I need to calculate timepoint-by-timepoint root mean square (RMS) from a grand-averaged ERP.
- My script currently calculates the grand averaged ERP using the
mne.grand_averagefunction, with return an
Evokedobject. How do I calculate the RMS timepoint-by-timepoint of my grand-average waveform? I have tried to do the following:
rms = np.sqrt((ga.data**2).mean())
But this will just calculate the overall RMS. I think this is because
ga.data is just the data without any temporal information. How do I do that? Any suggestion would be much appreciated!