bilby 0.0.0

A user-friendly Bayesian inference library

Bilby

A user-friendly Bayesian inference library. Fulfilling all your Bayesian dreams.

Online material to help you get started:

• Installation instructions

• Documentation

If you need help, find an issue, or just have a question/suggestion you can

• Join our Slack workspace (you may need to email the support desk to request an invite)

• Email our support desk: [e-mail]

• Ask questions (or search through other users questions and answers) on StackOverflow using the bilby tag

• For www.git.ligo.org users, submit issues directly through the issue tracker

• For www.chat.ligo.org users, join the #bilby-help or #bilby-devel channels

We encourage you to contribute to the development of bilby. This is done via a merge request. For help in creating a merge request, see this page or contact us directly. For advice on contributing, see the contributing guide.

Citation guide

If you use bilby in a scientific publication, please cite

• Bilby: A user-friendly Bayesian inference library for gravitational-wave astronomy

• Bayesian inference for compact binary coalescences with BILBY: validation and application to the first LIGO-Virgo gravitational-wave transient catalogue

The first of these papers introduces the software, while the second introduces advances in the sampling approaches and validation of the software. If you use the bilby_mcmc sampler, please additionally cite

• BILBY-MCMC: an MCMC sampler for gravitational-wave inference

Additionally, bilby builds on a number of open-source packages. If you make use of this functionality in your publications, we recommend you cite them as requested in their associated documentation.

Samplers

• dynesty

• nestle

• pymultinest

• cpnest

• emcee

• ptemcee

• ptmcmcsampler

• pypolychord

• PyMC3

Gravitational-wave tools

• gwpy

• lalsuite

• astropy

Plotting

• corner for generating corner plot

• matplotlib for general plotting routines