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<!DOCTYPE html>
<html>
<head>
<title>Matrix digital rain</title>
<meta charset="utf-8" />
<meta name="apple-mobile-web-app-capable" content="yes" /></meta>
<meta name="apple-mobile-web-app-status-bar-style" content="black-translucent" /></meta>
<meta name="viewport" content="width=device-width, user-scalable=no, minimum-scale=1.0, maximum-scale=1.0, viewport-fit=cover" />
<style>
@supports (padding-top: env(safe-area-inset-top)) {
body {
padding: 0;
height: calc(100% + env(safe-area-inset-top));
}
}
body {
background: transparent;
overflow: hidden;
margin: 0;
}
canvas {
width: 100vw;
height: 100vh;
}
</style>
</head>
<body>
<canvas id="matrixCanvas"></canvas>
<script type="text/javascript">
/*
MIT License
Copyright (c) 2018 Rezmason
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
*/
const extendedContext = {};
const programs = {};
const textures = {};
const dynamicSizes = { fullscreen: { scale: 1 } };
const framebuffers = {};
const geometry = {};
const attributes = {};
const uniforms = {};
const msdfDataURL = 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";
const extensionNames = [
"oes_texture_half_float",
"oes_texture_half_float_linear",
"ext_color_buffer_half_float",
"webgl_color_buffer_float",
"oes_standard_derivatives",
];
const palette = [
[0, 0, 0, 0],
[7, 33, 0, 255],
[15, 63, 2, 255],
[22, 96, 5, 255],
[38, 117, 17, 250],
[53, 137, 33, 250],
[71, 160, 48, 250],
[86, 181, 63, 250],
[104, 204, 79, 250],
[119, 224, 94, 250],
[135, 247, 109, 0],
[155, 247, 132, 0],
[175, 249, 158, 0],
[175, 249, 158, 0],
[175, 249, 158, 0],
[175, 249, 158, 0],
];
const fullscreen_frag_shader_source = `
precision mediump float;
varying vec2 vUV;
uniform sampler2D tex;
void main() {
vec4 color = texture2D(tex, vUV);
color.a = color.r; // Assuming the red channel is used for brightness
gl_FragColor = color;
}
`;
const fullscreen_vert_shader_source = `
precision mediump float;
attribute vec2 aPosition;
varying vec2 vUV;
void main() {
vUV = 0.5 * (aPosition + 1.0);
gl_Position = vec4(aPosition, 0, 1);
}
`;
const rain_compute_shader_source = `
precision highp float;
#define PI 3.14159265359
#define SQRT_2 1.4142135623730951
#define SQRT_5 2.23606797749979
uniform sampler2D previousComputeState;
uniform float numColumns, numRows;
uniform float time, tick;
uniform float fallSpeed, cycleSpeed;
uniform float glyphSequenceLength;
uniform float raindropLength;
highp float randomFloat( const in vec2 uv ) {
const highp float a = 12.9898, b = 78.233, c = 43758.5453;
highp float dt = dot( uv.xy, vec2( a,b ) ), sn = mod( dt, PI );
return fract(sin(sn) * c);
}
float wobble(float x) {
return x + 0.3 * sin(SQRT_2 * x) + 0.2 * sin(SQRT_5 * x);
}
float getRainBrightness(float simTime, vec2 glyphPos) {
float columnTimeOffset = randomFloat(vec2(glyphPos.x, 0.)) * 1000.;
float columnSpeedOffset = randomFloat(vec2(glyphPos.x + 0.1, 0.)) * 0.5 + 0.5;
float columnTime = columnTimeOffset + simTime * fallSpeed * columnSpeedOffset;
float rainTime = (glyphPos.y * 0.01 + columnTime) / raindropLength;
rainTime = wobble(rainTime);
return 1.0 - fract(rainTime);
}
vec2 computeRaindrop(float simTime, vec2 glyphPos) {
float brightness = getRainBrightness(simTime, glyphPos);
float brightnessBelow = getRainBrightness(simTime, glyphPos + vec2(0., -1.));
