Ecosyste.ms: Awesome

An open API service indexing awesome lists of open source software.

https://github.com/aarongarrett/inspyred

Python library for bio-inspired computational intelligence
https://github.com/aarongarrett/inspyred

Last synced: 3 months ago
JSON representation

Python library for bio-inspired computational intelligence

Lists

README

        

======================================================================================================
``inspyred`` -- A framework for creating bio-inspired computational intelligence algorithms in Python.
======================================================================================================

.. image:: https://img.shields.io/pypi/v/inspyred.svg
:target: https://pypi.python.org/pypi/inspyred
:alt: PyPi

.. image:: https://github.com/aarongarrett/inspyred/actions/workflows/ci.yml/badge.svg
:target: https://github.com/aarongarrett/inspyred/actions/workflows/ci.yml
:alt: GitHub Actions

.. image:: https://readthedocs.org/projects/inspyred/badge/?version=latest
:target: https://inspyred.readthedocs.io/en/latest/?badge=latest
:alt: Documentation Status

.. image:: https://img.shields.io/github/issues-pr/aarongarrett/inspyred
:target: https://github.com/aarongarrett/inspyred/pulls
:alt: PRs

.. image:: https://img.shields.io/github/issues/aarongarrett/inspyred
:target: https://github.com/aarongarrett/inspyred/issues
:alt: Issues

inspyred is a free, open source framework for creating biologically-inspired
computational intelligence algorithms in Python, including evolutionary
computation, swarm intelligence, and immunocomputing. Additionally, inspyred
provides easy-to-use canonical versions of many bio-inspired algorithms for
users who do not need much customization.

Example
-------

The following example illustrates the basics of the inspyred package. In this
example, candidate solutions are 10-bit binary strings whose decimal values
should be maximized::

import random
import time
import inspyred

def generate_binary(random, args):
bits = args.get('num_bits', 8)
return [random.choice([0, 1]) for i in range(bits)]

@inspyred.ec.evaluators.evaluator
def evaluate_binary(candidate, args):
return int("".join([str(c) for c in candidate]), 2)

rand = random.Random()
rand.seed(int(time.time()))
ga = inspyred.ec.GA(rand)
ga.observer = inspyred.ec.observers.stats_observer
ga.terminator = inspyred.ec.terminators.evaluation_termination
final_pop = ga.evolve(evaluator=evaluate_binary,
generator=generate_binary,
max_evaluations=1000,
num_elites=1,
pop_size=100,
num_bits=10)
final_pop.sort(reverse=True)
for ind in final_pop:
print(str(ind))

Requirements
------------

* Requires Python 3+.
* Numpy and Pylab are required for several functions in ``ec.observers``.
* Pylab and Matplotlib are required for several functions in ``ec.analysis``.
* Parallel Python (pp) is required if ``ec.evaluators.parallel_evaluation_pp`` is used.

License
-------

This package is distributed under the MIT License. This license can be found
online at http://www.opensource.org/licenses/MIT.

Resources
---------

* Homepage: http://aarongarrett.github.io/inspyred
* Email: [email protected]
* Documentation: https://inspyred.readthedocs.io.

Citing
------
Garrett, A. (2012). inspyred (Version 1.0.1) [software]. Inspired Intelligence. Retrieved from https://github.com/aarongarrett/inspyred [accessed CURRENT DATE].

Features
--------

* TODO

Credits
---------

This package was created with Cookiecutter_ and the `audreyr/cookiecutter-pypackage`_ project template.

.. _Cookiecutter: https://github.com/audreyr/cookiecutter
.. _`audreyr/cookiecutter-pypackage`: https://github.com/audreyr/cookiecutter-pypackage