[SciPy-dev] integration of symeig in SciPy

[Robert Cimrman]

Tiziano Zito wrote:
> Dear SciPy devs, 
> 
> there has been some discussion about integrating symeig in SciPy.
> symeig <http://mdp-toolkit.sourceforge.net/symeig.html> is a Python
> wrapper for the LAPACK functions to solve the standard and
> generalized eigenvalue problems for symmetric (hermitian) positive
> definite matrices. It is superior to the scipy "linalg.eigh" wrapper
> because it wraps *all* relevant LAPACK routines, enabling for
> example to just return a subset of all egenvectors/eigenvalues,
> which is a killer feature if you are dealing with huge-nonsparse
> matrices. Some of these LAPACK routines are available in
> scipy.lib.lapack.flapack and can be accessed through
> scipy.lib.lapack.get_lapack_funcs . Some of them are still missing
> in scipy, while symeig offers a unified interface to all relevant
> LAPACK functions.  symeig has been dowloaded  more than 1300 times
> since its first public appearance on sourceforge (under the
> mdp-toolkit package) in 2004. It features a complete unit test and a
> telling doc-string. I am one of the authors of symeig and have been
> contacted by some scipy devs to discuss the integration of symeig in
> scipy. I am more than willing to help doing this. The most difficult
> part (the LGPL license) has been addressed already: I've re-issued
> symeig under a BSD license. Next step would be to adapt symeig code
> and tests to the scipy framework. Some questions to you:

This is really good news. I had to use the missing functions directly 
via scipy.lib.lapack.get_lapack_funcs which was not very convenient. For 
example the lobpcg sparse eigensolver requires the symmetric routines.

Thank you!
r.