I had a quick look at the code (https://github.com/numpy/numpy/blob/master/numpy/linalg/linalg.py) and the numpy.linalg.svd function calls lapack_lite.dgesdd (for real matrices) so I guess the non-convergence occurs in this function. As I understood lapack_lite is used by default unless numpy is installed with ATLAS/MKL etc. I wonder why svd works for Nadav and not for anyone else? Any ideas anyone?
Charanpal On Sat, 13 Aug 2011 13:13:25 -0600, Charles R Harris wrote: > On Thu, Aug 11, 2011 at 7:23 AM, 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 >> [1] >> >> 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 >> didnt 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 > > > > Links: > ------ > [1] > > https://docs.google.com/leaf?id=0Bw0NXKxxc40jMWEyNTljMWUtMzBmNS00NGZmLThhZWUtY2I2MWU2MGZiNDgx|+|amp|+|hl=fr > [2] mailto:[email protected] _______________________________________________ NumPy-Discussion mailing list [email protected] http://mail.scipy.org/mailman/listinfo/numpy-discussion
