Northwest USA

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

Metadata

Code9N
Internal namedimacs9-NW
NameNorthwest 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 =1,207,945
Volume m =2,820,774
Loop count l =0
Wedge count s =2,414,774
Claw count z =17,007,896
Cross count x =15,343,462
Triangle count t =21,527
Square count q =64,556
4-Tour count T4 =12,996,318
Maximum degree dmax =18
Maximum outdegree d+max =9
Maximum indegree dmax =9
Average degree d =4.670 37
Fill p =1.933 19 × 10−6
Size of LCC N =1,207,945
Size of LSCC Ns =1,207,945
Relative size of LSCC Nrs =1.000 00
Diameter δ =1,994
50-Percentile effective diameter δ0.5 =763.928
90-Percentile effective diameter δ0.9 =1,155.23
Median distance δM =764
Mean distance δm =754.722
Gini coefficient G =0.219 823
Balanced inequality ratio P =0.414 165
Outdegree balanced inequality ratio P+ =0.414 165
Indegree balanced inequality ratio P =0.414 165
Relative edge distribution entropy Her =0.993 873
Power law exponent γ =2.332 13
Tail power law exponent γt =6.861 00
Degree assortativity ρ =+0.048 149 4
Degree assortativity p-value pρ =0.000 00
In/outdegree correlation ρ± =+1.000 00
Clustering coefficient c =0.026 744 1
Directed clustering coefficient c± =0.026 744 1
Spectral norm α =8.375 31
Operator 2-norm ν =4.187 65
Cyclic eigenvalue π =4.187 65
Algebraic connectivity a =6.362 32 × 10−7
Reciprocity y =1.000 00
Non-bipartivity bA =0.065 255 6
Normalized non-bipartivity bN =0.000 148 562
Algebraic non-bipartivity χ =0.000 296 058
Spectral bipartite frustration bK =3.169 53 × 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

Clustering coefficient distribution

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 ]