[PyCBC](http://pycbc.org) 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](https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.116.061102) 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
* https://pycbc.org/
Documentation is automatically built from the latest master version
* https://pycbc.org/pycbc/latest/html/
For the detailed installation instructions of PyCBC
* https://pycbc.org/pycbc/latest/html/install.html
Want to get going using PyCBC?
* [Try out our tutorials](https://github.com/gwastro/PyCBC-Tutorials). No software installation required and these can run entirely from the browser.
Quick Installation
```
pip install pycbc
```
To test the code on your machine
```
pip install pytest "tox<4.0.0"
tox
```
If you use any code from PyCBC in a scientific publication, then please see our [citation guidelines](http://pycbc.org/pycbc/latest/html/credit.html) 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](http://zenodo.org/).
[](https://zenodo.org/badge/latestdoi/31596861) [](https://travis-ci.org/gwastro/pycbc)
[](https://badge.fury.io/py/PyCBC)  [](https://anaconda.org/conda-forge/pycbc) [](https://anaconda.org/conda-forge/pycbc)
[](http://www.astropy.org/)
Raw data
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