[SciPy-User] scipy.test() causes segmentation fault for test_lobpcg

[hannah]

Hi,
Sorry if you've gotten this a few times, but I've had bad luck with
posting to the list.

I've gotten the same bug using:
scipy-'0.10.0.dev7144'
numpy-'1.6.0.dev-af1e833'
atlas-3.9.23
umfpack and amd (suitesparse 3.6.0)
compiled to shared using these instructions:
http://repository.slacky.eu/slackware-12.1/development/suitesparse/3.1.0/src/suitesparse.SlackBuild
python2.7
gfortran
RHEL Server 5.5 (Tikanga)

I changed the Elastic_Rod and Makota_Pair test cases per the
suggestions in your post, which results in all the other tests working
fine/failing as expected. (no seqfaults)

I'm thinking it may be sensible to just run scipy as is and be a bit
careful with lobpcg. According to the core dump, the crash seems to be
in atlas:
http://pastebin.com/zy0RnUCK



On Dec 25 2010, 9:51 pm, "Ryota Tomioka" <ryo... at gmx.de> wrote:
> Dear Scipy users,
>
> I have recently installed numpy 1.5.1rc1 and
> scipy 0.8.0 on a CentOS 5.5 server. ATLAS was
> compiled with gfortran and I also specified gfortran
> for the installation of both numpy and scipy.
>
> numpy.test() ran without trouble, but scipy.test()
> crashed due to segmentation fault and this was in
> test_lobpcg.test_ElasticRod.
>
> In order to reproduce the result I copied /usr/local/lib/python2.6/site-packages/scipy/sparse/linalg/eigen/lobpcg/tests/test_lobpcg.py
> to my home directory and did the following.
>
> [ryotat at cyprus ~]$ python
> Python 2.6.6 (r266:84292, Nov 19 2010, 22:23:00)
> [GCC 4.1.2 20080704 (Red Hat 4.1.2-48)] on linux2
> Type "help", "copyright", "credits" or "license" for more information.>>> from test_lobpcg import *
> >>> A,B=ElasticRod(100)
> >>> compare_solutions(A,B,100)
> >>> compare_solutions(A,B,80)
> >>> compare_solutions(A,B,40)
> >>> compare_solutions(A,B,30)
> >>> compare_solutions(A,B,22)
> >>> compare_solutions(A,B,21)
> >>> compare_solutions(A,B,20)
>
> Segmentation fault
>
> So it seems to happen only around m=20. m=10 did not cause
> segmentation fault but resulted in
>
> AssertionError:
> Arrays are not almost equal
>
> To see it in more detail, I tried
>
> >>> A,B=ElasticRod(100)
> >>> m=20
> >>> n=A.shape[0]
> >>> numpy.random.seed(0)
> >>> V=rand(n,m)
> >>> X=linalg.orth(V)
> >>> eigs,vecs=lobpcg(A,X,B=B,tol=1e-5,maxiter=30,verbosityLevel=10)
>
> Solving generalized eigenvalue problem with preconditioning
>
> matrix size 100
> block size 20
>
> No constraints
>
> iteration 0
> [ True  True  True  True  True  True  True  True  True  True  True  True  True  True  True
>   True  True  True  True  True]
> current block size: 20
> eigenvalue: [  1.785e+12   1.586e+12   1.356e+12   1.330e+12   1.212e+12   1.155e+12   1.080e+12
>    9.149e+11   8.272e+11   8.229e+11   7.664e+11   6.941e+11   6.769e+11   5.848e+11
>    5.553e+11   4.994e+11   4.283e+11   3.813e+11   3.537e+11   1.058e+10]
> residual norms: [  7.223e+10   6.780e+10   7.145e+10   7.305e+10   6.290e+10   7.085e+10   6.539e+10
>    5.466e+10   6.137e+10   5.374e+10   5.809e+10   5.725e+10   5.375e+10   5.334e+10
>    5.052e+10   4.746e+10   4.176e+10   3.650e+10   3.283e+10   6.905e+09]
> Segmentation fault
>
> Does anyone experienced something similar? Or could anyone suggest
> where I should look into?
>
> Thanks,
> Ryota
>
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