Had no problem on a gentoo 64 bit machine using atlas 3.8.0 (Core I7, python 2.7.2, numpy versions1.60 and 1.6.1)
Nadav ________________________________________ From: [email protected] [[email protected]] On Behalf Of [email protected] [[email protected]] Sent: 11 August 2011 16:23 To: [email protected] Subject: [Numpy-discussion] SVD does not converge on "clean" matrix 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 _______________________________________________ NumPy-Discussion mailing list [email protected] http://mail.scipy.org/mailman/listinfo/numpy-discussion _______________________________________________ NumPy-Discussion mailing list [email protected] http://mail.scipy.org/mailman/listinfo/numpy-discussion
