def setUp(self):
"""Init"""
set_seed(1)
project_path = os.path.dirname(os.path.abspath(__file__))
self.problem = Rmnk(project_path +
'/data/instances/rmnk_0_2_100_1_0.dat')
self.solution = self.problem.generate_random_solution()
class RmnkTest(unittest.TestCase):
"""Test the 'rmnk' problem."""
def setUp(self):
"""Init"""
project_path = os.path.dirname(os.path.abspath(__file__))
self.problem = Rmnk(project_path +
'/../data/instances/rmnk_0_2_100_1_0.dat')
def test_instance(self):
"""Test parameters"""
self.assertEqual(self.problem.rho, 0)
self.assertEqual(self.problem.m, 2)
self.assertEqual(self.problem.n, 100)
self.assertEqual(self.problem.k, 1)
def test_generate_random_solution(self):
"""Test the function 'generate_random_solution'"""
random_solution = self.problem.generate_random_solution()
self.assertEqual(len(random_solution.decision_vector), 100)
self.assertEqual(len(random_solution.F), 2)
for item in random_solution.decision_vector:
self.assertIn(item, [0, 1])
for function_i in random_solution.F:
self.assertLess(function_i, 0)
self.assertGreater(function_i, -1)
def test_generate_solution(self):
"""Test the function 'generate_solution'"""
array = []
for i in range(100):
array.append(random.randint(0, 1))
solution = self.problem.evaluate(array)
self.assertEqual(len(solution.decision_vector), 100)
self.assertEqual(len(solution.F), 2)
for item in solution.decision_vector:
self.assertIn(item, [0, 1])
for function_i in solution.F:
self.assertLess(function_i, 0)
self.assertGreater(function_i, -1)
def test_evaluation(self):
"""Test evaluation"""
array = []
for i in range(100):
array.append(1)
solution = self.problem.evaluate(array)
self.assertEqual(solution.F[0], -0.4884468640000001)
self.assertEqual(solution.F[1], -0.4930223456999998)
def setUp(self):
"""Init"""
set_seed(1)
project_path = os.path.dirname(os.path.abspath(__file__))
self.rmnk = Rmnk(instance_file=project_path +
'/data/instances/rmnk_0_2_100_1_0.dat')
self.rmnk3D = Rmnk(instance_file=project_path +
'/data/instances/rmnk_0_3_100_1_0.dat')
self.number_of_objective = self.rmnk.number_of_objective
def setUp(self):
"""Init"""
project_path = os.path.dirname(os.path.abspath(__file__))
self.problem = Rmnk(project_path + '/data/instances/rmnk_0_2_100_1_0.dat')
weight_file = project_path + "/data/weights/SOBOL-2objs-10wei.ws"
self.weights = generate_weight_vectors(weight_file, False)
array = []
for i in range(100):
array.append(1)
self.solution = self.problem.evaluate(array)
self.z = [1, 1]
def setUp(self):
"""Init"""
random.seed(1)
np.random.seed(1)
self.number_of_evaluations = 100
project_path = os.path.dirname(os.path.abspath(__file__))
self.rmnk = Rmnk(instance_file=project_path +
'/data/instances/rmnk_0_2_100_1_0.dat')
self.number_of_objective = self.rmnk.number_of_objective
self.number_of_weight = 10
self.number_of_weight_neighborhood = 10
self.number_of_crossover_points = 4
self.weight_file = project_path + "/data/weights/SOBOL-" \
+ str(self.number_of_objective) \
+ "objs-" + str(self.number_of_weight) \
+ "wei.ws"
self.moead = Moead(
problem=self.rmnk,
max_evaluation=self.number_of_evaluations,
number_of_objective=self.number_of_objective,
number_of_weight=self.number_of_weight,
aggregation_function=Tchebycheff,
number_of_weight_neighborhood=self.number_of_weight_neighborhood,
number_of_crossover_points=self.number_of_crossover_points,
weight_file=self.weight_file,
)
class RmnkTest(unittest.TestCase):
"""Test the 'rmnk' problem."""
