We have a eeg data ( n_channel * n_samples) . This needs to be converted into 3d array based on the event info we have . What is the standard way of doing this ? Somewhere i see the data is converted into 3d array as (n_channels * n_samples * n_events) and somewhere i see that ‘(n_events * n_channels * n_samples )’ . Can somebody please explain this?
You could just use this The Epochs data structure: discontinuous data — MNE 0.23.0 documentation
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As to the shape of the array, in my opinion, that just depends on how you would use the data. After all, that’s just two different presentation of dimension of your data(maybe numpy.ndarray). All you need is to clearly know what dimension of your data is, and the meaning of each dimension.