def on_pick(ax, info_idx, names_idx):
""" When a subplot representing a specific channel is clicked on the
main topography plot, show a new figure containing FOOOF fit plot
for every condition """
fig = ax.figure
fig.delaxes(ax)
for idx, (report_key, report) in enumerate(reports.items()):
report_ax = fig.add_subplot(1, len(reports), idx + 1)
fooof = report.get_fooof(names_idx)
# Use plot function from fooof
fooof.plot(
ax=report_ax,
plot_peaks='dot',
add_legend=False,
)
# Add information about the fit to the axis title
text = ("Condition: " + str(report_key) + "\n" + "R squred: " +
format_float(fooof.r_squared_) + "\n" + "Peaks: \n")
for peak_params in fooof.peak_params_:
text = text + '{0} ({1}, {2})\n'.format(
*format_floats(peak_params))
report_ax.set_title(text)
fig.tight_layout()
def run(self):
try:
selected_name = self.data['outputs']['spectrum'][0]
spectrum = self.experiment.active_subject.spectrum[selected_name]
params = spectrum.params
message = ""
message += "Name: " + spectrum.name + "\n\n"
if 'fmin' in params and 'fmax' in params:
message += 'Frequencies: {0}Hz - {1}Hz\n'.format(
format_float(params['fmin']), format_float(params['fmax']))
if 'nfft' in params:
message += 'Window length (samples): {0}\n'.format(
params['nfft'])
if 'overlap' in params:
message += 'Overlap (samples): {0}\n'.format(params['overlap'])
if 'intervals' in params:
message += '\nIntervals: \n'
for key, ivals in params['intervals'].items():
message += 'Condition ' + str(key) + ': '
message += ', '.join([
'({0}s - {1}s)'.format(format_float(ival[0]),
format_float(ival[1]))
for ival in ivals
])
message += '\n'
if 'groups' in params:
for key, names in params['groups'].items():
message += '\nGroup ' + str(key) + ': \n'
for name in names:
message += name + '\n'
except Exception as exc:
message = ""
return message
def tfr_info(experiment, data, window):
""" Fills info element
"""
try:
selected_name = data['outputs']['tfr'][0]
tfr = experiment.active_subject.tfr[selected_name]
params = tfr.params
message = ""
if 'decim' in params:
message += 'Decimated by factor: {0}\n'.format(params['decim'])
if 'evoked_subtracted' in params:
message += 'Evoked subtracted: {0}\n'.format(
params['evoked_subtracted'])
if 'conditions' in params:
message += 'Conditions: ' + ', '.join(params['conditions']) + '\n'
if 'n_cycles' in params:
message += 'Cycles: ' + ', '.join(format_floats(
params['n_cycles'])) + '\n'
if hasattr(tfr, 'times'):
message += 'Times: {0}s - {1}s\n'.format(
format_float(tfr.times[0]), format_float(tfr.times[-1]))
if hasattr(tfr, 'freqs'):
message += 'Freqs: {0} - {1}\n'.format(format_float(tfr.freqs[0]),
format_float(tfr.freqs[-1]))
if 'groups' in params:
for key, names in params['groups'].items():
message += '\nGroup ' + str(key) + ': \n'
for name in names:
message += name + '\n'
except Exception as exc:
message = ""
return message
def run(self):
try:
selected_name = self.data['outputs']['epochs'][0]
epochs = self.experiment.active_subject.epochs[selected_name]
params = epochs.params
message = ""
message += "Name: {0}\n\n".format(epochs.name)
message += "Count: {0}\n".format(epochs.count)
message += 'Baseline: {0}s - {1}s\n'.format(
format_float(params['bstart']), format_float(params['bend']))
message += 'Times: {0}s - {1}s\n'.format(
format_float(params['tmin']), format_float(params['tmax']))
message += '\nReject params: \n'
if 'grad' in params:
message += 'Gradiometers: {}\n'.format(
params.get('reject').get('grad'))
if 'mag' in params:
message += 'Magnetometers: {}\n'.format(
params.get('reject').get('mag'))
if 'eeg' in params:
message += 'EEG: {}\n'.format(params.get('reject').get('eeg'))
if 'events' in params:
message += '\nCreated from events: \n'
for event in params.get('events'):
message += 'ID: {0}, mask: {1}\n'.format(
event['event_id'], event['mask'])
except Exception as exc:
message = ""
return message
def save_all_channels(experiment, selected_name):
""" Saves peak params and aperiodic params to a csv file for every
subject and channel and condition """
row_descs = []
csv_data = []
column_names = ['CF', 'Amp', 'BW',
'Aperiodic offset', 'Aperiodic exponent']
for subject in experiment.subjects.values():
fooof_item = subject.fooof_report.get(selected_name)
if not fooof_item:
continue
for key, report in fooof_item.content.items():
for ch_idx, ch_name in enumerate(fooof_item.params['ch_names']):
ch_report = report.get_fooof(ch_idx)
for peak in ch_report.peak_params_:
csv_data.append([format_float(peak[0]),
format_float(peak[1]),
format_float(peak[2]),
'', ''])
row_descs.append((subject.name, key, ch_name))
aparams = ch_report.aperiodic_params_
csv_data.append(['', '', '',
format_float(aparams[0]),
format_float(aparams[1])])
row_descs.append((subject.name, key, ch_name))
# Save the resulting csv into a output folder 'meggie way'
folder = create_timestamped_folder(experiment)
fname = selected_name + '_all_subject_all_channels_fooof.csv'
path = os.path.join(folder, fname)
save_csv(path, csv_data, column_names, row_descs)
logging.getLogger('ui_logger').info('Saved the csv file to ' + path)