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* Tone.js v14.8.14 *  background: #000; color: #fff","level":"log","timestamp":1723942267533},{"text":"The AudioContext was not allowed to start. It must be resumed (or created) after a user gesture on the page. https://goo.gl/7K7WLu","level":"warning","timestamp":1723942267603},{"text":"The ScriptProcessorNode is deprecated. Use AudioWorkletNode instead. (https://bit.ly/audio-worklet)","level":"warning","timestamp":1723942267606},{"text":"The AudioContext was not allowed to start. It must be resumed (or created) after a user gesture on the page. https://goo.gl/7K7WLu","level":"warning","timestamp":1723942267607},{"text":"The AudioContext was not allowed to start. It must be resumed (or created) after a user gesture on the page. https://goo.gl/7K7WLu","level":"warning","timestamp":1723942267634},{"text":"The AudioContext was not allowed to start. It must be resumed (or created) after a user gesture on the page. https://goo.gl/7K7WLu","level":"warning","timestamp":1723942267634},{"text":"class HydraSynth {\n\n            constructor ({\n                pb = null,\n                width = 1024,\n                height = 1024,\n                numSources = 4,\n                numOutputs = 4,\n                makeGlobal = true,\n                autoLoop = true,\n                detectAudio = false,\n                enableStreamCapture = false,\n                canvas,\n                precision = 'mediump'\n            } = {}) {\n\n                this.bpm = 60\n                this.pb = pb\n                this.width = width\n                this.height = height\n                this.time = 0\n                this.makeGlobal = makeGlobal\n                this.renderAll = false\n                this.detectAudio = detectAudio\n\n                // only allow valid precision options\n                let precisionOptions = ['lowp','mediump','highp']\n                let precisionValid = precisionOptions.includes(precision.toLowerCase())\n\n                this.precision = precisionValid ? precision.toLowerCase() : 'mediump'\n\n                if(!precisionValid){\n                console.warn('[hydra-synth warning]\\nConstructor was provided an invalid floating point precision value of \"' + precision + '\". Using default value of \"mediump\" instead.')\n                }\n\n                // boolean to store when to save screenshot\n                this.saveFrame = false\n\n                // if stream capture is enabled, this object contains the capture stream\n                this.captureStream = null\n\n                this._initCanvas(canvas)\n                this._initRegl()\n                this._initOutputs(numOutputs)\n                this._initSources(numSources)\n                this._generateGlslTransforms()\n\n                window.screencap = () => {\n                this.saveFrame = true\n                }\n\n                if (enableStreamCapture) {\n                this.captureStream = this.canvas.captureStream(25)\n\n                // to do: enable capture stream of specific sources and outputs\n                window.vidRecorder = new VidRecorder(this.captureStream)\n                }\n\n                if(detectAudio) this._initAudio()\n                //if(makeGlobal) {\n                window.mouse = mouse\n                window.time = this.time\n                window['render'] = this.render.bind(this)\n                //  window.bpm = this.bpm\n                window.bpm = this._setBpm.bind(this)\n            //  }\n                if(autoLoop) loop(this.tick.bind(this)).start()\n            }\n\n            getScreenImage(callback) {\n                this.imageCallback = callback\n                this.saveFrame = true\n            }\n\n            resize(width, height) {\n                console.log(width, height)\n                this.canvas = document.querySelector('foreignObject').querySelector('canvas');\n                this.canvas.width = width\n                this.canvas.height = height\n                this.width = width\n                this.height = height\n                this.regl.poll()\n                this.o.forEach((output) => {\n                output.resize(width, height)\n                })\n                this.s.forEach((source) => {\n                source.resize(width, height)\n                })\n            }\n            canvasToImage (callback) {\n                const a = document.createElement('a')\n                a.style.display = 'none'\n\n                let d = new Date()\n                a.download = `hydra-${d.getFullYear()}-${d.getMonth() + 1}-${d.getDate()}-${d.getHours()}.${d.getMinutes()}.