Hi, I am glad it is resolved. Yes, we had this issue before with numpy's svd, which is why we included dgesvd option :) Sorry, the error message in PyMVPA misled me.
Thanks, Swarooop On Thu, Nov 23, 2017 at 2:41 AM, Müller, K. (Katja) <[email protected]> wrote: > Hi Swaroop, > > Thanks for your response, but I had already checked for 0 variance in > multiple variants and could not find voxels with 0 variance. I also checked > the variables used in this call (means and sum of squares ssqs), and could > not find something suspicious. > > This turned out to be an issue of the numpy SVD, which is used as a default > by the ProcrusteanMapper. For large matrices it apparently may result in this > error: > >>> init_dgesdd failed init > > > Initializing Hyperalignment() as > > Hyperalignment(alignment=ProcrusteanMapper(svd='dgesvd')) > > (i.e. using the LAPACK dgesvd) solves it. There might be documentation about > this that I'm not aware of. > > > Best regards, > Katja > >> Am 17.11.29 Heisei um 20:11 schrieb Swaroop Guntupalli <[email protected]>: >> >> Hi Katja, >> >> It looks the code is checking if variance/sum of squares of time >> series in your data is practically zero, and raising that error. >> Check if all your input datasets have non-zero variance in all voxels. >> >> Best, >> Swaroop >> >> On Mon, Nov 13, 2017 at 4:41 AM, Müller, K. (Katja) >> <[email protected]> wrote: >>> Dear all, >>> >>> It would be great if somebody has any kind of information about what causes >>> this issue, and ways to solve it. >>> >>> I am running hyperalignment ROI-by-ROI on 3 subjects. It works on every ROI >>> except the largest one with ~28k voxels (the dataset has 53k voxels in >>> total), where it fails with the error message: >>> "For now do not handle invariant in time datasets" >>> >>> It was suggested earlier (similar mailing list question from 2013) to >>> remove invariant voxels to solve this issue. I tried both >>> remove_invariant_features() and my own code for this, but the behaviour and >>> error message did not change. >>> >>> My datasets are inside a standard Python list. >>> >>> train_pymv_datasets = [mvpa2.datasets.Dataset(dataset) for dataset in >>> roi0_train_data] >>> hyperalign_fit = >>> mvpa2.algorithms.hyperalignment.Hyperalignment()(train_pymv_datasets) >>> >>> This is what I get when calling the second line: >>> >>> init_dgesdd failed init >>> init_dgesdd failed init >>> init_dgesdd failed init >>> init_dgesdd failed init >>> Traceback (most recent call last): >>> File "save_hyperaligned_subject.py", line 77, in <module> >>> hyperalign_fit = >>> mvpa2.algorithms.hyperalignment.Hyperalignment()(train_pymv_datasets) >>> File >>> ".../anaconda2/lib/python2.7/site-packages/mvpa2/algorithms/hyperalignment.py", >>> line 339, in __call__ >>> self.train(datasets) >>> File >>> ".../anaconda2/lib/python2.7/site-packages/mvpa2/algorithms/hyperalignment.py", >>> line 319, in train >>> residuals) >>> File >>> ".../anaconda2/lib/python2.7/site-packages/mvpa2/algorithms/hyperalignment.py", >>> line 483, in _level2 >>> m.train(ds_new) >>> File ".../anaconda2/lib/python2.7/site-packages/mvpa2/base/learner.py", >>> line 137, in train >>> self._train(ds) >>> File >>> ".../anaconda2/lib/python2.7/site-packages/mvpa2/mappers/procrustean.py", >>> line 123, in _train >>> raise ValueError, "For now do not handle invariant in time datasets" >>> ValueError: For now do not handle invariant in time datasets >>> >>> >>> I looked up the respective code section in procrustean.py, but am not sure >>> what the code is checking for there. >>> >>> >>> Best regards from the Netherlands, >>> Katja Müller >>> _______________________________________________ >>> 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 > > _______________________________________________ > 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
