[Numpy-discussion] SVD does not converge on "clean" matrix
Warren Weckesser
warren.weckesser@enthought....
Fri Aug 12 08:33:46 CDT 2011
On Fri, Aug 12, 2011 at 4:03 AM, Charanpal Dhanjal <
dhanjal@telecom-paristech.fr> wrote:
> Thank Nadav for testing out the matrix. I wonder if you had a chance to
> check if the resulting decomposition contained NaN or Inf values?
>
> As far I understood, numpy.linalg.svd uses routines in LAPACK and ATLAS
> (if available) to compute the corresponding SVD. I did some
> complementary tests on Debian Squeeze on an Intel Xeon W3550 CPU and the
> call to numpy.linalg.svd results in the LinAlgError "SVD did not
> converge", however the test leading to results containing NaN values ran
> on Debian Lenny on an Intel Core 2 Quad. In both of these situations we
> use Python 2.7.1 and numpy 1.5.1 (without ATLAS), and so the reasons for
> the differences seem to be OS or processor dependent. Any ideas?
>
> Charanpal
>
> Date: Thu, 11 Aug 2011 07:21:09 -0700
> From: Nadav Horesh <nadavh@visionsense.com>
> Subject: Re: [Numpy-discussion] SVD does not converge on "clean"
> matrix
> To: Discussion of Numerical Python <numpy-discussion@scipy.org>
> Message-ID:
>
> <26FC23E7C398A64083C980D16001012D246DFC5F90@VA3DIAXVS361.RED001.local>
> Content-Type: text/plain; charset="us-ascii"
>
>
> > 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)
>
Another data point: on Mac OS X, with Python 2.7.2 and numpy 1.6.0 (using
EPD 7.1), I get the error:
$ ipython --pylab
Enthought Python Distribution -- www.enthought.com
Python 2.7.2 |EPD 7.1-1 (32-bit)| (default, Jul 3 2011, 15:40:35)
Type "copyright", "credits" or "license" for more information.
IPython 0.11.rc1 -- An enhanced Interactive Python.
? -> Introduction and overview of IPython's features.
%quickref -> Quick reference.
help -> Python's own help system.
object? -> Details about 'object', use 'object??' for extra details.
Welcome to pylab, a matplotlib-based Python environment [backend: WXAgg].
For more information, type 'help(pylab)'.
In [1]: numpy.__version__
Out[1]: '1.6.0'
In [2]: arr = load('matrix_leading_to_bad_SVD.npz')['arr_0']
In [3]: np.linalg.svd(arr)
---------------------------------------------------------------------------
LinAlgError Traceback (most recent call last)
/Users/warren/tmp/<ipython-input-3-e475bd6de739> in <module>()
----> 1 np.linalg.svd(arr)
/Library/Frameworks/Python.framework/Versions/7.1/lib/python2.7/site-packages/numpy/linalg/linalg.py
in svd(a, full_matrices, compute_uv)
1319 work, lwork, iwork, 0)
1320 if results['info'] > 0:
-> 1321 raise LinAlgError, 'SVD did not converge'
1322 s = s.astype(_realType(result_t))
1323 if compute_uv:
LinAlgError: SVD did not converge
Warren
> >
> > Nadav
>
> >On Thu, 11 Aug 2011 15:23:22 +0200, dhanjal@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
>
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