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Note: This package is no longer actively maintained.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.
2. 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/`