Metadata-Version: 1.1
Name: pyswarms
Version: 0.1.4
Summary: A Python-based Particle Swarm Optimization (PSO) library.
Home-page: https://github.com/ljvmiranda921/pyswarms
Author: Lester James V. Miranda
Author-email: ljvmiranda@gmail.com
License: MIT license
Description: ========
        PySwarms
        ========
        
        .. image:: https://badge.fury.io/py/pyswarms.svg
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                :alt: Documentation Status
        
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             :target: https://raw.githubusercontent.com/ljvmiranda921/pyswarms/master/LICENSE
        
        
        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
        -------------
        * 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
        
        
        
        
        =======
        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)
        ~~~~~~~~~~~~~~~~~
        
        * Well, this is embarassing...
        * Added a patch to fix :code:`pip` installation
Keywords: pyswarms
Platform: UNKNOWN
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
