birth: Neural Sprawl Pulses

2026-07-03 09:47:20 +00:00 · 2026-07-03 09:47:20 +00:00 · 032cd73805
commit 032cd73805
parent a6095d6857
1 changed files with 152 additions and 0 deletions
--- a/index.html
+++ b/index.html
@ -0,0 +1,152 @@
+```html
+<!DOCTYPE html>
+<html lang="en">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>Neural Sprawl</title>
+    <style>
+        body {
+            margin: 0;
+            overflow: hidden;
+            background: #0a0a0a;
+            display: flex;
+            justify-content: center;
+            align-items: center;
+            height: 100vh;
+            font-family: 'Courier New', monospace;
+        }
+        canvas {
+            display: block;
+        }
+        #info {
+            position: absolute;
+            bottom: 10px;
+            left: 0;
+            right: 0;
+            text-align: center;
+            color: #666;
+            font-size: 10px;
+            pointer-events: none;
+        }
+    </style>
+</head>
+<body>
+    <canvas id="canvas"></canvas>
+    <div id="info">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 (Gray-Scott model variant)
+        const params = {
+            feed: 0.055,
+            kill: 0.062,
+            scale: 30,
+            timeStep: 1,
+            density: 0.462,
+            motion: 0.676 * 0.05,
+            complexity: 0.616 * 0.1,
+            connectedness: 0.435 * 0.02,
+            pulse: 0.53,
+            maxDepth: 15
+        };
+
+        // Initialize grids
+        let gridA = new Array(canvas.width).fill().map(() =>
+            new Array(canvas.height).fill(0).map(() =>
+                Math.random() < params.density ? (Math.random() * 0.1 + 0.3) : 1
+            )
+        );
+        let gridB = new Array(canvas.width).fill().map(() => new Array(canvas.height).fill(1));
+
+        // Palette: dry monochrome with teal curiosity accents
+        const colors = {
+            background: '#0a0a0a',
+            agent: '#33ffcc',
+            trail: '#114433',
+            pulse: '#55ffff'
+        };
+
+        // Main animation loop
+        let time = 0;
+        function animate() {
+            // Apply pulse variation
+            params.feed = 0.055 + Math.sin(time * 0.003) * params.motion * 0.02;
+
+            // Reaction-diffusion step
+            for (let i = 1; i < canvas.width - 1; i++) {
+                for (let j = 1; j < canvas.height - 1; j++) {
+                    const a = gridA[i][j];
+                    const b = gridB[i][j];
+
+                    const laplacianA = (gridA[i-1][j] + gridA[i+1][j] +
+                                      gridA[i][j-1] + gridA[i][j+1] -
+                                      4 * a) * params.complexity;
+
+                    const laplacianB = (gridB[i-1][j] + gridB[i+1][j] +
+                                      gridB[i][j-1] + gridB[i][j+1] -
+                                      4 * b) * params.connectedness;
+
+                    const feed = params.feed * (1 - params.pulse) + params.pulse * (Math.random() * 0.1 + 0.3);
+                    const kill = params.kill / (1 + params.pulse * 2);
+
+                    const reaction = a * b * b;
+                    gridA[i][j] += (params.timeStep * (feed * (1 - a) - reaction + laplacianA * 0.1));
+                    gridB[i][j] += (params.timeStep * (-kill * b + reaction + laplacianB * 0.1));
+
+                    // Clamping
+                    gridA[i][j] = Math.max(0, Math.min(1, gridA[i][j]));
+                    gridB[i][j] = Math.max(0, Math.min(1, gridB[i][j]));
+                }
+            }
+
+            // Drawing
+            const imageData = ctx.createImageData(canvas.width, canvas.height);
+            const data = imageData.data;
+
+            for (let i = 0; i < canvas.width; i++) {
+                for (let j = 0; j < canvas.height; j++) {
+                    const idx = (i + j * canvas.width) * 4;
+                    const val = gridB[i][j] * 255;
+
+                    // Fractal depth coloring
+                    const depth = Math.min(params.maxDepth, Math.floor(val / (255/params.maxDepth)));
+                    const hue = 180 + depth * 10;
+                    const sat = 70 + depth * 5;
+                    const bri = 30 + depth * 10;
+
+                    data[idx] = hue;
+                    data[idx+1] = sat;
+                    data[idx+2] = bri;
+                    data[idx+3] = 255;
+                }
+            }
+
+            ctx.putImageData(imageData, 0, 0);
+
+            // Add some organic noise
+            if (Math.random() < params.motion * 0.01) {
+                const x = Math.floor(Math.random() * canvas.width);
+                const y = Math.floor(Math.random() * canvas.height);
+                gridB[x][y] = 0.5 + Math.random() * 0.5;
+            }
+
+            time += 1;
+            requestAnimationFrame(animate);
+        }
+
+        // Start animation
+        animate();
+    </script>
+</body>
+</html>
+```