``optiHistoric``
========================================

.. py:module:: optimeed.optimize.optiHistoric


Module Contents
---------------

Classes
~~~~~~~

.. autoapisummary::

   optimeed.optimize.optiHistoric.OptiHistoric
   optimeed.optimize.optiHistoric.OptiHistoric_Fast
   optimeed.optimize.optiHistoric.OptiHistoric_Empty




.. py:class:: OptiHistoric(optiname='opti', autosave_timer=60 * 5, autosave=True, create_new_directory=True, performance_datastruct=True, folder=getPath_workspace())


   Contains all the points that have been evaluated

   .. py:class:: _pointData(currTime, objectives, constraints)


      .. py:attribute:: time
         :type: float

         

      .. py:attribute:: objectives
         :type: List[float]

         

      .. py:attribute:: constraints
         :type: List[float]

         


   .. py:class:: _LogParams


      .. py:method:: add_parameters(params)


      .. py:method:: get_rows_indices(list_of_params)



   .. py:method:: log_after_evaluation(returned_values: dict)

      Save the output of evaluate to optiHistoric. This function should be called by the optimizer IN a process safe context.


   .. py:method:: set_results(devicesList)


   .. py:method:: get_best_devices_without_reevaluating(list_of_best_params)


   .. py:method:: set_convergence(theConvergence)


   .. py:method:: save()


   .. py:method:: get_convergence()

      :return: convergence :class:`~optimeed.optimize.optiAlgorithms.convergence.interfaceConvergence.InterfaceConvergence` 


   .. py:method:: get_devices()

      :return: List of devices (ordered by evaluation number) 


   .. py:method:: get_logopti()

      :return: Log optimization (to check the convergence) 


   .. py:method:: start(optimization_parameters)

      Function called upon starting the optimization. Create folders.



.. py:class:: OptiHistoric_Fast(optiname='opti')


   Almost empty struct, just enough to display the graphs. Used to speed up optimization

   .. py:method:: log_after_evaluation(returned_values: dict)


   .. py:method:: set_results(theResults)


   .. py:method:: get_best_devices_without_reevaluating(_)


   .. py:method:: set_convergence(theConvergence)


   .. py:method:: save()


   .. py:method:: get_convergence()


   .. py:method:: get_devices()


   .. py:method:: get_logopti()


   .. py:method:: start(optimization_parameters)



.. py:class:: OptiHistoric_Empty


   Totally empty struct, cannot be used within visualization

   .. py:method:: log_after_evaluation(returned_values: dict)


   .. py:method:: set_results(theResults)


   .. py:method:: get_best_devices_without_reevaluating(_)


   .. py:method:: set_convergence(_)


   .. py:method:: save()


   .. py:method:: get_convergence()


   .. py:method:: get_devices()


   .. py:method:: get_logopti()


   .. py:method:: start(_)