def execute_task(task: TaskType, parameters: dict, save_folder: str) -> bool:
"""Execute Task.
Executes the desired task by setting up the display window and
data acquisition, then passing on to the start_task function
which will initialize experiment.
Input:
task(str): registered bcipy TaskType
parameters (dict): parameter dictionary
save_folder (str): path to save folder
"""
signal_model = None
language_model = None
filename = None
fake = parameters['fake_data']
# Init EEG Model, if needed. Calibration Tasks Don't require probabilistic
# modules to be loaded.
if not fake and task not in TaskType.calibration_tasks():
# Try loading in our signal_model and starting a langmodel(if enabled)
try:
signal_model, filename = load_signal_model()
except Exception as e:
print(f'Cannot load signal model. Exiting. {e}')
raise e
# if Language Model enabled init lm
if parameters['lang_model_enabled']:
language_model = init_language_model(parameters)
# Initialize DAQ
daq, server = init_eeg_acquisition(
parameters, save_folder, server=fake)
# Initialize Display Window
# We have to wait until after the prompt to load the signal model before
# displaying the window, otherwise in fullscreen mode this throws an error
display = init_display_window(parameters)
print_message(display, 'Initializing...')
# Start Task
try:
start_task(
display, daq, task, parameters, save_folder,
language_model=language_model,
signal_model=signal_model, fake=fake, auc_filename=filename)
# If exception, close all display and acquisition objects
except Exception as e:
_clean_up_session(display, daq, server)
raise e
return _clean_up_session(display, daq, server)
def test_can_use_lsl(self):
"""Test init_eeg_acquisition with LSL device"""
params = self.parameters
params['acq_device'] = 'LSL'
client, server = init_eeg_acquisition(params, self.save, server=True)
with client:
time.sleep(0.1)
client.cleanup()
server.stop()
self.assertEqual(client.device_info.name, 'LSL')
self.assertEqual(client.device_info.fs, 256)
def test_default_values(self):
self.parameters['acq_device'] = 'DSI'
client, server = init_eeg_acquisition(self.parameters,
self.save,
server=True)
client.start_acquisition()
time.sleep(0.1)
client.stop_acquisition()
client.cleanup()
server.stop()
self.assertEqual(client.device_info.name,
self.parameters['acq_device'])
self.assertEqual(client.device_info.fs, 300)
def test_allows_customization(self):
"""Test init_eeg_acquisition with custom values."""
params = self.parameters
params['raw_data_name'] = 'foo.csv'
params['acq_port'] = 9000
params['acq_device'] = 'DSI'
client, server = init_eeg_acquisition(params, self.save, server=True)
with client:
time.sleep(0.1)
client.cleanup()
server.stop()
self.assertEqual(client.device_info.name, params['acq_device'])
self.assertEqual(client.device_info.fs, 300)
def test_default_values(self):
print("Testing init_eeg_acquisition with default values.")
self.parameters['acq_device'] = 'DSI'
client, server = init_eeg_acquisition(
self.parameters, self.save, server=True)
client.start_acquisition()
time.sleep(0.1)
client.stop_acquisition()
client.cleanup()
server.stop()
server.join()
self.assertTrue('raw_data.csv' in client._processor._filename)
self.assertEqual(client.device_info.name, self.parameters['acq_device'])
self.assertEqual(client.device_info.fs, 300)