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eabcc4c3ca
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refactor: Major reorganization of optimization_engine module structure
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>
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2025-12-29 12:30:59 -05:00 |
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a0c008a593
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feat: Add neural loop automation - templates, auto-trainer, CLI
Closes the neural training loop with automated workflow:
- atomizer.py: One-command neural workflow CLI
- auto_trainer.py: Auto-training trigger system (50pt threshold)
- template_loader.py: Study creation from templates
- study_reset.py: Study reset/cleanup utility
- 3 templates: beam stiffness, bracket stress, frequency tuning
- State assessment document (Nov 25)
Usage: python atomizer.py neural-optimize --study my_study --trials 500
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
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2025-11-26 07:53:00 -05:00 |
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