bool cursor = brightness > brightnessBelow;
return vec2(brightness, cursor);
}
vec2 computeSymbol(float simTime, bool isFirstFrame, vec2 glyphPos, vec2 screenPos, vec4 previous) {
float previousSymbol = previous.r;
float previousAge = previous.g;
bool resetGlyph = isFirstFrame;
if (resetGlyph) {
previousAge = randomFloat(screenPos + 0.5);
previousSymbol = floor(glyphSequenceLength * randomFloat(screenPos));
}
float age = previousAge;
float symbol = previousSymbol;
if (mod(tick, 1.0) == 0.) {
age += cycleSpeed;
if (age >= 1.) {
symbol = floor(glyphSequenceLength * randomFloat(screenPos + simTime));
age = fract(age);
}
}
return vec2(symbol, age);
}
void main() {
vec2 glyphPos = gl_FragCoord.xy;
vec2 screenPos = glyphPos / vec2(numColumns, numRows);
vec2 raindrop = computeRaindrop(time, glyphPos);
bool isFirstFrame = tick <= 1.;
vec4 previous = texture2D( previousComputeState, screenPos );
vec4 previousSymbol = vec4(previous.ba, 0.0, 0.0);
vec2 symbol = computeSymbol(time, isFirstFrame, glyphPos, screenPos, previousSymbol);
gl_FragColor = vec4(raindrop, symbol);
}
`;
const rain_vert_shader_source = `
precision lowp float;
attribute vec2 aPosition;
uniform vec2 size;
varying vec2 vUV;
void main() {
vUV = aPosition;
vec2 proportion = (size.y > size.x ? vec2(size.y / size.x, 1.) : vec2(1., size.x / size.y));
gl_Position = vec4((aPosition - 0.5) * 2.0 * proportion, 0.0, 1.0);
}
`;
const rain_frag_shader_source = `
#define PI 3.14159265359
#ifdef GL_OES_standard_derivatives
#extension GL_OES_standard_derivatives: enable
#endif
precision lowp float;
uniform sampler2D computeState;
uniform float numColumns, numRows;
uniform sampler2D glyphMSDF;
uniform float msdfPxRange;
uniform vec2 glyphMSDFSize;
uniform float glyphSequenceLength;
uniform vec2 glyphTextureGridSize;
varying vec2 vUV;
float median3(vec3 i) {
return max(min(i.r, i.g), min(max(i.r, i.g), i.b));
}
float modI(float a, float b) {
float m = a - floor((a + 0.5) / b) * b;
return floor(m + 0.5);
}
vec3 getBrightness(vec2 raindrop, vec2 uv) {
float base = raindrop.r;
bool isCursor = bool(raindrop.g);
float glint = base;
base = base * 1.1 - 0.5;
glint = glint * 2.5 - 1.5;
return vec3(
(isCursor ? vec2(0.0, 1.0) : vec2(1.0, 0.0)) * base,
glint
);
}
vec2 getSymbolUV(float index) {
float symbolX = modI(index, glyphTextureGridSize.x);
float symbolY = (index - symbolX) / glyphTextureGridSize.x;
symbolY = glyphTextureGridSize.y - symbolY - 1.;
return vec2(symbolX, symbolY);
}
vec2 getSymbol(vec2 uv, float index) {
uv = fract(uv * vec2(numColumns, numRows));
uv = (uv + getSymbolUV(index)) / glyphTextureGridSize;
vec2 symbol;
{
vec2 unitRange = vec2(msdfPxRange) / glyphMSDFSize;
vec2 screenTexSize = vec2(1.0) / fwidth(uv);
float screenPxRange = max(0.5 * dot(unitRange, screenTexSize), 1.0);
float signedDistance = median3(texture2D(glyphMSDF, uv).rgb);
float screenPxDistance = screenPxRange * (signedDistance - 0.5);
symbol.r = clamp(screenPxDistance + 0.5, 0.0, 1.0);
}
return symbol;
}
void main() {
vec4 data = texture2D(computeState, vUV);
vec3 brightness = getBrightness(data.rg, vUV);
vec2 symbol = getSymbol(vUV, data.b);
gl_FragColor = vec4(brightness.rg * symbol.r, brightness.b * symbol.g, 0.);
}
`;
const bloom_high_pass_shader_source = `
precision mediump float;
