def test_mutation_called_based_on_mutation_factor(self):
self.mutation_factor = 1
self.neighborhood_calc = NeighborhoodWithOtherRepresentations(
self.number_of_activations, self.mutation_neighborhood,
self.mutation_factor, self.natural_process)
first_rep = (1, 3, 5)
second_rep = (2, 4, 6)
self.neighborhood_calc.get_neighborhood(first_rep, second_rep)
self.assertEqual(
self.number_of_activations, self.mutation_neighborhood.
get_neighborhood_of_representation.call_count)
class TestNeighborhoodWithPopulation(unittest.TestCase):
def setUp(self):
self.number_of_activations = 2
self.mutation_neighborhood = Mock()
self.natural_process = Mock()
def return_itself(*args):
return args[0]
self.mutation_neighborhood.get_neighborhood_of_representation.side_effect = return_itself
self.natural_process.get_a_mutation_from_the_reps.side_effect = return_itself
def test_no_mutation(self):
self.mutation_factor = 0
self.neighborhood_calc = NeighborhoodWithOtherRepresentations(
self.number_of_activations, self.mutation_neighborhood,
self.mutation_factor, self.natural_process)
first_rep = (1, 3, 5)
second_rep = (2, 4, 6)
self.neighborhood_calc.get_neighborhood(first_rep, second_rep)
self.assertEqual(
0, self.mutation_neighborhood.get_neighborhood_of_representation.
call_count)
def test_mutation_called_based_on_mutation_factor(self):
self.mutation_factor = 1
self.neighborhood_calc = NeighborhoodWithOtherRepresentations(
self.number_of_activations, self.mutation_neighborhood,
self.mutation_factor, self.natural_process)
first_rep = (1, 3, 5)
second_rep = (2, 4, 6)
self.neighborhood_calc.get_neighborhood(first_rep, second_rep)
self.assertEqual(
self.number_of_activations, self.mutation_neighborhood.
get_neighborhood_of_representation.call_count)
def test_no_mutation(self):
self.mutation_factor = 0
self.neighborhood_calc = NeighborhoodWithOtherRepresentations(
self.number_of_activations, self.mutation_neighborhood, self.mutation_factor, self.natural_process
)
first_rep = (1, 3, 5)
second_rep = (2, 4, 6)
self.neighborhood_calc.get_neighborhood(first_rep, second_rep)
self.assertEqual(0, self.mutation_neighborhood.get_neighborhood_of_representation.call_count)
class TestNeighborhoodWithPopulation(unittest.TestCase):
def setUp(self):
self.number_of_activations = 2
self.mutation_neighborhood = Mock()
self.natural_process = Mock()
def return_itself(*args):
return args[0]
self.mutation_neighborhood.get_neighborhood_of_representation.side_effect = return_itself
self.natural_process.get_a_mutation_from_the_reps.side_effect = return_itself
def test_no_mutation(self):
self.mutation_factor = 0
self.neighborhood_calc = NeighborhoodWithOtherRepresentations(
self.number_of_activations, self.mutation_neighborhood, self.mutation_factor, self.natural_process
)
first_rep = (1, 3, 5)
second_rep = (2, 4, 6)
self.neighborhood_calc.get_neighborhood(first_rep, second_rep)
self.assertEqual(0, self.mutation_neighborhood.get_neighborhood_of_representation.call_count)
def test_mutation_called_based_on_mutation_factor(self):
self.mutation_factor = 1
self.neighborhood_calc = NeighborhoodWithOtherRepresentations(
self.number_of_activations, self.mutation_neighborhood, self.mutation_factor, self.natural_process
)
first_rep = (1, 3, 5)
second_rep = (2, 4, 6)
self.neighborhood_calc.get_neighborhood(first_rep, second_rep)
self.assertEqual(
self.number_of_activations, self.mutation_neighborhood.get_neighborhood_of_representation.call_count
)
def recombination_main():
common_classes = CommonClassesCreator()
length, epsilon, mutation_neighborhood, tolerance = common_classes.get_common_classes(
)
mutation_factor = 0.1
concept_class = MonotoneConjunction(length)
performance = common_classes.get_perf_without_precomp(concept_class)
recomb_process = RecombinationProcess()
neighborhood = NeighborhoodWithOtherRepresentations(
length, mutation_neighborhood, mutation_factor, recomb_process)
recombinator = Recombinator(neighborhood, performance, tolerance, epsilon)
recombination = RecombinationConjunctionAlgorithm(recombinator, length,
epsilon, concept_class)
recombination.learn_ideal_function(concept_class)
def learn_DNF__HGT():
dnf = DNF()
length = 58
epsilon = (2**-53)
tau = (epsilon / length)**3 * log(1/epsilon)
tolerance = ConjunctionTolerance(length, epsilon)
conjunction_performance_oracle = OneSidedPerformanceOracleWithTolerance(dnf, tau)
performance_oracle = DNFOneSidePerformanceOracleWithTolerance(dnf, tau, epsilon,
conjunction_performance_oracle)
mutation_neighborhood = MonotoneConjunctionNeighborhood()
natural_process = HGTProcess(0.35, length)
neighborhood = NeighborhoodWithOtherRepresentations(length, mutation_neighborhood,
0.1, natural_process)
HGT_mutator = HGT_Mutator(neighborhood, performance_oracle, tolerance, epsilon, natural_process)
algorithm = ConstantPopulationMutationConjunctionAlgorithm(HGT_mutator, length, epsilon, performance_oracle, 75)
print algorithm.learn_ideal_function_until_match()
def HGT_main():
common_classes = CommonClassesCreator()
length, epsilon, mutation_neighborhood, tolerance = common_classes.get_common_classes(
)
mutation_factor = 0.1
HGT_factor = 1
concept_class = MonotoneConjunction(length)
performance = common_classes.get_perf_without_precomp(concept_class)
HGT_process = HGTProcess(HGT_factor, length)
neighborhood = NeighborhoodWithOtherRepresentations(
length, mutation_neighborhood, mutation_factor, HGT_process)
HGT_mutator = HGT_Mutator(neighborhood, performance, tolerance, epsilon,
HGT_process)
mutation = HGTConjunctionAlgorithm(HGT_mutator, length, epsilon,
performance)
final_population = mutation.learn_ideal_function(concept_class)
if len(final_population) <= 30:
print final_population
def get_neighborhood_with_other_representations(self, mutation_factor):
return NeighborhoodWithOtherRepresentations(self.number_of_mutations_from_mutator,
self.mutation_neighborhood,
mutation_factor, self.natural_process)
