pyswarms 0.1.2

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

========
PySwarms
========


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PySwarms is a simple, Python-based, Particle Swarm Optimization (PSO) library.

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


Features
--------
* High-level module for Particle Swarm Optimization
* Test optimizers using various objective functions
* (For Devs): Highly-extensible API for implementing your own techniques

Dependencies
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* Python 3.4 and above
* numpy >= 1.10.4
* scipy >= 0.17.0

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.

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.GBestPSO(n_particles=10, dims=2, **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




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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