[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
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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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