HI Swaroop, Thanks. This is exactly what we were looking for. We will run few tests and let you know.
Best, Andrea 2014-04-09 19:01 GMT+02:00 Swaroop Guntupalli <[email protected]>: > Hi Andrea, > > The algorithm will do it for you. > > I am pasting this from the docstring of Hyperalignment. > """ > Level 1 and 2 are performed by the ``train()`` method, and level 3 is > performed when the trained Hyperalignment instance is called with a > list of > datasets. This dataset list may or may not be identical to the training > datasets. > > Examples > -------- > >>> # get some example data > >>> from mvpa2.testing.datasets import datasets > >>> from mvpa2.misc.data_generators import random_affine_transformation > >>> ds4l = datasets['uni4large'] > >>> # generate a number of distorted variants of this data > >>> dss = [random_affine_transformation(ds4l) for i in xrange(4)] > >>> ha = Hyperalignment() > >>> ha.train(dss) > >>> mappers = ha(dss) > >>> len(mappers) > """ > > For your case (if I understand it correctly), you can do > >>> ha.train(ds_others) > >>> test_subject_mapper = ha(ds_test) > First line should build common space on a bunch of datasets > and second line computes the transformation to that common space from > a new dataset 'ds_test' > > Did I miss something? > > Best, > Swaroop > > On Wed, Apr 9, 2014 at 3:57 AM, andrea bertana > <[email protected]> wrote: > > Dear all, > > > > > > We are performing a few tests on hyperalignment, and we would want to > > project a new participant's brain to a commmon space computed over other > > participants' responses (all participants performed the same task). > > > > > > However, in terms of scripting, it is not clear to us where the common > space > > is stored. We would need it in order to compute the transformation matrix > > directly from our participant brain to the common space (same as step 3 > of > > hyperalignment). > > > > > > We are mainly referring to the example described in this webpage - > > http://dev.pymvpa.org/examples/hyperalignment.html > > > > > > What we thought about was to get the 'commonspace' parameter from hyper > > object (which seems to carry it as general one), and then evaluate > > algebrically the transformation matrix from the new participant to the > > common - space. > > > > > > Are we missing something? > > > > > > Thanks, > > > > Andrea > > > > > > _______________________________________________ > > 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 >
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