clusters {igraph}R Documentation

Connected components of a graph

Description

Calculate the maximal (weakly or strongly) connected components of a graph

Usage

is.connected(graph, mode=c("weak", "strong"))
clusters(graph, mode=c("weak", "strong"))
no.clusters(graph, mode=c("weak", "strong"))
cluster.distribution(graph, cumulative = FALSE, mul.size = FALSE, ...)

Arguments

graph The graph to analyze.
mode Character string, either “weak” or “strong”. For directed graphs “weak” implies weakly, “strong” strongly connected components to search. It is ignored for undirected graphs.
cumulative Logical, if TRUE the cumulative distirubution (relative frequency) is calculated.
mul.size Logical. If TRUE the relative frequencies will be multiplied by the cluster sizes.
... Additional attributes to pass to cluster, right now only mode makes sense.

Details

is.connected decides whether the graph is weakly or strongly connected.

clusters finds the maximal (weakly or strongly) connected components of a graph.

no.clusters does almost the same as clusters but returns only the number of clusters found instead of returning the actual clusters.

cluster.distribution creates a histogram for the maximal connected component sizes.

Breadth-first search is conducted from each not-yet visited vertex.

Value

For is.connected a logical constant.
For clusters a named list with three components:

membership numeric vector giving the cluster id to which each vertex belongs.
csize numeric vector giving the sizes of the clusters.
no numeric constant, the number of clusters.

normal-bracket42bracket-normal
For no.clusters an integer constant is returned.
For cluster.distribution a numeric vector with the relative frequencies. The length of the vector is the number of components.

Author(s)

Gabor Csardi csardi@rmki.kfki.hu

See Also

subcomponent

Examples

g <- erdos.renyi.game(20, 1/20)
clusters(g)

[Package igraph version 0.5.1 Index]