Metadata-Version: 1.1
Name: copt
Version: 0.8.4
Summary: Library for composite optimization in Python
Home-page: http://pypi.python.org/pypi/copt
Author: Fabian Pedregosa
Author-email: f@bianp.net
License: New BSD License
Description: .. image:: https://travis-ci.org/openopt/copt.svg?branch=master
           :target: https://travis-ci.org/openopt/copt
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        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/`
        
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Software Development
Classifier: Operating System :: POSIX
Classifier: Operating System :: Unix
