def test_select_returns_current_node_and_copy(self):
genomes = create_genomes(10)
results = self.selector.select(genomes[0], genomes, self.params)
self.assertEqual(len(results), 2)
self.assertIs(results[0], genomes[0])
self.assertIsNot(results[1], genomes[0])
self.assertEqual(results[0], results[1])
def test_crossing_pairs_with_probability_of_zero_and_odd_size(self):
genomes = create_genomes(11)
params = {"crossover.rate": 0.0}
gen_a, gen_b = self.crossover.extract_crossing_pairs(genomes, params)
self.assertEqual(len(gen_a), 0)
self.assertEqual(len(gen_b), 0)
self.assertEqual(len(genomes), 11)
def test_crossing_pairs_with_probability_of_one_and_even_size(self):
genomes = create_genomes(10)
params = {"crossover.rate": 1.0}
gen_a, gen_b = self.crossover.extract_crossing_pairs(genomes, params)
self.assertEqual(len(gen_a), 5)
self.assertEqual(len(gen_b), 5)
self.assertEqual(len(genomes), 0)
def test_replacement_selection_with_odd_size_list_in_parallel(self):
genomes = create_genomes(21)
genomes.sort(reverse=True, key=lambda g: g.fitness)
min_fitness = genomes[ceil(len(genomes) / 2)].fitness
shuffle(genomes)
results = self.selector.evolve(genomes, self.pool, self.params)
self.assertEqual(len(results), len(genomes))
for result in results:
self.assertGreaterEqual(result.fitness, min_fitness)
def test_uniform_crossover_in_parallel(self):
genomes = create_genomes(10)
fitness_scores = [x.fitness for x in genomes]
expected = [copy(g) for g in genomes]
results = self.crossover.evolve(genomes, self.pool, self.params)
for genome, result in zip(genomes, results):
self.assertEqual(genome.fitness, result.fitness)
for i in range(0, len(genomes), 2):
self.assertEqual(expected[i], results[i + 1])
self.assertEqual(expected[i + 1], results[i])