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Library for composite optimization in Python

Project description

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Note: This package is no longer actively maintained.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 | Examples

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

@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 py.test tests/

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copt-0.9.1.tar.gz (879.7 kB view hashes)

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