def test_compare_random_individuals(self):
individual_1 = Individual.generate(individual_type=3,
config=Config.get_instance())
RandomManager.clear_random_values()
RandomManager.load_random_values(self._random_file)
individual_2 = Individual.generate(individual_type=3,
config=Config.get_instance())
self.assertTrue(individual_1.compare(individual_2))
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 main():
# MATLAB random numbers, used in integration tests
RandomManager.load_random_values(
"./tests/integration_tests/matlab_randoms.txt")
# load configuration
config = initialize_config()
# set logger
log_mode = config.get('LOGGING', 'logmode')
set_logger(log_mode)
simulation = Simulation()
mlc = Application(simulation)
mlc.go(to_generation=3, display_best=False)
raw_input("Press enter to continue...")
def setUp(self):
set_logger("testing")
# Load randoms from file
random_file = './mlc/unit_matlab_randoms.txt'
RandomManager.clear_random_values()
RandomManager.load_random_values(random_file)
config = Config.get_instance()
config.read(
os.path.join(mlc_config_path.get_test_path(),
'mlc/individual/configuration.ini'))
self._individual_l0 = Individual("(root (cos 5.046))")
self._individual_l1 = Individual(
"(root (log (sin (exp (tanh 3.6284)))))")
self._individual_l2 = Individual(
"(root (cos (* (+ (* -1.912 -9.178) (cos S0)) 3.113)))")
self._individual_l3 = Individual(
"(root (log (/ (* (sin 4.37) (- -8.815 -3.902)) (log (+ 2.025 -8.685)))))"
)
self._individual_l4 = Individual("(root S0)")
def _load_random_values(self):
RandomManager.clear_random_values()
RandomManager.load_random_values(MLCWorkspaceTest.FILE_WITH_RANDOMS)