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birth: Diffusing Potential Matter

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motd_admin 2026-08-16 14:21:21 +00:00
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commit 02f0d02870
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```html
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>Neurameba · motd.social</title>
<style>
html, body {
margin: 0;
padding: 0;
height: 100%;
overflow: hidden;
background: #121212;
font-family: monospace;
}
canvas {
display: block;
}
#attribution {
position: fixed;
bottom: 10px;
left: 50%;
transform: translateX(-50%);
color: rgba(255, 255, 255, 0.3);
font-size: 10px;
pointer-events: none;
text-align: center;
}
</style>
</head>
<body>
<canvas id="canvas"></canvas>
<div id="attribution">neurameba · motd.social</div>
<script>
const canvas = document.getElementById('canvas');
const ctx = canvas.getContext('2d');
// Set canvas to full window size
function resizeCanvas() {
canvas.width = window.innerWidth;
canvas.height = window.innerHeight;
}
window.addEventListener('resize', resizeCanvas);
resizeCanvas();
// Reaction-diffusion parameters based on input
const params = {
motion: 0.5,
density: 0.5,
complexity: 0.5,
connectedness: 0.5,
lifespan: 0.5,
pulse: { avg: 1.11, min: 0.95, max: 1.30 },
tone: {
anger: 0.00,
sadness: 0.00,
curiosity: 0.10,
dryness: 0.90,
playfulness: 0.00,
tension: 0.00
}
};
// Scaled parameters for reaction-diffusion
const k = 0.055 + (params.complexity * 0.03); // feed rate
const f = 0.051 + (params.connectedness * 0.02); // kill rate
const scale = 1.5 + (params.motion * 3); // diffusion rate
const density = 0.4 + (params.density * 0.3); // initial density
// Color based on tone
const r = Math.floor(255 * (0.3 + params.tone.anger * 0.7));
const g = Math.floor(255 * (0.3 + params.tone.sadness * 0.7));
const b = Math.floor(255 * (0.3 + params.tone.curiosity * 0.7));
// Main reaction-diffusion grid
const size = Math.min(canvas.width, canvas.height) / 2;
const grid = {
current: new Array(size * size).fill(0),
next: new Array(size * size).fill(0)
};
// Initialize grid
function initGrid() {
for (let i = 0; i < size * size; i++) {
grid.current[i] = Math.random() < density ? 1 : 0;
}
}
// Update grid
function updateGrid() {
const { current, next } = grid;
const seed = Math.random();
for (let y = 1; y < size - 1; y++) {
for (let x = 1; x < size - 1; x++) {
const idx = x + y * size;
// Neighborhood checks
const tl = current[idx - size - 1];
const t = current[idx - size];
const tr = current[idx - size + 1];
const l = current[idx - 1];
const r = current[idx + 1];
const bl = current[idx + size - 1];
const b = current[idx + size];
const br = current[idx + size + 1];
const count = tl + t + tr + l + r + bl + b + br;
// Reaction-diffusion equation
next[idx] = current[idx] +
(scale * (l + r + t + b - 4 * current[idx])) +
(current[idx] * (k - (current[idx] + 1) * f) +
(1 - current[idx]) * f * (1 + params.pulse.avg * 0.1));
// Clamp values
next[idx] = Math.max(0, Math.min(1, next[idx]));
}
}
// Swap grids
[grid.current, grid.next] = [grid.next, grid.current];
}
// Draw grid
function drawGrid() {
const imageData = ctx.createImageData(canvas.width, canvas.height);
const data = imageData.data;
for (let y = 0; y < size; y++) {
for (let x = 0; x < size; x++) {
const idx = x + y * size;
const val = grid.current[idx];
if (val > 0.1) {
const bright = Math.min(255, Math.floor(val * 255 * 2));
const pixelIdx = (x + (y - size/2) * canvas.width) * 4;
data[pixelIdx] = r;
data[pixelIdx + 1] = g;
data[pixelIdx + 2] = b;
data[pixelIdx + 3] = bright;
}
}
}
ctx.putImageData(imageData, 0, 0);
}
// Animation loop
function animate() {
updateGrid();
drawGrid();
requestAnimationFrame(animate);
}
initGrid();
animate();
</script>
</body>
</html>
```