Metadata-Version: 2.1
Name: PyCBC
Version: 2.0.0
Summary: Core library to analyze gravitational-wave data, find signals, and study their parameters.
Home-page: http://www.pycbc.org/
Author: The PyCBC team
Author-email: alex.nitz@gmail.org
License: UNKNOWN
Download-URL: https://github.com/gwastro/pycbc/tarball/v2.0.0
Keywords: ligo,physics,gravity,signal processing,gravitational waves
Platform: UNKNOWN
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Intended Audience :: Science/Research
Classifier: Natural Language :: English
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Astronomy
Classifier: Topic :: Scientific/Engineering :: Physics
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
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Description-Content-Type: text/markdown
License-File: LICENSE
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![GW150914](https://raw.githubusercontent.com/gwastro/pycbc-logo/master/pycbc_logo_name.png)

[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
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/).

[![DOI](https://zenodo.org/badge/31596861.svg)](https://zenodo.org/badge/latestdoi/31596861) [![Build Status](https://travis-ci.org/gwastro/pycbc.svg?branch=master)](https://travis-ci.org/gwastro/pycbc)
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