Chicago

This is the directed road transportation network of the Chicago region (USA). Nodes are transport nodes, and edges are directed connections.

Metadata

CodeCR
Internal nametntp-ChicagoRegional
NameChicago
Data sourcehttp://www.bgu.ac.il/~bargera/tntp/
AvailabilityDataset is available for download
Consistency checkDataset passed all tests
Category
Infrastructure network
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 =12,982
Volume m =39,018
Loop count l =0
Wedge count s =53,155
Claw count z =435,211
Cross count x =558,250
Triangle count t =807
Square count q =3,027
4-Tour count T4 =278,090
Maximum degree dmax =14
Maximum outdegree d+max =7
Maximum indegree dmax =7
Average degree d =6.011 09
Fill p =0.000 231 641
Size of LCC N =12,979
Size of LSCC Ns =12,978
Relative size of LSCC Nrs =0.999 692
Diameter δ =106
50-Percentile effective diameter δ0.5 =42.128 0
90-Percentile effective diameter δ0.9 =66.912 8
Median distance δM =43
Mean distance δm =43.265 7
Gini coefficient G =0.216 238
Relative edge distribution entropy Her =0.990 770
Power law exponent γ =1.938 81
Tail power law exponent γt =8.581 00
Tail power law exponent with p γ3 =8.581 00
p-value p =0.000 00
Outdegree tail power law exponent with p γ3,o =8.541 00
Outdegree p-value po =0.000 00
Indegree tail power law exponent with p γ3,i =8.531 00
Indegree p-value pi =0.000 00
Degree assortativity ρ =−0.119 111
Degree assortativity p-value pρ =3.316 99 × 10−130
In/outdegree correlation ρ± =+0.960 178
Clustering coefficient c =0.045 546 0
Directed clustering coefficient c± =0.045 312 4
Spectral norm α =8.453 35
Operator 2-norm ν =4.227 22
Cyclic eigenvalue π =4.226 24
Algebraic connectivity a =0.000 795 844
Reciprocity y =0.942 693
Non-bipartivity bA =0.098 109 0
Normalized non-bipartivity bN =0.022 914 0
Algebraic non-bipartivity χ =0.051 149 7
Spectral bipartite frustration bK =0.004 023 08

Plots

Fruchterman–Reingold graph drawing

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

Degree assortativity

Zipf plot

Hop distribution

Double Laplacian graph drawing

Delaunay graph drawing

In/outdegree scatter plot

Clustering coefficient distribution

Average neighbor degree 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 ]
[2] R. W. Eash, K. S. Chon, Y. J. Lee, and D. E. Boyce. Equilibrium traffic assignment on an aggregated highway network for sketch planning. Transp. Res. Record, 994:30–37, 1983.
[3] D. E. Boyce, K. S. Chon, M. E. Ferris, Y. J. Lee, K-T. Lin, and R. W. Eash. Implementation and evaluation of combined models of urban travel and location on a sketch planning network. Chicago Area Transp. Study, pages xii + 169, 1985.