As Nick pointed out, lapack library has the svd implementation used by Matlab which seems more robust. If you have lapack library and ctypes installed, you can use hyper = Hyperalignment(ProcrusteanMapper(svd='dgesvd',space='commonspace'))
I have only tested this on linux, so please let me know if you run into any issues. Best, Swaroop On Wed, Apr 2, 2014 at 8:55 AM, Nick Oosterhof <[email protected]> wrote: > > On Apr 2, 2014, at 5:44 PM, andrea bertana <[email protected]> wrote: > >> I'm trying to use Hyperalignment() procedure to align different subjects' >> brain. >> I am mainly referring to the example described in this webpage - >> http://dev.pymvpa.org/examples/hyperalignment.html >> However, when I try to compute the common space on the training set (10 >> participant, single - participant matrix: 301 time-point x 1000 voxels ) I >> get the following message: >> >> LinAlgError, 'SVD did not converge' > > Yes, I've had that issue too, and we've had some discussion in the lab. It > turns out the blas library provides better SVD support than numpy itself. The > issue is reported here > > https://github.com/numpy/numpy/issues/1588 > > and seems still open. > > For me this problem occurred using mac os, where numpy did not use other > libraries . At some point I tried to use the blas libraries but failed > miserably. > On the positive side, using neurodebian in a virtualbox worked for me. > > On what platform are you working? If not neurodebian you might consider > trying it (either installed, or through virtualbox). > > (in a perfect world the blas or other SVD-supporting libraries would be made > to work on any platform, but I don't know how hard that is) > _______________________________________________ > Pkg-ExpPsy-PyMVPA mailing list > [email protected] > http://lists.alioth.debian.org/cgi-bin/mailman/listinfo/pkg-exppsy-pymvpa _______________________________________________ Pkg-ExpPsy-PyMVPA mailing list [email protected] http://lists.alioth.debian.org/cgi-bin/mailman/listinfo/pkg-exppsy-pymvpa
