geneticengine.evaluation.tracker

Module Contents

Classes

ProgressTracker

Helper class that provides a standard way to create an ABC using

SingleObjectiveProgressTracker

Helper class that provides a standard way to create an ABC using

MultiObjectiveProgressTracker

Helper class that provides a standard way to create an ABC using

class geneticengine.evaluation.tracker.ProgressTracker(problem, evaluator, recorders=None)

Bases: abc.ABC

Helper class that provides a standard way to create an ABC using inheritance.

Parameters:
problem: geneticengine.problems.Problem
evaluator: geneticengine.evaluation.Evaluator
start_time: int
recorders: list[geneticengine.evaluation.recorder.SearchRecorder]
get_problem()
Return type:

geneticengine.problems.Problem

get_number_evaluations()

The cumulative number of evaluations performed.

Return type:

int

get_elapsed_time()

The elapsed time since the start in seconds.

Return type:

float

evaluate(individuals)
Parameters:

individuals (Iterable[geneticengine.solutions.Individual])

evaluate_single(individual)
Parameters:

individual (geneticengine.solutions.Individual)

get_best_individual()
Return type:

geneticengine.solutions.Individual

class geneticengine.evaluation.tracker.SingleObjectiveProgressTracker(problem, evaluator=None, recorders=None)

Bases: ProgressTracker

Helper class that provides a standard way to create an ABC using inheritance.

Parameters:
best_individual: geneticengine.solutions.Individual | None
post_process(individual)
Parameters:

individual (geneticengine.solutions.Individual)

evaluate(individuals)
Parameters:

individuals (Iterable[geneticengine.solutions.Individual])

get_best_individual()
Return type:

geneticengine.solutions.Individual

class geneticengine.evaluation.tracker.MultiObjectiveProgressTracker(problem, evaluator=None, recorders=None)

Bases: ProgressTracker

Helper class that provides a standard way to create an ABC using inheritance.

Parameters:
pareto_front: list[geneticengine.solutions.Individual]
is_dominated(current, others)
Parameters:
evaluate(individuals)
Parameters:

individuals (Iterable[geneticengine.solutions.Individual])

get_best_individuals()
Return type:

list[geneticengine.solutions.Individual]