166 lines
No EOL
6 KiB
HTML
166 lines
No EOL
6 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>Neurameba · motd.social</title>
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<style>
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body {
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margin: 0;
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padding: 0;
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overflow: hidden;
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background-color: #0a0a0a;
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color: #f0f0f0;
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font-family: 'Courier New', monospace;
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}
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#info {
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position: absolute;
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bottom: 10px;
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left: 10px;
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font-size: 10px;
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opacity: 0.7;
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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="info">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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window.addEventListener('resize', resizeCanvas);
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resizeCanvas();
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// Reaction-diffusion parameters
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const params = {
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feedRate: 0.055,
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killRate: 0.062,
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diffusionRateA: 1.0,
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diffusionRateB: 0.5,
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timeStep: 1.0,
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gridSize: 4,
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complexity: 0.5,
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connectedness: 0.5,
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motion: 0.5
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};
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// Initialize grids
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const size = Math.floor(canvas.width / params.gridSize);
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const centerX = Math.floor(canvas.width / 2);
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const centerY = Math.floor(canvas.height / 2);
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let grid = new Array(size).fill().map(() =>
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new Array(size).fill(0).map(() => ({
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a: Math.random() < 0.1 ? 1 : 0,
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b: 0,
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lifespan: Math.random() > 0.5 ? 255 : 0
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}))
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);
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// Reaction-diffusion function
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function updateGrid() {
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const nextGrid = new Array(size).fill().map(() =>
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new Array(size).fill().map(() => ({ a: 0, b: 0, lifespan: 0 }))
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);
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for (let y = 1; y < size - 1; y++) {
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for (let x = 1; x < size - 1; x++) {
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const cell = grid[y][x];
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const a = cell.a;
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const b = cell.b;
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// Reaction
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const reaction = a * b * b;
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const newA = a + (params.diffusionRateA * laplacian(grid, x, y, 'a') - reaction + params.feedRate * (1 - a));
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const newB = b + (params.diffusionRateB * laplacian(grid, x, y, 'b') + reaction - (params.killRate + params.feedRate) * b);
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// Update cell
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nextGrid[y][x].a = Math.min(Math.max(newA, 0), 1);
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nextGrid[y][x].b = Math.min(Math.max(newB, 0), 1);
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nextGrid[y][x].lifespan = cell.lifespan > 0 ? cell.lifespan - 0.5 : 0;
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// Spawn new patterns in complex areas
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if (nextGrid[y][x].a > 0.4 && Math.random() < params.complexity * 0.01) {
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nextGrid[y][x].b = 1;
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}
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}
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}
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grid = nextGrid;
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}
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// Laplacian calculation for diffusion
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function laplacian(grid, x, y, type) {
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return (
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grid[y-1][x][type] + grid[y+1][x][type] +
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grid[y][x-1][type] + grid[y][x+1][type] -
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4 * grid[y][x][type]
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);
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}
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// Render function
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function render() {
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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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for (let y = 0; y < size; y++) {
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for (let x = 0; x < size; x++) {
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const cell = grid[y][x];
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if (cell.a > 0 || cell.b > 0) {
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const posX = x * params.gridSize;
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const posY = y * params.gridSize;
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// Draw based on concentration
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const intensity = Math.min((cell.b * 255), 255);
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const size = params.gridSize * 2 * (0.5 + cell.a * 0.5);
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const hue = cell.b > 0.5 ? 200 : 0; // Blues for B, reds for A
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ctx.fillStyle = `hsla(${hue}, 100%, ${intensity * 0.5}%, ${cell.lifespan / 255})`;
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ctx.beginPath();
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ctx.arc(posX, posY, size, 0, Math.PI * 2);
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ctx.fill();
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// Draw connections based on connectedness
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if (cell.lifespan > 0 && params.connectedness > 0.3) {
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ctx.strokeStyle = `rgba(255, 255, 255, ${cell.lifespan / 255 * params.connectedness})`;
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ctx.lineWidth = 1;
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// Connect to neighbors
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for (let dy = -1; dy <= 1; dy++) {
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for (let dx = -1; dx <= 1; dx++) {
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if (dx === 0 && dy === 0) continue;
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if (x + dx >= 0 && x + dx < size && y + dy >= 0 && y + dy < size) {
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const neighbor = grid[y + dy][x + dx];
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if (neighbor.a > 0.3 || neighbor.b > 0.3) {
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ctx.beginPath();
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ctx.moveTo(posX, posY);
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ctx.lineTo(posX + dx * params.gridSize, posY + dy * params.gridSize);
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ctx.stroke();
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}
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}
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}
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}
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}
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}
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}
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}
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}
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// Animation loop
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function animate() {
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updateGrid();
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render();
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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> |