• 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/ODLIS
  • Description: Pajek network: online dictionary of library & inf. sci
  • download as a MATLAB mat-file, file size: 89 KB. Use SJget(38) or SJget('Pajek/ODLIS') in MATLAB.
  • download in Matrix Market format, file size: 72 KB.
  • download in Rutherford/Boeing format, file size: 57 KB.


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


    scc of Pajek/ODLIS

    Matrix properties (click for a legend)  
    number of rows2,909
    number of columns2,909
    structural full rank?no
    structural rank1,961
    numerical rank 1,959
    dimension of the numerical null space950
    numerical rank / min(size(A))0.67343
    Euclidean norm of A 36.329
    calculated singular value # 19590.080695
    numerical rank defined using a tolerance
    max(size(A))*eps(norm(A)) =
    calculated singular value # 19603.8505e-014
    gap in the singular values at the numerical rank:
    singular value # 1959 / singular value # 1960
    calculated condition numberInf
    # of blocks from dmperm588
    # strongly connected comp.1,028
    explicit zero entries0
    nonzero pattern symmetry 20%
    numeric value symmetry 20%
    Cholesky candidate?no
    positive definite?no

    authorJ. Reitz
    editorV. Batagelj, A. Mrvar
    kinddirected multigraph
    2D/3D problem?no

    Additional fieldssize and type
    nodenamefull 2909-by-79


    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'))128,029 142,186
    Cholesky flop count2.9e+007 3.0e+007
    nnz(L+U), no partial pivoting253,149 281,463
    nnz(V) for QR, upper bound nnz(L) for LU495,628 455,220
    nnz(R) for QR, upper bound nnz(U) for LU187,289 208,989

    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.