def test_validate(self):
crossover_operator = StringCrossover(Probability(1), Random(), 1)
candidate1 = Candidate()
candidate1.data = 'AAAA'
candidate2 = Candidate()
candidate2.data = 'BBBB'
crossover_operator.validate_parents(candidate1, candidate2)
candidate2.data = 'BBBBB'
with self.assertRaises(ValidationException):
crossover_operator.validate_parents(candidate1, candidate2)
def test_validate(self):
crossover_operator = ListCrossover(Probability(1), Random(), 1)
candidate1 = Candidate()
candidate1.data = [1, 2, 3, 4]
candidate2 = Candidate()
candidate2.data = [5, 6, 7, 8]
crossover_operator.validate_parents(candidate1, candidate2)
candidate2.data = [1, 2, 3, 4, 5]
with self.assertRaises(ValidationException):
crossover_operator.validate_parents(candidate1, candidate2)
def _test_apply(self, strings, random, points):
candidate1 = Candidate()
candidate1.data = strings[0][0]
candidate2 = Candidate()
candidate2.data = strings[0][1]
crossover_points = points
crossover_operator = ListCrossover(Probability(1), random, crossover_points)
result = crossover_operator.mate(candidate1, candidate2)
self.assertEqual(len(result), 2)
self.assertEqual(result[0].data, strings[1][0])
self.assertEqual(result[1].data, strings[1][1])
def test_apply(self):
candidate1 = Candidate()
candidate1.data = [1, 2, 3, 4, 5, 6, 7, 8, 9]
candidate2 = Candidate()
candidate2.data = [9, 3, 7, 8, 2, 6, 5, 1, 4]
random = Random()
random.int = MagicMock(side_effect=[3, 7])
crossover_operator = ListOrderCrossover(Probability(1), random)
result = crossover_operator.mate(candidate1, candidate2)
self.assertEqual(len(result), 2)
self.assertEqual(result[0].data, [1, 7, 3, 8, 2, 6, 5, 4, 9])
self.assertEqual(result[1].data, [9, 3, 2, 4, 5, 6, 7, 1, 8])
def _test_get_fitness(self, target, inputs, score):
candidate = Candidate()
candidate.data = inputs
population = Population()
population.append(candidate)
fitness_evaluator = StringFitnessEvaluator(target)
result = fitness_evaluator.get_fitness(candidate, population)
self.assertIsInstance(result, Fitness)
self.assertEqual(result, score)
def test_apply(self):
candidate = Candidate()
candidate.data = [1, 2, 3, 4]
population = Population([candidate])
probability = Probability(1)
random = Random()
random.int = MagicMock(side_effect=[1, 3])
crossover_operator = ListOrderMutation(probability, random, 1)
result = crossover_operator.apply(population)
self.assertEqual(len(result), len(population))
self.assertEqual(result[0].data, [1, 4, 3, 2])
def test_apply_zero(self):
inputs, outputs = ('aaaa', 'aaaa')
candidate = Candidate()
candidate.data = inputs
population = Population()
population.append(candidate)
probability = Probability(0)
random = Random()
mutation_operator = BitStringMutation(probability, random)
result = mutation_operator.apply(population)
self.assertEqual(len(result), len(population))
self.assertEqual(result[0].data, outputs)
def test_apply_zero(self):
alphabet = 'abcd'
inputs, outputs = ('aaaa', 'aaaa')
candidate = Candidate()
candidate.data = inputs
population = Population()
population.append(candidate)
probability = Probability(0)
random = Random()
crossover_operator = StringMutation(probability, random, alphabet)
result = crossover_operator.apply(population)
self.assertEqual(len(result), len(population))
self.assertEqual(result[0].data, outputs)
def test_apply_one(self):
inputs, outputs = ('0110', '1010')
candidate = Candidate()
candidate.data = inputs
population = Population()
population.append(candidate)
probability = Probability(1)
random = Random()
random.float = MagicMock(side_effect=[0.6, 0.1, 0.9, 0.4])
mutation_operator = BitStringMutation(probability, random)
result = mutation_operator.apply(population)
self.assertEqual(len(result), len(population))
self.assertEqual(result[0].data, outputs)
def test_apply_one(self):
alphabet = 'abcd'
inputs, outputs = ('aaaa', 'abcd')
candidate = Candidate()
candidate.data = inputs
population = Population()
population.append(candidate)
probability = Probability(1)
random = Random()
random.choice = MagicMock(side_effect=['a', 'b', 'c', 'd'])
crossover_operator = StringMutation(probability, random, alphabet)
result = crossover_operator.apply(population)
self.assertEqual(len(result), len(population))
self.assertEqual(result[0].data, outputs)