def setUp(self):
"""Init"""
random.seed(1)
np.random.seed(1)
project_path = os.path.dirname(os.path.abspath(__file__))
self.problem = Rmnk(project_path +
'/data/instances/rmnk_0_2_100_1_0.dat')
self.solution = self.problem.generate_random_solution()
def test_set_item(self):
"""Test set item"""
# todo
self.assertEqual(self.solution[0], -0.5107130364200001)
self.solution[0] = -42
self.assertEqual(self.solution[0], -42)
def test_repr(self):
"""Test repr'"""
self.assertEqual(repr(self.solution),
"[-0.5107130364200001, -0.5078202645999998]")
def test_copy(self):
""""Test the copy of solution"""
copy_sol = copy(self.solution)
# address are different
self.assertNotEqual(copy_sol, self.solution)
# solution are equals
self.assertEqual(copy_sol.F, self.solution.F)
def setUp(self):
"""Init"""
set_seed(1)
self.number_of_evaluations = 100
project_path = os.path.dirname(os.path.abspath(__file__))
self.rmnk = Rmnk(instance_file=project_path + '/data/instances/rmnk_0_2_100_1_0.dat')
self.number_of_objective = self.rmnk.number_of_objective
self.number_of_weight = 10
self.number_of_weight_neighborhood = 2
self.number_of_crossover_points = 4
self.weight_file = project_path + "/data/weights/SOBOL-" \
+ str(self.number_of_objective) \
+ "objs-" + str(self.number_of_weight) \
+ "wei.ws"
self.weight_file50 = project_path + "/data/weights/SOBOL-" \
+ str(self.number_of_objective) \
+ "objs-" + str(50) \
+ "wei.ws"
class ScalarizingTest(unittest.TestCase):
"""Test aggregation functions."""
def setUp(self):
"""Init"""
project_path = os.path.dirname(os.path.abspath(__file__))
self.problem = Rmnk(project_path + '/data/instances/rmnk_0_2_100_1_0.dat')
weight_file = project_path + "/data/weights/SOBOL-2objs-10wei.ws"
self.weights = generate_weight_vectors(weight_file, False)
array = []
for i in range(100):
array.append(1)
self.solution = self.problem.evaluate(array)
self.z = [1, 1]
def test_tchebycheff(self):
"""Test Tchebycheff"""
value1 = Tchebycheff().run(self.solution, 2, self.weights, 3, self.z)
value2 = Tchebycheff().run(self.solution, 2, self.weights, 8, self.z)
self.assertEqual(value1, 1.1197667592749998)
self.assertEqual(value2, 1.3023910060000001)
self.assertFalse(Tchebycheff().is_better(value1, value2))
self.assertTrue(Tchebycheff().is_better(value2, value1))
def test_weighted_sum(self):
"""Test Weighted Sum"""
value1 = WeightedSum().run(self.solution, 2, self.weights, 3, self.z)
value2 = WeightedSum().run(self.solution, 2, self.weights, 8, self.z)
self.assertEqual(value1, -0.4918784752749999)
self.assertEqual(value2, -0.4890187992125)
self.assertFalse(WeightedSum().is_better(value1, value2))
self.assertTrue(WeightedSum().is_better(value2, value1))
from moead_framework.aggregation import Tchebycheff
from moead_framework.algorithm.combinatorial import Moead
from moead_framework.problem.combinatorial import Rmnk
from moead_framework.tool.result import save_population
###############################
# Initialize the problem #
###############################
# The file is available here : https://github.com/moead-framework/data/blob/master/problem/RMNK/Instances/rmnk_0_2_100_1_0.dat
# Others instances are available here : https://github.com/moead-framework/data/tree/master/problem/RMNK/Instances
instance_file = "rmnk_0_2_100_1_0.dat"
rmnk = Rmnk(instance_file=instance_file)
###############################
# Initialize the algorithm #
###############################
number_of_weight = 10
number_of_weight_neighborhood = 20
number_of_evaluations = 1000
# The file is available here : https://github.com/moead-framework/data/blob/master/weights/SOBOL-2objs-10wei.ws
# Others weights files are available here : https://github.com/moead-framework/data/tree/master/weights
weight_file = "SOBOL-" + str(
rmnk.function_numbers) + "objs-" + str(number_of_weight) + "wei.ws"
###############################
# Execute the algorithm #
###############################
moead = Moead(
problem=rmnk,
max_evaluation=number_of_evaluations,
number_of_weight_neighborhood=number_of_weight_neighborhood,
def setUp(self):
"""Init"""
project_path = os.path.dirname(os.path.abspath(__file__))
self.problem = Rmnk(project_path +
'/../data/instances/rmnk_0_2_100_1_0.dat')
class ToolsTest(unittest.TestCase):
"""Test implemented algorithms."""
