Matrix: Pajek/GD97_b
Description: Pajek network: Graph Drawing contest 1997
(undirected graph drawing) |
Matrix properties | |
number of rows | 47 |
number of columns | 47 |
nonzeros | 264 |
# strongly connected comp. | 2 |
explicit zero entries | 0 |
nonzero pattern symmetry | symmetric |
numeric value symmetry | symmetric |
type | real |
structure | symmetric |
Cholesky candidate? | no |
positive definite? | no |
author | Graph Drawing Contest |
editor | V. Batagelj |
date | 1997 |
kind | undirected weighted graph |
2D/3D problem? | no |
Additional fields | size and type |
nodename | full 47-by-30 |
coord | full 47-by-2 |
Notes:
------------------------------------------------------------------------------ Pajek network converted to sparse adjacency matrix for inclusion in UF sparse matrix collection, Tim Davis. For Pajek datasets, See V. Batagelj & A. Mrvar, http://vlado.fmf.uni-lj.si/pub/networks/data/. ------------------------------------------------------------------------------ Regarding conversion for UF sparse matrix collection: in the original data every edge appears exactly twice, with the same edge weight. It could be a multigraph, but it looks more like a graph. The duplicate edges are removed in this version. You can always add them back in yourself; just look at 2*A. ------------------------------------------------------------------------------ The original problem had 3D xyz coordinates, but all values of z were equal to 0.5, and have been removed. This graph has 2D coordinates.
SVD-based statistics: | |
norm(A) | 2841.06 |
min(svd(A)) | 0 |
cond(A) | Inf |
rank(A) | 44 |
null space dimension | 3 |
full numerical rank? | no |
singular value gap | 8.48707e+09 |
singular values (MAT file): | click here |
SVD method used: | s = svd (full (A)) |
status: | ok |
For a description of the statistics displayed above, click here.
Maintained by Tim Davis, last updated 12-Mar-2014.
Matrix pictures by cspy, a MATLAB function in the CSparse package.
Matrix graphs by Yifan Hu, AT&T Labs Visualization Group.