Anto01
eabcc4c3ca
BREAKING CHANGE: Module paths have been reorganized for better maintainability. Backwards compatibility aliases with deprecation warnings are provided. New Structure: - core/ - Optimization runners (runner, intelligent_optimizer, etc.) - processors/ - Data processing - surrogates/ - Neural network surrogates - nx/ - NX/Nastran integration (solver, updater, session_manager) - study/ - Study management (creator, wizard, state, reset) - reporting/ - Reports and analysis (visualizer, report_generator) - config/ - Configuration management (manager, builder) - utils/ - Utilities (logger, auto_doc, etc.) - future/ - Research/experimental code Migration: - ~200 import changes across 125 files - All __init__.py files use lazy loading to avoid circular imports - Backwards compatibility layer supports old import paths with warnings - All existing functionality preserved To migrate existing code: OLD: from optimization_engine.nx_solver import NXSolver NEW: from optimization_engine.nx.solver import NXSolver OLD: from optimization_engine.runner import OptimizationRunner NEW: from optimization_engine.core.runner import OptimizationRunner 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
70 lines
1.9 KiB
Python
70 lines
1.9 KiB
Python
"""
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Generate history.json from trial directories.
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For older substudies that don't have history.json,
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reconstruct it from individual trial results.json files.
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"""
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from pathlib import Path
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import json
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import sys
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def generate_history(substudy_dir: Path) -> list:
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"""Generate history from trial directories."""
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substudy_dir = Path(substudy_dir)
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trial_dirs = sorted(substudy_dir.glob('trial_*'))
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history = []
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for trial_dir in trial_dirs:
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results_file = trial_dir / 'results.json'
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if not results_file.exists():
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print(f"Warning: No results.json in {trial_dir.name}")
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continue
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with open(results_file, 'r') as f:
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trial_data = json.load(f)
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# Extract trial number from directory name
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trial_num = int(trial_dir.name.split('_')[-1])
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# Create history entry
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history_entry = {
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'trial_number': trial_num,
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'timestamp': trial_data.get('timestamp', ''),
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'design_variables': trial_data.get('design_variables', {}),
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'objectives': trial_data.get('objectives', {}),
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'constraints': trial_data.get('constraints', {}),
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'total_objective': trial_data.get('total_objective', 0.0)
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}
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history.append(history_entry)
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# Sort by trial number
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history.sort(key=lambda x: x['trial_number'])
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return history
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if __name__ == '__main__':
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if len(sys.argv) < 2:
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print("Usage: python generate_history_from_trials.py <substudy_directory>")
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sys.exit(1)
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substudy_path = Path(sys.argv[1])
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print(f"Generating history.json from trials in: {substudy_path}")
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history = generate_history(substudy_path)
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print(f"Generated {len(history)} history entries")
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# Save history.json
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history_file = substudy_path / 'history.json'
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with open(history_file, 'w') as f:
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json.dump(history, f, indent=2)
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print(f"Saved: {history_file}")
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