Western USA

This is the directed road network from the 9th DIMACS Implementation Challenge, for the area "Western USA".

Metadata

Code9W
Internal namedimacs9-W
NameWestern USA
Data sourcehttp://www.diag.uniroma1.it/challenge9/download.shtml
AvailabilityDataset is available for download
Consistency checkDataset passed all tests
Category
Infrastructure network
Dataset timestamp 1991
Node meaningNode
Edge meaningRoad
Network formatUnipartite, directed
Edge typeUnweighted, no multiple edges
ReciprocalContains reciprocal edges
Directed cyclesContains directed cycles
LoopsDoes not contain loops

Statistics

Size n =6,262,104
Volume m =15,119,284
Loop count l =0
Wedge count s =13,348,095
Claw count z =94,902,604
Cross count x =86,980,519
Triangle count t =136,115
Square count q =393,682
4-Tour count T4 =71,661,120
Maximum degree dmax =18
Maximum outdegree d+max =9
Maximum indegree dmax =9
Average degree d =4.828 82
Fill p =3.855 59 × 10−7
Size of LCC N =6,262,104
Size of LSCC Ns =6,262,104
Relative size of LSCC Nrs =1.000 00
Diameter δ =4,420
50-Percentile effective diameter δ0.5 =1,590.00
90-Percentile effective diameter δ0.9 =2,537.29
Mean distance δm =1,592.95
Gini coefficient G =0.208 097
Balanced inequality ratio P =0.421 020
Outdegree balanced inequality ratio P+ =0.421 020
Indegree balanced inequality ratio P =0.421 020
Relative edge distribution entropy Her =0.995 036
Power law exponent γ =2.261 36
Tail power law exponent γt =6.601 00
Degree assortativity ρ =+0.078 943 8
Degree assortativity p-value pρ =0.000 00
Clustering coefficient c =0.030 592 0
Spectral norm α =8.664 63
Operator 2-norm ν =4.332 32
Cyclic eigenvalue π =4.332 32
Algebraic connectivity a =1.105 90 × 10−7
Reciprocity y =1.000 00
Non-bipartivity bA =0.093 651 9
Normalized non-bipartivity bN =6.231 10 × 10−5
Spectral bipartite frustration bK =1.281 31 × 10−5

Plots

Degree distribution

Cumulative degree distribution

Lorenz curve

Spectral distribution of the adjacency matrix

Spectral distribution of the normalized adjacency matrix

Spectral distribution of the Laplacian

Spectral graph drawing based on the adjacency matrix

Spectral graph drawing based on the Laplacian

Spectral graph drawing based on the normalized adjacency matrix

Hop distribution

In/outdegree scatter plot

SynGraphy

Matrix decompositions plots

Downloads

References

[1] Jérôme Kunegis. KONECT – The Koblenz Network Collection. In Proc. Int. Conf. on World Wide Web Companion, pages 1343–1350, 2013. [ http ]