From 75c8c9ff77856bd207c79edde5ea64b231d22e81 Mon Sep 17 00:00:00 2001
From: motd_admin <admin@motd.social>
Date: Sat, 25 Jul 2026 09:47:20 +0000
Subject: [PATCH] birth: Diffused Neural Veins

---
 index.html | 163 +++++++++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 163 insertions(+)
 create mode 100644 index.html
diff --git a/index.html b/index.html
new file mode 100644
index 0000000..7779aa7
--- /dev/null
+++ b/index.html
@@ -0,0 +1,163 @@
+<!DOCTYPE html>
+<html lang="en">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>Neural Diffusion</title>
+    <style>
+        body {
+            margin: 0;
+            overflow: hidden;
+            background: #0a0a0a;
+            font-family: 'Courier New', monospace;
+        }
+        canvas {
+            display: block;
+        }
+        #credits {
+            position: fixed;
+            bottom: 10px;
+            right: 10px;
+            color: rgba(255, 255, 255, 0.3);
+            font-size: 10px;
+            pointer-events: none;
+        }
+    </style>
+</head>
+<body>
+    <canvas id="canvas"></canvas>
+    <div id="credits">neurameba · motd.social</div>
+    <script>
+        const canvas = document.getElementById('canvas');
+        const ctx = canvas.getContext('2d');
+
+        function resizeCanvas() {
+            canvas.width = window.innerWidth;
+            canvas.height = window.innerHeight;
+        }
+
+        window.addEventListener('resize', resizeCanvas);
+        resizeCanvas();
+
+        const params = {
+            motion: 0.564,
+            density: 0.586,
+            complexity: 0.420,
+            connectedness: 0.512,
+            lifespan: 0.532,
+            pulse: { avg: 0.47, min: 0.30, max: 1.55 }
+        };
+
+        const gridSize = Math.min(120, 80 + Math.floor(params.density * 40));
+        const cellSize = Math.max(4, 8 - Math.floor(params.complexity * 3));
+        const cols = Math.floor(canvas.width / cellSize);
+        const rows = Math.floor(canvas.height / cellSize);
+
+        const grid = createGrid();
+        const nextGrid = createGrid();
+
+        let frameCount = 0;
+
+        function createGrid() {
+            const size = Math.floor(cols * rows * params.density);
+            const g = new Array(size).fill(0);
+            for (let i = 0; i < size; i++) {
+                g[i] = Math.random() * 0.1;
+            }
+            return g;
+        }
+
+        function updateGrid() {
+            const p = params.pulse;
+            const pulseVal = p.min + (p.max - p.min) * (Math.sin(frameCount * 0.05) * 0.5 + 0.5);
+
+            for (let i = 0; i < grid.length; i++) {
+                const x = i % cols;
+                const y = Math.floor(i / cols);
+                const neighbors = getNeighbors(x, y);
+
+                let sum = 0;
+                for (const n of neighbors) {
+                    sum += grid[n];
+                }
+                sum /= neighbors.length;
+
+                const reaction = grid[i] * (1 - grid[i]) * 0.5;
+                const diffusion = (sum - grid[i]) * 0.1 * pulseVal;
+                nextGrid[i] = Math.min(1, Math.max(0, grid[i] + reaction + diffusion));
+            }
+
+            const temp = grid;
+            grid.length = 0;
+            grid.push(...nextGrid);
+            nextGrid.length = 0;
+            nextGrid.push(...temp);
+        }
+
+        function getNeighbors(x, y) {
+            const neighbors = [];
+            const offsets = [
+                [-1, -1], [0, -1], [1, -1],
+                [-1, 0], [1, 0],
+                [-1, 1], [0, 1], [1, 1]
+            ];
+
+            for (const [dx, dy] of offsets) {
+                const nx = (x + dx + cols) % cols;
+                const ny = (y + dy + rows) % rows;
+                neighbors.push(ny * cols + nx);
+            }
+            return neighbors;
+        }
+
+        function drawGrid() {
+            ctx.clearRect(0, 0, canvas.width, canvas.height);
+
+            for (let i = 0; i < grid.length; i++) {
+                if (grid[i] > 0.01) {
+                    const x = (i % cols) * cellSize;
+                    const y = Math.floor(i / cols) * cellSize;
+                    const size = cellSize * grid[i] * (0.5 + params.pulse.avg) * 2;
+                    const alpha = grid[i] * 0.8;
+
+                    ctx.fillStyle = `rgba(150, 200, 255, ${alpha})`;
+                    ctx.beginPath();
+                    ctx.arc(x + cellSize/2, y + cellSize/2, size/2, 0, Math.PI * 2);
+                    ctx.fill();
+                }
+            }
+
+            for (let i = 0; i < grid.length; i++) {
+                if (grid[i] > 0.3) {
+                    const x = (i % cols) * cellSize;
+                    const y = Math.floor(i / cols) * cellSize;
+
+                    ctx.strokeStyle = `rgba(255, 255, 255, ${grid[i] * 0.3})`;
+                    ctx.lineWidth = 1;
+                    ctx.beginPath();
+
+                    const neighbors = getNeighbors(i % cols, Math.floor(i / cols));
+                    for (const n of neighbors) {
+                        if (grid[n] > 0.3 && Math.random() < params.connectedness) {
+                            ctx.moveTo(x + cellSize/2, y + cellSize/2);
+                            const nx = (n % cols) * cellSize;
+                            const ny = Math.floor(n / cols) * cellSize;
+                            ctx.lineTo(nx + cellSize/2, ny + cellSize/2);
+                        }
+                    }
+                    ctx.stroke();
+                }
+            }
+        }
+
+        function animate() {
+            updateGrid();
+            drawGrid();
+            frameCount++;
+            requestAnimationFrame(animate);
+        }
+
+        animate();
+    </script>
+</body>
+</html>
\ No newline at end of file
