``evolutionaryConvergence``
==============================================================================

.. py:module:: optimeed.optimize.optiAlgorithms.convergence.evolutionaryConvergence


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

Classes
~~~~~~~

.. autoapisummary::

   optimeed.optimize.optiAlgorithms.convergence.evolutionaryConvergence.EvolutionaryConvergence




.. py:class:: EvolutionaryConvergence


   Bases: :py:obj:`optimeed.optimize.optiAlgorithms.convergence.interfaceConvergence.InterfaceConvergence`

   convergence class for population-based algorithm

   .. py:attribute:: objectives_per_step
      :type: Dict[int, List[List[float]]]

      

   .. py:attribute:: constraints_per_step
      :type: Dict[int, List[List[float]]]

      

   .. py:attribute:: paretos_per_step
      :type: Dict[int, List[List[float]]]

      

   .. py:attribute:: hypervolume_per_step
      :type: Dict[int, List[float]]

      

   .. py:method:: set_curr_step(theObjectives_list, theConstraints_list)


   .. py:method:: get_objectives_respect_constraint(objectives, constraints)
      :staticmethod:


   .. py:method:: _extract_N_steps(N)


   .. py:method:: get_pareto_convergence(max_number_of_points=None)


   .. py:method:: get_pareto_at_step(step)


   .. py:method:: get_hypervolume(pareto, refPoint=None)


   .. py:method:: get_hypervolume_convergence(max_number_of_points)


   .. py:method:: get_nadir_point(pareto)


   .. py:method:: last_step()


   .. py:method:: get_nb_objectives()


   .. py:method:: get_scalar_convergence_evolution(max_number_of_points)


   .. py:method:: get_graphs(max_number_of_points=None)

      Return :class:`~optimeed.core.graphs.Graphs`