def test_obtain_configuration_from_a_closed_experiment(self):
try:
mlc = MLCLocal(working_dir=MLCWorkspaceTest.WORKSPACE_DIR)
mlc.get_experiment_configuration(MLCWorkspaceTest.ORIGINAL_EXPERIMENT)
self.assertTrue(False, "Configuration from a closed experiment should not be obtained")
except MLC.api.mlc.ClosedExperimentException:
self.assertTrue(True)
def test_open_invalid_experiment(self):
try:
mlc = MLCLocal(working_dir=MLCWorkspaceTest.WORKSPACE_DIR)
mlc.open_experiment("invalid_name")
self.assertTrue(False)
except MLC.api.mlc.ExperimentNotExistException:
self.assertTrue(True)
def test_create_duplicated_experiment(self):
try:
mlc = MLCLocal(working_dir=MLCWorkspaceTest.WORKSPACE_DIR)
mlc.new_experiment(MLCWorkspaceTest.ORIGINAL_EXPERIMENT,
MLCWorkspaceTest.ORIGINAL_CONFIGURATION)
self.assertTrue(False)
except MLC.api.mlc.DuplicatedExperimentError:
self.assertTrue(True)
def test_get_info_empty_simulation(self):
mlc = MLCLocal(working_dir=MLCWorkspaceTest.WORKSPACE_DIR)
mlc.open_experiment(MLCWorkspaceTest.ORIGINAL_EXPERIMENT)
info = mlc.get_experiment_info(MLCWorkspaceTest.ORIGINAL_EXPERIMENT)
self._assert_key_value(info, "name", MLCWorkspaceTest.ORIGINAL_EXPERIMENT)
self._assert_key_value(info, "generations", 0)
self._assert_key_value(info, "individuals", 0)
self._assert_key_value(info, "individuals_per_generation", 10)
mlc.close_experiment(MLCWorkspaceTest.ORIGINAL_EXPERIMENT)
mlc.delete_experiment(MLCWorkspaceTest.ORIGINAL_EXPERIMENT)
def test_import_non_existent_experiment(self):
mlc = MLCLocal(working_dir=MLCWorkspaceTest.WORKSPACE_DIR)
import_experiment_path = os.path.join(os.path.dirname(os.path.abspath(__file__)),
"test4.mlc")
mlc.import_experiment(import_experiment_path)
self.assertTrue("test4" in mlc.get_workspace_experiments())
mlc.delete_experiment("test4")
def setUpClass(cls):
config_file = os.path.join(MLCIntegrationTest.TEST_DIRECTORY,
'./configuration.ini')
ev_script = os.path.join(MLCIntegrationTest.TEST_DIRECTORY,
'./default_evaluation_script.py')
preev_script = os.path.join(MLCIntegrationTest.TEST_DIRECTORY,
'./default_preevaluation_script.py')
# Load the config
config = Config.get_instance()
config.read(config_file)
# Load randoms from file
random_file = 'matlab_randoms.txt'
RandomManager.clear_random_values()
RandomManager.load_random_values(random_file)
# Create the workspace directory
try:
os.makedirs(MLCIntegrationTest.WORKSPACE_DIR)
except OSError:
shutil.rmtree(MLCIntegrationTest.WORKSPACE_DIR)
os.makedirs(MLCIntegrationTest.WORKSPACE_DIR)
# Create a new experiment, which will be used to
cls._mlc = MLCLocal(working_dir=MLCIntegrationTest.WORKSPACE_DIR)
cls._mlc.new_experiment(
experiment_name=MLCIntegrationTest.EXPERIMENT_NAME,
experiment_configuration=config_file,
evaluation_script=ev_script,
preevaluation_script=preev_script)
cls._mlc.open_experiment(
experiment_name=MLCIntegrationTest.EXPERIMENT_NAME)
for generation_params in MLCIntegrationTest.GENERATIONS:
if isinstance(generation_params, int):
cls._mlc.go(experiment_name=MLCIntegrationTest.EXPERIMENT_NAME,
