[Numpy-discussion] Eigenvalues did not converge

Paul Anton Letnes paul.anton.letnes@gmail....
Mon Aug 29 10:31:09 CDT 2011


I recently got into trouble with these calculations (although I used scipy). I actually got segfaults and "bus errors". The solution for me was to not link against ATLAS, but rather link against Apple's blas/lapack libraries. That got everything working again. I would suggest trying to install against something other than ATLAS and see if that helps (or, more generally, determining which blas/lapack you are linking against, and try something else).

Paul


On 29. aug. 2011, at 16.21, Charanpal Dhanjal wrote:

> I posted a similar question about the non-convergence of 
> numpy.linalg.svd a few weeks ago. I'm not sure I can help but I wonder 
> if you compiled numpy with ATLAS/MKL support (try numpy.show_config()) 
> and whether it made a difference? Also what is the condition number and 
> Frobenius norm of the matrix in question?
> 
> Charanpal
> 
> On Mon, 29 Aug 2011 08:56:31 -0600, Rick Muller wrote:
>> Im bumping into the old "Eigenvalues did not converge" error using
>> numpy.linalg.eigh() on several different linux builds of numpy
>> (1.4.1). The matrix is 166x166. I can compute the eigenvalues on a
>> Macintosh build of numpy, and I can confirm that there arent
>> degenerate eigenvalues, and that the matrix appears to be negative
>> definite.
>> 
>> Ive seen this before (though not for several years), and what I
>> normally do is to build lapack with -O0. This trick did not work in
>> the current instance. Does anyone have any tricks to getting eigh to
>> work?
>> 
>> Other weird things that Ive noticed about this case: I can compute
>> the eigenvalues using eigvals and eigvalsh, and can compute the
>> eigenvals/vecs using eig(). The matrix is real symmetric, and Ive
>> tested that its symmetric enough by forcibly symmetrizing it.
>> 
>> Thanks in advance for any help you can offer.
> 
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