• 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_AskCal
  • Description: Pajek network: student govt, Univ. Ljubljana, 1992 (ask opin., recall)
  • download as a MATLAB mat-file, file size: 1 KB. Use SJget(46) or SJget('Pajek/Tina_AskCal') in MATLAB.
  • download in Matrix Market format, file size: 779 bytes.
  • download in Rutherford/Boeing format, file size: 821 bytes.


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


    scc of Pajek/Tina_AskCal

    Matrix properties (click for a legend)  
    number of rows11
    number of columns11
    structural full rank?no
    structural rank9
    numerical rank 9
    dimension of the numerical null space2
    numerical rank / min(size(A))0.81818
    Euclidean norm of A 3.5455
    calculated singular value # 90.30155
    numerical rank defined using a tolerance
    max(size(A))*eps(norm(A)) =
    calculated singular value # 104.8417e-017
    gap in the singular values at the numerical rank:
    singular value # 9 / singular value # 10
    calculated condition numberInf
    # of blocks from dmperm2
    # strongly connected comp.4
    explicit zero entries0
    nonzero pattern symmetry 28%
    numeric value symmetry 28%
    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)                  
     asking for an opinion, recall                                                

    Ordering statistics:AMD METIS
    nnz(chol(P*(A+A'+s*I)*P'))40 44
    Cholesky flop count1.6e+002 2.0e+002
    nnz(L+U), no partial pivoting69 77
    nnz(V) for QR, upper bound nnz(L) for LU18 20
    nnz(R) for QR, upper bound nnz(U) for LU35 38

    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.