Matrix: Pajek/GD98_a

Description: Pajek network: Graph Drawing contest 1998

Pajek/GD98_a graph Pajek/GD98_a graph
(bipartite graph drawing) (graph drawing of A+A')


Pajek/GD98_a
scc of Pajek/GD98_a Pajek/GD98_a graph

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  • Matrix group: Pajek
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  • download as a MATLAB mat-file, file size: 2 KB. Use UFget(1495) or UFget('Pajek/GD98_a') in MATLAB.
  • download in Matrix Market format, file size: 1 KB.
  • download in Rutherford/Boeing format, file size: 1 KB.

    Matrix properties
    number of rows38
    number of columns38
    nonzeros50
    # strongly connected comp.35
    explicit zero entries0
    nonzero pattern symmetry 16%
    numeric value symmetry 16%
    typebinary
    structureunsymmetric
    Cholesky candidate?no
    positive definite?no

    authorGraph Drawing Contest
    editorV. Batagelj
    date1998
    kinddirected graph
    2D/3D problem?no

    Additional fieldssize and type
    nodenamefull 38-by-40
    coordfull 38-by-2

    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/.                                
    ------------------------------------------------------------------------------
    The original problem had 3D xyz coordinates, but all values of z were equal   
    to 0.5, and have been removed.  This graph has 2D coordinates.                
    

    SVD-based statistics:
    norm(A)3.94017
    min(svd(A))0
    cond(A)Inf
    rank(A)14
    null space dimension24
    full numerical rank?no
    singular value gap3.77784e+14

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

    Pajek/GD98_a 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.