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From: | Tamas Nepusz |
Subject: | Re: [igraph] Eigenpairs of sparse graphs |
Date: | Sun, 9 Mar 2008 21:38:36 +0100 |
Hi,
igraph includes an interface to the ARPACK library suitable for solving large scale eigenvalue problems. See the following page in the documentation for details: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?
http://cneurocvs.rmki.kfki.hu/igraph/doc/html/ch19s01.htmlSo 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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