def add_cluster_with_representative(self, genome_id: ObjectId): cluster = Cluster() cluster._id = ObjectId("00000000000000000000000"+str(self.next_id)) cluster.representative = genome_id cluster.fitness = int(str(genome_id)) self.clusters.append(cluster) self.next_id += 1
def test_selectClusterForCombination(self): offspring = [10, 10, 10, 10] cluster = [] counter = 0 for i in offspring: c = Cluster() c.offspring = i c.fitness = float(1/(counter+1)) cluster.append(c) counter += 1 self.mock_cluster_repository.get_current_clusters = MagicMock(return_value=cluster) c = Cluster() d = (c, c) test_comb = self.genome_selector.select_clusters_for_combination() self.assertEqual(type(d), type(self.genome_selector.select_clusters_for_combination())) self.assertFalse( test_comb[0].__eq__(test_comb[1]) )
def test_getClusterAreaSortedByFitness(self): unsorted = [0.0, 1.0, 2.4, 0.4, 0.9, 0.12, 4.32, 3.2, 5.1, 0.55] chosen = [0.4, 0.55, 0.9, 1.0, 2.4, 3.2] discard = [0.0, 0.12] cluster = [] cluster_chosen = [] cluster_discard = [] for i in unsorted: c = Cluster() c.fitness = i cluster.append(c) if i in chosen: cluster_chosen.append(c) if i in discard: cluster_discard.append(c) self.mock_cluster_repository.get_current_clusters = MagicMock(return_value=cluster) cluster_chosen.sort(key=lambda x: x.fitness) self.assertListEqual(cluster_chosen, self.genome_selector.get_cluster_area_sorted_by_fitness(0.2, 0.8)) self.assertListEqual(cluster_discard, self.genome_selector.select_clusters_for_discarding())