uniform sampler2D tex;
uniform float highPassThreshold;
varying vec2 vUV;
void main() {
vec4 color = texture2D(tex, vUV);
if (color.r < highPassThreshold) color.r = 0.0;
if (color.g < highPassThreshold) color.g = 0.0;
if (color.b < highPassThreshold) color.b = 0.0;
gl_FragColor = color;
}
`;
const bloom_blur_shader_source = `
precision mediump float;
uniform vec2 size;
uniform sampler2D tex;
uniform vec2 direction;
varying vec2 vUV;
void main() {
vec2 proportion = (size.y > size.x ? vec2(size.y / size.x, 1.) : vec2(1., size.x / size.y));
gl_FragColor =
texture2D(tex, vUV) * 0.442 +
(
texture2D(tex, vUV + direction / max(size.y, size.x) * proportion) +
texture2D(tex, vUV - direction / max(size.y, size.x) * proportion)
) * 0.279;
}
`;
const bloom_combine_shader_source = `
precision mediump float;
uniform sampler2D pyr_0, pyr_1, pyr_2, pyr_3, pyr_4;
uniform float bloomStrength;
varying vec2 vUV;
void main() {
vec4 total = vec4(0.);
total += texture2D(pyr_0, vUV) * 0.96549;
total += texture2D(pyr_1, vUV) * 0.92832;
total += texture2D(pyr_2, vUV) * 0.88790;
total += texture2D(pyr_3, vUV) * 0.84343;
total += texture2D(pyr_4, vUV) * 0.79370;
gl_FragColor = total * bloomStrength;
}
`;
const palette_shader_source = `
precision mediump float;
#define PI 3.14159265359
uniform sampler2D tex, bloomTex, paletteTex;
uniform float time;
varying vec2 vUV;
highp float rand( const in vec2 uv, const in float t ) {
const highp float a = 12.9898, b = 78.233, c = 43758.5453;
highp float dt = dot( uv.xy, vec2( a,b ) ), sn = mod( dt, PI );
return fract(sin(sn) * c + t);
}
void main() {
vec4 primary = texture2D(tex, vUV);
vec4 bloom = texture2D(bloomTex, vUV);
vec4 brightness = primary + bloom - rand( gl_FragCoord.xy, time ) * 0.0167;
gl_FragColor = vec4(
texture2D( paletteTex, vec2(brightness.r, 0.0)).rgb
+ min(vec3(0.756, 1.0, 0.46) * brightness.g * 2.0, vec3(1.0)),
1.0
);
}
`;
const init = (gl) => Object.assign(extendedContext, ...extensionNames.map((name) => Object.getPrototypeOf(gl.getExtension(name))));
const load = (gl, msdfImage, palette) => {
const buildShader = (source, isFragment) => {
const shader = gl.createShader(isFragment ? gl.FRAGMENT_SHADER : gl.VERTEX_SHADER);
gl.shaderSource(shader, source);
gl.compileShader(shader);
return shader;
};
const buildProgram = (vertexShader, fragmentShader) => {
const program = gl.createProgram();
gl.attachShader(program, vertexShader);
gl.attachShader(program, fragmentShader);
gl.linkProgram(program);
return program;
};
const fullscreen_frag_shader = buildShader(fullscreen_frag_shader_source, true);
const fullscreen_vert_shader = buildShader(fullscreen_vert_shader_source, false);
const rain_compute_shader = buildShader(rain_compute_shader_source, true);
const rain_frag_shader = buildShader(rain_frag_shader_source, true);
const rain_vert_shader = buildShader(rain_vert_shader_source, false);
const bloom_high_pass_shader = buildShader(bloom_high_pass_shader_source, true);
const bloom_blur_shader = buildShader(bloom_blur_shader_source, true);
const bloom_combine_shader = buildShader(bloom_combine_shader_source, true);
const palette_shader = buildShader(palette_shader_source, true);
programs.fullscreen = buildProgram(fullscreen_vert_shader, fullscreen_frag_shader);
uniforms.rain_program_tex = gl.getUniformLocation(programs.fullscreen, "tex");
