Scruff AI
107 lines
3.8 KiB
Python
107 lines
3.8 KiB
Python
#!/usr/bin/env python3
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"""
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Create a 256×256 brain state with guardians for testing
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"""
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import struct
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import numpy as np
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import math
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def create_brain_state_with_guardians(output_path, nx=256, ny=256, num_guardians=12):
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"""Create a brain state with guardian density perturbations."""
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q = 9 # D2Q9
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print(f"Creating {nx}×{ny} brain state with {num_guardians} guardians")
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# Create uniform distribution (equilibrium)
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f = np.zeros((q, ny, nx), dtype=np.float32)
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# Uniform density = 1.0, zero velocity
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rho = np.ones((ny, nx), dtype=np.float32)
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ux = np.zeros((ny, nx), dtype=np.float32)
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uy = np.zeros((ny, nx), dtype=np.float32)
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# D2Q9 weights
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w = np.array([4/9, 1/9, 1/9, 1/9, 1/9, 1/36, 1/36, 1/36, 1/36], dtype=np.float32)
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ex = np.array([0, 1, 0, -1, 0, 1, -1, -1, 1], dtype=np.int32)
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ey = np.array([0, 0, 1, 0, -1, 1, 1, -1, -1], dtype=np.int32)
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# Add guardian density perturbations
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print("Adding guardians...")
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guardian_positions = []
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# Place guardians in grid pattern
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spacing = int(math.sqrt(nx * ny / num_guardians))
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for y in range(spacing//2, ny, spacing):
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for x in range(spacing//2, nx, spacing):
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if len(guardian_positions) < num_guardians:
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guardian_positions.append((x, y))
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# Add Gaussian density bump
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radius = 8 # Guardian influence radius
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strength = 0.02 # Density increase
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for dy in range(-radius, radius + 1):
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for dx in range(-radius, radius + 1):
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dist2 = dx*dx + dy*dy
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if dist2 <= radius*radius:
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xx = (x + dx) % nx
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yy = (y + dy) % ny
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# Gaussian weight
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weight = math.exp(-dist2 / (radius*radius/4))
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rho[yy, xx] += strength * weight
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print(f" Guardian at ({x}, {y})")
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# Create equilibrium distribution
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print("Creating equilibrium distribution...")
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for i in range(q):
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eu = ex[i] * ux + ey[i] * uy
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u2 = ux**2 + uy**2
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f[i] = rho * w[i] * (1 + 3*eu + 4.5*eu**2 - 1.5*u2)
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# Write to file
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print(f"Writing to {output_path}...")
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with open(output_path, 'wb') as fout:
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# Header: magic, nx, ny, q
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magic = 0x4D424C46 # 'FLBM' in ASCII
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header = struct.pack('IIII', magic, nx, ny, q)
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fout.write(header)
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# Write data (flattened)
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data = f.reshape(-1).astype(np.float32)
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fout.write(data.tobytes())
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# Statistics
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print(f"\nStatistics:")
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print(f" Grid: {nx}×{ny} = {nx*ny:,} cells")
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print(f" Data size: {nx*ny*q:,} floats = {(nx*ny*q*4)/1024/1024:.1f} MB")
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print(f" Density range: [{rho.min():.6f}, {rho.max():.6f}]")
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print(f" Mean density: {rho.mean():.6f}")
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print(f" Guardians placed: {len(guardian_positions)}")
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if rho.max() > 1.002:
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print(f" ✓ Density exceeds RHO_THRESH=1.002 (max={rho.max():.6f})")
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else:
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print(f" ⚠️ Density below RHO_THRESH (max={rho.max():.6f})")
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return True
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# Create test brain state
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if __name__ == "__main__":
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output_file = "build/f_state_with_guardians.bin"
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# Make sure build directory exists
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import os
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os.makedirs("build", exist_ok=True)
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if create_brain_state_with_guardians(output_file, nx=256, ny=256, num_guardians=12):
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print(f"\n✅ Created: {output_file}")
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print("\nTo test:")
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print("1. Copy to build/f_state_post_relax.bin")
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print("2. Run probe_256_v2.exe")
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print("3. Should see guardians form (part > 0)")
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else:
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print("❌ Failed to create brain state") |