[SciPy-dev] Compiling pysparse from the sandbox

[Travis Oliphant]

Nathan Bell wrote:
> On 4/18/07, Daniel Wheeler <daniel.wheeler at nist.gov> 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.
>   

I'm interested.


> 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).
>   

Yes, because f2py should be re-entrant. 

-Travis