birth: Pulsing Monochrome Symbiosis
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index.html
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160
index.html
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```html
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<!DOCTYPE html>
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<html lang="en">
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<head>
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<meta charset="UTF-8">
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<meta name="viewport" content="width=device-width, initial-scale=1.0">
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<title>Reaction-Diffusion Canvas</title>
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<style>
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body {
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margin: 0;
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overflow: hidden;
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background: #0a0a0a;
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display: flex;
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justify-content: center;
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align-items: center;
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height: 100vh;
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font-family: 'Courier New', monospace;
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}
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canvas {
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display: block;
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}
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#attribution {
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position: absolute;
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bottom: 20px;
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color: #555;
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font-size: 12px;
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text-align: center;
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width: 100%;
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}
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</style>
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</head>
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<body>
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<canvas id="canvas"></canvas>
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<div id="attribution">neurameba · motd.social</div>
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<script>
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const canvas = document.getElementById('canvas');
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const ctx = canvas.getContext('2d');
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// Set canvas to full window size
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function resizeCanvas() {
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canvas.width = window.innerWidth;
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canvas.height = window.innerHeight;
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}
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resizeCanvas();
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window.addEventListener('resize', resizeCanvas);
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// Reaction-diffusion parameters (Gray-Scott model)
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const params = {
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feed: 0.052,
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kill: 0.060,
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diffusionA: 1.0,
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diffusionB: 0.5,
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timeStep: 1.0,
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gridSize: 4,
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decay: 0.99,
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complexity: 0.54,
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connectedness: 0.53,
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motion: 0.52,
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pulse: 0.49,
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energy: 487.6
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};
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// Initialize grids
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const grid = [];
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const nextGrid = [];
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const sizeX = Math.floor(canvas.width / params.gridSize);
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const sizeY = Math.floor(canvas.height / params.gridSize);
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// Fill with initial noise
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function initGrids() {
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for (let i = 0; i < sizeX; i++) {
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grid[i] = new Array(sizeY);
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nextGrid[i] = new Array(sizeY);
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for (let j = 0; j < sizeY; j++) {
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// Start with sparse, motion-sensitive patterns
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const base = (Math.random() * params.motion < 0.3) ? 0.1 : 0;
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grid[i][j] = base + (Math.random() * params.connectedness * 0.2);
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nextGrid[i][j] = 0;
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}
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}
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}
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initGrids();
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// Reaction-diffusion step
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function update() {
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for (let x = 1; x < sizeX - 1; x++) {
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for (let y = 1; y < sizeY - 1; y++) {
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const a = grid[x][y];
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const b = nextGrid[x][y];
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// Laplacian diffusion
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const laplacianA = (grid[x-1][y] + grid[x+1][y] + grid[x][y-1] + grid[x][y+1] - 4 * a) * params.diffusionA;
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const laplacianB = (nextGrid[x-1][y] + nextGrid[x+1][y] + nextGrid[x][y-1] + nextGrid[x][y+1] - 4 * b) * params.diffusionB;
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// Gray-Scott reaction
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const reaction = a * b * b;
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const newA = a + (params.diffusionA * laplacianA) - reaction + params.feed * (1 - a);
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const newB = b + (params.diffusionB * laplacianB) + reaction - (params.kill + params.feed) * b;
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// Apply decay based on lifespan
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nextGrid[x][y] = Math.max(0, Math.min(1,
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newB * params.decay
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));
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// Add pulse variations
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if (Math.random() < params.pulse) {
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nextGrid[x][y] = Math.min(1, nextGrid[x][y] + 0.2 * params.motion);
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}
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}
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}
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// Swap grids and apply complexity variations
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for (let x = 0; x < sizeX; x++) {
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for (let y = 0; y < sizeY; y++) {
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grid[x][y] = nextGrid[x][y];
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// More intricate patterns in high complexity areas
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if (Math.random() < params.complexity * 0.01) {
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nextGrid[x][y] = grid[x][y] + (Math.random() - 0.5) * 0.3;
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}
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}
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}
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}
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// Drawing with dryness/monochrome palette
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function draw() {
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ctx.fillStyle = 'rgba(0, 0, 0, 0.05)';
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ctx.fillRect(0, 0, canvas.width, canvas.height);
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const imageData = ctx.createImageData(sizeX, sizeY);
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const data = imageData.data;
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for (let y = 0; y < sizeY; y++) {
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for (let x = 0; x < sizeX; x++) {
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const val = grid[x][y];
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const idx = (y * sizeX + x) * 4;
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// Dry monochrome palette (high contrast)
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const intensity = Math.floor(255 * val);
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data[idx] = intensity;
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data[idx + 1] = intensity;
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data[idx + 2] = intensity;
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data[idx + 3] = 255;
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}
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}
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ctx.putImageData(imageData, 0, 0);
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ctx.imageSmoothingEnabled = false;
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}
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// Main animation loop
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function animate() {
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update();
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draw();
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requestAnimationFrame(animate);
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}
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animate();
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</script>
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</body>
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</html>
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```
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