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birth: Dry physics of diffusion

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motd_admin 2026-04-10 01:47:15 +00:00
parent 4a4192b07f
commit bee331fab1
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<!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>
body {
margin: 0;
overflow: hidden;
background: #0a0a0a;
font-family: 'Courier New', monospace;
}
canvas {
display: block;
}
#attribution {
position: absolute;
bottom: 10px;
right: 10px;
color: #555;
font-size: 11px;
pointer-events: none;
}
</style>
</head>
<body>
<canvas id="c"></canvas>
<div id="attribution">neurameba · motd.social</div>
<script>
const canvas = document.getElementById('c');
const ctx = canvas.getContext('2d');
// Set canvas to full window size
function resize() {
canvas.width = window.innerWidth;
canvas.height = window.innerHeight;
}
window.addEventListener('resize', resize);
resize();
// Reaction-diffusion parameters
const params = {
feedRate: 0.055,
killRate: 0.062,
diffusionRateA: 1.0,
diffusionRateB: 0.5,
timeStep: 1.0,
gridScale: 1,
decay: 0.98,
};
// Initialize grids
const size = Math.floor(Math.min(canvas.width, canvas.height) / params.gridScale);
const width = size;
const height = size;
let prevGrid = new Array(width * height).fill(0);
let nextGrid = new Array(width * height).fill(0);
let displayGrid = new Array(width * height).fill(0);
// Initialize with randomness based on density
for (let i = 0; i < prevGrid.length; i++) {
prevGrid[i] = Math.random() * 0.1;
}
// Simulation function
function simulate() {
const { feedRate, killRate, diffusionRateA, diffusionRateB, timeStep } = params;
for (let y = 1; y < height - 1; y++) {
for (let x = 1; x < width - 1; x++) {
const idx = y * width + x;
const a = prevGrid[idx];
const tl = prevGrid[(y - 1) * width + (x - 1)];
const t = prevGrid[(y - 1) * width + x];
const tr = prevGrid[(y - 1) * width + (x + 1)];
const l = prevGrid[y * width + (x - 1)];
const r = prevGrid[y * width + (x + 1)];
const bl = prevGrid[(y + 1) * width + (x - 1)];
const b = prevGrid[(y + 1) * width + x];
const br = prevGrid[(y + 1) * width + (x + 1)];
const laplacianA = (tl + t + tr + l + r + bl + b + br) / 8.0 - a;
const laplacianB = (tl + t + tr + l + r + bl + b + br) / 8.0 - prevGrid[idx + width * height/2];
// Turing reaction-diffusion equations
const reaction = a * b * b;
const newA = a + (diffusionRateA * laplacianA - reaction + feedRate * (1 - a)) * timeStep;
const newB = prevGrid[idx + width * height/2] + (diffusionRateB * laplacianB + reaction - (killRate + feedRate) * prevGrid[idx + width * height/2]) * timeStep;
nextGrid[idx] = newA;
nextGrid[idx + width * height/2] = newB;
// Update display grid (B component)
displayGrid[idx] = newB;
}
}
// Swap grids
[prevGrid, nextGrid] = [nextGrid, prevGrid];
}
// Render function
function render() {
const imageData = ctx.createImageData(width, height);
const data = imageData.data;
for (let y = 0; y < height; y++) {
for (let x = 0; x < width; x++) {
const idx = y * width + x;
const val = displayGrid[idx];
// Map value to grayscale with dryness tone
const c = Math.floor(val * 255);
const i = idx * 4;
data[i] = c; // R
data[i + 1] = c; // G
data[i + 2] = c; // B
data[i + 3] = 255; // Alpha
}
}
ctx.putImageData(imageData, 0, 0);
}
// Animation loop
function animate() {
for (let i = 0; i < 4; i++) {
simulate();
}
render();
requestAnimationFrame(animate);
}
// Start animation
animate();
</script>
</body>
</html>