On Sun, 06 Mar 2016, Adrian Smith wrote: > I’m a student researcher working with the Haxby ds105 data from OpenfMRI. I’m > not planning on using PyMVPA for my whole analysis of the data, but wanted to > use it in order to denoise, mask and detrend the data. What I want is to > input a 4D NIfTI (or group of NIfTIs), run some preprocessing on each file > like shown in http://www.pymvpa.org/tutorial_mappers.html > <http://www.pymvpa.org/tutorial_mappers.html>, and then output a processed > NIfTI for each input NIfTI. How can I do that with PyMVPA? > I’ve read through the tutorial, but it is written for someone trying to > operate their entire pipeline within PyMVPA, and I couldn’t find anything > that was what I am looking for.
I guess such toolkits as AFNI, SPM, Nipy, Nipype would be a better choice for preprocessing, and generally PyMVPA wouldn't be sufficient anyways since we do not provide e.g. motion correction and rely on those toolkits for that to be done first. Well -- ds105 iirc was already motion corrected so that state we shared it with openfmri indeed should be sufficient to carry out MVPA right away. So since you have asked, after you are done with your 'preprocessing' in PyMVPA you can just map2nifti that dataset back in its entirety, or per each chunk with a little loop. -- Yaroslav O. Halchenko Center for Open Neuroscience http://centerforopenneuroscience.org Dartmouth College, 419 Moore Hall, Hinman Box 6207, Hanover, NH 03755 Phone: +1 (603) 646-9834 Fax: +1 (603) 646-1419 WWW: http://www.linkedin.com/in/yarik _______________________________________________ Pkg-ExpPsy-PyMVPA mailing list [email protected] http://lists.alioth.debian.org/cgi-bin/mailman/listinfo/pkg-exppsy-pymvpa
