Anto01
38abb0d8d2
Phase 3 implements automated OP2 extraction code generation using pyNastran documentation research. This completes the zero-manual-coding pipeline for FEA optimization workflows. Key Features: - PyNastranResearchAgent for automated OP2 code generation - Documentation research via WebFetch integration - 3 core extraction patterns (displacement, stress, force) - Knowledge base architecture for learned patterns - Successfully tested on real OP2 files Phase 2.9 Integration: - Updated HookGenerator with lifecycle hook generation - Added POST_CALCULATION hook point to hooks.py - Created post_calculation/ plugin directory - Generated hooks integrate seamlessly with HookManager New Files: - optimization_engine/pynastran_research_agent.py (600+ lines) - optimization_engine/hook_generator.py (800+ lines) - optimization_engine/inline_code_generator.py - optimization_engine/plugins/post_calculation/ - tests/test_lifecycle_hook_integration.py - docs/SESSION_SUMMARY_PHASE_3.md - docs/SESSION_SUMMARY_PHASE_2_9.md - docs/SESSION_SUMMARY_PHASE_2_8.md - docs/HOOK_ARCHITECTURE.md Modified Files: - README.md - Added Phase 3 completion status - optimization_engine/plugins/hooks.py - Added POST_CALCULATION hook Test Results: - Phase 3 research agent: PASSED - Real OP2 extraction: PASSED (max_disp=0.362mm) - Lifecycle hook integration: PASSED Generated with Claude Code Co-Authored-By: Claude <noreply@anthropic.com>
76 lines
1.6 KiB
Python
76 lines
1.6 KiB
Python
"""
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Comparison Hook
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Auto-generated by Atomizer Phase 2.9
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Compare min force to average
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Operation: ratio
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Formula: min_to_avg_ratio = min_force / avg_force
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"""
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import sys
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import json
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from pathlib import Path
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def compare_ratio(min_force, avg_force):
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"""
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Compare values using ratio.
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Args:
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min_force: float
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avg_force: float
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Returns:
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float: Comparison result
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"""
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result = min_force / avg_force
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return result
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def main():
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"""Main entry point for hook execution."""
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if len(sys.argv) < 2:
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print("Usage: python {} <input_file.json>".format(sys.argv[0]))
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sys.exit(1)
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input_file = Path(sys.argv[1])
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# Read inputs
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with open(input_file, 'r') as f:
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inputs = json.load(f)
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# Extract required inputs
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min_force = inputs.get("min_force")
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if min_force is None:
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print(f"Error: Required input 'min_force' not found")
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sys.exit(1)
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avg_force = inputs.get("avg_force")
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if avg_force is None:
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print(f"Error: Required input 'avg_force' not found")
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sys.exit(1)
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# Calculate comparison
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result = compare_ratio(min_force, avg_force)
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# Write output
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output_file = input_file.parent / "min_to_avg_ratio.json"
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output = {
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"min_to_avg_ratio": result,
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"operation": "ratio",
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"formula": "min_force / avg_force",
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"inputs_used": {"min_force": min_force, "avg_force": avg_force}
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}
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with open(output_file, 'w') as f:
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json.dump(output, f, indent=2)
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print(f"min_to_avg_ratio = {result:.6f}")
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print(f"Result saved to: {output_file}")
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return result
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if __name__ == '__main__':
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main()
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