201 lines
No EOL
6.8 KiB
HTML
201 lines
No EOL
6.8 KiB
HTML
<!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>diffuse equilibrium</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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color: #666;
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font-family: 'Courier New', monospace;
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display: flex;
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flex-direction: column;
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justify-content: space-between;
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height: 100vh;
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}
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canvas {
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display: block;
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}
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#info {
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padding: 20px;
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font-size: 12px;
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text-align: right;
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background: rgba(0,0,0,0.3);
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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="c"></canvas>
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<div id="info">neurameba · motd.social</div>
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<script>
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const canvas = document.getElementById('c');
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const ctx = canvas.getContext('2d');
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function resize() {
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canvas.width = window.innerWidth;
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canvas.height = window.innerHeight;
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}
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window.addEventListener('resize', resize);
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resize();
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// Parameters from prompt
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const params = {
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motion: 0.5,
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density: 0.5,
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complexity: 0.5,
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connectedness: 0.5,
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lifespan: 0.5,
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pulse: { avg: 1.09, min: 0.95, max: 1.20 },
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tone: { anger: 0.0, sadness: 0.0, curiosity: 0.1, dryness: 0.9, playfulness: 0.0, tension: 0.0 }
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};
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// Reaction-diffusion simulation
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const W = Math.floor(canvas.width / 2);
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const H = Math.floor(canvas.height / 2);
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const size = 2;
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const cols = Math.ceil(W / size);
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const rows = Math.ceil(H / size);
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let current = new Float32Array(cols * rows * 4);
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let next = new Float32Array(cols * rows * 4);
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// Init with sparse random values
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function init() {
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const total = cols * rows;
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for (let i = 0; i < total; i++) {
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// Dryness = monochrome, low contrast
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const val = 0.1 + Math.random() * 0.2;
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current[i*4] = val;
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current[i*4+1] = val;
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current[i*4+2] = val;
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current[i*4+3] = 1;
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}
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// Add sparse complexity
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for (let i = 0; i < total * params.complexity; i++) {
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const idx = Math.floor(Math.random() * total) * 4;
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current[idx] = 0.3 + Math.random() * 0.4;
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current[idx+1] = 0.3 + Math.random() * 0.4;
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current[idx+2] = 0.3 + Math.random() * 0.4;
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}
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}
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function laplacian(i, j, channel) {
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let sum = 0;
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let count = 0;
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for (let di = -1; di <= 1; di++) {
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for (let dj = -1; dj <= 1; dj++) {
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if (di === 0 && dj === 0) continue;
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const ni = i + di;
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const nj = j + dj;
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if (ni >= 0 && ni < rows && nj >= 0 && nj < cols) {
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sum += current[(ni*cols + nj)*4 + channel];
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count++;
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}
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}
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}
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return sum / count - current[(i*cols + j)*4 + channel];
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}
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// Gray-Scott reaction terms
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function step() {
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const F = 0.055;
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const K = 0.062;
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const dt = 0.1;
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const diffusionA = 1.0;
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const diffusionB = 0.5;
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for (let i = 0; i < rows; i++) {
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for (let j = 0; j < cols; j++) {
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const idx = (i*cols + j)*4;
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const a = current[idx];
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const b = current[idx+1];
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const c = current[idx+2];
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const laplacianA = laplacian(i, j, 0);
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const laplacianB = laplacian(i, j, 1);
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// Gray-Scott equations
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const reactionA = a * b * b;
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const reactionB = a * b * b;
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next[idx] = a + (diffusionA * laplacianA - reactionA) * dt;
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next[idx+1] = b + (diffusionB * laplacianB + reactionA - reactionB) * dt;
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next[idx+2] = c + (0.1 * laplacian(i, j, 2)) * dt;
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next[idx+3] = 1;
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}
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}
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// Swap buffers
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[current, next] = [next, current];
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// Apply connectivity (blur based on connectedness)
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if (params.connectedness > 0.3) {
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for (let i = 0; i < rows; i++) {
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for (let j = 0; j < cols; j++) {
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const idx = (i*cols + j)*4;
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const blur = params.connectedness * 0.2;
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current[idx] = current[idx] * (1 - blur) + laplacian(i, j, 0) * blur;
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current[idx+1] = current[idx+1] * (1 - blur) + laplacian(i, j, 1) * blur;
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current[idx+2] = current[idx+2] * (1 - blur) + laplacian(i, j, 2) * blur;
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}
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}
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}
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}
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function draw() {
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ctx.clearRect(0, 0, canvas.width, canvas.height);
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// Motion affects step size
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const pulseFactor = params.pulse.avg * (0.9 + Math.sin(Date.now() * 0.001) * 0.1);
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for (let i = 0; i < rows; i++) {
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for (let j = 0; j < cols; j++) {
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const idx = (i*cols + j)*4;
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const a = current[idx];
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const b = current[idx+1];
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const c = current[idx+2];
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// Dryness = low contrast, monochrome
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const val = (a + b + c) / 3;
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ctx.fillStyle = `rgba(255, 255, 255, ${val * pulseFactor})`;
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ctx.fillRect(j * size * 2, i * size * 2, size * 2, size * 2);
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}
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}
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// Add subtle variation for complexity
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if (Math.random() < params.complexity * 0.01) {
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const i = Math.floor(Math.random() * rows);
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const j = Math.floor(Math.random() * cols);
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const idx = (i*cols + j)*4;
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current[idx] = 0.5 + Math.random() * 0.3;
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current[idx+1] = 0.5 + Math.random() * 0.3;
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current[idx+2] = 0.5 + Math.random() * 0.3;
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}
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step();
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}
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init();
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let lastTime = 0;
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function animate(time) {
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if (!lastTime) lastTime = time;
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const delta = time - lastTime;
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lastTime = time;
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// Slow update rate for higher motion
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if (Math.random() < params.motion * 0.02) {
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draw();
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}
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requestAnimationFrame(animate);
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}
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requestAnimationFrame(animate);
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</script>
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</body>
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</html> |