[Numpy-discussion] SVD error in Numpy. NumPy Update reversed?

[Charles R Harris]

On Wed, Mar 19, 2008 at 11:30 AM, Lou Pecora <lou_boog2000 at yahoo.com> wrote:

> I recently had a personal email reply from Damian
> Menscher who originally found the error in 2002.  He
> states:
>
> ------
>
> I explained the solution in a followup to my own post:
> http://mail.python.org/pipermail/python-list/2002-August/161395.html
> -- in short, find the dlasd4_ routine (for the current
> 1.0.4 version
> it's at numpy/linalg/dlapack_lite.c:21902) and change
> the max
> iteration count from 20 to 100 or higher.
>
> The basic problem was that they use an iterative
> method to converge on
> the solution, and they had a cutoff of the max number
> of iterations
> before giving up (to guard against an infinite loop or
> cases where an
> unlucky matrix would require an excessive number of
> iterations and
> therefore CPU).  The fix I used was simply to increase
> the max
> iteration count (from 20 to 100 -- 50 was enough to
> solve my problem
> but I went for overkill just to be sure I wouldn't see
> it again).  It
> *may* be reasonable to just leave this as an infinite
> loop, or to
> increase the count to 1000 or higher.  A lot depends
> on your preferred
> failure mode:
>  - count too low -> low cpu usage, but "SVD did not
> converge" errors
> somewhat common
>  - very high count -> some matrices will result in
> high cpu usage,
> non-convergence still possible
>  - infinite loop -> it will always converge, but may
> take forever
>
> NumPy was supposedly updated also (from 20 to 100, but
> you may want to
> go higher) in bug 601052.  They said the fix made it
> into CVS, but
> apparently it got lost or reverted when they did a
> release (the oldest
> release I can find is v1.0 from 2006 and has it set to
> 20).  I just
> filed another bug (copy/paste of the previous one) in
> hopes they'll
> fix it for real this time:
> http://scipy.org/scipy/numpy/ticket/706
>
> Damian
>
> ----------------------------------------
>
> I looked at line 21902  of dlapack_lite.c, it is,
>
>        for (niter = iter; niter <= 20; ++niter) {
>
> Indeed the upper limit for iterations in the
> linalg.svd code is set for 20.  For now I will go with
> my method (on earlier post) of squaring the matrix and
> then doing svd when the original try on the original
> matrix throws the linalg.linalg.LinAlgError.  I do not
> claim that this is a cure-all.  But it seems to work
> fast and avoids the original code from thrashing
> around in a long iteration.
>
> I would suggest this be made explicit in the NumPy
> documentation and then the user be given the option to
> reset the limit on the number of iterations.
>
> Well, it certainly shouldn't be hardwired in as 20. At minimum it should
be a #define, and ideally it should be passed in with the function call, but
I don't know if the interface allows that.

Chuck
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