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The package includes efficient implementations of the clustering coefficient and transitivity for weighted networks introduced by . As they can be applied to weighted graphs in general and not only to their partition into communities, they are simply called with the graph as the only argument:
data(karate, package="igraphdata")
weighted_clustering_coefficient(karate)
#> This graph was created by an old(er) igraph version.
#> Call upgrade_graph() on it to use with the current igraph version
#> For now we convert it on the fly...
#> [1] 0.8127164To be able to obtain the result for every community in the graph, we provide the function apply_subgraphs; which given a graph, a membership vector and a scalar function, applies the function to every community and returns the vector of results. In this case it works as follows:
apply_subgraphs(karate, V(karate)$Faction, weighted_clustering_coefficient)
#> [1] 0.9514233 0.7783815These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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