def test_parameter_controls_mutate_hoist(self):
# save and restore original configuration
with saved(Config.get_instance()):
Config.get_instance().set("POPULATION", "controls", "5")
individual = Individual(
'(root (/ (exp (/ 8.2118 S0)) (* (* S0 (* 1.6755 -0.0699)) (log (exp -3.2288)))) (* (+ (sin -9.8591) (exp S0)) -9.4159) 0.0290 (* (log (* (+ -5.0573 -6.2191) S0)) (/ (cos (log S0)) (cos (tanh 2.2886)))) (log -8.6795))'
)
new_ind = individual.mutate(Individual.MutationType.HOIST)
self.assertEqual(
new_ind.get_value(),
"(root (log (exp -3.2288)) (* (+ (sin -9.8591) (exp S0)) -9.4159) 0.0290 (* (log (* (+ -5.0573 -6.2191) S0)) (/ (cos (log S0)) (cos (tanh 2.2886)))) (log -8.6795))"
)
new_ind = individual.mutate(Individual.MutationType.HOIST)
self.assertEqual(
new_ind.get_value(),
"(root (/ (exp (/ 8.2118 S0)) (* (* S0 (* 1.6755 -0.0699)) (log (exp -3.2288)))) (exp S0) 0.0290 (* (log (* (+ -5.0573 -6.2191) S0)) (/ (cos (log S0)) (cos (tanh 2.2886)))) (log -8.6795))"
)
new_ind = individual.mutate(Individual.MutationType.HOIST)
self.assertEqual(
new_ind.get_value(),
"(root (* S0 (* 1.6755 -0.0699)) (* (+ (sin -9.8591) (exp S0)) -9.4159) 0.0290 (* (log (* (+ -5.0573 -6.2191) S0)) (/ (cos (log S0)) (cos (tanh 2.2886)))) (log -8.6795))"
)
def test_set_custom_gen_creator(self):
with saved(Config.get_instance()) as config:
Config.get_instance().set("POPULATION", "size", "5")
Config.get_instance().set("BEHAVIOUR", "save", "false")
from MLC.Population.Creation.BaseCreation import BaseCreation
from MLC.individual.Individual import Individual
class TestCreator(BaseCreation):
def __init__(self):
BaseCreation.__init__(self)
def create(self, gen_size):
MLCRepository.get_instance().add_individual(
Individual("(root 1)"))
MLCRepository.get_instance().add_individual(
Individual("(root 2)"))
MLCRepository.get_instance().add_individual(
Individual("(root 3)"))
MLCRepository.get_instance().add_individual(
Individual("(root 4)"))
MLCRepository.get_instance().add_individual(
Individual("(root 5)"))
def individuals(self):
return [(0, 1), (1, 2), (2, 3), (3, 4), (4, 5)]
simulation = Simulation("")
mlc = Application(simulation, gen_creator=TestCreator())
mlc.go(to_generation=1)
# Assert first Population was filled using the TestCreator
population = MLCRepository.get_instance().get_population(1)
self.assertEqual(population.get_individuals(), [1, 2, 3, 4, 5])
def test_list_of_callbacks(self):
with saved(Config.get_instance()) as config:
Config.get_instance().set("POPULATION", "size", "10")
Config.get_instance().set("BEHAVIOUR", "save", "false")
ApplicationTest.on_start = 0
ApplicationTest.on_start_counter_2 = 0
def test_on_start_callback():
ApplicationTest.on_start += 1
def test_on_start_callback_increment_2():
ApplicationTest.on_start_counter_2 += 1
start_callbacks = [
test_on_start_callback, test_on_start_callback_increment_2
]
ApplicationTest.mlc_local.new_experiment(
ApplicationTest.experiment_name,
ApplicationTest.test_conf_path)
ApplicationTest.mlc_local.open_experiment(
ApplicationTest.experiment_name)
ApplicationTest.mlc_local.go(
experiment_name=ApplicationTest.experiment_name,
to_generation=2,
from_generation=0,
callbacks={MLC_CALLBACKS.ON_START: start_callbacks})
ApplicationTest.mlc_local.close_experiment(
ApplicationTest.experiment_name)
ApplicationTest.mlc_local.delete_experiment(
ApplicationTest.experiment_name)
self.assertEqual(ApplicationTest.on_start, 1)
self.assertEqual(ApplicationTest.on_start_counter_2, 1)
def test_reload_individuals_from_file(self):
with saved(Config.get_instance()) as config:
config.set("BEHAVIOUR", "save", "true")
config.set("BEHAVIOUR", "savedir", "test.db")
config.set("POPULATION", "sensor_spec", "false")
config.set("POPULATION", "sensors", "0")
config.set("OPTIMIZATION", "simplify", "false")
mlc_repo = self.__get_new_repo()
# add individuals
mlc_repo.add_individual(Individual("(root (+ 1 1))"))
mlc_repo.add_individual(Individual("(root (+ 2 2))"))
