part_name = []
for folder in folders:
part_name.append(folder[1:])
#Variable where the number of trials that have at least a percentage of valid data are stored:
#0 - Participant
#1-5: 40, 60, 80, 90
#Number of trials with more than: 40, 60, 80 and 90% of valid samples.
number_trials_valid_data = np.zeros((len(part_name), 5), dtype=float)
for j, participant in enumerate(folders):
print "participant", participant
part_path = main_path + sep + participant
onset_file_name = find_files(part_path, 'onset_stimuli')
gaze_data_name = find_files(part_path, 'GazeData')
#Raise exception and continue with the next participant if the file is not in the folder
if onset_file_name == '':
print "the participant " + participant + "does not have the onset_video file required"
number_trials_valid_data[j] = -1
continue
if gaze_data_name == '':
print "the participant " + participant + "does not have the gaze_data file required"
number_trials_valid_data[j] = -1
continue
if len(onset_file_name) > 1:
print 'More than one onset file for participant ' + str(
f = open(results_path + sep + 'percentage_data.txt', 'w')
f.write('Participant' + '\t' + 'Perc valid' + '\t' + 'Perc inside' + '\t' +
'Perc outside' + '\t' + 'Perc outliers'
'\t' + 'Perc valid video' + '\t'
'Perc inside video' + '\t' + 'Perc outside video' + '\t' +
'Perc outliers video' + '\t' + 'Per valid erp' + '\t' +
'Perc inside erp' + '\t' + 'Perc outside erp' + '\t' +
'Perc outliers erp' + '\n')
folders = listdir(main_path)
part_name = []
percentage_data = np.zeros((len(part_name), 6), dtype=float)
for j, participant in enumerate(folders):
print "participant", participant
part_path = main_path + sep + participant
onset_file_name = find_files(part_path, 'onset_stimuli')
onset_video_name = find_files(part_path, 'onset_video', '.txt')
gaze_data_name = find_files(part_path, 'GazeData')
#Raise exception and continue with the next participant if the file is not in the folder
if onset_file_name == '':
print "the participant " + participant + "does not have the onset_video file required"
percentage_data[j] = -1
continue
if gaze_data_name == '':
print "the participant " + participant + "does not have the gaze_data file required"
percentage_data[j] = -1
continue
if len(onset_file_name) > 1:
def load_indexes(path, file_starts):
in_file = find_files(path, file_starts)
return np.loadtxt(path + sep + in_file[0], delimiter='\t', skiprows=1)
def load_et_data(path, file_starts):
gd_file = find_files(path, file_starts)
return open_gaze_data(path + sep + gd_file[0])
''' Participant info'''
print participant
part_path = general_path + os.sep + participant
f = open(part_path + os.sep + participant + '_new_eeg_video_events.txt', 'w')
#Calculate A or B sequence
cond = calculate_condition(participant)
if cond:
print 'Condition B'
else:
print 'Condition A'
''' Load Files '''
#EEG events
eeg_events_path = part_path + os.sep + find_files(part_path, 'CM_', '.txt')[0]
eeg_all_events = np.loadtxt(eeg_events_path, dtype=np.dtype([('event', (np.str, 20)), ('timestamp', np.int)]))
eeg_events = []
eeg_times = []
for event in eeg_all_events:
if event['event'].startswith('v'):
eeg_events.append(event['event'])
eeg_times.append(event['timestamp'])
#et events
et_events_path = part_path + os.sep + find_files(part_path, 'onset_video', 'txt')[0]
et_events = np.loadtxt(et_events_path, dtype=np.dtype([('video', np.float_), ('timestamp', np.float_)]))
''' split events in videos '''
#Videos order
video_order = unique_values(et_events['video'])
#ET events split
def load_indexes(path, file_starts):
in_file = find_files(path, file_starts)
return np.loadtxt(path + sep + in_file[0], delimiter='\t', skiprows=1)
def load_et_data(path, file_starts):
gd_file = find_files(path, file_starts)
return open_gaze_data(path + sep + gd_file[0])