602560c46a
Neural Acceleration (MLP Surrogate): - Add run_nn_optimization.py with hybrid FEA/NN workflow - MLP architecture: 4-layer (64->128->128->64) with BatchNorm/Dropout - Three workflow modes: - --all: Sequential export->train->optimize->validate - --hybrid-loop: Iterative Train->NN->Validate->Retrain cycle - --turbo: Aggressive single-best validation (RECOMMENDED) - Turbo mode: 5000 NN trials + 50 FEA validations in ~12 minutes - Separate nn_study.db to avoid overloading dashboard Performance Results (bracket_pareto_3obj study): - NN prediction errors: mass 1-5%, stress 1-4%, stiffness 5-15% - Found minimum mass designs at boundary (angle~30deg, thick~30mm) - 100x speedup vs pure FEA exploration Protocol Operating System: - Add .claude/skills/ with Bootstrap, Cheatsheet, Context Loader - Add docs/protocols/ with operations (OP_01-06) and system (SYS_10-14) - Update SYS_14_NEURAL_ACCELERATION.md with MLP Turbo Mode docs NX Automation: - Add optimization_engine/hooks/ for NX CAD/CAE automation - Add study_wizard.py for guided study creation - Fix FEM mesh update: load idealized part before UpdateFemodel() New Study: - bracket_pareto_3obj: 3-objective Pareto (mass, stress, stiffness) - 167 FEA trials + 5000 NN trials completed - Demonstrates full hybrid workflow 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
122 lines
3.7 KiB
Python
122 lines
3.7 KiB
Python
"""Test model introspection module."""
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import json
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import glob
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from pathlib import Path
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# Add project root to path
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import sys
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sys.path.insert(0, str(Path(__file__).parent.parent.parent))
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from optimization_engine.hooks.nx_cad.model_introspection import (
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introspect_op2,
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introspect_study,
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)
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def test_op2_introspection():
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"""Test OP2 introspection on bracket study."""
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print("=" * 60)
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print("OP2 INTROSPECTION TEST")
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print("=" * 60)
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# Find bracket OP2 files
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op2_files = glob.glob(
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"C:/Users/Antoine/Atomizer/studies/bracket_stiffness_optimization_V3/**/*.op2",
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recursive=True
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)
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print(f"\nFound {len(op2_files)} OP2 files")
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for f in op2_files[:5]:
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print(f" - {Path(f).name}")
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if not op2_files:
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print("No OP2 files found!")
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return
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# Introspect first OP2
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print(f"\nIntrospecting: {Path(op2_files[0]).name}")
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result = introspect_op2(op2_files[0])
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if not result["success"]:
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print(f"ERROR: {result['error']}")
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return
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data = result["data"]
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# Print results
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print(f"\nFile Info:")
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print(f" Size: {data['file_info']['size_mb']:.2f} MB")
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print(f" Subcases: {data['subcases']}")
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print(f"\nAvailable Results:")
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for r_type, info in data["results"].items():
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status = "YES" if info["available"] else "no"
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extra = ""
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if info["available"]:
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if "element_types" in info and info["element_types"]:
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extra = f" ({', '.join(info['element_types'][:3])})"
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elif "subcases" in info and info["subcases"]:
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extra = f" (subcases: {info['subcases'][:3]})"
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print(f" {r_type:20s}: {status:4s} {extra}")
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print(f"\nMesh Info:")
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print(f" Nodes: {data['mesh']['node_count']}")
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print(f" Elements: {data['mesh']['element_count']}")
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if data['mesh']['element_types']:
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print(f" Element types: {list(data['mesh']['element_types'].keys())[:5]}")
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print(f"\nExtractable results: {data['extractable']}")
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def test_study_introspection():
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"""Test study directory introspection."""
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print("\n" + "=" * 60)
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print("STUDY INTROSPECTION TEST")
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print("=" * 60)
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study_dir = "C:/Users/Antoine/Atomizer/studies/bracket_stiffness_optimization_V3"
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print(f"\nIntrospecting study: {study_dir}")
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result = introspect_study(study_dir)
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if not result["success"]:
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print(f"ERROR: {result['error']}")
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return
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data = result["data"]
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print(f"\nStudy Summary:")
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print(f" Parts (.prt): {data['summary']['part_count']}")
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print(f" Simulations (.sim): {data['summary']['simulation_count']}")
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print(f" Results (.op2): {data['summary']['results_count']}")
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print(f" Has config: {data['summary']['has_config']}")
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print(f"\nParts found:")
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for p in data["parts"][:5]:
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print(f" - {Path(p['path']).name}")
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print(f"\nSimulations found:")
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for s in data["simulations"][:5]:
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print(f" - {Path(s['path']).name}")
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if data["config"]:
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print(f"\nOptimization Config:")
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config = data["config"]
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if "variables" in config:
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print(f" Variables: {len(config['variables'])}")
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for v in config["variables"][:3]:
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print(f" - {v.get('name', 'unnamed')}: [{v.get('lower')}, {v.get('upper')}]")
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if "objectives" in config:
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print(f" Objectives: {len(config['objectives'])}")
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for o in config["objectives"][:3]:
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print(f" - {o.get('name', 'unnamed')} ({o.get('direction', 'minimize')})")
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if __name__ == "__main__":
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test_op2_introspection()
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test_study_introspection()
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print("\n" + "=" * 60)
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print("INTROSPECTION TESTS COMPLETE")
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print("=" * 60)
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