to_generation=generation_params)
elif isinstance(generation_params, list):
cls._mlc.go(experiment_name=MLCIntegrationTest.EXPERIMENT_NAME,
from_generation=generation_params[0],
to_generation=generation_params[1])
else:
raise Exception(
"Integration test, bad value for generations param")
# List with individuals data
cls._indivs = []
cls._populate_indiv_dict()
cls._pops = []
cls._populate_pop_dict()
def test_import_existent_experiment(self):
mlc = MLCLocal(working_dir=MLCWorkspaceTest.WORKSPACE_DIR)
mlc.new_experiment("test4", MLCWorkspaceTest.ORIGINAL_CONFIGURATION)
import_experiment_path = os.path.join(os.path.dirname(os.path.abspath(__file__)),
"test4.mlc")
try:
mlc.import_experiment(import_experiment_path)
self.assertTrue(False)
except MLC.api.mlc.DuplicatedExperimentError:
self.assertTrue(True)
finally:
mlc.delete_experiment("test4")
def test_delete_experiment(self):
# delete an experiment that not exists
try:
mlc = MLCLocal(working_dir=MLCWorkspaceTest.WORKSPACE_DIR)
mlc.delete_experiment(MLCWorkspaceTest.NEW_EXPERIMENT)
self.assertTrue(False)
except MLC.api.mlc.ExperimentNotExistException:
self.assertTrue(True)
mlc.new_experiment(MLCWorkspaceTest.NEW_EXPERIMENT,
MLCWorkspaceTest.NEW_CONFIGURATION)
mlc.delete_experiment(MLCWorkspaceTest.NEW_EXPERIMENT)
self.assertFalse(os.path.exists(os.path.join(MLCWorkspaceTest.WORKSPACE_DIR,
MLCWorkspaceTest.NEW_EXPERIMENT)))
def setUp(self):
try:
os.makedirs(MLCWorkspaceTest.WORKSPACE_DIR)
except OSError:
shutil.rmtree(MLCWorkspaceTest.WORKSPACE_DIR)
os.makedirs(MLCWorkspaceTest.WORKSPACE_DIR)
mlc = MLCLocal(working_dir=MLCWorkspaceTest.WORKSPACE_DIR)
# general settings for MLC
set_logger('console')
set_working_directory(MLCWorkspaceTest.WORKSPACE_DIR)
this_dir = os.path.dirname(os.path.abspath(__file__))
MLCWorkspaceTest.ORIGINAL_CONFIGURATION = os.path.join(this_dir,
MLCWorkspaceTest.ORIGINAL_EXPERIMENT + ".conf")
MLCWorkspaceTest.NEW_CONFIGURATION = os.path.join(this_dir,
MLCWorkspaceTest.NEW_EXPERIMENT + ".conf")
mlc.new_experiment(MLCWorkspaceTest.ORIGINAL_EXPERIMENT,
MLCWorkspaceTest.ORIGINAL_CONFIGURATION)
# random file for simulations
MLCWorkspaceTest.FILE_WITH_RANDOMS = os.path.join(this_dir, "matlab_randoms.txt")
def test_import_experiment_with_erroneous_path(self):
mlc = MLCLocal(working_dir=MLCWorkspaceTest.WORKSPACE_DIR)
import_experiment_path = os.path.join(os.path.dirname(os.path.abspath(__file__)),
"test5.mlc")
try:
mlc.import_experiment(import_experiment_path)
self.assertTrue(False)
mlc.delete_experiment("test5")
except MLC.api.mlc.ImportExperimentPathNotExistException:
self.assertTrue(True)
self.assertFalse("test5" in mlc.get_workspace_experiments())
def setUpClass(cls):
TestHelper.load_default_configuration()
try:
os.makedirs(ApplicationTest.workspace_dir)
except OSError:
shutil.rmtree(ApplicationTest.workspace_dir)
os.makedirs(ApplicationTest.workspace_dir)
# Create the MLCLocal and the workspace of MLC, and create
# a new experiment to be used to test the callbacks
set_working_directory(ApplicationTest.workspace_dir)
