gwpopulation_pipe provides a standardized interface to gravitational-wave popualtion inference

This is intended to be used with the command-line interface and limited support will be provided for directly calling the API.

Installation

The easiest way to install gwpopulation_pipe is via pypi

$ pip install gwpopulation_pipe

Examples

Here are a few examples of how to use the command line interface.

API:

common_format

data_analysis

Functions for running stochastic sampling with Bilby for pre-collected posteriors.

data_collection

Functions for collecting input samples from a range of sources and computing the fiducial prior for the appropriate parameters.

data_simulation

Functions for generating simulated event posteriors.

main

parser

post_plots

Post-processing plotting functions.

utils

vt_helper

Citing

If this software is useful for your research, please cite

Bilby
@ARTICLE{2019ApJS..241...27A,
       author = {{Ashton}, Gregory and {H{\"u}bner}, Moritz and {Lasky}, Paul D. and {Talbot}, Colm and {Ackley}, Kendall and {Biscoveanu}, Sylvia and {Chu}, Qi and {Divakarla}, Atul and {Easter}, Paul J. and {Goncharov}, Boris and {Hernandez Vivanco}, Francisco and {Harms}, Jan and {Lower}, Marcus E. and {Meadors}, Grant D. and {Melchor}, Denyz and {Payne}, Ethan and {Pitkin}, Matthew D. and {Powell}, Jade and {Sarin}, Nikhil and {Smith}, Rory J.~E. and {Thrane}, Eric},
        title = "{BILBY: A User-friendly Bayesian Inference Library for Gravitational-wave Astronomy}",
      journal = {\apjs},
     keywords = {gravitational waves, methods: data analysis, methods: statistical, stars: black holes, stars: neutron, Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - High Energy Astrophysical Phenomena, General Relativity and Quantum Cosmology},
         year = 2019,
        month = apr,
       volume = {241},
       number = {2},
          eid = {27},
        pages = {27},
          doi = {10.3847/1538-4365/ab06fc},
archivePrefix = {arXiv},
       eprint = {1811.02042},
 primaryClass = {astro-ph.IM},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2019ApJS..241...27A},
      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
GWPopulation
@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},
     keywords = {Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - High Energy Astrophysical Phenomena, General Relativity and Quantum Cosmology},
         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},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2019PhRvD.100d3030T},
      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
GWPopulation Pipe
@ARTICLE{
    gwpop_pipe,
    title={GWPopulation pipe},
    DOI={10.5281/zenodo.5654673},
    publisher={Zenodo},
    author={Talbot, Colm},
    year={2021},
    month={Nov},
    url={https://git.ligo.org/RatesAndPopulations/gwpopulation_pipe}
}

Along with whatever paper introduced the data, models, or sampler used.