Chicago
This is the directed road transportation network of the Chicago region (USA).
Nodes are transport nodes, and edges are directed connections.
Metadata
Statistics
Size | n = | 12,982
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Volume | m = | 39,018
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Loop count | l = | 0
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Wedge count | s = | 53,155
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Claw count | z = | 435,211
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Cross count | x = | 558,250
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Triangle count | t = | 807
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Square count | q = | 3,027
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4-Tour count | T4 = | 278,090
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Maximum degree | dmax = | 14
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Maximum outdegree | d+max = | 7
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Maximum indegree | d−max = | 7
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Average degree | d = | 6.011 09
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Fill | p = | 0.000 231 641
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Size of LCC | N = | 12,979
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Size of LSCC | Ns = | 12,978
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Relative size of LSCC | Nrs = | 0.999 692
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Diameter | δ = | 106
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50-Percentile effective diameter | δ0.5 = | 42.128 0
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90-Percentile effective diameter | δ0.9 = | 66.912 8
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Median distance | δM = | 43
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Mean distance | δm = | 43.265 7
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Gini coefficient | G = | 0.216 238
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Balanced inequality ratio | P = | 0.424 573
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Outdegree balanced inequality ratio | P+ = | 0.424 266
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Indegree balanced inequality ratio | P− = | 0.424 727
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Relative edge distribution entropy | Her = | 0.990 770
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Power law exponent | γ = | 1.938 81
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Tail power law exponent | γt = | 8.581 00
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Tail power law exponent with p | γ3 = | 8.581 00
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p-value | p = | 0.000 00
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Outdegree tail power law exponent with p | γ3,o = | 8.541 00
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Outdegree p-value | po = | 0.000 00
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Indegree tail power law exponent with p | γ3,i = | 8.531 00
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Indegree p-value | pi = | 0.000 00
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Degree assortativity | ρ = | −0.119 111
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Degree assortativity p-value | pρ = | 3.316 99 × 10−130
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In/outdegree correlation | ρ± = | +0.960 178
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Clustering coefficient | c = | 0.045 546 0
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Directed clustering coefficient | c± = | 0.045 312 4
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Spectral norm | α = | 8.453 35
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Operator 2-norm | ν = | 4.227 22
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Cyclic eigenvalue | π = | 4.226 24
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Algebraic connectivity | a = | 0.000 795 844
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Spectral separation | |λ1[A] / λ2[A]| = | 1.048 43
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Reciprocity | y = | 0.942 693
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Non-bipartivity | bA = | 0.098 109 0
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Normalized non-bipartivity | bN = | 0.022 914 0
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Algebraic non-bipartivity | χ = | 0.051 149 7
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Spectral bipartite frustration | bK = | 0.004 023 08
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Controllability | C = | 1,060
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Relative controllability | Cr = | 0.081 670 4
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Plots
Matrix decompositions plots
Downloads
References
[1]
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Jérôme Kunegis.
KONECT – The Koblenz Network Collection.
In Proc. Int. Conf. on World Wide Web Companion, pages
1343–1350, 2013.
[ http ]
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[2]
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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.
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[3]
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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.
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