[SciPy-User] Graph connect components and sparse matrices

Robert Cimrman cimrman3@ntc.zcu...
Thu Nov 19 10:24:25 CST 2009


Gael Varoquaux wrote:
> On Thu, Nov 19, 2009 at 11:01:19AM -0500, Nathan Bell wrote:
>> I think we should definitely include more graph algorithms in
>> scipy.sparse.  The cost of extracting the same info via eigenvectors
>> is high and the results are less trustworthy.
> 
>> We've implemented several such algorithms (like connected_components
>> [1]) in PyAMG.  
> 
> I thought you might have. By the way, that thing (pyAMG) is just
> fantastic).

+1. (BTW. I still have to explore why it does not work well with my matrices...)

>> Since the code is organized in similar fashion to scipy.sparse it would
>> make sense to transfer some or all of the functionality in pyamg.graph
>> into scipy.sparse.graph or some such namespace.  
> 
> I'd love to see all of it, actually.
> 
>> I'd also like to add some reordering methods like RCM and nested
>> bisection.
> 
> I am really interested in all that. I don't have time to contribute in
> the short term, but in the long run (one to two years), I have a big
> interest there.
> 
> I think moving these features in scipy would enable code sharing between
> a lot of other libraries (pyAMG, networkX, sfepy, and probably other PDE
> solvers). Beside, the nipy project has some graph algorithms for machine
> learning and computer vision that use custom structures, and should move
> to common structures in the long run, and maybe in a comon project (we
> are thinking of the scikit learn).

Again, +1. I was forced to code some linear algebra/graph stuff, which is now 
in sfepy, but which I would prefer to have in scipy instead.

r.


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