class documentation

BBOB Testbed for constrained problems.

Static Method constraint_category Return the number of constraints as a string formula.
Static Method number_of_constraints Return the number of constraints of function function_id
Method __init__ Undocumented
Method filter Does nothing but overwriting the method from superclass
Class Variable func_cons_groups Undocumented
Class Variable has_constraints Undocumented
Class Variable min_target Undocumented
Class Variable min_target_exponent Undocumented
Class Variable min_target_latex Undocumented
Class Variable min_target_scatter Undocumented
Class Variable pptable_targetsOfInterest Undocumented
Class Variable settings Undocumented
Class Variable shortinfo_filename Undocumented

Inherited from GECCOBBOBTestbed:

Class Variable dimsOfInterest Undocumented
Class Variable pptable_target_runlengths Undocumented
Instance Variable instancesOfInterest Undocumented

Inherited from Testbed (via GECCOBBOBTestbed):

Method info info on the testbed if fun_number is None or one-line info for function with number fun_number.
Method instantiate_attributes assign self.some_attr = class_(self.some_attr) if "some_attr" ends with any value in the suffix_list
Class Variable instances_are_uniform False for biobjective suites, used (so far only) for simulated restarts in pprldmany
Class Variable reference_algorithm_displayname Undocumented
Property string_evals Undocumented
Property string_evals_legend Undocumented
Property string_evals_short Undocumented
@staticmethod
def constraint_category(function_id, active_only=False):

Return the number of constraints as a string formula.

The formula is the same for all dimensions and may contain 'n' which stands for dimension. If active_only, it gives the number of constraints that are active in the global optimum.

@staticmethod
def number_of_constraints(dimension, function_id, active_only=False):

Return the number of constraints of function function_id

in the given dimension. If active_only, it is the number of constraints that are active in the global optimum.

def __init__(self, target_values):
def filter(self, dsl):

Does nothing but overwriting the method from superclass

func_cons_groups =

Undocumented

has_constraints: bool =
min_target: float =

Undocumented

min_target_exponent: float =

Undocumented

min_target_latex: str =

Undocumented

min_target_scatter: int =

Undocumented

pptable_targetsOfInterest =
shortinfo_filename: str =