Installation

Dependencies

Hardware

While it is in principle possible to run BayesEoR on CPUs, we strongly suggest using GPUs due to their increased speed and precision relative to CPU-based methods.

Software

BayesEoR is written primarily in python. It also uses a small wrapper to interface with the Matrix Algebra on GPU and Multicore Architectures (MAGMA) library written in C. As currently implemented, the following software dependencies must be installed to run BayesEoR on GPUs:

• MAGMA

• CUDA

• MPI

• MultiNest

On CPUs, the linear algebra functionality is implemented via scipy and thus MAGMA and CUDA are not required. However, as mentioned above, we recommend running BayesEoR on GPUs due to their speed and precision.

All of the required dependencies can be installed via mamba (recommended, more info here) or conda using the provided environment.yaml file:

name: bayeseor
channels:
  - conda-forge
dependencies:
  - astropy
  - astropy-healpix
  - cuda
  - gcc_linux-64
  - h5py
  - jsonargparse
  - magma
  - matplotlib
  - mpi4py>=3.0.0
  - numpy
  - pip
  - pycuda
  - pymultinest
  - python>=3.10
  - pyuvdata
  - rich
  - scipy
  - setuptools
  - setuptools_scm
  - sphinx
  - threadpoolctl

You can install all of these dependencies with mamba from the root directory of the BayesEoR repo via

mamba env create -f environment.yaml

If you use conda, simply replace conda with mamba in the above command.

If you wish to use an existing installation of CUDA, please comment out cuda in environment.yaml before installing the dependencies with mamba / conda. As long as a valid path to the existing CUDA binaries, e.g. /usr/local/cuda/bin, is present in your bash PATH variable, pycuda will be automatically configured to point to the existing CUDA.

If you wish to use an existing installation of MPI, please comment out mpi4py and pymultinest in environment.yaml before installing the dependencies with mamba / conda. pymultinest requires mpi4py as a dependency, so it too must be commented out. You can then install mpi4py via pip. For mpi4py, see this article to ensure mpi4py points to the desired MPI installation. Once mpi4py has been installed with pip, you can proceed with installing pymultinest via mamba / conda.

If you wish to use an existing installation of MultiNest, please comment out pymultinest in environment.yaml before installing the dependencies with mamba / conda. pymultinest can be installed with pip and forced to point to a particular installation by including the MultiNest installation in your LD_LIBRARY_PATH. See the pymultinest documentation for more details.

Installing BayesEoR

Once you have satisfied the above dependencies, you can install the BayesEoR python package (bayeseor) via pip with

pip install .

Updating BayesEoR

If you have recently pulled changes and wish to update your version of bayeseor, it is suggested that you remove the build, dist, bayeseor.egg-info, and bayeseor/_version.py files before attempting to update via

pip install .