Metadata-Version: 2.1
Name: groupyr
Version: 0.1.3
Summary: groupyr: Sparse Groups Lasso in Python
Home-page: https://richford.github.io/groupyr
Author: Adam Richie-Halford
Author-email: richiehalford@gmail.com
Maintainer: Adam Richie-Halford
Maintainer-email: richiehalford@gmail.com
License: BSD License
Download-URL: https://github.com/richford/groupyr
Platform: OS Independent
Classifier: Development Status :: 3 - Alpha
Classifier: Environment :: Console
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: BSD License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Topic :: Scientific/Engineering
Requires-Python: >=3.6
Description-Content-Type: text/markdown
Requires-Dist: copt (==0.8.4)
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![groupyr logo](https://raw.githubusercontent.com/richford/groupyr/main/doc/_static/groupyr-logo-large.svg)

# _Groupyr_: Sparse Group Lasso in Python

[![Build Status](https://github.com/richford/groupyr/workflows/Build/badge.svg)](https://github.com/richford/groupyr/workflows/Build/badge.svg)
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[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/python/black)
[![License](https://img.shields.io/badge/License-BSD%203--Clause-blue.svg)](https://opensource.org/licenses/BSD-3-Clause)
[![DOI](https://zenodo.org/badge/300933639.svg)](https://zenodo.org/badge/latestdoi/300933639)

_Groupyr_ is a Python library for penalized regression of grouped covariates.
This is the _groupyr_ development site. You can view the source code, file new issues, and contribute to _groupyr_'s development. If you just want to learn how to install and use _groupyr_, please look at the [_groupyr_ documentation](https://richford.github.io/groupyr/).

## Contributing

We love contributions! _Groupyr_ is open source, built on open source,
and we'd love to have you hang out in our community.

We have developed some [guidelines](.github/CONTRIBUTING.md) for contributing to
_groupyr_.

## Citing _groupyr_

If you use _groupyr_ in a scientific publication, please see our [citation
instructions](https://richford.github.io/groupyr/index.html#citing-groupyr).

## Acknowledgements

_Groupyr_ development is supported through a grant from the [Gordon
and Betty Moore Foundation](https://www.moore.org/) and from the
[Alfred P. Sloan Foundation](https://sloan.org/) to the [University of
Washington eScience Institute](http://escience.washington.edu/), as
well as
[NIMH BRAIN Initiative grant 1RF1MH121868-01](https://projectreporter.nih.gov/project_info_details.cfm?aid=9886761&icde=46874320&ddparam=&ddvalue=&ddsub=&cr=2&csb=default&cs=ASC&pball=)
to Ariel Rokem (University of Washington).

The API design of _groupyr_ was facilitated by the [scikit-learn project
template](https://github.com/scikit-learn-contrib/project-template) and it
therefore borrows heavily from
[scikit-learn](https://scikit-learn.org/stable/index.html). _Groupyr_ relies
on the [copt optimization library](http://openo.pt/copt/index.html) for its
solver. The _groupyr_ logo is a flipped silhouette of an [image from J. E.
Randall](https://commons.wikimedia.org/wiki/File:Epinephelus_amblycephalus,_banded_grouper.jpg)
and is licensed [CC BY-SA](https://creativecommons.org/licenses/by-sa/3.0).


