Matrix: Pajek/GD06_theory

Description: Pajek network: Graph Drawing contest 2006

Pajek/GD06_theory graph
(undirected graph drawing)


Pajek/GD06_theory

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  • Matrix group: Pajek
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  • download as a MATLAB mat-file, file size: 2 KB. Use UFget(1484) or UFget('Pajek/GD06_theory') in MATLAB.
  • download in Matrix Market format, file size: 1 KB.
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    Matrix properties
    number of rows101
    number of columns101
    nonzeros380
    # strongly connected comp.1
    explicit zero entries0
    nonzero pattern symmetrysymmetric
    numeric value symmetrysymmetric
    typebinary
    structuresymmetric
    Cholesky candidate?no
    positive definite?no

    authorGraph Drawing Contest
    editorV. Batagelj
    date2006
    kindundirected graph
    2D/3D problem?no

    Notes:

    ------------------------------------------------------------------------------
    Pajek network converted to sparse adjacency matrix for inclusion in UF sparse 
    matrix collection, Tim Davis.  For Pajek datasets, See V. Batagelj & A. Mrvar,
    http://vlado.fmf.uni-lj.si/pub/networks/data/.                                
    ------------------------------------------------------------------------------
     GD 2006 contest graph A: Theory                                              
     http://gd2006.org/contest/details.php#theory                                 
     graph in Pajek format                                                        
     transformed by Vladimir Batagelj, July 10, 2006                              
    

    SVD-based statistics:
    norm(A)6.78233
    min(svd(A))4.89431e-48
    cond(A)1.38576e+48
    rank(A)20
    null space dimension81
    full numerical rank?no
    singular value gap5.07594e+14

    singular values (MAT file):click here
    SVD method used:s = svd (full (A)) ;
    status:ok

    Pajek/GD06_theory svd

    For a description of the statistics displayed above, click here.

    Maintained by Tim Davis, last updated 12-Mar-2014.
    Matrix pictures by cspy, a MATLAB function in the CSparse package.
    Matrix graphs by Yifan Hu, AT&T Labs Visualization Group.