• 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/Tina_DisCog
  • Description: Pajek network: student govt, Univ. Ljubljana, 1992 (discuss, recog.)
  • download as a MATLAB mat-file, file size: 1 KB. Use SJget(48) or SJget('Pajek/Tina_DisCog') in MATLAB.
  • download in Matrix Market format, file size: 814 bytes.
  • download in Rutherford/Boeing format, file size: 826 bytes.


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


    Matrix properties (click for a legend)  
    number of rows11
    number of columns11
    structural full rank?yes
    structural rank11
    numerical rank 10
    dimension of the numerical null space1
    numerical rank / min(size(A))0.90909
    Euclidean norm of A 5.2026
    calculated singular value # 100.17004
    numerical rank defined using a tolerance
    max(size(A))*eps(norm(A)) =
    calculated singular value # 114.2919e-017
    gap in the singular values at the numerical rank:
    singular value # 10 / singular value # 11
    calculated condition number1.2122e+017
    # of blocks from dmperm2
    # strongly connected comp.1
    entries not in dmperm blocks3
    explicit zero entries0
    nonzero pattern symmetry 50%
    numeric value symmetry 50%
    Cholesky candidate?no
    positive definite?no

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

    Additional fieldssize and type
    nodenamefull 11-by-10


    Pajek network converted to sparse adjacency matrix for inclusion in UF sparse 
    matrix collection, Tim Davis.  For Pajek datasets, See V. Batagelj & A. Mrvar,
     STUDENT GOVERNMENT OF UNIVERSITY OF LJUBLJANA (Hlebec 1992)                  
     discussion, recognition                                                      

    Ordering statistics:AMD METIS DMPERM+
    nnz(chol(P*(A+A'+s*I)*P'))51 52 45
    Cholesky flop count2.8e+002 2.9e+002 2.3e+002
    nnz(L+U), no partial pivoting91 93 82
    nnz(V) for QR, upper bound nnz(L) for LU42 44 31
    nnz(R) for QR, upper bound nnz(U) for LU55 59 55

    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.