def setUp(self):
"""Init"""
random.seed(1)
np.random.seed(1)
project_path = os.path.dirname(os.path.abspath(__file__))
self.rmnk = Rmnk(instance_file=project_path +
'/data/instances/rmnk_0_2_100_1_0.dat')
self.rmnk3D = Rmnk(instance_file=project_path +
'/data/instances/rmnk_0_3_100_1_0.dat')
self.number_of_objective = self.rmnk.number_of_objective
def test_PF(self):
"""Test get Non dominated"""
solutions = []
for i in range(20):
solutions.append(self.rmnk.generate_random_solution())
non_dominated_pop = get_non_dominated(population=solutions)
non_dominated = []
for s in non_dominated_pop:
non_dominated.append(s.F)
test = [[-0.5571641596999998, -0.4450894643],
[-0.5483895551199999, -0.48251202308000013],
[-0.5428439510999998, -0.48726908450000017],
[-0.5107130364200001, -0.5078202645999998],
[-0.5070678622999999, -0.5411136235],
[-0.4660221059999998, -0.5569167061000001],
[-0.4493039854199998, -0.5587430658000001]]
self.assertEqual(len(non_dominated), len(test))
for elt in test:
self.assertIn(elt, non_dominated)
def test_population_size_without_duplicate(self):
"""test the function population_size_without_duplicate"""
population = []
for i in range(10):
population.append(self.rmnk.generate_random_solution())
# duplicate two solutions in the population
population.append(population[4])
population.append(population[2])
self.assertEqual(len(population), 12)
self.assertEqual(
population_size_without_duplicate(population=population), 10)
def test_hypervolume3D(self):
"""test the hypervolume in 3D"""
population = []
for i in range(10):
population.append(self.rmnk3D.generate_random_solution())
self.assertEqual(compute_hypervolume(population, [0, 0, 0]),
0.16108679722159508) # test the hypervolume value
def test_compute_crowding_distance(self):
"""test the function compute_crowding_distance"""
population = []
for i in range(10):
population.append(self.rmnk.generate_random_solution())
# distance equal to 0 before computing
self.assertEqual(population[0].distance, 0)
# compute the crowding distance
pop_with_distance = compute_crowding_distance(population)
self.assertEqual(population[0].distance, 0.07806191187999945)
self.assertEqual(pop_with_distance[0].distance, 0.07806191187999945)
def test_save_population(self):
"""test the function to save the population"""
population = []
for i in range(10):
population.append(self.rmnk.generate_random_solution())
save_population("test_save_population.txt", population)
f = open("test_save_population.txt", "r")
index_pop = 0
for line in f:
f1 = float(line.replace("\n", "").split(" ")[0])
f2 = float(line.replace("\n", "").split(" ")[1])
self.assertEqual(f1, population[index_pop].F[0])
self.assertEqual(f2, population[index_pop].F[1])
index_pop += 1
f.close()
os.remove("test_save_population.txt")
def test_save_population_full(self):
"""test the function to save the population with all decision variables"""
population = []
for i in range(10):
population.append(self.rmnk.generate_random_solution())
save_population_full("test_save_population_full.txt", population)
f = open("test_save_population_full.txt", "r")
index_pop = 0
for line in f:
f1 = float(
line.replace("\n", "").replace(" ", "_", 2).split("_")[0])
f2 = float(
line.replace("\n", "").replace(" ", "_", 2).split("_")[1])
solution = line.replace("\n", "").replace(" ", "_",
2).split("_")[2]
self.assertEqual(f1, population[index_pop].F[0])
self.assertEqual(f2, population[index_pop].F[1])
self.assertEqual(solution,
str(population[index_pop].solution.tolist()))
index_pop += 1
f.close()
os.remove("test_save_population_full.txt")
