Anto01
2b3573ec42
Major additions: - Training data export system for AtomizerField neural network training - Bracket stiffness optimization study with 50+ training samples - Intelligent NX model discovery (auto-detect solutions, expressions, mesh) - Result extractors module for displacement, stress, frequency, mass - User-generated NX journals for advanced workflows - Archive structure for legacy scripts and test outputs - Protocol documentation and dashboard launcher 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
36 lines
1.2 KiB
Python
36 lines
1.2 KiB
Python
"""Test neural surrogate integration"""
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import sys
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from pathlib import Path
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# Add project paths
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project_root = Path(__file__).parent
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sys.path.insert(0, str(project_root))
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sys.path.insert(0, str(project_root / 'atomizer-field'))
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from optimization_engine.neural_surrogate import create_parametric_surrogate_for_study
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# Create surrogate
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print("Creating parametric surrogate...")
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surrogate = create_parametric_surrogate_for_study(project_root=project_root)
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if surrogate:
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print('Surrogate created successfully!')
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print(f'Design vars: {surrogate.design_var_names}')
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print(f'Number of nodes: {surrogate.num_nodes}')
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# Test prediction with example params
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test_params = {name: 2.0 for name in surrogate.design_var_names}
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print(f'\nTest params: {test_params}')
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results = surrogate.predict(test_params)
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print(f'\nTest prediction:')
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print(f' Mass: {results["mass"]:.2f}')
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print(f' Frequency: {results["frequency"]:.2f}')
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print(f' Max Displacement: {results["max_displacement"]:.6f}')
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print(f' Max Stress: {results["max_stress"]:.2f}')
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print(f' Inference time: {results["inference_time_ms"]:.2f} ms')
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print('\nSurrogate is ready for use in optimization!')
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else:
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print('Failed to create surrogate')
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