<h1 align="center">
<img src="https://raw.githubusercontent.com/ColmTalbot/gwpopulation/main/docs/_static/logo-long.svg">
</h1>
------------------------------------------------------------------------------
[](https://github.com/ColmTalbot/gwpopulation/actions/workflows/python-package.yml)
[](https://codecov.io/gh/ColmTalbot/gwpopulation)
[](https://pypi.org/project/gwpopulation/)
Flexible, extensible, hardware-agnostic gravitational-wave population inference.
- [Documentation](https://ColmTalbot.github.io/gwpopulation)
- [Source Repository](https://github.com/ColmTalbot/GWPopulation)
- [Issues](https://github.com/ColmTalbot/GWPopulation/issues)
- [Contributing](https://colmtalbot.github.io/gwpopulation/contributing/index.html)
It provides:
- Simple use of GPU-acceleration via [JAX](https://jax.readthedocs.io/en/latest/) and [cupy](https://cupy.dev/).
- Implementations of widely used likelihood compatible with [Bilby](https://docs.ligo.org/lscsoft/bilby).
- A standard format for defining new population models.
- A collection of standard population models.
If you're using this on high-performance computing clusters, you may be interested in the associated pipeline code [gwpopulation_pipe](https://docs.ligo.org/RatesAndPopulations/gwpopulation_pipe/).
#### Attribution
------------------------------------------------------------------------------
Please cite [Talbot _et al._ (2019)](https://doi.org/10.1103/PhysRevD.100.043030) if you use `GWPopulation` in your research.
```bibtex
@ARTICLE{2019PhRvD.100d3030T,
author = {{Talbot}, Colm and {Smith}, Rory and {Thrane}, Eric and {Poole}, Gregory B.},
title = "{Parallelized inference for gravitational-wave astronomy}",
journal = {\prd},
year = 2019,
month = aug,
volume = {100},
number = {4},
eid = {043030},
pages = {043030},
doi = {10.1103/PhysRevD.100.043030},
archivePrefix = {arXiv},
eprint = {1904.02863},
primaryClass = {astro-ph.IM},
}
```
Additionally, please consider citing the original references for the implemented models which should be include in docstrings.
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