Calculate clustering coefficient for an undirected graph
Calculate clustering coefficient for an undirected graph
clusteringCoef(g, Weighted=FALSE, vW=degree(g))
g |
an instance of the |
Weighted |
calculate weighted clustering coefficient or not |
vW |
vertex weights to use when calculating weighted clustering coefficient |
For an undirected graph G, let delta(v) be the number of triangles with
v
as a node, let tau(v) be the number of triples, i.e., paths of length 2 with
v as the center node.
Let V' be the set of nodes with degree at least 2.
Define clustering coefficient for v, c(v) = (delta(v) / tau(v)).
Define clustering coefficient for G, C(G) = sum(c(v)) / |V'|,
for all v in V'.
Define weighted clustering coefficient for g,
Cw(G) = sum(w(v) * c(v)) / sum(w(v)), for all v in V'.
Clustering coefficient for graph G.
Li Long li.long@isb-sib.ch
Approximating Clustering Coefficient and Transitivity, T. Schank, D. Wagner, Journal of Graph Algorithms and Applications, Vol. 9, No. 2 (2005).
clusteringCoefAppr, transitivity, graphGenerator
con <- file(system.file("XML/conn.gxl",package="RBGL"))
g <- fromGXL(con)
close(con)
cc <- clusteringCoef(g)
ccw1 <- clusteringCoef(g, Weighted=TRUE)
vW <- c(1, 1, 1, 1, 1,1, 1, 1)
ccw2 <- clusteringCoef(g, Weighted=TRUE, vW)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.