Problem
Plotting the GFP of data with only a single sensor via plot_evoked(gfp=True) produces a GFP, although the GFP – describing the spatial standard deviation – should not exist.
Steps to reproduce
import os
import mne
sample_data_folder = mne.datasets.sample.data_path()
sample_data_raw_file = os.path.join(sample_data_folder, 'MEG', 'sample',
'sample_audvis_raw.fif')
raw = mne.io.read_raw_fif(sample_data_raw_file, verbose=False)
events = mne.find_events(raw, stim_channel='STI 014')
event_dict = {'auditory/left': 1, 'auditory/right': 2, 'visual/left': 3,
'visual/right': 4}
epochs = mne.Epochs(raw, events, tmin=-0.3, tmax=0.7, event_id=event_dict,
preload=True)
evoked = epochs['auditory/left'].average()
evoked.pick('EEG 001').plot(gfp=True)Expected results
- either no GFP trace, or
- a GFP constantly at zero, or
- a warning, or
- an error message
Actual results
GFP is displayed as the absolute value of the sensor signal.
Additional information
Using master.
Problem
Plotting the GFP of data with only a single sensor via
plot_evoked(gfp=True)produces a GFP, although the GFP – describing the spatial standard deviation – should not exist.Steps to reproduce
Expected results
Actual results
GFP is displayed as the absolute value of the sensor signal.
Additional information
Using
master.