Re: [igraph] Eigenpairs of sparse graphs

[Gabor Csardi]

In addition, you can do the same from the R interface, 
see ?arpack for an example. You need to write an R function 
that multiplies your matrix by a supplied vector.
Then call arpack() with this function as an argument. 

Please be catious with the arpack() function, however, as it 
was not tested too much, especially not when not the principal 
eigenvalue/vector is calculated.

Gabor

On Sun, Mar 09, 2008 at 09:38:36PM +0100, Tamas Nepusz wrote:
> Hi,
> 
> >I need to compute some extremal eigenvalues/eigenvectors of
> >adjacency and Laplacian matrices for very large and sparse graphs.
> >(to large for the matrices to be represented in their dense form  
> >anyway).
> >
> >Given the graphs, how can I achieve this task with igraph?
> igraph includes an interface to the ARPACK library suitable for  
> solving large scale eigenvalue problems. See the following page in the  
> documentation for details:
> 
> http://cneurocvs.rmki.kfki.hu/igraph/doc/html/ch19s01.html
> 
> So you should import your graph somehow into igraph (using the C core  
> directly), initialize an igraph_arpack_options_t data structure, set  
> its options appropriately for your specific problem, implement an  
> igraph_arpack_function_t function that multiplies a given vector with  
> your matrix (chances are that you'll have to use an adjacency list  
> representation of your graph, see 
> http://cneurocvs.rmki.kfki.hu/igraph/doc/html/igraph-Adjlists.html) , and 
> finally call igraph_arpack_rssolve if your matrix is symmetric,  
> igraph_arpack_rnsolve otherwise.
> 
> If you need examples, check the code for PageRank calculation or  
> eigenvector centrality in centrality.c in the igraph source code.
> 
> I hope this helps.
> 
> Regards,
> -- 
> T.
> 
> 
> 
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-- 
Csardi Gabor <address@hidden>    UNIL DGM