27.09.2011 10:40, Jaroslav Hajek kirjoitti:
I've been looking into options to do fast low-rank dense matrix factorization updates (aka Matlab's qrupdate) with NumPy, but couldn't find basically anything. Did I miss something?
At the moment, we do not have equivalents to these routines. However, such additions would be very welcome! If you wish to contribute here, we would be interested in adding routines for doing these operations. There are already some places inside Scipy where such routines could be used.
A few years ago I wrote the qrupdate library http://sourceforge.net/projects/qrupdate/, and subsequently wrapped it for Octave, giving it a broad spectrum of efficient factorization updating capabilities - see http://www.gnu.org/software/octave/doc/interpreter/Matrix-Factorizations.htm..., functions qrupdate, qrinsert, qrdelete, qrshift, cholupdate, cholinsert, choldelete, cholshift, luupdate. A Would there be interest in having similar functions in NumPy? Would NumPy or SciPy be a better place?
These routines probably fit in the scope of Scipy: the linear algebra package in Numpy is kept intentionally bare-bones. There is one question, though: your qrupdate code is licensed under the GPL. To include it in Scipy, we need to have it distributable under a BSD-compatible license. Would you be willing to relicense it? -- Pauli Virtanen