1.r + color2.r;\\n this.g = color1.g + color2.g;\\n this.b = color1.b + color2.b;\\n return this;\\n }\\n addScalar(s) {\\n this.r += s;\\n this.g += s;\\n this.b += s;\\n return this;\\n }\\n sub(color) {\\n this.r = Math.max(0, this.r - color.r);\\n this.g = Math.max(0, this.g - color.g);\\n this.b = Math.max(0, this.b - color.b);\\n return this;\\n }\\n multiply(color) {\\n this.r *= color.r;\\n this.g *= color.g;\\n this.b *= color.b;\\n return this;\\n }\\n multiplyScalar(s) {\\n this.r *= s;\\n this.g *= s;\\n this.b *= s;\\n return this;\\n }\\n lerp(color, alpha) {\\n this.r += (color.r - this.r) * alpha;\\n this.g += (color.g - this.g) * alpha;\\n this.b += (color.b - this.b) * alpha;\\n return this;\\n }\\n lerpColors(color1, color2, alpha) {\\n this.r = color1.r + (color2.r - color1.r) * alpha;\\n this.g = color1.g + (color2.g - color1.g) * alpha;\\n this.b = color1.b + (color2.b - color1.b) * alpha;\\n return this;\\n }\\n lerpHSL(color, alpha) {\\n this.getHSL(_hslA);\\n color.getHSL(_hslB);\\n const h = lerp(_hslA.h, _hslB.h, alpha);\\n const s = lerp(_hslA.s, _hslB.s, alpha);\\n const l = lerp(_hslA.l, _hslB.l, alpha);\\n this.setHSL(h, s, l);\\n return this;\\n }\\n equals(c) {\\n return c.r === this.r && c.g === this.g && c.b === this.b;\\n }\\n fromArray(array, offset = 0) {\\n this.r = array[offset];\\n this.g = array[offset + 1];\\n this.b = array[offset + 2];\\n return this;\\n }\\n toArray(array = [], offset = 0) {\\n array[offset] = this.r;\\n array[offset + 1] = this.g;\\n array[offset + 2] = this.b;\\n return array;\\n }\\n fromBufferAttribute(attribute, index) {\\n this.r = attribute.getX(index);\\n this.g = attribute.getY(index);\\n this.b = attribute.getZ(index);\\n if (attribute.normalized === true) {\\n this.r /= 255;\\n this.g /= 255;\\n this.b /= 255;\\n }\\n return this;\\n }\\n toJSON() {\\n return this.getHex();\\n }\\n};\\nColor.NAMES = _colorKeywords;\\nColor.prototype.isColor = true;\\nColor.prototype.r = 1;\\nColor.prototype.g = 1;\\nColor.prototype.b = 1;\\n\\n// ../../../node_modules/three/src/core/BufferAttribute.js\\nvar _vector4 = /* @__PURE__ */ new Vector3();\\nvar _vector23 = /* @__PURE__ */ new Vector2();\\nvar BufferAttribute = class {\\n constructor(array, itemSize, normalized) {\\n if (Array.isArray(array)) {\\n throw new TypeError(\\\\\\\"THREE.BufferAttribute: array should be a Typed Array.\\\\\\\");\\n }\\n this.name = \\\\\\\"\\\\\\\";\\n this.array = array;\\n this.itemSize = itemSize;\\n this.count = array !== void 0 ? array.length / itemSize : 0;\\n this.normalized = normalized === true;\\n this.usage = StaticDrawUsage;\\n this.updateRange = {offset: 0, count: -1};\\n this.version = 0;\\n }\\n onUploadCallback() {\\n }\\n set needsUpdate(value) {\\n if (value === true)\\n this.version++;\\n }\\n setUsage(value) {\\n this.usage = value;\\n return this;\\n }\\n copy(source) {\\n this.name = source.name;\\n this.array = new source.array.constructor(source.array);\\n this.itemSize = source.itemSize;\\n this.count = source.count;\\n this.normalized = source.normalized;\\n this.usage = source.usage;\\n return this;\\n }\\n copyAt(index1, attribute, index2) {\\n index1 *= this.itemSize;\\n index2 *= attribute.itemSize;\\n for (let i = 0, l = this.itemSize; i < l; i++) {\\n this.array[index1 + i] = attribute.array[index2 + i];\\n }\\n return this;\\n }\\n copyArray(array) {\\n this.array.set(array);\\n return this;\\n }\\n copyColorsArray(colors) {\\n const array = this.array;\\n let offset = 0;\\n for (let i = 0, l = colors.length; i < l; i++) {\\n let color = colors[i];\\n if (color === void 0) {\\n console.warn(\\\\\\\"THREE.BufferAttribute.copyColorsArray(): color is undefined\\\\\\\", i);\\n color = new Color();\\n }\\n array[offset++] = color.r;\\n array[offset++] = color.g;\\n array[offset++] = color.b;\\n }\\n return this;\\n }\\n copyVector2sArray(vectors) {\\n const array = this.array;\\n let offset = 0;\\n for (let i = 0, l = vectors.length; i < l; i++) {\\n let vector = vectors[i];\\n if (vector === void 0) {\\n console.warn(\\\\\\\"THREE.BufferAttribute.copyVector2sArray(): vector is undefined\\\\\\\", i);\\n vector = new Vector2();\\n }\\n array[offset++] = vector.x;\\n array[offset++] = vector.y;\\n }\\n return this;\\n }\\n copyVector3sArray(vectors) {\\n const array = this.array;\\n let offset = 0;\\n for (let i = 0, l = vectors.length; i < l; i++) {\\n let vector = vectors[i];\\n if (vector === void 0) {\\n console.warn(\\\\\\\"THREE.BufferAttribute.copyVector3sArray(): vector is undefined\\\\\\\", i);\\n vector = new Vector3();\\n }\\n array[offset++] = vector.x;\\n array[offset++] = vector.y;\\n array[offset++] = vector.z;\\n }\\n return this;\\n }\\n copyVector4sArray(vectors) {\\n const array = this.array;\\n let offset = 0;\\n for (let i = 0, l = vectors.length; i < l; i++) {\\n let vector = vectors[i];\\n if (vector === void 0) {\\n console.warn(\\\\\\\"THREE.BufferAttribute.copyVector4sArray(): vector is undefined\\\\\\\", i);\\n vector = new Vector4();\\n }\\n array[offset++] = vector.x;\\n array[offset++] = vector.y;\\n array[offset++] = vector.z;\\n array[offset++] = vector.w;\\n }\\n return this;\\n }\\n applyMatrix3(m) {\\n if (this.itemSize === 2) {\\n for (let i = 0, l = this.count; i < l; i++) {\\n _vector23.fromBufferAttribute(this, i);\\n _vector23.applyMatrix3(m);\\n this.setXY(i, _vector23.x, _vector23.y);\\n }\\n } else if (this.itemSize === 3) {\\n for (let i = 0, l = this.count; i < l; i++) {\\n _vector4.fromBufferAttribute(this, i);\\n _vector4.applyMatrix3(m);\\n this.setXYZ(i, _vector4.x, _vector4.y, _vector4.z);\\n }\\n }\\n return this;\\n }\\n applyMatrix4(m) {\\n for (let i = 0, l = this.count; i < l; i++) {\\n _vector4.x = this.getX(i);\\n _vector4.y = this.getY(i);\\n _vector4.z = this.getZ(i);\\n _vector4.applyMatrix4(m);\\n this.setXYZ(i, _vector4.x, _vector4.y, _vector4.z);\\n }\\n return this;\\n }\\n applyNormalMatrix(m) {\\n for (let i = 0, l = this.count; i < l; i++) {\\n _vector4.x = this.getX(i);\\n _vector4.y = this.getY(i);\\n _vector4.z = this.getZ(i);\\n _vector4.applyNormalMatrix(m);\\n this.setXYZ(i, _vector4.x, _vector4.y, _vector4.z);\\n }\\n return this;\\n }\\n transformDirection(m) {\\n for (let i = 0, l = this.count; i < l; i++) {\\n _vector4.x = this.getX(i);\\n _vector4.y = this.getY(i);\\n _vector4.z = this.getZ(i);\\n _vector4.transformDirection(m);\\n this.setXYZ(i, _vector4.x, _vector4.y, _vector4.z);\\n }\\n return this;\\n }\\n set(value, offset = 0) {\\n this.array.set(value, offset);\\n return this;\\n }\\n getX(index) {\\n return this.array[index * this.itemSize];\\n }\\n setX(index, x) {\\n this.array[index * this.itemSize] = x;\\n return this;\\n }\\n getY(index) {\\n return this.array[index * this.itemSize + 1];\\n }\\n setY(index, y) {\\n this.array[index * this.itemSize + 1] = y;\\n return this;\\n }\\n getZ(index) {\\n return this.array[index * this.itemSize + 2];\\n }\\n setZ(index, z) {\\n this.array[index * this.itemSize + 2] = z;\\n return this;\\n }\\n getW(index) {\\n return this.array[index * this.itemSize + 3];\\n }\\n setW(index, w) {\\n this.array[index * this.itemSize + 3] = w;\\n return this;\\n }\\n setXY(index, x, y) {\\n index *= this.itemSize;\\n this.array[index + 0] = x;\\n this.array[index + 1] = y;\\n return this;\\n }\\n setXYZ(index, x, y, z) {\\n index *= this.itemSize;\\n this.array[index + 0] = x;\\n this.array[index + 1] = y;\\n this.array[index + 2] = z;\\n return this;\\n }\\n setXYZW(index, x, y, z, w) {\\n index *= this.itemSize;\\n this.array[index + 0] = x;\\n this.array[index + 1] = y;\\n this.array[index + 2] = z;\\n this.array[index + 3] = w;\\n return this;\\n }\\n onUpload(callback) {\\n this.onUploadCallback = callback;\\n return this;\\n }\\n clone() {\\n return new this.constructor(this.array, this.itemSize).copy(this);\\n }\\n toJSON() {\\n const data = {\\n itemSize: this.itemSize,\\n type: this.array.constructor.name,\\n array: Array.prototype.slice.call(this.array),\\n normalized: this.normalized\\n };\\n if (this.name !== \\\\\\\"\\\\\\\")\\n data.name = this.name;\\n if (this.usage !== StaticDrawUsage)\\n data.usage = this.usage;\\n if (this.updateRange.offset !== 0 || this.updateRange.count !== -1)\\n data.updateRange = this.updateRange;\\n return data;\\n }\\n};\\nBufferAttribute.prototype.isBufferAttribute = true;\\nvar Uint16BufferAttribute = class extends BufferAttribute {\\n constructor(array, itemSize, normalized) {\\n super(new Uint16Array(array), itemSize, normalized);\\n }\\n};\\nvar Int32BufferAttribute = class extends BufferAttribute {\\n constructor(array, itemSize, normalized) {\\n super(new Int32Array(array), itemSize, normalized);\\n }\\n};\\nvar Uint32BufferAttribute = class extends BufferAttribute {\\n constructor(array, itemSize, normalized) {\\n super(new Uint32Array(array), itemSize, normalized);\\n }\\n};\\nvar Float16BufferAttribute = class extends BufferAttribute {\\n constructor(array, itemSize, normalized) {\\n super(new Uint16Array(array), itemSize, normalized);\\n }\\n};\\nFloat16BufferAttribute.prototype.isFloat16BufferAttribute = true;\\nvar Float32BufferAttribute = class extends BufferAttribute {\\n constructor(array, itemSize, normalized) {\\n super(new Float32Array(array), itemSize, normalized);\\n }\\n};\\n\\n// ../../../node_modules/three/src/utils.js\\nfunction arrayMax(array) {\\n if (array.length === 0)\\n return -Infinity;\\n let max = array[0];\\n for (let i = 1, l = array.length; i < l; ++i) {\\n if (array[i] > max)\\n max = array[i];\\n }\\n return max;\\n}\\nvar TYPED_ARRAYS = {\\n Int8Array,\\n Uint8Array,\\n Uint8ClampedArray,\\n Int16Array,\\n Uint16Array,\\n Int32Array,\\n Uint32Array,\\n Float32Array,\\n Float64Array\\n};\\nfunction createElementNS(name) {\\n return document.createElementNS(\\\\\\\"http://www.w3.org/1999/xhtml\\\\\\\", name);\\n}\\n\\n// ../../../node_modules/three/src/core/BufferGeometry.js\\nvar _id = 0;\\nvar _m13 = /* @__PURE__ */ new Matrix4();\\nvar _obj = /* @__PURE__ */ new Object3D();\\nvar _offset = /* @__PURE__ */ new Vector3();\\nvar _box3 = /* @__PURE__ */ new Box3();\\nvar _boxMorphTargets = /* @__PURE__ */ new Box3();\\nvar _vector5 = /* @__PURE__ */ new Vector3();\\nvar BufferGeometry = class extends EventDispatcher {\\n constructor() {\\n super();\\n Object.defineProperty(this, \\\\\\\"id\\\\\\\", {value: _id++});\\n this.uuid = generateUUID();\\n this.name = \\\\\\\"\\\\\\\";\\n this.type = \\\\\\\"BufferGeometry\\\\\\\";\\n this.index = null;\\n this.attributes = {};\\n this.morphAttributes = {};\\n this.morphTargetsRelative = false;\\n this.groups = [];\\n this.boundingBox = null;\\n this.boundingSphere = null;\\n this.drawRange = {start: 0, count: Infinity};\\n this.userData = {};\\n }\\n getIndex() {\\n return this.index;\\n }\\n setIndex(index) {\\n if (Array.isArray(index)) {\\n this.index = new (arrayMax(index) > 65535 ? Uint32BufferAttribute : Uint16BufferAttribute)(index, 1);\\n } else {\\n this.index = index;\\n }\\n return this;\\n }\\n getAttribute(name) {\\n return this.attributes[name];\\n }\\n setAttribute(name, attribute) {\\n this.attributes[name] = attribute;\\n return this;\\n }\\n deleteAttribute(name) {\\n delete this.attributes[name];\\n return this;\\n }\\n hasAttribute(name) {\\n return this.attributes[name] !== void 0;\\n }\\n addGroup(start, count, materialIndex = 0) {\\n this.groups.push({\\n start,\\n count,\\n materialIndex\\n });\\n }\\n clearGroups() {\\n this.groups = [];\\n }\\n setDrawRange(start, count) {\\n this.drawRange.start = start;\\n this.drawRange.count = count;\\n }\\n applyMatrix4(matrix) {\\n const position = this.attributes.position;\\n if (position !== void 0) {\\n position.applyMatrix4(matrix);\\n position.needsUpdate = true;\\n }\\n const normal = this.attributes.normal;\\n if (normal !== void 0) {\\n const normalMatrix = new Matrix3().getNormalMatrix(matrix);\\n normal.applyNormalMatrix(normalMatrix);\\n normal.needsUpdate = true;\\n }\\n const tangent = this.attributes.tangent;\\n if (tangent !== void 0) {\\n tangent.transformDirection(matrix);\\n tangent.needsUpdate = true;\\n }\\n if (this.boundingBox !== null) {\\n this.computeBoundingBox();\\n }\\n if (this.boundingSphere !== null) {\\n this.computeBoundingSphere();\\n }\\n return this;\\n }\\n applyQuaternion(q) {\\n _m13.makeRotationFromQuaternion(q);\\n this.applyMatrix4(_m13);\\n return this;\\n }\\n rotateX(angle) {\\n _m13.makeRotationX(angle);\\n this.applyMatrix4(_m13);\\n return this;\\n }\\n rotateY(angle) {\\n _m13.makeRotationY(angle);\\n this.applyMatrix4(_m13);\\n return this;\\n }\\n rotateZ(angle) {\\n _m13.makeRotationZ(angle);\\n this.applyMatrix4(_m13);\\n return this;\\n }\\n translate(x, y, z) {\\n _m13.makeTranslation(x, y, z);\\n this.applyMatrix4(_m13);\\n return this;\\n }\\n scale(x, y, z) {\\n _m13.makeScale(x, y, z);\\n this.applyMatrix4(_m13);\\n return this;\\n }\\n lookAt(vector) {\\n _obj.lookAt(vector);\\n _obj.updateMatrix();\\n this.applyMatrix4(_obj.matrix);\\n return this;\\n }\\n center() {\\n this.computeBoundingBox();\\n this.boundingBox.getCenter(_offset).negate();\\n this.translate(_offset.x, _offset.y, _offset.z);\\n return this;\\n }\\n setFromPoints(points2) {\\n const position = [];\\n for (let i = 0, l = points2.length; i < l; i++) {\\n const point = points2[i];\\n position.push(point.x, point.y, point.z || 0);\\n }\\n this.setAttribute(\\\\\\\"position\\\\\\\", new Float32BufferAttribute(position, 3));\\n return this;\\n }\\n computeBoundingBox() {\\n if (this.boundingBox === null) {\\n this.boundingBox = new Box3();\\n }\\n const position = this.attributes.position;\\n const morphAttributesPosition = this.morphAttributes.position;\\n if (position && position.isGLBufferAttribute) {\\n console.error('THREE.BufferGeometry.computeBoundingBox(): GLBufferAttribute requires a manual bounding box. Alternatively set \\\\\\\"mesh.frustumCulled\\\\\\\" to \\\\\\\"false\\\\\\\".', this);\\n this.boundingBox.set(new Vector3(-Infinity, -Infinity, -Infinity), new Vector3(Infinity, Infinity, Infinity));\\n return;\\n }\\n if (position !== void 0) {\\n this.boundingBox.setFromBufferAttribute(position);\\n if (morphAttributesPosition) {\\n for (let i = 0, il = morphAttributesPosition.length; i < il; i++) {\\n const morphAttribute = morphAttributesPosition[i];\\n _box3.setFromBufferAttribute(morphAttribute);\\n if (this.morphTargetsRelative) {\\n _vector5.addVectors(this.boundingBox.min, _box3.min);\\n this.boundingBox.expandByPoint(_vector5);\\n _vector5.addVectors(this.boundingBox.max, _box3.max);\\n this.boundingBox.expandByPoint(_vector5);\\n } else {\\n this.boundingBox.expandByPoint(_box3.min);\\n this.boundingBox.expandByPoint(_box3.max);\\n }\\n }\\n }\\n } else {\\n this.boundingBox.makeEmpty();\\n }\\n if (isNaN(this.boundingBox.min.x) || isNaN(this.boundingBox.min.y) || isNaN(this.boundingBox.min.z)) {\\n console.error('THREE.BufferGeometry.computeBoundingBox(): Computed min/max have NaN values. The \\\\\\\"position\\\\\\\" attribute is likely to have NaN values.', this);\\n }\\n }\\n computeBoundingSphere() {\\n if (this.boundingSphere === null) {\\n this.boundingSphere = new Sphere();\\n }\\n const position = this.attributes.position;\\n const morphAttributesPosition = this.morphAttributes.position;\\n if (position && position.isGLBufferAttribute) {\\n console.error('THREE.BufferGeometry.computeBoundingSphere(): GLBufferAttribute requires a manual bounding sphere. Alternatively set \\\\\\\"mesh.frustumCulled\\\\\\\" to \\\\\\\"false\\\\\\\".', this);\\n this.boundingSphere.set(new Vector3(), Infinity);\\n return;\\n }\\n if (position) {\\n const center = this.boundingSphere.center;\\n _box3.setFromBufferAttribute(position);\\n if (morphAttributesPosition) {\\n for (let i = 0, il = morphAttributesPosition.length; i < il; i++) {\\n const morphAttribute = morphAttributesPosition[i];\\n _boxMorphTargets.setFromBufferAttribute(morphAttribute);\\n if (this.morphTargetsRelative) {\\n _vector5.addVectors(_box3.min, _boxMorphTargets.min);\\n _box3.expandByPoint(_vector5);\\n _vector5.addVectors(_box3.max, _boxMorphTargets.max);\\n _box3.expandByPoint(_vector5);\\n } else {\\n _box3.expandByPoint(_boxMorphTargets.min);\\n _box3.expandByPoint(_boxMorphTargets.max);\\n }\\n }\\n }\\n _box3.getCenter(center);\\n let maxRadiusSq = 0;\\n for (let i = 0, il = position.count; i < il; i++) {\\n _vector5.fromBufferAttribute(position, i);\\n maxRadiusSq = Math.max(maxRadiusSq, center.distanceToSquared(_vector5));\\n }\\n if (morphAttributesPosition) {\\n for (let i = 0, il = morphAttributesPosition.length; i < il; i++) {\\n const morphAttribute = morphAttributesPosition[i];\\n const morphTargetsRelative = this.morphTargetsRelative;\\n for (let j = 0, jl = morphAttribute.count; j < jl; j++) {\\n _vector5.fromBufferAttribute(morphAttribute, j);\\n if (morphTargetsRelative) {\\n _offset.fromBufferAttribute(position, j);\\n _vector5.add(_offset);\\n }\\n maxRadiusSq = Math.max(maxRadiusSq, center.distanceToSquared(_vector5));\\n }\\n }\\n }\\n this.boundingSphere.radius = Math.sqrt(maxRadiusSq);\\n if (isNaN(this.boundingSphere.radius)) {\\n console.error('THREE.BufferGeometry.computeBoundingSphere(): Computed radius is NaN. The \\\\\\\"position\\\\\\\" attribute is likely to have NaN values.', this);\\n }\\n }\\n }\\n computeTangents() {\\n const index = this.index;\\n const attributes = this.attributes;\\n if (index === null || attributes.position === void 0 || attributes.normal === void 0 || attributes.uv === void 0) {\\n console.error(\\\\\\\"THREE.BufferGeometry: .computeTangents() failed. Missing required attributes (index, position, normal or uv)\\\\\\\");\\n return;\\n }\\n const indices = index.array;\\n const positions = attributes.position.array;\\n const normals = attributes.normal.array;\\n const uvs = attributes.uv.array;\\n const nVertices = positions.length / 3;\\n if (attributes.tangent === void 0) {\\n this.setAttribute(\\\\\\\"tangent\\\\\\\", new BufferAttribute(new Float32Array(4 * nVertices), 4));\\n }\\n const tangents = attributes.tangent.array;\\n const tan1 = [], tan2 = [];\\n for (let i = 0; i < nVertices; i++) {\\n tan1[i] = new Vector3();\\n tan2[i] = new Vector3();\\n }\\n const vA = new Vector3(), vB = new Vector3(), vC = new Vector3(), uvA = new Vector2(), uvB = new Vector2(), uvC = new Vector2(), sdir = new Vector3(), tdir = new Vector3();\\n function handleTriangle(a, b, c) {\\n vA.fromArray(positions, a * 3);\\n vB.fromArray(positions, b * 3);\\n vC.fromArray(positions, c * 3);\\n uvA.fromArray(uvs, a * 2);\\n uvB.fromArray(uvs, b * 2);\\n uvC.fromArray(uvs, c * 2);\\n vB.sub(vA);\\n vC.sub(vA);\\n uvB.sub(uvA);\\n uvC.sub(uvA);\\n const r = 1 / (uvB.x * uvC.y - uvC.x * uvB.y);\\n if (!isFinite(r))\\n return;\\n sdir.copy(vB).multiplyScalar(uvC.y).addScaledVector(vC, -uvB.y).multiplyScalar(r);\\n tdir.copy(vC).multiplyScalar(uvB.x).addScaledVector(vB, -uvC.x).multiplyScalar(r);\\n tan1[a].add(sdir);\\n tan1[b].add(sdir);\\n tan1[c].add(sdir);\\n tan2[a].add(tdir);\\n tan2[b].add(tdir);\\n tan2[c].add(tdir);\\n }\\n let groups = this.groups;\\n if (groups.length === 0) {\\n groups = [{\\n start: 0,\\n count: indices.length\\n }];\\n }\\n for (let i = 0, il = groups.length; i < il; ++i) {\\n const group = groups[i];\\n const start = group.start;\\n const count = group.count;\\n for (let j = start, jl = start + count; j < jl; j += 3) {\\n handleTriangle(indices[j + 0], indices[j + 1], indices[j + 2]);\\n }\\n }\\n const tmp = new Vector3(), tmp2 = new Vector3();\\n const n = new Vector3(), n2 = new Vector3();\\n function handleVertex(v) {\\n n.fromArray(normals, v * 3);\\n n2.copy(n);\\n const t = tan1[v];\\n tmp.copy(t);\\n tmp.sub(n.multiplyScalar(n.dot(t))).normalize();\\n tmp2.crossVectors(n2, t);\\n const test = tmp2.dot(tan2[v]);\\n const w = test < 0 ? -1 : 1;\\n tangents[v * 4] = tmp.x;\\n tangents[v * 4 + 1] = tmp.y;\\n tangents[v * 4 + 2] = tmp.z;\\n tangents[v * 4 + 3] = w;\\n }\\n for (let i = 0, il = groups.length; i < il; ++i) {\\n const group = groups[i];\\n const start = group.start;\\n const count = group.count;\\n for (let j = start, jl = start + count; j < jl; j += 3) {\\n handleVertex(indices[j + 0]);\\n handleVertex(indices[j + 1]);\\n handleVertex(indices[j + 2]);\\n }\\n }\\n }\\n computeVertexNormals() {\\n const index = this.index;\\n const positionAttribute = this.getAttribute(\\\\\\\"position\\\\\\\");\\n if (positionAttribute !== void 0) {\\n let normalAttribute = this.getAttribute(\\\\\\\"normal\\\\\\\");\\n if (normalAttribute === void 0) {\\n normalAttribute = new BufferAttribute(new Float32Array(positionAttribute.count * 3), 3);\\n this.setAttribute(\\\\\\\"normal\\\\\\\", normalAttribute);\\n } else {\\n for (let i = 0, il = normalAttribute.count; i < il; i++) {\\n normalAttribute.setXYZ(i, 0, 0, 0);\\n }\\n }\\n const pA = new Vector3(), pB = new Vector3(), pC = new Vector3();\\n const nA = new Vector3(), nB = new Vector3(), nC = new Vector3();\\n const cb = new Vector3(), ab = new Vector3();\\n if (index) {\\n for (let i = 0, il = index.count; i < il; i += 3) {\\n const vA = index.getX(i + 0);\\n const vB = index.getX(i + 1);\\n const vC = index.getX(i + 2);\\n pA.fromBufferAttribute(positionAttribute, vA);\\n pB.fromBufferAttribute(positionAttribute, vB);\\n pC.fromBufferAttribute(positionAttribute, vC);\\n cb.subVectors(pC, pB);\\n ab.subVectors(pA, pB);\\n cb.cross(ab);\\n nA.fromBufferAttribute(normalAttribute, vA);\\n nB.fromBufferAttribute(normalAttribute, vB);\\n nC.fromBufferAttribute(normalAttribute, vC);\\n nA.add(cb);\\n nB.add(cb);\\n nC.add(cb);\\n normalAttribute.setXYZ(vA, nA.x, nA.y, nA.z);\\n normalAttribute.setXYZ(vB, nB.x, nB.y, nB.z);\\n normalAttribute.setXYZ(vC, nC.x, nC.y, nC.z);\\n }\\n } else {\\n for (let i = 0, il = positionAttribute.count; i < il; i += 3) {\\n pA.fromBufferAttribute(positionAttribute, i + 0);\\n pB.fromBufferAttribute(positionAttribute, i + 1);\\n pC.fromBufferAttribute(positionAttribute, i + 2);\\n cb.subVectors(pC, pB);\\n ab.subVectors(pA, pB);\\n cb.cross(ab);\\n normalAttribute.setXYZ(i + 0, cb.x, cb.y, cb.z);\\n normalAttribute.setXYZ(i + 1, cb.x, cb.y, cb.z);\\n normalAttribute.setXYZ(i + 2, cb.x, cb.y, cb.z);\\n }\\n }\\n this.normalizeNormals();\\n normalAttribute.needsUpdate = true;\\n }\\n }\\n merge(geometry, offset) {\\n if (!(geometry && geometry.isBufferGeometry)) {\\n console.error(\\\\\\\"THREE.BufferGeometry.merge(): geometry not an instance of THREE.BufferGeometry.\\\\\\\", geometry);\\n return;\\n }\\n if (offset === void 0) {\\n offset = 0;\\n console.warn(\\\\\\\"THREE.BufferGeometry.merge(): Overwriting original geometry, starting at offset=0. Use BufferGeometryUtils.mergeBufferGeometries() for lossless merge.\\\\\\\");\\n }\\n const attributes = this.attributes;\\n for (const key in attributes) {\\n if (geometry.attributes[key] === void 0)\\n continue;\\n const attribute1 = attributes[key];\\n const attributeArray1 = attribute1.array;\\n const attribute2 = geometry.attributes[key];\\n const attributeArray2 = attribute2.array;\\n const attributeOffset = attribute2.itemSize * offset;\\n const length = Math.min(attributeArray2.length, attributeArray1.length - attributeOffset);\\n for (let i = 0, j = attributeOffset; i < length; i++, j++) {\\n attributeArray1[j] = attributeArray2[i];\\n }\\n }\\n return this;\\n }\\n normalizeNormals() {\\n const normals = this.attributes.normal;\\n for (let i = 0, il = normals.count; i < il; i++) {\\n _vector5.fromBufferAttribute(normals, i);\\n _vector5.normalize();\\n normals.setXYZ(i, _vector5.x, _vector5.y, _vector5.z);\\n }\\n }\\n toNonIndexed() {\\n function convertBufferAttribute(attribute, indices2) {\\n const array = attribute.array;\\n const itemSize = attribute.itemSize;\\n const normalized = attribute.normalized;\\n const array2 = new array.constructor(indices2.length * itemSize);\\n let index = 0, index2 = 0;\\n for (let i = 0, l = indices2.length; i < l; i++) {\\n if (attribute.isInterleavedBufferAttribute) {\\n index = indices2[i] * attribute.data.stride + attribute.offset;\\n } else {\\n index = indices2[i] * itemSize;\\n }\\n for (let j = 0; j < itemSize; j++) {\\n array2[index2++] = array[index++];\\n }\\n }\\n return new BufferAttribute(array2, itemSize, normalized);\\n }\\n if (this.index === null) {\\n console.warn(\\\\\\\"THREE.BufferGeometry.toNonIndexed(): BufferGeometry is already non-indexed.\\\\\\\");\\n return this;\\n }\\n const geometry2 = new BufferGeometry();\\n const indices = this.index.array;\\n const attributes = this.attributes;\\n for (const name in attributes) {\\n const attribute = attributes[name];\\n const newAttribute = convertBufferAttribute(attribute, indices);\\n geometry2.setAttribute(name, newAttribute);\\n }\\n const morphAttributes = this.morphAttributes;\\n for (const name in morphAttributes) {\\n const morphArray = [];\\n const morphAttribute = morphAttributes[name];\\n for (let i = 0, il = morphAttribute.length; i < il; i++) {\\n const attribute = morphAttribute[i];\\n const newAttribute = convertBufferAttribute(attribute, indices);\\n morphArray.push(newAttribute);\\n }\\n geometry2.morphAttributes[name] = morphArray;\\n }\\n geometry2.morphTargetsRelative = this.morphTargetsRelative;\\n const groups = this.groups;\\n for (let i = 0, l = groups.length; i < l; i++) {\\n const group = groups[i];\\n geometry2.addGroup(group.start, group.count, group.materialIndex);\\n }\\n return geometry2;\\n }\\n toJSON() {\\n const data = {\\n metadata: {\\n version: 4.5,\\n type: \\\\\\\"BufferGeometry\\\\\\\",\\n generator: \\\\\\\"BufferGeometry.toJSON\\\\\\\"\\n }\\n };\\n data.uuid = this.uuid;\\n data.type = this.type;\\n if (this.name !== \\\\\\\"\\\\\\\")\\n data.name = this.name;\\n if (Object.keys(this.userData).length > 0)\\n data.userData = this.userData;\\n if (this.parameters !== void 0) {\\n const parameters = this.parameters;\\n for (const key in parameters) {\\n if (parameters[key] !== void 0)\\n data[key] = parameters[key];\\n }\\n return data;\\n }\\n data.data = {attributes: {}};\\n const index = this.index;\\n if (index !== null) {\\n data.data.index = {\\n type: index.array.constructor.name,\\n array: Array.prototype.slice.call(index.array)\\n };\\n }\\n const attributes = this.attributes;\\n for (const key in attributes) {\\n const attribute = attributes[key];\\n data.data.attributes[key] = attribute.toJSON(data.data);\\n }\\n const morphAttributes = {};\\n let hasMorphAttributes = false;\\n for (const key in this.morphAttributes) {\\n const attributeArray = this.morphAttributes[key];\\n const array = [];\\n for (let i = 0, il = attributeArray.length; i < il; i++) {\\n const attribute = attributeArray[i];\\n array.push(attribute.toJSON(data.data));\\n }\\n if (array.length > 0) {\\n morphAttributes[key] = array;\\n hasMorphAttributes = true;\\n }\\n }\\n if (hasMorphAttributes) {\\n data.data.morphAttributes = morphAttributes;\\n data.data.morphTargetsRelative = this.morphTargetsRelative;\\n }\\n const groups = this.groups;\\n if (groups.length > 0) {\\n data.data.groups = JSON.parse(JSON.stringify(groups));\\n }\\n const boundingSphere = this.boundingSphere;\\n if (boundingSphere !== null) {\\n data.data.boundingSphere = {\\n center: boundingSphere.center.toArray(),\\n radius: boundingSphere.radius\\n };\\n }\\n return data;\\n }\\n clone() {\\n return new this.constructor().copy(this);\\n }\\n copy(source) {\\n this.index = null;\\n this.attributes = {};\\n this.morphAttributes = {};\\n this.groups = [];\\n this.boundingBox = null;\\n this.boundingSphere = null;\\n const data = {};\\n this.name = source.name;\\n const index = source.index;\\n if (index !== null) {\\n this.setIndex(index.clone(data));\\n }\\n const attributes = source.attributes;\\n for (const name in attributes) {\\n const attribute = attributes[name];\\n this.setAttribute(name, attribute.clone(data));\\n }\\n const morphAttributes = source.morphAttributes;\\n for (const name in morphAttributes) {\\n const array = [];\\n const morphAttribute = morphAttributes[name];\\n for (let i = 0, l = morphAttribute.length; i < l; i++) {\\n array.push(morphAttribute[i].clone(data));\\n }\\n this.morphAttributes[name] = array;\\n }\\n this.morphTargetsRelative = source.morphTargetsRelative;\\n const groups = source.groups;\\n for (let i = 0, l = groups.length; i < l; i++) {\\n const group = groups[i];\\n this.addGroup(group.start, group.count, group.materialIndex);\\n }\\n const boundingBox = source.boundingBox;\\n if (boundingBox !== null) {\\n this.boundingBox = boundingBox.clone();\\n }\\n const boundingSphere = source.boundingSphere;\\n if (boundingSphere !== null) {\\n this.boundingSphere = boundingSphere.clone();\\n }\\n this.drawRange.start = source.drawRange.start;\\n this.drawRange.count = source.drawRange.count;\\n this.userData = source.userData;\\n if (source.parameters !== void 0)\\n this.parameters = Object.assign({}, source.parameters);\\n return this;\\n }\\n dispose() {\\n this.dispatchEvent({type: \\\\\\\"dispose\\\\\\\"});\\n }\\n};\\nBufferGeometry.prototype.isBufferGeometry = true;\\n\\n// ../../../node_modules/three/src/geometries/BoxGeometry.js\\nvar BoxGeometry = class extends BufferGeometry {\\n constructor(width = 1, height = 1, depth2 = 1, widthSegments = 1, heightSegments = 1, depthSegments = 1) {\\n super();\\n this.type = \\\\\\\"BoxGeometry\\\\\\\";\\n this.parameters = {\\n width,\\n height,\\n depth: depth2,\\n widthSegments,\\n heightSegments,\\n depthSegments\\n };\\n const scope = this;\\n widthSegments = Math.floor(widthSegments);\\n heightSegments = Math.floor(heightSegments);\\n depthSegments = Math.floor(depthSegments);\\n const indices = [];\\n const vertices = [];\\n const normals = [];\\n const uvs = [];\\n let numberOfVertices = 0;\\n let groupStart = 0;\\n buildPlane(\\\\\\\"z\\\\\\\", \\\\\\\"y\\\\\\\", \\\\\\\"x\\\\\\\", -1, -1, depth2, height, width, depthSegments, heightSegments, 0);\\n buildPlane(\\\\\\\"z\\\\\\\", \\\\\\\"y\\\\\\\", \\\\\\\"x\\\\\\\", 1, -1, depth2, height, -width, depthSegments, heightSegments, 1);\\n buildPlane(\\\\\\\"x\\\\\\\", \\\\\\\"z\\\\\\\", \\\\\\\"y\\\\\\\", 1, 1, width, depth2, height, widthSegments, depthSegments, 2);\\n buildPlane(\\\\\\\"x\\\\\\\", \\\\\\\"z\\\\\\\", \\\\\\\"y\\\\\\\", 1, -1, width, depth2, -height, widthSegments, depthSegments, 3);\\n buildPlane(\\\\\\\"x\\\\\\\", \\\\\\\"y\\\\\\\", \\\\\\\"z\\\\\\\", 1, -1, width, height, depth2, widthSegments, heightSegments, 4);\\n buildPlane(\\\\\\\"x\\\\\\\", \\\\\\\"y\\\\\\\", \\\\\\\"z\\\\\\\", -1, -1, width, height, -depth2, widthSegments, heightSegments, 5);\\n this.setIndex(indices);\\n this.setAttribute(\\\\\\\"position\\\\\\\", new Float32BufferAttribute(vertices, 3));\\n this.setAttribute(\\\\\\\"normal\\\\\\\", new Float32BufferAttribute(normals, 3));\\n this.setAttribute(\\\\\\\"uv\\\\\\\", new Float32BufferAttribute(uvs, 2));\\n function buildPlane(u, v, w, udir, vdir, width2, height2, depth3, gridX, gridY, materialIndex) {\\n const segmentWidth = width2 / gridX;\\n const segmentHeight = height2 / gridY;\\n const widthHalf = width2 / 2;\\n const heightHalf = height2 / 2;\\n const depthHalf = depth3 / 2;\\n const gridX1 = gridX + 1;\\n const gridY1 = gridY + 1;\\n let vertexCounter = 0;\\n let groupCount = 0;\\n const vector = new Vector3();\\n for (let iy = 0; iy < gridY1; iy++) {\\n const y = iy * segmentHeight - heightHalf;\\n for (let ix = 0; ix < gridX1; ix++) {\\n const x = ix * segmentWidth - widthHalf;\\n vector[u] = x * udir;\\n vector[v] = y * vdir;\\n vector[w] = depthHalf;\\n vertices.push(vector.x, vector.y, vector.z);\\n vector[u] = 0;\\n vector[v] = 0;\\n vector[w] = depth3 > 0 ? 1 : -1;\\n normals.push(vector.x, vector.y, vector.z);\\n uvs.push(ix / gridX);\\n uvs.push(1 - iy / gridY);\\n vertexCounter += 1;\\n }\\n }\\n for (let iy = 0; iy < gridY; iy++) {\\n for (let ix = 0; ix < gridX; ix++) {\\n const a = numberOfVertices + ix + gridX1 * iy;\\n const b = numberOfVertices + ix + gridX1 * (iy + 1);\\n const c = numberOfVertices + (ix + 1) + gridX1 * (iy + 1);\\n const d = numberOfVertices + (ix + 1) + gridX1 * iy;\\n indices.push(a, b, d);\\n indices.push(b, c, d);\\n groupCount += 6;\\n }\\n }\\n scope.addGroup(groupStart, groupCount, materialIndex);\\n groupStart += groupCount;\\n numberOfVertices += vertexCounter;\\n }\\n }\\n static fromJSON(data) {\\n return new BoxGeometry(data.width, data.height, data.depth, data.widthSegments, data.heightSegments, data.depthSegments);\\n }\\n};\\n\\n// ../../../node_modules/three/src/geometries/PlaneGeometry.js\\nvar PlaneGeometry = class extends BufferGeometry {\\n constructor(width = 1, height = 1, widthSegments = 1, heightSegments = 1) {\\n super();\\n this.type = \\\\\\\"PlaneGeometry\\\\\\\";\\n this.parameters = {\\n width,\\n height,\\n widthSegments,\\n heightSegments\\n };\\n const width_half = width / 2;\\n const height_half = height / 2;\\n const gridX = Math.floor(widthSegments);\\n const gridY = Math.floor(heightSegments);\\n const gridX1 = gridX + 1;\\n const gridY1 = gridY + 1;\\n const segment_width = width / gridX;\\n const segment_height = height / gridY;\\n const indices = [];\\n const vertices = [];\\n const normals = [];\\n const uvs = [];\\n for (let iy = 0; iy < gridY1; iy++) {\\n const y = iy * segment_height - height_half;\\n for (let ix = 0; ix < gridX1; ix++) {\\n const x = ix * segment_width - width_half;\\n vertices.push(x, -y, 0);\\n normals.push(0, 0, 1);\\n uvs.push(ix / gridX);\\n uvs.push(1 - iy / gridY);\\n }\\n }\\n for (let iy = 0; iy < gridY; iy++) {\\n for (let ix = 0; ix < gridX; ix++) {\\n const a = ix + gridX1 * iy;\\n const b = ix + gridX1 * (iy + 1);\\n const c = ix + 1 + gridX1 * (iy + 1);\\n const d = ix + 1 + gridX1 * iy;\\n indices.push(a, b, d);\\n indices.push(b, c, d);\\n }\\n }\\n this.setIndex(indices);\\n this.setAttribute(\\\\\\\"position\\\\\\\", new Float32BufferAttribute(vertices, 3));\\n this.setAttribute(\\\\\\\"normal\\\\\\\", new Float32BufferAttribute(normals, 3));\\n this.setAttribute(\\\\\\\"uv\\\\\\\", new Float32BufferAttribute(uvs, 2));\\n }\\n static fromJSON(data) {\\n return new PlaneGeometry(data.width, data.height, data.widthSegments, data.heightSegments);\\n }\\n};\\n\\n// ../../../node_modules/three/src/materials/Material.js\\nvar materialId = 0;\\nvar Material = class extends EventDispatcher {\\n constructor() {\\n super();\\n Object.defineProperty(this, \\\\\\\"id\\\\\\\", {value: materialId++});\\n this.uuid = generateUUID();\\n this.name = \\\\\\\"\\\\\\\";\\n this.type = \\\\\\\"Material\\\\\\\";\\n this.fog = true;\\n this.blending = NormalBlending;\\n this.side = FrontSide;\\n this.vertexColors = false;\\n this.opacity = 1;\\n this.format = RGBAFormat;\\n this.transparent = false;\\n this.blendSrc = SrcAlphaFactor;\\n this.blendDst = OneMinusSrcAlphaFactor;\\n this.blendEquation = AddEquation;\\n this.blendSrcAlpha = null;\\n this.blendDstAlpha = null;\\n this.blendEquationAlpha = null;\\n this.depthFunc = LessEqualDepth;\\n this.depthTest = true;\\n this.depthWrite = true;\\n this.stencilWriteMask = 255;\\n this.stencilFunc = AlwaysStencilFunc;\\n this.stencilRef = 0;\\n this.stencilFuncMask = 255;\\n this.stencilFail = KeepStencilOp;\\n this.stencilZFail = KeepStencilOp;\\n this.stencilZPass = KeepStencilOp;\\n this.stencilWrite = false;\\n this.clippingPlanes = null;\\n this.clipIntersection = false;\\n this.clipShadows = false;\\n this.shadowSide = null;\\n this.colorWrite = true;\\n this.precision = null;\\n this.polygonOffset = false;\\n this.polygonOffsetFactor = 0;\\n this.polygonOffsetUnits = 0;\\n this.dithering = false;\\n this.alphaToCoverage = false;\\n this.premultipliedAlpha = false;\\n this.visible = true;\\n this.toneMapped = true;\\n this.userData = {};\\n this.version = 0;\\n this._alphaTest = 0;\\n }\\n get alphaTest() {\\n return this._alphaTest;\\n }\\n set alphaTest(value) {\\n if (this._alphaTest > 0 !== value > 0) {\\n this.version++;\\n }\\n this._alphaTest = value;\\n }\\n onBuild() {\\n }\\n onBeforeRender() {\\n }\\n onBeforeCompile() {\\n }\\n customProgramCacheKey() {\\n return this.onBeforeCompile.toString();\\n }\\n setValues(values) {\\n if (values === void 0)\\n return;\\n for (const key in values) {\\n const newValue = values[key];\\n if (newValue === void 0) {\\n console.warn(\\\\\\\"THREE.Material: '\\\\\\\" + key + \\\\\\\"' parameter is undefined.\\\\\\\");\\n continue;\\n }\\n if (key === \\\\\\\"shading\\\\\\\") {\\n console.warn(\\\\\\\"THREE.\\\\\\\" + this.type + \\\\\\\": .shading has been removed. Use the boolean .flatShading instead.\\\\\\\");\\n this.flatShading = newValue === FlatShading ? true : false;\\n continue;\\n }\\n const currentValue = this[key];\\n if (currentValue === void 0) {\\n console.warn(\\\\\\\"THREE.\\\\\\\" + this.type + \\\\\\\": '\\\\\\\" + key + \\\\\\\"' is not a property of this material.\\\\\\\");\\n continue;\\n }\\n if (currentValue && currentValue.isColor) {\\n currentValue.set(newValue);\\n } else if (currentValue && currentValue.isVector3 && (newValue && newValue.isVector3)) {\\n currentValue.copy(newValue);\\n } else {\\n this[key] = newValue;\\n }\\n }\\n }\\n toJSON(meta) {\\n const isRoot = meta === void 0 || typeof meta === \\\\\\\"string\\\\\\\";\\n if (isRoot) {\\n meta = {\\n textures: {},\\n images: {}\\n };\\n }\\n const data = {\\n metadata: {\\n version: 4.5,\\n type: \\\\\\\"Material\\\\\\\",\\n generator: \\\\\\\"Material.toJSON\\\\\\\"\\n }\\n };\\n data.uuid = this.uuid;\\n data.type = this.type;\\n if (this.name !== \\\\\\\"\\\\\\\")\\n data.name = this.name;\\n if (this.color && this.color.isColor)\\n data.color = this.color.getHex();\\n if (this.roughness !== void 0)\\n data.roughness = this.roughness;\\n if (this.metalness !== void 0)\\n data.metalness = this.metalness;\\n if (this.sheen !== void 0)\\n data.sheen = this.sheen;\\n if (this.sheenTint && this.sheenTint.isColor)\\n data.sheenTint = this.sheenTint.getHex();\\n if (this.sheenRoughness !== void 0)\\n data.sheenRoughness = this.sheenRoughness;\\n if (this.emissive && this.emissive.isColor)\\n data.emissive = this.emissive.getHex();\\n if (this.emissiveIntensity && this.emissiveIntensity !== 1)\\n data.emissiveIntensity = this.emissiveIntensity;\\n if (this.specular && this.specular.isColor)\\n data.specular = this.specular.getHex();\\n if (this.specularIntensity !== void 0)\\n data.specularIntensity = this.specularIntensity;\\n if (this.specularTint && this.specularTint.isColor)\\n data.specularTint = this.specularTint.getHex();\\n if (this.shininess !== void 0)\\n data.shininess = this.shininess;\\n if (this.clearcoat !== void 0)\\n data.clearcoat = this.clearcoat;\\n if (this.clearcoatRoughness !== void 0)\\n data.clearcoatRoughness = this.clearcoatRoughness;\\n if (this.clearcoatMap && this.clearcoatMap.isTexture) {\\n data.clearcoatMap = this.clearcoatMap.toJSON(meta).uuid;\\n }\\n if (this.clearcoatRoughnessMap && this.clearcoatRoughnessMap.isTexture) {\\n data.clearcoatRoughnessMap = this.clearcoatRoughnessMap.toJSON(meta).uuid;\\n }\\n if (this.clearcoatNormalMap && this.clearcoatNormalMap.isTexture) {\\n data.clearcoatNormalMap = this.clearcoatNormalMap.toJSON(meta).uuid;\\n data.clearcoatNormalScale = this.clearcoatNormalScale.toArray();\\n }\\n if (this.map && this.map.isTexture)\\n data.map = this.map.toJSON(meta).uuid;\\n if (this.matcap && this.matcap.isTexture)\\n data.matcap = this.matcap.toJSON(meta).uuid;\\n if (this.alphaMap && this.alphaMap.isTexture)\\n data.alphaMap = this.alphaMap.toJSON(meta).uuid;\\n if (this.lightMap && this.lightMap.isTexture) {\\n data.lightMap = this.lightMap.toJSON(meta).uuid;\\n data.lightMapIntensity = this.lightMapIntensity;\\n }\\n if (this.aoMap && this.aoMap.isTexture) {\\n data.aoMap = this.aoMap.toJSON(meta).uuid;\\n data.aoMapIntensity = this.aoMapIntensity;\\n }\\n if (this.bumpMap && this.bumpMap.isTexture) {\\n data.bumpMap = this.bumpMap.toJSON(meta).uuid;\\n data.bumpScale = this.bumpScale;\\n }\\n if (this.normalMap && this.normalMap.isTexture) {\\n data.normalMap = this.normalMap.toJSON(meta).uuid;\\n data.normalMapType = this.normalMapType;\\n data.normalScale = this.normalScale.toArray();\\n }\\n if (this.displacementMap && this.displacementMap.isTexture) {\\n data.displacementMap = this.displacementMap.toJSON(meta).uuid;\\n data.displacementScale = this.displacementScale;\\n data.displacementBias = this.displacementBias;\\n }\\n if (this.roughnessMap && this.roughnessMap.isTexture)\\n data.roughnessMap = this.roughnessMap.toJSON(meta).uuid;\\n if (this.metalnessMap && this.metalnessMap.isTexture)\\n data.metalnessMap = this.metalnessMap.toJSON(meta).uuid;\\n if (this.emissiveMap && this.emissiveMap.isTexture)\\n data.emissiveMap = this.emissiveMap.toJSON(meta).uuid;\\n if (this.specularMap && this.specularMap.isTexture)\\n data.specularMap = this.specularMap.toJSON(meta).uuid;\\n if (this.specularIntensityMap && this.specularIntensityMap.isTexture)\\n data.specularIntensityMap = this.specularIntensityMap.toJSON(meta).uuid;\\n if (this.specularTintMap && this.specularTintMap.isTexture)\\n data.specularTintMap = this.specularTintMap.toJSON(meta).uuid;\\n if (this.envMap && this.envMap.isTexture) {\\n data.envMap = this.envMap.toJSON(meta).uuid;\\n if (this.combine !== void 0)\\n data.combine = this.combine;\\n }\\n if (this.envMapIntensity !== void 0)\\n data.envMapIntensity = this.envMapIntensity;\\n if (this.reflectivity !== void 0)\\n data.reflectivity = this.reflectivity;\\n if (this.refractionRatio !== void 0)\\n data.refractionRatio = this.refractionRatio;\\n if (this.gradientMap && this.gradientMap.isTexture) {\\n data.gradientMap = this.gradientMap.toJSON(meta).uuid;\\n }\\n if (this.transmission !== void 0)\\n data.transmission = this.transmission;\\n if (this.transmissionMap && this.transmissionMap.isTexture)\\n data.transmissionMap = this.transmissionMap.toJSON(meta).uuid;\\n if (this.thickness !== void 0)\\n data.thickness = this.thickness;\\n if (this.thicknessMap && this.thicknessMap.isTexture)\\n data.thicknessMap = this.thicknessMap.toJSON(meta).uuid;\\n if (this.attenuationDistance !== void 0)\\n data.attenuationDistance = this.attenuationDistance;\\n if (this.attenuationTint !== void 0)\\n data.attenuationTint = this.attenuationTint.getHex();\\n if (this.size !== void 0)\\n data.size = this.size;\\n if (this.shadowSide !== null)\\n data.shadowSide = this.shadowSide;\\n if (this.sizeAttenuation !== void 0)\\n data.sizeAttenuation = this.sizeAttenuation;\\n if (this.blending !== NormalBlending)\\n data.blending = this.blending;\\n if (this.side !== FrontSide)\\n data.side = this.side;\\n if (this.vertexColors)\\n data.vertexColors = true;\\n if (this.opacity < 1)\\n data.opacity = this.opacity;\\n if (this.format !== RGBAFormat)\\n data.format = this.format;\\n if (this.transparent === true)\\n data.transparent = this.transparent;\\n data.depthFunc = this.depthFunc;\\n data.depthTest = this.depthTest;\\n data.depthWrite = this.depthWrite;\\n data.colorWrite = this.colorWrite;\\n data.stencilWrite = this.stencilWrite;\\n data.stencilWriteMask = this.stencilWriteMask;\\n data.stencilFunc = this.stencilFunc;\\n data.stencilRef = this.stencilRef;\\n data.stencilFuncMask = this.stencilFuncMask;\\n data.stencilFail = this.stencilFail;\\n data.stencilZFail = this.stencilZFail;\\n data.stencilZPass = this.stencilZPass;\\n if (this.rotation && this.rotation !== 0)\\n data.rotation = this.rotation;\\n if (this.polygonOffset === true)\\n data.polygonOffset = true;\\n if (this.polygonOffsetFactor !== 0)\\n data.polygonOffsetFactor = this.polygonOffsetFactor;\\n if (this.polygonOffsetUnits !== 0)\\n data.polygonOffsetUnits = this.polygonOffsetUnits;\\n if (this.linewidth && this.linewidth !== 1)\\n data.linewidth = this.linewidth;\\n if (this.dashSize !== void 0)\\n data.dashSize = this.dashSize;\\n if (this.gapSize !== void 0)\\n data.gapSize = this.gapSize;\\n if (this.scale !== void 0)\\n data.scale = this.scale;\\n if (this.dithering === true)\\n data.dithering = true;\\n if (this.alphaTest > 0)\\n data.alphaTest = this.alphaTest;\\n if (this.alphaToCoverage === true)\\n data.alphaToCoverage = this.alphaToCoverage;\\n if (this.premultipliedAlpha === true)\\n data.premultipliedAlpha = this.premultipliedAlpha;\\n if (this.wireframe === true)\\n data.wireframe = this.wireframe;\\n if (this.wireframeLinewidth > 1)\\n data.wireframeLinewidth = this.wireframeLinewidth;\\n if (this.wireframeLinecap !== \\\\\\\"round\\\\\\\")\\n data.wireframeLinecap = this.wireframeLinecap;\\n if (this.wireframeLinejoin !== \\\\\\\"round\\\\\\\")\\n data.wireframeLinejoin = this.wireframeLinejoin;\\n if (this.flatShading === true)\\n data.flatShading = this.flatShading;\\n if (this.visible === false)\\n data.visible = false;\\n if (this.toneMapped === false)\\n data.toneMapped = false;\\n if (JSON.stringify(this.userData) !== \\\\\\\"{}\\\\\\\")\\n data.userData = this.userData;\\n function extractFromCache(cache) {\\n const values = [];\\n for (const key in cache) {\\n const data2 = cache[key];\\n delete data2.metadata;\\n values.push(data2);\\n }\\n return values;\\n }\\n if (isRoot) {\\n const textures = extractFromCache(meta.textures);\\n const images = extractFromCache(meta.images);\\n if (textures.length > 0)\\n data.textures = textures;\\n if (images.length > 0)\\n data.images = images;\\n }\\n return data;\\n }\\n clone() {\\n return new this.constructor().copy(this);\\n }\\n copy(source) {\\n this.name = source.name;\\n this.fog = source.fog;\\n this.blending = source.blending;\\n this.side = source.side;\\n this.vertexColors = source.vertexColors;\\n this.opacity = source.opacity;\\n this.format = source.format;\\n this.transparent = source.transparent;\\n this.blendSrc = source.blendSrc;\\n this.blendDst = source.blendDst;\\n this.blendEquation = source.blendEquation;\\n this.blendSrcAlpha = source.blendSrcAlpha;\\n this.blendDstAlpha = source.blendDstAlpha;\\n this.blendEquationAlpha = source.blendEquationAlpha;\\n this.depthFunc = source.depthFunc;\\n this.depthTest = source.depthTest;\\n this.depthWrite = source.depthWrite;\\n this.stencilWriteMask = source.stencilWriteMask;\\n this.stencilFunc = source.stencilFunc;\\n this.stencilRef = source.stencilRef;\\n this.stencilFuncMask = source.stencilFuncMask;\\n this.stencilFail = source.stencilFail;\\n this.stencilZFail = source.stencilZFail;\\n this.stencilZPass = source.stencilZPass;\\n this.stencilWrite = source.stencilWrite;\\n const srcPlanes = source.clippingPlanes;\\n let dstPlanes = null;\\n if (srcPlanes !== null) {\\n const n = srcPlanes.length;\\n dstPlanes = new Array(n);\\n for (let i = 0; i !== n; ++i) {\\n dstPlanes[i] = srcPlanes[i].clone();\\n }\\n }\\n this.clippingPlanes = dstPlanes;\\n this.clipIntersection = source.clipIntersection;\\n this.clipShadows = source.clipShadows;\\n this.shadowSide = source.shadowSide;\\n this.colorWrite = source.colorWrite;\\n this.precision = source.precision;\\n this.polygonOffset = source.polygonOffset;\\n this.polygonOffsetFactor = source.polygonOffsetFactor;\\n this.polygonOffsetUnits = source.polygonOffsetUnits;\\n this.dithering = source.dithering;\\n this.alphaTest = source.alphaTest;\\n this.alphaToCoverage = source.alphaToCoverage;\\n this.premultipliedAlpha = source.premultipliedAlpha;\\n this.visible = source.visible;\\n this.toneMapped = source.toneMapped;\\n this.userData = JSON.parse(JSON.stringify(source.userData));\\n return this;\\n }\\n dispose() {\\n this.dispatchEvent({type: \\\\\\\"dispose\\\\\\\"});\\n }\\n set needsUpdate(value) {\\n if (value === true)\\n this.version++;\\n }\\n};\\nMaterial.prototype.isMaterial = true;\\n\\n// ../../../node_modules/three/src/renderers/shaders/UniformsUtils.js\\nfunction cloneUniforms(src) {\\n const dst = {};\\n for (const u in src) {\\n dst[u] = {};\\n for (const p in src[u]) {\\n const property = src[u][p];\\n if (property && (property.isColor || property.isMatrix3 || property.isMatrix4 || property.isVector2 || property.isVector3 || property.isVector4 || property.isTexture || property.isQuaternion)) {\\n dst[u][p] = property.clone();\\n } else if (Array.isArray(property)) {\\n dst[u][p] = property.slice();\\n } else {\\n dst[u][p] = property;\\n }\\n }\\n }\\n return dst;\\n}\\nfunction mergeUniforms(uniforms) {\\n const merged = {};\\n for (let u = 0; u < uniforms.length; u++) {\\n const tmp = cloneUniforms(uniforms[u]);\\n for (const p in tmp) {\\n merged[p] = tmp[p];\\n }\\n }\\n return merged;\\n}\\nvar UniformsUtils = {clone: cloneUniforms, merge: mergeUniforms};\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/default_vertex.glsl.js\\nvar default_vertex_glsl_default = `\\nvoid main() {\\n\\tgl_Position = projectionMatrix * modelViewMatrix * vec4( position, 1.0 );\\n}\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/default_fragment.glsl.js\\nvar default_fragment_glsl_default = `\\nvoid main() {\\n\\tgl_FragColor = vec4( 1.0, 0.0, 0.0, 1.0 );\\n}\\n`;\\n\\n// ../../../node_modules/three/src/materials/ShaderMaterial.js\\nvar ShaderMaterial = class extends Material {\\n constructor(parameters) {\\n super();\\n this.type = \\\\\\\"ShaderMaterial\\\\\\\";\\n this.defines = {};\\n this.uniforms = {};\\n this.vertexShader = default_vertex_glsl_default;\\n this.fragmentShader = default_fragment_glsl_default;\\n this.linewidth = 1;\\n this.wireframe = false;\\n this.wireframeLinewidth = 1;\\n this.fog = false;\\n this.lights = false;\\n this.clipping = false;\\n this.extensions = {\\n derivatives: false,\\n fragDepth: false,\\n drawBuffers: false,\\n shaderTextureLOD: false\\n };\\n this.defaultAttributeValues = {\\n color: [1, 1, 1],\\n uv: [0, 0],\\n uv2: [0, 0]\\n };\\n this.index0AttributeName = void 0;\\n this.uniformsNeedUpdate = false;\\n this.glslVersion = null;\\n if (parameters !== void 0) {\\n if (parameters.attributes !== void 0) {\\n console.error(\\\\\\\"THREE.ShaderMaterial: attributes should now be defined in THREE.BufferGeometry instead.\\\\\\\");\\n }\\n this.setValues(parameters);\\n }\\n }\\n copy(source) {\\n super.copy(source);\\n this.fragmentShader = source.fragmentShader;\\n this.vertexShader = source.vertexShader;\\n this.uniforms = cloneUniforms(source.uniforms);\\n this.defines = Object.assign({}, source.defines);\\n this.wireframe = source.wireframe;\\n this.wireframeLinewidth = source.wireframeLinewidth;\\n this.lights = source.lights;\\n this.clipping = source.clipping;\\n this.extensions = Object.assign({}, source.extensions);\\n this.glslVersion = source.glslVersion;\\n return this;\\n }\\n toJSON(meta) {\\n const data = super.toJSON(meta);\\n data.glslVersion = this.glslVersion;\\n data.uniforms = {};\\n for (const name in this.uniforms) {\\n const uniform = this.uniforms[name];\\n const value = uniform.value;\\n if (value && value.isTexture) {\\n data.uniforms[name] = {\\n type: \\\\\\\"t\\\\\\\",\\n value: value.toJSON(meta).uuid\\n };\\n } else if (value && value.isColor) {\\n data.uniforms[name] = {\\n type: \\\\\\\"c\\\\\\\",\\n value: value.getHex()\\n };\\n } else if (value && value.isVector2) {\\n data.uniforms[name] = {\\n type: \\\\\\\"v2\\\\\\\",\\n value: value.toArray()\\n };\\n } else if (value && value.isVector3) {\\n data.uniforms[name] = {\\n type: \\\\\\\"v3\\\\\\\",\\n value: value.toArray()\\n };\\n } else if (value && value.isVector4) {\\n data.uniforms[name] = {\\n type: \\\\\\\"v4\\\\\\\",\\n value: value.toArray()\\n };\\n } else if (value && value.isMatrix3) {\\n data.uniforms[name] = {\\n type: \\\\\\\"m3\\\\\\\",\\n value: value.toArray()\\n };\\n } else if (value && value.isMatrix4) {\\n data.uniforms[name] = {\\n type: \\\\\\\"m4\\\\\\\",\\n value: value.toArray()\\n };\\n } else {\\n data.uniforms[name] = {\\n value\\n };\\n }\\n }\\n if (Object.keys(this.defines).length > 0)\\n data.defines = this.defines;\\n data.vertexShader = this.vertexShader;\\n data.fragmentShader = this.fragmentShader;\\n const extensions = {};\\n for (const key in this.extensions) {\\n if (this.extensions[key] === true)\\n extensions[key] = true;\\n }\\n if (Object.keys(extensions).length > 0)\\n data.extensions = extensions;\\n return data;\\n }\\n};\\nShaderMaterial.prototype.isShaderMaterial = true;\\n\\n// ../../../node_modules/three/src/math/Ray.js\\nvar _vector6 = /* @__PURE__ */ new Vector3();\\nvar _segCenter = /* @__PURE__ */ new Vector3();\\nvar _segDir = /* @__PURE__ */ new Vector3();\\nvar _diff = /* @__PURE__ */ new Vector3();\\nvar _edge1 = /* @__PURE__ */ new Vector3();\\nvar _edge2 = /* @__PURE__ */ new Vector3();\\nvar _normal = /* @__PURE__ */ new Vector3();\\nvar Ray = class {\\n constructor(origin = new Vector3(), direction = new Vector3(0, 0, -1)) {\\n this.origin = origin;\\n this.direction = direction;\\n }\\n set(origin, direction) {\\n this.origin.copy(origin);\\n this.direction.copy(direction);\\n return this;\\n }\\n copy(ray) {\\n this.origin.copy(ray.origin);\\n this.direction.copy(ray.direction);\\n return this;\\n }\\n at(t, target) {\\n return target.copy(this.direction).multiplyScalar(t).add(this.origin);\\n }\\n lookAt(v) {\\n this.direction.copy(v).sub(this.origin).normalize();\\n return this;\\n }\\n recast(t) {\\n this.origin.copy(this.at(t, _vector6));\\n return this;\\n }\\n closestPointToPoint(point, target) {\\n target.subVectors(point, this.origin);\\n const directionDistance = target.dot(this.direction);\\n if (directionDistance < 0) {\\n return target.copy(this.origin);\\n }\\n return target.copy(this.direction).multiplyScalar(directionDistance).add(this.origin);\\n }\\n distanceToPoint(point) {\\n return Math.sqrt(this.distanceSqToPoint(point));\\n }\\n distanceSqToPoint(point) {\\n const directionDistance = _vector6.subVectors(point, this.origin).dot(this.direction);\\n if (directionDistance < 0) {\\n return this.origin.distanceToSquared(point);\\n }\\n _vector6.copy(this.direction).multiplyScalar(directionDistance).add(this.origin);\\n return _vector6.distanceToSquared(point);\\n }\\n distanceSqToSegment(v0, v1, optionalPointOnRay, optionalPointOnSegment) {\\n _segCenter.copy(v0).add(v1).multiplyScalar(0.5);\\n _segDir.copy(v1).sub(v0).normalize();\\n _diff.copy(this.origin).sub(_segCenter);\\n const segExtent = v0.distanceTo(v1) * 0.5;\\n const a01 = -this.direction.dot(_segDir);\\n const b0 = _diff.dot(this.direction);\\n const b1 = -_diff.dot(_segDir);\\n const c = _diff.lengthSq();\\n const det = Math.abs(1 - a01 * a01);\\n let s0, s1, sqrDist, extDet;\\n if (det > 0) {\\n s0 = a01 * b1 - b0;\\n s1 = a01 * b0 - b1;\\n extDet = segExtent * det;\\n if (s0 >= 0) {\\n if (s1 >= -extDet) {\\n if (s1 <= extDet) {\\n const invDet = 1 / det;\\n s0 *= invDet;\\n s1 *= invDet;\\n sqrDist = s0 * (s0 + a01 * s1 + 2 * b0) + s1 * (a01 * s0 + s1 + 2 * b1) + c;\\n } else {\\n s1 = segExtent;\\n s0 = Math.max(0, -(a01 * s1 + b0));\\n sqrDist = -s0 * s0 + s1 * (s1 + 2 * b1) + c;\\n }\\n } else {\\n s1 = -segExtent;\\n s0 = Math.max(0, -(a01 * s1 + b0));\\n sqrDist = -s0 * s0 + s1 * (s1 + 2 * b1) + c;\\n }\\n } else {\\n if (s1 <= -extDet) {\\n s0 = Math.max(0, -(-a01 * segExtent + b0));\\n s1 = s0 > 0 ? -segExtent : Math.min(Math.max(-segExtent, -b1), segExtent);\\n sqrDist = -s0 * s0 + s1 * (s1 + 2 * b1) + c;\\n } else if (s1 <= extDet) {\\n s0 = 0;\\n s1 = Math.min(Math.max(-segExtent, -b1), segExtent);\\n sqrDist = s1 * (s1 + 2 * b1) + c;\\n } else {\\n s0 = Math.max(0, -(a01 * segExtent + b0));\\n s1 = s0 > 0 ? segExtent : Math.min(Math.max(-segExtent, -b1), segExtent);\\n sqrDist = -s0 * s0 + s1 * (s1 + 2 * b1) + c;\\n }\\n }\\n } else {\\n s1 = a01 > 0 ? -segExtent : segExtent;\\n s0 = Math.max(0, -(a01 * s1 + b0));\\n sqrDist = -s0 * s0 + s1 * (s1 + 2 * b1) + c;\\n }\\n if (optionalPointOnRay) {\\n optionalPointOnRay.copy(this.direction).multiplyScalar(s0).add(this.origin);\\n }\\n if (optionalPointOnSegment) {\\n optionalPointOnSegment.copy(_segDir).multiplyScalar(s1).add(_segCenter);\\n }\\n return sqrDist;\\n }\\n intersectSphere(sphere, target) {\\n _vector6.subVectors(sphere.center, this.origin);\\n const tca = _vector6.dot(this.direction);\\n const d2 = _vector6.dot(_vector6) - tca * tca;\\n const radius2 = sphere.radius * sphere.radius;\\n if (d2 > radius2)\\n return null;\\n const thc = Math.sqrt(radius2 - d2);\\n const t0 = tca - thc;\\n const t1 = tca + thc;\\n if (t0 < 0 && t1 < 0)\\n return null;\\n if (t0 < 0)\\n return this.at(t1, target);\\n return this.at(t0, target);\\n }\\n intersectsSphere(sphere) {\\n return this.distanceSqToPoint(sphere.center) <= sphere.radius * sphere.radius;\\n }\\n distanceToPlane(plane) {\\n const denominator = plane.normal.dot(this.direction);\\n if (denominator === 0) {\\n if (plane.distanceToPoint(this.origin) === 0) {\\n return 0;\\n }\\n return null;\\n }\\n const t = -(this.origin.dot(plane.normal) + plane.constant) / denominator;\\n return t >= 0 ? t : null;\\n }\\n intersectPlane(plane, target) {\\n const t = this.distanceToPlane(plane);\\n if (t === null) {\\n return null;\\n }\\n return this.at(t, target);\\n }\\n intersectsPlane(plane) {\\n const distToPoint = plane.distanceToPoint(this.origin);\\n if (distToPoint === 0) {\\n return true;\\n }\\n const denominator = plane.normal.dot(this.direction);\\n if (denominator * distToPoint < 0) {\\n return true;\\n }\\n return false;\\n }\\n intersectBox(box, target) {\\n let tmin, tmax, tymin, tymax, tzmin, tzmax;\\n const invdirx = 1 / this.direction.x, invdiry = 1 / this.direction.y, invdirz = 1 / this.direction.z;\\n const origin = this.origin;\\n if (invdirx >= 0) {\\n tmin = (box.min.x - origin.x) * invdirx;\\n tmax = (box.max.x - origin.x) * invdirx;\\n } else {\\n tmin = (box.max.x - origin.x) * invdirx;\\n tmax = (box.min.x - origin.x) * invdirx;\\n }\\n if (invdiry >= 0) {\\n tymin = (box.min.y - origin.y) * invdiry;\\n tymax = (box.max.y - origin.y) * invdiry;\\n } else {\\n tymin = (box.max.y - origin.y) * invdiry;\\n tymax = (box.min.y - origin.y) * invdiry;\\n }\\n if (tmin > tymax || tymin > tmax)\\n return null;\\n if (tymin > tmin || tmin !== tmin)\\n tmin = tymin;\\n if (tymax < tmax || tmax !== tmax)\\n tmax = tymax;\\n if (invdirz >= 0) {\\n tzmin = (box.min.z - origin.z) * invdirz;\\n tzmax = (box.max.z - origin.z) * invdirz;\\n } else {\\n tzmin = (box.max.z - origin.z) * invdirz;\\n tzmax = (box.min.z - origin.z) * invdirz;\\n }\\n if (tmin > tzmax || tzmin > tmax)\\n return null;\\n if (tzmin > tmin || tmin !== tmin)\\n tmin = tzmin;\\n if (tzmax < tmax || tmax !== tmax)\\n tmax = tzmax;\\n if (tmax < 0)\\n return null;\\n return this.at(tmin >= 0 ? tmin : tmax, target);\\n }\\n intersectsBox(box) {\\n return this.intersectBox(box, _vector6) !== null;\\n }\\n intersectTriangle(a, b, c, backfaceCulling, target) {\\n _edge1.subVectors(b, a);\\n _edge2.subVectors(c, a);\\n _normal.crossVectors(_edge1, _edge2);\\n let DdN = this.direction.dot(_normal);\\n let sign;\\n if (DdN > 0) {\\n if (backfaceCulling)\\n return null;\\n sign = 1;\\n } else if (DdN < 0) {\\n sign = -1;\\n DdN = -DdN;\\n } else {\\n return null;\\n }\\n _diff.subVectors(this.origin, a);\\n const DdQxE2 = sign * this.direction.dot(_edge2.crossVectors(_diff, _edge2));\\n if (DdQxE2 < 0) {\\n return null;\\n }\\n const DdE1xQ = sign * this.direction.dot(_edge1.cross(_diff));\\n if (DdE1xQ < 0) {\\n return null;\\n }\\n if (DdQxE2 + DdE1xQ > DdN) {\\n return null;\\n }\\n const QdN = -sign * _diff.dot(_normal);\\n if (QdN < 0) {\\n return null;\\n }\\n return this.at(QdN / DdN, target);\\n }\\n applyMatrix4(matrix4) {\\n this.origin.applyMatrix4(matrix4);\\n this.direction.transformDirection(matrix4);\\n return this;\\n }\\n equals(ray) {\\n return ray.origin.equals(this.origin) && ray.direction.equals(this.direction);\\n }\\n clone() {\\n return new this.constructor().copy(this);\\n }\\n};\\n\\n// ../../../node_modules/three/src/math/Triangle.js\\nvar _v02 = /* @__PURE__ */ new Vector3();\\nvar _v15 = /* @__PURE__ */ new Vector3();\\nvar _v22 = /* @__PURE__ */ new Vector3();\\nvar _v3 = /* @__PURE__ */ new Vector3();\\nvar _vab = /* @__PURE__ */ new Vector3();\\nvar _vac = /* @__PURE__ */ new Vector3();\\nvar _vbc = /* @__PURE__ */ new Vector3();\\nvar _vap = /* @__PURE__ */ new Vector3();\\nvar _vbp = /* @__PURE__ */ new Vector3();\\nvar _vcp = /* @__PURE__ */ new Vector3();\\nvar Triangle = class {\\n constructor(a = new Vector3(), b = new Vector3(), c = new Vector3()) {\\n this.a = a;\\n this.b = b;\\n this.c = c;\\n }\\n static getNormal(a, b, c, target) {\\n target.subVectors(c, b);\\n _v02.subVectors(a, b);\\n target.cross(_v02);\\n const targetLengthSq = target.lengthSq();\\n if (targetLengthSq > 0) {\\n return target.multiplyScalar(1 / Math.sqrt(targetLengthSq));\\n }\\n return target.set(0, 0, 0);\\n }\\n static getBarycoord(point, a, b, c, target) {\\n _v02.subVectors(c, a);\\n _v15.subVectors(b, a);\\n _v22.subVectors(point, a);\\n const dot00 = _v02.dot(_v02);\\n const dot01 = _v02.dot(_v15);\\n const dot02 = _v02.dot(_v22);\\n const dot11 = _v15.dot(_v15);\\n const dot12 = _v15.dot(_v22);\\n const denom = dot00 * dot11 - dot01 * dot01;\\n if (denom === 0) {\\n return target.set(-2, -1, -1);\\n }\\n const invDenom = 1 / denom;\\n const u = (dot11 * dot02 - dot01 * dot12) * invDenom;\\n const v = (dot00 * dot12 - dot01 * dot02) * invDenom;\\n return target.set(1 - u - v, v, u);\\n }\\n static containsPoint(point, a, b, c) {\\n this.getBarycoord(point, a, b, c, _v3);\\n return _v3.x >= 0 && _v3.y >= 0 && _v3.x + _v3.y <= 1;\\n }\\n static getUV(point, p1, p2, p3, uv1, uv2, uv3, target) {\\n this.getBarycoord(point, p1, p2, p3, _v3);\\n target.set(0, 0);\\n target.addScaledVector(uv1, _v3.x);\\n target.addScaledVector(uv2, _v3.y);\\n target.addScaledVector(uv3, _v3.z);\\n return target;\\n }\\n static isFrontFacing(a, b, c, direction) {\\n _v02.subVectors(c, b);\\n _v15.subVectors(a, b);\\n return _v02.cross(_v15).dot(direction) < 0 ? true : false;\\n }\\n set(a, b, c) {\\n this.a.copy(a);\\n this.b.copy(b);\\n this.c.copy(c);\\n return this;\\n }\\n setFromPointsAndIndices(points2, i0, i1, i2) {\\n this.a.copy(points2[i0]);\\n this.b.copy(points2[i1]);\\n this.c.copy(points2[i2]);\\n return this;\\n }\\n setFromAttributeAndIndices(attribute, i0, i1, i2) {\\n this.a.fromBufferAttribute(attribute, i0);\\n this.b.fromBufferAttribute(attribute, i1);\\n this.c.fromBufferAttribute(attribute, i2);\\n return this;\\n }\\n clone() {\\n return new this.constructor().copy(this);\\n }\\n copy(triangle) {\\n this.a.copy(triangle.a);\\n this.b.copy(triangle.b);\\n this.c.copy(triangle.c);\\n return this;\\n }\\n getArea() {\\n _v02.subVectors(this.c, this.b);\\n _v15.subVectors(this.a, this.b);\\n return _v02.cross(_v15).length() * 0.5;\\n }\\n getMidpoint(target) {\\n return target.addVectors(this.a, this.b).add(this.c).multiplyScalar(1 / 3);\\n }\\n getNormal(target) {\\n return Triangle.getNormal(this.a, this.b, this.c, target);\\n }\\n getPlane(target) {\\n return target.setFromCoplanarPoints(this.a, this.b, this.c);\\n }\\n getBarycoord(point, target) {\\n return Triangle.getBarycoord(point, this.a, this.b, this.c, target);\\n }\\n getUV(point, uv1, uv2, uv3, target) {\\n return Triangle.getUV(point, this.a, this.b, this.c, uv1, uv2, uv3, target);\\n }\\n containsPoint(point) {\\n return Triangle.containsPoint(point, this.a, this.b, this.c);\\n }\\n isFrontFacing(direction) {\\n return Triangle.isFrontFacing(this.a, this.b, this.c, direction);\\n }\\n intersectsBox(box) {\\n return box.intersectsTriangle(this);\\n }\\n closestPointToPoint(p, target) {\\n const a = this.a, b = this.b, c = this.c;\\n let v, w;\\n _vab.subVectors(b, a);\\n _vac.subVectors(c, a);\\n _vap.subVectors(p, a);\\n const d1 = _vab.dot(_vap);\\n const d2 = _vac.dot(_vap);\\n if (d1 <= 0 && d2 <= 0) {\\n return target.copy(a);\\n }\\n _vbp.subVectors(p, b);\\n const d3 = _vab.dot(_vbp);\\n const d4 = _vac.dot(_vbp);\\n if (d3 >= 0 && d4 <= d3) {\\n return target.copy(b);\\n }\\n const vc = d1 * d4 - d3 * d2;\\n if (vc <= 0 && d1 >= 0 && d3 <= 0) {\\n v = d1 / (d1 - d3);\\n return target.copy(a).addScaledVector(_vab, v);\\n }\\n _vcp.subVectors(p, c);\\n const d5 = _vab.dot(_vcp);\\n const d6 = _vac.dot(_vcp);\\n if (d6 >= 0 && d5 <= d6) {\\n return target.copy(c);\\n }\\n const vb = d5 * d2 - d1 * d6;\\n if (vb <= 0 && d2 >= 0 && d6 <= 0) {\\n w = d2 / (d2 - d6);\\n return target.copy(a).addScaledVector(_vac, w);\\n }\\n const va = d3 * d6 - d5 * d4;\\n if (va <= 0 && d4 - d3 >= 0 && d5 - d6 >= 0) {\\n _vbc.subVectors(c, b);\\n w = (d4 - d3) / (d4 - d3 + (d5 - d6));\\n return target.copy(b).addScaledVector(_vbc, w);\\n }\\n const denom = 1 / (va + vb + vc);\\n v = vb * denom;\\n w = vc * denom;\\n return target.copy(a).addScaledVector(_vab, v).addScaledVector(_vac, w);\\n }\\n equals(triangle) {\\n return triangle.a.equals(this.a) && triangle.b.equals(this.b) && triangle.c.equals(this.c);\\n }\\n};\\n\\n// ../../../node_modules/three/src/materials/MeshBasicMaterial.js\\nvar MeshBasicMaterial = class extends Material {\\n constructor(parameters) {\\n super();\\n this.type = \\\\\\\"MeshBasicMaterial\\\\\\\";\\n this.color = new Color(16777215);\\n this.map = null;\\n this.lightMap = null;\\n this.lightMapIntensity = 1;\\n this.aoMap = null;\\n this.aoMapIntensity = 1;\\n this.specularMap = null;\\n this.alphaMap = null;\\n this.envMap = null;\\n this.combine = MultiplyOperation;\\n this.reflectivity = 1;\\n this.refractionRatio = 0.98;\\n this.wireframe = false;\\n this.wireframeLinewidth = 1;\\n this.wireframeLinecap = \\\\\\\"round\\\\\\\";\\n this.wireframeLinejoin = \\\\\\\"round\\\\\\\";\\n this.setValues(parameters);\\n }\\n copy(source) {\\n super.copy(source);\\n this.color.copy(source.color);\\n this.map = source.map;\\n this.lightMap = source.lightMap;\\n this.lightMapIntensity = source.lightMapIntensity;\\n this.aoMap = source.aoMap;\\n this.aoMapIntensity = source.aoMapIntensity;\\n this.specularMap = source.specularMap;\\n this.alphaMap = source.alphaMap;\\n this.envMap = source.envMap;\\n this.combine = source.combine;\\n this.reflectivity = source.reflectivity;\\n this.refractionRatio = source.refractionRatio;\\n this.wireframe = source.wireframe;\\n this.wireframeLinewidth = source.wireframeLinewidth;\\n this.wireframeLinecap = source.wireframeLinecap;\\n this.wireframeLinejoin = source.wireframeLinejoin;\\n return this;\\n }\\n};\\nMeshBasicMaterial.prototype.isMeshBasicMaterial = true;\\n\\n// ../../../node_modules/three/src/objects/Mesh.js\\nvar _inverseMatrix = /* @__PURE__ */ new Matrix4();\\nvar _ray = /* @__PURE__ */ new Ray();\\nvar _sphere2 = /* @__PURE__ */ new Sphere();\\nvar _vA = /* @__PURE__ */ new Vector3();\\nvar _vB = /* @__PURE__ */ new Vector3();\\nvar _vC = /* @__PURE__ */ new Vector3();\\nvar _tempA = /* @__PURE__ */ new Vector3();\\nvar _tempB = /* @__PURE__ */ new Vector3();\\nvar _tempC = /* @__PURE__ */ new Vector3();\\nvar _morphA = /* @__PURE__ */ new Vector3();\\nvar _morphB = /* @__PURE__ */ new Vector3();\\nvar _morphC = /* @__PURE__ */ new Vector3();\\nvar _uvA = /* @__PURE__ */ new Vector2();\\nvar _uvB = /* @__PURE__ */ new Vector2();\\nvar _uvC = /* @__PURE__ */ new Vector2();\\nvar _intersectionPoint = /* @__PURE__ */ new Vector3();\\nvar _intersectionPointWorld = /* @__PURE__ */ new Vector3();\\nvar Mesh = class extends Object3D {\\n constructor(geometry = new BufferGeometry(), material = new MeshBasicMaterial()) {\\n super();\\n this.type = \\\\\\\"Mesh\\\\\\\";\\n this.geometry = geometry;\\n this.material = material;\\n this.updateMorphTargets();\\n }\\n copy(source) {\\n super.copy(source);\\n if (source.morphTargetInfluences !== void 0) {\\n this.morphTargetInfluences = source.morphTargetInfluences.slice();\\n }\\n if (source.morphTargetDictionary !== void 0) {\\n this.morphTargetDictionary = Object.assign({}, source.morphTargetDictionary);\\n }\\n this.material = source.material;\\n this.geometry = source.geometry;\\n return this;\\n }\\n updateMorphTargets() {\\n const geometry = this.geometry;\\n if (geometry.isBufferGeometry) {\\n const morphAttributes = geometry.morphAttributes;\\n const keys = Object.keys(morphAttributes);\\n if (keys.length > 0) {\\n const morphAttribute = morphAttributes[keys[0]];\\n if (morphAttribute !== void 0) {\\n this.morphTargetInfluences = [];\\n this.morphTargetDictionary = {};\\n for (let m = 0, ml = morphAttribute.length; m < ml; m++) {\\n const name = morphAttribute[m].name || String(m);\\n this.morphTargetInfluences.push(0);\\n this.morphTargetDictionary[name] = m;\\n }\\n }\\n }\\n } else {\\n const morphTargets = geometry.morphTargets;\\n if (morphTargets !== void 0 && morphTargets.length > 0) {\\n console.error(\\\\\\\"THREE.Mesh.updateMorphTargets() no longer supports THREE.Geometry. Use THREE.BufferGeometry instead.\\\\\\\");\\n }\\n }\\n }\\n raycast(raycaster, intersects) {\\n const geometry = this.geometry;\\n const material = this.material;\\n const matrixWorld = this.matrixWorld;\\n if (material === void 0)\\n return;\\n if (geometry.boundingSphere === null)\\n geometry.computeBoundingSphere();\\n _sphere2.copy(geometry.boundingSphere);\\n _sphere2.applyMatrix4(matrixWorld);\\n if (raycaster.ray.intersectsSphere(_sphere2) === false)\\n return;\\n _inverseMatrix.copy(matrixWorld).invert();\\n _ray.copy(raycaster.ray).applyMatrix4(_inverseMatrix);\\n if (geometry.boundingBox !== null) {\\n if (_ray.intersectsBox(geometry.boundingBox) === false)\\n return;\\n }\\n let intersection;\\n if (geometry.isBufferGeometry) {\\n const index = geometry.index;\\n const position = geometry.attributes.position;\\n const morphPosition = geometry.morphAttributes.position;\\n const morphTargetsRelative = geometry.morphTargetsRelative;\\n const uv = geometry.attributes.uv;\\n const uv2 = geometry.attributes.uv2;\\n const groups = geometry.groups;\\n const drawRange = geometry.drawRange;\\n if (index !== null) {\\n if (Array.isArray(material)) {\\n for (let i = 0, il = groups.length; i < il; i++) {\\n const group = groups[i];\\n const groupMaterial = material[group.materialIndex];\\n const start = Math.max(group.start, drawRange.start);\\n const end = Math.min(index.count, Math.min(group.start + group.count, drawRange.start + drawRange.count));\\n for (let j = start, jl = end; j < jl; j += 3) {\\n const a = index.getX(j);\\n const b = index.getX(j + 1);\\n const c = index.getX(j + 2);\\n intersection = checkBufferGeometryIntersection(this, groupMaterial, raycaster, _ray, position, morphPosition, morphTargetsRelative, uv, uv2, a, b, c);\\n if (intersection) {\\n intersection.faceIndex = Math.floor(j / 3);\\n intersection.face.materialIndex = group.materialIndex;\\n intersects.push(intersection);\\n }\\n }\\n }\\n } else {\\n const start = Math.max(0, drawRange.start);\\n const end = Math.min(index.count, drawRange.start + drawRange.count);\\n for (let i = start, il = end; i < il; i += 3) {\\n const a = index.getX(i);\\n const b = index.getX(i + 1);\\n const c = index.getX(i + 2);\\n intersection = checkBufferGeometryIntersection(this, material, raycaster, _ray, position, morphPosition, morphTargetsRelative, uv, uv2, a, b, c);\\n if (intersection) {\\n intersection.faceIndex = Math.floor(i / 3);\\n intersects.push(intersection);\\n }\\n }\\n }\\n } else if (position !== void 0) {\\n if (Array.isArray(material)) {\\n for (let i = 0, il = groups.length; i < il; i++) {\\n const group = groups[i];\\n const groupMaterial = material[group.materialIndex];\\n const start = Math.max(group.start, drawRange.start);\\n const end = Math.min(position.count, Math.min(group.start + group.count, drawRange.start + drawRange.count));\\n for (let j = start, jl = end; j < jl; j += 3) {\\n const a = j;\\n const b = j + 1;\\n const c = j + 2;\\n intersection = checkBufferGeometryIntersection(this, groupMaterial, raycaster, _ray, position, morphPosition, morphTargetsRelative, uv, uv2, a, b, c);\\n if (intersection) {\\n intersection.faceIndex = Math.floor(j / 3);\\n intersection.face.materialIndex = group.materialIndex;\\n intersects.push(intersection);\\n }\\n }\\n }\\n } else {\\n const start = Math.max(0, drawRange.start);\\n const end = Math.min(position.count, drawRange.start + drawRange.count);\\n for (let i = start, il = end; i < il; i += 3) {\\n const a = i;\\n const b = i + 1;\\n const c = i + 2;\\n intersection = checkBufferGeometryIntersection(this, material, raycaster, _ray, position, morphPosition, morphTargetsRelative, uv, uv2, a, b, c);\\n if (intersection) {\\n intersection.faceIndex = Math.floor(i / 3);\\n intersects.push(intersection);\\n }\\n }\\n }\\n }\\n } else if (geometry.isGeometry) {\\n console.error(\\\\\\\"THREE.Mesh.raycast() no longer supports THREE.Geometry. Use THREE.BufferGeometry instead.\\\\\\\");\\n }\\n }\\n};\\nMesh.prototype.isMesh = true;\\nfunction checkIntersection(object, material, raycaster, ray, pA, pB, pC, point) {\\n let intersect;\\n if (material.side === BackSide) {\\n intersect = ray.intersectTriangle(pC, pB, pA, true, point);\\n } else {\\n intersect = ray.intersectTriangle(pA, pB, pC, material.side !== DoubleSide, point);\\n }\\n if (intersect === null)\\n return null;\\n _intersectionPointWorld.copy(point);\\n _intersectionPointWorld.applyMatrix4(object.matrixWorld);\\n const distance = raycaster.ray.origin.distanceTo(_intersectionPointWorld);\\n if (distance < raycaster.near || distance > raycaster.far)\\n return null;\\n return {\\n distance,\\n point: _intersectionPointWorld.clone(),\\n object\\n };\\n}\\nfunction checkBufferGeometryIntersection(object, material, raycaster, ray, position, morphPosition, morphTargetsRelative, uv, uv2, a, b, c) {\\n _vA.fromBufferAttribute(position, a);\\n _vB.fromBufferAttribute(position, b);\\n _vC.fromBufferAttribute(position, c);\\n const morphInfluences = object.morphTargetInfluences;\\n if (morphPosition && morphInfluences) {\\n _morphA.set(0, 0, 0);\\n _morphB.set(0, 0, 0);\\n _morphC.set(0, 0, 0);\\n for (let i = 0, il = morphPosition.length; i < il; i++) {\\n const influence = morphInfluences[i];\\n const morphAttribute = morphPosition[i];\\n if (influence === 0)\\n continue;\\n _tempA.fromBufferAttribute(morphAttribute, a);\\n _tempB.fromBufferAttribute(morphAttribute, b);\\n _tempC.fromBufferAttribute(morphAttribute, c);\\n if (morphTargetsRelative) {\\n _morphA.addScaledVector(_tempA, influence);\\n _morphB.addScaledVector(_tempB, influence);\\n _morphC.addScaledVector(_tempC, influence);\\n } else {\\n _morphA.addScaledVector(_tempA.sub(_vA), influence);\\n _morphB.addScaledVector(_tempB.sub(_vB), influence);\\n _morphC.addScaledVector(_tempC.sub(_vC), influence);\\n }\\n }\\n _vA.add(_morphA);\\n _vB.add(_morphB);\\n _vC.add(_morphC);\\n }\\n if (object.isSkinnedMesh) {\\n object.boneTransform(a, _vA);\\n object.boneTransform(b, _vB);\\n object.boneTransform(c, _vC);\\n }\\n const intersection = checkIntersection(object, material, raycaster, ray, _vA, _vB, _vC, _intersectionPoint);\\n if (intersection) {\\n if (uv) {\\n _uvA.fromBufferAttribute(uv, a);\\n _uvB.fromBufferAttribute(uv, b);\\n _uvC.fromBufferAttribute(uv, c);\\n intersection.uv = Triangle.getUV(_intersectionPoint, _vA, _vB, _vC, _uvA, _uvB, _uvC, new Vector2());\\n }\\n if (uv2) {\\n _uvA.fromBufferAttribute(uv2, a);\\n _uvB.fromBufferAttribute(uv2, b);\\n _uvC.fromBufferAttribute(uv2, c);\\n intersection.uv2 = Triangle.getUV(_intersectionPoint, _vA, _vB, _vC, _uvA, _uvB, _uvC, new Vector2());\\n }\\n const face = {\\n a,\\n b,\\n c,\\n normal: new Vector3(),\\n materialIndex: 0\\n };\\n Triangle.getNormal(_vA, _vB, _vC, face.normal);\\n intersection.face = face;\\n }\\n return intersection;\\n}\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/alphamap_fragment.glsl.js\\nvar alphamap_fragment_glsl_default = `\\n#ifdef USE_ALPHAMAP\\n\\n\\tdiffuseColor.a *= texture2D( alphaMap, vUv ).g;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/alphamap_pars_fragment.glsl.js\\nvar alphamap_pars_fragment_glsl_default = `\\n#ifdef USE_ALPHAMAP\\n\\n\\tuniform sampler2D alphaMap;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/alphatest_fragment.glsl.js\\nvar alphatest_fragment_glsl_default = `\\n#ifdef USE_ALPHATEST\\n\\n\\tif ( diffuseColor.a < alphaTest ) discard;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/alphatest_pars_fragment.glsl.js\\nvar alphatest_pars_fragment_glsl_default = `\\n#ifdef USE_ALPHATEST\\n\\tuniform float alphaTest;\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/aomap_fragment.glsl.js\\nvar aomap_fragment_glsl_default = `\\n#ifdef USE_AOMAP\\n\\n\\t// reads channel R, compatible with a combined OcclusionRoughnessMetallic (RGB) texture\\n\\tfloat ambientOcclusion = ( texture2D( aoMap, vUv2 ).r - 1.0 ) * aoMapIntensity + 1.0;\\n\\n\\treflectedLight.indirectDiffuse *= ambientOcclusion;\\n\\n\\t#if defined( USE_ENVMAP ) && defined( STANDARD )\\n\\n\\t\\tfloat dotNV = saturate( dot( geometry.normal, geometry.viewDir ) );\\n\\n\\t\\treflectedLight.indirectSpecular *= computeSpecularOcclusion( dotNV, ambientOcclusion, material.roughness );\\n\\n\\t#endif\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/aomap_pars_fragment.glsl.js\\nvar aomap_pars_fragment_glsl_default = `\\n#ifdef USE_AOMAP\\n\\n\\tuniform sampler2D aoMap;\\n\\tuniform float aoMapIntensity;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/begin_vertex.glsl.js\\nvar begin_vertex_glsl_default = `\\nvec3 transformed = vec3( position );\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/beginnormal_vertex.glsl.js\\nvar beginnormal_vertex_glsl_default = `\\nvec3 objectNormal = vec3( normal );\\n\\n#ifdef USE_TANGENT\\n\\n\\tvec3 objectTangent = vec3( tangent.xyz );\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/bsdfs.glsl.js\\nvar bsdfs_glsl_default = `\\n\\nvec3 BRDF_Lambert( const in vec3 diffuseColor ) {\\n\\n\\treturn RECIPROCAL_PI * diffuseColor;\\n\\n} // validated\\n\\nvec3 F_Schlick( const in vec3 f0, const in float f90, const in float dotVH ) {\\n\\n\\t// Original approximation by Christophe Schlick '94\\n\\t// float fresnel = pow( 1.0 - dotVH, 5.0 );\\n\\n\\t// Optimized variant (presented by Epic at SIGGRAPH '13)\\n\\t// https://cdn2.unrealengine.com/Resources/files/2013SiggraphPresentationsNotes-26915738.pdf\\n\\tfloat fresnel = exp2( ( - 5.55473 * dotVH - 6.98316 ) * dotVH );\\n\\n\\treturn f0 * ( 1.0 - fresnel ) + ( f90 * fresnel );\\n\\n} // validated\\n\\n// Moving Frostbite to Physically Based Rendering 3.0 - page 12, listing 2\\n// https://seblagarde.files.wordpress.com/2015/07/course_notes_moving_frostbite_to_pbr_v32.pdf\\nfloat V_GGX_SmithCorrelated( const in float alpha, const in float dotNL, const in float dotNV ) {\\n\\n\\tfloat a2 = pow2( alpha );\\n\\n\\tfloat gv = dotNL * sqrt( a2 + ( 1.0 - a2 ) * pow2( dotNV ) );\\n\\tfloat gl = dotNV * sqrt( a2 + ( 1.0 - a2 ) * pow2( dotNL ) );\\n\\n\\treturn 0.5 / max( gv + gl, EPSILON );\\n\\n}\\n\\n// Microfacet Models for Refraction through Rough Surfaces - equation (33)\\n// http://graphicrants.blogspot.com/2013/08/specular-brdf-reference.html\\n// alpha is \\\\\\\"roughness squared\\\\\\\" in Disney\\\\u2019s reparameterization\\nfloat D_GGX( const in float alpha, const in float dotNH ) {\\n\\n\\tfloat a2 = pow2( alpha );\\n\\n\\tfloat denom = pow2( dotNH ) * ( a2 - 1.0 ) + 1.0; // avoid alpha = 0 with dotNH = 1\\n\\n\\treturn RECIPROCAL_PI * a2 / pow2( denom );\\n\\n}\\n\\n// GGX Distribution, Schlick Fresnel, GGX_SmithCorrelated Visibility\\nvec3 BRDF_GGX( const in vec3 lightDir, const in vec3 viewDir, const in vec3 normal, const in vec3 f0, const in float f90, const in float roughness ) {\\n\\n\\tfloat alpha = pow2( roughness ); // UE4's roughness\\n\\n\\tvec3 halfDir = normalize( lightDir + viewDir );\\n\\n\\tfloat dotNL = saturate( dot( normal, lightDir ) );\\n\\tfloat dotNV = saturate( dot( normal, viewDir ) );\\n\\tfloat dotNH = saturate( dot( normal, halfDir ) );\\n\\tfloat dotVH = saturate( dot( viewDir, halfDir ) );\\n\\n\\tvec3 F = F_Schlick( f0, f90, dotVH );\\n\\n\\tfloat V = V_GGX_SmithCorrelated( alpha, dotNL, dotNV );\\n\\n\\tfloat D = D_GGX( alpha, dotNH );\\n\\n\\treturn F * ( V * D );\\n\\n}\\n\\n// Rect Area Light\\n\\n// Real-Time Polygonal-Light Shading with Linearly Transformed Cosines\\n// by Eric Heitz, Jonathan Dupuy, Stephen Hill and David Neubelt\\n// code: https://github.com/selfshadow/ltc_code/\\n\\nvec2 LTC_Uv( const in vec3 N, const in vec3 V, const in float roughness ) {\\n\\n\\tconst float LUT_SIZE = 64.0;\\n\\tconst float LUT_SCALE = ( LUT_SIZE - 1.0 ) / LUT_SIZE;\\n\\tconst float LUT_BIAS = 0.5 / LUT_SIZE;\\n\\n\\tfloat dotNV = saturate( dot( N, V ) );\\n\\n\\t// texture parameterized by sqrt( GGX alpha ) and sqrt( 1 - cos( theta ) )\\n\\tvec2 uv = vec2( roughness, sqrt( 1.0 - dotNV ) );\\n\\n\\tuv = uv * LUT_SCALE + LUT_BIAS;\\n\\n\\treturn uv;\\n\\n}\\n\\nfloat LTC_ClippedSphereFormFactor( const in vec3 f ) {\\n\\n\\t// Real-Time Area Lighting: a Journey from Research to Production (p.102)\\n\\t// An approximation of the form factor of a horizon-clipped rectangle.\\n\\n\\tfloat l = length( f );\\n\\n\\treturn max( ( l * l + f.z ) / ( l + 1.0 ), 0.0 );\\n\\n}\\n\\nvec3 LTC_EdgeVectorFormFactor( const in vec3 v1, const in vec3 v2 ) {\\n\\n\\tfloat x = dot( v1, v2 );\\n\\n\\tfloat y = abs( x );\\n\\n\\t// rational polynomial approximation to theta / sin( theta ) / 2PI\\n\\tfloat a = 0.8543985 + ( 0.4965155 + 0.0145206 * y ) * y;\\n\\tfloat b = 3.4175940 + ( 4.1616724 + y ) * y;\\n\\tfloat v = a / b;\\n\\n\\tfloat theta_sintheta = ( x > 0.0 ) ? v : 0.5 * inversesqrt( max( 1.0 - x * x, 1e-7 ) ) - v;\\n\\n\\treturn cross( v1, v2 ) * theta_sintheta;\\n\\n}\\n\\nvec3 LTC_Evaluate( const in vec3 N, const in vec3 V, const in vec3 P, const in mat3 mInv, const in vec3 rectCoords[ 4 ] ) {\\n\\n\\t// bail if point is on back side of plane of light\\n\\t// assumes ccw winding order of light vertices\\n\\tvec3 v1 = rectCoords[ 1 ] - rectCoords[ 0 ];\\n\\tvec3 v2 = rectCoords[ 3 ] - rectCoords[ 0 ];\\n\\tvec3 lightNormal = cross( v1, v2 );\\n\\n\\tif( dot( lightNormal, P - rectCoords[ 0 ] ) < 0.0 ) return vec3( 0.0 );\\n\\n\\t// construct orthonormal basis around N\\n\\tvec3 T1, T2;\\n\\tT1 = normalize( V - N * dot( V, N ) );\\n\\tT2 = - cross( N, T1 ); // negated from paper; possibly due to a different handedness of world coordinate system\\n\\n\\t// compute transform\\n\\tmat3 mat = mInv * transposeMat3( mat3( T1, T2, N ) );\\n\\n\\t// transform rect\\n\\tvec3 coords[ 4 ];\\n\\tcoords[ 0 ] = mat * ( rectCoords[ 0 ] - P );\\n\\tcoords[ 1 ] = mat * ( rectCoords[ 1 ] - P );\\n\\tcoords[ 2 ] = mat * ( rectCoords[ 2 ] - P );\\n\\tcoords[ 3 ] = mat * ( rectCoords[ 3 ] - P );\\n\\n\\t// project rect onto sphere\\n\\tcoords[ 0 ] = normalize( coords[ 0 ] );\\n\\tcoords[ 1 ] = normalize( coords[ 1 ] );\\n\\tcoords[ 2 ] = normalize( coords[ 2 ] );\\n\\tcoords[ 3 ] = normalize( coords[ 3 ] );\\n\\n\\t// calculate vector form factor\\n\\tvec3 vectorFormFactor = vec3( 0.0 );\\n\\tvectorFormFactor += LTC_EdgeVectorFormFactor( coords[ 0 ], coords[ 1 ] );\\n\\tvectorFormFactor += LTC_EdgeVectorFormFactor( coords[ 1 ], coords[ 2 ] );\\n\\tvectorFormFactor += LTC_EdgeVectorFormFactor( coords[ 2 ], coords[ 3 ] );\\n\\tvectorFormFactor += LTC_EdgeVectorFormFactor( coords[ 3 ], coords[ 0 ] );\\n\\n\\t// adjust for horizon clipping\\n\\tfloat result = LTC_ClippedSphereFormFactor( vectorFormFactor );\\n\\n/*\\n\\t// alternate method of adjusting for horizon clipping (see referece)\\n\\t// refactoring required\\n\\tfloat len = length( vectorFormFactor );\\n\\tfloat z = vectorFormFactor.z / len;\\n\\n\\tconst float LUT_SIZE = 64.0;\\n\\tconst float LUT_SCALE = ( LUT_SIZE - 1.0 ) / LUT_SIZE;\\n\\tconst float LUT_BIAS = 0.5 / LUT_SIZE;\\n\\n\\t// tabulated horizon-clipped sphere, apparently...\\n\\tvec2 uv = vec2( z * 0.5 + 0.5, len );\\n\\tuv = uv * LUT_SCALE + LUT_BIAS;\\n\\n\\tfloat scale = texture2D( ltc_2, uv ).w;\\n\\n\\tfloat result = len * scale;\\n*/\\n\\n\\treturn vec3( result );\\n\\n}\\n\\n// End Rect Area Light\\n\\n\\nfloat G_BlinnPhong_Implicit( /* const in float dotNL, const in float dotNV */ ) {\\n\\n\\t// geometry term is (n dot l)(n dot v) / 4(n dot l)(n dot v)\\n\\treturn 0.25;\\n\\n}\\n\\nfloat D_BlinnPhong( const in float shininess, const in float dotNH ) {\\n\\n\\treturn RECIPROCAL_PI * ( shininess * 0.5 + 1.0 ) * pow( dotNH, shininess );\\n\\n}\\n\\nvec3 BRDF_BlinnPhong( const in vec3 lightDir, const in vec3 viewDir, const in vec3 normal, const in vec3 specularColor, const in float shininess ) {\\n\\n\\tvec3 halfDir = normalize( lightDir + viewDir );\\n\\n\\tfloat dotNH = saturate( dot( normal, halfDir ) );\\n\\tfloat dotVH = saturate( dot( viewDir, halfDir ) );\\n\\n\\tvec3 F = F_Schlick( specularColor, 1.0, dotVH );\\n\\n\\tfloat G = G_BlinnPhong_Implicit( /* dotNL, dotNV */ );\\n\\n\\tfloat D = D_BlinnPhong( shininess, dotNH );\\n\\n\\treturn F * ( G * D );\\n\\n} // validated\\n\\n#if defined( USE_SHEEN )\\n\\n// https://github.com/google/filament/blob/master/shaders/src/brdf.fs\\nfloat D_Charlie( float roughness, float dotNH ) {\\n\\n\\tfloat alpha = pow2( roughness );\\n\\n\\t// Estevez and Kulla 2017, \\\\\\\"Production Friendly Microfacet Sheen BRDF\\\\\\\"\\n\\tfloat invAlpha = 1.0 / alpha;\\n\\tfloat cos2h = dotNH * dotNH;\\n\\tfloat sin2h = max( 1.0 - cos2h, 0.0078125 ); // 2^(-14/2), so sin2h^2 > 0 in fp16\\n\\n\\treturn ( 2.0 + invAlpha ) * pow( sin2h, invAlpha * 0.5 ) / ( 2.0 * PI );\\n\\n}\\n\\n// https://github.com/google/filament/blob/master/shaders/src/brdf.fs\\nfloat V_Neubelt( float dotNV, float dotNL ) {\\n\\n\\t// Neubelt and Pettineo 2013, \\\\\\\"Crafting a Next-gen Material Pipeline for The Order: 1886\\\\\\\"\\n\\treturn saturate( 1.0 / ( 4.0 * ( dotNL + dotNV - dotNL * dotNV ) ) );\\n\\n}\\n\\nvec3 BRDF_Sheen( const in vec3 lightDir, const in vec3 viewDir, const in vec3 normal, vec3 sheenTint, const in float sheenRoughness ) {\\n\\n\\tvec3 halfDir = normalize( lightDir + viewDir );\\n\\n\\tfloat dotNL = saturate( dot( normal, lightDir ) );\\n\\tfloat dotNV = saturate( dot( normal, viewDir ) );\\n\\tfloat dotNH = saturate( dot( normal, halfDir ) );\\n\\n\\tfloat D = D_Charlie( sheenRoughness, dotNH );\\n\\tfloat V = V_Neubelt( dotNV, dotNL );\\n\\n\\treturn sheenTint * ( D * V );\\n\\n}\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/bumpmap_pars_fragment.glsl.js\\nvar bumpmap_pars_fragment_glsl_default = `\\n#ifdef USE_BUMPMAP\\n\\n\\tuniform sampler2D bumpMap;\\n\\tuniform float bumpScale;\\n\\n\\t// Bump Mapping Unparametrized Surfaces on the GPU by Morten S. Mikkelsen\\n\\t// http://api.unrealengine.com/attachments/Engine/Rendering/LightingAndShadows/BumpMappingWithoutTangentSpace/mm_sfgrad_bump.pdf\\n\\n\\t// Evaluate the derivative of the height w.r.t. screen-space using forward differencing (listing 2)\\n\\n\\tvec2 dHdxy_fwd() {\\n\\n\\t\\tvec2 dSTdx = dFdx( vUv );\\n\\t\\tvec2 dSTdy = dFdy( vUv );\\n\\n\\t\\tfloat Hll = bumpScale * texture2D( bumpMap, vUv ).x;\\n\\t\\tfloat dBx = bumpScale * texture2D( bumpMap, vUv + dSTdx ).x - Hll;\\n\\t\\tfloat dBy = bumpScale * texture2D( bumpMap, vUv + dSTdy ).x - Hll;\\n\\n\\t\\treturn vec2( dBx, dBy );\\n\\n\\t}\\n\\n\\tvec3 perturbNormalArb( vec3 surf_pos, vec3 surf_norm, vec2 dHdxy, float faceDirection ) {\\n\\n\\t\\t// Workaround for Adreno 3XX dFd*( vec3 ) bug. See #9988\\n\\n\\t\\tvec3 vSigmaX = vec3( dFdx( surf_pos.x ), dFdx( surf_pos.y ), dFdx( surf_pos.z ) );\\n\\t\\tvec3 vSigmaY = vec3( dFdy( surf_pos.x ), dFdy( surf_pos.y ), dFdy( surf_pos.z ) );\\n\\t\\tvec3 vN = surf_norm;\\t\\t// normalized\\n\\n\\t\\tvec3 R1 = cross( vSigmaY, vN );\\n\\t\\tvec3 R2 = cross( vN, vSigmaX );\\n\\n\\t\\tfloat fDet = dot( vSigmaX, R1 ) * faceDirection;\\n\\n\\t\\tvec3 vGrad = sign( fDet ) * ( dHdxy.x * R1 + dHdxy.y * R2 );\\n\\t\\treturn normalize( abs( fDet ) * surf_norm - vGrad );\\n\\n\\t}\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/clipping_planes_fragment.glsl.js\\nvar clipping_planes_fragment_glsl_default = `\\n#if NUM_CLIPPING_PLANES > 0\\n\\n\\tvec4 plane;\\n\\n\\t#pragma unroll_loop_start\\n\\tfor ( int i = 0; i < UNION_CLIPPING_PLANES; i ++ ) {\\n\\n\\t\\tplane = clippingPlanes[ i ];\\n\\t\\tif ( dot( vClipPosition, plane.xyz ) > plane.w ) discard;\\n\\n\\t}\\n\\t#pragma unroll_loop_end\\n\\n\\t#if UNION_CLIPPING_PLANES < NUM_CLIPPING_PLANES\\n\\n\\t\\tbool clipped = true;\\n\\n\\t\\t#pragma unroll_loop_start\\n\\t\\tfor ( int i = UNION_CLIPPING_PLANES; i < NUM_CLIPPING_PLANES; i ++ ) {\\n\\n\\t\\t\\tplane = clippingPlanes[ i ];\\n\\t\\t\\tclipped = ( dot( vClipPosition, plane.xyz ) > plane.w ) && clipped;\\n\\n\\t\\t}\\n\\t\\t#pragma unroll_loop_end\\n\\n\\t\\tif ( clipped ) discard;\\n\\n\\t#endif\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/clipping_planes_pars_fragment.glsl.js\\nvar clipping_planes_pars_fragment_glsl_default = `\\n#if NUM_CLIPPING_PLANES > 0\\n\\n\\tvarying vec3 vClipPosition;\\n\\n\\tuniform vec4 clippingPlanes[ NUM_CLIPPING_PLANES ];\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/clipping_planes_pars_vertex.glsl.js\\nvar clipping_planes_pars_vertex_glsl_default = `\\n#if NUM_CLIPPING_PLANES > 0\\n\\n\\tvarying vec3 vClipPosition;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/clipping_planes_vertex.glsl.js\\nvar clipping_planes_vertex_glsl_default = `\\n#if NUM_CLIPPING_PLANES > 0\\n\\n\\tvClipPosition = - mvPosition.xyz;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/color_fragment.glsl.js\\nvar color_fragment_glsl_default = `\\n#if defined( USE_COLOR_ALPHA )\\n\\n\\tdiffuseColor *= vColor;\\n\\n#elif defined( USE_COLOR )\\n\\n\\tdiffuseColor.rgb *= vColor;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/color_pars_fragment.glsl.js\\nvar color_pars_fragment_glsl_default = `\\n#if defined( USE_COLOR_ALPHA )\\n\\n\\tvarying vec4 vColor;\\n\\n#elif defined( USE_COLOR )\\n\\n\\tvarying vec3 vColor;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/color_pars_vertex.glsl.js\\nvar color_pars_vertex_glsl_default = `\\n#if defined( USE_COLOR_ALPHA )\\n\\n\\tvarying vec4 vColor;\\n\\n#elif defined( USE_COLOR ) || defined( USE_INSTANCING_COLOR )\\n\\n\\tvarying vec3 vColor;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/color_vertex.glsl.js\\nvar color_vertex_glsl_default = `\\n#if defined( USE_COLOR_ALPHA )\\n\\n\\tvColor = vec4( 1.0 );\\n\\n#elif defined( USE_COLOR ) || defined( USE_INSTANCING_COLOR )\\n\\n\\tvColor = vec3( 1.0 );\\n\\n#endif\\n\\n#ifdef USE_COLOR\\n\\n\\tvColor *= color;\\n\\n#endif\\n\\n#ifdef USE_INSTANCING_COLOR\\n\\n\\tvColor.xyz *= instanceColor.xyz;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/common.glsl.js\\nvar common_glsl_default = `\\n#define PI 3.141592653589793\\n#define PI2 6.283185307179586\\n#define PI_HALF 1.5707963267948966\\n#define RECIPROCAL_PI 0.3183098861837907\\n#define RECIPROCAL_PI2 0.15915494309189535\\n#define EPSILON 1e-6\\n\\n#ifndef saturate\\n// may have defined saturate() already\\n#define saturate( a ) clamp( a, 0.0, 1.0 )\\n#endif\\n#define whiteComplement( a ) ( 1.0 - saturate( a ) )\\n\\nfloat pow2( const in float x ) { return x*x; }\\nfloat pow3( const in float x ) { return x*x*x; }\\nfloat pow4( const in float x ) { float x2 = x*x; return x2*x2; }\\nfloat max3( const in vec3 v ) { return max( max( v.x, v.y ), v.z ); }\\nfloat average( const in vec3 color ) { return dot( color, vec3( 0.3333 ) ); }\\n\\n// expects values in the range of [0,1]x[0,1], returns values in the [0,1] range.\\n// do not collapse into a single function per: http://byteblacksmith.com/improvements-to-the-canonical-one-liner-glsl-rand-for-opengl-es-2-0/\\nhighp float rand( const in vec2 uv ) {\\n\\n\\tconst highp float a = 12.9898, b = 78.233, c = 43758.5453;\\n\\thighp float dt = dot( uv.xy, vec2( a,b ) ), sn = mod( dt, PI );\\n\\n\\treturn fract( sin( sn ) * c );\\n\\n}\\n\\n#ifdef HIGH_PRECISION\\n\\tfloat precisionSafeLength( vec3 v ) { return length( v ); }\\n#else\\n\\tfloat precisionSafeLength( vec3 v ) {\\n\\t\\tfloat maxComponent = max3( abs( v ) );\\n\\t\\treturn length( v / maxComponent ) * maxComponent;\\n\\t}\\n#endif\\n\\nstruct IncidentLight {\\n\\tvec3 color;\\n\\tvec3 direction;\\n\\tbool visible;\\n};\\n\\nstruct ReflectedLight {\\n\\tvec3 directDiffuse;\\n\\tvec3 directSpecular;\\n\\tvec3 indirectDiffuse;\\n\\tvec3 indirectSpecular;\\n};\\n\\nstruct GeometricContext {\\n\\tvec3 position;\\n\\tvec3 normal;\\n\\tvec3 viewDir;\\n#ifdef USE_CLEARCOAT\\n\\tvec3 clearcoatNormal;\\n#endif\\n};\\n\\nvec3 transformDirection( in vec3 dir, in mat4 matrix ) {\\n\\n\\treturn normalize( ( matrix * vec4( dir, 0.0 ) ).xyz );\\n\\n}\\n\\nvec3 inverseTransformDirection( in vec3 dir, in mat4 matrix ) {\\n\\n\\t// dir can be either a direction vector or a normal vector\\n\\t// upper-left 3x3 of matrix is assumed to be orthogonal\\n\\n\\treturn normalize( ( vec4( dir, 0.0 ) * matrix ).xyz );\\n\\n}\\n\\nmat3 transposeMat3( const in mat3 m ) {\\n\\n\\tmat3 tmp;\\n\\n\\ttmp[ 0 ] = vec3( m[ 0 ].x, m[ 1 ].x, m[ 2 ].x );\\n\\ttmp[ 1 ] = vec3( m[ 0 ].y, m[ 1 ].y, m[ 2 ].y );\\n\\ttmp[ 2 ] = vec3( m[ 0 ].z, m[ 1 ].z, m[ 2 ].z );\\n\\n\\treturn tmp;\\n\\n}\\n\\n// https://en.wikipedia.org/wiki/Relative_luminance\\nfloat linearToRelativeLuminance( const in vec3 color ) {\\n\\n\\tvec3 weights = vec3( 0.2126, 0.7152, 0.0722 );\\n\\n\\treturn dot( weights, color.rgb );\\n\\n}\\n\\nbool isPerspectiveMatrix( mat4 m ) {\\n\\n\\treturn m[ 2 ][ 3 ] == - 1.0;\\n\\n}\\n\\nvec2 equirectUv( in vec3 dir ) {\\n\\n\\t// dir is assumed to be unit length\\n\\n\\tfloat u = atan( dir.z, dir.x ) * RECIPROCAL_PI2 + 0.5;\\n\\n\\tfloat v = asin( clamp( dir.y, - 1.0, 1.0 ) ) * RECIPROCAL_PI + 0.5;\\n\\n\\treturn vec2( u, v );\\n\\n}\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/cube_uv_reflection_fragment.glsl.js\\nvar cube_uv_reflection_fragment_glsl_default = `\\n#ifdef ENVMAP_TYPE_CUBE_UV\\n\\n\\t#define cubeUV_maxMipLevel 8.0\\n\\t#define cubeUV_minMipLevel 4.0\\n\\t#define cubeUV_maxTileSize 256.0\\n\\t#define cubeUV_minTileSize 16.0\\n\\n\\t// These shader functions convert between the UV coordinates of a single face of\\n\\t// a cubemap, the 0-5 integer index of a cube face, and the direction vector for\\n\\t// sampling a textureCube (not generally normalized ).\\n\\n\\tfloat getFace( vec3 direction ) {\\n\\n\\t\\tvec3 absDirection = abs( direction );\\n\\n\\t\\tfloat face = - 1.0;\\n\\n\\t\\tif ( absDirection.x > absDirection.z ) {\\n\\n\\t\\t\\tif ( absDirection.x > absDirection.y )\\n\\n\\t\\t\\t\\tface = direction.x > 0.0 ? 0.0 : 3.0;\\n\\n\\t\\t\\telse\\n\\n\\t\\t\\t\\tface = direction.y > 0.0 ? 1.0 : 4.0;\\n\\n\\t\\t} else {\\n\\n\\t\\t\\tif ( absDirection.z > absDirection.y )\\n\\n\\t\\t\\t\\tface = direction.z > 0.0 ? 2.0 : 5.0;\\n\\n\\t\\t\\telse\\n\\n\\t\\t\\t\\tface = direction.y > 0.0 ? 1.0 : 4.0;\\n\\n\\t\\t}\\n\\n\\t\\treturn face;\\n\\n\\t}\\n\\n\\t// RH coordinate system; PMREM face-indexing convention\\n\\tvec2 getUV( vec3 direction, float face ) {\\n\\n\\t\\tvec2 uv;\\n\\n\\t\\tif ( face == 0.0 ) {\\n\\n\\t\\t\\tuv = vec2( direction.z, direction.y ) / abs( direction.x ); // pos x\\n\\n\\t\\t} else if ( face == 1.0 ) {\\n\\n\\t\\t\\tuv = vec2( - direction.x, - direction.z ) / abs( direction.y ); // pos y\\n\\n\\t\\t} else if ( face == 2.0 ) {\\n\\n\\t\\t\\tuv = vec2( - direction.x, direction.y ) / abs( direction.z ); // pos z\\n\\n\\t\\t} else if ( face == 3.0 ) {\\n\\n\\t\\t\\tuv = vec2( - direction.z, direction.y ) / abs( direction.x ); // neg x\\n\\n\\t\\t} else if ( face == 4.0 ) {\\n\\n\\t\\t\\tuv = vec2( - direction.x, direction.z ) / abs( direction.y ); // neg y\\n\\n\\t\\t} else {\\n\\n\\t\\t\\tuv = vec2( direction.x, direction.y ) / abs( direction.z ); // neg z\\n\\n\\t\\t}\\n\\n\\t\\treturn 0.5 * ( uv + 1.0 );\\n\\n\\t}\\n\\n\\tvec3 bilinearCubeUV( sampler2D envMap, vec3 direction, float mipInt ) {\\n\\n\\t\\tfloat face = getFace( direction );\\n\\n\\t\\tfloat filterInt = max( cubeUV_minMipLevel - mipInt, 0.0 );\\n\\n\\t\\tmipInt = max( mipInt, cubeUV_minMipLevel );\\n\\n\\t\\tfloat faceSize = exp2( mipInt );\\n\\n\\t\\tfloat texelSize = 1.0 / ( 3.0 * cubeUV_maxTileSize );\\n\\n\\t\\tvec2 uv = getUV( direction, face ) * ( faceSize - 1.0 );\\n\\n\\t\\tvec2 f = fract( uv );\\n\\n\\t\\tuv += 0.5 - f;\\n\\n\\t\\tif ( face > 2.0 ) {\\n\\n\\t\\t\\tuv.y += faceSize;\\n\\n\\t\\t\\tface -= 3.0;\\n\\n\\t\\t}\\n\\n\\t\\tuv.x += face * faceSize;\\n\\n\\t\\tif ( mipInt < cubeUV_maxMipLevel ) {\\n\\n\\t\\t\\tuv.y += 2.0 * cubeUV_maxTileSize;\\n\\n\\t\\t}\\n\\n\\t\\tuv.y += filterInt * 2.0 * cubeUV_minTileSize;\\n\\n\\t\\tuv.x += 3.0 * max( 0.0, cubeUV_maxTileSize - 2.0 * faceSize );\\n\\n\\t\\tuv *= texelSize;\\n\\n\\t\\tvec3 tl = envMapTexelToLinear( texture2D( envMap, uv ) ).rgb;\\n\\n\\t\\tuv.x += texelSize;\\n\\n\\t\\tvec3 tr = envMapTexelToLinear( texture2D( envMap, uv ) ).rgb;\\n\\n\\t\\tuv.y += texelSize;\\n\\n\\t\\tvec3 br = envMapTexelToLinear( texture2D( envMap, uv ) ).rgb;\\n\\n\\t\\tuv.x -= texelSize;\\n\\n\\t\\tvec3 bl = envMapTexelToLinear( texture2D( envMap, uv ) ).rgb;\\n\\n\\t\\tvec3 tm = mix( tl, tr, f.x );\\n\\n\\t\\tvec3 bm = mix( bl, br, f.x );\\n\\n\\t\\treturn mix( tm, bm, f.y );\\n\\n\\t}\\n\\n\\t// These defines must match with PMREMGenerator\\n\\n\\t#define r0 1.0\\n\\t#define v0 0.339\\n\\t#define m0 - 2.0\\n\\t#define r1 0.8\\n\\t#define v1 0.276\\n\\t#define m1 - 1.0\\n\\t#define r4 0.4\\n\\t#define v4 0.046\\n\\t#define m4 2.0\\n\\t#define r5 0.305\\n\\t#define v5 0.016\\n\\t#define m5 3.0\\n\\t#define r6 0.21\\n\\t#define v6 0.0038\\n\\t#define m6 4.0\\n\\n\\tfloat roughnessToMip( float roughness ) {\\n\\n\\t\\tfloat mip = 0.0;\\n\\n\\t\\tif ( roughness >= r1 ) {\\n\\n\\t\\t\\tmip = ( r0 - roughness ) * ( m1 - m0 ) / ( r0 - r1 ) + m0;\\n\\n\\t\\t} else if ( roughness >= r4 ) {\\n\\n\\t\\t\\tmip = ( r1 - roughness ) * ( m4 - m1 ) / ( r1 - r4 ) + m1;\\n\\n\\t\\t} else if ( roughness >= r5 ) {\\n\\n\\t\\t\\tmip = ( r4 - roughness ) * ( m5 - m4 ) / ( r4 - r5 ) + m4;\\n\\n\\t\\t} else if ( roughness >= r6 ) {\\n\\n\\t\\t\\tmip = ( r5 - roughness ) * ( m6 - m5 ) / ( r5 - r6 ) + m5;\\n\\n\\t\\t} else {\\n\\n\\t\\t\\tmip = - 2.0 * log2( 1.16 * roughness ); // 1.16 = 1.79^0.25\\n\\t\\t}\\n\\n\\t\\treturn mip;\\n\\n\\t}\\n\\n\\tvec4 textureCubeUV( sampler2D envMap, vec3 sampleDir, float roughness ) {\\n\\n\\t\\tfloat mip = clamp( roughnessToMip( roughness ), m0, cubeUV_maxMipLevel );\\n\\n\\t\\tfloat mipF = fract( mip );\\n\\n\\t\\tfloat mipInt = floor( mip );\\n\\n\\t\\tvec3 color0 = bilinearCubeUV( envMap, sampleDir, mipInt );\\n\\n\\t\\tif ( mipF == 0.0 ) {\\n\\n\\t\\t\\treturn vec4( color0, 1.0 );\\n\\n\\t\\t} else {\\n\\n\\t\\t\\tvec3 color1 = bilinearCubeUV( envMap, sampleDir, mipInt + 1.0 );\\n\\n\\t\\t\\treturn vec4( mix( color0, color1, mipF ), 1.0 );\\n\\n\\t\\t}\\n\\n\\t}\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/defaultnormal_vertex.glsl.js\\nvar defaultnormal_vertex_glsl_default = `\\nvec3 transformedNormal = objectNormal;\\n\\n#ifdef USE_INSTANCING\\n\\n\\t// this is in lieu of a per-instance normal-matrix\\n\\t// shear transforms in the instance matrix are not supported\\n\\n\\tmat3 m = mat3( instanceMatrix );\\n\\n\\ttransformedNormal /= vec3( dot( m[ 0 ], m[ 0 ] ), dot( m[ 1 ], m[ 1 ] ), dot( m[ 2 ], m[ 2 ] ) );\\n\\n\\ttransformedNormal = m * transformedNormal;\\n\\n#endif\\n\\ntransformedNormal = normalMatrix * transformedNormal;\\n\\n#ifdef FLIP_SIDED\\n\\n\\ttransformedNormal = - transformedNormal;\\n\\n#endif\\n\\n#ifdef USE_TANGENT\\n\\n\\tvec3 transformedTangent = ( modelViewMatrix * vec4( objectTangent, 0.0 ) ).xyz;\\n\\n\\t#ifdef FLIP_SIDED\\n\\n\\t\\ttransformedTangent = - transformedTangent;\\n\\n\\t#endif\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/displacementmap_pars_vertex.glsl.js\\nvar displacementmap_pars_vertex_glsl_default = `\\n#ifdef USE_DISPLACEMENTMAP\\n\\n\\tuniform sampler2D displacementMap;\\n\\tuniform float displacementScale;\\n\\tuniform float displacementBias;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/displacementmap_vertex.glsl.js\\nvar displacementmap_vertex_glsl_default = `\\n#ifdef USE_DISPLACEMENTMAP\\n\\n\\ttransformed += normalize( objectNormal ) * ( texture2D( displacementMap, vUv ).x * displacementScale + displacementBias );\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/emissivemap_fragment.glsl.js\\nvar emissivemap_fragment_glsl_default = `\\n#ifdef USE_EMISSIVEMAP\\n\\n\\tvec4 emissiveColor = texture2D( emissiveMap, vUv );\\n\\n\\temissiveColor.rgb = emissiveMapTexelToLinear( emissiveColor ).rgb;\\n\\n\\ttotalEmissiveRadiance *= emissiveColor.rgb;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/emissivemap_pars_fragment.glsl.js\\nvar emissivemap_pars_fragment_glsl_default = `\\n#ifdef USE_EMISSIVEMAP\\n\\n\\tuniform sampler2D emissiveMap;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/encodings_fragment.glsl.js\\nvar encodings_fragment_glsl_default = `\\ngl_FragColor = linearToOutputTexel( gl_FragColor );\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/encodings_pars_fragment.glsl.js\\nvar encodings_pars_fragment_glsl_default = `\\n// For a discussion of what this is, please read this: http://lousodrome.net/blog/light/2013/05/26/gamma-correct-and-hdr-rendering-in-a-32-bits-buffer/\\n\\nvec4 LinearToLinear( in vec4 value ) {\\n\\treturn value;\\n}\\n\\nvec4 GammaToLinear( in vec4 value, in float gammaFactor ) {\\n\\treturn vec4( pow( value.rgb, vec3( gammaFactor ) ), value.a );\\n}\\n\\nvec4 LinearToGamma( in vec4 value, in float gammaFactor ) {\\n\\treturn vec4( pow( value.rgb, vec3( 1.0 / gammaFactor ) ), value.a );\\n}\\n\\nvec4 sRGBToLinear( in vec4 value ) {\\n\\treturn vec4( mix( pow( value.rgb * 0.9478672986 + vec3( 0.0521327014 ), vec3( 2.4 ) ), value.rgb * 0.0773993808, vec3( lessThanEqual( value.rgb, vec3( 0.04045 ) ) ) ), value.a );\\n}\\n\\nvec4 LinearTosRGB( in vec4 value ) {\\n\\treturn vec4( mix( pow( value.rgb, vec3( 0.41666 ) ) * 1.055 - vec3( 0.055 ), value.rgb * 12.92, vec3( lessThanEqual( value.rgb, vec3( 0.0031308 ) ) ) ), value.a );\\n}\\n\\nvec4 RGBEToLinear( in vec4 value ) {\\n\\treturn vec4( value.rgb * exp2( value.a * 255.0 - 128.0 ), 1.0 );\\n}\\n\\nvec4 LinearToRGBE( in vec4 value ) {\\n\\tfloat maxComponent = max( max( value.r, value.g ), value.b );\\n\\tfloat fExp = clamp( ceil( log2( maxComponent ) ), -128.0, 127.0 );\\n\\treturn vec4( value.rgb / exp2( fExp ), ( fExp + 128.0 ) / 255.0 );\\n\\t// return vec4( value.brg, ( 3.0 + 128.0 ) / 256.0 );\\n}\\n\\n// reference: http://iwasbeingirony.blogspot.ca/2010/06/difference-between-rgbm-and-rgbd.html\\nvec4 RGBMToLinear( in vec4 value, in float maxRange ) {\\n\\treturn vec4( value.rgb * value.a * maxRange, 1.0 );\\n}\\n\\nvec4 LinearToRGBM( in vec4 value, in float maxRange ) {\\n\\tfloat maxRGB = max( value.r, max( value.g, value.b ) );\\n\\tfloat M = clamp( maxRGB / maxRange, 0.0, 1.0 );\\n\\tM = ceil( M * 255.0 ) / 255.0;\\n\\treturn vec4( value.rgb / ( M * maxRange ), M );\\n}\\n\\n// reference: http://iwasbeingirony.blogspot.ca/2010/06/difference-between-rgbm-and-rgbd.html\\nvec4 RGBDToLinear( in vec4 value, in float maxRange ) {\\n\\treturn vec4( value.rgb * ( ( maxRange / 255.0 ) / value.a ), 1.0 );\\n}\\n\\nvec4 LinearToRGBD( in vec4 value, in float maxRange ) {\\n\\tfloat maxRGB = max( value.r, max( value.g, value.b ) );\\n\\tfloat D = max( maxRange / maxRGB, 1.0 );\\n\\t// NOTE: The implementation with min causes the shader to not compile on\\n\\t// a common Alcatel A502DL in Chrome 78/Android 8.1. Some research suggests \\n\\t// that the chipset is Mediatek MT6739 w/ IMG PowerVR GE8100 GPU.\\n\\t// D = min( floor( D ) / 255.0, 1.0 );\\n\\tD = clamp( floor( D ) / 255.0, 0.0, 1.0 );\\n\\treturn vec4( value.rgb * ( D * ( 255.0 / maxRange ) ), D );\\n}\\n\\n// LogLuv reference: http://graphicrants.blogspot.ca/2009/04/rgbm-color-encoding.html\\n\\n// M matrix, for encoding\\nconst mat3 cLogLuvM = mat3( 0.2209, 0.3390, 0.4184, 0.1138, 0.6780, 0.7319, 0.0102, 0.1130, 0.2969 );\\nvec4 LinearToLogLuv( in vec4 value ) {\\n\\tvec3 Xp_Y_XYZp = cLogLuvM * value.rgb;\\n\\tXp_Y_XYZp = max( Xp_Y_XYZp, vec3( 1e-6, 1e-6, 1e-6 ) );\\n\\tvec4 vResult;\\n\\tvResult.xy = Xp_Y_XYZp.xy / Xp_Y_XYZp.z;\\n\\tfloat Le = 2.0 * log2(Xp_Y_XYZp.y) + 127.0;\\n\\tvResult.w = fract( Le );\\n\\tvResult.z = ( Le - ( floor( vResult.w * 255.0 ) ) / 255.0 ) / 255.0;\\n\\treturn vResult;\\n}\\n\\n// Inverse M matrix, for decoding\\nconst mat3 cLogLuvInverseM = mat3( 6.0014, -2.7008, -1.7996, -1.3320, 3.1029, -5.7721, 0.3008, -1.0882, 5.6268 );\\nvec4 LogLuvToLinear( in vec4 value ) {\\n\\tfloat Le = value.z * 255.0 + value.w;\\n\\tvec3 Xp_Y_XYZp;\\n\\tXp_Y_XYZp.y = exp2( ( Le - 127.0 ) / 2.0 );\\n\\tXp_Y_XYZp.z = Xp_Y_XYZp.y / value.y;\\n\\tXp_Y_XYZp.x = value.x * Xp_Y_XYZp.z;\\n\\tvec3 vRGB = cLogLuvInverseM * Xp_Y_XYZp.rgb;\\n\\treturn vec4( max( vRGB, 0.0 ), 1.0 );\\n}\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/envmap_fragment.glsl.js\\nvar envmap_fragment_glsl_default = `\\n#ifdef USE_ENVMAP\\n\\n\\t#ifdef ENV_WORLDPOS\\n\\n\\t\\tvec3 cameraToFrag;\\n\\n\\t\\tif ( isOrthographic ) {\\n\\n\\t\\t\\tcameraToFrag = normalize( vec3( - viewMatrix[ 0 ][ 2 ], - viewMatrix[ 1 ][ 2 ], - viewMatrix[ 2 ][ 2 ] ) );\\n\\n\\t\\t} else {\\n\\n\\t\\t\\tcameraToFrag = normalize( vWorldPosition - cameraPosition );\\n\\n\\t\\t}\\n\\n\\t\\t// Transforming Normal Vectors with the Inverse Transformation\\n\\t\\tvec3 worldNormal = inverseTransformDirection( normal, viewMatrix );\\n\\n\\t\\t#ifdef ENVMAP_MODE_REFLECTION\\n\\n\\t\\t\\tvec3 reflectVec = reflect( cameraToFrag, worldNormal );\\n\\n\\t\\t#else\\n\\n\\t\\t\\tvec3 reflectVec = refract( cameraToFrag, worldNormal, refractionRatio );\\n\\n\\t\\t#endif\\n\\n\\t#else\\n\\n\\t\\tvec3 reflectVec = vReflect;\\n\\n\\t#endif\\n\\n\\t#ifdef ENVMAP_TYPE_CUBE\\n\\n\\t\\tvec4 envColor = textureCube( envMap, vec3( flipEnvMap * reflectVec.x, reflectVec.yz ) );\\n\\n\\t\\tenvColor = envMapTexelToLinear( envColor );\\n\\n\\t#elif defined( ENVMAP_TYPE_CUBE_UV )\\n\\n\\t\\tvec4 envColor = textureCubeUV( envMap, reflectVec, 0.0 );\\n\\n\\t#else\\n\\n\\t\\tvec4 envColor = vec4( 0.0 );\\n\\n\\t#endif\\n\\n\\t#ifdef ENVMAP_BLENDING_MULTIPLY\\n\\n\\t\\toutgoingLight = mix( outgoingLight, outgoingLight * envColor.xyz, specularStrength * reflectivity );\\n\\n\\t#elif defined( ENVMAP_BLENDING_MIX )\\n\\n\\t\\toutgoingLight = mix( outgoingLight, envColor.xyz, specularStrength * reflectivity );\\n\\n\\t#elif defined( ENVMAP_BLENDING_ADD )\\n\\n\\t\\toutgoingLight += envColor.xyz * specularStrength * reflectivity;\\n\\n\\t#endif\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/envmap_common_pars_fragment.glsl.js\\nvar envmap_common_pars_fragment_glsl_default = `\\n#ifdef USE_ENVMAP\\n\\n\\tuniform float envMapIntensity;\\n\\tuniform float flipEnvMap;\\n\\tuniform int maxMipLevel;\\n\\n\\t#ifdef ENVMAP_TYPE_CUBE\\n\\t\\tuniform samplerCube envMap;\\n\\t#else\\n\\t\\tuniform sampler2D envMap;\\n\\t#endif\\n\\t\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/envmap_pars_fragment.glsl.js\\nvar envmap_pars_fragment_glsl_default = `\\n#ifdef USE_ENVMAP\\n\\n\\tuniform float reflectivity;\\n\\n\\t#if defined( USE_BUMPMAP ) || defined( USE_NORMALMAP ) || defined( PHONG )\\n\\n\\t\\t#define ENV_WORLDPOS\\n\\n\\t#endif\\n\\n\\t#ifdef ENV_WORLDPOS\\n\\n\\t\\tvarying vec3 vWorldPosition;\\n\\t\\tuniform float refractionRatio;\\n\\t#else\\n\\t\\tvarying vec3 vReflect;\\n\\t#endif\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/envmap_pars_vertex.glsl.js\\nvar envmap_pars_vertex_glsl_default = `\\n#ifdef USE_ENVMAP\\n\\n\\t#if defined( USE_BUMPMAP ) || defined( USE_NORMALMAP ) ||defined( PHONG )\\n\\n\\t\\t#define ENV_WORLDPOS\\n\\n\\t#endif\\n\\n\\t#ifdef ENV_WORLDPOS\\n\\t\\t\\n\\t\\tvarying vec3 vWorldPosition;\\n\\n\\t#else\\n\\n\\t\\tvarying vec3 vReflect;\\n\\t\\tuniform float refractionRatio;\\n\\n\\t#endif\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/envmap_vertex.glsl.js\\nvar envmap_vertex_glsl_default = `\\n#ifdef USE_ENVMAP\\n\\n\\t#ifdef ENV_WORLDPOS\\n\\n\\t\\tvWorldPosition = worldPosition.xyz;\\n\\n\\t#else\\n\\n\\t\\tvec3 cameraToVertex;\\n\\n\\t\\tif ( isOrthographic ) {\\n\\n\\t\\t\\tcameraToVertex = normalize( vec3( - viewMatrix[ 0 ][ 2 ], - viewMatrix[ 1 ][ 2 ], - viewMatrix[ 2 ][ 2 ] ) );\\n\\n\\t\\t} else {\\n\\n\\t\\t\\tcameraToVertex = normalize( worldPosition.xyz - cameraPosition );\\n\\n\\t\\t}\\n\\n\\t\\tvec3 worldNormal = inverseTransformDirection( transformedNormal, viewMatrix );\\n\\n\\t\\t#ifdef ENVMAP_MODE_REFLECTION\\n\\n\\t\\t\\tvReflect = reflect( cameraToVertex, worldNormal );\\n\\n\\t\\t#else\\n\\n\\t\\t\\tvReflect = refract( cameraToVertex, worldNormal, refractionRatio );\\n\\n\\t\\t#endif\\n\\n\\t#endif\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/fog_vertex.glsl.js\\nvar fog_vertex_glsl_default = `\\n#ifdef USE_FOG\\n\\n\\tvFogDepth = - mvPosition.z;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/fog_pars_vertex.glsl.js\\nvar fog_pars_vertex_glsl_default = `\\n#ifdef USE_FOG\\n\\n\\tvarying float vFogDepth;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/fog_fragment.glsl.js\\nvar fog_fragment_glsl_default = `\\n#ifdef USE_FOG\\n\\n\\t#ifdef FOG_EXP2\\n\\n\\t\\tfloat fogFactor = 1.0 - exp( - fogDensity * fogDensity * vFogDepth * vFogDepth );\\n\\n\\t#else\\n\\n\\t\\tfloat fogFactor = smoothstep( fogNear, fogFar, vFogDepth );\\n\\n\\t#endif\\n\\n\\tgl_FragColor.rgb = mix( gl_FragColor.rgb, fogColor, fogFactor );\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/fog_pars_fragment.glsl.js\\nvar fog_pars_fragment_glsl_default = `\\n#ifdef USE_FOG\\n\\n\\tuniform vec3 fogColor;\\n\\tvarying float vFogDepth;\\n\\n\\t#ifdef FOG_EXP2\\n\\n\\t\\tuniform float fogDensity;\\n\\n\\t#else\\n\\n\\t\\tuniform float fogNear;\\n\\t\\tuniform float fogFar;\\n\\n\\t#endif\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/gradientmap_pars_fragment.glsl.js\\nvar gradientmap_pars_fragment_glsl_default = `\\n\\n#ifdef USE_GRADIENTMAP\\n\\n\\tuniform sampler2D gradientMap;\\n\\n#endif\\n\\nvec3 getGradientIrradiance( vec3 normal, vec3 lightDirection ) {\\n\\n\\t// dotNL will be from -1.0 to 1.0\\n\\tfloat dotNL = dot( normal, lightDirection );\\n\\tvec2 coord = vec2( dotNL * 0.5 + 0.5, 0.0 );\\n\\n\\t#ifdef USE_GRADIENTMAP\\n\\n\\t\\treturn texture2D( gradientMap, coord ).rgb;\\n\\n\\t#else\\n\\n\\t\\treturn ( coord.x < 0.7 ) ? vec3( 0.7 ) : vec3( 1.0 );\\n\\n\\t#endif\\n\\n}\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/lightmap_fragment.glsl.js\\nvar lightmap_fragment_glsl_default = `\\n#ifdef USE_LIGHTMAP\\n\\n\\tvec4 lightMapTexel = texture2D( lightMap, vUv2 );\\n\\tvec3 lightMapIrradiance = lightMapTexelToLinear( lightMapTexel ).rgb * lightMapIntensity;\\n\\n\\t#ifndef PHYSICALLY_CORRECT_LIGHTS\\n\\n\\t\\tlightMapIrradiance *= PI;\\n\\n\\t#endif\\n\\n\\treflectedLight.indirectDiffuse += lightMapIrradiance;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/lightmap_pars_fragment.glsl.js\\nvar lightmap_pars_fragment_glsl_default = `\\n#ifdef USE_LIGHTMAP\\n\\n\\tuniform sampler2D lightMap;\\n\\tuniform float lightMapIntensity;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/lights_lambert_vertex.glsl.js\\nvar lights_lambert_vertex_glsl_default = `\\nvec3 diffuse = vec3( 1.0 );\\n\\nGeometricContext geometry;\\ngeometry.position = mvPosition.xyz;\\ngeometry.normal = normalize( transformedNormal );\\ngeometry.viewDir = ( isOrthographic ) ? vec3( 0, 0, 1 ) : normalize( -mvPosition.xyz );\\n\\nGeometricContext backGeometry;\\nbackGeometry.position = geometry.position;\\nbackGeometry.normal = -geometry.normal;\\nbackGeometry.viewDir = geometry.viewDir;\\n\\nvLightFront = vec3( 0.0 );\\nvIndirectFront = vec3( 0.0 );\\n#ifdef DOUBLE_SIDED\\n\\tvLightBack = vec3( 0.0 );\\n\\tvIndirectBack = vec3( 0.0 );\\n#endif\\n\\nIncidentLight directLight;\\nfloat dotNL;\\nvec3 directLightColor_Diffuse;\\n\\nvIndirectFront += getAmbientLightIrradiance( ambientLightColor );\\n\\nvIndirectFront += getLightProbeIrradiance( lightProbe, geometry.normal );\\n\\n#ifdef DOUBLE_SIDED\\n\\n\\tvIndirectBack += getAmbientLightIrradiance( ambientLightColor );\\n\\n\\tvIndirectBack += getLightProbeIrradiance( lightProbe, backGeometry.normal );\\n\\n#endif\\n\\n#if NUM_POINT_LIGHTS > 0\\n\\n\\t#pragma unroll_loop_start\\n\\tfor ( int i = 0; i < NUM_POINT_LIGHTS; i ++ ) {\\n\\n\\t\\tgetPointLightInfo( pointLights[ i ], geometry, directLight );\\n\\n\\t\\tdotNL = dot( geometry.normal, directLight.direction );\\n\\t\\tdirectLightColor_Diffuse = directLight.color;\\n\\n\\t\\tvLightFront += saturate( dotNL ) * directLightColor_Diffuse;\\n\\n\\t\\t#ifdef DOUBLE_SIDED\\n\\n\\t\\t\\tvLightBack += saturate( - dotNL ) * directLightColor_Diffuse;\\n\\n\\t\\t#endif\\n\\n\\t}\\n\\t#pragma unroll_loop_end\\n\\n#endif\\n\\n#if NUM_SPOT_LIGHTS > 0\\n\\n\\t#pragma unroll_loop_start\\n\\tfor ( int i = 0; i < NUM_SPOT_LIGHTS; i ++ ) {\\n\\n\\t\\tgetSpotLightInfo( spotLights[ i ], geometry, directLight );\\n\\n\\t\\tdotNL = dot( geometry.normal, directLight.direction );\\n\\t\\tdirectLightColor_Diffuse = directLight.color;\\n\\n\\t\\tvLightFront += saturate( dotNL ) * directLightColor_Diffuse;\\n\\n\\t\\t#ifdef DOUBLE_SIDED\\n\\n\\t\\t\\tvLightBack += saturate( - dotNL ) * directLightColor_Diffuse;\\n\\n\\t\\t#endif\\n\\t}\\n\\t#pragma unroll_loop_end\\n\\n#endif\\n\\n#if NUM_DIR_LIGHTS > 0\\n\\n\\t#pragma unroll_loop_start\\n\\tfor ( int i = 0; i < NUM_DIR_LIGHTS; i ++ ) {\\n\\n\\t\\tgetDirectionalLightInfo( directionalLights[ i ], geometry, directLight );\\n\\n\\t\\tdotNL = dot( geometry.normal, directLight.direction );\\n\\t\\tdirectLightColor_Diffuse = directLight.color;\\n\\n\\t\\tvLightFront += saturate( dotNL ) * directLightColor_Diffuse;\\n\\n\\t\\t#ifdef DOUBLE_SIDED\\n\\n\\t\\t\\tvLightBack += saturate( - dotNL ) * directLightColor_Diffuse;\\n\\n\\t\\t#endif\\n\\n\\t}\\n\\t#pragma unroll_loop_end\\n\\n#endif\\n\\n#if NUM_HEMI_LIGHTS > 0\\n\\n\\t#pragma unroll_loop_start\\n\\tfor ( int i = 0; i < NUM_HEMI_LIGHTS; i ++ ) {\\n\\n\\t\\tvIndirectFront += getHemisphereLightIrradiance( hemisphereLights[ i ], geometry.normal );\\n\\n\\t\\t#ifdef DOUBLE_SIDED\\n\\n\\t\\t\\tvIndirectBack += getHemisphereLightIrradiance( hemisphereLights[ i ], backGeometry.normal );\\n\\n\\t\\t#endif\\n\\n\\t}\\n\\t#pragma unroll_loop_end\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/lights_pars_begin.glsl.js\\nvar lights_pars_begin_glsl_default = `\\nuniform bool receiveShadow;\\nuniform vec3 ambientLightColor;\\nuniform vec3 lightProbe[ 9 ];\\n\\n// get the irradiance (radiance convolved with cosine lobe) at the point 'normal' on the unit sphere\\n// source: https://graphics.stanford.edu/papers/envmap/envmap.pdf\\nvec3 shGetIrradianceAt( in vec3 normal, in vec3 shCoefficients[ 9 ] ) {\\n\\n\\t// normal is assumed to have unit length\\n\\n\\tfloat x = normal.x, y = normal.y, z = normal.z;\\n\\n\\t// band 0\\n\\tvec3 result = shCoefficients[ 0 ] * 0.886227;\\n\\n\\t// band 1\\n\\tresult += shCoefficients[ 1 ] * 2.0 * 0.511664 * y;\\n\\tresult += shCoefficients[ 2 ] * 2.0 * 0.511664 * z;\\n\\tresult += shCoefficients[ 3 ] * 2.0 * 0.511664 * x;\\n\\n\\t// band 2\\n\\tresult += shCoefficients[ 4 ] * 2.0 * 0.429043 * x * y;\\n\\tresult += shCoefficients[ 5 ] * 2.0 * 0.429043 * y * z;\\n\\tresult += shCoefficients[ 6 ] * ( 0.743125 * z * z - 0.247708 );\\n\\tresult += shCoefficients[ 7 ] * 2.0 * 0.429043 * x * z;\\n\\tresult += shCoefficients[ 8 ] * 0.429043 * ( x * x - y * y );\\n\\n\\treturn result;\\n\\n}\\n\\nvec3 getLightProbeIrradiance( const in vec3 lightProbe[ 9 ], const in vec3 normal ) {\\n\\n\\tvec3 worldNormal = inverseTransformDirection( normal, viewMatrix );\\n\\n\\tvec3 irradiance = shGetIrradianceAt( worldNormal, lightProbe );\\n\\n\\treturn irradiance;\\n\\n}\\n\\nvec3 getAmbientLightIrradiance( const in vec3 ambientLightColor ) {\\n\\n\\tvec3 irradiance = ambientLightColor;\\n\\n\\treturn irradiance;\\n\\n}\\n\\nfloat getDistanceAttenuation( const in float lightDistance, const in float cutoffDistance, const in float decayExponent ) {\\n\\n\\t#if defined ( PHYSICALLY_CORRECT_LIGHTS )\\n\\n\\t\\t// based upon Frostbite 3 Moving to Physically-based Rendering\\n\\t\\t// page 32, equation 26: E[window1]\\n\\t\\t// https://seblagarde.files.wordpress.com/2015/07/course_notes_moving_frostbite_to_pbr_v32.pdf\\n\\t\\tfloat distanceFalloff = 1.0 / max( pow( lightDistance, decayExponent ), 0.01 );\\n\\n\\t\\tif ( cutoffDistance > 0.0 ) {\\n\\n\\t\\t\\tdistanceFalloff *= pow2( saturate( 1.0 - pow4( lightDistance / cutoffDistance ) ) );\\n\\n\\t\\t}\\n\\n\\t\\treturn distanceFalloff;\\n\\n\\t#else\\n\\n\\t\\tif ( cutoffDistance > 0.0 && decayExponent > 0.0 ) {\\n\\n\\t\\t\\treturn pow( saturate( - lightDistance / cutoffDistance + 1.0 ), decayExponent );\\n\\n\\t\\t}\\n\\n\\t\\treturn 1.0;\\n\\n\\t#endif\\n\\n}\\n\\nfloat getSpotAttenuation( const in float coneCosine, const in float penumbraCosine, const in float angleCosine ) {\\n\\n\\treturn smoothstep( coneCosine, penumbraCosine, angleCosine );\\n\\n}\\n\\n#if NUM_DIR_LIGHTS > 0\\n\\n\\tstruct DirectionalLight {\\n\\t\\tvec3 direction;\\n\\t\\tvec3 color;\\n\\t};\\n\\n\\tuniform DirectionalLight directionalLights[ NUM_DIR_LIGHTS ];\\n\\n\\tvoid getDirectionalLightInfo( const in DirectionalLight directionalLight, const in GeometricContext geometry, out IncidentLight light ) {\\n\\n\\t\\tlight.color = directionalLight.color;\\n\\t\\tlight.direction = directionalLight.direction;\\n\\t\\tlight.visible = true;\\n\\n\\t}\\n\\n#endif\\n\\n\\n#if NUM_POINT_LIGHTS > 0\\n\\n\\tstruct PointLight {\\n\\t\\tvec3 position;\\n\\t\\tvec3 color;\\n\\t\\tfloat distance;\\n\\t\\tfloat decay;\\n\\t};\\n\\n\\tuniform PointLight pointLights[ NUM_POINT_LIGHTS ];\\n\\n\\t// light is an out parameter as having it as a return value caused compiler errors on some devices\\n\\tvoid getPointLightInfo( const in PointLight pointLight, const in GeometricContext geometry, out IncidentLight light ) {\\n\\n\\t\\tvec3 lVector = pointLight.position - geometry.position;\\n\\n\\t\\tlight.direction = normalize( lVector );\\n\\n\\t\\tfloat lightDistance = length( lVector );\\n\\n\\t\\tlight.color = pointLight.color;\\n\\t\\tlight.color *= getDistanceAttenuation( lightDistance, pointLight.distance, pointLight.decay );\\n\\t\\tlight.visible = ( light.color != vec3( 0.0 ) );\\n\\n\\t}\\n\\n#endif\\n\\n\\n#if NUM_SPOT_LIGHTS > 0\\n\\n\\tstruct SpotLight {\\n\\t\\tvec3 position;\\n\\t\\tvec3 direction;\\n\\t\\tvec3 color;\\n\\t\\tfloat distance;\\n\\t\\tfloat decay;\\n\\t\\tfloat coneCos;\\n\\t\\tfloat penumbraCos;\\n\\t};\\n\\n\\tuniform SpotLight spotLights[ NUM_SPOT_LIGHTS ];\\n\\n\\t// light is an out parameter as having it as a return value caused compiler errors on some devices\\n\\tvoid getSpotLightInfo( const in SpotLight spotLight, const in GeometricContext geometry, out IncidentLight light ) {\\n\\n\\t\\tvec3 lVector = spotLight.position - geometry.position;\\n\\n\\t\\tlight.direction = normalize( lVector );\\n\\n\\t\\tfloat angleCos = dot( light.direction, spotLight.direction );\\n\\n\\t\\tfloat spotAttenuation = getSpotAttenuation( spotLight.coneCos, spotLight.penumbraCos, angleCos );\\n\\n\\t\\tif ( spotAttenuation > 0.0 ) {\\n\\n\\t\\t\\tfloat lightDistance = length( lVector );\\n\\n\\t\\t\\tlight.color = spotLight.color * spotAttenuation;\\n\\t\\t\\tlight.color *= getDistanceAttenuation( lightDistance, spotLight.distance, spotLight.decay );\\n\\t\\t\\tlight.visible = ( light.color != vec3( 0.0 ) );\\n\\n\\t\\t} else {\\n\\n\\t\\t\\tlight.color = vec3( 0.0 );\\n\\t\\t\\tlight.visible = false;\\n\\n\\t\\t}\\n\\n\\t}\\n\\n#endif\\n\\n\\n#if NUM_RECT_AREA_LIGHTS > 0\\n\\n\\tstruct RectAreaLight {\\n\\t\\tvec3 color;\\n\\t\\tvec3 position;\\n\\t\\tvec3 halfWidth;\\n\\t\\tvec3 halfHeight;\\n\\t};\\n\\n\\t// Pre-computed values of LinearTransformedCosine approximation of BRDF\\n\\t// BRDF approximation Texture is 64x64\\n\\tuniform sampler2D ltc_1; // RGBA Float\\n\\tuniform sampler2D ltc_2; // RGBA Float\\n\\n\\tuniform RectAreaLight rectAreaLights[ NUM_RECT_AREA_LIGHTS ];\\n\\n#endif\\n\\n\\n#if NUM_HEMI_LIGHTS > 0\\n\\n\\tstruct HemisphereLight {\\n\\t\\tvec3 direction;\\n\\t\\tvec3 skyColor;\\n\\t\\tvec3 groundColor;\\n\\t};\\n\\n\\tuniform HemisphereLight hemisphereLights[ NUM_HEMI_LIGHTS ];\\n\\n\\tvec3 getHemisphereLightIrradiance( const in HemisphereLight hemiLight, const in vec3 normal ) {\\n\\n\\t\\tfloat dotNL = dot( normal, hemiLight.direction );\\n\\t\\tfloat hemiDiffuseWeight = 0.5 * dotNL + 0.5;\\n\\n\\t\\tvec3 irradiance = mix( hemiLight.groundColor, hemiLight.skyColor, hemiDiffuseWeight );\\n\\n\\t\\treturn irradiance;\\n\\n\\t}\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/envmap_physical_pars_fragment.glsl.js\\nvar envmap_physical_pars_fragment_glsl_default = `\\n#if defined( USE_ENVMAP )\\n\\n\\t#ifdef ENVMAP_MODE_REFRACTION\\n\\n\\t\\tuniform float refractionRatio;\\n\\n\\t#endif\\n\\n\\tvec3 getIBLIrradiance( const in vec3 normal ) {\\n\\n\\t\\t#if defined( ENVMAP_TYPE_CUBE_UV )\\n\\n\\t\\t\\tvec3 worldNormal = inverseTransformDirection( normal, viewMatrix );\\n\\n\\t\\t\\tvec4 envMapColor = textureCubeUV( envMap, worldNormal, 1.0 );\\n\\n\\t\\t\\treturn PI * envMapColor.rgb * envMapIntensity;\\n\\n\\t\\t#else\\n\\n\\t\\t\\treturn vec3( 0.0 );\\n\\n\\t\\t#endif\\n\\n\\t}\\n\\n\\tvec3 getIBLRadiance( const in vec3 viewDir, const in vec3 normal, const in float roughness ) {\\n\\n\\t\\t#if defined( ENVMAP_TYPE_CUBE_UV )\\n\\n\\t\\t\\tvec3 reflectVec;\\n\\n\\t\\t\\t#ifdef ENVMAP_MODE_REFLECTION\\n\\n\\t\\t\\t\\treflectVec = reflect( - viewDir, normal );\\n\\n\\t\\t\\t\\t// Mixing the reflection with the normal is more accurate and keeps rough objects from gathering light from behind their tangent plane.