opn

opn is a set of algorithms, problems, and visualisers to help in scientific experimentation on global optimization, especially metaheuristic optimization.

License & Warning

You may use this software freely in your academic work. For commercial use, contact developers.

This software is in alpha stage. They are useful for us, but we do not accept any kind of responsibility if you use them. They may ruin your day or more... You are warned.

Repository

The code is in https://bitbucket.org/oaltun/opn

The repository management will follow the approach explained in http://nvie.com/posts/a-successful-git-branching-model/

Installation & Dependencies

For installation, currently you need to download the zip from repository, extract the files, and either add ‘opn’ directory to your pythonpath, or run python setup.py install in the directory that has the setup.py script.

We have been using this software on Python 2.7.x and 64 bit Windows 7. You may have different luck with others.

You need to install following Python libraries before using opn: pyqt4 (or at least wxpython), numpy, mayavi, and matplotlib.

Documentation

The API page has the automatically generated documentation.

Also see examples directory.

Algorithms

You can find all included algorithms in API page for the opn.algorithm submodules.

Problems

You can find all included problems in API page for the opn.problem submodules.

API

The API page has automatically generated documentation using Sphinx.

Indices and tables