class FastNonDominatedRankingTestCases(unittest.TestCase):
def setUp(self):
self.ranking = FastNonDominatedRanking()
def test_should_constructor_create_a_valid_object(self):
self.assertIsNotNone(self.ranking)
def test_should_compute_ranking_of_an_emtpy_solution_list_return_a_empty_list_of_subranks(self):
solution_list = []
self.assertEqual(0, len(self.ranking.compute_ranking(solution_list)))
def test_should_compute_ranking_return_a_subfront_if_the_solution_list_contains_one_solution(self):
solution = Solution(2, 3)
solution_list = [solution]
ranking = self.ranking.compute_ranking(solution_list)
self.assertEqual(1, self.ranking.get_number_of_subfronts())
self.assertEqual(solution, ranking[0][0])
def test_should_compute_ranking_return_a_subfront_if_the_solution_list_contains_two_nondominated_solutions(self):
solution = Solution(2, 2)
solution.objectives = [1, 2]
solution2 = Solution(2, 2)
solution2.objectives = [2, 1]
solution_list = [solution, solution2]
ranking = self.ranking.compute_ranking(solution_list)
self.assertEqual(1, self.ranking.get_number_of_subfronts())
self.assertEqual(2, len(self.ranking.get_subfront(0)))
self.assertEqual(solution, ranking[0][0])
self.assertEqual(solution2, ranking[0][1])
def test_should_compute_ranking_work_properly_case1(self):
""" The list contains two solutions and one of them is dominated by the other one.
"""
solution = Solution(2, 2)
solution.objectives = [2, 3]
solution2 = Solution(2, 2)
solution2.objectives = [3, 6]
solution_list = [solution, solution2]
ranking = self.ranking.compute_ranking(solution_list)
self.assertEqual(2, self.ranking.get_number_of_subfronts())
self.assertEqual(1, len(self.ranking.get_subfront(0)))
self.assertEqual(1, len(self.ranking.get_subfront(1)))
self.assertEqual(solution, ranking[0][0])
self.assertEqual(solution2, ranking[1][0])
def test_should_ranking_of_a_population_with_three_dominated_solutions_return_three_subfronts(self):
solution = Solution(2, 2)
solution.objectives = [2, 3]
solution2 = Solution(2, 2)
solution2.objectives = [3, 6]
solution3 = Solution(2, 2)
solution3.objectives = [4, 8]
solution_list = [solution, solution2, solution3]
ranking = self.ranking.compute_ranking(solution_list)
self.assertEqual(3, self.ranking.get_number_of_subfronts())
self.assertEqual(1, len(self.ranking.get_subfront(0)))
self.assertEqual(1, len(self.ranking.get_subfront(1)))
self.assertEqual(1, len(self.ranking.get_subfront(2)))
self.assertEqual(solution, ranking[0][0])
self.assertEqual(solution2, ranking[1][0])
self.assertEqual(solution3, ranking[2][0])
def test_should_ranking_of_a_population_with_five_solutions_work_properly(self):
solution1 = Solution(2, 2)
solution2 = Solution(2, 2)
solution3 = Solution(2, 2)
solution4 = Solution(2, 2)
solution5 = Solution(2, 2)
solution1.objectives[0] = 1.0
solution1.objectives[1] = 0.0
solution2.objectives[0] = 0.5
solution2.objectives[1] = 0.5
solution3.objectives[0] = 0.0
solution3.objectives[1] = 1.0
solution4.objectives[0] = 0.6
solution4.objectives[1] = 0.6
solution5.objectives[0] = 0.7
solution5.objectives[1] = 0.5
solutions = [solution1, solution2, solution3, solution4, solution5]
ranking = self.ranking.compute_ranking(solutions)
self.assertEqual(2, self.ranking.get_number_of_subfronts())
self.assertEqual(3, len(self.ranking.get_subfront(0)))
self.assertEqual(2, len(self.ranking.get_subfront(1)))
self.assertEqual(solution1, ranking[0][0])
self.assertEqual(solution2, ranking[0][1])
self.assertEqual(solution3, ranking[0][2])
self.assertEqual(solution4, ranking[1][0])
self.assertEqual(solution5, ranking[1][1])
# random.seed(145600)
random.seed(1)
instance = DTLZInstance()
path = '/home/thinkpad/Documents/jemoa/src/main/resources/DTLZ_INSTANCES/DTLZ7_Instance.txt'
# path = '/home/thinkpad/PycharmProjects/jMetalPy/resources/DTLZ_INSTANCES/DTLZ1P_10.txt'
instance.read_(path)
isObjective = False
problem = DTLZ7P(instance)
_best = problem.generate_existing_solution(problem.instance_.attributes['best_compromise'][0], isObjective)
for s in problem.instance_.initial_solutions:
problem.evaluate(s)
print(s)
fndr = FastNonDominatedRanking()
fndr.compute_ranking(problem.instance_.initial_solutions)
print(fndr.get_number_of_subfronts())
classifier = InterClassNC(problem)
print('Best compromise:', _best.objectives,classifier.classify(_best))
# validate_interclass(problem)
# loadDataWithClass(problem,
# '/home/thinkpad/PycharmProjects/jMetalPy/results/Solutions.bag._class_enfoque_fronts_NSGAIII_custom.DTLZ1P_10.csv',
# 'enfoque_fronts_')
# load_objectives_from_gdm_file(problem, '/home/thinkpad/PycharmProjects/jMetalPy/resources/DTLZ_INSTANCES/objetivos_nelson.csv')
# dm_generator(obj, 14, obj * [Interval(0, (9 / 8) * k * 100)])
# dtlz_test(problem, 'enfoque_fronts')
print(problem)
reference_set(problem,is_objective=isObjective)
# looking_for_compromise(problem)
# test_classifier()
