[SciPy-dev] Why does orth use svd instead of QR ?

Charles R Harris charlesr.harris@gmail....
Thu Feb 4 23:58:23 CST 2010

On Thu, Feb 4, 2010 at 8:45 PM, David Cournapeau <david@silveregg.co.jp>wrote:

> Hi,
> I wanted to know if there was a rationale for using svd to
> orthonormalize the columns of a matrix (in scipy.linalg). QR-based
> methods are likely to be much faster, and I thought this was the
> standard, numerically-stable method to orthonormalize a basis ? If the
> reason is to deal with rank-deficient matrices, maybe we could add an
> option to choose between them ?
QR with column rotation would deal with rank-deficient matrices and routines
for that are available in LAPACK <http://netlib.org/lapack/lug/node42.html>.
The SVD was probably used because it was available. The diagonal elements of
the R matrix can somewhat take the place of the singular values when column
rotation is used.

-------------- next part --------------
An HTML attachment was scrubbed...
URL: http://mail.scipy.org/pipermail/scipy-dev/attachments/20100204/6aa7c58a/attachment.html 

More information about the SciPy-Dev mailing list