cma.constraints_handler

module documentation

A collection of (nonlinear) constraints handling classes and helper functions.

Class AugmentedLagrangian Augmented Lagrangian with adaptation of the coefficients
Class ConstrainedFitnessAL Construct an unconstrained objective function from constraints.
Class ConstrainedSolutionsArchive Biobjective Pareto archive to store some Pareto optimal solutions for constrained optimization.
Class CountLastSameChanges An array/list of successive same-sign counts.
Class DequeCDF a queue of vectors with element-wise cdf computation.
Class LoggerList list of loggers with plot method
Class PopulationEvaluator evaluate and store f- and g-values of a population in attributes F and G.
Function constraints_info_dict return dictionary with arg values, mainly there to unify names
Function _g_pos_max Undocumented
Function _g_pos_squared_sum Undocumented
Function _g_pos_sum Undocumented
Function _get_favorite_solution avoid unpicklable lambda construct
Function _log_feas_events Undocumented
Function _log_g Undocumented
Function _log_lam for active constraints, lam is generally positive because Dg and Df are opposed
Function _log_mu Undocumented
def constraints_info_dict(count, x, f, g, g_al):

return dictionary with arg values, mainly there to unify names

def _g_pos_max(gvals):

Undocumented

def _g_pos_squared_sum(gvals):

Undocumented

def _g_pos_sum(gvals):

Undocumented

def _get_favorite_solution(es):

avoid unpicklable lambda construct

def _log_feas_events(s):

Undocumented

def _log_g(s):

Undocumented

def _log_lam(s):

for active constraints, lam is generally positive because Dg and Df are opposed

def _log_mu(s):

Undocumented