• SJSU Singular Matrix Database
  • Matrix group: Pajek
  • Click here for a description of the Pajek group.
  • Click here for a list of all matrices
  • Click here for a list of all matrix groups

  • Matrix: Pajek/GD95_b
  • Description: Pajek network: Graph Drawing contest 1995
  • download as a MATLAB mat-file, file size: 4 KB. Use SJget(21) or SJget('Pajek/GD95_b') in MATLAB.
  • download in Matrix Market format, file size: 2 KB.
  • download in Rutherford/Boeing format, file size: 2 KB.


    Routine svd from Matlab (R2008a) used to calculate the singular values.


    scc of Pajek/GD95_b

    Pajek/GD95_b graph

    Matrix properties (click for a legend)  
    number of rows73
    number of columns73
    structural full rank?no
    structural rank34
    numerical rank 34
    dimension of the numerical null space39
    numerical rank / min(size(A))0.46575
    Euclidean norm of A 4.7938
    calculated singular value # 340.41864
    numerical rank defined using a tolerance
    max(size(A))*eps(norm(A)) =
    calculated singular value # 358.0822e-016
    gap in the singular values at the numerical rank:
    singular value # 34 / singular value # 35
    calculated condition numberInf
    # of blocks from dmperm27
    # strongly connected comp.71
    explicit zero entries0
    nonzero pattern symmetry 0%
    numeric value symmetry 0%
    Cholesky candidate?no
    positive definite?no

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

    Additional fieldssize and type
    nodenamefull 73-by-37
    coordfull 73-by-2


    Pajek network converted to sparse adjacency matrix for inclusion in UF sparse 
    matrix collection, Tim Davis.  For Pajek datasets, See V. Batagelj & A. Mrvar,
    The original problem had 3D xyz coordinates, but all values of z were equal   
    to 0, and have been removed.  This graph has 2D coordinates.                  

    Ordering statistics:AMD METIS
    nnz(chol(P*(A+A'+s*I)*P'))201 207
    Cholesky flop count6.7e+002 7.2e+002
    nnz(L+U), no partial pivoting329 341
    nnz(V) for QR, upper bound nnz(L) for LU105 97
    nnz(R) for QR, upper bound nnz(U) for LU476 476

    Maintained by Leslie Foster, last updated 24-Apr-2009.

    Entries 5 through 14 in the table of matrix properties and the singular
    value plot were created using SJsingular code. The other plots
    and statistics are produced using utilities from the SuiteSparse package.
    Matrix color plot pictures by cspy, a MATLAB function in the CSparse package.