d5ffba099e
Permanently integrates the Atomizer-Field GNN surrogate system: - neural_models/: Graph Neural Network for FEA field prediction - batch_parser.py: Parse training data from FEA exports - train.py: Neural network training pipeline - predict.py: Inference engine for fast predictions This enables 600x-2200x speedup over traditional FEA by replacing expensive simulations with millisecond neural network predictions. 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
57 lines
464 B
Plaintext
57 lines
464 B
Plaintext
# Python
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__pycache__/
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*.py[cod]
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*$py.class
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*.so
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.Python
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env/
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venv/
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ENV/
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*.egg-info/
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dist/
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build/
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# Jupyter Notebooks
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.ipynb_checkpoints/
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*.ipynb
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# IDEs
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.vscode/
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.idea/
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*.swp
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*.swo
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*~
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# OS
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.DS_Store
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Thumbs.db
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# Data files (large)
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*.op2
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*.bdf
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*.dat
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*.f06
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*.pch
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*.h5
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*.hdf5
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# Training data
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training_data/
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checkpoints/
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runs/
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logs/
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# Test outputs
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test_case_*/
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visualization_images/
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# Temporary files
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*.tmp
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*.log
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*.bak
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*.orig
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# Environment
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atomizer_env/
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.conda/
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