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!
_______________________________________________ Pkg-ExpPsy-PyMVPA mailing list Pkg-ExpPsy-PyMVPA@lists.alioth.debian.org http://lists.alioth.debian.org/cgi-bin/mailman/listinfo/pkg-exppsy-pymvpa