[SciPy-dev] Compiling pysparse from the sandbox
Wed Apr 18 21:02:46 CDT 2007
On 4/18/07, Daniel Wheeler <firstname.lastname@example.org> wrote:
> Probably not. Pysparse at sourceforge is being maintained and is at release
> 1.0. It's been updated
> to use numpy with the numpy/noprefix.h method mentioned above. Use cvs
> rather than 1.0 as 1.0
> doesn't see the numpy header files.
Just out of curiosity, is there important functionality that PySparse
offers that's not currently available in SciPy? From what I can tell,
PySparse has a few preconditioners and an eigensolver, in addition to
what SciPy also has.
Is there an interest in including these or any other sparse features in SciPy?
I have some Algebraic Multigrid code (AMG) that I've been working on
for a while. I've implemented the so-called "classical" AMG of Ruge &
Stuben and also Smoothed Aggregation as described in by Vanek et. al.
Would others be interested in using AMG in SciPy? For those not
familiar with AMG, or multigrid in general - multigrid can solve
linear systems that arise in certain elliptic PDEs (e.g. Poisson
equations, heat diffusion, linear elasticity, etc) in optimal time.
Furthermore, the AMG methods mentioned above are "black box" in the
sense that only the matrix needs to be provided to the solver - so no
knowledge of the mesh geometry is necessary.
Also, are the iterative methods (pcg,gmres,etc.) reentrant? I recall
having problems using cg with a preconditioner that also called cg
(for a coarse level solve).
Nathan Bell email@example.com
More information about the Scipy-dev