Files
Atomizer/tests/unit/test_neural_surrogate.py
Anto01 7bdb74f93b refactor: Reorganize code structure and create tests directory
- Consolidate surrogates module to processors/surrogates/
- Move ensemble_surrogate.py to proper location
- Add deprecation shim for old import path
- Create tests/ directory with pytest structure
- Move test files from archive/test_scripts/
- Add conftest.py with shared fixtures

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-07 09:01:37 -05:00

59 lines
1.7 KiB
Python

"""Test neural surrogate integration."""
import time
from optimization_engine.processors.surrogates.neural_surrogate import create_surrogate_for_study
print("Testing Neural Surrogate Integration")
print("=" * 60)
# Create surrogate with auto-detection
surrogate = create_surrogate_for_study()
if surrogate is None:
print("ERROR: Failed to create surrogate")
exit(1)
print(f"Surrogate created successfully!")
print(f" Device: {surrogate.device}")
print(f" Nodes: {surrogate.num_nodes}")
print(f" Model val_loss: {surrogate.best_val_loss:.4f}")
# Test prediction
test_params = {
"beam_half_core_thickness": 7.0,
"beam_face_thickness": 3.0,
"holes_diameter": 40.0,
"hole_count": 10.0
}
print(f"\nTest prediction with params: {test_params}")
results = surrogate.predict(test_params)
print(f"\nResults:")
print(f" Max displacement: {results['max_displacement']:.6f} mm")
print(f" Max stress: {results['max_stress']:.2f} (approx)")
print(f" Inference time: {results['inference_time_ms']:.2f} ms")
# Speed test
n = 100
start = time.time()
for _ in range(n):
surrogate.predict(test_params)
elapsed = time.time() - start
print(f"\nSpeed test: {n} predictions in {elapsed:.3f}s")
print(f" Average: {elapsed/n*1000:.2f} ms per prediction")
# Compare with FEA expectation
# From training data, typical max_displacement is ~0.02-0.03 mm
print(f"\nExpected range (from training data):")
print(f" Max displacement: ~0.02-0.03 mm")
print(f" Max stress: ~200-300 MPa")
stats = surrogate.get_statistics()
print(f"\nStatistics:")
print(f" Total predictions: {stats['total_predictions']}")
print(f" Average time: {stats['average_time_ms']:.2f} ms")
print("\nNeural surrogate test PASSED!")