attributes.fullscreen_program_aPosition = gl.getAttribLocation(programs.fullscreen, "aPosition");
programs.rain_compute = buildProgram(fullscreen_vert_shader, rain_compute_shader);
attributes.rain_compute_program_aPosition = gl.getAttribLocation(programs.rain_compute, "aPosition");
uniforms.rain_compute_program_time = gl.getUniformLocation(programs.rain_compute, "time");
uniforms.rain_compute_program_previousComputeState = gl.getUniformLocation(programs.rain_compute, "previousComputeState");
uniforms.rain_compute_program_tick = gl.getUniformLocation(programs.rain_compute, "tick");
gl.useProgram(programs.rain_compute);
gl.uniform1f(gl.getUniformLocation(programs.rain_compute, "numColumns"), 80);
gl.uniform1f(gl.getUniformLocation(programs.rain_compute, "glyphSequenceLength"), 57);
gl.uniform1f(gl.getUniformLocation(programs.rain_compute, "numRows"), 80);
gl.uniform1f(gl.getUniformLocation(programs.rain_compute, "fallSpeed"), 0.3);
gl.uniform1f(gl.getUniformLocation(programs.rain_compute, "raindropLength"), 0.75);
gl.uniform1f(gl.getUniformLocation(programs.rain_compute, "cycleSpeed"), 0.03);
programs.rain = buildProgram(rain_vert_shader, rain_frag_shader);
attributes.rain_program_aPosition = gl.getAttribLocation(programs.rain, "aPosition");
uniforms.rain_program_size = gl.getUniformLocation(programs.rain, "size");
uniforms.rain_program_computeState = gl.getUniformLocation(programs.rain, "computeState");
uniforms.rain_program_glyphMSDF = gl.getUniformLocation(programs.rain, "glyphMSDF");
gl.useProgram(programs.rain);
gl.uniform2f(gl.getUniformLocation(programs.rain, "glyphTextureGridSize"), 8, 8);
gl.uniform1f(gl.getUniformLocation(programs.rain, "numColumns"), 80);
gl.uniform2f(gl.getUniformLocation(programs.rain, "glyphMSDFSize"), 512, 512);
gl.uniform1f(gl.getUniformLocation(programs.rain, "numRows"), 80);
gl.uniform1f(gl.getUniformLocation(programs.rain, "msdfPxRange"), 4);
programs.bloom_high_pass = buildProgram(fullscreen_vert_shader, bloom_high_pass_shader);
attributes.bloom_high_pass_program_aPosition = gl.getAttribLocation(programs.bloom_high_pass, "aPosition");
uniforms.bloom_high_pass_program_tex = gl.getUniformLocation(programs.bloom_high_pass, "tex");
gl.useProgram(programs.bloom_high_pass);
gl.uniform1f(gl.getUniformLocation(programs.bloom_high_pass, "highPassThreshold"), 0.1);
programs.bloom_blur = buildProgram(fullscreen_vert_shader, bloom_blur_shader);
attributes.bloom_blur_program_aPosition = gl.getAttribLocation(programs.bloom_blur, "aPosition");
uniforms.bloom_blur_program_tex = gl.getUniformLocation(programs.bloom_blur, "tex");
uniforms.bloom_blur_program_size = gl.getUniformLocation(programs.bloom_blur, "size");
uniforms.bloom_blur_program_direction = gl.getUniformLocation(programs.bloom_blur, "direction");
programs.bloom_combine = buildProgram(fullscreen_vert_shader, bloom_combine_shader);
attributes.bloom_combine_program_aPosition = gl.getAttribLocation(programs.bloom_combine, "aPosition");
uniforms.bloom_combine_program_pyr_0 = gl.getUniformLocation(programs.bloom_combine, "pyr_0");
uniforms.bloom_combine_program_pyr_1 = gl.getUniformLocation(programs.bloom_combine, "pyr_1");
uniforms.bloom_combine_program_pyr_2 = gl.getUniformLocation(programs.bloom_combine, "pyr_2");
