shuffle_mutator.py

from numpy import nan as np_nan
from pygenalgo.genome.chromosome import Chromosome
from pygenalgo.operators.mutation.mutate_operator import MutationOperator


class ShuffleMutator(MutationOperator):
    """
    Description:

        Shuffle mutator mutates the chromosome by shuffling the gene
        values between two randomly selected gene end-positions.
    """

    def __init__(self, mutate_probability: float = 0.1):
        """
        Construct a 'ShuffleMutator' object with a given probability value.

        :param mutate_probability: (float).
        """

        # Call the super constructor with the provided
        # probability value.
        super().__init__(mutate_probability)
    # _end_def_

    def mutate(self, individual: Chromosome) -> None:
        """
        Perform the mutation operation by shuffling the genes
        between at two random positions.

        :param individual: (Chromosome).

        :return: None.
        """

        # If the mutation probability is higher than
        # a uniformly random value, make the changes.
        if self.is_operator_applicable():

            # Select randomly two mutation end-points.
            i, j = self.rng.choice(len(individual), size=2, replace=False,
                                   shuffle=False)

            # Swap indices (if necessary).
            if i > j:
                i, j = j, i
            # _end_if_

            # Make a slice list of the genes
            # we want to shuffle: i -> j.
            sliced_chromosome = individual[i:j]

            # Shuffle the copied slice in place.
            self.rng.shuffle(sliced_chromosome)

            # Put back the shuffled items.
            individual[i:j] = sliced_chromosome

            # Invalidate the fitness of the chromosome.
            individual.fitness = np_nan

            # Increase the mutator counter.
            self.inc_counter()
        # _end_if_
    # _end_def_

# _end_class_