Howdy - Let me preface this msg by saying that I only _barely_ know what I'm doing. This will probably become evident immediately.
In an experiment whose data I'm trying to analyze, I'd like to localize the analysis based on the results of various masks, including Brodmann masks created with the wfu pickatlas tool (http://fmri.wfubmc.edu/software/PickAtlas). I can use these masks in the course of univariate analyses with SPM despite the fact that the masks have different numbers of voxels than do our acquired volumes -- the NIFTI headers apparently contain enough info to match up the mask and the volumes in physical space, and SPM just does the right thing, which was a pleasant surprise. But now I'd like to use these masks with PyMVPA. I've been working through the tutorials with the Haxby dataset, and part 2 of the tutorial demonstrates loading the Haxby BOLD data with a mask, like so: ds = fmri_dataset(os.path.join(path, 'bold.nii.gz'), mask=os.path.join(path, 'mask_vt.nii.gz')) As it happens, the shape of the voxel matrix for this BOLD data, and for this mask, are the same. That's a luxury we don't have in our dataset, but I crossed my fingers and tried to load one of our volumes with the mask, but to no avail. I got this error: /opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/mvpa2/mappers/flatten.pyc in _forward_data(self, data) 103 raise ValueError("FlattenMapper has not been trained for data " 104 "shape '%s' (known only '%s')." --> 105 % (str(sshape), str(oshape))) 106 ## input matches the shape of a single sample 107 #if sshape == oshape: ValueError: FlattenMapper has not been trained for data shape '(91, 109, 91)' (known only '(96, 96, 37)'). The (91,109,91) are the dimensions of the masks produced by wfu pickatlas; our data is the (96, 96, 37). So my question is, how does one deal with these situations? I've googled as best as I'm able but haven't found the issue addressed. Can anyone point me in a good direction? Thanks very much, S _______________________________________________ Pkg-ExpPsy-PyMVPA mailing list [email protected] http://lists.alioth.debian.org/cgi-bin/mailman/listinfo/pkg-exppsy-pymvpa