\\n\\t\\t\\t\\treflectVec = normalize( mix( reflectVec, normal, roughness * roughness) );\\n\\n\\t\\t\\t#else\\n\\n\\t\\t\\t\\treflectVec = refract( - viewDir, normal, refractionRatio );\\n\\n\\t\\t\\t#endif\\n\\n\\t\\t\\treflectVec = inverseTransformDirection( reflectVec, viewMatrix );\\n\\n\\t\\t\\tvec4 envMapColor = textureCubeUV( envMap, reflectVec, roughness );\\n\\n\\t\\t\\treturn envMapColor.rgb * envMapIntensity;\\n\\n\\t\\t#else\\n\\n\\t\\t\\treturn vec3( 0.0 );\\n\\n\\t\\t#endif\\n\\n\\t}\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/lights_toon_fragment.glsl.js\\nvar lights_toon_fragment_glsl_default = `\\nToonMaterial material;\\nmaterial.diffuseColor = diffuseColor.rgb;\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/lights_toon_pars_fragment.glsl.js\\nvar lights_toon_pars_fragment_glsl_default = `\\nvarying vec3 vViewPosition;\\n\\nstruct ToonMaterial {\\n\\n\\tvec3 diffuseColor;\\n\\n};\\n\\nvoid RE_Direct_Toon( const in IncidentLight directLight, const in GeometricContext geometry, const in ToonMaterial material, inout ReflectedLight reflectedLight ) {\\n\\n\\tvec3 irradiance = getGradientIrradiance( geometry.normal, directLight.direction ) * directLight.color;\\n\\n\\treflectedLight.directDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );\\n\\n}\\n\\nvoid RE_IndirectDiffuse_Toon( const in vec3 irradiance, const in GeometricContext geometry, const in ToonMaterial material, inout ReflectedLight reflectedLight ) {\\n\\n\\treflectedLight.indirectDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );\\n\\n}\\n\\n#define RE_Direct\\t\\t\\t\\tRE_Direct_Toon\\n#define RE_IndirectDiffuse\\t\\tRE_IndirectDiffuse_Toon\\n\\n#define Material_LightProbeLOD( material )\\t(0)\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/lights_phong_fragment.glsl.js\\nvar lights_phong_fragment_glsl_default = `\\nBlinnPhongMaterial material;\\nmaterial.diffuseColor = diffuseColor.rgb;\\nmaterial.specularColor = specular;\\nmaterial.specularShininess = shininess;\\nmaterial.specularStrength = specularStrength;\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/lights_phong_pars_fragment.glsl.js\\nvar lights_phong_pars_fragment_glsl_default = `\\nvarying vec3 vViewPosition;\\n\\nstruct BlinnPhongMaterial {\\n\\n\\tvec3 diffuseColor;\\n\\tvec3 specularColor;\\n\\tfloat specularShininess;\\n\\tfloat specularStrength;\\n\\n};\\n\\nvoid RE_Direct_BlinnPhong( const in IncidentLight directLight, const in GeometricContext geometry, const in BlinnPhongMaterial material, inout ReflectedLight reflectedLight ) {\\n\\n\\tfloat dotNL = saturate( dot( geometry.normal, directLight.direction ) );\\n\\tvec3 irradiance = dotNL * directLight.color;\\n\\n\\treflectedLight.directDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );\\n\\n\\treflectedLight.directSpecular += irradiance * BRDF_BlinnPhong( directLight.direction, geometry.viewDir, geometry.normal, material.specularColor, material.specularShininess ) * material.specularStrength;\\n\\n}\\n\\nvoid RE_IndirectDiffuse_BlinnPhong( const in vec3 irradiance, const in GeometricContext geometry, const in BlinnPhongMaterial material, inout ReflectedLight reflectedLight ) {\\n\\n\\treflectedLight.indirectDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );\\n\\n}\\n\\n#define RE_Direct\\t\\t\\t\\tRE_Direct_BlinnPhong\\n#define RE_IndirectDiffuse\\t\\tRE_IndirectDiffuse_BlinnPhong\\n\\n#define Material_LightProbeLOD( material )\\t(0)\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/lights_physical_fragment.glsl.js\\nvar lights_physical_fragment_glsl_default = `\\nPhysicalMaterial material;\\nmaterial.diffuseColor = diffuseColor.rgb * ( 1.0 - metalnessFactor );\\n\\nvec3 dxy = max( abs( dFdx( geometryNormal ) ), abs( dFdy( geometryNormal ) ) );\\nfloat geometryRoughness = max( max( dxy.x, dxy.y ), dxy.z );\\n\\nmaterial.roughness = max( roughnessFactor, 0.0525 );// 0.0525 corresponds to the base mip of a 256 cubemap.\\nmaterial.roughness += geometryRoughness;\\nmaterial.roughness = min( material.roughness, 1.0 );\\n\\n#ifdef IOR\\n\\n\\t#ifdef SPECULAR\\n\\n\\t\\tfloat specularIntensityFactor = specularIntensity;\\n\\t\\tvec3 specularTintFactor = specularTint;\\n\\n\\t\\t#ifdef USE_SPECULARINTENSITYMAP\\n\\n\\t\\t\\tspecularIntensityFactor *= texture2D( specularIntensityMap, vUv ).a;\\n\\n\\t\\t#endif\\n\\n\\t\\t#ifdef USE_SPECULARTINTMAP\\n\\n\\t\\t\\tspecularTintFactor *= specularTintMapTexelToLinear( texture2D( specularTintMap, vUv ) ).rgb;\\n\\n\\t\\t#endif\\n\\n\\t\\tmaterial.specularF90 = mix( specularIntensityFactor, 1.0, metalnessFactor );\\n\\n\\t#else\\n\\n\\t\\tfloat specularIntensityFactor = 1.0;\\n\\t\\tvec3 specularTintFactor = vec3( 1.0 );\\n\\t\\tmaterial.specularF90 = 1.0;\\n\\n\\t#endif\\n\\n\\tmaterial.specularColor = mix( min( pow2( ( ior - 1.0 ) / ( ior + 1.0 ) ) * specularTintFactor, vec3( 1.0 ) ) * specularIntensityFactor, diffuseColor.rgb, metalnessFactor );\\n\\n#else\\n\\n\\tmaterial.specularColor = mix( vec3( 0.04 ), diffuseColor.rgb, metalnessFactor );\\n\\tmaterial.specularF90 = 1.0;\\n\\n#endif\\n\\n#ifdef USE_CLEARCOAT\\n\\n\\tmaterial.clearcoat = clearcoat;\\n\\tmaterial.clearcoatRoughness = clearcoatRoughness;\\n\\tmaterial.clearcoatF0 = vec3( 0.04 );\\n\\tmaterial.clearcoatF90 = 1.0;\\n\\n\\t#ifdef USE_CLEARCOATMAP\\n\\n\\t\\tmaterial.clearcoat *= texture2D( clearcoatMap, vUv ).x;\\n\\n\\t#endif\\n\\n\\t#ifdef USE_CLEARCOAT_ROUGHNESSMAP\\n\\n\\t\\tmaterial.clearcoatRoughness *= texture2D( clearcoatRoughnessMap, vUv ).y;\\n\\n\\t#endif\\n\\n\\tmaterial.clearcoat = saturate( material.clearcoat ); // Burley clearcoat model\\n\\tmaterial.clearcoatRoughness = max( material.clearcoatRoughness, 0.0525 );\\n\\tmaterial.clearcoatRoughness += geometryRoughness;\\n\\tmaterial.clearcoatRoughness = min( material.clearcoatRoughness, 1.0 );\\n\\n#endif\\n\\n#ifdef USE_SHEEN\\n\\n\\tmaterial.sheenTint = sheenTint;\\n\\tmaterial.sheenRoughness = clamp( sheenRoughness, 0.07, 1.0 );\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/lights_physical_pars_fragment.glsl.js\\nvar lights_physical_pars_fragment_glsl_default = `\\nstruct PhysicalMaterial {\\n\\n\\tvec3 diffuseColor;\\n\\tfloat roughness;\\n\\tvec3 specularColor;\\n\\tfloat specularF90;\\n\\n\\t#ifdef USE_CLEARCOAT\\n\\t\\tfloat clearcoat;\\n\\t\\tfloat clearcoatRoughness;\\n\\t\\tvec3 clearcoatF0;\\n\\t\\tfloat clearcoatF90;\\n\\t#endif\\n\\n\\t#ifdef USE_SHEEN\\n\\t\\tvec3 sheenTint;\\n\\t\\tfloat sheenRoughness;\\n\\t#endif\\n\\n};\\n\\n// temporary\\nvec3 clearcoatSpecular = vec3( 0.0 );\\n\\n// Analytical approximation of the DFG LUT, one half of the\\n// split-sum approximation used in indirect specular lighting.\\n// via 'environmentBRDF' from \\\\\\\"Physically Based Shading on Mobile\\\\\\\"\\n// https://www.unrealengine.com/blog/physically-based-shading-on-mobile\\nvec2 DFGApprox( const in vec3 normal, const in vec3 viewDir, const in float roughness ) {\\n\\n\\tfloat dotNV = saturate( dot( normal, viewDir ) );\\n\\n\\tconst vec4 c0 = vec4( - 1, - 0.0275, - 0.572, 0.022 );\\n\\n\\tconst vec4 c1 = vec4( 1, 0.0425, 1.04, - 0.04 );\\n\\n\\tvec4 r = roughness * c0 + c1;\\n\\n\\tfloat a004 = min( r.x * r.x, exp2( - 9.28 * dotNV ) ) * r.x + r.y;\\n\\n\\tvec2 fab = vec2( - 1.04, 1.04 ) * a004 + r.zw;\\n\\n\\treturn fab;\\n\\n}\\n\\nvec3 EnvironmentBRDF( const in vec3 normal, const in vec3 viewDir, const in vec3 specularColor, const in float specularF90, const in float roughness ) {\\n\\n\\tvec2 fab = DFGApprox( normal, viewDir, roughness );\\n\\n\\treturn specularColor * fab.x + specularF90 * fab.y;\\n\\n}\\n\\n// Fdez-Ag\\\\xFCera's \\\\\\\"Multiple-Scattering Microfacet Model for Real-Time Image Based Lighting\\\\\\\"\\n// Approximates multiscattering in order to preserve energy.\\n// http://www.jcgt.org/published/0008/01/03/\\nvoid computeMultiscattering( const in vec3 normal, const in vec3 viewDir, const in vec3 specularColor, const in float specularF90, const in float roughness, inout vec3 singleScatter, inout vec3 multiScatter ) {\\n\\n\\tvec2 fab = DFGApprox( normal, viewDir, roughness );\\n\\n\\tvec3 FssEss = specularColor * fab.x + specularF90 * fab.y;\\n\\n\\tfloat Ess = fab.x + fab.y;\\n\\tfloat Ems = 1.0 - Ess;\\n\\n\\tvec3 Favg = specularColor + ( 1.0 - specularColor ) * 0.047619; // 1/21\\n\\tvec3 Fms = FssEss * Favg / ( 1.0 - Ems * Favg );\\n\\n\\tsingleScatter += FssEss;\\n\\tmultiScatter += Fms * Ems;\\n\\n}\\n\\n#if NUM_RECT_AREA_LIGHTS > 0\\n\\n\\tvoid RE_Direct_RectArea_Physical( const in RectAreaLight rectAreaLight, const in GeometricContext geometry, const in PhysicalMaterial material, inout ReflectedLight reflectedLight ) {\\n\\n\\t\\tvec3 normal = geometry.normal;\\n\\t\\tvec3 viewDir = geometry.viewDir;\\n\\t\\tvec3 position = geometry.position;\\n\\t\\tvec3 lightPos = rectAreaLight.position;\\n\\t\\tvec3 halfWidth = rectAreaLight.halfWidth;\\n\\t\\tvec3 halfHeight = rectAreaLight.halfHeight;\\n\\t\\tvec3 lightColor = rectAreaLight.color;\\n\\t\\tfloat roughness = material.roughness;\\n\\n\\t\\tvec3 rectCoords[ 4 ];\\n\\t\\trectCoords[ 0 ] = lightPos + halfWidth - halfHeight; // counterclockwise; light shines in local neg z direction\\n\\t\\trectCoords[ 1 ] = lightPos - halfWidth - halfHeight;\\n\\t\\trectCoords[ 2 ] = lightPos - halfWidth + halfHeight;\\n\\t\\trectCoords[ 3 ] = lightPos + halfWidth + halfHeight;\\n\\n\\t\\tvec2 uv = LTC_Uv( normal, viewDir, roughness );\\n\\n\\t\\tvec4 t1 = texture2D( ltc_1, uv );\\n\\t\\tvec4 t2 = texture2D( ltc_2, uv );\\n\\n\\t\\tmat3 mInv = mat3(\\n\\t\\t\\tvec3( t1.x, 0, t1.y ),\\n\\t\\t\\tvec3( 0, 1, 0 ),\\n\\t\\t\\tvec3( t1.z, 0, t1.w )\\n\\t\\t);\\n\\n\\t\\t// LTC Fresnel Approximation by Stephen Hill\\n\\t\\t// http://blog.selfshadow.com/publications/s2016-advances/s2016_ltc_fresnel.pdf\\n\\t\\tvec3 fresnel = ( material.specularColor * t2.x + ( vec3( 1.0 ) - material.specularColor ) * t2.y );\\n\\n\\t\\treflectedLight.directSpecular += lightColor * fresnel * LTC_Evaluate( normal, viewDir, position, mInv, rectCoords );\\n\\n\\t\\treflectedLight.directDiffuse += lightColor * material.diffuseColor * LTC_Evaluate( normal, viewDir, position, mat3( 1.0 ), rectCoords );\\n\\n\\t}\\n\\n#endif\\n\\nvoid RE_Direct_Physical( const in IncidentLight directLight, const in GeometricContext geometry, const in PhysicalMaterial material, inout ReflectedLight reflectedLight ) {\\n\\n\\tfloat dotNL = saturate( dot( geometry.normal, directLight.direction ) );\\n\\n\\tvec3 irradiance = dotNL * directLight.color;\\n\\n\\t#ifdef USE_CLEARCOAT\\n\\n\\t\\tfloat dotNLcc = saturate( dot( geometry.clearcoatNormal, directLight.direction ) );\\n\\n\\t\\tvec3 ccIrradiance = dotNLcc * directLight.color;\\n\\n\\t\\tclearcoatSpecular += ccIrradiance * BRDF_GGX( directLight.direction, geometry.viewDir, geometry.clearcoatNormal, material.clearcoatF0, material.clearcoatF90, material.clearcoatRoughness );\\n\\n\\t#endif\\n\\n\\t#ifdef USE_SHEEN\\n\\n\\t\\treflectedLight.directSpecular += irradiance * BRDF_Sheen( directLight.direction, geometry.viewDir, geometry.normal, material.sheenTint, material.sheenRoughness );\\n\\n\\t#endif\\n\\n\\treflectedLight.directSpecular += irradiance * BRDF_GGX( directLight.direction, geometry.viewDir, geometry.normal, material.specularColor, material.specularF90, material.roughness );\\n\\n\\n\\treflectedLight.directDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );\\n}\\n\\nvoid RE_IndirectDiffuse_Physical( const in vec3 irradiance, const in GeometricContext geometry, const in PhysicalMaterial material, inout ReflectedLight reflectedLight ) {\\n\\n\\treflectedLight.indirectDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );\\n\\n}\\n\\nvoid RE_IndirectSpecular_Physical( const in vec3 radiance, const in vec3 irradiance, const in vec3 clearcoatRadiance, const in GeometricContext geometry, const in PhysicalMaterial material, inout ReflectedLight reflectedLight) {\\n\\n\\t#ifdef USE_CLEARCOAT\\n\\n\\t\\tclearcoatSpecular += clearcoatRadiance * EnvironmentBRDF( geometry.clearcoatNormal, geometry.viewDir, material.clearcoatF0, material.clearcoatF90, material.clearcoatRoughness );\\n\\n\\t#endif\\n\\n\\t// Both indirect specular and indirect diffuse light accumulate here\\n\\n\\tvec3 singleScattering = vec3( 0.0 );\\n\\tvec3 multiScattering = vec3( 0.0 );\\n\\tvec3 cosineWeightedIrradiance = irradiance * RECIPROCAL_PI;\\n\\n\\tcomputeMultiscattering( geometry.normal, geometry.viewDir, material.specularColor, material.specularF90, material.roughness, singleScattering, multiScattering );\\n\\n\\tvec3 diffuse = material.diffuseColor * ( 1.0 - ( singleScattering + multiScattering ) );\\n\\n\\treflectedLight.indirectSpecular += radiance * singleScattering;\\n\\treflectedLight.indirectSpecular += multiScattering * cosineWeightedIrradiance;\\n\\n\\treflectedLight.indirectDiffuse += diffuse * cosineWeightedIrradiance;\\n\\n}\\n\\n#define RE_Direct\\t\\t\\t\\tRE_Direct_Physical\\n#define RE_Direct_RectArea\\t\\tRE_Direct_RectArea_Physical\\n#define RE_IndirectDiffuse\\t\\tRE_IndirectDiffuse_Physical\\n#define RE_IndirectSpecular\\t\\tRE_IndirectSpecular_Physical\\n\\n// ref: https://seblagarde.files.wordpress.com/2015/07/course_notes_moving_frostbite_to_pbr_v32.pdf\\nfloat computeSpecularOcclusion( const in float dotNV, const in float ambientOcclusion, const in float roughness ) {\\n\\n\\treturn saturate( pow( dotNV + ambientOcclusion, exp2( - 16.0 * roughness - 1.0 ) ) - 1.0 + ambientOcclusion );\\n\\n}\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/lights_fragment_begin.glsl.js\\nvar lights_fragment_begin_glsl_default = `\\n/**\\n * This is a template that can be used to light a material, it uses pluggable\\n * RenderEquations (RE)for specific lighting scenarios.\\n *\\n * Instructions for use:\\n * - Ensure that both RE_Direct, RE_IndirectDiffuse and RE_IndirectSpecular are defined\\n * - If you have defined an RE_IndirectSpecular, you need to also provide a Material_LightProbeLOD. <---- ???\\n * - Create a material parameter that is to be passed as the third parameter to your lighting functions.\\n *\\n * TODO:\\n * - Add area light support.\\n * - Add sphere light support.\\n * - Add diffuse light probe (irradiance cubemap) support.\\n */\\n\\nGeometricContext geometry;\\n\\ngeometry.position = - vViewPosition;\\ngeometry.normal = normal;\\ngeometry.viewDir = ( isOrthographic ) ? vec3( 0, 0, 1 ) : normalize( vViewPosition );\\n\\n#ifdef USE_CLEARCOAT\\n\\n\\tgeometry.clearcoatNormal = clearcoatNormal;\\n\\n#endif\\n\\nIncidentLight directLight;\\n\\n#if ( NUM_POINT_LIGHTS > 0 ) && defined( RE_Direct )\\n\\n\\tPointLight pointLight;\\n\\t#if defined( USE_SHADOWMAP ) && NUM_POINT_LIGHT_SHADOWS > 0\\n\\tPointLightShadow pointLightShadow;\\n\\t#endif\\n\\n\\t#pragma unroll_loop_start\\n\\tfor ( int i = 0; i < NUM_POINT_LIGHTS; i ++ ) {\\n\\n\\t\\tpointLight = pointLights[ i ];\\n\\n\\t\\tgetPointLightInfo( pointLight, geometry, directLight );\\n\\n\\t\\t#if defined( USE_SHADOWMAP ) && ( UNROLLED_LOOP_INDEX < NUM_POINT_LIGHT_SHADOWS )\\n\\t\\tpointLightShadow = pointLightShadows[ i ];\\n\\t\\tdirectLight.color *= all( bvec2( directLight.visible, receiveShadow ) ) ? getPointShadow( pointShadowMap[ i ], pointLightShadow.shadowMapSize, pointLightShadow.shadowBias, pointLightShadow.shadowRadius, vPointShadowCoord[ i ], pointLightShadow.shadowCameraNear, pointLightShadow.shadowCameraFar ) : 1.0;\\n\\t\\t#endif\\n\\n\\t\\tRE_Direct( directLight, geometry, material, reflectedLight );\\n\\n\\t}\\n\\t#pragma unroll_loop_end\\n\\n#endif\\n\\n#if ( NUM_SPOT_LIGHTS > 0 ) && defined( RE_Direct )\\n\\n\\tSpotLight spotLight;\\n\\t#if defined( USE_SHADOWMAP ) && NUM_SPOT_LIGHT_SHADOWS > 0\\n\\tSpotLightShadow spotLightShadow;\\n\\t#endif\\n\\n\\t#pragma unroll_loop_start\\n\\tfor ( int i = 0; i < NUM_SPOT_LIGHTS; i ++ ) {\\n\\n\\t\\tspotLight = spotLights[ i ];\\n\\n\\t\\tgetSpotLightInfo( spotLight, geometry, directLight );\\n\\n\\t\\t#if defined( USE_SHADOWMAP ) && ( UNROLLED_LOOP_INDEX < NUM_SPOT_LIGHT_SHADOWS )\\n\\t\\tspotLightShadow = spotLightShadows[ i ];\\n\\t\\tdirectLight.color *= all( bvec2( directLight.visible, receiveShadow ) ) ? getShadow( spotShadowMap[ i ], spotLightShadow.shadowMapSize, spotLightShadow.shadowBias, spotLightShadow.shadowRadius, vSpotShadowCoord[ i ] ) : 1.0;\\n\\t\\t#endif\\n\\n\\t\\tRE_Direct( directLight, geometry, material, reflectedLight );\\n\\n\\t}\\n\\t#pragma unroll_loop_end\\n\\n#endif\\n\\n#if ( NUM_DIR_LIGHTS > 0 ) && defined( RE_Direct )\\n\\n\\tDirectionalLight directionalLight;\\n\\t#if defined( USE_SHADOWMAP ) && NUM_DIR_LIGHT_SHADOWS > 0\\n\\tDirectionalLightShadow directionalLightShadow;\\n\\t#endif\\n\\n\\t#pragma unroll_loop_start\\n\\tfor ( int i = 0; i < NUM_DIR_LIGHTS; i ++ ) {\\n\\n\\t\\tdirectionalLight = directionalLights[ i ];\\n\\n\\t\\tgetDirectionalLightInfo( directionalLight, geometry, directLight );\\n\\n\\t\\t#if defined( USE_SHADOWMAP ) && ( UNROLLED_LOOP_INDEX < NUM_DIR_LIGHT_SHADOWS )\\n\\t\\tdirectionalLightShadow = directionalLightShadows[ i ];\\n\\t\\tdirectLight.color *= all( bvec2( directLight.visible, receiveShadow ) ) ? getShadow( directionalShadowMap[ i ], directionalLightShadow.shadowMapSize, directionalLightShadow.shadowBias, directionalLightShadow.shadowRadius, vDirectionalShadowCoord[ i ] ) : 1.0;\\n\\t\\t#endif\\n\\n\\t\\tRE_Direct( directLight, geometry, material, reflectedLight );\\n\\n\\t}\\n\\t#pragma unroll_loop_end\\n\\n#endif\\n\\n#if ( NUM_RECT_AREA_LIGHTS > 0 ) && defined( RE_Direct_RectArea )\\n\\n\\tRectAreaLight rectAreaLight;\\n\\n\\t#pragma unroll_loop_start\\n\\tfor ( int i = 0; i < NUM_RECT_AREA_LIGHTS; i ++ ) {\\n\\n\\t\\trectAreaLight = rectAreaLights[ i ];\\n\\t\\tRE_Direct_RectArea( rectAreaLight, geometry, material, reflectedLight );\\n\\n\\t}\\n\\t#pragma unroll_loop_end\\n\\n#endif\\n\\n#if defined( RE_IndirectDiffuse )\\n\\n\\tvec3 iblIrradiance = vec3( 0.0 );\\n\\n\\tvec3 irradiance = getAmbientLightIrradiance( ambientLightColor );\\n\\n\\tirradiance += getLightProbeIrradiance( lightProbe, geometry.normal );\\n\\n\\t#if ( NUM_HEMI_LIGHTS > 0 )\\n\\n\\t\\t#pragma unroll_loop_start\\n\\t\\tfor ( int i = 0; i < NUM_HEMI_LIGHTS; i ++ ) {\\n\\n\\t\\t\\tirradiance += getHemisphereLightIrradiance( hemisphereLights[ i ], geometry.normal );\\n\\n\\t\\t}\\n\\t\\t#pragma unroll_loop_end\\n\\n\\t#endif\\n\\n#endif\\n\\n#if defined( RE_IndirectSpecular )\\n\\n\\tvec3 radiance = vec3( 0.0 );\\n\\tvec3 clearcoatRadiance = vec3( 0.0 );\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/lights_fragment_maps.glsl.js\\nvar lights_fragment_maps_glsl_default = `\\n#if defined( RE_IndirectDiffuse )\\n\\n\\t#ifdef USE_LIGHTMAP\\n\\n\\t\\tvec4 lightMapTexel = texture2D( lightMap, vUv2 );\\n\\t\\tvec3 lightMapIrradiance = lightMapTexelToLinear( lightMapTexel ).rgb * lightMapIntensity;\\n\\n\\t\\t#ifndef PHYSICALLY_CORRECT_LIGHTS\\n\\n\\t\\t\\tlightMapIrradiance *= PI;\\n\\n\\t\\t#endif\\n\\n\\t\\tirradiance += lightMapIrradiance;\\n\\n\\t#endif\\n\\n\\t#if defined( USE_ENVMAP ) && defined( STANDARD ) && defined( ENVMAP_TYPE_CUBE_UV )\\n\\n\\t\\tiblIrradiance += getIBLIrradiance( geometry.normal );\\n\\n\\t#endif\\n\\n#endif\\n\\n#if defined( USE_ENVMAP ) && defined( RE_IndirectSpecular )\\n\\n\\tradiance += getIBLRadiance( geometry.viewDir, geometry.normal, material.roughness );\\n\\n\\t#ifdef USE_CLEARCOAT\\n\\n\\t\\tclearcoatRadiance += getIBLRadiance( geometry.viewDir, geometry.clearcoatNormal, material.clearcoatRoughness );\\n\\n\\t#endif\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/lights_fragment_end.glsl.js\\nvar lights_fragment_end_glsl_default = `\\n#if defined( RE_IndirectDiffuse )\\n\\n\\tRE_IndirectDiffuse( irradiance, geometry, material, reflectedLight );\\n\\n#endif\\n\\n#if defined( RE_IndirectSpecular )\\n\\n\\tRE_IndirectSpecular( radiance, iblIrradiance, clearcoatRadiance, geometry, material, reflectedLight );\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/logdepthbuf_fragment.glsl.js\\nvar logdepthbuf_fragment_glsl_default = `\\n#if defined( USE_LOGDEPTHBUF ) && defined( USE_LOGDEPTHBUF_EXT )\\n\\n\\t// Doing a strict comparison with == 1.0 can cause noise artifacts\\n\\t// on some platforms. See issue #17623.\\n\\tgl_FragDepthEXT = vIsPerspective == 0.0 ? gl_FragCoord.z : log2( vFragDepth ) * logDepthBufFC * 0.5;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/logdepthbuf_pars_fragment.glsl.js\\nvar logdepthbuf_pars_fragment_glsl_default = `\\n#if defined( USE_LOGDEPTHBUF ) && defined( USE_LOGDEPTHBUF_EXT )\\n\\n\\tuniform float logDepthBufFC;\\n\\tvarying float vFragDepth;\\n\\tvarying float vIsPerspective;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/logdepthbuf_pars_vertex.glsl.js\\nvar logdepthbuf_pars_vertex_glsl_default = `\\n#ifdef USE_LOGDEPTHBUF\\n\\n\\t#ifdef USE_LOGDEPTHBUF_EXT\\n\\n\\t\\tvarying float vFragDepth;\\n\\t\\tvarying float vIsPerspective;\\n\\n\\t#else\\n\\n\\t\\tuniform float logDepthBufFC;\\n\\n\\t#endif\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/logdepthbuf_vertex.glsl.js\\nvar logdepthbuf_vertex_glsl_default = `\\n#ifdef USE_LOGDEPTHBUF\\n\\n\\t#ifdef USE_LOGDEPTHBUF_EXT\\n\\n\\t\\tvFragDepth = 1.0 + gl_Position.w;\\n\\t\\tvIsPerspective = float( isPerspectiveMatrix( projectionMatrix ) );\\n\\n\\t#else\\n\\n\\t\\tif ( isPerspectiveMatrix( projectionMatrix ) ) {\\n\\n\\t\\t\\tgl_Position.z = log2( max( EPSILON, gl_Position.w + 1.0 ) ) * logDepthBufFC - 1.0;\\n\\n\\t\\t\\tgl_Position.z *= gl_Position.w;\\n\\n\\t\\t}\\n\\n\\t#endif\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/map_fragment.glsl.js\\nvar map_fragment_glsl_default = `\\n#ifdef USE_MAP\\n\\n\\tvec4 texelColor = texture2D( map, vUv );\\n\\n\\ttexelColor = mapTexelToLinear( texelColor );\\n\\tdiffuseColor *= texelColor;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/map_pars_fragment.glsl.js\\nvar map_pars_fragment_glsl_default = `\\n#ifdef USE_MAP\\n\\n\\tuniform sampler2D map;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/map_particle_fragment.glsl.js\\nvar map_particle_fragment_glsl_default = `\\n#if defined( USE_MAP ) || defined( USE_ALPHAMAP )\\n\\n\\tvec2 uv = ( uvTransform * vec3( gl_PointCoord.x, 1.0 - gl_PointCoord.y, 1 ) ).xy;\\n\\n#endif\\n\\n#ifdef USE_MAP\\n\\n\\tvec4 mapTexel = texture2D( map, uv );\\n\\tdiffuseColor *= mapTexelToLinear( mapTexel );\\n\\n#endif\\n\\n#ifdef USE_ALPHAMAP\\n\\n\\tdiffuseColor.a *= texture2D( alphaMap, uv ).g;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/map_particle_pars_fragment.glsl.js\\nvar map_particle_pars_fragment_glsl_default = `\\n#if defined( USE_MAP ) || defined( USE_ALPHAMAP )\\n\\n\\tuniform mat3 uvTransform;\\n\\n#endif\\n\\n#ifdef USE_MAP\\n\\n\\tuniform sampler2D map;\\n\\n#endif\\n\\n#ifdef USE_ALPHAMAP\\n\\n\\tuniform sampler2D alphaMap;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/metalnessmap_fragment.glsl.js\\nvar metalnessmap_fragment_glsl_default = `\\nfloat metalnessFactor = metalness;\\n\\n#ifdef USE_METALNESSMAP\\n\\n\\tvec4 texelMetalness = texture2D( metalnessMap, vUv );\\n\\n\\t// reads channel B, compatible with a combined OcclusionRoughnessMetallic (RGB) texture\\n\\tmetalnessFactor *= texelMetalness.b;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/metalnessmap_pars_fragment.glsl.js\\nvar metalnessmap_pars_fragment_glsl_default = `\\n#ifdef USE_METALNESSMAP\\n\\n\\tuniform sampler2D metalnessMap;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/morphnormal_vertex.glsl.js\\nvar morphnormal_vertex_glsl_default = `\\n#ifdef USE_MORPHNORMALS\\n\\n\\t// morphTargetBaseInfluence is set based on BufferGeometry.morphTargetsRelative value:\\n\\t// When morphTargetsRelative is false, this is set to 1 - sum(influences); this results in normal = sum((target - base) * influence)\\n\\t// When morphTargetsRelative is true, this is set to 1; as a result, all morph targets are simply added to the base after weighting\\n\\tobjectNormal *= morphTargetBaseInfluence;\\n\\n\\t#ifdef MORPHTARGETS_TEXTURE\\n\\n\\t\\tfor ( int i = 0; i < MORPHTARGETS_COUNT; i ++ ) {\\n\\n\\t\\t\\tif ( morphTargetInfluences[ i ] > 0.0 ) objectNormal += getMorph( gl_VertexID, i, 1, 2 ) * morphTargetInfluences[ i ];\\n\\n\\t\\t}\\n\\n\\t#else\\n\\n\\t\\tobjectNormal += morphNormal0 * morphTargetInfluences[ 0 ];\\n\\t\\tobjectNormal += morphNormal1 * morphTargetInfluences[ 1 ];\\n\\t\\tobjectNormal += morphNormal2 * morphTargetInfluences[ 2 ];\\n\\t\\tobjectNormal += morphNormal3 * morphTargetInfluences[ 3 ];\\n\\n\\t#endif\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/morphtarget_pars_vertex.glsl.js\\nvar morphtarget_pars_vertex_glsl_default = `\\n#ifdef USE_MORPHTARGETS\\n\\n\\tuniform float morphTargetBaseInfluence;\\n\\n\\t#ifdef MORPHTARGETS_TEXTURE\\n\\n\\t\\tuniform float morphTargetInfluences[ MORPHTARGETS_COUNT ];\\n\\t\\tuniform sampler2DArray morphTargetsTexture;\\n\\t\\tuniform vec2 morphTargetsTextureSize;\\n\\n\\t\\tvec3 getMorph( const in int vertexIndex, const in int morphTargetIndex, const in int offset, const in int stride ) {\\n\\n\\t\\t\\tfloat texelIndex = float( vertexIndex * stride + offset );\\n\\t\\t\\tfloat y = floor( texelIndex / morphTargetsTextureSize.x );\\n\\t\\t\\tfloat x = texelIndex - y * morphTargetsTextureSize.x;\\n\\n\\t\\t\\tvec3 morphUV = vec3( ( x + 0.5 ) / morphTargetsTextureSize.x, y / morphTargetsTextureSize.y, morphTargetIndex );\\n\\t\\t\\treturn texture( morphTargetsTexture, morphUV ).xyz;\\n\\n\\t\\t}\\n\\n\\t#else\\n\\n\\t\\t#ifndef USE_MORPHNORMALS\\n\\n\\t\\t\\tuniform float morphTargetInfluences[ 8 ];\\n\\n\\t\\t#else\\n\\n\\t\\t\\tuniform float morphTargetInfluences[ 4 ];\\n\\n\\t\\t#endif\\n\\n\\t#endif\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/morphtarget_vertex.glsl.js\\nvar morphtarget_vertex_glsl_default = `\\n#ifdef USE_MORPHTARGETS\\n\\n\\t// morphTargetBaseInfluence is set based on BufferGeometry.morphTargetsRelative value:\\n\\t// When morphTargetsRelative is false, this is set to 1 - sum(influences); this results in position = sum((target - base) * influence)\\n\\t// When morphTargetsRelative is true, this is set to 1; as a result, all morph targets are simply added to the base after weighting\\n\\ttransformed *= morphTargetBaseInfluence;\\n\\n\\t#ifdef MORPHTARGETS_TEXTURE\\n\\n\\t\\tfor ( int i = 0; i < MORPHTARGETS_COUNT; i ++ ) {\\n\\n\\t\\t\\t#ifndef USE_MORPHNORMALS\\n\\n\\t\\t\\t\\tif ( morphTargetInfluences[ i ] > 0.0 ) transformed += getMorph( gl_VertexID, i, 0, 1 ) * morphTargetInfluences[ i ];\\n\\n\\t\\t\\t#else\\n\\n\\t\\t\\t\\tif ( morphTargetInfluences[ i ] > 0.0 ) transformed += getMorph( gl_VertexID, i, 0, 2 ) * morphTargetInfluences[ i ];\\n\\n\\t\\t\\t#endif\\n\\n\\t\\t}\\n\\n\\t#else\\n\\n\\t\\ttransformed += morphTarget0 * morphTargetInfluences[ 0 ];\\n\\t\\ttransformed += morphTarget1 * morphTargetInfluences[ 1 ];\\n\\t\\ttransformed += morphTarget2 * morphTargetInfluences[ 2 ];\\n\\t\\ttransformed += morphTarget3 * morphTargetInfluences[ 3 ];\\n\\n\\t\\t#ifndef USE_MORPHNORMALS\\n\\n\\t\\t\\ttransformed += morphTarget4 * morphTargetInfluences[ 4 ];\\n\\t\\t\\ttransformed += morphTarget5 * morphTargetInfluences[ 5 ];\\n\\t\\t\\ttransformed += morphTarget6 * morphTargetInfluences[ 6 ];\\n\\t\\t\\ttransformed += morphTarget7 * morphTargetInfluences[ 7 ];\\n\\n\\t\\t#endif\\n\\n\\t#endif\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/normal_fragment_begin.glsl.js\\nvar normal_fragment_begin_glsl_default = `\\nfloat faceDirection = gl_FrontFacing ? 1.0 : - 1.0;\\n\\n#ifdef FLAT_SHADED\\n\\n\\t// Workaround for Adreno GPUs not able to do dFdx( vViewPosition )\\n\\n\\tvec3 fdx = vec3( dFdx( vViewPosition.x ), dFdx( vViewPosition.y ), dFdx( vViewPosition.z ) );\\n\\tvec3 fdy = vec3( dFdy( vViewPosition.x ), dFdy( vViewPosition.y ), dFdy( vViewPosition.z ) );\\n\\tvec3 normal = normalize( cross( fdx, fdy ) );\\n\\n#else\\n\\n\\tvec3 normal = normalize( vNormal );\\n\\n\\t#ifdef DOUBLE_SIDED\\n\\n\\t\\tnormal = normal * faceDirection;\\n\\n\\t#endif\\n\\n\\t#ifdef USE_TANGENT\\n\\n\\t\\tvec3 tangent = normalize( vTangent );\\n\\t\\tvec3 bitangent = normalize( vBitangent );\\n\\n\\t\\t#ifdef DOUBLE_SIDED\\n\\n\\t\\t\\ttangent = tangent * faceDirection;\\n\\t\\t\\tbitangent = bitangent * faceDirection;\\n\\n\\t\\t#endif\\n\\n\\t\\t#if defined( TANGENTSPACE_NORMALMAP ) || defined( USE_CLEARCOAT_NORMALMAP )\\n\\n\\t\\t\\tmat3 vTBN = mat3( tangent, bitangent, normal );\\n\\n\\t\\t#endif\\n\\n\\t#endif\\n\\n#endif\\n\\n// non perturbed normal for clearcoat among others\\n\\nvec3 geometryNormal = normal;\\n\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/normal_fragment_maps.glsl.js\\nvar normal_fragment_maps_glsl_default = `\\n\\n#ifdef OBJECTSPACE_NORMALMAP\\n\\n\\tnormal = texture2D( normalMap, vUv ).xyz * 2.0 - 1.0; // overrides both flatShading and attribute normals\\n\\n\\t#ifdef FLIP_SIDED\\n\\n\\t\\tnormal = - normal;\\n\\n\\t#endif\\n\\n\\t#ifdef DOUBLE_SIDED\\n\\n\\t\\tnormal = normal * faceDirection;\\n\\n\\t#endif\\n\\n\\tnormal = normalize( normalMatrix * normal );\\n\\n#elif defined( TANGENTSPACE_NORMALMAP )\\n\\n\\tvec3 mapN = texture2D( normalMap, vUv ).xyz * 2.0 - 1.0;\\n\\tmapN.xy *= normalScale;\\n\\n\\t#ifdef USE_TANGENT\\n\\n\\t\\tnormal = normalize( vTBN * mapN );\\n\\n\\t#else\\n\\n\\t\\tnormal = perturbNormal2Arb( - vViewPosition, normal, mapN, faceDirection );\\n\\n\\t#endif\\n\\n#elif defined( USE_BUMPMAP )\\n\\n\\tnormal = perturbNormalArb( - vViewPosition, normal, dHdxy_fwd(), faceDirection );\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/normal_pars_fragment.glsl.js\\nvar normal_pars_fragment_glsl_default = `\\n#ifndef FLAT_SHADED\\n\\n\\tvarying vec3 vNormal;\\n\\n\\t#ifdef USE_TANGENT\\n\\n\\t\\tvarying vec3 vTangent;\\n\\t\\tvarying vec3 vBitangent;\\n\\n\\t#endif\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/normal_pars_vertex.glsl.js\\nvar normal_pars_vertex_glsl_default = `\\n#ifndef FLAT_SHADED\\n\\n\\tvarying vec3 vNormal;\\n\\n\\t#ifdef USE_TANGENT\\n\\n\\t\\tvarying vec3 vTangent;\\n\\t\\tvarying vec3 vBitangent;\\n\\n\\t#endif\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/normal_vertex.glsl.js\\nvar normal_vertex_glsl_default = `\\n#ifndef FLAT_SHADED // normal is computed with derivatives when FLAT_SHADED\\n\\n\\tvNormal = normalize( transformedNormal );\\n\\n\\t#ifdef USE_TANGENT\\n\\n\\t\\tvTangent = normalize( transformedTangent );\\n\\t\\tvBitangent = normalize( cross( vNormal, vTangent ) * tangent.w );\\n\\n\\t#endif\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/normalmap_pars_fragment.glsl.js\\nvar normalmap_pars_fragment_glsl_default = `\\n#ifdef USE_NORMALMAP\\n\\n\\tuniform sampler2D normalMap;\\n\\tuniform vec2 normalScale;\\n\\n#endif\\n\\n#ifdef OBJECTSPACE_NORMALMAP\\n\\n\\tuniform mat3 normalMatrix;\\n\\n#endif\\n\\n#if ! defined ( USE_TANGENT ) && ( defined ( TANGENTSPACE_NORMALMAP ) || defined ( USE_CLEARCOAT_NORMALMAP ) )\\n\\n\\t// Normal Mapping Without Precomputed Tangents\\n\\t// http://www.thetenthplanet.de/archives/1180\\n\\n\\tvec3 perturbNormal2Arb( vec3 eye_pos, vec3 surf_norm, vec3 mapN, float faceDirection ) {\\n\\n\\t\\t// Workaround for Adreno 3XX dFd*( vec3 ) bug. See #9988\\n\\n\\t\\tvec3 q0 = vec3( dFdx( eye_pos.x ), dFdx( eye_pos.y ), dFdx( eye_pos.z ) );\\n\\t\\tvec3 q1 = vec3( dFdy( eye_pos.x ), dFdy( eye_pos.y ), dFdy( eye_pos.z ) );\\n\\t\\tvec2 st0 = dFdx( vUv.st );\\n\\t\\tvec2 st1 = dFdy( vUv.st );\\n\\n\\t\\tvec3 N = surf_norm; // normalized\\n\\n\\t\\tvec3 q1perp = cross( q1, N );\\n\\t\\tvec3 q0perp = cross( N, q0 );\\n\\n\\t\\tvec3 T = q1perp * st0.x + q0perp * st1.x;\\n\\t\\tvec3 B = q1perp * st0.y + q0perp * st1.y;\\n\\n\\t\\tfloat det = max( dot( T, T ), dot( B, B ) );\\n\\t\\tfloat scale = ( det == 0.0 ) ? 0.0 : faceDirection * inversesqrt( det );\\n\\n\\t\\treturn normalize( T * ( mapN.x * scale ) + B * ( mapN.y * scale ) + N * mapN.z );\\n\\n\\t}\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/clearcoat_normal_fragment_begin.glsl.js\\nvar clearcoat_normal_fragment_begin_glsl_default = `\\n#ifdef USE_CLEARCOAT\\n\\n\\tvec3 clearcoatNormal = geometryNormal;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/clearcoat_normal_fragment_maps.glsl.js\\nvar clearcoat_normal_fragment_maps_glsl_default = `\\n#ifdef USE_CLEARCOAT_NORMALMAP\\n\\n\\tvec3 clearcoatMapN = texture2D( clearcoatNormalMap, vUv ).xyz * 2.0 - 1.0;\\n\\tclearcoatMapN.xy *= clearcoatNormalScale;\\n\\n\\t#ifdef USE_TANGENT\\n\\n\\t\\tclearcoatNormal = normalize( vTBN * clearcoatMapN );\\n\\n\\t#else\\n\\n\\t\\tclearcoatNormal = perturbNormal2Arb( - vViewPosition, clearcoatNormal, clearcoatMapN, faceDirection );\\n\\n\\t#endif\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/clearcoat_pars_fragment.glsl.js\\nvar clearcoat_pars_fragment_glsl_default = `\\n\\n#ifdef USE_CLEARCOATMAP\\n\\n\\tuniform sampler2D clearcoatMap;\\n\\n#endif\\n\\n#ifdef USE_CLEARCOAT_ROUGHNESSMAP\\n\\n\\tuniform sampler2D clearcoatRoughnessMap;\\n\\n#endif\\n\\n#ifdef USE_CLEARCOAT_NORMALMAP\\n\\n\\tuniform sampler2D clearcoatNormalMap;\\n\\tuniform vec2 clearcoatNormalScale;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/output_fragment.glsl.js\\nvar output_fragment_glsl_default = `\\n#ifdef OPAQUE\\ndiffuseColor.a = 1.0;\\n#endif\\n\\n// https://github.com/mrdoob/three.js/pull/22425\\n#ifdef USE_TRANSMISSION\\ndiffuseColor.a *= transmissionAlpha + 0.1;\\n#endif\\n\\ngl_FragColor = vec4( outgoingLight, diffuseColor.a );\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/packing.glsl.js\\nvar packing_glsl_default = `\\nvec3 packNormalToRGB( const in vec3 normal ) {\\n\\treturn normalize( normal ) * 0.5 + 0.5;\\n}\\n\\nvec3 unpackRGBToNormal( const in vec3 rgb ) {\\n\\treturn 2.0 * rgb.xyz - 1.0;\\n}\\n\\nconst float PackUpscale = 256. / 255.; // fraction -> 0..1 (including 1)\\nconst float UnpackDownscale = 255. / 256.; // 0..1 -> fraction (excluding 1)\\n\\nconst vec3 PackFactors = vec3( 256. * 256. * 256., 256. * 256., 256. );\\nconst vec4 UnpackFactors = UnpackDownscale / vec4( PackFactors, 1. );\\n\\nconst float ShiftRight8 = 1. / 256.;\\n\\nvec4 packDepthToRGBA( const in float v ) {\\n\\tvec4 r = vec4( fract( v * PackFactors ), v );\\n\\tr.yzw -= r.xyz * ShiftRight8; // tidy overflow\\n\\treturn r * PackUpscale;\\n}\\n\\nfloat unpackRGBAToDepth( const in vec4 v ) {\\n\\treturn dot( v, UnpackFactors );\\n}\\n\\nvec4 pack2HalfToRGBA( vec2 v ) {\\n\\tvec4 r = vec4( v.x, fract( v.x * 255.0 ), v.y, fract( v.y * 255.0 ) );\\n\\treturn vec4( r.x - r.y / 255.0, r.y, r.z - r.w / 255.0, r.w );\\n}\\n\\nvec2 unpackRGBATo2Half( vec4 v ) {\\n\\treturn vec2( v.x + ( v.y / 255.0 ), v.z + ( v.w / 255.0 ) );\\n}\\n\\n// NOTE: viewZ/eyeZ is < 0 when in front of the camera per OpenGL conventions\\n\\nfloat viewZToOrthographicDepth( const in float viewZ, const in float near, const in float far ) {\\n\\treturn ( viewZ + near ) / ( near - far );\\n}\\nfloat orthographicDepthToViewZ( const in float linearClipZ, const in float near, const in float far ) {\\n\\treturn linearClipZ * ( near - far ) - near;\\n}\\n\\n// NOTE: https://twitter.com/gonnavis/status/1377183786949959682\\n\\nfloat viewZToPerspectiveDepth( const in float viewZ, const in float near, const in float far ) {\\n\\treturn ( ( near + viewZ ) * far ) / ( ( far - near ) * viewZ );\\n}\\nfloat perspectiveDepthToViewZ( const in float invClipZ, const in float near, const in float far ) {\\n\\treturn ( near * far ) / ( ( far - near ) * invClipZ - far );\\n}\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/premultiplied_alpha_fragment.glsl.js\\nvar premultiplied_alpha_fragment_glsl_default = `\\n#ifdef PREMULTIPLIED_ALPHA\\n\\n\\t// Get get normal blending with premultipled, use with CustomBlending, OneFactor, OneMinusSrcAlphaFactor, AddEquation.\\n\\tgl_FragColor.rgb *= gl_FragColor.a;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/project_vertex.glsl.js\\nvar project_vertex_glsl_default = `\\nvec4 mvPosition = vec4( transformed, 1.0 );\\n\\n#ifdef USE_INSTANCING\\n\\n\\tmvPosition = instanceMatrix * mvPosition;\\n\\n#endif\\n\\nmvPosition = modelViewMatrix * mvPosition;\\n\\ngl_Position = projectionMatrix * mvPosition;\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/dithering_fragment.glsl.js\\nvar dithering_fragment_glsl_default = `\\n#ifdef DITHERING\\n\\n\\tgl_FragColor.rgb = dithering( gl_FragColor.rgb );\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/dithering_pars_fragment.glsl.js\\nvar dithering_pars_fragment_glsl_default = `\\n#ifdef DITHERING\\n\\n\\t// based on https://www.shadertoy.com/view/MslGR8\\n\\tvec3 dithering( vec3 color ) {\\n\\t\\t//Calculate grid position\\n\\t\\tfloat grid_position = rand( gl_FragCoord.xy );\\n\\n\\t\\t//Shift the individual colors differently, thus making it even harder to see the dithering pattern\\n\\t\\tvec3 dither_shift_RGB = vec3( 0.25 / 255.0, -0.25 / 255.0, 0.25 / 255.0 );\\n\\n\\t\\t//modify shift acording to grid position.\\n\\t\\tdither_shift_RGB = mix( 2.0 * dither_shift_RGB, -2.0 * dither_shift_RGB, grid_position );\\n\\n\\t\\t//shift the color by dither_shift\\n\\t\\treturn color + dither_shift_RGB;\\n\\t}\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/roughnessmap_fragment.glsl.js\\nvar roughnessmap_fragment_glsl_default = `\\nfloat roughnessFactor = roughness;\\n\\n#ifdef USE_ROUGHNESSMAP\\n\\n\\tvec4 texelRoughness = texture2D( roughnessMap, vUv );\\n\\n\\t// reads channel G, compatible with a combined OcclusionRoughnessMetallic (RGB) texture\\n\\troughnessFactor *= texelRoughness.g;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/roughnessmap_pars_fragment.glsl.js\\nvar roughnessmap_pars_fragment_glsl_default = `\\n#ifdef USE_ROUGHNESSMAP\\n\\n\\tuniform sampler2D roughnessMap;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/shadowmap_pars_fragment.glsl.js\\nvar shadowmap_pars_fragment_glsl_default = `\\n#ifdef USE_SHADOWMAP\\n\\n\\t#if NUM_DIR_LIGHT_SHADOWS > 0\\n\\n\\t\\tuniform sampler2D directionalShadowMap[ NUM_DIR_LIGHT_SHADOWS ];\\n\\t\\tvarying vec4 vDirectionalShadowCoord[ NUM_DIR_LIGHT_SHADOWS ];\\n\\n\\t\\tstruct DirectionalLightShadow {\\n\\t\\t\\tfloat shadowBias;\\n\\t\\t\\tfloat shadowNormalBias;\\n\\t\\t\\tfloat shadowRadius;\\n\\t\\t\\tvec2 shadowMapSize;\\n\\t\\t};\\n\\n\\t\\tuniform DirectionalLightShadow directionalLightShadows[ NUM_DIR_LIGHT_SHADOWS ];\\n\\n\\t#endif\\n\\n\\t#if NUM_SPOT_LIGHT_SHADOWS > 0\\n\\n\\t\\tuniform sampler2D spotShadowMap[ NUM_SPOT_LIGHT_SHADOWS ];\\n\\t\\tvarying vec4 vSpotShadowCoord[ NUM_SPOT_LIGHT_SHADOWS ];\\n\\n\\t\\tstruct SpotLightShadow {\\n\\t\\t\\tfloat shadowBias;\\n\\t\\t\\tfloat shadowNormalBias;\\n\\t\\t\\tfloat shadowRadius;\\n\\t\\t\\tvec2 shadowMapSize;\\n\\t\\t};\\n\\n\\t\\tuniform SpotLightShadow spotLightShadows[ NUM_SPOT_LIGHT_SHADOWS ];\\n\\n\\t#endif\\n\\n\\t#if NUM_POINT_LIGHT_SHADOWS > 0\\n\\n\\t\\tuniform sampler2D pointShadowMap[ NUM_POINT_LIGHT_SHADOWS ];\\n\\t\\tvarying vec4 vPointShadowCoord[ NUM_POINT_LIGHT_SHADOWS ];\\n\\n\\t\\tstruct PointLightShadow {\\n\\t\\t\\tfloat shadowBias;\\n\\t\\t\\tfloat shadowNormalBias;\\n\\t\\t\\tfloat shadowRadius;\\n\\t\\t\\tvec2 shadowMapSize;\\n\\t\\t\\tfloat shadowCameraNear;\\n\\t\\t\\tfloat shadowCameraFar;\\n\\t\\t};\\n\\n\\t\\tuniform PointLightShadow pointLightShadows[ NUM_POINT_LIGHT_SHADOWS ];\\n\\n\\t#endif\\n\\n\\t/*\\n\\t#if NUM_RECT_AREA_LIGHTS > 0\\n\\n\\t\\t// TODO (abelnation): create uniforms for area light shadows\\n\\n\\t#endif\\n\\t*/\\n\\n\\tfloat texture2DCompare( sampler2D depths, vec2 uv, float compare ) {\\n\\n\\t\\treturn step( compare, unpackRGBAToDepth( texture2D( depths, uv ) ) );\\n\\n\\t}\\n\\n\\tvec2 texture2DDistribution( sampler2D shadow, vec2 uv ) {\\n\\n\\t\\treturn unpackRGBATo2Half( texture2D( shadow, uv ) );\\n\\n\\t}\\n\\n\\tfloat VSMShadow (sampler2D shadow, vec2 uv, float compare ){\\n\\n\\t\\tfloat occlusion = 1.0;\\n\\n\\t\\tvec2 distribution = texture2DDistribution( shadow, uv );\\n\\n\\t\\tfloat hard_shadow = step( compare , distribution.x ); // Hard Shadow\\n\\n\\t\\tif (hard_shadow != 1.0 ) {\\n\\n\\t\\t\\tfloat distance = compare - distribution.x ;\\n\\t\\t\\tfloat variance = max( 0.00000, distribution.y * distribution.y );\\n\\t\\t\\tfloat softness_probability = variance / (variance + distance * distance ); // Chebeyshevs inequality\\n\\t\\t\\tsoftness_probability = clamp( ( softness_probability - 0.3 ) / ( 0.95 - 0.3 ), 0.0, 1.0 ); // 0.3 reduces light bleed\\n\\t\\t\\tocclusion = clamp( max( hard_shadow, softness_probability ), 0.0, 1.0 );\\n\\n\\t\\t}\\n\\t\\treturn occlusion;\\n\\n\\t}\\n\\n\\tfloat getShadow( sampler2D shadowMap, vec2 shadowMapSize, float shadowBias, float shadowRadius, vec4 shadowCoord ) {\\n\\n\\t\\tfloat shadow = 1.0;\\n\\n\\t\\tshadowCoord.xyz /= shadowCoord.w;\\n\\t\\tshadowCoord.z += shadowBias;\\n\\n\\t\\t// if ( something && something ) breaks ATI OpenGL shader compiler\\n\\t\\t// if ( all( something, something ) ) using this instead\\n\\n\\t\\tbvec4 inFrustumVec = bvec4 ( shadowCoord.x >= 0.0, shadowCoord.x <= 1.0, shadowCoord.y >= 0.0, shadowCoord.y <= 1.0 );\\n\\t\\tbool inFrustum = all( inFrustumVec );\\n\\n\\t\\tbvec2 frustumTestVec = bvec2( inFrustum, shadowCoord.z <= 1.0 );\\n\\n\\t\\tbool frustumTest = all( frustumTestVec );\\n\\n\\t\\tif ( frustumTest ) {\\n\\n\\t\\t#if defined( SHADOWMAP_TYPE_PCF )\\n\\n\\t\\t\\tvec2 texelSize = vec2( 1.0 ) / shadowMapSize;\\n\\n\\t\\t\\tfloat dx0 = - texelSize.x * shadowRadius;\\n\\t\\t\\tfloat dy0 = - texelSize.y * shadowRadius;\\n\\t\\t\\tfloat dx1 = + texelSize.x * shadowRadius;\\n\\t\\t\\tfloat dy1 = + texelSize.y * shadowRadius;\\n\\t\\t\\tfloat dx2 = dx0 / 2.0;\\n\\t\\t\\tfloat dy2 = dy0 / 2.0;\\n\\t\\t\\tfloat dx3 = dx1 / 2.0;\\n\\t\\t\\tfloat dy3 = dy1 / 2.0;\\n\\n\\t\\t\\tshadow = (\\n\\t\\t\\t\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx0, dy0 ), shadowCoord.z ) +\\n\\t\\t\\t\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( 0.0, dy0 ), shadowCoord.z ) +\\n\\t\\t\\t\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx1, dy0 ), shadowCoord.z ) +\\n\\t\\t\\t\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx2, dy2 ), shadowCoord.z ) +\\n\\t\\t\\t\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( 0.0, dy2 ), shadowCoord.z ) +\\n\\t\\t\\t\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx3, dy2 ), shadowCoord.z ) +\\n\\t\\t\\t\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx0, 0.0 ), shadowCoord.z ) +\\n\\t\\t\\t\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx2, 0.0 ), shadowCoord.z ) +\\n\\t\\t\\t\\ttexture2DCompare( shadowMap, shadowCoord.xy, shadowCoord.z ) +\\n\\t\\t\\t\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx3, 0.0 ), shadowCoord.z ) +\\n\\t\\t\\t\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx1, 0.0 ), shadowCoord.z ) +\\n\\t\\t\\t\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx2, dy3 ), shadowCoord.z ) +\\n\\t\\t\\t\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( 0.0, dy3 ), shadowCoord.z ) +\\n\\t\\t\\t\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx3, dy3 ), shadowCoord.z ) +\\n\\t\\t\\t\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx0, dy1 ), shadowCoord.z ) +\\n\\t\\t\\t\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( 0.0, dy1 ), shadowCoord.z ) +\\n\\t\\t\\t\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx1, dy1 ), shadowCoord.z )\\n\\t\\t\\t) * ( 1.0 / 17.0 );\\n\\n\\t\\t#elif defined( SHADOWMAP_TYPE_PCF_SOFT )\\n\\n\\t\\t\\tvec2 texelSize = vec2( 1.0 ) / shadowMapSize;\\n\\t\\t\\tfloat dx = texelSize.x;\\n\\t\\t\\tfloat dy = texelSize.y;\\n\\n\\t\\t\\tvec2 uv = shadowCoord.xy;\\n\\t\\t\\tvec2 f = fract( uv * shadowMapSize + 0.5 );\\n\\t\\t\\tuv -= f * texelSize;\\n\\n\\t\\t\\tshadow = (\\n\\t\\t\\t\\ttexture2DCompare( shadowMap, uv, shadowCoord.z ) +\\n\\t\\t\\t\\ttexture2DCompare( shadowMap, uv + vec2( dx, 0.0 ), shadowCoord.z ) +\\n\\t\\t\\t\\ttexture2DCompare( shadowMap, uv + vec2( 0.0, dy ), shadowCoord.z ) +\\n\\t\\t\\t\\ttexture2DCompare( shadowMap, uv + texelSize, shadowCoord.z ) +\\n\\t\\t\\t\\tmix( texture2DCompare( shadowMap, uv + vec2( -dx, 0.0 ), shadowCoord.z ), \\n\\t\\t\\t\\t\\t texture2DCompare( shadowMap, uv + vec2( 2.0 * dx, 0.0 ), shadowCoord.z ),\\n\\t\\t\\t\\t\\t f.x ) +\\n\\t\\t\\t\\tmix( texture2DCompare( shadowMap, uv + vec2( -dx, dy ), shadowCoord.z ), \\n\\t\\t\\t\\t\\t texture2DCompare( shadowMap, uv + vec2( 2.0 * dx, dy ), shadowCoord.z ),\\n\\t\\t\\t\\t\\t f.x ) +\\n\\t\\t\\t\\tmix( texture2DCompare( shadowMap, uv + vec2( 0.0, -dy ), shadowCoord.z ), \\n\\t\\t\\t\\t\\t texture2DCompare( shadowMap, uv + vec2( 0.0, 2.0 * dy ), shadowCoord.z ),\\n\\t\\t\\t\\t\\t f.y ) +\\n\\t\\t\\t\\tmix( texture2DCompare( shadowMap, uv + vec2( dx, -dy ), shadowCoord.z ), \\n\\t\\t\\t\\t\\t texture2DCompare( shadowMap, uv + vec2( dx, 2.0 * dy ), shadowCoord.z ),\\n\\t\\t\\t\\t\\t f.y ) +\\n\\t\\t\\t\\tmix( mix( texture2DCompare( shadowMap, uv + vec2( -dx, -dy ), shadowCoord.z ), \\n\\t\\t\\t\\t\\t\\t texture2DCompare( shadowMap, uv + vec2( 2.0 * dx, -dy ), shadowCoord.z ),\\n\\t\\t\\t\\t\\t\\t f.x ),\\n\\t\\t\\t\\t\\t mix( texture2DCompare( shadowMap, uv + vec2( -dx, 2.0 * dy ), shadowCoord.z ), \\n\\t\\t\\t\\t\\t\\t texture2DCompare( shadowMap, uv + vec2( 2.0 * dx, 2.0 * dy ), shadowCoord.z ),\\n\\t\\t\\t\\t\\t\\t f.x ),\\n\\t\\t\\t\\t\\t f.y )\\n\\t\\t\\t) * ( 1.0 / 9.0 );\\n\\n\\t\\t#elif defined( SHADOWMAP_TYPE_VSM )\\n\\n\\t\\t\\tshadow = VSMShadow( shadowMap, shadowCoord.xy, shadowCoord.z );\\n\\n\\t\\t#else // no percentage-closer filtering:\\n\\n\\t\\t\\tshadow = texture2DCompare( shadowMap, shadowCoord.xy, shadowCoord.z );\\n\\n\\t\\t#endif\\n\\n\\t\\t}\\n\\n\\t\\treturn shadow;\\n\\n\\t}\\n\\n\\t// cubeToUV() maps a 3D direction vector suitable for cube texture mapping to a 2D\\n\\t// vector suitable for 2D texture mapping. This code uses the following layout for the\\n\\t// 2D texture:\\n\\t//\\n\\t// xzXZ\\n\\t// y Y\\n\\t//\\n\\t// Y - Positive y direction\\n\\t// y - Negative y direction\\n\\t// X - Positive x direction\\n\\t// x - Negative x direction\\n\\t// Z - Positive z direction\\n\\t// z - Negative z direction\\n\\t//\\n\\t// Source and test bed:\\n\\t// https://gist.github.com/tschw/da10c43c467ce8afd0c4\\n\\n\\tvec2 cubeToUV( vec3 v, float texelSizeY ) {\\n\\n\\t\\t// Number of texels to avoid at the edge of each square\\n\\n\\t\\tvec3 absV = abs( v );\\n\\n\\t\\t// Intersect unit cube\\n\\n\\t\\tfloat scaleToCube = 1.0 / max( absV.x, max( absV.y, absV.z ) );\\n\\t\\tabsV *= scaleToCube;\\n\\n\\t\\t// Apply scale to avoid seams\\n\\n\\t\\t// two texels less per square (one texel will do for NEAREST)\\n\\t\\tv *= scaleToCube * ( 1.0 - 2.0 * texelSizeY );\\n\\n\\t\\t// Unwrap\\n\\n\\t\\t// space: -1 ... 1 range for each square\\n\\t\\t//\\n\\t\\t// #X##\\t\\tdim := ( 4 , 2 )\\n\\t\\t// # #\\t\\tcenter := ( 1 , 1 )\\n\\n\\t\\tvec2 planar = v.xy;\\n\\n\\t\\tfloat almostATexel = 1.5 * texelSizeY;\\n\\t\\tfloat almostOne = 1.0 - almostATexel;\\n\\n\\t\\tif ( absV.z >= almostOne ) {\\n\\n\\t\\t\\tif ( v.z > 0.0 )\\n\\t\\t\\t\\tplanar.x = 4.0 - v.x;\\n\\n\\t\\t} else if ( absV.x >= almostOne ) {\\n\\n\\t\\t\\tfloat signX = sign( v.x );\\n\\t\\t\\tplanar.x = v.z * signX + 2.0 * signX;\\n\\n\\t\\t} else if ( absV.y >= almostOne ) {\\n\\n\\t\\t\\tfloat signY = sign( v.y );\\n\\t\\t\\tplanar.x = v.x + 2.0 * signY + 2.0;\\n\\t\\t\\tplanar.y = v.z * signY - 2.0;\\n\\n\\t\\t}\\n\\n\\t\\t// Transform to UV space\\n\\n\\t\\t// scale := 0.5 / dim\\n\\t\\t// translate := ( center + 0.5 ) / dim\\n\\t\\treturn vec2( 0.125, 0.25 ) * planar + vec2( 0.375, 0.75 );\\n\\n\\t}\\n\\n\\tfloat getPointShadow( sampler2D shadowMap, vec2 shadowMapSize, float shadowBias, float shadowRadius, vec4 shadowCoord, float shadowCameraNear, float shadowCameraFar ) {\\n\\n\\t\\tvec2 texelSize = vec2( 1.0 ) / ( shadowMapSize * vec2( 4.0, 2.0 ) );\\n\\n\\t\\t// for point lights, the uniform @vShadowCoord is re-purposed to hold\\n\\t\\t// the vector from the light to the world-space position of the fragment.\\n\\t\\tvec3 lightToPosition = shadowCoord.xyz;\\n\\n\\t\\t// dp = normalized distance from light to fragment position\\n\\t\\tfloat dp = ( length( lightToPosition ) - shadowCameraNear ) / ( shadowCameraFar - shadowCameraNear ); // need to clamp?\\n\\t\\tdp += shadowBias;\\n\\n\\t\\t// bd3D = base direction 3D\\n\\t\\tvec3 bd3D = normalize( lightToPosition );\\n\\n\\t\\t#if defined( SHADOWMAP_TYPE_PCF ) || defined( SHADOWMAP_TYPE_PCF_SOFT ) || defined( SHADOWMAP_TYPE_VSM )\\n\\n\\t\\t\\tvec2 offset = vec2( - 1, 1 ) * shadowRadius * texelSize.y;\\n\\n\\t\\t\\treturn (\\n\\t\\t\\t\\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.xyy, texelSize.y ), dp ) +\\n\\t\\t\\t\\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.yyy, texelSize.y ), dp ) +\\n\\t\\t\\t\\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.xyx, texelSize.y ), dp ) +\\n\\t\\t\\t\\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.yyx, texelSize.y ), dp ) +\\n\\t\\t\\t\\ttexture2DCompare( shadowMap, cubeToUV( bd3D, texelSize.y ), dp ) +\\n\\t\\t\\t\\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.xxy, texelSize.y ), dp ) +\\n\\t\\t\\t\\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.yxy, texelSize.y ), dp ) +\\n\\t\\t\\t\\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.xxx, texelSize.y ), dp ) +\\n\\t\\t\\t\\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.yxx, texelSize.y ), dp )\\n\\t\\t\\t) * ( 1.0 / 9.0 );\\n\\n\\t\\t#else // no percentage-closer filtering\\n\\n\\t\\t\\treturn texture2DCompare( shadowMap, cubeToUV( bd3D, texelSize.y ), dp );\\n\\n\\t\\t#endif\\n\\n\\t}\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/shadowmap_pars_vertex.glsl.js\\nvar shadowmap_pars_vertex_glsl_default = `\\n#ifdef USE_SHADOWMAP\\n\\n\\t#if NUM_DIR_LIGHT_SHADOWS > 0\\n\\n\\t\\tuniform mat4 directionalShadowMatrix[ NUM_DIR_LIGHT_SHADOWS ];\\n\\t\\tvarying vec4 vDirectionalShadowCoord[ NUM_DIR_LIGHT_SHADOWS ];\\n\\n\\t\\tstruct DirectionalLightShadow {\\n\\t\\t\\tfloat shadowBias;\\n\\t\\t\\tfloat shadowNormalBias;\\n\\t\\t\\tfloat shadowRadius;\\n\\t\\t\\tvec2 shadowMapSize;\\n\\t\\t};\\n\\n\\t\\tuniform DirectionalLightShadow directionalLightShadows[ NUM_DIR_LIGHT_SHADOWS ];\\n\\n\\t#endif\\n\\n\\t#if NUM_SPOT_LIGHT_SHADOWS > 0\\n\\n\\t\\tuniform mat4 spotShadowMatrix[ NUM_SPOT_LIGHT_SHADOWS ];\\n\\t\\tvarying vec4 vSpotShadowCoord[ NUM_SPOT_LIGHT_SHADOWS ];\\n\\n\\t\\tstruct SpotLightShadow {\\n\\t\\t\\tfloat shadowBias;\\n\\t\\t\\tfloat shadowNormalBias;\\n\\t\\t\\tfloat shadowRadius;\\n\\t\\t\\tvec2 shadowMapSize;\\n\\t\\t};\\n\\n\\t\\tuniform SpotLightShadow spotLightShadows[ NUM_SPOT_LIGHT_SHADOWS ];\\n\\n\\t#endif\\n\\n\\t#if NUM_POINT_LIGHT_SHADOWS > 0\\n\\n\\t\\tuniform mat4 pointShadowMatrix[ NUM_POINT_LIGHT_SHADOWS ];\\n\\t\\tvarying vec4 vPointShadowCoord[ NUM_POINT_LIGHT_SHADOWS ];\\n\\n\\t\\tstruct PointLightShadow {\\n\\t\\t\\tfloat shadowBias;\\n\\t\\t\\tfloat shadowNormalBias;\\n\\t\\t\\tfloat shadowRadius;\\n\\t\\t\\tvec2 shadowMapSize;\\n\\t\\t\\tfloat shadowCameraNear;\\n\\t\\t\\tfloat shadowCameraFar;\\n\\t\\t};\\n\\n\\t\\tuniform PointLightShadow pointLightShadows[ NUM_POINT_LIGHT_SHADOWS ];\\n\\n\\t#endif\\n\\n\\t/*\\n\\t#if NUM_RECT_AREA_LIGHTS > 0\\n\\n\\t\\t// TODO (abelnation): uniforms for area light shadows\\n\\n\\t#endif\\n\\t*/\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/shadowmap_vertex.glsl.js\\nvar shadowmap_vertex_glsl_default = `\\n#ifdef USE_SHADOWMAP\\n\\n\\t#if NUM_DIR_LIGHT_SHADOWS > 0 || NUM_SPOT_LIGHT_SHADOWS > 0 || NUM_POINT_LIGHT_SHADOWS > 0\\n\\n\\t\\t// Offsetting the position used for querying occlusion along the world normal can be used to reduce shadow acne.\\n\\t\\tvec3 shadowWorldNormal = inverseTransformDirection( transformedNormal, viewMatrix );\\n\\t\\tvec4 shadowWorldPosition;\\n\\n\\t#endif\\n\\n\\t#if NUM_DIR_LIGHT_SHADOWS > 0\\n\\n\\t#pragma unroll_loop_start\\n\\tfor ( int i = 0; i < NUM_DIR_LIGHT_SHADOWS; i ++ ) {\\n\\n\\t\\tshadowWorldPosition = worldPosition + vec4( shadowWorldNormal * directionalLightShadows[ i ].shadowNormalBias, 0 );\\n\\t\\tvDirectionalShadowCoord[ i ] = directionalShadowMatrix[ i ] * shadowWorldPosition;\\n\\n\\t}\\n\\t#pragma unroll_loop_end\\n\\n\\t#endif\\n\\n\\t#if NUM_SPOT_LIGHT_SHADOWS > 0\\n\\n\\t#pragma unroll_loop_start\\n\\tfor ( int i = 0; i < NUM_SPOT_LIGHT_SHADOWS; i ++ ) {\\n\\n\\t\\tshadowWorldPosition = worldPosition + vec4( shadowWorldNormal * spotLightShadows[ i ].shadowNormalBias, 0 );\\n\\t\\tvSpotShadowCoord[ i ] = spotShadowMatrix[ i ] * shadowWorldPosition;\\n\\n\\t}\\n\\t#pragma unroll_loop_end\\n\\n\\t#endif\\n\\n\\t#if NUM_POINT_LIGHT_SHADOWS > 0\\n\\n\\t#pragma unroll_loop_start\\n\\tfor ( int i = 0; i < NUM_POINT_LIGHT_SHADOWS; i ++ ) {\\n\\n\\t\\tshadowWorldPosition = worldPosition + vec4( shadowWorldNormal * pointLightShadows[ i ].shadowNormalBias, 0 );\\n\\t\\tvPointShadowCoord[ i ] = pointShadowMatrix[ i ] * shadowWorldPosition;\\n\\n\\t}\\n\\t#pragma unroll_loop_end\\n\\n\\t#endif\\n\\n\\t/*\\n\\t#if NUM_RECT_AREA_LIGHTS > 0\\n\\n\\t\\t// TODO (abelnation): update vAreaShadowCoord with area light info\\n\\n\\t#endif\\n\\t*/\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/shadowmask_pars_fragment.glsl.js\\nvar shadowmask_pars_fragment_glsl_default = `\\nfloat getShadowMask() {\\n\\n\\tfloat shadow = 1.0;\\n\\n\\t#ifdef USE_SHADOWMAP\\n\\n\\t#if NUM_DIR_LIGHT_SHADOWS > 0\\n\\n\\tDirectionalLightShadow directionalLight;\\n\\n\\t#pragma unroll_loop_start\\n\\tfor ( int i = 0; i < NUM_DIR_LIGHT_SHADOWS; i ++ ) {\\n\\n\\t\\tdirectionalLight = directionalLightShadows[ i ];\\n\\t\\tshadow *= receiveShadow ? getShadow( directionalShadowMap[ i ], directionalLight.shadowMapSize, directionalLight.shadowBias, directionalLight.shadowRadius, vDirectionalShadowCoord[ i ] ) : 1.0;\\n\\n\\t}\\n\\t#pragma unroll_loop_end\\n\\n\\t#endif\\n\\n\\t#if NUM_SPOT_LIGHT_SHADOWS > 0\\n\\n\\tSpotLightShadow spotLight;\\n\\n\\t#pragma unroll_loop_start\\n\\tfor ( int i = 0; i < NUM_SPOT_LIGHT_SHADOWS; i ++ ) {\\n\\n\\t\\tspotLight = spotLightShadows[ i ];\\n\\t\\tshadow *= receiveShadow ? getShadow( spotShadowMap[ i ], spotLight.shadowMapSize, spotLight.shadowBias, spotLight.shadowRadius, vSpotShadowCoord[ i ] ) : 1.0;\\n\\n\\t}\\n\\t#pragma unroll_loop_end\\n\\n\\t#endif\\n\\n\\t#if NUM_POINT_LIGHT_SHADOWS > 0\\n\\n\\tPointLightShadow pointLight;\\n\\n\\t#pragma unroll_loop_start\\n\\tfor ( int i = 0; i < NUM_POINT_LIGHT_SHADOWS; i ++ ) {\\n\\n\\t\\tpointLight = pointLightShadows[ i ];\\n\\t\\tshadow *= receiveShadow ? getPointShadow( pointShadowMap[ i ], pointLight.shadowMapSize, pointLight.shadowBias, pointLight.shadowRadius, vPointShadowCoord[ i ], pointLight.shadowCameraNear, pointLight.shadowCameraFar ) : 1.0;\\n\\n\\t}\\n\\t#pragma unroll_loop_end\\n\\n\\t#endif\\n\\n\\t/*\\n\\t#if NUM_RECT_AREA_LIGHTS > 0\\n\\n\\t\\t// TODO (abelnation): update shadow for Area light\\n\\n\\t#endif\\n\\t*/\\n\\n\\t#endif\\n\\n\\treturn shadow;\\n\\n}\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/skinbase_vertex.glsl.js\\nvar skinbase_vertex_glsl_default = `\\n#ifdef USE_SKINNING\\n\\n\\tmat4 boneMatX = getBoneMatrix( skinIndex.x );\\n\\tmat4 boneMatY = getBoneMatrix( skinIndex.y );\\n\\tmat4 boneMatZ = getBoneMatrix( skinIndex.z );\\n\\tmat4 boneMatW = getBoneMatrix( skinIndex.w );\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/skinning_pars_vertex.glsl.js\\nvar skinning_pars_vertex_glsl_default = `\\n#ifdef USE_SKINNING\\n\\n\\tuniform mat4 bindMatrix;\\n\\tuniform mat4 bindMatrixInverse;\\n\\n\\t#ifdef BONE_TEXTURE\\n\\n\\t\\tuniform highp sampler2D boneTexture;\\n\\t\\tuniform int boneTextureSize;\\n\\n\\t\\tmat4 getBoneMatrix( const in float i ) {\\n\\n\\t\\t\\tfloat j = i * 4.0;\\n\\t\\t\\tfloat x = mod( j, float( boneTextureSize ) );\\n\\t\\t\\tfloat y = floor( j / float( boneTextureSize ) );\\n\\n\\t\\t\\tfloat dx = 1.0 / float( boneTextureSize );\\n\\t\\t\\tfloat dy = 1.0 / float( boneTextureSize );\\n\\n\\t\\t\\ty = dy * ( y + 0.5 );\\n\\n\\t\\t\\tvec4 v1 = texture2D( boneTexture, vec2( dx * ( x + 0.5 ), y ) );\\n\\t\\t\\tvec4 v2 = texture2D( boneTexture, vec2( dx * ( x + 1.5 ), y ) );\\n\\t\\t\\tvec4 v3 = texture2D( boneTexture, vec2( dx * ( x + 2.5 ), y ) );\\n\\t\\t\\tvec4 v4 = texture2D( boneTexture, vec2( dx * ( x + 3.5 ), y ) );\\n\\n\\t\\t\\tmat4 bone = mat4( v1, v2, v3, v4 );\\n\\n\\t\\t\\treturn bone;\\n\\n\\t\\t}\\n\\n\\t#else\\n\\n\\t\\tuniform mat4 boneMatrices[ MAX_BONES ];\\n\\n\\t\\tmat4 getBoneMatrix( const in float i ) {\\n\\n\\t\\t\\tmat4 bone = boneMatrices[ int(i) ];\\n\\t\\t\\treturn bone;\\n\\n\\t\\t}\\n\\n\\t#endif\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/skinning_vertex.glsl.js\\nvar skinning_vertex_glsl_default = `\\n#ifdef USE_SKINNING\\n\\n\\tvec4 skinVertex = bindMatrix * vec4( transformed, 1.0 );\\n\\n\\tvec4 skinned = vec4( 0.0 );\\n\\tskinned += boneMatX * skinVertex * skinWeight.x;\\n\\tskinned += boneMatY * skinVertex * skinWeight.y;\\n\\tskinned += boneMatZ * skinVertex * skinWeight.z;\\n\\tskinned += boneMatW * skinVertex * skinWeight.w;\\n\\n\\ttransformed = ( bindMatrixInverse * skinned ).xyz;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/skinnormal_vertex.glsl.js\\nvar skinnormal_vertex_glsl_default = `\\n#ifdef USE_SKINNING\\n\\n\\tmat4 skinMatrix = mat4( 0.0 );\\n\\tskinMatrix += skinWeight.x * boneMatX;\\n\\tskinMatrix += skinWeight.y * boneMatY;\\n\\tskinMatrix += skinWeight.z * boneMatZ;\\n\\tskinMatrix += skinWeight.w * boneMatW;\\n\\tskinMatrix = bindMatrixInverse * skinMatrix * bindMatrix;\\n\\n\\tobjectNormal = vec4( skinMatrix * vec4( objectNormal, 0.0 ) ).xyz;\\n\\n\\t#ifdef USE_TANGENT\\n\\n\\t\\tobjectTangent = vec4( skinMatrix * vec4( objectTangent, 0.0 ) ).xyz;\\n\\n\\t#endif\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/specularmap_fragment.glsl.js\\nvar specularmap_fragment_glsl_default = `\\nfloat specularStrength;\\n\\n#ifdef USE_SPECULARMAP\\n\\n\\tvec4 texelSpecular = texture2D( specularMap, vUv );\\n\\tspecularStrength = texelSpecular.r;\\n\\n#else\\n\\n\\tspecularStrength = 1.0;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/specularmap_pars_fragment.glsl.js\\nvar specularmap_pars_fragment_glsl_default = `\\n#ifdef USE_SPECULARMAP\\n\\n\\tuniform sampler2D specularMap;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/tonemapping_fragment.glsl.js\\nvar tonemapping_fragment_glsl_default = `\\n#if defined( TONE_MAPPING )\\n\\n\\tgl_FragColor.rgb = toneMapping( gl_FragColor.rgb );\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/tonemapping_pars_fragment.glsl.js\\nvar tonemapping_pars_fragment_glsl_default = `\\n#ifndef saturate\\n// may have defined saturate() already\\n#define saturate( a ) clamp( a, 0.0, 1.0 )\\n#endif\\n\\nuniform float toneMappingExposure;\\n\\n// exposure only\\nvec3 LinearToneMapping( vec3 color ) {\\n\\n\\treturn toneMappingExposure * color;\\n\\n}\\n\\n// source: https://www.cs.utah.edu/~reinhard/cdrom/\\nvec3 ReinhardToneMapping( vec3 color ) {\\n\\n\\tcolor *= toneMappingExposure;\\n\\treturn saturate( color / ( vec3( 1.0 ) + color ) );\\n\\n}\\n\\n// source: http://filmicworlds.com/blog/filmic-tonemapping-operators/\\nvec3 OptimizedCineonToneMapping( vec3 color ) {\\n\\n\\t// optimized filmic operator by Jim Hejl and Richard Burgess-Dawson\\n\\tcolor *= toneMappingExposure;\\n\\tcolor = max( vec3( 0.0 ), color - 0.004 );\\n\\treturn pow( ( color * ( 6.2 * color + 0.5 ) ) / ( color * ( 6.2 * color + 1.7 ) + 0.06 ), vec3( 2.2 ) );\\n\\n}\\n\\n// source: https://github.com/selfshadow/ltc_code/blob/master/webgl/shaders/ltc/ltc_blit.fs\\nvec3 RRTAndODTFit( vec3 v ) {\\n\\n\\tvec3 a = v * ( v + 0.0245786 ) - 0.000090537;\\n\\tvec3 b = v * ( 0.983729 * v + 0.4329510 ) + 0.238081;\\n\\treturn a / b;\\n\\n}\\n\\n// this implementation of ACES is modified to accommodate a brighter viewing environment.\\n// the scale factor of 1/0.6 is subjective. see discussion in #19621.\\n\\nvec3 ACESFilmicToneMapping( vec3 color ) {\\n\\n\\t// sRGB => XYZ => D65_2_D60 => AP1 => RRT_SAT\\n\\tconst mat3 ACESInputMat = mat3(\\n\\t\\tvec3( 0.59719, 0.07600, 0.02840 ), // transposed from source\\n\\t\\tvec3( 0.35458, 0.90834, 0.13383 ),\\n\\t\\tvec3( 0.04823, 0.01566, 0.83777 )\\n\\t);\\n\\n\\t// ODT_SAT => XYZ => D60_2_D65 => sRGB\\n\\tconst mat3 ACESOutputMat = mat3(\\n\\t\\tvec3( 1.60475, -0.10208, -0.00327 ), // transposed from source\\n\\t\\tvec3( -0.53108, 1.10813, -0.07276 ),\\n\\t\\tvec3( -0.07367, -0.00605, 1.07602 )\\n\\t);\\n\\n\\tcolor *= toneMappingExposure / 0.6;\\n\\n\\tcolor = ACESInputMat * color;\\n\\n\\t// Apply RRT and ODT\\n\\tcolor = RRTAndODTFit( color );\\n\\n\\tcolor = ACESOutputMat * color;\\n\\n\\t// Clamp to [0, 1]\\n\\treturn saturate( color );\\n\\n}\\n\\nvec3 CustomToneMapping( vec3 color ) { return color; }\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/transmission_fragment.glsl.js\\nvar transmission_fragment_glsl_default = `\\n#ifdef USE_TRANSMISSION\\n\\n\\tfloat transmissionAlpha = 1.0;\\n\\tfloat transmissionFactor = transmission;\\n\\tfloat thicknessFactor = thickness;\\n\\n\\t#ifdef USE_TRANSMISSIONMAP\\n\\n\\t\\ttransmissionFactor *= texture2D( transmissionMap, vUv ).r;\\n\\n\\t#endif\\n\\n\\t#ifdef USE_THICKNESSMAP\\n\\n\\t\\tthicknessFactor *= texture2D( thicknessMap, vUv ).g;\\n\\n\\t#endif\\n\\n\\tvec3 pos = vWorldPosition;\\n\\tvec3 v = normalize( cameraPosition - pos );\\n\\tvec3 n = inverseTransformDirection( normal, viewMatrix );\\n\\n\\tvec4 transmission = getIBLVolumeRefraction(\\n\\t\\tn, v, roughnessFactor, material.diffuseColor, material.specularColor, material.specularF90,\\n\\t\\tpos, modelMatrix, viewMatrix, projectionMatrix, ior, thicknessFactor,\\n\\t\\tattenuationTint, attenuationDistance );\\n\\n\\ttotalDiffuse = mix( totalDiffuse, transmission.rgb, transmissionFactor );\\n\\ttransmissionAlpha = mix( transmissionAlpha, transmission.a, transmissionFactor );\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/transmission_pars_fragment.glsl.js\\nvar transmission_pars_fragment_glsl_default = `\\n#ifdef USE_TRANSMISSION\\n\\n\\t// Transmission code is based on glTF-Sampler-Viewer\\n\\t// https://github.com/KhronosGroup/glTF-Sample-Viewer\\n\\n\\tuniform float transmission;\\n\\tuniform float thickness;\\n\\tuniform float attenuationDistance;\\n\\tuniform vec3 attenuationTint;\\n\\n\\t#ifdef USE_TRANSMISSIONMAP\\n\\n\\t\\tuniform sampler2D transmissionMap;\\n\\n\\t#endif\\n\\n\\t#ifdef USE_THICKNESSMAP\\n\\n\\t\\tuniform sampler2D thicknessMap;\\n\\n\\t#endif\\n\\n\\tuniform vec2 transmissionSamplerSize;\\n\\tuniform sampler2D transmissionSamplerMap;\\n\\n\\tuniform mat4 modelMatrix;\\n\\tuniform mat4 projectionMatrix;\\n\\n\\tvarying vec3 vWorldPosition;\\n\\n\\tvec3 getVolumeTransmissionRay( vec3 n, vec3 v, float thickness, float ior, mat4 modelMatrix ) {\\n\\n\\t\\t// Direction of refracted light.\\n\\t\\tvec3 refractionVector = refract( - v, normalize( n ), 1.0 / ior );\\n\\n\\t\\t// Compute rotation-independant scaling of the model matrix.\\n\\t\\tvec3 modelScale;\\n\\t\\tmodelScale.x = length( vec3( modelMatrix[ 0 ].xyz ) );\\n\\t\\tmodelScale.y = length( vec3( modelMatrix[ 1 ].xyz ) );\\n\\t\\tmodelScale.z = length( vec3( modelMatrix[ 2 ].xyz ) );\\n\\n\\t\\t// The thickness is specified in local space.\\n\\t\\treturn normalize( refractionVector ) * thickness * modelScale;\\n\\n\\t}\\n\\n\\tfloat applyIorToRoughness( float roughness, float ior ) {\\n\\n\\t\\t// Scale roughness with IOR so that an IOR of 1.0 results in no microfacet refraction and\\n\\t\\t// an IOR of 1.5 results in the default amount of microfacet refraction.\\n\\t\\treturn roughness * clamp( ior * 2.0 - 2.0, 0.0, 1.0 );\\n\\n\\t}\\n\\n\\tvec4 getTransmissionSample( vec2 fragCoord, float roughness, float ior ) {\\n\\n\\t\\tfloat framebufferLod = log2( transmissionSamplerSize.x ) * applyIorToRoughness( roughness, ior );\\n\\n\\t\\t#ifdef TEXTURE_LOD_EXT\\n\\n\\t\\t\\treturn texture2DLodEXT( transmissionSamplerMap, fragCoord.xy, framebufferLod );\\n\\n\\t\\t#else\\n\\n\\t\\t\\treturn texture2D( transmissionSamplerMap, fragCoord.xy, framebufferLod );\\n\\n\\t\\t#endif\\n\\n\\t}\\n\\n\\tvec3 applyVolumeAttenuation( vec3 radiance, float transmissionDistance, vec3 attenuationColor, float attenuationDistance ) {\\n\\n\\t\\tif ( attenuationDistance == 0.0 ) {\\n\\n\\t\\t\\t// Attenuation distance is +\\\\u221E (which we indicate by zero), i.e. the transmitted color is not attenuated at all.\\n\\t\\t\\treturn radiance;\\n\\n\\t\\t} else {\\n\\n\\t\\t\\t// Compute light attenuation using Beer's law.\\n\\t\\t\\tvec3 attenuationCoefficient = -log( attenuationColor ) / attenuationDistance;\\n\\t\\t\\tvec3 transmittance = exp( - attenuationCoefficient * transmissionDistance ); // Beer's law\\n\\t\\t\\treturn transmittance * radiance;\\n\\n\\t\\t}\\n\\n\\t}\\n\\n\\tvec4 getIBLVolumeRefraction( vec3 n, vec3 v, float roughness, vec3 diffuseColor, vec3 specularColor, float specularF90,\\n\\t\\tvec3 position, mat4 modelMatrix, mat4 viewMatrix, mat4 projMatrix, float ior, float thickness,\\n\\t\\tvec3 attenuationColor, float attenuationDistance ) {\\n\\n\\t\\tvec3 transmissionRay = getVolumeTransmissionRay( n, v, thickness, ior, modelMatrix );\\n\\t\\tvec3 refractedRayExit = position + transmissionRay;\\n\\n\\t\\t// Project refracted vector on the framebuffer, while mapping to normalized device coordinates.\\n\\t\\tvec4 ndcPos = projMatrix * viewMatrix * vec4( refractedRayExit, 1.0 );\\n\\t\\tvec2 refractionCoords = ndcPos.xy / ndcPos.w;\\n\\t\\trefractionCoords += 1.0;\\n\\t\\trefractionCoords /= 2.0;\\n\\n\\t\\t// Sample framebuffer to get pixel the refracted ray hits.\\n\\t\\tvec4 transmittedLight = getTransmissionSample( refractionCoords, roughness, ior );\\n\\n\\t\\tvec3 attenuatedColor = applyVolumeAttenuation( transmittedLight.rgb, length( transmissionRay ), attenuationColor, attenuationDistance );\\n\\n\\t\\t// Get the specular component.\\n\\t\\tvec3 F = EnvironmentBRDF( n, v, specularColor, specularF90, roughness );\\n\\n\\t\\treturn vec4( ( 1.0 - F ) * attenuatedColor * diffuseColor, transmittedLight.a );\\n\\n\\t}\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/uv_pars_fragment.glsl.js\\nvar uv_pars_fragment_glsl_default = `\\n#if ( defined( USE_UV ) && ! defined( UVS_VERTEX_ONLY ) )\\n\\n\\tvarying vec2 vUv;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/uv_pars_vertex.glsl.js\\nvar uv_pars_vertex_glsl_default = `\\n#ifdef USE_UV\\n\\n\\t#ifdef UVS_VERTEX_ONLY\\n\\n\\t\\tvec2 vUv;\\n\\n\\t#else\\n\\n\\t\\tvarying vec2 vUv;\\n\\n\\t#endif\\n\\n\\tuniform mat3 uvTransform;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/uv_vertex.glsl.js\\nvar uv_vertex_glsl_default = `\\n#ifdef USE_UV\\n\\n\\tvUv = ( uvTransform * vec3( uv, 1 ) ).xy;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/uv2_pars_fragment.glsl.js\\nvar uv2_pars_fragment_glsl_default = `\\n#if defined( USE_LIGHTMAP ) || defined( USE_AOMAP )\\n\\n\\tvarying vec2 vUv2;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/uv2_pars_vertex.glsl.js\\nvar uv2_pars_vertex_glsl_default = `\\n#if defined( USE_LIGHTMAP ) || defined( USE_AOMAP )\\n\\n\\tattribute vec2 uv2;\\n\\tvarying vec2 vUv2;\\n\\n\\tuniform mat3 uv2Transform;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/uv2_vertex.glsl.js\\nvar uv2_vertex_glsl_default = `\\n#if defined( USE_LIGHTMAP ) || defined( USE_AOMAP )\\n\\n\\tvUv2 = ( uv2Transform * vec3( uv2, 1 ) ).xy;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/worldpos_vertex.glsl.js\\nvar worldpos_vertex_glsl_default = `\\n#if defined( USE_ENVMAP ) || defined( DISTANCE ) || defined ( USE_SHADOWMAP ) || defined ( USE_TRANSMISSION )\\n\\n\\tvec4 worldPosition = vec4( transformed, 1.0 );\\n\\n\\t#ifdef USE_INSTANCING\\n\\n\\t\\tworldPosition = instanceMatrix * worldPosition;\\n\\n\\t#endif\\n\\n\\tworldPosition = modelMatrix * worldPosition;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderLib/background.glsl.js\\nvar vertex = `\\nvarying vec2 vUv;\\nuniform mat3 uvTransform;\\n\\nvoid main() {\\n\\n\\tvUv = ( uvTransform * vec3( uv, 1 ) ).xy;\\n\\n\\tgl_Position = vec4( position.xy, 1.0, 1.0 );\\n\\n}\\n`;\\nvar fragment = `\\nuniform sampler2D t2D;\\n\\nvarying vec2 vUv;\\n\\nvoid main() {\\n\\n\\tvec4 texColor = texture2D( t2D, vUv );\\n\\n\\tgl_FragColor = mapTexelToLinear( texColor );\\n\\n\\t#include \\n\\t#include \\n\\n}\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderLib/cube.glsl.js\\nvar vertex2 = `\\nvarying vec3 vWorldDirection;\\n\\n#include \\n\\nvoid main() {\\n\\n\\tvWorldDirection = transformDirection( position, modelMatrix );\\n\\n\\t#include \\n\\t#include \\n\\n\\tgl_Position.z = gl_Position.w; // set z to camera.far\\n\\n}\\n`;\\nvar fragment2 = `\\n#include \\nuniform float opacity;\\n\\nvarying vec3 vWorldDirection;\\n\\n#include \\n\\nvoid main() {\\n\\n\\tvec3 vReflect = vWorldDirection;\\n\\t#include \\n\\n\\tgl_FragColor = envColor;\\n\\tgl_FragColor.a *= opacity;\\n\\n\\t#include \\n\\t#include \\n\\n}\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderLib/depth.glsl.js\\nvar vertex3 = `\\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n\\n// This is used for computing an equivalent of gl_FragCoord.z that is as high precision as possible.\\n// Some platforms compute gl_FragCoord at a lower precision which makes the manually computed value better for\\n// depth-based postprocessing effects. Reproduced on iPad with A10 processor / iPadOS 13.3.1.\\nvarying vec2 vHighPrecisionZW;\\n\\nvoid main() {\\n\\n\\t#include \\n\\n\\t#include \\n\\n\\t#ifdef USE_DISPLACEMENTMAP\\n\\n\\t\\t#include \\n\\t\\t#include \\n\\t\\t#include \\n\\n\\t#endif\\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n\\tvHighPrecisionZW = gl_Position.zw;\\n\\n}\\n`;\\nvar fragment3 = `\\n#if DEPTH_PACKING == 3200\\n\\n\\tuniform float opacity;\\n\\n#endif\\n\\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n\\nvarying vec2 vHighPrecisionZW;\\n\\nvoid main() {\\n\\n\\t#include \\n\\n\\tvec4 diffuseColor = vec4( 1.0 );\\n\\n\\t#if DEPTH_PACKING == 3200\\n\\n\\t\\tdiffuseColor.a = opacity;\\n\\n\\t#endif\\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\n\\t#include \\n\\n\\t// Higher precision equivalent of gl_FragCoord.z. This assumes depthRange has been left to its default values.\\n\\tfloat fragCoordZ = 0.5 * vHighPrecisionZW[0] / vHighPrecisionZW[1] + 0.5;\\n\\n\\t#if DEPTH_PACKING == 3200\\n\\n\\t\\tgl_FragColor = vec4( vec3( 1.0 - fragCoordZ ), opacity );\\n\\n\\t#elif DEPTH_PACKING == 3201\\n\\n\\t\\tgl_FragColor = packDepthToRGBA( fragCoordZ );\\n\\n\\t#endif\\n\\n}\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderLib/distanceRGBA.glsl.js\\nvar vertex4 = `\\n#define DISTANCE\\n\\nvarying vec3 vWorldPosition;\\n\\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n\\nvoid main() {\\n\\n\\t#include \\n\\n\\t#include \\n\\n\\t#ifdef USE_DISPLACEMENTMAP\\n\\n\\t\\t#include \\n\\t\\t#include \\n\\t\\t#include \\n\\n\\t#endif\\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n\\tvWorldPosition = worldPosition.xyz;\\n\\n}\\n`;\\nvar fragment4 = `\\n#define DISTANCE\\n\\nuniform vec3 referencePosition;\\nuniform float nearDistance;\\nuniform float farDistance;\\nvarying vec3 vWorldPosition;\\n\\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n\\nvoid main () {\\n\\n\\t#include \\n\\n\\tvec4 diffuseColor = vec4( 1.0 );\\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\n\\tfloat dist = length( vWorldPosition - referencePosition );\\n\\tdist = ( dist - nearDistance ) / ( farDistance - nearDistance );\\n\\tdist = saturate( dist ); // clamp to [ 0, 1 ]\\n\\n\\tgl_FragColor = packDepthToRGBA( dist );\\n\\n}\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderLib/equirect.glsl.js\\nvar vertex5 = `\\nvarying vec3 vWorldDirection;\\n\\n#include \\n\\nvoid main() {\\n\\n\\tvWorldDirection = transformDirection( position, modelMatrix );\\n\\n\\t#include \\n\\t#include \\n\\n}\\n`;\\nvar fragment5 = `\\nuniform sampler2D tEquirect;\\n\\nvarying vec3 vWorldDirection;\\n\\n#include \\n\\nvoid main() {\\n\\n\\tvec3 direction = normalize( vWorldDirection );\\n\\n\\tvec2 sampleUV = equirectUv( direction );\\n\\n\\tvec4 texColor = texture2D( tEquirect, sampleUV );\\n\\n\\tgl_FragColor = mapTexelToLinear( texColor );\\n\\n\\t#include \\n\\t#include \\n\\n}\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderLib/linedashed.glsl.js\\nvar vertex6 = `\\nuniform float scale;\\nattribute float lineDistance;\\n\\nvarying float vLineDistance;\\n\\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n\\nvoid main() {\\n\\n\\tvLineDistance = scale * lineDistance;\\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n}\\n`;\\nvar fragment6 = `\\nuniform vec3 diffuse;\\nuniform float opacity;\\n\\nuniform float dashSize;\\nuniform float totalSize;\\n\\nvarying float vLineDistance;\\n\\n#include \\n#include \\n#include \\n#include \\n#include \\n\\nvoid main() {\\n\\n\\t#include \\n\\n\\tif ( mod( vLineDistance, totalSize ) > dashSize ) {\\n\\n\\t\\tdiscard;\\n\\n\\t}\\n\\n\\tvec3 outgoingLight = vec3( 0.0 );\\n\\tvec4 diffuseColor = vec4( diffuse, opacity );\\n\\n\\t#include \\n\\t#include \\n\\n\\toutgoingLight = diffuseColor.rgb; // simple shader\\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n}\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderLib/meshbasic.glsl.js\\nvar vertex7 = `\\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n\\nvoid main() {\\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\n\\t#if defined ( USE_ENVMAP ) || defined ( USE_SKINNING )\\n\\n\\t\\t#include \\n\\t\\t#include \\n\\t\\t#include \\n\\t\\t#include \\n\\t\\t#include \\n\\n\\t#endif\\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\n}\\n`;\\nvar fragment7 = `\\nuniform vec3 diffuse;\\nuniform float opacity;\\n\\n#ifndef FLAT_SHADED\\n\\n\\tvarying vec3 vNormal;\\n\\n#endif\\n\\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n\\nvoid main() {\\n\\n\\t#include \\n\\n\\tvec4 diffuseColor = vec4( diffuse, opacity );\\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n\\tReflectedLight reflectedLight = ReflectedLight( vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ) );\\n\\n\\t// accumulation (baked indirect lighting only)\\n\\t#ifdef USE_LIGHTMAP\\n\\n\\t\\tvec4 lightMapTexel= texture2D( lightMap, vUv2 );\\n\\t\\treflectedLight.indirectDiffuse += lightMapTexelToLinear( lightMapTexel ).rgb * lightMapIntensity;\\n\\n\\t#else\\n\\n\\t\\treflectedLight.indirectDiffuse += vec3( 1.0 );\\n\\n\\t#endif\\n\\n\\t// modulation\\n\\t#include \\n\\n\\treflectedLight.indirectDiffuse *= diffuseColor.rgb;\\n\\n\\tvec3 outgoingLight = reflectedLight.indirectDiffuse;\\n\\n\\t#include \\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n}\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderLib/meshlambert.glsl.js\\nvar vertex8 = `\\n#define LAMBERT\\n\\nvarying vec3 vLightFront;\\nvarying vec3 vIndirectFront;\\n\\n#ifdef DOUBLE_SIDED\\n\\tvarying vec3 vLightBack;\\n\\tvarying vec3 vIndirectBack;\\n#endif\\n\\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n\\nvoid main() {\\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n}\\n`;\\nvar fragment8 = `\\nuniform vec3 diffuse;\\nuniform vec3 emissive;\\nuniform float opacity;\\n\\nvarying vec3 vLightFront;\\nvarying vec3 vIndirectFront;\\n\\n#ifdef DOUBLE_SIDED\\n\\tvarying vec3 vLightBack;\\n\\tvarying vec3 vIndirectBack;\\n#endif\\n\\n\\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n\\nvoid main() {\\n\\n\\t#include \\n\\n\\tvec4 diffuseColor = vec4( diffuse, opacity );\\n\\tReflectedLight reflectedLight = ReflectedLight( vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ) );\\n\\tvec3 totalEmissiveRadiance = emissive;\\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n\\t// accumulation\\n\\n\\t#ifdef DOUBLE_SIDED\\n\\n\\t\\treflectedLight.indirectDiffuse += ( gl_FrontFacing ) ? vIndirectFront : vIndirectBack;\\n\\n\\t#else\\n\\n\\t\\treflectedLight.indirectDiffuse += vIndirectFront;\\n\\n\\t#endif\\n\\n\\t#include \\n\\n\\treflectedLight.indirectDiffuse *= BRDF_Lambert( diffuseColor.rgb );\\n\\n\\t#ifdef DOUBLE_SIDED\\n\\n\\t\\treflectedLight.directDiffuse = ( gl_FrontFacing ) ? vLightFront : vLightBack;\\n\\n\\t#else\\n\\n\\t\\treflectedLight.directDiffuse = vLightFront;\\n\\n\\t#endif\\n\\n\\treflectedLight.directDiffuse *= BRDF_Lambert( diffuseColor.rgb ) * getShadowMask();\\n\\n\\t// modulation\\n\\n\\t#include \\n\\n\\tvec3 outgoingLight = reflectedLight.directDiffuse + reflectedLight.indirectDiffuse + totalEmissiveRadiance;\\n\\n\\t#include \\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n}\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderLib/meshmatcap.glsl.js\\nvar vertex9 = `\\n#define MATCAP\\n\\nvarying vec3 vViewPosition;\\n\\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n\\n#include \\n#include \\n\\nvoid main() {\\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\n\\tvViewPosition = - mvPosition.xyz;\\n\\n}\\n`;\\nvar fragment9 = `\\n#define MATCAP\\n\\nuniform vec3 diffuse;\\nuniform float opacity;\\nuniform sampler2D matcap;\\n\\nvarying vec3 vViewPosition;\\n\\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n\\nvoid main() {\\n\\n\\t#include \\n\\n\\tvec4 diffuseColor = vec4( diffuse, opacity );\\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n\\tvec3 viewDir = normalize( vViewPosition );\\n\\tvec3 x = normalize( vec3( viewDir.z, 0.0, - viewDir.x ) );\\n\\tvec3 y = cross( viewDir, x );\\n\\tvec2 uv = vec2( dot( x, normal ), dot( y, normal ) ) * 0.495 + 0.5; // 0.495 to remove artifacts caused by undersized matcap disks\\n\\n\\t#ifdef USE_MATCAP\\n\\n\\t\\tvec4 matcapColor = texture2D( matcap, uv );\\n\\t\\tmatcapColor = matcapTexelToLinear( matcapColor );\\n\\n\\t#else\\n\\n\\t\\tvec4 matcapColor = vec4( 1.0 );\\n\\n\\t#endif\\n\\n\\tvec3 outgoingLight = diffuseColor.rgb * matcapColor.rgb;\\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n}\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderLib/meshnormal.glsl.js\\nvar vertex10 = `\\n#define NORMAL\\n\\n#if defined( FLAT_SHADED ) || defined( USE_BUMPMAP ) || defined( TANGENTSPACE_NORMALMAP )\\n\\n\\tvarying vec3 vViewPosition;\\n\\n#endif\\n\\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n\\nvoid main() {\\n\\n\\t#include \\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n#if defined( FLAT_SHADED ) || defined( USE_BUMPMAP ) || defined( TANGENTSPACE_NORMALMAP )\\n\\n\\tvViewPosition = - mvPosition.xyz;\\n\\n#endif\\n\\n}\\n`;\\nvar fragment10 = `\\n#define NORMAL\\n\\nuniform float opacity;\\n\\n#if defined( FLAT_SHADED ) || defined( USE_BUMPMAP ) || defined( TANGENTSPACE_NORMALMAP )\\n\\n\\tvarying vec3 vViewPosition;\\n\\n#endif\\n\\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n\\nvoid main() {\\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n\\tgl_FragColor = vec4( packNormalToRGB( normal ), opacity );\\n\\n}\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderLib/meshphong.glsl.js\\nvar vertex11 = `\\n#define PHONG\\n\\nvarying vec3 vViewPosition;\\n\\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n\\nvoid main() {\\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n\\tvViewPosition = - mvPosition.xyz;\\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n}\\n`;\\nvar fragment11 = `\\n#define PHONG\\n\\nuniform vec3 diffuse;\\nuniform vec3 emissive;\\nuniform vec3 specular;\\nuniform float shininess;\\nuniform float opacity;\\n\\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n\\nvoid main() {\\n\\n\\t#include \\n\\n\\tvec4 diffuseColor = vec4( diffuse, opacity );\\n\\tReflectedLight reflectedLight = ReflectedLight( vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ) );\\n\\tvec3 totalEmissiveRadiance = emissive;\\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n\\t// accumulation\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n\\t// modulation\\n\\t#include \\n\\n\\tvec3 outgoingLight = reflectedLight.directDiffuse + reflectedLight.indirectDiffuse + reflectedLight.directSpecular + reflectedLight.indirectSpecular + totalEmissiveRadiance;\\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n}\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderLib/meshphysical.glsl.js\\nvar vertex12 = `\\n#define STANDARD\\n\\nvarying vec3 vViewPosition;\\n\\n#ifdef USE_TRANSMISSION\\n\\n\\tvarying vec3 vWorldPosition;\\n\\n#endif\\n\\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n\\nvoid main() {\\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n\\tvViewPosition = - mvPosition.xyz;\\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\n#ifdef USE_TRANSMISSION\\n\\n\\tvWorldPosition = worldPosition.xyz;\\n\\n#endif\\n}\\n`;\\nvar fragment12 = `\\n#define STANDARD\\n\\n#ifdef PHYSICAL\\n\\t#define IOR\\n\\t#define SPECULAR\\n#endif\\n\\nuniform vec3 diffuse;\\nuniform vec3 emissive;\\nuniform float roughness;\\nuniform float metalness;\\nuniform float opacity;\\n\\n#ifdef IOR\\n\\tuniform float ior;\\n#endif\\n\\n#ifdef SPECULAR\\n\\tuniform float specularIntensity;\\n\\tuniform vec3 specularTint;\\n\\n\\t#ifdef USE_SPECULARINTENSITYMAP\\n\\t\\tuniform sampler2D specularIntensityMap;\\n\\t#endif\\n\\n\\t#ifdef USE_SPECULARTINTMAP\\n\\t\\tuniform sampler2D specularTintMap;\\n\\t#endif\\n#endif\\n\\n#ifdef USE_CLEARCOAT\\n\\tuniform float clearcoat;\\n\\tuniform float clearcoatRoughness;\\n#endif\\n\\n#ifdef USE_SHEEN\\n\\tuniform vec3 sheenTint;\\n\\tuniform float sheenRoughness;\\n#endif\\n\\nvarying vec3 vViewPosition;\\n\\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n\\nvoid main() {\\n\\n\\t#include \\n\\n\\tvec4 diffuseColor = vec4( diffuse, opacity );\\n\\tReflectedLight reflectedLight = ReflectedLight( vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ) );\\n\\tvec3 totalEmissiveRadiance = emissive;\\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n\\t// accumulation\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n\\t// modulation\\n\\t#include \\n\\n\\tvec3 totalDiffuse = reflectedLight.directDiffuse + reflectedLight.indirectDiffuse;\\n\\tvec3 totalSpecular = reflectedLight.directSpecular + reflectedLight.indirectSpecular;\\n\\n\\t#include \\n\\n\\tvec3 outgoingLight = totalDiffuse + totalSpecular + totalEmissiveRadiance;\\n\\n\\t#ifdef USE_CLEARCOAT\\n\\n\\t\\tfloat dotNVcc = saturate( dot( geometry.clearcoatNormal, geometry.viewDir ) );\\n\\n\\t\\tvec3 Fcc = F_Schlick( material.clearcoatF0, material.clearcoatF90, dotNVcc );\\n\\n\\t\\toutgoingLight = outgoingLight * ( 1.0 - clearcoat * Fcc ) + clearcoatSpecular * clearcoat;\\n\\n\\t#endif\\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n}\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderLib/meshtoon.glsl.js\\nvar vertex13 = `\\n#define TOON\\n\\nvarying vec3 vViewPosition;\\n\\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n\\nvoid main() {\\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n\\tvViewPosition = - mvPosition.xyz;\\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\n}\\n`;\\nvar fragment13 = `\\n#define TOON\\n\\nuniform vec3 diffuse;\\nuniform vec3 emissive;\\nuniform float opacity;\\n\\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n\\nvoid main() {\\n\\n\\t#include \\n\\n\\tvec4 diffuseColor = vec4( diffuse, opacity );\\n\\tReflectedLight reflectedLight = ReflectedLight( vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ) );\\n\\tvec3 totalEmissiveRadiance = emissive;\\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n\\t// accumulation\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n\\t// modulation\\n\\t#include \\n\\n\\tvec3 outgoingLight = reflectedLight.directDiffuse + reflectedLight.indirectDiffuse + totalEmissiveRadiance;\\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n}\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderLib/points.glsl.js\\nvar vertex14 = `\\nuniform float size;\\nuniform float scale;\\n\\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n\\nvoid main() {\\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n\\tgl_PointSize = size;\\n\\n\\t#ifdef USE_SIZEATTENUATION\\n\\n\\t\\tbool isPerspective = isPerspectiveMatrix( projectionMatrix );\\n\\n\\t\\tif ( isPerspective ) gl_PointSize *= ( scale / - mvPosition.z );\\n\\n\\t#endif\\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n}\\n`;\\nvar fragment14 = `\\nuniform vec3 diffuse;\\nuniform float opacity;\\n\\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n\\nvoid main() {\\n\\n\\t#include \\n\\n\\tvec3 outgoingLight = vec3( 0.0 );\\n\\tvec4 diffuseColor = vec4( diffuse, opacity );\\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n\\toutgoingLight = diffuseColor.rgb;\\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n}\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderLib/shadow.glsl.js\\nvar vertex15 = `\\n#include \\n#include \\n#include \\n#include \\n#include \\n\\nvoid main() {\\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\n}\\n`;\\nvar fragment15 = `\\nuniform vec3 color;\\nuniform float opacity;\\n\\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n\\nvoid main() {\\n\\n\\tgl_FragColor = vec4( color, opacity * ( 1.0 - getShadowMask() ) );\\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\n}\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderLib/sprite.glsl.js\\nvar vertex16 = `\\nuniform float rotation;\\nuniform vec2 center;\\n\\n#include \\n#include \\n#include \\n#include \\n#include \\n\\nvoid main() {\\n\\n\\t#include \\n\\n\\tvec4 mvPosition = modelViewMatrix * vec4( 0.0, 0.0, 0.0, 1.0 );\\n\\n\\tvec2 scale;\\n\\tscale.x = length( vec3( modelMatrix[ 0 ].x, modelMatrix[ 0 ].y, modelMatrix[ 0 ].z ) );\\n\\tscale.y = length( vec3( modelMatrix[ 1 ].x, modelMatrix[ 1 ].y, modelMatrix[ 1 ].z ) );\\n\\n\\t#ifndef USE_SIZEATTENUATION\\n\\n\\t\\tbool isPerspective = isPerspectiveMatrix( projectionMatrix );\\n\\n\\t\\tif ( isPerspective ) scale *= - mvPosition.z;\\n\\n\\t#endif\\n\\n\\tvec2 alignedPosition = ( position.xy - ( center - vec2( 0.5 ) ) ) * scale;\\n\\n\\tvec2 rotatedPosition;\\n\\trotatedPosition.x = cos( rotation ) * alignedPosition.x - sin( rotation ) * alignedPosition.y;\\n\\trotatedPosition.y = sin( rotation ) * alignedPosition.x + cos( rotation ) * alignedPosition.y;\\n\\n\\tmvPosition.xy += rotatedPosition;\\n\\n\\tgl_Position = projectionMatrix * mvPosition;\\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\n}\\n`;\\nvar fragment16 = `\\nuniform vec3 diffuse;\\nuniform float opacity;\\n\\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n\\nvoid main() {\\n\\n\\t#include \\n\\n\\tvec3 outgoingLight = vec3( 0.0 );\\n\\tvec4 diffuseColor = vec4( diffuse, opacity );\\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n\\toutgoingLight = diffuseColor.rgb;\\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n}\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk.js\\nvar ShaderChunk = {\\n alphamap_fragment: alphamap_fragment_glsl_default,\\n alphamap_pars_fragment: alphamap_pars_fragment_glsl_default,\\n alphatest_fragment: alphatest_fragment_glsl_default,\\n alphatest_pars_fragment: alphatest_pars_fragment_glsl_default,\\n aomap_fragment: aomap_fragment_glsl_default,\\n aomap_pars_fragment: aomap_pars_fragment_glsl_default,\\n begin_vertex: begin_vertex_glsl_default,\\n beginnormal_vertex: beginnormal_vertex_glsl_default,\\n bsdfs: bsdfs_glsl_default,\\n bumpmap_pars_fragment: bumpmap_pars_fragment_glsl_default,\\n clipping_planes_fragment: clipping_planes_fragment_glsl_default,\\n clipping_planes_pars_fragment: clipping_planes_pars_fragment_glsl_default,\\n clipping_planes_pars_vertex: clipping_planes_pars_vertex_glsl_default,\\n clipping_planes_vertex: clipping_planes_vertex_glsl_default,\\n color_fragment: color_fragment_glsl_default,\\n color_pars_fragment: color_pars_fragment_glsl_default,\\n color_pars_vertex: color_pars_vertex_glsl_default,\\n color_vertex: color_vertex_glsl_default,\\n common: common_glsl_default,\\n cube_uv_reflection_fragment: cube_uv_reflection_fragment_glsl_default,\\n defaultnormal_vertex: defaultnormal_vertex_glsl_default,\\n displacementmap_pars_vertex: displacementmap_pars_vertex_glsl_default,\\n displacementmap_vertex: displacementmap_vertex_glsl_default,\\n emissivemap_fragment: emissivemap_fragment_glsl_default,\\n emissivemap_pars_fragment: emissivemap_pars_fragment_glsl_default,\\n encodings_fragment: encodings_fragment_glsl_default,\\n encodings_pars_fragment: encodings_pars_fragment_glsl_default,\\n envmap_fragment: envmap_fragment_glsl_default,\\n envmap_common_pars_fragment: envmap_common_pars_fragment_glsl_default,\\n envmap_pars_fragment: envmap_pars_fragment_glsl_default,\\n envmap_pars_vertex: envmap_pars_vertex_glsl_default,\\n envmap_physical_pars_fragment: envmap_physical_pars_fragment_glsl_default,\\n envmap_vertex: envmap_vertex_glsl_default,\\n fog_vertex: fog_vertex_glsl_default,\\n fog_pars_vertex: fog_pars_vertex_glsl_default,\\n fog_fragment: fog_fragment_glsl_default,\\n fog_pars_fragment: fog_pars_fragment_glsl_default,\\n gradientmap_pars_fragment: gradientmap_pars_fragment_glsl_default,\\n lightmap_fragment: lightmap_fragment_glsl_default,\\n lightmap_pars_fragment: lightmap_pars_fragment_glsl_default,\\n lights_lambert_vertex: lights_lambert_vertex_glsl_default,\\n lights_pars_begin: lights_pars_begin_glsl_default,\\n lights_toon_fragment: lights_toon_fragment_glsl_default,\\n lights_toon_pars_fragment: lights_toon_pars_fragment_glsl_default,\\n lights_phong_fragment: lights_phong_fragment_glsl_default,\\n lights_phong_pars_fragment: lights_phong_pars_fragment_glsl_default,\\n lights_physical_fragment: lights_physical_fragment_glsl_default,\\n lights_physical_pars_fragment: lights_physical_pars_fragment_glsl_default,\\n lights_fragment_begin: lights_fragment_begin_glsl_default,\\n lights_fragment_maps: lights_fragment_maps_glsl_default,\\n lights_fragment_end: lights_fragment_end_glsl_default,\\n logdepthbuf_fragment: logdepthbuf_fragment_glsl_default,\\n logdepthbuf_pars_fragment: logdepthbuf_pars_fragment_glsl_default,\\n logdepthbuf_pars_vertex: logdepthbuf_pars_vertex_glsl_default,\\n logdepthbuf_vertex: logdepthbuf_vertex_glsl_default,\\n map_fragment: map_fragment_glsl_default,\\n map_pars_fragment: map_pars_fragment_glsl_default,\\n map_particle_fragment: map_particle_fragment_glsl_default,\\n map_particle_pars_fragment: map_particle_pars_fragment_glsl_default,\\n metalnessmap_fragment: metalnessmap_fragment_glsl_default,\\n metalnessmap_pars_fragment: metalnessmap_pars_fragment_glsl_default,\\n morphnormal_vertex: morphnormal_vertex_glsl_default,\\n morphtarget_pars_vertex: morphtarget_pars_vertex_glsl_default,\\n morphtarget_vertex: morphtarget_vertex_glsl_default,\\n normal_fragment_begin: normal_fragment_begin_glsl_default,\\n normal_fragment_maps: normal_fragment_maps_glsl_default,\\n normal_pars_fragment: normal_pars_fragment_glsl_default,\\n normal_pars_vertex: normal_pars_vertex_glsl_default,\\n normal_vertex: normal_vertex_glsl_default,\\n normalmap_pars_fragment: normalmap_pars_fragment_glsl_default,\\n clearcoat_normal_fragment_begin: clearcoat_normal_fragment_begin_glsl_default,\\n clearcoat_normal_fragment_maps: clearcoat_normal_fragment_maps_glsl_default,\\n clearcoat_pars_fragment: clearcoat_pars_fragment_glsl_default,\\n output_fragment: output_fragment_glsl_default,\\n packing: packing_glsl_default,\\n premultiplied_alpha_fragment: premultiplied_alpha_fragment_glsl_default,\\n project_vertex: project_vertex_glsl_default,\\n dithering_fragment: dithering_fragment_glsl_default,\\n dithering_pars_fragment: dithering_pars_fragment_glsl_default,\\n roughnessmap_fragment: roughnessmap_fragment_glsl_default,\\n roughnessmap_pars_fragment: roughnessmap_pars_fragment_glsl_default,\\n shadowmap_pars_fragment: shadowmap_pars_fragment_glsl_default,\\n shadowmap_pars_vertex: shadowmap_pars_vertex_glsl_default,\\n shadowmap_vertex: shadowmap_vertex_glsl_default,\\n shadowmask_pars_fragment: shadowmask_pars_fragment_glsl_default,\\n skinbase_vertex: skinbase_vertex_glsl_default,\\n skinning_pars_vertex: skinning_pars_vertex_glsl_default,\\n skinning_vertex: skinning_vertex_glsl_default,\\n skinnormal_vertex: skinnormal_vertex_glsl_default,\\n specularmap_fragment: specularmap_fragment_glsl_default,\\n specularmap_pars_fragment: specularmap_pars_fragment_glsl_default,\\n tonemapping_fragment: tonemapping_fragment_glsl_default,\\n tonemapping_pars_fragment: tonemapping_pars_fragment_glsl_default,\\n transmission_fragment: transmission_fragment_glsl_default,\\n transmission_pars_fragment: transmission_pars_fragment_glsl_default,\\n uv_pars_fragment: uv_pars_fragment_glsl_default,\\n uv_pars_vertex: uv_pars_vertex_glsl_default,\\n uv_vertex: uv_vertex_glsl_default,\\n uv2_pars_fragment: uv2_pars_fragment_glsl_default,\\n uv2_pars_vertex: uv2_pars_vertex_glsl_default,\\n uv2_vertex: uv2_vertex_glsl_default,\\n worldpos_vertex: worldpos_vertex_glsl_default,\\n background_vert: vertex,\\n background_frag: fragment,\\n cube_vert: vertex2,\\n cube_frag: fragment2,\\n depth_vert: vertex3,\\n depth_frag: fragment3,\\n distanceRGBA_vert: vertex4,\\n distanceRGBA_frag: fragment4,\\n equirect_vert: vertex5,\\n equirect_frag: fragment5,\\n linedashed_vert: vertex6,\\n linedashed_frag: fragment6,\\n meshbasic_vert: vertex7,\\n meshbasic_frag: fragment7,\\n meshlambert_vert: vertex8,\\n meshlambert_frag: fragment8,\\n meshmatcap_vert: vertex9,\\n meshmatcap_frag: fragment9,\\n meshnormal_vert: vertex10,\\n meshnormal_frag: fragment10,\\n meshphong_vert: vertex11,\\n meshphong_frag: fragment11,\\n meshphysical_vert: vertex12,\\n meshphysical_frag: fragment12,\\n meshtoon_vert: vertex13,\\n meshtoon_frag: fragment13,\\n points_vert: vertex14,\\n points_frag: fragment14,\\n shadow_vert: vertex15,\\n shadow_frag: fragment15,\\n sprite_vert: vertex16,\\n sprite_frag: fragment16\\n};\\n\\n// ../../../node_modules/three/src/renderers/shaders/UniformsLib.js\\nvar UniformsLib = {\\n common: {\\n diffuse: {value: new Color(16777215)},\\n opacity: {value: 1},\\n map: {value: null},\\n uvTransform: {value: new Matrix3()},\\n uv2Transform: {value: new Matrix3()},\\n alphaMap: {value: null},\\n alphaTest: {value: 0}\\n },\\n specularmap: {\\n specularMap: {value: null}\\n },\\n envmap: {\\n envMap: {value: null},\\n flipEnvMap: {value: -1},\\n reflectivity: {value: 1},\\n ior: {value: 1.5},\\n refractionRatio: {value: 0.98},\\n maxMipLevel: {value: 0}\\n },\\n aomap: {\\n aoMap: {value: null},\\n aoMapIntensity: {value: 1}\\n },\\n lightmap: {\\n lightMap: {value: null},\\n lightMapIntensity: {value: 1}\\n },\\n emissivemap: {\\n emissiveMap: {value: null}\\n },\\n bumpmap: {\\n bumpMap: {value: null},\\n bumpScale: {value: 1}\\n },\\n normalmap: {\\n normalMap: {value: null},\\n normalScale: {value: new Vector2(1, 1)}\\n },\\n displacementmap: {\\n displacementMap: {value: null},\\n displacementScale: {value: 1},\\n displacementBias: {value: 0}\\n },\\n roughnessmap: {\\n roughnessMap: {value: null}\\n },\\n metalnessmap: {\\n metalnessMap: {value: null}\\n },\\n gradientmap: {\\n gradientMap: {value: null}\\n },\\n fog: {\\n fogDensity: {value: 25e-5},\\n fogNear: {value: 1},\\n fogFar: {value: 2e3},\\n fogColor: {value: new Color(16777215)}\\n },\\n lights: {\\n ambientLightColor: {value: []},\\n lightProbe: {value: []},\\n directionalLights: {value: [], properties: {\\n direction: {},\\n color: {}\\n }},\\n directionalLightShadows: {value: [], properties: {\\n shadowBias: {},\\n shadowNormalBias: {},\\n shadowRadius: {},\\n shadowMapSize: {}\\n }},\\n directionalShadowMap: {value: []},\\n directionalShadowMatrix: {value: []},\\n spotLights: {value: [], properties: {\\n color: {},\\n position: {},\\n direction: {},\\n distance: {},\\n coneCos: {},\\n penumbraCos: {},\\n decay: {}\\n }},\\n spotLightShadows: {value: [], properties: {\\n shadowBias: {},\\n shadowNormalBias: {},\\n shadowRadius: {},\\n shadowMapSize: {}\\n }},\\n spotShadowMap: {value: []},\\n spotShadowMatrix: {value: []},\\n pointLights: {value: [], properties: {\\n color: {},\\n position: {},\\n decay: {},\\n distance: {}\\n }},\\n pointLightShadows: {value: [], properties: {\\n shadowBias: {},\\n shadowNormalBias: {},\\n shadowRadius: {},\\n shadowMapSize: {},\\n shadowCameraNear: {},\\n shadowCameraFar: {}\\n }},\\n pointShadowMap: {value: []},\\n pointShadowMatrix: {value: []},\\n hemisphereLights: {value: [], properties: {\\n direction: {},\\n skyColor: {},\\n groundColor: {}\\n }},\\n rectAreaLights: {value: [], properties: {\\n color: {},\\n position: {},\\n width: {},\\n height: {}\\n }},\\n ltc_1: {value: null},\\n ltc_2: {value: null}\\n },\\n points: {\\n diffuse: {value: new Color(16777215)},\\n opacity: {value: 1},\\n size: {value: 1},\\n scale: {value: 1},\\n map: {value: null},\\n alphaMap: {value: null},\\n alphaTest: {value: 0},\\n uvTransform: {value: new Matrix3()}\\n },\\n sprite: {\\n diffuse: {value: new Color(16777215)},\\n opacity: {value: 1},\\n center: {value: new Vector2(0.5, 0.5)},\\n rotation: {value: 0},\\n map: {value: null},\\n alphaMap: {value: null},\\n alphaTest: {value: 0},\\n uvTransform: {value: new Matrix3()}\\n }\\n};\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderLib.js\\nvar ShaderLib = {\\n basic: {\\n uniforms: mergeUniforms([\\n UniformsLib.common,\\n UniformsLib.specularmap,\\n UniformsLib.envmap,\\n UniformsLib.aomap,\\n UniformsLib.lightmap,\\n UniformsLib.fog\\n ]),\\n vertexShader: ShaderChunk.meshbasic_vert,\\n fragmentShader: ShaderChunk.meshbasic_frag\\n },\\n lambert: {\\n uniforms: mergeUniforms([\\n UniformsLib.common,\\n UniformsLib.specularmap,\\n UniformsLib.envmap,\\n UniformsLib.aomap,\\n UniformsLib.lightmap,\\n UniformsLib.emissivemap,\\n UniformsLib.fog,\\n UniformsLib.lights,\\n {\\n emissive: {value: new Color(0)}\\n }\\n ]),\\n vertexShader: ShaderChunk.meshlambert_vert,\\n fragmentShader: ShaderChunk.meshlambert_frag\\n },\\n phong: {\\n uniforms: mergeUniforms([\\n UniformsLib.common,\\n UniformsLib.specularmap,\\n UniformsLib.envmap,\\n UniformsLib.aomap,\\n UniformsLib.lightmap,\\n UniformsLib.emissivemap,\\n UniformsLib.bumpmap,\\n UniformsLib.normalmap,\\n UniformsLib.displacementmap,\\n UniformsLib.fog,\\n UniformsLib.lights,\\n {\\n emissive: {value: new Color(0)},\\n specular: {value: new Color(1118481)},\\n shininess: {value: 30}\\n }\\n ]),\\n vertexShader: ShaderChunk.meshphong_vert,\\n fragmentShader: ShaderChunk.meshphong_frag\\n },\\n standard: {\\n uniforms: mergeUniforms([\\n UniformsLib.common,\\n UniformsLib.envmap,\\n UniformsLib.aomap,\\n UniformsLib.lightmap,\\n UniformsLib.emissivemap,\\n UniformsLib.bumpmap,\\n UniformsLib.normalmap,\\n UniformsLib.displacementmap,\\n UniformsLib.roughnessmap,\\n UniformsLib.metalnessmap,\\n UniformsLib.fog,\\n UniformsLib.lights,\\n {\\n emissive: {value: new Color(0)},\\n roughness: {value: 1},\\n metalness: {value: 0},\\n envMapIntensity: {value: 1}\\n }\\n ]),\\n vertexShader: ShaderChunk.meshphysical_vert,\\n fragmentShader: ShaderChunk.meshphysical_frag\\n },\\n toon: {\\n uniforms: mergeUniforms([\\n UniformsLib.common,\\n UniformsLib.aomap,\\n UniformsLib.lightmap,\\n UniformsLib.emissivemap,\\n UniformsLib.bumpmap,\\n UniformsLib.normalmap,\\n UniformsLib.displacementmap,\\n UniformsLib.gradientmap,\\n UniformsLib.fog,\\n UniformsLib.lights,\\n {\\n emissive: {value: new Color(0)}\\n }\\n ]),\\n vertexShader: ShaderChunk.meshtoon_vert,\\n fragmentShader: ShaderChunk.meshtoon_frag\\n },\\n matcap: {\\n uniforms: mergeUniforms([\\n UniformsLib.common,\\n UniformsLib.bumpmap,\\n UniformsLib.normalmap,\\n UniformsLib.displacementmap,\\n UniformsLib.fog,\\n {\\n matcap: {value: null}\\n }\\n ]),\\n vertexShader: ShaderChunk.meshmatcap_vert,\\n fragmentShader: ShaderChunk.meshmatcap_frag\\n },\\n points: {\\n uniforms: mergeUniforms([\\n UniformsLib.points,\\n UniformsLib.fog\\n ]),\\n vertexShader: ShaderChunk.points_vert,\\n fragmentShader: ShaderChunk.points_frag\\n },\\n dashed: {\\n uniforms: mergeUniforms([\\n UniformsLib.common,\\n UniformsLib.fog,\\n {\\n scale: {value: 1},\\n dashSize: {value: 1},\\n totalSize: {value: 2}\\n }\\n ]),\\n vertexShader: ShaderChunk.linedashed_vert,\\n fragmentShader: ShaderChunk.linedashed_frag\\n },\\n depth: {\\n uniforms: mergeUniforms([\\n UniformsLib.common,\\n UniformsLib.displacementmap\\n ]),\\n vertexShader: ShaderChunk.depth_vert,\\n fragmentShader: ShaderChunk.depth_frag\\n },\\n normal: {\\n uniforms: mergeUniforms([\\n UniformsLib.common,\\n UniformsLib.bumpmap,\\n UniformsLib.normalmap,\\n UniformsLib.displacementmap,\\n {\\n opacity: {value: 1}\\n }\\n ]),\\n vertexShader: ShaderChunk.meshnormal_vert,\\n fragmentShader: ShaderChunk.meshnormal_frag\\n },\\n sprite: {\\n uniforms: mergeUniforms([\\n UniformsLib.sprite,\\n UniformsLib.fog\\n ]),\\n vertexShader: ShaderChunk.sprite_vert,\\n fragmentShader: ShaderChunk.sprite_frag\\n },\\n background: {\\n uniforms: {\\n uvTransform: {value: new Matrix3()},\\n t2D: {value: null}\\n },\\n vertexShader: ShaderChunk.background_vert,\\n fragmentShader: ShaderChunk.background_frag\\n },\\n cube: {\\n uniforms: mergeUniforms([\\n UniformsLib.envmap,\\n {\\n opacity: {value: 1}\\n }\\n ]),\\n vertexShader: ShaderChunk.cube_vert,\\n fragmentShader: ShaderChunk.cube_frag\\n },\\n equirect: {\\n uniforms: {\\n tEquirect: {value: null}\\n },\\n vertexShader: ShaderChunk.equirect_vert,\\n fragmentShader: ShaderChunk.equirect_frag\\n },\\n distanceRGBA: {\\n uniforms: mergeUniforms([\\n UniformsLib.common,\\n UniformsLib.displacementmap,\\n {\\n referencePosition: {value: new Vector3()},\\n nearDistance: {value: 1},\\n farDistance: {value: 1e3}\\n }\\n ]),\\n vertexShader: ShaderChunk.distanceRGBA_vert,\\n fragmentShader: ShaderChunk.distanceRGBA_frag\\n },\\n shadow: {\\n uniforms: mergeUniforms([\\n UniformsLib.lights,\\n UniformsLib.fog,\\n {\\n color: {value: new Color(0)},\\n opacity: {value: 1}\\n }\\n ]),\\n vertexShader: ShaderChunk.shadow_vert,\\n fragmentShader: ShaderChunk.shadow_frag\\n }\\n};\\nShaderLib.physical = {\\n uniforms: mergeUniforms([\\n ShaderLib.standard.uniforms,\\n {\\n clearcoat: {value: 0},\\n clearcoatMap: {value: null},\\n clearcoatRoughness: {value: 0},\\n clearcoatRoughnessMap: {value: null},\\n clearcoatNormalScale: {value: new Vector2(1, 1)},\\n clearcoatNormalMap: {value: null},\\n sheen: {value: 0},\\n sheenTint: {value: new Color(0)},\\n sheenRoughness: {value: 0},\\n transmission: {value: 0},\\n transmissionMap: {value: null},\\n transmissionSamplerSize: {value: new Vector2()},\\n transmissionSamplerMap: {value: null},\\n thickness: {value: 0},\\n thicknessMap: {value: null},\\n attenuationDistance: {value: 0},\\n attenuationTint: {value: new Color(0)},\\n specularIntensity: {value: 0},\\n specularIntensityMap: {value: null},\\n specularTint: {value: new Color(1, 1, 1)},\\n specularTintMap: {value: null}\\n }\\n ]),\\n vertexShader: ShaderChunk.meshphysical_vert,\\n fragmentShader: ShaderChunk.meshphysical_frag\\n};\\n\\n// ../../../node_modules/three/src/renderers/webgl/WebGLBackground.js\\nfunction WebGLBackground(renderer, cubemaps, state, objects, premultipliedAlpha) {\\n const clearColor = new Color(0);\\n let clearAlpha = 0;\\n let planeMesh;\\n let boxMesh;\\n let currentBackground = null;\\n let currentBackgroundVersion = 0;\\n let currentTonemapping = null;\\n function render(renderList, scene) {\\n let forceClear = false;\\n let background2 = scene.isScene === true ? scene.background : null;\\n if (background2 && background2.isTexture) {\\n background2 = cubemaps.get(background2);\\n }\\n const xr = renderer.xr;\\n const session = xr.getSession && xr.getSession();\\n if (session && session.environmentBlendMode === \\\\\\\"additive\\\\\\\") {\\n background2 = null;\\n }\\n if (background2 === null) {\\n setClear(clearColor, clearAlpha);\\n } else if (background2 && background2.isColor) {\\n setClear(background2, 1);\\n forceClear = true;\\n }\\n if (renderer.autoClear || forceClear) {\\n renderer.clear(renderer.autoClearColor, renderer.autoClearDepth, renderer.autoClearStencil);\\n }\\n if (background2 && (background2.isCubeTexture || background2.mapping === CubeUVReflectionMapping)) {\\n if (boxMesh === void 0) {\\n boxMesh = new Mesh(new BoxGeometry(1, 1, 1), new ShaderMaterial({\\n name: \\\\\\\"BackgroundCubeMaterial\\\\\\\",\\n uniforms: cloneUniforms(ShaderLib.cube.uniforms),\\n vertexShader: ShaderLib.cube.vertexShader,\\n fragmentShader: ShaderLib.cube.fragmentShader,\\n side: BackSide,\\n depthTest: false,\\n depthWrite: false,\\n fog: false\\n }));\\n boxMesh.geometry.deleteAttribute(\\\\\\\"normal\\\\\\\");\\n boxMesh.geometry.deleteAttribute(\\\\\\\"uv\\\\\\\");\\n boxMesh.onBeforeRender = function(renderer2, scene2, camera) {\\n this.matrixWorld.copyPosition(camera.matrixWorld);\\n };\\n Object.defineProperty(boxMesh.material, \\\\\\\"envMap\\\\\\\", {\\n get: function() {\\n return this.uniforms.envMap.value;\\n }\\n });\\n objects.update(boxMesh);\\n }\\n boxMesh.material.uniforms.envMap.value = background2;\\n boxMesh.material.uniforms.flipEnvMap.value = background2.isCubeTexture && background2.isRenderTargetTexture === false ? -1 : 1;\\n if (currentBackground !== background2 || currentBackgroundVersion !== background2.version || currentTonemapping !== renderer.toneMapping) {\\n boxMesh.material.needsUpdate = true;\\n currentBackground = background2;\\n currentBackgroundVersion = background2.version;\\n currentTonemapping = renderer.toneMapping;\\n }\\n renderList.unshift(boxMesh, boxMesh.geometry, boxMesh.material, 0, 0, null);\\n } else if (background2 && background2.isTexture) {\\n if (planeMesh === void 0) {\\n planeMesh = new Mesh(new PlaneGeometry(2, 2), new ShaderMaterial({\\n name: \\\\\\\"BackgroundMaterial\\\\\\\",\\n uniforms: cloneUniforms(ShaderLib.background.uniforms),\\n vertexShader: ShaderLib.background.vertexShader,\\n fragmentShader: ShaderLib.background.fragmentShader,\\n side: FrontSide,\\n depthTest: false,\\n depthWrite: false,\\n fog: false\\n }));\\n planeMesh.geometry.deleteAttribute(\\\\\\\"normal\\\\\\\");\\n Object.defineProperty(planeMesh.material, \\\\\\\"map\\\\\\\", {\\n get: function() {\\n return this.uniforms.t2D.value;\\n }\\n });\\n objects.update(planeMesh);\\n }\\n planeMesh.material.uniforms.t2D.value = background2;\\n if (background2.matrixAutoUpdate === true) {\\n background2.updateMatrix();\\n }\\n planeMesh.material.uniforms.uvTransform.value.copy(background2.matrix);\\n if (currentBackground !== background2 || currentBackgroundVersion !== background2.version || currentTonemapping !== renderer.toneMapping) {\\n planeMesh.material.needsUpdate = true;\\n currentBackground = background2;\\n currentBackgroundVersion = background2.version;\\n currentTonemapping = renderer.toneMapping;\\n }\\n renderList.unshift(planeMesh, planeMesh.geometry, planeMesh.material, 0, 0, null);\\n }\\n }\\n function setClear(color, alpha) {\\n state.buffers.color.setClear(color.r, color.g, color.b, alpha, premultipliedAlpha);\\n }\\n return {\\n getClearColor: function() {\\n return clearColor;\\n },\\n setClearColor: function(color, alpha = 1) {\\n clearColor.set(color);\\n clearAlpha = alpha;\\n setClear(clearColor, clearAlpha);\\n },\\n getClearAlpha: function() {\\n return clearAlpha;\\n },\\n setClearAlpha: function(alpha) {\\n clearAlpha = alpha;\\n setClear(clearColor, clearAlpha);\\n },\\n render\\n };\\n}\\n\\n// ../../../node_modules/three/src/renderers/webgl/WebGLBindingStates.js\\nfunction WebGLBindingStates(gl, extensions, attributes, capabilities) {\\n const maxVertexAttributes = gl.getParameter(gl.MAX_VERTEX_ATTRIBS);\\n const extension = capabilities.isWebGL2 ? null : extensions.get(\\\\\\\"OES_vertex_array_object\\\\\\\");\\n const vaoAvailable = capabilities.isWebGL2 || extension !== null;\\n const bindingStates = {};\\n const defaultState = createBindingState(null);\\n let currentState = defaultState;\\n function setup(object, material, program, geometry, index) {\\n let updateBuffers = false;\\n if (vaoAvailable) {\\n const state = getBindingState(geometry, program, material);\\n if (currentState !== state) {\\n currentState = state;\\n bindVertexArrayObject(currentState.object);\\n }\\n updateBuffers = needsUpdate(geometry, index);\\n if (updateBuffers)\\n saveCache(geometry, index);\\n } else {\\n const wireframe = material.wireframe === true;\\n if (currentState.geometry !== geometry.id || currentState.program !== program.id || currentState.wireframe !== wireframe) {\\n currentState.geometry = geometry.id;\\n currentState.program = program.id;\\n currentState.wireframe = wireframe;\\n updateBuffers = true;\\n }\\n }\\n if (object.isInstancedMesh === true) {\\n updateBuffers = true;\\n }\\n if (index !== null) {\\n attributes.update(index, gl.ELEMENT_ARRAY_BUFFER);\\n }\\n if (updateBuffers) {\\n setupVertexAttributes(object, material, program, geometry);\\n if (index !== null) {\\n gl.bindBuffer(gl.ELEMENT_ARRAY_BUFFER, attributes.get(index).buffer);\\n }\\n }\\n }\\n function createVertexArrayObject() {\\n if (capabilities.isWebGL2)\\n return gl.createVertexArray();\\n return extension.createVertexArrayOES();\\n }\\n function bindVertexArrayObject(vao) {\\n if (capabilities.isWebGL2)\\n return gl.bindVertexArray(vao);\\n return extension.bindVertexArrayOES(vao);\\n }\\n function deleteVertexArrayObject(vao) {\\n if (capabilities.isWebGL2)\\n return gl.deleteVertexArray(vao);\\n return extension.deleteVertexArrayOES(vao);\\n }\\n function getBindingState(geometry, program, material) {\\n const wireframe = material.wireframe === true;\\n let programMap = bindingStates[geometry.id];\\n if (programMap === void 0) {\\n programMap = {};\\n bindingStates[geometry.id] = programMap;\\n }\\n let stateMap = programMap[program.id];\\n if (stateMap === void 0) {\\n stateMap = {};\\n programMap[program.id] = stateMap;\\n }\\n let state = stateMap[wireframe];\\n if (state === void 0) {\\n state = createBindingState(createVertexArrayObject());\\n stateMap[wireframe] = state;\\n }\\n return state;\\n }\\n function createBindingState(vao) {\\n const newAttributes = [];\\n const enabledAttributes = [];\\n const attributeDivisors = [];\\n for (let i = 0; i < maxVertexAttributes; i++) {\\n newAttributes[i] = 0;\\n enabledAttributes[i] = 0;\\n attributeDivisors[i] = 0;\\n }\\n return {\\n geometry: null,\\n program: null,\\n wireframe: false,\\n newAttributes,\\n enabledAttributes,\\n attributeDivisors,\\n object: vao,\\n attributes: {},\\n index: null\\n };\\n }\\n function needsUpdate(geometry, index) {\\n const cachedAttributes = currentState.attributes;\\n const geometryAttributes = geometry.attributes;\\n let attributesNum = 0;\\n for (const key in geometryAttributes) {\\n const cachedAttribute = cachedAttributes[key];\\n const geometryAttribute = geometryAttributes[key];\\n if (cachedAttribute === void 0)\\n return true;\\n if (cachedAttribute.attribute !== geometryAttribute)\\n return true;\\n if (cachedAttribute.data !== geometryAttribute.data)\\n return true;\\n attributesNum++;\\n }\\n if (currentState.attributesNum !== attributesNum)\\n return true;\\n if (currentState.index !== index)\\n return true;\\n return false;\\n }\\n function saveCache(geometry, index) {\\n const cache = {};\\n const attributes2 = geometry.attributes;\\n let attributesNum = 0;\\n for (const key in attributes2) {\\n const attribute = attributes2[key];\\n const data = {};\\n data.attribute = attribute;\\n if (attribute.data) {\\n data.data = attribute.data;\\n }\\n cache[key] = data;\\n attributesNum++;\\n }\\n currentState.attributes = cache;\\n currentState.attributesNum = attributesNum;\\n currentState.index = index;\\n }\\n function initAttributes() {\\n const newAttributes = currentState.newAttributes;\\n for (let i = 0, il = newAttributes.length; i < il; i++) {\\n newAttributes[i] = 0;\\n }\\n }\\n function enableAttribute(attribute) {\\n enableAttributeAndDivisor(attribute, 0);\\n }\\n function enableAttributeAndDivisor(attribute, meshPerAttribute) {\\n const newAttributes = currentState.newAttributes;\\n const enabledAttributes = currentState.enabledAttributes;\\n const attributeDivisors = currentState.attributeDivisors;\\n newAttributes[attribute] = 1;\\n if (enabledAttributes[attribute] === 0) {\\n gl.enableVertexAttribArray(attribute);\\n enabledAttributes[attribute] = 1;\\n }\\n if (attributeDivisors[attribute] !== meshPerAttribute) {\\n const extension2 = capabilities.isWebGL2 ? gl : extensions.get(\\\\\\\"ANGLE_instanced_arrays\\\\\\\");\\n extension2[capabilities.isWebGL2 ? \\\\\\\"vertexAttribDivisor\\\\\\\" : \\\\\\\"vertexAttribDivisorANGLE\\\\\\\"](attribute, meshPerAttribute);\\n attributeDivisors[attribute] = meshPerAttribute;\\n }\\n }\\n function disableUnusedAttributes() {\\n const newAttributes = currentState.newAttributes;\\n const enabledAttributes = currentState.enabledAttributes;\\n for (let i = 0, il = enabledAttributes.length; i < il; i++) {\\n if (enabledAttributes[i] !== newAttributes[i]) {\\n gl.disableVertexAttribArray(i);\\n enabledAttributes[i] = 0;\\n }\\n }\\n }\\n function vertexAttribPointer(index, size, type, normalized, stride, offset) {\\n if (capabilities.isWebGL2 === true && (type === gl.INT || type === gl.UNSIGNED_INT)) {\\n gl.vertexAttribIPointer(index, size, type, stride, offset);\\n } else {\\n gl.vertexAttribPointer(index, size, type, normalized, stride, offset);\\n }\\n }\\n function setupVertexAttributes(object, material, program, geometry) {\\n if (capabilities.isWebGL2 === false && (object.isInstancedMesh || geometry.isInstancedBufferGeometry)) {\\n if (extensions.get(\\\\\\\"ANGLE_instanced_arrays\\\\\\\") === null)\\n return;\\n }\\n initAttributes();\\n const geometryAttributes = geometry.attributes;\\n const programAttributes = program.getAttributes();\\n const materialDefaultAttributeValues = material.defaultAttributeValues;\\n for (const name in programAttributes) {\\n const programAttribute = programAttributes[name];\\n if (programAttribute.location >= 0) {\\n let geometryAttribute = geometryAttributes[name];\\n if (geometryAttribute === void 0) {\\n if (name === \\\\\\\"instanceMatrix\\\\\\\" && object.instanceMatrix)\\n geometryAttribute = object.instanceMatrix;\\n if (name === \\\\\\\"instanceColor\\\\\\\" && object.instanceColor)\\n geometryAttribute = object.instanceColor;\\n }\\n if (geometryAttribute !== void 0) {\\n const normalized = geometryAttribute.normalized;\\n const size = geometryAttribute.itemSize;\\n const attribute = attributes.get(geometryAttribute);\\n if (attribute === void 0)\\n continue;\\n const buffer = attribute.buffer;\\n const type = attribute.type;\\n const bytesPerElement = attribute.bytesPerElement;\\n if (geometryAttribute.isInterleavedBufferAttribute) {\\n const data = geometryAttribute.data;\\n const stride = data.stride;\\n const offset = geometryAttribute.offset;\\n if (data && data.isInstancedInterleavedBuffer) {\\n for (let i = 0; i < programAttribute.locationSize; i++) {\\n enableAttributeAndDivisor(programAttribute.location + i, data.meshPerAttribute);\\n }\\n if (object.isInstancedMesh !== true && geometry._maxInstanceCount === void 0) {\\n geometry._maxInstanceCount = data.meshPerAttribute * data.count;\\n }\\n } else {\\n for (let i = 0; i < programAttribute.locationSize; i++) {\\n enableAttribute(programAttribute.location + i);\\n }\\n }\\n gl.bindBuffer(gl.ARRAY_BUFFER, buffer);\\n for (let i = 0; i < programAttribute.locationSize; i++) {\\n vertexAttribPointer(programAttribute.location + i, size / programAttribute.locationSize, type, normalized, stride * bytesPerElement, (offset + size / programAttribute.locationSize * i) * bytesPerElement);\\n }\\n } else {\\n if (geometryAttribute.isInstancedBufferAttribute) {\\n for (let i = 0; i < programAttribute.locationSize; i++) {\\n enableAttributeAndDivisor(programAttribute.location + i, geometryAttribute.meshPerAttribute);\\n }\\n if (object.isInstancedMesh !== true && geometry._maxInstanceCount === void 0) {\\n geometry._maxInstanceCount = geometryAttribute.meshPerAttribute * geometryAttribute.count;\\n }\\n } else {\\n for (let i = 0; i < programAttribute.locationSize; i++) {\\n enableAttribute(programAttribute.location + i);\\n }\\n }\\n gl.bindBuffer(gl.ARRAY_BUFFER, buffer);\\n for (let i = 0; i < programAttribute.locationSize; i++) {\\n vertexAttribPointer(programAttribute.location + i, size / programAttribute.locationSize, type, normalized, size * bytesPerElement, size / programAttribute.locationSize * i * bytesPerElement);\\n }\\n }\\n } else if (materialDefaultAttributeValues !== void 0) {\\n const value = materialDefaultAttributeValues[name];\\n if (value !== void 0) {\\n switch (value.length) {\\n case 2:\\n gl.vertexAttrib2fv(programAttribute.location, value);\\n break;\\n case 3:\\n gl.vertexAttrib3fv(programAttribute.location, value);\\n break;\\n case 4:\\n gl.vertexAttrib4fv(programAttribute.location, value);\\n break;\\n default:\\n gl.vertexAttrib1fv(programAttribute.location, value);\\n }\\n }\\n }\\n }\\n }\\n disableUnusedAttributes();\\n }\\n function dispose() {\\n reset();\\n for (const geometryId in bindingStates) {\\n const programMap = bindingStates[geometryId];\\n for (const programId in programMap) {\\n const stateMap = programMap[programId];\\n for (const wireframe in stateMap) {\\n deleteVertexArrayObject(stateMap[wireframe].object);\\n delete stateMap[wireframe];\\n }\\n delete programMap[programId];\\n }\\n delete bindingStates[geometryId];\\n }\\n }\\n function releaseStatesOfGeometry(geometry) {\\n if (bindingStates[geometry.id] === void 0)\\n return;\\n const programMap = bindingStates[geometry.id];\\n for (const programId in programMap) {\\n const stateMap = programMap[programId];\\n for (const wireframe in stateMap) {\\n deleteVertexArrayObject(stateMap[wireframe].object);\\n delete stateMap[wireframe];\\n }\\n delete programMap[programId];\\n }\\n delete bindingStates[geometry.id];\\n }\\n function releaseStatesOfProgram(program) {\\n for (const geometryId in bindingStates) {\\n const programMap = bindingStates[geometryId];\\n if (programMap[program.id] === void 0)\\n continue;\\n const stateMap = programMap[program.id];\\n for (const wireframe in stateMap) {\\n deleteVertexArrayObject(stateMap[wireframe].object);\\n delete stateMap[wireframe];\\n }\\n delete programMap[program.id];\\n }\\n }\\n function reset() {\\n resetDefaultState();\\n if (currentState === defaultState)\\n return;\\n currentState = defaultState;\\n bindVertexArrayObject(currentState.object);\\n }\\n function resetDefaultState() {\\n defaultState.geometry = null;\\n defaultState.program = null;\\n defaultState.wireframe = false;\\n }\\n return {\\n setup,\\n reset,\\n resetDefaultState,\\n dispose,\\n releaseStatesOfGeometry,\\n releaseStatesOfProgram,\\n initAttributes,\\n enableAttribute,\\n disableUnusedAttributes\\n };\\n}\\n\\n// ../../../node_modules/three/src/renderers/webgl/WebGLBufferRenderer.js\\nfunction WebGLBufferRenderer(gl, extensions, info, capabilities) {\\n const isWebGL2 = capabilities.isWebGL2;\\n let mode;\\n function setMode(value) {\\n mode = value;\\n }\\n function render(start, count) {\\n gl.drawArrays(mode, start, count);\\n info.update(count, mode, 1);\\n }\\n function renderInstances(start, count, primcount) {\\n if (primcount === 0)\\n return;\\n let extension, methodName;\\n if (isWebGL2) {\\n extension = gl;\\n methodName = \\\\\\\"drawArraysInstanced\\\\\\\";\\n } else {\\n extension = extensions.get(\\\\\\\"ANGLE_instanced_arrays\\\\\\\");\\n methodName = \\\\\\\"drawArraysInstancedANGLE\\\\\\\";\\n if (extension === null) {\\n console.error(\\\\\\\"THREE.WebGLBufferRenderer: using THREE.InstancedBufferGeometry but hardware does not support extension ANGLE_instanced_arrays.\\\\\\\");\\n return;\\n }\\n }\\n extension[methodName](mode, start, count, primcount);\\n info.update(count, mode, primcount);\\n }\\n this.setMode = setMode;\\n this.render = render;\\n this.renderInstances = renderInstances;\\n}\\n\\n// ../../../node_modules/three/src/renderers/webgl/WebGLCapabilities.js\\nfunction WebGLCapabilities(gl, extensions, parameters) {\\n let maxAnisotropy;\\n function getMaxAnisotropy() {\\n if (maxAnisotropy !