[pymvpa] Found the problem (hopefully): suspicious results

[Nynke van der Laan]

Hello all,

again, many many thanks for the responses and suggestions!

I think/hope that I've found the problem with my data. I've looked
somewhat further into the more direct results I retrieved from the
searchlight analysis and I think that the conversion to a nifti-map is
causing the >0.5 accuracy bias.
When I plot a histogram of the direct results that I get from the
searchlight in python, more specifically, the sl_map. Then the
distribution looks ok. The peak is at 0.5 with a kind of normal
distribution. However, what I have been looking at earlier was a
histogram from the data mapped back to nifti ( with:
dataset.map2Nifti(sl_map).save('filename.nii.gz'). When I open this
nifti in MRIcron than the distribution suddenly is totally different
(as I reported earlier: the histogram with a peak at 0.6).

I did an additional check on it: Aside from the sl_map (the errormap
from the searchlight analysis), I also constructed an accuracymap
(with the following code: sl_map_accuracy = [1-x for x in sl_map]).
When both maps are converted to nifti, they both have the >0.5 bias.
While with a correct conversion to nifti you would expect the errormap
to be the inverse from the accuracymap. (which is the case when I look
at the distributions in python, so the problem seems to be in the
conversion)

Any suggestions what could be going wrong in the conversion to nifti?
Any known problems? Because I would really like to use the data mapped
back to the original dataspace in nifti.

Thanks in advance!

Best,
Nynke