genetic_function.py

class GeneticFunction(object):
    def probability_crossover(self):
        r"""returns rate of occur crossover(0.0-1.0)"""
        return 1.0

    def probability_mutation(self):
        r"""returns rate of occur mutation(0.0-1.0)"""
        return 0.0

    def initial(self):
        r"""returns list of initial population
        """
        return []

    def fitness(self, chromosome):
        r"""returns domain fitness value of chromosome
        """
        return len(chromosome)

    def get_generation_count(self):
        r"""return current generation number
        """
        return self.counter

    def check_stop(self, fits_populations):
        r"""stop run if returns True
        - fits_populations: list of (fitness_value, chromosome)
        """
        return False

    def parents(self, fits_populations):
        r"""generator of selected parents
        """
        gen = iter(sorted(fits_populations))
        while True:
            f1, ch1 = next(gen)
            f2, ch2 = next(gen)
            yield (ch1, ch2)
            pass
        return

    def crossover(self, parents):
        r"""breed children
        """
        return parents

    def mutation(self, chromosome):
        r"""mutate chromosome
        """
        return chromosome