== void 0)\\n return maxAnisotropy;\\n if (extensions.has(\\\\\\\"EXT_texture_filter_anisotropic\\\\\\\") === true) {\\n const extension = extensions.get(\\\\\\\"EXT_texture_filter_anisotropic\\\\\\\");\\n maxAnisotropy = gl.getParameter(extension.MAX_TEXTURE_MAX_ANISOTROPY_EXT);\\n } else {\\n maxAnisotropy = 0;\\n }\\n return maxAnisotropy;\\n }\\n function getMaxPrecision(precision2) {\\n if (precision2 === \\\\\\\"highp\\\\\\\") {\\n if (gl.getShaderPrecisionFormat(gl.VERTEX_SHADER, gl.HIGH_FLOAT).precision > 0 && gl.getShaderPrecisionFormat(gl.FRAGMENT_SHADER, gl.HIGH_FLOAT).precision > 0) {\\n return \\\\\\\"highp\\\\\\\";\\n }\\n precision2 = \\\\\\\"mediump\\\\\\\";\\n }\\n if (precision2 === \\\\\\\"mediump\\\\\\\") {\\n if (gl.getShaderPrecisionFormat(gl.VERTEX_SHADER, gl.MEDIUM_FLOAT).precision > 0 && gl.getShaderPrecisionFormat(gl.FRAGMENT_SHADER, gl.MEDIUM_FLOAT).precision > 0) {\\n return \\\\\\\"mediump\\\\\\\";\\n }\\n }\\n return \\\\\\\"lowp\\\\\\\";\\n }\\n const isWebGL2 = typeof WebGL2RenderingContext !== \\\\\\\"undefined\\\\\\\" && gl instanceof WebGL2RenderingContext || typeof WebGL2ComputeRenderingContext !== \\\\\\\"undefined\\\\\\\" && gl instanceof WebGL2ComputeRenderingContext;\\n let precision = parameters.precision !== void 0 ? parameters.precision : \\\\\\\"highp\\\\\\\";\\n const maxPrecision = getMaxPrecision(precision);\\n if (maxPrecision !== precision) {\\n console.warn(\\\\\\\"THREE.WebGLRenderer:\\\\\\\", precision, \\\\\\\"not supported, using\\\\\\\", maxPrecision, \\\\\\\"instead.\\\\\\\");\\n precision = maxPrecision;\\n }\\n const drawBuffers = isWebGL2 || extensions.has(\\\\\\\"WEBGL_draw_buffers\\\\\\\");\\n const logarithmicDepthBuffer = parameters.logarithmicDepthBuffer === true;\\n const maxTextures = gl.getParameter(gl.MAX_TEXTURE_IMAGE_UNITS);\\n const maxVertexTextures = gl.getParameter(gl.MAX_VERTEX_TEXTURE_IMAGE_UNITS);\\n const maxTextureSize = gl.getParameter(gl.MAX_TEXTURE_SIZE);\\n const maxCubemapSize = gl.getParameter(gl.MAX_CUBE_MAP_TEXTURE_SIZE);\\n const maxAttributes = gl.getParameter(gl.MAX_VERTEX_ATTRIBS);\\n const maxVertexUniforms = gl.getParameter(gl.MAX_VERTEX_UNIFORM_VECTORS);\\n const maxVaryings = gl.getParameter(gl.MAX_VARYING_VECTORS);\\n const maxFragmentUniforms = gl.getParameter(gl.MAX_FRAGMENT_UNIFORM_VECTORS);\\n const vertexTextures = maxVertexTextures > 0;\\n const floatFragmentTextures = isWebGL2 || extensions.has(\\\\\\\"OES_texture_float\\\\\\\");\\n const floatVertexTextures = vertexTextures && floatFragmentTextures;\\n const maxSamples = isWebGL2 ? gl.getParameter(gl.MAX_SAMPLES) : 0;\\n return {\\n isWebGL2,\\n drawBuffers,\\n getMaxAnisotropy,\\n getMaxPrecision,\\n precision,\\n logarithmicDepthBuffer,\\n maxTextures,\\n maxVertexTextures,\\n maxTextureSize,\\n maxCubemapSize,\\n maxAttributes,\\n maxVertexUniforms,\\n maxVaryings,\\n maxFragmentUniforms,\\n vertexTextures,\\n floatFragmentTextures,\\n floatVertexTextures,\\n maxSamples\\n };\\n}\\n\\n// ../../../node_modules/three/src/renderers/webgl/WebGLClipping.js\\nfunction WebGLClipping(properties) {\\n const scope = this;\\n let globalState = null, numGlobalPlanes = 0, localClippingEnabled = false, renderingShadows = false;\\n const plane = new Plane(), viewNormalMatrix = new Matrix3(), uniform = {value: null, needsUpdate: false};\\n this.uniform = uniform;\\n this.numPlanes = 0;\\n this.numIntersection = 0;\\n this.init = function(planes, enableLocalClipping, camera) {\\n const enabled = planes.length !== 0 || enableLocalClipping || numGlobalPlanes !== 0 || localClippingEnabled;\\n localClippingEnabled = enableLocalClipping;\\n globalState = projectPlanes(planes, camera, 0);\\n numGlobalPlanes = planes.length;\\n return enabled;\\n };\\n this.beginShadows = function() {\\n renderingShadows = true;\\n projectPlanes(null);\\n };\\n this.endShadows = function() {\\n renderingShadows = false;\\n resetGlobalState();\\n };\\n this.setState = function(material, camera, useCache) {\\n const planes = material.clippingPlanes, clipIntersection = material.clipIntersection, clipShadows = material.clipShadows;\\n const materialProperties = properties.get(material);\\n if (!localClippingEnabled || planes === null || planes.length === 0 || renderingShadows && !clipShadows) {\\n if (renderingShadows) {\\n projectPlanes(null);\\n } else {\\n resetGlobalState();\\n }\\n } else {\\n const nGlobal = renderingShadows ? 0 : numGlobalPlanes, lGlobal = nGlobal * 4;\\n let dstArray = materialProperties.clippingState || null;\\n uniform.value = dstArray;\\n dstArray = projectPlanes(planes, camera, lGlobal, useCache);\\n for (let i = 0; i !== lGlobal; ++i) {\\n dstArray[i] = globalState[i];\\n }\\n materialProperties.clippingState = dstArray;\\n this.numIntersection = clipIntersection ? this.numPlanes : 0;\\n this.numPlanes += nGlobal;\\n }\\n };\\n function resetGlobalState() {\\n if (uniform.value !== globalState) {\\n uniform.value = globalState;\\n uniform.needsUpdate = numGlobalPlanes > 0;\\n }\\n scope.numPlanes = numGlobalPlanes;\\n scope.numIntersection = 0;\\n }\\n function projectPlanes(planes, camera, dstOffset, skipTransform) {\\n const nPlanes = planes !== null ? planes.length : 0;\\n let dstArray = null;\\n if (nPlanes !== 0) {\\n dstArray = uniform.value;\\n if (skipTransform !== true || dstArray === null) {\\n const flatSize = dstOffset + nPlanes * 4, viewMatrix = camera.matrixWorldInverse;\\n viewNormalMatrix.getNormalMatrix(viewMatrix);\\n if (dstArray === null || dstArray.length < flatSize) {\\n dstArray = new Float32Array(flatSize);\\n }\\n for (let i = 0, i4 = dstOffset; i !== nPlanes; ++i, i4 += 4) {\\n plane.copy(planes[i]).applyMatrix4(viewMatrix, viewNormalMatrix);\\n plane.normal.toArray(dstArray, i4);\\n dstArray[i4 + 3] = plane.constant;\\n }\\n }\\n uniform.value = dstArray;\\n uniform.needsUpdate = true;\\n }\\n scope.numPlanes = nPlanes;\\n scope.numIntersection = 0;\\n return dstArray;\\n }\\n}\\n\\n// ../../../node_modules/three/src/extras/ImageUtils.js\\nvar _canvas;\\nvar ImageUtils = class {\\n static getDataURL(image) {\\n if (/^data:/i.test(image.src)) {\\n return image.src;\\n }\\n if (typeof HTMLCanvasElement == \\\\\\\"undefined\\\\\\\") {\\n return image.src;\\n }\\n let canvas;\\n if (image instanceof HTMLCanvasElement) {\\n canvas = image;\\n } else {\\n if (_canvas === void 0)\\n _canvas = createElementNS(\\\\\\\"canvas\\\\\\\");\\n _canvas.width = image.width;\\n _canvas.height = image.height;\\n const context = _canvas.getContext(\\\\\\\"2d\\\\\\\");\\n if (image instanceof ImageData) {\\n context.putImageData(image, 0, 0);\\n } else {\\n context.drawImage(image, 0, 0, image.width, image.height);\\n }\\n canvas = _canvas;\\n }\\n if (canvas.width > 2048 || canvas.height > 2048) {\\n console.warn(\\\\\\\"THREE.ImageUtils.getDataURL: Image converted to jpg for performance reasons\\\\\\\", image);\\n return canvas.toDataURL(\\\\\\\"image/jpeg\\\\\\\", 0.6);\\n } else {\\n return canvas.toDataURL(\\\\\\\"image/png\\\\\\\");\\n }\\n }\\n};\\n\\n// ../../../node_modules/three/src/textures/Texture.js\\nvar textureId = 0;\\nvar Texture = class extends EventDispatcher {\\n constructor(image = Texture.DEFAULT_IMAGE, mapping = Texture.DEFAULT_MAPPING, wrapS = ClampToEdgeWrapping, wrapT = ClampToEdgeWrapping, magFilter = LinearFilter, minFilter = LinearMipmapLinearFilter, format = RGBAFormat, type = UnsignedByteType, anisotropy = 1, encoding = LinearEncoding) {\\n super();\\n Object.defineProperty(this, \\\\\\\"id\\\\\\\", {value: textureId++});\\n this.uuid = generateUUID();\\n this.name = \\\\\\\"\\\\\\\";\\n this.image = image;\\n this.mipmaps = [];\\n this.mapping = mapping;\\n this.wrapS = wrapS;\\n this.wrapT = wrapT;\\n this.magFilter = magFilter;\\n this.minFilter = minFilter;\\n this.anisotropy = anisotropy;\\n this.format = format;\\n this.internalFormat = null;\\n this.type = type;\\n this.offset = new Vector2(0, 0);\\n this.repeat = new Vector2(1, 1);\\n this.center = new Vector2(0, 0);\\n this.rotation = 0;\\n this.matrixAutoUpdate = true;\\n this.matrix = new Matrix3();\\n this.generateMipmaps = true;\\n this.premultiplyAlpha = false;\\n this.flipY = true;\\n this.unpackAlignment = 4;\\n this.encoding = encoding;\\n this.version = 0;\\n this.onUpdate = null;\\n this.isRenderTargetTexture = false;\\n }\\n updateMatrix() {\\n this.matrix.setUvTransform(this.offset.x, this.offset.y, this.repeat.x, this.repeat.y, this.rotation, this.center.x, this.center.y);\\n }\\n clone() {\\n return new this.constructor().copy(this);\\n }\\n copy(source) {\\n this.name = source.name;\\n this.image = source.image;\\n this.mipmaps = source.mipmaps.slice(0);\\n this.mapping = source.mapping;\\n this.wrapS = source.wrapS;\\n this.wrapT = source.wrapT;\\n this.magFilter = source.magFilter;\\n this.minFilter = source.minFilter;\\n this.anisotropy = source.anisotropy;\\n this.format = source.format;\\n this.internalFormat = source.internalFormat;\\n this.type = source.type;\\n this.offset.copy(source.offset);\\n this.repeat.copy(source.repeat);\\n this.center.copy(source.center);\\n this.rotation = source.rotation;\\n this.matrixAutoUpdate = source.matrixAutoUpdate;\\n this.matrix.copy(source.matrix);\\n this.generateMipmaps = source.generateMipmaps;\\n this.premultiplyAlpha = source.premultiplyAlpha;\\n this.flipY = source.flipY;\\n this.unpackAlignment = source.unpackAlignment;\\n this.encoding = source.encoding;\\n return this;\\n }\\n toJSON(meta) {\\n const isRootObject = meta === void 0 || typeof meta === \\\\\\\"string\\\\\\\";\\n if (!isRootObject && meta.textures[this.uuid] !== void 0) {\\n return meta.textures[this.uuid];\\n }\\n const output = {\\n metadata: {\\n version: 4.5,\\n type: \\\\\\\"Texture\\\\\\\",\\n generator: \\\\\\\"Texture.toJSON\\\\\\\"\\n },\\n uuid: this.uuid,\\n name: this.name,\\n mapping: this.mapping,\\n repeat: [this.repeat.x, this.repeat.y],\\n offset: [this.offset.x, this.offset.y],\\n center: [this.center.x, this.center.y],\\n rotation: this.rotation,\\n wrap: [this.wrapS, this.wrapT],\\n format: this.format,\\n type: this.type,\\n encoding: this.encoding,\\n minFilter: this.minFilter,\\n magFilter: this.magFilter,\\n anisotropy: this.anisotropy,\\n flipY: this.flipY,\\n premultiplyAlpha: this.premultiplyAlpha,\\n unpackAlignment: this.unpackAlignment\\n };\\n if (this.image !== void 0) {\\n const image = this.image;\\n if (image.uuid === void 0) {\\n image.uuid = generateUUID();\\n }\\n if (!isRootObject && meta.images[image.uuid] === void 0) {\\n let url;\\n if (Array.isArray(image)) {\\n url = [];\\n for (let i = 0, l = image.length; i < l; i++) {\\n if (image[i].isDataTexture) {\\n url.push(serializeImage(image[i].image));\\n } else {\\n url.push(serializeImage(image[i]));\\n }\\n }\\n } else {\\n url = serializeImage(image);\\n }\\n meta.images[image.uuid] = {\\n uuid: image.uuid,\\n url\\n };\\n }\\n output.image = image.uuid;\\n }\\n if (!isRootObject) {\\n meta.textures[this.uuid] = output;\\n }\\n return output;\\n }\\n dispose() {\\n this.dispatchEvent({type: \\\\\\\"dispose\\\\\\\"});\\n }\\n transformUv(uv) {\\n if (this.mapping !== UVMapping)\\n return uv;\\n uv.applyMatrix3(this.matrix);\\n if (uv.x < 0 || uv.x > 1) {\\n switch (this.wrapS) {\\n case RepeatWrapping:\\n uv.x = uv.x - Math.floor(uv.x);\\n break;\\n case ClampToEdgeWrapping:\\n uv.x = uv.x < 0 ? 0 : 1;\\n break;\\n case MirroredRepeatWrapping:\\n if (Math.abs(Math.floor(uv.x) % 2) === 1) {\\n uv.x = Math.ceil(uv.x) - uv.x;\\n } else {\\n uv.x = uv.x - Math.floor(uv.x);\\n }\\n break;\\n }\\n }\\n if (uv.y < 0 || uv.y > 1) {\\n switch (this.wrapT) {\\n case RepeatWrapping:\\n uv.y = uv.y - Math.floor(uv.y);\\n break;\\n case ClampToEdgeWrapping:\\n uv.y = uv.y < 0 ? 0 : 1;\\n break;\\n case MirroredRepeatWrapping:\\n if (Math.abs(Math.floor(uv.y) % 2) === 1) {\\n uv.y = Math.ceil(uv.y) - uv.y;\\n } else {\\n uv.y = uv.y - Math.floor(uv.y);\\n }\\n break;\\n }\\n }\\n if (this.flipY) {\\n uv.y = 1 - uv.y;\\n }\\n return uv;\\n }\\n set needsUpdate(value) {\\n if (value === true)\\n this.version++;\\n }\\n};\\nTexture.DEFAULT_IMAGE = void 0;\\nTexture.DEFAULT_MAPPING = UVMapping;\\nTexture.prototype.isTexture = true;\\nfunction serializeImage(image) {\\n if (typeof HTMLImageElement !== \\\\\\\"undefined\\\\\\\" && image instanceof HTMLImageElement || typeof HTMLCanvasElement !== \\\\\\\"undefined\\\\\\\" && image instanceof HTMLCanvasElement || typeof ImageBitmap !== \\\\\\\"undefined\\\\\\\" && image instanceof ImageBitmap) {\\n return ImageUtils.getDataURL(image);\\n } else {\\n if (image.data) {\\n return {\\n data: Array.prototype.slice.call(image.data),\\n width: image.width,\\n height: image.height,\\n type: image.data.constructor.name\\n };\\n } else {\\n console.warn(\\\\\\\"THREE.Texture: Unable to serialize Texture.\\\\\\\");\\n return {};\\n }\\n }\\n}\\n\\n// ../../../node_modules/three/src/renderers/WebGLRenderTarget.js\\nvar WebGLRenderTarget = class extends EventDispatcher {\\n constructor(width, height, options = {}) {\\n super();\\n this.width = width;\\n this.height = height;\\n this.depth = 1;\\n this.scissor = new Vector4(0, 0, width, height);\\n this.scissorTest = false;\\n this.viewport = new Vector4(0, 0, width, height);\\n this.texture = new Texture(void 0, options.mapping, options.wrapS, options.wrapT, options.magFilter, options.minFilter, options.format, options.type, options.anisotropy, options.encoding);\\n this.texture.isRenderTargetTexture = true;\\n this.texture.image = {width, height, depth: 1};\\n this.texture.generateMipmaps = options.generateMipmaps !== void 0 ? options.generateMipmaps : false;\\n this.texture.internalFormat = options.internalFormat !== void 0 ? options.internalFormat : null;\\n this.texture.minFilter = options.minFilter !== void 0 ? options.minFilter : LinearFilter;\\n this.depthBuffer = options.depthBuffer !== void 0 ? options.depthBuffer : true;\\n this.stencilBuffer = options.stencilBuffer !== void 0 ? options.stencilBuffer : false;\\n this.depthTexture = options.depthTexture !== void 0 ? options.depthTexture : null;\\n }\\n setTexture(texture) {\\n texture.image = {\\n width: this.width,\\n height: this.height,\\n depth: this.depth\\n };\\n this.texture = texture;\\n }\\n setSize(width, height, depth2 = 1) {\\n if (this.width !== width || this.height !== height || this.depth !== depth2) {\\n this.width = width;\\n this.height = height;\\n this.depth = depth2;\\n this.texture.image.width = width;\\n this.texture.image.height = height;\\n this.texture.image.depth = depth2;\\n this.dispose();\\n }\\n this.viewport.set(0, 0, width, height);\\n this.scissor.set(0, 0, width, height);\\n }\\n clone() {\\n return new this.constructor().copy(this);\\n }\\n copy(source) {\\n this.width = source.width;\\n this.height = source.height;\\n this.depth = source.depth;\\n this.viewport.copy(source.viewport);\\n this.texture = source.texture.clone();\\n this.texture.image = {...this.texture.image};\\n this.depthBuffer = source.depthBuffer;\\n this.stencilBuffer = source.stencilBuffer;\\n this.depthTexture = source.depthTexture;\\n return this;\\n }\\n dispose() {\\n this.dispatchEvent({type: \\\\\\\"dispose\\\\\\\"});\\n }\\n};\\nWebGLRenderTarget.prototype.isWebGLRenderTarget = true;\\n\\n// ../../../node_modules/three/src/cameras/Camera.js\\nvar Camera = class extends Object3D {\\n constructor() {\\n super();\\n this.type = \\\\\\\"Camera\\\\\\\";\\n this.matrixWorldInverse = new Matrix4();\\n this.projectionMatrix = new Matrix4();\\n this.projectionMatrixInverse = new Matrix4();\\n }\\n copy(source, recursive) {\\n super.copy(source, recursive);\\n this.matrixWorldInverse.copy(source.matrixWorldInverse);\\n this.projectionMatrix.copy(source.projectionMatrix);\\n this.projectionMatrixInverse.copy(source.projectionMatrixInverse);\\n return this;\\n }\\n getWorldDirection(target) {\\n this.updateWorldMatrix(true, false);\\n const e = this.matrixWorld.elements;\\n return target.set(-e[8], -e[9], -e[10]).normalize();\\n }\\n updateMatrixWorld(force) {\\n super.updateMatrixWorld(force);\\n this.matrixWorldInverse.copy(this.matrixWorld).invert();\\n }\\n updateWorldMatrix(updateParents, updateChildren) {\\n super.updateWorldMatrix(updateParents, updateChildren);\\n this.matrixWorldInverse.copy(this.matrixWorld).invert();\\n }\\n clone() {\\n return new this.constructor().copy(this);\\n }\\n};\\nCamera.prototype.isCamera = true;\\n\\n// ../../../node_modules/three/src/cameras/PerspectiveCamera.js\\nvar PerspectiveCamera = class extends Camera {\\n constructor(fov2 = 50, aspect2 = 1, near = 0.1, far = 2e3) {\\n super();\\n this.type = \\\\\\\"PerspectiveCamera\\\\\\\";\\n this.fov = fov2;\\n this.zoom = 1;\\n this.near = near;\\n this.far = far;\\n this.focus = 10;\\n this.aspect = aspect2;\\n this.view = null;\\n this.filmGauge = 35;\\n this.filmOffset = 0;\\n this.updateProjectionMatrix();\\n }\\n copy(source, recursive) {\\n super.copy(source, recursive);\\n this.fov = source.fov;\\n this.zoom = source.zoom;\\n this.near = source.near;\\n this.far = source.far;\\n this.focus = source.focus;\\n this.aspect = source.aspect;\\n this.view = source.view === null ? null : Object.assign({}, source.view);\\n this.filmGauge = source.filmGauge;\\n this.filmOffset = source.filmOffset;\\n return this;\\n }\\n setFocalLength(focalLength) {\\n const vExtentSlope = 0.5 * this.getFilmHeight() / focalLength;\\n this.fov = RAD2DEG * 2 * Math.atan(vExtentSlope);\\n this.updateProjectionMatrix();\\n }\\n getFocalLength() {\\n const vExtentSlope = Math.tan(DEG2RAD * 0.5 * this.fov);\\n return 0.5 * this.getFilmHeight() / vExtentSlope;\\n }\\n getEffectiveFOV() {\\n return RAD2DEG * 2 * Math.atan(Math.tan(DEG2RAD * 0.5 * this.fov) / this.zoom);\\n }\\n getFilmWidth() {\\n return this.filmGauge * Math.min(this.aspect, 1);\\n }\\n getFilmHeight() {\\n return this.filmGauge / Math.max(this.aspect, 1);\\n }\\n setViewOffset(fullWidth, fullHeight, x, y, width, height) {\\n this.aspect = fullWidth / fullHeight;\\n if (this.view === null) {\\n this.view = {\\n enabled: true,\\n fullWidth: 1,\\n fullHeight: 1,\\n offsetX: 0,\\n offsetY: 0,\\n width: 1,\\n height: 1\\n };\\n }\\n this.view.enabled = true;\\n this.view.fullWidth = fullWidth;\\n this.view.fullHeight = fullHeight;\\n this.view.offsetX = x;\\n this.view.offsetY = y;\\n this.view.width = width;\\n this.view.height = height;\\n this.updateProjectionMatrix();\\n }\\n clearViewOffset() {\\n if (this.view !== null) {\\n this.view.enabled = false;\\n }\\n this.updateProjectionMatrix();\\n }\\n updateProjectionMatrix() {\\n const near = this.near;\\n let top = near * Math.tan(DEG2RAD * 0.5 * this.fov) / this.zoom;\\n let height = 2 * top;\\n let width = this.aspect * height;\\n let left = -0.5 * width;\\n const view = this.view;\\n if (this.view !== null && this.view.enabled) {\\n const fullWidth = view.fullWidth, fullHeight = view.fullHeight;\\n left += view.offsetX * width / fullWidth;\\n top -= view.offsetY * height / fullHeight;\\n width *= view.width / fullWidth;\\n height *= view.height / fullHeight;\\n }\\n const skew = this.filmOffset;\\n if (skew !== 0)\\n left += near * skew / this.getFilmWidth();\\n this.projectionMatrix.makePerspective(left, left + width, top, top - height, near, this.far);\\n this.projectionMatrixInverse.copy(this.projectionMatrix).invert();\\n }\\n toJSON(meta) {\\n const data = super.toJSON(meta);\\n data.object.fov = this.fov;\\n data.object.zoom = this.zoom;\\n data.object.near = this.near;\\n data.object.far = this.far;\\n data.object.focus = this.focus;\\n data.object.aspect = this.aspect;\\n if (this.view !== null)\\n data.object.view = Object.assign({}, this.view);\\n data.object.filmGauge = this.filmGauge;\\n data.object.filmOffset = this.filmOffset;\\n return data;\\n }\\n};\\nPerspectiveCamera.prototype.isPerspectiveCamera = true;\\n\\n// ../../../node_modules/three/src/cameras/CubeCamera.js\\nvar fov = 90;\\nvar aspect = 1;\\nvar CubeCamera = class extends Object3D {\\n constructor(near, far, renderTarget) {\\n super();\\n this.type = \\\\\\\"CubeCamera\\\\\\\";\\n if (renderTarget.isWebGLCubeRenderTarget !== true) {\\n console.error(\\\\\\\"THREE.CubeCamera: The constructor now expects an instance of WebGLCubeRenderTarget as third parameter.\\\\\\\");\\n return;\\n }\\n this.renderTarget = renderTarget;\\n const cameraPX = new PerspectiveCamera(fov, aspect, near, far);\\n cameraPX.layers = this.layers;\\n cameraPX.up.set(0, -1, 0);\\n cameraPX.lookAt(new Vector3(1, 0, 0));\\n this.add(cameraPX);\\n const cameraNX = new PerspectiveCamera(fov, aspect, near, far);\\n cameraNX.layers = this.layers;\\n cameraNX.up.set(0, -1, 0);\\n cameraNX.lookAt(new Vector3(-1, 0, 0));\\n this.add(cameraNX);\\n const cameraPY = new PerspectiveCamera(fov, aspect, near, far);\\n cameraPY.layers = this.layers;\\n cameraPY.up.set(0, 0, 1);\\n cameraPY.lookAt(new Vector3(0, 1, 0));\\n this.add(cameraPY);\\n const cameraNY = new PerspectiveCamera(fov, aspect, near, far);\\n cameraNY.layers = this.layers;\\n cameraNY.up.set(0, 0, -1);\\n cameraNY.lookAt(new Vector3(0, -1, 0));\\n this.add(cameraNY);\\n const cameraPZ = new PerspectiveCamera(fov, aspect, near, far);\\n cameraPZ.layers = this.layers;\\n cameraPZ.up.set(0, -1, 0);\\n cameraPZ.lookAt(new Vector3(0, 0, 1));\\n this.add(cameraPZ);\\n const cameraNZ = new PerspectiveCamera(fov, aspect, near, far);\\n cameraNZ.layers = this.layers;\\n cameraNZ.up.set(0, -1, 0);\\n cameraNZ.lookAt(new Vector3(0, 0, -1));\\n this.add(cameraNZ);\\n }\\n update(renderer, scene) {\\n if (this.parent === null)\\n this.updateMatrixWorld();\\n const renderTarget = this.renderTarget;\\n const [cameraPX, cameraNX, cameraPY, cameraNY, cameraPZ, cameraNZ] = this.children;\\n const currentXrEnabled = renderer.xr.enabled;\\n const currentRenderTarget = renderer.getRenderTarget();\\n renderer.xr.enabled = false;\\n const generateMipmaps = renderTarget.texture.generateMipmaps;\\n renderTarget.texture.generateMipmaps = false;\\n renderer.setRenderTarget(renderTarget, 0);\\n renderer.render(scene, cameraPX);\\n renderer.setRenderTarget(renderTarget, 1);\\n renderer.render(scene, cameraNX);\\n renderer.setRenderTarget(renderTarget, 2);\\n renderer.render(scene, cameraPY);\\n renderer.setRenderTarget(renderTarget, 3);\\n renderer.render(scene, cameraNY);\\n renderer.setRenderTarget(renderTarget, 4);\\n renderer.render(scene, cameraPZ);\\n renderTarget.texture.generateMipmaps = generateMipmaps;\\n renderer.setRenderTarget(renderTarget, 5);\\n renderer.render(scene, cameraNZ);\\n renderer.setRenderTarget(currentRenderTarget);\\n renderer.xr.enabled = currentXrEnabled;\\n }\\n};\\n\\n// ../../../node_modules/three/src/textures/CubeTexture.js\\nvar CubeTexture = class extends Texture {\\n constructor(images, mapping, wrapS, wrapT, magFilter, minFilter, format, type, anisotropy, encoding) {\\n images = images !== void 0 ? images : [];\\n mapping = mapping !== void 0 ? mapping : CubeReflectionMapping;\\n super(images, mapping, wrapS, wrapT, magFilter, minFilter, format, type, anisotropy, encoding);\\n this.flipY = false;\\n }\\n get images() {\\n return this.image;\\n }\\n set images(value) {\\n this.image = value;\\n }\\n};\\nCubeTexture.prototype.isCubeTexture = true;\\n\\n// ../../../node_modules/three/src/renderers/WebGLCubeRenderTarget.js\\nvar WebGLCubeRenderTarget = class extends WebGLRenderTarget {\\n constructor(size, options, dummy) {\\n if (Number.isInteger(options)) {\\n console.warn(\\\\\\\"THREE.WebGLCubeRenderTarget: constructor signature is now WebGLCubeRenderTarget( size, options )\\\\\\\");\\n options = dummy;\\n }\\n super(size, size, options);\\n options = options || {};\\n this.texture = new CubeTexture(void 0, options.mapping, options.wrapS, options.wrapT, options.magFilter, options.minFilter, options.format, options.type, options.anisotropy, options.encoding);\\n this.texture.isRenderTargetTexture = true;\\n this.texture.generateMipmaps = options.generateMipmaps !== void 0 ? options.generateMipmaps : false;\\n this.texture.minFilter = options.minFilter !== void 0 ? options.minFilter : LinearFilter;\\n this.texture._needsFlipEnvMap = false;\\n }\\n fromEquirectangularTexture(renderer, texture) {\\n this.texture.type = texture.type;\\n this.texture.format = RGBAFormat;\\n this.texture.encoding = texture.encoding;\\n this.texture.generateMipmaps = texture.generateMipmaps;\\n this.texture.minFilter = texture.minFilter;\\n this.texture.magFilter = texture.magFilter;\\n const shader = {\\n uniforms: {\\n tEquirect: {value: null}\\n },\\n vertexShader: `\\n\\n\\t\\t\\t\\tvarying vec3 vWorldDirection;\\n\\n\\t\\t\\t\\tvec3 transformDirection( in vec3 dir, in mat4 matrix ) {\\n\\n\\t\\t\\t\\t\\treturn normalize( ( matrix * vec4( dir, 0.0 ) ).xyz );\\n\\n\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\tvoid main() {\\n\\n\\t\\t\\t\\t\\tvWorldDirection = transformDirection( position, modelMatrix );\\n\\n\\t\\t\\t\\t\\t#include \\n\\t\\t\\t\\t\\t#include \\n\\n\\t\\t\\t\\t}\\n\\t\\t\\t`,\\n fragmentShader: `\\n\\n\\t\\t\\t\\tuniform sampler2D tEquirect;\\n\\n\\t\\t\\t\\tvarying vec3 vWorldDirection;\\n\\n\\t\\t\\t\\t#include \\n\\n\\t\\t\\t\\tvoid main() {\\n\\n\\t\\t\\t\\t\\tvec3 direction = normalize( vWorldDirection );\\n\\n\\t\\t\\t\\t\\tvec2 sampleUV = equirectUv( direction );\\n\\n\\t\\t\\t\\t\\tgl_FragColor = texture2D( tEquirect, sampleUV );\\n\\n\\t\\t\\t\\t}\\n\\t\\t\\t`\\n };\\n const geometry = new BoxGeometry(5, 5, 5);\\n const material = new ShaderMaterial({\\n name: \\\\\\\"CubemapFromEquirect\\\\\\\",\\n uniforms: cloneUniforms(shader.uniforms),\\n vertexShader: shader.vertexShader,\\n fragmentShader: shader.fragmentShader,\\n side: BackSide,\\n blending: NoBlending\\n });\\n material.uniforms.tEquirect.value = texture;\\n const mesh = new Mesh(geometry, material);\\n const currentMinFilter = texture.minFilter;\\n if (texture.minFilter === LinearMipmapLinearFilter)\\n texture.minFilter = LinearFilter;\\n const camera = new CubeCamera(1, 10, this);\\n camera.update(renderer, mesh);\\n texture.minFilter = currentMinFilter;\\n mesh.geometry.dispose();\\n mesh.material.dispose();\\n return this;\\n }\\n clear(renderer, color, depth2, stencil) {\\n const currentRenderTarget = renderer.getRenderTarget();\\n for (let i = 0; i < 6; i++) {\\n renderer.setRenderTarget(this, i);\\n renderer.clear(color, depth2, stencil);\\n }\\n renderer.setRenderTarget(currentRenderTarget);\\n }\\n};\\nWebGLCubeRenderTarget.prototype.isWebGLCubeRenderTarget = true;\\n\\n// ../../../node_modules/three/src/renderers/webgl/WebGLCubeMaps.js\\nfunction WebGLCubeMaps(renderer) {\\n let cubemaps = new WeakMap();\\n function mapTextureMapping(texture, mapping) {\\n if (mapping === EquirectangularReflectionMapping) {\\n texture.mapping = CubeReflectionMapping;\\n } else if (mapping === EquirectangularRefractionMapping) {\\n texture.mapping = CubeRefractionMapping;\\n }\\n return texture;\\n }\\n function get(texture) {\\n if (texture && texture.isTexture && texture.isRenderTargetTexture === false) {\\n const mapping = texture.mapping;\\n if (mapping === EquirectangularReflectionMapping || mapping === EquirectangularRefractionMapping) {\\n if (cubemaps.has(texture)) {\\n const cubemap = cubemaps.get(texture).texture;\\n return mapTextureMapping(cubemap, texture.mapping);\\n } else {\\n const image = texture.image;\\n if (image && image.height > 0) {\\n const currentRenderTarget = renderer.getRenderTarget();\\n const renderTarget = new WebGLCubeRenderTarget(image.height / 2);\\n renderTarget.fromEquirectangularTexture(renderer, texture);\\n cubemaps.set(texture, renderTarget);\\n renderer.setRenderTarget(currentRenderTarget);\\n texture.addEventListener(\\\\\\\"dispose\\\\\\\", onTextureDispose);\\n return mapTextureMapping(renderTarget.texture, texture.mapping);\\n } else {\\n return null;\\n }\\n }\\n }\\n }\\n return texture;\\n }\\n function onTextureDispose(event) {\\n const texture = event.target;\\n texture.removeEventListener(\\\\\\\"dispose\\\\\\\", onTextureDispose);\\n const cubemap = cubemaps.get(texture);\\n if (cubemap !== void 0) {\\n cubemaps.delete(texture);\\n cubemap.dispose();\\n }\\n }\\n function dispose() {\\n cubemaps = new WeakMap();\\n }\\n return {\\n get,\\n dispose\\n };\\n}\\n\\n// ../../../node_modules/three/src/cameras/OrthographicCamera.js\\nvar OrthographicCamera = class extends Camera {\\n constructor(left = -1, right = 1, top = 1, bottom = -1, near = 0.1, far = 2e3) {\\n super();\\n this.type = \\\\\\\"OrthographicCamera\\\\\\\";\\n this.zoom = 1;\\n this.view = null;\\n this.left = left;\\n this.right = right;\\n this.top = top;\\n this.bottom = bottom;\\n this.near = near;\\n this.far = far;\\n this.updateProjectionMatrix();\\n }\\n copy(source, recursive) {\\n super.copy(source, recursive);\\n this.left = source.left;\\n this.right = source.right;\\n this.top = source.top;\\n this.bottom = source.bottom;\\n this.near = source.near;\\n this.far = source.far;\\n this.zoom = source.zoom;\\n this.view = source.view === null ? null : Object.assign({}, source.view);\\n return this;\\n }\\n setViewOffset(fullWidth, fullHeight, x, y, width, height) {\\n if (this.view === null) {\\n this.view = {\\n enabled: true,\\n fullWidth: 1,\\n fullHeight: 1,\\n offsetX: 0,\\n offsetY: 0,\\n width: 1,\\n height: 1\\n };\\n }\\n this.view.enabled = true;\\n this.view.fullWidth = fullWidth;\\n this.view.fullHeight = fullHeight;\\n this.view.offsetX = x;\\n this.view.offsetY = y;\\n this.view.width = width;\\n this.view.height = height;\\n this.updateProjectionMatrix();\\n }\\n clearViewOffset() {\\n if (this.view !== null) {\\n this.view.enabled = false;\\n }\\n this.updateProjectionMatrix();\\n }\\n updateProjectionMatrix() {\\n const dx = (this.right - this.left) / (2 * this.zoom);\\n const dy = (this.top - this.bottom) / (2 * this.zoom);\\n const cx = (this.right + this.left) / 2;\\n const cy = (this.top + this.bottom) / 2;\\n let left = cx - dx;\\n let right = cx + dx;\\n let top = cy + dy;\\n let bottom = cy - dy;\\n if (this.view !== null && this.view.enabled) {\\n const scaleW = (this.right - this.left) / this.view.fullWidth / this.zoom;\\n const scaleH = (this.top - this.bottom) / this.view.fullHeight / this.zoom;\\n left += scaleW * this.view.offsetX;\\n right = left + scaleW * this.view.width;\\n top -= scaleH * this.view.offsetY;\\n bottom = top - scaleH * this.view.height;\\n }\\n this.projectionMatrix.makeOrthographic(left, right, top, bottom, this.near, this.far);\\n this.projectionMatrixInverse.copy(this.projectionMatrix).invert();\\n }\\n toJSON(meta) {\\n const data = super.toJSON(meta);\\n data.object.zoom = this.zoom;\\n data.object.left = this.left;\\n data.object.right = this.right;\\n data.object.top = this.top;\\n data.object.bottom = this.bottom;\\n data.object.near = this.near;\\n data.object.far = this.far;\\n if (this.view !== null)\\n data.object.view = Object.assign({}, this.view);\\n return data;\\n }\\n};\\nOrthographicCamera.prototype.isOrthographicCamera = true;\\n\\n// ../../../node_modules/three/src/materials/RawShaderMaterial.js\\nvar RawShaderMaterial = class extends ShaderMaterial {\\n constructor(parameters) {\\n super(parameters);\\n this.type = \\\\\\\"RawShaderMaterial\\\\\\\";\\n }\\n};\\nRawShaderMaterial.prototype.isRawShaderMaterial = true;\\n\\n// ../../../node_modules/three/src/extras/PMREMGenerator.js\\nvar LOD_MIN = 4;\\nvar LOD_MAX = 8;\\nvar SIZE_MAX = Math.pow(2, LOD_MAX);\\nvar EXTRA_LOD_SIGMA = [0.125, 0.215, 0.35, 0.446, 0.526, 0.582];\\nvar TOTAL_LODS = LOD_MAX - LOD_MIN + 1 + EXTRA_LOD_SIGMA.length;\\nvar MAX_SAMPLES = 20;\\nvar ENCODINGS = {\\n [LinearEncoding]: 0,\\n [sRGBEncoding]: 1,\\n [RGBEEncoding]: 2,\\n [RGBM7Encoding]: 3,\\n [RGBM16Encoding]: 4,\\n [RGBDEncoding]: 5,\\n [GammaEncoding]: 6\\n};\\nvar _flatCamera = /* @__PURE__ */ new OrthographicCamera();\\nvar {_lodPlanes, _sizeLods, _sigmas} = /* @__PURE__ */ _createPlanes();\\nvar _clearColor = /* @__PURE__ */ new Color();\\nvar _oldTarget = null;\\nvar PHI = (1 + Math.sqrt(5)) / 2;\\nvar INV_PHI = 1 / PHI;\\nvar _axisDirections = [\\n /* @__PURE__ */ new Vector3(1, 1, 1),\\n /* @__PURE__ */ new Vector3(-1, 1, 1),\\n /* @__PURE__ */ new Vector3(1, 1, -1),\\n /* @__PURE__ */ new Vector3(-1, 1, -1),\\n /* @__PURE__ */ new Vector3(0, PHI, INV_PHI),\\n /* @__PURE__ */ new Vector3(0, PHI, -INV_PHI),\\n /* @__PURE__ */ new Vector3(INV_PHI, 0, PHI),\\n /* @__PURE__ */ new Vector3(-INV_PHI, 0, PHI),\\n /* @__PURE__ */ new Vector3(PHI, INV_PHI, 0),\\n /* @__PURE__ */ new Vector3(-PHI, INV_PHI, 0)\\n];\\nvar PMREMGenerator = class {\\n constructor(renderer) {\\n this._renderer = renderer;\\n this._pingPongRenderTarget = null;\\n this._blurMaterial = _getBlurShader(MAX_SAMPLES);\\n this._equirectShader = null;\\n this._cubemapShader = null;\\n this._compileMaterial(this._blurMaterial);\\n }\\n fromScene(scene, sigma = 0, near = 0.1, far = 100) {\\n _oldTarget = this._renderer.getRenderTarget();\\n const cubeUVRenderTarget = this._allocateTargets();\\n this._sceneToCubeUV(scene, near, far, cubeUVRenderTarget);\\n if (sigma > 0) {\\n this._blur(cubeUVRenderTarget, 0, 0, sigma);\\n }\\n this._applyPMREM(cubeUVRenderTarget);\\n this._cleanup(cubeUVRenderTarget);\\n return cubeUVRenderTarget;\\n }\\n fromEquirectangular(equirectangular) {\\n return this._fromTexture(equirectangular);\\n }\\n fromCubemap(cubemap) {\\n return this._fromTexture(cubemap);\\n }\\n compileCubemapShader() {\\n if (this._cubemapShader === null) {\\n this._cubemapShader = _getCubemapShader();\\n this._compileMaterial(this._cubemapShader);\\n }\\n }\\n compileEquirectangularShader() {\\n if (this._equirectShader === null) {\\n this._equirectShader = _getEquirectShader();\\n this._compileMaterial(this._equirectShader);\\n }\\n }\\n dispose() {\\n this._blurMaterial.dispose();\\n if (this._cubemapShader !== null)\\n this._cubemapShader.dispose();\\n if (this._equirectShader !== null)\\n this._equirectShader.dispose();\\n for (let i = 0; i < _lodPlanes.length; i++) {\\n _lodPlanes[i].dispose();\\n }\\n }\\n _cleanup(outputTarget) {\\n this._pingPongRenderTarget.dispose();\\n this._renderer.setRenderTarget(_oldTarget);\\n outputTarget.scissorTest = false;\\n _setViewport(outputTarget, 0, 0, outputTarget.width, outputTarget.height);\\n }\\n _fromTexture(texture) {\\n _oldTarget = this._renderer.getRenderTarget();\\n const cubeUVRenderTarget = this._allocateTargets(texture);\\n this._textureToCubeUV(texture, cubeUVRenderTarget);\\n this._applyPMREM(cubeUVRenderTarget);\\n this._cleanup(cubeUVRenderTarget);\\n return cubeUVRenderTarget;\\n }\\n _allocateTargets(texture) {\\n const params = {\\n magFilter: NearestFilter,\\n minFilter: NearestFilter,\\n generateMipmaps: false,\\n type: UnsignedByteType,\\n format: RGBEFormat,\\n encoding: _isLDR(texture) ? texture.encoding : RGBEEncoding,\\n depthBuffer: false\\n };\\n const cubeUVRenderTarget = _createRenderTarget(params);\\n cubeUVRenderTarget.depthBuffer = texture ? false : true;\\n this._pingPongRenderTarget = _createRenderTarget(params);\\n return cubeUVRenderTarget;\\n }\\n _compileMaterial(material) {\\n const tmpMesh = new Mesh(_lodPlanes[0], material);\\n this._renderer.compile(tmpMesh, _flatCamera);\\n }\\n _sceneToCubeUV(scene, near, far, cubeUVRenderTarget) {\\n const fov2 = 90;\\n const aspect2 = 1;\\n const cubeCamera = new PerspectiveCamera(fov2, aspect2, near, far);\\n const upSign = [1, -1, 1, 1, 1, 1];\\n const forwardSign = [1, 1, 1, -1, -1, -1];\\n const renderer = this._renderer;\\n const originalAutoClear = renderer.autoClear;\\n const outputEncoding = renderer.outputEncoding;\\n const toneMapping = renderer.toneMapping;\\n renderer.getClearColor(_clearColor);\\n renderer.toneMapping = NoToneMapping;\\n renderer.outputEncoding = LinearEncoding;\\n renderer.autoClear = false;\\n const backgroundMaterial = new MeshBasicMaterial({\\n name: \\\\\\\"PMREM.Background\\\\\\\",\\n side: BackSide,\\n depthWrite: false,\\n depthTest: false\\n });\\n const backgroundBox = new Mesh(new BoxGeometry(), backgroundMaterial);\\n let useSolidColor = false;\\n const background2 = scene.background;\\n if (background2) {\\n if (background2.isColor) {\\n backgroundMaterial.color.copy(background2);\\n scene.background = null;\\n useSolidColor = true;\\n }\\n } else {\\n backgroundMaterial.color.copy(_clearColor);\\n useSolidColor = true;\\n }\\n for (let i = 0; i < 6; i++) {\\n const col = i % 3;\\n if (col == 0) {\\n cubeCamera.up.set(0, upSign[i], 0);\\n cubeCamera.lookAt(forwardSign[i], 0, 0);\\n } else if (col == 1) {\\n cubeCamera.up.set(0, 0, upSign[i]);\\n cubeCamera.lookAt(0, forwardSign[i], 0);\\n } else {\\n cubeCamera.up.set(0, upSign[i], 0);\\n cubeCamera.lookAt(0, 0, forwardSign[i]);\\n }\\n _setViewport(cubeUVRenderTarget, col * SIZE_MAX, i > 2 ? SIZE_MAX : 0, SIZE_MAX, SIZE_MAX);\\n renderer.setRenderTarget(cubeUVRenderTarget);\\n if (useSolidColor) {\\n renderer.render(backgroundBox, cubeCamera);\\n }\\n renderer.render(scene, cubeCamera);\\n }\\n backgroundBox.geometry.dispose();\\n backgroundBox.material.dispose();\\n renderer.toneMapping = toneMapping;\\n renderer.outputEncoding = outputEncoding;\\n renderer.autoClear = originalAutoClear;\\n scene.background = background2;\\n }\\n _setEncoding(uniform, texture) {\\n if (this._renderer.capabilities.isWebGL2 === true && texture.format === RGBAFormat && texture.type === UnsignedByteType && texture.encoding === sRGBEncoding) {\\n uniform.value = ENCODINGS[LinearEncoding];\\n } else {\\n uniform.value = ENCODINGS[texture.encoding];\\n }\\n }\\n _textureToCubeUV(texture, cubeUVRenderTarget) {\\n const renderer = this._renderer;\\n if (texture.isCubeTexture) {\\n if (this._cubemapShader == null) {\\n this._cubemapShader = _getCubemapShader();\\n }\\n } else {\\n if (this._equirectShader == null) {\\n this._equirectShader = _getEquirectShader();\\n }\\n }\\n const material = texture.isCubeTexture ? this._cubemapShader : this._equirectShader;\\n const mesh = new Mesh(_lodPlanes[0], material);\\n const uniforms = material.uniforms;\\n uniforms[\\\\\\\"envMap\\\\\\\"].value = texture;\\n if (!texture.isCubeTexture) {\\n uniforms[\\\\\\\"texelSize\\\\\\\"].value.set(1 / texture.image.width, 1 / texture.image.height);\\n }\\n this._setEncoding(uniforms[\\\\\\\"inputEncoding\\\\\\\"], texture);\\n this._setEncoding(uniforms[\\\\\\\"outputEncoding\\\\\\\"], cubeUVRenderTarget.texture);\\n _setViewport(cubeUVRenderTarget, 0, 0, 3 * SIZE_MAX, 2 * SIZE_MAX);\\n renderer.setRenderTarget(cubeUVRenderTarget);\\n renderer.render(mesh, _flatCamera);\\n }\\n _applyPMREM(cubeUVRenderTarget) {\\n const renderer = this._renderer;\\n const autoClear = renderer.autoClear;\\n renderer.autoClear = false;\\n for (let i = 1; i < TOTAL_LODS; i++) {\\n const sigma = Math.sqrt(_sigmas[i] * _sigmas[i] - _sigmas[i - 1] * _sigmas[i - 1]);\\n const poleAxis = _axisDirections[(i - 1) % _axisDirections.length];\\n this._blur(cubeUVRenderTarget, i - 1, i, sigma, poleAxis);\\n }\\n renderer.autoClear = autoClear;\\n }\\n _blur(cubeUVRenderTarget, lodIn, lodOut, sigma, poleAxis) {\\n const pingPongRenderTarget = this._pingPongRenderTarget;\\n this._halfBlur(cubeUVRenderTarget, pingPongRenderTarget, lodIn, lodOut, sigma, \\\\\\\"latitudinal\\\\\\\", poleAxis);\\n this._halfBlur(pingPongRenderTarget, cubeUVRenderTarget, lodOut, lodOut, sigma, \\\\\\\"longitudinal\\\\\\\", poleAxis);\\n }\\n _halfBlur(targetIn, targetOut, lodIn, lodOut, sigmaRadians, direction, poleAxis) {\\n const renderer = this._renderer;\\n const blurMaterial = this._blurMaterial;\\n if (direction !== \\\\\\\"latitudinal\\\\\\\" && direction !== \\\\\\\"longitudinal\\\\\\\") {\\n console.error(\\\\\\\"blur direction must be either latitudinal or longitudinal!\\\\\\\");\\n }\\n const STANDARD_DEVIATIONS = 3;\\n const blurMesh = new Mesh(_lodPlanes[lodOut], blurMaterial);\\n const blurUniforms = blurMaterial.uniforms;\\n const pixels = _sizeLods[lodIn] - 1;\\n const radiansPerPixel = isFinite(sigmaRadians) ? Math.PI / (2 * pixels) : 2 * Math.PI / (2 * MAX_SAMPLES - 1);\\n const sigmaPixels = sigmaRadians / radiansPerPixel;\\n const samples = isFinite(sigmaRadians) ? 1 + Math.floor(STANDARD_DEVIATIONS * sigmaPixels) : MAX_SAMPLES;\\n if (samples > MAX_SAMPLES) {\\n console.warn(`sigmaRadians, ${sigmaRadians}, is too large and will clip, as it requested ${samples} samples when the maximum is set to ${MAX_SAMPLES}`);\\n }\\n const weights = [];\\n let sum = 0;\\n for (let i = 0; i < MAX_SAMPLES; ++i) {\\n const x2 = i / sigmaPixels;\\n const weight = Math.exp(-x2 * x2 / 2);\\n weights.push(weight);\\n if (i == 0) {\\n sum += weight;\\n } else if (i < samples) {\\n sum += 2 * weight;\\n }\\n }\\n for (let i = 0; i < weights.length; i++) {\\n weights[i] = weights[i] / sum;\\n }\\n blurUniforms[\\\\\\\"envMap\\\\\\\"].value = targetIn.texture;\\n blurUniforms[\\\\\\\"samples\\\\\\\"].value = samples;\\n blurUniforms[\\\\\\\"weights\\\\\\\"].value = weights;\\n blurUniforms[\\\\\\\"latitudinal\\\\\\\"].value = direction === \\\\\\\"latitudinal\\\\\\\";\\n if (poleAxis) {\\n blurUniforms[\\\\\\\"poleAxis\\\\\\\"].value = poleAxis;\\n }\\n blurUniforms[\\\\\\\"dTheta\\\\\\\"].value = radiansPerPixel;\\n blurUniforms[\\\\\\\"mipInt\\\\\\\"].value = LOD_MAX - lodIn;\\n this._setEncoding(blurUniforms[\\\\\\\"inputEncoding\\\\\\\"], targetIn.texture);\\n this._setEncoding(blurUniforms[\\\\\\\"outputEncoding\\\\\\\"], targetIn.texture);\\n const outputSize = _sizeLods[lodOut];\\n const x = 3 * Math.max(0, SIZE_MAX - 2 * outputSize);\\n const y = (lodOut === 0 ? 0 : 2 * SIZE_MAX) + 2 * outputSize * (lodOut > LOD_MAX - LOD_MIN ? lodOut - LOD_MAX + LOD_MIN : 0);\\n _setViewport(targetOut, x, y, 3 * outputSize, 2 * outputSize);\\n renderer.setRenderTarget(targetOut);\\n renderer.render(blurMesh, _flatCamera);\\n }\\n};\\nfunction _isLDR(texture) {\\n if (texture === void 0 || texture.type !== UnsignedByteType)\\n return false;\\n return texture.encoding === LinearEncoding || texture.encoding === sRGBEncoding || texture.encoding === GammaEncoding;\\n}\\nfunction _createPlanes() {\\n const _lodPlanes2 = [];\\n const _sizeLods2 = [];\\n const _sigmas2 = [];\\n let lod = LOD_MAX;\\n for (let i = 0; i < TOTAL_LODS; i++) {\\n const sizeLod = Math.pow(2, lod);\\n _sizeLods2.push(sizeLod);\\n let sigma = 1 / sizeLod;\\n if (i > LOD_MAX - LOD_MIN) {\\n sigma = EXTRA_LOD_SIGMA[i - LOD_MAX + LOD_MIN - 1];\\n } else if (i == 0) {\\n sigma = 0;\\n }\\n _sigmas2.push(sigma);\\n const texelSize = 1 / (sizeLod - 1);\\n const min = -texelSize / 2;\\n const max = 1 + texelSize / 2;\\n const uv1 = [min, min, max, min, max, max, min, min, max, max, min, max];\\n const cubeFaces = 6;\\n const vertices = 6;\\n const positionSize = 3;\\n const uvSize = 2;\\n const faceIndexSize = 1;\\n const position = new Float32Array(positionSize * vertices * cubeFaces);\\n const uv = new Float32Array(uvSize * vertices * cubeFaces);\\n const faceIndex = new Float32Array(faceIndexSize * vertices * cubeFaces);\\n for (let face = 0; face < cubeFaces; face++) {\\n const x = face % 3 * 2 / 3 - 1;\\n const y = face > 2 ? 0 : -1;\\n const coordinates = [\\n x,\\n y,\\n 0,\\n x + 2 / 3,\\n y,\\n 0,\\n x + 2 / 3,\\n y + 1,\\n 0,\\n x,\\n y,\\n 0,\\n x + 2 / 3,\\n y + 1,\\n 0,\\n x,\\n y + 1,\\n 0\\n ];\\n position.set(coordinates, positionSize * vertices * face);\\n uv.set(uv1, uvSize * vertices * face);\\n const fill = [face, face, face, face, face, face];\\n faceIndex.set(fill, faceIndexSize * vertices * face);\\n }\\n const planes = new BufferGeometry();\\n planes.setAttribute(\\\\\\\"position\\\\\\\", new BufferAttribute(position, positionSize));\\n planes.setAttribute(\\\\\\\"uv\\\\\\\", new BufferAttribute(uv, uvSize));\\n planes.setAttribute(\\\\\\\"faceIndex\\\\\\\", new BufferAttribute(faceIndex, faceIndexSize));\\n _lodPlanes2.push(planes);\\n if (lod > LOD_MIN) {\\n lod--;\\n }\\n }\\n return {_lodPlanes: _lodPlanes2, _sizeLods: _sizeLods2, _sigmas: _sigmas2};\\n}\\nfunction _createRenderTarget(params) {\\n const cubeUVRenderTarget = new WebGLRenderTarget(3 * SIZE_MAX, 3 * SIZE_MAX, params);\\n cubeUVRenderTarget.texture.mapping = CubeUVReflectionMapping;\\n cubeUVRenderTarget.texture.name = \\\\\\\"PMREM.cubeUv\\\\\\\";\\n cubeUVRenderTarget.scissorTest = true;\\n return cubeUVRenderTarget;\\n}\\nfunction _setViewport(target, x, y, width, height) {\\n target.viewport.set(x, y, width, height);\\n target.scissor.set(x, y, width, height);\\n}\\nfunction _getBlurShader(maxSamples) {\\n const weights = new Float32Array(maxSamples);\\n const poleAxis = new Vector3(0, 1, 0);\\n const shaderMaterial = new RawShaderMaterial({\\n name: \\\\\\\"SphericalGaussianBlur\\\\\\\",\\n defines: {n: maxSamples},\\n uniforms: {\\n envMap: {value: null},\\n samples: {value: 1},\\n weights: {value: weights},\\n latitudinal: {value: false},\\n dTheta: {value: 0},\\n mipInt: {value: 0},\\n poleAxis: {value: poleAxis},\\n inputEncoding: {value: ENCODINGS[LinearEncoding]},\\n outputEncoding: {value: ENCODINGS[LinearEncoding]}\\n },\\n vertexShader: _getCommonVertexShader(),\\n fragmentShader: `\\n\\n\\t\\t\\tprecision mediump float;\\n\\t\\t\\tprecision mediump int;\\n\\n\\t\\t\\tvarying vec3 vOutputDirection;\\n\\n\\t\\t\\tuniform sampler2D envMap;\\n\\t\\t\\tuniform int samples;\\n\\t\\t\\tuniform float weights[ n ];\\n\\t\\t\\tuniform bool latitudinal;\\n\\t\\t\\tuniform float dTheta;\\n\\t\\t\\tuniform float mipInt;\\n\\t\\t\\tuniform vec3 poleAxis;\\n\\n\\t\\t\\t${_getEncodings()}\\n\\n\\t\\t\\t#define ENVMAP_TYPE_CUBE_UV\\n\\t\\t\\t#include \\n\\n\\t\\t\\tvec3 getSample( float theta, vec3 axis ) {\\n\\n\\t\\t\\t\\tfloat cosTheta = cos( theta );\\n\\t\\t\\t\\t// Rodrigues' axis-angle rotation\\n\\t\\t\\t\\tvec3 sampleDirection = vOutputDirection * cosTheta\\n\\t\\t\\t\\t\\t+ cross( axis, vOutputDirection ) * sin( theta )\\n\\t\\t\\t\\t\\t+ axis * dot( axis, vOutputDirection ) * ( 1.0 - cosTheta );\\n\\n\\t\\t\\t\\treturn bilinearCubeUV( envMap, sampleDirection, mipInt );\\n\\n\\t\\t\\t}\\n\\n\\t\\t\\tvoid main() {\\n\\n\\t\\t\\t\\tvec3 axis = latitudinal ? poleAxis : cross( poleAxis, vOutputDirection );\\n\\n\\t\\t\\t\\tif ( all( equal( axis, vec3( 0.0 ) ) ) ) {\\n\\n\\t\\t\\t\\t\\taxis = vec3( vOutputDirection.z, 0.0, - vOutputDirection.x );\\n\\n\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\taxis = normalize( axis );\\n\\n\\t\\t\\t\\tgl_FragColor = vec4( 0.0, 0.0, 0.0, 1.0 );\\n\\t\\t\\t\\tgl_FragColor.rgb += weights[ 0 ] * getSample( 0.0, axis );\\n\\n\\t\\t\\t\\tfor ( int i = 1; i < n; i++ ) {\\n\\n\\t\\t\\t\\t\\tif ( i >= samples ) {\\n\\n\\t\\t\\t\\t\\t\\tbreak;\\n\\n\\t\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\t\\tfloat theta = dTheta * float( i );\\n\\t\\t\\t\\t\\tgl_FragColor.rgb += weights[ i ] * getSample( -1.0 * theta, axis );\\n\\t\\t\\t\\t\\tgl_FragColor.rgb += weights[ i ] * getSample( theta, axis );\\n\\n\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\tgl_FragColor = linearToOutputTexel( gl_FragColor );\\n\\n\\t\\t\\t}\\n\\t\\t`,\\n blending: NoBlending,\\n depthTest: false,\\n depthWrite: false\\n });\\n return shaderMaterial;\\n}\\nfunction _getEquirectShader() {\\n const texelSize = new Vector2(1, 1);\\n const shaderMaterial = new RawShaderMaterial({\\n name: \\\\\\\"EquirectangularToCubeUV\\\\\\\",\\n uniforms: {\\n envMap: {value: null},\\n texelSize: {value: texelSize},\\n inputEncoding: {value: ENCODINGS[LinearEncoding]},\\n outputEncoding: {value: ENCODINGS[LinearEncoding]}\\n },\\n vertexShader: _getCommonVertexShader(),\\n fragmentShader: `\\n\\n\\t\\t\\tprecision mediump float;\\n\\t\\t\\tprecision mediump int;\\n\\n\\t\\t\\tvarying vec3 vOutputDirection;\\n\\n\\t\\t\\tuniform sampler2D envMap;\\n\\t\\t\\tuniform vec2 texelSize;\\n\\n\\t\\t\\t${_getEncodings()}\\n\\n\\t\\t\\t#include \\n\\n\\t\\t\\tvoid main() {\\n\\n\\t\\t\\t\\tgl_FragColor = vec4( 0.0, 0.0, 0.0, 1.0 );\\n\\n\\t\\t\\t\\tvec3 outputDirection = normalize( vOutputDirection );\\n\\t\\t\\t\\tvec2 uv = equirectUv( outputDirection );\\n\\n\\t\\t\\t\\tvec2 f = fract( uv / texelSize - 0.5 );\\n\\t\\t\\t\\tuv -= f * texelSize;\\n\\t\\t\\t\\tvec3 tl = envMapTexelToLinear( texture2D ( envMap, uv ) ).rgb;\\n\\t\\t\\t\\tuv.x += texelSize.x;\\n\\t\\t\\t\\tvec3 tr = envMapTexelToLinear( texture2D ( envMap, uv ) ).rgb;\\n\\t\\t\\t\\tuv.y += texelSize.y;\\n\\t\\t\\t\\tvec3 br = envMapTexelToLinear( texture2D ( envMap, uv ) ).rgb;\\n\\t\\t\\t\\tuv.x -= texelSize.x;\\n\\t\\t\\t\\tvec3 bl = envMapTexelToLinear( texture2D ( envMap, uv ) ).rgb;\\n\\n\\t\\t\\t\\tvec3 tm = mix( tl, tr, f.x );\\n\\t\\t\\t\\tvec3 bm = mix( bl, br, f.x );\\n\\t\\t\\t\\tgl_FragColor.rgb = mix( tm, bm, f.y );\\n\\n\\t\\t\\t\\tgl_FragColor = linearToOutputTexel( gl_FragColor );\\n\\n\\t\\t\\t}\\n\\t\\t`,\\n blending: NoBlending,\\n depthTest: false,\\n depthWrite: false\\n });\\n return shaderMaterial;\\n}\\nfunction _getCubemapShader() {\\n const shaderMaterial = new RawShaderMaterial({\\n name: \\\\\\\"CubemapToCubeUV\\\\\\\",\\n uniforms: {\\n envMap: {value: null},\\n inputEncoding: {value: ENCODINGS[LinearEncoding]},\\n outputEncoding: {value: ENCODINGS[LinearEncoding]}\\n },\\n vertexShader: _getCommonVertexShader(),\\n fragmentShader: `\\n\\n\\t\\t\\tprecision mediump float;\\n\\t\\t\\tprecision mediump int;\\n\\n\\t\\t\\tvarying vec3 vOutputDirection;\\n\\n\\t\\t\\tuniform samplerCube envMap;\\n\\n\\t\\t\\t${_getEncodings()}\\n\\n\\t\\t\\tvoid main() {\\n\\n\\t\\t\\t\\tgl_FragColor = vec4( 0.0, 0.0, 0.0, 1.0 );\\n\\t\\t\\t\\tgl_FragColor.rgb = envMapTexelToLinear( textureCube( envMap, vec3( - vOutputDirection.x, vOutputDirection.yz ) ) ).rgb;\\n\\t\\t\\t\\tgl_FragColor = linearToOutputTexel( gl_FragColor );\\n\\n\\t\\t\\t}\\n\\t\\t`,\\n blending: NoBlending,\\n depthTest: false,\\n depthWrite: false\\n });\\n return shaderMaterial;\\n}\\nfunction _getCommonVertexShader() {\\n return `\\n\\n\\t\\tprecision mediump float;\\n\\t\\tprecision mediump int;\\n\\n\\t\\tattribute vec3 position;\\n\\t\\tattribute vec2 uv;\\n\\t\\tattribute float faceIndex;\\n\\n\\t\\tvarying vec3 vOutputDirection;\\n\\n\\t\\t// RH coordinate system; PMREM face-indexing convention\\n\\t\\tvec3 getDirection( vec2 uv, float face ) {\\n\\n\\t\\t\\tuv = 2.0 * uv - 1.0;\\n\\n\\t\\t\\tvec3 direction = vec3( uv, 1.0 );\\n\\n\\t\\t\\tif ( face == 0.0 ) {\\n\\n\\t\\t\\t\\tdirection = direction.zyx; // ( 1, v, u ) pos x\\n\\n\\t\\t\\t} else if ( face == 1.0 ) {\\n\\n\\t\\t\\t\\tdirection = direction.xzy;\\n\\t\\t\\t\\tdirection.xz *= -1.0; // ( -u, 1, -v ) pos y\\n\\n\\t\\t\\t} else if ( face == 2.0 ) {\\n\\n\\t\\t\\t\\tdirection.x *= -1.0; // ( -u, v, 1 ) pos z\\n\\n\\t\\t\\t} else if ( face == 3.0 ) {\\n\\n\\t\\t\\t\\tdirection = direction.zyx;\\n\\t\\t\\t\\tdirection.xz *= -1.0; // ( -1, v, -u ) neg x\\n\\n\\t\\t\\t} else if ( face == 4.0 ) {\\n\\n\\t\\t\\t\\tdirection = direction.xzy;\\n\\t\\t\\t\\tdirection.xy *= -1.0; // ( -u, -1, v ) neg y\\n\\n\\t\\t\\t} else if ( face == 5.0 ) {\\n\\n\\t\\t\\t\\tdirection.z *= -1.0; // ( u, v, -1 ) neg z\\n\\n\\t\\t\\t}\\n\\n\\t\\t\\treturn direction;\\n\\n\\t\\t}\\n\\n\\t\\tvoid main() {\\n\\n\\t\\t\\tvOutputDirection = getDirection( uv, faceIndex );\\n\\t\\t\\tgl_Position = vec4( position, 1.0 );\\n\\n\\t\\t}\\n\\t`;\\n}\\nfunction _getEncodings() {\\n return `\\n\\n\\t\\tuniform int inputEncoding;\\n\\t\\tuniform int outputEncoding;\\n\\n\\t\\t#include \\n\\n\\t\\tvec4 inputTexelToLinear( vec4 value ) {\\n\\n\\t\\t\\tif ( inputEncoding == 0 ) {\\n\\n\\t\\t\\t\\treturn value;\\n\\n\\t\\t\\t} else if ( inputEncoding == 1 ) {\\n\\n\\t\\t\\t\\treturn sRGBToLinear( value );\\n\\n\\t\\t\\t} else if ( inputEncoding == 2 ) {\\n\\n\\t\\t\\t\\treturn RGBEToLinear( value );\\n\\n\\t\\t\\t} else if ( inputEncoding == 3 ) {\\n\\n\\t\\t\\t\\treturn RGBMToLinear( value, 7.0 );\\n\\n\\t\\t\\t} else if ( inputEncoding == 4 ) {\\n\\n\\t\\t\\t\\treturn RGBMToLinear( value, 16.0 );\\n\\n\\t\\t\\t} else if ( inputEncoding == 5 ) {\\n\\n\\t\\t\\t\\treturn RGBDToLinear( value, 256.0 );\\n\\n\\t\\t\\t} else {\\n\\n\\t\\t\\t\\treturn GammaToLinear( value, 2.2 );\\n\\n\\t\\t\\t}\\n\\n\\t\\t}\\n\\n\\t\\tvec4 linearToOutputTexel( vec4 value ) {\\n\\n\\t\\t\\tif ( outputEncoding == 0 ) {\\n\\n\\t\\t\\t\\treturn value;\\n\\n\\t\\t\\t} else if ( outputEncoding == 1 ) {\\n\\n\\t\\t\\t\\treturn LinearTosRGB( value );\\n\\n\\t\\t\\t} else if ( outputEncoding == 2 ) {\\n\\n\\t\\t\\t\\treturn LinearToRGBE( value );\\n\\n\\t\\t\\t} else if ( outputEncoding == 3 ) {\\n\\n\\t\\t\\t\\treturn LinearToRGBM( value, 7.0 );\\n\\n\\t\\t\\t} else if ( outputEncoding == 4 ) {\\n\\n\\t\\t\\t\\treturn LinearToRGBM( value, 16.0 );\\n\\n\\t\\t\\t} else if ( outputEncoding == 5 ) {\\n\\n\\t\\t\\t\\treturn LinearToRGBD( value, 256.0 );\\n\\n\\t\\t\\t} else {\\n\\n\\t\\t\\t\\treturn LinearToGamma( value, 2.2 );\\n\\n\\t\\t\\t}\\n\\n\\t\\t}\\n\\n\\t\\tvec4 envMapTexelToLinear( vec4 color ) {\\n\\n\\t\\t\\treturn inputTexelToLinear( color );\\n\\n\\t\\t}\\n\\t`;\\n}\\n\\n// ../../../node_modules/three/src/renderers/webgl/WebGLCubeUVMaps.js\\nfunction WebGLCubeUVMaps(renderer) {\\n let cubeUVmaps = new WeakMap();\\n let pmremGenerator = null;\\n function get(texture) {\\n if (texture && texture.isTexture && texture.isRenderTargetTexture === false) {\\n const mapping = texture.mapping;\\n const isEquirectMap = mapping === EquirectangularReflectionMapping || mapping === EquirectangularRefractionMapping;\\n const isCubeMap = mapping === CubeReflectionMapping || mapping === CubeRefractionMapping;\\n if (isEquirectMap || isCubeMap) {\\n if (cubeUVmaps.has(texture)) {\\n return cubeUVmaps.get(texture).texture;\\n } else {\\n const image = texture.image;\\n if (isEquirectMap && image && image.height > 0 || isCubeMap && image && isCubeTextureComplete(image)) {\\n const currentRenderTarget = renderer.getRenderTarget();\\n if (pmremGenerator === null)\\n pmremGenerator = new PMREMGenerator(renderer);\\n const renderTarget = isEquirectMap ? pmremGenerator.fromEquirectangular(texture) : pmremGenerator.fromCubemap(texture);\\n cubeUVmaps.set(texture, renderTarget);\\n renderer.setRenderTarget(currentRenderTarget);\\n texture.addEventListener(\\\\\\\"dispose\\\\\\\", onTextureDispose);\\n return renderTarget.texture;\\n } else {\\n return null;\\n }\\n }\\n }\\n }\\n return texture;\\n }\\n function isCubeTextureComplete(image) {\\n let count = 0;\\n const length = 6;\\n for (let i = 0; i < length; i++) {\\n if (image[i] !== void 0)\\n count++;\\n }\\n return count === length;\\n }\\n function onTextureDispose(event) {\\n const texture = event.target;\\n texture.removeEventListener(\\\\\\\"dispose\\\\\\\", onTextureDispose);\\n const cubemapUV = cubeUVmaps.get(texture);\\n if (cubemapUV !== void 0) {\\n cubeUVmaps.delete(texture);\\n cubemapUV.dispose();\\n }\\n }\\n function dispose() {\\n cubeUVmaps = new WeakMap();\\n if (pmremGenerator !== null) {\\n pmremGenerator.dispose();\\n pmremGenerator = null;\\n }\\n }\\n return {\\n get,\\n dispose\\n };\\n}\\n\\n// ../../../node_modules/three/src/renderers/webgl/WebGLExtensions.js\\nfunction WebGLExtensions(gl) {\\n const extensions = {};\\n function getExtension(name) {\\n if (extensions[name] !== void 0) {\\n return extensions[name];\\n }\\n let extension;\\n switch (name) {\\n case \\\\\\\"WEBGL_depth_texture\\\\\\\":\\n extension = gl.getExtension(\\\\\\\"WEBGL_depth_texture\\\\\\\") || gl.getExtension(\\\\\\\"MOZ_WEBGL_depth_texture\\\\\\\") || gl.getExtension(\\\\\\\"WEBKIT_WEBGL_depth_texture\\\\\\\");\\n break;\\n case \\\\\\\"EXT_texture_filter_anisotropic\\\\\\\":\\n extension = gl.getExtension(\\\\\\\"EXT_texture_filter_anisotropic\\\\\\\") || gl.getExtension(\\\\\\\"MOZ_EXT_texture_filter_anisotropic\\\\\\\") || gl.getExtension(\\\\\\\"WEBKIT_EXT_texture_filter_anisotropic\\\\\\\");\\n break;\\n case \\\\\\\"WEBGL_compressed_texture_s3tc\\\\\\\":\\n extension = gl.getExtension(\\\\\\\"WEBGL_compressed_texture_s3tc\\\\\\\") || gl.getExtension(\\\\\\\"MOZ_WEBGL_compressed_texture_s3tc\\\\\\\") || gl.getExtension(\\\\\\\"WEBKIT_WEBGL_compressed_texture_s3tc\\\\\\\");\\n break;\\n case \\\\\\\"WEBGL_compressed_texture_pvrtc\\\\\\\":\\n extension = gl.getExtension(\\\\\\\"WEBGL_compressed_texture_pvrtc\\\\\\\") || gl.getExtension(\\\\\\\"WEBKIT_WEBGL_compressed_texture_pvrtc\\\\\\\");\\n break;\\n default:\\n extension = gl.getExtension(name);\\n }\\n extensions[name] = extension;\\n return extension;\\n }\\n return {\\n has: function(name) {\\n return getExtension(name) !== null;\\n },\\n init: function(capabilities) {\\n if (capabilities.isWebGL2) {\\n getExtension(\\\\\\\"EXT_color_buffer_float\\\\\\\");\\n } else {\\n getExtension(\\\\\\\"WEBGL_depth_texture\\\\\\\");\\n getExtension(\\\\\\\"OES_texture_float\\\\\\\");\\n getExtension(\\\\\\\"OES_texture_half_float\\\\\\\");\\n getExtension(\\\\\\\"OES_texture_half_float_linear\\\\\\\");\\n getExtension(\\\\\\\"OES_standard_derivatives\\\\\\\");\\n getExtension(\\\\\\\"OES_element_index_uint\\\\\\\");\\n getExtension(\\\\\\\"OES_vertex_array_object\\\\\\\");\\n getExtension(\\\\\\\"ANGLE_instanced_arrays\\\\\\\");\\n }\\n getExtension(\\\\\\\"OES_texture_float_linear\\\\\\\");\\n getExtension(\\\\\\\"EXT_color_buffer_half_float\\\\\\\");\\n },\\n get: function(name) {\\n const extension = getExtension(name);\\n if (extension === null) {\\n console.warn(\\\\\\\"THREE.WebGLRenderer: \\\\\\\" + name + \\\\\\\" extension not supported.\\\\\\\");\\n }\\n return extension;\\n }\\n };\\n}\\n\\n// ../../../node_modules/three/src/renderers/webgl/WebGLGeometries.js\\nfunction WebGLGeometries(gl, attributes, info, bindingStates) {\\n const geometries = {};\\n const wireframeAttributes = new WeakMap();\\n function onGeometryDispose(event) {\\n const geometry = event.target;\\n if (geometry.index !== null) {\\n attributes.remove(geometry.index);\\n }\\n for (const name in geometry.attributes) {\\n attributes.remove(geometry.attributes[name]);\\n }\\n geometry.removeEventListener(\\\\\\\"dispose\\\\\\\", onGeometryDispose);\\n delete geometries[geometry.id];\\n const attribute = wireframeAttributes.get(geometry);\\n if (attribute) {\\n attributes.remove(attribute);\\n wireframeAttributes.delete(geometry);\\n }\\n bindingStates.releaseStatesOfGeometry(geometry);\\n if (geometry.isInstancedBufferGeometry === true) {\\n delete geometry._maxInstanceCount;\\n }\\n info.memory.geometries--;\\n }\\n function get(object, geometry) {\\n if (geometries[geometry.id] === true)\\n return geometry;\\n geometry.addEventListener(\\\\\\\"dispose\\\\\\\", onGeometryDispose);\\n geometries[geometry.id] = true;\\n info.memory.geometries++;\\n return geometry;\\n }\\n function update(geometry) {\\n const geometryAttributes = geometry.attributes;\\n for (const name in geometryAttributes) {\\n attributes.update(geometryAttributes[name], gl.ARRAY_BUFFER);\\n }\\n const morphAttributes = geometry.morphAttributes;\\n for (const name in morphAttributes) {\\n const array = morphAttributes[name];\\n for (let i = 0, l = array.length; i < l; i++) {\\n attributes.update(array[i], gl.ARRAY_BUFFER);\\n }\\n }\\n }\\n function updateWireframeAttribute(geometry) {\\n const indices = [];\\n const geometryIndex = geometry.index;\\n const geometryPosition = geometry.attributes.position;\\n let version = 0;\\n if (geometryIndex !== null) {\\n const array = geometryIndex.array;\\n version = geometryIndex.version;\\n for (let i = 0, l = array.length; i < l; i += 3) {\\n const a = array[i + 0];\\n const b = array[i + 1];\\n const c = array[i + 2];\\n indices.push(a, b, b, c, c, a);\\n }\\n } else {\\n const array = geometryPosition.array;\\n version = geometryPosition.version;\\n for (let i = 0, l = array.length / 3 - 1; i < l; i += 3) {\\n const a = i + 0;\\n const b = i + 1;\\n const c = i + 2;\\n indices.push(a, b, b, c, c, a);\\n }\\n }\\n const attribute = new (arrayMax(indices) > 65535 ? Uint32BufferAttribute : Uint16BufferAttribute)(indices, 1);\\n attribute.version = version;\\n const previousAttribute = wireframeAttributes.get(geometry);\\n if (previousAttribute)\\n attributes.remove(previousAttribute);\\n wireframeAttributes.set(geometry, attribute);\\n }\\n function getWireframeAttribute(geometry) {\\n const currentAttribute = wireframeAttributes.get(geometry);\\n if (currentAttribute) {\\n const geometryIndex = geometry.index;\\n if (geometryIndex !== null) {\\n if (currentAttribute.version < geometryIndex.version) {\\n updateWireframeAttribute(geometry);\\n }\\n }\\n } else {\\n updateWireframeAttribute(geometry);\\n }\\n return wireframeAttributes.get(geometry);\\n }\\n return {\\n get,\\n update,\\n getWireframeAttribute\\n };\\n}\\n\\n// ../../../node_modules/three/src/renderers/webgl/WebGLIndexedBufferRenderer.js\\nfunction WebGLIndexedBufferRenderer(gl, extensions, info, capabilities) {\\n const isWebGL2 = capabilities.isWebGL2;\\n let mode;\\n function setMode(value) {\\n mode = value;\\n }\\n let type, bytesPerElement;\\n function setIndex(value) {\\n type = value.type;\\n bytesPerElement = value.bytesPerElement;\\n }\\n function render(start, count) {\\n gl.drawElements(mode, count, type, start * bytesPerElement);\\n info.update(count, mode, 1);\\n }\\n function renderInstances(start, count, primcount) {\\n if (primcount === 0)\\n return;\\n let extension, methodName;\\n if (isWebGL2) {\\n extension = gl;\\n methodName = \\\\\\\"drawElementsInstanced\\\\\\\";\\n } else {\\n extension = extensions.get(\\\\\\\"ANGLE_instanced_arrays\\\\\\\");\\n methodName = \\\\\\\"drawElementsInstancedANGLE\\\\\\\";\\n if (extension === null) {\\n console.error(\\\\\\\"THREE.WebGLIndexedBufferRenderer: using THREE.InstancedBufferGeometry but hardware does not support extension ANGLE_instanced_arrays.\\\\\\\");\\n return;\\n }\\n }\\n extension[methodName](mode, count, type, start * bytesPerElement, primcount);\\n info.update(count, mode, primcount);\\n }\\n this.setMode = setMode;\\n this.setIndex = setIndex;\\n this.render = render;\\n this.renderInstances = renderInstances;\\n}\\n\\n// ../../../node_modules/three/src/renderers/webgl/WebGLInfo.js\\nfunction WebGLInfo(gl) {\\n const memory = {\\n geometries: 0,\\n textures: 0\\n };\\n const render = {\\n frame: 0,\\n calls: 0,\\n triangles: 0,\\n points: 0,\\n lines: 0\\n };\\n function update(count, mode, instanceCount) {\\n render.calls++;\\n switch (mode) {\\n case gl.TRIANGLES:\\n render.triangles += instanceCount * (count / 3);\\n break;\\n case gl.LINES:\\n render.lines += instanceCount * (count / 2);\\n break;\\n case gl.LINE_STRIP:\\n render.lines += instanceCount * (count - 1);\\n break;\\n case gl.LINE_LOOP:\\n render.lines += instanceCount * count;\\n break;\\n case gl.POINTS:\\n render.points += instanceCount * count;\\n break;\\n default:\\n console.error(\\\\\\\"THREE.WebGLInfo: Unknown draw mode:\\\\\\\", mode);\\n break;\\n }\\n }\\n function reset() {\\n render.frame++;\\n render.calls = 0;\\n render.triangles = 0;\\n render.points = 0;\\n render.lines = 0;\\n }\\n return {\\n memory,\\n render,\\n programs: null,\\n autoReset: true,\\n reset,\\n update\\n };\\n}\\n\\n// ../../../node_modules/three/src/textures/DataTexture2DArray.js\\nvar DataTexture2DArray = class extends Texture {\\n constructor(data = null, width = 1, height = 1, depth2 = 1) {\\n super(null);\\n this.image = {data, width, height, depth: depth2};\\n this.magFilter = NearestFilter;\\n this.minFilter = NearestFilter;\\n this.wrapR = ClampToEdgeWrapping;\\n this.generateMipmaps = false;\\n this.flipY = false;\\n this.unpackAlignment = 1;\\n this.needsUpdate = true;\\n }\\n};\\nDataTexture2DArray.prototype.isDataTexture2DArray = true;\\n\\n// ../../../node_modules/three/src/renderers/webgl/WebGLMorphtargets.js\\nfunction numericalSort(a, b) {\\n return a[0] - b[0];\\n}\\nfunction absNumericalSort(a, b) {\\n return Math.abs(b[1]) - Math.abs(a[1]);\\n}\\nfunction denormalize(morph, attribute) {\\n let denominator = 1;\\n const array = attribute.isInterleavedBufferAttribute ? attribute.data.array : attribute.array;\\n if (array instanceof Int8Array)\\n denominator = 127;\\n else if (array instanceof Int16Array)\\n denominator = 32767;\\n else if (array instanceof Int32Array)\\n denominator = 2147483647;\\n else\\n console.error(\\\\\\\"THREE.WebGLMorphtargets: Unsupported morph attribute data type: \\\\\\\", array);\\n morph.divideScalar(denominator);\\n}\\nfunction WebGLMorphtargets(gl, capabilities, textures) {\\n const influencesList = {};\\n const morphInfluences = new Float32Array(8);\\n const morphTextures = new WeakMap();\\n const morph = new Vector3();\\n const workInfluences = [];\\n for (let i = 0; i < 8; i++) {\\n workInfluences[i] = [i, 0];\\n }\\n function update(object, geometry, material, program) {\\n const objectInfluences = object.morphTargetInfluences;\\n if (capabilities.isWebGL2 === true) {\\n const numberOfMorphTargets = geometry.morphAttributes.position.length;\\n let entry = morphTextures.get(geometry);\\n if (entry === void 0 || entry.count !== numberOfMorphTargets) {\\n if (entry !== void 0)\\n entry.texture.dispose();\\n const hasMorphNormals = geometry.morphAttributes.normal !== void 0;\\n const morphTargets = geometry.morphAttributes.position;\\n const morphNormals = geometry.morphAttributes.normal || [];\\n const numberOfVertices = geometry.attributes.position.count;\\n const numberOfVertexData = hasMorphNormals === true ? 2 : 1;\\n let width = numberOfVertices * numberOfVertexData;\\n let height = 1;\\n if (width > capabilities.maxTextureSize) {\\n height = Math.ceil(width / capabilities.maxTextureSize);\\n width = capabilities.maxTextureSize;\\n }\\n const buffer = new Float32Array(width * height * 4 * numberOfMorphTargets);\\n const texture = new DataTexture2DArray(buffer, width, height, numberOfMorphTargets);\\n texture.format = RGBAFormat;\\n texture.type = FloatType;\\n const vertexDataStride = numberOfVertexData * 4;\\n for (let i = 0; i < numberOfMorphTargets; i++) {\\n const morphTarget = morphTargets[i];\\n const morphNormal = morphNormals[i];\\n const offset = width * height * 4 * i;\\n for (let j = 0; j < morphTarget.count; j++) {\\n morph.fromBufferAttribute(morphTarget, j);\\n if (morphTarget.normalized === true)\\n denormalize(morph, morphTarget);\\n const stride = j * vertexDataStride;\\n buffer[offset + stride + 0] = morph.x;\\n buffer[offset + stride + 1] = morph.y;\\n buffer[offset + stride + 2] = morph.z;\\n buffer[offset + stride + 3] = 0;\\n if (hasMorphNormals === true) {\\n morph.fromBufferAttribute(morphNormal, j);\\n if (morphNormal.normalized === true)\\n denormalize(morph, morphNormal);\\n buffer[offset + stride + 4] = morph.x;\\n buffer[offset + stride + 5] = morph.y;\\n buffer[offset + stride + 6] = morph.z;\\n buffer[offset + stride + 7] = 0;\\n }\\n }\\n }\\n entry = {\\n count: numberOfMorphTargets,\\n texture,\\n size: new Vector2(width, height)\\n };\\n morphTextures.set(geometry, entry);\\n }\\n let morphInfluencesSum = 0;\\n for (let i = 0; i < objectInfluences.length; i++) {\\n morphInfluencesSum += objectInfluences[i];\\n }\\n const morphBaseInfluence = geometry.morphTargetsRelative ? 1 : 1 - morphInfluencesSum;\\n program.getUniforms().setValue(gl, \\\\\\\"morphTargetBaseInfluence\\\\\\\", morphBaseInfluence);\\n program.getUniforms().setValue(gl, \\\\\\\"morphTargetInfluences\\\\\\\", objectInfluences);\\n program.getUniforms().setValue(gl, \\\\\\\"morphTargetsTexture\\\\\\\", entry.texture, textures);\\n program.getUniforms().setValue(gl, \\\\\\\"morphTargetsTextureSize\\\\\\\", entry.size);\\n } else {\\n const length = objectInfluences === void 0 ? 0 : objectInfluences.length;\\n let influences = influencesList[geometry.id];\\n if (influences === void 0 || influences.length !== length) {\\n influences = [];\\n for (let i = 0; i < length; i++) {\\n influences[i] = [i, 0];\\n }\\n influencesList[geometry.id] = influences;\\n }\\n for (let i = 0; i < length; i++) {\\n const influence = influences[i];\\n influence[0] = i;\\n influence[1] = objectInfluences[i];\\n }\\n influences.sort(absNumericalSort);\\n for (let i = 0; i < 8; i++) {\\n if (i < length && influences[i][1]) {\\n workInfluences[i][0] = influences[i][0];\\n workInfluences[i][1] = influences[i][1];\\n } else {\\n workInfluences[i][0] = Number.MAX_SAFE_INTEGER;\\n workInfluences[i][1] = 0;\\n }\\n }\\n workInfluences.sort(numericalSort);\\n const morphTargets = geometry.morphAttributes.position;\\n const morphNormals = geometry.morphAttributes.normal;\\n let morphInfluencesSum = 0;\\n for (let i = 0; i < 8; i++) {\\n const influence = workInfluences[i];\\n const index = influence[0];\\n const value = influence[1];\\n if (index !== Number.MAX_SAFE_INTEGER && value) {\\n if (morphTargets && geometry.getAttribute(\\\\\\\"morphTarget\\\\\\\" + i) !== morphTargets[index]) {\\n geometry.setAttribute(\\\\\\\"morphTarget\\\\\\\" + i, morphTargets[index]);\\n }\\n if (morphNormals && geometry.getAttribute(\\\\\\\"morphNormal\\\\\\\" + i) !== morphNormals[index]) {\\n geometry.setAttribute(\\\\\\\"morphNormal\\\\\\\" + i, morphNormals[index]);\\n }\\n morphInfluences[i] = value;\\n morphInfluencesSum += value;\\n } else {\\n if (morphTargets && geometry.hasAttribute(\\\\\\\"morphTarget\\\\\\\" + i) === true) {\\n geometry.deleteAttribute(\\\\\\\"morphTarget\\\\\\\" + i);\\n }\\n if (morphNormals && geometry.hasAttribute(\\\\\\\"morphNormal\\\\\\\" + i) === true) {\\n geometry.deleteAttribute(\\\\\\\"morphNormal\\\\\\\" + i);\\n }\\n morphInfluences[i] = 0;\\n }\\n }\\n const morphBaseInfluence = geometry.morphTargetsRelative ? 1 : 1 - morphInfluencesSum;\\n program.getUniforms().setValue(gl, \\\\\\\"morphTargetBaseInfluence\\\\\\\", morphBaseInfluence);\\n program.getUniforms().setValue(gl, \\\\\\\"morphTargetInfluences\\\\\\\", morphInfluences);\\n }\\n }\\n return {\\n update\\n };\\n}\\n\\n// ../../../node_modules/three/src/renderers/WebGLMultisampleRenderTarget.js\\nvar WebGLMultisampleRenderTarget = class extends WebGLRenderTarget {\\n constructor(width, height, options) {\\n super(width, height, options);\\n this.samples = 4;\\n }\\n copy(source) {\\n super.copy.call(this, source);\\n this.samples = source.samples;\\n return this;\\n }\\n};\\nWebGLMultisampleRenderTarget.prototype.isWebGLMultisampleRenderTarget = true;\\n\\n// ../../../node_modules/three/src/renderers/webgl/WebGLObjects.js\\nfunction WebGLObjects(gl, geometries, attributes, info) {\\n let updateMap = new WeakMap();\\n function update(object) {\\n const frame = info.render.frame;\\n const geometry = object.geometry;\\n const buffergeometry = geometries.get(object, geometry);\\n if (updateMap.get(buffergeometry) !== frame) {\\n geometries.update(buffergeometry);\\n updateMap.set(buffergeometry, frame);\\n }\\n if (object.isInstancedMesh) {\\n if (object.hasEventListener(\\\\\\\"dispose\\\\\\\", onInstancedMeshDispose) === false) {\\n object.addEventListener(\\\\\\\"dispose\\\\\\\", onInstancedMeshDispose);\\n }\\n attributes.update(object.instanceMatrix, gl.ARRAY_BUFFER);\\n if (object.instanceColor !== null) {\\n attributes.update(object.instanceColor, gl.ARRAY_BUFFER);\\n }\\n }\\n return buffergeometry;\\n }\\n function dispose() {\\n updateMap = new WeakMap();\\n }\\n function onInstancedMeshDispose(event) {\\n const instancedMesh = event.target;\\n instancedMesh.removeEventListener(\\\\\\\"dispose\\\\\\\", onInstancedMeshDispose);\\n attributes.remove(instancedMesh.instanceMatrix);\\n if (instancedMesh.instanceColor !== null)\\n attributes.remove(instancedMesh.instanceColor);\\n }\\n return {\\n update,\\n dispose\\n };\\n}\\n\\n// ../../../node_modules/three/src/textures/DataTexture3D.js\\nvar DataTexture3D = class extends Texture {\\n constructor(data = null, width = 1, height = 1, depth2 = 1) {\\n super(null);\\n this.image = {data, width, height, depth: depth2};\\n this.magFilter = NearestFilter;\\n this.minFilter = NearestFilter;\\n this.wrapR = ClampToEdgeWrapping;\\n this.generateMipmaps = false;\\n this.flipY = false;\\n this.unpackAlignment = 1;\\n this.needsUpdate = true;\\n }\\n};\\nDataTexture3D.prototype.isDataTexture3D = true;\\n\\n// ../../../node_modules/three/src/renderers/webgl/WebGLUniforms.js\\nvar emptyTexture = new Texture();\\nvar emptyTexture2dArray = new DataTexture2DArray();\\nvar emptyTexture3d = new DataTexture3D();\\nvar emptyCubeTexture = new CubeTexture();\\nvar arrayCacheF32 = [];\\nvar arrayCacheI32 = [];\\nvar mat4array = new Float32Array(16);\\nvar mat3array = new Float32Array(9);\\nvar mat2array = new Float32Array(4);\\nfunction flatten(array, nBlocks, blockSize) {\\n const firstElem = array[0];\\n if (firstElem <= 0 || firstElem > 0)\\n return array;\\n const n = nBlocks * blockSize;\\n let r = arrayCacheF32[n];\\n if (r === void 0) {\\n r = new Float32Array(n);\\n arrayCacheF32[n] = r;\\n }\\n if (nBlocks !== 0) {\\n firstElem.toArray(r, 0);\\n for (let i = 1, offset = 0; i !== nBlocks; ++i) {\\n offset += blockSize;\\n array[i].toArray(r, offset);\\n }\\n }\\n return r;\\n}\\nfunction arraysEqual(a, b) {\\n if (a.length !== b.length)\\n return false;\\n for (let i = 0, l = a.length; i < l; i++) {\\n if (a[i] !== b[i])\\n return false;\\n }\\n return true;\\n}\\nfunction copyArray(a, b) {\\n for (let i = 0, l = b.length; i < l; i++) {\\n a[i] = b[i];\\n }\\n}\\nfunction allocTexUnits(textures, n) {\\n let r = arrayCacheI32[n];\\n if (r === void 0) {\\n r = new Int32Array(n);\\n arrayCacheI32[n] = r;\\n }\\n for (let i = 0; i !== n; ++i) {\\n r[i] = textures.allocateTextureUnit();\\n }\\n return r;\\n}\\nfunction setValueV1f(gl, v) {\\n const cache = this.cache;\\n if (cache[0] === v)\\n return;\\n gl.uniform1f(this.addr, v);\\n cache[0] = v;\\n}\\nfunction setValueV2f(gl, v) {\\n const cache = this.cache;\\n if (v.x !== void 0) {\\n if (cache[0] !== v.x || cache[1] !== v.y) {\\n gl.uniform2f(this.addr, v.x, v.y);\\n cache[0] = v.x;\\n cache[1] = v.y;\\n }\\n } else {\\n if (arraysEqual(cache, v))\\n return;\\n gl.uniform2fv(this.addr, v);\\n copyArray(cache, v);\\n }\\n}\\nfunction setValueV3f(gl, v) {\\n const cache = this.cache;\\n if (v.x !== void 0) {\\n if (cache[0] !== v.x || cache[1] !== v.y || cache[2] !== v.z) {\\n gl.uniform3f(this.addr, v.x, v.y, v.z);\\n cache[0] = v.x;\\n cache[1] = v.y;\\n cache[2] = v.z;\\n }\\n } else if (v.r !== void 0) {\\n if (cache[0] !== v.r || cache[1] !== v.g || cache[2] !== v.b) {\\n gl.uniform3f(this.addr, v.r, v.g, v.b);\\n cache[0] = v.r;\\n cache[1] = v.g;\\n cache[2] = v.b;\\n }\\n } else {\\n if (arraysEqual(cache, v))\\n return;\\n gl.uniform3fv(this.addr, v);\\n copyArray(cache, v);\\n }\\n}\\nfunction setValueV4f(gl, v) {\\n const cache = this.cache;\\n if (v.x !== void 0) {\\n if (cache[0] !== v.x || cache[1] !== v.y || cache[2] !== v.z || cache[3] !== v.w) {\\n gl.uniform4f(this.addr, v.x, v.y, v.z, v.w);\\n cache[0] = v.x;\\n cache[1] = v.y;\\n cache[2] = v.z;\\n cache[3] = v.w;\\n }\\n } else {\\n if (arraysEqual(cache, v))\\n return;\\n gl.uniform4fv(this.addr, v);\\n copyArray(cache, v);\\n }\\n}\\nfunction setValueM2(gl, v) {\\n const cache = this.cache;\\n const elements = v.elements;\\n if (elements === void 0) {\\n if (arraysEqual(cache, v))\\n return;\\n gl.uniformMatrix2fv(this.addr, false, v);\\n copyArray(cache, v);\\n } else {\\n if (arraysEqual(cache, elements))\\n return;\\n mat2array.set(elements);\\n gl.uniformMatrix2fv(this.addr, false, mat2array);\\n copyArray(cache, elements);\\n }\\n}\\nfunction setValueM3(gl, v) {\\n const cache = this.cache;\\n const elements = v.elements;\\n if (elements === void 0) {\\n if (arraysEqual(cache, v))\\n return;\\n gl.uniformMatrix3fv(this.addr, false, v);\\n copyArray(cache, v);\\n } else {\\n if (arraysEqual(cache, elements))\\n return;\\n mat3array.set(elements);\\n gl.uniformMatrix3fv(this.addr, false, mat3array);\\n copyArray(cache, elements);\\n }\\n}\\nfunction setValueM4(gl, v) {\\n const cache = this.cache;\\n const elements = v.elements;\\n if (elements === void 0) {\\n if (arraysEqual(cache, v))\\n return;\\n gl.uniformMatrix4fv(this.addr, false, v);\\n copyArray(cache, v);\\n } else {\\n if (arraysEqual(cache, elements))\\n return;\\n mat4array.set(elements);\\n gl.uniformMatrix4fv(this.addr, false, mat4array);\\n copyArray(cache, elements);\\n }\\n}\\nfunction setValueV1i(gl, v) {\\n const cache = this.cache;\\n if (cache[0] === v)\\n return;\\n gl.uniform1i(this.addr, v);\\n cache[0] = v;\\n}\\nfunction setValueV2i(gl, v) {\\n const cache = this.cache;\\n if (arraysEqual(cache, v))\\n return;\\n gl.uniform2iv(this.addr, v);\\n copyArray(cache, v);\\n}\\nfunction setValueV3i(gl, v) {\\n const cache = this.cache;\\n if (arraysEqual(cache, v))\\n return;\\n gl.uniform3iv(this.addr, v);\\n copyArray(cache, v);\\n}\\nfunction setValueV4i(gl, v) {\\n const cache = this.cache;\\n if (arraysEqual(cache, v))\\n return;\\n gl.uniform4iv(this.addr, v);\\n copyArray(cache, v);\\n}\\nfunction setValueV1ui(gl, v) {\\n const cache = this.cache;\\n if (cache[0] === v)\\n return;\\n gl.uniform1ui(this.addr, v);\\n cache[0] = v;\\n}\\nfunction setValueV2ui(gl, v) {\\n const cache = this.cache;\\n if (arraysEqual(cache, v))\\n return;\\n gl.uniform2uiv(this.addr, v);\\n copyArray(cache, v);\\n}\\nfunction setValueV3ui(gl, v) {\\n const cache = this.cache;\\n if (arraysEqual(cache, v))\\n return;\\n gl.uniform3uiv(this.addr, v);\\n copyArray(cache, v);\\n}\\nfunction setValueV4ui(gl, v) {\\n const cache = this.cache;\\n if (arraysEqual(cache, v))\\n return;\\n gl.uniform4uiv(this.addr, v);\\n copyArray(cache, v);\\n}\\nfunction setValueT1(gl, v, textures) {\\n const cache = this.cache;\\n const unit = textures.allocateTextureUnit();\\n if (cache[0] !== unit) {\\n gl.uniform1i(this.addr, unit);\\n cache[0] = unit;\\n }\\n textures.safeSetTexture2D(v || emptyTexture, unit);\\n}\\nfunction setValueT3D1(gl, v, textures) {\\n const cache = this.cache;\\n const unit = textures.allocateTextureUnit();\\n if (cache[0] !== unit) {\\n gl.uniform1i(this.addr, unit);\\n cache[0] = unit;\\n }\\n textures.setTexture3D(v || emptyTexture3d, unit);\\n}\\nfunction setValueT6(gl, v, textures) {\\n const cache = this.cache;\\n const unit = textures.allocateTextureUnit();\\n if (cache[0] !== unit) {\\n gl.uniform1i(this.addr, unit);\\n cache[0] = unit;\\n }\\n textures.safeSetTextureCube(v || emptyCubeTexture, unit);\\n}\\nfunction setValueT2DArray1(gl, v, textures) {\\n const cache = this.cache;\\n const unit = textures.allocateTextureUnit();\\n if (cache[0] !== unit) {\\n gl.uniform1i(this.addr, unit);\\n cache[0] = unit;\\n }\\n textures.setTexture2DArray(v || emptyTexture2dArray, unit);\\n}\\nfunction getSingularSetter(type) {\\n switch (type) {\\n case 5126:\\n return setValueV1f;\\n case 35664:\\n return setValueV2f;\\n case 35665:\\n return setValueV3f;\\n case 35666:\\n return setValueV4f;\\n case 35674:\\n return setValueM2;\\n case 35675:\\n return setValueM3;\\n case 35676:\\n return setValueM4;\\n case 5124:\\n case 35670:\\n return setValueV1i;\\n case 35667:\\n case 35671:\\n return setValueV2i;\\n case 35668:\\n case 35672:\\n return setValueV3i;\\n case 35669:\\n case 35673:\\n return setValueV4i;\\n case 5125:\\n return setValueV1ui;\\n case 36294:\\n return setValueV2ui;\\n case 36295:\\n return setValueV3ui;\\n case 36296:\\n return setValueV4ui;\\n case 35678:\\n case 36198:\\n case 36298:\\n case 36306:\\n case 35682:\\n return setValueT1;\\n case 35679:\\n case 36299:\\n case 36307:\\n return setValueT3D1;\\n case 35680:\\n case 36300:\\n case 36308:\\n case 36293:\\n return setValueT6;\\n case 36289:\\n case 36303:\\n case 36311:\\n case 36292:\\n return setValueT2DArray1;\\n }\\n}\\nfunction setValueV1fArray(gl, v) {\\n gl.uniform1fv(this.addr, v);\\n}\\nfunction setValueV2fArray(gl, v) {\\n const data = flatten(v, this.size, 2);\\n gl.uniform2fv(this.addr, data);\\n}\\nfunction setValueV3fArray(gl, v) {\\n const data = flatten(v, this.size, 3);\\n gl.uniform3fv(this.addr, data);\\n}\\nfunction setValueV4fArray(gl, v) {\\n const data = flatten(v, this.size, 4);\\n gl.uniform4fv(this.addr, data);\\n}\\nfunction setValueM2Array(gl, v) {\\n const data = flatten(v, this.size, 4);\\n gl.uniformMatrix2fv(this.addr, false, data);\\n}\\nfunction setValueM3Array(gl, v) {\\n const data = flatten(v, this.size, 9);\\n gl.uniformMatrix3fv(this.addr, false, data);\\n}\\nfunction setValueM4Array(gl, v) {\\n const data = flatten(v, this.size, 16);\\n gl.uniformMatrix4fv(this.addr, false, data);\\n}\\nfunction setValueV1iArray(gl, v) {\\n gl.uniform1iv(this.addr, v);\\n}\\nfunction setValueV2iArray(gl, v) {\\n gl.uniform2iv(this.addr, v);\\n}\\nfunction setValueV3iArray(gl, v) {\\n gl.uniform3iv(this.addr, v);\\n}\\nfunction setValueV4iArray(gl, v) {\\n gl.uniform4iv(this.addr, v);\\n}\\nfunction setValueV1uiArray(gl, v) {\\n gl.uniform1uiv(this.addr, v);\\n}\\nfunction setValueV2uiArray(gl, v) {\\n gl.uniform2uiv(this.addr, v);\\n}\\nfunction setValueV3uiArray(gl, v) {\\n gl.uniform3uiv(this.addr, v);\\n}\\nfunction setValueV4uiArray(gl, v) {\\n gl.uniform4uiv(this.addr, v);\\n}\\nfunction setValueT1Array(gl, v, textures) {\\n const n = v.length;\\n const units = allocTexUnits(textures, n);\\n gl.uniform1iv(this.addr, units);\\n for (let i = 0; i !== n; ++i) {\\n textures.safeSetTexture2D(v[i] || emptyTexture, units[i]);\\n }\\n}\\nfunction setValueT6Array(gl, v, textures) {\\n const n = v.length;\\n const units = allocTexUnits(textures, n);\\n gl.uniform1iv(this.addr, units);\\n for (let i = 0; i !== n; ++i) {\\n textures.safeSetTextureCube(v[i] || emptyCubeTexture, units[i]);\\n }\\n}\\nfunction getPureArraySetter(type) {\\n switch (type) {\\n case 5126:\\n return setValueV1fArray;\\n case 35664:\\n return setValueV2fArray;\\n case 35665:\\n return setValueV3fArray;\\n case 35666:\\n return setValueV4fArray;\\n case 35674:\\n return setValueM2Array;\\n case 35675:\\n return setValueM3Array;\\n case 35676:\\n return setValueM4Array;\\n case 5124:\\n case 35670:\\n return setValueV1iArray;\\n case 35667:\\n case 35671:\\n return setValueV2iArray;\\n case 35668:\\n case 35672:\\n return setValueV3iArray;\\n case 35669:\\n case 35673:\\n return setValueV4iArray;\\n case 5125:\\n return setValueV1uiArray;\\n case 36294:\\n return setValueV2uiArray;\\n case 36295:\\n return setValueV3uiArray;\\n case 36296:\\n return setValueV4uiArray;\\n case 35678:\\n case 36198:\\n case 36298:\\n case 36306:\\n case 35682:\\n return setValueT1Array;\\n case 35680:\\n case 36300:\\n case 36308:\\n case 36293:\\n return setValueT6Array;\\n }\\n}\\nfunction SingleUniform(id, activeInfo, addr) {\\n this.id = id;\\n this.addr = addr;\\n this.cache = [];\\n this.setValue = getSingularSetter(activeInfo.type);\\n}\\nfunction PureArrayUniform(id, activeInfo, addr) {\\n this.id = id;\\n this.addr = addr;\\n this.cache = [];\\n this.size = activeInfo.size;\\n this.setValue = getPureArraySetter(activeInfo.type);\\n}\\nPureArrayUniform.prototype.updateCache = function(data) {\\n const cache = this.cache;\\n if (data instanceof Float32Array && cache.length !== data.length) {\\n this.cache = new Float32Array(data.length);\\n }\\n copyArray(cache, data);\\n};\\nfunction StructuredUniform(id) {\\n this.id = id;\\n this.seq = [];\\n this.map = {};\\n}\\nStructuredUniform.prototype.setValue = function(gl, value, textures) {\\n const seq = this.seq;\\n for (let i = 0, n = seq.length; i !== n; ++i) {\\n const u = seq[i];\\n u.setValue(gl, value[u.id], textures);\\n }\\n};\\nvar RePathPart = /(\\\\w+)(\\\\])?(\\\\[|\\\\.)?/g;\\nfunction addUniform(container, uniformObject) {\\n container.seq.push(uniformObject);\\n container.map[uniformObject.id] = uniformObject;\\n}\\nfunction parseUniform(activeInfo, addr, container) {\\n const path = activeInfo.name, pathLength = path.length;\\n RePathPart.lastIndex = 0;\\n while (true) {\\n const match = RePathPart.exec(path), matchEnd = RePathPart.lastIndex;\\n let id = match[1];\\n const idIsIndex = match[2] === \\\\\\\"]\\\\\\\", subscript = match[3];\\n if (idIsIndex)\\n id = id | 0;\\n if (subscript === void 0 || subscript === \\\\\\\"[\\\\\\\" && matchEnd + 2 === pathLength) {\\n addUniform(container, subscript === void 0 ? new SingleUniform(id, activeInfo, addr) : new PureArrayUniform(id, activeInfo, addr));\\n break;\\n } else {\\n const map = container.map;\\n let next = map[id];\\n if (next === void 0) {\\n next = new StructuredUniform(id);\\n addUniform(container, next);\\n }\\n container = next;\\n }\\n }\\n}\\nfunction WebGLUniforms(gl, program) {\\n this.seq = [];\\n this.map = {};\\n const n = gl.getProgramParameter(program, gl.ACTIVE_UNIFORMS);\\n for (let i = 0; i < n; ++i) {\\n const info = gl.getActiveUniform(program, i), addr = gl.getUniformLocation(program, info.name);\\n parseUniform(info, addr, this);\\n }\\n}\\nWebGLUniforms.prototype.setValue = function(gl, name, value, textures) {\\n const u = this.map[name];\\n if (u !== void 0)\\n u.setValue(gl, value, textures);\\n};\\nWebGLUniforms.prototype.setOptional = function(gl, object, name) {\\n const v = object[name];\\n if (v !== void 0)\\n this.setValue(gl, name, v);\\n};\\nWebGLUniforms.upload = function(gl, seq, values, textures) {\\n for (let i = 0, n = seq.length; i !== n; ++i) {\\n const u = seq[i], v = values[u.id];\\n if (v.needsUpdate !== false) {\\n u.setValue(gl, v.value, textures);\\n }\\n }\\n};\\nWebGLUniforms.seqWithValue = function(seq, values) {\\n const r = [];\\n for (let i = 0, n = seq.length; i !== n; ++i) {\\n const u = seq[i];\\n if (u.id in values)\\n r.push(u);\\n }\\n return r;\\n};\\n\\n// ../../../node_modules/three/src/renderers/webgl/WebGLShader.js\\nfunction WebGLShader(gl, type, string) {\\n const shader = gl.createShader(type);\\n gl.shaderSource(shader, string);\\n gl.compileShader(shader);\\n return shader;\\n}\\n\\n// ../../../node_modules/three/src/renderers/webgl/WebGLProgram.js\\nvar programIdCount = 0;\\nfunction addLineNumbers(string) {\\n const lines = string.split(\\\\\\\"\\\\n\\\\\\\");\\n for (let i = 0; i < lines.length; i++) {\\n lines[i] = i + 1 + \\\\\\\": \\\\\\\" + lines[i];\\n }\\n return lines.join(\\\\\\\"\\\\n\\\\\\\");\\n}\\nfunction getEncodingComponents(encoding) {\\n switch (encoding) {\\n case LinearEncoding:\\n return [\\\\\\\"Linear\\\\\\\", \\\\\\\"( value )\\\\\\\"];\\n case sRGBEncoding:\\n return [\\\\\\\"sRGB\\\\\\\", \\\\\\\"( value )\\\\\\\"];\\n case RGBEEncoding:\\n return [\\\\\\\"RGBE\\\\\\\", \\\\\\\"( value )\\\\\\\"];\\n case RGBM7Encoding:\\n return [\\\\\\\"RGBM\\\\\\\", \\\\\\\"( value, 7.0 )\\\\\\\"];\\n case RGBM16Encoding:\\n return [\\\\\\\"RGBM\\\\\\\", \\\\\\\"( value, 16.0 )\\\\\\\"];\\n case RGBDEncoding:\\n return [\\\\\\\"RGBD\\\\\\\", \\\\\\\"( value, 256.0 )\\\\\\\"];\\n case GammaEncoding:\\n return [\\\\\\\"Gamma\\\\\\\", \\\\\\\"( value, float( GAMMA_FACTOR ) )\\\\\\\"];\\n case LogLuvEncoding:\\n return [\\\\\\\"LogLuv\\\\\\\", \\\\\\\"( value )\\\\\\\"];\\n default:\\n console.warn(\\\\\\\"THREE.WebGLProgram: Unsupported encoding:\\\\\\\", encoding);\\n return [\\\\\\\"Linear\\\\\\\", \\\\\\\"( value )\\\\\\\"];\\n }\\n}\\nfunction getShaderErrors(gl, shader, type) {\\n const status = gl.getShaderParameter(shader, gl.COMPILE_STATUS);\\n const errors = gl.getShaderInfoLog(shader).trim();\\n if (status && errors === \\\\\\\"\\\\\\\")\\n return \\\\\\\"\\\\\\\";\\n return type.toUpperCase() + \\\\\\\"\\\\n\\\\n\\\\\\\" + errors + \\\\\\\"\\\\n\\\\n\\\\\\\" + addLineNumbers(gl.getShaderSource(shader));\\n}\\nfunction getTexelDecodingFunction(functionName, encoding) {\\n const components = getEncodingComponents(encoding);\\n return \\\\\\\"vec4 \\\\\\\" + functionName + \\\\\\\"( vec4 value ) { return \\\\\\\" + components[0] + \\\\\\\"ToLinear\\\\\\\" + components[1] + \\\\\\\"; }\\\\\\\";\\n}\\nfunction getTexelEncodingFunction(functionName, encoding) {\\n const components = getEncodingComponents(encoding);\\n return \\\\\\\"vec4 \\\\\\\" + functionName + \\\\\\\"( vec4 value ) { return LinearTo\\\\\\\" + components[0] + components[1] + \\\\\\\"; }\\\\\\\";\\n}\\nfunction getToneMappingFunction(functionName, toneMapping) {\\n let toneMappingName;\\n switch (toneMapping) {\\n case LinearToneMapping:\\n toneMappingName = \\\\\\\"Linear\\\\\\\";\\n break;\\n case ReinhardToneMapping:\\n toneMappingName = \\\\\\\"Reinhard\\\\\\\";\\n break;\\n case CineonToneMapping:\\n toneMappingName = \\\\\\\"OptimizedCineon\\\\\\\";\\n break;\\n case ACESFilmicToneMapping:\\n toneMappingName = \\\\\\\"ACESFilmic\\\\\\\";\\n break;\\n case CustomToneMapping:\\n toneMappingName = \\\\\\\"Custom\\\\\\\";\\n break;\\n default:\\n console.warn(\\\\\\\"THREE.WebGLProgram: Unsupported toneMapping:\\\\\\\", toneMapping);\\n toneMappingName = \\\\\\\"Linear\\\\\\\";\\n }\\n return \\\\\\\"vec3 \\\\\\\" + functionName + \\\\\\\"( vec3 color ) { return \\\\\\\" + toneMappingName + \\\\\\\"ToneMapping( color ); }\\\\\\\";\\n}\\nfunction generateExtensions(parameters) {\\n const chunks = [\\n parameters.extensionDerivatives || parameters.envMapCubeUV || parameters.bumpMap || parameters.tangentSpaceNormalMap || parameters.clearcoatNormalMap || parameters.flatShading || parameters.shaderID === \\\\\\\"physical\\\\\\\" ? \\\\\\\"#extension GL_OES_standard_derivatives : enable\\\\\\\" : \\\\\\\"\\\\\\\",\\n (parameters.extensionFragDepth || parameters.logarithmicDepthBuffer) && parameters.rendererExtensionFragDepth ? \\\\\\\"#extension GL_EXT_frag_depth : enable\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.extensionDrawBuffers && parameters.rendererExtensionDrawBuffers ? \\\\\\\"#extension GL_EXT_draw_buffers : require\\\\\\\" : \\\\\\\"\\\\\\\",\\n (parameters.extensionShaderTextureLOD || parameters.envMap || parameters.transmission) && parameters.rendererExtensionShaderTextureLod ? \\\\\\\"#extension GL_EXT_shader_texture_lod : enable\\\\\\\" : \\\\\\\"\\\\\\\"\\n ];\\n return chunks.filter(filterEmptyLine).join(\\\\\\\"\\\\n\\\\\\\");\\n}\\nfunction generateDefines(defines) {\\n const chunks = [];\\n for (const name in defines) {\\n const value = defines[name];\\n if (value === false)\\n continue;\\n chunks.push(\\\\\\\"#define \\\\\\\" + name + \\\\\\\" \\\\\\\" + value);\\n }\\n return chunks.join(\\\\\\\"\\\\n\\\\\\\");\\n}\\nfunction fetchAttributeLocations(gl, program) {\\n const attributes = {};\\n const n = gl.getProgramParameter(program, gl.ACTIVE_ATTRIBUTES);\\n for (let i = 0; i < n; i++) {\\n const info = gl.getActiveAttrib(program, i);\\n const name = info.name;\\n let locationSize = 1;\\n if (info.type === gl.FLOAT_MAT2)\\n locationSize = 2;\\n if (info.type === gl.FLOAT_MAT3)\\n locationSize = 3;\\n if (info.type === gl.FLOAT_MAT4)\\n locationSize = 4;\\n attributes[name] = {\\n type: info.type,\\n location: gl.getAttribLocation(program, name),\\n locationSize\\n };\\n }\\n return attributes;\\n}\\nfunction filterEmptyLine(string) {\\n return string !== \\\\\\\"\\\\\\\";\\n}\\nfunction replaceLightNums(string, parameters) {\\n return string.replace(/NUM_DIR_LIGHTS/g, parameters.numDirLights).replace(/NUM_SPOT_LIGHTS/g, parameters.numSpotLights).replace(/NUM_RECT_AREA_LIGHTS/g, parameters.numRectAreaLights).replace(/NUM_POINT_LIGHTS/g, parameters.numPointLights).replace(/NUM_HEMI_LIGHTS/g, parameters.numHemiLights).replace(/NUM_DIR_LIGHT_SHADOWS/g, parameters.numDirLightShadows).replace(/NUM_SPOT_LIGHT_SHADOWS/g, parameters.numSpotLightShadows).replace(/NUM_POINT_LIGHT_SHADOWS/g, parameters.numPointLightShadows);\\n}\\nfunction replaceClippingPlaneNums(string, parameters) {\\n return string.replace(/NUM_CLIPPING_PLANES/g, parameters.numClippingPlanes).replace(/UNION_CLIPPING_PLANES/g, parameters.numClippingPlanes - parameters.numClipIntersection);\\n}\\nvar includePattern = /^[ \\\\t]*#include +<([\\\\w\\\\d./]+)>/gm;\\nfunction resolveIncludes(string) {\\n return string.replace(includePattern, includeReplacer);\\n}\\nfunction includeReplacer(match, include) {\\n const string = ShaderChunk[include];\\n if (string === void 0) {\\n throw new Error(\\\\\\\"Can not resolve #include <\\\\\\\" + include + \\\\\\\">\\\\\\\");\\n }\\n return resolveIncludes(string);\\n}\\nvar deprecatedUnrollLoopPattern = /#pragma unroll_loop[\\\\s]+?for \\\\( int i \\\\= (\\\\d+)\\\\; i < (\\\\d+)\\\\; i \\\\+\\\\+ \\\\) \\\\{([\\\\s\\\\S]+?)(?=\\\\})\\\\}/g;\\nvar unrollLoopPattern = /#pragma unroll_loop_start\\\\s+for\\\\s*\\\\(\\\\s*int\\\\s+i\\\\s*=\\\\s*(\\\\d+)\\\\s*;\\\\s*i\\\\s*<\\\\s*(\\\\d+)\\\\s*;\\\\s*i\\\\s*\\\\+\\\\+\\\\s*\\\\)\\\\s*{([\\\\s\\\\S]+?)}\\\\s+#pragma unroll_loop_end/g;\\nfunction unrollLoops(string) {\\n return string.replace(unrollLoopPattern, loopReplacer).replace(deprecatedUnrollLoopPattern, deprecatedLoopReplacer);\\n}\\nfunction deprecatedLoopReplacer(match, start, end, snippet) {\\n console.warn(\\\\\\\"WebGLProgram: #pragma unroll_loop shader syntax is deprecated. Please use #pragma unroll_loop_start syntax instead.\\\\\\\");\\n return loopReplacer(match, start, end, snippet);\\n}\\nfunction loopReplacer(match, start, end, snippet) {\\n let string = \\\\\\\"\\\\\\\";\\n for (let i = parseInt(start); i < parseInt(end); i++) {\\n string += snippet.replace(/\\\\[\\\\s*i\\\\s*\\\\]/g, \\\\\\\"[ \\\\\\\" + i + \\\\\\\" ]\\\\\\\").replace(/UNROLLED_LOOP_INDEX/g, i);\\n }\\n return string;\\n}\\nfunction generatePrecision(parameters) {\\n let precisionstring = \\\\\\\"precision \\\\\\\" + parameters.precision + \\\\\\\" float;\\\\nprecision \\\\\\\" + parameters.precision + \\\\\\\" int;\\\\\\\";\\n if (parameters.precision === \\\\\\\"highp\\\\\\\") {\\n precisionstring += \\\\\\\"\\\\n#define HIGH_PRECISION\\\\\\\";\\n } else if (parameters.precision === \\\\\\\"mediump\\\\\\\") {\\n precisionstring += \\\\\\\"\\\\n#define MEDIUM_PRECISION\\\\\\\";\\n } else if (parameters.precision === \\\\\\\"lowp\\\\\\\") {\\n precisionstring += \\\\\\\"\\\\n#define LOW_PRECISION\\\\\\\";\\n }\\n return precisionstring;\\n}\\nfunction generateShadowMapTypeDefine(parameters) {\\n let shadowMapTypeDefine = \\\\\\\"SHADOWMAP_TYPE_BASIC\\\\\\\";\\n if (parameters.shadowMapType === PCFShadowMap) {\\n shadowMapTypeDefine = \\\\\\\"SHADOWMAP_TYPE_PCF\\\\\\\";\\n } else if (parameters.shadowMapType === PCFSoftShadowMap) {\\n shadowMapTypeDefine = \\\\\\\"SHADOWMAP_TYPE_PCF_SOFT\\\\\\\";\\n } else if (parameters.shadowMapType === VSMShadowMap) {\\n shadowMapTypeDefine = \\\\\\\"SHADOWMAP_TYPE_VSM\\\\\\\";\\n }\\n return shadowMapTypeDefine;\\n}\\nfunction generateEnvMapTypeDefine(parameters) {\\n let envMapTypeDefine = \\\\\\\"ENVMAP_TYPE_CUBE\\\\\\\";\\n if (parameters.envMap) {\\n switch (parameters.envMapMode) {\\n case CubeReflectionMapping:\\n case CubeRefractionMapping:\\n envMapTypeDefine = \\\\\\\"ENVMAP_TYPE_CUBE\\\\\\\";\\n break;\\n case CubeUVReflectionMapping:\\n case CubeUVRefractionMapping:\\n envMapTypeDefine = \\\\\\\"ENVMAP_TYPE_CUBE_UV\\\\\\\";\\n break;\\n }\\n }\\n return envMapTypeDefine;\\n}\\nfunction generateEnvMapModeDefine(parameters) {\\n let envMapModeDefine = \\\\\\\"ENVMAP_MODE_REFLECTION\\\\\\\";\\n if (parameters.envMap) {\\n switch (parameters.envMapMode) {\\n case CubeRefractionMapping:\\n case CubeUVRefractionMapping:\\n envMapModeDefine = \\\\\\\"ENVMAP_MODE_REFRACTION\\\\\\\";\\n break;\\n }\\n }\\n return envMapModeDefine;\\n}\\nfunction generateEnvMapBlendingDefine(parameters) {\\n let envMapBlendingDefine = \\\\\\\"ENVMAP_BLENDING_NONE\\\\\\\";\\n if (parameters.envMap) {\\n switch (parameters.combine) {\\n case MultiplyOperation:\\n envMapBlendingDefine = \\\\\\\"ENVMAP_BLENDING_MULTIPLY\\\\\\\";\\n break;\\n case MixOperation:\\n envMapBlendingDefine = \\\\\\\"ENVMAP_BLENDING_MIX\\\\\\\";\\n break;\\n case AddOperation:\\n envMapBlendingDefine = \\\\\\\"ENVMAP_BLENDING_ADD\\\\\\\";\\n break;\\n }\\n }\\n return envMapBlendingDefine;\\n}\\nfunction WebGLProgram(renderer, cacheKey, parameters, bindingStates) {\\n const gl = renderer.getContext();\\n const defines = parameters.defines;\\n let vertexShader = parameters.vertexShader;\\n let fragmentShader = parameters.fragmentShader;\\n const shadowMapTypeDefine = generateShadowMapTypeDefine(parameters);\\n const envMapTypeDefine = generateEnvMapTypeDefine(parameters);\\n const envMapModeDefine = generateEnvMapModeDefine(parameters);\\n const envMapBlendingDefine = generateEnvMapBlendingDefine(parameters);\\n const gammaFactorDefine = renderer.gammaFactor > 0 ? renderer.gammaFactor : 1;\\n const customExtensions = parameters.isWebGL2 ? \\\\\\\"\\\\\\\" : generateExtensions(parameters);\\n const customDefines = generateDefines(defines);\\n const program = gl.createProgram();\\n let prefixVertex, prefixFragment;\\n let versionString = parameters.glslVersion ? \\\\\\\"#version \\\\\\\" + parameters.glslVersion + \\\\\\\"\\\\n\\\\\\\" : \\\\\\\"\\\\\\\";\\n if (parameters.isRawShaderMaterial) {\\n prefixVertex = [\\n customDefines\\n ].filter(filterEmptyLine).join(\\\\\\\"\\\\n\\\\\\\");\\n if (prefixVertex.length > 0) {\\n prefixVertex += \\\\\\\"\\\\n\\\\\\\";\\n }\\n prefixFragment = [\\n customExtensions,\\n customDefines\\n ].filter(filterEmptyLine).join(\\\\\\\"\\\\n\\\\\\\");\\n if (prefixFragment.length > 0) {\\n prefixFragment += \\\\\\\"\\\\n\\\\\\\";\\n }\\n } else {\\n prefixVertex = [\\n generatePrecision(parameters),\\n \\\\\\\"#define SHADER_NAME \\\\\\\" + parameters.shaderName,\\n customDefines,\\n parameters.instancing ? \\\\\\\"#define USE_INSTANCING\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.instancingColor ? \\\\\\\"#define USE_INSTANCING_COLOR\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.supportsVertexTextures ? \\\\\\\"#define VERTEX_TEXTURES\\\\\\\" : \\\\\\\"\\\\\\\",\\n \\\\\\\"#define GAMMA_FACTOR \\\\\\\" + gammaFactorDefine,\\n \\\\\\\"#define MAX_BONES \\\\\\\" + parameters.maxBones,\\n parameters.useFog && parameters.fog ? \\\\\\\"#define USE_FOG\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.useFog && parameters.fogExp2 ? \\\\\\\"#define FOG_EXP2\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.map ? \\\\\\\"#define USE_MAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.envMap ? \\\\\\\"#define USE_ENVMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.envMap ? \\\\\\\"#define \\\\\\\" + envMapModeDefine : \\\\\\\"\\\\\\\",\\n parameters.lightMap ? \\\\\\\"#define USE_LIGHTMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.aoMap ? \\\\\\\"#define USE_AOMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.emissiveMap ? \\\\\\\"#define USE_EMISSIVEMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.bumpMap ? \\\\\\\"#define USE_BUMPMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.normalMap ? \\\\\\\"#define USE_NORMALMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.normalMap && parameters.objectSpaceNormalMap ? \\\\\\\"#define OBJECTSPACE_NORMALMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.normalMap && parameters.tangentSpaceNormalMap ? \\\\\\\"#define TANGENTSPACE_NORMALMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.clearcoatMap ? \\\\\\\"#define USE_CLEARCOATMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.clearcoatRoughnessMap ? \\\\\\\"#define USE_CLEARCOAT_ROUGHNESSMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.clearcoatNormalMap ? \\\\\\\"#define USE_CLEARCOAT_NORMALMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.displacementMap && parameters.supportsVertexTextures ? \\\\\\\"#define USE_DISPLACEMENTMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.specularMap ? \\\\\\\"#define USE_SPECULARMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.specularIntensityMap ? \\\\\\\"#define USE_SPECULARINTENSITYMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.specularTintMap ? \\\\\\\"#define USE_SPECULARTINTMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.roughnessMap ? \\\\\\\"#define USE_ROUGHNESSMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.metalnessMap ? \\\\\\\"#define USE_METALNESSMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.alphaMap ? \\\\\\\"#define USE_ALPHAMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.transmission ? \\\\\\\"#define USE_TRANSMISSION\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.transmissionMap ? \\\\\\\"#define USE_TRANSMISSIONMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.thicknessMap ? \\\\\\\"#define USE_THICKNESSMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.vertexTangents ? \\\\\\\"#define USE_TANGENT\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.vertexColors ? \\\\\\\"#define USE_COLOR\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.vertexAlphas ? \\\\\\\"#define USE_COLOR_ALPHA\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.vertexUvs ? \\\\\\\"#define USE_UV\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.uvsVertexOnly ? \\\\\\\"#define UVS_VERTEX_ONLY\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.flatShading ? \\\\\\\"#define FLAT_SHADED\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.skinning ? \\\\\\\"#define USE_SKINNING\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.useVertexTexture ? \\\\\\\"#define BONE_TEXTURE\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.morphTargets ? \\\\\\\"#define USE_MORPHTARGETS\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.morphNormals && parameters.flatShading === false ? \\\\\\\"#define USE_MORPHNORMALS\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.morphTargets && parameters.isWebGL2 ? \\\\\\\"#define MORPHTARGETS_TEXTURE\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.morphTargets && parameters.isWebGL2 ? \\\\\\\"#define MORPHTARGETS_COUNT \\\\\\\" + parameters.morphTargetsCount : \\\\\\\"\\\\\\\",\\n parameters.doubleSided ? \\\\\\\"#define DOUBLE_SIDED\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.flipSided ? \\\\\\\"#define FLIP_SIDED\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.shadowMapEnabled ? \\\\\\\"#define USE_SHADOWMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.shadowMapEnabled ? \\\\\\\"#define \\\\\\\" + shadowMapTypeDefine : \\\\\\\"\\\\\\\",\\n parameters.sizeAttenuation ? \\\\\\\"#define USE_SIZEATTENUATION\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.logarithmicDepthBuffer ? \\\\\\\"#define USE_LOGDEPTHBUF\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.logarithmicDepthBuffer && parameters.rendererExtensionFragDepth ? \\\\\\\"#define USE_LOGDEPTHBUF_EXT\\\\\\\" : \\\\\\\"\\\\\\\",\\n \\\\\\\"uniform mat4 modelMatrix;\\\\\\\",\\n \\\\\\\"uniform mat4 modelViewMatrix;\\\\\\\",\\n \\\\\\\"uniform mat4 projectionMatrix;\\\\\\\",\\n \\\\\\\"uniform mat4 viewMatrix;\\\\\\\",\\n \\\\\\\"uniform mat3 normalMatrix;\\\\\\\",\\n \\\\\\\"uniform vec3 cameraPosition;\\\\\\\",\\n \\\\\\\"uniform bool isOrthographic;\\\\\\\",\\n \\\\\\\"#ifdef USE_INSTANCING\\\\\\\",\\n \\\\\\\"\\tattribute mat4 instanceMatrix;\\\\\\\",\\n \\\\\\\"#endif\\\\\\\",\\n \\\\\\\"#ifdef USE_INSTANCING_COLOR\\\\\\\",\\n \\\\\\\"\\tattribute vec3 instanceColor;\\\\\\\",\\n \\\\\\\"#endif\\\\\\\",\\n \\\\\\\"attribute vec3 position;\\\\\\\",\\n \\\\\\\"attribute vec3 normal;\\\\\\\",\\n \\\\\\\"attribute vec2 uv;\\\\\\\",\\n \\\\\\\"#ifdef USE_TANGENT\\\\\\\",\\n \\\\\\\"\\tattribute vec4 tangent;\\\\\\\",\\n \\\\\\\"#endif\\\\\\\",\\n \\\\\\\"#if defined( USE_COLOR_ALPHA )\\\\\\\",\\n \\\\\\\"\\tattribute vec4 color;\\\\\\\",\\n \\\\\\\"#elif defined( USE_COLOR )\\\\\\\",\\n \\\\\\\"\\tattribute vec3 color;\\\\\\\",\\n \\\\\\\"#endif\\\\\\\",\\n \\\\\\\"#if ( defined( USE_MORPHTARGETS ) && ! defined( MORPHTARGETS_TEXTURE ) )\\\\\\\",\\n \\\\\\\"\\tattribute vec3 morphTarget0;\\\\\\\",\\n \\\\\\\"\\tattribute vec3 morphTarget1;\\\\\\\",\\n \\\\\\\"\\tattribute vec3 morphTarget2;\\\\\\\",\\n \\\\\\\"\\tattribute vec3 morphTarget3;\\\\\\\",\\n \\\\\\\"\\t#ifdef USE_MORPHNORMALS\\\\\\\",\\n \\\\\\\"\\t\\tattribute vec3 morphNormal0;\\\\\\\",\\n \\\\\\\"\\t\\tattribute vec3 morphNormal1;\\\\\\\",\\n \\\\\\\"\\t\\tattribute vec3 morphNormal2;\\\\\\\",\\n \\\\\\\"\\t\\tattribute vec3 morphNormal3;\\\\\\\",\\n \\\\\\\"\\t#else\\\\\\\",\\n \\\\\\\"\\t\\tattribute vec3 morphTarget4;\\\\\\\",\\n \\\\\\\"\\t\\tattribute vec3 morphTarget5;\\\\\\\",\\n \\\\\\\"\\t\\tattribute vec3 morphTarget6;\\\\\\\",\\n \\\\\\\"\\t\\tattribute vec3 morphTarget7;\\\\\\\",\\n \\\\\\\"\\t#endif\\\\\\\",\\n \\\\\\\"#endif\\\\\\\",\\n \\\\\\\"#ifdef USE_SKINNING\\\\\\\",\\n \\\\\\\"\\tattribute vec4 skinIndex;\\\\\\\",\\n \\\\\\\"\\tattribute vec4 skinWeight;\\\\\\\",\\n \\\\\\\"#endif\\\\\\\",\\n \\\\\\\"\\\\n\\\\\\\"\\n ].filter(filterEmptyLine).join(\\\\\\\"\\\\n\\\\\\\");\\n prefixFragment = [\\n customExtensions,\\n generatePrecision(parameters),\\n \\\\\\\"#define SHADER_NAME \\\\\\\" + parameters.shaderName,\\n customDefines,\\n \\\\\\\"#define GAMMA_FACTOR \\\\\\\" + gammaFactorDefine,\\n parameters.useFog && parameters.fog ? \\\\\\\"#define USE_FOG\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.useFog && parameters.fogExp2 ? \\\\\\\"#define FOG_EXP2\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.map ? \\\\\\\"#define USE_MAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.matcap ? \\\\\\\"#define USE_MATCAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.envMap ? \\\\\\\"#define USE_ENVMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.envMap ? \\\\\\\"#define \\\\\\\" + envMapTypeDefine : \\\\\\\"\\\\\\\",\\n parameters.envMap ? \\\\\\\"#define \\\\\\\" + envMapModeDefine : \\\\\\\"\\\\\\\",\\n parameters.envMap ? \\\\\\\"#define \\\\\\\" + envMapBlendingDefine : \\\\\\\"\\\\\\\",\\n parameters.lightMap ? \\\\\\\"#define USE_LIGHTMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.aoMap ? \\\\\\\"#define USE_AOMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.emissiveMap ? \\\\\\\"#define USE_EMISSIVEMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.bumpMap ? \\\\\\\"#define USE_BUMPMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.normalMap ? \\\\\\\"#define USE_NORMALMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.normalMap && parameters.objectSpaceNormalMap ? \\\\\\\"#define OBJECTSPACE_NORMALMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.normalMap && parameters.tangentSpaceNormalMap ? \\\\\\\"#define TANGENTSPACE_NORMALMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.clearcoat ? \\\\\\\"#define USE_CLEARCOAT\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.clearcoatMap ? \\\\\\\"#define USE_CLEARCOATMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.clearcoatRoughnessMap ? \\\\\\\"#define USE_CLEARCOAT_ROUGHNESSMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.clearcoatNormalMap ? \\\\\\\"#define USE_CLEARCOAT_NORMALMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.specularMap ? \\\\\\\"#define USE_SPECULARMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.specularIntensityMap ? \\\\\\\"#define USE_SPECULARINTENSITYMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.specularTintMap ? \\\\\\\"#define USE_SPECULARTINTMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.roughnessMap ? \\\\\\\"#define USE_ROUGHNESSMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.metalnessMap ? \\\\\\\"#define USE_METALNESSMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.alphaMap ? \\\\\\\"#define USE_ALPHAMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.alphaTest ? \\\\\\\"#define USE_ALPHATEST\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.sheen ? \\\\\\\"#define USE_SHEEN\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.transmission ? \\\\\\\"#define USE_TRANSMISSION\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.transmissionMap ? \\\\\\\"#define USE_TRANSMISSIONMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.thicknessMap ? \\\\\\\"#define USE_THICKNESSMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.vertexTangents ? \\\\\\\"#define USE_TANGENT\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.vertexColors || parameters.instancingColor ? \\\\\\\"#define USE_COLOR\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.vertexAlphas ? \\\\\\\"#define USE_COLOR_ALPHA\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.vertexUvs ? \\\\\\\"#define USE_UV\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.uvsVertexOnly ? \\\\\\\"#define UVS_VERTEX_ONLY\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.gradientMap ? \\\\\\\"#define USE_GRADIENTMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.flatShading ? \\\\\\\"#define FLAT_SHADED\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.doubleSided ? \\\\\\\"#define DOUBLE_SIDED\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.flipSided ? \\\\\\\"#define FLIP_SIDED\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.shadowMapEnabled ? \\\\\\\"#define USE_SHADOWMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.shadowMapEnabled ? \\\\\\\"#define \\\\\\\" + shadowMapTypeDefine : \\\\\\\"\\\\\\\",\\n parameters.premultipliedAlpha ? \\\\\\\"#define PREMULTIPLIED_ALPHA\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.physicallyCorrectLights ? \\\\\\\"#define PHYSICALLY_CORRECT_LIGHTS\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.logarithmicDepthBuffer ? \\\\\\\"#define USE_LOGDEPTHBUF\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.logarithmicDepthBuffer && parameters.rendererExtensionFragDepth ? \\\\\\\"#define USE_LOGDEPTHBUF_EXT\\\\\\\" : \\\\\\\"\\\\\\\",\\n (parameters.extensionShaderTextureLOD || parameters.envMap) && parameters.rendererExtensionShaderTextureLod ? \\\\\\\"#define TEXTURE_LOD_EXT\\\\\\\" : \\\\\\\"\\\\\\\",\\n \\\\\\\"uniform mat4 viewMatrix;\\\\\\\",\\n \\\\\\\"uniform vec3 cameraPosition;\\\\\\\",\\n \\\\\\\"uniform bool isOrthographic;\\\\\\\",\\n parameters.toneMapping !== NoToneMapping ? \\\\\\\"#define TONE_MAPPING\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.toneMapping !== NoToneMapping ? ShaderChunk[\\\\\\\"tonemapping_pars_fragment\\\\\\\"] : \\\\\\\"\\\\\\\",\\n parameters.toneMapping !== NoToneMapping ? getToneMappingFunction(\\\\\\\"toneMapping\\\\\\\", parameters.toneMapping) : \\\\\\\"\\\\\\\",\\n parameters.dithering ? \\\\\\\"#define DITHERING\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.format === RGBFormat ? \\\\\\\"#define OPAQUE\\\\\\\" : \\\\\\\"\\\\\\\",\\n ShaderChunk[\\\\\\\"encodings_pars_fragment\\\\\\\"],\\n parameters.map ? getTexelDecodingFunction(\\\\\\\"mapTexelToLinear\\\\\\\", parameters.mapEncoding) : \\\\\\\"\\\\\\\",\\n parameters.matcap ? getTexelDecodingFunction(\\\\\\\"matcapTexelToLinear\\\\\\\", parameters.matcapEncoding) : \\\\\\\"\\\\\\\",\\n parameters.envMap ? getTexelDecodingFunction(\\\\\\\"envMapTexelToLinear\\\\\\\", parameters.envMapEncoding) : \\\\\\\"\\\\\\\",\\n parameters.emissiveMap ? getTexelDecodingFunction(\\\\\\\"emissiveMapTexelToLinear\\\\\\\", parameters.emissiveMapEncoding) : \\\\\\\"\\\\\\\",\\n parameters.specularTintMap ? getTexelDecodingFunction(\\\\\\\"specularTintMapTexelToLinear\\\\\\\", parameters.specularTintMapEncoding) : \\\\\\\"\\\\\\\",\\n parameters.lightMap ? getTexelDecodingFunction(\\\\\\\"lightMapTexelToLinear\\\\\\\", parameters.lightMapEncoding) : \\\\\\\"\\\\\\\",\\n getTexelEncodingFunction(\\\\\\\"linearToOutputTexel\\\\\\\", parameters.outputEncoding),\\n parameters.depthPacking ? \\\\\\\"#define DEPTH_PACKING \\\\\\\" + parameters.depthPacking : \\\\\\\"\\\\\\\",\\n \\\\\\\"\\\\n\\\\\\\"\\n ].filter(filterEmptyLine).join(\\\\\\\"\\\\n\\\\\\\");\\n }\\n vertexShader = resolveIncludes(vertexShader);\\n vertexShader = replaceLightNums(vertexShader, parameters);\\n vertexShader = replaceClippingPlaneNums(vertexShader, parameters);\\n fragmentShader = resolveIncludes(fragmentShader);\\n fragmentShader = replaceLightNums(fragmentShader, parameters);\\n fragmentShader = replaceClippingPlaneNums(fragmentShader, parameters);\\n vertexShader = unrollLoops(vertexShader);\\n fragmentShader = unrollLoops(fragmentShader);\\n if (parameters.isWebGL2 && parameters.isRawShaderMaterial !== true) {\\n versionString = \\\\\\\"#version 300 es\\\\n\\\\\\\";\\n prefixVertex = [\\n \\\\\\\"precision mediump sampler2DArray;\\\\\\\",\\n \\\\\\\"#define attribute in\\\\\\\",\\n \\\\\\\"#define varying out\\\\\\\",\\n \\\\\\\"#define texture2D texture\\\\\\\"\\n ].join(\\\\\\\"\\\\n\\\\\\\") + \\\\\\\"\\\\n\\\\\\\" + prefixVertex;\\n prefixFragment = [\\n \\\\\\\"#define varying in\\\\\\\",\\n parameters.glslVersion === GLSL3 ? \\\\\\\"\\\\\\\" : \\\\\\\"out highp vec4 pc_fragColor;\\\\\\\",\\n parameters.glslVersion === GLSL3 ? \\\\\\\"\\\\\\\" : \\\\\\\"#define gl_FragColor pc_fragColor\\\\\\\",\\n \\\\\\\"#define gl_FragDepthEXT gl_FragDepth\\\\\\\",\\n \\\\\\\"#define texture2D texture\\\\\\\",\\n \\\\\\\"#define textureCube texture\\\\\\\",\\n \\\\\\\"#define texture2DProj textureProj\\\\\\\",\\n \\\\\\\"#define texture2DLodEXT textureLod\\\\\\\",\\n \\\\\\\"#define texture2DProjLodEXT textureProjLod\\\\\\\",\\n \\\\\\\"#define textureCubeLodEXT textureLod\\\\\\\",\\n \\\\\\\"#define texture2DGradEXT textureGrad\\\\\\\",\\n \\\\\\\"#define texture2DProjGradEXT textureProjGrad\\\\\\\",\\n \\\\\\\"#define textureCubeGradEXT textureGrad\\\\\\\"\\n ].join(\\\\\\\"\\\\n\\\\\\\") + \\\\\\\"\\\\n\\\\\\\" + prefixFragment;\\n }\\n const vertexGlsl = versionString + prefixVertex + vertexShader;\\n const fragmentGlsl = versionString + prefixFragment + fragmentShader;\\n const glVertexShader = WebGLShader(gl, gl.VERTEX_SHADER, vertexGlsl);\\n const glFragmentShader = WebGLShader(gl, gl.FRAGMENT_SHADER, fragmentGlsl);\\n gl.attachShader(program, glVertexShader);\\n gl.attachShader(program, glFragmentShader);\\n if (parameters.index0AttributeName !== void 0) {\\n gl.bindAttribLocation(program, 0, parameters.index0AttributeName);\\n } else if (parameters.morphTargets === true) {\\n gl.bindAttribLocation(program, 0, \\\\\\\"position\\\\\\\");\\n }\\n gl.linkProgram(program);\\n if (renderer.debug.checkShaderErrors) {\\n const programLog = gl.getProgramInfoLog(program).trim();\\n const vertexLog = gl.getShaderInfoLog(glVertexShader).trim();\\n const fragmentLog = gl.getShaderInfoLog(glFragmentShader).trim();\\n let runnable = true;\\n let haveDiagnostics = true;\\n if (gl.getProgramParameter(program, gl.LINK_STATUS) === false) {\\n runnable = false;\\n const vertexErrors = getShaderErrors(gl, glVertexShader, \\\\\\\"vertex\\\\\\\");\\n const fragmentErrors = getShaderErrors(gl, glFragmentShader, \\\\\\\"fragment\\\\\\\");\\n console.error(\\\\\\\"THREE.WebGLProgram: Shader Error \\\\\\\" + gl.getError() + \\\\\\\" - VALIDATE_STATUS \\\\\\\" + gl.getProgramParameter(program, gl.VALIDATE_STATUS) + \\\\\\\"\\\\n\\\\nProgram Info Log: \\\\\\\" + programLog + \\\\\\\"\\\\n\\\\\\\" + vertexErrors + \\\\\\\"\\\\n\\\\\\\" + fragmentErrors);\\n } else if (programLog !== \\\\\\\"\\\\\\\") {\\n console.warn(\\\\\\\"THREE.WebGLProgram: Program Info Log:\\\\\\\", programLog);\\n } else if (vertexLog === \\\\\\\"\\\\\\\" || fragmentLog === \\\\\\\"\\\\\\\") {\\n haveDiagnostics = false;\\n }\\n if (haveDiagnostics) {\\n this.diagnostics = {\\n runnable,\\n programLog,\\n vertexShader: {\\n log: vertexLog,\\n prefix: prefixVertex\\n },\\n fragmentShader: {\\n log: fragmentLog,\\n prefix: prefixFragment\\n }\\n };\\n }\\n }\\n gl.deleteShader(glVertexShader);\\n gl.deleteShader(glFragmentShader);\\n let cachedUniforms;\\n this.getUniforms = function() {\\n if (cachedUniforms === void 0) {\\n cachedUniforms = new WebGLUniforms(gl, program);\\n }\\n return cachedUniforms;\\n };\\n let cachedAttributes;\\n this.getAttributes = function() {\\n if (cachedAttributes === void 0) {\\n cachedAttributes = fetchAttributeLocations(gl, program);\\n }\\n return cachedAttributes;\\n };\\n this.destroy = function() {\\n bindingStates.releaseStatesOfProgram(this);\\n gl.deleteProgram(program);\\n this.program = void 0;\\n };\\n this.name = parameters.shaderName;\\n this.id = programIdCount++;\\n this.cacheKey = cacheKey;\\n this.usedTimes = 1;\\n this.program = program;\\n this.vertexShader = glVertexShader;\\n this.fragmentShader = glFragmentShader;\\n return this;\\n}\\n\\n// ../../../node_modules/three/src/renderers/webgl/WebGLPrograms.js\\nfunction WebGLPrograms(renderer, cubemaps, cubeuvmaps, extensions, capabilities, bindingStates, clipping) {\\n const programs = [];\\n const isWebGL2 = capabilities.isWebGL2;\\n const logarithmicDepthBuffer = capabilities.logarithmicDepthBuffer;\\n const floatVertexTextures = capabilities.floatVertexTextures;\\n const maxVertexUniforms = capabilities.maxVertexUniforms;\\n const vertexTextures = capabilities.vertexTextures;\\n let precision = capabilities.precision;\\n const shaderIDs = {\\n MeshDepthMaterial: \\\\\\\"depth\\\\\\\",\\n MeshDistanceMaterial: \\\\\\\"distanceRGBA\\\\\\\",\\n MeshNormalMaterial: \\\\\\\"normal\\\\\\\",\\n MeshBasicMaterial: \\\\\\\"basic\\\\\\\",\\n MeshLambertMaterial: \\\\\\\"lambert\\\\\\\",\\n MeshPhongMaterial: \\\\\\\"phong\\\\\\\",\\n MeshToonMaterial: \\\\\\\"toon\\\\\\\",\\n MeshStandardMaterial: \\\\\\\"physical\\\\\\\",\\n MeshPhysicalMaterial: \\\\\\\"physical\\\\\\\",\\n MeshMatcapMaterial: \\\\\\\"matcap\\\\\\\",\\n LineBasicMaterial: \\\\\\\"basic\\\\\\\",\\n LineDashedMaterial: \\\\\\\"dashed\\\\\\\",\\n PointsMaterial: \\\\\\\"points\\\\\\\",\\n ShadowMaterial: \\\\\\\"shadow\\\\\\\",\\n SpriteMaterial: \\\\\\\"sprite\\\\\\\"\\n };\\n const parameterNames = [\\n \\\\\\\"precision\\\\\\\",\\n \\\\\\\"isWebGL2\\\\\\\",\\n \\\\\\\"supportsVertexTextures\\\\\\\",\\n \\\\\\\"outputEncoding\\\\\\\",\\n \\\\\\\"instancing\\\\\\\",\\n \\\\\\\"instancingColor\\\\\\\",\\n \\\\\\\"map\\\\\\\",\\n \\\\\\\"mapEncoding\\\\\\\",\\n \\\\\\\"matcap\\\\\\\",\\n \\\\\\\"matcapEncoding\\\\\\\",\\n \\\\\\\"envMap\\\\\\\",\\n \\\\\\\"envMapMode\\\\\\\",\\n \\\\\\\"envMapEncoding\\\\\\\",\\n \\\\\\\"envMapCubeUV\\\\\\\",\\n \\\\\\\"lightMap\\\\\\\",\\n \\\\\\\"lightMapEncoding\\\\\\\",\\n \\\\\\\"aoMap\\\\\\\",\\n \\\\\\\"emissiveMap\\\\\\\",\\n \\\\\\\"emissiveMapEncoding\\\\\\\",\\n \\\\\\\"bumpMap\\\\\\\",\\n \\\\\\\"normalMap\\\\\\\",\\n \\\\\\\"objectSpaceNormalMap\\\\\\\",\\n \\\\\\\"tangentSpaceNormalMap\\\\\\\",\\n \\\\\\\"clearcoat\\\\\\\",\\n \\\\\\\"clearcoatMap\\\\\\\",\\n \\\\\\\"clearcoatRoughnessMap\\\\\\\",\\n \\\\\\\"clearcoatNormalMap\\\\\\\",\\n \\\\\\\"displacementMap\\\\\\\",\\n \\\\\\\"specularMap\\\\\\\",\\n \\\\\\\"specularIntensityMap\\\\\\\",\\n \\\\\\\"specularTintMap\\\\\\\",\\n \\\\\\\"specularTintMapEncoding\\\\\\\",\\n \\\\\\\"roughnessMap\\\\\\\",\\n \\\\\\\"metalnessMap\\\\\\\",\\n \\\\\\\"gradientMap\\\\\\\",\\n \\\\\\\"alphaMap\\\\\\\",\\n \\\\\\\"alphaTest\\\\\\\",\\n \\\\\\\"combine\\\\\\\",\\n \\\\\\\"vertexColors\\\\\\\",\\n \\\\\\\"vertexAlphas\\\\\\\",\\n \\\\\\\"vertexTangents\\\\\\\",\\n \\\\\\\"vertexUvs\\\\\\\",\\n \\\\\\\"uvsVertexOnly\\\\\\\",\\n \\\\\\\"fog\\\\\\\",\\n \\\\\\\"useFog\\\\\\\",\\n \\\\\\\"fogExp2\\\\\\\",\\n \\\\\\\"flatShading\\\\\\\",\\n \\\\\\\"sizeAttenuation\\\\\\\",\\n \\\\\\\"logarithmicDepthBuffer\\\\\\\",\\n \\\\\\\"skinning\\\\\\\",\\n \\\\\\\"maxBones\\\\\\\",\\n \\\\\\\"useVertexTexture\\\\\\\",\\n \\\\\\\"morphTargets\\\\\\\",\\n \\\\\\\"morphNormals\\\\\\\",\\n \\\\\\\"morphTargetsCount\\\\\\\",\\n \\\\\\\"premultipliedAlpha\\\\\\\",\\n \\\\\\\"numDirLights\\\\\\\",\\n \\\\\\\"numPointLights\\\\\\\",\\n \\\\\\\"numSpotLights\\\\\\\",\\n \\\\\\\"numHemiLights\\\\\\\",\\n \\\\\\\"numRectAreaLights\\\\\\\",\\n \\\\\\\"numDirLightShadows\\\\\\\",\\n \\\\\\\"numPointLightShadows\\\\\\\",\\n \\\\\\\"numSpotLightShadows\\\\\\\",\\n \\\\\\\"shadowMapEnabled\\\\\\\",\\n \\\\\\\"shadowMapType\\\\\\\",\\n \\\\\\\"toneMapping\\\\\\\",\\n \\\\\\\"physicallyCorrectLights\\\\\\\",\\n \\\\\\\"doubleSided\\\\\\\",\\n \\\\\\\"flipSided\\\\\\\",\\n \\\\\\\"numClippingPlanes\\\\\\\",\\n \\\\\\\"numClipIntersection\\\\\\\",\\n \\\\\\\"depthPacking\\\\\\\",\\n \\\\\\\"dithering\\\\\\\",\\n \\\\\\\"format\\\\\\\",\\n \\\\\\\"sheen\\\\\\\",\\n \\\\\\\"transmission\\\\\\\",\\n \\\\\\\"transmissionMap\\\\\\\",\\n \\\\\\\"thicknessMap\\\\\\\"\\n ];\\n function getMaxBones(object) {\\n const skeleton = object.skeleton;\\n const bones = skeleton.bones;\\n if (floatVertexTextures) {\\n return 1024;\\n } else {\\n const nVertexUniforms = maxVertexUniforms;\\n const nVertexMatrices = Math.floor((nVertexUniforms - 20) / 4);\\n const maxBones = Math.min(nVertexMatrices, bones.length);\\n if (maxBones < bones.length) {\\n console.warn(\\\\\\\"THREE.WebGLRenderer: Skeleton has \\\\\\\" + bones.length + \\\\\\\" bones. This GPU supports \\\\\\\" + maxBones + \\\\\\\".\\\\\\\");\\n return 0;\\n }\\n return maxBones;\\n }\\n }\\n function getTextureEncodingFromMap(map) {\\n let encoding;\\n if (map && map.isTexture) {\\n encoding = map.encoding;\\n } else if (map && map.isWebGLRenderTarget) {\\n console.warn(\\\\\\\"THREE.WebGLPrograms.getTextureEncodingFromMap: don't use render targets as textures. Use their .texture property instead.