A framework for creating evolutionary computations in Python.
Project description
ECsPy (Evolutionary Computations in Python) is a free, open source framework for creating evolutionary computations in Python. Additionally, ECsPy provides an easy-to-use canonical genetic algorithm (GA), evolution strategy (ES), estimation of distribution algorithm (EDA), differential evolution algorithm (DEA), and particle swarm optimizer (PSO) for users who don’t need much customization.
Requirements
Requires at least Python 2.6 (not compatible with Python 3+).
Numpy and Matplotlib are required if the line plot observer is used.
Parallel Python (pp) is required if parallel_evaluation_pp is used.
License
This package is distributed under the GNU General Public License version 3.0 (GPLv3). This license can be found online at http://www.opensource.org/licenses/gpl-3.0.html.
Package Structure
ECsPy consists of the following modules:
analysis.py – provides tools for analyzing the results of an EC
archivers.py – defines useful archiving methods, particularly for EMO algorithms
benchmarks.py – defines several single- and multi-objective benchmark optimization problems
ec.py – provides the basic framework for an EvolutionaryComputation and specific ECs
emo.py – provides the Pareto class for multiobjective optimization along with specific EMOs (e.g. NSGA-II)
evaluators.py – defines useful evaluation schemes, such as parallel evaluation
migrators.py – defines a few built-in migrators, including migration via network and migration among concurrent processes
observers.py – defines a few built-in observers, including screen, file, and plotting observers
replacers.py – defines standard replacement schemes such as generational and steady-state replacement
selectors.py – defines standard selectors (e.g., tournament)
swarm.py – provides a basic particle swarm optimizer
terminators.py – defines standard terminators (e.g., exceeding a maximum number of generations)
topologies.py – defines standard topologies for particle swarms
variators.py – defines standard variators (crossover and mutation schemes such as n-point crossover)
Resources
Homepage: http://ecspy.googlecode.com
Email: aaron.lee.garrett@gmail.com
