[Nipy-devel] fif IO in Python
Fri Jan 7 09:51:56 CST 2011
> At the risk of restating the obvious, let me just add that I would
> definitely advocate separating these two as much as possible. IMHO,
> all the IO part needs to give you is the raw data in a numpy array +
> all the information in the file you might need for an analysis
> (dimensions, scale, etc.). This should be right at home within
read raw files in fairly easy to support in nibabel. However starting from
raw files there are many steps that need to be taken before doing
brain imaging with M/EEG. It means that only reading raw files is not
very helpful if you don't provide the MEG tools with it. Once Matti
says yes for BSD licensing I'll fork nibabel.
> The processing part could live better in an MEG-specific context, or
> can always go into something like nitime ;)
I plan to look in the near future at the time frequency tools that are
in nitime. Just being curious, how would you compare nitime with fieldtrip
from TF analysis?
> Are there MEG-specific challenges with separating these two? I mean,
> is processing entangled with IO in some particular way in MEG data, in
> contrast to fMRI data, for example?
Indeed. MNE does all the preprocessing of raw data (artefact rejection,
filtering, averaging etc.) in pure C in a very efficient way. It would probably
be a waste of time now to do this in python.
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