ApplicationTest.mlc_local = MLCLocal(
working_dir=ApplicationTest.workspace_dir)
def test_obtain_configuration(self):
mlc = MLCLocal(working_dir=MLCWorkspaceTest.WORKSPACE_DIR)
mlc.open_experiment(MLCWorkspaceTest.ORIGINAL_EXPERIMENT)
configuration = mlc.get_experiment_configuration(MLCWorkspaceTest.ORIGINAL_EXPERIMENT)
mlc.close_experiment(MLCWorkspaceTest.ORIGINAL_EXPERIMENT)
# check configuration structure
self.assertIsInstance(configuration, dict)
self.assertTrue(configuration.has_key("BEHAVIOUR"))
self.assertIsInstance(configuration["BEHAVIOUR"], dict)
self.assertTrue(configuration["BEHAVIOUR"].has_key("showeveryitbest"))
self.assertEqual(configuration["BEHAVIOUR"]["showeveryitbest"], "true")
def test_get_default_board_configuration(self):
try:
mlc = MLCLocal(working_dir=MLCWorkspaceTest.WORKSPACE_DIR)
mlc.new_experiment(MLCWorkspaceTest.NEW_EXPERIMENT,
MLCWorkspaceTest.NEW_CONFIGURATION)
mlc.open_experiment(MLCWorkspaceTest.NEW_EXPERIMENT)
board_configuration, serial_connection = mlc.get_board_configuration(MLCWorkspaceTest.NEW_EXPERIMENT)
self.assertEqual(board_configuration.board_type, boards.Due)
self.assertEqual(board_configuration.read_count, 2)
self.assertEqual(board_configuration.read_delay, 0)
self.assertEqual(board_configuration.report_mode, 0)
self.assertEqual(board_configuration.analog_resolution, 12)
self.assertEqual(serial_connection.port, "/dev/ttyACM0")
self.assertEqual(serial_connection.baudrate, 115200)
self.assertEqual(serial_connection.parity, "N")
self.assertEqual(serial_connection.stopbits, 1)
self.assertEqual(serial_connection.bytesize, 8)
finally:
# FIXME: use Setup/TearDown testcase
mlc.delete_experiment(MLCWorkspaceTest.NEW_EXPERIMENT)
def test_go_and_check_simulation_info(self):
# load random values for the simulation
self._load_random_values()
# Execute a simulation
mlc = MLCLocal(working_dir=MLCWorkspaceTest.WORKSPACE_DIR)
mlc.new_experiment("test_go_and_check", MLCWorkspaceTest.ORIGINAL_CONFIGURATION)
mlc.open_experiment("test_go_and_check")
mlc.go("test_go_and_check", 2)
# check simulation info
info = mlc.get_experiment_info("test_go_and_check")
self._assert_key_value(info, "name", "test_go_and_check")
self._assert_key_value(info, "generations", 2)
self._assert_key_value(info, "individuals", 11)
self._assert_key_value(info, "individuals_per_generation", 10)
mlc.close_experiment("test_go_and_check")
mlc.delete_experiment("test_go_and_check")
def test_obtain_experiments(self):
mlc = MLCLocal(working_dir=MLCWorkspaceTest.WORKSPACE_DIR)
experiments = mlc.get_workspace_experiments()
self.assertEqual(len(experiments), 1)
self.assertEqual(experiments[0], MLCWorkspaceTest.ORIGINAL_EXPERIMENT)
def test_go_and_get_generations(self):
try:
# load random values for the simulation
self._load_random_values()
# Execute a simulation
mlc = MLCLocal(working_dir=MLCWorkspaceTest.WORKSPACE_DIR)
mlc.new_experiment("test_go_and_check", MLCWorkspaceTest.ORIGINAL_CONFIGURATION)
mlc.open_experiment("test_go_and_check")
