On Thu, Aug 11, 2011 at 7:23 AM, <[email protected]> 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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