Matrix: Pajek/geom
Description: Pajek network: collaboration in computational geometry
(undirected graph drawing) |
Matrix properties | |
number of rows | 7,343 |
number of columns | 7,343 |
nonzeros | 23,796 |
# strongly connected comp. | 2,060 |
explicit zero entries | 0 |
nonzero pattern symmetry | symmetric |
numeric value symmetry | symmetric |
type | integer |
structure | symmetric |
Cholesky candidate? | no |
positive definite? | no |
author | Edelsbrunner, van Leeuwen, Guibas, Stolfi |
editor | V. Batagelj |
date | 2002 |
kind | undirected weighted graph |
2D/3D problem? | no |
Additional fields | size and type |
nodename | full 7343-by-31 |
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/. ------------------------------------------------------------------------------
SVD-based statistics: | |
norm(A) | 204.482 |
min(svd(A)) | 2.49988e-57 |
cond(A) | 8.17967e+58 |
rank(A) | 5,499 |
null space dimension | 1,844 |
full numerical rank? | no |
singular value gap | 6.33794e+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.