mlc.go("test_go_and_check", 2)
# get first population
first_generation = mlc.get_generation("test_go_and_check", 1)
self.assertIsInstance(first_generation, MLCPopulation)
# get second generation
second_generation = mlc.get_generation("test_go_and_check", 2)
self.assertIsInstance(second_generation, MLCPopulation)
# third generation does not exist and must raise an Exception
# TODO: Use a specific exception instead of IndexError
try:
third_generation = mlc.get_generation("test_go_and_check", 3)
self.assertIsInstance(third_generation, MLCPopulation)
self.assertTrue(False)
except IndexError:
self.assertTrue(True)
finally:
# FIXME: use Setup/TearDown testcase
os.unlink(os.path.join(MLCWorkspaceTest.WORKSPACE_DIR, "test_go_and_check") + ".conf")
os.unlink(os.path.join(MLCWorkspaceTest.WORKSPACE_DIR, "test_go_and_check") + ".mlc")
pass
def test_go_and_get_individuals(self):
# load random values for the simulation
self._load_random_values()
# Execute a simulation
mlc = MLCLocal(working_dir=MLCWorkspaceTest.WORKSPACE_DIR)
mlc.new_experiment("test_go_and_check", MLCWorkspaceTest.ORIGINAL_CONFIGURATION)
mlc.open_experiment("test_go_and_check")
mlc.go("test_go_and_check", 2)
# obtain individuals
individuals = mlc.get_individuals("test_go_and_check")
# check number of individuals
self.assertEqual(len(individuals), 11)
# TODO: Check individual values
for indiv_id, indiv_data in individuals.items():
self.assertIsInstance(indiv_data, IndividualData)
# Test Update Individual Cost in all generations
mlc.update_individual_cost("test_go_and_check", 2, 1000, 1001)
indiv_data = mlc.get_individuals("test_go_and_check")[2]
self.assertEqual(indiv_data.get_appearances(), 2)
self.assertEqual(indiv_data.get_cost_history(), {1: [(1000.0, 1001)], 2: [(1000.0, 1001)]})
mlc.close_experiment("test_go_and_check")
mlc.delete_experiment("test_go_and_check")
def test_update_board_configuration(self):
try:
mlc = MLCLocal(working_dir=MLCWorkspaceTest.WORKSPACE_DIR)
mlc.new_experiment(MLCWorkspaceTest.NEW_EXPERIMENT, MLCWorkspaceTest.NEW_CONFIGURATION)
mlc.open_experiment(MLCWorkspaceTest.NEW_EXPERIMENT)
board_configuration, serial_connection = mlc.get_board_configuration(MLCWorkspaceTest.NEW_EXPERIMENT)
new_board_config = ProtocolConfig(None, report_mode=12, read_count=10, read_delay=11, board_type=boards.Leonardo, analog_resolution=13)
new_connection = SerialConnectionConfig("/dev/ttyACM1", baudrate=5000, parity="P", stopbits=2, bytesize=6)
mlc.save_board_configuration(MLCWorkspaceTest.NEW_EXPERIMENT, new_board_config, new_connection)
loaded_board_configuration, loaded_connection = mlc.get_board_configuration(MLCWorkspaceTest.NEW_EXPERIMENT)
self.assertEqual(loaded_board_configuration.board_type, boards.Leonardo)
self.assertEqual(loaded_board_configuration.read_count, 10)
self.assertEqual(loaded_board_configuration.read_delay, 11)
self.assertEqual(loaded_board_configuration.report_mode, 12)
self.assertEqual(loaded_board_configuration.analog_resolution, 13)
self.assertEqual(loaded_connection.port, "/dev/ttyACM1")
