requirements.txt

# Core
numpy<2          # TF 2.x / scipy / pandas wheels are built against the NumPy 1.x ABI; numpy 2.x crashes them
pandas
matplotlib
scipy
scikit-learn
rdata

# Deep learning (MRI CNN)
torch
torchvision
captum

# MRI / neuroimaging preprocessing
antspyx
nibabel
SimpleITK   # sorted DICOM series read (ImageSeriesReader) — ants.dicom_read does not sort by ImagePositionPatient
pydicom     # raw DICOM header inspection
deepbrain @ git+https://github.com/lucasthim/deepbrain.git   # TF1.x->compat.v1 patch for TF2; needs TensorFlow
tensorflow ; sys_platform != 'linux'              # macOS/other: plain wheel
tensorflow[and-cuda] ; sys_platform == 'linux'    # Linux GPU box (RTX 4090): bundles CUDA/cuDNN userspace libs for GPU
# Linux GPU: after install, run `bash scripts/setup_gpu_linux.sh`. The venv gets both cu12
# and cu13 NVIDIA wheels, and TF 2.21 needs cu12 libcusolver.so.11 preloaded or it runs on
# CPU. The script installs that preload and verifies the GPU. Not needed on macOS.

# Tabular modeling + ensemble explainability
pycaret==3.3.2   # 3.3.2 pins sklearn<1.5 (needs _print_elapsed_time); 2.x/3.3.0 break on modern sklearn
interpret        # Explainable Boosting Machine (EBM); resolves to 0.7.3 under sklearn 1.4.2

# --- dev/test ---
pytest