Skip to content

Installation

The viprs software is written in C/C++ and Cython/Python3 and is designed to be fast and accurate. The software is designed to be used in a variety of computing environments, including local workstations, shared computing environments, and cloud-based computing environments. Because of the dependencies on C/C++, you need to ensure that a C/C++ Compiler (with appropriate flags) is present on your system.

Requirements

Building the viprs package requires the following dependencies:

  • python (>=3.8)
  • C/C++ Compilers
  • cython
  • numPy
  • pkg-config
  • sciPy (>=1.5.4)

To take full advantage of the parallel processing capabilities of the package, you will also need to make sure that the following packages/libraries are available:

  • OpenMP
  • BLAS

Setting up the environment with conda

If you can use Anaconda or miniconda to manage your Python environment, we recommend using them to create a new environment with the required dependencies as follows:

python_version=3.11  # Change python version here if needed
conda create --name "viprs_env" -c anaconda -c conda-forge python=$python_version compilers pkg-config openblas -y
conda activate viprs_env

Using conda to setup and manage your environment is especially recommended if you have trouble compiling the C/C++ extensions on your system.

Installation

Using pip

The package is available for easy installation via the Python Package Index (pypi) can be installed using pip:

python -m pip install viprs>=0.1

Building from source

You may also build the package from source, by cloning the repository and running the make install command:

git clone https://github.com/shz9/viprs.git
cd viprs
make install

Using a virtual environment

If you wish to use viprs on a shared computing environment or cluster, it is recommended that you install the package in a virtual environment. Here's a quick example of how to install viprs on a SLURM-based cluster:

module load python/3.11
python3 -m venv viprs_env  # Assumes venv is available
source viprs_env/bin/activate
python -m pip install --upgrade pip
python -m pip install viprs>=0.1

Using Docker containers

If you are using Docker containers, you can build a container with the viprs package and all its dependencies by downloading the relevant Dockerfile from the repository and building it as follows:

# Build the docker image:
docker build -f cli.Dockerfile -t viprs-cli .
# Run the container in interactive mode:
docker run -it viprs-cli /bin/bash
# Test that the package installed successfully:
viprs_fit -h

We plan to publish pre-built Docker images on DockerHub in the future.