self.assertEqual(loaded_connection.baudrate, 5000)
self.assertEqual(loaded_connection.parity, "P")
self.assertEqual(loaded_connection.stopbits, 2)
self.assertEqual(loaded_connection.bytesize, 6)
finally:
# FIXME: use Setup/TearDown testcase
mlc.delete_experiment(MLCWorkspaceTest.NEW_EXPERIMENT)
def test_create_experiment_and_obtain_configuration(self):
try:
mlc = MLCLocal(working_dir=MLCWorkspaceTest.WORKSPACE_DIR)
mlc.new_experiment(MLCWorkspaceTest.NEW_EXPERIMENT,
MLCWorkspaceTest.NEW_CONFIGURATION)
mlc.open_experiment(MLCWorkspaceTest.NEW_EXPERIMENT)
configuration = mlc.get_experiment_configuration(
MLCWorkspaceTest.NEW_EXPERIMENT)
print configuration
mlc.close_experiment(MLCWorkspaceTest.NEW_EXPERIMENT)
# check configuration structure
self.assertIsInstance(configuration, dict)
self.assertTrue(configuration.has_key("PARAMS"))
self.assertIsInstance(configuration["PARAMS"], dict)
self.assertTrue(configuration["PARAMS"].has_key("test_param"))
self.assertEqual(configuration["PARAMS"]["test_param"],
"test_value")
finally:
# FIXME: use Setup/TearDown testcase
mlc.delete_experiment(MLCWorkspaceTest.NEW_EXPERIMENT)
def test_set_configuration(self):
mlc = MLCLocal(working_dir=MLCWorkspaceTest.WORKSPACE_DIR)
# check original configuration
mlc.new_experiment(MLCWorkspaceTest.NEW_EXPERIMENT, MLCWorkspaceTest.NEW_CONFIGURATION)
mlc.open_experiment(MLCWorkspaceTest.NEW_EXPERIMENT)
original_config = mlc.get_experiment_configuration(MLCWorkspaceTest.NEW_EXPERIMENT)
self.assertEqual(original_config["PARAMS"]["test_param"], "test_value")
# chage paramenter value
mlc.set_experiment_configuration(MLCWorkspaceTest.NEW_EXPERIMENT, {"PARAMS": {"test_param": "new_value"}})
mlc.close_experiment(MLCWorkspaceTest.NEW_EXPERIMENT)
# reload mlc_workspace
mlc_reloaded = MLCLocal(working_dir=MLCWorkspaceTest.WORKSPACE_DIR)
mlc_reloaded.open_experiment(MLCWorkspaceTest.NEW_EXPERIMENT)
original_config = mlc_reloaded.get_experiment_configuration(MLCWorkspaceTest.NEW_EXPERIMENT)
self.assertEqual(original_config["PARAMS"]["test_param"], "new_value")
mlc_reloaded.close_experiment(MLCWorkspaceTest.NEW_EXPERIMENT)
# set specific parameter
mlc = MLCLocal(working_dir=MLCWorkspaceTest.WORKSPACE_DIR)
mlc.open_experiment(MLCWorkspaceTest.NEW_EXPERIMENT)
mlc.set_experiment_configuration_parameter(MLCWorkspaceTest.NEW_EXPERIMENT,
"another_section", "another_param",
"another_value")
mlc.close_experiment(MLCWorkspaceTest.NEW_EXPERIMENT)
# reload mlc_workspace
mlc_reloaded = MLCLocal(working_dir=MLCWorkspaceTest.WORKSPACE_DIR)
mlc_reloaded.open_experiment(MLCWorkspaceTest.NEW_EXPERIMENT)
config = mlc_reloaded.get_experiment_configuration(MLCWorkspaceTest.NEW_EXPERIMENT)
mlc_reloaded.close_experiment(MLCWorkspaceTest.NEW_EXPERIMENT)
mlc.delete_experiment(MLCWorkspaceTest.NEW_EXPERIMENT)
self.assertEqual(config["PARAMS"]["test_param"], "new_value")
self.assertIn("another_section", config)
self.assertIn("another_param", config["another_section"])
self.assertEqual(config["another_section"]["another_param"], "another_value")