Skip to content

Core package to analyze gravitational-wave data, find signals, and study their parameters. This package was used in the first direct detection of gravitational waves (GW150914), and is used in the ongoing analysis of LIGO/Virgo data.

License

Notifications You must be signed in to change notification settings

Prasia-Pankunni/pycbc

 
 

Repository files navigation

GW150914

PyCBC is a software package used to explore astrophysical sources of gravitational waves. It contains algorithms to analyze gravitational-wave data, detect coalescing compact binaries, and make bayesian inferences from gravitational-wave data. PyCBC was used in the first direct detection of gravitational waves and is used in flagship analyses of LIGO and Virgo data.

PyCBC is collaboratively developed by the community and is lead by a team of GW astronomers with the aim to build accessible tools for gravitational-wave data analysis.

The PyCBC home page is located on github at

Documentation is automatically built from the latest master version

For the detailed installation instructions of PyCBC

Want to get going using PyCBC?

Quick Installation

pip install pycbc

To test the code on your machine

pip install pytest tox
tox

If you use any code from PyCBC in a scientific publication, then please see our citation guidelines for more details on how to cite pycbc algorithms and programs.

For the citation of the pycbc library, please use a bibtex entry and DOI for the appropriate release of the PyCBC software (or the latest available release). A bibtex key and DOI for each release is avaliable from Zenodo.

DOI Build Status PyPI version PyPI - Downloads Anaconda-Server Badge Anaconda-Server Badge astropy

About

Core package to analyze gravitational-wave data, find signals, and study their parameters. This package was used in the first direct detection of gravitational waves (GW150914), and is used in the ongoing analysis of LIGO/Virgo data.

Resources

License

Code of conduct

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Python 95.9%
  • Shell 1.8%
  • Cython 0.8%
  • C++ 0.6%
  • HTML 0.5%
  • C 0.1%
  • Other 0.3%