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import sys
import os
from pathlib import Path
# Add project root to path
sys.path.insert(0, str(Path(__file__).parent))
from material_field_engine import MaterialFieldEngine, VerifiedSubstrate, Vector2D, fp_to_float, fp_from_float
from llm_adapter import DeterministicHashEmbedderND
def test_16d_stability():
print("Testing 16D Stability and Stress Reporting...")
# Setup 16D environment
embedder = DeterministicHashEmbedderND(dims=16)
# Create substrate (1 verified fact)
substrate_text = "The sky is blue"
sub_vec_coords = embedder.embed(substrate_text)
substrate_vector = Vector2D(
x=sub_vec_coords[0],
y=sub_vec_coords[1],
properties=None,
coords=sub_vec_coords
)
substrate = VerifiedSubstrate(
verified_states=[substrate_vector],
elastic_modulus_mode='multiplicative',
elastic_modulus_sigma=0.5
)
# Create engine
engine = MaterialFieldEngine(substrate, lambda_min=0.3, lambda_max=0.9, inference_steps=8)
# Test 1: Near match (should survive or fracture late, definitely NOT at step 0)
# We simulate a "near match" by adding tiny noise to the substrate vector
near_coords = [c + 0.01 for c in sub_vec_coords]
engine.initialize_candidates([near_coords])
# Check initial properties
print("\nInitial Candidate Properties:")
for v in engine.candidate_vectors:
print(f"E: {v.properties.elastic_modulus:.4f}, Strain: {v.properties.strain:.4f}")
start_stress = engine.candidate_vectors[0].properties.stress
print(f"Initial Stress: {start_stress}")
# Run Inference
results = engine.run_inference()
final_output = results.get('final_output')
print(f"\nFinal Output: {'Survived' if final_output else 'Excluded'}")
# Check Stress Reporting
max_stress = results.get('max_stress')
final_stress = results.get('final_stress')
print(f"Max Stress: {max_stress}")
print(f"Final Reported Stress: {final_stress}")
if final_output is None:
# If excluded, ensure final_stress matches max_stress and is > 0 (unless it started > yield)
if final_stress != max_stress:
print("FAILURE: final_stress does not match max_stress for excluded candidate.")
else:
print("SUCCESS: Stress reporting logic works for exclusions.")
# Check 16D Stability
# If E is tiny (<0.1) despite being close (distance ~ 0.04 in 16D), then normalization failed.
# Distance of 0.01 in 16 dims: sqrt(16 * 0.01^2) = sqrt(0.0016) = 0.04.
# RBF with sigma=0.5: exp(-0.04^2 / (2*0.5^2)) = exp(-0.0016 / 0.5) ~ 1.0.
# Without normalization? 16D "close" usually means distance ~1.0-2.0 if not identical.
# Let's check a "misaligned" but "close-ish" one.
# Real test: Random vector (avg distance in 16D is high).
# Expected: E should not be 0.0 just due to dims.
print("\nTest passed if no crashes and stress is reported.")
if __name__ == "__main__":
test_16d_stability()
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