class SimulatorAdapterTest(TransactionalTestCase):
"""
Basic testing that SImulator is still working from UI.
"""
CONNECTIVITY_NODES = 74
def setUp(self):
"""
Reset the database before each test.
"""
initialize_storage()
user = model.User("test_user", "test_pass", "*****@*****.**", True, "user")
self.test_user = dao.store_entity(user)
data = dict(name='test_proj', description='desc', users=[])
self.test_project = ProjectService().store_project(self.test_user, True, None, **data)
meta = {DataTypeMetaData.KEY_SUBJECT: "John Doe",
DataTypeMetaData.KEY_STATE: "RAW"}
algo_group = dao.find_group(SIMULATOR_MODULE, SIMULATOR_CLASS)
self.simulator_adapter = FlowService().build_adapter_instance(algo_group)
self.operation = model.Operation(self.test_user.id, self.test_project.id, algo_group.id,
json.dumps(SIMULATOR_PARAMETERS),
meta=json.dumps(meta), status=model.STATUS_STARTED,
method_name=ABCAdapter.LAUNCH_METHOD)
self.operation = dao.store_entity(self.operation)
SIMULATOR_PARAMETERS['connectivity'] = self._create_connectivity(self.CONNECTIVITY_NODES)
def _create_connectivity(self, nodes_number):
"""
Create a connectivity entity and return its GID
"""
storage_path = FilesHelper().get_project_folder(self.test_project, str(self.operation.id))
connectivity = Connectivity(storage_path=storage_path)
connectivity.weights = numpy.ones((nodes_number, nodes_number))
connectivity.centres = numpy.ones((nodes_number, 3))
adapter_instance = StoreAdapter([connectivity])
OperationService().initiate_prelaunch(self.operation, adapter_instance, {})
return dao.get_datatype_by_id(connectivity.id).gid
def test_happy_flow_launch(self):
"""
Test that launching a simulation from UI works.
"""
OperationService().initiate_prelaunch(self.operation, self.simulator_adapter, {}, **SIMULATOR_PARAMETERS)
sim_result = dao.get_generic_entity(TimeSeriesRegion, 'TimeSeriesRegion', 'type')[0]
self.assertEquals(sim_result.read_data_shape(), (32, 1, self.CONNECTIVITY_NODES, 1))
def _estimate_hdd(self, new_parameters_dict):
""" Private method, to return HDD estimation for a given set of input parameters"""
filtered_params = self.simulator_adapter.prepare_ui_inputs(new_parameters_dict)
self.simulator_adapter.configure(**filtered_params)
return self.simulator_adapter.get_required_disk_size(**filtered_params)
def test_estimate_hdd(self):
"""
Test that occupied HDD estimation for simulation results considers simulation length.
"""
factor = 5
simulation_parameters = copy(SIMULATOR_PARAMETERS)
## Estimate HDD with default simulation parameters
estimate1 = self._estimate_hdd(simulation_parameters)
self.assertTrue(estimate1 > 1)
## Change simulation length and monitor period, we expect a direct proportial increase in estimated HDD
simulation_parameters['simulation_length'] = float(simulation_parameters['simulation_length']) * factor
period = float(simulation_parameters['monitors_parameters_option_TemporalAverage_period'])
simulation_parameters['monitors_parameters_option_TemporalAverage_period'] = period / factor
estimate2 = self._estimate_hdd(simulation_parameters)
self.assertEqual(estimate1, estimate2 / factor / factor)
## Change number of nodes in connectivity. Expect HDD estimation increase.
simulation_parameters['connectivity'] = self._create_connectivity(self.CONNECTIVITY_NODES * factor)
estimate3 = self._estimate_hdd(simulation_parameters)
self.assertEqual(estimate2, estimate3 / factor)
def _estimate_execution_time(self, new_parameters_dict):
""" Private method, to return execution time estimation for a given set of input parameters"""
filtered_params = self.simulator_adapter.prepare_ui_inputs(new_parameters_dict)
self.simulator_adapter.configure(**filtered_params)
return self.simulator_adapter.get_execution_time_approximation(**filtered_params)
def test_execution_time_approximation(self):
simulation_parameters = copy(SIMULATOR_PARAMETERS)
base_time_length = 400
factors = (2, 4, 13)
simulation_parameters['simulation_length'] = float(base_time_length)
base_estimate = self._estimate_execution_time(simulation_parameters)
self.assertTrue(base_estimate > 0)
for scale_factor in factors:
# Test that time estimation scales linear with simulation length
simulation_parameters['simulation_length'] = float(base_time_length * scale_factor)
scaled_estimate = self._estimate_execution_time(simulation_parameters)
self.assertEqual(scaled_estimate / (base_estimate * scale_factor), 1)
# Even in absurd case where simulation length is 0 or negative operation should still
# be estimate as a larger than 0s value
simulation_parameters['simulation_length'] = 0.0
estimate = self._estimate_execution_time(simulation_parameters)
self.assertTrue(estimate >= 0, "Actually got %s" % estimate)
def test_noise_2d_bad_shape(self):
"""
Test a simulation with noise. Pass a wrong shape and expect exception to be raised.