uniforms.bloom_combine_program_pyr_3 = gl.getUniformLocation(programs.bloom_combine, "pyr_3");
uniforms.bloom_combine_program_pyr_4 = gl.getUniformLocation(programs.bloom_combine, "pyr_4");
gl.useProgram(programs.bloom_combine);
gl.uniform1f(gl.getUniformLocation(programs.bloom_combine, "bloomStrength"), 0.7);
programs.palette = buildProgram(fullscreen_vert_shader, palette_shader);
attributes.palette_program_aPosition = gl.getAttribLocation(programs.palette, "aPosition");
uniforms.palette_program_tex = gl.getUniformLocation(programs.palette, "tex");
uniforms.palette_program_bloomTex = gl.getUniformLocation(programs.palette, "bloomTex");
uniforms.palette_program_time = gl.getUniformLocation(programs.palette, "time");
uniforms.palette_program_paletteTex = gl.getUniformLocation(programs.palette, "paletteTex");
geometry.rain = gl.createBuffer();
gl.bindBuffer(gl.ARRAY_BUFFER, geometry.rain);
gl.bufferData(gl.ARRAY_BUFFER, Float32Array.from([0, 0, 0, 1, 1, 1, 0, 0, 1, 1, 1, 0]), gl.STATIC_DRAW);
geometry.fullscreen = gl.createBuffer();
gl.bindBuffer(gl.ARRAY_BUFFER, geometry.fullscreen);
gl.bufferData(gl.ARRAY_BUFFER, Float32Array.from([-4, -4, 4, -4, 0, 4]), gl.STATIC_DRAW);
const setTexParams = (texture, isLinear, data) => {
gl.activeTexture(gl.TEXTURE0);
gl.bindTexture(gl.TEXTURE_2D, texture);
const filter = isLinear ? gl.LINEAR : gl.NEAREST;
gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_MIN_FILTER, filter);
gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_MAG_FILTER, filter);
gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_WRAP_S, gl.CLAMP_TO_EDGE);
gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_WRAP_T, gl.CLAMP_TO_EDGE);
if (data != null) {
if (data instanceof HTMLImageElement) {
gl.pixelStorei(gl.UNPACK_FLIP_Y_WEBGL, true);
gl.texImage2D(gl.TEXTURE_2D, 0, gl.RGBA, gl.RGBA, gl.UNSIGNED_BYTE, data);
} else {
gl.texImage2D(gl.TEXTURE_2D, 0, gl.RGBA, data.length, 1, 0, gl.RGBA, gl.UNSIGNED_BYTE, Uint8ClampedArray.from(data.flat()));
}
}
};
for (let i = 0; i < 2; i++) {
const name = "rain_compute_doublebuffer_" + i;
const texture = gl.createTexture();
gl.activeTexture(gl.TEXTURE0);
gl.bindTexture(gl.TEXTURE_2D, texture);
gl.texImage2D(gl.TEXTURE_2D, 0, gl.RGBA, 80, 80, 0, gl.RGBA, extendedContext.HALF_FLOAT_OES, null);
setTexParams(texture, false);
const framebuffer = gl.createFramebuffer();
gl.bindFramebuffer(gl.FRAMEBUFFER, framebuffer);
gl.framebufferTexture2D(gl.FRAMEBUFFER, gl.COLOR_ATTACHMENT0, gl.TEXTURE_2D, texture, 0);
textures[name] = texture;
framebuffers[name] = framebuffer;
}
const buildAndAddRTT = (name, scale) => {
const texture = gl.createTexture();
dynamicSizes[name] = { scale };
setTexParams(texture, true);
const framebuffer = gl.createFramebuffer();
gl.bindFramebuffer(gl.FRAMEBUFFER, framebuffer);
gl.framebufferTexture2D(gl.FRAMEBUFFER, gl.COLOR_ATTACHMENT0, gl.TEXTURE_2D, texture, 0);
textures[name] = texture;
framebuffers[name] = framebuffer;
};
buildAndAddRTT("rain_output", 1);
for (let i = 0; i < 5; i++) {
const scale = 0.4 / 2 ** i;
buildAndAddRTT("bloom_high_pass_pyr_" + i, scale);
buildAndAddRTT("bloom_h_blur_pyr_" + i, scale);
buildAndAddRTT("bloom_v_blur_pyr_" + i, scale);
}
buildAndAddRTT("bloom_output", 1);
buildAndAddRTT("palette_output", 1);
textures.palette = gl.createTexture();
setTexParams(textures.palette, true, palette);
