def execute_task(task_type: dict, parameters: dict, save_folder: str) -> bool:
"""Excecute Task.
Executes the desired task by setting up the display window and
data acquisition, then passing on to the start_task funtion
which will initialize experiment.
Input:
parameters (dict): parameter dictionary
task_type (dict): type and mode of experiment
save_folder (str): path to save folder
"""
signal_model = None
language_model = None
filename = None
exp_type = ExperimentType(task_type['exp_type'])
fake = parameters['fake_data']
# Init EEG Model, if needed. Calibration Tasks Don't require probabilistic
# modules to be loaded.
if not fake and exp_type not in ExperimentType.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:
logging.debug('Cannot load signal model. Exiting')
raise e
# if Language Model enabled init lm
if parameters['languagemodelenabled']:
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,
exp_type,
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_load_classifier(self):
"""Test load classifier can load pickled file when given path."""
# create a pickle file to save a pickled json
pickle_file = self.temp_dir + "save.p"
pickle.dump(self.parameters, open(pickle_file, "wb"))
# Load classifier
unpickled_parameters = load_signal_model(pickle_file)
# assert the same data was returned
self.assertEqual(unpickled_parameters, (self.parameters, pickle_file))