\\\\\\\");\\n encoding = map.texture.encoding;\\n } else {\\n encoding = LinearEncoding;\\n }\\n if (isWebGL2 && map && map.isTexture && map.format === RGBAFormat && map.type === UnsignedByteType && map.encoding === sRGBEncoding) {\\n encoding = LinearEncoding;\\n }\\n return encoding;\\n }\\n function getParameters(material, lights, shadows, scene, object) {\\n const fog = scene.fog;\\n const environment = material.isMeshStandardMaterial ? scene.environment : null;\\n const envMap = (material.isMeshStandardMaterial ? cubeuvmaps : cubemaps).get(material.envMap || environment);\\n const shaderID = shaderIDs[material.type];\\n const maxBones = object.isSkinnedMesh ? getMaxBones(object) : 0;\\n if (material.precision !== null) {\\n precision = capabilities.getMaxPrecision(material.precision);\\n if (precision !== material.precision) {\\n console.warn(\\\\\\\"THREE.WebGLProgram.getParameters:\\\\\\\", material.precision, \\\\\\\"not supported, using\\\\\\\", precision, \\\\\\\"instead.\\\\\\\");\\n }\\n }\\n let vertexShader, fragmentShader;\\n if (shaderID) {\\n const shader = ShaderLib[shaderID];\\n vertexShader = shader.vertexShader;\\n fragmentShader = shader.fragmentShader;\\n } else {\\n vertexShader = material.vertexShader;\\n fragmentShader = material.fragmentShader;\\n }\\n const currentRenderTarget = renderer.getRenderTarget();\\n const useAlphaTest = material.alphaTest > 0;\\n const useClearcoat = material.clearcoat > 0;\\n const parameters = {\\n isWebGL2,\\n shaderID,\\n shaderName: material.type,\\n vertexShader,\\n fragmentShader,\\n defines: material.defines,\\n isRawShaderMaterial: material.isRawShaderMaterial === true,\\n glslVersion: material.glslVersion,\\n precision,\\n instancing: object.isInstancedMesh === true,\\n instancingColor: object.isInstancedMesh === true && object.instanceColor !== null,\\n supportsVertexTextures: vertexTextures,\\n outputEncoding: currentRenderTarget !== null ? getTextureEncodingFromMap(currentRenderTarget.texture) : renderer.outputEncoding,\\n map: !!material.map,\\n mapEncoding: getTextureEncodingFromMap(material.map),\\n matcap: !!material.matcap,\\n matcapEncoding: getTextureEncodingFromMap(material.matcap),\\n envMap: !!envMap,\\n envMapMode: envMap && envMap.mapping,\\n envMapEncoding: getTextureEncodingFromMap(envMap),\\n envMapCubeUV: !!envMap && (envMap.mapping === CubeUVReflectionMapping || envMap.mapping === CubeUVRefractionMapping),\\n lightMap: !!material.lightMap,\\n lightMapEncoding: getTextureEncodingFromMap(material.lightMap),\\n aoMap: !!material.aoMap,\\n emissiveMap: !!material.emissiveMap,\\n emissiveMapEncoding: getTextureEncodingFromMap(material.emissiveMap),\\n bumpMap: !!material.bumpMap,\\n normalMap: !!material.normalMap,\\n objectSpaceNormalMap: material.normalMapType === ObjectSpaceNormalMap,\\n tangentSpaceNormalMap: material.normalMapType === TangentSpaceNormalMap,\\n clearcoat: useClearcoat,\\n clearcoatMap: useClearcoat && !!material.clearcoatMap,\\n clearcoatRoughnessMap: useClearcoat && !!material.clearcoatRoughnessMap,\\n clearcoatNormalMap: useClearcoat && !!material.clearcoatNormalMap,\\n displacementMap: !!material.displacementMap,\\n roughnessMap: !!material.roughnessMap,\\n metalnessMap: !!material.metalnessMap,\\n specularMap: !!material.specularMap,\\n specularIntensityMap: !!material.specularIntensityMap,\\n specularTintMap: !!material.specularTintMap,\\n specularTintMapEncoding: getTextureEncodingFromMap(material.specularTintMap),\\n alphaMap: !!material.alphaMap,\\n alphaTest: useAlphaTest,\\n gradientMap: !!material.gradientMap,\\n sheen: material.sheen > 0,\\n transmission: material.transmission > 0,\\n transmissionMap: !!material.transmissionMap,\\n thicknessMap: !!material.thicknessMap,\\n combine: material.combine,\\n vertexTangents: !!material.normalMap && !!object.geometry && !!object.geometry.attributes.tangent,\\n vertexColors: material.vertexColors,\\n vertexAlphas: material.vertexColors === true && !!object.geometry && !!object.geometry.attributes.color && object.geometry.attributes.color.itemSize === 4,\\n vertexUvs: !!material.map || !!material.bumpMap || !!material.normalMap || !!material.specularMap || !!material.alphaMap || !!material.emissiveMap || !!material.roughnessMap || !!material.metalnessMap || !!material.clearcoatMap || !!material.clearcoatRoughnessMap || !!material.clearcoatNormalMap || !!material.displacementMap || !!material.transmissionMap || !!material.thicknessMap || !!material.specularIntensityMap || !!material.specularTintMap,\\n uvsVertexOnly: !(!!material.map || !!material.bumpMap || !!material.normalMap || !!material.specularMap || !!material.alphaMap || !!material.emissiveMap || !!material.roughnessMap || !!material.metalnessMap || !!material.clearcoatNormalMap || material.transmission > 0 || !!material.transmissionMap || !!material.thicknessMap || !!material.specularIntensityMap || !!material.specularTintMap) && !!material.displacementMap,\\n fog: !!fog,\\n useFog: material.fog,\\n fogExp2: fog && fog.isFogExp2,\\n flatShading: !!material.flatShading,\\n sizeAttenuation: material.sizeAttenuation,\\n logarithmicDepthBuffer,\\n skinning: object.isSkinnedMesh === true && maxBones > 0,\\n maxBones,\\n useVertexTexture: floatVertexTextures,\\n morphTargets: !!object.geometry && !!object.geometry.morphAttributes.position,\\n morphNormals: !!object.geometry && !!object.geometry.morphAttributes.normal,\\n morphTargetsCount: !!object.geometry && !!object.geometry.morphAttributes.position ? object.geometry.morphAttributes.position.length : 0,\\n numDirLights: lights.directional.length,\\n numPointLights: lights.point.length,\\n numSpotLights: lights.spot.length,\\n numRectAreaLights: lights.rectArea.length,\\n numHemiLights: lights.hemi.length,\\n numDirLightShadows: lights.directionalShadowMap.length,\\n numPointLightShadows: lights.pointShadowMap.length,\\n numSpotLightShadows: lights.spotShadowMap.length,\\n numClippingPlanes: clipping.numPlanes,\\n numClipIntersection: clipping.numIntersection,\\n format: material.format,\\n dithering: material.dithering,\\n shadowMapEnabled: renderer.shadowMap.enabled && shadows.length > 0,\\n shadowMapType: renderer.shadowMap.type,\\n toneMapping: material.toneMapped ? renderer.toneMapping : NoToneMapping,\\n physicallyCorrectLights: renderer.physicallyCorrectLights,\\n premultipliedAlpha: material.premultipliedAlpha,\\n doubleSided: material.side === DoubleSide,\\n flipSided: material.side === BackSide,\\n depthPacking: material.depthPacking !== void 0 ? material.depthPacking : false,\\n index0AttributeName: material.index0AttributeName,\\n extensionDerivatives: material.extensions && material.extensions.derivatives,\\n extensionFragDepth: material.extensions && material.extensions.fragDepth,\\n extensionDrawBuffers: material.extensions && material.extensions.drawBuffers,\\n extensionShaderTextureLOD: material.extensions && material.extensions.shaderTextureLOD,\\n rendererExtensionFragDepth: isWebGL2 || extensions.has(\\\\\\\"EXT_frag_depth\\\\\\\"),\\n rendererExtensionDrawBuffers: isWebGL2 || extensions.has(\\\\\\\"WEBGL_draw_buffers\\\\\\\"),\\n rendererExtensionShaderTextureLod: isWebGL2 || extensions.has(\\\\\\\"EXT_shader_texture_lod\\\\\\\"),\\n customProgramCacheKey: material.customProgramCacheKey()\\n };\\n return parameters;\\n }\\n function getProgramCacheKey(parameters) {\\n const array = [];\\n if (parameters.shaderID) {\\n array.push(parameters.shaderID);\\n } else {\\n array.push(parameters.fragmentShader);\\n array.push(parameters.vertexShader);\\n }\\n if (parameters.defines !== void 0) {\\n for (const name in parameters.defines) {\\n array.push(name);\\n array.push(parameters.defines[name]);\\n }\\n }\\n if (parameters.isRawShaderMaterial === false) {\\n for (let i = 0; i < parameterNames.length; i++) {\\n array.push(parameters[parameterNames[i]]);\\n }\\n array.push(renderer.outputEncoding);\\n array.push(renderer.gammaFactor);\\n }\\n array.push(parameters.customProgramCacheKey);\\n return array.join();\\n }\\n function getUniforms(material) {\\n const shaderID = shaderIDs[material.type];\\n let uniforms;\\n if (shaderID) {\\n const shader = ShaderLib[shaderID];\\n uniforms = UniformsUtils.clone(shader.uniforms);\\n } else {\\n uniforms = material.uniforms;\\n }\\n return uniforms;\\n }\\n function acquireProgram(parameters, cacheKey) {\\n let program;\\n for (let p = 0, pl = programs.length; p < pl; p++) {\\n const preexistingProgram = programs[p];\\n if (preexistingProgram.cacheKey === cacheKey) {\\n program = preexistingProgram;\\n ++program.usedTimes;\\n break;\\n }\\n }\\n if (program === void 0) {\\n program = new WebGLProgram(renderer, cacheKey, parameters, bindingStates);\\n programs.push(program);\\n }\\n return program;\\n }\\n function releaseProgram(program) {\\n if (--program.usedTimes === 0) {\\n const i = programs.indexOf(program);\\n programs[i] = programs[programs.length - 1];\\n programs.pop();\\n program.destroy();\\n }\\n }\\n return {\\n getParameters,\\n getProgramCacheKey,\\n getUniforms,\\n acquireProgram,\\n releaseProgram,\\n programs\\n };\\n}\\n\\n// ../../../node_modules/three/src/renderers/webgl/WebGLProperties.js\\nfunction WebGLProperties() {\\n let properties = new WeakMap();\\n function get(object) {\\n let map = properties.get(object);\\n if (map === void 0) {\\n map = {};\\n properties.set(object, map);\\n }\\n return map;\\n }\\n function remove(object) {\\n properties.delete(object);\\n }\\n function update(object, key, value) {\\n properties.get(object)[key] = value;\\n }\\n function dispose() {\\n properties = new WeakMap();\\n }\\n return {\\n get,\\n remove,\\n update,\\n dispose\\n };\\n}\\n\\n// ../../../node_modules/three/src/renderers/webgl/WebGLRenderLists.js\\nfunction painterSortStable(a, b) {\\n if (a.groupOrder !== b.groupOrder) {\\n return a.groupOrder - b.groupOrder;\\n } else if (a.renderOrder !== b.renderOrder) {\\n return a.renderOrder - b.renderOrder;\\n } else if (a.program !== b.program) {\\n return a.program.id - b.program.id;\\n } else if (a.material.id !== b.material.id) {\\n return a.material.id - b.material.id;\\n } else if (a.z !== b.z) {\\n return a.z - b.z;\\n } else {\\n return a.id - b.id;\\n }\\n}\\nfunction reversePainterSortStable(a, b) {\\n if (a.groupOrder !== b.groupOrder) {\\n return a.groupOrder - b.groupOrder;\\n } else if (a.renderOrder !== b.renderOrder) {\\n return a.renderOrder - b.renderOrder;\\n } else if (a.z !== b.z) {\\n return b.z - a.z;\\n } else {\\n return a.id - b.id;\\n }\\n}\\nfunction WebGLRenderList(properties) {\\n const renderItems = [];\\n let renderItemsIndex = 0;\\n const opaque = [];\\n const transmissive = [];\\n const transparent = [];\\n const defaultProgram = {id: -1};\\n function init() {\\n renderItemsIndex = 0;\\n opaque.length = 0;\\n transmissive.length = 0;\\n transparent.length = 0;\\n }\\n function getNextRenderItem(object, geometry, material, groupOrder, z, group) {\\n let renderItem = renderItems[renderItemsIndex];\\n const materialProperties = properties.get(material);\\n if (renderItem === void 0) {\\n renderItem = {\\n id: object.id,\\n object,\\n geometry,\\n material,\\n program: materialProperties.program || defaultProgram,\\n groupOrder,\\n renderOrder: object.renderOrder,\\n z,\\n group\\n };\\n renderItems[renderItemsIndex] = renderItem;\\n } else {\\n renderItem.id = object.id;\\n renderItem.object = object;\\n renderItem.geometry = geometry;\\n renderItem.material = material;\\n renderItem.program = materialProperties.program || defaultProgram;\\n renderItem.groupOrder = groupOrder;\\n renderItem.renderOrder = object.renderOrder;\\n renderItem.z = z;\\n renderItem.group = group;\\n }\\n renderItemsIndex++;\\n return renderItem;\\n }\\n function push(object, geometry, material, groupOrder, z, group) {\\n const renderItem = getNextRenderItem(object, geometry, material, groupOrder, z, group);\\n if (material.transmission > 0) {\\n transmissive.push(renderItem);\\n } else if (material.transparent === true) {\\n transparent.push(renderItem);\\n } else {\\n opaque.push(renderItem);\\n }\\n }\\n function unshift(object, geometry, material, groupOrder, z, group) {\\n const renderItem = getNextRenderItem(object, geometry, material, groupOrder, z, group);\\n if (material.transmission > 0) {\\n transmissive.unshift(renderItem);\\n } else if (material.transparent === true) {\\n transparent.unshift(renderItem);\\n } else {\\n opaque.unshift(renderItem);\\n }\\n }\\n function sort(customOpaqueSort, customTransparentSort) {\\n if (opaque.length > 1)\\n opaque.sort(customOpaqueSort || painterSortStable);\\n if (transmissive.length > 1)\\n transmissive.sort(customTransparentSort || reversePainterSortStable);\\n if (transparent.length > 1)\\n transparent.sort(customTransparentSort || reversePainterSortStable);\\n }\\n function finish() {\\n for (let i = renderItemsIndex, il = renderItems.length; i < il; i++) {\\n const renderItem = renderItems[i];\\n if (renderItem.id === null)\\n break;\\n renderItem.id = null;\\n renderItem.object = null;\\n renderItem.geometry = null;\\n renderItem.material = null;\\n renderItem.program = null;\\n renderItem.group = null;\\n }\\n }\\n return {\\n opaque,\\n transmissive,\\n transparent,\\n init,\\n push,\\n unshift,\\n finish,\\n sort\\n };\\n}\\nfunction WebGLRenderLists(properties) {\\n let lists = new WeakMap();\\n function get(scene, renderCallDepth) {\\n let list;\\n if (lists.has(scene) === false) {\\n list = new WebGLRenderList(properties);\\n lists.set(scene, [list]);\\n } else {\\n if (renderCallDepth >= lists.get(scene).length) {\\n list = new WebGLRenderList(properties);\\n lists.get(scene).push(list);\\n } else {\\n list = lists.get(scene)[renderCallDepth];\\n }\\n }\\n return list;\\n }\\n function dispose() {\\n lists = new WeakMap();\\n }\\n return {\\n get,\\n dispose\\n };\\n}\\n\\n// ../../../node_modules/three/src/renderers/webgl/WebGLLights.js\\nfunction UniformsCache() {\\n const lights = {};\\n return {\\n get: function(light) {\\n if (lights[light.id] !== void 0) {\\n return lights[light.id];\\n }\\n let uniforms;\\n switch (light.type) {\\n case \\\\\\\"DirectionalLight\\\\\\\":\\n uniforms = {\\n direction: new Vector3(),\\n color: new Color()\\n };\\n break;\\n case \\\\\\\"SpotLight\\\\\\\":\\n uniforms = {\\n position: new Vector3(),\\n direction: new Vector3(),\\n color: new Color(),\\n distance: 0,\\n coneCos: 0,\\n penumbraCos: 0,\\n decay: 0\\n };\\n break;\\n case \\\\\\\"PointLight\\\\\\\":\\n uniforms = {\\n position: new Vector3(),\\n color: new Color(),\\n distance: 0,\\n decay: 0\\n };\\n break;\\n case \\\\\\\"HemisphereLight\\\\\\\":\\n uniforms = {\\n direction: new Vector3(),\\n skyColor: new Color(),\\n groundColor: new Color()\\n };\\n break;\\n case \\\\\\\"RectAreaLight\\\\\\\":\\n uniforms = {\\n color: new Color(),\\n position: new Vector3(),\\n halfWidth: new Vector3(),\\n halfHeight: new Vector3()\\n };\\n break;\\n }\\n lights[light.id] = uniforms;\\n return uniforms;\\n }\\n };\\n}\\nfunction ShadowUniformsCache() {\\n const lights = {};\\n return {\\n get: function(light) {\\n if (lights[light.id] !== void 0) {\\n return lights[light.id];\\n }\\n let uniforms;\\n switch (light.type) {\\n case \\\\\\\"DirectionalLight\\\\\\\":\\n uniforms = {\\n shadowBias: 0,\\n shadowNormalBias: 0,\\n shadowRadius: 1,\\n shadowMapSize: new Vector2()\\n };\\n break;\\n case \\\\\\\"SpotLight\\\\\\\":\\n uniforms = {\\n shadowBias: 0,\\n shadowNormalBias: 0,\\n shadowRadius: 1,\\n shadowMapSize: new Vector2()\\n };\\n break;\\n case \\\\\\\"PointLight\\\\\\\":\\n uniforms = {\\n shadowBias: 0,\\n shadowNormalBias: 0,\\n shadowRadius: 1,\\n shadowMapSize: new Vector2(),\\n shadowCameraNear: 1,\\n shadowCameraFar: 1e3\\n };\\n break;\\n }\\n lights[light.id] = uniforms;\\n return uniforms;\\n }\\n };\\n}\\nvar nextVersion = 0;\\nfunction shadowCastingLightsFirst(lightA, lightB) {\\n return (lightB.castShadow ? 1 : 0) - (lightA.castShadow ? 1 : 0);\\n}\\nfunction WebGLLights(extensions, capabilities) {\\n const cache = new UniformsCache();\\n const shadowCache = ShadowUniformsCache();\\n const state = {\\n version: 0,\\n hash: {\\n directionalLength: -1,\\n pointLength: -1,\\n spotLength: -1,\\n rectAreaLength: -1,\\n hemiLength: -1,\\n numDirectionalShadows: -1,\\n numPointShadows: -1,\\n numSpotShadows: -1\\n },\\n ambient: [0, 0, 0],\\n probe: [],\\n directional: [],\\n directionalShadow: [],\\n directionalShadowMap: [],\\n directionalShadowMatrix: [],\\n spot: [],\\n spotShadow: [],\\n spotShadowMap: [],\\n spotShadowMatrix: [],\\n rectArea: [],\\n rectAreaLTC1: null,\\n rectAreaLTC2: null,\\n point: [],\\n pointShadow: [],\\n pointShadowMap: [],\\n pointShadowMatrix: [],\\n hemi: []\\n };\\n for (let i = 0; i < 9; i++)\\n state.probe.push(new Vector3());\\n const vector3 = new Vector3();\\n const matrix4 = new Matrix4();\\n const matrix42 = new Matrix4();\\n function setup(lights, physicallyCorrectLights) {\\n let r = 0, g = 0, b = 0;\\n for (let i = 0; i < 9; i++)\\n state.probe[i].set(0, 0, 0);\\n let directionalLength = 0;\\n let pointLength = 0;\\n let spotLength = 0;\\n let rectAreaLength = 0;\\n let hemiLength = 0;\\n let numDirectionalShadows = 0;\\n let numPointShadows = 0;\\n let numSpotShadows = 0;\\n lights.sort(shadowCastingLightsFirst);\\n const scaleFactor = physicallyCorrectLights !== true ? Math.PI : 1;\\n for (let i = 0, l = lights.length; i < l; i++) {\\n const light = lights[i];\\n const color = light.color;\\n const intensity = light.intensity;\\n const distance = light.distance;\\n const shadowMap = light.shadow && light.shadow.map ? light.shadow.map.texture : null;\\n if (light.isAmbientLight) {\\n r += color.r * intensity * scaleFactor;\\n g += color.g * intensity * scaleFactor;\\n b += color.b * intensity * scaleFactor;\\n } else if (light.isLightProbe) {\\n for (let j = 0; j < 9; j++) {\\n state.probe[j].addScaledVector(light.sh.coefficients[j], intensity);\\n }\\n } else if (light.isDirectionalLight) {\\n const uniforms = cache.get(light);\\n uniforms.color.copy(light.color).multiplyScalar(light.intensity * scaleFactor);\\n if (light.castShadow) {\\n const shadow2 = light.shadow;\\n const shadowUniforms = shadowCache.get(light);\\n shadowUniforms.shadowBias = shadow2.bias;\\n shadowUniforms.shadowNormalBias = shadow2.normalBias;\\n shadowUniforms.shadowRadius = shadow2.radius;\\n shadowUniforms.shadowMapSize = shadow2.mapSize;\\n state.directionalShadow[directionalLength] = shadowUniforms;\\n state.directionalShadowMap[directionalLength] = shadowMap;\\n state.directionalShadowMatrix[directionalLength] = light.shadow.matrix;\\n numDirectionalShadows++;\\n }\\n state.directional[directionalLength] = uniforms;\\n directionalLength++;\\n } else if (light.isSpotLight) {\\n const uniforms = cache.get(light);\\n uniforms.position.setFromMatrixPosition(light.matrixWorld);\\n uniforms.color.copy(color).multiplyScalar(intensity * scaleFactor);\\n uniforms.distance = distance;\\n uniforms.coneCos = Math.cos(light.angle);\\n uniforms.penumbraCos = Math.cos(light.angle * (1 - light.penumbra));\\n uniforms.decay = light.decay;\\n if (light.castShadow) {\\n const shadow2 = light.shadow;\\n const shadowUniforms = shadowCache.get(light);\\n shadowUniforms.shadowBias = shadow2.bias;\\n shadowUniforms.shadowNormalBias = shadow2.normalBias;\\n shadowUniforms.shadowRadius = shadow2.radius;\\n shadowUniforms.shadowMapSize = shadow2.mapSize;\\n state.spotShadow[spotLength] = shadowUniforms;\\n state.spotShadowMap[spotLength] = shadowMap;\\n state.spotShadowMatrix[spotLength] = light.shadow.matrix;\\n numSpotShadows++;\\n }\\n state.spot[spotLength] = uniforms;\\n spotLength++;\\n } else if (light.isRectAreaLight) {\\n const uniforms = cache.get(light);\\n uniforms.color.copy(color).multiplyScalar(intensity);\\n uniforms.halfWidth.set(light.width * 0.5, 0, 0);\\n uniforms.halfHeight.set(0, light.height * 0.5, 0);\\n state.rectArea[rectAreaLength] = uniforms;\\n rectAreaLength++;\\n } else if (light.isPointLight) {\\n const uniforms = cache.get(light);\\n uniforms.color.copy(light.color).multiplyScalar(light.intensity * scaleFactor);\\n uniforms.distance = light.distance;\\n uniforms.decay = light.decay;\\n if (light.castShadow) {\\n const shadow2 = light.shadow;\\n const shadowUniforms = shadowCache.get(light);\\n shadowUniforms.shadowBias = shadow2.bias;\\n shadowUniforms.shadowNormalBias = shadow2.normalBias;\\n shadowUniforms.shadowRadius = shadow2.radius;\\n shadowUniforms.shadowMapSize = shadow2.mapSize;\\n shadowUniforms.shadowCameraNear = shadow2.camera.near;\\n shadowUniforms.shadowCameraFar = shadow2.camera.far;\\n state.pointShadow[pointLength] = shadowUniforms;\\n state.pointShadowMap[pointLength] = shadowMap;\\n state.pointShadowMatrix[pointLength] = light.shadow.matrix;\\n numPointShadows++;\\n }\\n state.point[pointLength] = uniforms;\\n pointLength++;\\n } else if (light.isHemisphereLight) {\\n const uniforms = cache.get(light);\\n uniforms.skyColor.copy(light.color).multiplyScalar(intensity * scaleFactor);\\n uniforms.groundColor.copy(light.groundColor).multiplyScalar(intensity * scaleFactor);\\n state.hemi[hemiLength] = uniforms;\\n hemiLength++;\\n }\\n }\\n if (rectAreaLength > 0) {\\n if (capabilities.isWebGL2) {\\n state.rectAreaLTC1 = UniformsLib.LTC_FLOAT_1;\\n state.rectAreaLTC2 = UniformsLib.LTC_FLOAT_2;\\n } else {\\n if (extensions.has(\\\\\\\"OES_texture_float_linear\\\\\\\") === true) {\\n state.rectAreaLTC1 = UniformsLib.LTC_FLOAT_1;\\n state.rectAreaLTC2 = UniformsLib.LTC_FLOAT_2;\\n } else if (extensions.has(\\\\\\\"OES_texture_half_float_linear\\\\\\\") === true) {\\n state.rectAreaLTC1 = UniformsLib.LTC_HALF_1;\\n state.rectAreaLTC2 = UniformsLib.LTC_HALF_2;\\n } else {\\n console.error(\\\\\\\"THREE.WebGLRenderer: Unable to use RectAreaLight. Missing WebGL extensions.\\\\\\\");\\n }\\n }\\n }\\n state.ambient[0] = r;\\n state.ambient[1] = g;\\n state.ambient[2] = b;\\n const hash = state.hash;\\n if (hash.directionalLength !== directionalLength || hash.pointLength !== pointLength || hash.spotLength !== spotLength || hash.rectAreaLength !== rectAreaLength || hash.hemiLength !== hemiLength || hash.numDirectionalShadows !== numDirectionalShadows || hash.numPointShadows !== numPointShadows || hash.numSpotShadows !== numSpotShadows) {\\n state.directional.length = directionalLength;\\n state.spot.length = spotLength;\\n state.rectArea.length = rectAreaLength;\\n state.point.length = pointLength;\\n state.hemi.length = hemiLength;\\n state.directionalShadow.length = numDirectionalShadows;\\n state.directionalShadowMap.length = numDirectionalShadows;\\n state.pointShadow.length = numPointShadows;\\n state.pointShadowMap.length = numPointShadows;\\n state.spotShadow.length = numSpotShadows;\\n state.spotShadowMap.length = numSpotShadows;\\n state.directionalShadowMatrix.length = numDirectionalShadows;\\n state.pointShadowMatrix.length = numPointShadows;\\n state.spotShadowMatrix.length = numSpotShadows;\\n hash.directionalLength = directionalLength;\\n hash.pointLength = pointLength;\\n hash.spotLength = spotLength;\\n hash.rectAreaLength = rectAreaLength;\\n hash.hemiLength = hemiLength;\\n hash.numDirectionalShadows = numDirectionalShadows;\\n hash.numPointShadows = numPointShadows;\\n hash.numSpotShadows = numSpotShadows;\\n state.version = nextVersion++;\\n }\\n }\\n function setupView(lights, camera) {\\n let directionalLength = 0;\\n let pointLength = 0;\\n let spotLength = 0;\\n let rectAreaLength = 0;\\n let hemiLength = 0;\\n const viewMatrix = camera.matrixWorldInverse;\\n for (let i = 0, l = lights.length; i < l; i++) {\\n const light = lights[i];\\n if (light.isDirectionalLight) {\\n const uniforms = state.directional[directionalLength];\\n uniforms.direction.setFromMatrixPosition(light.matrixWorld);\\n vector3.setFromMatrixPosition(light.target.matrixWorld);\\n uniforms.direction.sub(vector3);\\n uniforms.direction.transformDirection(viewMatrix);\\n directionalLength++;\\n } else if (light.isSpotLight) {\\n const uniforms = state.spot[spotLength];\\n uniforms.position.setFromMatrixPosition(light.matrixWorld);\\n uniforms.position.applyMatrix4(viewMatrix);\\n uniforms.direction.setFromMatrixPosition(light.matrixWorld);\\n vector3.setFromMatrixPosition(light.target.matrixWorld);\\n uniforms.direction.sub(vector3);\\n uniforms.direction.transformDirection(viewMatrix);\\n spotLength++;\\n } else if (light.isRectAreaLight) {\\n const uniforms = state.rectArea[rectAreaLength];\\n uniforms.position.setFromMatrixPosition(light.matrixWorld);\\n uniforms.position.applyMatrix4(viewMatrix);\\n matrix42.identity();\\n matrix4.copy(light.matrixWorld);\\n matrix4.premultiply(viewMatrix);\\n matrix42.extractRotation(matrix4);\\n uniforms.halfWidth.set(light.width * 0.5, 0, 0);\\n uniforms.halfHeight.set(0, light.height * 0.5, 0);\\n uniforms.halfWidth.applyMatrix4(matrix42);\\n uniforms.halfHeight.applyMatrix4(matrix42);\\n rectAreaLength++;\\n } else if (light.isPointLight) {\\n const uniforms = state.point[pointLength];\\n uniforms.position.setFromMatrixPosition(light.matrixWorld);\\n uniforms.position.applyMatrix4(viewMatrix);\\n pointLength++;\\n } else if (light.isHemisphereLight) {\\n const uniforms = state.hemi[hemiLength];\\n uniforms.direction.setFromMatrixPosition(light.matrixWorld);\\n uniforms.direction.transformDirection(viewMatrix);\\n uniforms.direction.normalize();\\n hemiLength++;\\n }\\n }\\n }\\n return {\\n setup,\\n setupView,\\n state\\n };\\n}\\n\\n// ../../../node_modules/three/src/renderers/webgl/WebGLRenderStates.js\\nfunction WebGLRenderState(extensions, capabilities) {\\n const lights = new WebGLLights(extensions, capabilities);\\n const lightsArray = [];\\n const shadowsArray = [];\\n function init() {\\n lightsArray.length = 0;\\n shadowsArray.length = 0;\\n }\\n function pushLight(light) {\\n lightsArray.push(light);\\n }\\n function pushShadow(shadowLight) {\\n shadowsArray.push(shadowLight);\\n }\\n function setupLights(physicallyCorrectLights) {\\n lights.setup(lightsArray, physicallyCorrectLights);\\n }\\n function setupLightsView(camera) {\\n lights.setupView(lightsArray, camera);\\n }\\n const state = {\\n lightsArray,\\n shadowsArray,\\n lights\\n };\\n return {\\n init,\\n state,\\n setupLights,\\n setupLightsView,\\n pushLight,\\n pushShadow\\n };\\n}\\nfunction WebGLRenderStates(extensions, capabilities) {\\n let renderStates = new WeakMap();\\n function get(scene, renderCallDepth = 0) {\\n let renderState;\\n if (renderStates.has(scene) === false) {\\n renderState = new WebGLRenderState(extensions, capabilities);\\n renderStates.set(scene, [renderState]);\\n } else {\\n if (renderCallDepth >= renderStates.get(scene).length) {\\n renderState = new WebGLRenderState(extensions, capabilities);\\n renderStates.get(scene).push(renderState);\\n } else {\\n renderState = renderStates.get(scene)[renderCallDepth];\\n }\\n }\\n return renderState;\\n }\\n function dispose() {\\n renderStates = new WeakMap();\\n }\\n return {\\n get,\\n dispose\\n };\\n}\\n\\n// ../../../node_modules/three/src/materials/MeshDepthMaterial.js\\nvar MeshDepthMaterial = class extends Material {\\n constructor(parameters) {\\n super();\\n this.type = \\\\\\\"MeshDepthMaterial\\\\\\\";\\n this.depthPacking = BasicDepthPacking;\\n this.map = null;\\n this.alphaMap = null;\\n this.displacementMap = null;\\n this.displacementScale = 1;\\n this.displacementBias = 0;\\n this.wireframe = false;\\n this.wireframeLinewidth = 1;\\n this.fog = false;\\n this.setValues(parameters);\\n }\\n copy(source) {\\n super.copy(source);\\n this.depthPacking = source.depthPacking;\\n this.map = source.map;\\n this.alphaMap = source.alphaMap;\\n this.displacementMap = source.displacementMap;\\n this.displacementScale = source.displacementScale;\\n this.displacementBias = source.displacementBias;\\n this.wireframe = source.wireframe;\\n this.wireframeLinewidth = source.wireframeLinewidth;\\n return this;\\n }\\n};\\nMeshDepthMaterial.prototype.isMeshDepthMaterial = true;\\n\\n// ../../../node_modules/three/src/materials/MeshDistanceMaterial.js\\nvar MeshDistanceMaterial = class extends Material {\\n constructor(parameters) {\\n super();\\n this.type = \\\\\\\"MeshDistanceMaterial\\\\\\\";\\n this.referencePosition = new Vector3();\\n this.nearDistance = 1;\\n this.farDistance = 1e3;\\n this.map = null;\\n this.alphaMap = null;\\n this.displacementMap = null;\\n this.displacementScale = 1;\\n this.displacementBias = 0;\\n this.fog = false;\\n this.setValues(parameters);\\n }\\n copy(source) {\\n super.copy(source);\\n this.referencePosition.copy(source.referencePosition);\\n this.nearDistance = source.nearDistance;\\n this.farDistance = source.farDistance;\\n this.map = source.map;\\n this.alphaMap = source.alphaMap;\\n this.displacementMap = source.displacementMap;\\n this.displacementScale = source.displacementScale;\\n this.displacementBias = source.displacementBias;\\n return this;\\n }\\n};\\nMeshDistanceMaterial.prototype.isMeshDistanceMaterial = true;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderLib/vsm.glsl.js\\nvar vertex17 = `\\nvoid main() {\\n\\n\\tgl_Position = vec4( position, 1.0 );\\n\\n}\\n`;\\nvar fragment17 = `\\nuniform sampler2D shadow_pass;\\nuniform vec2 resolution;\\nuniform float radius;\\nuniform float samples;\\n\\n#include \\n\\nvoid main() {\\n\\n\\tfloat mean = 0.0;\\n\\tfloat squared_mean = 0.0;\\n\\n\\t// This seems totally useless but it's a crazy work around for a Adreno compiler bug\\n\\t// float depth = unpackRGBAToDepth( texture2D( shadow_pass, ( gl_FragCoord.xy ) / resolution ) );\\n\\n\\tfloat uvStride = samples <= 1.0 ? 0.0 : 2.0 / ( samples - 1.0 );\\n\\tfloat uvStart = samples <= 1.0 ? 0.0 : - 1.0;\\n\\tfor ( float i = 0.0; i < samples; i ++ ) {\\n\\n\\t\\tfloat uvOffset = uvStart + i * uvStride;\\n\\n\\t\\t#ifdef HORIZONTAL_PASS\\n\\n\\t\\t\\tvec2 distribution = unpackRGBATo2Half( texture2D( shadow_pass, ( gl_FragCoord.xy + vec2( uvOffset, 0.0 ) * radius ) / resolution ) );\\n\\t\\t\\tmean += distribution.x;\\n\\t\\t\\tsquared_mean += distribution.y * distribution.y + distribution.x * distribution.x;\\n\\n\\t\\t#else\\n\\n\\t\\t\\tfloat depth = unpackRGBAToDepth( texture2D( shadow_pass, ( gl_FragCoord.xy + vec2( 0.0, uvOffset ) * radius ) / resolution ) );\\n\\t\\t\\tmean += depth;\\n\\t\\t\\tsquared_mean += depth * depth;\\n\\n\\t\\t#endif\\n\\n\\t}\\n\\n\\tmean = mean / samples;\\n\\tsquared_mean = squared_mean / samples;\\n\\n\\tfloat std_dev = sqrt( squared_mean - mean * mean );\\n\\n\\tgl_FragColor = pack2HalfToRGBA( vec2( mean, std_dev ) );\\n\\n}\\n`;\\n\\n// ../../../node_modules/three/src/renderers/webgl/WebGLShadowMap.js\\nfunction WebGLShadowMap(_renderer, _objects, _capabilities) {\\n let _frustum = new Frustum();\\n const _shadowMapSize = new Vector2(), _viewportSize = new Vector2(), _viewport = new Vector4(), _depthMaterial = new MeshDepthMaterial({depthPacking: RGBADepthPacking}), _distanceMaterial = new MeshDistanceMaterial(), _materialCache = {}, _maxTextureSize = _capabilities.maxTextureSize;\\n const shadowSide = {0: BackSide, 1: FrontSide, 2: DoubleSide};\\n const shadowMaterialVertical = new ShaderMaterial({\\n uniforms: {\\n shadow_pass: {value: null},\\n resolution: {value: new Vector2()},\\n radius: {value: 4},\\n samples: {value: 8}\\n },\\n vertexShader: vertex17,\\n fragmentShader: fragment17\\n });\\n const shadowMaterialHorizontal = shadowMaterialVertical.clone();\\n shadowMaterialHorizontal.defines.HORIZONTAL_PASS = 1;\\n const fullScreenTri = new BufferGeometry();\\n fullScreenTri.setAttribute(\\\\\\\"position\\\\\\\", new BufferAttribute(new Float32Array([-1, -1, 0.5, 3, -1, 0.5, -1, 3, 0.5]), 3));\\n const fullScreenMesh = new Mesh(fullScreenTri, shadowMaterialVertical);\\n const scope = this;\\n this.enabled = false;\\n this.autoUpdate = true;\\n this.needsUpdate = false;\\n this.type = PCFShadowMap;\\n this.render = function(lights, scene, camera) {\\n if (scope.enabled === false)\\n return;\\n if (scope.autoUpdate === false && scope.needsUpdate === false)\\n return;\\n if (lights.length === 0)\\n return;\\n const currentRenderTarget = _renderer.getRenderTarget();\\n const activeCubeFace = _renderer.getActiveCubeFace();\\n const activeMipmapLevel = _renderer.getActiveMipmapLevel();\\n const _state = _renderer.state;\\n _state.setBlending(NoBlending);\\n _state.buffers.color.setClear(1, 1, 1, 1);\\n _state.buffers.depth.setTest(true);\\n _state.setScissorTest(false);\\n for (let i = 0, il = lights.length; i < il; i++) {\\n const light = lights[i];\\n const shadow2 = light.shadow;\\n if (shadow2 === void 0) {\\n console.warn(\\\\\\\"THREE.WebGLShadowMap:\\\\\\\", light, \\\\\\\"has no shadow.\\\\\\\");\\n continue;\\n }\\n if (shadow2.autoUpdate === false && shadow2.needsUpdate === false)\\n continue;\\n _shadowMapSize.copy(shadow2.mapSize);\\n const shadowFrameExtents = shadow2.getFrameExtents();\\n _shadowMapSize.multiply(shadowFrameExtents);\\n _viewportSize.copy(shadow2.mapSize);\\n if (_shadowMapSize.x > _maxTextureSize || _shadowMapSize.y > _maxTextureSize) {\\n if (_shadowMapSize.x > _maxTextureSize) {\\n _viewportSize.x = Math.floor(_maxTextureSize / shadowFrameExtents.x);\\n _shadowMapSize.x = _viewportSize.x * shadowFrameExtents.x;\\n shadow2.mapSize.x = _viewportSize.x;\\n }\\n if (_shadowMapSize.y > _maxTextureSize) {\\n _viewportSize.y = Math.floor(_maxTextureSize / shadowFrameExtents.y);\\n _shadowMapSize.y = _viewportSize.y * shadowFrameExtents.y;\\n shadow2.mapSize.y = _viewportSize.y;\\n }\\n }\\n if (shadow2.map === null && !shadow2.isPointLightShadow && this.type === VSMShadowMap) {\\n const pars = {minFilter: LinearFilter, magFilter: LinearFilter, format: RGBAFormat};\\n shadow2.map = new WebGLRenderTarget(_shadowMapSize.x, _shadowMapSize.y, pars);\\n shadow2.map.texture.name = light.name + \\\\\\\".shadowMap\\\\\\\";\\n shadow2.mapPass = new WebGLRenderTarget(_shadowMapSize.x, _shadowMapSize.y, pars);\\n shadow2.camera.updateProjectionMatrix();\\n }\\n if (shadow2.map === null) {\\n const pars = {minFilter: NearestFilter, magFilter: NearestFilter, format: RGBAFormat};\\n shadow2.map = new WebGLRenderTarget(_shadowMapSize.x, _shadowMapSize.y, pars);\\n shadow2.map.texture.name = light.name + \\\\\\\".shadowMap\\\\\\\";\\n shadow2.camera.updateProjectionMatrix();\\n }\\n _renderer.setRenderTarget(shadow2.map);\\n _renderer.clear();\\n const viewportCount = shadow2.getViewportCount();\\n for (let vp = 0; vp < viewportCount; vp++) {\\n const viewport = shadow2.getViewport(vp);\\n _viewport.set(_viewportSize.x * viewport.x, _viewportSize.y * viewport.y, _viewportSize.x * viewport.z, _viewportSize.y * viewport.w);\\n _state.viewport(_viewport);\\n shadow2.updateMatrices(light, vp);\\n _frustum = shadow2.getFrustum();\\n renderObject(scene, camera, shadow2.camera, light, this.type);\\n }\\n if (!shadow2.isPointLightShadow && this.type === VSMShadowMap) {\\n VSMPass(shadow2, camera);\\n }\\n shadow2.needsUpdate = false;\\n }\\n scope.needsUpdate = false;\\n _renderer.setRenderTarget(currentRenderTarget, activeCubeFace, activeMipmapLevel);\\n };\\n function VSMPass(shadow2, camera) {\\n const geometry = _objects.update(fullScreenMesh);\\n shadowMaterialVertical.uniforms.shadow_pass.value = shadow2.map.texture;\\n shadowMaterialVertical.uniforms.resolution.value = shadow2.mapSize;\\n shadowMaterialVertical.uniforms.radius.value = shadow2.radius;\\n shadowMaterialVertical.uniforms.samples.value = shadow2.blurSamples;\\n _renderer.setRenderTarget(shadow2.mapPass);\\n _renderer.clear();\\n _renderer.renderBufferDirect(camera, null, geometry, shadowMaterialVertical, fullScreenMesh, null);\\n shadowMaterialHorizontal.uniforms.shadow_pass.value = shadow2.mapPass.texture;\\n shadowMaterialHorizontal.uniforms.resolution.value = shadow2.mapSize;\\n shadowMaterialHorizontal.uniforms.radius.value = shadow2.radius;\\n shadowMaterialHorizontal.uniforms.samples.value = shadow2.blurSamples;\\n _renderer.setRenderTarget(shadow2.map);\\n _renderer.clear();\\n _renderer.renderBufferDirect(camera, null, geometry, shadowMaterialHorizontal, fullScreenMesh, null);\\n }\\n function getDepthMaterial(object, geometry, material, light, shadowCameraNear, shadowCameraFar, type) {\\n let result = null;\\n const customMaterial = light.isPointLight === true ? object.customDistanceMaterial : object.customDepthMaterial;\\n if (customMaterial !== void 0) {\\n result = customMaterial;\\n } else {\\n result = light.isPointLight === true ? _distanceMaterial : _depthMaterial;\\n }\\n if (_renderer.localClippingEnabled && material.clipShadows === true && material.clippingPlanes.length !== 0 || material.displacementMap && material.displacementScale !== 0 || material.alphaMap && material.alphaTest > 0) {\\n const keyA = result.uuid, keyB = material.uuid;\\n let materialsForVariant = _materialCache[keyA];\\n if (materialsForVariant === void 0) {\\n materialsForVariant = {};\\n _materialCache[keyA] = materialsForVariant;\\n }\\n let cachedMaterial = materialsForVariant[keyB];\\n if (cachedMaterial === void 0) {\\n cachedMaterial = result.clone();\\n materialsForVariant[keyB] = cachedMaterial;\\n }\\n result = cachedMaterial;\\n }\\n result.visible = material.visible;\\n result.wireframe = material.wireframe;\\n if (type === VSMShadowMap) {\\n result.side = material.shadowSide !== null ? material.shadowSide : material.side;\\n } else {\\n result.side = material.shadowSide !== null ? material.shadowSide : shadowSide[material.side];\\n }\\n result.alphaMap = material.alphaMap;\\n result.alphaTest = material.alphaTest;\\n result.clipShadows = material.clipShadows;\\n result.clippingPlanes = material.clippingPlanes;\\n result.clipIntersection = material.clipIntersection;\\n result.displacementMap = material.displacementMap;\\n result.displacementScale = material.displacementScale;\\n result.displacementBias = material.displacementBias;\\n result.wireframeLinewidth = material.wireframeLinewidth;\\n result.linewidth = material.linewidth;\\n if (light.isPointLight === true && result.isMeshDistanceMaterial === true) {\\n result.referencePosition.setFromMatrixPosition(light.matrixWorld);\\n result.nearDistance = shadowCameraNear;\\n result.farDistance = shadowCameraFar;\\n }\\n return result;\\n }\\n function renderObject(object, camera, shadowCamera, light, type) {\\n if (object.visible === false)\\n return;\\n const visible = object.layers.test(camera.layers);\\n if (visible && (object.isMesh || object.isLine || object.isPoints)) {\\n if ((object.castShadow || object.receiveShadow && type === VSMShadowMap) && (!object.frustumCulled || _frustum.intersectsObject(object))) {\\n object.modelViewMatrix.multiplyMatrices(shadowCamera.matrixWorldInverse, object.matrixWorld);\\n const geometry = _objects.update(object);\\n const material = object.material;\\n if (Array.isArray(material)) {\\n const groups = geometry.groups;\\n for (let k = 0, kl = groups.length; k < kl; k++) {\\n const group = groups[k];\\n const groupMaterial = material[group.materialIndex];\\n if (groupMaterial && groupMaterial.visible) {\\n const depthMaterial = getDepthMaterial(object, geometry, groupMaterial, light, shadowCamera.near, shadowCamera.far, type);\\n _renderer.renderBufferDirect(shadowCamera, null, geometry, depthMaterial, object, group);\\n }\\n }\\n } else if (material.visible) {\\n const depthMaterial = getDepthMaterial(object, geometry, material, light, shadowCamera.near, shadowCamera.far, type);\\n _renderer.renderBufferDirect(shadowCamera, null, geometry, depthMaterial, object, null);\\n }\\n }\\n }\\n const children = object.children;\\n for (let i = 0, l = children.length; i < l; i++) {\\n renderObject(children[i], camera, shadowCamera, light, type);\\n }\\n }\\n}\\n\\n// ../../../node_modules/three/src/renderers/webgl/WebGLState.js\\nfunction WebGLState(gl, extensions, capabilities) {\\n const isWebGL2 = capabilities.isWebGL2;\\n function ColorBuffer() {\\n let locked = false;\\n const color = new Vector4();\\n let currentColorMask = null;\\n const currentColorClear = new Vector4(0, 0, 0, 0);\\n return {\\n setMask: function(colorMask) {\\n if (currentColorMask !== colorMask && !locked) {\\n gl.colorMask(colorMask, colorMask, colorMask, colorMask);\\n currentColorMask = colorMask;\\n }\\n },\\n setLocked: function(lock) {\\n locked = lock;\\n },\\n setClear: function(r, g, b, a, premultipliedAlpha) {\\n if (premultipliedAlpha === true) {\\n r *= a;\\n g *= a;\\n b *= a;\\n }\\n color.set(r, g, b, a);\\n if (currentColorClear.equals(color) === false) {\\n gl.clearColor(r, g, b, a);\\n currentColorClear.copy(color);\\n }\\n },\\n reset: function() {\\n locked = false;\\n currentColorMask = null;\\n currentColorClear.set(-1, 0, 0, 0);\\n }\\n };\\n }\\n function DepthBuffer() {\\n let locked = false;\\n let currentDepthMask = null;\\n let currentDepthFunc = null;\\n let currentDepthClear = null;\\n return {\\n setTest: function(depthTest) {\\n if (depthTest) {\\n enable(gl.DEPTH_TEST);\\n } else {\\n disable(gl.DEPTH_TEST);\\n }\\n },\\n setMask: function(depthMask) {\\n if (currentDepthMask !== depthMask && !locked) {\\n gl.depthMask(depthMask);\\n currentDepthMask = depthMask;\\n }\\n },\\n setFunc: function(depthFunc) {\\n if (currentDepthFunc !== depthFunc) {\\n if (depthFunc) {\\n switch (depthFunc) {\\n case NeverDepth:\\n gl.depthFunc(gl.NEVER);\\n break;\\n case AlwaysDepth:\\n gl.depthFunc(gl.ALWAYS);\\n break;\\n case LessDepth:\\n gl.depthFunc(gl.LESS);\\n break;\\n case LessEqualDepth:\\n gl.depthFunc(gl.LEQUAL);\\n break;\\n case EqualDepth:\\n gl.depthFunc(gl.EQUAL);\\n break;\\n case GreaterEqualDepth:\\n gl.depthFunc(gl.GEQUAL);\\n break;\\n case GreaterDepth:\\n gl.depthFunc(gl.GREATER);\\n break;\\n case NotEqualDepth:\\n gl.depthFunc(gl.NOTEQUAL);\\n break;\\n default:\\n gl.depthFunc(gl.LEQUAL);\\n }\\n } else {\\n gl.depthFunc(gl.LEQUAL);\\n }\\n currentDepthFunc = depthFunc;\\n }\\n },\\n setLocked: function(lock) {\\n locked = lock;\\n },\\n setClear: function(depth2) {\\n if (currentDepthClear !== depth2) {\\n gl.clearDepth(depth2);\\n currentDepthClear = depth2;\\n }\\n },\\n reset: function() {\\n locked = false;\\n currentDepthMask = null;\\n currentDepthFunc = null;\\n currentDepthClear = null;\\n }\\n };\\n }\\n function StencilBuffer() {\\n let locked = false;\\n let currentStencilMask = null;\\n let currentStencilFunc = null;\\n let currentStencilRef = null;\\n let currentStencilFuncMask = null;\\n let currentStencilFail = null;\\n let currentStencilZFail = null;\\n let currentStencilZPass = null;\\n let currentStencilClear = null;\\n return {\\n setTest: function(stencilTest) {\\n if (!locked) {\\n if (stencilTest) {\\n enable(gl.STENCIL_TEST);\\n } else {\\n disable(gl.STENCIL_TEST);\\n }\\n }\\n },\\n setMask: function(stencilMask) {\\n if (currentStencilMask !== stencilMask && !locked) {\\n gl.stencilMask(stencilMask);\\n currentStencilMask = stencilMask;\\n }\\n },\\n setFunc: function(stencilFunc, stencilRef, stencilMask) {\\n if (currentStencilFunc !== stencilFunc || currentStencilRef !== stencilRef || currentStencilFuncMask !== stencilMask) {\\n gl.stencilFunc(stencilFunc, stencilRef, stencilMask);\\n currentStencilFunc = stencilFunc;\\n currentStencilRef = stencilRef;\\n currentStencilFuncMask = stencilMask;\\n }\\n },\\n setOp: function(stencilFail, stencilZFail, stencilZPass) {\\n if (currentStencilFail !== stencilFail || currentStencilZFail !== stencilZFail || currentStencilZPass !== stencilZPass) {\\n gl.stencilOp(stencilFail, stencilZFail, stencilZPass);\\n currentStencilFail = stencilFail;\\n currentStencilZFail = stencilZFail;\\n currentStencilZPass = stencilZPass;\\n }\\n },\\n setLocked: function(lock) {\\n locked = lock;\\n },\\n setClear: function(stencil) {\\n if (currentStencilClear !== stencil) {\\n gl.clearStencil(stencil);\\n currentStencilClear = stencil;\\n }\\n },\\n reset: function() {\\n locked = false;\\n currentStencilMask = null;\\n currentStencilFunc = null;\\n currentStencilRef = null;\\n currentStencilFuncMask = null;\\n currentStencilFail = null;\\n currentStencilZFail = null;\\n currentStencilZPass = null;\\n currentStencilClear = null;\\n }\\n };\\n }\\n const colorBuffer = new ColorBuffer();\\n const depthBuffer = new DepthBuffer();\\n const stencilBuffer = new StencilBuffer();\\n let enabledCapabilities = {};\\n let xrFramebuffer = null;\\n let currentBoundFramebuffers = {};\\n let currentProgram = null;\\n let currentBlendingEnabled = false;\\n let currentBlending = null;\\n let currentBlendEquation = null;\\n let currentBlendSrc = null;\\n let currentBlendDst = null;\\n let currentBlendEquationAlpha = null;\\n let currentBlendSrcAlpha = null;\\n let currentBlendDstAlpha = null;\\n let currentPremultipledAlpha = false;\\n let currentFlipSided = null;\\n let currentCullFace = null;\\n let currentLineWidth = null;\\n let currentPolygonOffsetFactor = null;\\n let currentPolygonOffsetUnits = null;\\n const maxTextures = gl.getParameter(gl.MAX_COMBINED_TEXTURE_IMAGE_UNITS);\\n let lineWidthAvailable = false;\\n let version = 0;\\n const glVersion = gl.getParameter(gl.VERSION);\\n if (glVersion.indexOf(\\\\\\\"WebGL\\\\\\\") !== -1) {\\n version = parseFloat(/^WebGL (\\\\d)/.exec(glVersion)[1]);\\n lineWidthAvailable = version >= 1;\\n } else if (glVersion.indexOf(\\\\\\\"OpenGL ES\\\\\\\") !== -1) {\\n version = parseFloat(/^OpenGL ES (\\\\d)/.exec(glVersion)[1]);\\n lineWidthAvailable = version >= 2;\\n }\\n let currentTextureSlot = null;\\n let currentBoundTextures = {};\\n const scissorParam = gl.getParameter(gl.SCISSOR_BOX);\\n const viewportParam = gl.getParameter(gl.VIEWPORT);\\n const currentScissor = new Vector4().fromArray(scissorParam);\\n const currentViewport = new Vector4().fromArray(viewportParam);\\n function createTexture(type, target, count) {\\n const data = new Uint8Array(4);\\n const texture = gl.createTexture();\\n gl.bindTexture(type, texture);\\n gl.texParameteri(type, gl.TEXTURE_MIN_FILTER, gl.NEAREST);\\n gl.texParameteri(type, gl.TEXTURE_MAG_FILTER, gl.NEAREST);\\n for (let i = 0; i < count; i++) {\\n gl.texImage2D(target + i, 0, gl.RGBA, 1, 1, 0, gl.RGBA, gl.UNSIGNED_BYTE, data);\\n }\\n return texture;\\n }\\n const emptyTextures = {};\\n emptyTextures[gl.TEXTURE_2D] = createTexture(gl.TEXTURE_2D, gl.TEXTURE_2D, 1);\\n emptyTextures[gl.TEXTURE_CUBE_MAP] = createTexture(gl.TEXTURE_CUBE_MAP, gl.TEXTURE_CUBE_MAP_POSITIVE_X, 6);\\n colorBuffer.setClear(0, 0, 0, 1);\\n depthBuffer.setClear(1);\\n stencilBuffer.setClear(0);\\n enable(gl.DEPTH_TEST);\\n depthBuffer.setFunc(LessEqualDepth);\\n setFlipSided(false);\\n setCullFace(CullFaceBack);\\n enable(gl.CULL_FACE);\\n setBlending(NoBlending);\\n function enable(id) {\\n if (enabledCapabilities[id] !== true) {\\n gl.enable(id);\\n enabledCapabilities[id] = true;\\n }\\n }\\n function disable(id) {\\n if (enabledCapabilities[id] !== false) {\\n gl.disable(id);\\n enabledCapabilities[id] = false;\\n }\\n }\\n function bindXRFramebuffer(framebuffer) {\\n if (framebuffer !== xrFramebuffer) {\\n gl.bindFramebuffer(gl.FRAMEBUFFER, framebuffer);\\n xrFramebuffer = framebuffer;\\n }\\n }\\n function bindFramebuffer(target, framebuffer) {\\n if (framebuffer === null && xrFramebuffer !== null)\\n framebuffer = xrFramebuffer;\\n if (currentBoundFramebuffers[target] !== framebuffer) {\\n gl.bindFramebuffer(target, framebuffer);\\n currentBoundFramebuffers[target] = framebuffer;\\n if (isWebGL2) {\\n if (target === gl.DRAW_FRAMEBUFFER) {\\n currentBoundFramebuffers[gl.FRAMEBUFFER] = framebuffer;\\n }\\n if (target === gl.FRAMEBUFFER) {\\n currentBoundFramebuffers[gl.DRAW_FRAMEBUFFER] = framebuffer;\\n }\\n }\\n return true;\\n }\\n return false;\\n }\\n function useProgram(program) {\\n if (currentProgram !== program) {\\n gl.useProgram(program);\\n currentProgram = program;\\n return true;\\n }\\n return false;\\n }\\n const equationToGL = {\\n [AddEquation]: gl.FUNC_ADD,\\n [SubtractEquation]: gl.FUNC_SUBTRACT,\\n [ReverseSubtractEquation]: gl.FUNC_REVERSE_SUBTRACT\\n };\\n if (isWebGL2) {\\n equationToGL[MinEquation] = gl.MIN;\\n equationToGL[MaxEquation] = gl.MAX;\\n } else {\\n const extension = extensions.get(\\\\\\\"EXT_blend_minmax\\\\\\\");\\n if (extension !== null) {\\n equationToGL[MinEquation] = extension.MIN_EXT;\\n equationToGL[MaxEquation] = extension.MAX_EXT;\\n }\\n }\\n const factorToGL = {\\n [ZeroFactor]: gl.ZERO,\\n [OneFactor]: gl.ONE,\\n [SrcColorFactor]: gl.SRC_COLOR,\\n [SrcAlphaFactor]: gl.SRC_ALPHA,\\n [SrcAlphaSaturateFactor]: gl.SRC_ALPHA_SATURATE,\\n [DstColorFactor]: gl.DST_COLOR,\\n [DstAlphaFactor]: gl.DST_ALPHA,\\n [OneMinusSrcColorFactor]: gl.ONE_MINUS_SRC_COLOR,\\n [OneMinusSrcAlphaFactor]: gl.ONE_MINUS_SRC_ALPHA,\\n [OneMinusDstColorFactor]: gl.ONE_MINUS_DST_COLOR,\\n [OneMinusDstAlphaFactor]: gl.ONE_MINUS_DST_ALPHA\\n };\\n function setBlending(blending, blendEquation, blendSrc, blendDst, blendEquationAlpha, blendSrcAlpha, blendDstAlpha, premultipliedAlpha) {\\n if (blending === NoBlending) {\\n if (currentBlendingEnabled === true) {\\n disable(gl.BLEND);\\n currentBlendingEnabled = false;\\n }\\n return;\\n }\\n if (currentBlendingEnabled === false) {\\n enable(gl.BLEND);\\n currentBlendingEnabled = true;\\n }\\n if (blending !== CustomBlending) {\\n if (blending !== currentBlending || premultipliedAlpha !== currentPremultipledAlpha) {\\n if (currentBlendEquation !== AddEquation || currentBlendEquationAlpha !== AddEquation) {\\n gl.blendEquation(gl.FUNC_ADD);\\n currentBlendEquation = AddEquation;\\n currentBlendEquationAlpha = AddEquation;\\n }\\n if (premultipliedAlpha) {\\n switch (blending) {\\n case NormalBlending:\\n gl.blendFuncSeparate(gl.ONE, gl.ONE_MINUS_SRC_ALPHA, gl.ONE, gl.ONE_MINUS_SRC_ALPHA);\\n break;\\n case AdditiveBlending:\\n gl.blendFunc(gl.ONE, gl.ONE);\\n break;\\n case SubtractiveBlending:\\n gl.blendFuncSeparate(gl.ZERO, gl.ZERO, gl.ONE_MINUS_SRC_COLOR, gl.ONE_MINUS_SRC_ALPHA);\\n break;\\n case MultiplyBlending:\\n gl.blendFuncSeparate(gl.ZERO, gl.SRC_COLOR, gl.ZERO, gl.SRC_ALPHA);\\n break;\\n default:\\n console.error(\\\\\\\"THREE.WebGLState: Invalid blending: \\\\\\\", blending);\\n break;\\n }\\n } else {\\n switch (blending) {\\n case NormalBlending:\\n gl.blendFuncSeparate(gl.SRC_ALPHA, gl.ONE_MINUS_SRC_ALPHA, gl.ONE, gl.ONE_MINUS_SRC_ALPHA);\\n break;\\n case AdditiveBlending:\\n gl.blendFunc(gl.SRC_ALPHA, gl.ONE);\\n break;\\n case SubtractiveBlending:\\n gl.blendFunc(gl.ZERO, gl.ONE_MINUS_SRC_COLOR);\\n break;\\n case MultiplyBlending:\\n gl.blendFunc(gl.ZERO, gl.SRC_COLOR);\\n break;\\n default:\\n console.error(\\\\\\\"THREE.WebGLState: Invalid blending: \\\\\\\", blending);\\n break;\\n }\\n }\\n currentBlendSrc = null;\\n currentBlendDst = null;\\n currentBlendSrcAlpha = null;\\n currentBlendDstAlpha = null;\\n currentBlending = blending;\\n currentPremultipledAlpha = premultipliedAlpha;\\n }\\n return;\\n }\\n blendEquationAlpha = blendEquationAlpha || blendEquation;\\n blendSrcAlpha = blendSrcAlpha || blendSrc;\\n blendDstAlpha = blendDstAlpha || blendDst;\\n if (blendEquation !== currentBlendEquation || blendEquationAlpha !== currentBlendEquationAlpha) {\\n gl.blendEquationSeparate(equationToGL[blendEquation], equationToGL[blendEquationAlpha]);\\n currentBlendEquation = blendEquation;\\n currentBlendEquationAlpha = blendEquationAlpha;\\n }\\n if (blendSrc !== currentBlendSrc || blendDst !== currentBlendDst || blendSrcAlpha !== currentBlendSrcAlpha || blendDstAlpha !== currentBlendDstAlpha) {\\n gl.blendFuncSeparate(factorToGL[blendSrc], factorToGL[blendDst], factorToGL[blendSrcAlpha], factorToGL[blendDstAlpha]);\\n currentBlendSrc = blendSrc;\\n currentBlendDst = blendDst;\\n currentBlendSrcAlpha = blendSrcAlpha;\\n currentBlendDstAlpha = blendDstAlpha;\\n }\\n currentBlending = blending;\\n currentPremultipledAlpha = null;\\n }\\n function setMaterial(material, frontFaceCW) {\\n material.side === DoubleSide ? disable(gl.CULL_FACE) : enable(gl.CULL_FACE);\\n let flipSided = material.side === BackSide;\\n if (frontFaceCW)\\n flipSided = !flipSided;\\n setFlipSided(flipSided);\\n material.blending === NormalBlending && material.transparent === false ? setBlending(NoBlending) : setBlending(material.blending, material.blendEquation, material.blendSrc, material.blendDst, material.blendEquationAlpha, material.blendSrcAlpha, material.blendDstAlpha, material.premultipliedAlpha);\\n depthBuffer.setFunc(material.depthFunc);\\n depthBuffer.setTest(material.depthTest);\\n depthBuffer.setMask(material.depthWrite);\\n colorBuffer.setMask(material.colorWrite);\\n const stencilWrite = material.stencilWrite;\\n stencilBuffer.setTest(stencilWrite);\\n if (stencilWrite) {\\n stencilBuffer.setMask(material.stencilWriteMask);\\n stencilBuffer.setFunc(material.stencilFunc, material.stencilRef, material.stencilFuncMask);\\n stencilBuffer.setOp(material.stencilFail, material.stencilZFail, material.stencilZPass);\\n }\\n setPolygonOffset(material.polygonOffset, material.polygonOffsetFactor, material.polygonOffsetUnits);\\n material.alphaToCoverage === true ? enable(gl.SAMPLE_ALPHA_TO_COVERAGE) : disable(gl.SAMPLE_ALPHA_TO_COVERAGE);\\n }\\n function setFlipSided(flipSided) {\\n if (currentFlipSided !== flipSided) {\\n if (flipSided) {\\n gl.frontFace(gl.CW);\\n } else {\\n gl.frontFace(gl.CCW);\\n }\\n currentFlipSided = flipSided;\\n }\\n }\\n function setCullFace(cullFace) {\\n if (cullFace !== CullFaceNone) {\\n enable(gl.CULL_FACE);\\n if (cullFace !== currentCullFace) {\\n if (cullFace === CullFaceBack) {\\n gl.cullFace(gl.BACK);\\n } else if (cullFace === CullFaceFront) {\\n gl.cullFace(gl.FRONT);\\n } else {\\n gl.cullFace(gl.FRONT_AND_BACK);\\n }\\n }\\n } else {\\n disable(gl.CULL_FACE);\\n }\\n currentCullFace = cullFace;\\n }\\n function setLineWidth(width) {\\n if (width !== currentLineWidth) {\\n if (lineWidthAvailable)\\n gl.lineWidth(width);\\n currentLineWidth = width;\\n }\\n }\\n function setPolygonOffset(polygonOffset, factor, units) {\\n if (polygonOffset) {\\n enable(gl.POLYGON_OFFSET_FILL);\\n if (currentPolygonOffsetFactor !== factor || currentPolygonOffsetUnits !== units) {\\n gl.polygonOffset(factor, units);\\n currentPolygonOffsetFactor = factor;\\n currentPolygonOffsetUnits = units;\\n }\\n } else {\\n disable(gl.POLYGON_OFFSET_FILL);\\n }\\n }\\n function setScissorTest(scissorTest) {\\n if (scissorTest) {\\n enable(gl.SCISSOR_TEST);\\n } else {\\n disable(gl.SCISSOR_TEST);\\n }\\n }\\n function activeTexture(webglSlot) {\\n if (webglSlot === void 0)\\n webglSlot = gl.TEXTURE0 + maxTextures - 1;\\n if (currentTextureSlot !== webglSlot) {\\n gl.activeTexture(webglSlot);\\n currentTextureSlot = webglSlot;\\n }\\n }\\n function bindTexture(webglType, webglTexture) {\\n if (currentTextureSlot === null) {\\n activeTexture();\\n }\\n let boundTexture = currentBoundTextures[currentTextureSlot];\\n if (boundTexture === void 0) {\\n boundTexture = {type: void 0, texture: void 0};\\n currentBoundTextures[currentTextureSlot] = boundTexture;\\n }\\n if (boundTexture.type !== webglType || boundTexture.texture !== webglTexture) {\\n gl.bindTexture(webglType, webglTexture || emptyTextures[webglType]);\\n boundTexture.type = webglType;\\n boundTexture.texture = webglTexture;\\n }\\n }\\n function unbindTexture() {\\n const boundTexture = currentBoundTextures[currentTextureSlot];\\n if (boundTexture !== void 0 && boundTexture.type !== void 0) {\\n gl.bindTexture(boundTexture.type, null);\\n boundTexture.type = void 0;\\n boundTexture.texture = void 0;\\n }\\n }\\n function compressedTexImage2D() {\\n try {\\n gl.compressedTexImage2D.apply(gl, arguments);\\n } catch (error) {\\n console.error(\\\\\\\"THREE.WebGLState:\\\\\\\", error);\\n }\\n }\\n function texImage2D() {\\n try {\\n gl.texImage2D.apply(gl, arguments);\\n } catch (error) {\\n console.error(\\\\\\\"THREE.WebGLState:\\\\\\\", error);\\n }\\n }\\n function texImage3D() {\\n try {\\n gl.texImage3D.apply(gl, arguments);\\n } catch (error) {\\n console.error(\\\\\\\"THREE.WebGLState:\\\\\\\", error);\\n }\\n }\\n function scissor(scissor2) {\\n if (currentScissor.equals(scissor2) === false) {\\n gl.scissor(scissor2.x, scissor2.y, scissor2.z, scissor2.w);\\n currentScissor.copy(scissor2);\\n }\\n }\\n function viewport(viewport2) {\\n if (currentViewport.equals(viewport2) === false) {\\n gl.viewport(viewport2.x, viewport2.y, viewport2.z, viewport2.w);\\n currentViewport.copy(viewport2);\\n }\\n }\\n function reset() {\\n gl.disable(gl.BLEND);\\n gl.disable(gl.CULL_FACE);\\n gl.disable(gl.DEPTH_TEST);\\n gl.disable(gl.POLYGON_OFFSET_FILL);\\n gl.disable(gl.SCISSOR_TEST);\\n gl.disable(gl.STENCIL_TEST);\\n gl.disable(gl.SAMPLE_ALPHA_TO_COVERAGE);\\n gl.blendEquation(gl.FUNC_ADD);\\n gl.blendFunc(gl.ONE, gl.ZERO);\\n gl.blendFuncSeparate(gl.ONE, gl.ZERO, gl.ONE, gl.ZERO);\\n gl.colorMask(true, true, true, true);\\n gl.clearColor(0, 0, 0, 0);\\n gl.depthMask(true);\\n gl.depthFunc(gl.LESS);\\n gl.clearDepth(1);\\n gl.stencilMask(4294967295);\\n gl.stencilFunc(gl.ALWAYS, 0, 4294967295);\\n gl.stencilOp(gl.KEEP, gl.KEEP, gl.KEEP);\\n gl.clearStencil(0);\\n gl.cullFace(gl.BACK);\\n gl.frontFace(gl.CCW);\\n gl.polygonOffset(0, 0);\\n gl.activeTexture(gl.TEXTURE0);\\n gl.bindFramebuffer(gl.FRAMEBUFFER, null);\\n if (isWebGL2 === true) {\\n gl.bindFramebuffer(gl.DRAW_FRAMEBUFFER, null);\\n gl.bindFramebuffer(gl.READ_FRAMEBUFFER, null);\\n }\\n gl.useProgram(null);\\n gl.lineWidth(1);\\n gl.scissor(0, 0, gl.canvas.width, gl.canvas.height);\\n gl.viewport(0, 0, gl.canvas.width, gl.canvas.height);\\n enabledCapabilities = {};\\n currentTextureSlot = null;\\n currentBoundTextures = {};\\n xrFramebuffer = null;\\n currentBoundFramebuffers = {};\\n currentProgram = null;\\n currentBlendingEnabled = false;\\n currentBlending = null;\\n currentBlendEquation = null;\\n currentBlendSrc = null;\\n currentBlendDst = null;\\n currentBlendEquationAlpha = null;\\n currentBlendSrcAlpha = null;\\n currentBlendDstAlpha = null;\\n currentPremultipledAlpha = false;\\n currentFlipSided = null;\\n currentCullFace = null;\\n currentLineWidth = null;\\n currentPolygonOffsetFactor = null;\\n currentPolygonOffsetUnits = null;\\n currentScissor.set(0, 0, gl.canvas.width, gl.canvas.height);\\n currentViewport.set(0, 0, gl.canvas.width, gl.canvas.height);\\n colorBuffer.reset();\\n depthBuffer.reset();\\n stencilBuffer.reset();\\n }\\n return {\\n buffers: {\\n color: colorBuffer,\\n depth: depthBuffer,\\n stencil: stencilBuffer\\n },\\n enable,\\n disable,\\n bindFramebuffer,\\n bindXRFramebuffer,\\n useProgram,\\n setBlending,\\n setMaterial,\\n setFlipSided,\\n setCullFace,\\n setLineWidth,\\n setPolygonOffset,\\n setScissorTest,\\n activeTexture,\\n bindTexture,\\n unbindTexture,\\n compressedTexImage2D,\\n texImage2D,\\n texImage3D,\\n scissor,\\n viewport,\\n reset\\n };\\n}\\n\\n// ../../../node_modules/three/src/renderers/webgl/WebGLTextures.js\\nfunction WebGLTextures(_gl, extensions, state, properties, capabilities, utils, info) {\\n const isWebGL2 = capabilities.isWebGL2;\\n const maxTextures = capabilities.maxTextures;\\n const maxCubemapSize = capabilities.maxCubemapSize;\\n const maxTextureSize = capabilities.maxTextureSize;\\n const maxSamples = capabilities.maxSamples;\\n const _videoTextures = new WeakMap();\\n let _canvas2;\\n let useOffscreenCanvas = false;\\n try {\\n useOffscreenCanvas = typeof OffscreenCanvas !== \\\\\\\"undefined\\\\\\\" && new OffscreenCanvas(1, 1).getContext(\\\\\\\"2d\\\\\\\") !== null;\\n } catch (err) {\\n }\\n function createCanvas(width, height) {\\n return useOffscreenCanvas ? new OffscreenCanvas(width, height) : createElementNS(\\\\\\\"canvas\\\\\\\");\\n }\\n function resizeImage(image, needsPowerOfTwo, needsNewCanvas, maxSize) {\\n let scale = 1;\\n if (image.width > maxSize || image.height > maxSize) {\\n scale = maxSize / Math.max(image.width, image.height);\\n }\\n if (scale < 1 || needsPowerOfTwo === true) {\\n if (typeof HTMLImageElement !== \\\\\\\"undefined\\\\\\\" && image instanceof HTMLImageElement || typeof HTMLCanvasElement !== \\\\\\\"undefined\\\\\\\" && image instanceof HTMLCanvasElement || typeof ImageBitmap !== \\\\\\\"undefined\\\\\\\" && image instanceof ImageBitmap) {\\n const floor = needsPowerOfTwo ? floorPowerOfTwo : Math.floor;\\n const width = floor(scale * image.width);\\n const height = floor(scale * image.height);\\n if (_canvas2 === void 0)\\n _canvas2 = createCanvas(width, height);\\n const canvas = needsNewCanvas ? createCanvas(width, height) : _canvas2;\\n canvas.width = width;\\n canvas.height = height;\\n const context = canvas.getContext(\\\\\\\"2d\\\\\\\");\\n context.drawImage(image, 0, 0, width, height);\\n console.warn(\\\\\\\"THREE.WebGLRenderer: Texture has been resized from (\\\\\\\" + image.width + \\\\\\\"x\\\\\\\" + image.height + \\\\\\\") to (\\\\\\\" + width + \\\\\\\"x\\\\\\\" + height + \\\\\\\").\\\\\\\");\\n return canvas;\\n } else {\\n if (\\\\\\\"data\\\\\\\" in image) {\\n console.warn(\\\\\\\"THREE.WebGLRenderer: Image in DataTexture is too big (\\\\\\\" + image.width + \\\\\\\"x\\\\\\\" + image.height + \\\\\\\").\\\\\\\");\\n }\\n return image;\\n }\\n }\\n return image;\\n }\\n function isPowerOfTwo2(image) {\\n return isPowerOfTwo(image.width) && isPowerOfTwo(image.height);\\n }\\n function textureNeedsPowerOfTwo(texture) {\\n if (isWebGL2)\\n return false;\\n return texture.wrapS !== ClampToEdgeWrapping || texture.wrapT !== ClampToEdgeWrapping || texture.minFilter !== NearestFilter && texture.minFilter !== LinearFilter;\\n }\\n function textureNeedsGenerateMipmaps(texture, supportsMips) {\\n return texture.generateMipmaps && supportsMips && texture.minFilter !== NearestFilter && texture.minFilter !== LinearFilter;\\n }\\n function generateMipmap(target, texture, width, height, depth2 = 1) {\\n _gl.generateMipmap(target);\\n const textureProperties = properties.get(texture);\\n textureProperties.__maxMipLevel = Math.log2(Math.max(width, height, depth2));\\n }\\n function getInternalFormat(internalFormatName, glFormat, glType, encoding) {\\n if (isWebGL2 === false)\\n return glFormat;\\n if (internalFormatName !== null) {\\n if (_gl[internalFormatName] !== void 0)\\n return _gl[internalFormatName];\\n console.warn(\\\\\\\"THREE.WebGLRenderer: Attempt to use non-existing WebGL internal format '\\\\\\\" + internalFormatName + \\\\\\\"'\\\\\\\");\\n }\\n let internalFormat = glFormat;\\n if (glFormat === _gl.RED) {\\n if (glType === _gl.FLOAT)\\n internalFormat = _gl.R32F;\\n if (glType === _gl.HALF_FLOAT)\\n internalFormat = _gl.R16F;\\n if (glType === _gl.UNSIGNED_BYTE)\\n internalFormat = _gl.R8;\\n }\\n if (glFormat === _gl.RGB) {\\n if (glType === _gl.FLOAT)\\n internalFormat = _gl.RGB32F;\\n if (glType === _gl.HALF_FLOAT)\\n internalFormat = _gl.RGB16F;\\n if (glType === _gl.UNSIGNED_BYTE)\\n internalFormat = _gl.RGB8;\\n }\\n if (glFormat === _gl.RGBA) {\\n if (glType === _gl.FLOAT)\\n internalFormat = _gl.RGBA32F;\\n if (glType === _gl.HALF_FLOAT)\\n internalFormat = _gl.RGBA16F;\\n if (glType === _gl.UNSIGNED_BYTE)\\n internalFormat = encoding === sRGBEncoding ? _gl.SRGB8_ALPHA8 : _gl.RGBA8;\\n }\\n if (internalFormat === _gl.R16F || internalFormat === _gl.R32F || internalFormat === _gl.RGBA16F || internalFormat === _gl.RGBA32F) {\\n extensions.get(\\\\\\\"EXT_color_buffer_float\\\\\\\");\\n }\\n return internalFormat;\\n }\\n function filterFallback(f) {\\n if (f === NearestFilter || f === NearestMipmapNearestFilter || f === NearestMipmapLinearFilter) {\\n return _gl.NEAREST;\\n }\\n return _gl.LINEAR;\\n }\\n function onTextureDispose(event) {\\n const texture = event.target;\\n texture.removeEventListener(\\\\\\\"dispose\\\\\\\", onTextureDispose);\\n deallocateTexture(texture);\\n if (texture.isVideoTexture) {\\n _videoTextures.delete(texture);\\n }\\n info.memory.textures--;\\n }\\n function onRenderTargetDispose(event) {\\n const renderTarget = event.target;\\n renderTarget.removeEventListener(\\\\\\\"dispose\\\\\\\", onRenderTargetDispose);\\n deallocateRenderTarget(renderTarget);\\n }\\n function deallocateTexture(texture) {\\n const textureProperties = properties.get(texture);\\n if (textureProperties.__webglInit === void 0)\\n return;\\n _gl.deleteTexture(textureProperties.__webglTexture);\\n properties.remove(texture);\\n }\\n function deallocateRenderTarget(renderTarget) {\\n const texture = renderTarget.texture;\\n const renderTargetProperties = properties.get(renderTarget);\\n const textureProperties = properties.get(texture);\\n if (!renderTarget)\\n return;\\n if (textureProperties.__webglTexture !== void 0) {\\n _gl.deleteTexture(textureProperties.__webglTexture);\\n info.memory.textures--;\\n }\\n if (renderTarget.depthTexture) {\\n renderTarget.depthTexture.dispose();\\n }\\n if (renderTarget.isWebGLCubeRenderTarget) {\\n for (let i = 0; i < 6; i++) {\\n _gl.deleteFramebuffer(renderTargetProperties.__webglFramebuffer[i]);\\n if (renderTargetProperties.__webglDepthbuffer)\\n _gl.deleteRenderbuffer(renderTargetProperties.__webglDepthbuffer[i]);\\n }\\n } else {\\n _gl.deleteFramebuffer(renderTargetProperties.__webglFramebuffer);\\n if (renderTargetProperties.__webglDepthbuffer)\\n _gl.deleteRenderbuffer(renderTargetProperties.__webglDepthbuffer);\\n if (renderTargetProperties.__webglMultisampledFramebuffer)\\n _gl.deleteFramebuffer(renderTargetProperties.__webglMultisampledFramebuffer);\\n if (renderTargetProperties.__webglColorRenderbuffer)\\n _gl.deleteRenderbuffer(renderTargetProperties.__webglColorRenderbuffer);\\n if (renderTargetProperties.__webglDepthRenderbuffer)\\n _gl.deleteRenderbuffer(renderTargetProperties.__webglDepthRenderbuffer);\\n }\\n if (renderTarget.isWebGLMultipleRenderTargets) {\\n for (let i = 0, il = texture.length; i < il; i++) {\\n const attachmentProperties = properties.get(texture[i]);\\n if (attachmentProperties.__webglTexture) {\\n _gl.deleteTexture(attachmentProperties.__webglTexture);\\n info.memory.textures--;\\n }\\n properties.remove(texture[i]);\\n }\\n }\\n properties.remove(texture);\\n properties.remove(renderTarget);\\n }\\n let textureUnits = 0;\\n function resetTextureUnits() {\\n textureUnits = 0;\\n }\\n function allocateTextureUnit() {\\n const textureUnit = textureUnits;\\n if (textureUnit >= maxTextures) {\\n console.warn(\\\\\\\"THREE.WebGLTextures: Trying to use \\\\\\\" + textureUnit + \\\\\\\" texture units while this GPU supports only \\\\\\\" + maxTextures);\\n }\\n textureUnits += 1;\\n return textureUnit;\\n }\\n function setTexture2D(texture, slot) {\\n const textureProperties = properties.get(texture);\\n if (texture.isVideoTexture)\\n updateVideoTexture(texture);\\n if (texture.version > 0 && textureProperties.__version !== texture.version) {\\n const image = texture.image;\\n if (image === void 0) {\\n console.warn(\\\\\\\"THREE.WebGLRenderer: Texture marked for update but image is undefined\\\\\\\");\\n } else if (image.complete === false) {\\n console.warn(\\\\\\\"THREE.WebGLRenderer: Texture marked for update but image is incomplete\\\\\\\");\\n } else {\\n uploadTexture(textureProperties, texture, slot);\\n return;\\n }\\n }\\n state.activeTexture(_gl.TEXTURE0 + slot);\\n state.bindTexture(_gl.TEXTURE_2D, textureProperties.__webglTexture);\\n }\\n function setTexture2DArray(texture, slot) {\\n const textureProperties = properties.get(texture);\\n if (texture.version > 0 && textureProperties.__version !== texture.version) {\\n uploadTexture(textureProperties, texture, slot);\\n return;\\n }\\n state.activeTexture(_gl.TEXTURE0 + slot);\\n state.bindTexture(_gl.TEXTURE_2D_ARRAY, textureProperties.__webglTexture);\\n }\\n function setTexture3D(texture, slot) {\\n const textureProperties = properties.get(texture);\\n if (texture.version > 0 && textureProperties.__version !== texture.version) {\\n uploadTexture(textureProperties, texture, slot);\\n return;\\n }\\n state.activeTexture(_gl.TEXTURE0 + slot);\\n state.bindTexture(_gl.TEXTURE_3D, textureProperties.__webglTexture);\\n }\\n function setTextureCube(texture, slot) {\\n const textureProperties = properties.get(texture);\\n if (texture.version > 0 && textureProperties.__version !== texture.version) {\\n uploadCubeTexture(textureProperties, texture, slot);\\n return;\\n }\\n state.activeTexture(_gl.TEXTURE0 + slot);\\n state.bindTexture(_gl.TEXTURE_CUBE_MAP, textureProperties.__webglTexture);\\n }\\n const wrappingToGL = {\\n [RepeatWrapping]: _gl.REPEAT,\\n [ClampToEdgeWrapping]: _gl.CLAMP_TO_EDGE,\\n [MirroredRepeatWrapping]: _gl.MIRRORED_REPEAT\\n };\\n const filterToGL = {\\n [NearestFilter]: _gl.NEAREST,\\n [NearestMipmapNearestFilter]: _gl.NEAREST_MIPMAP_NEAREST,\\n [NearestMipmapLinearFilter]: _gl.NEAREST_MIPMAP_LINEAR,\\n [LinearFilter]: _gl.LINEAR,\\n [LinearMipmapNearestFilter]: _gl.LINEAR_MIPMAP_NEAREST,\\n [LinearMipmapLinearFilter]: _gl.LINEAR_MIPMAP_LINEAR\\n };\\n function setTextureParameters(textureType, texture, supportsMips) {\\n if (supportsMips) {\\n _gl.texParameteri(textureType, _gl.TEXTURE_WRAP_S, wrappingToGL[texture.wrapS]);\\n _gl.texParameteri(textureType, _gl.TEXTURE_WRAP_T, wrappingToGL[texture.wrapT]);\\n if (textureType === _gl.TEXTURE_3D || textureType === _gl.TEXTURE_2D_ARRAY) {\\n _gl.texParameteri(textureType, _gl.TEXTURE_WRAP_R, wrappingToGL[texture.wrapR]);\\n }\\n _gl.texParameteri(textureType, _gl.TEXTURE_MAG_FILTER, filterToGL[texture.magFilter]);\\n _gl.texParameteri(textureType, _gl.TEXTURE_MIN_FILTER, filterToGL[texture.minFilter]);\\n } else {\\n _gl.texParameteri(textureType, _gl.TEXTURE_WRAP_S, _gl.CLAMP_TO_EDGE);\\n _gl.texParameteri(textureType, _gl.TEXTURE_WRAP_T, _gl.CLAMP_TO_EDGE);\\n if (textureType === _gl.TEXTURE_3D || textureType === _gl.TEXTURE_2D_ARRAY) {\\n _gl.texParameteri(textureType, _gl.TEXTURE_WRAP_R, _gl.CLAMP_TO_EDGE);\\n }\\n if (texture.wrapS !== ClampToEdgeWrapping || texture.wrapT !== ClampToEdgeWrapping) {\\n console.warn(\\\\\\\"THREE.WebGLRenderer: Texture is not power of two. Texture.wrapS and Texture.wrapT should be set to THREE.ClampToEdgeWrapping.\\\\\\\");\\n }\\n _gl.texParameteri(textureType, _gl.TEXTURE_MAG_FILTER, filterFallback(texture.magFilter));\\n _gl.texParameteri(textureType, _gl.TEXTURE_MIN_FILTER, filterFallback(texture.minFilter));\\n if (texture.minFilter !== NearestFilter && texture.minFilter !== LinearFilter) {\\n console.warn(\\\\\\\"THREE.WebGLRenderer: Texture is not power of two. Texture.minFilter should be set to THREE.NearestFilter or THREE.LinearFilter.\\\\\\\");\\n }\\n }\\n if (extensions.has(\\\\\\\"EXT_texture_filter_anisotropic\\\\\\\") === true) {\\n const extension = extensions.get(\\\\\\\"EXT_texture_filter_anisotropic\\\\\\\");\\n if (texture.type === FloatType && extensions.has(\\\\\\\"OES_texture_float_linear\\\\\\\") === false)\\n return;\\n if (isWebGL2 === false && (texture.type === HalfFloatType && extensions.has(\\\\\\\"OES_texture_half_float_linear\\\\\\\") === false))\\n return;\\n if (texture.anisotropy > 1 || properties.get(texture).__currentAnisotropy) {\\n _gl.texParameterf(textureType, extension.TEXTURE_MAX_ANISOTROPY_EXT, Math.min(texture.anisotropy, capabilities.getMaxAnisotropy()));\\n properties.get(texture).__currentAnisotropy = texture.anisotropy;\\n }\\n }\\n }\\n function initTexture(textureProperties, texture) {\\n if (textureProperties.__webglInit === void 0) {\\n textureProperties.__webglInit = true;\\n texture.addEventListener(\\\\\\\"dispose\\\\\\\", onTextureDispose);\\n textureProperties.__webglTexture = _gl.createTexture();\\n info.memory.textures++;\\n }\\n }\\n function uploadTexture(textureProperties, texture, slot) {\\n let textureType = _gl.TEXTURE_2D;\\n if (texture.isDataTexture2DArray)\\n textureType = _gl.TEXTURE_2D_ARRAY;\\n if (texture.isDataTexture3D)\\n textureType = _gl.TEXTURE_3D;\\n initTexture(textureProperties, texture);\\n state.activeTexture(_gl.TEXTURE0 + slot);\\n state.bindTexture(textureType, textureProperties.__webglTexture);\\n _gl.pixelStorei(_gl.UNPACK_FLIP_Y_WEBGL, texture.flipY);\\n _gl.pixelStorei(_gl.UNPACK_PREMULTIPLY_ALPHA_WEBGL, texture.premultiplyAlpha);\\n _gl.pixelStorei(_gl.UNPACK_ALIGNMENT, texture.unpackAlignment);\\n _gl.pixelStorei(_gl.UNPACK_COLORSPACE_CONVERSION_WEBGL, _gl.NONE);\\n const needsPowerOfTwo = textureNeedsPowerOfTwo(texture) && isPowerOfTwo2(texture.image) === false;\\n const image = resizeImage(texture.image, needsPowerOfTwo, false, maxTextureSize);\\n const supportsMips = isPowerOfTwo2(image) || isWebGL2, glFormat = utils.convert(texture.format);\\n let glType = utils.convert(texture.type), glInternalFormat = getInternalFormat(texture.internalFormat, glFormat, glType, texture.encoding);\\n setTextureParameters(textureType, texture, supportsMips);\\n let mipmap;\\n const mipmaps = texture.mipmaps;\\n if (texture.isDepthTexture) {\\n glInternalFormat = _gl.DEPTH_COMPONENT;\\n if (isWebGL2) {\\n if (texture.type === FloatType) {\\n glInternalFormat = _gl.DEPTH_COMPONENT32F;\\n } else if (texture.type === UnsignedIntType) {\\n glInternalFormat = _gl.DEPTH_COMPONENT24;\\n } else if (texture.type === UnsignedInt248Type) {\\n glInternalFormat = _gl.DEPTH24_STENCIL8;\\n } else {\\n glInternalFormat = _gl.DEPTH_COMPONENT16;\\n }\\n } else {\\n if (texture.type === FloatType) {\\n console.error(\\\\\\\"WebGLRenderer: Floating point depth texture requires WebGL2.\\\\\\\");\\n }\\n }\\n if (texture.format === DepthFormat && glInternalFormat === _gl.DEPTH_COMPONENT) {\\n if (texture.type !== UnsignedShortType && texture.type !== UnsignedIntType) {\\n console.warn(\\\\\\\"THREE.WebGLRenderer: Use UnsignedShortType or UnsignedIntType for DepthFormat DepthTexture.\\\\\\\");\\n texture.type = UnsignedShortType;\\n glType = utils.convert(texture.type);\\n }\\n }\\n if (texture.format === DepthStencilFormat && glInternalFormat === _gl.DEPTH_COMPONENT) {\\n glInternalFormat = _gl.DEPTH_STENCIL;\\n if (texture.type !== UnsignedInt248Type) {\\n console.warn(\\\\\\\"THREE.WebGLRenderer: Use UnsignedInt248Type for DepthStencilFormat DepthTexture.\\\\\\\");\\n texture.type = UnsignedInt248Type;\\n glType = utils.convert(texture.type);\\n }\\n }\\n state.texImage2D(_gl.TEXTURE_2D, 0, glInternalFormat, image.width, image.height, 0, glFormat, glType, null);\\n } else if (texture.isDataTexture) {\\n if (mipmaps.length > 0 && supportsMips) {\\n for (let i = 0, il = mipmaps.length; i < il; i++) {\\n mipmap = mipmaps[i];\\n state.texImage2D(_gl.TEXTURE_2D, i, glInternalFormat, mipmap.width, mipmap.height, 0, glFormat, glType, mipmap.data);\\n }\\n texture.generateMipmaps = false;\\n textureProperties.__maxMipLevel = mipmaps.length - 1;\\n } else {\\n state.texImage2D(_gl.TEXTURE_2D, 0, glInternalFormat, image.width, image.height, 0, glFormat, glType, image.data);\\n textureProperties.__maxMipLevel = 0;\\n }\\n } else if (texture.isCompressedTexture) {\\n for (let i = 0, il = mipmaps.length; i < il; i++) {\\n mipmap = mipmaps[i];\\n if (texture.format !== RGBAFormat && texture.format !== RGBFormat) {\\n if (glFormat !== null) {\\n state.compressedTexImage2D(_gl.TEXTURE_2D, i, glInternalFormat, mipmap.width, mipmap.height, 0, mipmap.data);\\n } else {\\n console.warn(\\\\\\\"THREE.WebGLRenderer: Attempt to load unsupported compressed texture format in .uploadTexture()\\\\\\\");\\n }\\n } else {\\n state.texImage2D(_gl.TEXTURE_2D, i, glInternalFormat, mipmap.width, mipmap.height, 0, glFormat, glType, mipmap.data);\\n }\\n }\\n textureProperties.__maxMipLevel = mipmaps.length - 1;\\n } else if (texture.isDataTexture2DArray) {\\n state.texImage3D(_gl.TEXTURE_2D_ARRAY, 0, glInternalFormat, image.width, image.height, image.depth, 0, glFormat, glType, image.data);\\n textureProperties.__maxMipLevel = 0;\\n } else if (texture.isDataTexture3D) {\\n state.texImage3D(_gl.TEXTURE_3D, 0, glInternalFormat, image.width, image.height, image.depth, 0, glFormat, glType, image.data);\\n textureProperties.__maxMipLevel = 0;\\n } else {\\n if (mipmaps.length > 0 && supportsMips) {\\n for (let i = 0, il = mipmaps.length; i < il; i++) {\\n mipmap = mipmaps[i];\\n state.texImage2D(_gl.TEXTURE_2D, i, glInternalFormat, glFormat, glType, mipmap);\\n }\\n texture.generateMipmaps = false;\\n textureProperties.__maxMipLevel = mipmaps.length - 1;\\n } else {\\n state.texImage2D(_gl.TEXTURE_2D, 0, glInternalFormat, glFormat, glType, image);\\n textureProperties.__maxMipLevel = 0;\\n }\\n }\\n if (textureNeedsGenerateMipmaps(texture, supportsMips)) {\\n generateMipmap(textureType, texture, image.width, image.height);\\n }\\n textureProperties.__version = texture.version;\\n if (texture.onUpdate)\\n texture.onUpdate(texture);\\n }\\n function uploadCubeTexture(textureProperties, texture, slot) {\\n if (texture.image.length !== 6)\\n return;\\n initTexture(textureProperties, texture);\\n state.activeTexture(_gl.TEXTURE0 + slot);\\n state.bindTexture(_gl.TEXTURE_CUBE_MAP, textureProperties.__webglTexture);\\n _gl.pixelStorei(_gl.UNPACK_FLIP_Y_WEBGL, texture.flipY);\\n _gl.pixelStorei(_gl.UNPACK_PREMULTIPLY_ALPHA_WEBGL, texture.premultiplyAlpha);\\n _gl.pixelStorei(_gl.UNPACK_ALIGNMENT, texture.unpackAlignment);\\n _gl.pixelStorei(_gl.UNPACK_COLORSPACE_CONVERSION_WEBGL, _gl.NONE);\\n const isCompressed = texture && (texture.isCompressedTexture || texture.image[0].isCompressedTexture);\\n const isDataTexture = texture.image[0] && texture.image[0].isDataTexture;\\n const cubeImage = [];\\n for (let i = 0; i < 6; i++) {\\n if (!isCompressed && !isDataTexture) {\\n cubeImage[i] = resizeImage(texture.image[i], false, true, maxCubemapSize);\\n } else {\\n cubeImage[i] = isDataTexture ? texture.image[i].image : texture.image[i];\\n }\\n }\\n const image = cubeImage[0], supportsMips = isPowerOfTwo2(image) || isWebGL2, glFormat = utils.convert(texture.format), glType = utils.convert(texture.type), glInternalFormat = getInternalFormat(texture.internalFormat, glFormat, glType, texture.encoding);\\n setTextureParameters(_gl.TEXTURE_CUBE_MAP, texture, supportsMips);\\n let mipmaps;\\n if (isCompressed) {\\n for (let i = 0; i < 6; i++) {\\n mipmaps = cubeImage[i].mipmaps;\\n for (let j = 0; j < mipmaps.length; j++) {\\n const mipmap = mipmaps[j];\\n if (texture.format !== RGBAFormat && texture.format !== RGBFormat) {\\n if (glFormat !== null) {\\n state.compressedTexImage2D(_gl.TEXTURE_CUBE_MAP_POSITIVE_X + i, j, glInternalFormat, mipmap.width, mipmap.height, 0, mipmap.data);\\n } else {\\n console.warn(\\\\\\\"THREE.WebGLRenderer: Attempt to load unsupported compressed texture format in .setTextureCube()\\\\\\\");\\n }\\n } else {\\n state.texImage2D(_gl.TEXTURE_CUBE_MAP_POSITIVE_X + i, j, glInternalFormat, mipmap.width, mipmap.height, 0, glFormat, glType, mipmap.data);\\n }\\n }\\n }\\n textureProperties.__maxMipLevel = mipmaps.length - 1;\\n } else {\\n mipmaps = texture.mipmaps;\\n for (let i = 0; i < 6; i++) {\\n if (isDataTexture) {\\n state.texImage2D(_gl.TEXTURE_CUBE_MAP_POSITIVE_X + i, 0, glInternalFormat, cubeImage[i].width, cubeImage[i].height, 0, glFormat, glType, cubeImage[i].data);\\n for (let j = 0; j < mipmaps.length; j++) {\\n const mipmap = mipmaps[j];\\n const mipmapImage = mipmap.image[i].image;\\n state.texImage2D(_gl.TEXTURE_CUBE_MAP_POSITIVE_X + i, j + 1, glInternalFormat, mipmapImage.width, mipmapImage.height, 0, glFormat, glType, mipmapImage.data);\\n }\\n } else {\\n state.texImage2D(_gl.TEXTURE_CUBE_MAP_POSITIVE_X + i, 0, glInternalFormat, glFormat, glType, cubeImage[i]);\\n for (let j = 0; j < mipmaps.length; j++) {\\n const mipmap = mipmaps[j];\\n state.texImage2D(_gl.TEXTURE_CUBE_MAP_POSITIVE_X + i, j + 1, glInternalFormat, glFormat, glType, mipmap.image[i]);\\n }\\n }\\n }\\n textureProperties.__maxMipLevel = mipmaps.length;\\n }\\n if (textureNeedsGenerateMipmaps(texture, supportsMips)) {\\n generateMipmap(_gl.TEXTURE_CUBE_MAP, texture, image.width, image.height);\\n }\\n textureProperties.__version = texture.version;\\n if (texture.onUpdate)\\n texture.onUpdate(texture);\\n }\\n function setupFrameBufferTexture(framebuffer, renderTarget, texture, attachment, textureTarget) {\\n const glFormat = utils.convert(texture.format);\\n const glType = utils.convert(texture.type);\\n const glInternalFormat = getInternalFormat(texture.internalFormat, glFormat, glType, texture.encoding);\\n if (textureTarget === _gl.TEXTURE_3D || textureTarget === _gl.TEXTURE_2D_ARRAY) {\\n state.texImage3D(textureTarget, 0, glInternalFormat, renderTarget.width, renderTarget.height, renderTarget.depth, 0, glFormat, glType, null);\\n } else {\\n state.texImage2D(textureTarget, 0, glInternalFormat, renderTarget.width, renderTarget.height, 0, glFormat, glType, null);\\n }\\n state.bindFramebuffer(_gl.FRAMEBUFFER, framebuffer);\\n _gl.framebufferTexture2D(_gl.FRAMEBUFFER, attachment, textureTarget, properties.get(texture).__webglTexture, 0);\\n state.bindFramebuffer(_gl.FRAMEBUFFER, null);\\n }\\n function setupRenderBufferStorage(renderbuffer, renderTarget, isMultisample) {\\n _gl.bindRenderbuffer(_gl.RENDERBUFFER, renderbuffer);\\n if (renderTarget.depthBuffer && !renderTarget.stencilBuffer) {\\n let glInternalFormat = _gl.DEPTH_COMPONENT16;\\n if (isMultisample) {\\n const depthTexture = renderTarget.depthTexture;\\n if (depthTexture && depthTexture.isDepthTexture) {\\n if (depthTexture.type === FloatType) {\\n glInternalFormat = _gl.DEPTH_COMPONENT32F;\\n } else if (depthTexture.type === UnsignedIntType) {\\n glInternalFormat = _gl.DEPTH_COMPONENT24;\\n }\\n }\\n const samples = getRenderTargetSamples(renderTarget);\\n _gl.renderbufferStorageMultisample(_gl.RENDERBUFFER, samples, glInternalFormat, renderTarget.width, renderTarget.height);\\n } else {\\n _gl.renderbufferStorage(_gl.RENDERBUFFER, glInternalFormat, renderTarget.width, renderTarget.height);\\n }\\n _gl.framebufferRenderbuffer(_gl.FRAMEBUFFER, _gl.DEPTH_ATTACHMENT, _gl.RENDERBUFFER, renderbuffer);\\n } else if (renderTarget.depthBuffer && renderTarget.stencilBuffer) {\\n if (isMultisample) {\\n const samples = getRenderTargetSamples(renderTarget);\\n _gl.renderbufferStorageMultisample(_gl.RENDERBUFFER, samples, _gl.DEPTH24_STENCIL8, renderTarget.width, renderTarget.height);\\n } else {\\n _gl.renderbufferStorage(_gl.RENDERBUFFER, _gl.DEPTH_STENCIL, renderTarget.width, renderTarget.height);\\n }\\n _gl.framebufferRenderbuffer(_gl.FRAMEBUFFER, _gl.DEPTH_STENCIL_ATTACHMENT, _gl.RENDERBUFFER, renderbuffer);\\n } else {\\n const texture = renderTarget.isWebGLMultipleRenderTargets === true ? renderTarget.texture[0] : renderTarget.texture;\\n const glFormat = utils.convert(texture.format);\\n const glType = utils.convert(texture.type);\\n const glInternalFormat = getInternalFormat(texture.internalFormat, glFormat, glType, texture.encoding);\\n if (isMultisample) {\\n const samples = getRenderTargetSamples(renderTarget);\\n _gl.renderbufferStorageMultisample(_gl.RENDERBUFFER, samples, glInternalFormat, renderTarget.width, renderTarget.height);\\n } else {\\n _gl.renderbufferStorage(_gl.RENDERBUFFER, glInternalFormat, renderTarget.width, renderTarget.height);\\n }\\n }\\n _gl.bindRenderbuffer(_gl.RENDERBUFFER, null);\\n }\\n function setupDepthTexture(framebuffer, renderTarget) {\\n const isCube = renderTarget && renderTarget.isWebGLCubeRenderTarget;\\n if (isCube)\\n throw new Error(\\\\\\\"Depth Texture with cube render targets is not supported\\\\\\\");\\n state.bindFramebuffer(_gl.FRAMEBUFFER, framebuffer);\\n if (!(renderTarget.depthTexture && renderTarget.depthTexture.isDepthTexture)) {\\n throw new Error(\\\\\\\"renderTarget.depthTexture must be an instance of THREE.DepthTexture\\\\\\\");\\n }\\n if (!properties.get(renderTarget.depthTexture).__webglTexture || renderTarget.depthTexture.image.width !== renderTarget.width || renderTarget.depthTexture.image.height !== renderTarget.height) {\\n renderTarget.depthTexture.image.width = renderTarget.width;\\n renderTarget.depthTexture.image.height = renderTarget.height;\\n renderTarget.depthTexture.needsUpdate = true;\\n }\\n setTexture2D(renderTarget.depthTexture, 0);\\n const webglDepthTexture = properties.get(renderTarget.depthTexture).__webglTexture;\\n if (renderTarget.depthTexture.format === DepthFormat) {\\n _gl.framebufferTexture2D(_gl.FRAMEBUFFER, _gl.DEPTH_ATTACHMENT, _gl.TEXTURE_2D, webglDepthTexture, 0);\\n } else if (renderTarget.depthTexture.format === DepthStencilFormat) {\\n _gl.framebufferTexture2D(_gl.FRAMEBUFFER, _gl.DEPTH_STENCIL_ATTACHMENT, _gl.TEXTURE_2D, webglDepthTexture, 0);\\n } else {\\n throw new Error(\\\\\\\"Unknown depthTexture format\\\\\\\");\\n }\\n }\\n function setupDepthRenderbuffer(renderTarget) {\\n const renderTargetProperties = properties.get(renderTarget);\\n const isCube = renderTarget.isWebGLCubeRenderTarget === true;\\n if (renderTarget.depthTexture) {\\n if (isCube)\\n throw new Error(\\\\\\\"target.depthTexture not supported in Cube render targets\\\\\\\");\\n setupDepthTexture(renderTargetProperties.__webglFramebuffer, renderTarget);\\n } else {\\n if (isCube) {\\n renderTargetProperties.__webglDepthbuffer = [];\\n for (let i = 0; i < 6; i++) {\\n state.bindFramebuffer(_gl.FRAMEBUFFER, renderTargetProperties.__webglFramebuffer[i]);\\n renderTargetProperties.__webglDepthbuffer[i] = _gl.createRenderbuffer();\\n setupRenderBufferStorage(renderTargetProperties.__webglDepthbuffer[i], renderTarget, false);\\n }\\n } else {\\n state.bindFramebuffer(_gl.FRAMEBUFFER, renderTargetProperties.__webglFramebuffer);\\n renderTargetProperties.__webglDepthbuffer = _gl.createRenderbuffer();\\n setupRenderBufferStorage(renderTargetProperties.__webglDepthbuffer, renderTarget, false);\\n }\\n }\\n state.bindFramebuffer(_gl.FRAMEBUFFER, null);\\n }\\n function setupRenderTarget(renderTarget) {\\n const texture = renderTarget.texture;\\n const renderTargetProperties = properties.get(renderTarget);\\n const textureProperties = properties.get(texture);\\n renderTarget.addEventListener(\\\\\\\"dispose\\\\\\\", onRenderTargetDispose);\\n if (renderTarget.isWebGLMultipleRenderTargets !== true) {\\n textureProperties.__webglTexture = _gl.createTexture();\\n textureProperties.__version = texture.version;\\n info.memory.textures++;\\n }\\n const isCube = renderTarget.isWebGLCubeRenderTarget === true;\\n const isMultipleRenderTargets = renderTarget.isWebGLMultipleRenderTargets === true;\\n const isMultisample = renderTarget.isWebGLMultisampleRenderTarget === true;\\n const isRenderTarget3D = texture.isDataTexture3D || texture.isDataTexture2DArray;\\n const supportsMips = isPowerOfTwo2(renderTarget) || isWebGL2;\\n if (isWebGL2 && texture.format === RGBFormat && (texture.type === FloatType || texture.type === HalfFloatType)) {\\n texture.format = RGBAFormat;\\n console.warn(\\\\\\\"THREE.WebGLRenderer: Rendering to textures with RGB format is not supported. Using RGBA format instead.\\\\\\\");\\n }\\n if (isCube) {\\n renderTargetProperties.__webglFramebuffer = [];\\n for (let i = 0; i < 6; i++) {\\n renderTargetProperties.__webglFramebuffer[i] = _gl.createFramebuffer();\\n }\\n } else {\\n renderTargetProperties.__webglFramebuffer = _gl.createFramebuffer();\\n if (isMultipleRenderTargets) {\\n if (capabilities.drawBuffers) {\\n const textures = renderTarget.texture;\\n for (let i = 0, il = textures.length; i < il; i++) {\\n const attachmentProperties = properties.get(textures[i]);\\n if (attachmentProperties.__webglTexture === void 0) {\\n attachmentProperties.__webglTexture = _gl.createTexture();\\n info.memory.textures++;\\n }\\n }\\n } else {\\n console.warn(\\\\\\\"THREE.WebGLRenderer: WebGLMultipleRenderTargets can only be used with WebGL2 or WEBGL_draw_buffers extension.\\\\\\\");\\n }\\n } else if (isMultisample) {\\n if (isWebGL2) {\\n renderTargetProperties.__webglMultisampledFramebuffer = _gl.createFramebuffer();\\n renderTargetProperties.__webglColorRenderbuffer = _gl.createRenderbuffer();\\n _gl.bindRenderbuffer(_gl.RENDERBUFFER, renderTargetProperties.__webglColorRenderbuffer);\\n const glFormat = utils.convert(texture.format);\\n const glType = utils.convert(texture.type);\\n const glInternalFormat = getInternalFormat(texture.internalFormat, glFormat, glType, texture.encoding);\\n const samples = getRenderTargetSamples(renderTarget);\\n _gl.renderbufferStorageMultisample(_gl.RENDERBUFFER, samples, glInternalFormat, renderTarget.width, renderTarget.height);\\n state.bindFramebuffer(_gl.FRAMEBUFFER, renderTargetProperties.__webglMultisampledFramebuffer);\\n _gl.framebufferRenderbuffer(_gl.FRAMEBUFFER, _gl.COLOR_ATTACHMENT0, _gl.RENDERBUFFER, renderTargetProperties.__webglColorRenderbuffer);\\n _gl.bindRenderbuffer(_gl.RENDERBUFFER, null);\\n if (renderTarget.depthBuffer) {\\n renderTargetProperties.__webglDepthRenderbuffer = _gl.createRenderbuffer();\\n setupRenderBufferStorage(renderTargetProperties.__webglDepthRenderbuffer, renderTarget, true);\\n }\\n state.bindFramebuffer(_gl.FRAMEBUFFER, null);\\n } else {\\n console.warn(\\\\\\\"THREE.WebGLRenderer: WebGLMultisampleRenderTarget can only be used with WebGL2.\\\\\\\");\\n }\\n }\\n }\\n if (isCube) {\\n state.bindTexture(_gl.TEXTURE_CUBE_MAP, textureProperties.__webglTexture);\\n setTextureParameters(_gl.TEXTURE_CUBE_MAP, texture, supportsMips);\\n for (let i = 0; i < 6; i++) {\\n setupFrameBufferTexture(renderTargetProperties.__webglFramebuffer[i], renderTarget, texture, _gl.COLOR_ATTACHMENT0, _gl.TEXTURE_CUBE_MAP_POSITIVE_X + i);\\n }\\n if (textureNeedsGenerateMipmaps(texture, supportsMips)) {\\n generateMipmap(_gl.TEXTURE_CUBE_MAP, texture, renderTarget.width, renderTarget.height);\\n }\\n state.unbindTexture();\\n } else if (isMultipleRenderTargets) {\\n const textures = renderTarget.texture;\\n for (let i = 0, il = textures.length; i < il; i++) {\\n const attachment = textures[i];\\n const attachmentProperties = properties.get(attachment);\\n state.bindTexture(_gl.TEXTURE_2D, attachmentProperties.__webglTexture);\\n setTextureParameters(_gl.TEXTURE_2D, attachment, supportsMips);\\n setupFrameBufferTexture(renderTargetProperties.__webglFramebuffer, renderTarget, attachment, _gl.COLOR_ATTACHMENT0 + i, _gl.TEXTURE_2D);\\n if (textureNeedsGenerateMipmaps(attachment, supportsMips)) {\\n generateMipmap(_gl.TEXTURE_2D, attachment, renderTarget.width, renderTarget.height);\\n }\\n }\\n state.unbindTexture();\\n } else {\\n let glTextureType = _gl.TEXTURE_2D;\\n if (isRenderTarget3D) {\\n if (isWebGL2) {\\n const isTexture3D = texture.isDataTexture3D;\\n glTextureType = isTexture3D ? _gl.TEXTURE_3D : _gl.TEXTURE_2D_ARRAY;\\n } else {\\n console.warn(\\\\\\\"THREE.DataTexture3D and THREE.DataTexture2DArray only supported with WebGL2.\\\\\\\");\\n }\\n }\\n state.bindTexture(glTextureType, textureProperties.__webglTexture);\\n setTextureParameters(glTextureType, texture, supportsMips);\\n setupFrameBufferTexture(renderTargetProperties.__webglFramebuffer, renderTarget, texture, _gl.COLOR_ATTACHMENT0, glTextureType);\\n if (textureNeedsGenerateMipmaps(texture, supportsMips)) {\\n generateMipmap(glTextureType, texture, renderTarget.width, renderTarget.height, renderTarget.depth);\\n }\\n state.unbindTexture();\\n }\\n if (renderTarget.depthBuffer) {\\n setupDepthRenderbuffer(renderTarget);\\n }\\n }\\n function updateRenderTargetMipmap(renderTarget) {\\n const supportsMips = isPowerOfTwo2(renderTarget) || isWebGL2;\\n const textures = renderTarget.isWebGLMultipleRenderTargets === true ? renderTarget.texture : [renderTarget.texture];\\n for (let i = 0, il = textures.length; i < il; i++) {\\n const texture = textures[i];\\n if (textureNeedsGenerateMipmaps(texture, supportsMips)) {\\n const target = renderTarget.isWebGLCubeRenderTarget ? _gl.TEXTURE_CUBE_MAP : _gl.TEXTURE_2D;\\n const webglTexture = properties.get(texture).__webglTexture;\\n state.bindTexture(target, webglTexture);\\n generateMipmap(target, texture, renderTarget.width, renderTarget.height);\\n state.unbindTexture();\\n }\\n }\\n }\\n function updateMultisampleRenderTarget(renderTarget) {\\n if (renderTarget.isWebGLMultisampleRenderTarget) {\\n if (isWebGL2) {\\n const width = renderTarget.width;\\n const height = renderTarget.height;\\n let mask = _gl.COLOR_BUFFER_BIT;\\n if (renderTarget.depthBuffer)\\n mask |= _gl.DEPTH_BUFFER_BIT;\\n if (renderTarget.stencilBuffer)\\n mask |= _gl.STENCIL_BUFFER_BIT;\\n const renderTargetProperties = properties.get(renderTarget);\\n state.bindFramebuffer(_gl.READ_FRAMEBUFFER, renderTargetProperties.__webglMultisampledFramebuffer);\\n state.bindFramebuffer(_gl.DRAW_FRAMEBUFFER, renderTargetProperties.__webglFramebuffer);\\n _gl.blitFramebuffer(0, 0, width, height, 0, 0, width, height, mask, _gl.NEAREST);\\n state.bindFramebuffer(_gl.READ_FRAMEBUFFER, null);\\n state.bindFramebuffer(_gl.DRAW_FRAMEBUFFER, renderTargetProperties.__webglMultisampledFramebuffer);\\n } else {\\n console.warn(\\\\\\\"THREE.WebGLRenderer: WebGLMultisampleRenderTarget can only be used with WebGL2.\\\\\\\");\\n }\\n }\\n }\\n function getRenderTargetSamples(renderTarget) {\\n return isWebGL2 && renderTarget.isWebGLMultisampleRenderTarget ? Math.min(maxSamples, renderTarget.samples) : 0;\\n }\\n function updateVideoTexture(texture) {\\n const frame = info.render.frame;\\n if (_videoTextures.get(texture) !== frame) {\\n _videoTextures.set(texture, frame);\\n texture.update();\\n }\\n }\\n let warnedTexture2D = false;\\n let warnedTextureCube = false;\\n function safeSetTexture2D(texture, slot) {\\n if (texture && texture.isWebGLRenderTarget) {\\n if (warnedTexture2D === false) {\\n console.warn(\\\\\\\"THREE.WebGLTextures.safeSetTexture2D: don't use render targets as textures. Use their .texture property instead.\\\\\\\");\\n warnedTexture2D = true;\\n }\\n texture = texture.texture;\\n }\\n setTexture2D(texture, slot);\\n }\\n function safeSetTextureCube(texture, slot) {\\n if (texture && texture.isWebGLCubeRenderTarget) {\\n if (warnedTextureCube === false) {\\n console.warn(\\\\\\\"THREE.WebGLTextures.safeSetTextureCube: don't use cube render targets as textures. Use their .texture property instead.\\\\\\\");\\n warnedTextureCube = true;\\n }\\n texture = texture.texture;\\n }\\n setTextureCube(texture, slot);\\n }\\n this.allocateTextureUnit = allocateTextureUnit;\\n this.resetTextureUnits = resetTextureUnits;\\n this.setTexture2D = setTexture2D;\\n this.setTexture2DArray = setTexture2DArray;\\n this.setTexture3D = setTexture3D;\\n this.setTextureCube = setTextureCube;\\n this.setupRenderTarget = setupRenderTarget;\\n this.updateRenderTargetMipmap = updateRenderTargetMipmap;\\n this.updateMultisampleRenderTarget = updateMultisampleRenderTarget;\\n this.safeSetTexture2D = safeSetTexture2D;\\n this.safeSetTextureCube = safeSetTextureCube;\\n}\\n\\n// ../../../node_modules/three/src/renderers/webgl/WebGLUtils.js\\nfunction WebGLUtils(gl, extensions, capabilities) {\\n const isWebGL2 = capabilities.isWebGL2;\\n function convert(p) {\\n let extension;\\n if (p === UnsignedByteType)\\n return gl.UNSIGNED_BYTE;\\n if (p === UnsignedShort4444Type)\\n return gl.UNSIGNED_SHORT_4_4_4_4;\\n if (p === UnsignedShort5551Type)\\n return gl.UNSIGNED_SHORT_5_5_5_1;\\n if (p === UnsignedShort565Type)\\n return gl.UNSIGNED_SHORT_5_6_5;\\n if (p === ByteType)\\n return gl.BYTE;\\n if (p === ShortType)\\n return gl.SHORT;\\n if (p === UnsignedShortType)\\n return gl.UNSIGNED_SHORT;\\n if (p === IntType)\\n return gl.INT;\\n if (p === UnsignedIntType)\\n return gl.UNSIGNED_INT;\\n if (p === FloatType)\\n return gl.FLOAT;\\n if (p === HalfFloatType) {\\n if (isWebGL2)\\n return gl.HALF_FLOAT;\\n extension = extensions.get(\\\\\\\"OES_texture_half_float\\\\\\\");\\n if (extension !== null) {\\n return extension.HALF_FLOAT_OES;\\n } else {\\n return null;\\n }\\n }\\n if (p === AlphaFormat)\\n return gl.ALPHA;\\n if (p === RGBFormat)\\n return gl.RGB;\\n if (p === RGBAFormat)\\n return gl.RGBA;\\n if (p === LuminanceFormat)\\n return gl.LUMINANCE;\\n if (p === LuminanceAlphaFormat)\\n return gl.LUMINANCE_ALPHA;\\n if (p === DepthFormat)\\n return gl.DEPTH_COMPONENT;\\n if (p === DepthStencilFormat)\\n return gl.DEPTH_STENCIL;\\n if (p === RedFormat)\\n return gl.RED;\\n if (p === RedIntegerFormat)\\n return gl.RED_INTEGER;\\n if (p === RGFormat)\\n return gl.RG;\\n if (p === RGIntegerFormat)\\n return gl.RG_INTEGER;\\n if (p === RGBIntegerFormat)\\n return gl.RGB_INTEGER;\\n if (p === RGBAIntegerFormat)\\n return gl.RGBA_INTEGER;\\n if (p === RGB_S3TC_DXT1_Format || p === RGBA_S3TC_DXT1_Format || p === RGBA_S3TC_DXT3_Format || p === RGBA_S3TC_DXT5_Format) {\\n extension = extensions.get(\\\\\\\"WEBGL_compressed_texture_s3tc\\\\\\\");\\n if (extension !== null) {\\n if (p === RGB_S3TC_DXT1_Format)\\n return extension.COMPRESSED_RGB_S3TC_DXT1_EXT;\\n if (p === RGBA_S3TC_DXT1_Format)\\n return extension.COMPRESSED_RGBA_S3TC_DXT1_EXT;\\n if (p === RGBA_S3TC_DXT3_Format)\\n return extension.COMPRESSED_RGBA_S3TC_DXT3_EXT;\\n if (p === RGBA_S3TC_DXT5_Format)\\n return extension.COMPRESSED_RGBA_S3TC_DXT5_EXT;\\n } else {\\n return null;\\n }\\n }\\n if (p === RGB_PVRTC_4BPPV1_Format || p === RGB_PVRTC_2BPPV1_Format || p === RGBA_PVRTC_4BPPV1_Format || p === RGBA_PVRTC_2BPPV1_Format) {\\n extension = extensions.get(\\\\\\\"WEBGL_compressed_texture_pvrtc\\\\\\\");\\n if (extension !== null) {\\n if (p === RGB_PVRTC_4BPPV1_Format)\\n return extension.COMPRESSED_RGB_PVRTC_4BPPV1_IMG;\\n if (p === RGB_PVRTC_2BPPV1_Format)\\n return extension.COMPRESSED_RGB_PVRTC_2BPPV1_IMG;\\n if (p === RGBA_PVRTC_4BPPV1_Format)\\n return extension.COMPRESSED_RGBA_PVRTC_4BPPV1_IMG;\\n if (p === RGBA_PVRTC_2BPPV1_Format)\\n return extension.COMPRESSED_RGBA_PVRTC_2BPPV1_IMG;\\n } else {\\n return null;\\n }\\n }\\n if (p === RGB_ETC1_Format) {\\n extension = extensions.get(\\\\\\\"WEBGL_compressed_texture_etc1\\\\\\\");\\n if (extension !== null) {\\n return extension.COMPRESSED_RGB_ETC1_WEBGL;\\n } else {\\n return null;\\n }\\n }\\n if (p === RGB_ETC2_Format || p === RGBA_ETC2_EAC_Format) {\\n extension = extensions.get(\\\\\\\"WEBGL_compressed_texture_etc\\\\\\\");\\n if (extension !== null) {\\n if (p === RGB_ETC2_Format)\\n return extension.COMPRESSED_RGB8_ETC2;\\n if (p === RGBA_ETC2_EAC_Format)\\n return extension.COMPRESSED_RGBA8_ETC2_EAC;\\n }\\n }\\n if (p === RGBA_ASTC_4x4_Format || p === RGBA_ASTC_5x4_Format || p === RGBA_ASTC_5x5_Format || p === RGBA_ASTC_6x5_Format || p === RGBA_ASTC_6x6_Format || p === RGBA_ASTC_8x5_Format || p === RGBA_ASTC_8x6_Format || p === RGBA_ASTC_8x8_Format || p === RGBA_ASTC_10x5_Format || p === RGBA_ASTC_10x6_Format || p === RGBA_ASTC_10x8_Format || p === RGBA_ASTC_10x10_Format || p === RGBA_ASTC_12x10_Format || p === RGBA_ASTC_12x12_Format || p === SRGB8_ALPHA8_ASTC_4x4_Format || p === SRGB8_ALPHA8_ASTC_5x4_Format || p === SRGB8_ALPHA8_ASTC_5x5_Format || p === SRGB8_ALPHA8_ASTC_6x5_Format || p === SRGB8_ALPHA8_ASTC_6x6_Format || p === SRGB8_ALPHA8_ASTC_8x5_Format || p === SRGB8_ALPHA8_ASTC_8x6_Format || p === SRGB8_ALPHA8_ASTC_8x8_Format || p === SRGB8_ALPHA8_ASTC_10x5_Format || p === SRGB8_ALPHA8_ASTC_10x6_Format || p === SRGB8_ALPHA8_ASTC_10x8_Format || p === SRGB8_ALPHA8_ASTC_10x10_Format || p === SRGB8_ALPHA8_ASTC_12x10_Format || p === SRGB8_ALPHA8_ASTC_12x12_Format) {\\n extension = extensions.get(\\\\\\\"WEBGL_compressed_texture_astc\\\\\\\");\\n if (extension !== null) {\\n return p;\\n } else {\\n return null;\\n }\\n }\\n if (p === RGBA_BPTC_Format) {\\n extension = extensions.get(\\\\\\\"EXT_texture_compression_bptc\\\\\\\");\\n if (extension !== null) {\\n return p;\\n } else {\\n return null;\\n }\\n }\\n if (p === UnsignedInt248Type) {\\n if (isWebGL2)\\n return gl.UNSIGNED_INT_24_8;\\n extension = extensions.get(\\\\\\\"WEBGL_depth_texture\\\\\\\");\\n if (extension !== null) {\\n return extension.UNSIGNED_INT_24_8_WEBGL;\\n } else {\\n return null;\\n }\\n }\\n }\\n return {convert};\\n}\\n\\n// ../../../node_modules/three/src/cameras/ArrayCamera.js\\nvar ArrayCamera = class extends PerspectiveCamera {\\n constructor(array = []) {\\n super();\\n this.cameras = array;\\n }\\n};\\nArrayCamera.prototype.isArrayCamera = true;\\n\\n// ../../../node_modules/three/src/objects/Group.js\\nvar Group = class extends Object3D {\\n constructor() {\\n super();\\n this.type = \\\\\\\"Group\\\\\\\";\\n }\\n};\\nGroup.prototype.isGroup = true;\\n\\n// ../../../node_modules/three/src/renderers/webxr/WebXRController.js\\nvar _moveEvent = {type: \\\\\\\"move\\\\\\\"};\\nvar WebXRController = class {\\n constructor() {\\n this._targetRay = null;\\n this._grip = null;\\n this._hand = null;\\n }\\n getHandSpace() {\\n if (this._hand === null) {\\n this._hand = new Group();\\n this._hand.matrixAutoUpdate = false;\\n this._hand.visible = false;\\n this._hand.joints = {};\\n this._hand.inputState = {pinching: false};\\n }\\n return this._hand;\\n }\\n getTargetRaySpace() {\\n if (this._targetRay === null) {\\n this._targetRay = new Group();\\n this._targetRay.matrixAutoUpdate = false;\\n this._targetRay.visible = false;\\n this._targetRay.hasLinearVelocity = false;\\n this._targetRay.linearVelocity = new Vector3();\\n this._targetRay.hasAngularVelocity = false;\\n this._targetRay.angularVelocity = new Vector3();\\n }\\n return this._targetRay;\\n }\\n getGripSpace() {\\n if (this._grip === null) {\\n this._grip = new Group();\\n this._grip.matrixAutoUpdate = false;\\n this._grip.visible = false;\\n this._grip.hasLinearVelocity = false;\\n this._grip.linearVelocity = new Vector3();\\n this._grip.hasAngularVelocity = false;\\n this._grip.angularVelocity = new Vector3();\\n }\\n return this._grip;\\n }\\n dispatchEvent(event) {\\n if (this._targetRay !== null) {\\n this._targetRay.dispatchEvent(event);\\n }\\n if (this._grip !== null) {\\n this._grip.dispatchEvent(event);\\n }\\n if (this._hand !== null) {\\n this._hand.dispatchEvent(event);\\n }\\n return this;\\n }\\n disconnect(inputSource) {\\n this.dispatchEvent({type: \\\\\\\"disconnected\\\\\\\", data: inputSource});\\n if (this._targetRay !== null) {\\n this._targetRay.visible = false;\\n }\\n if (this._grip !== null) {\\n this._grip.visible = false;\\n }\\n if (this._hand !== null) {\\n this._hand.visible = false;\\n }\\n return this;\\n }\\n update(inputSource, frame, referenceSpace) {\\n let inputPose = null;\\n let gripPose = null;\\n let handPose = null;\\n const targetRay = this._targetRay;\\n const grip = this._grip;\\n const hand = this._hand;\\n if (inputSource && frame.session.visibilityState !== \\\\\\\"visible-blurred\\\\\\\") {\\n if (targetRay !== null) {\\n inputPose = frame.getPose(inputSource.targetRaySpace, referenceSpace);\\n if (inputPose !== null) {\\n targetRay.matrix.fromArray(inputPose.transform.matrix);\\n targetRay.matrix.decompose(targetRay.position, targetRay.rotation, targetRay.scale);\\n if (inputPose.linearVelocity) {\\n targetRay.hasLinearVelocity = true;\\n targetRay.linearVelocity.copy(inputPose.linearVelocity);\\n } else {\\n targetRay.hasLinearVelocity = false;\\n }\\n if (inputPose.angularVelocity) {\\n targetRay.hasAngularVelocity = true;\\n targetRay.angularVelocity.copy(inputPose.angularVelocity);\\n } else {\\n targetRay.hasAngularVelocity = false;\\n }\\n this.dispatchEvent(_moveEvent);\\n }\\n }\\n if (hand && inputSource.hand) {\\n handPose = true;\\n for (const inputjoint of inputSource.hand.values()) {\\n const jointPose = frame.getJointPose(inputjoint, referenceSpace);\\n if (hand.joints[inputjoint.jointName] === void 0) {\\n const joint2 = new Group();\\n joint2.matrixAutoUpdate = false;\\n joint2.visible = false;\\n hand.joints[inputjoint.jointName] = joint2;\\n hand.add(joint2);\\n }\\n const joint = hand.joints[inputjoint.jointName];\\n if (jointPose !== null) {\\n joint.matrix.fromArray(jointPose.transform.matrix);\\n joint.matrix.decompose(joint.position, joint.rotation, joint.scale);\\n joint.jointRadius = jointPose.radius;\\n }\\n joint.visible = jointPose !== null;\\n }\\n const indexTip = hand.joints[\\\\\\\"index-finger-tip\\\\\\\"];\\n const thumbTip = hand.joints[\\\\\\\"thumb-tip\\\\\\\"];\\n const distance = indexTip.position.distanceTo(thumbTip.position);\\n const distanceToPinch = 0.02;\\n const threshold = 5e-3;\\n if (hand.inputState.pinching && distance > distanceToPinch + threshold) {\\n hand.inputState.pinching = false;\\n this.dispatchEvent({\\n type: \\\\\\\"pinchend\\\\\\\",\\n handedness: inputSource.handedness,\\n target: this\\n });\\n } else if (!hand.inputState.pinching && distance <= distanceToPinch - threshold) {\\n hand.inputState.pinching = true;\\n this.dispatchEvent({\\n type: \\\\\\\"pinchstart\\\\\\\",\\n handedness: inputSource.handedness,\\n target: this\\n });\\n }\\n } else {\\n if (grip !== null && inputSource.gripSpace) {\\n gripPose = frame.getPose(inputSource.gripSpace, referenceSpace);\\n if (gripPose !== null) {\\n grip.matrix.fromArray(gripPose.transform.matrix);\\n grip.matrix.decompose(grip.position, grip.rotation, grip.scale);\\n if (gripPose.linearVelocity) {\\n grip.hasLinearVelocity = true;\\n grip.linearVelocity.copy(gripPose.linearVelocity);\\n } else {\\n grip.hasLinearVelocity = false;\\n }\\n if (gripPose.angularVelocity) {\\n grip.hasAngularVelocity = true;\\n grip.angularVelocity.copy(gripPose.angularVelocity);\\n } else {\\n grip.hasAngularVelocity = false;\\n }\\n }\\n }\\n }\\n }\\n if (targetRay !== null) {\\n targetRay.visible = inputPose !== null;\\n }\\n if (grip !== null) {\\n grip.visible = gripPose !== null;\\n }\\n if (hand !== null) {\\n hand.visible = handPose !== null;\\n }\\n return this;\\n }\\n};\\n\\n// ../../../node_modules/three/src/renderers/webxr/WebXRManager.js\\nvar WebXRManager = class extends EventDispatcher {\\n constructor(renderer, gl) {\\n super();\\n const scope = this;\\n const state = renderer.state;\\n let session = null;\\n let framebufferScaleFactor = 1;\\n let referenceSpace = null;\\n let referenceSpaceType = \\\\\\\"local-floor\\\\\\\";\\n let pose = null;\\n let glBinding = null;\\n let glFramebuffer = null;\\n let glProjLayer = null;\\n let glBaseLayer = null;\\n let isMultisample = false;\\n let glMultisampledFramebuffer = null;\\n let glColorRenderbuffer = null;\\n let glDepthRenderbuffer = null;\\n let xrFrame = null;\\n let depthStyle = null;\\n let clearStyle = null;\\n const controllers = [];\\n const inputSourcesMap = new Map();\\n const cameraL = new PerspectiveCamera();\\n cameraL.layers.enable(1);\\n cameraL.viewport = new Vector4();\\n const cameraR = new PerspectiveCamera();\\n cameraR.layers.enable(2);\\n cameraR.viewport = new Vector4();\\n const cameras = [cameraL, cameraR];\\n const cameraVR = new ArrayCamera();\\n cameraVR.layers.enable(1);\\n cameraVR.layers.enable(2);\\n let _currentDepthNear = null;\\n let _currentDepthFar = null;\\n this.cameraAutoUpdate = true;\\n this.enabled = false;\\n this.isPresenting = false;\\n this.getController = function(index) {\\n let controller = controllers[index];\\n if (controller === void 0) {\\n controller = new WebXRController();\\n controllers[index] = controller;\\n }\\n return controller.getTargetRaySpace();\\n };\\n this.getControllerGrip = function(index) {\\n let controller = controllers[index];\\n if (controller === void 0) {\\n controller = new WebXRController();\\n controllers[index] = controller;\\n }\\n return controller.getGripSpace();\\n };\\n this.getHand = function(index) {\\n let controller = controllers[index];\\n if (controller === void 0) {\\n controller = new WebXRController();\\n controllers[index] = controller;\\n }\\n return controller.getHandSpace();\\n };\\n function onSessionEvent(event) {\\n const controller = inputSourcesMap.get(event.inputSource);\\n if (controller) {\\n controller.dispatchEvent({type: event.type, data: event.inputSource});\\n }\\n }\\n function onSessionEnd() {\\n inputSourcesMap.forEach(function(controller, inputSource) {\\n controller.disconnect(inputSource);\\n });\\n inputSourcesMap.clear();\\n _currentDepthNear = null;\\n _currentDepthFar = null;\\n state.bindXRFramebuffer(null);\\n renderer.setRenderTarget(renderer.getRenderTarget());\\n if (glFramebuffer)\\n gl.deleteFramebuffer(glFramebuffer);\\n if (glMultisampledFramebuffer)\\n gl.deleteFramebuffer(glMultisampledFramebuffer);\\n if (glColorRenderbuffer)\\n gl.deleteRenderbuffer(glColorRenderbuffer);\\n if (glDepthRenderbuffer)\\n gl.deleteRenderbuffer(glDepthRenderbuffer);\\n glFramebuffer = null;\\n glMultisampledFramebuffer = null;\\n glColorRenderbuffer = null;\\n glDepthRenderbuffer = null;\\n glBaseLayer = null;\\n glProjLayer = null;\\n glBinding = null;\\n session = null;\\n animation.stop();\\n scope.isPresenting = false;\\n scope.dispatchEvent({type: \\\\\\\"sessionend\\\\\\\"});\\n }\\n this.setFramebufferScaleFactor = function(value) {\\n framebufferScaleFactor = value;\\n if (scope.isPresenting === true) {\\n console.warn(\\\\\\\"THREE.WebXRManager: Cannot change framebuffer scale while presenting.\\\\\\\");\\n }\\n };\\n this.setReferenceSpaceType = function(value) {\\n referenceSpaceType = value;\\n if (scope.isPresenting === true) {\\n console.warn(\\\\\\\"THREE.WebXRManager: Cannot change reference space type while presenting.\\\\\\\");\\n }\\n };\\n this.getReferenceSpace = function() {\\n return referenceSpace;\\n };\\n this.getBaseLayer = function() {\\n return glProjLayer !== null ? glProjLayer : glBaseLayer;\\n };\\n this.getBinding = function() {\\n return glBinding;\\n };\\n this.getFrame = function() {\\n return xrFrame;\\n };\\n this.getSession = function() {\\n return session;\\n };\\n this.setSession = async function(value) {\\n session = value;\\n if (session !== null) {\\n session.addEventListener(\\\\\\\"select\\\\\\\", onSessionEvent);\\n session.addEventListener(\\\\\\\"selectstart\\\\\\\", onSessionEvent);\\n session.addEventListener(\\\\\\\"selectend\\\\\\\", onSessionEvent);\\n session.addEventListener(\\\\\\\"squeeze\\\\\\\", onSessionEvent);\\n session.addEventListener(\\\\\\\"squeezestart\\\\\\\", onSessionEvent);\\n session.addEventListener(\\\\\\\"squeezeend\\\\\\\", onSessionEvent);\\n session.addEventListener(\\\\\\\"end\\\\\\\", onSessionEnd);\\n session.addEventListener(\\\\\\\"inputsourceschange\\\\\\\", onInputSourcesChange);\\n const attributes = gl.getContextAttributes();\\n if (attributes.xrCompatible !== true) {\\n await gl.makeXRCompatible();\\n }\\n if (session.renderState.layers === void 0) {\\n const layerInit = {\\n antialias: attributes.antialias,\\n alpha: attributes.alpha,\\n depth: attributes.depth,\\n stencil: attributes.stencil,\\n framebufferScaleFactor\\n };\\n glBaseLayer = new XRWebGLLayer(session, gl, layerInit);\\n session.updateRenderState({baseLayer: glBaseLayer});\\n } else if (gl instanceof WebGLRenderingContext) {\\n const layerInit = {\\n antialias: true,\\n alpha: attributes.alpha,\\n depth: attributes.depth,\\n stencil: attributes.stencil,\\n framebufferScaleFactor\\n };\\n glBaseLayer = new XRWebGLLayer(session, gl, layerInit);\\n session.updateRenderState({layers: [glBaseLayer]});\\n } else {\\n isMultisample = attributes.antialias;\\n let depthFormat = null;\\n if (attributes.depth) {\\n clearStyle = gl.DEPTH_BUFFER_BIT;\\n if (attributes.stencil)\\n clearStyle |= gl.STENCIL_BUFFER_BIT;\\n depthStyle = attributes.stencil ? gl.DEPTH_STENCIL_ATTACHMENT : gl.DEPTH_ATTACHMENT;\\n depthFormat = attributes.stencil ? gl.DEPTH24_STENCIL8 : gl.DEPTH_COMPONENT24;\\n }\\n const projectionlayerInit = {\\n colorFormat: attributes.alpha ? gl.RGBA8 : gl.RGB8,\\n depthFormat,\\n scaleFactor: framebufferScaleFactor\\n };\\n glBinding = new XRWebGLBinding(session, gl);\\n glProjLayer = glBinding.createProjectionLayer(projectionlayerInit);\\n glFramebuffer = gl.createFramebuffer();\\n session.updateRenderState({layers: [glProjLayer]});\\n if (isMultisample) {\\n glMultisampledFramebuffer = gl.createFramebuffer();\\n glColorRenderbuffer = gl.createRenderbuffer();\\n gl.bindRenderbuffer(gl.RENDERBUFFER, glColorRenderbuffer);\\n gl.renderbufferStorageMultisample(gl.RENDERBUFFER, 4, gl.RGBA8, glProjLayer.textureWidth, glProjLayer.textureHeight);\\n state.bindFramebuffer(gl.FRAMEBUFFER, glMultisampledFramebuffer);\\n gl.framebufferRenderbuffer(gl.FRAMEBUFFER, gl.COLOR_ATTACHMENT0, gl.RENDERBUFFER, glColorRenderbuffer);\\n gl.bindRenderbuffer(gl.RENDERBUFFER, null);\\n if (depthFormat !== null) {\\n glDepthRenderbuffer = gl.createRenderbuffer();\\n gl.bindRenderbuffer(gl.RENDERBUFFER, glDepthRenderbuffer);\\n gl.renderbufferStorageMultisample(gl.RENDERBUFFER, 4, depthFormat, glProjLayer.textureWidth, glProjLayer.textureHeight);\\n gl.framebufferRenderbuffer(gl.FRAMEBUFFER, depthStyle, gl.RENDERBUFFER, glDepthRenderbuffer);\\n gl.bindRenderbuffer(gl.RENDERBUFFER, null);\\n }\\n state.bindFramebuffer(gl.FRAMEBUFFER, null);\\n }\\n }\\n referenceSpace = await session.requestReferenceSpace(referenceSpaceType);\\n animation.setContext(session);\\n animation.start();\\n scope.isPresenting = true;\\n scope.dispatchEvent({type: \\\\\\\"sessionstart\\\\\\\"});\\n }\\n };\\n function onInputSourcesChange(event) {\\n const inputSources = session.inputSources;\\n for (let i = 0; i < controllers.length; i++) {\\n inputSourcesMap.set(inputSources[i], controllers[i]);\\n }\\n for (let i = 0; i < event.removed.length; i++) {\\n const inputSource = event.removed[i];\\n const controller = inputSourcesMap.get(inputSource);\\n if (controller) {\\n controller.dispatchEvent({type: \\\\\\\"disconnected\\\\\\\", data: inputSource});\\n inputSourcesMap.delete(inputSource);\\n }\\n }\\n for (let i = 0; i < event.added.length; i++) {\\n const inputSource = event.added[i];\\n const controller = inputSourcesMap.get(inputSource);\\n if (controller) {\\n controller.dispatchEvent({type: \\\\\\\"connected\\\\\\\", data: inputSource});\\n }\\n }\\n }\\n const cameraLPos = new Vector3();\\n const cameraRPos = new Vector3();\\n function setProjectionFromUnion(camera, cameraL2, cameraR2) {\\n cameraLPos.setFromMatrixPosition(cameraL2.matrixWorld);\\n cameraRPos.setFromMatrixPosition(cameraR2.matrixWorld);\\n const ipd = cameraLPos.distanceTo(cameraRPos);\\n const projL = cameraL2.projectionMatrix.elements;\\n const projR = cameraR2.projectionMatrix.elements;\\n const near = projL[14] / (projL[10] - 1);\\n const far = projL[14] / (projL[10] + 1);\\n const topFov = (projL[9] + 1) / projL[5];\\n const bottomFov = (projL[9] - 1) / projL[5];\\n const leftFov = (projL[8] - 1) / projL[0];\\n const rightFov = (projR[8] + 1) / projR[0];\\n const left = near * leftFov;\\n const right = near * rightFov;\\n const zOffset = ipd / (-leftFov + rightFov);\\n const xOffset = zOffset * -leftFov;\\n cameraL2.matrixWorld.decompose(camera.position, camera.quaternion, camera.scale);\\n camera.translateX(xOffset);\\n camera.translateZ(zOffset);\\n camera.matrixWorld.compose(camera.position, camera.quaternion, camera.scale);\\n camera.matrixWorldInverse.copy(camera.matrixWorld).invert();\\n const near2 = near + zOffset;\\n const far2 = far + zOffset;\\n const left2 = left - xOffset;\\n const right2 = right + (ipd - xOffset);\\n const top2 = topFov * far / far2 * near2;\\n const bottom2 = bottomFov * far / far2 * near2;\\n camera.projectionMatrix.makePerspective(left2, right2, top2, bottom2, near2, far2);\\n }\\n function updateCamera(camera, parent) {\\n if (parent === null) {\\n camera.matrixWorld.copy(camera.matrix);\\n } else {\\n camera.matrixWorld.multiplyMatrices(parent.matrixWorld, camera.matrix);\\n }\\n camera.matrixWorldInverse.copy(camera.matrixWorld).invert();\\n }\\n this.updateCamera = function(camera) {\\n if (session === null)\\n return;\\n cameraVR.near = cameraR.near = cameraL.near = camera.near;\\n cameraVR.far = cameraR.far = cameraL.far = camera.far;\\n if (_currentDepthNear !== cameraVR.near || _currentDepthFar !== cameraVR.far) {\\n session.updateRenderState({\\n depthNear: cameraVR.near,\\n depthFar: cameraVR.far\\n });\\n _currentDepthNear = cameraVR.near;\\n _currentDepthFar = cameraVR.far;\\n }\\n const parent = camera.parent;\\n const cameras2 = cameraVR.cameras;\\n updateCamera(cameraVR, parent);\\n for (let i = 0; i < cameras2.length; i++) {\\n updateCamera(cameras2[i], parent);\\n }\\n cameraVR.matrixWorld.decompose(cameraVR.position, cameraVR.quaternion, cameraVR.scale);\\n camera.position.copy(cameraVR.position);\\n camera.quaternion.copy(cameraVR.quaternion);\\n camera.scale.copy(cameraVR.scale);\\n camera.matrix.copy(cameraVR.matrix);\\n camera.matrixWorld.copy(cameraVR.matrixWorld);\\n const children = camera.children;\\n for (let i = 0, l = children.length; i < l; i++) {\\n children[i].updateMatrixWorld(true);\\n }\\n if (cameras2.length === 2) {\\n setProjectionFromUnion(cameraVR, cameraL, cameraR);\\n } else {\\n cameraVR.projectionMatrix.copy(cameraL.projectionMatrix);\\n }\\n };\\n this.getCamera = function() {\\n return cameraVR;\\n };\\n this.getFoveation = function() {\\n if (glProjLayer !== null) {\\n return glProjLayer.fixedFoveation;\\n }\\n if (glBaseLayer !== null) {\\n return glBaseLayer.fixedFoveation;\\n }\\n return void 0;\\n };\\n this.setFoveation = function(foveation) {\\n if (glProjLayer !== null) {\\n glProjLayer.fixedFoveation = foveation;\\n }\\n if (glBaseLayer !== null && glBaseLayer.fixedFoveation !== void 0) {\\n glBaseLayer.fixedFoveation = foveation;\\n }\\n };\\n let onAnimationFrameCallback = null;\\n function onAnimationFrame(time, frame) {\\n pose = frame.getViewerPose(referenceSpace);\\n xrFrame = frame;\\n if (pose !== null) {\\n const views = pose.views;\\n if (glBaseLayer !== null) {\\n state.bindXRFramebuffer(glBaseLayer.framebuffer);\\n }\\n let cameraVRNeedsUpdate = false;\\n if (views.length !== cameraVR.cameras.length) {\\n cameraVR.cameras.length = 0;\\n cameraVRNeedsUpdate = true;\\n }\\n for (let i = 0; i < views.length; i++) {\\n const view = views[i];\\n let viewport = null;\\n if (glBaseLayer !== null) {\\n viewport = glBaseLayer.getViewport(view);\\n } else {\\n const glSubImage = glBinding.getViewSubImage(glProjLayer, view);\\n state.bindXRFramebuffer(glFramebuffer);\\n if (glSubImage.depthStencilTexture !== void 0) {\\n gl.framebufferTexture2D(gl.FRAMEBUFFER, depthStyle, gl.TEXTURE_2D, glSubImage.depthStencilTexture, 0);\\n }\\n gl.framebufferTexture2D(gl.FRAMEBUFFER, gl.COLOR_ATTACHMENT0, gl.TEXTURE_2D, glSubImage.colorTexture, 0);\\n viewport = glSubImage.viewport;\\n }\\n const camera = cameras[i];\\n camera.matrix.fromArray(view.transform.matrix);\\n camera.projectionMatrix.fromArray(view.projectionMatrix);\\n camera.viewport.set(viewport.x, viewport.y, viewport.width, viewport.height);\\n if (i === 0) {\\n cameraVR.matrix.copy(camera.matrix);\\n }\\n if (cameraVRNeedsUpdate === true) {\\n cameraVR.cameras.push(camera);\\n }\\n }\\n if (isMultisample) {\\n state.bindXRFramebuffer(glMultisampledFramebuffer);\\n if (clearStyle !== null)\\n gl.clear(clearStyle);\\n }\\n }\\n const inputSources = session.inputSources;\\n for (let i = 0; i < controllers.length; i++) {\\n const controller = controllers[i];\\n const inputSource = inputSources[i];\\n controller.update(inputSource, frame, referenceSpace);\\n }\\n if (onAnimationFrameCallback)\\n onAnimationFrameCallback(time, frame);\\n if (isMultisample) {\\n const width = glProjLayer.textureWidth;\\n const height = glProjLayer.textureHeight;\\n state.bindFramebuffer(gl.READ_FRAMEBUFFER, glMultisampledFramebuffer);\\n state.bindFramebuffer(gl.DRAW_FRAMEBUFFER, glFramebuffer);\\n gl.invalidateFramebuffer(gl.READ_FRAMEBUFFER, [depthStyle]);\\n gl.invalidateFramebuffer(gl.DRAW_FRAMEBUFFER, [depthStyle]);\\n gl.blitFramebuffer(0, 0, width, height, 0, 0, width, height, gl.COLOR_BUFFER_BIT, gl.NEAREST);\\n gl.invalidateFramebuffer(gl.READ_FRAMEBUFFER, [gl.COLOR_ATTACHMENT0]);\\n state.bindFramebuffer(gl.READ_FRAMEBUFFER, null);\\n state.bindFramebuffer(gl.DRAW_FRAMEBUFFER, null);\\n state.bindFramebuffer(gl.FRAMEBUFFER, glMultisampledFramebuffer);\\n }\\n xrFrame = null;\\n }\\n const animation = new WebGLAnimation();\\n animation.setAnimationLoop(onAnimationFrame);\\n this.setAnimationLoop = function(callback) {\\n onAnimationFrameCallback = callback;\\n };\\n this.dispose = function() {\\n };\\n }\\n};\\n\\n// ../../../node_modules/three/src/renderers/webgl/WebGLMaterials.js\\nfunction WebGLMaterials(properties) {\\n function refreshFogUniforms(uniforms, fog) {\\n uniforms.fogColor.value.copy(fog.color);\\n if (fog.isFog) {\\n uniforms.fogNear.value = fog.near;\\n uniforms.fogFar.value = fog.far;\\n } else if (fog.isFogExp2) {\\n uniforms.fogDensity.value = fog.density;\\n }\\n }\\n function refreshMaterialUniforms(uniforms, material, pixelRatio, height, transmissionRenderTarget) {\\n if (material.isMeshBasicMaterial) {\\n refreshUniformsCommon(uniforms, material);\\n } else if (material.isMeshLambertMaterial) {\\n refreshUniformsCommon(uniforms, material);\\n refreshUniformsLambert(uniforms, material);\\n } else if (material.isMeshToonMaterial) {\\n refreshUniformsCommon(uniforms, material);\\n refreshUniformsToon(uniforms, material);\\n } else if (material.isMeshPhongMaterial) {\\n refreshUniformsCommon(uniforms, material);\\n refreshUniformsPhong(uniforms, material);\\n } else if (material.isMeshStandardMaterial) {\\n refreshUniformsCommon(uniforms, material);\\n if (material.isMeshPhysicalMaterial) {\\n refreshUniformsPhysical(uniforms, material, transmissionRenderTarget);\\n } else {\\n refreshUniformsStandard(uniforms, material);\\n }\\n } else if (material.isMeshMatcapMaterial) {\\n refreshUniformsCommon(uniforms, material);\\n refreshUniformsMatcap(uniforms, material);\\n } else if (material.isMeshDepthMaterial) {\\n refreshUniformsCommon(uniforms, material);\\n refreshUniformsDepth(uniforms, material);\\n } else if (material.isMeshDistanceMaterial) {\\n refreshUniformsCommon(uniforms, material);\\n refreshUniformsDistance(uniforms, material);\\n } else if (material.isMeshNormalMaterial) {\\n refreshUniformsCommon(uniforms, material);\\n refreshUniformsNormal(uniforms, material);\\n } else if (material.isLineBasicMaterial) {\\n refreshUniformsLine(uniforms, material);\\n if (material.isLineDashedMaterial) {\\n refreshUniformsDash(uniforms, material);\\n }\\n } else if (material.isPointsMaterial) {\\n refreshUniformsPoints(uniforms, material, pixelRatio, height);\\n } else if (material.isSpriteMaterial) {\\n refreshUniformsSprites(uniforms, material);\\n } else if (material.isShadowMaterial) {\\n uniforms.color.value.copy(material.color);\\n uniforms.opacity.value = material.opacity;\\n } else if (material.isShaderMaterial) {\\n material.uniformsNeedUpdate = false;\\n }\\n }\\n function refreshUniformsCommon(uniforms, material) {\\n uniforms.opacity.value = material.opacity;\\n if (material.color) {\\n uniforms.diffuse.value.copy(material.color);\\n }\\n if (material.emissive) {\\n uniforms.emissive.value.copy(material.emissive).multiplyScalar(material.emissiveIntensity);\\n }\\n if (material.map) {\\n uniforms.map.value = material.map;\\n }\\n if (material.alphaMap) {\\n uniforms.alphaMap.value = material.alphaMap;\\n }\\n if (material.specularMap) {\\n uniforms.specularMap.value = material.specularMap;\\n }\\n if (material.alphaTest > 0) {\\n uniforms.alphaTest.value = material.alphaTest;\\n }\\n const envMap = properties.get(material).envMap;\\n if (envMap) {\\n uniforms.envMap.value = envMap;\\n uniforms.flipEnvMap.value = envMap.isCubeTexture && envMap.isRenderTargetTexture === false ? -1 : 1;\\n uniforms.reflectivity.value = material.reflectivity;\\n uniforms.ior.value = material.ior;\\n uniforms.refractionRatio.value = material.refractionRatio;\\n const maxMipLevel = properties.get(envMap).