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

[hannah]

Hi,
I got the same bug using:
scipy- '0.10.0.dev7144'
numpy-'1.6.0.dev-af1e833'
atlas3.9.23
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
gfortran
python2.7
Red Hat Enterprise Linux Server release 5.5 (Tikanga)

I ended up just changing the test cases (Elastic_Rod and Makota_Pair)
following your instructions, which resulted in all the other tests
running fine. So I'd suggest basically ignoring this bug and taking
care when using lobpcg.

If you want to totally debug, according to the coredump the seqfault
is in libblas:
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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