[SciPy-dev] integration of symeig in SciPy
Thu Oct 23 11:04:02 CDT 2008
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:
- where would you like to have symeig? (I would suggest scipy.linalg)
- should we change the signature to match or resamble that of other
eigenproblem-related functions in scipy?
- is there a responsible scipy dev for the linalg package I can bother
with any questions I may have in the process?
- do I get svn commit rights or should I work on a local copy and
send a patch?
let me know,
More information about the Scipy-dev