• 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/Ragusa16
  • Description: Pajek network: Ragusa set
  • download as a MATLAB mat-file, file size: 2 KB. Use SJget(39) or SJget('Pajek/Ragusa16') in MATLAB.
  • download in Matrix Market format, file size: 1 KB.
  • download in Rutherford/Boeing format, file size: 1 KB.


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


    scc of Pajek/Ragusa16

    Pajek/Ragusa16 graph

    Matrix properties (click for a legend)  
    number of rows24
    number of columns24
    structural full rank?no
    structural rank18
    numerical rank 18
    dimension of the numerical null space6
    numerical rank / min(size(A))0.75
    Euclidean norm of A 10.72
    calculated singular value # 180.14663
    numerical rank defined using a tolerance
    max(size(A))*eps(norm(A)) =
    calculated singular value # 194.4655e-016
    gap in the singular values at the numerical rank:
    singular value # 18 / singular value # 19
    calculated condition numberInf
    # of blocks from dmperm6
    # strongly connected comp.10
    explicit zero entries0
    nonzero pattern symmetry 37%
    numeric value symmetry 20%
    Cholesky candidate?no
    positive definite?no

    authorV. Batagelj
    editorV. Batagelj
    kinddirected weighted graph
    2D/3D problem?no

    Additional fieldssize and type
    nodenamefull 24-by-9
    coordfull 24-by-3


    Pajek network converted to sparse adjacency matrix for inclusion in UF sparse 
    matrix collection, Tim Davis.  For Pajek datasets, See V. Batagelj & A. Mrvar,

    Ordering statistics:AMD METIS
    nnz(chol(P*(A+A'+s*I)*P'))95 96
    Cholesky flop count4.7e+002 4.8e+002
    nnz(L+U), no partial pivoting166 168
    nnz(V) for QR, upper bound nnz(L) for LU64 60
    nnz(R) for QR, upper bound nnz(U) for LU144 154

    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.