eckity.termination_checkers.threshold_from_target_termination_checker

 1from eckity.termination_checkers.termination_checker import TerminationChecker
 2
 3
 4class ThresholdFromTargetTerminationChecker(TerminationChecker):
 5    """
 6    Concrete Termination Checker that checks the distance from best existing fitness value to target fitness value.
 7
 8    Parameters
 9    ----------
10    optimal: float, default=0.
11        Target fitness value.
12        This termination checker checks if the currently best fitness is "close enough" to the optimal value.
13
14    threshold: float, default=0.
15        How close should the current best fitness be to the target fitness.
16
17    higher_is_better: bool, default=False
18        Determines if higher fitness values are better.
19    """
20    def __init__(self, optimal=0., threshold=0., higher_is_better=False):
21        super().__init__()
22        self.optimal = optimal
23        self.threshold = threshold
24        self.higher_is_better = higher_is_better
25
26    def should_terminate(self, population, best_individual, gen_number):
27        """
28        Determines if the currently best fitness is close enough to the target fitness.
29        If so, recommends the algorithm to terminate early.
30
31        Parameters
32        ----------
33        population: Population
34            The evolutionary experiment population of individuals.
35
36        best_individual: Individual
37            The individual that has the best fitness of the current generation.
38
39        gen_number: int
40            Current generation number.
41
42        Returns
43        -------
44        bool
45            True if the algorithm should terminate early, False otherwise.
46        """
47        return abs(best_individual.get_pure_fitness() - self.optimal) <= self.threshold