[Numpy-discussion] SVD does not converge on "clean" matrix

[Charles R Harris]

On Thu, Aug 11, 2011 at 7:23 AM, <dhanjal at telecom-paristech.fr> wrote:

> Hi all,
>
> I get an error message "numpy.linalg.linalg.LinAlgError: SVD did not
> converge" when calling numpy.linalg.svd on a "clean" matrix of size (1952,
> 895). The matrix is clean in the sense that it contains no NaN or Inf
> values. The corresponding npz file is available here:
>
> https://docs.google.com/leaf?id=0Bw0NXKxxc40jMWEyNTljMWUtMzBmNS00NGZmLThhZWUtY2I2MWU2MGZiNDgx&hl=fr
>
> Here is some information about my setup: I use Python 2.7.1 on Ubuntu
> 11.04 with numpy 1.6.1. Furthermore, I thought the problem might be solved
> by recompiling numpy with my local ATLAS library (version 3.8.3), and this
> didn't seem to help. On another machine with Python 2.7.1 and numpy 1.5.1
> the SVD does converge however it contains 1 NaN singular value and 3
> negative singular values of the order -10^-1 (singular values should
> always be non-negative).
>
> I also tried computing the SVD of the matrix using Octave 3.2.4 and Matlab
> 7.10.0.499 (R2010a) 64-bit (glnxa64) and there were no problems. Any help
> is greatly appreciated.
>
> Thanks in advance,
> Charanpal
>
>
>
Fails here also, fedora 15 64 bits AMD 940. There should be a maximum
iterations argument somewhere...

Chuck
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