Metadata-Version: 2.4
Name: ecvis
Version: 0.1.0
Summary: Visualisation methods for evolutionary computation and multi-objective optimisation
Author-email: David Walker <D.J.Walker2@exeter.ac.uk>
License: BSD 3-Clause License
Requires-Python: >=3.11
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy
Requires-Dist: scikit-learn
Requires-Dist: scipy
Requires-Dist: matplotlib
Dynamic: license-file

# ECVis
This library contains a range of methods for visualising the operation of evolutionary algorithms and the solutions they produce, including many-objective solution sets. Some of the methods are based on the following papers:

* Walker, David J., Everson, Richard M., and Fieldsend, Jonathan E. "[Visualizing mutually nondominating solution sets in many-objective optimization](https://ieeexplore.ieee.org/abstract/document/6342906)." IEEE Transactions on Evolutionary Computation 17, no. 2 (2012): 165-184.

The code is maintained by [David Walker](https://experts.exeter.ac.uk/22721-david-walker) at the University of Exeter. If you make use of the code, please cite the relevant paper.