${d.getSeconds()}.png`\n                document.body.appendChild(a)\n                var self = this\n                this.canvas.toBlob( (blob) => {\n                //  var url = window.URL.createObjectURL(blob)\n\n                    if(self.imageCallback){\n                    self.imageCallback(blob)\n                    delete self.imageCallback\n                    } else {\n                    a.href = URL.createObjectURL(blob)\n                    console.log(a.href)\n                    a.click()\n                    }\n                }, 'image/png')\n                setTimeout(() => {\n                document.body.removeChild(a);\n                window.URL.revokeObjectURL(a.href);\n                }, 300);\n            }\n\n            _initAudio () {\n                this.audio = new Audio({\n                numBins: 4\n                })\n                if(this.makeGlobal) window.a = this.audio\n            }\n            // create main output canvas and add to screen\n            _initCanvas (canvas) {\n                if (canvas) {\n                this.canvas = canvas\n                this.width = canvas.width\n                this.height = canvas.height\n                } else {\n                this.canvas = document.createElement('canvas')\n                this.canvas.width = this.width\n                this.canvas.height = this.height\n                this.canvas.style.width = '100%'\n                this.canvas.style.height = '100%'\n                document.body.appendChild(this.canvas)\n                }\n            }\n\n            _initRegl () {\n                this.regl = require('regl')({\n                canvas: this.canvas,\n                pixelRatio: 1,\n                extensions: [\n                    'oes_texture_half_float',\n                    'oes_texture_half_float_linear'\n                ],\n                optionalExtensions: [\n                    'oes_texture_float',\n                    'oes_texture_float_linear'\n                ]})\n\n                // This clears the color buffer to black and the depth buffer to 1\n                this.regl.clear({\n                color: [0, 0, 0, 1]\n                })\n\n                this.renderAll = this.regl({\n                frag: `\n                precision ${this.precision} float;\n                varying vec2 uv;\n                uniform sampler2D tex0;\n                uniform sampler2D tex1;\n                uniform sampler2D tex2;\n                uniform sampler2D tex3;\n\n                void main () {\n                    vec2 st = vec2(1.0 - uv.x, uv.y);\n                    st*= vec2(2);\n                    vec2 q = floor(st).xy*(vec2(2.0, 1.0));\n                    int quad = int(q.x) + int(q.y);\n                    st.x += step(1., mod(st.y,2.0));\n                    st.y += step(1., mod(st.x,2.0));\n                    st = fract(st);\n                    if(quad==0){\n                    gl_FragColor = texture2D(tex0, st);\n                    } else if(quad==1){\n                    gl_FragColor = texture2D(tex1, st);\n                    } else if (quad==2){\n                    gl_FragColor = texture2D(tex2, st);\n                    } else {\n                    gl_FragColor = texture2D(tex3, st);\n                    }\n\n                }\n                `,\n                vert: `\n                precision ${this.precision} float;\n                attribute vec2 position;\n                varying vec2 uv;\n\n                void main () {\n                    uv = position;\n                    gl_Position = vec4(1.0 - 2.0 * position, 0, 1);\n                }`,\n                attributes: {\n                    position: [\n                    [-2, 0],\n                    [0, -2],\n                    [2, 2]\n                    ]\n                },\n                uniforms: {\n                    tex0: this.regl.prop('tex0'),\n                    tex1: this.regl.prop('tex1'),\n                    tex2: this.regl.prop('tex2'),\n                    tex3: this.regl.prop('tex3')\n                },\n                count: 3,\n                depth: { enable: false }\n                })\n\n                this.renderFbo = this.regl({\n                frag: `\n                precision ${this.precision} float;\n                varying vec2 uv;\n                uniform vec2 resolution;\n                uniform sampler2D tex0;\n\n                void main () {\n                    gl_FragColor = texture2D(tex0, vec2(1.0 - uv.x, uv.y));\n                }\n                `,\n                vert: `\n                precision ${this.precision} float;\n                attribute vec2 position;\n                varying vec2 uv;\n\n                void main () {\n                    uv = position;\n                    gl_Position = vec4(1.0 - 2.0 * position, 0, 1);\n                }`,\n                attributes: {\n                    position: [\n                    [-2, 0],\n                    [0, -2],\n                    [2, 2]\n                    ]\n                },\n                uniforms: {\n                    tex0: this.regl.prop('tex0'),\n                    resolution: this.regl.prop('resolution')\n                },\n                count: 3,\n                depth: { enable: false }\n                })\n            }\n\n            _initOutputs (numOutputs) {\n                const self = this\n                this.o = (Array(numOutputs)).fill().map((el, index) => {\n                var o = new Output({\n                    regl: this.regl,\n                    width: this.width,\n                    height: this.height,\n                    precision: this.precision\n                })\n                o.render()\n                o.id = index\n                if (self.makeGlobal) window['o' + index] = o\n                return o\n                })\n\n                // set default output\n                this.output = this.o[0]\n            }\n\n            _initSources (numSources) {\n                this.s = []\n                for(var i = 0; i < numSources; i++) {\n                this.createSource()\n                }\n            }\n\n            _setBpm(bpm) {\n                this.bpm = bpm\n            }\n\n            createSource () {\n                let s = new Source({regl: this.regl, pb: this.pb, width: this.width, height: this.height})\n                if(this.makeGlobal) {\n                window['s' + this.s.length] = s\n                }\n                this.s.push(s)\n                return s\n            }\n\n            _generateGlslTransforms () {\n                const self = this\n                const gen = new GeneratorFactory(this.o[0], this.precision)\n                window.generator = gen\n                Object.keys(gen.functions).forEach((key)=>{\n                self[key] = gen.functions[key]\n                if(self.makeGlobal === true) {\n                    window[key] = gen.functions[key]\n                }\n                })\n            }\n\n            render (output) {\n                if (output) {\n                this.output = output\n                this.isRenderingAll = false\n                } else {\n                this.isRenderingAll = true\n                }\n            }\n\n            tick (dt, uniforms) {\n\n            //  if(self.detectAudio === true) self.fft = self.audio.frequencies()\n            // this.regl.frame(function () {\n                this.time += dt * 0.001\n                // console.log(this.time)\n                // this.regl.clear({\n                //   color: [0, 0, 0, 1]\n                // })\n                window.time = this.time\n                if(this.detectAudio === true) this.audio.tick()\n                for (let i = 0; i < this.s.length; i++) {\n                this.s[i].tick(this.time)\n                }\n\n                for (let i = 0; i < this.o.length; i++) {\n                //  console.log('WIDTH', this.canvas.width, this.o[0].getCurrent())\n                this.o[i].tick({\n                    time: this.time,\n                    mouse: mouse,\n                    bpm: this.bpm,\n                    resolution: [this.canvas.width, this.canvas.height]\n                })\n                }\n\n                // console.log(\"looping\", self.o[0].fbo)\n                if (this.isRenderingAll) {\n                this.renderAll({\n                    tex0: this.o[0].getCurrent(),\n                    tex1: this.o[1].getCurrent(),\n                    tex2: this.o[2].getCurrent(),\n                    tex3: this.o[3].getCurrent(),\n                    resolution: [this.canvas.width, this.canvas.height]\n                })\n                } else {\n                //  console.log('out', self.output.id)\n                this.renderFbo({\n                    tex0: this.output.getCurrent(),\n                    resolution: [this.canvas.width, this.canvas.height]\n                })\n                }\n                if(this.saveFrame === true) {\n                this.canvasToImage()\n                this.saveFrame = false\n                }\n            }\n\n\n            }","level":"log","timestamp":1723942267956},{"text":"352434081.31031936","level":"log","timestamp":1723942268119},{"text":"0.8256237899337312","level":"log","timestamp":1723942268119},{"text":"[.WebGL-0x29800378e00]GL Driver Message (OpenGL, Performance, GL_CLOSE_PATH_NV, High): GPU stall due to ReadPixels","level":"warning","timestamp":1723942268479},{"text":"[.WebGL-0x29800378e00]GL Driver Message (OpenGL, Performance, GL_CLOSE_PATH_NV, High): GPU stall due to ReadPixels","level":"warning","timestamp":1723942268479},{"text":"[.WebGL-0x29800378e00]GL Driver Message (OpenGL, Performance, GL_CLOSE_PATH_NV, High): GPU stall due to ReadPixels","level":"warning","timestamp":1723942268479},{"text":"[.WebGL-0x29800378e00]GL Driver Message (OpenGL, Performance, GL_CLOSE_PATH_NV, High): GPU stall due to ReadPixels (this message will no longer repeat)","level":"warning","timestamp":1723942268659}],"screenshotDelay":10000},"timestamp":1723942266538},"created_at":"2024-08-18T00:51:18.409+00:00","updated_at":"2024-08-18T00:51:18.409+00:00"}