Installation Guide

To install DIRAC, you must first have PyTorch and PyTorch Geometric (PyG) installed.

Step 1: Set Up Conda Environment

Start by setting up a conda environment. Run the following command:

conda create -n dirac-env python=3.9 r-base=4.3.1 rpy2 r-mclust r-yarrr

Note

Any R version >= 4.1 works. We use r-base=4.3.1 in the example above.

Step 2: Install PyTorch and PyG

Activate the environment and install PyTorch and PyG. Make sure to adjust the installation commands based on your CUDA version, or choose the CPU-only version if necessary.

Warning

The commands below are examples based on PyTorch 2.1.0. You must choose the appropriate PyTorch build (CUDA or CPU) according to your own server hardware and driver setup.

We recommend first selecting and installing PyTorch by following the official instructions at PyTorch Get Started, and then installing the matching PyG wheels.

The suffix in pyg_lib (e.g. +pt21cu118, +pt21cu121, +pt21cpu) must match the PyTorch build you install; otherwise you may encounter “No matching distribution found” errors.

• General Installation Command:

conda activate dirac-env
pip install torch==2.1.0 torchvision==0.16.0 torchaudio==2.1.0 --index-url https://download.pytorch.org/whl/cu118
pip install pyg_lib==0.3.1+pt21cu118 torch_scatter torch_sparse torch_cluster torch_spline_conv -f https://data.pyg.org/whl/torch-2.1.0+cu118.html
pip install torch_geometric==2.3.1

• Tips for Selecting the Correct CUDA Version:

  To verify your CUDA version, you can run the following command:

  nvcc --version
  

  Alternatively, use:

  nvidia-smi
  

• Modify Installation Commands Based on CUDA Version:

  • For CUDA 12.1:

  pip install torch==2.1.0 torchvision==0.16.0 torchaudio==2.1.0 --index-url https://download.pytorch.org/whl/cu121
  pip install pyg_lib==0.3.1+pt21cu121 torch_scatter torch_sparse torch_cluster torch_spline_conv -f https://data.pyg.org/whl/torch-2.1.0+cu121.html
  pip install torch_geometric==2.3.1
  

  • For CPU-only Installation:

  pip install torch==2.1.0 torchvision==0.16.0 torchaudio==2.1.0 --index-url https://download.pytorch.org/whl/cpu
  pip install pyg_lib==0.3.1+pt21cpu torch_scatter torch_sparse torch_cluster torch_spline_conv -f https://data.pyg.org/whl/torch-2.1.0+cpu.html
  pip install torch_geometric==2.3.1
  

Step 3: Install DIRAC

After installing PyTorch and PyG, install the DIRAC package by running:

pip install sodirac

Step 4: Import DIRAC in Your Jupyter Notebooks or Scripts

To use DIRAC in your code, import it as follows:

import sodirac as sd

Note

To avoid potential dependency conflicts, it is recommended to install DIRAC within a conda environment.

Now you are all set! Proceed to the tutorials for guidance on how to use the DIRAC package.