textures.msdf = gl.createTexture();
setTexParams(textures.msdf, true, msdfImage);
gl.enableVertexAttribArray(0);
gl.disable(gl.DEPTH_TEST);
gl.blendFuncSeparate(1, 1, 1, 1);
gl.clearColor(0, 0, 0, 1);
};
const resize = (gl, width, height) => {
dynamicSizes.fullscreen.width = width;
dynamicSizes.fullscreen.height = height;
for (var name in textures) {
const size = dynamicSizes[name];
if (size == null) {
continue;
}
size.width = Math.floor(width * size.scale);
size.height = Math.floor(height * size.scale);
gl.activeTexture(gl.TEXTURE0);
gl.bindTexture(gl.TEXTURE_2D, textures[name]);
gl.texImage2D(gl.TEXTURE_2D, 0, gl.RGBA, size.width, size.height, 0, gl.RGBA, gl.UNSIGNED_BYTE, null);
}
gl.useProgram(programs.rain);
gl.uniform2f(uniforms.rain_program_size, width, height);
};
const setViewportSizeTo = (gl, name) => {
const size = dynamicSizes[name];
gl.viewport(0, 0, size.width, size.height);
};
const bindTextureTo = (gl, texName, uniformName, index) => {
gl.activeTexture(gl.TEXTURE0 + index);
gl.bindTexture(gl.TEXTURE_2D, textures[texName]);
gl.uniform1i(uniforms[uniformName], index);
};
const bindGeometryTo = (gl, geometryName, attributeName) => {
gl.bindBuffer(gl.ARRAY_BUFFER, geometry[geometryName]);
gl.vertexAttribPointer(attributes[attributeName], 2, gl.FLOAT, false, 0, 0);
};
const draw = (gl, tick, time) => {
const doubleBufferFrontName = "rain_compute_doublebuffer_" + (tick % 2);
const doubleBufferBackName = "rain_compute_doublebuffer_" + ((tick + 1) % 2);
// rain compute
gl.bindFramebuffer(gl.FRAMEBUFFER, framebuffers[doubleBufferFrontName]);
gl.viewport(0, 0, 80, 80);
gl.useProgram(programs.rain_compute);
bindGeometryTo(gl, "fullscreen", "rain_compute_program_aPosition");
bindTextureTo(gl, doubleBufferBackName, "rain_compute_program_previousComputeState", 0);
gl.uniform1f(uniforms.rain_compute_program_time, time);
gl.uniform1f(uniforms.rain_compute_program_tick, tick);
gl.drawArrays(gl.TRIANGLES, 0, 3);
// rain
gl.bindFramebuffer(gl.FRAMEBUFFER, framebuffers.rain_output);
setViewportSizeTo(gl, "rain_output");
gl.clear(gl.COLOR_BUFFER_BIT);
gl.enable(gl.BLEND);
gl.useProgram(programs.rain);
bindGeometryTo(gl, "rain", "rain_program_aPosition");
bindTextureTo(gl, doubleBufferFrontName, "rain_program_computeState", 0);
bindTextureTo(gl, "msdf", "rain_program_glyphMSDF", 1);
gl.drawArrays(gl.TRIANGLES, 0, 6);
gl.disable(gl.BLEND);
// high pass pyramid
gl.useProgram(programs.bloom_high_pass);
gl.bindBuffer(gl.ARRAY_BUFFER, geometry.fullscreen);
gl.vertexAttribPointer(attributes.bloom_high_pass_program_aPosition, 2, gl.FLOAT, false, 0, 0);
for (let i = 0; i < 5; i++) {
const name = "bloom_high_pass_pyr_" + i;
gl.bindFramebuffer(gl.FRAMEBUFFER, framebuffers[name]);
const size = dynamicSizes[name];
gl.viewport(0, 0, size.width, size.height);
const src = i === 0 ? textures.rain_output : textures["bloom_high_pass_pyr_" + (i - 1)];
gl.activeTexture(gl.TEXTURE0);
gl.bindTexture(gl.TEXTURE_2D, src);
gl.uniform1i(uniforms.bloom_high_pass_program_tex, 0);
gl.drawArrays(gl.TRIANGLES, 0, 3);
}
// blur pyramids
gl.useProgram(programs.bloom_blur);
gl.bindBuffer(gl.ARRAY_BUFFER, geometry.fullscreen);
gl.vertexAttribPointer(attributes.bloom_blur_program_aPosition, 2, gl.FLOAT, false, 0, 0);
for (let i = 0; i < 5; i++) {
