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_open_and_close_experiment(self):
mlc = MLCLocal(working_dir=MLCWorkspaceTest.WORKSPACE_DIR)
mlc.open_experiment(MLCWorkspaceTest.ORIGINAL_EXPERIMENT)
mlc.close_experiment(MLCWorkspaceTest.ORIGINAL_EXPERIMENT)
try:
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_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_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_create_experiment_and_obtain_configuration(self):
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)
mlc.close_experiment(MLCWorkspaceTest.NEW_EXPERIMENT)
mlc.delete_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")
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_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")