__maxMipLevel;\\n if (maxMipLevel !== void 0) {\\n uniforms.maxMipLevel.value = maxMipLevel;\\n }\\n }\\n if (material.lightMap) {\\n uniforms.lightMap.value = material.lightMap;\\n uniforms.lightMapIntensity.value = material.lightMapIntensity;\\n }\\n if (material.aoMap) {\\n uniforms.aoMap.value = material.aoMap;\\n uniforms.aoMapIntensity.value = material.aoMapIntensity;\\n }\\n let uvScaleMap;\\n if (material.map) {\\n uvScaleMap = material.map;\\n } else if (material.specularMap) {\\n uvScaleMap = material.specularMap;\\n } else if (material.displacementMap) {\\n uvScaleMap = material.displacementMap;\\n } else if (material.normalMap) {\\n uvScaleMap = material.normalMap;\\n } else if (material.bumpMap) {\\n uvScaleMap = material.bumpMap;\\n } else if (material.roughnessMap) {\\n uvScaleMap = material.roughnessMap;\\n } else if (material.metalnessMap) {\\n uvScaleMap = material.metalnessMap;\\n } else if (material.alphaMap) {\\n uvScaleMap = material.alphaMap;\\n } else if (material.emissiveMap) {\\n uvScaleMap = material.emissiveMap;\\n } else if (material.clearcoatMap) {\\n uvScaleMap = material.clearcoatMap;\\n } else if (material.clearcoatNormalMap) {\\n uvScaleMap = material.clearcoatNormalMap;\\n } else if (material.clearcoatRoughnessMap) {\\n uvScaleMap = material.clearcoatRoughnessMap;\\n } else if (material.specularIntensityMap) {\\n uvScaleMap = material.specularIntensityMap;\\n } else if (material.specularTintMap) {\\n uvScaleMap = material.specularTintMap;\\n } else if (material.transmissionMap) {\\n uvScaleMap = material.transmissionMap;\\n } else if (material.thicknessMap) {\\n uvScaleMap = material.thicknessMap;\\n }\\n if (uvScaleMap !== void 0) {\\n if (uvScaleMap.isWebGLRenderTarget) {\\n uvScaleMap = uvScaleMap.texture;\\n }\\n if (uvScaleMap.matrixAutoUpdate === true) {\\n uvScaleMap.updateMatrix();\\n }\\n uniforms.uvTransform.value.copy(uvScaleMap.matrix);\\n }\\n let uv2ScaleMap;\\n if (material.aoMap) {\\n uv2ScaleMap = material.aoMap;\\n } else if (material.lightMap) {\\n uv2ScaleMap = material.lightMap;\\n }\\n if (uv2ScaleMap !== void 0) {\\n if (uv2ScaleMap.isWebGLRenderTarget) {\\n uv2ScaleMap = uv2ScaleMap.texture;\\n }\\n if (uv2ScaleMap.matrixAutoUpdate === true) {\\n uv2ScaleMap.updateMatrix();\\n }\\n uniforms.uv2Transform.value.copy(uv2ScaleMap.matrix);\\n }\\n }\\n function refreshUniformsLine(uniforms, material) {\\n uniforms.diffuse.value.copy(material.color);\\n uniforms.opacity.value = material.opacity;\\n }\\n function refreshUniformsDash(uniforms, material) {\\n uniforms.dashSize.value = material.dashSize;\\n uniforms.totalSize.value = material.dashSize + material.gapSize;\\n uniforms.scale.value = material.scale;\\n }\\n function refreshUniformsPoints(uniforms, material, pixelRatio, height) {\\n uniforms.diffuse.value.copy(material.color);\\n uniforms.opacity.value = material.opacity;\\n uniforms.size.value = material.size * pixelRatio;\\n uniforms.scale.value = height * 0.5;\\n if (material.map) {\\n uniforms.map.value = material.map;\\n }\\n if (material.alphaMap) {\\n uniforms.alphaMap.value = material.alphaMap;\\n }\\n if (material.alphaTest > 0) {\\n uniforms.alphaTest.value = material.alphaTest;\\n }\\n let uvScaleMap;\\n if (material.map) {\\n uvScaleMap = material.map;\\n } else if (material.alphaMap) {\\n uvScaleMap = material.alphaMap;\\n }\\n if (uvScaleMap !== void 0) {\\n if (uvScaleMap.matrixAutoUpdate === true) {\\n uvScaleMap.updateMatrix();\\n }\\n uniforms.uvTransform.value.copy(uvScaleMap.matrix);\\n }\\n }\\n function refreshUniformsSprites(uniforms, material) {\\n uniforms.diffuse.value.copy(material.color);\\n uniforms.opacity.value = material.opacity;\\n uniforms.rotation.value = material.rotation;\\n if (material.map) {\\n uniforms.map.value = material.map;\\n }\\n if (material.alphaMap) {\\n uniforms.alphaMap.value = material.alphaMap;\\n }\\n if (material.alphaTest > 0) {\\n uniforms.alphaTest.value = material.alphaTest;\\n }\\n let uvScaleMap;\\n if (material.map) {\\n uvScaleMap = material.map;\\n } else if (material.alphaMap) {\\n uvScaleMap = material.alphaMap;\\n }\\n if (uvScaleMap !== void 0) {\\n if (uvScaleMap.matrixAutoUpdate === true) {\\n uvScaleMap.updateMatrix();\\n }\\n uniforms.uvTransform.value.copy(uvScaleMap.matrix);\\n }\\n }\\n function refreshUniformsLambert(uniforms, material) {\\n if (material.emissiveMap) {\\n uniforms.emissiveMap.value = material.emissiveMap;\\n }\\n }\\n function refreshUniformsPhong(uniforms, material) {\\n uniforms.specular.value.copy(material.specular);\\n uniforms.shininess.value = Math.max(material.shininess, 1e-4);\\n if (material.emissiveMap) {\\n uniforms.emissiveMap.value = material.emissiveMap;\\n }\\n if (material.bumpMap) {\\n uniforms.bumpMap.value = material.bumpMap;\\n uniforms.bumpScale.value = material.bumpScale;\\n if (material.side === BackSide)\\n uniforms.bumpScale.value *= -1;\\n }\\n if (material.normalMap) {\\n uniforms.normalMap.value = material.normalMap;\\n uniforms.normalScale.value.copy(material.normalScale);\\n if (material.side === BackSide)\\n uniforms.normalScale.value.negate();\\n }\\n if (material.displacementMap) {\\n uniforms.displacementMap.value = material.displacementMap;\\n uniforms.displacementScale.value = material.displacementScale;\\n uniforms.displacementBias.value = material.displacementBias;\\n }\\n }\\n function refreshUniformsToon(uniforms, material) {\\n if (material.gradientMap) {\\n uniforms.gradientMap.value = material.gradientMap;\\n }\\n if (material.emissiveMap) {\\n uniforms.emissiveMap.value = material.emissiveMap;\\n }\\n if (material.bumpMap) {\\n uniforms.bumpMap.value = material.bumpMap;\\n uniforms.bumpScale.value = material.bumpScale;\\n if (material.side === BackSide)\\n uniforms.bumpScale.value *= -1;\\n }\\n if (material.normalMap) {\\n uniforms.normalMap.value = material.normalMap;\\n uniforms.normalScale.value.copy(material.normalScale);\\n if (material.side === BackSide)\\n uniforms.normalScale.value.negate();\\n }\\n if (material.displacementMap) {\\n uniforms.displacementMap.value = material.displacementMap;\\n uniforms.displacementScale.value = material.displacementScale;\\n uniforms.displacementBias.value = material.displacementBias;\\n }\\n }\\n function refreshUniformsStandard(uniforms, material) {\\n uniforms.roughness.value = material.roughness;\\n uniforms.metalness.value = material.metalness;\\n if (material.roughnessMap) {\\n uniforms.roughnessMap.value = material.roughnessMap;\\n }\\n if (material.metalnessMap) {\\n uniforms.metalnessMap.value = material.metalnessMap;\\n }\\n if (material.emissiveMap) {\\n uniforms.emissiveMap.value = material.emissiveMap;\\n }\\n if (material.bumpMap) {\\n uniforms.bumpMap.value = material.bumpMap;\\n uniforms.bumpScale.value = material.bumpScale;\\n if (material.side === BackSide)\\n uniforms.bumpScale.value *= -1;\\n }\\n if (material.normalMap) {\\n uniforms.normalMap.value = material.normalMap;\\n uniforms.normalScale.value.copy(material.normalScale);\\n if (material.side === BackSide)\\n uniforms.normalScale.value.negate();\\n }\\n if (material.displacementMap) {\\n uniforms.displacementMap.value = material.displacementMap;\\n uniforms.displacementScale.value = material.displacementScale;\\n uniforms.displacementBias.value = material.displacementBias;\\n }\\n const envMap = properties.get(material).envMap;\\n if (envMap) {\\n uniforms.envMapIntensity.value = material.envMapIntensity;\\n }\\n }\\n function refreshUniformsPhysical(uniforms, material, transmissionRenderTarget) {\\n refreshUniformsStandard(uniforms, material);\\n uniforms.ior.value = material.ior;\\n if (material.sheen > 0) {\\n uniforms.sheenTint.value.copy(material.sheenTint).multiplyScalar(material.sheen);\\n uniforms.sheenRoughness.value = material.sheenRoughness;\\n }\\n if (material.clearcoat > 0) {\\n uniforms.clearcoat.value = material.clearcoat;\\n uniforms.clearcoatRoughness.value = material.clearcoatRoughness;\\n if (material.clearcoatMap) {\\n uniforms.clearcoatMap.value = material.clearcoatMap;\\n }\\n if (material.clearcoatRoughnessMap) {\\n uniforms.clearcoatRoughnessMap.value = material.clearcoatRoughnessMap;\\n }\\n if (material.clearcoatNormalMap) {\\n uniforms.clearcoatNormalScale.value.copy(material.clearcoatNormalScale);\\n uniforms.clearcoatNormalMap.value = material.clearcoatNormalMap;\\n if (material.side === BackSide) {\\n uniforms.clearcoatNormalScale.value.negate();\\n }\\n }\\n }\\n if (material.transmission > 0) {\\n uniforms.transmission.value = material.transmission;\\n uniforms.transmissionSamplerMap.value = transmissionRenderTarget.texture;\\n uniforms.transmissionSamplerSize.value.set(transmissionRenderTarget.width, transmissionRenderTarget.height);\\n if (material.transmissionMap) {\\n uniforms.transmissionMap.value = material.transmissionMap;\\n }\\n uniforms.thickness.value = material.thickness;\\n if (material.thicknessMap) {\\n uniforms.thicknessMap.value = material.thicknessMap;\\n }\\n uniforms.attenuationDistance.value = material.attenuationDistance;\\n uniforms.attenuationTint.value.copy(material.attenuationTint);\\n }\\n uniforms.specularIntensity.value = material.specularIntensity;\\n uniforms.specularTint.value.copy(material.specularTint);\\n if (material.specularIntensityMap) {\\n uniforms.specularIntensityMap.value = material.specularIntensityMap;\\n }\\n if (material.specularTintMap) {\\n uniforms.specularTintMap.value = material.specularTintMap;\\n }\\n }\\n function refreshUniformsMatcap(uniforms, material) {\\n if (material.matcap) {\\n uniforms.matcap.value = material.matcap;\\n }\\n if (material.bumpMap) {\\n uniforms.bumpMap.value = material.bumpMap;\\n uniforms.bumpScale.value = material.bumpScale;\\n if (material.side === BackSide)\\n uniforms.bumpScale.value *= -1;\\n }\\n if (material.normalMap) {\\n uniforms.normalMap.value = material.normalMap;\\n uniforms.normalScale.value.copy(material.normalScale);\\n if (material.side === BackSide)\\n uniforms.normalScale.value.negate();\\n }\\n if (material.displacementMap) {\\n uniforms.displacementMap.value = material.displacementMap;\\n uniforms.displacementScale.value = material.displacementScale;\\n uniforms.displacementBias.value = material.displacementBias;\\n }\\n }\\n function refreshUniformsDepth(uniforms, material) {\\n if (material.displacementMap) {\\n uniforms.displacementMap.value = material.displacementMap;\\n uniforms.displacementScale.value = material.displacementScale;\\n uniforms.displacementBias.value = material.displacementBias;\\n }\\n }\\n function refreshUniformsDistance(uniforms, material) {\\n if (material.displacementMap) {\\n uniforms.displacementMap.value = material.displacementMap;\\n uniforms.displacementScale.value = material.displacementScale;\\n uniforms.displacementBias.value = material.displacementBias;\\n }\\n uniforms.referencePosition.value.copy(material.referencePosition);\\n uniforms.nearDistance.value = material.nearDistance;\\n uniforms.farDistance.value = material.farDistance;\\n }\\n function refreshUniformsNormal(uniforms, material) {\\n if (material.bumpMap) {\\n uniforms.bumpMap.value = material.bumpMap;\\n uniforms.bumpScale.value = material.bumpScale;\\n if (material.side === BackSide)\\n uniforms.bumpScale.value *= -1;\\n }\\n if (material.normalMap) {\\n uniforms.normalMap.value = material.normalMap;\\n uniforms.normalScale.value.copy(material.normalScale);\\n if (material.side === BackSide)\\n uniforms.normalScale.value.negate();\\n }\\n if (material.displacementMap) {\\n uniforms.displacementMap.value = material.displacementMap;\\n uniforms.displacementScale.value = material.displacementScale;\\n uniforms.displacementBias.value = material.displacementBias;\\n }\\n }\\n return {\\n refreshFogUniforms,\\n refreshMaterialUniforms\\n };\\n}\\n\\n// ../../../node_modules/three/src/renderers/WebGLRenderer.js\\nfunction createCanvasElement() {\\n const canvas = createElementNS(\\\\\\\"canvas\\\\\\\");\\n canvas.style.display = \\\\\\\"block\\\\\\\";\\n return canvas;\\n}\\nfunction WebGLRenderer(parameters = {}) {\\n const _canvas2 = parameters.canvas !== void 0 ? parameters.canvas : createCanvasElement(), _context2 = parameters.context !== void 0 ? parameters.context : null, _alpha = parameters.alpha !== void 0 ? parameters.alpha : false, _depth = parameters.depth !== void 0 ? parameters.depth : true, _stencil = parameters.stencil !== void 0 ? parameters.stencil : true, _antialias = parameters.antialias !== void 0 ? parameters.antialias : false, _premultipliedAlpha = parameters.premultipliedAlpha !== void 0 ? parameters.premultipliedAlpha : true, _preserveDrawingBuffer = parameters.preserveDrawingBuffer !== void 0 ? parameters.preserveDrawingBuffer : false, _powerPreference = parameters.powerPreference !== void 0 ? parameters.powerPreference : \\\\\\\"default\\\\\\\", _failIfMajorPerformanceCaveat = parameters.failIfMajorPerformanceCaveat !== void 0 ? parameters.failIfMajorPerformanceCaveat : false;\\n let currentRenderList = null;\\n let currentRenderState = null;\\n const renderListStack = [];\\n const renderStateStack = [];\\n this.domElement = _canvas2;\\n this.debug = {\\n checkShaderErrors: true\\n };\\n this.autoClear = true;\\n this.autoClearColor = true;\\n this.autoClearDepth = true;\\n this.autoClearStencil = true;\\n this.sortObjects = true;\\n this.clippingPlanes = [];\\n this.localClippingEnabled = false;\\n this.gammaFactor = 2;\\n this.outputEncoding = LinearEncoding;\\n this.physicallyCorrectLights = false;\\n this.toneMapping = NoToneMapping;\\n this.toneMappingExposure = 1;\\n const _this = this;\\n let _isContextLost = false;\\n let _currentActiveCubeFace = 0;\\n let _currentActiveMipmapLevel = 0;\\n let _currentRenderTarget = null;\\n let _currentMaterialId = -1;\\n let _currentCamera = null;\\n const _currentViewport = new Vector4();\\n const _currentScissor = new Vector4();\\n let _currentScissorTest = null;\\n let _width = _canvas2.width;\\n let _height = _canvas2.height;\\n let _pixelRatio = 1;\\n let _opaqueSort = null;\\n let _transparentSort = null;\\n const _viewport = new Vector4(0, 0, _width, _height);\\n const _scissor = new Vector4(0, 0, _width, _height);\\n let _scissorTest = false;\\n const _currentDrawBuffers = [];\\n const _frustum = new Frustum();\\n let _clippingEnabled = false;\\n let _localClippingEnabled = false;\\n let _transmissionRenderTarget = null;\\n const _projScreenMatrix = new Matrix4();\\n const _vector32 = new Vector3();\\n const _emptyScene = {background: null, fog: null, environment: null, overrideMaterial: null, isScene: true};\\n function getTargetPixelRatio() {\\n return _currentRenderTarget === null ? _pixelRatio : 1;\\n }\\n let _gl = _context2;\\n function getContext(contextNames, contextAttributes) {\\n for (let i = 0; i < contextNames.length; i++) {\\n const contextName = contextNames[i];\\n const context = _canvas2.getContext(contextName, contextAttributes);\\n if (context !== null)\\n return context;\\n }\\n return null;\\n }\\n try {\\n const contextAttributes = {\\n alpha: _alpha,\\n depth: _depth,\\n stencil: _stencil,\\n antialias: _antialias,\\n premultipliedAlpha: _premultipliedAlpha,\\n preserveDrawingBuffer: _preserveDrawingBuffer,\\n powerPreference: _powerPreference,\\n failIfMajorPerformanceCaveat: _failIfMajorPerformanceCaveat\\n };\\n _canvas2.addEventListener(\\\\\\\"webglcontextlost\\\\\\\", onContextLost, false);\\n _canvas2.addEventListener(\\\\\\\"webglcontextrestored\\\\\\\", onContextRestore, false);\\n if (_gl === null) {\\n const contextNames = [\\\\\\\"webgl2\\\\\\\", \\\\\\\"webgl\\\\\\\", \\\\\\\"experimental-webgl\\\\\\\"];\\n if (_this.isWebGL1Renderer === true) {\\n contextNames.shift();\\n }\\n _gl = getContext(contextNames, contextAttributes);\\n if (_gl === null) {\\n if (getContext(contextNames)) {\\n throw new Error(\\\\\\\"Error creating WebGL context with your selected attributes.\\\\\\\");\\n } else {\\n throw new Error(\\\\\\\"Error creating WebGL context.\\\\\\\");\\n }\\n }\\n }\\n if (_gl.getShaderPrecisionFormat === void 0) {\\n _gl.getShaderPrecisionFormat = function() {\\n return {rangeMin: 1, rangeMax: 1, precision: 1};\\n };\\n }\\n } catch (error) {\\n console.error(\\\\\\\"THREE.WebGLRenderer: \\\\\\\" + error.message);\\n throw error;\\n }\\n let extensions, capabilities, state, info;\\n let properties, textures, cubemaps, cubeuvmaps, attributes, geometries, objects;\\n let programCache, materials2, renderLists, renderStates, clipping, shadowMap;\\n let background2, morphtargets, bufferRenderer, indexedBufferRenderer;\\n let utils, bindingStates;\\n function initGLContext() {\\n extensions = new WebGLExtensions(_gl);\\n capabilities = new WebGLCapabilities(_gl, extensions, parameters);\\n extensions.init(capabilities);\\n utils = new WebGLUtils(_gl, extensions, capabilities);\\n state = new WebGLState(_gl, extensions, capabilities);\\n _currentDrawBuffers[0] = _gl.BACK;\\n info = new WebGLInfo(_gl);\\n properties = new WebGLProperties();\\n textures = new WebGLTextures(_gl, extensions, state, properties, capabilities, utils, info);\\n cubemaps = new WebGLCubeMaps(_this);\\n cubeuvmaps = new WebGLCubeUVMaps(_this);\\n attributes = new WebGLAttributes(_gl, capabilities);\\n bindingStates = new WebGLBindingStates(_gl, extensions, attributes, capabilities);\\n geometries = new WebGLGeometries(_gl, attributes, info, bindingStates);\\n objects = new WebGLObjects(_gl, geometries, attributes, info);\\n morphtargets = new WebGLMorphtargets(_gl, capabilities, textures);\\n clipping = new WebGLClipping(properties);\\n programCache = new WebGLPrograms(_this, cubemaps, cubeuvmaps, extensions, capabilities, bindingStates, clipping);\\n materials2 = new WebGLMaterials(properties);\\n renderLists = new WebGLRenderLists(properties);\\n renderStates = new WebGLRenderStates(extensions, capabilities);\\n background2 = new WebGLBackground(_this, cubemaps, state, objects, _premultipliedAlpha);\\n shadowMap = new WebGLShadowMap(_this, objects, capabilities);\\n bufferRenderer = new WebGLBufferRenderer(_gl, extensions, info, capabilities);\\n indexedBufferRenderer = new WebGLIndexedBufferRenderer(_gl, extensions, info, capabilities);\\n info.programs = programCache.programs;\\n _this.capabilities = capabilities;\\n _this.extensions = extensions;\\n _this.properties = properties;\\n _this.renderLists = renderLists;\\n _this.shadowMap = shadowMap;\\n _this.state = state;\\n _this.info = info;\\n }\\n initGLContext();\\n const xr = new WebXRManager(_this, _gl);\\n this.xr = xr;\\n this.getContext = function() {\\n return _gl;\\n };\\n this.getContextAttributes = function() {\\n return _gl.getContextAttributes();\\n };\\n this.forceContextLoss = function() {\\n const extension = extensions.get(\\\\\\\"WEBGL_lose_context\\\\\\\");\\n if (extension)\\n extension.loseContext();\\n };\\n this.forceContextRestore = function() {\\n const extension = extensions.get(\\\\\\\"WEBGL_lose_context\\\\\\\");\\n if (extension)\\n extension.restoreContext();\\n };\\n this.getPixelRatio = function() {\\n return _pixelRatio;\\n };\\n this.setPixelRatio = function(value) {\\n if (value === void 0)\\n return;\\n _pixelRatio = value;\\n this.setSize(_width, _height, false);\\n };\\n this.getSize = function(target) {\\n return target.set(_width, _height);\\n };\\n this.setSize = function(width, height, updateStyle) {\\n if (xr.isPresenting) {\\n console.warn(\\\\\\\"THREE.WebGLRenderer: Can't change size while VR device is presenting.\\\\\\\");\\n return;\\n }\\n _width = width;\\n _height = height;\\n _canvas2.width = Math.floor(width * _pixelRatio);\\n _canvas2.height = Math.floor(height * _pixelRatio);\\n if (updateStyle !== false) {\\n _canvas2.style.width = width + \\\\\\\"px\\\\\\\";\\n _canvas2.style.height = height + \\\\\\\"px\\\\\\\";\\n }\\n this.setViewport(0, 0, width, height);\\n };\\n this.getDrawingBufferSize = function(target) {\\n return target.set(_width * _pixelRatio, _height * _pixelRatio).floor();\\n };\\n this.setDrawingBufferSize = function(width, height, pixelRatio) {\\n _width = width;\\n _height = height;\\n _pixelRatio = pixelRatio;\\n _canvas2.width = Math.floor(width * pixelRatio);\\n _canvas2.height = Math.floor(height * pixelRatio);\\n this.setViewport(0, 0, width, height);\\n };\\n this.getCurrentViewport = function(target) {\\n return target.copy(_currentViewport);\\n };\\n this.getViewport = function(target) {\\n return target.copy(_viewport);\\n };\\n this.setViewport = function(x, y, width, height) {\\n if (x.isVector4) {\\n _viewport.set(x.x, x.y, x.z, x.w);\\n } else {\\n _viewport.set(x, y, width, height);\\n }\\n state.viewport(_currentViewport.copy(_viewport).multiplyScalar(_pixelRatio).floor());\\n };\\n this.getScissor = function(target) {\\n return target.copy(_scissor);\\n };\\n this.setScissor = function(x, y, width, height) {\\n if (x.isVector4) {\\n _scissor.set(x.x, x.y, x.z, x.w);\\n } else {\\n _scissor.set(x, y, width, height);\\n }\\n state.scissor(_currentScissor.copy(_scissor).multiplyScalar(_pixelRatio).floor());\\n };\\n this.getScissorTest = function() {\\n return _scissorTest;\\n };\\n this.setScissorTest = function(boolean) {\\n state.setScissorTest(_scissorTest = boolean);\\n };\\n this.setOpaqueSort = function(method) {\\n _opaqueSort = method;\\n };\\n this.setTransparentSort = function(method) {\\n _transparentSort = method;\\n };\\n this.getClearColor = function(target) {\\n return target.copy(background2.getClearColor());\\n };\\n this.setClearColor = function() {\\n background2.setClearColor.apply(background2, arguments);\\n };\\n this.getClearAlpha = function() {\\n return background2.getClearAlpha();\\n };\\n this.setClearAlpha = function() {\\n background2.setClearAlpha.apply(background2, arguments);\\n };\\n this.clear = function(color, depth2, stencil) {\\n let bits = 0;\\n if (color === void 0 || color)\\n bits |= _gl.COLOR_BUFFER_BIT;\\n if (depth2 === void 0 || depth2)\\n bits |= _gl.DEPTH_BUFFER_BIT;\\n if (stencil === void 0 || stencil)\\n bits |= _gl.STENCIL_BUFFER_BIT;\\n _gl.clear(bits);\\n };\\n this.clearColor = function() {\\n this.clear(true, false, false);\\n };\\n this.clearDepth = function() {\\n this.clear(false, true, false);\\n };\\n this.clearStencil = function() {\\n this.clear(false, false, true);\\n };\\n this.dispose = function() {\\n _canvas2.removeEventListener(\\\\\\\"webglcontextlost\\\\\\\", onContextLost, false);\\n _canvas2.removeEventListener(\\\\\\\"webglcontextrestored\\\\\\\", onContextRestore, false);\\n renderLists.dispose();\\n renderStates.dispose();\\n properties.dispose();\\n cubemaps.dispose();\\n cubeuvmaps.dispose();\\n objects.dispose();\\n bindingStates.dispose();\\n xr.dispose();\\n xr.removeEventListener(\\\\\\\"sessionstart\\\\\\\", onXRSessionStart);\\n xr.removeEventListener(\\\\\\\"sessionend\\\\\\\", onXRSessionEnd);\\n if (_transmissionRenderTarget) {\\n _transmissionRenderTarget.dispose();\\n _transmissionRenderTarget = null;\\n }\\n animation.stop();\\n };\\n function onContextLost(event) {\\n event.preventDefault();\\n console.log(\\\\\\\"THREE.WebGLRenderer: Context Lost.\\\\\\\");\\n _isContextLost = true;\\n }\\n function onContextRestore() {\\n console.log(\\\\\\\"THREE.WebGLRenderer: Context Restored.\\\\\\\");\\n _isContextLost = false;\\n const infoAutoReset = info.autoReset;\\n const shadowMapEnabled = shadowMap.enabled;\\n const shadowMapAutoUpdate = shadowMap.autoUpdate;\\n const shadowMapNeedsUpdate = shadowMap.needsUpdate;\\n const shadowMapType = shadowMap.type;\\n initGLContext();\\n info.autoReset = infoAutoReset;\\n shadowMap.enabled = shadowMapEnabled;\\n shadowMap.autoUpdate = shadowMapAutoUpdate;\\n shadowMap.needsUpdate = shadowMapNeedsUpdate;\\n shadowMap.type = shadowMapType;\\n }\\n function onMaterialDispose(event) {\\n const material = event.target;\\n material.removeEventListener(\\\\\\\"dispose\\\\\\\", onMaterialDispose);\\n deallocateMaterial(material);\\n }\\n function deallocateMaterial(material) {\\n releaseMaterialProgramReferences(material);\\n properties.remove(material);\\n }\\n function releaseMaterialProgramReferences(material) {\\n const programs = properties.get(material).programs;\\n if (programs !== void 0) {\\n programs.forEach(function(program) {\\n programCache.releaseProgram(program);\\n });\\n }\\n }\\n function renderObjectImmediate(object, program) {\\n object.render(function(object2) {\\n _this.renderBufferImmediate(object2, program);\\n });\\n }\\n this.renderBufferImmediate = function(object, program) {\\n bindingStates.initAttributes();\\n const buffers = properties.get(object);\\n if (object.hasPositions && !buffers.position)\\n buffers.position = _gl.createBuffer();\\n if (object.hasNormals && !buffers.normal)\\n buffers.normal = _gl.createBuffer();\\n if (object.hasUvs && !buffers.uv)\\n buffers.uv = _gl.createBuffer();\\n if (object.hasColors && !buffers.color)\\n buffers.color = _gl.createBuffer();\\n const programAttributes = program.getAttributes();\\n if (object.hasPositions) {\\n _gl.bindBuffer(_gl.ARRAY_BUFFER, buffers.position);\\n _gl.bufferData(_gl.ARRAY_BUFFER, object.positionArray, _gl.DYNAMIC_DRAW);\\n bindingStates.enableAttribute(programAttributes.position.location);\\n _gl.vertexAttribPointer(programAttributes.position.location, 3, _gl.FLOAT, false, 0, 0);\\n }\\n if (object.hasNormals) {\\n _gl.bindBuffer(_gl.ARRAY_BUFFER, buffers.normal);\\n _gl.bufferData(_gl.ARRAY_BUFFER, object.normalArray, _gl.DYNAMIC_DRAW);\\n bindingStates.enableAttribute(programAttributes.normal.location);\\n _gl.vertexAttribPointer(programAttributes.normal.location, 3, _gl.FLOAT, false, 0, 0);\\n }\\n if (object.hasUvs) {\\n _gl.bindBuffer(_gl.ARRAY_BUFFER, buffers.uv);\\n _gl.bufferData(_gl.ARRAY_BUFFER, object.uvArray, _gl.DYNAMIC_DRAW);\\n bindingStates.enableAttribute(programAttributes.uv.location);\\n _gl.vertexAttribPointer(programAttributes.uv.location, 2, _gl.FLOAT, false, 0, 0);\\n }\\n if (object.hasColors) {\\n _gl.bindBuffer(_gl.ARRAY_BUFFER, buffers.color);\\n _gl.bufferData(_gl.ARRAY_BUFFER, object.colorArray, _gl.DYNAMIC_DRAW);\\n bindingStates.enableAttribute(programAttributes.color.location);\\n _gl.vertexAttribPointer(programAttributes.color.location, 3, _gl.FLOAT, false, 0, 0);\\n }\\n bindingStates.disableUnusedAttributes();\\n _gl.drawArrays(_gl.TRIANGLES, 0, object.count);\\n object.count = 0;\\n };\\n this.renderBufferDirect = function(camera, scene, geometry, material, object, group) {\\n if (scene === null)\\n scene = _emptyScene;\\n const frontFaceCW = object.isMesh && object.matrixWorld.determinant() < 0;\\n const program = setProgram(camera, scene, geometry, material, object);\\n state.setMaterial(material, frontFaceCW);\\n let index = geometry.index;\\n const position = geometry.attributes.position;\\n if (index === null) {\\n if (position === void 0 || position.count === 0)\\n return;\\n } else if (index.count === 0) {\\n return;\\n }\\n let rangeFactor = 1;\\n if (material.wireframe === true) {\\n index = geometries.getWireframeAttribute(geometry);\\n rangeFactor = 2;\\n }\\n bindingStates.setup(object, material, program, geometry, index);\\n let attribute;\\n let renderer = bufferRenderer;\\n if (index !== null) {\\n attribute = attributes.get(index);\\n renderer = indexedBufferRenderer;\\n renderer.setIndex(attribute);\\n }\\n const dataCount = index !== null ? index.count : position.count;\\n const rangeStart = geometry.drawRange.start * rangeFactor;\\n const rangeCount = geometry.drawRange.count * rangeFactor;\\n const groupStart = group !== null ? group.start * rangeFactor : 0;\\n const groupCount = group !== null ? group.count * rangeFactor : Infinity;\\n const drawStart = Math.max(rangeStart, groupStart);\\n const drawEnd = Math.min(dataCount, rangeStart + rangeCount, groupStart + groupCount) - 1;\\n const drawCount = Math.max(0, drawEnd - drawStart + 1);\\n if (drawCount === 0)\\n return;\\n if (object.isMesh) {\\n if (material.wireframe === true) {\\n state.setLineWidth(material.wireframeLinewidth * getTargetPixelRatio());\\n renderer.setMode(_gl.LINES);\\n } else {\\n renderer.setMode(_gl.TRIANGLES);\\n }\\n } else if (object.isLine) {\\n let lineWidth = material.linewidth;\\n if (lineWidth === void 0)\\n lineWidth = 1;\\n state.setLineWidth(lineWidth * getTargetPixelRatio());\\n if (object.isLineSegments) {\\n renderer.setMode(_gl.LINES);\\n } else if (object.isLineLoop) {\\n renderer.setMode(_gl.LINE_LOOP);\\n } else {\\n renderer.setMode(_gl.LINE_STRIP);\\n }\\n } else if (object.isPoints) {\\n renderer.setMode(_gl.POINTS);\\n } else if (object.isSprite) {\\n renderer.setMode(_gl.TRIANGLES);\\n }\\n if (object.isInstancedMesh) {\\n renderer.renderInstances(drawStart, drawCount, object.count);\\n } else if (geometry.isInstancedBufferGeometry) {\\n const instanceCount = Math.min(geometry.instanceCount, geometry._maxInstanceCount);\\n renderer.renderInstances(drawStart, drawCount, instanceCount);\\n } else {\\n renderer.render(drawStart, drawCount);\\n }\\n };\\n this.compile = function(scene, camera) {\\n currentRenderState = renderStates.get(scene);\\n currentRenderState.init();\\n renderStateStack.push(currentRenderState);\\n scene.traverseVisible(function(object) {\\n if (object.isLight && object.layers.test(camera.layers)) {\\n currentRenderState.pushLight(object);\\n if (object.castShadow) {\\n currentRenderState.pushShadow(object);\\n }\\n }\\n });\\n currentRenderState.setupLights(_this.physicallyCorrectLights);\\n scene.traverse(function(object) {\\n const material = object.material;\\n if (material) {\\n if (Array.isArray(material)) {\\n for (let i = 0; i < material.length; i++) {\\n const material2 = material[i];\\n getProgram(material2, scene, object);\\n }\\n } else {\\n getProgram(material, scene, object);\\n }\\n }\\n });\\n renderStateStack.pop();\\n currentRenderState = null;\\n };\\n let onAnimationFrameCallback = null;\\n function onAnimationFrame(time) {\\n if (onAnimationFrameCallback)\\n onAnimationFrameCallback(time);\\n }\\n function onXRSessionStart() {\\n animation.stop();\\n }\\n function onXRSessionEnd() {\\n animation.start();\\n }\\n const animation = new WebGLAnimation();\\n animation.setAnimationLoop(onAnimationFrame);\\n if (typeof window !== \\\\\\\"undefined\\\\\\\")\\n animation.setContext(window);\\n this.setAnimationLoop = function(callback) {\\n onAnimationFrameCallback = callback;\\n xr.setAnimationLoop(callback);\\n callback === null ? animation.stop() : animation.start();\\n };\\n xr.addEventListener(\\\\\\\"sessionstart\\\\\\\", onXRSessionStart);\\n xr.addEventListener(\\\\\\\"sessionend\\\\\\\", onXRSessionEnd);\\n this.render = function(scene, camera) {\\n if (camera !== void 0 && camera.isCamera !== true) {\\n console.error(\\\\\\\"THREE.WebGLRenderer.render: camera is not an instance of THREE.Camera.\\\\\\\");\\n return;\\n }\\n if (_isContextLost === true)\\n return;\\n if (scene.autoUpdate === true)\\n scene.updateMatrixWorld();\\n if (camera.parent === null)\\n camera.updateMatrixWorld();\\n if (xr.enabled === true && xr.isPresenting === true) {\\n if (xr.cameraAutoUpdate === true)\\n xr.updateCamera(camera);\\n camera = xr.getCamera();\\n }\\n if (scene.isScene === true)\\n scene.onBeforeRender(_this, scene, camera, _currentRenderTarget);\\n currentRenderState = renderStates.get(scene, renderStateStack.length);\\n currentRenderState.init();\\n renderStateStack.push(currentRenderState);\\n _projScreenMatrix.multiplyMatrices(camera.projectionMatrix, camera.matrixWorldInverse);\\n _frustum.setFromProjectionMatrix(_projScreenMatrix);\\n _localClippingEnabled = this.localClippingEnabled;\\n _clippingEnabled = clipping.init(this.clippingPlanes, _localClippingEnabled, camera);\\n currentRenderList = renderLists.get(scene, renderListStack.length);\\n currentRenderList.init();\\n renderListStack.push(currentRenderList);\\n projectObject(scene, camera, 0, _this.sortObjects);\\n currentRenderList.finish();\\n if (_this.sortObjects === true) {\\n currentRenderList.sort(_opaqueSort, _transparentSort);\\n }\\n if (_clippingEnabled === true)\\n clipping.beginShadows();\\n const shadowsArray = currentRenderState.state.shadowsArray;\\n shadowMap.render(shadowsArray, scene, camera);\\n if (_clippingEnabled === true)\\n clipping.endShadows();\\n if (this.info.autoReset === true)\\n this.info.reset();\\n background2.render(currentRenderList, scene);\\n currentRenderState.setupLights(_this.physicallyCorrectLights);\\n if (camera.isArrayCamera) {\\n const cameras = camera.cameras;\\n for (let i = 0, l = cameras.length; i < l; i++) {\\n const camera2 = cameras[i];\\n renderScene(currentRenderList, scene, camera2, camera2.viewport);\\n }\\n } else {\\n renderScene(currentRenderList, scene, camera);\\n }\\n if (_currentRenderTarget !== null) {\\n textures.updateMultisampleRenderTarget(_currentRenderTarget);\\n textures.updateRenderTargetMipmap(_currentRenderTarget);\\n }\\n if (scene.isScene === true)\\n scene.onAfterRender(_this, scene, camera);\\n state.buffers.depth.setTest(true);\\n state.buffers.depth.setMask(true);\\n state.buffers.color.setMask(true);\\n state.setPolygonOffset(false);\\n bindingStates.resetDefaultState();\\n _currentMaterialId = -1;\\n _currentCamera = null;\\n renderStateStack.pop();\\n if (renderStateStack.length > 0) {\\n currentRenderState = renderStateStack[renderStateStack.length - 1];\\n } else {\\n currentRenderState = null;\\n }\\n renderListStack.pop();\\n if (renderListStack.length > 0) {\\n currentRenderList = renderListStack[renderListStack.length - 1];\\n } else {\\n currentRenderList = null;\\n }\\n };\\n function projectObject(object, camera, groupOrder, sortObjects) {\\n if (object.visible === false)\\n return;\\n const visible = object.layers.test(camera.layers);\\n if (visible) {\\n if (object.isGroup) {\\n groupOrder = object.renderOrder;\\n } else if (object.isLOD) {\\n if (object.autoUpdate === true)\\n object.update(camera);\\n } else if (object.isLight) {\\n currentRenderState.pushLight(object);\\n if (object.castShadow) {\\n currentRenderState.pushShadow(object);\\n }\\n } else if (object.isSprite) {\\n if (!object.frustumCulled || _frustum.intersectsSprite(object)) {\\n if (sortObjects) {\\n _vector32.setFromMatrixPosition(object.matrixWorld).applyMatrix4(_projScreenMatrix);\\n }\\n const geometry = objects.update(object);\\n const material = object.material;\\n if (material.visible) {\\n currentRenderList.push(object, geometry, material, groupOrder, _vector32.z, null);\\n }\\n }\\n } else if (object.isImmediateRenderObject) {\\n if (sortObjects) {\\n _vector32.setFromMatrixPosition(object.matrixWorld).applyMatrix4(_projScreenMatrix);\\n }\\n currentRenderList.push(object, null, object.material, groupOrder, _vector32.z, null);\\n } else if (object.isMesh || object.isLine || object.isPoints) {\\n if (object.isSkinnedMesh) {\\n if (object.skeleton.frame !== info.render.frame) {\\n object.skeleton.update();\\n object.skeleton.frame = info.render.frame;\\n }\\n }\\n if (!object.frustumCulled || _frustum.intersectsObject(object)) {\\n if (sortObjects) {\\n _vector32.setFromMatrixPosition(object.matrixWorld).applyMatrix4(_projScreenMatrix);\\n }\\n const geometry = objects.update(object);\\n const material = object.material;\\n if (Array.isArray(material)) {\\n const groups = geometry.groups;\\n for (let i = 0, l = groups.length; i < l; i++) {\\n const group = groups[i];\\n const groupMaterial = material[group.materialIndex];\\n if (groupMaterial && groupMaterial.visible) {\\n currentRenderList.push(object, geometry, groupMaterial, groupOrder, _vector32.z, group);\\n }\\n }\\n } else if (material.visible) {\\n currentRenderList.push(object, geometry, material, groupOrder, _vector32.z, null);\\n }\\n }\\n }\\n }\\n const children = object.children;\\n for (let i = 0, l = children.length; i < l; i++) {\\n projectObject(children[i], camera, groupOrder, sortObjects);\\n }\\n }\\n function renderScene(currentRenderList2, scene, camera, viewport) {\\n const opaqueObjects = currentRenderList2.opaque;\\n const transmissiveObjects = currentRenderList2.transmissive;\\n const transparentObjects = currentRenderList2.transparent;\\n currentRenderState.setupLightsView(camera);\\n if (transmissiveObjects.length > 0)\\n renderTransmissionPass(opaqueObjects, scene, camera);\\n if (viewport)\\n state.viewport(_currentViewport.copy(viewport));\\n if (opaqueObjects.length > 0)\\n renderObjects(opaqueObjects, scene, camera);\\n if (transmissiveObjects.length > 0)\\n renderObjects(transmissiveObjects, scene, camera);\\n if (transparentObjects.length > 0)\\n renderObjects(transparentObjects, scene, camera);\\n }\\n function renderTransmissionPass(opaqueObjects, scene, camera) {\\n if (_transmissionRenderTarget === null) {\\n const needsAntialias = _antialias === true && capabilities.isWebGL2 === true;\\n const renderTargetType = needsAntialias ? WebGLMultisampleRenderTarget : WebGLRenderTarget;\\n _transmissionRenderTarget = new renderTargetType(1024, 1024, {\\n generateMipmaps: true,\\n type: utils.convert(HalfFloatType) !== null ? HalfFloatType : UnsignedByteType,\\n minFilter: LinearMipmapLinearFilter,\\n magFilter: NearestFilter,\\n wrapS: ClampToEdgeWrapping,\\n wrapT: ClampToEdgeWrapping\\n });\\n }\\n const currentRenderTarget = _this.getRenderTarget();\\n _this.setRenderTarget(_transmissionRenderTarget);\\n _this.clear();\\n const currentToneMapping = _this.toneMapping;\\n _this.toneMapping = NoToneMapping;\\n renderObjects(opaqueObjects, scene, camera);\\n _this.toneMapping = currentToneMapping;\\n textures.updateMultisampleRenderTarget(_transmissionRenderTarget);\\n textures.updateRenderTargetMipmap(_transmissionRenderTarget);\\n _this.setRenderTarget(currentRenderTarget);\\n }\\n function renderObjects(renderList, scene, camera) {\\n const overrideMaterial = scene.isScene === true ? scene.overrideMaterial : null;\\n for (let i = 0, l = renderList.length; i < l; i++) {\\n const renderItem = renderList[i];\\n const object = renderItem.object;\\n const geometry = renderItem.geometry;\\n const material = overrideMaterial === null ? renderItem.material : overrideMaterial;\\n const group = renderItem.group;\\n if (object.layers.test(camera.layers)) {\\n renderObject(object, scene, camera, geometry, material, group);\\n }\\n }\\n }\\n function renderObject(object, scene, camera, geometry, material, group) {\\n object.onBeforeRender(_this, scene, camera, geometry, material, group);\\n object.modelViewMatrix.multiplyMatrices(camera.matrixWorldInverse, object.matrixWorld);\\n object.normalMatrix.getNormalMatrix(object.modelViewMatrix);\\n material.onBeforeRender(_this, scene, camera, geometry, object, group);\\n if (object.isImmediateRenderObject) {\\n const program = setProgram(camera, scene, geometry, material, object);\\n state.setMaterial(material);\\n bindingStates.reset();\\n renderObjectImmediate(object, program);\\n } else {\\n if (material.transparent === true && material.side === DoubleSide) {\\n material.side = BackSide;\\n material.needsUpdate = true;\\n _this.renderBufferDirect(camera, scene, geometry, material, object, group);\\n material.side = FrontSide;\\n material.needsUpdate = true;\\n _this.renderBufferDirect(camera, scene, geometry, material, object, group);\\n material.side = DoubleSide;\\n } else {\\n _this.renderBufferDirect(camera, scene, geometry, material, object, group);\\n }\\n }\\n object.onAfterRender(_this, scene, camera, geometry, material, group);\\n }\\n function getProgram(material, scene, object) {\\n if (scene.isScene !== true)\\n scene = _emptyScene;\\n const materialProperties = properties.get(material);\\n const lights = currentRenderState.state.lights;\\n const shadowsArray = currentRenderState.state.shadowsArray;\\n const lightsStateVersion = lights.state.version;\\n const parameters2 = programCache.getParameters(material, lights.state, shadowsArray, scene, object);\\n const programCacheKey = programCache.getProgramCacheKey(parameters2);\\n let programs = materialProperties.programs;\\n materialProperties.environment = material.isMeshStandardMaterial ? scene.environment : null;\\n materialProperties.fog = scene.fog;\\n materialProperties.envMap = (material.isMeshStandardMaterial ? cubeuvmaps : cubemaps).get(material.envMap || materialProperties.environment);\\n if (programs === void 0) {\\n material.addEventListener(\\\\\\\"dispose\\\\\\\", onMaterialDispose);\\n programs = new Map();\\n materialProperties.programs = programs;\\n }\\n let program = programs.get(programCacheKey);\\n if (program !== void 0) {\\n if (materialProperties.currentProgram === program && materialProperties.lightsStateVersion === lightsStateVersion) {\\n updateCommonMaterialProperties(material, parameters2);\\n return program;\\n }\\n } else {\\n parameters2.uniforms = programCache.getUniforms(material);\\n material.onBuild(parameters2, _this);\\n material.onBeforeCompile(parameters2, _this);\\n program = programCache.acquireProgram(parameters2, programCacheKey);\\n programs.set(programCacheKey, program);\\n materialProperties.uniforms = parameters2.uniforms;\\n }\\n const uniforms = materialProperties.uniforms;\\n if (!material.isShaderMaterial && !material.isRawShaderMaterial || material.clipping === true) {\\n uniforms.clippingPlanes = clipping.uniform;\\n }\\n updateCommonMaterialProperties(material, parameters2);\\n materialProperties.needsLights = materialNeedsLights(material);\\n materialProperties.lightsStateVersion = lightsStateVersion;\\n if (materialProperties.needsLights) {\\n uniforms.ambientLightColor.value = lights.state.ambient;\\n uniforms.lightProbe.value = lights.state.probe;\\n uniforms.directionalLights.value = lights.state.directional;\\n uniforms.directionalLightShadows.value = lights.state.directionalShadow;\\n uniforms.spotLights.value = lights.state.spot;\\n uniforms.spotLightShadows.value = lights.state.spotShadow;\\n uniforms.rectAreaLights.value = lights.state.rectArea;\\n uniforms.ltc_1.value = lights.state.rectAreaLTC1;\\n uniforms.ltc_2.value = lights.state.rectAreaLTC2;\\n uniforms.pointLights.value = lights.state.point;\\n uniforms.pointLightShadows.value = lights.state.pointShadow;\\n uniforms.hemisphereLights.value = lights.state.hemi;\\n uniforms.directionalShadowMap.value = lights.state.directionalShadowMap;\\n uniforms.directionalShadowMatrix.value = lights.state.directionalShadowMatrix;\\n uniforms.spotShadowMap.value = lights.state.spotShadowMap;\\n uniforms.spotShadowMatrix.value = lights.state.spotShadowMatrix;\\n uniforms.pointShadowMap.value = lights.state.pointShadowMap;\\n uniforms.pointShadowMatrix.value = lights.state.pointShadowMatrix;\\n }\\n const progUniforms = program.getUniforms();\\n const uniformsList = WebGLUniforms.seqWithValue(progUniforms.seq, uniforms);\\n materialProperties.currentProgram = program;\\n materialProperties.uniformsList = uniformsList;\\n return program;\\n }\\n function updateCommonMaterialProperties(material, parameters2) {\\n const materialProperties = properties.get(material);\\n materialProperties.outputEncoding = parameters2.outputEncoding;\\n materialProperties.instancing = parameters2.instancing;\\n materialProperties.skinning = parameters2.skinning;\\n materialProperties.morphTargets = parameters2.morphTargets;\\n materialProperties.morphNormals = parameters2.morphNormals;\\n materialProperties.morphTargetsCount = parameters2.morphTargetsCount;\\n materialProperties.numClippingPlanes = parameters2.numClippingPlanes;\\n materialProperties.numIntersection = parameters2.numClipIntersection;\\n materialProperties.vertexAlphas = parameters2.vertexAlphas;\\n materialProperties.vertexTangents = parameters2.vertexTangents;\\n }\\n function setProgram(camera, scene, geometry, material, object) {\\n if (scene.isScene !== true)\\n scene = _emptyScene;\\n textures.resetTextureUnits();\\n const fog = scene.fog;\\n const environment = material.isMeshStandardMaterial ? scene.environment : null;\\n const encoding = _currentRenderTarget === null ? _this.outputEncoding : _currentRenderTarget.texture.encoding;\\n const envMap = (material.isMeshStandardMaterial ? cubeuvmaps : cubemaps).get(material.envMap || environment);\\n const vertexAlphas = material.vertexColors === true && !!geometry && !!geometry.attributes.color && geometry.attributes.color.itemSize === 4;\\n const vertexTangents = !!material.normalMap && !!geometry && !!geometry.attributes.tangent;\\n const morphTargets = !!geometry && !!geometry.morphAttributes.position;\\n const morphNormals = !!geometry && !!geometry.morphAttributes.normal;\\n const morphTargetsCount = !!geometry && !!geometry.morphAttributes.position ? geometry.morphAttributes.position.length : 0;\\n const materialProperties = properties.get(material);\\n const lights = currentRenderState.state.lights;\\n if (_clippingEnabled === true) {\\n if (_localClippingEnabled === true || camera !== _currentCamera) {\\n const useCache = camera === _currentCamera && material.id === _currentMaterialId;\\n clipping.setState(material, camera, useCache);\\n }\\n }\\n let needsProgramChange = false;\\n if (material.version === materialProperties.__version) {\\n if (materialProperties.needsLights && materialProperties.lightsStateVersion !== lights.state.version) {\\n needsProgramChange = true;\\n } else if (materialProperties.outputEncoding !== encoding) {\\n needsProgramChange = true;\\n } else if (object.isInstancedMesh && materialProperties.instancing === false) {\\n needsProgramChange = true;\\n } else if (!object.isInstancedMesh && materialProperties.instancing === true) {\\n needsProgramChange = true;\\n } else if (object.isSkinnedMesh && materialProperties.skinning === false) {\\n needsProgramChange = true;\\n } else if (!object.isSkinnedMesh && materialProperties.skinning === true) {\\n needsProgramChange = true;\\n } else if (materialProperties.envMap !== envMap) {\\n needsProgramChange = true;\\n } else if (material.fog && materialProperties.fog !== fog) {\\n needsProgramChange = true;\\n } else if (materialProperties.numClippingPlanes !== void 0 && (materialProperties.numClippingPlanes !== clipping.numPlanes || materialProperties.numIntersection !== clipping.numIntersection)) {\\n needsProgramChange = true;\\n } else if (materialProperties.vertexAlphas !== vertexAlphas) {\\n needsProgramChange = true;\\n } else if (materialProperties.vertexTangents !== vertexTangents) {\\n needsProgramChange = true;\\n } else if (materialProperties.morphTargets !== morphTargets) {\\n needsProgramChange = true;\\n } else if (materialProperties.morphNormals !== morphNormals) {\\n needsProgramChange = true;\\n } else if (capabilities.isWebGL2 === true && materialProperties.morphTargetsCount !== morphTargetsCount) {\\n needsProgramChange = true;\\n }\\n } else {\\n needsProgramChange = true;\\n materialProperties.__version = material.version;\\n }\\n let program = materialProperties.currentProgram;\\n if (needsProgramChange === true) {\\n program = getProgram(material, scene, object);\\n }\\n let refreshProgram = false;\\n let refreshMaterial = false;\\n let refreshLights = false;\\n const p_uniforms = program.getUniforms(), m_uniforms = materialProperties.uniforms;\\n if (state.useProgram(program.program)) {\\n refreshProgram = true;\\n refreshMaterial = true;\\n refreshLights = true;\\n }\\n if (material.id !== _currentMaterialId) {\\n _currentMaterialId = material.id;\\n refreshMaterial = true;\\n }\\n if (refreshProgram || _currentCamera !== camera) {\\n p_uniforms.setValue(_gl, \\\\\\\"projectionMatrix\\\\\\\", camera.projectionMatrix);\\n if (capabilities.logarithmicDepthBuffer) {\\n p_uniforms.setValue(_gl, \\\\\\\"logDepthBufFC\\\\\\\", 2 / (Math.log(camera.far + 1) / Math.LN2));\\n }\\n if (_currentCamera !== camera) {\\n _currentCamera = camera;\\n refreshMaterial = true;\\n refreshLights = true;\\n }\\n if (material.isShaderMaterial || material.isMeshPhongMaterial || material.isMeshToonMaterial || material.isMeshStandardMaterial || material.envMap) {\\n const uCamPos = p_uniforms.map.cameraPosition;\\n if (uCamPos !== void 0) {\\n uCamPos.setValue(_gl, _vector32.setFromMatrixPosition(camera.matrixWorld));\\n }\\n }\\n if (material.isMeshPhongMaterial || material.isMeshToonMaterial || material.isMeshLambertMaterial || material.isMeshBasicMaterial || material.isMeshStandardMaterial || material.isShaderMaterial) {\\n p_uniforms.setValue(_gl, \\\\\\\"isOrthographic\\\\\\\", camera.isOrthographicCamera === true);\\n }\\n if (material.isMeshPhongMaterial || material.isMeshToonMaterial || material.isMeshLambertMaterial || material.isMeshBasicMaterial || material.isMeshStandardMaterial || material.isShaderMaterial || material.isShadowMaterial || object.isSkinnedMesh) {\\n p_uniforms.setValue(_gl, \\\\\\\"viewMatrix\\\\\\\", camera.matrixWorldInverse);\\n }\\n }\\n if (object.isSkinnedMesh) {\\n p_uniforms.setOptional(_gl, object, \\\\\\\"bindMatrix\\\\\\\");\\n p_uniforms.setOptional(_gl, object, \\\\\\\"bindMatrixInverse\\\\\\\");\\n const skeleton = object.skeleton;\\n if (skeleton) {\\n if (capabilities.floatVertexTextures) {\\n if (skeleton.boneTexture === null)\\n skeleton.computeBoneTexture();\\n p_uniforms.setValue(_gl, \\\\\\\"boneTexture\\\\\\\", skeleton.boneTexture, textures);\\n p_uniforms.setValue(_gl, \\\\\\\"boneTextureSize\\\\\\\", skeleton.boneTextureSize);\\n } else {\\n p_uniforms.setOptional(_gl, skeleton, \\\\\\\"boneMatrices\\\\\\\");\\n }\\n }\\n }\\n if (!!geometry && (geometry.morphAttributes.position !== void 0 || geometry.morphAttributes.normal !== void 0)) {\\n morphtargets.update(object, geometry, material, program);\\n }\\n if (refreshMaterial || materialProperties.receiveShadow !== object.receiveShadow) {\\n materialProperties.receiveShadow = object.receiveShadow;\\n p_uniforms.setValue(_gl, \\\\\\\"receiveShadow\\\\\\\", object.receiveShadow);\\n }\\n if (refreshMaterial) {\\n p_uniforms.setValue(_gl, \\\\\\\"toneMappingExposure\\\\\\\", _this.toneMappingExposure);\\n if (materialProperties.needsLights) {\\n markUniformsLightsNeedsUpdate(m_uniforms, refreshLights);\\n }\\n if (fog && material.fog) {\\n materials2.refreshFogUniforms(m_uniforms, fog);\\n }\\n materials2.refreshMaterialUniforms(m_uniforms, material, _pixelRatio, _height, _transmissionRenderTarget);\\n WebGLUniforms.upload(_gl, materialProperties.uniformsList, m_uniforms, textures);\\n }\\n if (material.isShaderMaterial && material.uniformsNeedUpdate === true) {\\n WebGLUniforms.upload(_gl, materialProperties.uniformsList, m_uniforms, textures);\\n material.uniformsNeedUpdate = false;\\n }\\n if (material.isSpriteMaterial) {\\n p_uniforms.setValue(_gl, \\\\\\\"center\\\\\\\", object.center);\\n }\\n p_uniforms.setValue(_gl, \\\\\\\"modelViewMatrix\\\\\\\", object.modelViewMatrix);\\n p_uniforms.setValue(_gl, \\\\\\\"normalMatrix\\\\\\\", object.normalMatrix);\\n p_uniforms.setValue(_gl, \\\\\\\"modelMatrix\\\\\\\", object.matrixWorld);\\n return program;\\n }\\n function markUniformsLightsNeedsUpdate(uniforms, value) {\\n uniforms.ambientLightColor.needsUpdate = value;\\n uniforms.lightProbe.needsUpdate = value;\\n uniforms.directionalLights.needsUpdate = value;\\n uniforms.directionalLightShadows.needsUpdate = value;\\n uniforms.pointLights.needsUpdate = value;\\n uniforms.pointLightShadows.needsUpdate = value;\\n uniforms.spotLights.needsUpdate = value;\\n uniforms.spotLightShadows.needsUpdate = value;\\n uniforms.rectAreaLights.needsUpdate = value;\\n uniforms.hemisphereLights.needsUpdate = value;\\n }\\n function materialNeedsLights(material) {\\n return material.isMeshLambertMaterial || material.isMeshToonMaterial || material.isMeshPhongMaterial || material.isMeshStandardMaterial || material.isShadowMaterial || material.isShaderMaterial && material.lights === true;\\n }\\n this.getActiveCubeFace = function() {\\n return _currentActiveCubeFace;\\n };\\n this.getActiveMipmapLevel = function() {\\n return _currentActiveMipmapLevel;\\n };\\n this.getRenderTarget = function() {\\n return _currentRenderTarget;\\n };\\n this.setRenderTarget = function(renderTarget, activeCubeFace = 0, activeMipmapLevel = 0) {\\n _currentRenderTarget = renderTarget;\\n _currentActiveCubeFace = activeCubeFace;\\n _currentActiveMipmapLevel = activeMipmapLevel;\\n if (renderTarget && properties.get(renderTarget).__webglFramebuffer === void 0) {\\n textures.setupRenderTarget(renderTarget);\\n }\\n let framebuffer = null;\\n let isCube = false;\\n let isRenderTarget3D = false;\\n if (renderTarget) {\\n const texture = renderTarget.texture;\\n if (texture.isDataTexture3D || texture.isDataTexture2DArray) {\\n isRenderTarget3D = true;\\n }\\n const __webglFramebuffer = properties.get(renderTarget).__webglFramebuffer;\\n if (renderTarget.isWebGLCubeRenderTarget) {\\n framebuffer = __webglFramebuffer[activeCubeFace];\\n isCube = true;\\n } else if (renderTarget.isWebGLMultisampleRenderTarget) {\\n framebuffer = properties.get(renderTarget).__webglMultisampledFramebuffer;\\n } else {\\n framebuffer = __webglFramebuffer;\\n }\\n _currentViewport.copy(renderTarget.viewport);\\n _currentScissor.copy(renderTarget.scissor);\\n _currentScissorTest = renderTarget.scissorTest;\\n } else {\\n _currentViewport.copy(_viewport).multiplyScalar(_pixelRatio).floor();\\n _currentScissor.copy(_scissor).multiplyScalar(_pixelRatio).floor();\\n _currentScissorTest = _scissorTest;\\n }\\n const framebufferBound = state.bindFramebuffer(_gl.FRAMEBUFFER, framebuffer);\\n if (framebufferBound && capabilities.drawBuffers) {\\n let needsUpdate = false;\\n if (renderTarget) {\\n if (renderTarget.isWebGLMultipleRenderTargets) {\\n const textures2 = renderTarget.texture;\\n if (_currentDrawBuffers.length !== textures2.length || _currentDrawBuffers[0] !== _gl.COLOR_ATTACHMENT0) {\\n for (let i = 0, il = textures2.length; i < il; i++) {\\n _currentDrawBuffers[i] = _gl.COLOR_ATTACHMENT0 + i;\\n }\\n _currentDrawBuffers.length = textures2.length;\\n needsUpdate = true;\\n }\\n } else {\\n if (_currentDrawBuffers.length !== 1 || _currentDrawBuffers[0] !== _gl.COLOR_ATTACHMENT0) {\\n _currentDrawBuffers[0] = _gl.COLOR_ATTACHMENT0;\\n _currentDrawBuffers.length = 1;\\n needsUpdate = true;\\n }\\n }\\n } else {\\n if (_currentDrawBuffers.length !== 1 || _currentDrawBuffers[0] !== _gl.BACK) {\\n _currentDrawBuffers[0] = _gl.BACK;\\n _currentDrawBuffers.length = 1;\\n needsUpdate = true;\\n }\\n }\\n if (needsUpdate) {\\n if (capabilities.isWebGL2) {\\n _gl.drawBuffers(_currentDrawBuffers);\\n } else {\\n extensions.get(\\\\\\\"WEBGL_draw_buffers\\\\\\\").drawBuffersWEBGL(_currentDrawBuffers);\\n }\\n }\\n }\\n state.viewport(_currentViewport);\\n state.scissor(_currentScissor);\\n state.setScissorTest(_currentScissorTest);\\n if (isCube) {\\n const textureProperties = properties.get(renderTarget.texture);\\n _gl.framebufferTexture2D(_gl.FRAMEBUFFER, _gl.COLOR_ATTACHMENT0, _gl.TEXTURE_CUBE_MAP_POSITIVE_X + activeCubeFace, textureProperties.__webglTexture, activeMipmapLevel);\\n } else if (isRenderTarget3D) {\\n const textureProperties = properties.get(renderTarget.texture);\\n const layer = activeCubeFace || 0;\\n _gl.framebufferTextureLayer(_gl.FRAMEBUFFER, _gl.COLOR_ATTACHMENT0, textureProperties.__webglTexture, activeMipmapLevel || 0, layer);\\n }\\n _currentMaterialId = -1;\\n };\\n this.readRenderTargetPixels = function(renderTarget, x, y, width, height, buffer, activeCubeFaceIndex) {\\n if (!(renderTarget && renderTarget.isWebGLRenderTarget)) {\\n console.error(\\\\\\\"THREE.WebGLRenderer.readRenderTargetPixels: renderTarget is not THREE.WebGLRenderTarget.\\\\\\\");\\n return;\\n }\\n let framebuffer = properties.get(renderTarget).__webglFramebuffer;\\n if (renderTarget.isWebGLCubeRenderTarget && activeCubeFaceIndex !== void 0) {\\n framebuffer = framebuffer[activeCubeFaceIndex];\\n }\\n if (framebuffer) {\\n state.bindFramebuffer(_gl.FRAMEBUFFER, framebuffer);\\n try {\\n const texture = renderTarget.texture;\\n const textureFormat = texture.format;\\n const textureType = texture.type;\\n if (textureFormat !== RGBAFormat && utils.convert(textureFormat) !== _gl.getParameter(_gl.IMPLEMENTATION_COLOR_READ_FORMAT)) {\\n console.error(\\\\\\\"THREE.WebGLRenderer.readRenderTargetPixels: renderTarget is not in RGBA or implementation defined format.\\\\\\\");\\n return;\\n }\\n const halfFloatSupportedByExt = textureType === HalfFloatType && (extensions.has(\\\\\\\"EXT_color_buffer_half_float\\\\\\\") || capabilities.isWebGL2 && extensions.has(\\\\\\\"EXT_color_buffer_float\\\\\\\"));\\n if (textureType !== UnsignedByteType && utils.convert(textureType) !== _gl.getParameter(_gl.IMPLEMENTATION_COLOR_READ_TYPE) && !(textureType === FloatType && (capabilities.isWebGL2 || extensions.has(\\\\\\\"OES_texture_float\\\\\\\") || extensions.has(\\\\\\\"WEBGL_color_buffer_float\\\\\\\"))) && !halfFloatSupportedByExt) {\\n console.error(\\\\\\\"THREE.WebGLRenderer.readRenderTargetPixels: renderTarget is not in UnsignedByteType or implementation defined type.\\\\\\\");\\n return;\\n }\\n if (_gl.checkFramebufferStatus(_gl.FRAMEBUFFER) === _gl.FRAMEBUFFER_COMPLETE) {\\n if (x >= 0 && x <= renderTarget.width - width && (y >= 0 && y <= renderTarget.height - height)) {\\n _gl.readPixels(x, y, width, height, utils.convert(textureFormat), utils.convert(textureType), buffer);\\n }\\n } else {\\n console.error(\\\\\\\"THREE.WebGLRenderer.readRenderTargetPixels: readPixels from renderTarget failed. Framebuffer not complete.\\\\\\\");\\n }\\n } finally {\\n const framebuffer2 = _currentRenderTarget !== null ? properties.get(_currentRenderTarget).__webglFramebuffer : null;\\n state.bindFramebuffer(_gl.FRAMEBUFFER, framebuffer2);\\n }\\n }\\n };\\n this.copyFramebufferToTexture = function(position, texture, level = 0) {\\n const levelScale = Math.pow(2, -level);\\n const width = Math.floor(texture.image.width * levelScale);\\n const height = Math.floor(texture.image.height * levelScale);\\n let glFormat = utils.convert(texture.format);\\n if (capabilities.isWebGL2) {\\n if (glFormat === _gl.RGB)\\n glFormat = _gl.RGB8;\\n if (glFormat === _gl.RGBA)\\n glFormat = _gl.RGBA8;\\n }\\n textures.setTexture2D(texture, 0);\\n _gl.copyTexImage2D(_gl.TEXTURE_2D, level, glFormat, position.x, position.y, width, height, 0);\\n state.unbindTexture();\\n };\\n this.copyTextureToTexture = function(position, srcTexture, dstTexture, level = 0) {\\n const width = srcTexture.image.width;\\n const height = srcTexture.image.height;\\n const glFormat = utils.convert(dstTexture.format);\\n const glType = utils.convert(dstTexture.type);\\n textures.setTexture2D(dstTexture, 0);\\n _gl.pixelStorei(_gl.UNPACK_FLIP_Y_WEBGL, dstTexture.flipY);\\n _gl.pixelStorei(_gl.UNPACK_PREMULTIPLY_ALPHA_WEBGL, dstTexture.premultiplyAlpha);\\n _gl.pixelStorei(_gl.UNPACK_ALIGNMENT, dstTexture.unpackAlignment);\\n if (srcTexture.isDataTexture) {\\n _gl.texSubImage2D(_gl.TEXTURE_2D, level, position.x, position.y, width, height, glFormat, glType, srcTexture.image.data);\\n } else {\\n if (srcTexture.isCompressedTexture) {\\n _gl.compressedTexSubImage2D(_gl.TEXTURE_2D, level, position.x, position.y, srcTexture.mipmaps[0].width, srcTexture.mipmaps[0].height, glFormat, srcTexture.mipmaps[0].data);\\n } else {\\n _gl.texSubImage2D(_gl.TEXTURE_2D, level, position.x, position.y, glFormat, glType, srcTexture.image);\\n }\\n }\\n if (level === 0 && dstTexture.generateMipmaps)\\n _gl.generateMipmap(_gl.TEXTURE_2D);\\n state.unbindTexture();\\n };\\n this.copyTextureToTexture3D = function(sourceBox, position, srcTexture, dstTexture, level = 0) {\\n if (_this.isWebGL1Renderer) {\\n console.warn(\\\\\\\"THREE.WebGLRenderer.copyTextureToTexture3D: can only be used with WebGL2.\\\\\\\");\\n return;\\n }\\n const width = sourceBox.max.x - sourceBox.min.x + 1;\\n const height = sourceBox.max.y - sourceBox.min.y + 1;\\n const depth2 = sourceBox.max.z - sourceBox.min.z + 1;\\n const glFormat = utils.convert(dstTexture.format);\\n const glType = utils.convert(dstTexture.type);\\n let glTarget;\\n if (dstTexture.isDataTexture3D) {\\n textures.setTexture3D(dstTexture, 0);\\n glTarget = _gl.TEXTURE_3D;\\n } else if (dstTexture.isDataTexture2DArray) {\\n textures.setTexture2DArray(dstTexture, 0);\\n glTarget = _gl.TEXTURE_2D_ARRAY;\\n } else {\\n console.warn(\\\\\\\"THREE.WebGLRenderer.copyTextureToTexture3D: only supports THREE.DataTexture3D and THREE.DataTexture2DArray.\\\\\\\");\\n return;\\n }\\n _gl.pixelStorei(_gl.UNPACK_FLIP_Y_WEBGL, dstTexture.flipY);\\n _gl.pixelStorei(_gl.UNPACK_PREMULTIPLY_ALPHA_WEBGL, dstTexture.premultiplyAlpha);\\n _gl.pixelStorei(_gl.UNPACK_ALIGNMENT, dstTexture.unpackAlignment);\\n const unpackRowLen = _gl.getParameter(_gl.UNPACK_ROW_LENGTH);\\n const unpackImageHeight = _gl.getParameter(_gl.UNPACK_IMAGE_HEIGHT);\\n const unpackSkipPixels = _gl.getParameter(_gl.UNPACK_SKIP_PIXELS);\\n const unpackSkipRows = _gl.getParameter(_gl.UNPACK_SKIP_ROWS);\\n const unpackSkipImages = _gl.getParameter(_gl.UNPACK_SKIP_IMAGES);\\n const image = srcTexture.isCompressedTexture ? srcTexture.mipmaps[0] : srcTexture.image;\\n _gl.pixelStorei(_gl.UNPACK_ROW_LENGTH, image.width);\\n _gl.pixelStorei(_gl.UNPACK_IMAGE_HEIGHT, image.height);\\n _gl.pixelStorei(_gl.UNPACK_SKIP_PIXELS, sourceBox.min.x);\\n _gl.pixelStorei(_gl.UNPACK_SKIP_ROWS, sourceBox.min.y);\\n _gl.pixelStorei(_gl.UNPACK_SKIP_IMAGES, sourceBox.min.z);\\n if (srcTexture.isDataTexture || srcTexture.isDataTexture3D) {\\n _gl.texSubImage3D(glTarget, level, position.x, position.y, position.z, width, height, depth2, glFormat, glType, image.data);\\n } else {\\n if (srcTexture.isCompressedTexture) {\\n console.warn(\\\\\\\"THREE.WebGLRenderer.copyTextureToTexture3D: untested support for compressed srcTexture.\\\\\\\");\\n _gl.compressedTexSubImage3D(glTarget, level, position.x, position.y, position.z, width, height, depth2, glFormat, image.data);\\n } else {\\n _gl.texSubImage3D(glTarget, level, position.x, position.y, position.z, width, height, depth2, glFormat, glType, image);\\n }\\n }\\n _gl.pixelStorei(_gl.UNPACK_ROW_LENGTH, unpackRowLen);\\n _gl.pixelStorei(_gl.UNPACK_IMAGE_HEIGHT, unpackImageHeight);\\n _gl.pixelStorei(_gl.UNPACK_SKIP_PIXELS, unpackSkipPixels);\\n _gl.pixelStorei(_gl.UNPACK_SKIP_ROWS, unpackSkipRows);\\n _gl.pixelStorei(_gl.UNPACK_SKIP_IMAGES, unpackSkipImages);\\n if (level === 0 && dstTexture.generateMipmaps)\\n _gl.generateMipmap(glTarget);\\n state.unbindTexture();\\n };\\n this.initTexture = function(texture) {\\n textures.setTexture2D(texture, 0);\\n state.unbindTexture();\\n };\\n this.resetState = function() {\\n _currentActiveCubeFace = 0;\\n _currentActiveMipmapLevel = 0;\\n _currentRenderTarget = null;\\n state.reset();\\n bindingStates.reset();\\n };\\n if (typeof __THREE_DEVTOOLS__ !== \\\\\\\"undefined\\\\\\\") {\\n __THREE_DEVTOOLS__.dispatchEvent(new CustomEvent(\\\\\\\"observe\\\\\\\", {detail: this}));\\n }\\n}\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/poly/RenderersController.ts\\nvar CONTEXT_OPTIONS = {};\\nvar WebGLContext;\\n(function(WebGLContext2) {\\n WebGLContext2[\\\\\\\"WEBGL\\\\\\\"] = \\\\\\\"webgl\\\\\\\";\\n WebGLContext2[\\\\\\\"WEBGL2\\\\\\\"] = \\\\\\\"webgl2\\\\\\\";\\n WebGLContext2[\\\\\\\"EXPERIMENTAL_WEBGL\\\\\\\"] = \\\\\\\"experimental-webgl\\\\\\\";\\n WebGLContext2[\\\\\\\"EXPERIMENTAL_WEBGL2\\\\\\\"] = \\\\\\\"experimental-webgl2\\\\\\\";\\n})(WebGLContext || (WebGLContext = {}));\\nvar RenderersController = class {\\n constructor() {\\n this._next_renderer_id = 0;\\n this._renderers = {};\\n this._printDebug = false;\\n this._require_webgl2 = false;\\n this._resolves = [];\\n }\\n setPrintDebug(state = true) {\\n this._printDebug = state;\\n }\\n printDebug() {\\n return this._printDebug;\\n }\\n printDebugMessage(message) {\\n if (!this._printDebug) {\\n return;\\n }\\n console.warn(\\\\\\\"[Poly debug]\\\\\\\", message);\\n }\\n setRequireWebGL2() {\\n if (!this._require_webgl2) {\\n this._require_webgl2 = true;\\n }\\n }\\n webgl2Available() {\\n if (this._webgl2_available === void 0) {\\n this._webgl2_available = this._set_webgl2_available();\\n }\\n return this._webgl2_available;\\n }\\n _set_webgl2_available() {\\n const canvas = document.createElement(\\\\\\\"canvas\\\\\\\");\\n return (window.WebGL2RenderingContext && canvas.getContext(WebGLContext.WEBGL2)) != null;\\n }\\n createWebGLRenderer(params) {\\n const renderer = new WebGLRenderer(params);\\n this.printDebugMessage([`create renderer:`, params]);\\n return renderer;\\n }\\n createRenderingContext(canvas) {\\n let gl = null;\\n if (this._require_webgl2) {\\n gl = this._getRenderingContextWebgl(canvas, true);\\n if (!gl) {\\n console.warn(\\\\\\\"failed to create webgl2 context\\\\\\\");\\n }\\n }\\n if (!gl) {\\n gl = this._getRenderingContextWebgl(canvas, false);\\n }\\n return gl;\\n }\\n _getRenderingContextWebgl(canvas, webgl2) {\\n let context_name;\\n if (this.webgl2Available()) {\\n context_name = WebGLContext.WEBGL2;\\n } else {\\n context_name = webgl2 ? WebGLContext.WEBGL2 : WebGLContext.WEBGL;\\n }\\n let gl = canvas.getContext(context_name, CONTEXT_OPTIONS);\\n if (gl) {\\n this.printDebugMessage(`create gl context: ${context_name}.`);\\n } else {\\n context_name = webgl2 ? WebGLContext.EXPERIMENTAL_WEBGL2 : WebGLContext.EXPERIMENTAL_WEBGL;\\n this.printDebugMessage(`create gl context: ${context_name}.`);\\n gl = canvas.getContext(context_name, CONTEXT_OPTIONS);\\n }\\n return gl;\\n }\\n registerRenderer(renderer) {\\n if (renderer._polygon_id) {\\n throw new Error(\\\\\\\"render already registered\\\\\\\");\\n }\\n renderer._polygon_id = this._next_renderer_id += 1;\\n this._renderers[renderer._polygon_id] = renderer;\\n if (Object.keys(this._renderers).length == 1) {\\n this.flush_callbacks_with_renderer(renderer);\\n }\\n }\\n deregisterRenderer(renderer) {\\n delete this._renderers[renderer._polygon_id];\\n renderer.dispose();\\n }\\n firstRenderer() {\\n const first_id = Object.keys(this._renderers)[0];\\n if (first_id) {\\n return this._renderers[first_id];\\n }\\n return null;\\n }\\n renderers() {\\n return Object.values(this._renderers);\\n }\\n flush_callbacks_with_renderer(renderer) {\\n let callback;\\n while (callback = this._resolves.pop()) {\\n callback(renderer);\\n }\\n }\\n async waitForRenderer() {\\n const renderer = this.firstRenderer();\\n if (renderer) {\\n return renderer;\\n } else {\\n return new Promise((resolve, reject) => {\\n this._resolves.push(resolve);\\n });\\n }\\n }\\n renderTarget(width, height, parameters) {\\n if (this.webgl2Available()) {\\n return new WebGLMultisampleRenderTarget(width, height, parameters);\\n } else {\\n return new WebGLRenderTarget(width, height, parameters);\\n }\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/poly/PolyLibsController.ts\\nvar PolyLibsController = class {\\n constructor() {\\n this._root = \\\\\\\"/three/js/libs\\\\\\\";\\n this._BASISPath = \\\\\\\"/basis\\\\\\\";\\n this._DRACOPath = \\\\\\\"/draco\\\\\\\";\\n this._DRACOGLTFPath = \\\\\\\"/draco/gltf\\\\\\\";\\n }\\n root() {\\n return this._root;\\n }\\n setRoot(url) {\\n this._root = url;\\n }\\n BASISPath() {\\n return this._BASISPath;\\n }\\n DRACOPath() {\\n return this._DRACOPath;\\n }\\n DRACOGLTFPath() {\\n return this._DRACOGLTFPath;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/poly/registers/nodes/NodesRegister.ts\\nvar NodesRegister = class {\\n constructor(poly) {\\n this.poly = poly;\\n this._node_register = new Map();\\n this._node_register_categories = new Map();\\n this._node_register_options = new Map();\\n }\\n static type(node) {\\n return this.filterType(node.type());\\n }\\n static filterType(nodeType) {\\n return nodeType.toLowerCase();\\n }\\n register(node, tab_menu_category, options) {\\n const context = node.context();\\n const nodeType = NodesRegister.type(node);\\n let current_nodes_for_context = this._node_register.get(context);\\n if (!current_nodes_for_context) {\\n current_nodes_for_context = new Map();\\n this._node_register.set(context, current_nodes_for_context);\\n }\\n const already_registered_node = current_nodes_for_context.get(nodeType);\\n if (already_registered_node) {\\n console.error(`node ${context}/${nodeType} already registered`);\\n return;\\n }\\n current_nodes_for_context.set(nodeType, node);\\n if (tab_menu_category) {\\n let current_categories = this._node_register_categories.get(context);\\n if (!current_categories) {\\n current_categories = new Map();\\n this._node_register_categories.set(context, current_categories);\\n }\\n current_categories.set(nodeType, tab_menu_category);\\n }\\n if (options) {\\n let current_options = this._node_register_options.get(context);\\n if (!current_options) {\\n current_options = new Map();\\n this._node_register_options.set(context, current_options);\\n }\\n current_options.set(nodeType, options);\\n }\\n this.poly.pluginsRegister.registerNode(node);\\n }\\n deregister(context, nodeType) {\\n nodeType = NodesRegister.filterType(nodeType);\\n this._node_register.get(context)?.delete(nodeType);\\n this._node_register_categories.get(context)?.delete(nodeType);\\n this._node_register_options.get(context)?.delete(nodeType);\\n }\\n isRegistered(context, nodeType) {\\n const nodes_for_context = this._node_register.get(context);\\n if (!nodes_for_context) {\\n return false;\\n }\\n nodeType = NodesRegister.filterType(nodeType);\\n return nodes_for_context.get(nodeType) != null;\\n }\\n nodeOptions(context, nodeType) {\\n nodeType = NodesRegister.filterType(nodeType);\\n return this._node_register_options.get(context)?.get(nodeType);\\n }\\n registeredNodesForContextAndParentType(context, parent_node_type) {\\n const map = this._node_register.get(context);\\n if (map) {\\n const nodes_for_context = [];\\n this._node_register.get(context)?.forEach((node, type) => {\\n nodes_for_context.push(node);\\n });\\n return nodes_for_context.filter((node) => {\\n const nodeType = NodesRegister.type(node);\\n const options = this._node_register_options.get(context)?.get(nodeType);\\n if (!options) {\\n return true;\\n } else {\\n const option_only = options[\\\\\\\"only\\\\\\\"];\\n const option_except = options[\\\\\\\"except\\\\\\\"];\\n const context_and_type = `${context}/${parent_node_type}`;\\n if (option_only) {\\n return option_only.includes(context_and_type);\\n }\\n if (option_except) {\\n return !option_except.includes(context_and_type);\\n }\\n return true;\\n }\\n });\\n } else {\\n return [];\\n }\\n }\\n registeredNodes(context, parentNodeType) {\\n const nodesByType = {};\\n const nodes = this.registeredNodesForContextAndParentType(context, parentNodeType);\\n for (let node of nodes) {\\n const nodeType = NodesRegister.type(node);\\n nodesByType[nodeType] = node;\\n }\\n return nodesByType;\\n }\\n registeredCategory(context, nodeType) {\\n nodeType = NodesRegister.filterType(nodeType);\\n return this._node_register_categories.get(context)?.get(nodeType);\\n }\\n map() {\\n return this._node_register;\\n }\\n};\\nvar OperationsRegister = class {\\n constructor(poly) {\\n this.poly = poly;\\n this._operation_register = new Map();\\n }\\n static type(node) {\\n return this.filterType(node.type());\\n }\\n static filterType(nodeType) {\\n return nodeType.toLowerCase();\\n }\\n register(operation) {\\n const context = operation.context();\\n let current_operations_for_context = this._operation_register.get(context);\\n if (!current_operations_for_context) {\\n current_operations_for_context = new Map();\\n this._operation_register.set(context, current_operations_for_context);\\n }\\n const operationType = OperationsRegister.type(operation);\\n const already_registered_operation = current_operations_for_context.get(operationType);\\n if (already_registered_operation) {\\n const message = `operation ${context}/${operationType} already registered`;\\n console.error(message);\\n return;\\n }\\n current_operations_for_context.set(operationType, operation);\\n this.poly.pluginsRegister.registerOperation(operation);\\n }\\n registeredOperationsForContextAndParentType(context, parentNodeType) {\\n const map = this._operation_register.get(context);\\n if (map) {\\n const nodes_for_context = [];\\n this._operation_register.get(context)?.forEach((operation, type) => {\\n nodes_for_context.push(operation);\\n });\\n return nodes_for_context;\\n } else {\\n return [];\\n }\\n }\\n registeredOperation(context, operationType) {\\n const current_operations_for_context = this._operation_register.get(context);\\n if (current_operations_for_context) {\\n operationType = OperationsRegister.filterType(operationType);\\n return current_operations_for_context.get(operationType);\\n }\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/poly/registers/expressions/_BaseRegister.ts\\nvar BaseExpressionRegister = class {\\n constructor() {\\n this._methods_names = [];\\n this._methods_by_name = new Map();\\n }\\n register(expression, name) {\\n this._methods_names.push(name);\\n this._methods_by_name.set(name, expression);\\n }\\n getMethod(name) {\\n return this._methods_by_name.get(name);\\n }\\n availableMethods() {\\n return this._methods_names;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/poly/registers/expressions/ExpressionRegister.ts\\nvar ExpressionRegister = class extends BaseExpressionRegister {\\n getMethod(name) {\\n return super.getMethod(name);\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/poly/registers/modules/_BaseRegister.ts\\nvar BaseModulesRegister = class {\\n constructor() {\\n this._module_by_name = new Map();\\n }\\n register(name, module) {\\n this._module_by_name.set(name, module);\\n }\\n moduleNames() {\\n const list = [];\\n this._module_by_name.forEach((module, moduleName) => {\\n list.push(moduleName);\\n });\\n return list;\\n }\\n module(moduleName) {\\n return this._module_by_name.get(moduleName);\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/poly/registers/modules/DynamicModulesRegister.ts\\nvar DynamicModulesRegister = class extends BaseModulesRegister {\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/poly/registers/assemblers/_BaseRegister.ts\\nvar AssemblerName;\\n(function(AssemblerName3) {\\n AssemblerName3[\\\\\\\"GL_MESH_BASIC\\\\\\\"] = \\\\\\\"GL_MESH_BASIC\\\\\\\";\\n AssemblerName3[\\\\\\\"GL_MESH_LAMBERT\\\\\\\"] = \\\\\\\"GL_MESH_LAMBERT\\\\\\\";\\n AssemblerName3[\\\\\\\"GL_MESH_STANDARD\\\\\\\"] = \\\\\\\"GL_MESH_STANDARD\\\\\\\";\\n AssemblerName3[\\\\\\\"GL_MESH_PHONG\\\\\\\"] = \\\\\\\"GL_MESH_PHONG\\\\\\\";\\n AssemblerName3[\\\\\\\"GL_MESH_PHYSICAL\\\\\\\"] = \\\\\\\"GL_MESH_PHYSICAL\\\\\\\";\\n AssemblerName3[\\\\\\\"GL_PARTICLES\\\\\\\"] = \\\\\\\"GL_PARTICLES\\\\\\\";\\n AssemblerName3[\\\\\\\"GL_POINTS\\\\\\\"] = \\\\\\\"GL_POINTS\\\\\\\";\\n AssemblerName3[\\\\\\\"GL_LINE\\\\\\\"] = \\\\\\\"GL_LINE\\\\\\\";\\n AssemblerName3[\\\\\\\"GL_TEXTURE\\\\\\\"] = \\\\\\\"GL_TEXTURE\\\\\\\";\\n AssemblerName3[\\\\\\\"GL_VOLUME\\\\\\\"] = \\\\\\\"GL_VOLUME\\\\\\\";\\n})(AssemblerName || (AssemblerName = {}));\\nvar BaseAssemblersRegister = class {\\n constructor() {\\n this._controller_assembler_by_name = new Map();\\n }\\n register(name, controller, assembler) {\\n this._controller_assembler_by_name.set(name, {\\n controller,\\n assembler\\n });\\n }\\n unregister(name) {\\n this._controller_assembler_by_name.delete(name);\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/poly/registers/assemblers/AssemblersRegistry.ts\\nvar AssemblersRegister = class extends BaseAssemblersRegister {\\n assembler(node, name) {\\n const pair = this._controller_assembler_by_name.get(name);\\n if (pair) {\\n const controller = pair.controller;\\n const assembler = pair.assembler;\\n return new controller(node, assembler);\\n }\\n return pair;\\n }\\n unregister(name) {\\n const pair = this._controller_assembler_by_name.get(name);\\n super.unregister(name);\\n return pair;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/poly/registers/plugins/PluginsRegister.ts\\nvar PluginsRegister = class {\\n constructor(poly) {\\n this.poly = poly;\\n this._plugins_by_name = new Map();\\n this._plugin_name_by_node_context_by_type = new Map();\\n this._plugin_name_by_operation_context_by_type = new Map();\\n }\\n register(plugin) {\\n this._current_plugin = plugin;\\n this._plugins_by_name.set(plugin.name(), plugin);\\n plugin.init(this.poly);\\n this._current_plugin = void 0;\\n }\\n pluginByName(pluginName) {\\n return this._plugins_by_name.get(pluginName);\\n }\\n registerNode(node) {\\n if (!this._current_plugin) {\\n return;\\n }\\n const context = node.context();\\n const type = node.type();\\n let map_for_context = this._plugin_name_by_node_context_by_type.get(context);\\n if (!map_for_context) {\\n map_for_context = new Map();\\n this._plugin_name_by_node_context_by_type.set(context, map_for_context);\\n }\\n map_for_context.set(type, this._current_plugin.name());\\n }\\n registerOperation(operation) {\\n if (!this._current_plugin) {\\n return;\\n }\\n const context = operation.context();\\n const type = operation.type();\\n let map_for_context = this._plugin_name_by_operation_context_by_type.get(context);\\n if (!map_for_context) {\\n map_for_context = new Map();\\n this._plugin_name_by_operation_context_by_type.set(context, map_for_context);\\n }\\n map_for_context.set(type, this._current_plugin.name());\\n }\\n toJson() {\\n const data = {\\n plugins: {},\\n nodes: {},\\n operations: {}\\n };\\n this._plugins_by_name.forEach((plugin, name) => {\\n data.plugins[name] = plugin.toJSON();\\n });\\n this._plugin_name_by_node_context_by_type.forEach((map_for_context, context) => {\\n data.nodes[context] = {};\\n map_for_context.forEach((plugin_name, type) => {\\n data.nodes[context][type] = plugin_name;\\n });\\n });\\n this._plugin_name_by_operation_context_by_type.forEach((map_for_context, context) => {\\n data.operations[context] = {};\\n map_for_context.forEach((plugin_name, type) => {\\n data.operations[context][type] = plugin_name;\\n });\\n });\\n return data;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/poly/registers/cameras/CamerasRegister.ts\\nvar CamerasRegister = class {\\n constructor(poly) {\\n this._camera_types = [];\\n }\\n register(node) {\\n const node_type = node.type();\\n if (!this._camera_types.includes(node_type)) {\\n this._camera_types.push(node_type);\\n }\\n }\\n registeredTypes() {\\n return this._camera_types;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/core/BlobUtils.ts\\nfunction createObjectURL(fileOrBlob) {\\n const urlCreator = window.URL || window.webkitURL;\\n return urlCreator.createObjectURL(fileOrBlob);\\n}\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/poly/BlobsController.ts\\nvar BlobsController = class {\\n constructor() {\\n this._blobUrlsByStoredUrl = new Map();\\n this._blobsByStoredUrl = new Map();\\n this._blobDataByNodeId = new Map();\\n this._globalBlobsByStoredUrl = new Map();\\n }\\n registerBlobUrl(data) {\\n if (!Poly.playerMode()) {\\n return;\\n }\\n this._blobUrlsByStoredUrl.set(data.storedUrl, data.blobUrl);\\n }\\n deregisterUrl(url) {\\n this._blobUrlsByStoredUrl.delete(url);\\n }\\n blobUrl(storedUrl) {\\n return this._blobUrlsByStoredUrl.get(storedUrl);\\n }\\n clear() {\\n this._blobUrlsByStoredUrl.clear();\\n this._blobsByStoredUrl.clear();\\n this._blobDataByNodeId.clear();\\n }\\n _clearBlobForNode(node) {\\n const blobData = this._blobDataByNodeId.get(node.graphNodeId());\\n if (blobData) {\\n this._blobsByStoredUrl.delete(blobData.storedUrl);\\n this._blobUrlsByStoredUrl.delete(blobData.storedUrl);\\n }\\n this._blobDataByNodeId.delete(node.graphNodeId());\\n }\\n _assignBlobToNode(node, blobData) {\\n this._clearBlobForNode(node);\\n this._blobDataByNodeId.set(node.graphNodeId(), {\\n storedUrl: blobData.storedUrl,\\n fullUrl: blobData.fullUrl\\n });\\n }\\n async fetchBlobGlobal(options) {\\n if (Poly.playerMode()) {\\n return {};\\n }\\n try {\\n const existingBlob = this._blobUrlsByStoredUrl.get(options.storedUrl);\\n if (existingBlob) {\\n return {};\\n }\\n const remapedUrl = Poly.assetUrls.remapedUrl(options.fullUrl);\\n const response = await fetch(remapedUrl || options.fullUrl);\\n if (response.ok) {\\n const blob = await response.blob();\\n this._blobsByStoredUrl.set(options.storedUrl, blob);\\n this._blobUrlsByStoredUrl.set(options.storedUrl, this.createBlobUrl(blob));\\n this._globalBlobsByStoredUrl.set(options.storedUrl, blob);\\n return {\\n blobData: {\\n storedUrl: options.storedUrl,\\n fullUrl: options.fullUrl\\n }\\n };\\n } else {\\n return {error: `failed to fetch ${options.fullUrl}`};\\n }\\n } catch (err) {\\n return {error: `failed to fetch ${options.fullUrl}`};\\n }\\n }\\n async fetchBlobForNode(options) {\\n if (Poly.playerMode()) {\\n return {};\\n }\\n try {\\n const existingBlob = this._blobUrlsByStoredUrl.get(options.storedUrl);\\n if (existingBlob) {\\n return {};\\n }\\n const remapedUrl = Poly.assetUrls.remapedUrl(options.fullUrl);\\n const response = await fetch(remapedUrl || options.fullUrl);\\n if (response.ok) {\\n const blob = await response.blob();\\n this._blobsByStoredUrl.set(options.storedUrl, blob);\\n this._blobUrlsByStoredUrl.set(options.storedUrl, this.createBlobUrl(blob));\\n this._scene = options.node.scene();\\n this._assignBlobToNode(options.node, {\\n storedUrl: options.storedUrl,\\n fullUrl: options.fullUrl\\n });\\n return {\\n blobData: {\\n storedUrl: options.storedUrl,\\n fullUrl: options.fullUrl\\n }\\n };\\n } else {\\n return {error: `failed to fetch ${options.fullUrl}`};\\n }\\n } catch (err) {\\n return {error: `failed to fetch ${options.fullUrl}`};\\n }\\n }\\n forEachBlob(callback) {\\n this._blobDataByNodeId.forEach((blobData, nodeGraphNodeId) => {\\n if (this._scene) {\\n const node = this._scene.graph.nodeFromId(nodeGraphNodeId);\\n if (node) {\\n const {storedUrl} = blobData;\\n const blob = this._blobsByStoredUrl.get(storedUrl);\\n if (blob) {\\n callback(blob, storedUrl);\\n }\\n }\\n }\\n });\\n let storedUrls = [];\\n const blobsByStoreUrl = new Map();\\n this._globalBlobsByStoredUrl.forEach((blob, storedUrl) => {\\n storedUrls.push(storedUrl);\\n blobsByStoreUrl.set(storedUrl, blob);\\n });\\n storedUrls = storedUrls.sort();\\n storedUrls.forEach((storedUrl) => {\\n const blob = this._globalBlobsByStoredUrl.get(storedUrl);\\n if (blob) {\\n callback(blob, storedUrl);\\n }\\n });\\n }\\n createBlobUrl(blob) {\\n return createObjectURL(blob);\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/poly/AssetUrlsController.ts\\nvar AssetUrlsController = class {\\n setMap(map) {\\n this._map = map;\\n }\\n remapedUrl(url) {\\n if (!this._map) {\\n return;\\n }\\n const elements = url.split(\\\\\\\"?\\\\\\\");\\n const preQuery = elements[0];\\n const query = elements[1];\\n const remapedUrl = this._map[preQuery];\\n if (remapedUrl) {\\n if (query) {\\n return `${remapedUrl}?${query}`;\\n } else {\\n return remapedUrl;\\n }\\n }\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/core/DomEffects.ts\\nvar DomEffects = class {\\n static fadeOut(element) {\\n return new Promise((resolve) => {\\n const fadeEffect = setInterval(() => {\\n if (!element.style.opacity) {\\n element.style.opacity = \\\\\\\"1\\\\\\\";\\n }\\n const opacity = parseFloat(element.style.opacity);\\n if (opacity > 0) {\\n element.style.opacity = `${opacity - 0.05}`;\\n } else {\\n resolve();\\n clearInterval(fadeEffect);\\n }\\n }, 20);\\n });\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/io/self_contained/Common.ts\\nvar SelfContainedFileName;\\n(function(SelfContainedFileName2) {\\n SelfContainedFileName2[\\\\\\\"CODE\\\\\\\"] = \\\\\\\"code.json\\\\\\\";\\n SelfContainedFileName2[\\\\\\\"EDITOR\\\\\\\"] = \\\\\\\"editor.json\\\\\\\";\\n SelfContainedFileName2[\\\\\\\"ASSETS\\\\\\\"] = \\\\\\\"assets.json\\\\\\\";\\n SelfContainedFileName2[\\\\\\\"POLYGONJS\\\\\\\"] = \\\\\\\"js/all.js\\\\\\\";\\n SelfContainedFileName2[\\\\\\\"POLY_CONFIG\\\\\\\"] = \\\\\\\"js/polyConfig.js\\\\\\\";\\n SelfContainedFileName2[\\\\\\\"JS_FILES\\\\\\\"] = \\\\\\\"js_files.json\\\\\\\";\\n SelfContainedFileName2[\\\\\\\"POSTER\\\\\\\"] = \\\\\\\"poster.png\\\\\\\";\\n})(SelfContainedFileName || (SelfContainedFileName = {}));\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/poly/SelfContainedSceneLoader.ts\\nvar SelfContainedScenesLoader = class {\\n markAsLoaded(callback, sceneJsonImporterContructor) {\\n this._sceneJsonImporterContructor = sceneJsonImporterContructor;\\n callback();\\n }\\n load(map) {\\n if (!this._sceneJsonImporterContructor) {\\n return;\\n }\\n const elements = [];\\n map.forEach((data, element) => {\\n elements.push(element);\\n });\\n for (let element of elements) {\\n const data = map.get(element);\\n if (data) {\\n this._loadElement(element, data, this._sceneJsonImporterContructor);\\n map.delete(element);\\n }\\n }\\n }\\n async _loadElement(element, viewerData, sceneJsonImporterContructor) {\\n const {sceneData, assetsManifest, unzippedData} = viewerData;\\n const storedUrls = Object.keys(assetsManifest);\\n for (let storedUrl of storedUrls) {\\n const assetUrl = assetsManifest[storedUrl];\\n const assetUintArray = unzippedData[`assets/${assetUrl}`];\\n if (!assetUintArray) {\\n console.error(storedUrl, assetUintArray);\\n return;\\n }\\n const assetBlob = new Blob([assetUintArray]);\\n const blobUrl = Poly.blobs.createBlobUrl(assetBlob);\\n const blobUrlData = {\\n storedUrl,\\n blobUrl\\n };\\n Poly.blobs.registerBlobUrl(blobUrlData);\\n }\\n Poly.setPlayerMode(true);\\n Poly.libs.setRoot(null);\\n const polyConfigId = `${Math.random()}`.replace(\\\\\\\".\\\\\\\", \\\\\\\"_\\\\\\\");\\n const ids = {\\n Poly: `___POLY_polyConfig_configurePolygonjs_${polyConfigId}`,\\n scriptElementId: `___POLY_polyConfig_scriptElement_${polyConfigId}`,\\n loadSceneArgs: `___POLY_polyConfig_loadSceneArgs_${polyConfigId}`\\n };\\n window[ids.Poly] = Poly;\\n const method = this._loadScene.bind(this);\\n const loadSceneArgs = {\\n method,\\n element,\\n sceneData,\\n sceneJsonImporterContructor\\n };\\n window[ids.loadSceneArgs] = loadSceneArgs;\\n const polyConfigLoaded = this._loadPolyConfig(ids, unzippedData);\\n if (polyConfigLoaded) {\\n return;\\n }\\n this._loadScene(element, sceneData, sceneJsonImporterContructor);\\n }\\n _loadPolyConfig(ids, unzippedData) {\\n const polyConfigArray = unzippedData[SelfContainedFileName.POLY_CONFIG];\\n if (!polyConfigArray) {\\n return false;\\n }\\n const polyConfigUrl = this._createJsBlob(polyConfigArray, \\\\\\\"polyConfig\\\\\\\");\\n let script = document.getElementById(ids.scriptElementId);\\n const lines = [];\\n lines.push(`import {configurePolygonjs, configureScene} from '${polyConfigUrl}';`);\\n lines.push(`configurePolygonjs(window.${ids.Poly});`);\\n lines.push(`window.${ids.loadSceneArgs}.method(window.${ids.loadSceneArgs}.element, window.${ids.loadSceneArgs}.sceneData, window.${ids.loadSceneArgs}.sceneJsonImporterContructor, configureScene);`);\\n lines.push(`delete window.${ids.loadSceneArgs};`);\\n if (!script) {\\n script = document.createElement(\\\\\\\"script\\\\\\\");\\n script.setAttribute(\\\\\\\"type\\\\\\\", \\\\\\\"module\\\\\\\");\\n script.text = lines.join(\\\\\\\"\\\\n\\\\\\\");\\n document.body.append(script);\\n }\\n return true;\\n }\\n async _loadScene(element, sceneData, sceneJsonImporterContructor, configureScene2) {\\n this._fadeOutPoster(element);\\n const importer = new sceneJsonImporterContructor(sceneData);\\n const scene = await importer.scene();\\n if (configureScene2) {\\n configureScene2(scene);\\n }\\n const cameraNode = scene.mainCameraNode();\\n if (!cameraNode) {\\n console.warn(\\\\\\\"no master camera found\\\\\\\");\\n return;\\n }\\n const viewer = cameraNode.createViewer(element);\\n scene.play();\\n element.scene = scene;\\n element.viewer = viewer;\\n }\\n _fadeOutPoster(element) {\\n const posterElement = element.firstElementChild;\\n if (posterElement) {\\n posterElement.style.pointerEvents = \\\\\\\"none\\\\\\\";\\n DomEffects.fadeOut(posterElement).then(() => {\\n posterElement.parentElement?.removeChild(posterElement);\\n });\\n }\\n }\\n _createJsBlob(array, filename) {\\n const blob = new Blob([array]);\\n const file = new File([blob], `${filename}.js`, {type: \\\\\\\"application/javascript\\\\\\\"});\\n return createObjectURL(file);\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/poly/PerformanceController.ts\\nvar PolyPerformanceformanceController = class {\\n setPerformanceManager(p) {\\n this._performanceManager = p;\\n }\\n performanceManager() {\\n return this._performanceManager || window.performance;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/Poly.ts\\nvar PolyEngine = class {\\n constructor() {\\n this.renderersController = new RenderersController();\\n this.nodesRegister = new NodesRegister(this);\\n this.operationsRegister = new OperationsRegister(this);\\n this.expressionsRegister = new ExpressionRegister();\\n this.modulesRegister = new DynamicModulesRegister();\\n this.assemblersRegister = new AssemblersRegister();\\n this.pluginsRegister = new PluginsRegister(this);\\n this.camerasRegister = new CamerasRegister(this);\\n this.blobs = new BlobsController();\\n this.assetUrls = new AssetUrlsController();\\n this.selfContainedScenesLoader = new SelfContainedScenesLoader();\\n this.performance = new PolyPerformanceformanceController();\\n this.scenesByUuid = {};\\n this._player_mode = true;\\n this._logger = null;\\n }\\n static _instance_() {\\n if (window.__POLYGONJS_POLY_INSTANCE__) {\\n return window.__POLYGONJS_POLY_INSTANCE__;\\n } else {\\n const instance = new PolyEngine();\\n window.__POLYGONJS_POLY_INSTANCE__ = instance;\\n return window.__POLYGONJS_POLY_INSTANCE__;\\n }\\n }\\n setPlayerMode(mode) {\\n this._player_mode = mode;\\n }\\n playerMode() {\\n return this._player_mode;\\n }\\n registerNode(node, tab_menu_category, options) {\\n this.nodesRegister.register(node, tab_menu_category, options);\\n }\\n registerOperation(operation) {\\n this.operationsRegister.register(operation);\\n }\\n registerCamera(node) {\\n this.camerasRegister.register(node);\\n }\\n registerPlugin(plugin) {\\n this.pluginsRegister.register(plugin);\\n }\\n registeredNodes(parent_context, type) {\\n return this.nodesRegister.registeredNodes(parent_context, type);\\n }\\n registeredOperation(parent_context, operation_type) {\\n return this.operationsRegister.registeredOperation(parent_context, operation_type);\\n }\\n registeredCameraTypes() {\\n return this.camerasRegister.registeredTypes();\\n }\\n inWorkerThread() {\\n return false;\\n }\\n desktopController() {\\n }\\n get libs() {\\n return this._libs_controller = this._libs_controller || new PolyLibsController();\\n }\\n setEnv(env) {\\n this._env = env;\\n }\\n env() {\\n return this._env;\\n }\\n setLogger(logger) {\\n this._logger = logger;\\n }\\n log(message, ...optionalParams) {\\n this._logger?.log(...[message, ...optionalParams]);\\n }\\n warn(message, ...optionalParams) {\\n this._logger?.warn(...[message, ...optionalParams]);\\n }\\n error(message, ...optionalParams) {\\n this._logger?.error(...[message, ...optionalParams]);\\n }\\n};\\nvar Poly = PolyEngine._instance_();\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/core/graph/DirtyController.ts\\nvar DirtyController = class {\\n constructor(node) {\\n this.node = node;\\n this._dirty_count = 0;\\n this._dirty = true;\\n }\\n dispose() {\\n this._cached_successors = void 0;\\n this._post_dirty_hooks = void 0;\\n this._post_dirty_hook_names = void 0;\\n }\\n isDirty() {\\n return this._dirty === true;\\n }\\n dirtyTimestamp() {\\n return this._dirty_timestamp;\\n }\\n dirtyCount() {\\n return this._dirty_count;\\n }\\n addPostDirtyHook(name, method) {\\n this._post_dirty_hook_names = this._post_dirty_hook_names || [];\\n this._post_dirty_hooks = this._post_dirty_hooks || [];\\n if (!this._post_dirty_hook_names.includes(name)) {\\n this._post_dirty_hook_names.push(name);\\n this._post_dirty_hooks.push(method);\\n } else {\\n console.warn(`hook with name ${name} already exists`, this.node);\\n }\\n }\\n removePostDirtyHook(name) {\\n if (this._post_dirty_hook_names && this._post_dirty_hooks) {\\n const index = this._post_dirty_hook_names.indexOf(name);\\n if (index >= 0) {\\n this._post_dirty_hook_names.splice(index, 1);\\n this._post_dirty_hooks.splice(index, 1);\\n }\\n }\\n }\\n hasHook(name) {\\n if (this._post_dirty_hook_names) {\\n return this._post_dirty_hook_names.includes(name);\\n }\\n return false;\\n }\\n removeDirtyState() {\\n this._dirty = false;\\n }\\n setForbiddenTriggerNodes(nodes) {\\n this._forbidden_trigger_nodes = nodes.map((n) => n.graphNodeId());\\n }\\n setDirty(original_trigger_graph_node, propagate) {\\n if (propagate == null) {\\n propagate = true;\\n }\\n if (original_trigger_graph_node && this._forbidden_trigger_nodes && this._forbidden_trigger_nodes.includes(original_trigger_graph_node.graphNodeId())) {\\n return;\\n }\\n if (original_trigger_graph_node == null) {\\n original_trigger_graph_node = this.node;\\n }\\n this._dirty = true;\\n const performance2 = Poly.performance.performanceManager();\\n this._dirty_timestamp = performance2.now();\\n this._dirty_count += 1;\\n this.runPostDirtyHooks(original_trigger_graph_node);\\n if (propagate === true) {\\n this.setSuccessorsDirty(original_trigger_graph_node);\\n }\\n }\\n runPostDirtyHooks(original_trigger_graph_node) {\\n if (this._post_dirty_hooks) {\\n const cooker = this.node.scene().cooker;\\n if (cooker.blocked) {\\n cooker.enqueue(this.node, original_trigger_graph_node);\\n } else {\\n for (let hook of this._post_dirty_hooks) {\\n hook(original_trigger_graph_node);\\n }\\n }\\n }\\n }\\n setSuccessorsDirty(original_trigger_graph_node) {\\n const propagate = false;\\n this._cached_successors = this._cached_successors || this.node.graphAllSuccessors();\\n for (let successor of this._cached_successors) {\\n successor.dirtyController.setDirty(original_trigger_graph_node, propagate);\\n }\\n }\\n clearSuccessorsCache() {\\n this._cached_successors = void 0;\\n }\\n clearSuccessorsCacheWithPredecessors() {\\n this.clearSuccessorsCache();\\n for (let predecessor of this.node.graphAllPredecessors()) {\\n predecessor.dirtyController.clearSuccessorsCache();\\n }\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/core/graph/CoreGraphNode.ts\\nvar CoreGraphNode = class {\\n constructor(_scene, _name) {\\n this._scene = _scene;\\n this._name = _name;\\n this._dirty_controller = new DirtyController(this);\\n this._graph_node_id = _scene.graph.nextId();\\n _scene.graph.addNode(this);\\n this._graph = _scene.graph;\\n }\\n dispose() {\\n this._dirty_controller.dispose();\\n this.graphRemove();\\n }\\n name() {\\n return this._name;\\n }\\n setName(name) {\\n this._name = name;\\n }\\n scene() {\\n return this._scene;\\n }\\n graphNodeId() {\\n return this._graph_node_id;\\n }\\n get dirtyController() {\\n return this._dirty_controller;\\n }\\n setDirty(trigger) {\\n trigger = trigger || this;\\n this._dirty_controller.setDirty(trigger);\\n }\\n setSuccessorsDirty(trigger) {\\n this._dirty_controller.setSuccessorsDirty(trigger);\\n }\\n removeDirtyState() {\\n this._dirty_controller.removeDirtyState();\\n }\\n isDirty() {\\n return this._dirty_controller.isDirty();\\n }\\n addPostDirtyHook(name, callback) {\\n this._dirty_controller.addPostDirtyHook(name, callback);\\n }\\n graphRemove() {\\n this._graph.removeNode(this);\\n }\\n addGraphInput(src, check_if_graph_has_cycle = true) {\\n return this._graph.connect(src, this, check_if_graph_has_cycle);\\n }\\n removeGraphInput(src) {\\n this._graph.disconnect(src, this);\\n }\\n graphDisconnectPredecessors() {\\n this._graph.disconnectPredecessors(this);\\n }\\n graphDisconnectSuccessors() {\\n this._graph.disconnectSuccessors(this);\\n }\\n graphPredecessorIds() {\\n return this._graph.predecessorIds(this._graph_node_id) || [];\\n }\\n graphPredecessors() {\\n return this._graph.predecessors(this);\\n }\\n graphSuccessors() {\\n return this._graph.successors(this);\\n }\\n graphAllPredecessors() {\\n return this._graph.allPredecessors(this);\\n }\\n graphAllSuccessors() {\\n return this._graph.allSuccessors(this);\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/poly/NodeEvent.ts\\nvar NodeEvent;\\n(function(NodeEvent2) {\\n NodeEvent2[\\\\\\\"CREATED\\\\\\\"] = \\\\\\\"node_created\\\\\\\";\\n NodeEvent2[\\\\\\\"DELETED\\\\\\\"] = \\\\\\\"node_deleted\\\\\\\";\\n NodeEvent2[\\\\\\\"NAME_UPDATED\\\\\\\"] = \\\\\\\"node_name_update\\\\\\\";\\n NodeEvent2[\\\\\\\"OVERRIDE_CLONABLE_STATE_UPDATE\\\\\\\"] = \\\\\\\"node_override_clonable_state_update\\\\\\\";\\n NodeEvent2[\\\\\\\"NAMED_OUTPUTS_UPDATED\\\\\\\"] = \\\\\\\"node_named_outputs_updated\\\\\\\";\\n NodeEvent2[\\\\\\\"NAMED_INPUTS_UPDATED\\\\\\\"] = \\\\\\\"node_named_inputs_updated\\\\\\\";\\n NodeEvent2[\\\\\\\"INPUTS_UPDATED\\\\\\\"] = \\\\\\\"node_inputs_updated\\\\\\\";\\n NodeEvent2[\\\\\\\"PARAMS_UPDATED\\\\\\\"] = \\\\\\\"node_params_updated\\\\\\\";\\n NodeEvent2[\\\\\\\"UI_DATA_POSITION_UPDATED\\\\\\\"] = \\\\\\\"node_ui_data_position_updated\\\\\\\";\\n NodeEvent2[\\\\\\\"UI_DATA_COMMENT_UPDATED\\\\\\\"] = \\\\\\\"node_ui_data_comment_updated\\\\\\\";\\n NodeEvent2[\\\\\\\"ERROR_UPDATED\\\\\\\"] = \\\\\\\"node_error_updated\\\\\\\";\\n NodeEvent2[\\\\\\\"FLAG_BYPASS_UPDATED\\\\\\\"] = \\\\\\\"bypass_flag_updated\\\\\\\";\\n NodeEvent2[\\\\\\\"FLAG_DISPLAY_UPDATED\\\\\\\"] = \\\\\\\"display_flag_updated\\\\\\\";\\n NodeEvent2[\\\\\\\"FLAG_OPTIMIZE_UPDATED\\\\\\\"] = \\\\\\\"optimize_flag_updated\\\\\\\";\\n NodeEvent2[\\\\\\\"SELECTION_UPDATED\\\\\\\"] = \\\\\\\"selection_updated\\\\\\\";\\n})(NodeEvent || (NodeEvent = {}));\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/core/Type.ts\\nvar CoreType = class {\\n static isNumber(value) {\\n return typeof value == \\\\\\\"number\\\\\\\";\\n }\\n static isVector(value) {\\n return value instanceof Vector2 || value instanceof Vector3 || value instanceof Vector4;\\n }\\n static isString(value) {\\n return typeof value == \\\\\\\"string\\\\\\\";\\n }\\n static isBoolean(value) {\\n return value === true || value === false;\\n }\\n static isNaN(value) {\\n return isNaN(value);\\n }\\n static isArray(value) {\\n return Array.isArray(value);\\n }\\n static isObject(value) {\\n var type = typeof value;\\n return value != null && (type == \\\\\\\"object\\\\\\\" || type == \\\\\\\"function\\\\\\\");\\n }\\n};\\nfunction isBooleanTrue(value) {\\n return value;\\n}\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/utils/UIData.ts\\nvar UIData = class {\\n constructor(node, x = 0, y = 0) {\\n this.node = node;\\n this._position = new Vector2();\\n this._width = 50;\\n this._color = new Color(0.75, 0.75, 0.75);\\n this._layout_vertical = true;\\n this._json = {\\n x: 0,\\n y: 0\\n };\\n this._position.x = x;\\n this._position.y = y;\\n }\\n setComment(comment) {\\n this._comment = comment;\\n this.node.emit(NodeEvent.UI_DATA_COMMENT_UPDATED);\\n }\\n comment() {\\n return this._comment;\\n }\\n setColor(color) {\\n this._color = color;\\n }\\n color() {\\n return this._color;\\n }\\n setLayoutHorizontal() {\\n this._layout_vertical = false;\\n }\\n isLayoutVertical() {\\n return this._layout_vertical;\\n }\\n copy(ui_data) {\\n this._position.copy(ui_data.position());\\n this._color.copy(ui_data.color());\\n }\\n position() {\\n return this._position;\\n }\\n setPosition(new_position, y = 0) {\\n if (CoreType.isNumber(new_position)) {\\n const x = new_position;\\n this._position.set(x, y);\\n } else {\\n this._position.copy(new_position);\\n }\\n this.node.emit(NodeEvent.UI_DATA_POSITION_UPDATED);\\n }\\n translate(offset, snap = false) {\\n this._position.add(offset);\\n if (snap) {\\n this._position.x = Math.round(this._position.x);\\n this._position.y = Math.round(this._position.y);\\n }\\n this.node.emit(NodeEvent.UI_DATA_POSITION_UPDATED);\\n }\\n toJSON() {\\n this._json.x = this._position.x;\\n this._json.y = this._position.y;\\n this._json.comment = this._comment;\\n return this._json;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/utils/flags/Base.ts\\nvar BaseFlag = class {\\n constructor(node) {\\n this.node = node;\\n this._state = true;\\n this._hooks = null;\\n }\\n onUpdate(hook) {\\n this._hooks = this._hooks || [];\\n this._hooks.push(hook);\\n }\\n _on_update() {\\n }\\n set(new_state) {\\n if (this._state != new_state) {\\n this._state = new_state;\\n this._on_update();\\n this.runHooks();\\n }\\n }\\n active() {\\n return this._state;\\n }\\n toggle() {\\n this.set(!this._state);\\n }\\n runHooks() {\\n if (this._hooks) {\\n for (let hook of this._hooks) {\\n hook();\\n }\\n }\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/utils/flags/Bypass.ts\\nvar BypassFlag = class extends BaseFlag {\\n constructor() {\\n super(...arguments);\\n this._state = false;\\n }\\n _on_update() {\\n this.node.emit(NodeEvent.FLAG_BYPASS_UPDATED);\\n this.node.setDirty();\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/utils/flags/Display.ts\\nvar DisplayFlag = class extends BaseFlag {\\n _on_update() {\\n this.node.emit(NodeEvent.FLAG_DISPLAY_UPDATED);\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/utils/flags/Optimize.ts\\nvar OptimizeFlag = class extends BaseFlag {\\n constructor() {\\n super(...arguments);\\n this._state = false;\\n }\\n _on_update() {\\n this.node.emit(NodeEvent.FLAG_OPTIMIZE_UPDATED);\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/utils/FlagsController.ts\\nvar FlagsController = class {\\n constructor(node) {\\n this.node = node;\\n }\\n hasDisplay() {\\n return false;\\n }\\n hasBypass() {\\n return false;\\n }\\n hasOptimize() {\\n return false;\\n }\\n};\\nfunction Display(Base) {\\n return class Mixin extends Base {\\n constructor() {\\n super(...arguments);\\n this.display = new DisplayFlag(this.node);\\n }\\n hasDisplay() {\\n return true;\\n }\\n };\\n}\\nfunction Bypass(Base) {\\n return class Mixin extends Base {\\n constructor() {\\n super(...arguments);\\n this.bypass = new BypassFlag(this.node);\\n }\\n hasBypass() {\\n return true;\\n }\\n };\\n}\\nfunction Optimize(Base) {\\n return class Mixin extends Base {\\n constructor() {\\n super(...arguments);\\n this.optimize = new OptimizeFlag(this.node);\\n }\\n hasOptimize() {\\n return true;\\n }\\n };\\n}\\nvar FlagsControllerD = class extends Display(FlagsController) {\\n};\\nvar FlagsControllerB = class extends Bypass(FlagsController) {\\n};\\nvar FlagsControllerDB = class extends Bypass(Display(FlagsController)) {\\n};\\nvar FlagsControllerBO = class extends Optimize(Bypass(FlagsController)) {\\n};\\nvar FlagsControllerDBO = class extends Optimize(Bypass(Display(FlagsController))) {\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/utils/states/Base.ts\\nvar BaseState = class {\\n constructor(node) {\\n this.node = node;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/utils/states/TimeDependent.ts\\nvar TimeDependentState = class extends BaseState {\\n active() {\\n return this.paramsTimeDependent() || this.inputsTimeDependent();\\n }\\n paramsTimeDependent() {\\n const param_names = this.node.params.names;\\n for (let param_name of param_names) {\\n const param = this.node.params.get(param_name);\\n if (param && param.states.timeDependent.active()) {\\n return true;\\n }\\n }\\n return false;\\n }\\n inputsTimeDependent() {\\n const inputs = this.node.io.inputs.inputs();\\n for (let input of inputs) {\\n if (input && input.states.timeDependent.active()) {\\n return true;\\n }\\n }\\n return false;\\n }\\n forceTimeDependent() {\\n const predecessor_ids = this.node.graphPredecessors().map((n) => n.graphNodeId());\\n const frame_node = this.node.scene().timeController.graphNode;\\n if (!predecessor_ids.includes(frame_node.graphNodeId())) {\\n this.node.addGraphInput(frame_node, false);\\n }\\n }\\n unforceTimeDependent() {\\n const frame_node = this.node.scene().timeController.graphNode;\\n this.node.removeGraphInput(frame_node);\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/utils/states/Error.ts\\nvar NodeErrorState = class extends BaseState {\\n set(message) {\\n if (this._message != message) {\\n if (message) {\\n Poly.error(`[${this.node.path()}] error: '${message}'`);\\n }\\n this._message = message;\\n this.onUpdate();\\n }\\n }\\n message() {\\n return this._message;\\n }\\n clear() {\\n this.set(void 0);\\n }\\n active() {\\n return this._message != null;\\n }\\n onUpdate() {\\n if (this._message != null) {\\n this.node._setContainer(null, `from error '${this._message}'`);\\n }\\n this.node.emit(NodeEvent.ERROR_UPDATED);\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/utils/StatesController.ts\\nvar StatesController = class {\\n constructor(node) {\\n this.node = node;\\n this.timeDependent = new TimeDependentState(this.node);\\n this.error = new NodeErrorState(this.node);\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/utils/NameController.ts\\nvar NameController = class {\\n constructor(node) {\\n this.node = node;\\n this._graph_node = new CoreGraphNode(node.scene(), \\\\\\\"node_name_controller\\\\\\\");\\n }\\n dispose() {\\n this._graph_node.dispose();\\n this._on_set_name_hooks = void 0;\\n this._on_set_fullPath_hooks = void 0;\\n }\\n get graph_node() {\\n return this._graph_node;\\n }\\n static base_name(node) {\\n let base = node.type();\\n const last_char = base[base.length - 1];\\n if (!CoreType.isNaN(parseInt(last_char))) {\\n base += \\\\\\\"_\\\\\\\";\\n }\\n return `${base}1`;\\n }\\n requestNameToParent(new_name) {\\n const parent = this.node.parent();\\n if (parent && parent.childrenAllowed() && parent.childrenController) {\\n parent.childrenController.setChildName(this.node, new_name);\\n } else {\\n console.warn(\\\\\\\"requestNameToParent failed, no parent found\\\\\\\");\\n }\\n }\\n setName(new_name) {\\n if (new_name != this.node.name()) {\\n this.requestNameToParent(new_name);\\n }\\n }\\n updateNameFromParent(new_name) {\\n this.node._set_core_name(new_name);\\n this._postSetName();\\n this.runPostSetFullPathHooks();\\n if (this.node.childrenAllowed()) {\\n const children = this.node.childrenController?.children();\\n if (children) {\\n for (let child_node of children) {\\n child_node.nameController.runPostSetFullPathHooks();\\n }\\n }\\n }\\n if (this.node.lifecycle.creationCompleted()) {\\n this.node.scene().missingExpressionReferencesController.checkForMissingReferences(this.node);\\n this.node.scene().expressionsController.regenerateReferringExpressions(this.node);\\n }\\n this.node.scene().referencesController.notifyNameUpdated(this.node);\\n this.node.emit(NodeEvent.NAME_UPDATED);\\n }\\n add_post_set_name_hook(hook) {\\n this._on_set_name_hooks = this._on_set_name_hooks || [];\\n this._on_set_name_hooks.push(hook);\\n }\\n add_post_set_fullPath_hook(hook) {\\n this._on_set_fullPath_hooks = this._on_set_fullPath_hooks || [];\\n this._on_set_fullPath_hooks.push(hook);\\n }\\n _postSetName() {\\n if (this._on_set_name_hooks) {\\n for (let hook of this._on_set_name_hooks) {\\n hook();\\n }\\n }\\n }\\n runPostSetFullPathHooks() {\\n if (this._on_set_fullPath_hooks) {\\n for (let hook of this._on_set_fullPath_hooks) {\\n hook();\\n }\\n }\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/core/Walker.ts\\nvar TypedNodePathParamValue = class {\\n constructor(_path = \\\\\\\"\\\\\\\") {\\n this._path = _path;\\n this._node = null;\\n }\\n set_path(path) {\\n this._path = path;\\n }\\n set_node(node) {\\n this._node = node;\\n }\\n path() {\\n return this._path;\\n }\\n node() {\\n return this._node;\\n }\\n resolve(node_start) {\\n this._node = CoreWalker.findNode(node_start, this._path);\\n }\\n clone() {\\n const cloned = new TypedNodePathParamValue(this._path);\\n cloned.set_node(this._node);\\n return cloned;\\n }\\n nodeWithContext(context, error_state) {\\n const found_node = this.node();\\n if (!found_node) {\\n error_state?.set(`no node found at ${this.path()}`);\\n return;\\n }\\n const node_context = found_node.context();\\n if (node_context == context) {\\n return found_node;\\n } else {\\n error_state?.set(`expected ${context} node, but got a ${node_context}`);\\n return;\\n }\\n }\\n};\\nvar TypedParamPathParamValue = class {\\n constructor(_path = \\\\\\\"\\\\\\\") {\\n this._path = _path;\\n this._param = null;\\n }\\n set_path(path) {\\n this._path = path;\\n }\\n set_param(param) {\\n this._param = param;\\n }\\n path() {\\n return this._path;\\n }\\n param() {\\n return this._param;\\n }\\n resolve(node_start) {\\n this._param = CoreWalker.findParam(node_start, this._path);\\n }\\n clone() {\\n const cloned = new TypedParamPathParamValue(this._path);\\n cloned.set_param(this._param);\\n return cloned;\\n }\\n paramWithType(paramType, error_state) {\\n const foundParam = this.param();\\n if (!foundParam) {\\n error_state?.set(`no param found at ${this.path()}`);\\n return;\\n }\\n if (foundParam.type() == paramType) {\\n return foundParam;\\n } else {\\n error_state?.set(`expected ${paramType} node, but got a ${foundParam.type()}`);\\n return;\\n }\\n }\\n};\\nvar CoreWalker2 = class {\\n static split_parent_child(path) {\\n const elements = path.split(CoreWalker2.SEPARATOR).filter((e) => e.length > 0);\\n const child_path = elements.pop();\\n const parent_path = elements.join(CoreWalker2.SEPARATOR);\\n return {parent: parent_path, child: child_path};\\n }\\n static findNode(node_src, path, decomposed_path) {\\n if (!node_src) {\\n return null;\\n }\\n const elements = path.split(CoreWalker2.SEPARATOR).filter((e) => e.length > 0);\\n const first_element = elements[0];\\n let next_node = null;\\n if (path[0] === CoreWalker2.SEPARATOR) {\\n const path_from_root = path.substr(1);\\n next_node = this.findNode(node_src.root(), path_from_root, decomposed_path);\\n } else {\\n switch (first_element) {\\n case CoreWalker2.PARENT:\\n decomposed_path?.add_path_element(first_element);\\n next_node = node_src.parent();\\n break;\\n case CoreWalker2.CURRENT:\\n decomposed_path?.add_path_element(first_element);\\n next_node = node_src;\\n break;\\n default:\\n next_node = node_src.node(first_element);\\n if (next_node) {\\n decomposed_path?.add_node(first_element, next_node);\\n }\\n }\\n if (next_node != null && elements.length > 1) {\\n const remainder = elements.slice(1).join(CoreWalker2.SEPARATOR);\\n next_node = this.findNode(next_node, remainder, decomposed_path);\\n }\\n return next_node;\\n }\\n return next_node;\\n }\\n static findParam(node_src, path, decomposed_path) {\\n if (!node_src) {\\n return null;\\n }\\n const elements = path.split(CoreWalker2.SEPARATOR);\\n if (elements.length === 1) {\\n return node_src.params.get(elements[0]);\\n } else {\\n const node_path = elements.slice(0, +(elements.length - 2) + 1 || void 0).join(CoreWalker2.SEPARATOR);\\n const node = this.findNode(node_src, node_path, decomposed_path);\\n if (node != null) {\\n const param_name = elements[elements.length - 1];\\n const param = node.params.get(param_name);\\n if (decomposed_path && param) {\\n decomposed_path.add_node(param_name, param);\\n }\\n return param;\\n } else {\\n return null;\\n }\\n }\\n }\\n static relativePath(src_graph_node, dest_graph_node) {\\n const parent = this.closestCommonParent(src_graph_node, dest_graph_node);\\n if (!parent) {\\n return dest_graph_node.path();\\n } else {\\n const distance = this.distanceToParent(src_graph_node, parent);\\n let up = \\\\\\\"\\\\\\\";\\n if (distance > 0) {\\n let i = 0;\\n const ups = [];\\n while (i++ < distance) {\\n ups.push(CoreWalker2.PARENT);\\n }\\n up = ups.join(CoreWalker2.SEPARATOR) + CoreWalker2.SEPARATOR;\\n }\\n const parent_path_elements = parent.path().split(CoreWalker2.SEPARATOR).filter((e) => e.length > 0);\\n const dest_path_elements = dest_graph_node.path().split(CoreWalker2.SEPARATOR).filter((e) => e.length > 0);\\n const remaining_elements = [];\\n let cmptr = 0;\\n for (let dest_path_element of dest_path_elements) {\\n if (!parent_path_elements[cmptr]) {\\n remaining_elements.push(dest_path_element);\\n }\\n cmptr++;\\n }\\n const down = remaining_elements.join(CoreWalker2.SEPARATOR);\\n return `${up}${down}`;\\n }\\n }\\n static closestCommonParent(graph_node1, graph_node2) {\\n const parents1 = this.parents(graph_node1).reverse().concat([graph_node1]);\\n const parents2 = this.parents(graph_node2).reverse().concat([graph_node2]);\\n const min_depth = Math.min(parents1.length, parents2.length);\\n let found_parent = null;\\n for (let i = 0; i < min_depth; i++) {\\n if (parents1[i].graphNodeId() == parents2[i].graphNodeId()) {\\n found_parent = parents1[i];\\n }\\n }\\n return found_parent;\\n }\\n static parents(graph_node) {\\n const parents = [];\\n let parent = graph_node.parent();\\n while (parent) {\\n parents.push(parent);\\n parent = parent.parent();\\n }\\n return parents;\\n }\\n static distanceToParent(graph_node, dest) {\\n let distance = 0;\\n let current = graph_node;\\n const dest_id = dest.graphNodeId();\\n while (current && current.graphNodeId() != dest_id) {\\n distance += 1;\\n current = current.parent();\\n }\\n if (current && current.graphNodeId() == dest_id) {\\n return distance;\\n } else {\\n return -1;\\n }\\n }\\n static makeAbsolutePath(nodeSrc, path) {\\n if (path[0] == CoreWalker2.SEPARATOR) {\\n return path;\\n }\\n const pathElements = path.split(CoreWalker2.SEPARATOR);\\n const firstElement = pathElements.shift();\\n if (firstElement) {\\n switch (firstElement) {\\n case \\\\\\\"..\\\\\\\": {\\n const parent = nodeSrc.parent();\\n if (parent) {\\n if (parent == nodeSrc.scene().root()) {\\n return CoreWalker2.SEPARATOR + pathElements.join(CoreWalker2.SEPARATOR);\\n } else {\\n return this.makeAbsolutePath(parent, pathElements.join(CoreWalker2.SEPARATOR));\\n }\\n } else {\\n return null;\\n }\\n }\\n case \\\\\\\".\\\\\\\": {\\n return this.makeAbsolutePath(nodeSrc, pathElements.join(CoreWalker2.SEPARATOR));\\n }\\n default: {\\n return [nodeSrc.path(), path].join(CoreWalker2.SEPARATOR);\\n }\\n }\\n } else {\\n return nodeSrc.path();\\n }\\n }\\n};\\nvar CoreWalker = CoreWalker2;\\nCoreWalker.SEPARATOR = \\\\\\\"/\\\\\\\";\\nCoreWalker.DOT = \\\\\\\".\\\\\\\";\\nCoreWalker.CURRENT = CoreWalker2.DOT;\\nCoreWalker.PARENT = \\\\\\\"..\\\\\\\";\\nCoreWalker.CURRENT_WITH_SLASH = `${CoreWalker2.CURRENT}/`;\\nCoreWalker.PARENT_WITH_SLASH = `${CoreWalker2.PARENT}/`;\\nCoreWalker.NON_LETTER_PREFIXES = [CoreWalker2.SEPARATOR, CoreWalker2.DOT];\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/utils/hierarchy/ParentController.ts\\nvar HierarchyParentController = class {\\n constructor(node) {\\n this.node = node;\\n this._parent = null;\\n }\\n parent() {\\n return this._parent;\\n }\\n setParent(parent) {\\n if (parent != this.node.parentController.parent()) {\\n this._parent = parent;\\n if (this._parent) {\\n this.node.nameController.requestNameToParent(NameController.base_name(this.node));\\n }\\n }\\n }\\n firstAncestorWithContext(context) {\\n if (this._parent) {\\n if (this._parent.context() == context) {\\n return this._parent;\\n } else {\\n return this._parent.parentController.firstAncestorWithContext(context);\\n }\\n }\\n return null;\\n }\\n path(relative_to_parent) {\\n const separator = CoreWalker.SEPARATOR;\\n if (this._parent != null) {\\n if (this._parent == relative_to_parent) {\\n return this.node.name();\\n } else {\\n const parent_fullPath = this._parent.path(relative_to_parent);\\n if (parent_fullPath === separator) {\\n return parent_fullPath + this.node.name();\\n } else {\\n return parent_fullPath + separator + this.node.name();\\n }\\n }\\n } else {\\n return separator;\\n }\\n }\\n onSetParent() {\\n if (this._on_set_parent_hooks) {\\n for (let hook of this._on_set_parent_hooks) {\\n hook();\\n }\\n }\\n }\\n findNode(path) {\\n if (path == null) {\\n return null;\\n }\\n if (path == CoreWalker.CURRENT || path == CoreWalker.CURRENT_WITH_SLASH) {\\n return this.node;\\n }\\n if (path == CoreWalker.PARENT || path == CoreWalker.PARENT_WITH_SLASH) {\\n return this.node.parent();\\n }\\n const separator = CoreWalker.SEPARATOR;\\n if (path === separator) {\\n return this.node.scene().root();\\n }\\n if (path[0] === separator) {\\n path = path.substring(1, path.length);\\n return this.node.scene().root().node(path);\\n }\\n if (path.split) {\\n const elements = path.split(separator);\\n if (elements.length === 1) {\\n const name = elements[0];\\n if (this.node.childrenController) {\\n return this.node.childrenController.childByName(name);\\n } else {\\n return null;\\n }\\n } else {\\n return CoreWalker.findNode(this.node, path);\\n }\\n } else {\\n console.error(\\\\\\\"unexpected path given:\\\\\\\", path);\\n return null;\\n }\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/core/MapUtils.ts\\nvar MapUtils = class {\\n static arrayFromValues(map) {\\n const array = [];\\n map.forEach((v) => {\\n array.push(v);\\n });\\n return array;\\n }\\n static pushOnArrayAtEntry(map, key, newElement) {\\n let has_entry = map.has(key);\\n if (has_entry) {\\n map.get(key).push(newElement);\\n } else {\\n map.set(key, [newElement]);\\n }\\n }\\n static addToSetAtEntry(map, key, newElement) {\\n let has_entry = map.has(key);\\n if (has_entry) {\\n map.get(key).add(newElement);\\n } else {\\n const set = new Set();\\n set.add(newElement);\\n map.set(key, set);\\n }\\n }\\n static popFromArrayAtEntry(map, key, elementToRemove) {\\n let has_entry = map.has(key);\\n if (has_entry) {\\n const array = map.get(key);\\n const index = array.indexOf(elementToRemove);\\n if (index >= 0) {\\n array.splice(index, 1);\\n }\\n }\\n }\\n static removeFromSetAtEntry(map, key, elementToRemove) {\\n let has_entry = map.has(key);\\n if (has_entry) {\\n const set = map.get(key);\\n set.delete(elementToRemove);\\n if (set.size == 0) {\\n map.delete(key);\\n }\\n }\\n }\\n static unshiftOnArrayAtEntry(map, key, newElement) {\\n let has_entry = map.has(key);\\n if (has_entry) {\\n map.get(key).unshift(newElement);\\n } else {\\n map.set(key, [newElement]);\\n }\\n }\\n static concatOnArrayAtEntry(map, key, newElements) {\\n let has_entry = map.has(key);\\n if (has_entry) {\\n let array = map.get(key);\\n for (let element of newElements) {\\n array.push(element);\\n }\\n } else {\\n map.set(key, newElements);\\n }\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/core/SetUtils.ts\\nvar SetUtils = class {\\n static toArray(set) {\\n const array = [];\\n set.forEach((elem) => {\\n array.push(elem);\\n });\\n return array;\\n }\\n static union(set0, set1) {\\n const newSet = new Set();\\n set0.forEach((val) => newSet.add(val));\\n set1.forEach((val) => newSet.add(val));\\n return newSet;\\n }\\n static intersection(set0, set1) {\\n const newSet = new Set();\\n set0.forEach((val) => {\\n if (set1.has(val)) {\\n newSet.add(val);\\n }\\n });\\n set1.forEach((val) => {\\n if (set0.has(val)) {\\n newSet.add(val);\\n }\\n });\\n return newSet;\\n }\\n static difference(set0, set1) {\\n const newSet = new Set();\\n set0.forEach((val) => {\\n if (!set1.has(val)) {\\n newSet.add(val);\\n }\\n });\\n set1.forEach((val) => {\\n if (!set0.has(val)) {\\n newSet.add(val);\\n }\\n });\\n return newSet;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/core/ArrayUtils.ts\\nvar ArrayUtils = class {\\n static shallowClone(array) {\\n return [...array];\\n }\\n static min(array) {\\n let min = array[0];\\n for (let element of array) {\\n if (element < min) {\\n min = element;\\n }\\n }\\n return min;\\n }\\n static max(array) {\\n let min = array[0];\\n for (let element of array) {\\n if (element > min) {\\n min = element;\\n }\\n }\\n return min;\\n }\\n static sum(array) {\\n let sum = 0;\\n for (let element of array) {\\n sum += element;\\n }\\n return sum;\\n }\\n static compact(array) {\\n const newArray = [];\\n for (let elem of array) {\\n if (elem != null) {\\n newArray.push(elem);\\n }\\n }\\n return newArray;\\n }\\n static uniq(array) {\\n const tmpSet = new Set();\\n for (let elem of array) {\\n tmpSet.add(elem);\\n }\\n const newArray = new Array(tmpSet.size);\\n let i = 0;\\n tmpSet.forEach((elem) => {\\n newArray[i] = elem;\\n i++;\\n });\\n return newArray;\\n }\\n static chunk(array, chunkSize) {\\n const newArray = [];\\n let newSubArray = [];\\n newArray.push(newSubArray);\\n for (let i = 0; i < array.length; i++) {\\n if (newSubArray.length == chunkSize) {\\n newSubArray = [];\\n newArray.push(newSubArray);\\n }\\n newSubArray.push(array[i]);\\n }\\n return newArray;\\n }\\n static union(array0, array1) {\\n const newArray = [];\\n const unionSet = SetUtils.union(this.toSet(array0), this.toSet(array1));\\n unionSet.forEach((val) => newArray.push(val));\\n return newArray;\\n }\\n static intersection(array0, array1) {\\n const newArray = [];\\n const intersectionSet = SetUtils.intersection(this.toSet(array0), this.toSet(array1));\\n intersectionSet.forEach((val) => newArray.push(val));\\n return newArray;\\n }\\n static difference(array0, array1) {\\n const newArray = [];\\n const differenceSet = SetUtils.difference(this.toSet(array0), this.toSet(array1));\\n differenceSet.forEach((val) => newArray.push(val));\\n return newArray;\\n }\\n static toSet(array) {\\n const set = new Set();\\n for (let elem of array) {\\n set.add(elem);\\n }\\n return set;\\n }\\n static isEqual(array0, array1) {\\n if (array0.length != array1.length) {\\n return false;\\n }\\n const count = array0.length;\\n for (let i = 0; i < count; i++) {\\n if (array0[i] != array1[i]) {\\n return false;\\n }\\n }\\n return true;\\n }\\n static sortBy(array, callback) {\\n if (array.length == 0) {\\n return [];\\n }\\n const elementsByValue = new Map();\\n const valuesSet = new Set();\\n for (let elem of array) {\\n const value = callback(elem);\\n valuesSet.add(value);\\n MapUtils.pushOnArrayAtEntry(elementsByValue, value, elem);\\n }\\n const values = new Array(valuesSet.size);\\n let i = 0;\\n valuesSet.forEach((value) => {\\n values[i] = value;\\n i++;\\n });\\n if (CoreType.isString(values[0])) {\\n values.sort();\\n } else {\\n values.sort((a, b) => a - b);\\n }\\n const sorted_elements = new Array(array.length);\\n i = 0;\\n for (let value of values) {\\n const elements_for_value = elementsByValue.get(value);\\n if (elements_for_value) {\\n for (let element of elements_for_value) {\\n sorted_elements[i] = element;\\n i++;\\n }\\n }\\n }\\n return sorted_elements;\\n }\\n static range(start, end, step = 1) {\\n if (end == null) {\\n end = start;\\n start = 0;\\n }\\n const length = Math.floor((end - start) / step);\\n const array = new Array(length);\\n for (let i = 0; i < array.length; i++) {\\n array[i] = start + i * step;\\n }\\n return array;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/core/String.ts\\nvar ATTRIB_NAMES_SEPARATOR = /[, ]/;\\nvar TAIL_DIGIT_MATCH_REGEXP = /\\\\d+$/;\\nvar LEADING_ZEROS_MATCH_REGEXP = /^0+/;\\nvar INDICES_LIST_SEPARATOR = /,| /;\\nvar ZERO = \\\\\\\"0\\\\\\\";\\nvar SPACE = \\\\\\\" \\\\\\\";\\nvar NUM_REGEXP = /^-?