"""
SIMULATOR_PARAMETERS['integrator'] = u'HeunStochastic'
noise_4d_config = [[1 for _ in xrange(self.CONNECTIVITY_NODES)] for _ in xrange(4)]
SIMULATOR_PARAMETERS['integrator_parameters_option_HeunStochastic_dt'] = u'0.01220703125'
SIMULATOR_PARAMETERS['integrator_parameters_option_HeunStochastic_noise'] = u'Additive'
SIMULATOR_PARAMETERS['integrator_parameters_option_HeunStochastic_noise_parameters_option_Additive_nsig'] = str(noise_4d_config)
SIMULATOR_PARAMETERS['integrator_parameters_option_HeunStochastic_noise_parameters_option_Additive_ntau'] = u'0.0'
SIMULATOR_PARAMETERS['integrator_parameters_option_HeunStochastic_noise_parameters_option_Additive_random_stream'] = u'RandomStream'
SIMULATOR_PARAMETERS['integrator_parameters_option_HeunStochastic_noise_parameters_option_Additive_random_stream_parameters_option_RandomStream_init_seed'] = u'42'
filtered_params = self.simulator_adapter.prepare_ui_inputs(SIMULATOR_PARAMETERS)
self.simulator_adapter.configure(**filtered_params)
if hasattr(self.simulator_adapter, 'algorithm'):
self.assertEqual((4, 74), self.simulator_adapter.algorithm.integrator.noise.nsig.shape)
else:
self.fail("Simulator adapter was not initialized properly")
self.assertRaises(Exception, OperationService().initiate_prelaunch, self.operation, self.simulator_adapter, {}, **SIMULATOR_PARAMETERS)
def test_noise_2d_happy_flow(self):
"""
Test a simulation with noise.
"""
SIMULATOR_PARAMETERS['integrator'] = u'HeunStochastic'
noise_2d_config = [[1 for _ in xrange(self.CONNECTIVITY_NODES)] for _ in xrange(2)]
SIMULATOR_PARAMETERS['integrator_parameters_option_HeunStochastic_dt'] = u'0.01220703125'
SIMULATOR_PARAMETERS['integrator_parameters_option_HeunStochastic_noise'] = u'Additive'
SIMULATOR_PARAMETERS['integrator_parameters_option_HeunStochastic_noise_parameters_option_Additive_nsig'] = str(noise_2d_config)
SIMULATOR_PARAMETERS['integrator_parameters_option_HeunStochastic_noise_parameters_option_Additive_ntau'] = u'0.0'
SIMULATOR_PARAMETERS['integrator_parameters_option_HeunStochastic_noise_parameters_option_Additive_random_stream'] = u'RandomStream'
SIMULATOR_PARAMETERS['integrator_parameters_option_HeunStochastic_noise_parameters_option_Additive_random_stream_parameters_option_RandomStream_init_seed'] = u'42'
filtered_params = self.simulator_adapter.prepare_ui_inputs(SIMULATOR_PARAMETERS)
self.simulator_adapter.configure(**filtered_params)
if hasattr(self.simulator_adapter, 'algorithm'):
self.assertEqual((2, 74, 1), self.simulator_adapter.algorithm.integrator.noise.nsig.shape)
else:
self.fail("Simulator adapter was not initialized properly")
OperationService().initiate_prelaunch(self.operation, self.simulator_adapter, {}, **SIMULATOR_PARAMETERS)
sim_result = dao.get_generic_entity(TimeSeriesRegion, 'TimeSeriesRegion', 'type')[0]
self.assertEquals(sim_result.read_data_shape(), (32, 1, self.CONNECTIVITY_NODES, 1))
SIMULATOR_PARAMETERS['integrator_parameters_option_HeunStochastic_noise_parameters_option_Additive_nsig'] = '[1]'
filtered_params = self.simulator_adapter.prepare_ui_inputs(SIMULATOR_PARAMETERS)
self.simulator_adapter.configure(**filtered_params)
if hasattr(self.simulator_adapter, 'algorithm'):
self.assertEqual((1,), self.simulator_adapter.algorithm.integrator.noise.nsig.shape)
else:
self.fail("Simulator adapter was not initialized properly")
OperationService().initiate_prelaunch(self.operation, self.simulator_adapter, {}, **SIMULATOR_PARAMETERS)
class SimulatorAdapterTest(TransactionalTestCase):
"""
Basic testing that SImulator is still working from UI.
