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openopt / copt

A Python library for mathematical optimization
http://openo.pt/copt
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machine-learning optimization python

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.. image:: https://travis-ci.org/openopt/copt.svg?branch=master :target: https://travis-ci.org/openopt/copt .. image:: https://coveralls.io/repos/github/openopt/copt/badge.svg?branch=master :target: https://coveralls.io/github/openopt/copt?branch=master .. image:: https://zenodo.org/badge/46262908.svg :target: https://zenodo.org/badge/latestdoi/46262908 .. image:: https://storage.googleapis.com/copt-doc/doc_status.svg :target: http://openopt.github.io/copt/ .. image:: https://storage.googleapis.com/copt-doc/pylint.svg :target: https://storage.googleapis.com/copt-doc/pylint.txt

Note: This package is no longer actively maintained. I won't be actively responding to issues. If you'd like to volunteer to maintain it, please drop me a line at f@bianp.net

copt: composite optimization in Python

copt is an optimization library for Python. Its goal is to provide a high quality implementation of classical optimization algorithms under a consistent API.

Docs <http://openopt.github.io/copt/>_ | Examples <http://openopt.github.io/copt/auto_examples/index.html>_

Installation

If you already have a working installation of numpy and scipy, the easiest way to install copt is using pip ::

pip install -U copt

Alternatively, you can install the latest development from github with the command::

pip install git+https://github.com/openopt/copt.git

Citing

If this software is useful for your research, please consider citing it as

.. code::

@article{copt,
  author       = {Fabian Pedregosa, Geoffrey Negiar, Gideon Dresdner},
  title        = {copt: composite optimization in Python},
  year         = 2020,
  DOI          = {10.5281/zenodo.1283339},
  url={http://openopt.github.io/copt/}
}

Development

The recommended way to work on the development versionis the following:

  1. Clone locally the github repo. This can be done with the command::

    git clone https://github.com/openopt/copt.git

This will create a copt directory.

  1. Link this directory to your Python interpreter. This can be done by running the following command from the copt directory created with the previous step::

    python setup.py develop

Now you can run the tests with :code:py.test tests/