themetal / pycma

Python implementation of CMA-ES

pycma        

[BibTeX] cite as:

Nikolaus Hansen, Youhei Akimoto, and Petr Baudis. CMA-ES/pycma on Github. Zenodo, DOI:10.5281/zenodo.2559634, February 2019.

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pycma is a Python implementation of CMA-ES and a few related numerical optimization tools.

The Covariance Matrix Adaptation Evolution Strategy (CMA-ES) is a stochastic derivative-free numerical optimization algorithm for difficult (non-convex, ill-conditioned, multi-modal, rugged, noisy) optimization problems in continuous search spaces.

Useful links:

• A quick start guide with a few usage examples

• The API Documentation

• Hints for how to use this (kind of) optimization module in practice

Installation of the (almost) latest release

Type

  python -m pip install cma

in a system shell to install the latest release from the Python Package Index (PyPI) (which may be behind the lastest release tag on Github). The release link also provides more installation hints and a quick start guide.

Installation of the current master branch

The quick way (requires git to be installed):

 pip install git+https://github.com/CMA-ES/pycma.git@master

The long version: download and unzip the code (see green button above) or git clone https://github.com/CMA-ES/pycma.git and

• either, copy (or move) the cma source code folder into a folder visible to Python, namely a folder which is in the Python path (e.g. the current folder). Then, import cma works without any further installation.

• or, install the cma package by typing within the folder, where the cma source code folder is visible,

  pip install -e cma
  

  Moving the cma folder away from its location would invalidate this installation.

It may be necessary to replace pip with python -m pip and/or prefixing either of these with sudo.

Version History

• Version 2.7.0 logger now writes into a folder, new fitness model module, various fixes

• Version 2.6.1 allow possibly much larger condition numbers, fix corner case with growing more-to-write list.

• Version 2.6.0 allows initial solution x0 to be a callable.

• Version 2.4.2 added the function cma.fmin2 which, similar to cma.purecma.fmin, returns (x_best:numpy.ndarray, es:cma.CMAEvolutionStrategy) instead of a 10-tuple like cma.fmin.

• Version 2.4.1 included bbob testbed.

• Version 2.2.0 added VkD CMA-ES to the master branch.

• Version 2.* is a multi-file split-up of the original module.

• Version 1.x.* is a one file implementation and not available in the history of this repository. The latest 1.* version ```1.1.7`` can be found here.