Atomizer/environment.yml

# 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