Jonathan Guyer wrote:

> On Oct 7, 2005, at 4:00 PM, I wrote:
> 
>   
> 
> > regardless, pysparse is BSD
> >licensed, so it's perfectly legal to use his code to improve
> >scipy.sparse (assuming that rigorous benchmarking determines that there
> >are, in fact, improvements to be made). We'll do some tests and, if a
> >merge is warranted, we'll run it by Roman out of courtesy.
> >    
> >
> 
> I've finally done some benchmarking of scipy.sparse and PySparse and 
> posted my results and comments on plone[*]:
> 
>      <http://www.scipy.org/wikis/featurerequests/SparseSolvers>
> 
> Bottom line is that, with a couple of exceptions, PySparse is both 
> faster and less memory intensive than SciPy. I don't know whether 
> anything can be lifted from PySparse to improve SciPy's implementation.
> 
>   
> 
This is very, very good information.  Thank you for going through the 
effort.  

Yes, I think definitely we can improve the sparse matrix support in 
SciPy.  For one, the ll_mat matrix can be lifted from  PySparse.  It is 
definitely useful for building arrays.

In addition we can look into why the lu decomposition is faster for 
PySparse when presumably they are both using the same code underneath. 

I think those two issues would solve the major problems your graphs 
point out.  Right now, pysparse is in the sandbox of svn scipy so that 
it can be used for improvements on the sparse matrix in scipy. 

-Travis



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