requirements.txt

# P-Adic VAE V7.2 - Requirements
# Python 3.10+

# Core Dependencies
torch>=2.0.0
numpy>=1.24.0
scipy>=1.10.0

# Hyperbolic Geometry
geoopt>=0.5.0  # Riemannian optimization and manifold operations

# Optional: Vectorized Scatter Ops (auto-fallback to pure torch if absent)
# torch-scatter>=2.1.2  # Uncomment for GPU-accelerated scatter_mean/scatter_std
# NOTE: Requires CUDA-specific wheel: pip install torch-scatter -f https://data.pyg.org/whl/torch-2.X.X+cuXXX.html

# Configuration
pyyaml>=6.0
yamllint>=1.33.0  # YAML linting
pydantic>=2.0    # Schema validation for YAML configs

# Machine Learning (used in training loop for live ARI computation)
scikit-learn>=1.3.0  # KMeans, adjusted_rand_score

# Training Visualization (REQUIRED — without this, all TensorBoard logging is silently skipped)
tensorboard>=2.13.0

# Progress Bars
tqdm>=4.65.0

# Visualization (used by diagnose_direction_geometry.py and VisualizationPipeline)
matplotlib>=3.7.0
umap-learn>=0.5.0  # UMAP; metric='precomputed' for Poincaré distance matrix input
pacmap>=0.7.0      # PaCMAP; pair_neighbors injected from hyperbolic kNN
trimap>=1.1.0      # TriMAP; use_dist_matrix=True for Poincaré distance matrix input
ripser>=0.6.0      # Vietoris-Rips persistent homology on hyperbolic distance matrix
persim>=0.3.0      # Persistence diagram utilities (plot_diagrams, persistent_entropy)
plotly>=5.0.0      # Interactive HTML outputs (poincare_3d.html, umap_3d.html, etc.)
pillow>=10.0.0     # Image backend for matplotlib

# Data Analysis
pandas>=2.0.0

# Phylogeny validation pipeline (docs/plans/PHYLOGENY-VALIDATION-PIPELINE.md):
# UniProt/NCBI REST API calls in scripts/data/fetch_cytochrome_c.py, fetch_taxonomy.py
requests>=2.28.0
biopython>=1.80  # Bio.Align.PairwiseAligner in scripts/data/align_cytochrome_c.py

# Testing
pytest>=7.3.0
pytest-cov>=4.1.0