Dear Yaroslav
Woops, that was embarrassing! Thanks for clearing that up. However, I've just spotted another potential problem in my code. I assumed that the experimental design was the same for all runs, because only task001_run001 (in the sub001/BOLD directory) has an attributes.txt file indicating the order of stimulus presentations (unless I'm very much mistaken?) None of the other runs contain this file, so I used... targets = SampleAttributes(pjoin('haxby2001, 'sub001', 'BOLD','task001_run001', 'attributes.txt'))['targets'] for every chunk in ds. However, when examining the data loaded in by load_tutorial_data... print ds.targets[ds.chunks==0] > ['scissors' 'scissors' 'scissors'... print ds.targets[ds.chunks==1] > ['face' 'face' 'face'.... SO I was clearly wrong on that front. Is there a way to access information about the experimental design from the other runs? As I mentioned above, only task001_run001 contains the relevant attributes.txt file, so I'm rather at a loss as to where the necessary info might be located. --------------------------------------------------------- Lyam Bailey, B.Sc., M.Sc. Doctoral Student Department of Psychology & Neuroscience Dalhousie University ________________________________ From: Pkg-ExpPsy-PyMVPA <pkg-exppsy-pymvpa-bounces+lyam.bailey=dal...@alioth-lists.debian.net> on behalf of Yaroslav O Halchenko <y...@onerussian.com> Sent: Wednesday, August 14, 2019 12:25:19 PM To: pkg-exppsy-pymvpa@alioth-lists.debian.net <pkg-exppsy-pymvpa@alioth-lists.debian.net> Subject: Re: [pymvpa] Loading multiple ROIs with fmri_dataset On Wed, 14 Aug 2019, Lyam Bailey wrote: > Dear Yaroslav, > Thanks so much for the quick reply. I tried implementing this with: > fa_fname = {a: "haxby2001/sub001/masks/25mm/%s.nii.gz" % a for a in ["vt, > hoc"]} > temp_ds = fmri_dataset(bold_fname, mask=None, targets = targets, > add_fa=fa_fname, chunks = int(i)-1) > The code ran without errors, however when I continued through the example > RSA script (http://www.pymvpa.org/examples/rsa_fmri.html) the > dissimilarity matrices appeared very different to those generated when > using load_tutorial_data. I experimented with > fa_fname = {a: "haxby2001/sub001/masks/25mm/%s.nii.gz" % a for a in > ["white"]} > ...and this turned out to generate exactly the same results. I also get > the same results with add_fa = None. So I get the feeling that add_fa is > not actually being implemented. Can you see a problem in the way I've > called fmri_dataset? add_fa just adds those feature attributes. You would still need to subselect those features if you decide to work with specific ROIs. for se3lection could do smth like roi_ds = temp_ds[:, temp_ds.fa.vt != 0] or am I missing what you are missing? ;) -- 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 Pkg-ExpPsy-PyMVPA@alioth-lists.debian.net https://alioth-lists.debian.net/cgi-bin/mailman/listinfo/pkg-exppsy-pymvpa
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