# Atomizer Conda Environment # =========================== # # Complete environment for Atomizer FEA optimization framework # Includes: Core optimization, NX/Nastran integration, Neural surrogates (AtomizerField) # # Installation: # conda env create -f environment.yml # conda activate atomizer # # Update existing environment: # conda env update -f environment.yml --prune name: atomizer channels: - pytorch - nvidia - pyg - conda-forge - defaults dependencies: # Python version (compatible with NX 2412) - python=3.11 # ============================================================================ # Core Scientific Computing # ============================================================================ # numpy<2 required for pyNastran compatibility - numpy>=1.24.0,<2.0.0 - scipy>=1.10.0 - pandas>=2.0.0 - scikit-learn>=1.3.0 # ============================================================================ # Optimization Framework # ============================================================================ - optuna>=3.5.0 - plotly>=5.18.0 - matplotlib>=3.5.0 # ============================================================================ # FEA/Nastran Parsing # ============================================================================ - h5py>=3.0.0 # ============================================================================ # Neural Network / AtomizerField # ============================================================================ # PyTorch with CUDA support - pytorch>=2.0.0 - pytorch-cuda=12.1 # PyTorch Geometric for Graph Neural Networks - pyg>=2.3.0 # TensorBoard for training visualization - tensorboard>=2.13.0 # ============================================================================ # Web Framework (Dashboard/API) # ============================================================================ - fastapi>=0.109.0 - uvicorn>=0.27.0 - websockets>=12.0 - pydantic>=2.5.0 - jinja2>=3.1.3 # ============================================================================ # System Utilities # ============================================================================ - psutil>=5.9.0 - tqdm>=4.65.0 # ============================================================================ # Development Tools # ============================================================================ - pytest>=7.4.0 - pytest-cov>=4.1.0 # ============================================================================ # pip-only packages (not available in conda) # ============================================================================ - pip - pip: # Nastran file parser (numpy<2 constraint is handled above) - pyNastran>=1.4.0,<1.5.0 # Python-multipart for FastAPI file uploads - python-multipart>=0.0.6 # ============================================================================ # Post-installation notes: # ============================================================================ # # 1. Verify installation: # python -c "import optuna; import pyNastran; import torch; print('All imports OK')" # # 2. Check GPU: # python -c "import torch; print(f'CUDA: {torch.cuda.is_available()}')" # # 3. For NX integration, ensure NX Python stubs are accessible: # See config.py for NX_PYTHON_STUBS path