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A Python-based Particle Swarm Optimization (PSO) library.

Project description

.. image:: docs/pyswarms-header.png
:alt: PySwarms Logo
:align: center

------------

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:alt: License

PySwarms is a an extensible research toolkit for particle swarm optimization (PSO) in Python.

* Free software: MIT license
* Documentation: https://pyswarms.readthedocs.io.


Features
--------
* High-level module for Particle Swarm Optimization. For a list of all optimizers, check this_ link.
* Test optimizers using various objective functions
* (For Devs and Researchers): Highly-extensible API for implementing your own techniques
* Easy API built on :code:`matplotlib` to create animations like these:

.. image:: docs/examples/output_3d.gif
:target: docs/examples/output_3d.gif
:width: 320 px
:alt: 3d particle plot

.. image:: docs/examples/output_9_0.png
:target: docs/examples/output_9_0.png
:width: 320 px
:alt: cost history plot

.. _this: https://pyswarms.readthedocs.io/en/latest/features.html

Dependencies
-------------
* numpy >= 1.13.0
* scipy >= 0.17.0
* matplotlib >= 1.3.1

Installation
-------------
To install PySwarms, run this command in your terminal:

.. code-block:: console

$ pip install pyswarms

This is the preferred method to install PySwarms, as it will always install the most recent stable release.

In case you want to install the bleeding-edge version, clone this repo:

.. code-block:: console

$ git clone https://github.com/ljvmiranda921/pyswarms.git

and then run

.. code-block:: console

$ python setup.py install

Basic Usage
------------
To use PySwarms in your project,

.. code-block:: python

import pyswarms as ps

Suppose you want to find the minima of :math:`f(x) = x^2` using global best PSO, simply import the
built-in sphere function, :code:`pyswarms.utils.functions.sphere_func()`, and the necessary optimizer:

.. code-block:: python

import pyswarms as ps
from pyswarms.utils.functions import single_obj as fx

# Set-up hyperparameters
options = {'c1': 0.5, 'c2': 0.3, 'w':0.9}

# Call instance of PSO
optimizer = ps.single.GlobalBestPSO(n_particles=10, dimensions=2, options=options)

# Perform optimization
stats = optimizer.optimize(fx.sphere_func, iters=100)

Credits
-------
This project was inspired by the pyswarm_ module that performs PSO with constrained support.
The package was created with Cookiecutter_ and the `audreyr/cookiecutter-pypackage`_ project template.

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

Others
------
Like it? Love it? Leave us a star on Github_ to show your appreciation!

.. _Github: https://github.com/ljvmiranda921/pyswarms


=======
History
=======

0.1.0 (2017-07-12)
------------------

* First release on PyPI.

0.1.1 (2017-07-25)
~~~~~~~~~~~~~~~~~

* Pre-release
* Bug fixes on calling local-best
* Implemented Local Best PSO

0.1.2 (2017-08-02)
~~~~~~~~~~~~~~~~~

* Pre-release
* Implemented Binary PSO
* More efficient API for gbest and lbest
* Documentation and tests

0.1.4 (2017-08-03)
~~~~~~~~~~~~~~~~~

* Added a patch to fix :code:`pip` installation

0.1.5 (2017-08-11)
~~~~~~~~~~~~~~~~~~

* Added graphics environment to plot the costs and swarm movement in 2D/3D

0.1.6 (2017-09-24)
~~~~~~~~~~~~~~~~~~

* Added hyperparameter search tools: GridSearch and RandomSearch
* Updated structure of Base classes for higher extensibility
* More robust tests for PlotEnvironment

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