[pymvpa] Searchlight statistical inference

[Richard Dinga]

This is achieved through a 'searchlight' command from command line
interface (http://www.pymvpa.org/generated/cmd_searchlight.html),
which is a different thing as 'sphere_searchlight' you are calling
from python. In the code it is done in dosl.sh script.
You can see that preprocessing and cv setup are python files passed as
arguments into the command (those files are also included in the
repository). If/else clause is there just so we save some space in
outputs, since feature and dataset attributes are same for all
permutations, they are saved only once for original map and maps
created by permutation are saved only as numpy arrays. Those maps are
then loaded and combined in the dogrpstats.py.

I don't know how to do it outside of cmd, I guess you should use
scatter_neighbourhood function somehow and then use a center_ids
parameter in the sphere_searchlight

It's worth to note that for the analysis it doesn't matter what kind
of sl you use, you can use 'sphere_searchlight' without any problems.
Sparse SL just saved us weeks of CPU time.


> Richard, in the code you referred to it is stated:
> "The values mapped onto each voxel represent the mean accuracy across all
> classification (spheres)
> a voxel was included in."

> How is this achieved? I scanned the code and nothing popped out but I must
> be missing something.
> Thanks!
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