I have raw MEG data that contains responses to four different conditions,
120 responses to each condition. The epochs of certain condition can be
extracted by giving event_id as an argument to mne.Epochs. However, I would
need a file containing a subset of 40 epochs per condition (i.e. 160 epochs
in total). The epochs should be selected randomly. I wonder if there is
some way to do this with mne Python?
Many thanks Alex!
I just tested and this seems to work!
-Maria
2014-10-05 18:54 GMT+03:00 Alexandre Gramfort <
alexandre.gramfort at telecom-paristech.fr>:
hi Maria,
to balance the number of epochs in each condition you can use the
equalize_event_counts method.
epochs.equalize_event_counts(...)
otherwise you can index epochs with integers.
epochs[[1, 4, 5]] will return a new set of 3 epochs.
HTH
Alex
> Hi all,
>
> I have raw MEG data that contains responses to four different conditions,
> 120 responses to each condition. The epochs of certain condition can be
> extracted by giving event_id as an argument to mne.Epochs. However, I
would
> need a file containing a subset of 40 epochs per condition (i.e. 160
epochs
> in total). The epochs should be selected randomly. I wonder if there is
some
> way to do this with mne Python?
>
> Thank you very much,
> Maria
>
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