Installation

Requirements

  • Python ≥ 3.9

  • PyTorch ≥ 1.9 (installed separately for CUDA compatibility)

Install from GitHub

We recommend a fresh conda environment:

# Create environment
conda create -n velot python=3.10 -y
conda activate velot

# Install PyTorch first (adjust for your CUDA version)
# GPU:
pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118
# CPU only:
# pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cpu

# Install VelOT
git clone https://github.com/lucas-rdlr/velot.git
cd velot
pip install -e .

Note

PyTorch is installed separately to allow users to choose the appropriate CUDA version for their system. See pytorch.org for installation options.

Verify Installation

import velot
print(velot.__version__)
# 1.0.0

Dependencies

VelOT automatically installs the following packages:

  • numpy, scipy, pandas

  • anndata, scanpy

  • scikit-learn

  • matplotlib

  • POT (Python Optimal Transport)

  • scvelo

  • tqdm