# add population
p = Population(3, 0, Config.get_instance(), mlc_repo)
p._individuals = [2, 1, 2]
mlc_repo.add_population(p)
# check status
self.assertEqual(mlc_repo.count_individual(), 2)
self.assertEqual(mlc_repo.count_population(), 1)
# reload mlc_repository using another instance
mlc_repo = self.__get_new_repo()
self.assertEqual(mlc_repo.count_individual(), 2)
self.assertEqual(mlc_repo.count_population(), 1)
def __fill_and_assert(self, fill_creator, expected_pop_indexes,
expected_individuals):
with saved(Config.get_instance()) as config:
Config.get_instance().set("POPULATION", "size", "5")
Config.get_instance().set("BEHAVIOUR", "save", "false")
from MLC.Log.log import set_logger
set_logger('testing')
population = Population(5, 0, Config.get_instance(),
MLCRepository.make(""))
population.fill(fill_creator)
MLCRepository.get_instance().add_population(population)
# Assert that one Population was added
self.assertEqual(MLCRepository.get_instance().count_population(),
1)
# Assert that the individuals are in the expected position inside the Population
for position, i in enumerate(expected_pop_indexes):
expected_individual = expected_individuals[i]
inserted_individual_id = population.get_individuals()[position]
inserted_individual = MLCRepository.get_instance(
).get_individual(inserted_individual_id)
self.assertEqual(expected_individual.get_value(),
inserted_individual.get_value())
def test_sensor_list(self):
# save and restore original configuration
with saved(Config.get_instance()):
Config.get_instance().set("POPULATION", "sensor_list",
"6,15,2,8,4,10")
Config.get_instance().set("POPULATION", "sensors", "6")
Config.get_instance().set("POPULATION", "sensor_spec", "true")
Config.get_instance().set("POPULATION", "sensor_prob", "1.0")
# test generate and mutate using sensor list
individual = Individual.generate(individual_type=3,
config=Config.get_instance())
self.assertEqual(
individual.get_value(),
'(root (sin (/ (+ (exp S6) (cos S10)) (/ (log S10) (log S4)))))'
)
individual = Individual.generate(individual_type=3,
config=Config.get_instance())
self.assertEqual(
individual.get_value(),
'(root (exp (* (- (tanh S6) (tanh S10)) (- (/ S6 S6) (/ S6 S4)))))'
)
new_ind = self._individual_l2.mutate(
Individual.MutationType.REMOVE_SUBTREE_AND_REPLACE)
self.assertEqual(
individual.get_value(),
'(root (exp (* (- (tanh S6) (tanh S10)) (- (/ S6 S6) (/ S6 S4)))))'
)
new_ind = self._individual_l2.mutate(
Individual.MutationType.REMOVE_SUBTREE_AND_REPLACE)
self.assertEqual(
individual.get_value(),
'(root (exp (* (- (tanh S6) (tanh S10)) (- (/ S6 S6) (/ S6 S4)))))'
)
new_ind = self._individual_l2.mutate(
Individual.MutationType.SHRINK)
self.assertEqual(
individual.get_value(),
'(root (exp (* (- (tanh S6) (tanh S10)) (- (/ S6 S6) (/ S6 S4)))))'
)
new_ind = self._individual_l2.mutate(
Individual.MutationType.SHRINK)
self.assertEqual(
individual.get_value(),
'(root (exp (* (- (tanh S6) (tanh S10)) (- (/ S6 S6) (/ S6 S4)))))'
)
def test_callback_on_evaluate(self):
with saved(Config.get_instance()) as config:
Config.get_instance().set("POPULATION", "size", "10")
Config.get_instance().set("BEHAVIOUR", "save", "false")
def test_on_start_callback():
ApplicationTest.on_start += 1
def test_on_evaluate_callback(individual_id, cost):
ApplicationTest.on_evaluate += 1
def test_on_new_generation_callback(generation_number):
ApplicationTest.on_new_generation.append(generation_number)
def test_on_finish_callback():
ApplicationTest.on_finish += 1
callbacks_dict = {
MLC_CALLBACKS.ON_START: test_on_start_callback,
MLC_CALLBACKS.ON_EVALUATE: test_on_evaluate_callback,
MLC_CALLBACKS.ON_NEW_GENERATION:
test_on_new_generation_callback,
MLC_CALLBACKS.ON_FINISH: test_on_finish_callback
}
ApplicationTest.mlc_local.new_experiment(
ApplicationTest.experiment_name,
ApplicationTest.test_conf_path)
ApplicationTest.mlc_local.open_experiment(
ApplicationTest.experiment_name)
