Thanks a lot!
in mvpa2 you would need to use something more than Sphere. Sphere is just defining what kind of neighborhood you are seeking for. But classes of QueryEngine's are there to do actual job given a specific dataset. e.g. here is one of the examples from the mvpa2/tests/test_neighborhood.pywhich would have more. Here is one demonstrating somewhat having spatio-temporal neighborhood search sphere = ne.Sphere(1) ds = Dataset([data, data], fa={'s_ind': np.concatenate((ind, ind)), 't_ind': np.repeat([0,1], 27)}) qe = ne.IndexQueryEngine(s_ind=sphere, t_ind=None) qe.train(ds) qa[1] would return neighbors for feature 1 (in space and all in time since t_ind=None in above) helps?
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