**convergence** ====================================================== .. py:module:: optimeed.optimize.optiAlgorithms.convergence .. toctree:: :titlesonly: :maxdepth: 1 evolutionaryConvergence/index.rst hypervolume/index.rst interfaceConvergence/index.rst Package Contents ---------------- Classes ~~~~~~~ .. autoapisummary:: optimeed.optimize.optiAlgorithms.convergence.EvolutionaryConvergence optimeed.optimize.optiAlgorithms.convergence.InterfaceConvergence .. 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` .. py:class:: InterfaceConvergence Simple interface to visually get the convergence of any optimization problem .. py:method:: get_graphs(*args, **kwargs) :abstractmethod: Return :class:`~optimeed.core.graphs.Graphs`