"""
CONNECTIVITY_NODES = 74
def setUp(self):
"""
Reset the database before each test.
"""
initialize_storage()
user = model.User("test_user", "test_pass", "*****@*****.**", True, "user")
self.test_user = dao.store_entity(user)
data = dict(name='test_proj', description='desc', users=[])
self.test_project = ProjectService().store_project(self.test_user, True, None, **data)
meta = {DataTypeMetaData.KEY_SUBJECT : "John Doe",
DataTypeMetaData.KEY_STATE : "RAW"}
algo_group = dao.find_group(SIMULATOR_MODULE, SIMULATOR_CLASS)
self.simulator_adapter = FlowService().build_adapter_instance(algo_group)
self.operation = model.Operation(self.test_user.id, self.test_project.id, algo_group.id,
json.dumps(SIMULATOR_PARAMETERS),
meta = json.dumps(meta), status="STARTED",
method_name = ABCAdapter.LAUNCH_METHOD)
self.operation = dao.store_entity(self.operation)
SIMULATOR_PARAMETERS['connectivity'] = self._create_connectivity(self.CONNECTIVITY_NODES)
def _create_connectivity(self, nodes_number):
"""
Create a connectivity entity and return its GID
"""
storage_path = FilesHelper().get_project_folder(self.test_project, str(self.operation.id))
connectivity = Connectivity(storage_path=storage_path)
connectivity.weights = numpy.ones((nodes_number, nodes_number))
connectivity.centres = numpy.ones((nodes_number, 3))
adapter_instance = StoreAdapter([connectivity])
OperationService().initiate_prelaunch(self.operation, adapter_instance, {})
return dao.get_datatype_by_id(connectivity.id).gid
def test_happy_flow_launch(self):
"""
Test that launching a simulation from UI works.
"""
OperationService().initiate_prelaunch(self.operation, self.simulator_adapter, {}, **SIMULATOR_PARAMETERS)
sim_result = dao.get_generic_entity(TimeSeriesRegion, 'TimeSeriesRegion', 'type')[0]
self.assertEquals(sim_result.read_data_shape(), (32, 1, self.CONNECTIVITY_NODES, 1))
def _estimate_hdd(self, new_parameters_dict):
""" Private method, to return HDD estimation for a given set of input parameters"""
filtered_params = self.simulator_adapter.prepare_ui_inputs(new_parameters_dict)
self.simulator_adapter.configure(**filtered_params)
return self.simulator_adapter.get_required_disk_size(**filtered_params)
def test_estimate_hdd(self):
"""
Test that occupied HDD estimation for simulation results considers simulation length.
"""
factor = 5
simulation_parameters = copy(SIMULATOR_PARAMETERS)
## Estimate HDD with default simulation parameters
estimate1 = self._estimate_hdd(simulation_parameters)
self.assertTrue(estimate1 > 1)
## Change simulation length and monitor period, we expect a direct proportial increase in estimated HDD
simulation_parameters['simulation_length'] = float(simulation_parameters['simulation_length']) * factor
period = float(simulation_parameters['monitors_parameters_option_TemporalAverage_period'])
simulation_parameters['monitors_parameters_option_TemporalAverage_period'] = period / factor
estimate2 = self._estimate_hdd(simulation_parameters)
self.assertEqual(estimate1, estimate2 / factor / factor)
## Change number of nodes in connectivity. Expect HDD estimation increase.
simulation_parameters['connectivity'] = self._create_connectivity(self.CONNECTIVITY_NODES * factor)
estimate3 = self._estimate_hdd(simulation_parameters)
self.assertEqual(estimate2, estimate3 / factor)