ApplicationTest.mlc_local.go(
experiment_name=ApplicationTest.experiment_name,
to_generation=2,
from_generation=0,
callbacks=callbacks_dict)
ApplicationTest.mlc_local.close_experiment(
ApplicationTest.experiment_name)
ApplicationTest.mlc_local.delete_experiment(
ApplicationTest.experiment_name)
self.assertEqual(ApplicationTest.on_start, 1)
self.assertEqual(ApplicationTest.on_evaluate, 2 * 10)
self.assertEqual(ApplicationTest.on_new_generation,
range(1, 2 + 1))
self.assertEqual(ApplicationTest.on_finish, 1)
def test_parameter_controls_generate(self):
# save and restore original configuration
with saved(Config.get_instance()):
# random generation
Config.get_instance().set("POPULATION", "controls", "3")
individual = Individual.generate(individual_type=2,
config=Config.get_instance())
self.assertEqual(
individual.get_value(),
'(root (/ -3.0632 (cos -3.0973)) (exp (log (* (* S0 -0.8182) (sin -6.5057)))) (/ (/ -1.4169 (/ (* S0 S0) (cos -7.5988))) (log (cos (* S0 5.7489)))))'
)
formal_exp = individual.get_formal()
self.assertIsInstance(formal_exp, list)
self.assertEqual(len(formal_exp), 3)
self.assertEqual(formal_exp[0],
'(my_div((-3.0632),cos((-3.0973))))')
self.assertEqual(
formal_exp[1],
'exp(my_log(((S0 .* (-0.8182)) .* sin((-6.5057)))))')
self.assertEqual(
formal_exp[2],
'(my_div((my_div((-1.4169),(my_div((S0 .* S0),cos((-7.5988)))))),my_log(cos((S0 .* 5.7489)))))'
)
self.assertEqual(individual.get_complexity(), 46)
# generate individual with one control
Config.get_instance().set("POPULATION", "controls", "1")
individual = Individual("(root (cos (- 5.0161 (sin (log S0)))))",
Config.get_instance())
self.assertIsInstance(individual.get_formal(), str)
self.assertEqual(individual.get_formal(),
'cos((5.0161 - sin(my_log(S0))))')
self.assertEqual(individual.get_complexity(), 14)
# generate individual with 3 controls
Config.get_instance().set("POPULATION", "controls", "3")
individual = Individual(
'(root (exp 2.1314) (* (+ (sin -9.8591) (exp S0)) -9.4159) (exp (/ (/ 8.0187 -8.5969) S0)))',
Config.get_instance())
formal_exp = individual.get_formal()
self.assertIsInstance(formal_exp, list)
self.assertEqual(len(formal_exp), 3)
self.assertEqual(formal_exp[0], 'exp(2.1314)')
self.assertEqual(formal_exp[1],
'((sin((-9.8591)) + exp(S0)) .* (-9.4159))')
self.assertEqual(formal_exp[2],
'exp((my_div((my_div(8.0187,(-8.5969))),S0)))')
self.assertEqual(individual.get_complexity(), 29)
# generate individual with 5 controls
Config.get_instance().set("POPULATION", "controls", "5")
individual = Individual(
'(root (/ (exp (/ 8.2118 S0)) (* (* S0 (* 1.6755 -0.0699)) (log (exp -3.2288)))) S0 0.0290 (* (log (* (+ -5.0573 -6.2191) S0)) (/ (cos (log S0)) (cos (tanh 2.2886)))) (log -8.6795))',
Config.get_instance())
formal_exp = individual.get_formal()
self.assertIsInstance(formal_exp, list)
self.assertEqual(len(formal_exp), 5)
self.assertEqual(
formal_exp[0],
'(my_div(exp((my_div(8.2118,S0))),((S0 .* (1.6755 .* (-0.0699))) .* my_log(exp((-3.2288))))))'
)
self.assertEqual(formal_exp[1], 'S0')
self.assertEqual(formal_exp[2], '0.0290')
self.assertEqual(
formal_exp[3],
'(my_log((((-5.0573) + (-6.2191)) .* S0)) .* (my_div(cos(my_log(S0)),cos(tanh(2.2886)))))'
)
self.assertEqual(formal_exp[4], 'my_log((-8.6795))')
self.assertEqual(individual.get_complexity(), 64)
# generate individual with multiple simplifications
Config.get_instance().set("POPULATION", "controls", "3")
Config.get_instance().set("OPTIMIZATION", "simplify", "true")
individual = Individual(
'(root (exp 2.1314) (* (+ (sin -9.8591) (exp S0)) -9.4159) (exp (/ (/ 8.0187 -8.5969) S0)))',
Config.get_instance())
formal_exp = individual.get_formal()
self.assertIsInstance(formal_exp, list)
self.assertEqual(len(formal_exp), 3)
self.assertEqual(formal_exp[0], 'exp(2.1314)')
self.assertEqual(formal_exp[1],
'((sin((-9.8591)) + exp(S0)) .* (-9.4159))')
self.assertEqual(formal_exp[2],
'exp((my_div((my_div(8.0187,(-8.5969))),S0)))')