**pyswarm**
==================================================

.. py:module:: optimeed.optimize.optiAlgorithms.pyswarm


.. toctree::
   :titlesonly:
   :maxdepth: 1

   pso/index.rst


Package Contents
----------------

Classes
~~~~~~~

.. autoapisummary::

   optimeed.optimize.optiAlgorithms.pyswarm.MyMapEvaluator
   optimeed.optimize.optiAlgorithms.pyswarm.MyMultiprocessEvaluator
   optimeed.optimize.optiAlgorithms.pyswarm.MyArrayEvaluator



Functions
~~~~~~~~~

.. autoapisummary::

   optimeed.optimize.optiAlgorithms.pyswarm._is_feasible
   optimeed.optimize.optiAlgorithms.pyswarm._format_fx_fs
   optimeed.optimize.optiAlgorithms.pyswarm.pso



.. py:function:: _is_feasible(theList)


.. py:function:: _format_fx_fs(objectives_pop, constraints_pop)


.. py:class:: MyMapEvaluator(evaluation_function, callback_on_evaluation)


   .. py:method:: evaluate_all(x)



.. py:class:: MyMultiprocessEvaluator(evaluation_function, callback_on_evaluation, numberOfCores)


   .. py:method:: evaluate_all(x)



.. py:class:: MyArrayEvaluator(evaluation_function)


   .. py:method:: evaluate_all(list_of_x)



.. py:function:: pso(lb, ub, initialVectorGuess, theEvaluator, terminationCondition, callback_generation=lambda objectives, constraints: None, swarmsize=100, omega=0.5, phip=0.5, phig=0.5)

   Perform a particle swarm optimization (PSO)

   :param lb: List. Lower bounds of each parameter
   :param ub: List. Upper bounds of each parameter
   :param initialVectorGuess: List. initial vector guess for the solution (to be included inside population)
   :param theEvaluator: object define before
   :param terminationCondition: Termination condition with shouldTerminated method
   :param callback_generation: function lambda (objectives (as list), constraints (as list)) per step
   :param swarmsize: Int. The number of particles in the swarm (Default: 100)
   :param omega: Float. Particle velocity scaling factor (Default: 0.5)
   :param phip: Float. Scaling factor to search away from the particle's best known position (Default: 0.5)
   :param phig: Float. Scaling factor to search away from the swarm's best known position (Default: 0.5)
   :return: (g) array The swarm's best known position (optimal design). (f) scalar, the objective value at (g)