lya_2pt

lya_2pt computes three-dimensional correlation functions from the Lyman-alpha forest and associated tracers. It currently supports auto-correlation functions and their distortion matrices.

Install

Python 3.10 or later and an MPI implementation are required. Install MPICH or Open MPI using your platform package manager, then install the package:

python -m pip install --upgrade pip
python -m pip install .

On NERSC, build mpi4py against the system MPI before installing the package:

MPICC="cc -shared" python -m pip install --force-reinstall --no-cache-dir --no-binary=mpi4py mpi4py
python -m pip install .

For development, clone the repository and install the developer tools:

git clone https://github.com/igmhub/lya_2pt.git
cd lya_2pt
python -m pip install -e '.[dev]'
pre-commit install

Run

Run the configuration-driven workflow with an INI file:

lya-2pt -i path/to/config.ini

The repository includes an annotated example at examples/lyaxlya_cf.ini. Other entry points are lya-2pt-cf, lya-2pt-dmat, lya-2pt-export, and lya-2pt-mpi; use <command> --help for their options. MPI jobs are normally launched through the local scheduler, for example srun lya-2pt-mpi -i path/to/config.ini.

Development

Run the local checks before opening a pull request:

ruff format --check .
ruff check .
pytest

See the documentation for configuration and API guidance, and CONTRIBUTING.md for repository workflow and release conventions.

Credits

This package is based in part on picca.