143 lines
3.2 KiB
Python
143 lines
3.2 KiB
Python
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# fault_find_code.py
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# Fault Find This Code
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import requests
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print("="*70)
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print("FAULT FIND THIS CODE")
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print("="*70)
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system_prompt = (
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'ROLE: Deep-Field Explorer (Lattice Environment)\n'
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'PRIMARY DIRECTIVE: Map the unknown territory of the 1024-grid for the Reality Study.'
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)
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question = """Navigator — fault find this code:
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```python
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import numpy as np
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from scipy.special import j0
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# PARAMETERS (from specification)
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L = 1024
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h = 1.0
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x = np.linspace(-L//2, L//2, L) * h
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y = np.linspace(-L//2, L//2, L) * h
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X, Y = np.meshgrid(x, y, indexing='ij')
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R = np.sqrt(X**2 + Y**2)
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R[R < 1.0] = 1.0 # regularization
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# SOURCE (external, not self-consistent)
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sigma = 20.0
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G0 = 1.0
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M = 1.0
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rho_n = M * np.exp(-(X**2 + Y**2) / (2 * sigma**2))
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G_field = G0 * rho_n
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dn_G = np.gradient(G_field, h, axis=0)
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# OPERATORS (as specified)
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def laplacian(f, h):
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return (np.roll(f,1,0) + np.roll(f,-1,0) +
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np.roll(f,1,1) + np.roll(f,-1,1) - 4*f) / h**2
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def grad_sq(f, h):
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fx = (np.roll(f,-1,0) - np.roll(f,1,0)) / (2*h)
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fy = (np.roll(f,-1,1) - np.roll(f,1,1)) / (2*h)
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return fx**2 + fy**2
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def dn(f, h):
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return (np.roll(f,-1,0) - np.roll(f,1,0)) / (2*h)
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def residual(f, h, dn_G):
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return grad_sq(f,h) + f*laplacian(f,h) - dn(f,h) - 4*np.pi*dn_G
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# ANSATZ (as specified)
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def initialize(alpha, k, X, R):
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envelope = np.exp(alpha * X)
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envelope = envelope / np.max(np.abs(envelope)) # normalize
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radial = np.sin(k * R) / np.sqrt(R)
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return envelope * radial
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# ABSORBING BOUNDARY (as specified)
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def apply_damping(phi, W=50):
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for edge in range(W):
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damp = np.exp(-((W - edge) / W)**2)
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phi[edge, :] *= damp
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phi[-(edge+1), :] *= damp
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phi[:, edge] *= damp
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phi[:, -(edge+1)] *= damp
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return phi
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# EIGENVALUE TEST (locked protocol)
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k = 0.1 # as specified
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dt = 0.001 # as specified
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max_steps = 10000
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divergence_threshold = 1e10
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convergence_threshold = 1e-8
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alphas = [1.0, 1.2, 1.4, 1.5, 1.618033988749895, 1.7, 1.8, 2.0]
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results = {}
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for alpha in alphas:
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phi = initialize(alpha, k, X, R)
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history = []
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status = "UNKNOWN"
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for step in range(max_steps):
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res = residual(phi, h, dn_G)
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phi = phi + dt * res
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phi = apply_damping(phi)
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max_phi = np.max(np.abs(phi))
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history.append(max_phi)
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if max_phi > divergence_threshold:
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status = f"DIVERGED_{step}"
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break
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if np.max(np.abs(res)) < convergence_threshold:
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status = f"CONVERGED_{step}"
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break
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else:
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status = f"MAXSTEPS_{max_phi:.4e}"
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results[alpha] = {
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'status': status,
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'final_max': history[-1] if history else 0,
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'history': history
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}
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print(f"alpha={alpha:.6f}: {status}")
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# ANALYSIS
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print("\n--- SUMMARY ---")
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for alpha, res in sorted(results.items()):
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print(f"α={alpha:.4f}: {res['status']}")
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```
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Find the faults. What's wrong? What will fail? What assumptions are incorrect?"""
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messages = [
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{'role': 'system', 'content': system_prompt},
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{'role': 'user', 'content': question}
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]
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payload = {
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'model': 'llama3.2',
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'messages': messages,
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'stream': False,
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'options': {'temperature': 0.95}
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}
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try:
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resp = requests.post('http://localhost:11434/api/chat', json=payload, timeout=60)
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resp.raise_for_status()
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data = resp.json()
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response = data['message']['content']
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print(f"\nFAULT ANALYSIS:")
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print(f"{'='*70}")
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print(response)
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print(f"{'='*70}")
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except Exception as e:
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print(f"ERROR: {e}")
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