gl.bindFramebuffer(gl.FRAMEBUFFER, framebuffers["bloom_h_blur_pyr_" + i]);
const hSize = dynamicSizes["bloom_h_blur_pyr_" + i];
gl.viewport(0, 0, hSize.width, hSize.height);
gl.uniform2f(uniforms.bloom_blur_program_size, hSize.width, hSize.height);
bindTextureTo(gl, "bloom_high_pass_pyr_" + i, "bloom_blur_program_tex", 0);
gl.uniform2f(uniforms.bloom_blur_program_direction, 1, 0);
gl.drawArrays(gl.TRIANGLES, 0, 3);
gl.bindFramebuffer(gl.FRAMEBUFFER, framebuffers["bloom_v_blur_pyr_" + i]);
const vSize = dynamicSizes["bloom_v_blur_pyr_" + i];
gl.viewport(0, 0, vSize.width, vSize.height);
bindTextureTo(gl, "bloom_h_blur_pyr_" + i, "bloom_blur_program_tex", 0);
gl.uniform2f(uniforms.bloom_blur_program_direction, 0, 1);
gl.drawArrays(gl.TRIANGLES, 0, 3);
}
// bloom combine
gl.useProgram(programs.bloom_combine);
bindGeometryTo(gl, "fullscreen", "bloom_combine_program_aPosition");
gl.bindFramebuffer(gl.FRAMEBUFFER, framebuffers.bloom_output);
setViewportSizeTo(gl, "bloom_output");
for (let i = 0; i < 5; i++) {
gl.activeTexture(gl.TEXTURE0 + i);
gl.bindTexture(gl.TEXTURE_2D, textures["bloom_v_blur_pyr_" + i]);
gl.uniform1i(uniforms["bloom_combine_program_pyr_" + i], i);
}
gl.drawArrays(gl.TRIANGLES, 0, 3);
// palette
gl.bindFramebuffer(gl.FRAMEBUFFER, framebuffers.palette_output);
setViewportSizeTo(gl, "palette_output");
gl.useProgram(programs.palette);
bindGeometryTo(gl, "fullscreen", "palette_program_aPosition");
bindTextureTo(gl, "rain_output", "palette_program_tex", 0);
bindTextureTo(gl, "bloom_output", "palette_program_bloomTex", 1);
gl.uniform1f(uniforms.palette_program_time, time);
bindTextureTo(gl, "palette", "palette_program_paletteTex", 2);
gl.drawArrays(gl.TRIANGLES, 0, 3);
// upscale
gl.bindFramebuffer(gl.FRAMEBUFFER, null);
setViewportSizeTo(gl, "fullscreen");
gl.useProgram(programs.fullscreen);
bindGeometryTo(gl, "fullscreen", "fullscreen_program_aPosition");
bindTextureTo(gl, "palette_output", "fullscreen_program_tex", 0);
gl.drawArrays(gl.TRIANGLES, 0, 3);
};
document.body.onload = async () => {
document.addEventListener("touchmove", (e) => e.preventDefault(), { passive: false });
const canvas = document.getElementById('matrixCanvas'); // Adjust this if needed
const offscreenCanvas = document.createElement('canvas');
const dimensions = { width: 1, height: 1 };
const resizeViewport = () => {
const devicePixelRatio = window.devicePixelRatio ?? 1;
canvas.width = Math.ceil(canvas.clientWidth * devicePixelRatio * 0.75);
canvas.height = Math.ceil(canvas.clientHeight * devicePixelRatio * 0.75);
offscreenCanvas.width = canvas.width;
offscreenCanvas.height = canvas.height;
};
window.onresize = resizeViewport;
resizeViewport();
const gl = canvas.getContext("webgl");
const offscreenCtx = offscreenCanvas.getContext('2d', { willReadFrequently: true });
const image = new Image();
image.crossOrigin = "anonymous";
image.src = msdfDataURL;
await image.decode();
init(gl);
load(gl, image, palette);
let tick = 0;
const start = Date.now();
const update = () => {
tick++;
let frameCount = 0;
if (dimensions.width !== canvas.width || dimensions.height !== canvas.height) {
dimensions.width = canvas.width;
dimensions.height = canvas.height;
resize(gl, dimensions.width, dimensions.height);
}
draw(gl, tick, (Date.now() - start) / 1000);
};
update();
};
</script>
</body>
</html>