def test_should_the_operator_work_with_a_solution_with_three_binary_variables(
self, random_call):
operator = SPXCrossover(1.0)
solution1 = BinarySolution(number_of_variables=3,
number_of_objectives=1)
solution1.variables[0] = [True, False, False, True, True, False]
solution1.variables[1] = [True, False, False, True, False, False]
solution1.variables[2] = [True, False, True, True, True, True]
solution2 = BinarySolution(number_of_variables=3,
number_of_objectives=1)
solution2.variables[0] = [False, True, False, False, True, True]
solution2.variables[1] = [True, True, False, False, True, False]
solution2.variables[2] = [True, True, True, False, False, True]
random_call.return_value = 8
offspring = operator.execute([solution1, solution2])
self.assertEqual([True, False, False, True, True, False],
offspring[0].variables[0])
self.assertEqual([True, False, False, False, True, False],
offspring[0].variables[1])
self.assertEqual([True, True, True, False, False, True],
offspring[0].variables[2])
self.assertEqual([False, True, False, False, True, True],
offspring[1].variables[0])
self.assertEqual([True, True, False, True, False, False],
offspring[1].variables[1])
self.assertEqual([True, False, True, True, True, True],
offspring[1].variables[2])
def test_should_the_solution_remain_unchanged_if_the_probability_is_zero(self):
operator = SPXCrossover(0.0)
solution1 = BinarySolution(number_of_variables=1, number_of_objectives=1)
solution1.variables[0] = [True, False, False, True, True, False]
solution2 = BinarySolution(number_of_variables=1, number_of_objectives=1)
solution2.variables[0] = [False, True, False, False, True, False]
offspring = operator.execute([solution1, solution2])
self.assertEqual([True, False, False, True, True, False], offspring[0].variables[0])
self.assertEqual([False, True, False, False, True, False], offspring[1].variables[0])
def test_should_the_operator_work_if_the_third_bit_is_selected(self, random_call):
operator = SPXCrossover(1.0)
solution1 = BinarySolution(number_of_variables=1, number_of_objectives=1)
solution1.variables[0] = [True, False, False, True, True, False]
solution2 = BinarySolution(number_of_variables=1, number_of_objectives=1)
solution2.variables[0] = [False, True, False, False, True, True]
random_call.return_value = 3
offspring = operator.execute([solution1, solution2])
self.assertEqual([True, False, False, False, True, True], offspring[0].variables[0])
self.assertEqual([False, True, False, True, True, False], offspring[1].variables[0])
def setUp(self):
self.solution_a = BinarySolution(number_of_objectives=1,
number_of_variables=1,
initial_energy=20)
self.solution_b = FloatSolution(lower_bound=[0.1],
upper_bound=[0.5],
number_of_objectives=1,
initial_energy=40)
self.solution_c = BinarySolution(number_of_objectives=1,
number_of_variables=1,
initial_energy=30)
self.solutions = [self.solution_a, self.solution_b, self.solution_c]
def test_should_the_solution_remain_unchanged(self):
operator = Null()
solution1 = BinarySolution(number_of_variables=1,
number_of_objectives=1)
solution1.variables[0] = [True, False, False, True, True, False]
solution2 = BinarySolution(number_of_variables=1,
number_of_objectives=1)
solution2.variables[0] = [False, True, False, False, True, False]
offspring = operator.execute([solution1, solution2])
self.assertEqual([True, False, False, True, True, False],
offspring[0].variables[0])
self.assertEqual([False, True, False, False, True, False],
offspring[1].variables[0])
def setUp(self) -> None:
self.solution_a = BinarySolution(number_of_objectives=1,
number_of_variables=1,
initial_energy=20)
self.solution_b = FloatSolution(lower_bound=[0.1],
upper_bound=[0.5],
number_of_objectives=1,
initial_energy=40)
self.solution_c = BinarySolution(number_of_objectives=1,
number_of_variables=2,
initial_energy=30)
self.solution_d = BinarySolution(number_of_objectives=1,
number_of_variables=2,
initial_energy=30)
self.neighbours_operator = RandomNeighbours(seed=1)
def create_solution(self) -> BinarySolution:
new_solution = BinarySolution(number_of_variables=1,
number_of_objectives=1)
new_solution.variables[0] = \
[True if random.randint(0, 1) == 0 else False for _ in range(self.number_of_bits)]
return new_solution
def test_should_the_solution_remain_unchanged_if_the_probability_is_zero(self):
operator = BitFlip(0.0)
solution = BinarySolution(number_of_variables=1, number_of_objectives=1)
solution.variables[0] = [True, True, False, False, True, False]
mutated_solution = operator.execute(solution)
self.assertEqual([True, True, False, False, True, False], mutated_solution.variables[0])
def test_should_get_total_number_of_bits_return_the_right_value(
self) -> None:
solution = BinarySolution(number_of_variables=2,
number_of_objectives=3)
solution.variables[0] = [True, False]
solution.variables[1] = [False, True, False]
self.assertEqual(5, solution.get_total_number_of_bits())
def create_solution(self) -> BinarySolution:
new_solution = BinarySolution(number_of_variables=3,
number_of_objectives=1)
new_solution.variables[0] = [
random.randint(0, self.number_of_variables)
for _ in range(self.number_of_bits)
]
return new_solution
def generate_existing_solution(self, variables: str) -> BinarySolution:
new_solution = BinarySolution(
number_of_variables=self.number_of_variables,
number_of_objectives=self.number_of_objectives)
new_solution.variables[0] = \
[True if variables[_] == '1' else False for _ in range(
self.number_of_bits)]
self.evaluate(new_solution)
