Connected components of a graph
is.connected(graph, mode="weak") clusters(graph, mode="weak") no.clusters(graph, mode="weak") cluster.distribution(graph, cumulative = FALSE, mul.size = FALSE, ...)
- The graph to analyze.
- Character string, either
weakor strong. For directed graphs weakimplies weakly, strongstrongly connected components to search. It is ignored for undirected graphs.
- Logical, if TRUE the cumulative distirubution (relative frequency) is calculated.
- Logical. If TRUE the relative frequencies will be multiplied by the cluster sizes.
- Additional attributes to pass to
cluster, right now only
is.connected decides whether the graph is weakly or strongly
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
cluster.distribution creates a histogram for the maximal
connected component sizes.
Breadth-first search is conducted from each not-yet visited
is.connecteda logical constant. For
clustersa named list with two components:
csize numeric vector giving the sizes of the clusters.
g <- erdos.renyi.game(20, 1/20) clusters(g)