def crossover_parents_to_create_children()

in src/genetic_algorithm.py [0:0]

• 21 lines of code
• 9 McCabe index (conditional complexity)

def crossover_parents_to_create_children(parent_one, parent_two):
    child1 = copy.deepcopy(parent_one)
    child2 = copy.deepcopy(parent_two)

    # sometimes we don't cross over, so use copies of the parents
    if random.random() >= CROSSOVER_RATE:
        return child1, child2

    num_genes = len(parent_one.path)
    start_cross_at = random.randint(0, num_genes - 2)  # pick a point between 0 and the end - 2, so we can cross at least 1 stop
    num_remaining = num_genes - start_cross_at
    end_cross_at = random.randint(num_genes - num_remaining + 1, num_genes - 1)

    for index in range(start_cross_at, end_cross_at + 1):
        child1_stop = child1.path[index]
        child2_stop = child2.path[index]

        # if the same, skip it since there is no crossover needed at this gene
        if child1_stop == child2_stop:
            continue

        # find within child1 and swap
        first_found_at = child1.path.index(child1_stop)
        second_found_at = child1.path.index(child2_stop)
        child1.path[first_found_at], child1.path[second_found_at] = child1.path[second_found_at], child1.path[first_found_at]

        # and the same for the second child
        first_found_at = child2.path.index(child1_stop)
        second_found_at = child2.path.index(child2_stop)
        child2.path[first_found_at], child2.path[second_found_at] = child2.path[second_found_at], child2.path[first_found_at]

    return child1, child2