return new_solution
def test_should_the_solution_change_all_the_bits_if_the_probability_is_one(self):
operator = BitFlip(1.0)
solution = BinarySolution(number_of_variables=2, number_of_objectives=1)
solution.variables[0] = [True, True, False, False, True, False]
solution.variables[1] = [False, True, True, False, False, True]
mutated_solution = operator.execute(solution)
self.assertEqual([False, False, True, True, False, True], mutated_solution.variables[0])
self.assertEqual([True, False, False, True, True, False], mutated_solution.variables[1])
def create_from_string(self, variables: str) -> BinarySolution:
new_solution = BinarySolution(
number_of_variables=self.number_of_variables,
number_of_objectives=self.number_of_objectives)
new_solution.variables[0] = \
[True if variables[_] == '1' else False for _ in range(
self.number_of_bits)]
return new_solution
def setUp(self):
self.solution_a = BinarySolution(number_of_objectives=1,
number_of_variables=1,
initial_energy=20)
self.solution_a.objectives = [-50.] # solution_a is worse
self.solution_b = FloatSolution(lower_bound=[0.1],
upper_bound=[0.5],
number_of_objectives=1,
initial_energy=40)
self.solution_b.objectives = [-100.] # solution_b is better
def test_should_constructor_create_a_valid_solution(self) -> None:
solution = BinarySolution(number_of_variables=2, number_of_objectives=3)
solution.variables[0] = [True, False]
solution.variables[1] = [False]
self.assertEqual(2, solution.number_of_variables)
self.assertEqual(3, solution.number_of_objectives)
self.assertEqual(2, len(solution.variables))
self.assertEqual(3, len(solution.objectives))
self.assertEqual([True, False], solution.variables[0])
self.assertEqual([False], solution.variables[1])
def create_solution(self) -> BinarySolution: solution = BinarySolution( self.number_of_variables, self.number_of_objectives ) notes = [np.random.choice(self.note_candidates[i]) for i in range(self.number_of_notes)] solution.variables[0] = notes solution.variables[1] = self.note_candidates return solution
def create_solution(self):
sol = BinarySolution(number_of_variables=2, number_of_objectives=4)
sol.variables[0] = [
True if random.randint(0, 1) == 0 else False
for _ in range(self.instances)
]
sol.variables[1] = [
True if random.randint(0, 1) == 0 else False
for _ in range(self.attributes)
]
return sol
def create_solution(self):
new_solution = BinarySolution(
number_of_variables=self.number_of_variables,
number_of_objectives=self.number_of_objectives)
new_solution.variables[0] = [
True if random.randint(0, 1) == 0 else False
for _ in range(self.instances)
]
new_solution.variables[1] = [
True if random.randint(0, 1) == 0 else False
for _ in range(self.attributes)
]
return new_solution
def __HYPE(self) -> None:
reference_point = BinarySolution(self.__problem.number_of_variables, self.__problem.number_of_objectives, self.__problem.number_of_constraints)
reference_point.objectives = [1.0 for _ in range(self.__problem.number_of_objectives)]
self.__solver = HYPE(
problem=self.__problem,
reference_point=reference_point,
population_size=POPULATION_SIZE,
offspring_population_size=OFFSPRING_SIZE,
#mutation=BitFlipMutation(probability=1.0/self.__problem.number_of_variables),
mutation=BitFlipMutation(probability=0.035),
crossover=SPXCrossover(probability=1.0),
termination_criterion=StoppingByEvaluations(max_evaluations=MAX_EVALUATION)
)
def create_solution(self) -> BinarySolution:
random.seed(123)
new_solution = BinarySolution(
number_of_variables=self.number_of_variables,
number_of_objectives=self.number_of_objectives,
)
new_solution.variables[0] = [
True if random.randint(0, 1) == 0 else False
for _ in range(self.number_of_tests)
]
return new_solution
def test_should_execute_raise_and_exception_if_the_types_of_the_solutions_do_not_match_the_operators(
self):
operator = CompositeMutation(
[PolynomialMutation(1.0, 5.0),
PolynomialMutation(0.9, 25.0)])
float_solution = FloatSolution([2.0], [3.9], 3)
binary_solution = BinarySolution(1, 3, 0)
float_solution.variables = [3.0]
composite_solution = CompositeSolution(
[float_solution, binary_solution])
with self.assertRaises(InvalidConditionException):
operator.execute(composite_solution)
def create_solution(self) -> BinarySolution:
new_solution = BinarySolution(
number_of_variables=self.number_of_variables,
number_of_objectives=self.number_of_objectives)
new_solution.variables[0] = []
budget = Interval(0)
random.shuffle(self.positions)
new_solution.variables[0] = self.number_of_bits * [False]
for v in self.positions:
tmp = budget + self.instance_.projects[v][0]
poss = self.budget.poss_greater_than_or_eq(tmp)
if poss >= self.get_preference_model(0).chi:
new_solution.variables[0][v] = True
budget = tmp
return new_solution
def test_should_get_total_number_of_bits_return_zero_if_the_object_variables_are_not_initialized(self) -> None:
solution = BinarySolution(number_of_variables=2, number_of_objectives=3)
self.assertEqual(0, solution.get_total_number_of_bits())
def create_solution(self) -> BinarySolution:
new_solution = BinarySolution(self.number_of_variables, self.number_of_objectives, self.number_of_constraints)
new_solution.variables = \
[self.sf.get_random_individual() for i in range(self.number_of_variables)]
return new_solution
def test_should_default_constructor_create_a_valid_solution(self) -> None:
solution = BinarySolution(2, 3)
self.assertEqual(2, solution.number_of_variables)
self.assertEqual(3, solution.number_of_objectives)
