def test_best_challenge_changes_best_individual(self):
""" Covers best challenge cases """
self.config.mutation_probability = 0.0
self.config.fitness_function_type = FitnessType.BASIC
p = Population(self.samples, self.grammar, self.stats)
i1 = Individual(self.samples,
self.grammar,
self.stats,
dna='00000000000000000000000000000000')
i2 = Individual(self.samples,
self.grammar,
self.stats,
dna='01110101100101100110010110010101')
# When there's no best individual yet, population's best individual is updated
p.best_individual = None
p.generation = [i2]
p._best_challenge()
super().assertEqual(p.best_individual, p.generation[0])
# When a better individual is better fitted in a new generation, population's best individual is updated
p.best_individual = i1
p.generation = [i2]
p._best_challenge()
super().assertEqual(p.best_individual, p.generation[0])
# When a worse individual is the most fitted in a new generation, population's best individual remains the same
p.best_individual = i2
p.generation = [i1]
p._best_challenge()
super().assertEqual(i2, p.best_individual)
def test_mu_lambda_no_elite(self):
""" Tests that replacement 'mu lambda without elitism' works as expected """
self.config.replacement_type = ReplacementType.MU_LAMBDA_WITHOUT_ELITISM
p = Population(self.samples, self.grammar, self.stats)
mating_pool = p.selection(p.generation)
p.offspring = p.recombination(mating_pool, p.generation)
p.generation, p.offspring = p.replacement(p.generation, p.offspring)
super().assertListEqual(p.offspring, [])
def test_mu_plus_lambda(self):
""" Tests that replacement 'mu plus lambda' works as expected """
self.config.replacement_type = ReplacementType.MU_PLUS_LAMBDA
p = Population(self.samples, self.grammar, self.stats)
mating_pool = p.selection(p.generation)
p.offspring = p.recombination(mating_pool, p.generation)
p.generation, p.offspring = p.replacement(p.generation, p.offspring)
super().assertListEqual(p.offspring, [])