\\\\d+\\\\.?\\\\d*$/;\\nvar BooleanString;\\n(function(BooleanString2) {\\n BooleanString2[\\\\\\\"TRUE\\\\\\\"] = \\\\\\\"true\\\\\\\";\\n BooleanString2[\\\\\\\"FALSE\\\\\\\"] = \\\\\\\"false\\\\\\\";\\n})(BooleanString || (BooleanString = {}));\\nvar CoreString = class {\\n static isBoolean(word) {\\n return word == BooleanString.TRUE || word == BooleanString.FALSE;\\n }\\n static toBoolean(word) {\\n return word == BooleanString.TRUE;\\n }\\n static isNumber(word) {\\n return NUM_REGEXP.test(word);\\n }\\n static tailDigits(word) {\\n const match = word.match(TAIL_DIGIT_MATCH_REGEXP);\\n if (match) {\\n return parseInt(match[0]);\\n } else {\\n return 0;\\n }\\n }\\n static increment(word) {\\n const match = word.match(TAIL_DIGIT_MATCH_REGEXP);\\n if (match) {\\n let numbers_as_str = match[0];\\n let zeros_prefix = \\\\\\\"\\\\\\\";\\n const leading_zeros_match = numbers_as_str.match(LEADING_ZEROS_MATCH_REGEXP);\\n if (leading_zeros_match) {\\n zeros_prefix = leading_zeros_match[0];\\n }\\n const digits = parseInt(numbers_as_str);\\n if (digits == 0) {\\n if (zeros_prefix.length > 0) {\\n if (zeros_prefix[zeros_prefix.length - 1] == ZERO) {\\n zeros_prefix = zeros_prefix.slice(0, -1);\\n }\\n }\\n }\\n const prefix = word.substring(0, word.length - match[0].length);\\n return `${prefix}${zeros_prefix}${digits + 1}`;\\n } else {\\n return `${word}1`;\\n }\\n }\\n static pluralize(word) {\\n const last_char = word[word.length - 1];\\n if (last_char !== \\\\\\\"s\\\\\\\") {\\n return `${word}s`;\\n } else {\\n return word;\\n }\\n }\\n static camelCase(str) {\\n const elements = str.replace(/_/g, \\\\\\\" \\\\\\\").split(\\\\\\\" \\\\\\\");\\n let newWord = \\\\\\\"\\\\\\\";\\n for (let i = 0; i < elements.length; i++) {\\n let element = elements[i].toLowerCase();\\n if (i > 0) {\\n element = this.upperFirst(element);\\n }\\n newWord += element;\\n }\\n return newWord;\\n }\\n static upperFirst(word) {\\n const newString = word[0].toUpperCase() + word.substr(1);\\n return newString;\\n }\\n static titleize(word) {\\n const elements = word.split(/\\\\s|_/g);\\n const newElements = elements.map((elem) => this.upperFirst(elem));\\n return newElements.join(\\\\\\\" \\\\\\\");\\n }\\n static precision(val, decimals = 2) {\\n decimals = Math.max(decimals, 0);\\n const elements = `${val}`.split(\\\\\\\".\\\\\\\");\\n if (decimals <= 0) {\\n return elements[0];\\n }\\n let frac = elements[1];\\n if (frac !== void 0) {\\n if (frac.length > decimals) {\\n frac = frac.substring(0, decimals);\\n }\\n frac = frac.padEnd(decimals, \\\\\\\"0\\\\\\\");\\n return `${elements[0]}.${frac}`;\\n } else {\\n const string_to_pad = `${val}.`;\\n const pad = string_to_pad.length + decimals;\\n return string_to_pad.padEnd(pad, \\\\\\\"0\\\\\\\");\\n }\\n }\\n static ensureFloat(num) {\\n const num_as_string = `${num}`;\\n const dot_pos = num_as_string.indexOf(\\\\\\\".\\\\\\\");\\n if (dot_pos >= 0) {\\n return num_as_string;\\n } else {\\n return `${num_as_string}.0`;\\n }\\n }\\n static ensureInteger(num) {\\n const num_as_string = `${num}`;\\n const dot_pos = num_as_string.indexOf(\\\\\\\".\\\\\\\");\\n if (dot_pos >= 0) {\\n return num_as_string.split(\\\\\\\".\\\\\\\")[0];\\n } else {\\n return num_as_string;\\n }\\n }\\n static matchMask(word, mask) {\\n if (mask === \\\\\\\"*\\\\\\\") {\\n return true;\\n }\\n if (word == mask) {\\n return true;\\n }\\n const elements = mask.split(SPACE);\\n if (elements.length > 1) {\\n for (let element of elements) {\\n const match = this.matchMask(word, element);\\n if (match) {\\n return true;\\n }\\n }\\n return false;\\n }\\n mask = mask.split(\\\\\\\"*\\\\\\\").join(\\\\\\\".*\\\\\\\");\\n mask = `^${mask}$`;\\n const regex = new RegExp(mask);\\n return regex.test(word);\\n }\\n static matchesOneMask(word, masks) {\\n let matches_one_mask = false;\\n for (let mask of masks) {\\n if (CoreString.matchMask(word, mask)) {\\n matches_one_mask = true;\\n }\\n }\\n return matches_one_mask;\\n }\\n static attribNames(word) {\\n const elements = word.split(ATTRIB_NAMES_SEPARATOR);\\n const names_set = new Set();\\n for (let element of elements) {\\n element = element.trim();\\n if (element.length > 0) {\\n names_set.add(element);\\n }\\n }\\n const names = new Array(names_set.size);\\n let i = 0;\\n names_set.forEach((name) => {\\n names[i] = name;\\n i++;\\n });\\n return names;\\n }\\n static indices(indices_string) {\\n const elements = indices_string.split(INDICES_LIST_SEPARATOR);\\n if (elements.length > 1) {\\n const indices = elements.flatMap((element) => this.indices(element));\\n return ArrayUtils.uniq(indices).sort((a, b) => a - b);\\n } else {\\n const element = elements[0];\\n if (element) {\\n const range_separator = \\\\\\\"-\\\\\\\";\\n if (element.indexOf(range_separator) > 0) {\\n const range_elements = element.split(range_separator);\\n return ArrayUtils.range(parseInt(range_elements[0]), parseInt(range_elements[1]) + 1);\\n } else {\\n const parsed = parseInt(element);\\n if (CoreType.isNumber(parsed)) {\\n return [parsed];\\n } else {\\n return [];\\n }\\n }\\n } else {\\n return [];\\n }\\n }\\n }\\n static escapeLineBreaks(word) {\\n return word.replace(/(\\\\r\\\\n|\\\\n|\\\\r)/gm, \\\\\\\"\\\\\\\\n\\\\\\\");\\n }\\n static sanitizeName(name) {\\n name = name.replace(/[^A-Za-z0-9]/g, \\\\\\\"_\\\\\\\");\\n name = name.replace(/^[0-9]/, \\\\\\\"_\\\\\\\");\\n return name;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/core/NodeSelection.ts\\nvar CoreNodeSelection = class {\\n constructor(_node) {\\n this._node = _node;\\n this._node_ids = [];\\n this._json = [];\\n }\\n node() {\\n return this._node;\\n }\\n nodes() {\\n return this._node.scene().graph.nodesFromIds(this._node_ids);\\n }\\n contains(node) {\\n return this._node_ids.includes(node.graphNodeId());\\n }\\n equals(nodes) {\\n const node_ids = nodes.map((node) => node.graphNodeId()).sort();\\n return ArrayUtils.isEqual(node_ids, this._node_ids);\\n }\\n clear() {\\n this._node_ids = [];\\n this.send_update_event();\\n }\\n set(nodes) {\\n this._node_ids = [];\\n this.add(nodes);\\n }\\n add(nodes_to_add) {\\n const node_ids_to_add = nodes_to_add.map((node) => node.graphNodeId());\\n this._node_ids = ArrayUtils.union(this._node_ids, node_ids_to_add);\\n this.send_update_event();\\n }\\n remove(nodes_to_remove) {\\n const node_ids_to_remove = nodes_to_remove.map((node) => node.graphNodeId());\\n this._node_ids = ArrayUtils.difference(this._node_ids, node_ids_to_remove);\\n this.send_update_event();\\n }\\n send_update_event() {\\n this._node.emit(NodeEvent.SELECTION_UPDATED);\\n }\\n toJSON() {\\n this._json = this._json || [];\\n this._json = this._node_ids.map((id) => id);\\n return this._json;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/poly/InputCloneMode.ts\\nvar InputCloneMode;\\n(function(InputCloneMode2) {\\n InputCloneMode2[\\\\\\\"ALWAYS\\\\\\\"] = \\\\\\\"always\\\\\\\";\\n InputCloneMode2[\\\\\\\"NEVER\\\\\\\"] = \\\\\\\"never\\\\\\\";\\n InputCloneMode2[\\\\\\\"FROM_NODE\\\\\\\"] = \\\\\\\"from_node\\\\\\\";\\n})(InputCloneMode || (InputCloneMode = {}));\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/poly/Assert.ts\\nvar TypeAssert = class {\\n static unreachable(x) {\\n throw new Error(\\\\\\\"Didn't expect to get here\\\\\\\");\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/operations/container/utils/inputs/ClonedStatesController.ts\\nvar ClonedStatesController = class {\\n constructor(inputs_controller) {\\n this.inputs_controller = inputs_controller;\\n this._clone_required_states = [];\\n this._overridden = false;\\n }\\n init_inputs_cloned_state(states) {\\n if (CoreType.isArray(states)) {\\n this._cloned_states = states;\\n } else {\\n this._cloned_state = states;\\n }\\n this._update_clone_required_state();\\n }\\n override_cloned_state_allowed() {\\n if (this._cloned_states) {\\n for (let state of this._cloned_states) {\\n if (state == InputCloneMode.FROM_NODE) {\\n return true;\\n }\\n }\\n }\\n if (this._cloned_state) {\\n return this._cloned_state == InputCloneMode.FROM_NODE;\\n }\\n return false;\\n }\\n clone_required_state(index) {\\n return this._clone_required_states[index];\\n }\\n clone_required_states() {\\n return this._clone_required_states;\\n }\\n _get_clone_required_state(index) {\\n const states = this._cloned_states;\\n if (states) {\\n const state = states[index];\\n if (state != null) {\\n return this.clone_required_from_state(state);\\n }\\n }\\n if (this._cloned_state) {\\n return this.clone_required_from_state(this._cloned_state);\\n }\\n return true;\\n }\\n clone_required_from_state(state) {\\n switch (state) {\\n case InputCloneMode.ALWAYS:\\n return true;\\n case InputCloneMode.NEVER:\\n return false;\\n case InputCloneMode.FROM_NODE:\\n return !this._overridden;\\n }\\n return TypeAssert.unreachable(state);\\n }\\n override_cloned_state(state) {\\n this._overridden = state;\\n this._update_clone_required_state();\\n }\\n overriden() {\\n return this._overridden;\\n }\\n _update_clone_required_state() {\\n if (this._cloned_states) {\\n const states = [];\\n for (let i = 0; i < this._cloned_states.length; i++) {\\n states[i] = this._get_clone_required_state(i);\\n }\\n this._clone_required_states = states;\\n return;\\n }\\n if (this._cloned_state) {\\n const max_inputs = this.inputs_controller.inputs_count();\\n const states = [];\\n for (let i = 0; i < max_inputs; i++) {\\n states[i] = this._get_clone_required_state(i);\\n }\\n this._clone_required_states = states;\\n return;\\n }\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/operations/container/utils/InputsController.ts\\nvar InputsController = class {\\n constructor(operation_container) {\\n this.operation_container = operation_container;\\n }\\n inputs_count() {\\n return this.operation_container.inputs_count();\\n }\\n init_inputs_cloned_state(states) {\\n if (!this._cloned_states_controller) {\\n this._cloned_states_controller = new ClonedStatesController(this);\\n this._cloned_states_controller.init_inputs_cloned_state(states);\\n }\\n }\\n clone_required(index) {\\n const state = this._cloned_states_controller?.clone_required_state(index);\\n if (state != null) {\\n return state;\\n }\\n return true;\\n }\\n override_cloned_state(state) {\\n this._cloned_states_controller?.override_cloned_state(state);\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/operations/container/_Base.ts\\nvar BaseOperationContainer = class {\\n constructor(operation, name, init_params) {\\n this.operation = operation;\\n this.name = name;\\n this.params = {};\\n this._apply_default_params();\\n this._apply_init_params(init_params);\\n this._init_cloned_states();\\n }\\n path_param_resolve_required() {\\n return this._path_params != null;\\n }\\n resolve_path_params(node_start) {\\n if (!this._path_params) {\\n return;\\n }\\n for (let path_param of this._path_params) {\\n path_param.resolve(node_start);\\n }\\n }\\n _apply_default_params() {\\n const default_params = this.operation.constructor.DEFAULT_PARAMS;\\n const param_names = Object.keys(default_params);\\n for (let param_name of param_names) {\\n const param_data = default_params[param_name];\\n const clone_param_data = this._convert_param_data(param_name, param_data);\\n if (clone_param_data != void 0) {\\n this.params[param_name] = clone_param_data;\\n }\\n }\\n }\\n _apply_init_params(init_params) {\\n const param_names = Object.keys(init_params);\\n for (let param_name of param_names) {\\n const param_data = init_params[param_name];\\n if (param_data.simple_data != null) {\\n const simple_data = param_data.simple_data;\\n const clone_param_data = this._convert_export_param_data(param_name, simple_data);\\n if (clone_param_data != void 0) {\\n this.params[param_name] = clone_param_data;\\n }\\n }\\n }\\n }\\n _convert_param_data(param_name, param_data) {\\n if (CoreType.isNumber(param_data) || CoreType.isBoolean(param_data) || CoreType.isString(param_data)) {\\n return param_data;\\n }\\n if (param_data instanceof TypedNodePathParamValue) {\\n const cloned = param_data.clone();\\n if (!this._path_params) {\\n this._path_params = [];\\n }\\n this._path_params.push(cloned);\\n return cloned;\\n }\\n if (param_data instanceof Color || param_data instanceof Vector2 || param_data instanceof Vector3 || param_data instanceof Vector4) {\\n return param_data.clone();\\n }\\n }\\n _convert_export_param_data(param_name, param_data) {\\n const default_param = this.params[param_name];\\n if (CoreType.isBoolean(param_data)) {\\n return param_data;\\n }\\n if (CoreType.isNumber(param_data)) {\\n if (CoreType.isBoolean(default_param)) {\\n return param_data >= 1 ? true : false;\\n } else {\\n return param_data;\\n }\\n }\\n if (CoreType.isString(param_data)) {\\n if (default_param) {\\n if (default_param instanceof TypedNodePathParamValue) {\\n return default_param.set_path(param_data);\\n }\\n if (default_param instanceof TypedParamPathParamValue) {\\n return default_param.set_path(param_data);\\n }\\n }\\n return param_data;\\n }\\n if (CoreType.isArray(param_data)) {\\n this.params[param_name].fromArray(param_data);\\n }\\n }\\n setInput(index, input) {\\n this._inputs = this._inputs || [];\\n this._inputs[index] = input;\\n }\\n inputs_count() {\\n if (this._inputs) {\\n return this._inputs.length;\\n } else {\\n return 0;\\n }\\n }\\n inputsController() {\\n return this._inputs_controller = this._inputs_controller || new InputsController(this);\\n }\\n _init_cloned_states() {\\n const default_cloned_states = this.operation.constructor.INPUT_CLONED_STATE;\\n this.inputsController().init_inputs_cloned_state(default_cloned_states);\\n }\\n input_clone_required(index) {\\n if (!this._inputs_controller) {\\n return true;\\n }\\n return this._inputs_controller.clone_required(index);\\n }\\n override_input_clone_state(state) {\\n this.inputsController().override_cloned_state(state);\\n }\\n cook(input_contents) {\\n return this.operation.cook(input_contents, this.params);\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/operations/container/sop.ts\\nvar SopOperationContainer = class extends BaseOperationContainer {\\n constructor(operation, name, init_params) {\\n super(operation, name, init_params);\\n this.operation = operation;\\n this.name = name;\\n this.init_params = init_params;\\n this._inputs = [];\\n this._current_input_index = 0;\\n this._dirty = true;\\n }\\n add_input(input) {\\n super.setInput(this._current_input_index, input);\\n this.increment_input_index();\\n }\\n increment_input_index() {\\n this._current_input_index++;\\n }\\n current_input_index() {\\n return this._current_input_index;\\n }\\n setDirty() {\\n if (this._dirty) {\\n return;\\n }\\n this._compute_result = void 0;\\n for (let i = 0; i < this._inputs.length; i++) {\\n const input_operation = this._inputs[i];\\n input_operation.setDirty();\\n }\\n }\\n async compute(input_contents, operation_inputs_map) {\\n if (this._compute_result) {\\n return this._compute_result;\\n }\\n const operation_input_contents = [];\\n const node_inputs_map = operation_inputs_map.get(this);\\n if (node_inputs_map) {\\n node_inputs_map.forEach((node_input_index, operation_input_index) => {\\n operation_input_contents[operation_input_index] = input_contents[node_input_index];\\n });\\n }\\n for (let i = 0; i < this._inputs.length; i++) {\\n const input_operation = this._inputs[i];\\n let result2 = await input_operation.compute(input_contents, operation_inputs_map);\\n if (result2) {\\n if (this.input_clone_required(i)) {\\n result2 = result2.clone();\\n }\\n operation_input_contents[i] = result2;\\n }\\n }\\n const result = this.operation.cook(operation_input_contents, this.params);\\n if (result) {\\n if (result instanceof Promise) {\\n this._compute_result = await result;\\n } else {\\n this._compute_result = result;\\n }\\n } else {\\n this._compute_result = void 0;\\n }\\n this._dirty = false;\\n return this._compute_result;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/utils/hierarchy/ChildrenController.ts\\nvar HierarchyChildrenController = class {\\n constructor(node, _context2) {\\n this.node = node;\\n this._context = _context2;\\n this._childrenByName = new Map();\\n this._childrenByType = new Map();\\n this._childrenAndGrandchildrenByContext = new Map();\\n }\\n get selection() {\\n return this._selection = this._selection || new CoreNodeSelection(this.node);\\n }\\n dispose() {\\n const children = this.children();\\n for (let child of children) {\\n this.node.removeNode(child);\\n }\\n this._selection = void 0;\\n }\\n get context() {\\n return this._context;\\n }\\n set_output_node_find_method(method) {\\n this._output_node_find_method = method;\\n }\\n output_node() {\\n if (this._output_node_find_method) {\\n return this._output_node_find_method();\\n }\\n }\\n setChildName(node, new_name) {\\n let current_child_with_name;\\n new_name = CoreString.sanitizeName(new_name);\\n if ((current_child_with_name = this._childrenByName.get(new_name)) != null) {\\n if (node.name() === new_name && current_child_with_name.graphNodeId() === node.graphNodeId()) {\\n return;\\n }\\n new_name = CoreString.increment(new_name);\\n return this.setChildName(node, new_name);\\n } else {\\n const current_name = node.name();\\n const current_child = this._childrenByName.get(current_name);\\n if (current_child) {\\n this._childrenByName.delete(current_name);\\n }\\n this._childrenByName.set(new_name, node);\\n node.nameController.updateNameFromParent(new_name);\\n this._addToNodesByType(node);\\n this.node.scene().nodesController.addToInstanciatedNode(node);\\n }\\n }\\n node_context_signature() {\\n return `${this.node.context()}/${this.node.type()}`;\\n }\\n available_children_classes() {\\n return Poly.registeredNodes(this._context, this.node.type());\\n }\\n isValidChildType(node_type) {\\n const node_class = this.available_children_classes()[node_type];\\n return node_class != null;\\n }\\n createNode(node_class_or_string, params_init_value_overrides, node_type = \\\\\\\"\\\\\\\") {\\n if (typeof node_class_or_string == \\\\\\\"string\\\\\\\") {\\n const node_class = this._find_node_class(node_class_or_string);\\n return this._create_and_init_node(node_class, params_init_value_overrides, node_type);\\n } else {\\n return this._create_and_init_node(node_class_or_string, params_init_value_overrides, node_type);\\n }\\n }\\n _create_and_init_node(node_class, params_init_value_overrides, node_type = \\\\\\\"\\\\\\\") {\\n const child_node = new node_class(this.node.scene(), `child_node_${node_type}`, params_init_value_overrides);\\n child_node.initialize_base_and_node();\\n this._addNode(child_node);\\n child_node.lifecycle.setCreationCompleted();\\n return child_node;\\n }\\n _find_node_class(node_type) {\\n const node_class = this.available_children_classes()[node_type.toLowerCase()];\\n if (node_class == null) {\\n const message = `child node type '${node_type}' not found for node '${this.node.path()}'. Available types are: ${Object.keys(this.available_children_classes()).join(\\\\\\\", \\\\\\\")}, ${this._context}, ${this.node.type()}`;\\n console.error(message);\\n throw message;\\n }\\n return node_class;\\n }\\n create_operation_container(operation_type, operation_container_name, params_init_value_overrides) {\\n const operation_class = Poly.registeredOperation(this._context, operation_type);\\n if (operation_class == null) {\\n const message = `no operation found with context ${this._context}/${operation_type}`;\\n console.error(message);\\n throw message;\\n } else {\\n const operation = new operation_class(this.node.scene());\\n const operation_container = new SopOperationContainer(operation, operation_container_name, params_init_value_overrides || {});\\n return operation_container;\\n }\\n }\\n _addNode(child_node) {\\n child_node.setParent(this.node);\\n child_node.params.init();\\n child_node.parentController.onSetParent();\\n child_node.nameController.runPostSetFullPathHooks();\\n if (child_node.childrenAllowed() && child_node.childrenController) {\\n for (let child of child_node.childrenController.children()) {\\n child.nameController.runPostSetFullPathHooks();\\n }\\n }\\n this.node.emit(NodeEvent.CREATED, {child_node_json: child_node.toJSON()});\\n if (this.node.scene().lifecycleController.onCreateHookAllowed()) {\\n child_node.lifecycle.run_on_create_hooks();\\n }\\n child_node.lifecycle.run_on_add_hooks();\\n this.setChildName(child_node, NameController.base_name(child_node));\\n this.node.lifecycle.run_on_child_add_hooks(child_node);\\n if (child_node.require_webgl2()) {\\n this.node.scene().webgl_controller.set_require_webgl2();\\n }\\n this.node.scene().missingExpressionReferencesController.checkForMissingReferences(child_node);\\n return child_node;\\n }\\n removeNode(child_node) {\\n if (child_node.parent() != this.node) {\\n return console.warn(`node ${child_node.name()} not under parent ${this.node.path()}`);\\n } else {\\n if (this.selection.contains(child_node)) {\\n this.selection.remove([child_node]);\\n }\\n const first_connection = child_node.io.connections.firstInputConnection();\\n const input_connections = child_node.io.connections.inputConnections();\\n const output_connections = child_node.io.connections.outputConnections();\\n if (input_connections) {\\n for (let input_connection of input_connections) {\\n if (input_connection) {\\n input_connection.disconnect({setInput: true});\\n }\\n }\\n }\\n if (output_connections) {\\n for (let output_connection of output_connections) {\\n if (output_connection) {\\n output_connection.disconnect({setInput: true});\\n if (first_connection) {\\n const old_src = first_connection.node_src;\\n const old_output_index = output_connection.output_index;\\n const old_dest = output_connection.node_dest;\\n const old_input_index = output_connection.input_index;\\n old_dest.io.inputs.setInput(old_input_index, old_src, old_output_index);\\n }\\n }\\n }\\n }\\n child_node.setParent(null);\\n this._childrenByName.delete(child_node.name());\\n this._removeFromNodesByType(child_node);\\n this.node.scene().nodesController.removeFromInstanciatedNode(child_node);\\n child_node.setSuccessorsDirty(this.node);\\n child_node.graphDisconnectSuccessors();\\n this.node.lifecycle.run_on_child_remove_hooks(child_node);\\n child_node.lifecycle.run_on_delete_hooks();\\n child_node.dispose();\\n child_node.emit(NodeEvent.DELETED, {parent_id: this.node.graphNodeId()});\\n }\\n }\\n _addToNodesByType(node) {\\n const nodeId = node.graphNodeId();\\n const type = node.type();\\n MapUtils.addToSetAtEntry(this._childrenByType, type, nodeId);\\n this._addToChildrenAndGrandchildrenByContext(node);\\n }\\n _removeFromNodesByType(node) {\\n const nodeId = node.graphNodeId();\\n const type = node.type();\\n MapUtils.removeFromSetAtEntry(this._childrenByType, type, nodeId);\\n this._removeFromChildrenAndGrandchildrenByContext(node);\\n }\\n _addToChildrenAndGrandchildrenByContext(node) {\\n const nodeId = node.graphNodeId();\\n const nodeContext = node.context();\\n MapUtils.addToSetAtEntry(this._childrenAndGrandchildrenByContext, nodeContext, nodeId);\\n const parent = this.node.parent();\\n if (parent && parent.childrenAllowed()) {\\n parent.childrenController?._addToChildrenAndGrandchildrenByContext(node);\\n }\\n }\\n _removeFromChildrenAndGrandchildrenByContext(node) {\\n const nodeId = node.graphNodeId();\\n const type = node.context();\\n MapUtils.removeFromSetAtEntry(this._childrenAndGrandchildrenByContext, type, nodeId);\\n const parent = this.node.parent();\\n if (parent && parent.childrenAllowed()) {\\n parent.childrenController?._removeFromChildrenAndGrandchildrenByContext(node);\\n }\\n }\\n nodesByType(type) {\\n const nodeIds = this._childrenByType.get(type);\\n if (!nodeIds) {\\n return [];\\n }\\n const graph = this.node.scene().graph;\\n const nodes = [];\\n for (let node_id of nodeIds) {\\n const node = graph.nodeFromId(node_id);\\n if (node) {\\n nodes.push(node);\\n }\\n }\\n return nodes;\\n }\\n childByName(name) {\\n return this._childrenByName.get(name) || null;\\n }\\n hasChildrenAndGrandchildrenWithContext(context) {\\n return this._childrenAndGrandchildrenByContext.get(context) != null;\\n }\\n children() {\\n const nodes = [];\\n this._childrenByName.forEach((node) => {\\n nodes.push(node);\\n });\\n return nodes;\\n }\\n childrenNames() {\\n const names = [];\\n this._childrenByName.forEach((node, nodeName) => {\\n names.push(nodeName);\\n });\\n return names;\\n }\\n traverseChildren(callback) {\\n this._childrenByName.forEach((childNode) => {\\n callback(childNode);\\n childNode.childrenController?.traverseChildren(callback);\\n });\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/utils/LifeCycleController.ts\\nvar LifeCycleController = class {\\n constructor(node) {\\n this.node = node;\\n this._creation_completed = false;\\n }\\n dispose() {\\n this._on_child_add_hooks = void 0;\\n this._on_child_remove_hooks = void 0;\\n this._on_create_hooks = void 0;\\n this._on_add_hooks = void 0;\\n this._on_delete_hooks = void 0;\\n }\\n setCreationCompleted() {\\n if (!this._creation_completed) {\\n this._creation_completed = true;\\n }\\n }\\n creationCompleted() {\\n return this.node.scene().loadingController.loaded() && this._creation_completed;\\n }\\n add_on_child_add_hook(callback) {\\n this._on_child_add_hooks = this._on_child_add_hooks || [];\\n this._on_child_add_hooks.push(callback);\\n }\\n run_on_child_add_hooks(node) {\\n this.execute_hooks_with_child_node(this._on_child_add_hooks, node);\\n }\\n add_on_child_remove_hook(callback) {\\n this._on_child_remove_hooks = this._on_child_remove_hooks || [];\\n this._on_child_remove_hooks.push(callback);\\n }\\n run_on_child_remove_hooks(node) {\\n this.execute_hooks_with_child_node(this._on_child_remove_hooks, node);\\n }\\n add_on_create_hook(callback) {\\n this._on_create_hooks = this._on_create_hooks || [];\\n this._on_create_hooks.push(callback);\\n }\\n run_on_create_hooks() {\\n this.execute_hooks(this._on_create_hooks);\\n }\\n add_on_add_hook(callback) {\\n this._on_add_hooks = this._on_add_hooks || [];\\n this._on_add_hooks.push(callback);\\n }\\n run_on_add_hooks() {\\n this.execute_hooks(this._on_add_hooks);\\n }\\n add_delete_hook(callback) {\\n this._on_delete_hooks = this._on_delete_hooks || [];\\n this._on_delete_hooks.push(callback);\\n }\\n run_on_delete_hooks() {\\n this.execute_hooks(this._on_delete_hooks);\\n }\\n execute_hooks(hooks) {\\n if (hooks) {\\n let hook;\\n for (hook of hooks) {\\n hook();\\n }\\n }\\n }\\n execute_hooks_with_child_node(hooks, child_node) {\\n if (hooks) {\\n let hook;\\n for (hook of hooks) {\\n hook(child_node);\\n }\\n }\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/poly/NodeContext.ts\\nvar NodeContext;\\n(function(NodeContext3) {\\n NodeContext3[\\\\\\\"ANIM\\\\\\\"] = \\\\\\\"anim\\\\\\\";\\n NodeContext3[\\\\\\\"COP\\\\\\\"] = \\\\\\\"cop\\\\\\\";\\n NodeContext3[\\\\\\\"EVENT\\\\\\\"] = \\\\\\\"event\\\\\\\";\\n NodeContext3[\\\\\\\"GL\\\\\\\"] = \\\\\\\"gl\\\\\\\";\\n NodeContext3[\\\\\\\"JS\\\\\\\"] = \\\\\\\"js\\\\\\\";\\n NodeContext3[\\\\\\\"MANAGER\\\\\\\"] = \\\\\\\"manager\\\\\\\";\\n NodeContext3[\\\\\\\"MAT\\\\\\\"] = \\\\\\\"mat\\\\\\\";\\n NodeContext3[\\\\\\\"OBJ\\\\\\\"] = \\\\\\\"obj\\\\\\\";\\n NodeContext3[\\\\\\\"POST\\\\\\\"] = \\\\\\\"post\\\\\\\";\\n NodeContext3[\\\\\\\"ROP\\\\\\\"] = \\\\\\\"rop\\\\\\\";\\n NodeContext3[\\\\\\\"SOP\\\\\\\"] = \\\\\\\"sop\\\\\\\";\\n})(NodeContext || (NodeContext = {}));\\nvar NetworkNodeType;\\n(function(NetworkNodeType2) {\\n NetworkNodeType2[\\\\\\\"ANIM\\\\\\\"] = \\\\\\\"animationsNetwork\\\\\\\";\\n NetworkNodeType2[\\\\\\\"COP\\\\\\\"] = \\\\\\\"copNetwork\\\\\\\";\\n NetworkNodeType2[\\\\\\\"EVENT\\\\\\\"] = \\\\\\\"eventsNetwork\\\\\\\";\\n NetworkNodeType2[\\\\\\\"MAT\\\\\\\"] = \\\\\\\"materialsNetwork\\\\\\\";\\n NetworkNodeType2[\\\\\\\"POST\\\\\\\"] = \\\\\\\"postProcessNetwork\\\\\\\";\\n NetworkNodeType2[\\\\\\\"ROP\\\\\\\"] = \\\\\\\"renderersNetwork\\\\\\\";\\n})(NetworkNodeType || (NetworkNodeType = {}));\\nvar NetworkChildNodeType;\\n(function(NetworkChildNodeType2) {\\n NetworkChildNodeType2[\\\\\\\"INPUT\\\\\\\"] = \\\\\\\"subnetInput\\\\\\\";\\n NetworkChildNodeType2[\\\\\\\"OUTPUT\\\\\\\"] = \\\\\\\"subnetOutput\\\\\\\";\\n})(NetworkChildNodeType || (NetworkChildNodeType = {}));\\nvar CameraNodeType;\\n(function(CameraNodeType2) {\\n CameraNodeType2[\\\\\\\"PERSPECTIVE\\\\\\\"] = \\\\\\\"perspectiveCamera\\\\\\\";\\n CameraNodeType2[\\\\\\\"ORTHOGRAPHIC\\\\\\\"] = \\\\\\\"orthographicCamera\\\\\\\";\\n})(CameraNodeType || (CameraNodeType = {}));\\nvar CAMERA_TYPES = [CameraNodeType.ORTHOGRAPHIC, CameraNodeType.PERSPECTIVE];\\nvar GlNodeType;\\n(function(GlNodeType2) {\\n GlNodeType2[\\\\\\\"ATTRIBUTE\\\\\\\"] = \\\\\\\"attribute\\\\\\\";\\n})(GlNodeType || (GlNodeType = {}));\\nvar CameraControlsNodeType;\\n(function(CameraControlsNodeType2) {\\n CameraControlsNodeType2[\\\\\\\"DEVICE_ORIENTATION\\\\\\\"] = \\\\\\\"cameraDeviceOrientationControls\\\\\\\";\\n CameraControlsNodeType2[\\\\\\\"MAP\\\\\\\"] = \\\\\\\"cameraMapControls\\\\\\\";\\n CameraControlsNodeType2[\\\\\\\"ORBIT\\\\\\\"] = \\\\\\\"cameraOrbitControls\\\\\\\";\\n CameraControlsNodeType2[\\\\\\\"FIRST_PERSON\\\\\\\"] = \\\\\\\"firstPersonControls\\\\\\\";\\n CameraControlsNodeType2[\\\\\\\"PLAYER\\\\\\\"] = \\\\\\\"playerControls\\\\\\\";\\n CameraControlsNodeType2[\\\\\\\"MOBILE_JOYSTICK\\\\\\\"] = \\\\\\\"mobileJoystickControls\\\\\\\";\\n})(CameraControlsNodeType || (CameraControlsNodeType = {}));\\nvar CAMERA_CONTROLS_NODE_TYPES = [\\n CameraControlsNodeType.DEVICE_ORIENTATION,\\n CameraControlsNodeType.MAP,\\n CameraControlsNodeType.ORBIT,\\n CameraControlsNodeType.FIRST_PERSON,\\n CameraControlsNodeType.MOBILE_JOYSTICK\\n];\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/containers/_Base.ts\\nvar TypedContainer = class {\\n constructor(_node) {\\n this._node = _node;\\n }\\n set_node(node) {\\n this._node = node;\\n }\\n node() {\\n return this._node;\\n }\\n set_content(content) {\\n this._content = content;\\n this._post_set_content();\\n }\\n has_content() {\\n return this._content != null;\\n }\\n content() {\\n return this._content;\\n }\\n _post_set_content() {\\n }\\n coreContent() {\\n return this._content;\\n }\\n coreContentCloned() {\\n return this._content;\\n }\\n infos() {\\n return [];\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/containers/Animation.ts\\nvar AnimationContainer = class extends TypedContainer {\\n set_content(content) {\\n super.set_content(content);\\n }\\n setTimelineBuilder(timeline_builder) {\\n return this.set_content(timeline_builder);\\n }\\n timeline_builder() {\\n return this.content();\\n }\\n coreContentCloned() {\\n if (this._content) {\\n return this._content.clone();\\n }\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/containers/Event.ts\\nvar EventContainer = class extends TypedContainer {\\n set_content(content) {\\n super.set_content(content);\\n }\\n};\\n\\n// ../../../node_modules/three/src/objects/SkinnedMesh.js\\nvar _basePosition = /* @__PURE__ */ new Vector3();\\nvar _skinIndex = /* @__PURE__ */ new Vector4();\\nvar _skinWeight = /* @__PURE__ */ new Vector4();\\nvar _vector7 = /* @__PURE__ */ new Vector3();\\nvar _matrix2 = /* @__PURE__ */ new Matrix4();\\nvar SkinnedMesh = class extends Mesh {\\n constructor(geometry, material) {\\n super(geometry, material);\\n this.type = \\\\\\\"SkinnedMesh\\\\\\\";\\n this.bindMode = \\\\\\\"attached\\\\\\\";\\n this.bindMatrix = new Matrix4();\\n this.bindMatrixInverse = new Matrix4();\\n }\\n copy(source) {\\n super.copy(source);\\n this.bindMode = source.bindMode;\\n this.bindMatrix.copy(source.bindMatrix);\\n this.bindMatrixInverse.copy(source.bindMatrixInverse);\\n this.skeleton = source.skeleton;\\n return this;\\n }\\n bind(skeleton, bindMatrix) {\\n this.skeleton = skeleton;\\n if (bindMatrix === void 0) {\\n this.updateMatrixWorld(true);\\n this.skeleton.calculateInverses();\\n bindMatrix = this.matrixWorld;\\n }\\n this.bindMatrix.copy(bindMatrix);\\n this.bindMatrixInverse.copy(bindMatrix).invert();\\n }\\n pose() {\\n this.skeleton.pose();\\n }\\n normalizeSkinWeights() {\\n const vector = new Vector4();\\n const skinWeight = this.geometry.attributes.skinWeight;\\n for (let i = 0, l = skinWeight.count; i < l; i++) {\\n vector.x = skinWeight.getX(i);\\n vector.y = skinWeight.getY(i);\\n vector.z = skinWeight.getZ(i);\\n vector.w = skinWeight.getW(i);\\n const scale = 1 / vector.manhattanLength();\\n if (scale !== Infinity) {\\n vector.multiplyScalar(scale);\\n } else {\\n vector.set(1, 0, 0, 0);\\n }\\n skinWeight.setXYZW(i, vector.x, vector.y, vector.z, vector.w);\\n }\\n }\\n updateMatrixWorld(force) {\\n super.updateMatrixWorld(force);\\n if (this.bindMode === \\\\\\\"attached\\\\\\\") {\\n this.bindMatrixInverse.copy(this.matrixWorld).invert();\\n } else if (this.bindMode === \\\\\\\"detached\\\\\\\") {\\n this.bindMatrixInverse.copy(this.bindMatrix).invert();\\n } else {\\n console.warn(\\\\\\\"THREE.SkinnedMesh: Unrecognized bindMode: \\\\\\\" + this.bindMode);\\n }\\n }\\n boneTransform(index, target) {\\n const skeleton = this.skeleton;\\n const geometry = this.geometry;\\n _skinIndex.fromBufferAttribute(geometry.attributes.skinIndex, index);\\n _skinWeight.fromBufferAttribute(geometry.attributes.skinWeight, index);\\n _basePosition.copy(target).applyMatrix4(this.bindMatrix);\\n target.set(0, 0, 0);\\n for (let i = 0; i < 4; i++) {\\n const weight = _skinWeight.getComponent(i);\\n if (weight !== 0) {\\n const boneIndex = _skinIndex.getComponent(i);\\n _matrix2.multiplyMatrices(skeleton.bones[boneIndex].matrixWorld, skeleton.boneInverses[boneIndex]);\\n target.addScaledVector(_vector7.copy(_basePosition).applyMatrix4(_matrix2), weight);\\n }\\n }\\n return target.applyMatrix4(this.bindMatrixInverse);\\n }\\n};\\nSkinnedMesh.prototype.isSkinnedMesh = true;\\n\\n// ../../../node_modules/three/src/scenes/Scene.js\\nvar Scene = class extends Object3D {\\n constructor() {\\n super();\\n this.type = \\\\\\\"Scene\\\\\\\";\\n this.background = null;\\n this.environment = null;\\n this.fog = null;\\n this.overrideMaterial = null;\\n this.autoUpdate = true;\\n if (typeof __THREE_DEVTOOLS__ !== \\\\\\\"undefined\\\\\\\") {\\n __THREE_DEVTOOLS__.dispatchEvent(new CustomEvent(\\\\\\\"observe\\\\\\\", {detail: this}));\\n }\\n }\\n copy(source, recursive) {\\n super.copy(source, recursive);\\n if (source.background !== null)\\n this.background = source.background.clone();\\n if (source.environment !== null)\\n this.environment = source.environment.clone();\\n if (source.fog !== null)\\n this.fog = source.fog.clone();\\n if (source.overrideMaterial !== null)\\n this.overrideMaterial = source.overrideMaterial.clone();\\n this.autoUpdate = source.autoUpdate;\\n this.matrixAutoUpdate = source.matrixAutoUpdate;\\n return this;\\n }\\n toJSON(meta) {\\n const data = super.toJSON(meta);\\n if (this.fog !== null)\\n data.object.fog = this.fog.toJSON();\\n return data;\\n }\\n};\\nScene.prototype.isScene = true;\\n\\n// ../../../node_modules/three/src/materials/PointsMaterial.js\\nvar PointsMaterial = class extends Material {\\n constructor(parameters) {\\n super();\\n this.type = \\\\\\\"PointsMaterial\\\\\\\";\\n this.color = new Color(16777215);\\n this.map = null;\\n this.alphaMap = null;\\n this.size = 1;\\n this.sizeAttenuation = true;\\n this.setValues(parameters);\\n }\\n copy(source) {\\n super.copy(source);\\n this.color.copy(source.color);\\n this.map = source.map;\\n this.alphaMap = source.alphaMap;\\n this.size = source.size;\\n this.sizeAttenuation = source.sizeAttenuation;\\n return this;\\n }\\n};\\nPointsMaterial.prototype.isPointsMaterial = true;\\n\\n// ../../../node_modules/three/src/objects/Points.js\\nvar _inverseMatrix2 = /* @__PURE__ */ new Matrix4();\\nvar _ray2 = /* @__PURE__ */ new Ray();\\nvar _sphere3 = /* @__PURE__ */ new Sphere();\\nvar _position2 = /* @__PURE__ */ new Vector3();\\nvar Points = class extends Object3D {\\n constructor(geometry = new BufferGeometry(), material = new PointsMaterial()) {\\n super();\\n this.type = \\\\\\\"Points\\\\\\\";\\n this.geometry = geometry;\\n this.material = material;\\n this.updateMorphTargets();\\n }\\n copy(source) {\\n super.copy(source);\\n this.material = source.material;\\n this.geometry = source.geometry;\\n return this;\\n }\\n raycast(raycaster, intersects) {\\n const geometry = this.geometry;\\n const matrixWorld = this.matrixWorld;\\n const threshold = raycaster.params.Points.threshold;\\n const drawRange = geometry.drawRange;\\n if (geometry.boundingSphere === null)\\n geometry.computeBoundingSphere();\\n _sphere3.copy(geometry.boundingSphere);\\n _sphere3.applyMatrix4(matrixWorld);\\n _sphere3.radius += threshold;\\n if (raycaster.ray.intersectsSphere(_sphere3) === false)\\n return;\\n _inverseMatrix2.copy(matrixWorld).invert();\\n _ray2.copy(raycaster.ray).applyMatrix4(_inverseMatrix2);\\n const localThreshold = threshold / ((this.scale.x + this.scale.y + this.scale.z) / 3);\\n const localThresholdSq = localThreshold * localThreshold;\\n if (geometry.isBufferGeometry) {\\n const index = geometry.index;\\n const attributes = geometry.attributes;\\n const positionAttribute = attributes.position;\\n if (index !== null) {\\n const start = Math.max(0, drawRange.start);\\n const end = Math.min(index.count, drawRange.start + drawRange.count);\\n for (let i = start, il = end; i < il; i++) {\\n const a = index.getX(i);\\n _position2.fromBufferAttribute(positionAttribute, a);\\n testPoint(_position2, a, localThresholdSq, matrixWorld, raycaster, intersects, this);\\n }\\n } else {\\n const start = Math.max(0, drawRange.start);\\n const end = Math.min(positionAttribute.count, drawRange.start + drawRange.count);\\n for (let i = start, l = end; i < l; i++) {\\n _position2.fromBufferAttribute(positionAttribute, i);\\n testPoint(_position2, i, localThresholdSq, matrixWorld, raycaster, intersects, this);\\n }\\n }\\n } else {\\n console.error(\\\\\\\"THREE.Points.raycast() no longer supports THREE.Geometry. Use THREE.BufferGeometry instead.\\\\\\\");\\n }\\n }\\n updateMorphTargets() {\\n const geometry = this.geometry;\\n if (geometry.isBufferGeometry) {\\n const morphAttributes = geometry.morphAttributes;\\n const keys = Object.keys(morphAttributes);\\n if (keys.length > 0) {\\n const morphAttribute = morphAttributes[keys[0]];\\n if (morphAttribute !== void 0) {\\n this.morphTargetInfluences = [];\\n this.morphTargetDictionary = {};\\n for (let m = 0, ml = morphAttribute.length; m < ml; m++) {\\n const name = morphAttribute[m].name || String(m);\\n this.morphTargetInfluences.push(0);\\n this.morphTargetDictionary[name] = m;\\n }\\n }\\n }\\n } else {\\n const morphTargets = geometry.morphTargets;\\n if (morphTargets !== void 0 && morphTargets.length > 0) {\\n console.error(\\\\\\\"THREE.Points.updateMorphTargets() does not support THREE.Geometry. Use THREE.BufferGeometry instead.\\\\\\\");\\n }\\n }\\n }\\n};\\nPoints.prototype.isPoints = true;\\nfunction testPoint(point, index, localThresholdSq, matrixWorld, raycaster, intersects, object) {\\n const rayPointDistanceSq = _ray2.distanceSqToPoint(point);\\n if (rayPointDistanceSq < localThresholdSq) {\\n const intersectPoint = new Vector3();\\n _ray2.closestPointToPoint(point, intersectPoint);\\n intersectPoint.applyMatrix4(matrixWorld);\\n const distance = raycaster.ray.origin.distanceTo(intersectPoint);\\n if (distance < raycaster.near || distance > raycaster.far)\\n return;\\n intersects.push({\\n distance,\\n distanceToRay: Math.sqrt(rayPointDistanceSq),\\n point: intersectPoint,\\n index,\\n face: null,\\n object\\n });\\n }\\n}\\n\\n// ../../../node_modules/three/src/objects/Bone.js\\nvar Bone = class extends Object3D {\\n constructor() {\\n super();\\n this.type = \\\\\\\"Bone\\\\\\\";\\n }\\n};\\nBone.prototype.isBone = true;\\n\\n// ../../../node_modules/three/src/materials/MeshStandardMaterial.js\\nvar MeshStandardMaterial = class extends Material {\\n constructor(parameters) {\\n super();\\n this.defines = {STANDARD: \\\\\\\"\\\\\\\"};\\n this.type = \\\\\\\"MeshStandardMaterial\\\\\\\";\\n this.color = new Color(16777215);\\n this.roughness = 1;\\n this.metalness = 0;\\n this.map = null;\\n this.lightMap = null;\\n this.lightMapIntensity = 1;\\n this.aoMap = null;\\n this.aoMapIntensity = 1;\\n this.emissive = new Color(0);\\n this.emissiveIntensity = 1;\\n this.emissiveMap = null;\\n this.bumpMap = null;\\n this.bumpScale = 1;\\n this.normalMap = null;\\n this.normalMapType = TangentSpaceNormalMap;\\n this.normalScale = new Vector2(1, 1);\\n this.displacementMap = null;\\n this.displacementScale = 1;\\n this.displacementBias = 0;\\n this.roughnessMap = null;\\n this.metalnessMap = null;\\n this.alphaMap = null;\\n this.envMap = null;\\n this.envMapIntensity = 1;\\n this.refractionRatio = 0.98;\\n this.wireframe = false;\\n this.wireframeLinewidth = 1;\\n this.wireframeLinecap = \\\\\\\"round\\\\\\\";\\n this.wireframeLinejoin = \\\\\\\"round\\\\\\\";\\n this.flatShading = false;\\n this.setValues(parameters);\\n }\\n copy(source) {\\n super.copy(source);\\n this.defines = {STANDARD: \\\\\\\"\\\\\\\"};\\n this.color.copy(source.color);\\n this.roughness = source.roughness;\\n this.metalness = source.metalness;\\n this.map = source.map;\\n this.lightMap = source.lightMap;\\n this.lightMapIntensity = source.lightMapIntensity;\\n this.aoMap = source.aoMap;\\n this.aoMapIntensity = source.aoMapIntensity;\\n this.emissive.copy(source.emissive);\\n this.emissiveMap = source.emissiveMap;\\n this.emissiveIntensity = source.emissiveIntensity;\\n this.bumpMap = source.bumpMap;\\n this.bumpScale = source.bumpScale;\\n this.normalMap = source.normalMap;\\n this.normalMapType = source.normalMapType;\\n this.normalScale.copy(source.normalScale);\\n this.displacementMap = source.displacementMap;\\n this.displacementScale = source.displacementScale;\\n this.displacementBias = source.displacementBias;\\n this.roughnessMap = source.roughnessMap;\\n this.metalnessMap = source.metalnessMap;\\n this.alphaMap = source.alphaMap;\\n this.envMap = source.envMap;\\n this.envMapIntensity = source.envMapIntensity;\\n this.refractionRatio = source.refractionRatio;\\n this.wireframe = source.wireframe;\\n this.wireframeLinewidth = source.wireframeLinewidth;\\n this.wireframeLinecap = source.wireframeLinecap;\\n this.wireframeLinejoin = source.wireframeLinejoin;\\n this.flatShading = source.flatShading;\\n return this;\\n }\\n};\\nMeshStandardMaterial.prototype.isMeshStandardMaterial = true;\\n\\n// ../../../node_modules/three/src/materials/MeshLambertMaterial.js\\nvar MeshLambertMaterial = class extends Material {\\n constructor(parameters) {\\n super();\\n this.type = \\\\\\\"MeshLambertMaterial\\\\\\\";\\n this.color = new Color(16777215);\\n this.map = null;\\n this.lightMap = null;\\n this.lightMapIntensity = 1;\\n this.aoMap = null;\\n this.aoMapIntensity = 1;\\n this.emissive = new Color(0);\\n this.emissiveIntensity = 1;\\n this.emissiveMap = null;\\n this.specularMap = null;\\n this.alphaMap = null;\\n this.envMap = null;\\n this.combine = MultiplyOperation;\\n this.reflectivity = 1;\\n this.refractionRatio = 0.98;\\n this.wireframe = false;\\n this.wireframeLinewidth = 1;\\n this.wireframeLinecap = \\\\\\\"round\\\\\\\";\\n this.wireframeLinejoin = \\\\\\\"round\\\\\\\";\\n this.setValues(parameters);\\n }\\n copy(source) {\\n super.copy(source);\\n this.color.copy(source.color);\\n this.map = source.map;\\n this.lightMap = source.lightMap;\\n this.lightMapIntensity = source.lightMapIntensity;\\n this.aoMap = source.aoMap;\\n this.aoMapIntensity = source.aoMapIntensity;\\n this.emissive.copy(source.emissive);\\n this.emissiveMap = source.emissiveMap;\\n this.emissiveIntensity = source.emissiveIntensity;\\n this.specularMap = source.specularMap;\\n this.alphaMap = source.alphaMap;\\n this.envMap = source.envMap;\\n this.combine = source.combine;\\n this.reflectivity = source.reflectivity;\\n this.refractionRatio = source.refractionRatio;\\n this.wireframe = source.wireframe;\\n this.wireframeLinewidth = source.wireframeLinewidth;\\n this.wireframeLinecap = source.wireframeLinecap;\\n this.wireframeLinejoin = source.wireframeLinejoin;\\n return this;\\n }\\n};\\nMeshLambertMaterial.prototype.isMeshLambertMaterial = true;\\n\\n// ../../../node_modules/three/src/materials/LineBasicMaterial.js\\nvar LineBasicMaterial = class extends Material {\\n constructor(parameters) {\\n super();\\n this.type = \\\\\\\"LineBasicMaterial\\\\\\\";\\n this.color = new Color(16777215);\\n this.linewidth = 1;\\n this.linecap = \\\\\\\"round\\\\\\\";\\n this.linejoin = \\\\\\\"round\\\\\\\";\\n this.setValues(parameters);\\n }\\n copy(source) {\\n super.copy(source);\\n this.color.copy(source.color);\\n this.linewidth = source.linewidth;\\n this.linecap = source.linecap;\\n this.linejoin = source.linejoin;\\n return this;\\n }\\n};\\nLineBasicMaterial.prototype.isLineBasicMaterial = true;\\n\\n// ../../../node_modules/three/src/objects/Line.js\\nvar _start = /* @__PURE__ */ new Vector3();\\nvar _end = /* @__PURE__ */ new Vector3();\\nvar _inverseMatrix3 = /* @__PURE__ */ new Matrix4();\\nvar _ray3 = /* @__PURE__ */ new Ray();\\nvar _sphere4 = /* @__PURE__ */ new Sphere();\\nvar Line = class extends Object3D {\\n constructor(geometry = new BufferGeometry(), material = new LineBasicMaterial()) {\\n super();\\n this.type = \\\\\\\"Line\\\\\\\";\\n this.geometry = geometry;\\n this.material = material;\\n this.updateMorphTargets();\\n }\\n copy(source) {\\n super.copy(source);\\n this.material = source.material;\\n this.geometry = source.geometry;\\n return this;\\n }\\n computeLineDistances() {\\n const geometry = this.geometry;\\n if (geometry.isBufferGeometry) {\\n if (geometry.index === null) {\\n const positionAttribute = geometry.attributes.position;\\n const lineDistances = [0];\\n for (let i = 1, l = positionAttribute.count; i < l; i++) {\\n _start.fromBufferAttribute(positionAttribute, i - 1);\\n _end.fromBufferAttribute(positionAttribute, i);\\n lineDistances[i] = lineDistances[i - 1];\\n lineDistances[i] += _start.distanceTo(_end);\\n }\\n geometry.setAttribute(\\\\\\\"lineDistance\\\\\\\", new Float32BufferAttribute(lineDistances, 1));\\n } else {\\n console.warn(\\\\\\\"THREE.Line.computeLineDistances(): Computation only possible with non-indexed BufferGeometry.\\\\\\\");\\n }\\n } else if (geometry.isGeometry) {\\n console.error(\\\\\\\"THREE.Line.computeLineDistances() no longer supports THREE.Geometry. Use THREE.BufferGeometry instead.\\\\\\\");\\n }\\n return this;\\n }\\n raycast(raycaster, intersects) {\\n const geometry = this.geometry;\\n const matrixWorld = this.matrixWorld;\\n const threshold = raycaster.params.Line.threshold;\\n const drawRange = geometry.drawRange;\\n if (geometry.boundingSphere === null)\\n geometry.computeBoundingSphere();\\n _sphere4.copy(geometry.boundingSphere);\\n _sphere4.applyMatrix4(matrixWorld);\\n _sphere4.radius += threshold;\\n if (raycaster.ray.intersectsSphere(_sphere4) === false)\\n return;\\n _inverseMatrix3.copy(matrixWorld).invert();\\n _ray3.copy(raycaster.ray).applyMatrix4(_inverseMatrix3);\\n const localThreshold = threshold / ((this.scale.x + this.scale.y + this.scale.z) / 3);\\n const localThresholdSq = localThreshold * localThreshold;\\n const vStart = new Vector3();\\n const vEnd = new Vector3();\\n const interSegment = new Vector3();\\n const interRay = new Vector3();\\n const step = this.isLineSegments ? 2 : 1;\\n if (geometry.isBufferGeometry) {\\n const index = geometry.index;\\n const attributes = geometry.attributes;\\n const positionAttribute = attributes.position;\\n if (index !== null) {\\n const start = Math.max(0, drawRange.start);\\n const end = Math.min(index.count, drawRange.start + drawRange.count);\\n for (let i = start, l = end - 1; i < l; i += step) {\\n const a = index.getX(i);\\n const b = index.getX(i + 1);\\n vStart.fromBufferAttribute(positionAttribute, a);\\n vEnd.fromBufferAttribute(positionAttribute, b);\\n const distSq = _ray3.distanceSqToSegment(vStart, vEnd, interRay, interSegment);\\n if (distSq > localThresholdSq)\\n continue;\\n interRay.applyMatrix4(this.matrixWorld);\\n const distance = raycaster.ray.origin.distanceTo(interRay);\\n if (distance < raycaster.near || distance > raycaster.far)\\n continue;\\n intersects.push({\\n distance,\\n point: interSegment.clone().applyMatrix4(this.matrixWorld),\\n index: i,\\n face: null,\\n faceIndex: null,\\n object: this\\n });\\n }\\n } else {\\n const start = Math.max(0, drawRange.start);\\n const end = Math.min(positionAttribute.count, drawRange.start + drawRange.count);\\n for (let i = start, l = end - 1; i < l; i += step) {\\n vStart.fromBufferAttribute(positionAttribute, i);\\n vEnd.fromBufferAttribute(positionAttribute, i + 1);\\n const distSq = _ray3.distanceSqToSegment(vStart, vEnd, interRay, interSegment);\\n if (distSq > localThresholdSq)\\n continue;\\n interRay.applyMatrix4(this.matrixWorld);\\n const distance = raycaster.ray.origin.distanceTo(interRay);\\n if (distance < raycaster.near || distance > raycaster.far)\\n continue;\\n intersects.push({\\n distance,\\n point: interSegment.clone().applyMatrix4(this.matrixWorld),\\n index: i,\\n face: null,\\n faceIndex: null,\\n object: this\\n });\\n }\\n }\\n } else if (geometry.isGeometry) {\\n console.error(\\\\\\\"THREE.Line.raycast() no longer supports THREE.Geometry. Use THREE.BufferGeometry instead.\\\\\\\");\\n }\\n }\\n updateMorphTargets() {\\n const geometry = this.geometry;\\n if (geometry.isBufferGeometry) {\\n const morphAttributes = geometry.morphAttributes;\\n const keys = Object.keys(morphAttributes);\\n if (keys.length > 0) {\\n const morphAttribute = morphAttributes[keys[0]];\\n if (morphAttribute !== void 0) {\\n this.morphTargetInfluences = [];\\n this.morphTargetDictionary = {};\\n for (let m = 0, ml = morphAttribute.length; m < ml; m++) {\\n const name = morphAttribute[m].name || String(m);\\n this.morphTargetInfluences.push(0);\\n this.morphTargetDictionary[name] = m;\\n }\\n }\\n }\\n } else {\\n const morphTargets = geometry.morphTargets;\\n if (morphTargets !== void 0 && morphTargets.length > 0) {\\n console.error(\\\\\\\"THREE.Line.updateMorphTargets() does not support THREE.Geometry. Use THREE.BufferGeometry instead.\\\\\\\");\\n }\\n }\\n }\\n};\\nLine.prototype.isLine = true;\\n\\n// ../../../node_modules/three/src/objects/LineSegments.js\\nvar _start2 = /* @__PURE__ */ new Vector3();\\nvar _end2 = /* @__PURE__ */ new Vector3();\\nvar LineSegments = class extends Line {\\n constructor(geometry, material) {\\n super(geometry, material);\\n this.type = \\\\\\\"LineSegments\\\\\\\";\\n }\\n computeLineDistances() {\\n const geometry = this.geometry;\\n if (geometry.isBufferGeometry) {\\n if (geometry.index === null) {\\n const positionAttribute = geometry.attributes.position;\\n const lineDistances = [];\\n for (let i = 0, l = positionAttribute.count; i < l; i += 2) {\\n _start2.fromBufferAttribute(positionAttribute, i);\\n _end2.fromBufferAttribute(positionAttribute, i + 1);\\n lineDistances[i] = i === 0 ? 0 : lineDistances[i - 1];\\n lineDistances[i + 1] = lineDistances[i] + _start2.distanceTo(_end2);\\n }\\n geometry.setAttribute(\\\\\\\"lineDistance\\\\\\\", new Float32BufferAttribute(lineDistances, 1));\\n } else {\\n console.warn(\\\\\\\"THREE.LineSegments.computeLineDistances(): Computation only possible with non-indexed BufferGeometry.\\\\\\\");\\n }\\n } else if (geometry.isGeometry) {\\n console.error(\\\\\\\"THREE.LineSegments.computeLineDistances() no longer supports THREE.Geometry. Use THREE.BufferGeometry instead.\\\\\\\");\\n }\\n return this;\\n }\\n};\\nLineSegments.prototype.isLineSegments = true;\\n\\n// ../../../node_modules/three/src/objects/LOD.js\\nvar _v16 = /* @__PURE__ */ new Vector3();\\nvar _v23 = /* @__PURE__ */ new Vector3();\\nvar LOD = class extends Object3D {\\n constructor() {\\n super();\\n this._currentLevel = 0;\\n this.type = \\\\\\\"LOD\\\\\\\";\\n Object.defineProperties(this, {\\n levels: {\\n enumerable: true,\\n value: []\\n },\\n isLOD: {\\n value: true\\n }\\n });\\n this.autoUpdate = true;\\n }\\n copy(source) {\\n super.copy(source, false);\\n const levels = source.levels;\\n for (let i = 0, l = levels.length; i < l; i++) {\\n const level = levels[i];\\n this.addLevel(level.object.clone(), level.distance);\\n }\\n this.autoUpdate = source.autoUpdate;\\n return this;\\n }\\n addLevel(object, distance = 0) {\\n distance = Math.abs(distance);\\n const levels = this.levels;\\n let l;\\n for (l = 0; l < levels.length; l++) {\\n if (distance < levels[l].distance) {\\n break;\\n }\\n }\\n levels.splice(l, 0, {distance, object});\\n this.add(object);\\n return this;\\n }\\n getCurrentLevel() {\\n return this._currentLevel;\\n }\\n getObjectForDistance(distance) {\\n const levels = this.levels;\\n if (levels.length > 0) {\\n let i, l;\\n for (i = 1, l = levels.length; i < l; i++) {\\n if (distance < levels[i].distance) {\\n break;\\n }\\n }\\n return levels[i - 1].object;\\n }\\n return null;\\n }\\n raycast(raycaster, intersects) {\\n const levels = this.levels;\\n if (levels.length > 0) {\\n _v16.setFromMatrixPosition(this.matrixWorld);\\n const distance = raycaster.ray.origin.distanceTo(_v16);\\n this.getObjectForDistance(distance).raycast(raycaster, intersects);\\n }\\n }\\n update(camera) {\\n const levels = this.levels;\\n if (levels.length > 1) {\\n _v16.setFromMatrixPosition(camera.matrixWorld);\\n _v23.setFromMatrixPosition(this.matrixWorld);\\n const distance = _v16.distanceTo(_v23) / camera.zoom;\\n levels[0].object.visible = true;\\n let i, l;\\n for (i = 1, l = levels.length; i < l; i++) {\\n if (distance >= levels[i].distance) {\\n levels[i - 1].object.visible = false;\\n levels[i].object.visible = true;\\n } else {\\n break;\\n }\\n }\\n this._currentLevel = i - 1;\\n for (; i < l; i++) {\\n levels[i].object.visible = false;\\n }\\n }\\n }\\n toJSON(meta) {\\n const data = super.toJSON(meta);\\n if (this.autoUpdate === false)\\n data.object.autoUpdate = false;\\n data.object.levels = [];\\n const levels = this.levels;\\n for (let i = 0, l = levels.length; i < l; i++) {\\n const level = levels[i];\\n data.object.levels.push({\\n object: level.object.uuid,\\n distance: level.distance\\n });\\n }\\n return data;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/core/geometry/Constant.ts\\nvar ObjectType;\\n(function(ObjectType2) {\\n ObjectType2[\\\\\\\"OBJECT3D\\\\\\\"] = \\\\\\\"Object3D\\\\\\\";\\n ObjectType2[\\\\\\\"GROUP\\\\\\\"] = \\\\\\\"Group\\\\\\\";\\n ObjectType2[\\\\\\\"MESH\\\\\\\"] = \\\\\\\"Mesh\\\\\\\";\\n ObjectType2[\\\\\\\"POINTS\\\\\\\"] = \\\\\\\"Points\\\\\\\";\\n ObjectType2[\\\\\\\"LINE_SEGMENTS\\\\\\\"] = \\\\\\\"LineSegments\\\\\\\";\\n ObjectType2[\\\\\\\"LOD\\\\\\\"] = \\\\\\\"LOD\\\\\\\";\\n})(ObjectType || (ObjectType = {}));\\nvar OBJECT_CONSTRUCTOR_BY_OBJECT_TYPE = {\\n [ObjectType.MESH]: Mesh,\\n [ObjectType.GROUP]: Group,\\n [ObjectType.POINTS]: Points,\\n [ObjectType.LINE_SEGMENTS]: LineSegments,\\n [ObjectType.OBJECT3D]: Object3D,\\n [ObjectType.LOD]: LOD\\n};\\nfunction objectTypeFromConstructor(constructor) {\\n switch (constructor) {\\n case Object3D:\\n return ObjectType.OBJECT3D;\\n case Group:\\n return ObjectType.GROUP;\\n case Mesh:\\n return ObjectType.MESH;\\n case Points:\\n return ObjectType.POINTS;\\n case LineSegments:\\n return ObjectType.LINE_SEGMENTS;\\n case LOD:\\n return ObjectType.LOD;\\n default:\\n Poly.warn(\\\\\\\"object type not supported\\\\\\\", constructor);\\n return ObjectType.MESH;\\n }\\n}\\nvar ObjectTypes = [ObjectType.MESH, ObjectType.POINTS, ObjectType.LINE_SEGMENTS];\\nvar ObjectTypeMenuEntries = [\\n {name: \\\\\\\"Mesh\\\\\\\", value: ObjectTypes.indexOf(ObjectType.MESH)},\\n {name: \\\\\\\"Points\\\\\\\", value: ObjectTypes.indexOf(ObjectType.POINTS)},\\n {name: \\\\\\\"LineSegments\\\\\\\", value: ObjectTypes.indexOf(ObjectType.LINE_SEGMENTS)}\\n];\\nvar materials = {\\n MeshStandard: new MeshStandardMaterial({\\n color: 16777215,\\n side: FrontSide,\\n metalness: 0.5,\\n roughness: 0.9\\n }),\\n [ObjectType.MESH]: new MeshLambertMaterial({\\n color: new Color(1, 1, 1),\\n side: FrontSide,\\n vertexColors: false,\\n transparent: true,\\n depthTest: true\\n }),\\n [ObjectType.POINTS]: new PointsMaterial({\\n color: 16777215,\\n size: 0.1,\\n depthTest: true\\n }),\\n [ObjectType.LINE_SEGMENTS]: new LineBasicMaterial({\\n color: 16777215,\\n linewidth: 1\\n })\\n};\\nvar AttribClass;\\n(function(AttribClass3) {\\n AttribClass3[AttribClass3[\\\\\\\"VERTEX\\\\\\\"] = 0] = \\\\\\\"VERTEX\\\\\\\";\\n AttribClass3[AttribClass3[\\\\\\\"OBJECT\\\\\\\"] = 1] = \\\\\\\"OBJECT\\\\\\\";\\n})(AttribClass || (AttribClass = {}));\\nvar AttribType;\\n(function(AttribType2) {\\n AttribType2[AttribType2[\\\\\\\"NUMERIC\\\\\\\"] = 0] = \\\\\\\"NUMERIC\\\\\\\";\\n AttribType2[AttribType2[\\\\\\\"STRING\\\\\\\"] = 1] = \\\\\\\"STRING\\\\\\\";\\n})(AttribType || (AttribType = {}));\\nvar AttribSize;\\n(function(AttribSize5) {\\n AttribSize5[AttribSize5[\\\\\\\"FLOAT\\\\\\\"] = 1] = \\\\\\\"FLOAT\\\\\\\";\\n AttribSize5[AttribSize5[\\\\\\\"VECTOR2\\\\\\\"] = 2] = \\\\\\\"VECTOR2\\\\\\\";\\n AttribSize5[AttribSize5[\\\\\\\"VECTOR3\\\\\\\"] = 3] = \\\\\\\"VECTOR3\\\\\\\";\\n AttribSize5[AttribSize5[\\\\\\\"VECTOR4\\\\\\\"] = 4] = \\\\\\\"VECTOR4\\\\\\\";\\n})(AttribSize || (AttribSize = {}));\\nvar CoreConstant = {\\n ATTRIB_CLASS: {\\n VERTEX: 0,\\n OBJECT: 1\\n },\\n OBJECT_TYPES: ObjectTypes,\\n CONSTRUCTOR_NAMES_BY_CONSTRUCTOR_NAME: {\\n [Scene.name]: \\\\\\\"Scene\\\\\\\",\\n [Group.name]: \\\\\\\"Group\\\\\\\",\\n [Object3D.name]: \\\\\\\"Object3D\\\\\\\",\\n [Mesh.name]: \\\\\\\"Mesh\\\\\\\",\\n [Points.name]: \\\\\\\"Points\\\\\\\",\\n [LineSegments.name]: \\\\\\\"LineSegments\\\\\\\",\\n [Bone.name]: \\\\\\\"Bone\\\\\\\",\\n [SkinnedMesh.name]: \\\\\\\"SkinnedMesh\\\\\\\"\\n },\\n CONSTRUCTORS_BY_NAME: {\\n [ObjectType.MESH]: Mesh,\\n [ObjectType.POINTS]: Points,\\n [ObjectType.LINE_SEGMENTS]: LineSegments\\n },\\n MATERIALS: materials\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/core/geometry/Attribute.ts\\nvar Attribute;\\n(function(Attribute2) {\\n Attribute2[\\\\\\\"COLOR\\\\\\\"] = \\\\\\\"color\\\\\\\";\\n Attribute2[\\\\\\\"NORMAL\\\\\\\"] = \\\\\\\"normal\\\\\\\";\\n Attribute2[\\\\\\\"POSITION\\\\\\\"] = \\\\\\\"position\\\\\\\";\\n Attribute2[\\\\\\\"PSCALE\\\\\\\"] = \\\\\\\"pscale\\\\\\\";\\n Attribute2[\\\\\\\"UP\\\\\\\"] = \\\\\\\"up\\\\\\\";\\n Attribute2[\\\\\\\"UV\\\\\\\"] = \\\\\\\"uv\\\\\\\";\\n Attribute2[\\\\\\\"SCALE\\\\\\\"] = \\\\\\\"scale\\\\\\\";\\n Attribute2[\\\\\\\"TANGENT\\\\\\\"] = \\\\\\\"tangent\\\\\\\";\\n})(Attribute || (Attribute = {}));\\nvar ATTRIB_NAME_MAP = {\\n P: Attribute.POSITION,\\n N: Attribute.NORMAL,\\n Cd: Attribute.COLOR\\n};\\nvar CoreAttribute = class {\\n static remapName(name) {\\n return ATTRIB_NAME_MAP[name] || name;\\n }\\n static arrayToIndexedArrays(array) {\\n const index_by_value = {};\\n let current_index = 0;\\n const indices = [];\\n const values = [];\\n let i = 0;\\n while (i < array.length) {\\n const value = array[i];\\n const index = index_by_value[value];\\n if (index != null) {\\n indices.push(index);\\n } else {\\n values.push(value);\\n indices.push(current_index);\\n index_by_value[value] = current_index;\\n current_index += 1;\\n }\\n i++;\\n }\\n return {\\n indices,\\n values\\n };\\n }\\n static default_value(size) {\\n switch (size) {\\n case 1:\\n return 0;\\n case 2:\\n return new Vector2(0, 0);\\n case 3:\\n return new Vector3(0, 0, 0);\\n default:\\n throw `size ${size} not yet implemented`;\\n }\\n }\\n static copy(src, dest, mark_as_needs_update = true) {\\n const src_array = src?.array;\\n const dest_array = dest?.array;\\n if (src_array && dest_array) {\\n const min_length = Math.min(src_array.length, dest_array.length);\\n for (let i = 0; i < min_length; i++) {\\n dest_array[i] = src_array[i];\\n }\\n if (mark_as_needs_update) {\\n dest.needsUpdate = true;\\n }\\n }\\n }\\n static attribSizeFromValue(val) {\\n if (CoreType.isString(val) || CoreType.isNumber(val)) {\\n return AttribSize.FLOAT;\\n }\\n if (CoreType.isArray(val)) {\\n return val.length;\\n }\\n switch (val.constructor) {\\n case Vector2:\\n return AttribSize.VECTOR2;\\n case Vector3:\\n return AttribSize.VECTOR3;\\n case Vector4:\\n return AttribSize.VECTOR4;\\n }\\n return 0;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/core/geometry/Entity.ts\\nvar CoreEntity = class {\\n constructor(_index) {\\n this._index = _index;\\n }\\n index() {\\n return this._index;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/core/geometry/Point.ts\\nvar ATTRIB_NAMES = {\\n POSITION: \\\\\\\"position\\\\\\\",\\n NORMAL: \\\\\\\"normal\\\\\\\"\\n};\\nvar ComponentName;\\n(function(ComponentName2) {\\n ComponentName2[\\\\\\\"x\\\\\\\"] = \\\\\\\"x\\\\\\\";\\n ComponentName2[\\\\\\\"y\\\\\\\"] = \\\\\\\"y\\\\\\\";\\n ComponentName2[\\\\\\\"z\\\\\\\"] = \\\\\\\"z\\\\\\\";\\n ComponentName2[\\\\\\\"w\\\\\\\"] = \\\\\\\"w\\\\\\\";\\n ComponentName2[\\\\\\\"r\\\\\\\"] = \\\\\\\"r\\\\\\\";\\n ComponentName2[\\\\\\\"g\\\\\\\"] = \\\\\\\"g\\\\\\\";\\n ComponentName2[\\\\\\\"b\\\\\\\"] = \\\\\\\"b\\\\\\\";\\n})(ComponentName || (ComponentName = {}));\\nvar COMPONENT_INDICES = {\\n x: 0,\\n y: 1,\\n z: 2,\\n w: 3,\\n r: 0,\\n g: 1,\\n b: 2\\n};\\nvar PTNUM = \\\\\\\"ptnum\\\\\\\";\\nvar DOT = \\\\\\\".\\\\\\\";\\nvar CorePoint = class extends CoreEntity {\\n constructor(_coreGeometry, _index) {\\n super(_index);\\n this._coreGeometry = _coreGeometry;\\n this._geometry = this._coreGeometry.geometry();\\n }\\n applyMatrix4(matrix) {\\n this.position().applyMatrix4(matrix);\\n }\\n coreGeometry() {\\n return this._coreGeometry;\\n }\\n geometry() {\\n return this._geometry = this._geometry || this._coreGeometry.geometry();\\n }\\n attribSize(name) {\\n name = CoreAttribute.remapName(name);\\n return this._geometry.getAttribute(name).itemSize;\\n }\\n hasAttrib(name) {\\n const remapped_name = CoreAttribute.remapName(name);\\n return this._coreGeometry.hasAttrib(remapped_name);\\n }\\n attribValue(name, target) {\\n if (name === PTNUM) {\\n return this.index();\\n } else {\\n let component_name = null;\\n let component_index = null;\\n if (name[name.length - 2] === DOT) {\\n component_name = name[name.length - 1];\\n component_index = COMPONENT_INDICES[component_name];\\n name = name.substring(0, name.length - 2);\\n }\\n const remaped_name = CoreAttribute.remapName(name);\\n const attrib = this._geometry.getAttribute(remaped_name);\\n if (attrib) {\\n const {array} = attrib;\\n if (this._coreGeometry.isAttribIndexed(remaped_name)) {\\n return this.indexedAttribValue(remaped_name);\\n } else {\\n const size = attrib.itemSize;\\n const start_index = this._index * size;\\n if (component_index == null) {\\n switch (size) {\\n case 1:\\n return array[start_index];\\n break;\\n case 2:\\n target = target || new Vector2();\\n target.fromArray(array, start_index);\\n return target;\\n break;\\n case 3:\\n target = target || new Vector3();\\n target.fromArray(array, start_index);\\n return target;\\n break;\\n case 4:\\n target = target || new Vector4();\\n target.fromArray(array, start_index);\\n return target;\\n break;\\n default:\\n throw `size not valid (${size})`;\\n }\\n } else {\\n switch (size) {\\n case 1:\\n return array[start_index];\\n break;\\n default:\\n return array[start_index + component_index];\\n }\\n }\\n }\\n } else {\\n const message = `attrib ${name} not found. availables are: ${Object.keys(this._geometry.attributes || {}).join(\\\\\\\",\\\\\\\")}`;\\n console.warn(message);\\n throw message;\\n }\\n }\\n }\\n attribValueNumber(name) {\\n const remapedName = CoreAttribute.remapName(name);\\n const attrib = this._geometry.getAttribute(remapedName);\\n return attrib.array[this._index];\\n }\\n attribValueVector2(name, target) {\\n const remapedName = CoreAttribute.remapName(name);\\n const attrib = this._geometry.getAttribute(remapedName);\\n target.fromArray(attrib.array, this._index * 2);\\n return target;\\n }\\n attribValueVector3(name, target) {\\n const remapedName = CoreAttribute.remapName(name);\\n const attrib = this._geometry.getAttribute(remapedName);\\n target.fromArray(attrib.array, this._index * 3);\\n return target;\\n }\\n attribValueVector4(name, target) {\\n const remapedName = CoreAttribute.remapName(name);\\n const attrib = this._geometry.getAttribute(remapedName);\\n target.fromArray(attrib.array, this._index * 4);\\n return target;\\n }\\n indexedAttribValue(name) {\\n const value_index = this.attribValueIndex(name);\\n return this._coreGeometry.userDataAttrib(name)[value_index];\\n }\\n stringAttribValue(name) {\\n return this.indexedAttribValue(name);\\n }\\n attribValueIndex(name) {\\n if (this._coreGeometry.isAttribIndexed(name)) {\\n return this._geometry.getAttribute(name).array[this._index];\\n } else {\\n return -1;\\n }\\n }\\n isAttribIndexed(name) {\\n return this._coreGeometry.isAttribIndexed(name);\\n }\\n position() {\\n return this._position || (this._position = this.getPosition(new Vector3()));\\n }\\n getPosition(target) {\\n const {array} = this._geometry.getAttribute(ATTRIB_NAMES.POSITION);\\n return target.fromArray(array, this._index * 3);\\n }\\n setPosition(new_position) {\\n this.setAttribValueVector3(ATTRIB_NAMES.POSITION, new_position);\\n }\\n normal() {\\n return this._normal = this._normal || this.getNormal(new Vector3());\\n }\\n getNormal(target) {\\n const {array} = this._geometry.getAttribute(ATTRIB_NAMES.NORMAL);\\n return target.fromArray(array, this._index * 3);\\n }\\n setNormal(new_normal) {\\n return this.setAttribValueVector3(ATTRIB_NAMES.NORMAL, new_normal);\\n }\\n setAttribValue(attribName, value) {\\n const attrib = this._geometry.getAttribute(attribName);\\n const array = attrib.array;\\n const attribSize = attrib.itemSize;\\n if (CoreType.isArray(value)) {\\n for (let i = 0; i < attribSize; i++) {\\n array[this._index * attribSize + i] = value[i];\\n }\\n return;\\n }\\n switch (attribSize) {\\n case 1:\\n array[this._index] = value;\\n break;\\n case 2:\\n const v2 = value;\\n const i2 = this._index * 2;\\n array[i2 + 0] = v2.x;\\n array[i2 + 1] = v2.y;\\n break;\\n case 3:\\n const isColor = value.r != null;\\n const i3 = this._index * 3;\\n if (isColor) {\\n const col = value;\\n array[i3 + 0] = col.r;\\n array[i3 + 1] = col.g;\\n array[i3 + 2] = col.b;\\n } else {\\n const v3 = value;\\n array[i3 + 0] = v3.x;\\n array[i3 + 1] = v3.y;\\n array[i3 + 2] = v3.z;\\n }\\n break;\\n case 4:\\n const v4 = value;\\n const i4 = this._index * 4;\\n array[i4 + 0] = v4.x;\\n array[i4 + 1] = v4.y;\\n array[i4 + 2] = v4.z;\\n array[i4 + 3] = v4.w;\\n break;\\n default:\\n console.warn(`Point.set_attrib_value does not yet allow attrib size ${attribSize}`);\\n throw `attrib size ${attribSize} not implemented`;\\n }\\n }\\n setAttribValueFromNumber(attribName, value) {\\n const attrib = this._geometry.getAttribute(attribName);\\n const array = attrib.array;\\n array[this._index] = value;\\n }\\n setAttribValueFromVector2(attribName, value) {\\n const attrib = this._geometry.getAttribute(attribName);\\n value.toArray(attrib.array, this._index * 2);\\n }\\n setAttribValueFromVector3(attribName, value) {\\n const attrib = this._geometry.getAttribute(attribName);\\n value.toArray(attrib.array, this._index * 3);\\n }\\n setAttribValueFromVector4(attribName, value) {\\n const attrib = this._geometry.getAttribute(attribName);\\n value.toArray(attrib.array, this._index * 4);\\n }\\n setAttribValueVector3(name, value) {\\n if (value == null) {\\n return;\\n }\\n if (name == null) {\\n throw \\\\\\\"Point.set_attrib_value requires a name\\\\\\\";\\n }\\n const attrib = this._geometry.getAttribute(name);\\n const array = attrib.array;\\n const i = this._index * 3;\\n array[i] = value.x;\\n array[i + 1] = value.y;\\n array[i + 2] = value.z;\\n }\\n setAttribIndex(name, new_value_index) {\\n const array = this._geometry.getAttribute(name).array;\\n return array[this._index] = new_value_index;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/core/math/Easing.ts\\nvar ease_i = function(power) {\\n return function(t) {\\n return Math.pow(t, power);\\n };\\n};\\nvar ease_o = function(power) {\\n return function(t) {\\n return 1 - Math.abs(Math.pow(t - 1, power));\\n };\\n};\\nvar ease_io = function(power) {\\n return function(t) {\\n return t < 0.5 ? ease_i(power)(t * 2) / 2 : ease_o(power)(t * 2 - 1) / 2 + 0.5;\\n };\\n};\\nvar Easing = {\\n linear: ease_io(1),\\n ease_i: function(t, power) {\\n return ease_i(power)(t);\\n },\\n ease_o: function(t, power) {\\n return ease_o(power)(t);\\n },\\n ease_io: function(t, power) {\\n return ease_io(power)(t);\\n },\\n ease_i2: ease_i(2),\\n ease_o2: ease_o(2),\\n ease_io2: ease_io(2),\\n ease_i3: ease_io(3),\\n ease_o3: ease_io(3),\\n ease_io3: ease_io(3),\\n ease_i4: ease_io(4),\\n ease_o4: ease_io(4),\\n ease_io4: ease_io(4),\\n ease_i_sin: function(t) {\\n return 1 + Math.sin(Math.PI / 2 * t - Math.PI / 2);\\n },\\n ease_o_sin: function(t) {\\n return Math.sin(Math.PI / 2 * t);\\n },\\n ease_io_sin: function(t) {\\n return (1 + Math.sin(Math.PI * t - Math.PI / 2)) / 2;\\n },\\n ease_i_elastic: function(t) {\\n return (0.04 - 0.04 / t) * Math.sin(25 * t) + 1;\\n },\\n ease_o_elastic: function(t) {\\n return 0.04 * t / --t * Math.sin(25 * t);\\n },\\n ease_io_elastic: function(t) {\\n return (t -= 0.5) < 0 ? (0.02 + 0.01 / t) * Math.sin(50 * t) : (0.02 - 0.01 / t) * Math.sin(50 * t) + 1;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/core/math/_Module.ts\\nvar RAD_DEG_RATIO = Math.PI / 180;\\nvar RAND_A = 12.9898;\\nvar RAND_B = 78.233;\\nvar RAND_C = 43758.5453;\\nvar CoreMath = class {\\n static clamp(val, min, max) {\\n if (val < min) {\\n return min;\\n } else if (val > max) {\\n return max;\\n } else {\\n return val;\\n }\\n }\\n static fit01(val, dest_min, dest_max) {\\n return this.fit(val, 0, 1, dest_min, dest_max);\\n }\\n static fit(val, src_min, src_max, dest_min, dest_max) {\\n const src_range = src_max - src_min;\\n const dest_range = dest_max - dest_min;\\n const r = (val - src_min) / src_range;\\n return r * dest_range + dest_min;\\n }\\n static blend(num0, num1, blend) {\\n return (1 - blend) * num0 + blend * num1;\\n }\\n static degrees_to_radians(degrees) {\\n return degrees * RAD_DEG_RATIO;\\n }\\n static radians_to_degrees(radians) {\\n return radians / RAD_DEG_RATIO;\\n }\\n static deg2rad(deg) {\\n return this.degrees_to_radians(deg);\\n }\\n static rad2deg(rad) {\\n return this.radians_to_degrees(rad);\\n }\\n static rand(number) {\\n if (CoreType.isNumber(number)) {\\n return this.randFloat(number);\\n } else {\\n return this.randVec2(number);\\n }\\n }\\n static round(number, step_size) {\\n const steps_count = number / step_size;\\n const rounded_steps_count = number < 0 ? Math.ceil(steps_count) : Math.floor(steps_count);\\n return rounded_steps_count * step_size;\\n }\\n static highest_even(number) {\\n return 2 * Math.ceil(number * 0.5);\\n }\\n static randFloat(x, y = 136574) {\\n this._vec.x = x;\\n this._vec.y = y;\\n return this.randVec2(this._vec);\\n }\\n static randVec2(uv) {\\n const dt = uv.x * RAND_A + uv.y * RAND_B;\\n const sn = dt % Math.PI;\\n return this.fract(Math.sin(sn) * RAND_C);\\n }\\n static geodesic_distance(lnglat1, lnglat2) {\\n var R = 6371e3;\\n var d1 = this.deg2rad(lnglat1.lat);\\n var d2 = this.deg2rad(lnglat2.lat);\\n var ad1 = this.deg2rad(lnglat2.lat - lnglat1.lat);\\n var ad2 = this.deg2rad(lnglat2.lng - lnglat1.lng);\\n var a = Math.sin(ad1 / 2) * Math.sin(ad1 / 2) + Math.cos(d1) * Math.cos(d2) * Math.sin(ad2 / 2) * Math.sin(ad2 / 2);\\n var c = 2 * Math.atan2(Math.sqrt(a), Math.sqrt(1 - a));\\n var d = R * c;\\n return d;\\n }\\n static expand_triangle(triangle, margin) {\\n triangle.getMidpoint(this._triangle_mid);\\n this._triangle_mid_to_corner.copy(triangle.a).sub(this._triangle_mid);\\n this._triangle_mid_to_corner.normalize().multiplyScalar(margin);\\n triangle.a.add(this._triangle_mid_to_corner);\\n this._triangle_mid_to_corner.copy(triangle.b).sub(this._triangle_mid);\\n this._triangle_mid_to_corner.normalize().multiplyScalar(margin);\\n triangle.b.add(this._triangle_mid_to_corner);\\n this._triangle_mid_to_corner.copy(triangle.c).sub(this._triangle_mid);\\n this._triangle_mid_to_corner.normalize().multiplyScalar(margin);\\n triangle.c.add(this._triangle_mid_to_corner);\\n }\\n static nearestPower2(num) {\\n return Math.pow(2, Math.ceil(Math.log(num) / Math.log(2)));\\n }\\n};\\nCoreMath.Easing = Easing;\\nCoreMath.fract = (number) => number - Math.floor(number);\\nCoreMath._vec = {x: 0, y: 136574};\\nCoreMath._triangle_mid = new Vector3();\\nCoreMath._triangle_mid_to_corner = new Vector3();\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/core/geometry/Face.ts\\nvar CoreFace = class {\\n constructor(_coreGeometry, _index) {\\n this._coreGeometry = _coreGeometry;\\n this._index = _index;\\n this._geometry = this._coreGeometry.geometry();\\n }\\n index() {\\n return this._index;\\n }\\n points() {\\n return this._points = this._points || this._get_points();\\n }\\n applyMatrix4(matrix) {\\n for (let point of this.points()) {\\n point.applyMatrix4(matrix);\\n }\\n }\\n _get_points() {\\n const indexArray = this._geometry.index?.array || [];\\n const start = this._index * 3;\\n return [\\n new CorePoint(this._coreGeometry, indexArray[start + 0]),\\n new CorePoint(this._coreGeometry, indexArray[start + 1]),\\n new CorePoint(this._coreGeometry, indexArray[start + 2])\\n ];\\n }\\n positions() {\\n return this._positions = this._positions || this._getPositions();\\n }\\n _getPositions() {\\n const points2 = this.points();\\n return [points2[0].position(), points2[1].position(), points2[2].position()];\\n }\\n triangle() {\\n return this._triangle = this._triangle || this._get_triangle();\\n }\\n _get_triangle() {\\n const positions = this.positions();\\n return new Triangle(positions[0], positions[1], positions[2]);\\n }\\n deltas() {\\n return this._deltas = this._deltas || this._getDeltas();\\n }\\n _getDeltas() {\\n const positions = this.positions();\\n return [positions[1].clone().sub(positions[0]), positions[2].clone().sub(positions[0])];\\n }\\n area() {\\n return this.triangle().getArea();\\n }\\n center(target) {\\n const positions = this.positions();\\n target.x = (positions[0].x + positions[1].x + positions[2].x) / 3;\\n target.y = (positions[0].y + positions[1].y + positions[2].y) / 3;\\n target.z = (positions[0].z + positions[1].z + positions[2].z) / 3;\\n return target;\\n }\\n randomPosition(seed) {\\n let weights = [CoreMath.randFloat(seed), CoreMath.randFloat(seed * 6541)];\\n if (weights[0] + weights[1] > 1) {\\n weights[0] = 1 - weights[0];\\n weights[1] = 1 - weights[1];\\n }\\n return this.positions()[0].clone().add(this.deltas()[0].clone().multiplyScalar(weights[0])).add(this.deltas()[1].clone().multiplyScalar(weights[1]));\\n }\\n attribValueAtPosition(attrib_name, position) {\\n const barycentricCoordinates = new Vector3();\\n this.triangle().getBarycoord(position, barycentricCoordinates);\\n const weights = barycentricCoordinates.toArray();\\n const attrib = this._geometry.attributes[attrib_name];\\n const attribSize = attrib.itemSize;\\n const pointValues = this.points().map((point) => point.attribValue(attrib_name));\\n let newAttribValue;\\n let sum;\\n let index = 0;\\n switch (attribSize) {\\n case 1: {\\n sum = 0;\\n for (let pointValue of pointValues) {\\n sum += pointValue * weights[index];\\n index++;\\n }\\n newAttribValue = sum;\\n break;\\n }\\n default: {\\n for (let pointValue of pointValues) {\\n const weightedValue = pointValue.multiplyScalar(weights[index]);\\n if (sum) {\\n sum.add(weightedValue);\\n } else {\\n sum = weightedValue;\\n }\\n index++;\\n }\\n newAttribValue = sum;\\n }\\n }\\n return newAttribValue;\\n }\\n static interpolatedValue(geometry, face, intersectPoint, attrib) {\\n const pointIndices = [face.a, face.b, face.c];\\n const positionAttrib = geometry.getAttribute(\\\\\\\"position\\\\\\\");\\n const positionAttribArray = positionAttrib.array;\\n const pointPositions = pointIndices.map((point_index) => new Vector3(positionAttribArray[point_index * 3 + 0], positionAttribArray[point_index * 3 + 1], positionAttribArray[point_index * 3 + 2]));\\n const attribSize = attrib.itemSize;\\n const attribArray = attrib.array;\\n let attribValues = [];\\n switch (attribSize) {\\n case 1:\\n attribValues = pointIndices.map((point_index) => attribArray[point_index]);\\n break;\\n case 2:\\n attribValues = pointIndices.map((point_index) => new Vector2(attribArray[point_index * 2 + 0], attribArray[point_index * 2 + 1]));\\n break;\\n case 3:\\n attribValues = pointIndices.map((point_index) => new Vector3(attribArray[point_index * 3 + 0], attribArray[point_index * 3 + 1], attribArray[point_index * 3 + 2]));\\n break;\\n }\\n const distToPoints = pointIndices.map((point_index, i) => intersectPoint.distanceTo(pointPositions[i]));\\n const distanceTotal = ArrayUtils.sum([\\n distToPoints[0] * distToPoints[1],\\n distToPoints[0] * distToPoints[2],\\n distToPoints[1] * distToPoints[2]\\n ]);\\n const weights = [\\n distToPoints[1] * distToPoints[2] / distanceTotal,\\n distToPoints[0] * distToPoints[2] / distanceTotal,\\n distToPoints[0] * distToPoints[1] / distanceTotal\\n ];\\n let newAttribValue;\\n switch (attribSize) {\\n case 1:\\n newAttribValue = ArrayUtils.sum(pointIndices.map((point_indx, i) => weights[i] * attribValues[i]));\\n break;\\n default:\\n var values = pointIndices.map((point_index, i) => attribValues[i].multiplyScalar(weights[i]));\\n newAttribValue = null;\\n for (let value of values) {\\n if (newAttribValue) {\\n newAttribValue.add(value);\\n } else {\\n newAttribValue = value;\\n }\\n }\\n }\\n return newAttribValue;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/core/geometry/builders/_Base.ts\\nvar CoreGeometryBuilderBase = class {\\n from_points(points2) {\\n points2 = this._filter_points(points2);\\n const geometry = new BufferGeometry();\\n const core_geometry = new CoreGeometry(geometry);\\n const first_point = points2[0];\\n if (first_point != null) {\\n const old_geometry = first_point.geometry();\\n const old_core_geometry = first_point.coreGeometry();\\n const new_index_by_old_index = {};\\n for (let i = 0; i < points2.length; i++) {\\n new_index_by_old_index[points2[i].index()] = i;\\n }\\n const indices = this._indices_from_points(new_index_by_old_index, old_geometry);\\n if (indices) {\\n geometry.setIndex(indices);\\n }\\n const {attributes} = old_geometry;\\n for (let attribute_name of Object.keys(attributes)) {\\n const attrib_values = old_core_geometry.userDataAttribs()[attribute_name];\\n const is_attrib_indexed = attrib_values != null;\\n if (is_attrib_indexed) {\\n const new_values = ArrayUtils.uniq(points2.map((point) => point.indexedAttribValue(attribute_name)));\\n const new_index_by_value = {};\\n new_values.forEach((new_value, i) => new_index_by_value[new_value] = i);\\n core_geometry.userDataAttribs()[attribute_name] = new_values;\\n const new_attrib_indices = [];\\n for (let point of points2) {\\n const new_index = new_index_by_value[point.indexedAttribValue(attribute_name)];\\n new_attrib_indices.push(new_index);\\n }\\n geometry.setAttribute(attribute_name, new Float32BufferAttribute(new_attrib_indices, 1));\\n } else {\\n const attrib_size = attributes[attribute_name].itemSize;\\n const values = new Array(points2.length * attrib_size);\\n switch (attrib_size) {\\n case 1:\\n for (let i = 0; i < points2.length; i++) {\\n values[i] = points2[i].attribValue(attribute_name);\\n }\\n break;\\n default:\\n let value;\\n for (let i = 0; i < points2.length; i++) {\\n value = points2[i].attribValue(attribute_name);\\n value.toArray(values, i * attrib_size);\\n }\\n break;\\n }\\n geometry.setAttribute(attribute_name, new Float32BufferAttribute(values, attrib_size));\\n }\\n }\\n }\\n return geometry;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/core/geometry/builders/Points.ts\\nvar CoreGeometryBuilderPoints = class extends CoreGeometryBuilderBase {\\n _filter_points(points2) {\\n return points2;\\n }\\n _indices_from_points(new_index_by_old_index, old_geometry) {\\n const index_attrib = old_geometry.index;\\n if (index_attrib != null) {\\n const old_indices = index_attrib.array;\\n const new_indices = [];\\n let old_index;\\n let new_index;\\n for (let i = 0; i < old_indices.length; i++) {\\n old_index = old_indices[i];\\n new_index = new_index_by_old_index[old_index];\\n if (new_index != null) {\\n new_indices.push(new_index);\\n }\\n }\\n return new_indices;\\n }\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/modules/three/examples/jsm/utils/BufferGeometryUtils.js\\nfunction mergeBufferGeometries(geometries, useGroups = false) {\\n const isIndexed = geometries[0].index !== null;\\n const attributesUsed = new Set(Object.keys(geometries[0].attributes));\\n const morphAttributesUsed = new Set(Object.keys(geometries[0].morphAttributes));\\n const attributes = {};\\n const morphAttributes = {};\\n const morphTargetsRelative = geometries[0].morphTargetsRelative;\\n const mergedGeometry = new BufferGeometry();\\n let offset = 0;\\n for (let i = 0; i < geometries.length; ++i) {\\n const geometry = geometries[i];\\n let attributesCount = 0;\\n if (isIndexed !== (geometry.index !== null)) {\\n console.error(\\\\\\\"THREE.BufferGeometryUtils: .mergeBufferGeometries() failed with geometry at index \\\\\\\" + i + \\\\\\\". All geometries must have compatible attributes; make sure index attribute exists among all geometries, or in none of them.\\\\\\\");\\n return null;\\n }\\n for (const name in geometry.attributes) {\\n if (!attributesUsed.has(name)) {\\n console.error(\\\\\\\"THREE.BufferGeometryUtils: .mergeBufferGeometries() failed with geometry at index \\\\\\\" + i + '. All geometries must have compatible attributes; make sure \\\\\\\"' + name + '\\\\\\\" attribute exists among all geometries, or in none of them.');\\n return null;\\n }\\n if (attributes[name] === void 0)\\n attributes[name] = [];\\n attributes[name].push(geometry.attributes[name]);\\n attributesCount++;\\n }\\n if (attributesCount !== attributesUsed.size) {\\n console.error(\\\\\\\"THREE.BufferGeometryUtils: .mergeBufferGeometries() failed with geometry at index \\\\\\\" + i + \\\\\\\". Make sure all geometries have the same number of attributes.\\\\\\\");\\n return null;\\n }\\n if (morphTargetsRelative !== geometry.morphTargetsRelative) {\\n console.error(\\\\\\\"THREE.BufferGeometryUtils: .mergeBufferGeometries() failed with geometry at index \\\\\\\" + i + \\\\\\\". .morphTargetsRelative must be consistent throughout all geometries.\\\\\\\");\\n return null;\\n }\\n for (const name in geometry.morphAttributes) {\\n if (!morphAttributesUsed.has(name)) {\\n console.error(\\\\\\\"THREE.BufferGeometryUtils: .mergeBufferGeometries() failed with geometry at index \\\\\\\" + i + \\\\\\\". .morphAttributes must be consistent throughout all geometries.\\\\\\\");\\n return null;\\n }\\n if (morphAttributes[name] === void 0)\\n morphAttributes[name] = [];\\n morphAttributes[name].push(geometry.morphAttributes[name]);\\n }\\n mergedGeometry.userData.mergedUserData = mergedGeometry.userData.mergedUserData || [];\\n mergedGeometry.userData.mergedUserData.push(geometry.userData);\\n if (useGroups) {\\n let count;\\n if (isIndexed) {\\n count = geometry.index.count;\\n } else if (geometry.attributes.position !== void 0) {\\n count = geometry.attributes.position.count;\\n } else {\\n console.error(\\\\\\\"THREE.BufferGeometryUtils: .mergeBufferGeometries() failed with geometry at index \\\\\\\" + i + \\\\\\\". The geometry must have either an index or a position attribute\\\\\\\");\\n return null;\\n }\\n mergedGeometry.addGroup(offset, count, i);\\n offset += count;\\n }\\n }\\n if (isIndexed) {\\n let indexOffset = 0;\\n const mergedIndex = [];\\n for (let i = 0; i < geometries.length; ++i) {\\n const index = geometries[i].index;\\n for (let j = 0; j < index.count; ++j) {\\n mergedIndex.push(index.getX(j) + indexOffset);\\n }\\n indexOffset += geometries[i].attributes.position.count;\\n }\\n mergedGeometry.setIndex(mergedIndex);\\n }\\n for (const name in attributes) {\\n const mergedAttribute = mergeBufferAttributes(attributes[name]);\\n if (!mergedAttribute) {\\n console.error(\\\\\\\"THREE.BufferGeometryUtils: .mergeBufferGeometries() failed while trying to merge the \\\\\\\" + name + \\\\\\\" attribute.\\\\\\\");\\n return null;\\n }\\n mergedGeometry.setAttribute(name, mergedAttribute);\\n }\\n for (const name in morphAttributes) {\\n const numMorphTargets = morphAttributes[name][0].length;\\n if (numMorphTargets === 0)\\n break;\\n mergedGeometry.morphAttributes = mergedGeometry.morphAttributes || {};\\n mergedGeometry.morphAttributes[name] = [];\\n for (let i = 0; i < numMorphTargets; ++i) {\\n const morphAttributesToMerge = [];\\n for (let j = 0; j < morphAttributes[name].length; ++j) {\\n morphAttributesToMerge.push(morphAttributes[name][j][i]);\\n }\\n const mergedMorphAttribute = mergeBufferAttributes(morphAttributesToMerge);\\n if (!mergedMorphAttribute) {\\n console.error(\\\\\\\"THREE.BufferGeometryUtils: .mergeBufferGeometries() failed while trying to merge the \\\\\\\" + name + \\\\\\\" morphAttribute.\\\\\\\");\\n return null;\\n }\\n mergedGeometry.morphAttributes[name].push(mergedMorphAttribute);\\n }\\n }\\n return mergedGeometry;\\n}\\nfunction mergeBufferAttributes(attributes) {\\n let TypedArray;\\n let itemSize;\\n let normalized;\\n let arrayLength = 0;\\n for (let i = 0; i < attributes.length; ++i) {\\n const attribute = attributes[i];\\n if (attribute.isInterleavedBufferAttribute) {\\n console.error(\\\\\\\"THREE.BufferGeometryUtils: .mergeBufferAttributes() failed. InterleavedBufferAttributes are not supported.\\\\\\\");\\n return null;\\n }\\n if (TypedArray === void 0)\\n TypedArray = attribute.array.constructor;\\n if (TypedArray !== attribute.array.constructor) {\\n console.error(\\\\\\\"THREE.BufferGeometryUtils: .mergeBufferAttributes() failed. BufferAttribute.array must be of consistent array types across matching attributes.\\\\\\\");\\n return null;\\n }\\n if (itemSize === void 0)\\n itemSize = attribute.itemSize;\\n if (itemSize !== attribute.itemSize) {\\n console.error(\\\\\\\"THREE.BufferGeometryUtils: .mergeBufferAttributes() failed. BufferAttribute.itemSize must be consistent across matching attributes.\\\\\\\");\\n return null;\\n }\\n if (normalized === void 0)\\n normalized = attribute.normalized;\\n if (normalized !== attribute.normalized) {\\n console.error(\\\\\\\"THREE.BufferGeometryUtils: .mergeBufferAttributes() failed. BufferAttribute.normalized must be consistent across matching attributes.\\\\\\\");\\n return null;\\n }\\n arrayLength += attribute.array.length;\\n }\\n const array = new TypedArray(arrayLength);\\n let offset = 0;\\n for (let i = 0; i < attributes.length; ++i) {\\n array.set(attributes[i].array, offset);\\n offset += attributes[i].array.length;\\n }\\n return new BufferAttribute(array, itemSize, normalized);\\n}\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/core/geometry/util/IndexBuilder.ts\\nvar POSITION = \\\\\\\"position\\\\\\\";\\nvar CoreGeometryIndexBuilder = class {\\n static createIndexIfNone(geometry) {\\n if (!geometry.index) {\\n const position = geometry.getAttribute(POSITION);\\n if (position) {\\n const position_array = position.array;\\n geometry.setIndex(ArrayUtils.range(position_array.length / 3));\\n }\\n }\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/core/geometry/builders/Merge.ts\\nvar CoreGeometryBuilderMerge = class {\\n static merge(geometries) {\\n if (geometries.length === 0) {\\n return;\\n }\\n for (let geometry of geometries) {\\n CoreGeometryIndexBuilder.createIndexIfNone(geometry);\\n }\\n const core_geometries = geometries.map((geometry) => new CoreGeometry(geometry));\\n const indexed_attribute_names = core_geometries[0].indexedAttributeNames();\\n const new_values_by_attribute_name = {};\\n for (let indexed_attribute_name of indexed_attribute_names) {\\n const index_by_values = {};\\n const all_geometries_points = [];\\n for (let core_geometry of core_geometries) {\\n const geometry_points = core_geometry.points();\\n for (let point of geometry_points) {\\n all_geometries_points.push(point);\\n const value = point.indexedAttribValue(indexed_attribute_name);\\n index_by_values[value] != null ? index_by_values[value] : index_by_values[value] = Object.keys(index_by_values).length;\\n }\\n }\\n const values = Object.keys(index_by_values);\\n for (let point of all_geometries_points) {\\n const value = point.indexedAttribValue(indexed_attribute_name);\\n const new_index = index_by_values[value];\\n point.setAttribIndex(indexed_attribute_name, new_index);\\n }\\n new_values_by_attribute_name[indexed_attribute_name] = values;\\n }\\n const merged_geometry = mergeBufferGeometries(geometries);\\n const merged_core_geometry = new CoreGeometry(merged_geometry);\\n Object.keys(new_values_by_attribute_name).forEach((indexed_attribute_name) => {\\n const values = new_values_by_attribute_name[indexed_attribute_name];\\n merged_core_geometry.setIndexedAttributeValues(indexed_attribute_name, values);\\n });\\n if (merged_geometry) {\\n delete merged_geometry.userData.mergedUserData;\\n }\\n return merged_geometry;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/core/geometry/builders/Mesh.ts\\nvar CoreGeometryBuilderMesh = class extends CoreGeometryBuilderBase {\\n _filter_points(points2) {\\n const first_point = points2[0];\\n if (first_point) {\\n const geometry = first_point.geometry();\\n const indices = geometry.getIndex()?.array;\\n if (indices) {\\n const points_by_index = {};\\n for (let point of points2) {\\n points_by_index[point.index()] = point;\\n }\\n const filtered_points = [];\\n const index_length = indices.length;\\n let pt0;\\n let pt1;\\n let pt2;\\n for (let i = 0; i < index_length; i += 3) {\\n pt0 = points_by_index[indices[i + 0]];\\n pt1 = points_by_index[indices[i + 1]];\\n pt2 = points_by_index[indices[i + 2]];\\n if (pt0 && pt1 && pt2) {\\n filtered_points.push(pt0);\\n filtered_points.push(pt1);\\n filtered_points.push(pt2);\\n }\\n }\\n return filtered_points;\\n }\\n }\\n return [];\\n }\\n _indices_from_points(new_index_by_old_index, old_geometry) {\\n const index_attrib = old_geometry.index;\\n if (index_attrib != null) {\\n const old_indices = index_attrib.array;\\n const new_indices = [];\\n let old_index0;\\n let old_index1;\\n let old_index2;\\n let new_index0;\\n let new_index1;\\n let new_index2;\\n for (let i = 0; i < old_indices.length; i += 3) {\\n old_index0 = old_indices[i + 0];\\n old_index1 = old_indices[i + 1];\\n old_index2 = old_indices[i + 2];\\n new_index0 = new_index_by_old_index[old_index0];\\n new_index1 = new_index_by_old_index[old_index1];\\n new_index2 = new_index_by_old_index[old_index2];\\n if (new_index0 != null && new_index1 != null && new_index2 != null) {\\n new_indices.push(new_index0);\\n new_indices.push(new_index1);\\n new_indices.push(new_index2);\\n }\\n }\\n return new_indices;\\n }\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/core/geometry/builders/LineSegments.ts\\nvar CoreGeometryBuilderLineSegments = class extends CoreGeometryBuilderBase {\\n _filter_points(points2) {\\n const first_point = points2[0];\\n if (first_point) {\\n const geometry = first_point.geometry();\\n const indices = geometry.getIndex()?.array;\\n if (indices) {\\n const points_by_index = {};\\n for (let point of points2) {\\n points_by_index[point.index()] = point;\\n }\\n const filtered_points = [];\\n const index_length = indices.length;\\n let pt0;\\n let pt1;\\n for (let i = 0; i < index_length; i += 2) {\\n pt0 = points_by_index[indices[i + 0]];\\n pt1 = points_by_index[indices[i + 1]];\\n if (pt0 && pt1) {\\n filtered_points.push(pt0);\\n filtered_points.push(pt1);\\n }\\n }\\n return filtered_points;\\n }\\n }\\n return [];\\n }\\n _indices_from_points(new_index_by_old_index, old_geometry) {\\n const index_attrib = old_geometry.index;\\n if (index_attrib != null) {\\n const old_indices = index_attrib.array;\\n const new_indices = [];\\n let old_index0;\\n let old_index1;\\n let new_index0;\\n let new_index1;\\n for (let i = 0; i < old_indices.length; i += 2) {\\n old_index0 = old_indices[i];\\n old_index1 = old_indices[i + 1];\\n new_index0 = new_index_by_old_index[old_index0];\\n new_index1 = new_index_by_old_index[old_index1];\\n if (new_index0 != null && new_index1 != null) {\\n new_indices.push(new_index0);\\n new_indices.push(new_index1);\\n }\\n }\\n return new_indices;\\n }\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/core/ObjectUtils.ts\\nvar import_cloneDeep = __toModule(require_cloneDeep());\\nvar import_clone = __toModule(require_clone());\\nvar ObjectUtils = class {\\n static isEqual(object0, object1) {\\n if (CoreType.isObject(object0) && CoreType.isObject(object1)) {\\n const keys0 = Object.keys(object0);\\n const keys1 = Object.keys(object1);\\n if (!ArrayUtils.isEqual(keys0, keys1)) {\\n return false;\\n }\\n return JSON.stringify(object0) == JSON.stringify(object1);\\n }\\n return false;\\n }\\n static merge(object0, object1) {\\n return Object.assign(object0, object1);\\n }\\n static clone(value) {\\n return import_clone.default(value);\\n }\\n static cloneDeep(value) {\\n return import_cloneDeep.default(value);\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/core/geometry/Geometry.ts\\nvar IS_INSTANCE_KEY = \\\\\\\"isInstance\\\\\\\";\\nvar INDEX_ATTRIB_VALUES = \\\\\\\"indexed_attrib_values\\\\\\\";\\nvar CoreGeometry2 = class {\\n constructor(_geometry) {\\n this._geometry = _geometry;\\n }\\n geometry() {\\n return this._geometry;\\n }\\n uuid() {\\n return this._geometry.uuid;\\n }\\n boundingBox() {\\n return this._bounding_box = this._bounding_box || this._create_bounding_box();\\n }\\n _create_bounding_box() {\\n this._geometry.computeBoundingBox();\\n if (this._geometry.boundingBox) {\\n return this._geometry.boundingBox;\\n }\\n }\\n markAsInstance() {\\n this._geometry.userData[IS_INSTANCE_KEY] = true;\\n }\\n static markedAsInstance(geometry) {\\n return geometry.userData[IS_INSTANCE_KEY] === true;\\n }\\n markedAsInstance() {\\n return CoreGeometry2.markedAsInstance(this._geometry);\\n }\\n positionAttribName() {\\n let name = \\\\\\\"position\\\\\\\";\\n if (this.markedAsInstance()) {\\n name = \\\\\\\"instancePosition\\\\\\\";\\n }\\n return name;\\n }\\n computeVertexNormals() {\\n this._geometry.computeVertexNormals();\\n }\\n userDataAttribs() {\\n return this._geometry.userData[INDEX_ATTRIB_VALUES] = this._geometry.userData[INDEX_ATTRIB_VALUES] || {};\\n }\\n indexedAttributeNames() {\\n return Object.keys(this.userDataAttribs() || {});\\n }\\n userDataAttrib(name) {\\n name = CoreAttribute.remapName(name);\\n return this.userDataAttribs()[name];\\n }\\n isAttribIndexed(name) {\\n name = CoreAttribute.remapName(name);\\n return this.userDataAttrib(name) != null;\\n }\\n hasAttrib(name) {\\n if (name === \\\\\\\"ptnum\\\\\\\") {\\n return true;\\n }\\n name = CoreAttribute.remapName(name);\\n return this._geometry.attributes[name] != null;\\n }\\n attribType(name) {\\n if (this.isAttribIndexed(name)) {\\n return AttribType.STRING;\\n } else {\\n return AttribType.NUMERIC;\\n }\\n }\\n static attribNames(geometry) {\\n return Object.keys(geometry.attributes);\\n }\\n attribNames() {\\n return CoreGeometry2.attribNames(this._geometry);\\n }\\n static attribNamesMatchingMask(geometry, masks_string) {\\n const masks = CoreString.attribNames(masks_string);\\n const matching_attrib_names = [];\\n for (let attrib_name of this.attribNames(geometry)) {\\n for (let mask of masks) {\\n if (CoreString.matchMask(attrib_name, mask)) {\\n matching_attrib_names.push(attrib_name);\\n }\\n }\\n }\\n return ArrayUtils.uniq(matching_attrib_names);\\n }\\n attribSizes() {\\n const h = {};\\n for (let attrib_name of this.attribNames()) {\\n h[attrib_name] = this._geometry.attributes[attrib_name].itemSize;\\n }\\n return h;\\n }\\n attribSize(name) {\\n let attrib;\\n name = CoreAttribute.remapName(name);\\n if ((attrib = this._geometry.attributes[name]) != null) {\\n return attrib.itemSize;\\n } else {\\n if (name === \\\\\\\"ptnum\\\\\\\") {\\n return 1;\\n } else {\\n return 0;\\n }\\n }\\n }\\n setIndexedAttributeValues(name, values) {\\n this.userDataAttribs()[name] = values;\\n }\\n setIndexedAttribute(name, values, indices) {\\n this.setIndexedAttributeValues(name, values);\\n this._geometry.setAttribute(name, new Int32BufferAttribute(indices, 1));\\n }\\n addNumericAttrib(name, size = 1, default_value = 0) {\\n const values = [];\\n let attribute_added = false;\\n if (CoreType.isNumber(default_value)) {\\n for (let i = 0; i < this.pointsCount(); i++) {\\n for (let j = 0; j < size; j++) {\\n values.push(default_value);\\n }\\n }\\n attribute_added = true;\\n } else {\\n if (size > 1) {\\n if (CoreType.isArray(default_value)) {\\n for (let i = 0; i < this.pointsCount(); i++) {\\n for (let j = 0; j < size; j++) {\\n values.push(default_value[j]);\\n }\\n }\\n attribute_added = true;\\n } else {\\n const vec2 = default_value;\\n if (size == 2 && vec2.x != null && vec2.y != null) {\\n for (let i = 0; i < this.pointsCount(); i++) {\\n values.push(vec2.x);\\n values.push(vec2.y);\\n }\\n attribute_added = true;\\n }\\n const vec3 = default_value;\\n if (size == 3 && vec3.x != null && vec3.y != null && vec3.z != null) {\\n for (let i = 0; i < this.pointsCount(); i++) {\\n values.push(vec3.x);\\n values.push(vec3.y);\\n values.push(vec3.z);\\n }\\n attribute_added = true;\\n }\\n const col = default_value;\\n if (size == 3 && col.r != null && col.g != null && col.b != null) {\\n for (let i = 0; i < this.pointsCount(); i++) {\\n values.push(col.r);\\n values.push(col.g);\\n values.push(col.b);\\n }\\n attribute_added = true;\\n }\\n const vec4 = default_value;\\n if (size == 4 && vec4.x != null && vec4.y != null && vec4.z != null && vec4.w != null) {\\n for (let i = 0; i < this.pointsCount(); i++) {\\n values.push(vec4.x);\\n values.push(vec4.y);\\n values.push(vec4.z);\\n values.push(vec4.w);\\n }\\n attribute_added = true;\\n }\\n }\\n }\\n }\\n if (attribute_added) {\\n this._geometry.setAttribute(name.trim(), new Float32BufferAttribute(values, size));\\n } else {\\n console.warn(default_value);\\n throw `CoreGeometry.add_numeric_attrib error: no other default value allowed for now in add_numeric_attrib (default given: ${default_value})`;\\n }\\n }\\n initPositionAttribute(points_count, default_value) {\\n const values = [];\\n if (default_value == null) {\\n default_value = new Vector3();\\n }\\n for (let i = 0; i < points_count; i++) {\\n values.push(default_value.x);\\n values.push(default_value.y);\\n values.push(default_value.z);\\n }\\n return this._geometry.setAttribute(\\\\\\\"position\\\\\\\", new Float32BufferAttribute(values, 3));\\n }\\n addAttribute(name, attrib_data) {\\n switch (attrib_data.type()) {\\n case AttribType.STRING:\\n return console.log(\\\\\\\"TODO: to implement\\\\\\\");\\n case AttribType.NUMERIC:\\n return this.addNumericAttrib(name, attrib_data.size());\\n }\\n }\\n renameAttrib(old_name, new_name) {\\n if (this.isAttribIndexed(old_name)) {\\n this.userDataAttribs()[new_name] = ObjectUtils.clone(this.userDataAttribs()[old_name]);\\n delete this.userDataAttribs()[old_name];\\n }\\n const old_attrib = this._geometry.getAttribute(old_name);\\n this._geometry.setAttribute(new_name.trim(), new Float32BufferAttribute(old_attrib.array, old_attrib.itemSize));\\n return this._geometry.deleteAttribute(old_name);\\n }\\n deleteAttribute(name) {\\n if (this.isAttribIndexed(name)) {\\n delete this.userDataAttribs()[name];\\n }\\n return this._geometry.deleteAttribute(name);\\n }\\n clone() {\\n return CoreGeometry2.clone(this._geometry);\\n }\\n static clone(src_geometry) {\\n let src_userData;\\n const new_geometry = src_geometry.clone();\\n if ((src_userData = src_geometry.userData) != null) {\\n new_geometry.userData = ObjectUtils.cloneDeep(src_userData);\\n }\\n return new_geometry;\\n }\\n pointsCount() {\\n return CoreGeometry2.pointsCount(this._geometry);\\n }\\n static pointsCount(geometry) {\\n let position;\\n let count = 0;\\n const core_geometry = new this(geometry);\\n let position_attrib_name = \\\\\\\"position\\\\\\\";\\n if (core_geometry.markedAsInstance()) {\\n position_attrib_name = \\\\\\\"instancePosition\\\\\\\";\\n }\\n if ((position = geometry.getAttribute(position_attrib_name)) != null) {\\n let array;\\n if ((array = position.array) != null) {\\n count = array.length / 3;\\n }\\n }\\n return count;\\n }\\n points() {\\n return this.pointsFromGeometry();\\n }\\n pointsFromGeometry() {\\n const points2 = [];\\n const positionAttrib = this._geometry.getAttribute(this.positionAttribName());\\n if (positionAttrib != null) {\\n const count = positionAttrib.array.length / 3;\\n for (let i = 0; i < count; i++) {\\n const point = new CorePoint(this, i);\\n points2.push(point);\\n }\\n }\\n return points2;\\n }\\n static geometryFromPoints(points2, object_type) {\\n switch (object_type) {\\n case ObjectType.MESH:\\n return this._mesh_builder.from_points(points2);\\n case ObjectType.POINTS:\\n return this._points_builder.from_points(points2);\\n case ObjectType.LINE_SEGMENTS:\\n return this._lines_segment_builder.from_points(points2);\\n case ObjectType.OBJECT3D:\\n return null;\\n case ObjectType.GROUP:\\n return null;\\n case ObjectType.LOD:\\n return null;\\n }\\n TypeAssert.unreachable(object_type);\\n }\\n static mergeGeometries(geometries) {\\n return CoreGeometryBuilderMerge.merge(geometries);\\n }\\n static merge_geometries(geometries) {\\n return CoreGeometryBuilderMerge.merge(geometries);\\n }\\n segments() {\\n const index = this.geometry().index?.array || [];\\n return ArrayUtils.chunk(index, 2);\\n }\\n faces() {\\n return this.facesFromGeometry();\\n }\\n facesFromGeometry() {\\n const index_array = this.geometry().index?.array || [];\\n const faces_count = index_array.length / 3;\\n return ArrayUtils.range(faces_count).map((i) => new CoreFace(this, i));\\n }\\n};\\nvar CoreGeometry = CoreGeometry2;\\nCoreGeometry._mesh_builder = new CoreGeometryBuilderMesh();\\nCoreGeometry._points_builder = new CoreGeometryBuilderPoints();\\nCoreGeometry._lines_segment_builder = new CoreGeometryBuilderLineSegments();\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/core/geometry/Material.ts\\nvar CustomMaterialName;\\n(function(CustomMaterialName2) {\\n CustomMaterialName2[\\\\\\\"customDistanceMaterial\\\\\\\"] = \\\\\\\"customDistanceMaterial\\\\\\\";\\n CustomMaterialName2[\\\\\\\"customDepthMaterial\\\\\\\"] = \\\\\\\"customDepthMaterial\\\\\\\";\\n CustomMaterialName2[\\\\\\\"customDepthDOFMaterial\\\\\\\"] = \\\\\\\"customDepthDOFMaterial\\\\\\\";\\n})(CustomMaterialName || (CustomMaterialName = {}));\\nvar RENDER_HOOK_USER_DATA_KEY = \\\\\\\"POLY_render_hook\\\\\\\";\\nvar EMPTY_RENDER_HOOK = (renderer, scene, camera, geometry, material, group) => {\\n};\\nvar CoreMaterial = class {\\n static node(scene, material) {\\n return scene.node(material.name);\\n }\\n static clone(src_material) {\\n const cloned_material = src_material.clone();\\n const src_uniforms = src_material.uniforms;\\n if (src_uniforms) {\\n cloned_material.uniforms = UniformsUtils.clone(src_uniforms);\\n }\\n return cloned_material;\\n }\\n static add_user_data_render_hook(material, render_hook) {\\n material.userData[RENDER_HOOK_USER_DATA_KEY] = render_hook;\\n }\\n static apply_render_hook(object, material) {\\n if (material.userData) {\\n const render_hook = material.userData[RENDER_HOOK_USER_DATA_KEY];\\n if (render_hook) {\\n object.onBeforeRender = (renderer, scene, camera, geometry, material2, group) => {\\n render_hook(renderer, scene, camera, geometry, material2, group, object);\\n };\\n return;\\n }\\n }\\n object.onBeforeRender = EMPTY_RENDER_HOOK;\\n }\\n static applyCustomMaterials(object, material) {\\n const material_with_custom = material;\\n if (material_with_custom.customMaterials) {\\n for (let name of Object.keys(material_with_custom.customMaterials)) {\\n const mat_name = name;\\n const custom_material = material_with_custom.customMaterials[mat_name];\\n if (custom_material) {\\n object[mat_name] = custom_material;\\n custom_material.needsUpdate = true;\\n }\\n }\\n }\\n }\\n static assign_custom_uniforms(mat, uniform_name, uniform_value) {\\n const material = mat;\\n if (material.customMaterials) {\\n for (let name of Object.keys(material.customMaterials)) {\\n const mat_name = name;\\n const custom_material = material.customMaterials[mat_name];\\n if (custom_material) {\\n custom_material.uniforms[uniform_name].value = uniform_value;\\n }\\n }\\n }\\n }\\n static init_custom_material_uniforms(mat, uniform_name, uniform_value) {\\n const material = mat;\\n if (material.customMaterials) {\\n for (let name of Object.keys(material.customMaterials)) {\\n const mat_name = name;\\n const custom_material = material.customMaterials[mat_name];\\n if (custom_material) {\\n custom_material.uniforms[uniform_name] = custom_material.uniforms[uniform_name] || uniform_value;\\n }\\n }\\n }\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/core/geometry/Object.ts\\nvar PTNUM2 = \\\\\\\"ptnum\\\\\\\";\\nvar NAME_ATTR = \\\\\\\"name\\\\\\\";\\nvar ATTRIBUTES = \\\\\\\"attributes\\\\\\\";\\nvar CoreObject = class extends CoreEntity {\\n constructor(_object, index) {\\n super(index);\\n this._object = _object;\\n if (this._object.userData[ATTRIBUTES] == null) {\\n this._object.userData[ATTRIBUTES] = {};\\n }\\n }\\n object() {\\n return this._object;\\n }\\n geometry() {\\n return this._object.geometry;\\n }\\n coreGeometry() {\\n const geo = this.geometry();\\n if (geo) {\\n return new CoreGeometry(geo);\\n } else {\\n return null;\\n }\\n }\\n points() {\\n return this.coreGeometry()?.points() || [];\\n }\\n pointsFromGroup(group) {\\n if (group) {\\n const indices = CoreString.indices(group);\\n if (indices) {\\n const points2 = this.points();\\n return indices.map((i) => points2[i]);\\n } else {\\n return [];\\n }\\n } else {\\n return this.points();\\n }\\n }\\n static isInGroup(groupString, object) {\\n const group = groupString.trim();\\n if (group.length == 0) {\\n return true;\\n }\\n const elements = group.split(\\\\\\\"=\\\\\\\");\\n const attribNameWithPrefix = elements[0];\\n if (attribNameWithPrefix[0] == \\\\\\\"@\\\\\\\") {\\n const attribName = attribNameWithPrefix.substr(1);\\n const expectedAttribValue = elements[1];\\n const currentAttribValue = this.attribValue(object, attribName);\\n return expectedAttribValue == currentAttribValue;\\n }\\n return false;\\n }\\n computeVertexNormals() {\\n this.coreGeometry()?.computeVertexNormals();\\n }\\n static _convert_array_to_vector(value) {\\n switch (value.length) {\\n case 1:\\n return value[0];\\n case 2:\\n return new Vector2(value[0], value[1]);\\n case 3:\\n return new Vector3(value[0], value[1], value[2]);\\n case 4:\\n return new Vector4(value[0], value[1], value[2], value[3]);\\n }\\n }\\n static addAttribute(object, attrib_name, value) {\\n if (CoreType.isArray(value)) {\\n const converted_value = this._convert_array_to_vector(value);\\n if (!converted_value) {\\n const message = `attribute_value invalid`;\\n console.error(message, value);\\n throw new Error(message);\\n }\\n }\\n const data = value;\\n const user_data = object.userData;\\n user_data[ATTRIBUTES] = user_data[ATTRIBUTES] || {};\\n user_data[ATTRIBUTES][attrib_name] = data;\\n }\\n addAttribute(name, value) {\\n CoreObject.addAttribute(this._object, name, value);\\n }\\n addNumericAttrib(name, value) {\\n this.addAttribute(name, value);\\n }\\n setAttribValue(name, value) {\\n this.addAttribute(name, value);\\n }\\n addNumericVertexAttrib(name, size, default_value) {\\n if (default_value == null) {\\n default_value = CoreAttribute.default_value(size);\\n }\\n this.coreGeometry()?.addNumericAttrib(name, size, default_value);\\n }\\n attributeNames() {\\n return Object.keys(this._object.userData[ATTRIBUTES]);\\n }\\n attribNames() {\\n return this.attributeNames();\\n }\\n hasAttrib(name) {\\n return this.attributeNames().includes(name);\\n }\\n renameAttrib(old_name, new_name) {\\n const current_value = this.attribValue(old_name);\\n if (current_value != null) {\\n this.addAttribute(new_name, current_value);\\n this.deleteAttribute(old_name);\\n } else {\\n console.warn(`attribute ${old_name} not found`);\\n }\\n }\\n deleteAttribute(name) {\\n delete this._object.userData[ATTRIBUTES][name];\\n }\\n static attribValue(object, name, index = 0, target) {\\n if (name === PTNUM2) {\\n return index;\\n }\\n if (object.userData && object.userData[ATTRIBUTES]) {\\n const val = object.userData[ATTRIBUTES][name];\\n if (val == null) {\\n if (name == NAME_ATTR) {\\n return object.name;\\n }\\n } else {\\n if (CoreType.isArray(val) && target) {\\n target.fromArray(val);\\n return target;\\n }\\n }\\n return val;\\n }\\n if (name == NAME_ATTR) {\\n return object.name;\\n }\\n }\\n static stringAttribValue(object, name, index = 0) {\\n const str = this.attribValue(object, name, index);\\n if (str != null) {\\n if (CoreType.isString(str)) {\\n return str;\\n } else {\\n return `${str}`;\\n }\\n }\\n }\\n attribValue(name, target) {\\n return CoreObject.attribValue(this._object, name, this._index, target);\\n }\\n stringAttribValue(name) {\\n return CoreObject.stringAttribValue(this._object, name, this._index);\\n }\\n name() {\\n return this.attribValue(NAME_ATTR);\\n }\\n humanType() {\\n return CoreConstant.CONSTRUCTOR_NAMES_BY_CONSTRUCTOR_NAME[this._object.constructor.name];\\n }\\n attribTypes() {\\n const h = {};\\n for (let attrib_name of this.attribNames()) {\\n const type = this.attribType(attrib_name);\\n if (type != null) {\\n h[attrib_name] = type;\\n }\\n }\\n return h;\\n }\\n attribType(name) {\\n const val = this.attribValue(name);\\n if (CoreType.isString(val)) {\\n return AttribType.STRING;\\n } else {\\n return AttribType.NUMERIC;\\n }\\n }\\n attribSizes() {\\n const h = {};\\n for (let attrib_name of this.attribNames()) {\\n const size = this.attribSize(attrib_name);\\n if (size != null) {\\n h[attrib_name] = size;\\n }\\n }\\n return h;\\n }\\n attribSize(name) {\\n const val = this.attribValue(name);\\n if (val == null) {\\n return null;\\n }\\n return CoreAttribute.attribSizeFromValue(val);\\n }\\n clone() {\\n return CoreObject.clone(this._object);\\n }\\n static clone(src_object) {\\n const new_object = src_object.clone();\\n var sourceLookup = new Map();\\n var cloneLookup = new Map();\\n CoreObject.parallelTraverse(src_object, new_object, function(sourceNode, clonedNode) {\\n sourceLookup.set(clonedNode, sourceNode);\\n cloneLookup.set(sourceNode, clonedNode);\\n });\\n new_object.traverse(function(node) {\\n const src_node = sourceLookup.get(node);\\n const mesh_node = node;\\n if (mesh_node.geometry) {\\n const src_node_geometry = src_node.geometry;\\n mesh_node.geometry = CoreGeometry.clone(src_node_geometry);\\n const mesh_node_geometry = mesh_node.geometry;\\n if (mesh_node_geometry.userData) {\\n mesh_node_geometry.userData = ObjectUtils.cloneDeep(src_node_geometry.userData);\\n }\\n }\\n if (mesh_node.material) {\\n mesh_node.material = src_node.material;\\n CoreMaterial.applyCustomMaterials(node, mesh_node.material);\\n const material_with_color = mesh_node.material;\\n if (material_with_color.color == null) {\\n material_with_color.color = new Color(1, 1, 1);\\n }\\n }\\n if (src_object.userData) {\\n node.userData = ObjectUtils.cloneDeep(src_node.userData);\\n }\\n const src_node_with_animations = src_node;\\n if (src_node_with_animations.animations) {\\n node.animations = src_node_with_animations.animations.map((animation) => animation.clone());\\n }\\n const skinned_node = node;\\n if (skinned_node.isSkinnedMesh) {\\n var clonedMesh = skinned_node;\\n var sourceMesh = src_node;\\n var sourceBones = sourceMesh.skeleton.bones;\\n clonedMesh.skeleton = sourceMesh.skeleton.clone();\\n clonedMesh.bindMatrix.copy(sourceMesh.bindMatrix);\\n const new_bones = sourceBones.map(function(bone) {\\n return cloneLookup.get(bone);\\n });\\n clonedMesh.skeleton.bones = new_bones;\\n clonedMesh.bind(clonedMesh.skeleton, clonedMesh.bindMatrix);\\n }\\n });\\n return new_object;\\n }\\n static parallelTraverse(a, b, callback) {\\n callback(a, b);\\n for (var i = 0; i < a.children.length; i++) {\\n this.parallelTraverse(a.children[i], b.children[i], callback);\\n }\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/containers/Geometry.ts\\nvar GeometryContainer = class extends TypedContainer {\\n coreContentCloned() {\\n if (this._content) {\\n return this._content.clone();\\n }\\n }\\n set_content(content) {\\n super.set_content(content);\\n }\\n firstObject() {\\n if (this._content) {\\n return this._content.objects()[0];\\n }\\n }\\n firstCoreObject() {\\n const object = this.firstObject();\\n if (object) {\\n return new CoreObject(object, 0);\\n }\\n }\\n firstGeometry() {\\n const object = this.firstObject();\\n if (object) {\\n return object.geometry;\\n } else {\\n return null;\\n }\\n }\\n objectsCount() {\\n if (this._content) {\\n return this._content.objects().length;\\n } else {\\n return 0;\\n }\\n }\\n objectsVisibleCount() {\\n let count = 0;\\n if (this._content) {\\n const objects = this._content.objects();\\n for (let object of objects) {\\n if (object.visible) {\\n count++;\\n }\\n }\\n }\\n return count;\\n }\\n objectsCountByType() {\\n const count_by_type = {};\\n const core_group = this._content;\\n if (this._content && core_group) {\\n for (let core_object of core_group.coreObjects()) {\\n const human_type = core_object.humanType();\\n if (count_by_type[human_type] == null) {\\n count_by_type[human_type] = 0;\\n }\\n count_by_type[human_type] += 1;\\n }\\n }\\n return count_by_type;\\n }\\n objectsNamesByType() {\\n const names_by_type = {};\\n const core_group = this._content;\\n if (this._content && core_group) {\\n for (let core_object of core_group.coreObjects()) {\\n const human_type = core_object.humanType();\\n names_by_type[human_type] = names_by_type[human_type] || [];\\n names_by_type[human_type].push(core_object.name());\\n }\\n }\\n return names_by_type;\\n }\\n pointAttributeNames() {\\n let names = [];\\n const geometry = this.firstGeometry();\\n if (geometry) {\\n names = Object.keys(geometry.attributes);\\n }\\n return names;\\n }\\n pointAttributeSizesByName() {\\n let sizes_by_name = {};\\n const geometry = this.firstGeometry();\\n if (geometry) {\\n Object.keys(geometry.attributes).forEach((attrib_name) => {\\n const attrib = geometry.attributes[attrib_name];\\n sizes_by_name[attrib_name] = attrib.itemSize;\\n });\\n }\\n return sizes_by_name;\\n }\\n objectAttributeSizesByName() {\\n let sizes_by_name = {};\\n const core_object = this.firstCoreObject();\\n if (core_object) {\\n const attribNames = core_object.attribNames();\\n for (let name of attribNames) {\\n const size = core_object.attribSize(name);\\n if (size != null) {\\n sizes_by_name[name] = size;\\n }\\n }\\n }\\n return sizes_by_name;\\n }\\n pointAttributeTypesByName() {\\n let types_by_name = {};\\n const geometry = this.firstGeometry();\\n if (geometry) {\\n const core_geo = new CoreGeometry(geometry);\\n Object.keys(geometry.attributes).forEach((attrib_name) => {\\n types_by_name[attrib_name] = core_geo.attribType(attrib_name);\\n });\\n }\\n return types_by_name;\\n }\\n objectAttributeTypesByName() {\\n let types_by_name = {};\\n const core_object = this.firstCoreObject();\\n if (core_object) {\\n for (let name of core_object.attribNames()) {\\n types_by_name[name] = core_object.attribType(name);\\n }\\n }\\n return types_by_name;\\n }\\n objectAttributeNames() {\\n let names = [];\\n const object = this.firstObject();\\n if (object) {\\n names = Object.keys(object.userData[\\\\\\\"attributes\\\\\\\"] || {});\\n }\\n return names;\\n }\\n pointsCount() {\\n if (this._content) {\\n return this._content.pointsCount();\\n } else {\\n return 0;\\n }\\n }\\n totalPointsCount() {\\n if (this._content) {\\n return this._content.totalPointsCount();\\n } else {\\n return 0;\\n }\\n }\\n objectsData() {\\n if (this._content) {\\n return this._content.objectsData();\\n } else {\\n return [];\\n }\\n }\\n boundingBox(forceUpdate = false) {\\n return this._content.boundingBox(forceUpdate);\\n }\\n center() {\\n return this._content.center();\\n }\\n size() {\\n return this._content.size();\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/containers/Gl.ts\\nvar GlContainer = class extends TypedContainer {\\n object() {\\n return this._content;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/containers/Js.ts\\nvar JsContainer = class extends TypedContainer {\\n object() {\\n return this._content;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/containers/Manager.ts\\nvar ManagerContainer = class extends TypedContainer {\\n set_content(content) {\\n super.set_content(content);\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/containers/Material.ts\\nvar MaterialContainer = class extends TypedContainer {\\n set_content(content) {\\n super.set_content(content);\\n }\\n set_material(material) {\\n if (this._content != null) {\\n this._content.dispose();\\n }\\n this.set_content(material);\\n }\\n has_material() {\\n return this.has_content();\\n }\\n material() {\\n return this.content();\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/containers/Object.ts\\nvar ObjectContainer = class extends TypedContainer {\\n set_content(content) {\\n super.set_content(content);\\n }\\n set_object(object) {\\n return this.set_content(object);\\n }\\n has_object() {\\n return this.has_content();\\n }\\n object() {\\n return this.content();\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/containers/Texture.ts\\nvar TextureContainer = class extends TypedContainer {\\n set_content(content) {\\n super.set_content(content);\\n }\\n texture() {\\n return this._content;\\n }\\n coreContent() {\\n return this._content;\\n }\\n coreContentCloned() {\\n const texture = this._content?.clone();\\n if (texture) {\\n texture.needsUpdate = true;\\n }\\n return texture;\\n }\\n object() {\\n return this.texture();\\n }\\n infos() {\\n if (this._content != null) {\\n return [this._content];\\n }\\n }\\n resolution() {\\n if (this._content) {\\n const image = this._content.image;\\n if (image) {\\n if (image instanceof HTMLImageElement || image instanceof Image || image instanceof ImageData || image instanceof HTMLCanvasElement) {\\n return [image.width, image.height];\\n }\\n if (image.data && image.width != null && image.height != null) {\\n return [image.width, image.height];\\n }\\n const video = image;\\n return [video.videoWidth, video.videoHeight];\\n }\\n }\\n return [-1, -1];\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/containers/PostProcess.ts\\nvar PostProcessContainer = class extends TypedContainer {\\n set_content(content) {\\n super.set_content(content);\\n }\\n render_pass() {\\n return this._content;\\n }\\n object(options = {}) {\\n return this.render_pass();\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/containers/Rop.ts\\nvar RopContainer = class extends TypedContainer {\\n set_content(content) {\\n super.set_content(content);\\n }\\n renderer() {\\n return this._content;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/containers/utils/ContainerMap.ts\\nvar ContainerClassMap = {\\n [NodeContext.ANIM]: AnimationContainer,\\n [NodeContext.COP]: TextureContainer,\\n [NodeContext.EVENT]: EventContainer,\\n [NodeContext.GL]: GlContainer,\\n [NodeContext.JS]: JsContainer,\\n [NodeContext.MANAGER]: ManagerContainer,\\n [NodeContext.MAT]: MaterialContainer,\\n [NodeContext.OBJ]: ObjectContainer,\\n [NodeContext.POST]: PostProcessContainer,\\n [NodeContext.ROP]: RopContainer,\\n [NodeContext.SOP]: GeometryContainer\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/utils/ContainerController.ts\\nvar TypedContainerController = class {\\n constructor(node) {\\n this.node = node;\\n this._callbacks = [];\\n this._callbacks_tmp = [];\\n const container_class = ContainerClassMap[node.context()];\\n this._container = new container_class(this.node);\\n }\\n container() {\\n return this._container;\\n }\\n async compute() {\\n if (this.node.flags?.bypass?.active()) {\\n const container = await this.requestInputContainer(0) || this._container;\\n this.node.cookController.endCook();\\n return container;\\n }\\n if (this.node.isDirty()) {\\n return new Promise((resolve, reject) => {\\n this._callbacks.push(resolve);\\n this.node.cookController.cookMain();\\n });\\n }\\n return this._container;\\n }\\n async requestInputContainer(input_index) {\\n const inputNode = this.node.io.inputs.input(input_index);\\n if (inputNode) {\\n return await inputNode.compute();\\n } else {\\n this.node.states.error.set(`input ${input_index} required`);\\n this.notifyRequesters();\\n return null;\\n }\\n }\\n notifyRequesters(container) {\\n this._callbacks_tmp = this._callbacks.slice();\\n this._callbacks.splice(0, this._callbacks.length);\\n if (!container) {\\n container = this.node.containerController.container();\\n }\\n let callback;\\n while (callback = this._callbacks_tmp.pop()) {\\n callback(container);\\n }\\n this.node.scene().cookController.removeNode(this.node);\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/utils/cook/PerformanceController.ts\\nvar performance = Poly.performance.performanceManager();\\nvar NodeCookPerformanceformanceController = class {\\n constructor(cookController) {\\n this.cookController = cookController;\\n this._inputs_start = 0;\\n this._params_start = 0;\\n this._cook_start = 0;\\n this._cooksCount = 0;\\n this._data = {\\n inputsTime: 0,\\n paramsTime: 0,\\n cookTime: 0\\n };\\n }\\n cooksCount() {\\n return this._cooksCount;\\n }\\n data2() {\\n return this._data;\\n }\\n active() {\\n return this.cookController.performanceRecordStarted();\\n }\\n recordInputsStart() {\\n if (this.active()) {\\n this._inputs_start = performance.now();\\n }\\n }\\n recordInputsEnd() {\\n if (this.active()) {\\n this._data.inputsTime = performance.now() - this._inputs_start;\\n }\\n }\\n recordParamsStart() {\\n if (this.active()) {\\n this._params_start = performance.now();\\n }\\n }\\n recordParamsEnd() {\\n if (this.active()) {\\n this._data.paramsTime = performance.now() - this._params_start;\\n }\\n }\\n recordCookStart() {\\n if (this.active()) {\\n this._cook_start = performance.now();\\n }\\n }\\n recordCookEnd() {\\n if (this.active()) {\\n this._data.cookTime = performance.now() - this._cook_start;\\n this._cooksCount += 1;\\n }\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/utils/CookController.ts\\nvar NodeCookController = class {\\n constructor(node) {\\n this.node = node;\\n this._cooking = false;\\n this._performanceController = new NodeCookPerformanceformanceController(this);\\n this._inputs_evaluation_required = true;\\n this._core_performance = this.node.scene().performance;\\n }\\n performanceRecordStarted() {\\n return this._core_performance.started();\\n }\\n disallowInputsEvaluation() {\\n this._inputs_evaluation_required = false;\\n }\\n isCooking() {\\n return this._cooking === true;\\n }\\n _start_cook_if_no_errors(input_contents) {\\n if (this.node.states.error.active()) {\\n this.endCook();\\n } else {\\n try {\\n this._performanceController.recordCookStart();\\n this.node.cook(input_contents);\\n } catch (e) {\\n this.node.states.error.set(`node internal error: '${e}'.