[SciPy-user] Possible bug in linalg.svdvals

[My VDI Freemail]

-------------------
> 
> On Mon, 21 Oct 2002, Nils Wagner wrote:
> 
> > Hi,
> > 
> > I am interested in the singular values of the following matrix
> > 
> > >>> A
> > array([[ 0.  ,  0.  ,  1.  ,  0.  ],
> >        [ 0.  ,  0.  ,  0.  ,  1.  ],
> >        [-0.81,  0.15, -0.02,  0.  ],
> >        [ 0.25, -1.21,  0.  , -0.02]])
> > 
> > 
> > 
> > >>> print svdvals(A)
> > [              nan               nan               nan              
> > nan]
> 
> Strange, it works here:
> 
> >>> linalg.svdvals(a)
> array([ 1.29446282,  1.00042554,  0.99970394,  0.72808433])
> 
> when using ATLAS 3.3.14 or 3.4.1 and LAPACK-3.0, ifc or gcc.
> 
Atlas 3.4.1

rpm -q -i lapack

Name        : lapack                       Relocations: (not relocateable)
Version     : 3.0                               Vendor: SuSE Linux AG, Nuernberg, Germany
Release     : 566                           Build Date: Mit 11 Sep 2002 08:48:21 CEST
Install date: Mon 30 Sep 2002 22:00:27 CEST      Build Host: x330-4.suse.de
Group       : Development/Libraries/Parallel   Source RPM: lapack-3.0-566.src.rpm
Size        : 10885418                         License: distributable
Packager    : http://www.suse.de/feedback
URL         : http://www.netlib.org/lapack/
Summary     : Linear Algebra Package
Description :
LAPACK provides routines for solving systems of simultaneous linear equations, least-squares solutions of linear systems of equations, eigenvalue problems, and singular value problems. The associated matrix factorizations (LU, Cholesky, QR, SVD, Schur, generalized Schur) are also provided, as are related computations such as reordering of the Schur factorizations and estimating condition numbers. Dense and banded matrices are handled, but not general sparse matrices. In all areas, similar functionality is provided for real and complex matrices, in both single and double precision.


Authors:
--------
    Jack Dongarra <lapack at cs.utk.edu>
Distribution: SuSE Linux 8.1 (i386)


Nils

> In your case, what ATLAS/LAPACK are you using? Is  
> scipy.linalg.test(1) succesful?
> 
> Pearu
> 
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