[Mne_analysis] Grand average over subjects when bad channels are excluded?
Maria Hakonen
maria.hakonen at gmail.com
Mon Nov 17 02:59:38 EST 2014
Hi all,
I have computed grand average over subjects as follows:
for subject in subjects:
evoked = mne.read_evokeds(filename, baseline=(None, 0),
proj=True,verbose=False)
if flag == 1:
evoked_all = evoked[0]
flag = 0
else:
evoked_all = evoked_all+evoked[0]
evoked_all = evoked_all / len(subjects)
However, a problem arises when the evoked files don't contain the same
channels (this is because I have excluded bad channels and they are not
same in all files):
AssertionError: <Evoked | comment : 'Unknown', time : [-0.099994,
2.999808], n_epochs : 147, n_channels x n_times : 305 x 3721> and <Evoked
| comment : 'Unknown', time : [-0.099994, 2.999808], n_epochs : 154,
n_channels x n_times : 306 x 3721> do not contain the same channels
I wonder if there is any way to get the grand average over subjects if bad
channels are excluded?
Many thanks already in advance!
Regards,
Maria
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