`);\\n Poly.warn(e);\\n this.endCook();\\n }\\n }\\n }\\n async cookMain() {\\n if (this.isCooking()) {\\n return;\\n }\\n this._initCookingState();\\n this.node.states.error.clear();\\n this.node.scene().cookController.addNode(this.node);\\n let input_contents;\\n if (this._inputs_evaluation_required) {\\n input_contents = await this._evaluateInputs();\\n } else {\\n input_contents = [];\\n }\\n if (this.node.params.paramsEvalRequired()) {\\n await this._evaluateParams();\\n }\\n this._start_cook_if_no_errors(input_contents);\\n }\\n async cookMainWithoutInputs() {\\n this.node.scene().cookController.addNode(this.node);\\n if (this.isCooking()) {\\n Poly.warn(\\\\\\\"cook_main_without_inputs already cooking\\\\\\\", this.node.path());\\n return;\\n }\\n this._initCookingState();\\n this.node.states.error.clear();\\n if (this.node.params.paramsEvalRequired()) {\\n await this._evaluateParams();\\n }\\n this._start_cook_if_no_errors([]);\\n }\\n endCook(message) {\\n this._finalizeCookPerformance();\\n const dirty_timestamp = this.node.dirtyController.dirtyTimestamp();\\n if (dirty_timestamp == null || dirty_timestamp === this._cooking_dirty_timestamp) {\\n this.node.removeDirtyState();\\n this._terminateCookProcess();\\n } else {\\n Poly.log(\\\\\\\"COOK AGAIN\\\\\\\", dirty_timestamp, this._cooking_dirty_timestamp, this.node.path());\\n this._cooking = false;\\n this.cookMain();\\n }\\n }\\n _initCookingState() {\\n this._cooking = true;\\n this._cooking_dirty_timestamp = this.node.dirtyController.dirtyTimestamp();\\n }\\n _terminateCookProcess() {\\n if (this.isCooking()) {\\n this._cooking = false;\\n this.node.containerController.notifyRequesters();\\n this._run_on_cook_complete_hooks();\\n }\\n }\\n async _evaluateInputs() {\\n this._performanceController.recordInputsStart();\\n let input_containers = [];\\n const io_inputs = this.node.io.inputs;\\n if (this._inputs_evaluation_required) {\\n if (io_inputs.is_any_input_dirty()) {\\n input_containers = await io_inputs.eval_required_inputs();\\n } else {\\n input_containers = await io_inputs.containers_without_evaluation();\\n }\\n }\\n const inputs = io_inputs.inputs();\\n const input_contents = [];\\n let input_container;\\n for (let i = 0; i < inputs.length; i++) {\\n input_container = input_containers[i];\\n if (input_container) {\\n if (io_inputs.cloneRequired(i)) {\\n input_contents[i] = input_container.coreContentCloned();\\n } else {\\n input_contents[i] = input_container.coreContent();\\n }\\n }\\n }\\n this._performanceController.recordInputsEnd();\\n return input_contents;\\n }\\n async _evaluateParams() {\\n this._performanceController.recordParamsStart();\\n await this.node.params.evalAll();\\n this._performanceController.recordParamsEnd();\\n }\\n cooksCount() {\\n return this._performanceController.cooksCount();\\n }\\n cookTime() {\\n return this._performanceController.data2().cookTime;\\n }\\n _finalizeCookPerformance() {\\n if (!this._core_performance.started()) {\\n return;\\n }\\n this._performanceController.recordCookEnd();\\n this._core_performance.record_node_cook_data(this.node, this._performanceController.data2());\\n }\\n registerOnCookEnd(callbackName, callback) {\\n this._on_cook_complete_hook_names = this._on_cook_complete_hook_names || [];\\n this._on_cook_complete_hooks = this._on_cook_complete_hooks || [];\\n this._on_cook_complete_hook_names.push(callbackName);\\n this._on_cook_complete_hooks.push(callback);\\n }\\n deregisterOnCookEnd(callbackName) {\\n if (!this._on_cook_complete_hook_names || !this._on_cook_complete_hooks) {\\n return;\\n }\\n const index = this._on_cook_complete_hook_names?.indexOf(callbackName);\\n this._on_cook_complete_hook_names.splice(index, 1);\\n this._on_cook_complete_hooks.splice(index, 1);\\n }\\n _run_on_cook_complete_hooks() {\\n if (this._on_cook_complete_hooks) {\\n for (let hook of this._on_cook_complete_hooks) {\\n hook();\\n }\\n }\\n }\\n onCookEndCallbackNames() {\\n return this._on_cook_complete_hook_names;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/utils/Serializer.ts\\nvar NodeSerializer = class {\\n constructor(node) {\\n this.node = node;\\n }\\n toJSON(include_param_components = false) {\\n const data = {\\n name: this.node.name(),\\n type: this.node.type(),\\n graph_node_id: this.node.graphNodeId(),\\n is_dirty: this.node.isDirty(),\\n ui_data_json: this.node.uiData.toJSON(),\\n error_message: this.node.states.error.message(),\\n children: this.childrenIds(),\\n maxInputsCount: this.maxInputsCount(),\\n inputs: this.inputIds(),\\n input_connection_output_indices: this.inputConnectionOutputIndices(),\\n named_input_connection_points: this.namedInputConnectionPoints(),\\n named_output_connection_points: this.namedOutputConnectionPoints(),\\n param_ids: this.to_json_params(include_param_components),\\n override_cloned_state_allowed: this.node.io.inputs.overrideClonedStateAllowed(),\\n inputs_clone_required_states: this.node.io.inputs.cloneRequiredStates(),\\n flags: {\\n display: this.node.flags?.display?.active(),\\n bypass: this.node.flags?.bypass?.active(),\\n optimize: this.node.flags?.optimize?.active()\\n },\\n selection: void 0\\n };\\n if (this.node.childrenAllowed() && this.node.childrenController) {\\n data[\\\\\\\"selection\\\\\\\"] = this.node.childrenController.selection.toJSON();\\n }\\n return data;\\n }\\n childrenIds() {\\n return this.node.children().map((node) => node.graphNodeId());\\n }\\n maxInputsCount() {\\n return this.node.io.inputs.maxInputsCount();\\n }\\n inputIds() {\\n return this.node.io.inputs.inputs().map((node) => node != null ? node.graphNodeId() : void 0);\\n }\\n inputConnectionOutputIndices() {\\n return this.node.io.connections.inputConnections()?.map((connection) => connection != null ? connection.output_index : void 0);\\n }\\n namedInputConnectionPoints() {\\n return this.node.io.inputs.namedInputConnectionPoints().map((i) => i.toJSON());\\n }\\n namedOutputConnectionPoints() {\\n return this.node.io.outputs.namedOutputConnectionPoints().map((o) => o.toJSON());\\n }\\n to_json_params_from_names(param_names, include_components = false) {\\n return param_names.map((param_name) => {\\n return this.node.params.get(param_name).graphNodeId();\\n });\\n }\\n to_json_params(include_components = false) {\\n return this.to_json_params_from_names(this.node.params.names, include_components);\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/poly/ParamType.ts\\nvar ParamType;\\n(function(ParamType2) {\\n ParamType2[\\\\\\\"BOOLEAN\\\\\\\"] = \\\\\\\"boolean\\\\\\\";\\n ParamType2[\\\\\\\"BUTTON\\\\\\\"] = \\\\\\\"button\\\\\\\";\\n ParamType2[\\\\\\\"COLOR\\\\\\\"] = \\\\\\\"color\\\\\\\";\\n ParamType2[\\\\\\\"FLOAT\\\\\\\"] = \\\\\\\"float\\\\\\\";\\n ParamType2[\\\\\\\"FOLDER\\\\\\\"] = \\\\\\\"folder\\\\\\\";\\n ParamType2[\\\\\\\"INTEGER\\\\\\\"] = \\\\\\\"integer\\\\\\\";\\n ParamType2[\\\\\\\"OPERATOR_PATH\\\\\\\"] = \\\\\\\"operator_path\\\\\\\";\\n ParamType2[\\\\\\\"PARAM_PATH\\\\\\\"] = \\\\\\\"param_path\\\\\\\";\\n ParamType2[\\\\\\\"NODE_PATH\\\\\\\"] = \\\\\\\"node_path\\\\\\\";\\n ParamType2[\\\\\\\"RAMP\\\\\\\"] = \\\\\\\"ramp\\\\\\\";\\n ParamType2[\\\\\\\"STRING\\\\\\\"] = \\\\\\\"string\\\\\\\";\\n ParamType2[\\\\\\\"VECTOR2\\\\\\\"] = \\\\\\\"vector2\\\\\\\";\\n ParamType2[\\\\\\\"VECTOR3\\\\\\\"] = \\\\\\\"vector3\\\\\\\";\\n ParamType2[\\\\\\\"VECTOR4\\\\\\\"] = \\\\\\\"vector4\\\\\\\";\\n})(ParamType || (ParamType = {}));\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/poly/ParamEvent.ts\\nvar ParamEvent;\\n(function(ParamEvent2) {\\n ParamEvent2[\\\\\\\"VISIBLE_UPDATED\\\\\\\"] = \\\\\\\"param_visible_updated\\\\\\\";\\n ParamEvent2[\\\\\\\"RAW_INPUT_UPDATED\\\\\\\"] = \\\\\\\"raw_input_updated\\\\\\\";\\n ParamEvent2[\\\\\\\"VALUE_UPDATED\\\\\\\"] = \\\\\\\"param_value_updated\\\\\\\";\\n ParamEvent2[\\\\\\\"EXPRESSION_UPDATED\\\\\\\"] = \\\\\\\"param_expression_update\\\\\\\";\\n ParamEvent2[\\\\\\\"ERROR_UPDATED\\\\\\\"] = \\\\\\\"param_error_updated\\\\\\\";\\n ParamEvent2[\\\\\\\"DELETED\\\\\\\"] = \\\\\\\"param_deleted\\\\\\\";\\n})(ParamEvent || (ParamEvent = {}));\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/params/utils/OptionsController.ts\\nvar CALLBACK_OPTION = \\\\\\\"callback\\\\\\\";\\nvar CALLBACK_STRING_OPTION = \\\\\\\"callbackString\\\\\\\";\\nvar COMPUTE_ON_DIRTY = \\\\\\\"computeOnDirty\\\\\\\";\\nvar COOK_OPTION = \\\\\\\"cook\\\\\\\";\\nvar FILE_BROWSE_OPTION = \\\\\\\"fileBrowse\\\\\\\";\\nvar FILE_TYPE_OPTION = \\\\\\\"type\\\\\\\";\\nvar EXPRESSION = \\\\\\\"expression\\\\\\\";\\nvar FOR_ENTITIES = \\\\\\\"forEntities\\\\\\\";\\nvar LABEL = \\\\\\\"label\\\\\\\";\\nvar LEVEL = \\\\\\\"level\\\\\\\";\\nvar MENU = \\\\\\\"menu\\\\\\\";\\nvar MENU_STRING = \\\\\\\"menuString\\\\\\\";\\nvar ENTRIES = \\\\\\\"entries\\\\\\\";\\nvar MULTILINE_OPTION = \\\\\\\"multiline\\\\\\\";\\nvar LANGUAGE_OPTION = \\\\\\\"language\\\\\\\";\\nvar NODE_SELECTION = \\\\\\\"nodeSelection\\\\\\\";\\nvar NODE_SELECTION_CONTEXT = \\\\\\\"context\\\\\\\";\\nvar NODE_SELECTION_TYPES = \\\\\\\"types\\\\\\\";\\nvar PARAM_SELECTION = \\\\\\\"paramSelection\\\\\\\";\\nvar DEPENDENT_ON_FOUND_NODE = \\\\\\\"dependentOnFoundNode\\\\\\\";\\nvar RANGE_OPTION = \\\\\\\"range\\\\\\\";\\nvar RANGE_LOCKED_OPTION = \\\\\\\"rangeLocked\\\\\\\";\\nvar STEP_OPTION = \\\\\\\"step\\\\\\\";\\nvar SPARE_OPTION = \\\\\\\"spare\\\\\\\";\\nvar TEXTURE_OPTION = \\\\\\\"texture\\\\\\\";\\nvar ENV_OPTION = \\\\\\\"env\\\\\\\";\\nvar HIDDEN_OPTION = \\\\\\\"hidden\\\\\\\";\\nvar FIELD_OPTION = \\\\\\\"field\\\\\\\";\\nvar VISIBLE_IF_OPTION = \\\\\\\"visibleIf\\\\\\\";\\nvar COLOR_CONVERSION = \\\\\\\"conversion\\\\\\\";\\nvar SEPARATOR_BEFORE_OPTION = \\\\\\\"separatorBefore\\\\\\\";\\nvar SEPARATOR_AFTER_OPTION = \\\\\\\"separatorAfter\\\\\\\";\\nvar StringParamLanguage;\\n(function(StringParamLanguage2) {\\n StringParamLanguage2[\\\\\\\"TYPESCRIPT\\\\\\\"] = \\\\\\\"typescript\\\\\\\";\\n})(StringParamLanguage || (StringParamLanguage = {}));\\nvar FileType;\\n(function(FileType2) {\\n FileType2[\\\\\\\"AUDIO\\\\\\\"] = \\\\\\\"audio\\\\\\\";\\n FileType2[\\\\\\\"TEXTURE_IMAGE\\\\\\\"] = \\\\\\\"texture_image\\\\\\\";\\n FileType2[\\\\\\\"TEXTURE_VIDEO\\\\\\\"] = \\\\\\\"texture_video\\\\\\\";\\n FileType2[\\\\\\\"GEOMETRY\\\\\\\"] = \\\\\\\"geometry\\\\\\\";\\n FileType2[\\\\\\\"FONT\\\\\\\"] = \\\\\\\"font\\\\\\\";\\n FileType2[\\\\\\\"SVG\\\\\\\"] = \\\\\\\"svg\\\\\\\";\\n FileType2[\\\\\\\"JSON\\\\\\\"] = \\\\\\\"json\\\\\\\";\\n})(FileType || (FileType = {}));\\nvar OptionsController = class {\\n constructor(_param) {\\n this._param = _param;\\n this._programatic_visible_state = true;\\n this._callbackAllowed = false;\\n this._updateVisibilityAndRemoveDirtyBound = this.updateVisibilityAndRemoveDirty.bind(this);\\n this._ui_data_dependency_set = false;\\n }\\n dispose() {\\n try {\\n this._options[CALLBACK_OPTION] = void 0;\\n this._options[CALLBACK_STRING_OPTION] = void 0;\\n } catch (err) {\\n }\\n this._visibility_graph_node?.dispose();\\n }\\n set(options) {\\n this._default_options = options;\\n this._options = ObjectUtils.cloneDeep(this._default_options);\\n this.post_set_options();\\n }\\n copy(options_controller) {\\n this._default_options = ObjectUtils.cloneDeep(options_controller.default());\\n this._options = ObjectUtils.cloneDeep(options_controller.current());\\n this.post_set_options();\\n }\\n setOption(name, value) {\\n this._options[name] = value;\\n if (this._param.components) {\\n for (let component of this._param.components) {\\n component.options.setOption(name, value);\\n }\\n }\\n }\\n post_set_options() {\\n this._handleComputeOnDirty();\\n }\\n param() {\\n return this._param;\\n }\\n node() {\\n return this._param.node;\\n }\\n default() {\\n return this._default_options;\\n }\\n current() {\\n return this._options;\\n }\\n hasOptionsOverridden() {\\n return !ObjectUtils.isEqual(this._options, this._default_options);\\n }\\n overriddenOptions() {\\n const overriden = {};\\n const option_names = Object.keys(this._options);\\n for (let option_name of option_names) {\\n if (!ObjectUtils.isEqual(this._options[option_name], this._default_options[option_name])) {\\n const cloned_option = ObjectUtils.cloneDeep(this._options[option_name]);\\n Object.assign(overriden, {[option_name]: cloned_option});\\n }\\n }\\n return overriden;\\n }\\n overriddenOptionNames() {\\n return Object.keys(this.overriddenOptions());\\n }\\n computeOnDirty() {\\n return this._options[COMPUTE_ON_DIRTY] || false;\\n }\\n _handleComputeOnDirty() {\\n if (this.computeOnDirty()) {\\n if (!this._computeOnDirty_callback_added) {\\n this.param().addPostDirtyHook(\\\\\\\"computeOnDirty\\\\\\\", this._computeParam.bind(this));\\n this._computeOnDirty_callback_added = true;\\n }\\n }\\n }\\n async _computeParam() {\\n await this.param().compute();\\n }\\n hasCallback() {\\n return this._options[CALLBACK_OPTION] != null || this._options[CALLBACK_STRING_OPTION] != null;\\n }\\n allowCallback() {\\n this._callbackAllowed = true;\\n }\\n executeCallback() {\\n if (!this._callbackAllowed) {\\n return;\\n }\\n if (!this.node()) {\\n return;\\n }\\n const callback = this.getCallback();\\n if (!callback) {\\n return;\\n }\\n if (!this.node().scene().loadingController.loaded()) {\\n return;\\n }\\n const parent_param = this.param().parent_param;\\n if (parent_param) {\\n parent_param.options.executeCallback();\\n } else {\\n callback(this.node(), this.param());\\n }\\n }\\n getCallback() {\\n if (this.hasCallback()) {\\n return this._options[CALLBACK_OPTION] = this._options[CALLBACK_OPTION] || this.createCallbackFromString();\\n }\\n }\\n createCallbackFromString() {\\n const callbackString = this._options[CALLBACK_STRING_OPTION];\\n if (callbackString) {\\n const callback_function = new Function(\\\\\\\"node\\\\\\\", \\\\\\\"scene\\\\\\\", \\\\\\\"window\\\\\\\", \\\\\\\"location\\\\\\\", callbackString);\\n return () => {\\n callback_function(this.node(), this.node().scene(), null, null);\\n };\\n }\\n }\\n colorConversion() {\\n return this._options[COLOR_CONVERSION];\\n }\\n makesNodeDirtyWhenDirty() {\\n let cook_options;\\n if (this.param().parent_param != null) {\\n return false;\\n }\\n let value = true;\\n if ((cook_options = this._options[COOK_OPTION]) != null) {\\n value = cook_options;\\n }\\n return value;\\n }\\n fileBrowseOption() {\\n return this._options[FILE_BROWSE_OPTION];\\n }\\n fileBrowseAllowed() {\\n return this.fileBrowseOption() != null;\\n }\\n fileBrowseType() {\\n const option = this.fileBrowseOption();\\n if (option) {\\n return option[FILE_TYPE_OPTION];\\n } else {\\n return null;\\n }\\n }\\n separatorBefore() {\\n return this._options[SEPARATOR_BEFORE_OPTION];\\n }\\n separatorAfter() {\\n return this._options[SEPARATOR_AFTER_OPTION];\\n }\\n isExpressionForEntities() {\\n const expr_option = this._options[EXPRESSION];\\n if (expr_option) {\\n return expr_option[FOR_ENTITIES] || false;\\n }\\n return false;\\n }\\n level() {\\n return this._options[LEVEL] || 0;\\n }\\n hasMenu() {\\n return this.menuOptions() != null || this.menuStringOptions() != null;\\n }\\n menuOptions() {\\n return this._options[MENU];\\n }\\n menuStringOptions() {\\n return this._options[MENU_STRING];\\n }\\n menuEntries() {\\n const options = this.menuOptions() || this.menuStringOptions();\\n if (options) {\\n return options[ENTRIES];\\n } else {\\n return [];\\n }\\n }\\n isMultiline() {\\n return this._options[MULTILINE_OPTION] === true;\\n }\\n language() {\\n return this._options[LANGUAGE_OPTION];\\n }\\n isCode() {\\n return this.language() != null;\\n }\\n nodeSelectionOptions() {\\n return this._options[NODE_SELECTION];\\n }\\n nodeSelectionContext() {\\n const options = this.nodeSelectionOptions();\\n if (options) {\\n return options[NODE_SELECTION_CONTEXT];\\n }\\n }\\n nodeSelectionTypes() {\\n const options = this.nodeSelectionOptions();\\n if (options) {\\n return options[NODE_SELECTION_TYPES];\\n }\\n }\\n dependentOnFoundNode() {\\n if (DEPENDENT_ON_FOUND_NODE in this._options) {\\n return this._options[DEPENDENT_ON_FOUND_NODE];\\n } else {\\n return true;\\n }\\n }\\n isSelectingParam() {\\n return this.paramSelectionOptions() != null;\\n }\\n paramSelectionOptions() {\\n return this._options[PARAM_SELECTION];\\n }\\n paramSelectionType() {\\n const options = this.paramSelectionOptions();\\n if (options) {\\n const type_or_boolean = options;\\n if (!CoreType.isBoolean(type_or_boolean)) {\\n return type_or_boolean;\\n }\\n }\\n }\\n range() {\\n return this._options[RANGE_OPTION] || [0, 1];\\n }\\n step() {\\n return this._options[STEP_OPTION];\\n }\\n rangeLocked() {\\n return this._options[RANGE_LOCKED_OPTION] || [false, false];\\n }\\n ensureInRange(value) {\\n const range = this.range();\\n if (value >= range[0] && value <= range[1]) {\\n return value;\\n } else {\\n if (value < range[0]) {\\n return this.rangeLocked()[0] === true ? range[0] : value;\\n } else {\\n return this.rangeLocked()[1] === true ? range[1] : value;\\n }\\n }\\n }\\n isSpare() {\\n return this._options[SPARE_OPTION] || false;\\n }\\n textureOptions() {\\n return this._options[TEXTURE_OPTION];\\n }\\n textureAsEnv() {\\n const texture_options = this.textureOptions();\\n if (texture_options != null) {\\n return texture_options[ENV_OPTION] === true;\\n }\\n return false;\\n }\\n isHidden() {\\n return this._options[HIDDEN_OPTION] === true || this._programatic_visible_state === false;\\n }\\n isVisible() {\\n return !this.isHidden();\\n }\\n setVisibleState(state) {\\n this._options[HIDDEN_OPTION] = !state;\\n this.param().emit(ParamEvent.VISIBLE_UPDATED);\\n }\\n label() {\\n return this._options[LABEL];\\n }\\n isLabelHidden() {\\n const type = this.param().type();\\n return type === ParamType.BUTTON || type === ParamType.BOOLEAN && this.isFieldHidden();\\n }\\n isFieldHidden() {\\n return this._options[FIELD_OPTION] === false;\\n }\\n uiDataDependsOnOtherParams() {\\n return VISIBLE_IF_OPTION in this._options;\\n }\\n visibilityPredecessors() {\\n const visibility_options = this._options[VISIBLE_IF_OPTION];\\n if (!visibility_options) {\\n return [];\\n }\\n let predecessor_names = [];\\n if (CoreType.isArray(visibility_options)) {\\n predecessor_names = ArrayUtils.uniq(visibility_options.map((options) => Object.keys(options)).flat());\\n } else {\\n predecessor_names = Object.keys(visibility_options);\\n }\\n const node = this.param().node;\\n return ArrayUtils.compact(predecessor_names.map((name) => {\\n const param = node.params.get(name);\\n if (param) {\\n return param;\\n } else {\\n console.error(`param ${name} not found as visibility condition for ${this.param().name()} in node ${this.param().node.type()}`);\\n }\\n }));\\n }\\n setUiDataDependency() {\\n if (this._ui_data_dependency_set) {\\n return;\\n }\\n this._ui_data_dependency_set = true;\\n const predecessors = this.visibilityPredecessors();\\n if (predecessors.length > 0) {\\n this._visibility_graph_node = new CoreGraphNode(this.param().scene(), \\\\\\\"param_visibility\\\\\\\");\\n for (let predecessor of predecessors) {\\n this._visibility_graph_node.addGraphInput(predecessor);\\n }\\n this._visibility_graph_node.addPostDirtyHook(\\\\\\\"_update_visibility_and_remove_dirty\\\\\\\", this._updateVisibilityAndRemoveDirtyBound);\\n }\\n }\\n updateVisibilityAndRemoveDirty() {\\n this.updateVisibility();\\n this.param().removeDirtyState();\\n }\\n async updateVisibility() {\\n const options = this._options[VISIBLE_IF_OPTION];\\n if (options) {\\n const params = this.visibilityPredecessors();\\n const promises = params.map((p) => {\\n if (p.isDirty()) {\\n return p.compute();\\n }\\n });\\n this._programatic_visible_state = false;\\n await Promise.all(promises);\\n if (CoreType.isArray(options)) {\\n for (let options_set of options) {\\n const satisfied_values = params.filter((param) => param.value == options_set[param.name()]);\\n if (satisfied_values.length == params.length) {\\n this._programatic_visible_state = true;\\n }\\n }\\n } else {\\n const satisfied_values = params.filter((param) => param.value == options[param.name()]);\\n this._programatic_visible_state = satisfied_values.length == params.length;\\n }\\n this.param().emit(ParamEvent.VISIBLE_UPDATED);\\n }\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/params/utils/EmitController.ts\\nvar EmitController = class {\\n constructor(param) {\\n this.param = param;\\n this._blocked_emit = false;\\n this._blocked_parent_emit = false;\\n this._count_by_event_name = {};\\n }\\n emitAllowed() {\\n if (this._blocked_emit === true) {\\n return false;\\n }\\n if (this.param.scene().loadingController.isLoading()) {\\n return false;\\n }\\n return this.param.scene().dispatchController.emitAllowed();\\n }\\n blockEmit() {\\n this._blocked_emit = true;\\n if (this.param.isMultiple() && this.param.components) {\\n for (let component of this.param.components) {\\n component.emitController.blockEmit();\\n }\\n }\\n return true;\\n }\\n unblockEmit() {\\n this._blocked_emit = false;\\n if (this.param.isMultiple() && this.param.components) {\\n for (let component of this.param.components) {\\n component.emitController.unblockEmit();\\n }\\n }\\n return true;\\n }\\n blockParentEmit() {\\n this._blocked_parent_emit = true;\\n return true;\\n }\\n unblockParentEmit() {\\n this._blocked_parent_emit = false;\\n return true;\\n }\\n incrementCount(event_name) {\\n this._count_by_event_name[event_name] = this._count_by_event_name[event_name] || 0;\\n this._count_by_event_name[event_name] += 1;\\n }\\n eventsCount(event_name) {\\n return this._count_by_event_name[event_name] || 0;\\n }\\n emit(event) {\\n if (this.emitAllowed()) {\\n this.param.emit(event);\\n if (this.param.parent_param != null && this._blocked_parent_emit !== true) {\\n this.param.parent_param.emit(event);\\n }\\n }\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/params/utils/Serializer.ts\\nvar ParamSerializer = class {\\n constructor(param) {\\n this.param = param;\\n }\\n toJSON() {\\n const data = {\\n name: this.param.name(),\\n type: this.param.type(),\\n raw_input: this.rawInput(),\\n value: this.value(),\\n value_pre_conversion: this.value_pre_conversion(),\\n expression: this.expression(),\\n graph_node_id: this.param.graphNodeId(),\\n error_message: this.error_message(),\\n is_visible: this.is_visible(),\\n components: void 0\\n };\\n if (this.param.isMultiple() && this.param.components) {\\n data[\\\\\\\"components\\\\\\\"] = this.param.components.map((component) => component.graphNodeId());\\n }\\n return data;\\n }\\n rawInput() {\\n return this.param.rawInputSerialized();\\n }\\n value() {\\n return this.param.valueSerialized();\\n }\\n value_pre_conversion() {\\n return this.param.valuePreConversionSerialized();\\n }\\n expression() {\\n return this.param.hasExpression() ? this.param.expressionController?.expression() : void 0;\\n }\\n error_message() {\\n return this.param.states.error.message();\\n }\\n is_visible() {\\n return this.param.options.isVisible();\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/params/utils/states/TimeDependent.ts\\nvar TimeDependentState2 = class {\\n constructor(param) {\\n this.param = param;\\n }\\n active() {\\n const frame_graph_node_id = this.param.scene().timeController.graphNode.graphNodeId();\\n return this.param.graphPredecessorIds().includes(frame_graph_node_id);\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/params/utils/states/Error.ts\\nvar ParamErrorState = class {\\n constructor(param) {\\n this.param = param;\\n }\\n set(message) {\\n if (this._message != message) {\\n this._message = message;\\n if (this._message) {\\n Poly.warn(this.param.path(), this._message);\\n }\\n this.param.emitController.emit(ParamEvent.ERROR_UPDATED);\\n }\\n }\\n message() {\\n return this._message;\\n }\\n clear() {\\n this.set(void 0);\\n }\\n active() {\\n return this._message != null;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/params/utils/StatesController.ts\\nvar StatesController2 = class {\\n constructor(param) {\\n this.param = param;\\n this.timeDependent = new TimeDependentState2(this.param);\\n this.error = new ParamErrorState(this.param);\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/expressions/MethodDependency.ts\\nvar MethodDependency = class extends CoreGraphNode {\\n constructor(param, path_argument, decomposed_path) {\\n super(param.scene(), \\\\\\\"MethodDependency\\\\\\\");\\n this.param = param;\\n this.path_argument = path_argument;\\n this.decomposed_path = decomposed_path;\\n this._update_from_name_change_bound = this._update_from_name_change.bind(this);\\n param.expressionController?.registerMethodDependency(this);\\n this.addPostDirtyHook(\\\\\\\"_update_from_name_change\\\\\\\", this._update_from_name_change_bound);\\n }\\n _update_from_name_change(trigger) {\\n if (trigger && this.decomposed_path) {\\n const node = trigger;\\n this.decomposed_path.update_from_name_change(node);\\n const new_path = this.decomposed_path.to_path();\\n const literal = this.jsep_node;\\n if (literal) {\\n literal.value = `${literal.value}`.replace(`${this.path_argument}`, new_path);\\n literal.raw = literal.raw.replace(`${this.path_argument}`, new_path);\\n }\\n if (this.param.expressionController) {\\n this.param.expressionController.updateFromMethodDependencyNameChange();\\n }\\n }\\n }\\n reset() {\\n this.graphDisconnectPredecessors();\\n }\\n listen_for_name_changes() {\\n if (this.jsep_node && this.decomposed_path) {\\n for (let node_in_path of this.decomposed_path.named_nodes()) {\\n if (node_in_path) {\\n const node = node_in_path;\\n if (node.nameController) {\\n this.addGraphInput(node.nameController.graph_node);\\n }\\n }\\n }\\n }\\n }\\n set_jsep_node(jsep_node) {\\n this.jsep_node = jsep_node;\\n }\\n set_resolved_graph_node(node) {\\n this.resolved_graph_node = node;\\n }\\n set_unresolved_path(path) {\\n this.unresolved_path = path;\\n }\\n static create(param, index_or_path, node, decomposed_path) {\\n const is_index = CoreType.isNumber(index_or_path);\\n const instance = new MethodDependency(param, index_or_path, decomposed_path);\\n if (node) {\\n instance.set_resolved_graph_node(node);\\n } else {\\n if (!is_index) {\\n const path = index_or_path;\\n instance.set_unresolved_path(path);\\n }\\n }\\n return instance;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/params/_Base.ts\\nvar TYPED_PARAM_DEFAULT_COMPONENT_NAMES = [];\\nvar TypedParam = class extends CoreGraphNode {\\n constructor(scene, node) {\\n super(scene, \\\\\\\"BaseParam\\\\\\\");\\n this._options = new OptionsController(this);\\n this._emit_controller = new EmitController(this);\\n this._is_computing = false;\\n this._node = node;\\n this.initialize_param();\\n }\\n get options() {\\n return this._options = this._options || new OptionsController(this);\\n }\\n get emitController() {\\n return this._emit_controller = this._emit_controller || new EmitController(this);\\n }\\n get expressionController() {\\n return this._expression_controller;\\n }\\n get serializer() {\\n return this._serializer = this._serializer || new ParamSerializer(this);\\n }\\n get states() {\\n return this._states = this._states || new StatesController2(this);\\n }\\n dispose() {\\n const predecessors = this.graphPredecessors();\\n for (let predecessor of predecessors) {\\n if (predecessor instanceof MethodDependency) {\\n predecessor.dispose();\\n }\\n }\\n this.scene().missingExpressionReferencesController.deregisterParam(this);\\n this._expression_controller?.dispose();\\n super.dispose();\\n this._options?.dispose();\\n }\\n initialize_param() {\\n }\\n static type() {\\n return ParamType.FLOAT;\\n }\\n type() {\\n return this.constructor.type();\\n }\\n isNumeric() {\\n return false;\\n }\\n setName(name) {\\n super.setName(name);\\n }\\n get value() {\\n return this._value;\\n }\\n copy_value(param) {\\n if (param.type() == this.type()) {\\n this._copy_value(param);\\n } else {\\n console.warn(`cannot copy value from ${param.type()} to ${this.type()}`);\\n }\\n }\\n _copy_value(param) {\\n throw \\\\\\\"abstract method param._copy_value\\\\\\\";\\n }\\n valuePreConversionSerialized() {\\n return void 0;\\n }\\n convert(raw_val) {\\n return null;\\n }\\n static are_raw_input_equal(val1, val2) {\\n return false;\\n }\\n is_raw_input_equal(other_raw_input) {\\n return this.constructor.are_raw_input_equal(this._raw_input, other_raw_input);\\n }\\n static are_values_equal(val1, val2) {\\n return false;\\n }\\n is_value_equal(other_val) {\\n return this.constructor.are_values_equal(this.value, other_val);\\n }\\n _clone_raw_input(raw_input) {\\n return raw_input;\\n }\\n set(raw_input) {\\n this._raw_input = this._clone_raw_input(this._prefilter_invalid_raw_input(raw_input));\\n this.emitController.emit(ParamEvent.RAW_INPUT_UPDATED);\\n this.processRawInput();\\n }\\n _prefilter_invalid_raw_input(raw_input) {\\n return raw_input;\\n }\\n defaultValue() {\\n return this._default_value;\\n }\\n isDefault() {\\n return this._raw_input == this._default_value;\\n }\\n rawInput() {\\n return this._raw_input;\\n }\\n processRawInput() {\\n }\\n async compute() {\\n if (this.scene().loadingController.isLoading()) {\\n console.warn(`param attempt to compute ${this.path()}`);\\n }\\n if (this.isDirty()) {\\n if (!this._is_computing) {\\n this._is_computing = true;\\n await this.processComputation();\\n this._is_computing = false;\\n if (this._compute_resolves) {\\n let callback;\\n while (callback = this._compute_resolves.pop()) {\\n callback();\\n }\\n }\\n } else {\\n return new Promise((resolve, reject) => {\\n this._compute_resolves = this._compute_resolves || [];\\n this._compute_resolves.push(resolve);\\n });\\n }\\n }\\n }\\n async processComputation() {\\n }\\n setInitValue(init_value) {\\n this._default_value = this._clone_raw_input(this._prefilter_invalid_raw_input(init_value));\\n }\\n _setupNodeDependencies(node) {\\n if (!node) {\\n if (this._node) {\\n this._node.params.params_node?.removeGraphInput(this);\\n }\\n } else {\\n this.options.allowCallback();\\n if (!this.parent_param) {\\n if (this.options.makesNodeDirtyWhenDirty()) {\\n node.params.params_node?.addGraphInput(this, false);\\n } else {\\n this.dirtyController.addPostDirtyHook(\\\\\\\"run callback\\\\\\\", async () => {\\n await this.compute();\\n this.options.executeCallback();\\n });\\n }\\n }\\n }\\n if (this.components) {\\n for (let c of this.components) {\\n c._setupNodeDependencies(node);\\n }\\n }\\n }\\n get node() {\\n return this._node;\\n }\\n parent() {\\n return this.node;\\n }\\n set_parent_param(param) {\\n param.addGraphInput(this, false);\\n this._parent_param = param;\\n }\\n get parent_param() {\\n return this._parent_param;\\n }\\n has_parent_param() {\\n return this._parent_param != null;\\n }\\n path() {\\n return this.node?.path() + \\\\\\\"/\\\\\\\" + this.name();\\n }\\n pathRelativeTo(node) {\\n const nodeRelativePath = CoreWalker.relativePath(node, this.node);\\n if (nodeRelativePath.length > 0) {\\n return `${nodeRelativePath}${CoreWalker.SEPARATOR}${this.name()}`;\\n } else {\\n return this.name();\\n }\\n }\\n emit(event_name) {\\n if (this.emitController.emitAllowed()) {\\n this.emitController.incrementCount(event_name);\\n this.scene().dispatchController.dispatch(this, event_name);\\n }\\n }\\n get components() {\\n return this._components;\\n }\\n componentNames() {\\n return TYPED_PARAM_DEFAULT_COMPONENT_NAMES;\\n }\\n isMultiple() {\\n return this.componentNames().length > 0;\\n }\\n initComponents() {\\n }\\n hasExpression() {\\n return this.expressionController != null && this.expressionController.active();\\n }\\n toJSON() {\\n return this.serializer.toJSON();\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/expressions/traversers/ParsedTree.ts\\nvar import_jsep = __toModule(require_jsep());\\nimport_jsep.default.addUnaryOp(\\\\\\\"@\\\\\\\");\\nvar precedence = 10;\\nimport_jsep.default.addBinaryOp(\\\\\\\"**\\\\\\\", precedence);\\nvar JSEP_IDENTIFIER = \\\\\\\"Identifier\\\\\\\";\\nvar JSEP_LITERAL = \\\\\\\"Literal\\\\\\\";\\nvar JSEP_CALL_EXPRESSION = \\\\\\\"CallExpression\\\\\\\";\\nvar STRING_EXPRESSION_SEPARATOR = \\\\\\\"`\\\\\\\";\\nvar ParsedTree = class {\\n constructor() {\\n }\\n parse_expression(string) {\\n try {\\n this.reset();\\n this.node = import_jsep.default(string);\\n } catch (e) {\\n const message = `could not parse the expression '${string}' (error: ${e})`;\\n this.error_message = message;\\n }\\n }\\n parse_expression_for_string_param(string) {\\n try {\\n this.reset();\\n const elements = ParsedTree.string_value_elements(string);\\n const nodes = [];\\n for (let i = 0; i < elements.length; i++) {\\n const element = elements[i];\\n let node;\\n if (i % 2 == 1) {\\n node = import_jsep.default(element);\\n } else {\\n const sanitizedElement = element.replace(/\\\\'/g, \\\\\\\"\\\\\\\\'\\\\\\\");\\n node = {\\n type: JSEP_LITERAL,\\n value: `'${sanitizedElement}'`,\\n raw: `'${sanitizedElement}'`\\n };\\n }\\n nodes.push(node);\\n }\\n this.node = {\\n type: JSEP_CALL_EXPRESSION,\\n arguments: nodes,\\n callee: {\\n type: JSEP_IDENTIFIER,\\n name: \\\\\\\"strConcat\\\\\\\"\\n }\\n };\\n } catch (e) {\\n const message = `could not parse the expression '${string}' (error: ${e})`;\\n this.error_message = message;\\n }\\n }\\n static string_value_elements(v) {\\n if (v != null) {\\n if (CoreType.isString(v)) {\\n return v.split(STRING_EXPRESSION_SEPARATOR);\\n } else {\\n return [];\\n }\\n } else {\\n return [];\\n }\\n }\\n reset() {\\n this.node = void 0;\\n this.error_message = void 0;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/expressions/LiteralConstructsController.ts\\nvar LiteralConstructsController = class {\\n static if(args) {\\n const condition = args[0];\\n const val_true = args[1];\\n const val_false = args[2];\\n return `(${condition}) ? (${val_true}) : (${val_false})`;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/expressions/traversers/_Base.ts\\nvar VARIABLE_PREFIX = \\\\\\\"$\\\\\\\";\\nvar BaseTraverser = class {\\n constructor(param) {\\n this.param = param;\\n this._set_error_from_error_bound = this._set_error_from_error.bind(this);\\n }\\n clear_error() {\\n this._error_message = void 0;\\n }\\n set_error(message) {\\n this._error_message = this._error_message || message;\\n }\\n _set_error_from_error(error) {\\n if (CoreType.isString(error)) {\\n this._error_message = error;\\n } else {\\n this._error_message = error.message;\\n }\\n }\\n is_errored() {\\n return this._error_message != null;\\n }\\n error_message() {\\n return this._error_message;\\n }\\n reset() {\\n this._error_message = void 0;\\n }\\n traverse_node(node) {\\n const method_name = `traverse_${node.type}`;\\n const method = this[method_name];\\n if (method) {\\n return this[method_name](node);\\n } else {\\n this.set_error(`expression unknown node type: ${node.type}`);\\n }\\n }\\n traverse_BinaryExpression(node) {\\n return `${this.traverse_node(node.left)} ${node.operator} ${this.traverse_node(node.right)}`;\\n }\\n traverse_LogicalExpression(node) {\\n return `${this.traverse_node(node.left)} ${node.operator} ${this.traverse_node(node.right)}`;\\n }\\n traverse_MemberExpression(node) {\\n return `${this.traverse_node(node.object)}.${this.traverse_node(node.property)}`;\\n }\\n traverse_ConditionalExpression(node) {\\n return `(${this.traverse_node(node.test)}) ? (${this.traverse_node(node.consequent)}) : (${this.traverse_node(node.alternate)})`;\\n }\\n traverse_Compound(node) {\\n const args = node.body;\\n let traversed_args = [];\\n for (let i = 0; i < args.length; i++) {\\n const arg_node = args[i];\\n if (arg_node.type == \\\\\\\"Identifier\\\\\\\") {\\n if (arg_node.name[0] == VARIABLE_PREFIX) {\\n traversed_args.push(\\\\\\\"`${\\\\\\\" + this.traverse_node(arg_node) + \\\\\\\"}`\\\\\\\");\\n } else {\\n traversed_args.push(`'${arg_node.name}'`);\\n }\\n } else {\\n traversed_args.push(\\\\\\\"`${\\\\\\\" + this.traverse_node(arg_node) + \\\\\\\"}`\\\\\\\");\\n }\\n }\\n return traversed_args.join(\\\\\\\" + \\\\\\\");\\n }\\n traverse_Literal(node) {\\n return `${node.raw}`;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/expressions/AttributeRequirementsController.ts\\nvar VAR_CORE_GEOMETRY = `coreGeometry`;\\nvar AttributeRequirementsController = class {\\n constructor() {\\n }\\n reset() {\\n if (this._attributeNames) {\\n this._attributeNames.clear();\\n }\\n }\\n assignAttributesLines() {\\n if (this._attributeNames) {\\n const lines = [];\\n for (let attribName of this._attributeNames) {\\n lines.push(AttributeRequirementsController.assignAttributeLine(attribName));\\n }\\n return lines.join(\\\\\\\";\\\\n\\\\\\\");\\n } else {\\n return \\\\\\\"\\\\\\\";\\n }\\n }\\n assignArraysLines() {\\n if (this._attributeNames) {\\n const lines = [];\\n if (this._attributeNames.size > 0) {\\n const coreGeoLine = `const ${VAR_CORE_GEOMETRY} = entities[0].coreGeometry();`;\\n lines.push(coreGeoLine);\\n }\\n for (let attribName of this._attributeNames) {\\n lines.push(AttributeRequirementsController.assignItemSizeLine(attribName));\\n lines.push(AttributeRequirementsController.assignArrayLine(attribName));\\n }\\n return lines.join(\\\\\\\";\\\\n\\\\\\\");\\n } else {\\n return \\\\\\\"\\\\\\\";\\n }\\n }\\n attributePresenceCheckLine() {\\n if (this._attributeNames) {\\n const varNames = [];\\n for (let attribName of this._attributeNames) {\\n const varName = AttributeRequirementsController._varAttribute(attribName);\\n varNames.push(varName);\\n }\\n if (varNames.length > 0) {\\n return varNames.join(\\\\\\\" && \\\\\\\");\\n }\\n }\\n return \\\\\\\"true\\\\\\\";\\n }\\n add(attribName) {\\n this._attributeNames = this._attributeNames || new Set();\\n this._attributeNames.add(attribName);\\n }\\n static assignAttributeLine(attribName) {\\n const varAttribute = this._varAttribute(attribName);\\n return `const ${varAttribute} = entities[0].geometry().attributes['${attribName}']`;\\n }\\n static assignItemSizeLine(attribName) {\\n const varAttribute = this._varAttribute(attribName);\\n const varAttributeSize = this._varAttribSize(attribName);\\n return `const ${varAttributeSize} = ${varAttribute}.itemSize`;\\n }\\n static assignArrayLine(attribName) {\\n const varAttribute = this._varAttribute(attribName);\\n const varArray = this._varArray(attribName);\\n const isIndexedCondition = `${VAR_CORE_GEOMETRY}.isAttribIndexed('${attribName}')`;\\n const indexedArray = `entities.map(e=>e.indexedAttribValue('${attribName}'))`;\\n const nonIndexedArray = `${varAttribute}.array`;\\n return `const ${varArray} = ${isIndexedCondition} ? ${indexedArray} : ${nonIndexedArray}`;\\n }\\n static _varAttribute(attribName) {\\n return `attrib_${attribName}`;\\n }\\n static _varAttribSize(attribName) {\\n return `attrib_size_${attribName}`;\\n }\\n static _varArray(attribName) {\\n return `array_${attribName}`;\\n }\\n varAttributeSize(attribName) {\\n return AttributeRequirementsController._varAttribSize(attribName);\\n }\\n varArray(attribName) {\\n return AttributeRequirementsController._varArray(attribName);\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/expressions/traversers/FunctionGenerator.ts\\nvar NATIVE_MATH_METHODS = [\\n \\\\\\\"abs\\\\\\\",\\n \\\\\\\"acos\\\\\\\",\\n \\\\\\\"acosh\\\\\\\",\\n \\\\\\\"asin\\\\\\\",\\n \\\\\\\"asinh\\\\\\\",\\n \\\\\\\"atan\\\\\\\",\\n \\\\\\\"atan2\\\\\\\",\\n \\\\\\\"atanh\\\\\\\",\\n \\\\\\\"ceil\\\\\\\",\\n \\\\\\\"cos\\\\\\\",\\n \\\\\\\"cosh\\\\\\\",\\n \\\\\\\"exp\\\\\\\",\\n \\\\\\\"expm1\\\\\\\",\\n \\\\\\\"floor\\\\\\\",\\n \\\\\\\"log\\\\\\\",\\n \\\\\\\"log1p\\\\\\\",\\n \\\\\\\"log2\\\\\\\",\\n \\\\\\\"log10\\\\\\\",\\n \\\\\\\"max\\\\\\\",\\n \\\\\\\"min\\\\\\\",\\n \\\\\\\"pow\\\\\\\",\\n \\\\\\\"round\\\\\\\",\\n \\\\\\\"sign\\\\\\\",\\n \\\\\\\"sin\\\\\\\",\\n \\\\\\\"sinh\\\\\\\",\\n \\\\\\\"sqrt\\\\\\\",\\n \\\\\\\"tan\\\\\\\",\\n \\\\\\\"tanh\\\\\\\"\\n];\\nvar NATIVE_ES6_MATH_METHODS = [\\\\\\\"cbrt\\\\\\\", \\\\\\\"hypot\\\\\\\", \\\\\\\"log10\\\\\\\", \\\\\\\"trunc\\\\\\\"];\\nvar NATIVE_MATH_METHODS_RENAMED = {\\n math_random: \\\\\\\"random\\\\\\\"\\n};\\nvar CORE_MATH_METHODS = [\\\\\\\"fit\\\\\\\", \\\\\\\"fit01\\\\\\\", \\\\\\\"fract\\\\\\\", \\\\\\\"deg2rad\\\\\\\", \\\\\\\"rad2deg\\\\\\\", \\\\\\\"rand\\\\\\\", \\\\\\\"clamp\\\\\\\"];\\nvar EASING_METHODS = Object.keys(Easing);\\nvar CORE_STRING_METHODS = [\\\\\\\"precision\\\\\\\"];\\nvar NATIVE_MATH_CONSTANTS = [\\\\\\\"E\\\\\\\", \\\\\\\"LN2\\\\\\\", \\\\\\\"LN10\\\\\\\", \\\\\\\"LOG10E\\\\\\\", \\\\\\\"LOG2E\\\\\\\", \\\\\\\"PI\\\\\\\", \\\\\\\"SQRT1_2\\\\\\\", \\\\\\\"SQRT2\\\\\\\"];\\nvar DIRECT_EXPRESSION_FUNCTIONS = {};\\nNATIVE_MATH_METHODS.forEach((name) => {\\n DIRECT_EXPRESSION_FUNCTIONS[name] = `Math.${name}`;\\n});\\nNATIVE_ES6_MATH_METHODS.forEach((name) => {\\n DIRECT_EXPRESSION_FUNCTIONS[name] = `Math.${name}`;\\n});\\nObject.keys(NATIVE_MATH_METHODS_RENAMED).forEach((name) => {\\n const remaped = NATIVE_MATH_METHODS_RENAMED[name];\\n DIRECT_EXPRESSION_FUNCTIONS[name] = `Math.${remaped}`;\\n});\\nCORE_MATH_METHODS.forEach((name) => {\\n DIRECT_EXPRESSION_FUNCTIONS[name] = `Core.Math.${name}`;\\n});\\nEASING_METHODS.forEach((name) => {\\n DIRECT_EXPRESSION_FUNCTIONS[name] = `Core.Math.Easing.${name}`;\\n});\\nCORE_STRING_METHODS.forEach((name) => {\\n DIRECT_EXPRESSION_FUNCTIONS[name] = `Core.String.${name}`;\\n});\\nvar LITERAL_CONSTRUCT = {\\n if: LiteralConstructsController.if\\n};\\nvar GLOBAL_CONSTANTS = {};\\nNATIVE_MATH_CONSTANTS.forEach((name) => {\\n GLOBAL_CONSTANTS[name] = `Math.${name}`;\\n});\\nvar QUOTE = \\\\\\\"'\\\\\\\";\\nvar ARGUMENTS_SEPARATOR = \\\\\\\", \\\\\\\";\\nvar ATTRIBUTE_PREFIX = \\\\\\\"@\\\\\\\";\\nvar PROPERTY_OFFSETS = {\\n x: 0,\\n y: 1,\\n z: 2,\\n w: 3,\\n r: 0,\\n g: 1,\\n b: 2\\n};\\nvar FunctionGenerator = class extends BaseTraverser {\\n constructor(param) {\\n super(param);\\n this.param = param;\\n this._attribute_requirements_controller = new AttributeRequirementsController();\\n this.methods = [];\\n this.method_index = -1;\\n this.method_dependencies = [];\\n this.immutable_dependencies = [];\\n }\\n parse_tree(parsed_tree) {\\n this.reset();\\n if (parsed_tree.error_message == null) {\\n try {\\n this._attribute_requirements_controller = new AttributeRequirementsController();\\n if (parsed_tree.node) {\\n const function_main_string = this.traverse_node(parsed_tree.node);\\n if (function_main_string && !this.is_errored()) {\\n this.function_main_string = function_main_string;\\n }\\n } else {\\n console.warn(\\\\\\\"no parsed_tree.node\\\\\\\");\\n }\\n } catch (e) {\\n console.warn(`error in expression for param ${this.param.path()}`);\\n console.warn(e);\\n }\\n if (this.function_main_string) {\\n try {\\n const body = this._functionBody();\\n this.function = new Function(\\\\\\\"Core\\\\\\\", \\\\\\\"param\\\\\\\", \\\\\\\"methods\\\\\\\", \\\\\\\"_set_error_from_error\\\\\\\", `\\n\\t\\t\\t\\t\\ttry {\\n\\t\\t\\t\\t\\t\\t${body}\\n\\t\\t\\t\\t\\t} catch(e) {\\n\\t\\t\\t\\t\\t\\t_set_error_from_error(e)\\n\\t\\t\\t\\t\\t\\treturn null;\\n\\t\\t\\t\\t\\t}`);\\n } catch (e) {\\n console.warn(e);\\n this.set_error(\\\\\\\"cannot generate function\\\\\\\");\\n }\\n } else {\\n this.set_error(\\\\\\\"cannot generate function body\\\\\\\");\\n }\\n } else {\\n this.set_error(\\\\\\\"cannot parse expression\\\\\\\");\\n }\\n }\\n reset() {\\n super.reset();\\n this.function_main_string = void 0;\\n this.methods = [];\\n this.method_index = -1;\\n this.function = void 0;\\n this.method_dependencies = [];\\n this.immutable_dependencies = [];\\n }\\n _functionBody() {\\n if (this.param.options.isExpressionForEntities()) {\\n return `\\n\\t\\t\\tconst entities = param.expressionController.entities();\\n\\t\\t\\tif(entities){\\n\\t\\t\\t\\treturn new Promise( async (resolve, reject)=>{\\n\\t\\t\\t\\t\\tlet entity;\\n\\t\\t\\t\\t\\tconst entity_callback = param.expressionController.entity_callback();\\n\\t\\t\\t\\t\\t// assign_attributes_lines\\n\\t\\t\\t\\t\\t${this._attribute_requirements_controller.assignAttributesLines()}\\n\\t\\t\\t\\t\\t// check if attributes are present\\n\\t\\t\\t\\t\\tif( ${this._attribute_requirements_controller.attributePresenceCheckLine()} ){\\n\\t\\t\\t\\t\\t\\t// assign_arrays_lines\\n\\t\\t\\t\\t\\t\\t${this._attribute_requirements_controller.assignArraysLines()}\\n\\t\\t\\t\\t\\t\\tfor(let index=0; index < entities.length; index++){\\n\\t\\t\\t\\t\\t\\t\\tentity = entities[index];\\n\\t\\t\\t\\t\\t\\t\\tresult = ${this.function_main_string};\\n\\t\\t\\t\\t\\t\\t\\tentity_callback(entity, result);\\n\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\tresolve()\\n\\t\\t\\t\\t\\t} else {\\n\\t\\t\\t\\t\\t\\tconst error = new Error('attribute not found')\\n\\t\\t\\t\\t\\t\\t_set_error_from_error(error)\\n\\t\\t\\t\\t\\t\\treject(error)\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t})\\n\\t\\t\\t}\\n\\t\\t\\treturn []`;\\n } else {\\n return `\\n\\t\\t\\treturn new Promise( async (resolve, reject)=>{\\n\\t\\t\\t\\ttry {\\n\\t\\t\\t\\t\\tconst value = ${this.function_main_string}\\n\\t\\t\\t\\t\\tresolve(value)\\n\\t\\t\\t\\t} catch(e) {\\n\\t\\t\\t\\t\\t_set_error_from_error(e)\\n\\t\\t\\t\\t\\treject()\\n\\t\\t\\t\\t}\\n\\t\\t\\t})\\n\\t\\t\\t`;\\n }\\n }\\n evalAllowed() {\\n return this.function != null;\\n }\\n evalFunction() {\\n if (this.function) {\\n this.clear_error();\\n const Core = {\\n Math: CoreMath,\\n String: CoreString\\n };\\n const result = this.function(Core, this.param, this.methods, this._set_error_from_error_bound);\\n return result;\\n }\\n }\\n traverse_CallExpression(node) {\\n const method_arguments = node.arguments.map((arg) => {\\n return this.traverse_node(arg);\\n });\\n const callee = node.callee;\\n const method_name = callee.name;\\n if (method_name) {\\n const literal_contruct = LITERAL_CONSTRUCT[method_name];\\n if (literal_contruct) {\\n return literal_contruct(method_arguments);\\n }\\n const arguments_joined = `${method_arguments.join(ARGUMENTS_SEPARATOR)}`;\\n const direct_function_name = DIRECT_EXPRESSION_FUNCTIONS[method_name];\\n if (direct_function_name) {\\n return `${direct_function_name}(${arguments_joined})`;\\n }\\n const expressionRegister = Poly.expressionsRegister;\\n const indirect_method = expressionRegister.getMethod(method_name);\\n if (indirect_method) {\\n const path_node = node.arguments[0];\\n const function_string = `return ${method_arguments[0]}`;\\n let path_argument_function;\\n let path_argument = [];\\n try {\\n path_argument_function = new Function(function_string);\\n path_argument = path_argument_function();\\n } catch {\\n }\\n this._create_method_and_dependencies(method_name, path_argument, path_node);\\n return `(await methods[${this.method_index}].processArguments([${arguments_joined}]))`;\\n } else {\\n const available_methods = expressionRegister.availableMethods().join(\\\\\\\", \\\\\\\");\\n const message = `method not found (${method_name}), available methods are: ${available_methods}`;\\n Poly.warn(message);\\n }\\n }\\n this.set_error(`unknown method: ${method_name}`);\\n }\\n traverse_BinaryExpression(node) {\\n return `(${this.traverse_node(node.left)} ${node.operator} ${this.traverse_node(node.right)})`;\\n }\\n traverse_LogicalExpression(node) {\\n return `(${this.traverse_node(node.left)} ${node.operator} ${this.traverse_node(node.right)})`;\\n }\\n traverse_MemberExpression(node) {\\n return `${this.traverse_node(node.object)}.${this.traverse_node(node.property)}`;\\n }\\n traverse_UnaryExpression(node) {\\n if (node.operator === ATTRIBUTE_PREFIX) {\\n let argument = node.argument;\\n let attribute_name;\\n let property;\\n switch (argument.type) {\\n case \\\\\\\"Identifier\\\\\\\": {\\n const argument_identifier = argument;\\n attribute_name = argument_identifier.name;\\n break;\\n }\\n case \\\\\\\"MemberExpression\\\\\\\": {\\n const argument_member_expression = argument;\\n const attrib_node = argument_member_expression.object;\\n const property_node = argument_member_expression.property;\\n attribute_name = attrib_node.name;\\n property = property_node.name;\\n break;\\n }\\n }\\n if (attribute_name) {\\n attribute_name = CoreAttribute.remapName(attribute_name);\\n if (attribute_name == \\\\\\\"ptnum\\\\\\\") {\\n return \\\\\\\"((entity != null) ? entity.index() : 0)\\\\\\\";\\n } else {\\n const var_attribute_size = this._attribute_requirements_controller.varAttributeSize(attribute_name);\\n const var_array = this._attribute_requirements_controller.varArray(attribute_name);\\n this._attribute_requirements_controller.add(attribute_name);\\n if (property) {\\n const property_offset = PROPERTY_OFFSETS[property];\\n return `${var_array}[entity.index()*${var_attribute_size}+${property_offset}]`;\\n } else {\\n return `${var_array}[entity.index()*${var_attribute_size}]`;\\n }\\n }\\n } else {\\n console.warn(\\\\\\\"attribute not found\\\\\\\");\\n return \\\\\\\"\\\\\\\";\\n }\\n } else {\\n return `${node.operator}${this.traverse_node(node.argument)}`;\\n }\\n }\\n traverse_Literal(node) {\\n return `${node.raw}`;\\n }\\n traverse_Identifier(node) {\\n const identifier_first_char = node.name[0];\\n if (identifier_first_char == VARIABLE_PREFIX) {\\n const identifier_name_without_dollar_sign = node.name.substr(1);\\n const direct_constant_name = GLOBAL_CONSTANTS[identifier_name_without_dollar_sign];\\n if (direct_constant_name) {\\n return direct_constant_name;\\n }\\n const method_name = `traverse_Identifier_${identifier_name_without_dollar_sign}`;\\n const method = this[method_name];\\n if (method) {\\n return this[method_name]();\\n } else {\\n this.set_error(`identifier unknown: ${node.name}`);\\n }\\n } else {\\n return node.name;\\n }\\n }\\n traverse_Identifier_F() {\\n this.immutable_dependencies.push(this.param.scene().timeController.graphNode);\\n return `param.scene().timeController.frame()`;\\n }\\n traverse_Identifier_T() {\\n this.immutable_dependencies.push(this.param.scene().timeController.graphNode);\\n return `param.scene().timeController.time()`;\\n }\\n traverse_Identifier_OS() {\\n return `${QUOTE}${this.param.node.name()}${QUOTE}`;\\n }\\n traverse_Identifier_CH() {\\n return `${QUOTE}${this.param.name()}${QUOTE}`;\\n }\\n traverse_Identifier_CEX() {\\n return this._method_centroid(\\\\\\\"x\\\\\\\");\\n }\\n traverse_Identifier_CEY() {\\n return this._method_centroid(\\\\\\\"y\\\\\\\");\\n }\\n traverse_Identifier_CEZ() {\\n return this._method_centroid(\\\\\\\"z\\\\\\\");\\n }\\n _method_centroid(component) {\\n const method_arguments = [0, `${QUOTE}${component}${QUOTE}`];\\n const arguments_joined = method_arguments.join(ARGUMENTS_SEPARATOR);\\n this._create_method_and_dependencies(\\\\\\\"centroid\\\\\\\", 0);\\n return `(await methods[${this.method_index}].processArguments([${arguments_joined}]))`;\\n }\\n _create_method_and_dependencies(method_name, path_argument, path_node) {\\n const expressionRegister = Poly.expressionsRegister;\\n const method_constructor = expressionRegister.getMethod(method_name);\\n if (!method_constructor) {\\n const available_methods = expressionRegister.availableMethods();\\n const message = `method not found (${method_name}), available methods are: ${available_methods.join(\\\\\\\", \\\\\\\")}`;\\n this.set_error(message);\\n Poly.warn(message);\\n return;\\n }\\n const method = new method_constructor(this.param);\\n this.method_index += 1;\\n this.methods[this.method_index] = method;\\n if (method.require_dependency()) {\\n const method_dependency = method.findDependency(path_argument);\\n if (method_dependency) {\\n if (path_node) {\\n method_dependency.set_jsep_node(path_node);\\n }\\n this.method_dependencies.push(method_dependency);\\n } else {\\n if (path_node && CoreType.isString(path_argument)) {\\n this.param.scene().missingExpressionReferencesController.register(this.param, path_argument);\\n }\\n }\\n }\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/expressions/traversers/ExpressionStringGenerator.ts\\nvar ARGUMENTS_SEPARATOR2 = \\\\\\\", \\\\\\\";\\nvar ExpressionStringGenerator = class extends BaseTraverser {\\n constructor(param) {\\n super(param);\\n this.param = param;\\n }\\n parse_tree(parsed_tree) {\\n if (parsed_tree.error_message == null && parsed_tree.node) {\\n try {\\n return this.traverse_node(parsed_tree.node);\\n } catch (e) {\\n this.set_error(\\\\\\\"could not traverse tree\\\\\\\");\\n }\\n } else {\\n this.set_error(\\\\\\\"cannot parse tree\\\\\\\");\\n }\\n }\\n traverse_CallExpression(node) {\\n const method_arguments = node.arguments.map((arg) => {\\n return this.traverse_node(arg);\\n });\\n const arguments_joined = `${method_arguments.join(ARGUMENTS_SEPARATOR2)}`;\\n const method_name = node.callee.name;\\n return `${method_name}(${arguments_joined})`;\\n }\\n traverse_UnaryExpression(node) {\\n return `${node.operator}${this.traverse_node(node.argument)}`;\\n }\\n traverse_Identifier(node) {\\n return `${node.name}`;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/expressions/DependenciesController.ts\\nvar DependenciesController = class {\\n constructor(param) {\\n this.param = param;\\n this.cyclic_graph_detected = false;\\n this.method_dependencies = [];\\n }\\n set_error(message) {\\n this.error_message = this.error_message || message;\\n }\\n reset() {\\n this.param.graphDisconnectPredecessors();\\n this.method_dependencies.forEach((method_dependency) => {\\n method_dependency.reset();\\n });\\n this.method_dependencies = [];\\n }\\n update(function_generator) {\\n this.cyclic_graph_detected = false;\\n this.connect_immutable_dependencies(function_generator);\\n this.method_dependencies = function_generator.method_dependencies;\\n this.handle_method_dependencies();\\n this.listen_for_name_changes();\\n }\\n connect_immutable_dependencies(function_generator) {\\n function_generator.immutable_dependencies.forEach((dependency) => {\\n if (this.cyclic_graph_detected == false) {\\n if (this.param.addGraphInput(dependency) == false) {\\n this.cyclic_graph_detected = true;\\n this.set_error(\\\\\\\"cannot create expression, infinite graph detected\\\\\\\");\\n this.reset();\\n return;\\n }\\n }\\n });\\n }\\n handle_method_dependencies() {\\n this.method_dependencies.forEach((method_dependency) => {\\n if (this.cyclic_graph_detected == false) {\\n this.handle_method_dependency(method_dependency);\\n }\\n });\\n }\\n handle_method_dependency(method_dependency) {\\n const node_simple = method_dependency.resolved_graph_node;\\n if (node_simple) {\\n if (!this.param.addGraphInput(node_simple)) {\\n this.cyclic_graph_detected = true;\\n this.set_error(\\\\\\\"cannot create expression, infinite graph detected\\\\\\\");\\n this.reset();\\n return;\\n }\\n }\\n }\\n listen_for_name_changes() {\\n this.method_dependencies.forEach((method_dependency) => {\\n method_dependency.listen_for_name_changes();\\n });\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/expressions/ExpressionManager.ts\\nvar ExpressionManager = class {\\n constructor(param) {\\n this.param = param;\\n this.parse_completed = false;\\n this.parse_started = false;\\n this.parsed_tree = new ParsedTree();\\n this._functionGenerator = new FunctionGenerator(this.param);\\n this.dependencies_controller = new DependenciesController(this.param);\\n }\\n parseExpression(expression) {\\n if (this.parse_started) {\\n throw new Error(`parse in progress for param ${this.param.path()}`);\\n }\\n this.parse_started = true;\\n this.parse_completed = false;\\n this.parsed_tree = this.parsed_tree || new ParsedTree();\\n this.reset();\\n if (this.param.type() == ParamType.STRING) {\\n this.parsed_tree.parse_expression_for_string_param(expression);\\n } else {\\n this.parsed_tree.parse_expression(expression);\\n }\\n this._functionGenerator.parse_tree(this.parsed_tree);\\n if (this._functionGenerator.error_message() == null) {\\n this.dependencies_controller.update(this._functionGenerator);\\n if (this.dependencies_controller.error_message) {\\n this.param.states.error.set(this.dependencies_controller.error_message);\\n } else {\\n this.parse_completed = true;\\n this.parse_started = false;\\n }\\n }\\n }\\n async computeFunction() {\\n if (this._computeAllowed()) {\\n try {\\n const new_value = await this._functionGenerator.evalFunction();\\n return new_value;\\n } catch (e) {\\n return;\\n }\\n } else {\\n return new Promise((resolve, reject) => {\\n resolve(null);\\n });\\n }\\n }\\n reset() {\\n this.parse_completed = false;\\n this.parse_started = false;\\n this.dependencies_controller.reset();\\n this._functionGenerator.reset();\\n }\\n is_errored() {\\n return this._functionGenerator.is_errored();\\n }\\n error_message() {\\n return this._functionGenerator.error_message();\\n }\\n _computeAllowed() {\\n return this._functionGenerator.evalAllowed();\\n }\\n updateFromMethodDependencyNameChange() {\\n this.expression_string_generator = this.expression_string_generator || new ExpressionStringGenerator(this.param);\\n const new_expression_string = this.expression_string_generator.parse_tree(this.parsed_tree);\\n if (new_expression_string) {\\n this.param.set(new_expression_string);\\n } else {\\n console.warn(\\\\\\\"failed to regenerate expression\\\\\\\");\\n }\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/params/utils/ExpressionController.ts\\nvar ExpressionController = class {\\n constructor(param) {\\n this.param = param;\\n }\\n dispose() {\\n this.param.scene().expressionsController.deregisterParam(this.param);\\n this._resetMethodDependencies();\\n }\\n _resetMethodDependencies() {\\n this._method_dependencies_by_graph_node_id?.forEach((method_dependency) => {\\n method_dependency.dispose();\\n });\\n this._method_dependencies_by_graph_node_id?.clear();\\n }\\n registerMethodDependency(method_dependency) {\\n this._method_dependencies_by_graph_node_id = this._method_dependencies_by_graph_node_id || new Map();\\n this._method_dependencies_by_graph_node_id.set(method_dependency.graphNodeId(), method_dependency);\\n }\\n active() {\\n return this._expression != null;\\n }\\n expression() {\\n return this._expression;\\n }\\n is_errored() {\\n if (this._manager) {\\n return this._manager.is_errored();\\n }\\n return false;\\n }\\n error_message() {\\n if (this._manager) {\\n return this._manager.error_message();\\n }\\n return null;\\n }\\n requires_entities() {\\n return this.param.options.isExpressionForEntities();\\n }\\n set_expression(expression, set_dirty = true) {\\n this.param.scene().missingExpressionReferencesController.deregisterParam(this.param);\\n this.param.scene().expressionsController.deregisterParam(this.param);\\n if (this._expression != expression) {\\n this._resetMethodDependencies();\\n this._expression = expression;\\n if (this._expression) {\\n this._manager = this._manager || new ExpressionManager(this.param);\\n this._manager.parseExpression(this._expression);\\n } else {\\n this._manager?.reset();\\n }\\n if (set_dirty) {\\n this.param.setDirty();\\n }\\n }\\n }\\n updateFromMethodDependencyNameChange() {\\n if (this._manager && this.active()) {\\n this._manager.updateFromMethodDependencyNameChange();\\n }\\n }\\n async computeExpression() {\\n if (this._manager && this.active()) {\\n const result = await this._manager.computeFunction();\\n return result;\\n }\\n }\\n async computeExpressionForEntities(entities, callback) {\\n this.set_entities(entities, callback);\\n await this.computeExpression();\\n if (this._manager?.error_message()) {\\n this.param.node.states.error.set(`expression evalution error: ${this._manager?.error_message()}`);\\n }\\n this.reset_entities();\\n }\\n computeExpressionForPoints(entities, callback) {\\n return this.computeExpressionForEntities(entities, callback);\\n }\\n computeExpressionForObjects(entities, callback) {\\n return this.computeExpressionForEntities(entities, callback);\\n }\\n entities() {\\n return this._entities;\\n }\\n entity_callback() {\\n return this._entity_callback;\\n }\\n set_entities(entities, callback) {\\n this._entities = entities;\\n this._entity_callback = callback;\\n }\\n reset_entities() {\\n this._entities = void 0;\\n this._entity_callback = void 0;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/params/_Numeric.ts\\nvar TypedNumericParam = class extends TypedParam {\\n isNumeric() {\\n return true;\\n }\\n isDefault() {\\n return this._raw_input == this._default_value;\\n }\\n _prefilter_invalid_raw_input(raw_input) {\\n if (CoreType.isArray(raw_input)) {\\n return raw_input[0];\\n } else {\\n return raw_input;\\n }\\n }\\n processRawInput() {\\n this.states.error.clear();\\n const converted = this.convert(this._raw_input);\\n if (converted != null) {\\n if (this._expression_controller) {\\n this._expression_controller.set_expression(void 0, false);\\n this.emitController.emit(ParamEvent.EXPRESSION_UPDATED);\\n }\\n if (converted != this._value) {\\n this._update_value(converted);\\n this.setSuccessorsDirty(this);\\n }\\n } else {\\n if (CoreType.isString(this._raw_input)) {\\n this._expression_controller = this._expression_controller || new ExpressionController(this);\\n if (this._raw_input != this._expression_controller.expression()) {\\n this._expression_controller.set_expression(this._raw_input);\\n this.emitController.emit(ParamEvent.EXPRESSION_UPDATED);\\n }\\n } else {\\n this.states.error.set(`param input is invalid (${this.path()})`);\\n }\\n }\\n }\\n async processComputation() {\\n if (this.expressionController?.active() && !this.expressionController.requires_entities()) {\\n const expression_result = await this.expressionController.computeExpression();\\n if (this.expressionController.is_errored()) {\\n this.states.error.set(`expression error: \\\\\\\"${this.expressionController.expression()}\\\\\\\" (${this.expressionController.error_message()})`);\\n } else {\\n const converted = this.convert(expression_result);\\n if (converted != null) {\\n if (this.states.error.active()) {\\n this.states.error.clear();\\n }\\n this._update_value(converted);\\n } else {\\n this.states.error.set(`expression returns an invalid type (${expression_result}) (${this.expressionController.expression()})`);\\n }\\n }\\n }\\n }\\n _update_value(new_value) {\\n this._value = new_value;\\n if (this.parent_param) {\\n this.parent_param.set_value_from_components();\\n }\\n this.options.executeCallback();\\n this.emitController.emit(ParamEvent.VALUE_UPDATED);\\n this.removeDirtyState();\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/params/Boolean.ts\\nvar BooleanParam = class extends TypedNumericParam {\\n static type() {\\n return ParamType.BOOLEAN;\\n }\\n defaultValueSerialized() {\\n if (CoreType.isString(this._default_value)) {\\n return this._default_value;\\n } else {\\n return this.convert(this._default_value) || false;\\n }\\n }\\n rawInputSerialized() {\\n return this._raw_input;\\n }\\n valueSerialized() {\\n return this.value;\\n }\\n _copy_value(param) {\\n this.set(param.value);\\n }\\n static are_raw_input_equal(raw_input1, raw_input2) {\\n return raw_input1 == raw_input2;\\n }\\n static are_values_equal(val1, val2) {\\n return val1 == val2;\\n }\\n convert(raw_val) {\\n if (CoreType.isBoolean(raw_val)) {\\n return raw_val;\\n } else {\\n if (CoreType.isNumber(raw_val)) {\\n return raw_val >= 1;\\n } else {\\n if (CoreType.isString(raw_val)) {\\n if (CoreString.isBoolean(raw_val)) {\\n return CoreString.toBoolean(raw_val);\\n } else {\\n if (CoreString.isNumber(raw_val)) {\\n const parsed = parseFloat(raw_val);\\n return parsed >= 1;\\n }\\n }\\n }\\n }\\n }\\n return null;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/params/Button.ts\\nvar ButtonParam = class extends TypedParam {\\n static type() {\\n return ParamType.BUTTON;\\n }\\n defaultValueSerialized() {\\n return this._default_value;\\n }\\n rawInputSerialized() {\\n return this._raw_input;\\n }\\n valueSerialized() {\\n return this.value;\\n }\\n _copy_value(param) {\\n }\\n static are_raw_input_equal(raw_input1, raw_input2) {\\n return true;\\n }\\n static are_values_equal(val1, val2) {\\n return true;\\n }\\n async pressButton() {\\n if (this.node.isDirty() || this.node.cookController.isCooking()) {\\n await this.node.compute();\\n }\\n this.options.executeCallback();\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/params/Float.ts\\nvar FloatParam = class extends TypedNumericParam {\\n static type() {\\n return ParamType.FLOAT;\\n }\\n defaultValueSerialized() {\\n return this._default_value;\\n }\\n rawInputSerialized() {\\n return this._raw_input;\\n }\\n valueSerialized() {\\n return this.value;\\n }\\n _copy_value(param) {\\n this.set(param.valueSerialized());\\n }\\n _prefilter_invalid_raw_input(raw_input) {\\n if (CoreType.isArray(raw_input)) {\\n return raw_input[0];\\n }\\n if (CoreType.isString(raw_input) && CoreString.isNumber(raw_input)) {\\n return parseFloat(raw_input);\\n }\\n return raw_input;\\n }\\n static are_raw_input_equal(raw_input1, raw_input2) {\\n return raw_input1 == raw_input2;\\n }\\n static are_values_equal(val1, val2) {\\n return val1 == val2;\\n }\\n static convert(raw_val) {\\n if (CoreType.isNumber(raw_val)) {\\n return raw_val;\\n } else {\\n if (CoreType.isBoolean(raw_val)) {\\n return raw_val ? 1 : 0;\\n } else {\\n if (CoreString.isNumber(raw_val)) {\\n const parsed = parseFloat(raw_val);\\n if (CoreType.isNumber(parsed)) {\\n return parsed;\\n }\\n }\\n }\\n return null;\\n }\\n }\\n convert(raw_val) {\\n const result = FloatParam.convert(raw_val);\\n if (result) {\\n return this.options.ensureInRange(result);\\n } else {\\n return result;\\n }\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/params/_Multiple.ts\\nvar TypedMultipleParam = class extends TypedParam {\\n constructor() {\\n super(...arguments);\\n this._components_contructor = FloatParam;\\n }\\n get components() {\\n return this._components;\\n }\\n isNumeric() {\\n return true;\\n }\\n isDefault() {\\n for (let c of this.components) {\\n if (!c.isDefault()) {\\n return false;\\n }\\n }\\n return true;\\n }\\n rawInput() {\\n return this._components.map((c) => c.rawInput());\\n }\\n rawInputSerialized() {\\n return this._components.map((c) => c.rawInputSerialized());\\n }\\n _copy_value(param) {\\n for (let i = 0; i < this.components.length; i++) {\\n const component = this.components[i];\\n const src_component = param.components[i];\\n component.copy_value(src_component);\\n }\\n }\\n initComponents() {\\n if (this._components != null) {\\n return;\\n }\\n let index = 0;\\n this._components = new Array(this.componentNames().length);\\n for (let component_name of this.componentNames()) {\\n const component = new this._components_contructor(this.scene(), this._node);\\n let default_val;\\n if (CoreType.isArray(this._default_value)) {\\n default_val = this._default_value[index];\\n } else {\\n default_val = this._default_value[component_name];\\n }\\n component.options.copy(this.options);\\n component.setInitValue(default_val);\\n component.setName(`${this.name()}${component_name}`);\\n component.set_parent_param(this);\\n this._components[index] = component;\\n index++;\\n }\\n }\\n async processComputation() {\\n await this.compute_components();\\n this.set_value_from_components();\\n }\\n set_value_from_components() {\\n }\\n hasExpression() {\\n for (let c of this.components) {\\n if (c.expressionController?.active()) {\\n return true;\\n }\\n }\\n return false;\\n }\\n async compute_components() {\\n const components = this.components;\\n const promises = [];\\n for (let c of components) {\\n if (c.isDirty()) {\\n promises.push(c.compute());\\n }\\n }\\n await Promise.all(promises);\\n this.removeDirtyState();\\n }\\n _prefilter_invalid_raw_input(raw_input) {\\n if (!CoreType.isArray(raw_input)) {\\n const number_or_string = raw_input;\\n const raw_input_wrapped_in_array = this.componentNames().map(() => number_or_string);\\n return raw_input_wrapped_in_array;\\n } else {\\n return raw_input;\\n }\\n }\\n processRawInput() {\\n const cooker = this.scene().cooker;\\n cooker.block();\\n const components = this.components;\\n for (let c of components) {\\n c.emitController.blockParentEmit();\\n }\\n const value = this._raw_input;\\n let prev_value = 0;\\n if (CoreType.isArray(value)) {\\n for (let i = 0; i < components.length; i++) {\\n let component_value = value[i];\\n if (component_value == null) {\\n component_value = prev_value;\\n }\\n components[i].set(component_value);\\n prev_value = component_value;\\n }\\n } else {\\n for (let i = 0; i < components.length; i++) {\\n const component_name = this.componentNames()[i];\\n let component_value = value[component_name];\\n if (component_value == null) {\\n component_value = prev_value;\\n }\\n components[i].set(component_value);\\n prev_value = component_value;\\n }\\n }\\n cooker.unblock();\\n for (let i = 0; i < components.length; i++) {\\n components[i].emitController.unblockParentEmit();\\n }\\n this.emitController.emit(ParamEvent.VALUE_UPDATED);\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/core/Color.ts\\nvar ColorConversion;\\n(function(ColorConversion2) {\\n ColorConversion2[\\\\\\\"NONE\\\\\\\"] = \\\\\\\"no conversion\\\\\\\";\\n ColorConversion2[\\\\\\\"GAMMA_TO_LINEAR\\\\\\\"] = \\\\\\\"gamma -> linear\\\\\\\";\\n ColorConversion2[\\\\\\\"LINEAR_TO_GAMMA\\\\\\\"] = \\\\\\\"linear -> gamma\\\\\\\";\\n ColorConversion2[\\\\\\\"SRGB_TO_LINEAR\\\\\\\"] = \\\\\\\"sRGB -> linear\\\\\\\";\\n ColorConversion2[\\\\\\\"LINEAR_TO_SRGB\\\\\\\"] = \\\\\\\"linear -> sRGB\\\\\\\";\\n})(ColorConversion || (ColorConversion = {}));\\nvar COLOR_CONVERSIONS = [\\n ColorConversion.NONE,\\n ColorConversion.GAMMA_TO_LINEAR,\\n ColorConversion.LINEAR_TO_GAMMA,\\n ColorConversion.SRGB_TO_LINEAR,\\n ColorConversion.LINEAR_TO_SRGB\\n];\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/params/Color.ts\\nvar COMPONENT_NAMES_COLOR = [\\\\\\\"r\\\\\\\", \\\\\\\"g\\\\\\\", \\\\\\\"b\\\\\\\"];\\nvar ColorParam = class extends TypedMultipleParam {\\n constructor() {\\n super(...arguments);\\n this._value = new Color();\\n this._value_pre_conversion = new Color();\\n this._value_serialized_dirty = false;\\n this._value_serialized = [0, 0, 0];\\n this._value_pre_conversion_serialized = [0, 0, 0];\\n this._copied_value = [0, 0, 0];\\n }\\n static type() {\\n return ParamType.COLOR;\\n }\\n componentNames() {\\n return COMPONENT_NAMES_COLOR;\\n }\\n defaultValueSerialized() {\\n if (CoreType.isArray(this._default_value)) {\\n return this._default_value;\\n } else {\\n return this._default_value.toArray();\\n }\\n }\\n valueSerialized() {\\n this._update_value_serialized_if_required();\\n return this._value_serialized;\\n }\\n valuePreConversionSerialized() {\\n this._update_value_serialized_if_required();\\n return this._value_pre_conversion_serialized;\\n }\\n _copy_value(param) {\\n param.value.toArray(this._copied_value);\\n this.set(this._copied_value);\\n }\\n _clone_raw_input(raw_input) {\\n if (raw_input instanceof Color) {\\n return raw_input.clone();\\n } else {\\n const new_array = [raw_input[0], raw_input[1], raw_input[2]];\\n if (new_array[0] == null) {\\n new_array[0] = new_array[0] || 0;\\n }\\n if (new_array[1] == null) {\\n new_array[1] = new_array[1] || new_array[0];\\n }\\n if (new_array[2] == null) {\\n new_array[2] = new_array[2] || new_array[1];\\n }\\n return new_array;\\n }\\n }\\n static are_raw_input_equal(raw_input1, raw_input2) {\\n if (raw_input1 instanceof Color) {\\n if (raw_input2 instanceof Color) {\\n return raw_input1.equals(raw_input2);\\n } else {\\n return raw_input1.r == raw_input2[0] && raw_input1.g == raw_input2[1] && raw_input1.b == raw_input2[2];\\n }\\n } else {\\n if (raw_input2 instanceof Color) {\\n return raw_input1[0] == raw_input2.r && raw_input1[1] == raw_input2.g && raw_input1[2] == raw_input2.b;\\n } else {\\n return raw_input1[0] == raw_input2[0] && raw_input1[1] == raw_input2[1] && raw_input1[2] == raw_input2[2];\\n }\\n }\\n }\\n static are_values_equal(val1, val2) {\\n return val1.equals(val2);\\n }\\n initComponents() {\\n super.initComponents();\\n this.r = this.components[0];\\n this.g = this.components[1];\\n this.b = this.components[2];\\n this._value_serialized_dirty = true;\\n }\\n _update_value_serialized_if_required() {\\n if (!this._value_serialized_dirty) {\\n return;\\n }\\n this._value_serialized[0] = this._value.r;\\n this._value_serialized[1] = this._value.g;\\n this._value_serialized[2] = this._value.b;\\n this._value_pre_conversion_serialized[0] = this._value_pre_conversion.r;\\n this._value_pre_conversion_serialized[1] = this._value_pre_conversion.g;\\n this._value_pre_conversion_serialized[2] = this._value_pre_conversion.b;\\n }\\n valuePreConversion() {\\n return this._value_pre_conversion;\\n }\\n set_value_from_components() {\\n this._value_pre_conversion.r = this.r.value;\\n this._value_pre_conversion.g = this.g.value;\\n this._value_pre_conversion.b = this.b.value;\\n this._value.copy(this._value_pre_conversion);\\n const conversion = this.options.colorConversion();\\n if (conversion != null && conversion != ColorConversion.NONE) {\\n switch (conversion) {\\n case ColorConversion.GAMMA_TO_LINEAR: {\\n this._value.convertGammaToLinear();\\n return;\\n }\\n case ColorConversion.LINEAR_TO_GAMMA: {\\n this._value.convertLinearToGamma();\\n return;\\n }\\n case ColorConversion.SRGB_TO_LINEAR: {\\n this._value.convertSRGBToLinear();\\n return;\\n }\\n case ColorConversion.LINEAR_TO_SRGB: {\\n this._value.convertLinearToSRGB();\\n return;\\n }\\n }\\n TypeAssert.unreachable(conversion);\\n }\\n this._value_serialized_dirty = true;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/params/Folder.ts\\nvar FolderParam = class extends TypedParam {\\n static type() {\\n return ParamType.FOLDER;\\n }\\n defaultValueSerialized() {\\n return this._default_value;\\n }\\n rawInputSerialized() {\\n return this._raw_input;\\n }\\n valueSerialized() {\\n return this.value;\\n }\\n _copy_value(param) {\\n }\\n static are_raw_input_equal(raw_input1, raw_input2) {\\n return true;\\n }\\n static are_values_equal(val1, val2) {\\n return true;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/params/Integer.ts\\nvar IntegerParam = class extends TypedNumericParam {\\n static type() {\\n return ParamType.INTEGER;\\n }\\n defaultValueSerialized() {\\n return this._default_value;\\n }\\n rawInputSerialized() {\\n return this._raw_input;\\n }\\n valueSerialized() {\\n return this.value;\\n }\\n _copy_value(param) {\\n this.set(param.valueSerialized());\\n }\\n _prefilter_invalid_raw_input(raw_input) {\\n if (CoreType.isArray(raw_input)) {\\n return raw_input[0];\\n }\\n if (CoreType.isString(raw_input) && CoreString.isNumber(raw_input)) {\\n return parseInt(raw_input);\\n }\\n return raw_input;\\n }\\n static are_raw_input_equal(raw_input1, raw_input2) {\\n return raw_input1 == raw_input2;\\n }\\n static are_values_equal(val1, val2) {\\n return val1 == val2;\\n }\\n static convert(raw_val) {\\n if (CoreType.isNumber(raw_val)) {\\n return Math.round(raw_val);\\n } else {\\n if (CoreType.isBoolean(raw_val)) {\\n return raw_val ? 1 : 0;\\n } else {\\n if (CoreString.isNumber(raw_val)) {\\n const parsed = parseInt(raw_val);\\n if (CoreType.isNumber(parsed)) {\\n return parsed;\\n }\\n }\\n }\\n return null;\\n }\\n }\\n convert(raw_val) {\\n const result = IntegerParam.convert(raw_val);\\n if (result) {\\n return this.options.ensureInRange(result);\\n } else {\\n return result;\\n }\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/core/DecomposedPath.ts\\nvar DecomposedPath = class {\\n constructor() {\\n this._index = -1;\\n this._path_elements = [];\\n this._named_nodes = [];\\n this._graph_node_ids = [];\\n this._node_element_by_graph_node_id = new Map();\\n }\\n reset() {\\n this._index = -1;\\n this._path_elements = [];\\n this._named_nodes = [];\\n this._graph_node_ids = [];\\n this._node_element_by_graph_node_id.clear();\\n }\\n add_node(name, node) {\\n this._index += 1;\\n if (name == node.name()) {\\n this._named_nodes[this._index] = node;\\n }\\n this._graph_node_ids[this._index] = node.graphNodeId();\\n this._node_element_by_graph_node_id.set(node.graphNodeId(), name);\\n }\\n add_path_element(path_element) {\\n this._index += 1;\\n this._path_elements[this._index] = path_element;\\n }\\n named_graph_nodes() {\\n return this._named_nodes;\\n }\\n named_nodes() {\\n const nodes = [];\\n for (let graph_node of this._named_nodes) {\\n if (graph_node) {\\n const node = graph_node;\\n if (node.nameController) {\\n nodes.push(node);\\n }\\n }\\n }\\n return nodes;\\n }\\n update_from_name_change(node) {\\n const named_graph_node_ids = this._named_nodes.map((n) => n?.graphNodeId());\\n if (named_graph_node_ids.includes(node.graphNodeId())) {\\n this._node_element_by_graph_node_id.set(node.graphNodeId(), node.name());\\n }\\n }\\n to_path() {\\n const elements = new Array(this._index);\\n for (let i = 0; i <= this._index; i++) {\\n const node = this._named_nodes[i];\\n if (node) {\\n const node_name = this._node_element_by_graph_node_id.get(node.graphNodeId());\\n if (node_name) {\\n elements[i] = node_name;\\n }\\n } else {\\n const path_element = this._path_elements[i];\\n if (path_element) {\\n elements[i] = path_element;\\n }\\n }\\n }\\n let joined_path = elements.join(CoreWalker.SEPARATOR);\\n const first_char = joined_path[0];\\n if (first_char) {\\n if (!CoreWalker.NON_LETTER_PREFIXES.includes(first_char)) {\\n joined_path = `${CoreWalker.SEPARATOR}${joined_path}`;\\n }\\n }\\n return joined_path;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/params/_BasePath.ts\\nvar TypedPathParam = class extends TypedParam {\\n constructor() {\\n super(...arguments);\\n this.decomposed_path = new DecomposedPath();\\n }\\n _handleReferences(node, path) {\\n this.scene().referencesController.setNamedNodesFromParam(this);\\n if (node) {\\n this.scene().referencesController.setReferenceFromParam(this, node);\\n } else {\\n this.scene().missingExpressionReferencesController.register(this, path);\\n }\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/params/OperatorPath.ts\\nvar OperatorPathMode;\\n(function(OperatorPathMode2) {\\n OperatorPathMode2[\\\\\\\"NODE\\\\\\\"] = \\\\\\\"NODE\\\\\\\";\\n OperatorPathMode2[\\\\\\\"PARAM\\\\\\\"] = \\\\\\\"PARAM\\\\\\\";\\n})(OperatorPathMode || (OperatorPathMode = {}));\\nvar OperatorPathParam = class extends TypedPathParam {\\n constructor() {\\n super(...arguments);\\n this._found_node = null;\\n this._found_node_with_expected_type = null;\\n this._found_param = null;\\n this._found_param_with_expected_type = null;\\n }\\n static type() {\\n return ParamType.OPERATOR_PATH;\\n }\\n defaultValueSerialized() {\\n return this._default_value;\\n }\\n rawInputSerialized() {\\n return `${this._raw_input}`;\\n }\\n valueSerialized() {\\n return `${this.value}`;\\n }\\n _copy_value(param) {\\n this.set(param.valueSerialized());\\n }\\n static are_raw_input_equal(raw_input1, raw_input2) {\\n return raw_input1 == raw_input2;\\n }\\n static are_values_equal(val1, val2) {\\n return val1 == val2;\\n }\\n isDefault() {\\n return this._value == this._default_value;\\n }\\n setNode(node) {\\n this.set(node.path());\\n }\\n processRawInput() {\\n if (this._value != this._raw_input) {\\n this._value = this._raw_input;\\n this.setDirty();\\n this.emitController.emit(ParamEvent.VALUE_UPDATED);\\n }\\n }\\n async processComputation() {\\n this.find_target();\\n }\\n find_target() {\\n if (!this.node) {\\n return;\\n }\\n const path = this._value;\\n let node = null;\\n let param = null;\\n const path_non_empty = path != null && path !== \\\\\\\"\\\\\\\";\\n const mode = this.options.paramSelectionOptions() ? OperatorPathMode.PARAM : OperatorPathMode.NODE;\\n this.scene().referencesController.resetReferenceFromParam(this);\\n this.decomposed_path.reset();\\n if (path_non_empty) {\\n if (mode == OperatorPathMode.PARAM) {\\n param = CoreWalker.findParam(this.node, path, this.decomposed_path);\\n } else {\\n node = CoreWalker.findNode(this.node, path, this.decomposed_path);\\n }\\n }\\n const current_found_entity = mode == OperatorPathMode.PARAM ? this._found_param : this._found_node;\\n const newly_found_entity = mode == OperatorPathMode.PARAM ? param : node;\\n this._handleReferences(node, path);\\n if (current_found_entity?.graphNodeId() !== newly_found_entity?.graphNodeId()) {\\n const dependent_on_found_node = this.options.dependentOnFoundNode();\\n if (this._found_node) {\\n if (dependent_on_found_node) {\\n this.removeGraphInput(this._found_node);\\n } else {\\n }\\n }\\n if (mode == OperatorPathMode.PARAM) {\\n this._found_param = param;\\n this._found_node = null;\\n } else {\\n this._found_node = node;\\n this._found_param = null;\\n }\\n if (node) {\\n this._assign_found_node(node);\\n }\\n if (param) {\\n this._assign_found_param(param);\\n }\\n this.options.executeCallback();\\n }\\n this.removeDirtyState();\\n }\\n _assign_found_node(node) {\\n const dependent_on_found_node = this.options.dependentOnFoundNode();\\n if (this._is_node_expected_context(node)) {\\n if (this._is_node_expected_type(node)) {\\n this._found_node_with_expected_type = node;\\n if (dependent_on_found_node) {\\n this.addGraphInput(node);\\n }\\n } else {\\n this.states.error.set(`node type is ${node.type()} but the params expects one of ${(this._expected_node_types() || []).join(\\\\\\\", \\\\\\\")}`);\\n }\\n } else {\\n this.states.error.set(`node context is ${node.context()} but the params expects a ${this._expected_context()}`);\\n }\\n }\\n _assign_found_param(param) {\\n if (this._is_param_expected_type(param)) {\\n this._found_param_with_expected_type = param;\\n } else {\\n this.states.error.set(`param type is ${param.type()} but the params expects a ${this._expected_param_type()}`);\\n }\\n }\\n found_node() {\\n return this._found_node;\\n }\\n found_param() {\\n return this._found_param;\\n }\\n found_node_with_context(context) {\\n return this._found_node_with_expected_type;\\n }\\n found_node_with_context_and_type(context, type_or_types) {\\n const node = this.found_node_with_context(context);\\n if (node) {\\n if (CoreType.isArray(type_or_types)) {\\n for (let type of type_or_types) {\\n if (node.type() == type) {\\n return node;\\n }\\n }\\n this.states.error.set(`expected node type to be ${type_or_types.join(\\\\\\\", \\\\\\\")}, but was instead ${node.type()}`);\\n } else {\\n const type = type_or_types;\\n if (node.type() == type) {\\n return node;\\n } else {\\n this.states.error.set(`expected node type to be ${type}, but was instead ${node.type()}`);\\n }\\n }\\n }\\n }\\n found_param_with_type(type) {\\n if (this._found_param_with_expected_type) {\\n return this._found_param_with_expected_type;\\n }\\n }\\n found_node_with_expected_type() {\\n return this._found_node_with_expected_type;\\n }\\n _expected_context() {\\n return this.options.nodeSelectionContext();\\n }\\n _is_node_expected_context(node) {\\n const expected_context = this._expected_context();\\n if (expected_context == null) {\\n return true;\\n }\\n const node_context = node.parent()?.childrenController?.context;\\n return expected_context == node_context;\\n }\\n _expected_node_types() {\\n return this.options.nodeSelectionTypes();\\n }\\n _expected_param_type() {\\n return this.options.paramSelectionType();\\n }\\n _is_node_expected_type(node) {\\n const expected_types = this._expected_node_types();\\n if (expected_types == null) {\\n return true;\\n }\\n return expected_types?.includes(node.type());\\n }\\n _is_param_expected_type(param) {\\n const expected_types = this._expected_node_types();\\n if (expected_types == null) {\\n return true;\\n }\\n return expected_types.includes(param.type());\\n }\\n notifyPathRebuildRequired(node) {\\n this.decomposed_path.update_from_name_change(node);\\n const new_path = this.decomposed_path.to_path();\\n this.set(new_path);\\n }\\n notifyTargetParamOwnerParamsUpdated(node) {\\n this.setDirty();\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/params/ParamPath.ts\\nvar ParamPathParam = class extends TypedPathParam {\\n static type() {\\n return ParamType.PARAM_PATH;\\n }\\n initialize_param() {\\n this._value = new TypedParamPathParamValue();\\n }\\n defaultValueSerialized() {\\n return this._default_value;\\n }\\n rawInputSerialized() {\\n return `${this._raw_input}`;\\n }\\n valueSerialized() {\\n return `${this.value}`;\\n }\\n _copy_value(param) {\\n this.set(param.valueSerialized());\\n }\\n static are_raw_input_equal(raw_input1, raw_input2) {\\n return raw_input1 == raw_input2;\\n }\\n static are_values_equal(val1, val2) {\\n return val1 == val2;\\n }\\n isDefault() {\\n return this._raw_input == this._default_value;\\n }\\n setParam(param) {\\n this.set(param.path());\\n }\\n processRawInput() {\\n if (this._value.path() != this._raw_input) {\\n this._value.set_path(this._raw_input);\\n this.find_target();\\n this.setDirty();\\n this.emitController.emit(ParamEvent.VALUE_UPDATED);\\n }\\n }\\n async processComputation() {\\n this.find_target();\\n }\\n find_target() {\\n if (!this.node) {\\n return;\\n }\\n const path = this._raw_input;\\n let param = null;\\n const path_non_empty = path != null && path !== \\\\\\\"\\\\\\\";\\n this.scene().referencesController.resetReferenceFromParam(this);\\n this.decomposed_path.reset();\\n if (path_non_empty) {\\n param = CoreWalker.findParam(this.node, path, this.decomposed_path);\\n }\\n const current_found_entity = this._value.param();\\n const newly_found_entity = param;\\n this._handleReferences(param, path);\\n if (current_found_entity?.graphNodeId() !== newly_found_entity?.graphNodeId()) {\\n const dependent_on_found_node = this.options.dependentOnFoundNode();\\n const previously_found_node = this._value.param();\\n if (previously_found_node) {\\n if (dependent_on_found_node) {\\n this.removeGraphInput(previously_found_node);\\n } else {\\n }\\n }\\n if (param) {\\n this._assign_found_node(param);\\n } else {\\n this._value.set_param(null);\\n }\\n this.options.executeCallback();\\n }\\n this.removeDirtyState();\\n }\\n _assign_found_node(param) {\\n const dependent_on_found_node = this.options.dependentOnFoundNode();\\n this._value.set_param(param);\\n if (dependent_on_found_node) {\\n this.addGraphInput(param);\\n }\\n }\\n notifyPathRebuildRequired(param) {\\n this.decomposed_path.update_from_name_change(param);\\n const new_path = this.decomposed_path.to_path();\\n this.set(new_path);\\n }\\n notifyTargetParamOwnerParamsUpdated(node) {\\n this.setDirty();\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/params/NodePath.ts\\nvar NodePathParam = class extends TypedPathParam {\\n static type() {\\n return ParamType.NODE_PATH;\\n }\\n initialize_param() {\\n this._value = new TypedNodePathParamValue();\\n }\\n defaultValueSerialized() {\\n return this._default_value;\\n }\\n rawInputSerialized() {\\n return `${this._raw_input}`;\\n }\\n valueSerialized() {\\n return `${this.value}`;\\n }\\n _copy_value(param) {\\n this.set(param.valueSerialized());\\n }\\n static are_raw_input_equal(raw_input1, raw_input2) {\\n return raw_input1 == raw_input2;\\n }\\n static are_values_equal(val1, val2) {\\n return val1 == val2;\\n }\\n isDefault() {\\n return this._raw_input == this._default_value;\\n }\\n setNode(node) {\\n this.set(node.path());\\n }\\n processRawInput() {\\n if (this._value.path() != this._raw_input) {\\n this._value.set_path(this._raw_input);\\n this._findTarget();\\n this.setDirty();\\n this.emitController.emit(ParamEvent.VALUE_UPDATED);\\n }\\n }\\n async processComputation() {\\n this._findTarget();\\n }\\n _findTarget() {\\n if (!this.node) {\\n return;\\n }\\n const path = this._raw_input;\\n let node = null;\\n const path_non_empty = path != null && path !== \\\\\\\"\\\\\\\";\\n this.scene().referencesController.resetReferenceFromParam(this);\\n this.decomposed_path.reset();\\n if (path_non_empty) {\\n node = CoreWalker.findNode(this.node, path, this.decomposed_path);\\n }\\n const current_found_entity = this._value.node();\\n const newly_found_entity = node;\\n this._handleReferences(node, path);\\n if (current_found_entity?.graphNodeId() !== newly_found_entity?.graphNodeId()) {\\n const dependent_on_found_node = this.options.dependentOnFoundNode();\\n const previously_found_node = this._value.node();\\n if (previously_found_node) {\\n if (dependent_on_found_node) {\\n this.removeGraphInput(previously_found_node);\\n } else {\\n }\\n }\\n if (node) {\\n this._assign_found_node(node);\\n } else {\\n this._value.set_node(null);\\n }\\n this.options.executeCallback();\\n }\\n if (path_non_empty && !node && this.scene().loadingController.loaded()) {\\n if (path_non_empty) {\\n this.states.error.set(`no node found at path '${path}'`);\\n }\\n }\\n this.removeDirtyState();\\n }\\n _assign_found_node(node) {\\n const dependent_on_found_node = this.options.dependentOnFoundNode();\\n if (this._isNodeExpectedContext(node)) {\\n if (this._is_node_expected_type(node)) {\\n this.states.error.clear();\\n this._value.set_node(node);\\n if (dependent_on_found_node) {\\n this.addGraphInput(node);\\n }\\n } else {\\n this.states.error.set(`node type is ${node.type()} but the params expects one of ${(this._expected_node_types() || []).join(\\\\\\\", \\\\\\\")}`);\\n }\\n } else {\\n this.states.error.set(`node context is ${node.context()} but the params expects a ${this._expectedContext()}`);\\n }\\n }\\n _expectedContext() {\\n return this.options.nodeSelectionContext();\\n }\\n _isNodeExpectedContext(node) {\\n const expected_context = this._expectedContext();\\n if (expected_context == null) {\\n return true;\\n }\\n const node_context = node.parent()?.childrenController?.context;\\n return expected_context == node_context;\\n }\\n _expected_node_types() {\\n return this.options.nodeSelectionTypes();\\n }\\n _is_node_expected_type(node) {\\n const expected_types = this._expected_node_types();\\n if (expected_types == null) {\\n return true;\\n }\\n return expected_types?.includes(node.type());\\n }\\n notifyPathRebuildRequired(node) {\\n this.decomposed_path.update_from_name_change(node);\\n const newPath = this.decomposed_path.to_path();\\n this.set(newPath);\\n }\\n notifyTargetParamOwnerParamsUpdated(node) {\\n this.setDirty();\\n }\\n};\\n\\n// ../../../node_modules/three/src/textures/DataTexture.js\\nvar DataTexture = class extends Texture {\\n constructor(data = null, width = 1, height = 1, format, type, mapping, wrapS, wrapT, magFilter = NearestFilter, minFilter = NearestFilter, anisotropy, encoding) {\\n super(null, mapping, wrapS, wrapT, magFilter, minFilter, format, type, anisotropy, encoding);\\n this.image = {data, width, height};\\n this.magFilter = magFilter;\\n this.minFilter = minFilter;\\n this.generateMipmaps = false;\\n this.flipY = false;\\n this.unpackAlignment = 1;\\n this.needsUpdate = true;\\n }\\n};\\nDataTexture.prototype.isDataTexture = true;\\n\\n// ../../../node_modules/three/src/math/Interpolant.js\\nvar Interpolant = class {\\n constructor(parameterPositions, sampleValues, sampleSize, resultBuffer) {\\n this.parameterPositions = parameterPositions;\\n this._cachedIndex = 0;\\n this.resultBuffer = resultBuffer !== void 0 ? resultBuffer : new sampleValues.constructor(sampleSize);\\n this.sampleValues = sampleValues;\\n this.valueSize = sampleSize;\\n this.settings = null;\\n this.DefaultSettings_ = {};\\n }\\n evaluate(t) {\\n const pp = this.parameterPositions;\\n let i1 = this._cachedIndex, t1 = pp[i1], t0 = pp[i1 - 1];\\n validate_interval: {\\n seek: {\\n let right;\\n linear_scan: {\\n forward_scan:\\n if (!(t < t1)) {\\n for (let giveUpAt = i1 + 2; ; ) {\\n if (t1 === void 0) {\\n if (t < t0)\\n break forward_scan;\\n i1 = pp.length;\\n this._cachedIndex = i1;\\n return this.afterEnd_(i1 - 1, t, t0);\\n }\\n if (i1 === giveUpAt)\\n break;\\n t0 = t1;\\n t1 = pp[++i1];\\n if (t < t1) {\\n break seek;\\n }\\n }\\n right = pp.length;\\n break linear_scan;\\n }\\n if (!(t >= t0)) {\\n const t1global = pp[1];\\n if (t < t1global) {\\n i1 = 2;\\n t0 = t1global;\\n }\\n for (let giveUpAt = i1 - 2; ; ) {\\n if (t0 === void 0) {\\n this._cachedIndex = 0;\\n return this.beforeStart_(0, t, t1);\\n }\\n if (i1 === giveUpAt)\\n break;\\n t1 = t0;\\n t0 = pp[--i1 - 1];\\n if (t >= t0) {\\n break seek;\\n }\\n }\\n right = i1;\\n i1 = 0;\\n break linear_scan;\\n }\\n break validate_interval;\\n }\\n while (i1 < right) {\\n const mid = i1 + right >>> 1;\\n if (t < pp[mid]) {\\n right = mid;\\n } else {\\n i1 = mid + 1;\\n }\\n }\\n t1 = pp[i1];\\n t0 = pp[i1 - 1];\\n if (t0 === void 0) {\\n this._cachedIndex = 0;\\n return this.beforeStart_(0, t, t1);\\n }\\n if (t1 === void 0) {\\n i1 = pp.length;\\n this._cachedIndex = i1;\\n return this.afterEnd_(i1 - 1, t0, t);\\n }\\n }\\n this._cachedIndex = i1;\\n this.intervalChanged_(i1, t0, t1);\\n }\\n return this.interpolate_(i1, t0, t, t1);\\n }\\n getSettings_() {\\n return this.settings || this.DefaultSettings_;\\n }\\n copySampleValue_(index) {\\n const result = this.resultBuffer, values = this.sampleValues, stride = this.valueSize, offset = index * stride;\\n for (let i = 0; i !== stride; ++i) {\\n result[i] = values[offset + i];\\n }\\n return result;\\n }\\n interpolate_() {\\n throw new Error(\\\\\\\"call to abstract method\\\\\\\");\\n }\\n intervalChanged_() {\\n }\\n};\\nInterpolant.prototype.beforeStart_ = Interpolant.prototype.copySampleValue_;\\nInterpolant.prototype.afterEnd_ = Interpolant.prototype.copySampleValue_;\\n\\n// ../../../node_modules/three/src/math/interpolants/CubicInterpolant.js\\nvar CubicInterpolant = class extends Interpolant {\\n constructor(parameterPositions, sampleValues, sampleSize, resultBuffer) {\\n super(parameterPositions, sampleValues, sampleSize, resultBuffer);\\n this._weightPrev = -0;\\n this._offsetPrev = -0;\\n this._weightNext = -0;\\n this._offsetNext = -0;\\n this.DefaultSettings_ = {\\n endingStart: ZeroCurvatureEnding,\\n endingEnd: ZeroCurvatureEnding\\n };\\n }\\n intervalChanged_(i1, t0, t1) {\\n const pp = this.parameterPositions;\\n let iPrev = i1 - 2, iNext = i1 + 1, tPrev = pp[iPrev], tNext = pp[iNext];\\n if (tPrev === void 0) {\\n switch (this.getSettings_().endingStart) {\\n case ZeroSlopeEnding:\\n iPrev = i1;\\n tPrev = 2 * t0 - t1;\\n break;\\n case WrapAroundEnding:\\n iPrev = pp.length - 2;\\n tPrev = t0 + pp[iPrev] - pp[iPrev + 1];\\n break;\\n default:\\n iPrev = i1;\\n tPrev = t1;\\n }\\n }\\n if (tNext === void 0) {\\n switch (this.getSettings_().endingEnd) {\\n case ZeroSlopeEnding:\\n iNext = i1;\\n tNext = 2 * t1 - t0;\\n break;\\n case WrapAroundEnding:\\n iNext = 1;\\n tNext = t1 + pp[1] - pp[0];\\n break;\\n default:\\n iNext = i1 - 1;\\n tNext = t0;\\n }\\n }\\n const halfDt = (t1 - t0) * 0.5, stride = this.valueSize;\\n this._weightPrev = halfDt / (t0 - tPrev);\\n this._weightNext = halfDt / (tNext - t1);\\n this._offsetPrev = iPrev * stride;\\n this._offsetNext = iNext * stride;\\n }\\n interpolate_(i1, t0, t, t1) {\\n const result = this.resultBuffer, values = this.sampleValues, stride = this.valueSize, o1 = i1 * stride, o0 = o1 - stride, oP = this._offsetPrev, oN = this._offsetNext, wP = this._weightPrev, wN = this._weightNext, p = (t - t0) / (t1 - t0), pp = p * p, ppp = pp * p;\\n const sP = -wP * ppp + 2 * wP * pp - wP * p;\\n const s0 = (1 + wP) * ppp + (-1.5 - 2 * wP) * pp + (-0.5 + wP) * p + 1;\\n const s1 = (-1 - wN) * ppp + (1.5 + wN) * pp + 0.5 * p;\\n const sN = wN * ppp - wN * pp;\\n for (let i = 0; i !== stride; ++i) {\\n result[i] = sP * values[oP + i] + s0 * values[o0 + i] + s1 * values[o1 + i] + sN * values[oN + i];\\n }\\n return result;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/params/ramp/RampValue.ts\\nvar RampPoint = class {\\n constructor(_position3 = 0, _value = 0) {\\n this._position = _position3;\\n this._value = _value;\\n }\\n toJSON() {\\n return {\\n position: this._position,\\n value: this._value\\n };\\n }\\n position() {\\n return this._position;\\n }\\n value() {\\n return this._value;\\n }\\n copy(point) {\\n this._position = point.position();\\n this._value = point.value();\\n }\\n clone() {\\n const point = new RampPoint();\\n point.copy(this);\\n return point;\\n }\\n isEqual(other_point) {\\n return this._position == other_point.position() && this._value == other_point.value();\\n }\\n isEqualJSON(json) {\\n return this._position == json.position && this._value == json.value;\\n }\\n fromJSON(json) {\\n this._position = json.position;\\n this._value = json.value;\\n }\\n static areEqualJSON(json1, json2) {\\n return json1.position == json2.position && json1.value == json2.value;\\n }\\n static fromJSON(json) {\\n return new RampPoint(json.position, json.value);\\n }\\n};\\nvar RampInterpolation;\\n(function(RampInterpolation2) {\\n RampInterpolation2[\\\\\\\"LINEAR\\\\\\\"] = \\\\\\\"linear\\\\\\\";\\n})(RampInterpolation || (RampInterpolation = {}));\\nvar RampValue = class {\\n constructor(_interpolation = RampInterpolation.LINEAR, _points2 = []) {\\n this._interpolation = _interpolation;\\n this._points = _points2;\\n this._uuid = generateUUID();\\n }\\n uuid() {\\n return this._uuid;\\n }\\n interpolation() {\\n return this._interpolation;\\n }\\n points() {\\n return this._points;\\n }\\n static fromJSON(json) {\\n const points2 = [];\\n for (let jsonPoint of json.points) {\\n points2.push(RampPoint.fromJSON(jsonPoint));\\n }\\n return new RampValue(json.interpolation, points2);\\n }\\n toJSON() {\\n return {\\n interpolation: this._interpolation,\\n points: this._points.map((p) => p.toJSON())\\n };\\n }\\n clone() {\\n const ramp = new RampValue();\\n ramp.copy(this);\\n return ramp;\\n }\\n copy(ramp) {\\n this._interpolation = ramp.interpolation();\\n let index = 0;\\n for (let point of ramp.points()) {\\n const current_point = this._points[index];\\n if (current_point) {\\n current_point.copy(point);\\n } else {\\n this._points.push(point.clone());\\n }\\n index += 1;\\n }\\n }\\n is_equal(other_ramp_value) {\\n if (this._interpolation != other_ramp_value.interpolation()) {\\n return false;\\n }\\n const other_points = other_ramp_value.points();\\n if (this._points.length != other_points.length) {\\n return false;\\n }\\n let index = 0;\\n for (let point of this._points) {\\n const other_point = other_points[index];\\n if (!point.isEqual(other_point)) {\\n return false;\\n }\\n index += 1;\\n }\\n return true;\\n }\\n is_equal_json(json) {\\n if (this._interpolation != json.interpolation) {\\n return false;\\n }\\n if (this._points.length != json.points.length) {\\n return false;\\n }\\n let index = 0;\\n for (let point of this._points) {\\n const other_point = json.points[index];\\n if (!point.isEqualJSON(other_point)) {\\n return false;\\n }\\n index += 1;\\n }\\n return true;\\n }\\n static are_json_equal(json1, json2) {\\n if (json1.interpolation != json2.interpolation) {\\n return false;\\n }\\n if (json1.points.length != json2.points.length) {\\n return false;\\n }\\n let index = 0;\\n for (let point1 of json1.points) {\\n const point2 = json2.points[index];\\n if (!RampPoint.areEqualJSON(point1, point2)) {\\n return false;\\n }\\n index += 1;\\n }\\n return true;\\n }\\n from_json(json) {\\n this._interpolation = json.interpolation;\\n let index = 0;\\n for (let json_point of json.points) {\\n const current_point = this._points[index];\\n if (current_point) {\\n current_point.fromJSON(json_point);\\n } else {\\n this._points.push(RampPoint.fromJSON(json_point));\\n }\\n index += 1;\\n }\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/params/Ramp.ts\\nvar TEXTURE_WIDTH = 1024;\\nvar TEXTURE_HEIGHT = 1;\\nvar TEXTURE_SIZE = TEXTURE_WIDTH * TEXTURE_HEIGHT;\\nvar TEXTURE_BYTES_MULT = 255;\\nvar RampParam2 = class extends TypedParam {\\n constructor() {\\n super(...arguments);\\n this._texture_data = new Uint8Array(3 * TEXTURE_SIZE);\\n this._ramp_texture = new DataTexture(this._texture_data, TEXTURE_WIDTH, TEXTURE_HEIGHT, RGBFormat);\\n }\\n static type() {\\n return ParamType.RAMP;\\n }\\n defaultValueSerialized() {\\n if (this._default_value instanceof RampValue) {\\n return this._default_value.toJSON();\\n } else {\\n return this._default_value;\\n }\\n }\\n _clone_raw_input(raw_input) {\\n if (raw_input instanceof RampValue) {\\n return raw_input.clone();\\n } else {\\n return RampValue.fromJSON(raw_input).toJSON();\\n }\\n }\\n rawInputSerialized() {\\n if (this._raw_input instanceof RampValue) {\\n return this._raw_input.toJSON();\\n } else {\\n return RampValue.fromJSON(this._raw_input).toJSON();\\n }\\n }\\n valueSerialized() {\\n return this.value.toJSON();\\n }\\n _copy_value(param) {\\n this.set(param.valueSerialized());\\n }\\n static are_raw_input_equal(raw_input1, raw_input2) {\\n if (raw_input1 instanceof RampValue) {\\n if (raw_input2 instanceof RampValue) {\\n return raw_input1.is_equal(raw_input2);\\n } else {\\n return raw_input1.is_equal_json(raw_input2);\\n }\\n } else {\\n if (raw_input2 instanceof RampValue) {\\n return raw_input2.is_equal_json(raw_input1);\\n } else {\\n return RampValue.are_json_equal(raw_input1, raw_input2);\\n }\\n }\\n }\\n static are_values_equal(val1, val2) {\\n return val1.is_equal(val2);\\n }\\n isDefault() {\\n if (this._default_value instanceof RampValue) {\\n return this.value.is_equal(this._default_value);\\n } else {\\n return this.value.is_equal_json(this._default_value);\\n }\\n }\\n processRawInput() {\\n if (this._raw_input instanceof RampValue) {\\n if (!this._value) {\\n this._value = this._raw_input;\\n } else {\\n this._value.copy(this._raw_input);\\n }\\n } else {\\n if (!this._value) {\\n this._value = RampValue.fromJSON(this._raw_input);\\n } else {\\n this._value.from_json(this._raw_input);\\n }\\n }\\n this._resetRampInterpolant();\\n this._updateRampTexture();\\n this.options.executeCallback();\\n this.emitController.emit(ParamEvent.VALUE_UPDATED);\\n this.setSuccessorsDirty(this);\\n }\\n hasExpression() {\\n return false;\\n }\\n _resetRampInterpolant() {\\n this._ramp_interpolant = void 0;\\n }\\n rampTexture() {\\n return this._ramp_texture;\\n }\\n _updateRampTexture() {\\n this._updateRampTextureData();\\n this.rampTexture().needsUpdate = true;\\n }\\n _updateRampTextureData() {\\n let stride = 0;\\n let position = 0;\\n let value = 0;\\n for (var i = 0; i < TEXTURE_SIZE; i++) {\\n stride = i * 3;\\n position = i / TEXTURE_WIDTH;\\n value = this.valueAtPosition(position);\\n if (value <= 0) {\\n this._texture_data[stride + 0] = (clamp(value, -1, 0) + 1) * TEXTURE_BYTES_MULT;\\n this._texture_data[stride + 1] = 0;\\n this._texture_data[stride + 2] = 0;\\n } else {\\n if (value <= 1) {\\n this._texture_data[stride + 0] = TEXTURE_BYTES_MULT;\\n this._texture_data[stride + 1] = clamp(value, 0, 1) * TEXTURE_BYTES_MULT;\\n this._texture_data[stride + 2] = 0;\\n } else {\\n this._texture_data[stride + 0] = TEXTURE_BYTES_MULT;\\n this._texture_data[stride + 1] = TEXTURE_BYTES_MULT;\\n this._texture_data[stride + 2] = (clamp(value, 1, 2) - 1) * TEXTURE_BYTES_MULT;\\n }\\n }\\n }\\n }\\n static createInterpolant(positions, values) {\\n const valuesCount = 1;\\n const interpolatedValues = new Float32Array(valuesCount);\\n return new CubicInterpolant(positions, values, valuesCount, interpolatedValues);\\n }\\n interpolant() {\\n return this._ramp_interpolant = this._ramp_interpolant || this._createInterpolant();\\n }\\n _createInterpolant() {\\n const points2 = this.value.points();\\n const sortedPoints = ArrayUtils.sortBy(points2, (point) => point.position());\\n const positions = new Float32Array(sortedPoints.length);\\n const values = new Float32Array(sortedPoints.length);\\n let i = 0;\\n for (let sortedPoint of sortedPoints) {\\n positions[i] = sortedPoint.position();\\n values[i] = sortedPoint.value();\\n i++;\\n }\\n return RampParam2.createInterpolant(positions, values);\\n }\\n valueAtPosition(position) {\\n return this.interpolant().evaluate(position)[0];\\n }\\n};\\nvar RampParam = RampParam2;\\nRampParam.DEFAULT_VALUE = new RampValue(RampInterpolation.LINEAR, [new RampPoint(0, 0), new RampPoint(1, 1)]);\\nRampParam.DEFAULT_VALUE_JSON = RampParam2.DEFAULT_VALUE.toJSON();\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/params/String.ts\\nvar StringParam = class extends TypedParam {\\n static type() {\\n return ParamType.STRING;\\n }\\n defaultValueSerialized() {\\n return this._default_value;\\n }\\n _clone_raw_input(raw_input) {\\n return `${raw_input}`;\\n }\\n rawInputSerialized() {\\n return `${this._raw_input}`;\\n }\\n valueSerialized() {\\n return `${this.value}`;\\n }\\n _copy_value(param) {\\n this.set(param.value);\\n }\\n static are_raw_input_equal(raw_input1, raw_input2) {\\n return raw_input1 == raw_input2;\\n }\\n static are_values_equal(val1, val2) {\\n return val1 == val2;\\n }\\n isDefault() {\\n return this._raw_input == this._default_value;\\n }\\n convert(raw_val) {\\n if (CoreType.isString(raw_val)) {\\n return raw_val;\\n }\\n return `${raw_val}`;\\n }\\n rawInput() {\\n return this._raw_input;\\n }\\n processRawInput() {\\n this.states.error.clear();\\n if (this._value_elements(this._raw_input).length >= 3) {\\n this._expression_controller = this._expression_controller || new ExpressionController(this);\\n if (this._raw_input != this._expression_controller.expression()) {\\n this._expression_controller.set_expression(this._raw_input);\\n this.setDirty();\\n this.emitController.emit(ParamEvent.EXPRESSION_UPDATED);\\n }\\n } else {\\n if (this._raw_input != this._value) {\\n this._value = this._raw_input;\\n this.removeDirtyState();\\n this.setSuccessorsDirty(this);\\n this.emitController.emit(ParamEvent.VALUE_UPDATED);\\n this.options.executeCallback();\\n if (this._expression_controller) {\\n this._expression_controller.set_expression(void 0, false);\\n this.emitController.emit(ParamEvent.EXPRESSION_UPDATED);\\n }\\n }\\n }\\n }\\n async processComputation() {\\n if (this.expressionController?.active() && !this.expressionController.requires_entities()) {\\n const expression_result = await this.expressionController.computeExpression();\\n if (this.expressionController.is_errored()) {\\n this.states.error.set(`expression error: ${this.expressionController.error_message()}`);\\n } else {\\n const converted = this.convert(expression_result);\\n if (converted != null) {\\n this._value = converted;\\n this.emitController.emit(ParamEvent.VALUE_UPDATED);\\n this.options.executeCallback();\\n } else {\\n this.states.error.set(`expression returns an invalid type (${expression_result})`);\\n }\\n this.removeDirtyState();\\n }\\n }\\n }\\n _value_elements(v) {\\n return ParsedTree.string_value_elements(v);\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/params/Vector2.ts\\nvar COMPONENT_NAMES_VECTOR2 = [\\\\\\\"x\\\\\\\", \\\\\\\"y\\\\\\\"];\\nvar Vector2Param = class extends TypedMultipleParam {\\n constructor() {\\n super(...arguments);\\n this._value = new Vector2();\\n this._copied_value = [0, 0];\\n }\\n static type() {\\n return ParamType.VECTOR2;\\n }\\n componentNames() {\\n return COMPONENT_NAMES_VECTOR2;\\n }\\n defaultValueSerialized() {\\n if (CoreType.isArray(this._default_value)) {\\n return this._default_value;\\n } else {\\n return this._default_value.toArray();\\n }\\n }\\n valueSerialized() {\\n return this.value.toArray();\\n }\\n _copy_value(param) {\\n param.value.toArray(this._copied_value);\\n this.set(this._copied_value);\\n }\\n _clone_raw_input(raw_input) {\\n if (raw_input instanceof Vector2) {\\n return raw_input.clone();\\n } else {\\n const new_array = [raw_input[0], raw_input[1]];\\n if (new_array[0] == null) {\\n new_array[0] = new_array[0] || 0;\\n }\\n if (new_array[1] == null) {\\n new_array[1] = new_array[1] || new_array[0];\\n }\\n return new_array;\\n }\\n }\\n static are_raw_input_equal(raw_input1, raw_input2) {\\n if (raw_input1 instanceof Vector2) {\\n if (raw_input2 instanceof Vector2) {\\n return raw_input1.equals(raw_input2);\\n } else {\\n return raw_input1.x == raw_input2[0] && raw_input1.y == raw_input2[1];\\n }\\n } else {\\n if (raw_input2 instanceof Vector2) {\\n return raw_input1[0] == raw_input2.x && raw_input1[1] == raw_input2.y;\\n } else {\\n return raw_input1[0] == raw_input2[0] && raw_input1[1] == raw_input2[1];\\n }\\n }\\n }\\n static are_values_equal(val1, val2) {\\n return val1.equals(val2);\\n }\\n initComponents() {\\n super.initComponents();\\n this.x = this.components[0];\\n this.y = this.components[1];\\n }\\n set_value_from_components() {\\n this._value.x = this.x.value;\\n this._value.y = this.y.value;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/params/Vector3.ts\\nvar COMPONENT_NAMES_VECTOR3 = [\\\\\\\"x\\\\\\\", \\\\\\\"y\\\\\\\", \\\\\\\"z\\\\\\\"];\\nvar Vector3Param = class extends TypedMultipleParam {\\n constructor() {\\n super(...arguments);\\n this._value = new Vector3();\\n this._copied_value = [0, 0, 0];\\n }\\n static type() {\\n return ParamType.VECTOR3;\\n }\\n componentNames() {\\n return COMPONENT_NAMES_VECTOR3;\\n }\\n defaultValueSerialized() {\\n if (CoreType.isArray(this._default_value)) {\\n return this._default_value;\\n } else {\\n return this._default_value.toArray();\\n }\\n }\\n valueSerialized() {\\n return this.value.toArray();\\n }\\n _copy_value(param) {\\n param.value.toArray(this._copied_value);\\n this.set(this._copied_value);\\n }\\n _clone_raw_input(raw_input) {\\n if (raw_input instanceof Vector3) {\\n return raw_input.clone();\\n } else {\\n const new_array = [raw_input[0], raw_input[1], raw_input[2]];\\n if (new_array[0] == null) {\\n new_array[0] = new_array[0] || 0;\\n }\\n if (new_array[1] == null) {\\n new_array[1] = new_array[1] || new_array[0];\\n }\\n if (new_array[2] == null) {\\n new_array[2] = new_array[2] || new_array[1];\\n }\\n return new_array;\\n }\\n }\\n static are_raw_input_equal(raw_input1, raw_input2) {\\n if (raw_input1 instanceof Vector3) {\\n if (raw_input2 instanceof Vector3) {\\n return raw_input1.equals(raw_input2);\\n } else {\\n return raw_input1.x == raw_input2[0] && raw_input1.y == raw_input2[1] && raw_input1.z == raw_input2[2];\\n }\\n } else {\\n if (raw_input2 instanceof Vector3) {\\n return raw_input1[0] == raw_input2.x && raw_input1[1] == raw_input2.y && raw_input1[2] == raw_input2.z;\\n } else {\\n return raw_input1[0] == raw_input2[0] && raw_input1[1] == raw_input2[1] && raw_input1[2] == raw_input2[2];\\n }\\n }\\n }\\n static are_values_equal(val1, val2) {\\n return val1.equals(val2);\\n }\\n initComponents() {\\n super.initComponents();\\n this.x = this.components[0];\\n this.y = this.components[1];\\n this.z = this.components[2];\\n }\\n set_value_from_components() {\\n this._value.x = this.x.value;\\n this._value.y = this.y.value;\\n this._value.z = this.z.value;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/params/Vector4.ts\\nvar COMPONENT_NAMES_VECTOR4 = [\\\\\\\"x\\\\\\\", \\\\\\\"y\\\\\\\", \\\\\\\"z\\\\\\\", \\\\\\\"w\\\\\\\"];\\nvar Vector4Param = class extends TypedMultipleParam {\\n constructor() {\\n super(...arguments);\\n this._value = new Vector4();\\n this._copied_value = [0, 0, 0, 0];\\n }\\n static type() {\\n return ParamType.VECTOR4;\\n }\\n componentNames() {\\n return COMPONENT_NAMES_VECTOR4;\\n }\\n defaultValueSerialized() {\\n if (CoreType.isArray(this._default_value)) {\\n return this._default_value;\\n } else {\\n return this._default_value.toArray();\\n }\\n }\\n valueSerialized() {\\n return this.value.toArray();\\n }\\n _copy_value(param) {\\n param.value.toArray(this._copied_value);\\n this.set(this._copied_value);\\n }\\n _clone_raw_input(raw_input) {\\n if (raw_input instanceof Vector4) {\\n return raw_input.clone();\\n } else {\\n const new_array = [raw_input[0], raw_input[1], raw_input[2], raw_input[3]];\\n if (new_array[0] == null) {\\n new_array[0] = new_array[0] || 0;\\n }\\n if (new_array[1] == null) {\\n new_array[1] = new_array[1] || new_array[0];\\n }\\n if (new_array[2] == null) {\\n new_array[2] = new_array[2] || new_array[1];\\n }\\n if (new_array[3] == null) {\\n new_array[3] = new_array[3] || new_array[2];\\n }\\n return new_array;\\n }\\n }\\n static are_raw_input_equal(raw_input1, raw_input2) {\\n if (raw_input1 instanceof Vector4) {\\n if (raw_input2 instanceof Vector4) {\\n return raw_input1.equals(raw_input2);\\n } else {\\n return raw_input1.x == raw_input2[0] && raw_input1.y == raw_input2[1] && raw_input1.z == raw_input2[2] && raw_input1.w == raw_input2[3];\\n }\\n } else {\\n if (raw_input2 instanceof Vector4) {\\n return raw_input1[0] == raw_input2.x && raw_input1[1] == raw_input2.y && raw_input1[2] == raw_input2.z && raw_input1[3] == raw_input2.w;\\n } else {\\n return raw_input1[0] == raw_input2[0] && raw_input1[1] == raw_input2[1] && raw_input1[2] == raw_input2[2] && raw_input1[3] == raw_input2[3];\\n }\\n }\\n }\\n static are_values_equal(val1, val2) {\\n return val1.equals(val2);\\n }\\n initComponents() {\\n super.initComponents();\\n this.x = this.components[0];\\n this.y = this.components[1];\\n this.z = this.components[2];\\n this.w = this.components[3];\\n }\\n set_value_from_components() {\\n this._value.x = this.x.value;\\n this._value.y = this.y.value;\\n this._value.z = this.z.value;\\n this._value.w = this.w.value;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/params/types/ParamConstructorByType.ts\\nvar ParamConstructorByType = {\\n [ParamType.BOOLEAN]: BooleanParam,\\n [ParamType.BUTTON]: ButtonParam,\\n [ParamType.COLOR]: ColorParam,\\n [ParamType.FLOAT]: FloatParam,\\n [ParamType.FOLDER]: FolderParam,\\n [ParamType.INTEGER]: IntegerParam,\\n [ParamType.OPERATOR_PATH]: OperatorPathParam,\\n [ParamType.PARAM_PATH]: ParamPathParam,\\n [ParamType.NODE_PATH]: NodePathParam,\\n [ParamType.RAMP]: RampParam,\\n [ParamType.STRING]: StringParam,\\n [ParamType.VECTOR2]: Vector2Param,\\n [ParamType.VECTOR3]: Vector3Param,\\n [ParamType.VECTOR4]: Vector4Param\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/utils/params/ParamsLabelController.ts\\nvar ParamsLabelController = class {\\n dispose() {\\n this._callback = void 0;\\n }\\n params() {\\n return this._params;\\n }\\n callback() {\\n return this._callback;\\n }\\n init(params, callback) {\\n this._params = params;\\n if (callback) {\\n this._callback = callback;\\n } else {\\n const param = this._params[0];\\n switch (param.type()) {\\n case ParamType.STRING:\\n return this._handle_string_param(param);\\n case ParamType.OPERATOR_PATH:\\n return this._handle_operator_path_param(param);\\n case ParamType.NODE_PATH:\\n return this._handle_node_path_param(param);\\n case ParamType.PARAM_PATH:\\n return this._handle_param_path_param(param);\\n case ParamType.FLOAT:\\n return this._handle_number_param(param);\\n case ParamType.INTEGER:\\n return this._handle_number_param(param);\\n }\\n }\\n }\\n _handle_string_param(param) {\\n this._callback = () => {\\n return param.value;\\n };\\n }\\n _handle_operator_path_param(param) {\\n this._callback = () => {\\n return param.value;\\n };\\n }\\n _handle_node_path_param(param) {\\n this._callback = () => {\\n return param.value.path();\\n };\\n }\\n _handle_param_path_param(param) {\\n this._callback = () => {\\n return param.value.path();\\n };\\n }\\n _handle_number_param(param) {\\n this._callback = () => {\\n return `${param.value}`;\\n };\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/utils/params/ParamsController.ts\\nvar NODE_SIMPLE_NAME = \\\\\\\"params\\\\\\\";\\nvar ParamsController = class {\\n constructor(node) {\\n this.node = node;\\n this._param_create_mode = false;\\n this._params_created = false;\\n this._params_by_name = {};\\n this._params_list = [];\\n this._param_names = [];\\n this._non_spare_params = [];\\n this._spare_params = [];\\n this._non_spare_param_names = [];\\n this._spare_param_names = [];\\n this._params_added_since_last_params_eval = false;\\n }\\n get label() {\\n return this._label_controller = this._label_controller || new ParamsLabelController();\\n }\\n hasLabelController() {\\n return this._label_controller != null;\\n }\\n dispose() {\\n if (this._params_node) {\\n this._params_node.dispose();\\n }\\n for (let param of this.all) {\\n param.dispose();\\n }\\n this._post_create_params_hook_names = void 0;\\n this._post_create_params_hooks = void 0;\\n this._on_scene_load_hooks = void 0;\\n this._on_scene_load_hook_names = void 0;\\n this._label_controller?.dispose();\\n }\\n initDependencyNode() {\\n if (!this._params_node) {\\n this._params_node = new CoreGraphNode(this.node.scene(), NODE_SIMPLE_NAME);\\n this.node.addGraphInput(this._params_node, false);\\n }\\n }\\n init() {\\n this.initDependencyNode();\\n this._param_create_mode = true;\\n this._initFromParamsConfig();\\n this.node.createParams();\\n this._postCreateParams();\\n }\\n _postCreateParams() {\\n this._updateCaches();\\n this._initParamAccessors();\\n this._param_create_mode = false;\\n this._params_created = true;\\n this._runPostCreateParamsHooks();\\n }\\n postCreateSpareParams() {\\n this._updateCaches();\\n this._initParamAccessors();\\n this.node.scene().referencesController.notifyParamsUpdated(this.node);\\n this.node.emit(NodeEvent.PARAMS_UPDATED);\\n }\\n updateParams(options) {\\n let has_created_a_param = false;\\n let has_deleted_a_param = false;\\n if (options.namesToDelete) {\\n for (let param_name of options.namesToDelete) {\\n if (this.has(param_name)) {\\n this._deleteParam(param_name);\\n has_deleted_a_param = true;\\n }\\n }\\n }\\n if (options.toAdd) {\\n for (let param_data of options.toAdd) {\\n const param = this.addParam(param_data.type, param_data.name, param_data.init_value, param_data.options);\\n if (param) {\\n if (param_data.raw_input != null) {\\n param.set(param_data.raw_input);\\n }\\n has_created_a_param = true;\\n }\\n }\\n }\\n if (has_deleted_a_param || has_created_a_param) {\\n this.postCreateSpareParams();\\n }\\n }\\n _initFromParamsConfig() {\\n const paramsConfig = this.node.paramsConfig;\\n let init_values_used = false;\\n if (paramsConfig) {\\n for (let name of Object.keys(paramsConfig)) {\\n const config = paramsConfig[name];\\n let init_value;\\n if (this.node.params_init_value_overrides) {\\n init_value = this.node.params_init_value_overrides[name];\\n init_values_used = true;\\n }\\n this.addParam(config.type, name, config.init_value, config.options, init_value);\\n }\\n }\\n if (init_values_used) {\\n this.node.setDirty();\\n }\\n this.node.params_init_value_overrides = void 0;\\n }\\n _initParamAccessors() {\\n let current_names_in_accessor = Object.getOwnPropertyNames(this.node.pv);\\n this._removeUnneededAccessors(current_names_in_accessor);\\n current_names_in_accessor = Object.getOwnPropertyNames(this.node.pv);\\n for (let param of this.all) {\\n const is_spare = param.options.isSpare();\\n const param_not_yet_in_accessors = !current_names_in_accessor.includes(param.name());\\n if (param_not_yet_in_accessors || is_spare) {\\n Object.defineProperty(this.node.pv, param.name(), {\\n get: () => {\\n return param.value;\\n },\\n configurable: is_spare\\n });\\n Object.defineProperty(this.node.p, param.name(), {\\n get: () => {\\n return param;\\n },\\n configurable: is_spare\\n });\\n }\\n }\\n }\\n _removeUnneededAccessors(current_names_in_accessor) {\\n const current_param_names = this._param_names;\\n const names_to_remove = [];\\n for (let current_name_in_accessor of current_names_in_accessor) {\\n if (!current_param_names.includes(current_name_in_accessor)) {\\n names_to_remove.push(current_name_in_accessor);\\n }\\n }\\n for (let name_to_remove of names_to_remove) {\\n Object.defineProperty(this.node.pv, name_to_remove, {\\n get: () => {\\n return void 0;\\n },\\n configurable: true\\n });\\n Object.defineProperty(this.node.p, name_to_remove, {\\n get: () => {\\n return void 0;\\n },\\n configurable: true\\n });\\n }\\n }\\n get params_node() {\\n return this._params_node;\\n }\\n get all() {\\n return this._params_list;\\n }\\n get non_spare() {\\n return this._non_spare_params;\\n }\\n get spare() {\\n return this._spare_params;\\n }\\n get names() {\\n return this._param_names;\\n }\\n get non_spare_names() {\\n return this._non_spare_param_names;\\n }\\n get spare_names() {\\n return this._spare_param_names;\\n }\\n set_with_type(param_name, value, type) {\\n const param = this.param_with_type(param_name, type);\\n if (param) {\\n param.set(value);\\n } else {\\n Poly.warn(`param ${param_name} not found with type ${type}`);\\n }\\n }\\n set_float(param_name, value) {\\n this.set_with_type(param_name, value, ParamType.FLOAT);\\n }\\n set_vector3(param_name, value) {\\n this.set_with_type(param_name, value, ParamType.VECTOR3);\\n }\\n has_param(param_name) {\\n return this._params_by_name[param_name] != null;\\n }\\n has(param_name) {\\n return this.has_param(param_name);\\n }\\n get(param_name) {\\n return this.param(param_name);\\n }\\n param_with_type(param_name, type) {\\n const param = this.param(param_name);\\n if (param && param.type() == type) {\\n return param;\\n }\\n }\\n get_float(param_name) {\\n return this.param_with_type(param_name, ParamType.FLOAT);\\n }\\n get_operator_path(param_name) {\\n return this.param_with_type(param_name, ParamType.OPERATOR_PATH);\\n }\\n value(param_name) {\\n return this.param(param_name)?.value;\\n }\\n value_with_type(param_name, type) {\\n return this.param_with_type(param_name, type)?.value;\\n }\\n boolean(param_name) {\\n return this.value_with_type(param_name, ParamType.BOOLEAN);\\n }\\n float(param_name) {\\n return this.value_with_type(param_name, ParamType.FLOAT);\\n }\\n integer(param_name) {\\n return this.value_with_type(param_name, ParamType.INTEGER);\\n }\\n string(param_name) {\\n return this.value_with_type(param_name, ParamType.STRING);\\n }\\n vector2(param_name) {\\n return this.value_with_type(param_name, ParamType.VECTOR2);\\n }\\n vector3(param_name) {\\n return this.value_with_type(param_name, ParamType.VECTOR3);\\n }\\n color(param_name) {\\n return this.value_with_type(param_name, ParamType.COLOR);\\n }\\n param(param_name) {\\n const p = this._params_by_name[param_name];\\n if (p != null) {\\n return p;\\n } else {\\n Poly.warn(`tried to access param '${param_name}' in node ${this.node.path()}, but existing params are: ${this.names} on node ${this.node.path()}`);\\n return null;\\n }\\n }\\n _deleteParam(param_name) {\\n const param = this._params_by_name[param_name];\\n if (param) {\\n if (this._params_node) {\\n this._params_node.removeGraphInput(this._params_by_name[param_name]);\\n }\\n param._setupNodeDependencies(null);\\n delete this._params_by_name[param_name];\\n if (param.isMultiple() && param.components) {\\n for (let component of param.components) {\\n const child_name = component.name();\\n delete this._params_by_name[child_name];\\n }\\n }\\n } else {\\n throw new Error(`param '${param_name}' does not exist on node ${this.node.path()}`);\\n }\\n }\\n addParam(type, param_name, default_value, options = {}, init_data) {\\n const is_spare = options[\\\\\\\"spare\\\\\\\"] || false;\\n if (this._param_create_mode === false && !is_spare) {\\n Poly.warn(`node ${this.node.path()} (${this.node.type()}) param '${param_name}' cannot be created outside of create_params`);\\n }\\n if (this.node.scene() == null) {\\n Poly.warn(`node ${this.node.path()} (${this.node.type()}) has no scene assigned`);\\n }\\n const constructor = ParamConstructorByType[type];\\n if (constructor != null) {\\n const existing_param = this._params_by_name[param_name];\\n if (existing_param) {\\n if (is_spare) {\\n if (existing_param.type() != type) {\\n this._deleteParam(existing_param.name());\\n }\\n } else {\\n Poly.warn(`a param named ${param_name} already exists`, this.node);\\n }\\n }\\n const param = new constructor(this.node.scene(), this.node);\\n param.options.set(options);\\n param.setName(param_name);\\n param.setInitValue(default_value);\\n param.initComponents();\\n if (init_data == null) {\\n param.set(default_value);\\n } else {\\n if (param.options.isExpressionForEntities()) {\\n param.set(default_value);\\n }\\n if (init_data.raw_input != null) {\\n param.set(init_data.raw_input);\\n } else {\\n if (init_data.simple_data != null) {\\n param.set(init_data.simple_data);\\n } else {\\n if (init_data.complex_data != null) {\\n const raw_input = init_data.complex_data.raw_input;\\n if (raw_input) {\\n param.set(raw_input);\\n } else {\\n param.set(default_value);\\n }\\n const overriden_options = init_data.complex_data.overriden_options;\\n if (overriden_options != null) {\\n const keys = Object.keys(overriden_options);\\n for (let key of keys) {\\n param.options.setOption(key, overriden_options[key]);\\n }\\n }\\n }\\n }\\n }\\n }\\n param._setupNodeDependencies(this.node);\\n this._params_by_name[param.name()] = param;\\n if (param.isMultiple() && param.components) {\\n for (let component of param.components) {\\n this._params_by_name[component.name()] = component;\\n }\\n }\\n this._params_added_since_last_params_eval = true;\\n return param;\\n }\\n }\\n _updateCaches() {\\n this._params_list = Object.values(this._params_by_name);\\n this._param_names = Object.keys(this._params_by_name);\\n this._non_spare_params = Object.values(this._params_by_name).filter((p) => !p.options.isSpare());\\n this._spare_params = Object.values(this._params_by_name).filter((p) => p.options.isSpare());\\n this._non_spare_param_names = Object.values(this._params_by_name).filter((p) => !p.options.isSpare()).map((p) => p.name());\\n this._spare_param_names = Object.values(this._params_by_name).filter((p) => p.options.isSpare()).map((p) => p.name());\\n }\\n async _evalParam(param) {\\n if (param.isDirty()) {\\n await param.compute();\\n if (param.states.error.active()) {\\n this.node.states.error.set(`param '${param.name()}' error: ${param.states.error.message()}`);\\n }\\n } else {\\n }\\n }\\n async evalParams(params) {\\n const promises = [];\\n for (let param of params) {\\n if (param.isDirty()) {\\n promises.push(this._evalParam(param));\\n }\\n }\\n await Promise.all(promises);\\n if (this.node.states.error.active()) {\\n this.node._setContainer(null);\\n }\\n }\\n paramsEvalRequired() {\\n return this._params_node != null && (this._params_node.isDirty() || this._params_added_since_last_params_eval);\\n }\\n async evalAll() {\\n if (this.paramsEvalRequired()) {\\n await this.evalParams(this._params_list);\\n this._params_node?.removeDirtyState();\\n this._params_added_since_last_params_eval = false;\\n }\\n }\\n onParamsCreated(hook_name, hook) {\\n if (this._params_created) {\\n hook();\\n } else {\\n if (this._post_create_params_hook_names && this._post_create_params_hook_names.includes(hook_name)) {\\n Poly.error(`hook name ${hook_name} already exists`);\\n return;\\n }\\n this._post_create_params_hook_names = this._post_create_params_hook_names || [];\\n this._post_create_params_hook_names.push(hook_name);\\n this._post_create_params_hooks = this._post_create_params_hooks || [];\\n this._post_create_params_hooks.push(hook);\\n }\\n }\\n addOnSceneLoadHook(param_name, method) {\\n this._on_scene_load_hook_names = this._on_scene_load_hook_names || [];\\n this._on_scene_load_hooks = this._on_scene_load_hooks || [];\\n if (!this._on_scene_load_hook_names.includes(param_name)) {\\n this._on_scene_load_hook_names.push(param_name);\\n this._on_scene_load_hooks.push(method);\\n } else {\\n Poly.warn(`hook with name ${param_name} already exists`, this.node);\\n }\\n }\\n _runPostCreateParamsHooks() {\\n if (this._post_create_params_hooks) {\\n for (let hook of this._post_create_params_hooks) {\\n hook();\\n }\\n }\\n }\\n runOnSceneLoadHooks() {\\n if (this._on_scene_load_hooks) {\\n for (let hook of this._on_scene_load_hooks) {\\n hook();\\n }\\n }\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/utils/params/ParamsValueAccessor.ts\\nvar ParamsValueAccessor = class {\\n constructor() {\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/utils/io/NodeConnection.ts\\nvar TypedNodeConnection2 = class {\\n constructor(_node_src, _node_dest, _output_index = 0, _input_index = 0) {\\n this._node_src = _node_src;\\n this._node_dest = _node_dest;\\n this._output_index = _output_index;\\n this._input_index = _input_index;\\n if (this._output_index == null) {\\n throw \\\\\\\"bad output index\\\\\\\";\\n }\\n if (this._input_index == null) {\\n throw \\\\\\\"bad input index\\\\\\\";\\n }\\n this._id = TypedNodeConnection2._next_id++;\\n if (this._node_src.io.connections && this._node_dest.io.connections) {\\n this._node_src.io.connections.addOutputConnection(this);\\n this._node_dest.io.connections.addInputConnection(this);\\n }\\n }\\n get id() {\\n return this._id;\\n }\\n get node_src() {\\n return this._node_src;\\n }\\n get node_dest() {\\n return this._node_dest;\\n }\\n get output_index() {\\n return this._output_index;\\n }\\n get input_index() {\\n return this._input_index;\\n }\\n src_connection_point() {\\n const node_src = this._node_src;\\n const output_index = this._output_index;\\n return node_src.io.outputs.namedOutputConnectionPoints()[output_index];\\n }\\n dest_connection_point() {\\n const node_dest = this._node_dest;\\n const input_index = this._input_index;\\n return node_dest.io.inputs.namedInputConnectionPoints()[input_index];\\n }\\n disconnect(options = {}) {\\n if (this._node_src.io.connections && this._node_dest.io.connections) {\\n this._node_src.io.connections.removeOutputConnection(this);\\n this._node_dest.io.connections.removeInputConnection(this);\\n }\\n if (options.setInput === true) {\\n this._node_dest.io.inputs.setInput(this._input_index, null);\\n }\\n }\\n};\\nvar TypedNodeConnection = TypedNodeConnection2;\\nTypedNodeConnection._next_id = 0;\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/utils/io/utils/ClonedStatesController.ts\\nvar ClonedStatesController2 = class {\\n constructor(inputs_controller) {\\n this.inputs_controller = inputs_controller;\\n this._clone_required_states = [];\\n this._overridden = false;\\n this.node = inputs_controller.node;\\n }\\n initInputsClonedState(states) {\\n if (CoreType.isArray(states)) {\\n this._cloned_states = states;\\n } else {\\n this._cloned_state = states;\\n }\\n this._update_clone_required_state();\\n }\\n overrideClonedStateAllowed() {\\n if (this._cloned_states) {\\n for (let state of this._cloned_states) {\\n if (state == InputCloneMode.FROM_NODE) {\\n return true;\\n }\\n }\\n }\\n if (this._cloned_state) {\\n return this._cloned_state == InputCloneMode.FROM_NODE;\\n }\\n return false;\\n }\\n cloneRequiredState(index) {\\n return this._clone_required_states[index];\\n }\\n cloneRequiredStates() {\\n return this._clone_required_states;\\n }\\n _get_clone_required_state(index) {\\n const states = this._cloned_states;\\n if (states) {\\n const state = states[index];\\n if (state != null) {\\n return this.clone_required_from_state(state);\\n }\\n }\\n if (this._cloned_state) {\\n return this.clone_required_from_state(this._cloned_state);\\n }\\n return true;\\n }\\n clone_required_from_state(state) {\\n switch (state) {\\n case InputCloneMode.ALWAYS:\\n return true;\\n case InputCloneMode.NEVER:\\n return false;\\n case InputCloneMode.FROM_NODE:\\n return !this._overridden;\\n }\\n return TypeAssert.unreachable(state);\\n }\\n overrideClonedState(state) {\\n this._overridden = state;\\n this._update_clone_required_state();\\n this.node.emit(NodeEvent.OVERRIDE_CLONABLE_STATE_UPDATE);\\n this.node.setDirty();\\n }\\n overriden() {\\n return this._overridden;\\n }\\n _update_clone_required_state() {\\n if (this._cloned_states) {\\n const states = [];\\n for (let i = 0; i < this._cloned_states.length; i++) {\\n states[i] = this._get_clone_required_state(i);\\n }\\n this._clone_required_states = states;\\n return;\\n }\\n if (this._cloned_state) {\\n const max_inputs = this.inputs_controller.maxInputsCount();\\n const states = [];\\n for (let i = 0; i < max_inputs; i++) {\\n states[i] = this._get_clone_required_state(i);\\n }\\n this._clone_required_states = states;\\n return;\\n }\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/utils/io/InputsController.ts\\nvar MAX_INPUTS_COUNT_UNSET = 0;\\nvar InputsController2 = class {\\n constructor(node) {\\n this.node = node;\\n this._graph_node_inputs = [];\\n this._inputs = [];\\n this._has_named_inputs = false;\\n this._minInputsCount = 0;\\n this._maxInputsCount = MAX_INPUTS_COUNT_UNSET;\\n this._maxInputsCountOnInput = MAX_INPUTS_COUNT_UNSET;\\n this._depends_on_inputs = true;\\n }\\n dispose() {\\n if (this._graph_node) {\\n this._graph_node.dispose();\\n }\\n for (let graph_node of this._graph_node_inputs) {\\n if (graph_node) {\\n graph_node.dispose();\\n }\\n }\\n this._on_update_hooks = void 0;\\n this._on_update_hook_names = void 0;\\n }\\n set_depends_on_inputs(depends_on_inputs) {\\n this._depends_on_inputs = depends_on_inputs;\\n }\\n setMinCount(minInputsCount) {\\n this._minInputsCount = minInputsCount;\\n }\\n minCount() {\\n return this._minInputsCount;\\n }\\n setMaxCount(maxInputsCount) {\\n if (this._maxInputsCount == MAX_INPUTS_COUNT_UNSET) {\\n this._maxInputsCountOnInput = maxInputsCount;\\n }\\n this._maxInputsCount = maxInputsCount;\\n this._initGraphNodeInputs();\\n }\\n namedInputConnectionPointsByName(name) {\\n if (this._named_input_connection_points) {\\n for (let connection_point of this._named_input_connection_points) {\\n if (connection_point && connection_point.name() == name) {\\n return connection_point;\\n }\\n }\\n }\\n }\\n setNamedInputConnectionPoints(connection_points) {\\n this._has_named_inputs = true;\\n const connections = this.node.io.connections.inputConnections();\\n if (connections) {\\n for (let connection of connections) {\\n if (connection) {\\n if (connection.input_index >= connection_points.length) {\\n connection.disconnect({setInput: true});\\n }\\n }\\n }\\n }\\n this._named_input_connection_points = connection_points;\\n this.setMinCount(0);\\n this.setMaxCount(connection_points.length);\\n this._initGraphNodeInputs();\\n this.node.emit(NodeEvent.NAMED_INPUTS_UPDATED);\\n }\\n hasNamedInputs() {\\n return this._has_named_inputs;\\n }\\n namedInputConnectionPoints() {\\n return this._named_input_connection_points || [];\\n }\\n _initGraphNodeInputs() {\\n for (let i = 0; i < this._maxInputsCount; i++) {\\n this._graph_node_inputs[i] = this._graph_node_inputs[i] || this._createGraphNodeInput(i);\\n }\\n }\\n _createGraphNodeInput(index) {\\n const graph_input_node = new CoreGraphNode(this.node.scene(), `input_${index}`);\\n if (!this._graph_node) {\\n this._graph_node = new CoreGraphNode(this.node.scene(), \\\\\\\"inputs\\\\\\\");\\n this.node.addGraphInput(this._graph_node, false);\\n }\\n this._graph_node.addGraphInput(graph_input_node, false);\\n return graph_input_node;\\n }\\n maxInputsCount() {\\n return this._maxInputsCount || 0;\\n }\\n maxInputsCountOverriden() {\\n return this._maxInputsCount != this._maxInputsCountOnInput;\\n }\\n inputGraphNode(input_index) {\\n return this._graph_node_inputs[input_index];\\n }\\n setCount(min, max) {\\n if (max == null) {\\n max = min;\\n }\\n this.setMinCount(min);\\n this.setMaxCount(max);\\n this._initConnectionControllerInputs();\\n }\\n _initConnectionControllerInputs() {\\n this.node.io.connections.initInputs();\\n }\\n is_any_input_dirty() {\\n return this._graph_node?.isDirty() || false;\\n }\\n async containers_without_evaluation() {\\n const containers = [];\\n for (let i = 0; i < this._inputs.length; i++) {\\n const input_node = this._inputs[i];\\n let container = void 0;\\n if (input_node) {\\n container = await input_node.compute();\\n }\\n containers.push(container);\\n }\\n return containers;\\n }\\n existing_input_indices() {\\n const existing_input_indices = [];\\n if (this._maxInputsCount > 0) {\\n for (let i = 0; i < this._inputs.length; i++) {\\n if (this._inputs[i]) {\\n existing_input_indices.push(i);\\n }\\n }\\n }\\n return existing_input_indices;\\n }\\n async eval_required_inputs() {\\n let containers = [];\\n if (this._maxInputsCount > 0) {\\n const existing_input_indices = this.existing_input_indices();\\n if (existing_input_indices.length < this._minInputsCount) {\\n this.node.states.error.set(\\\\\\\"inputs are missing\\\\\\\");\\n } else {\\n if (existing_input_indices.length > 0) {\\n const promises = [];\\n let input;\\n for (let i = 0; i < this._inputs.length; i++) {\\n input = this._inputs[i];\\n if (input) {\\n promises.push(this.eval_required_input(i));\\n }\\n }\\n containers = await Promise.all(promises);\\n this._graph_node?.removeDirtyState();\\n }\\n }\\n }\\n return containers;\\n }\\n async eval_required_input(input_index) {\\n let container = void 0;\\n const input_node = this.input(input_index);\\n if (input_node) {\\n container = await input_node.compute();\\n this._graph_node_inputs[input_index].removeDirtyState();\\n }\\n if (container && container.coreContent()) {\\n } else {\\n const input_node2 = this.input(input_index);\\n if (input_node2) {\\n const input_error_message = input_node2.states.error.message();\\n if (input_error_message) {\\n this.node.states.error.set(`input ${input_index} is invalid (error: ${input_error_message})`);\\n }\\n }\\n }\\n return container;\\n }\\n get_named_input_index(name) {\\n if (this._named_input_connection_points) {\\n for (let i = 0; i < this._named_input_connection_points.length; i++) {\\n if (this._named_input_connection_points[i]?.name() == name) {\\n return i;\\n }\\n }\\n }\\n return -1;\\n }\\n get_input_index(input_index_or_name) {\\n if (CoreType.isString(input_index_or_name)) {\\n if (this.hasNamedInputs()) {\\n return this.get_named_input_index(input_index_or_name);\\n } else {\\n throw new Error(`node ${this.node.path()} has no named inputs`);\\n }\\n } else {\\n return input_index_or_name;\\n }\\n }\\n setInput(input_index_or_name, node, output_index_or_name = 0) {\\n const input_index = this.get_input_index(input_index_or_name) || 0;\\n if (input_index < 0) {\\n const message = `invalid input (${input_index_or_name}) for node ${this.node.path()}`;\\n console.warn(message);\\n throw new Error(message);\\n }\\n let output_index = 0;\\n if (node) {\\n if (node.io.outputs.hasNamedOutputs()) {\\n output_index = node.io.outputs.getOutputIndex(output_index_or_name);\\n if (output_index == null || output_index < 0) {\\n const connection_points = node.io.outputs.namedOutputConnectionPoints();\\n const names = connection_points.map((cp) => cp.name());\\n console.warn(`node ${node.path()} does not have an output named ${output_index_or_name}. inputs are: ${names.join(\\\\\\\", \\\\\\\")}`);\\n return;\\n }\\n }\\n }\\n const graph_input_node = this._graph_node_inputs[input_index];\\n if (graph_input_node == null) {\\n const message = `graph_input_node not found at index ${input_index}`;\\n console.warn(message);\\n throw new Error(message);\\n }\\n if (node && this.node.parent() != node.parent()) {\\n return;\\n }\\n const old_input_node = this._inputs[input_index];\\n let old_output_index = null;\\n let old_connection = void 0;\\n if (this.node.io.connections) {\\n old_connection = this.node.io.connections.inputConnection(input_index);\\n }\\n if (old_connection) {\\n old_output_index = old_connection.output_index;\\n }\\n if (node !== old_input_node || output_index != old_output_index) {\\n if (old_input_node != null) {\\n if (this._depends_on_inputs) {\\n graph_input_node.removeGraphInput(old_input_node);\\n }\\n }\\n if (node != null) {\\n if (graph_input_node.addGraphInput(node)) {\\n if (!this._depends_on_inputs) {\\n graph_input_node.removeGraphInput(node);\\n }\\n if (old_connection) {\\n old_connection.disconnect({setInput: false});\\n }\\n this._inputs[input_index] = node;\\n new TypedNodeConnection(node, this.node, output_index, input_index);\\n } else {\\n console.warn(`cannot connect ${node.path()} to ${this.node.path()}`);\\n }\\n } else {\\n this._inputs[input_index] = null;\\n if (old_connection) {\\n old_connection.disconnect({setInput: false});\\n }\\n }\\n this._run_on_set_input_hooks();\\n graph_input_node.setSuccessorsDirty();\\n this.node.emit(NodeEvent.INPUTS_UPDATED);\\n }\\n }\\n remove_input(node) {\\n const inputs = this.inputs();\\n let input;\\n for (let i = 0; i < inputs.length; i++) {\\n input = inputs[i];\\n if (input != null && node != null) {\\n if (input.graphNodeId() === node.graphNodeId()) {\\n this.setInput(i, null);\\n }\\n }\\n }\\n }\\n input(input_index) {\\n return this._inputs[input_index];\\n }\\n named_input(input_name) {\\n if (this.hasNamedInputs()) {\\n const input_index = this.get_input_index(input_name);\\n return this._inputs[input_index];\\n } else {\\n return null;\\n }\\n }\\n named_input_connection_point(input_name) {\\n if (this.hasNamedInputs() && this._named_input_connection_points) {\\n const input_index = this.get_input_index(input_name);\\n return this._named_input_connection_points[input_index];\\n }\\n }\\n has_named_input(name) {\\n return this.get_named_input_index(name) >= 0;\\n }\\n has_input(input_index) {\\n return this._inputs[input_index] != null;\\n }\\n inputs() {\\n return this._inputs;\\n }\\n initInputsClonedState(states) {\\n if (!this._cloned_states_controller) {\\n this._cloned_states_controller = new ClonedStatesController2(this);\\n this._cloned_states_controller.initInputsClonedState(states);\\n }\\n }\\n overrideClonedStateAllowed() {\\n return this._cloned_states_controller?.overrideClonedStateAllowed() || false;\\n }\\n overrideClonedState(state) {\\n this._cloned_states_controller?.overrideClonedState(state);\\n }\\n clonedStateOverriden() {\\n return this._cloned_states_controller?.overriden() || false;\\n }\\n cloneRequired(index) {\\n const state = this._cloned_states_controller?.cloneRequiredState(index);\\n if (state != null) {\\n return state;\\n }\\n return true;\\n }\\n cloneRequiredStates() {\\n const states = this._cloned_states_controller?.cloneRequiredStates();\\n if (states != null) {\\n return states;\\n }\\n return true;\\n }\\n add_on_set_input_hook(name, hook) {\\n this._on_update_hooks = this._on_update_hooks || [];\\n this._on_update_hook_names = this._on_update_hook_names || [];\\n if (!this._on_update_hook_names.includes(name)) {\\n this._on_update_hooks.push(hook);\\n this._on_update_hook_names.push(name);\\n } else {\\n console.warn(`hook with name ${name} already exists`, this.node);\\n }\\n }\\n _run_on_set_input_hooks() {\\n if (this._on_update_hooks) {\\n for (let hook of this._on_update_hooks) {\\n hook();\\n }\\n }\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/utils/io/OutputsController.ts\\nvar OutputsController = class {\\n constructor(node) {\\n this.node = node;\\n this._has_outputs = false;\\n this._has_named_outputs = false;\\n }\\n setHasOneOutput() {\\n this._has_outputs = true;\\n }\\n setHasNoOutput() {\\n this._has_outputs = false;\\n }\\n hasOutputs() {\\n return this._has_outputs;\\n }\\n hasNamedOutputs() {\\n return this._has_named_outputs;\\n }\\n hasNamedOutput(name) {\\n return this.getNamedOutputIndex(name) >= 0;\\n }\\n namedOutputConnectionPoints() {\\n return this._named_output_connection_points || [];\\n }\\n namedOutputConnection(index) {\\n if (this._named_output_connection_points) {\\n return this._named_output_connection_points[index];\\n }\\n }\\n getNamedOutputIndex(name) {\\n if (this._named_output_connection_points) {\\n for (let i = 0; i < this._named_output_connection_points.length; i++) {\\n if (this._named_output_connection_points[i]?.name() == name) {\\n return i;\\n }\\n }\\n }\\n return -1;\\n }\\n getOutputIndex(output_index_or_name) {\\n if (output_index_or_name != null) {\\n if (CoreType.isString(output_index_or_name)) {\\n if (this.hasNamedOutputs()) {\\n return this.getNamedOutputIndex(output_index_or_name);\\n } else {\\n console.warn(`node ${this.node.path()} has no named outputs`);\\n return -1;\\n }\\n } else {\\n return output_index_or_name;\\n }\\n }\\n return -1;\\n }\\n namedOutputConnectionPointsByName(name) {\\n if (this._named_output_connection_points) {\\n for (let connection_point of this._named_output_connection_points) {\\n if (connection_point?.name() == name) {\\n return connection_point;\\n }\\n }\\n }\\n }\\n setNamedOutputConnectionPoints(connection_points, set_dirty = true) {\\n this._has_named_outputs = true;\\n const connections = this.node.io.connections.outputConnections();\\n if (connections) {\\n for (let connection of connections) {\\n if (connection) {\\n if (connection.output_index >= connection_points.length) {\\n connection.disconnect({setInput: true});\\n }\\n }\\n }\\n }\\n this._named_output_connection_points = connection_points;\\n if (set_dirty && this.node.scene()) {\\n this.node.setDirty(this.node);\\n }\\n this.node.emit(NodeEvent.NAMED_OUTPUTS_UPDATED);\\n }\\n used_output_names() {\\n const connections_controller = this.node.io.connections;\\n if (connections_controller) {\\n const output_connections = connections_controller.outputConnections();\\n let output_indices = output_connections.map((connection) => connection ? connection.output_index : null);\\n output_indices = ArrayUtils.uniq(output_indices);\\n const used_output_indices = [];\\n output_indices.forEach((index) => {\\n if (CoreType.isNumber(index)) {\\n used_output_indices.push(index);\\n }\\n });\\n const used_output_names = [];\\n for (let index of used_output_indices) {\\n const name = this.namedOutputConnectionPoints()[index]?.name();\\n if (name) {\\n used_output_names.push(name);\\n }\\n }\\n return used_output_names;\\n } else {\\n return [];\\n }\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/utils/io/ConnectionsController.ts\\nvar ConnectionsController = class {\\n constructor(_node) {\\n this._node = _node;\\n this._output_connections = new Map();\\n }\\n initInputs() {\\n const count = this._node.io.inputs.maxInputsCount();\\n this._input_connections = this._input_connections || new Array(count);\\n while (this._input_connections.length < count) {\\n this._input_connections.push(void 0);\\n }\\n }\\n addInputConnection(connection) {\\n if (this._input_connections) {\\n this._input_connections[connection.input_index] = connection;\\n } else {\\n console.warn(`input connections array not initialized`);\\n }\\n }\\n removeInputConnection(connection) {\\n if (this._input_connections) {\\n if (connection.input_index < this._input_connections.length) {\\n this._input_connections[connection.input_index] = void 0;\\n let all_connections_after_are_undefined = true;\\n for (let i = connection.input_index; i < this._input_connections.length; i++) {\\n if (this._input_connections[i]) {\\n all_connections_after_are_undefined = false;\\n }\\n }\\n if (all_connections_after_are_undefined) {\\n this._input_connections = this._input_connections.slice(0, connection.input_index);\\n }\\n } else {\\n console.warn(`attempt to remove an input connection at index ${connection.input_index}`);\\n }\\n } else {\\n console.warn(`input connections array not initialized`);\\n }\\n }\\n inputConnection(index) {\\n if (this._input_connections) {\\n return this._input_connections[index];\\n }\\n }\\n firstInputConnection() {\\n if (this._input_connections) {\\n return ArrayUtils.compact(this._input_connections)[0];\\n } else {\\n return null;\\n }\\n }\\n inputConnections() {\\n return this._input_connections;\\n }\\n existingInputConnections() {\\n const current_connections = this._input_connections;\\n if (current_connections) {\\n while (current_connections.length > 1 && current_connections[current_connections.length - 1] === void 0) {\\n current_connections.pop();\\n }\\n }\\n return current_connections;\\n }\\n addOutputConnection(connection) {\\n const output_index = connection.output_index;\\n const id = connection.id;\\n let connections_by_id = this._output_connections.get(output_index);\\n if (!connections_by_id) {\\n connections_by_id = new Map();\\n this._output_connections.set(output_index, connections_by_id);\\n }\\n connections_by_id.set(id, connection);\\n }\\n removeOutputConnection(connection) {\\n const output_index = connection.output_index;\\n const id = connection.id;\\n let connections_by_id = this._output_connections.get(output_index);\\n if (connections_by_id) {\\n connections_by_id.delete(id);\\n }\\n }\\n outputConnections() {\\n let list = [];\\n this._output_connections.forEach((connections_by_id, output_index) => {\\n connections_by_id.forEach((connection, id) => {\\n if (connection) {\\n list.push(connection);\\n }\\n });\\n });\\n return list;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/utils/io/SavedConnectionPointsDataController.ts\\nvar SavedConnectionPointsDataController = class {\\n constructor(_node) {\\n this._node = _node;\\n }\\n set_in(data) {\\n this._in = data;\\n }\\n set_out(data) {\\n this._out = data;\\n }\\n clear() {\\n this._in = void 0;\\n this._out = void 0;\\n }\\n in() {\\n return this._in;\\n }\\n out() {\\n return this._out;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/utils/io/connections/_Base.ts\\nvar BaseConnectionPoint = class {\\n constructor(_name, _type, _init_value) {\\n this._name = _name;\\n this._type = _type;\\n this._init_value = _init_value;\\n }\\n get init_value() {\\n return this._init_value;\\n }\\n name() {\\n return this._name;\\n }\\n type() {\\n return this._type;\\n }\\n are_types_matched(src_type, dest_type) {\\n return true;\\n }\\n toJSON() {\\n return this._json = this._json || this._create_json();\\n }\\n _create_json() {\\n return {\\n name: this._name,\\n type: this._type\\n };\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/utils/io/connections/Gl.ts\\nvar GlConnectionPointType;\\n(function(GlConnectionPointType2) {\\n GlConnectionPointType2[\\\\\\\"BOOL\\\\\\\"] = \\\\\\\"bool\\\\\\\";\\n GlConnectionPointType2[\\\\\\\"INT\\\\\\\"] = \\\\\\\"int\\\\\\\";\\n GlConnectionPointType2[\\\\\\\"FLOAT\\\\\\\"] = \\\\\\\"float\\\\\\\";\\n GlConnectionPointType2[\\\\\\\"VEC2\\\\\\\"] = \\\\\\\"vec2\\\\\\\";\\n GlConnectionPointType2[\\\\\\\"VEC3\\\\\\\"] = \\\\\\\"vec3\\\\\\\";\\n GlConnectionPointType2[\\\\\\\"VEC4\\\\\\\"] = \\\\\\\"vec4\\\\\\\";\\n GlConnectionPointType2[\\\\\\\"SAMPLER_2D\\\\\\\"] = \\\\\\\"sampler2D\\\\\\\";\\n GlConnectionPointType2[\\\\\\\"SSS_MODEL\\\\\\\"] = \\\\\\\"SSSModel\\\\\\\";\\n})(GlConnectionPointType || (GlConnectionPointType = {}));\\nvar GL_CONNECTION_POINT_TYPES = [\\n GlConnectionPointType.BOOL,\\n GlConnectionPointType.INT,\\n GlConnectionPointType.FLOAT,\\n GlConnectionPointType.VEC2,\\n GlConnectionPointType.VEC3,\\n GlConnectionPointType.VEC4\\n];\\nvar GlConnectionPointTypeToParamTypeMap = {\\n [GlConnectionPointType.BOOL]: ParamType.BOOLEAN,\\n [GlConnectionPointType.INT]: ParamType.INTEGER,\\n [GlConnectionPointType.FLOAT]: ParamType.FLOAT,\\n [GlConnectionPointType.VEC2]: ParamType.VECTOR2,\\n [GlConnectionPointType.VEC3]: ParamType.VECTOR3,\\n [GlConnectionPointType.VEC4]: ParamType.VECTOR4,\\n [GlConnectionPointType.SAMPLER_2D]: ParamType.RAMP,\\n [GlConnectionPointType.SSS_MODEL]: ParamType.STRING\\n};\\nvar GLParamTypeToConnectionPointTypeMap = {\\n [ParamType.BOOLEAN]: GlConnectionPointType.BOOL,\\n [ParamType.COLOR]: GlConnectionPointType.VEC3,\\n [ParamType.INTEGER]: GlConnectionPointType.INT,\\n [ParamType.FLOAT]: GlConnectionPointType.FLOAT,\\n [ParamType.FOLDER]: void 0,\\n [ParamType.VECTOR2]: GlConnectionPointType.VEC2,\\n [ParamType.VECTOR3]: GlConnectionPointType.VEC3,\\n [ParamType.VECTOR4]: GlConnectionPointType.VEC4,\\n [ParamType.BUTTON]: void 0,\\n [ParamType.OPERATOR_PATH]: void 0,\\n [ParamType.PARAM_PATH]: void 0,\\n [ParamType.NODE_PATH]: void 0,\\n [ParamType.RAMP]: void 0,\\n [ParamType.STRING]: void 0\\n};\\nvar GlConnectionPointInitValueMap = {\\n [GlConnectionPointType.BOOL]: false,\\n [GlConnectionPointType.INT]: 0,\\n [GlConnectionPointType.FLOAT]: 0,\\n [GlConnectionPointType.VEC2]: [0, 0],\\n [GlConnectionPointType.VEC3]: [0, 0, 0],\\n [GlConnectionPointType.VEC4]: [0, 0, 0, 0],\\n [GlConnectionPointType.SAMPLER_2D]: RampParam.DEFAULT_VALUE_JSON,\\n [GlConnectionPointType.SSS_MODEL]: \\\\\\\"SSSModel()\\\\\\\"\\n};\\nvar GlConnectionPointComponentsCountMap = {\\n [GlConnectionPointType.BOOL]: 1,\\n [GlConnectionPointType.INT]: 1,\\n [GlConnectionPointType.FLOAT]: 1,\\n [GlConnectionPointType.VEC2]: 2,\\n [GlConnectionPointType.VEC3]: 3,\\n [GlConnectionPointType.VEC4]: 4,\\n [GlConnectionPointType.SAMPLER_2D]: 1,\\n [GlConnectionPointType.SSS_MODEL]: 1\\n};\\nvar GlConnectionPoint = class extends BaseConnectionPoint {\\n constructor(_name, _type, _init_value) {\\n super(_name, _type);\\n this._name = _name;\\n this._type = _type;\\n this._init_value = _init_value;\\n this._init_value = this._init_value || GlConnectionPointInitValueMap[this._type];\\n }\\n type() {\\n return this._type;\\n }\\n are_types_matched(src_type, dest_type) {\\n return src_type == dest_type;\\n }\\n get param_type() {\\n return GlConnectionPointTypeToParamTypeMap[this._type];\\n }\\n get init_value() {\\n return this._init_value;\\n }\\n toJSON() {\\n return this._json = this._json || this._create_json();\\n }\\n _create_json() {\\n return {\\n name: this._name,\\n type: this._type\\n };\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/utils/io/connections/Js.ts\\nvar JsConnectionPointType;\\n(function(JsConnectionPointType2) {\\n JsConnectionPointType2[\\\\\\\"BOOL\\\\\\\"] = \\\\\\\"bool\\\\\\\";\\n JsConnectionPointType2[\\\\\\\"INT\\\\\\\"] = \\\\\\\"int\\\\\\\";\\n JsConnectionPointType2[\\\\\\\"FLOAT\\\\\\\"] = \\\\\\\"float\\\\\\\";\\n JsConnectionPointType2[\\\\\\\"VEC2\\\\\\\"] = \\\\\\\"vec2\\\\\\\";\\n JsConnectionPointType2[\\\\\\\"VEC3\\\\\\\"] = \\\\\\\"vec3\\\\\\\";\\n JsConnectionPointType2[\\\\\\\"VEC4\\\\\\\"] = \\\\\\\"vec4\\\\\\\";\\n})(JsConnectionPointType || (JsConnectionPointType = {}));\\nvar JS_CONNECTION_POINT_TYPES = [\\n JsConnectionPointType.BOOL,\\n JsConnectionPointType.INT,\\n JsConnectionPointType.FLOAT,\\n JsConnectionPointType.VEC2,\\n JsConnectionPointType.VEC3,\\n JsConnectionPointType.VEC4\\n];\\nvar JsConnectionPointTypeToParamTypeMap = {\\n [JsConnectionPointType.BOOL]: ParamType.BOOLEAN,\\n [JsConnectionPointType.INT]: ParamType.INTEGER,\\n [JsConnectionPointType.FLOAT]: ParamType.FLOAT,\\n [JsConnectionPointType.VEC2]: ParamType.VECTOR2,\\n [JsConnectionPointType.VEC3]: ParamType.VECTOR3,\\n [JsConnectionPointType.VEC4]: ParamType.VECTOR4\\n};\\nvar JsParamTypeToConnectionPointTypeMap = {\\n [ParamType.BOOLEAN]: JsConnectionPointType.BOOL,\\n [ParamType.COLOR]: JsConnectionPointType.VEC3,\\n [ParamType.INTEGER]: JsConnectionPointType.INT,\\n [ParamType.FLOAT]: JsConnectionPointType.FLOAT,\\n [ParamType.FOLDER]: void 0,\\n [ParamType.VECTOR2]: JsConnectionPointType.VEC2,\\n [ParamType.VECTOR3]: JsConnectionPointType.VEC3,\\n [ParamType.VECTOR4]: JsConnectionPointType.VEC4,\\n [ParamType.BUTTON]: void 0,\\n [ParamType.OPERATOR_PATH]: void 0,\\n [ParamType.PARAM_PATH]: void 0,\\n [ParamType.NODE_PATH]: void 0,\\n [ParamType.RAMP]: void 0,\\n [ParamType.STRING]: void 0\\n};\\nvar JsConnectionPointInitValueMap = {\\n [JsConnectionPointType.BOOL]: false,\\n [JsConnectionPointType.INT]: 0,\\n [JsConnectionPointType.FLOAT]: 0,\\n [JsConnectionPointType.VEC2]: [0, 0],\\n [JsConnectionPointType.VEC3]: [0, 0, 0],\\n [JsConnectionPointType.VEC4]: [0, 0, 0, 0]\\n};\\nvar GlConnectionPointComponentsCountMap2 = {\\n [JsConnectionPointType.BOOL]: 1,\\n [JsConnectionPointType.INT]: 1,\\n [JsConnectionPointType.FLOAT]: 1,\\n [JsConnectionPointType.VEC2]: 2,\\n [JsConnectionPointType.VEC3]: 3,\\n [JsConnectionPointType.VEC4]: 4\\n};\\nvar JsConnectionPoint = class extends BaseConnectionPoint {\\n constructor(_name, _type) {\\n super(_name, _type);\\n this._name = _name;\\n this._type = _type;\\n this._init_value = JsConnectionPointInitValueMap[this._type];\\n }\\n type() {\\n return this._type;\\n }\\n are_types_matched(src_type, dest_type) {\\n return src_type == dest_type;\\n }\\n get param_type() {\\n return JsConnectionPointTypeToParamTypeMap[this._type];\\n }\\n get init_value() {\\n return this._init_value;\\n }\\n toJSON() {\\n return this._json = this._json || this._create_json();\\n }\\n _create_json() {\\n return {\\n name: this._name,\\n type: this._type\\n };\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/utils/io/connections/Event.ts\\nvar EventConnectionPointType;\\n(function(EventConnectionPointType2) {\\n EventConnectionPointType2[\\\\\\\"BASE\\\\\\\"] = \\\\\\\"base\\\\\\\";\\n EventConnectionPointType2[\\\\\\\"DRAG\\\\\\\"] = \\\\\\\"drag\\\\\\\";\\n EventConnectionPointType2[\\\\\\\"KEYBOARD\\\\\\\"] = \\\\\\\"keyboard\\\\\\\";\\n EventConnectionPointType2[\\\\\\\"MOUSE\\\\\\\"] = \\\\\\\"mouse\\\\\\\";\\n EventConnectionPointType2[\\\\\\\"POINTER\\\\\\\"] = \\\\\\\"pointer\\\\\\\";\\n})(EventConnectionPointType || (EventConnectionPointType = {}));\\nvar EventConnectionPoint = class extends BaseConnectionPoint {\\n constructor(_name, _type, _event_listener) {\\n super(_name, _type);\\n this._name = _name;\\n this._type = _type;\\n this._event_listener = _event_listener;\\n }\\n type() {\\n return this._type;\\n }\\n get param_type() {\\n return ParamType.FLOAT;\\n }\\n are_types_matched(src_type, dest_type) {\\n if (dest_type == EventConnectionPointType.BASE) {\\n return true;\\n } else {\\n return src_type == dest_type;\\n }\\n }\\n get event_listener() {\\n return this._event_listener;\\n }\\n toJSON() {\\n return this._json = this._json || this._create_json();\\n }\\n _create_json() {\\n return {\\n name: this._name,\\n type: this._type\\n };\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/utils/io/connections/ConnectionMap.ts\\nvar DEFAULT_CONNECTION_POINT_ENUM_MAP = {\\n [NodeContext.ANIM]: void 0,\\n [NodeContext.COP]: void 0,\\n [NodeContext.EVENT]: EventConnectionPointType.BASE,\\n [NodeContext.GL]: GlConnectionPointType.FLOAT,\\n [NodeContext.JS]: JsConnectionPointType.FLOAT,\\n [NodeContext.MANAGER]: void 0,\\n [NodeContext.MAT]: void 0,\\n [NodeContext.OBJ]: void 0,\\n [NodeContext.POST]: void 0,\\n [NodeContext.ROP]: void 0,\\n [NodeContext.SOP]: void 0\\n};\\nfunction create_connection_point(context, name, type) {\\n switch (context) {\\n case NodeContext.EVENT: {\\n return new EventConnectionPoint(name, type);\\n }\\n case NodeContext.GL: {\\n return new GlConnectionPoint(name, type);\\n }\\n case NodeContext.JS: {\\n return new JsConnectionPoint(name, type);\\n }\\n default: {\\n return void 0;\\n }\\n }\\n}\\nfunction param_type_to_connection_point_type_map(context) {\\n switch (context) {\\n case NodeContext.EVENT: {\\n return void 0;\\n }\\n case NodeContext.GL: {\\n return GLParamTypeToConnectionPointTypeMap;\\n }\\n case NodeContext.JS: {\\n return JsParamTypeToConnectionPointTypeMap;\\n }\\n default: {\\n return void 0;\\n }\\n }\\n}\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/utils/io/ConnectionPointsSpareParamsController.ts\\nvar ConnectionPointsSpareParamsController = class {\\n constructor(node, _context2) {\\n this.node = node;\\n this._context = _context2;\\n this._raw_input_serialized_by_param_name = new Map();\\n this._default_value_serialized_by_param_name = new Map();\\n this._initialized = false;\\n }\\n initializeNode() {\\n if (this._initialized) {\\n console.warn(\\\\\\\"already initialized\\\\\\\", this.node);\\n return;\\n }\\n this._initialized = true;\\n this.node.params.onParamsCreated(\\\\\\\"create_inputs_from_params\\\\\\\", this.create_inputs_from_params.bind(this));\\n }\\n initialized() {\\n return this._initialized;\\n }\\n create_inputs_from_params() {\\n const connection_type_map = param_type_to_connection_point_type_map(this._context);\\n if (!connection_type_map) {\\n return;\\n }\\n const connection_points = [];\\n for (let param_name of this.node.params.names) {\\n let add_input = true;\\n if (this._inputless_param_names && this._inputless_param_names.length > 0 && this._inputless_param_names.includes(param_name)) {\\n add_input = false;\\n }\\n if (add_input) {\\n if (this.node.params.has(param_name)) {\\n const param = this.node.params.get(param_name);\\n if (param && !param.parent_param) {\\n const connection_type = connection_type_map[param.type()];\\n if (connection_type) {\\n const connection_point = create_connection_point(this._context, param.name(), connection_type);\\n if (connection_point) {\\n connection_points.push(connection_point);\\n }\\n }\\n }\\n }\\n }\\n }\\n this.node.io.inputs.setNamedInputConnectionPoints(connection_points);\\n }\\n set_inputless_param_names(names) {\\n return this._inputless_param_names = names;\\n }\\n createSpareParameters() {\\n if (this.node.scene().loadingController.isLoading()) {\\n return;\\n }\\n const current_param_names = this.node.params.spare_names;\\n const params_update_options = {};\\n for (let param_name of current_param_names) {\\n if (this.node.params.has(param_name)) {\\n const param = this.node.params.get(param_name);\\n if (param) {\\n this._raw_input_serialized_by_param_name.set(param_name, param.rawInputSerialized());\\n this._default_value_serialized_by_param_name.set(param_name, param.defaultValueSerialized());\\n params_update_options.namesToDelete = params_update_options.namesToDelete || [];\\n params_update_options.namesToDelete.push(param_name);\\n }\\n }\\n }\\n for (let connection_point of this.node.io.inputs.namedInputConnectionPoints()) {\\n if (connection_point) {\\n const param_name = connection_point.name();\\n const param_type = connection_point.param_type;\\n let init_value = connection_point.init_value;\\n const last_param_init_value = this._default_value_serialized_by_param_name.get(param_name);\\n let default_value_from_name = this.node.paramDefaultValue(param_name);\\n if (default_value_from_name != null) {\\n init_value = default_value_from_name;\\n } else {\\n if (last_param_init_value != null) {\\n init_value = last_param_init_value;\\n } else {\\n init_value = connection_point.init_value;\\n }\\n }\\n if (CoreType.isArray(connection_point.init_value)) {\\n if (CoreType.isNumber(init_value)) {\\n const array = new Array(connection_point.init_value.length);\\n array.fill(init_value);\\n init_value = array;\\n } else if (CoreType.isArray(init_value)) {\\n if (init_value.length == connection_point.init_value.length) {\\n if (last_param_init_value != null) {\\n init_value = connection_point.init_value;\\n }\\n }\\n }\\n }\\n if (init_value != null) {\\n params_update_options.toAdd = params_update_options.toAdd || [];\\n params_update_options.toAdd.push({\\n name: param_name,\\n type: param_type,\\n init_value: ObjectUtils.clone(init_value),\\n raw_input: ObjectUtils.clone(init_value),\\n options: {\\n spare: true\\n }\\n });\\n }\\n }\\n }\\n this.node.params.updateParams(params_update_options);\\n for (let spare_param of this.node.params.spare) {\\n if (!spare_param.parent_param) {\\n const raw_input = this._raw_input_serialized_by_param_name.get(spare_param.name());\\n if (raw_input) {\\n spare_param.set(raw_input);\\n }\\n }\\n }\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/utils/io/ConnectionPointsController.ts\\nvar ConnectionPointsController = class {\\n constructor(node, _context2) {\\n this.node = node;\\n this._context = _context2;\\n this._create_spare_params_from_inputs = true;\\n this._functions_overridden = false;\\n this._input_name_function = (index) => {\\n return `in${index}`;\\n };\\n this._output_name_function = (index) => {\\n return index == 0 ? \\\\\\\"val\\\\\\\" : `val${index}`;\\n };\\n this._expected_input_types_function = () => {\\n const type = this.first_input_connection_type() || this.default_connection_type();\\n return [type, type];\\n };\\n this._expected_output_types_function = () => {\\n return [this._expected_input_types_function()[0]];\\n };\\n this._update_signature_if_required_bound = this.update_signature_if_required.bind(this);\\n this._initialized = false;\\n this._spare_params_controller = new ConnectionPointsSpareParamsController(this.node, this._context);\\n }\\n default_connection_type() {\\n return DEFAULT_CONNECTION_POINT_ENUM_MAP[this._context];\\n }\\n create_connection_point(name, type) {\\n return create_connection_point(this._context, name, type);\\n }\\n functions_overridden() {\\n return this._functions_overridden;\\n }\\n initialized() {\\n return this._initialized;\\n }\\n set_create_spare_params_from_inputs(state) {\\n this._create_spare_params_from_inputs = state;\\n }\\n set_input_name_function(func) {\\n this._initialize_if_required();\\n this._input_name_function = func;\\n }\\n set_output_name_function(func) {\\n this._initialize_if_required();\\n this._output_name_function = func;\\n }\\n set_expected_input_types_function(func) {\\n this._initialize_if_required();\\n this._functions_overridden = true;\\n this._expected_input_types_function = func;\\n }\\n set_expected_output_types_function(func) {\\n this._initialize_if_required();\\n this._functions_overridden = true;\\n this._expected_output_types_function = func;\\n }\\n input_name(index) {\\n return this._wrapped_input_name_function(index);\\n }\\n output_name(index) {\\n return this._wrapped_output_name_function(index);\\n }\\n initializeNode() {\\n if (this._initialized) {\\n console.warn(\\\\\\\"already initialized\\\\\\\", this.node);\\n return;\\n }\\n this._initialized = true;\\n this.node.io.inputs.add_on_set_input_hook(\\\\\\\"_update_signature_if_required\\\\\\\", this._update_signature_if_required_bound);\\n this.node.params.addOnSceneLoadHook(\\\\\\\"_update_signature_if_required\\\\\\\", this._update_signature_if_required_bound);\\n this.node.params.onParamsCreated(\\\\\\\"_update_signature_if_required_bound\\\\\\\", this._update_signature_if_required_bound);\\n this.node.addPostDirtyHook(\\\\\\\"_update_signature_if_required\\\\\\\", this._update_signature_if_required_bound);\\n if (!this._spare_params_controller.initialized()) {\\n this._spare_params_controller.initializeNode();\\n }\\n }\\n _initialize_if_required() {\\n if (!this._initialized) {\\n this.initializeNode();\\n }\\n }\\n get spare_params() {\\n return this._spare_params_controller;\\n }\\n update_signature_if_required(dirty_trigger) {\\n if (!this.node.lifecycle.creationCompleted() || !this._connections_match_inputs()) {\\n this.update_connection_types();\\n this.node.removeDirtyState();\\n if (!this.node.scene().loadingController.isLoading()) {\\n this.make_successors_update_signatures();\\n }\\n }\\n }\\n make_successors_update_signatures() {\\n const successors = this.node.graphAllSuccessors();\\n if (this.node.childrenAllowed()) {\\n const subnet_inputs = this.node.nodesByType(NetworkChildNodeType.INPUT);\\n const subnet_outputs = this.node.nodesByType(NetworkChildNodeType.OUTPUT);\\n for (let subnet_input of subnet_inputs) {\\n successors.push(subnet_input);\\n }\\n for (let subnet_output of subnet_outputs) {\\n successors.push(subnet_output);\\n }\\n }\\n for (let graph_node of successors) {\\n const node = graph_node;\\n if (node.io && node.io.has_connection_points_controller && node.io.connection_points.initialized()) {\\n node.io.connection_points.update_signature_if_required(this.node);\\n }\\n }\\n }\\n update_connection_types() {\\n const set_dirty = false;\\n const expected_input_types = this._wrapped_expected_input_types_function();\\n const expected_output_types = this._wrapped_expected_output_types_function();\\n const named_input_connection_points = [];\\n for (let i = 0; i < expected_input_types.length; i++) {\\n const type = expected_input_types[i];\\n const point = this.create_connection_point(this._wrapped_input_name_function(i), type);\\n named_input_connection_points.push(point);\\n }\\n const named_output_connect_points = [];\\n for (let i = 0; i < expected_output_types.length; i++) {\\n const type = expected_output_types[i];\\n const point = this.create_connection_point(this._wrapped_output_name_function(i), type);\\n named_output_connect_points.push(point);\\n }\\n this.node.io.inputs.setNamedInputConnectionPoints(named_input_connection_points);\\n this.node.io.outputs.setNamedOutputConnectionPoints(named_output_connect_points, set_dirty);\\n if (this._create_spare_params_from_inputs) {\\n this._spare_params_controller.createSpareParameters();\\n }\\n }\\n _connections_match_inputs() {\\n const current_input_types = this.node.io.inputs.namedInputConnectionPoints().map((c) => c?.type());\\n const current_output_types = this.node.io.outputs.namedOutputConnectionPoints().map((c) => c?.type());\\n const expected_input_types = this._wrapped_expected_input_types_function();\\n const expected_output_types = this._wrapped_expected_output_types_function();\\n if (expected_input_types.length != current_input_types.length) {\\n return false;\\n }\\n if (expected_output_types.length != current_output_types.length) {\\n return false;\\n }\\n for (let i = 0; i < current_input_types.length; i++) {\\n if (current_input_types[i] != expected_input_types[i]) {\\n return false;\\n }\\n }\\n for (let i = 0; i < current_output_types.length; i++) {\\n if (current_output_types[i] != expected_output_types[i]) {\\n return false;\\n }\\n }\\n return true;\\n }\\n _wrapped_expected_input_types_function() {\\n if (this.node.scene().loadingController.isLoading()) {\\n const in_data = this.node.io.saved_connection_points_data.in();\\n if (in_data) {\\n return in_data.map((d) => d.type);\\n }\\n }\\n return this._expected_input_types_function();\\n }\\n _wrapped_expected_output_types_function() {\\n if (this.node.scene().loadingController.isLoading()) {\\n const out_data = this.node.io.saved_connection_points_data.out();\\n if (out_data) {\\n return out_data.map((d) => d.type);\\n }\\n }\\n return this._expected_output_types_function();\\n }\\n _wrapped_input_name_function(index) {\\n if (this.node.scene().loadingController.isLoading()) {\\n const in_data = this.node.io.saved_connection_points_data.in();\\n if (in_data) {\\n return in_data[index].name;\\n }\\n }\\n return this._input_name_function(index);\\n }\\n _wrapped_output_name_function(index) {\\n if (this.node.scene().loadingController.isLoading()) {\\n const out_data = this.node.io.saved_connection_points_data.out();\\n if (out_data) {\\n return out_data[index].name;\\n }\\n }\\n return this._output_name_function(index);\\n }\\n first_input_connection_type() {\\n return this.input_connection_type(0);\\n }\\n input_connection_type(index) {\\n const connections = this.node.io.connections.inputConnections();\\n if (connections) {\\n const connection = connections[index];\\n if (connection) {\\n return connection.src_connection_point().type();\\n }\\n }\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/utils/io/IOController.ts\\nvar IOController = class {\\n constructor(node) {\\n this.node = node;\\n this._connections = new ConnectionsController(this.node);\\n }\\n get connections() {\\n return this._connections;\\n }\\n get inputs() {\\n return this._inputs = this._inputs || new InputsController2(this.node);\\n }\\n has_inputs() {\\n return this._inputs != null;\\n }\\n get outputs() {\\n return this._outputs = this._outputs || new OutputsController(this.node);\\n }\\n has_outputs() {\\n return this._outputs != null;\\n }\\n get connection_points() {\\n return this._connection_points = this._connection_points || new ConnectionPointsController(this.node, this.node.context());\\n }\\n get has_connection_points_controller() {\\n return this._connection_points != null;\\n }\\n get saved_connection_points_data() {\\n return this._saved_connection_points_data = this._saved_connection_points_data || new SavedConnectionPointsDataController(this.node);\\n }\\n clear_saved_connection_points_data() {\\n if (this._saved_connection_points_data) {\\n this._saved_connection_points_data.clear();\\n this._saved_connection_points_data = void 0;\\n }\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/utils/params/ParamsAccessor.ts\\nvar ParamsAccessor = class {\\n constructor() {\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/_Base.ts\\nvar TypedNode = class extends CoreGraphNode {\\n constructor(scene, name = \\\\\\\"BaseNode\\\\\\\", params_init_value_overrides) {\\n super(scene, name);\\n this.params_init_value_overrides = params_init_value_overrides;\\n this.containerController = new TypedContainerController(this);\\n this.pv = new ParamsValueAccessor();\\n this.p = new ParamsAccessor();\\n this._initialized = false;\\n }\\n copy_param_values(node) {\\n const non_spare = this.params.non_spare;\\n for (let param of non_spare) {\\n const other_param = node.params.get(param.name());\\n if (other_param) {\\n param.copy_value(other_param);\\n }\\n }\\n }\\n get parentController() {\\n return this._parent_controller = this._parent_controller || new HierarchyParentController(this);\\n }\\n static displayedInputNames() {\\n return [];\\n }\\n get childrenControllerContext() {\\n return this._children_controller_context;\\n }\\n _create_children_controller() {\\n if (this._children_controller_context) {\\n return new HierarchyChildrenController(this, this._children_controller_context);\\n }\\n }\\n get childrenController() {\\n return this._children_controller = this._children_controller || this._create_children_controller();\\n }\\n childrenAllowed() {\\n return this._children_controller_context != null;\\n }\\n get uiData() {\\n return this._ui_data = this._ui_data || new UIData(this);\\n }\\n get states() {\\n return this._states = this._states || new StatesController(this);\\n }\\n get lifecycle() {\\n return this._lifecycle = this._lifecycle || new LifeCycleController(this);\\n }\\n get serializer() {\\n return this._serializer = this._serializer || new NodeSerializer(this);\\n }\\n get cookController() {\\n return this._cook_controller = this._cook_controller || new NodeCookController(this);\\n }\\n get io() {\\n return this._io = this._io || new IOController(this);\\n }\\n get nameController() {\\n return this._name_controller = this._name_controller || new NameController(this);\\n }\\n setName(name) {\\n this.nameController.setName(name);\\n }\\n _set_core_name(name) {\\n this._name = name;\\n }\\n get params() {\\n return this._params_controller = this._params_controller || new ParamsController(this);\\n }\\n initialize_base_and_node() {\\n if (!this._initialized) {\\n this._initialized = true;\\n this.displayNodeController?.initializeNode();\\n this.initializeBaseNode();\\n this.initializeNode();\\n if (this.polyNodeController) {\\n this.polyNodeController.initializeNode();\\n }\\n } else {\\n console.warn(\\\\\\\"node already initialized\\\\\\\");\\n }\\n }\\n initializeBaseNode() {\\n }\\n initializeNode() {\\n }\\n static type() {\\n throw \\\\\\\"type to be overriden\\\\\\\";\\n }\\n type() {\\n const c = this.constructor;\\n return c.type();\\n }\\n static context() {\\n console.error(\\\\\\\"node has no node_context\\\\\\\", this);\\n throw \\\\\\\"context requires override\\\\\\\";\\n }\\n context() {\\n const c = this.constructor;\\n return c.context();\\n }\\n static require_webgl2() {\\n return false;\\n }\\n require_webgl2() {\\n const c = this.constructor;\\n return c.require_webgl2();\\n }\\n setParent(parent) {\\n this.parentController.setParent(parent);\\n }\\n parent() {\\n return this.parentController.parent();\\n }\\n firstAncestorWithContext(context) {\\n return this.parentController.firstAncestorWithContext(context);\\n }\\n root() {\\n return this._scene.root();\\n }\\n path(relative_to_parent) {\\n return this.parentController.path(relative_to_parent);\\n }\\n createParams() {\\n }\\n addParam(type, name, default_value, options) {\\n return this._params_controller?.addParam(type, name, default_value, options);\\n }\\n paramDefaultValue(name) {\\n return null;\\n }\\n cook(input_contents) {\\n return null;\\n }\\n onCookEnd(callbackName, callback) {\\n this.cookController.registerOnCookEnd(callbackName, callback);\\n }\\n async compute() {\\n if (this.isDirty() || this.flags?.bypass?.active()) {\\n return await this.containerController.compute();\\n } else {\\n return this.containerController.container();\\n }\\n }\\n _setContainer(content, message = null) {\\n this.containerController.container().set_content(content);\\n if (content != null) {\\n if (!content.name) {\\n content.name = this.path();\\n }\\n if (!content.node) {\\n content.node = this;\\n }\\n }\\n this.cookController.endCook(message);\\n }\\n createNode(nodeClass, params_init_value_overrides) {\\n return this.childrenController?.createNode(nodeClass, params_init_value_overrides);\\n }\\n create_operation_container(type, operation_container_name, params_init_value_overrides) {\\n return this.childrenController?.create_operation_container(type, operation_container_name, params_init_value_overrides);\\n }\\n removeNode(node) {\\n this.childrenController?.removeNode(node);\\n }\\n dispose() {\\n super.dispose();\\n this.setParent(null);\\n this.io.inputs.dispose();\\n this.lifecycle.dispose();\\n this.displayNodeController?.dispose();\\n this.nameController.dispose();\\n this.childrenController?.dispose();\\n this.params.dispose();\\n }\\n children() {\\n return this.childrenController?.children() || [];\\n }\\n node(path) {\\n return this.parentController?.findNode(path) || null;\\n }\\n nodeSibbling(name) {\\n const parent = this.parent();\\n if (parent) {\\n const node = parent.childrenController?.childByName(name);\\n if (node) {\\n return node;\\n }\\n }\\n return null;\\n }\\n nodesByType(type) {\\n return this.childrenController?.nodesByType(type) || [];\\n }\\n setInput(input_index_or_name, node, output_index_or_name = 0) {\\n this.io.inputs.setInput(input_index_or_name, node, output_index_or_name);\\n }\\n emit(event_name, data = null) {\\n this.scene().dispatchController.dispatch(this, event_name, data);\\n }\\n toJSON(include_param_components = false) {\\n return this.serializer.toJSON(include_param_components);\\n }\\n async requiredModules() {\\n }\\n usedAssembler() {\\n }\\n integrationData() {\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/obj/_Base.ts\\nvar INPUT_OBJECT_NAME = \\\\\\\"parent object\\\\\\\";\\nvar DEFAULT_INPUT_NAMES = [INPUT_OBJECT_NAME, INPUT_OBJECT_NAME, INPUT_OBJECT_NAME, INPUT_OBJECT_NAME];\\nvar ObjNodeRenderOrder;\\n(function(ObjNodeRenderOrder2) {\\n ObjNodeRenderOrder2[ObjNodeRenderOrder2[\\\\\\\"MANAGER\\\\\\\"] = 0] = \\\\\\\"MANAGER\\\\\\\";\\n ObjNodeRenderOrder2[ObjNodeRenderOrder2[\\\\\\\"CAMERA\\\\\\\"] = 2] = \\\\\\\"CAMERA\\\\\\\";\\n ObjNodeRenderOrder2[ObjNodeRenderOrder2[\\\\\\\"LIGHT\\\\\\\"] = 3] = \\\\\\\"LIGHT\\\\\\\";\\n})(ObjNodeRenderOrder || (ObjNodeRenderOrder = {}));\\nvar TypedObjNode = class extends TypedNode {\\n constructor() {\\n super(...arguments);\\n this.renderOrder = 0;\\n this._children_group = this._create_children_group();\\n this._attachableToHierarchy = true;\\n this._used_in_scene = true;\\n }\\n static context() {\\n return NodeContext.OBJ;\\n }\\n static displayedInputNames() {\\n return DEFAULT_INPUT_NAMES;\\n }\\n _create_children_group() {\\n const group = new Group();\\n group.matrixAutoUpdate = false;\\n return group;\\n }\\n attachableToHierarchy() {\\n return this._attachableToHierarchy;\\n }\\n usedInScene() {\\n return this._used_in_scene;\\n }\\n addObjectToParent(parent) {\\n if (this.attachableToHierarchy()) {\\n parent.add(this.object);\\n }\\n }\\n removeObjectFromParent() {\\n if (this.attachableToHierarchy()) {\\n const parent = this.object.parent;\\n if (parent) {\\n parent.remove(this.object);\\n }\\n }\\n }\\n initializeBaseNode() {\\n this._object = this._create_object_with_attributes();\\n this.nameController.add_post_set_fullPath_hook(this.set_object_name.bind(this));\\n this.set_object_name();\\n }\\n get children_group() {\\n return this._children_group;\\n }\\n get object() {\\n return this._object;\\n }\\n _create_object_with_attributes() {\\n const object = this.createObject();\\n object.node = this;\\n object.add(this._children_group);\\n return object;\\n }\\n set_object_name() {\\n if (this._object) {\\n this._object.name = this.path();\\n this._children_group.name = `${this.path()}:parented_outputs`;\\n }\\n }\\n createObject() {\\n const object = new Object3D();\\n object.matrixAutoUpdate = false;\\n return object;\\n }\\n isDisplayNodeCooking() {\\n if (this.displayNodeController) {\\n const displayNode = this.displayNodeController.displayNode();\\n if (displayNode) {\\n return displayNode.cookController.isCooking();\\n }\\n }\\n return false;\\n }\\n isDisplayed() {\\n return this.flags?.display?.active() || false;\\n }\\n};\\n\\n// ../../../node_modules/three/src/audio/AudioAnalyser.js\\nvar AudioAnalyser = class {\\n constructor(audio, fftSize = 2048) {\\n this.analyser = audio.context.createAnalyser();\\n this.analyser.fftSize = fftSize;\\n this.data = new Uint8Array(this.analyser.frequencyBinCount);\\n audio.getOutput().connect(this.analyser);\\n }\\n getFrequencyData() {\\n this.analyser.getByteFrequencyData(this.data);\\n return this.data;\\n }\\n getAverageFrequency() {\\n let value = 0;\\n const data = this.getFrequencyData();\\n for (let i = 0; i < data.length; i++) {\\n value += data[i];\\n }\\n return value / data.length;\\n }\\n};\\n\\n// ../../../node_modules/three/src/audio/Audio.js\\nvar Audio2 = class extends Object3D {\\n constructor(listener) {\\n super();\\n this.type = \\\\\\\"Audio\\\\\\\";\\n this.listener = listener;\\n this.context = listener.context;\\n this.gain = this.context.createGain();\\n this.gain.connect(listener.getInput());\\n this.autoplay = false;\\n this.buffer = null;\\n this.detune = 0;\\n this.loop = false;\\n this.loopStart = 0;\\n this.loopEnd = 0;\\n this.offset = 0;\\n this.duration = void 0;\\n this.playbackRate = 1;\\n this.isPlaying = false;\\n this.hasPlaybackControl = true;\\n this.source = null;\\n this.sourceType = \\\\\\\"empty\\\\\\\";\\n this._startedAt = 0;\\n this._progress = 0;\\n this._connected = false;\\n this.filters = [];\\n }\\n getOutput() {\\n return this.gain;\\n }\\n setNodeSource(audioNode) {\\n this.hasPlaybackControl = false;\\n this.sourceType = \\\\\\\"audioNode\\\\\\\";\\n this.source = audioNode;\\n this.connect();\\n return this;\\n }\\n setMediaElementSource(mediaElement) {\\n this.hasPlaybackControl = false;\\n this.sourceType = \\\\\\\"mediaNode\\\\\\\";\\n this.source = this.context.createMediaElementSource(mediaElement);\\n this.connect();\\n return this;\\n }\\n setMediaStreamSource(mediaStream) {\\n this.hasPlaybackControl = false;\\n this.sourceType = \\\\\\\"mediaStreamNode\\\\\\\";\\n this.source = this.context.createMediaStreamSource(mediaStream);\\n this.connect();\\n return this;\\n }\\n setBuffer(audioBuffer) {\\n this.buffer = audioBuffer;\\n this.sourceType = \\\\\\\"buffer\\\\\\\";\\n if (this.autoplay)\\n this.play();\\n return this;\\n }\\n play(delay = 0) {\\n if (this.isPlaying === true) {\\n console.warn(\\\\\\\"THREE.Audio: Audio is already playing.\\\\\\\");\\n return;\\n }\\n if (this.hasPlaybackControl === false) {\\n console.warn(\\\\\\\"THREE.Audio: this Audio has no playback control.\\\\\\\");\\n return;\\n }\\n this._startedAt = this.context.currentTime + delay;\\n const source = this.context.createBufferSource();\\n source.buffer = this.buffer;\\n source.loop = this.loop;\\n source.loopStart = this.loopStart;\\n source.loopEnd = this.loopEnd;\\n source.onended = this.onEnded.bind(this);\\n source.start(this._startedAt, this._progress + this.offset, this.duration);\\n this.isPlaying = true;\\n this.source = source;\\n this.setDetune(this.detune);\\n this.setPlaybackRate(this.playbackRate);\\n return this.connect();\\n }\\n pause() {\\n if (this.hasPlaybackControl === false) {\\n console.warn(\\\\\\\"THREE.Audio: this Audio has no playback control.\\\\\\\");\\n return;\\n }\\n if (this.isPlaying === true) {\\n this._progress += Math.max(this.context.currentTime - this._startedAt, 0) * this.playbackRate;\\n if (this.loop === true) {\\n this._progress = this._progress % (this.duration || this.buffer.duration);\\n }\\n this.source.stop();\\n this.source.onended = null;\\n this.isPlaying = false;\\n }\\n return this;\\n }\\n stop() {\\n if (this.hasPlaybackControl === false) {\\n console.warn(\\\\\\\"THREE.Audio: this Audio has no playback control.\\\\\\\");\\n return;\\n }\\n this._progress = 0;\\n this.source.stop();\\n this.source.onended = null;\\n this.isPlaying = false;\\n return this;\\n }\\n connect() {\\n if (this.filters.length > 0) {\\n this.source.connect(this.filters[0]);\\n for (let i = 1, l = this.filters.length; i < l; i++) {\\n this.filters[i - 1].connect(this.filters[i]);\\n }\\n this.filters[this.filters.length - 1].connect(this.getOutput());\\n } else {\\n this.source.connect(this.getOutput());\\n }\\n this._connected = true;\\n return this;\\n }\\n disconnect() {\\n if (this.filters.length > 0) {\\n this.source.disconnect(this.filters[0]);\\n for (let i = 1, l = this.filters.length; i < l; i++) {\\n this.filters[i - 1].disconnect(this.filters[i]);\\n }\\n this.filters[this.filters.length - 1].disconnect(this.getOutput());\\n } else {\\n this.source.disconnect(this.getOutput());\\n }\\n this._connected = false;\\n return this;\\n }\\n getFilters() {\\n return this.filters;\\n }\\n setFilters(value) {\\n if (!value)\\n value = [];\\n if (this._connected === true) {\\n this.disconnect();\\n this.filters = value.slice();\\n this.connect();\\n } else {\\n this.filters = value.slice();\\n }\\n return this;\\n }\\n setDetune(value) {\\n this.detune = value;\\n if (this.source.detune === void 0)\\n return;\\n if (this.isPlaying === true) {\\n this.source.detune.setTargetAtTime(this.detune, this.context.currentTime, 0.01);\\n }\\n return this;\\n }\\n getDetune() {\\n return this.detune;\\n }\\n getFilter() {\\n return this.getFilters()[0];\\n }\\n setFilter(filter) {\\n return this.setFilters(filter ? [filter] : []);\\n }\\n setPlaybackRate(value) {\\n if (this.hasPlaybackControl === false) {\\n console.warn(\\\\\\\"THREE.Audio: this Audio has no playback control.\\\\\\\");\\n return;\\n }\\n this.playbackRate = value;\\n if (this.isPlaying === true) {\\n this.source.playbackRate.setTargetAtTime(this.playbackRate, this.context.currentTime, 0.01);\\n }\\n return this;\\n }\\n getPlaybackRate() {\\n return this.playbackRate;\\n }\\n onEnded() {\\n this.isPlaying = false;\\n }\\n getLoop() {\\n if (this.hasPlaybackControl === false) {\\n console.warn(\\\\\\\"THREE.Audio: this Audio has no playback control.\\\\\\\");\\n return false;\\n }\\n return this.loop;\\n }\\n setLoop(value) {\\n if (this.hasPlaybackControl === false) {\\n console.warn(\\\\\\\"THREE.Audio: this Audio has no playback control.\\\\\\\");\\n return;\\n }\\n this.loop = value;\\n if (this.isPlaying === true) {\\n this.source.loop = this.loop;\\n }\\n return this;\\n }\\n setLoopStart(value) {\\n this.loopStart = value;\\n return this;\\n }\\n setLoopEnd(value) {\\n this.loopEnd = value;\\n return this;\\n }\\n getVolume() {\\n return this.gain.gain.value;\\n }\\n setVolume(value) {\\n this.gain.gain.setTargetAtTime(value, this.context.currentTime, 0.01);\\n return this;\\n }\\n};\\n\\n// ../../../node_modules/three/src/audio/AudioContext.js\\nvar _context;\\nvar AudioContext = {\\n getContext: function() {\\n if (_context === void 0) {\\n _context = new (window.AudioContext || window.webkitAudioContext)();\\n }\\n return _context;\\n },\\n setContext: function(value) {\\n _context = value;\\n }\\n};\\n\\n// ../../../node_modules/three/src/loaders/Cache.js\\nvar Cache = {\\n enabled: false,\\n files: {},\\n add: function(key, file) {\\n if (this.enabled === false)\\n return;\\n this.files[key] = file;\\n },\\n get: function(key) {\\n if (this.enabled === false)\\n return;\\n return this.files[key];\\n },\\n remove: function(key) {\\n delete this.files[key];\\n },\\n clear: function() {\\n this.files = {};\\n }\\n};\\n\\n// ../../../node_modules/three/src/loaders/LoadingManager.js\\nvar LoadingManager = class {\\n constructor(onLoad, onProgress, onError) {\\n const scope = this;\\n let isLoading = false;\\n let itemsLoaded = 0;\\n let itemsTotal = 0;\\n let urlModifier = void 0;\\n const handlers = [];\\n this.onStart = void 0;\\n this.onLoad = onLoad;\\n this.onProgress = onProgress;\\n this.onError = onError;\\n this.itemStart = function(url) {\\n itemsTotal++;\\n if (isLoading === false) {\\n if (scope.onStart !== void 0) {\\n scope.onStart(url, itemsLoaded, itemsTotal);\\n }\\n }\\n isLoading = true;\\n };\\n this.itemEnd = function(url) {\\n itemsLoaded++;\\n if (scope.onProgress !== void 0) {\\n scope.onProgress(url, itemsLoaded, itemsTotal);\\n }\\n if (itemsLoaded === itemsTotal) {\\n isLoading = false;\\n if (scope.onLoad !== void 0) {\\n scope.onLoad();\\n }\\n }\\n };\\n this.itemError = function(url) {\\n if (scope.onError !== void 0) {\\n scope.onError(url);\\n }\\n };\\n this.resolveURL = function(url) {\\n if (urlModifier) {\\n return urlModifier(url);\\n }\\n return url;\\n };\\n this.setURLModifier = function(transform) {\\n urlModifier = transform;\\n return this;\\n };\\n this.addHandler = function(regex, loader) {\\n handlers.push(regex, loader);\\n return this;\\n };\\n this.removeHandler = function(regex) {\\n const index = handlers.indexOf(regex);\\n if (index !== -1) {\\n handlers.splice(index, 2);\\n }\\n return this;\\n };\\n this.getHandler = function(file) {\\n for (let i = 0, l = handlers.length; i < l; i += 2) {\\n const regex = handlers[i];\\n const loader = handlers[i + 1];\\n if (regex.global)\\n regex.lastIndex = 0;\\n if (regex.test(file)) {\\n return loader;\\n }\\n }\\n return null;\\n };\\n }\\n};\\nvar DefaultLoadingManager = new LoadingManager();\\n\\n// ../../../node_modules/three/src/loaders/Loader.js\\nvar Loader = class {\\n constructor(manager) {\\n this.manager = manager !== void 0 ? manager : DefaultLoadingManager;\\n this.crossOrigin = \\\\\\\"anonymous\\\\\\\";\\n this.withCredentials = false;\\n this.path = \\\\\\\"\\\\\\\";\\n this.resourcePath = \\\\\\\"\\\\\\\";\\n this.requestHeader = {};\\n }\\n load() {\\n }\\n loadAsync(url, onProgress) {\\n const scope = this;\\n return new Promise(function(resolve, reject) {\\n scope.load(url, resolve, onProgress, reject);\\n });\\n }\\n parse() {\\n }\\n setCrossOrigin(crossOrigin) {\\n this.crossOrigin = crossOrigin;\\n return this;\\n }\\n setWithCredentials(value) {\\n this.withCredentials = value;\\n return this;\\n }\\n setPath(path) {\\n this.path = path;\\n return this;\\n }\\n setResourcePath(resourcePath) {\\n this.resourcePath = resourcePath;\\n return this;\\n }\\n setRequestHeader(requestHeader) {\\n this.requestHeader = requestHeader;\\n return this;\\n }\\n};\\n\\n// ../../../node_modules/three/src/loaders/FileLoader.js\\nvar loading = {};\\nvar FileLoader = class extends Loader {\\n constructor(manager) {\\n super(manager);\\n }\\n load(url, onLoad, onProgress, onError) {\\n if (url === void 0)\\n url = \\\\\\\"\\\\\\\";\\n if (this.path !== void 0)\\n url = this.path + url;\\n url = this.manager.resolveURL(url);\\n const scope = this;\\n const cached = Cache.get(url);\\n if (cached !== void 0) {\\n scope.manager.itemStart(url);\\n setTimeout(function() {\\n if (onLoad)\\n onLoad(cached);\\n scope.manager.itemEnd(url);\\n }, 0);\\n return cached;\\n }\\n if (loading[url] !== void 0) {\\n loading[url].push({\\n onLoad,\\n onProgress,\\n onError\\n });\\n return;\\n }\\n const dataUriRegex = /^data:(.*?)(;base64)?,(.*)$/;\\n const dataUriRegexResult = url.match(dataUriRegex);\\n let request;\\n if (dataUriRegexResult) {\\n const mimeType = dataUriRegexResult[1];\\n const isBase64 = !!dataUriRegexResult[2];\\n let data = dataUriRegexResult[3];\\n data = decodeURIComponent(data);\\n if (isBase64)\\n data = atob(data);\\n try {\\n let response;\\n const responseType = (this.responseType || \\\\\\\"\\\\\\\").toLowerCase();\\n switch (responseType) {\\n case \\\\\\\"arraybuffer\\\\\\\":\\n case \\\\\\\"blob\\\\\\\":\\n const view = new Uint8Array(data.length);\\n for (let i = 0; i < data.length; i++) {\\n view[i] = data.charCodeAt(i);\\n }\\n if (responseType === \\\\\\\"blob\\\\\\\") {\\n response = new Blob([view.buffer], {type: mimeType});\\n } else {\\n response = view.buffer;\\n }\\n break;\\n case \\\\\\\"document\\\\\\\":\\n const parser = new DOMParser();\\n response = parser.parseFromString(data, mimeType);\\n break;\\n case \\\\\\\"json\\\\\\\":\\n response = JSON.parse(data);\\n break;\\n default:\\n response = data;\\n break;\\n }\\n setTimeout(function() {\\n if (onLoad)\\n onLoad(response);\\n scope.manager.itemEnd(url);\\n }, 0);\\n } catch (error) {\\n setTimeout(function() {\\n if (onError)\\n onError(error);\\n scope.manager.itemError(url);\\n scope.manager.itemEnd(url);\\n }, 0);\\n }\\n } else {\\n loading[url] = [];\\n loading[url].push({\\n onLoad,\\n onProgress,\\n onError\\n });\\n request = new XMLHttpRequest();\\n request.open(\\\\\\\"GET\\\\\\\", url, true);\\n request.addEventListener(\\\\\\\"load\\\\\\\", function(event) {\\n const response = this.response;\\n const callbacks = loading[url];\\n delete loading[url];\\n if (this.status === 200 || this.status === 0) {\\n if (this.status === 0)\\n console.warn(\\\\\\\"THREE.FileLoader: HTTP Status 0 received.\\\\\\\");\\n Cache.add(url, response);\\n for (let i = 0, il = callbacks.length; i < il; i++) {\\n const callback = callbacks[i];\\n if (callback.onLoad)\\n callback.onLoad(response);\\n }\\n scope.manager.itemEnd(url);\\n } else {\\n for (let i = 0, il = callbacks.length; i < il; i++) {\\n const callback = callbacks[i];\\n if (callback.onError)\\n callback.onError(event);\\n }\\n scope.manager.itemError(url);\\n scope.manager.itemEnd(url);\\n }\\n }, false);\\n request.addEventListener(\\\\\\\"progress\\\\\\\", function(event) {\\n const callbacks = loading[url];\\n for (let i = 0, il = callbacks.length; i < il; i++) {\\n const callback = callbacks[i];\\n if (callback.onProgress)\\n callback.onProgress(event);\\n }\\n }, false);\\n request.addEventListener(\\\\\\\"error\\\\\\\", function(event) {\\n const callbacks = loading[url];\\n delete loading[url];\\n for (let i = 0, il = callbacks.length; i < il; i++) {\\n const callback = callbacks[i];\\n if (callback.onError)\\n callback.onError(event);\\n }\\n scope.manager.itemError(url);\\n scope.manager.itemEnd(url);\\n }, false);\\n request.addEventListener(\\\\\\\"abort\\\\\\\", function(event) {\\n const callbacks = loading[url];\\n delete loading[url];\\n for (let i = 0, il = callbacks.length; i < il; i++) {\\n const callback = callbacks[i];\\n if (callback.onError)\\n callback.onError(event);\\n }\\n scope.manager.itemError(url);\\n scope.manager.itemEnd(url);\\n }, false);\\n if (this.responseType !== void 0)\\n request.responseType = this.responseType;\\n if (this.withCredentials !== void 0)\\n request.withCredentials = this.withCredentials;\\n if (request.overrideMimeType)\\n request.overrideMimeType(this.mimeType !== void 0 ? this.mimeType : \\\\\\\"text/plain\\\\\\\");\\n for (const header in this.requestHeader) {\\n request.setRequestHeader(header, this.requestHeader[header]);\\n }\\n request.send(null);\\n }\\n scope.manager.itemStart(url);\\n return request;\\n }\\n setResponseType(value) {\\n this.responseType = value;\\n return this;\\n }\\n setMimeType(value) {\\n this.mimeType = value;\\n return this;\\n }\\n};\\n\\n// ../../../node_modules/three/src/loaders/AudioLoader.js\\nvar AudioLoader = class extends Loader {\\n constructor(manager) {\\n super(manager);\\n }\\n load(url, onLoad, onProgress, onError) {\\n const scope = this;\\n const loader = new FileLoader(this.manager);\\n loader.setResponseType(\\\\\\\"arraybuffer\\\\\\\");\\n loader.setPath(this.path);\\n loader.setRequestHeader(this.requestHeader);\\n loader.setWithCredentials(this.withCredentials);\\n loader.load(url, function(buffer) {\\n try {\\n const bufferCopy = buffer.slice(0);\\n const context = AudioContext.getContext();\\n context.decodeAudioData(bufferCopy, function(audioBuffer) {\\n onLoad(audioBuffer);\\n });\\n } catch (e) {\\n if (onError) {\\n onError(e);\\n } else {\\n console.error(e);\\n }\\n scope.manager.itemError(url);\\n }\\n }, onProgress, onError);\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/utils/params/ParamsConfig.ts\\nvar ParamTemplate = class {\\n constructor(type, init_value, options) {\\n this.type = type;\\n this.init_value = init_value;\\n this.options = options;\\n }\\n};\\nvar ParamConfig = class {\\n static BUTTON(init_value, options) {\\n return new ParamTemplate(ParamType.BUTTON, init_value, options);\\n }\\n static BOOLEAN(init_value, options) {\\n return new ParamTemplate(ParamType.BOOLEAN, init_value, options);\\n }\\n static COLOR(init_value, options) {\\n if (init_value instanceof Color) {\\n init_value = init_value.toArray();\\n }\\n return new ParamTemplate(ParamType.COLOR, init_value, options);\\n }\\n static FLOAT(init_value, options) {\\n return new ParamTemplate(ParamType.FLOAT, init_value, options);\\n }\\n static FOLDER(init_value = null, options) {\\n return new ParamTemplate(ParamType.FOLDER, init_value, options);\\n }\\n static INTEGER(init_value, options) {\\n return new ParamTemplate(ParamType.INTEGER, init_value, options);\\n }\\n static RAMP(init_value = RampParam.DEFAULT_VALUE, options) {\\n return new ParamTemplate(ParamType.RAMP, init_value, options);\\n }\\n static STRING(init_value = \\\\\\\"\\\\\\\", options) {\\n return new ParamTemplate(ParamType.STRING, init_value, options);\\n }\\n static VECTOR2(init_value, options) {\\n if (init_value instanceof Vector2) {\\n init_value = init_value.toArray();\\n }\\n return new ParamTemplate(ParamType.VECTOR2, init_value, options);\\n }\\n static VECTOR3(init_value, options) {\\n if (init_value instanceof Vector3) {\\n init_value = init_value.toArray();\\n }\\n return new ParamTemplate(ParamType.VECTOR3, init_value, options);\\n }\\n static VECTOR4(init_value, options) {\\n if (init_value instanceof Vector4) {\\n init_value = init_value.toArray();\\n }\\n return new ParamTemplate(ParamType.VECTOR4, init_value, options);\\n }\\n static OPERATOR_PATH(init_value, options) {\\n return new ParamTemplate(ParamType.OPERATOR_PATH, init_value, options);\\n }\\n static NODE_PATH(init_value, options) {\\n return new ParamTemplate(ParamType.NODE_PATH, init_value, options);\\n }\\n static PARAM_PATH(init_value, options) {\\n return new ParamTemplate(ParamType.PARAM_PATH, init_value, options);\\n }\\n};\\nvar NodeParamsConfig = class {\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/core/Transform.ts\\nvar TransformTargetType;\\n(function(TransformTargetType2) {\\n TransformTargetType2[\\\\\\\"OBJECTS\\\\\\\"] = \\\\\\\"objects\\\\\\\";\\n TransformTargetType2[\\\\\\\"GEOMETRIES\\\\\\\"] = \\\\\\\"geometries\\\\\\\";\\n})(TransformTargetType || (TransformTargetType = {}));\\nvar TRANSFORM_TARGET_TYPES = [\\n TransformTargetType.GEOMETRIES,\\n TransformTargetType.OBJECTS\\n];\\nvar RotationOrder;\\n(function(RotationOrder2) {\\n RotationOrder2[\\\\\\\"XYZ\\\\\\\"] = \\\\\\\"XYZ\\\\\\\";\\n RotationOrder2[\\\\\\\"XZY\\\\\\\"] = \\\\\\\"XZY\\\\\\\";\\n RotationOrder2[\\\\\\\"YXZ\\\\\\\"] = \\\\\\\"YXZ\\\\\\\";\\n RotationOrder2[\\\\\\\"YZX\\\\\\\"] = \\\\\\\"YZX\\\\\\\";\\n RotationOrder2[\\\\\\\"ZYX\\\\\\\"] = \\\\\\\"ZYX\\\\\\\";\\n RotationOrder2[\\\\\\\"ZXY\\\\\\\"] = \\\\\\\"ZXY\\\\\\\";\\n})(RotationOrder || (RotationOrder = {}));\\nvar ROTATION_ORDERS = [\\n RotationOrder.XYZ,\\n RotationOrder.XZY,\\n RotationOrder.YXZ,\\n RotationOrder.YZX,\\n RotationOrder.ZXY,\\n RotationOrder.ZYX\\n];\\nvar DEFAULT_ROTATION_ORDER = RotationOrder.XYZ;\\nvar CoreTransform = class {\\n constructor() {\\n this._translation_matrix = new Matrix4();\\n this._translation_matrix_q = new Quaternion();\\n this._translation_matrix_s = new Vector3(1, 1, 1);\\n this._matrix = new Matrix4().identity();\\n this._matrix_q = new Quaternion();\\n this._matrix_euler = new Euler();\\n this._matrix_s = new Vector3();\\n this._rotate_geometry_m = new Matrix4();\\n this._rotate_geometry_q = new Quaternion();\\n this._rotate_geometry_vec_dest = new Vector3();\\n }\\n static setParamsFromMatrix(matrix, node, options = {}) {\\n let update_scale = options[\\\\\\\"scale\\\\\\\"];\\n if (update_scale == null) {\\n update_scale = true;\\n }\\n matrix.decompose(this.set_params_from_matrix_position, this.set_params_from_matrix_quaternion, this.set_params_from_matrix_scale);\\n this.set_params_from_matrix_euler.setFromQuaternion(this.set_params_from_matrix_quaternion);\\n this.set_params_from_matrix_euler.toVector3(this.set_params_from_matrix_rotation);\\n this.set_params_from_matrix_rotation.divideScalar(Math.PI / 180);\\n this.set_params_from_matrix_position.toArray(this.set_params_from_matrix_t);\\n this.set_params_from_matrix_rotation.toArray(this.set_params_from_matrix_r);\\n this.set_params_from_matrix_scale.toArray(this.set_params_from_matrix_s);\\n node.scene().batchUpdates(() => {\\n node.params.set_vector3(\\\\\\\"t\\\\\\\", this.set_params_from_matrix_t);\\n node.params.set_vector3(\\\\\\\"r\\\\\\\", this.set_params_from_matrix_r);\\n node.params.set_vector3(\\\\\\\"s\\\\\\\", this.set_params_from_matrix_s);\\n if (update_scale) {\\n node.params.set_float(\\\\\\\"scale\\\\\\\", 1);\\n }\\n });\\n }\\n static setParamsFromObject(object, node) {\\n object.position.toArray(this.set_params_from_object_position_array);\\n object.rotation.toArray(this.set_params_from_object_rotation_array);\\n this.set_params_from_object_rotation_deg.fromArray(this.set_params_from_object_rotation_array);\\n this.set_params_from_object_rotation_deg.multiplyScalar(180 / Math.PI);\\n this.set_params_from_object_rotation_deg.toArray(this.set_params_from_object_rotation_array);\\n node.scene().batchUpdates(() => {\\n node.params.set_vector3(\\\\\\\"t\\\\\\\", this.set_params_from_object_position_array);\\n node.params.set_vector3(\\\\\\\"r\\\\\\\", this.set_params_from_object_rotation_array);\\n });\\n }\\n translationMatrix(t) {\\n this._translation_matrix.compose(t, this._translation_matrix_q, this._translation_matrix_s);\\n return this._translation_matrix;\\n }\\n matrix(t, r, s, scale, rotation_order) {\\n this._matrix_euler.set(degToRad(r.x), degToRad(r.y), degToRad(r.z), rotation_order);\\n this._matrix_q.setFromEuler(this._matrix_euler);\\n this._matrix_s.copy(s).multiplyScalar(scale);\\n this._matrix.compose(t, this._matrix_q, this._matrix_s);\\n return this._matrix;\\n }\\n rotateGeometry(geometry, vec_origin, vec_dest) {\\n this._rotate_geometry_vec_dest.copy(vec_dest);\\n this._rotate_geometry_vec_dest.normalize();\\n this._rotate_geometry_q.setFromUnitVectors(vec_origin, this._rotate_geometry_vec_dest);\\n this._rotate_geometry_m.makeRotationFromQuaternion(this._rotate_geometry_q);\\n geometry.applyMatrix4(this._rotate_geometry_m);\\n }\\n static decomposeMatrix(object) {\\n object.matrix.decompose(object.position, object.quaternion, object.scale);\\n }\\n};\\nCoreTransform.set_params_from_matrix_position = new Vector3();\\nCoreTransform.set_params_from_matrix_quaternion = new Quaternion();\\nCoreTransform.set_params_from_matrix_scale = new Vector3();\\nCoreTransform.set_params_from_matrix_euler = new Euler();\\nCoreTransform.set_params_from_matrix_rotation = new Vector3();\\nCoreTransform.set_params_from_matrix_t = [0, 0, 0];\\nCoreTransform.set_params_from_matrix_r = [0, 0, 0];\\nCoreTransform.set_params_from_matrix_s = [0, 0, 0];\\nCoreTransform.set_params_from_object_position_array = [0, 0, 0];\\nCoreTransform.set_params_from_object_rotation_deg = new Vector3();\\nCoreTransform.set_params_from_object_rotation_array = [0, 0, 0];\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/obj/utils/TransformController.ts\\nfunction TransformedParamConfig(Base, default_params) {\\n const matrixAutoUpdate = default_params?.matrixAutoUpdate || false;\\n return class Mixin extends Base {\\n constructor() {\\n super(...arguments);\\n this.transform = ParamConfig.FOLDER();\\n this.keepPosWhenParenting = ParamConfig.BOOLEAN(0);\\n this.rotationOrder = ParamConfig.INTEGER(ROTATION_ORDERS.indexOf(RotationOrder.XYZ), {\\n menu: {\\n entries: ROTATION_ORDERS.map((order, v) => {\\n return {name: order, value: v};\\n })\\n }\\n });\\n this.t = ParamConfig.VECTOR3([0, 0, 0]);\\n this.r = ParamConfig.VECTOR3([0, 0, 0]);\\n this.s = ParamConfig.VECTOR3([1, 1, 1]);\\n this.scale = ParamConfig.FLOAT(1);\\n this.matrixAutoUpdate = ParamConfig.BOOLEAN(matrixAutoUpdate ? 1 : 0);\\n this.updateTransformFromObject = ParamConfig.BUTTON(null, {\\n callback: (node) => {\\n TransformController.PARAM_CALLBACK_update_transform_from_object(node);\\n }\\n });\\n }\\n };\\n}\\nvar TransformedParamsConfig = class extends TransformedParamConfig(NodeParamsConfig) {\\n};\\nvar HOOK_NAME = \\\\\\\"_cook_main_without_inputs_when_dirty\\\\\\\";\\nvar TransformController = class {\\n constructor(node) {\\n this.node = node;\\n this._cook_main_without_inputs_when_dirty_bound = this._cook_main_without_inputs_when_dirty.bind(this);\\n this._core_transform = new CoreTransform();\\n this._keep_pos_when_parenting_m_object = new Matrix4();\\n this._keep_pos_when_parenting_m_new_parent_inv = new Matrix4();\\n }\\n initializeNode() {\\n if (!this.node.dirtyController.hasHook(HOOK_NAME)) {\\n this.node.dirtyController.addPostDirtyHook(HOOK_NAME, this._cook_main_without_inputs_when_dirty_bound);\\n }\\n }\\n async _cook_main_without_inputs_when_dirty() {\\n await this.node.cookController.cookMainWithoutInputs();\\n }\\n update() {\\n this.update_transform_with_matrix();\\n const object = this.node.object;\\n object.matrixAutoUpdate = isBooleanTrue(this.node.pv.matrixAutoUpdate);\\n }\\n update_transform_with_matrix(matrix) {\\n const object = this.node.object;\\n if (matrix != null && !matrix.equals(object.matrix)) {\\n object.matrix.copy(matrix);\\n object.dispatchEvent({type: \\\\\\\"change\\\\\\\"});\\n } else {\\n this._update_matrix_from_params_with_core_transform();\\n }\\n }\\n _update_matrix_from_params_with_core_transform() {\\n const object = this.node.object;\\n let prev_auto_update = object.matrixAutoUpdate;\\n if (prev_auto_update) {\\n object.matrixAutoUpdate = false;\\n }\\n const matrix = this._core_transform.matrix(this.node.pv.t, this.node.pv.r, this.node.pv.s, this.node.pv.scale, ROTATION_ORDERS[this.node.pv.rotationOrder]);\\n object.matrix.identity();\\n object.applyMatrix4(matrix);\\n this._apply_look_at();\\n object.updateMatrix();\\n if (prev_auto_update) {\\n object.matrixAutoUpdate = true;\\n }\\n object.dispatchEvent({type: \\\\\\\"change\\\\\\\"});\\n }\\n _apply_look_at() {\\n }\\n set_params_from_matrix(matrix, options = {}) {\\n CoreTransform.setParamsFromMatrix(matrix, this.node, options);\\n }\\n static update_node_transform_params_if_required(node, new_parent_object) {\\n node.transformController.update_node_transform_params_if_required(new_parent_object);\\n }\\n update_node_transform_params_if_required(new_parent_object) {\\n if (!isBooleanTrue(this.node.pv.keepPosWhenParenting)) {\\n return;\\n }\\n if (!this.node.scene().loadingController.loaded()) {\\n return;\\n }\\n if (new_parent_object == this.node.object.parent) {\\n return;\\n }\\n const object = this.node.object;\\n object.updateMatrixWorld(true);\\n new_parent_object.updateMatrixWorld(true);\\n this._keep_pos_when_parenting_m_object.copy(object.matrixWorld);\\n this._keep_pos_when_parenting_m_new_parent_inv.copy(new_parent_object.matrixWorld);\\n this._keep_pos_when_parenting_m_new_parent_inv.invert();\\n this._keep_pos_when_parenting_m_object.premultiply(this._keep_pos_when_parenting_m_new_parent_inv);\\n CoreTransform.setParamsFromMatrix(this._keep_pos_when_parenting_m_object, this.node, {scale: true});\\n }\\n update_node_transform_params_from_object(update_matrix = false) {\\n const object = this.node.object;\\n if (update_matrix) {\\n object.updateMatrix();\\n }\\n CoreTransform.setParamsFromMatrix(object.matrix, this.node, {scale: true});\\n }\\n static PARAM_CALLBACK_update_transform_from_object(node) {\\n node.transformController.update_node_transform_params_from_object();\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/obj/utils/HierarchyController.ts\\nvar HierarchyController = class {\\n constructor(node) {\\n this.node = node;\\n }\\n initializeNode() {\\n this.node.io.inputs.setCount(0, 1);\\n this.node.io.inputs.set_depends_on_inputs(false);\\n this.node.io.outputs.setHasOneOutput();\\n this.node.io.inputs.add_on_set_input_hook(\\\\\\\"on_input_updated:update_parent\\\\\\\", () => {\\n this.on_input_updated();\\n });\\n }\\n static on_input_updated(node) {\\n const parent_object = node.root().getParentForNode(node);\\n if (node.transformController && parent_object) {\\n TransformController.update_node_transform_params_if_required(node, parent_object);\\n }\\n if (node.io.inputs.input(0) != null) {\\n node.root().addToParentTransform(node);\\n } else {\\n node.root().removeFromParentTransform(node);\\n }\\n }\\n on_input_updated() {\\n HierarchyController.on_input_updated(this.node);\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/core/loader/_Base.ts\\nvar LOADING_MANAGER = new LoadingManager();\\nLOADING_MANAGER.setURLModifier((url) => {\\n const remapedUrl = Poly.assetUrls.remapedUrl(url);\\n if (remapedUrl) {\\n return remapedUrl;\\n }\\n const blobUrl = Poly.blobs.blobUrl(url);\\n if (blobUrl) {\\n return blobUrl;\\n }\\n return url;\\n});\\nvar CoreBaseLoader2 = class {\\n constructor(_url, _scene, _node) {\\n this._url = _url;\\n this._scene = _scene;\\n this._node = _node;\\n this.loadingManager = LOADING_MANAGER;\\n }\\n static extension(url) {\\n let ext = null;\\n try {\\n const _url = new URL(url);\\n ext = _url.searchParams.get(\\\\\\\"ext\\\\\\\");\\n } catch (e) {\\n }\\n if (!ext) {\\n const url_without_params = url.split(\\\\\\\"?\\\\\\\")[0];\\n const elements = url_without_params.split(\\\\\\\".\\\\\\\");\\n ext = elements[elements.length - 1].toLowerCase();\\n }\\n return ext;\\n }\\n extension() {\\n return CoreBaseLoader2.extension(this._url);\\n }\\n async _urlToLoad() {\\n const {storedUrl, fullUrl} = this._urlData();\\n if (this._node) {\\n await Poly.blobs.fetchBlobForNode({storedUrl, fullUrl, node: this._node});\\n }\\n const blobUrl = Poly.blobs.blobUrl(storedUrl);\\n return blobUrl || fullUrl;\\n }\\n deregisterUrl() {\\n const {storedUrl} = this._urlData();\\n Poly.blobs.deregisterUrl(storedUrl);\\n }\\n _urlData() {\\n let fullUrl = this._url;\\n const storedUrl = this._url.split(\\\\\\\"?\\\\\\\")[0];\\n if (fullUrl[0] != \\\\\\\"h\\\\\\\") {\\n const assets_root = this._scene.assets.root();\\n if (assets_root) {\\n fullUrl = `${assets_root}${fullUrl}`;\\n }\\n }\\n return {fullUrl, storedUrl};\\n }\\n static async _loadMultipleBlobGlobal(options) {\\n const promises = [];\\n for (let file of options.files) {\\n const storedUrl = file.storedUrl;\\n const fullUrl = file.fullUrl;\\n const node = options.node;\\n promises.push(Poly.blobs.fetchBlobGlobal({storedUrl, fullUrl, node}));\\n }\\n const responses = await Promise.all(promises);\\n for (let response of responses) {\\n if (response.error) {\\n options.node.states.error.set(options.error);\\n }\\n }\\n }\\n};\\nvar CoreBaseLoader = CoreBaseLoader2;\\nCoreBaseLoader.loadingManager = LOADING_MANAGER;\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/core/loader/Audio.ts\\nvar Extension;\\n(function(Extension2) {\\n Extension2[\\\\\\\"MP3\\\\\\\"] = \\\\\\\"mp3\\\\\\\";\\n Extension2[\\\\\\\"WAV\\\\\\\"] = \\\\\\\"wav\\\\\\\";\\n})(Extension || (Extension = {}));\\nvar AUDIO_EXTENSIONS = [Extension.MP3, Extension.WAV];\\nvar CoreLoaderAudio = class extends CoreBaseLoader {\\n async load() {\\n const audioLoader = new AudioLoader(this.loadingManager);\\n const url = await this._urlToLoad();\\n return new Promise((resolve) => {\\n audioLoader.load(url, function(buffer) {\\n resolve(buffer);\\n });\\n });\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/poly/registers/nodes/types/Obj.ts\\nvar ObjType;\\n(function(ObjType2) {\\n ObjType2[\\\\\\\"GEO\\\\\\\"] = \\\\\\\"geo\\\\\\\";\\n ObjType2[\\\\\\\"CUBE_CAMERA\\\\\\\"] = \\\\\\\"cubeCamera\\\\\\\";\\n ObjType2[\\\\\\\"AUDIO_LISTENER\\\\\\\"] = \\\\\\\"audioListener\\\\\\\";\\n ObjType2[\\\\\\\"POSITIONAL_AUDIO\\\\\\\"] = \\\\\\\"positionalAudio\\\\\\\";\\n})(ObjType || (ObjType = {}));\\n\\n// src/engine/nodes/obj/AudioAnalyzer.ts\\nvar AudioAnalyzerParamConfig = class extends NodeParamsConfig {\\n constructor() {\\n super(...arguments);\\n this.url = ParamConfig.STRING(\\\\\\\"\\\\\\\", {\\n fileBrowse: {type: [FileType.AUDIO]}\\n });\\n this.listener = ParamConfig.NODE_PATH(\\\\\\\"\\\\\\\", {\\n nodeSelection: {\\n context: NodeContext.OBJ,\\n types: [ObjType.AUDIO_LISTENER]\\n }\\n });\\n this.fftSize = ParamConfig.INTEGER(128, {\\n range: [1, 1024]\\n });\\n this.output0 = ParamConfig.FLOAT(1);\\n this.output1 = ParamConfig.FLOAT(1);\\n this.play = ParamConfig.BUTTON(null, {\\n callback: (node) => {\\n AudioAnalyzerObjNode.PARAM_CALLBACK_play(node);\\n }\\n });\\n this.pause = ParamConfig.BUTTON(null, {\\n callback: (node) => {\\n AudioAnalyzerObjNode.PARAM_CALLBACK_pause(node);\\n }\\n });\\n }\\n};\\nvar ParamsConfig = new AudioAnalyzerParamConfig();\\nvar AudioAnalyzerObjNode = class extends TypedObjNode {\\n constructor() {\\n super(...arguments);\\n this.paramsConfig = ParamsConfig;\\n this.hierarchyController = new HierarchyController(this);\\n this.flags = new FlagsControllerD(this);\\n }\\n static type() {\\n return \\\\\\\"audioAnalyzer\\\\\\\";\\n }\\n createObject() {\\n const group = new Group();\\n group.matrixAutoUpdate = false;\\n return group;\\n }\\n initializeNode() {\\n this.hierarchyController.initializeNode();\\n }\\n cook() {\\n this.cookController.endCook();\\n }\\n async audioAnalyzer() {\\n return this._audioAnalyzer = this._audioAnalyzer || await this._createAudioAnalyzer();\\n }\\n async _createAudioAnalyzer() {\\n console.log(\\\\\\\"_createAudioAnalyzer\\\\\\\");\\n if (this.p.listener.isDirty()) {\\n await this.p.listener.compute();\\n }\\n const node = this.pv.listener.nodeWithContext(NodeContext.OBJ);\\n if (!node) {\\n return;\\n }\\n console.log(\\\\\\\"_createAudioAnalyzer B\\\\\\\");\\n const listener = node.object;\\n this._audio = new Audio2(listener);\\n if (/(iPad|iPhone|iPod)/g.test(navigator.userAgent)) {\\n const loader2 = new AudioLoader();\\n loader2.load(this.pv.url, (buffer) => {\\n if (this._audio) {\\n this._audio.setBuffer(buffer);\\n this._audio.hasPlaybackControl = true;\\n console.log(\\\\\\\"play A\\\\\\\");\\n }\\n });\\n } else {\\n this._mediaElement = new Audio(this.pv.url);\\n console.log(\\\\\\\"play B\\\\\\\");\\n this._audio.setMediaElementSource(this._mediaElement);\\n this._audio.hasPlaybackControl = true;\\n }\\n const audioAnalyzer = new AudioAnalyser(this._audio, this.pv.fftSize);\\n const loader = new CoreLoaderAudio(this.pv.url, this.scene(), this);\\n this.scene().registerOnBeforeTick(`audioAnalyzer-${this.path()}`, () => {\\n if (this._audioAnalyzer) {\\n this._audioAnalyzer.getFrequencyData();\\n const value = this._audioAnalyzer.data[0];\\n this.p.output0.set(value);\\n const average = this._audioAnalyzer.getAverageFrequency();\\n this.p.output1.set(average);\\n }\\n });\\n return audioAnalyzer;\\n }\\n isPlaying() {\\n if (this._audio) {\\n return isBooleanTrue(this._audio.isPlaying);\\n }\\n if (this._mediaElement) {\\n return isBooleanTrue(this._mediaElement.isPlaying);\\n }\\n return false;\\n }\\n static PARAM_CALLBACK_play(node) {\\n node.PARAM_CALLBACK_play();\\n }\\n static PARAM_CALLBACK_pause(node) {\\n node.PARAM_CALLBACK_pause();\\n }\\n PARAM_CALLBACK_play() {\\n this.audioAnalyzer();\\n if (!this.isPlaying()) {\\n console.log(\\\\\\\"play !\\\\\\\");\\n this._audio?.play();\\n this._mediaElement?.play();\\n }\\n }\\n PARAM_CALLBACK_pause() {\\n this.audioAnalyzer();\\n if (this.isPlaying()) {\\n console.log(\\\\\\\"-pause-\\\\\\\");\\n this._audio?.pause();\\n this._mediaElement?.pause();\\n }\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/core/geometry/Group.ts\\nvar CoreGroup = class {\\n constructor() {\\n this._objects = [];\\n this._objects_with_geo = [];\\n this.touch();\\n }\\n timestamp() {\\n return this._timestamp;\\n }\\n touch() {\\n const performance2 = Poly.performance.performanceManager();\\n this._timestamp = performance2.now();\\n this.reset();\\n }\\n reset() {\\n this._bounding_box = void 0;\\n this._core_geometries = void 0;\\n this._core_objects = void 0;\\n }\\n clone() {\\n const core_group = new CoreGroup();\\n if (this._objects) {\\n const objects = [];\\n for (let object of this._objects) {\\n objects.push(CoreObject.clone(object));\\n }\\n core_group.setObjects(objects);\\n }\\n return core_group;\\n }\\n setObjects(objects) {\\n this._objects = objects;\\n this._objects_with_geo = objects.filter((obj) => obj.geometry != null);\\n this.touch();\\n }\\n objects() {\\n return this._objects;\\n }\\n objectsWithGeo() {\\n return this._objects_with_geo;\\n }\\n coreObjects() {\\n return this._core_objects = this._core_objects || this._create_core_objects();\\n }\\n _create_core_objects() {\\n if (this._objects) {\\n return this._objects.map((object, i) => new CoreObject(object, i));\\n }\\n return [];\\n }\\n objectsData() {\\n if (this._objects) {\\n return this._objects.map((object) => this._objectData(object));\\n }\\n return [];\\n }\\n _objectData(object) {\\n let points_count = 0;\\n if (object.geometry) {\\n points_count = CoreGeometry.pointsCount(object.geometry);\\n }\\n return {\\n type: objectTypeFromConstructor(object.constructor),\\n name: object.name,\\n children_count: object.children.length,\\n points_count\\n };\\n }\\n geometries() {\\n const list = [];\\n for (let core_object of this.coreObjects()) {\\n const geometry = core_object.object().geometry;\\n if (geometry) {\\n list.push(geometry);\\n }\\n }\\n return list;\\n }\\n coreGeometries() {\\n return this._core_geometries = this._core_geometries || this._createCoreGeometries();\\n }\\n _createCoreGeometries() {\\n const list = [];\\n for (let geometry of this.geometries()) {\\n list.push(new CoreGeometry(geometry));\\n }\\n return list;\\n }\\n static geometryFromObject(object) {\\n if (object.isMesh || object.isLine || object.isPoints) {\\n return object.geometry;\\n }\\n return null;\\n }\\n faces() {\\n const faces = [];\\n for (let object of this.objectsWithGeo()) {\\n if (object.geometry) {\\n const coreGeo = new CoreGeometry(object.geometry);\\n const geoFaces = coreGeo.faces();\\n for (let geoFace of geoFaces) {\\n geoFace.applyMatrix4(object.matrix);\\n faces.push(geoFace);\\n }\\n }\\n }\\n return faces;\\n }\\n points() {\\n return this.coreGeometries().map((g) => g.points()).flat();\\n }\\n pointsCount() {\\n return ArrayUtils.sum(this.coreGeometries().map((g) => g.pointsCount()));\\n }\\n totalPointsCount() {\\n if (this._objects) {\\n let sum = 0;\\n for (let object of this._objects) {\\n object.traverse((object2) => {\\n const geometry = object2.geometry;\\n if (geometry) {\\n sum += CoreGeometry.pointsCount(geometry);\\n }\\n });\\n }\\n return sum;\\n } else {\\n return 0;\\n }\\n }\\n pointsFromGroup(group) {\\n if (group) {\\n const indices = CoreString.indices(group);\\n const points2 = this.points();\\n return ArrayUtils.compact(indices.map((i) => points2[i]));\\n } else {\\n return this.points();\\n }\\n }\\n static _fromObjects(objects) {\\n const core_group = new CoreGroup();\\n core_group.setObjects(objects);\\n return core_group;\\n }\\n objectsFromGroup(group_name) {\\n return this.coreObjectsFromGroup(group_name).map((co) => co.object());\\n }\\n coreObjectsFromGroup(group_name) {\\n group_name = group_name.trim();\\n if (group_name !== \\\\\\\"\\\\\\\") {\\n const index = parseInt(group_name);\\n if (!CoreType.isNaN(index)) {\\n return ArrayUtils.compact([this.coreObjects()[index]]);\\n } else {\\n return this.coreObjects().filter((core_object) => {\\n return CoreString.matchMask(group_name, core_object.name());\\n });\\n }\\n } else {\\n return this.coreObjects();\\n }\\n }\\n boundingBox(forceUpdate = false) {\\n if (forceUpdate) {\\n return this._bounding_box = this._computeBoundingBox();\\n }\\n return this._bounding_box = this._bounding_box || this._computeBoundingBox();\\n }\\n center() {\\n const center = new Vector3();\\n this.boundingBox().getCenter(center);\\n return center;\\n }\\n size() {\\n const size = new Vector3();\\n this.boundingBox().getSize(size);\\n return size;\\n }\\n _computeBoundingBox() {\\n let bbox;\\n if (this._objects) {\\n for (let object of this._objects) {\\n const geometry = object.geometry;\\n if (geometry) {\\n geometry.computeBoundingBox();\\n if (bbox) {\\n bbox.expandByObject(object);\\n } else {\\n if (geometry.boundingBox) {\\n bbox = geometry.boundingBox.clone();\\n }\\n }\\n }\\n }\\n }\\n bbox = bbox || new Box3(new Vector3(-1, -1, -1), new Vector3(1, 1, 1));\\n return bbox;\\n }\\n computeVertexNormals() {\\n for (let object of this.coreObjects()) {\\n object.computeVertexNormals();\\n }\\n }\\n hasAttrib(name) {\\n let first_geometry;\\n if ((first_geometry = this.coreGeometries()[0]) != null) {\\n return first_geometry.hasAttrib(name);\\n } else {\\n return false;\\n }\\n }\\n attribType(name) {\\n const first_core_geometry = this.coreGeometries()[0];\\n if (first_core_geometry != null) {\\n return first_core_geometry.attribType(name);\\n } else {\\n return null;\\n }\\n }\\n objectAttribType(name) {\\n const first_core_object = this.coreObjects()[0];\\n if (first_core_object != null) {\\n return first_core_object.attribType(name);\\n } else {\\n return null;\\n }\\n }\\n renameAttrib(old_name, new_name, attrib_class) {\\n switch (attrib_class) {\\n case CoreConstant.ATTRIB_CLASS.VERTEX:\\n if (this.hasAttrib(old_name)) {\\n if (this._objects) {\\n for (let object of this._objects) {\\n object.traverse((child) => {\\n const geometry = CoreGroup.geometryFromObject(child);\\n if (geometry) {\\n const core_geometry = new CoreGeometry(geometry);\\n core_geometry.renameAttrib(old_name, new_name);\\n }\\n });\\n }\\n }\\n }\\n break;\\n case CoreConstant.ATTRIB_CLASS.OBJECT:\\n if (this.hasAttrib(old_name)) {\\n if (this._objects) {\\n for (let object of this._objects) {\\n object.traverse((child) => {\\n const core_object = new CoreObject(child, 0);\\n core_object.renameAttrib(old_name, new_name);\\n });\\n }\\n }\\n }\\n break;\\n }\\n }\\n attribNames() {\\n let first_geometry;\\n if ((first_geometry = this.coreGeometries()[0]) != null) {\\n return first_geometry.attribNames();\\n } else {\\n return [];\\n }\\n }\\n objectAttribNames() {\\n let first_object;\\n if ((first_object = this.coreObjects()[0]) != null) {\\n return first_object.attribNames();\\n } else {\\n return [];\\n }\\n }\\n attribNamesMatchingMask(masks_string) {\\n const masks = CoreString.attribNames(masks_string);\\n const matching_attrib_names = [];\\n for (let attrib_name of this.attribNames()) {\\n for (let mask of masks) {\\n if (CoreString.matchMask(attrib_name, mask)) {\\n matching_attrib_names.push(attrib_name);\\n } else {\\n const remapped = CoreAttribute.remapName(mask);\\n if (attrib_name == remapped) {\\n matching_attrib_names.push(attrib_name);\\n }\\n }\\n }\\n }\\n return ArrayUtils.uniq(matching_attrib_names);\\n }\\n attribSizes() {\\n let first_geometry;\\n if ((first_geometry = this.coreGeometries()[0]) != null) {\\n return first_geometry.attribSizes();\\n } else {\\n return {};\\n }\\n }\\n objectAttribSizes() {\\n let first_object;\\n if ((first_object = this.coreObjects()[0]) != null) {\\n return first_object.attribSizes();\\n } else {\\n return {};\\n }\\n }\\n attribSize(attrib_name) {\\n let first_geometry;\\n if ((first_geometry = this.coreGeometries()[0]) != null) {\\n return first_geometry.attribSize(attrib_name);\\n } else {\\n return 0;\\n }\\n }\\n addNumericVertexAttrib(name, size, default_value) {\\n if (default_value == null) {\\n default_value = CoreAttribute.default_value(size);\\n }\\n for (let core_geometry of this.coreGeometries()) {\\n core_geometry.addNumericAttrib(name, size, default_value);\\n }\\n }\\n static clone(src_group) {\\n const new_group = new Group();\\n src_group.children.forEach((src_object) => {\\n const new_object = CoreObject.clone(src_object);\\n new_group.add(new_object);\\n });\\n return new_group;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/operations/_Base.ts\\nvar BaseOperation = class {\\n constructor(_scene, states, _node) {\\n this._scene = _scene;\\n this.states = states;\\n this._node = _node;\\n }\\n static type() {\\n throw \\\\\\\"type to be overriden\\\\\\\";\\n }\\n type() {\\n const c = this.constructor;\\n return c.type();\\n }\\n static context() {\\n console.error(\\\\\\\"operation has no node_context\\\\\\\", this);\\n throw \\\\\\\"context requires override\\\\\\\";\\n }\\n context() {\\n const c = this.constructor;\\n return c.context();\\n }\\n scene() {\\n return this._scene;\\n }\\n cook(input_contents, params) {\\n }\\n};\\nBaseOperation.DEFAULT_PARAMS = {};\\nBaseOperation.INPUT_CLONED_STATE = [];\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/operations/sop/_Base.ts\\nvar BaseSopOperation = class extends BaseOperation {\\n static context() {\\n return NodeContext.SOP;\\n }\\n cook(input_contents, params) {\\n }\\n createCoreGroupFromObjects(objects) {\\n const core_group = new CoreGroup();\\n core_group.setObjects(objects);\\n return core_group;\\n }\\n createCoreGroupFromGeometry(geometry, type = ObjectType.MESH) {\\n const object = BaseSopOperation.createObject(geometry, type);\\n return this.createCoreGroupFromObjects([object]);\\n }\\n createObject(geometry, type, material) {\\n return BaseSopOperation.createObject(geometry, type, material);\\n }\\n static createObject(geometry, type, material) {\\n this.createIndexIfNone(geometry);\\n const object_constructor = OBJECT_CONSTRUCTOR_BY_OBJECT_TYPE[type];\\n material = material || CoreConstant.MATERIALS[type].clone();\\n const object = new object_constructor(geometry, material);\\n object.castShadow = true;\\n object.receiveShadow = true;\\n object.frustumCulled = false;\\n object.matrixAutoUpdate = false;\\n return object;\\n }\\n createIndexIfNone(geometry) {\\n BaseSopOperation.createIndexIfNone(geometry);\\n }\\n static createIndexIfNone(geometry) {\\n CoreGeometryIndexBuilder.createIndexIfNone(geometry);\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/sop/_Base.ts\\nvar MESSAGE;\\n(function(MESSAGE2) {\\n MESSAGE2[\\\\\\\"FROM_SET_CORE_GROUP\\\\\\\"] = \\\\\\\"from set_core_group\\\\\\\";\\n MESSAGE2[\\\\\\\"FROM_SET_GROUP\\\\\\\"] = \\\\\\\"from set_group\\\\\\\";\\n MESSAGE2[\\\\\\\"FROM_SET_OBJECTS\\\\\\\"] = \\\\\\\"from set_objects\\\\\\\";\\n MESSAGE2[\\\\\\\"FROM_SET_OBJECT\\\\\\\"] = \\\\\\\"from set_object\\\\\\\";\\n MESSAGE2[\\\\\\\"FROM_SET_GEOMETRIES\\\\\\\"] = \\\\\\\"from set_geometries\\\\\\\";\\n MESSAGE2[\\\\\\\"FROM_SET_GEOMETRY\\\\\\\"] = \\\\\\\"from set_geometry\\\\\\\";\\n})(MESSAGE || (MESSAGE = {}));\\nvar INPUT_GEOMETRY_NAME = \\\\\\\"input geometry\\\\\\\";\\nvar DEFAULT_INPUT_NAMES2 = [INPUT_GEOMETRY_NAME, INPUT_GEOMETRY_NAME, INPUT_GEOMETRY_NAME, INPUT_GEOMETRY_NAME];\\nvar TypedSopNode = class extends TypedNode {\\n constructor() {\\n super(...arguments);\\n this.flags = new FlagsControllerDBO(this);\\n }\\n static context() {\\n return NodeContext.SOP;\\n }\\n static displayedInputNames() {\\n return DEFAULT_INPUT_NAMES2;\\n }\\n initializeBaseNode() {\\n this.flags.display.set(false);\\n this.flags.display.onUpdate(() => {\\n if (this.flags.display.active()) {\\n const parent = this.parent();\\n if (parent && parent.displayNodeController) {\\n parent.displayNodeController.setDisplayNode(this);\\n }\\n }\\n });\\n this.io.outputs.setHasOneOutput();\\n }\\n setCoreGroup(core_group) {\\n this._setContainer(core_group, MESSAGE.FROM_SET_CORE_GROUP);\\n }\\n setObject(object) {\\n this._setContainerObjects([object], MESSAGE.FROM_SET_OBJECT);\\n }\\n setObjects(objects) {\\n this._setContainerObjects(objects, MESSAGE.FROM_SET_OBJECTS);\\n }\\n setGeometry(geometry, type = ObjectType.MESH) {\\n const object = this.createObject(geometry, type);\\n this._setContainerObjects([object], MESSAGE.FROM_SET_GEOMETRY);\\n }\\n setGeometries(geometries, type = ObjectType.MESH) {\\n const objects = [];\\n let object;\\n for (let geometry of geometries) {\\n object = this.createObject(geometry, type);\\n objects.push(object);\\n }\\n this._setContainerObjects(objects, MESSAGE.FROM_SET_GEOMETRIES);\\n }\\n _setContainerObjects(objects, message) {\\n const core_group = this.containerController.container().coreContent() || new CoreGroup();\\n core_group.setObjects(objects);\\n core_group.touch();\\n this._setContainer(core_group);\\n }\\n static createObject(geometry, type, material) {\\n return BaseSopOperation.createObject(geometry, type, material);\\n }\\n createObject(geometry, type, material) {\\n return TypedSopNode.createObject(geometry, type, material);\\n }\\n static createIndexIfNone(geometry) {\\n BaseSopOperation.createIndexIfNone(geometry);\\n }\\n _createIndexIfNone(geometry) {\\n TypedSopNode.createIndexIfNone(geometry);\\n }\\n};\\n\\n// src/engine/nodes/sop/AudioAnalyzer.ts\\nvar AudioAnalyzerParamConfig2 = class extends NodeParamsConfig {\\n constructor() {\\n super(...arguments);\\n this.url = ParamConfig.STRING(\\\\\\\"\\\\\\\", {\\n fileBrowse: {type: [FileType.AUDIO]}\\n });\\n this.listener = ParamConfig.NODE_PATH(\\\\\\\"\\\\\\\", {\\n nodeSelection: {\\n context: NodeContext.OBJ,\\n types: [ObjType.AUDIO_LISTENER]\\n }\\n });\\n this.fftSize = ParamConfig.INTEGER(128, {\\n range: [1, 1024]\\n });\\n this.outputMult = ParamConfig.FLOAT(0.1);\\n this.average = ParamConfig.FLOAT(1, {\\n cook: false\\n });\\n this.play = ParamConfig.BUTTON(null, {\\n callback: (node) => {\\n AudioAnalyzerSopNode.PARAM_CALLBACK_play(node);\\n }\\n });\\n this.pause = ParamConfig.BUTTON(null, {\\n callback: (node) => {\\n AudioAnalyzerSopNode.PARAM_CALLBACK_pause(node);\\n }\\n });\\n }\\n};\\nvar ParamsConfig2 = new AudioAnalyzerParamConfig2();\\nvar AudioAnalyzerSopNode = class extends TypedSopNode {\\n constructor() {\\n super(...arguments);\\n this.paramsConfig = ParamsConfig2;\\n }\\n static type() {\\n return \\\\\\\"audioAnalyzer\\\\\\\";\\n }\\n initializeNode() {\\n this.io.inputs.setCount(1);\\n this.addGraphInput(this.scene().timeController.graphNode);\\n this.io.inputs.initInputsClonedState(InputCloneMode.FROM_NODE);\\n }\\n cook(input_contents) {\\n console.log(\\\\\\\"cook\\\\\\\");\\n const core_group = input_contents[0];\\n const objects = core_group.objects();\\n if (this._audioAnalyzer) {\\n const outputMult = this.pv.outputMult;\\n this._audioAnalyzer.getFrequencyData();\\n const data = this._audioAnalyzer.data;\\n const maxCount = Math.min(objects.length, data.length);\\n for (let i = 0; i < maxCount; i++) {\\n const object = objects[i];\\n const dataEntry = data[i] * outputMult;\\n object.position.y = dataEntry;\\n }\\n const average = this._audioAnalyzer.getAverageFrequency();\\n this.p.average.set(average);\\n }\\n this.setCoreGroup(core_group);\\n }\\n async audioAnalyzer() {\\n return this._audioAnalyzer = this._audioAnalyzer || await this._createAudioAnalyzer();\\n }\\n async _createAudioAnalyzer() {\\n console.log(\\\\\\\"_createAudioAnalyzer\\\\\\\");\\n if (this.p.listener.isDirty()) {\\n await this.p.listener.compute();\\n }\\n const node = this.pv.listener.nodeWithContext(NodeContext.OBJ);\\n if (!node) {\\n return;\\n }\\n console.log(\\\\\\\"_createAudioAnalyzer B\\\\\\\");\\n const listener = node.object;\\n this._audio = new Audio2(listener);\\n if (/(iPad|iPhone|iPod)/g.test(navigator.userAgent)) {\\n const loader = new AudioLoader();\\n loader.load(this.pv.url, (buffer) => {\\n if (this._audio) {\\n this._audio.setBuffer(buffer);\\n console.log(\\\\\\\"play A\\\\\\\");\\n }\\n });\\n } else {\\n this._mediaElement = new Audio(this.pv.url);\\n console.log(\\\\\\\"play B\\\\\\\");\\n this._audio.setMediaElementSource(this._mediaElement);\\n }\\n const audioAnalyzer = new AudioAnalyser(this._audio, this.pv.fftSize);\\n return audioAnalyzer;\\n }\\n isPlaying() {\\n if (this._audio) {\\n return isBooleanTrue(this._audio.isPlaying);\\n }\\n if (this._mediaElement) {\\n return isBooleanTrue(this._mediaElement.isPlaying);\\n }\\n return false;\\n }\\n static PARAM_CALLBACK_play(node) {\\n node.PARAM_CALLBACK_play();\\n }\\n static PARAM_CALLBACK_pause(node) {\\n node.PARAM_CALLBACK_pause();\\n }\\n PARAM_CALLBACK_play() {\\n this.audioAnalyzer();\\n if (!this.isPlaying()) {\\n console.log(\\\\\\\"play !\\\\\\\");\\n this._audio?.play();\\n this._mediaElement?.play();\\n }\\n }\\n PARAM_CALLBACK_pause() {\\n if (this.isPlaying()) {\\n this._audio?.pause();\\n this._mediaElement?.pause();\\n }\\n }\\n};\\n\\n// src/polygonjs/PolyConfig.ts\\nfunction configurePolygonjs(poly) {\\n poly.nodesRegister.register(AudioAnalyzerObjNode, \\\\\\\"myNodes\\\\\\\");\\n poly.nodesRegister.register(AudioAnalyzerSopNode, \\\\\\\"myNodes\\\\\\\");\\n}\\nfunction configureScene(scene) {\\n}\\nexport {\\n configurePolygonjs,\\n configureScene\\n};\\n\"","status":200,"headers":{"content-type":"application/javascript","content-length":"1180177"}},"type":2,"external":true,"timestamp":1723920082920},{"data":{"url":"blob:https://ipfs.arkivo.art/c715dc52-c1c7-45c7-bd92-45ce5c7c3049","body":"\"����\\u0000\\u0010JFIF\\u0000\\u0001\\u0001\\u0000\\u0000\\u0001\\u0000\\u0001\\u0000\\u0000��\\u0000\\fNeoGeo\\u0000\\u0000\\u0000<��\\u0000C\\u0000\\r\\t\\n\\u000b\\n\\b\\r\\u000b\\n\\u000b\\u000e\\u000e\\r\\u000f\\u0013 \\u0015\\u0013\\u0012\\u0012\\u0013'\\u001c\\u001e\\u0017 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","consoleMessages":[{"text":"Unrecognized Content-Security-Policy directive 'prefetch-src'.","level":"error","timestamp":1723920075262},{"text":"[.WebGL-0x24380154b800]GL Driver Message (OpenGL, Performance, GL_CLOSE_PATH_NV, High): GPU stall due to ReadPixels","level":"warning","timestamp":1723920086251},{"text":"[.WebGL-0x24380154b800]GL Driver Message (OpenGL, Performance, GL_CLOSE_PATH_NV, High): GPU stall due to ReadPixels","level":"warning","timestamp":1723920089569},{"text":"[.WebGL-0x24380154b800]GL Driver Message (OpenGL, Performance, GL_CLOSE_PATH_NV, High): GPU stall due to ReadPixels","level":"warning","timestamp":1723920089573},{"text":"[.WebGL-0x24380154b800]GL Driver Message (OpenGL, Performance, GL_CLOSE_PATH_NV, High): GPU stall due to ReadPixels (this message will no longer repeat)","level":"warning","timestamp":1723920092983}],"screenshotDelay":10000},"timestamp":1723920074826},"created_at":"2024-08-17T18:42:12.790+00:00","updated_at":"2024-08-17T18:42:12.791+00:00"}