edge.connectivity(graph, source=NULL, target=NULL)
edge.disjoint.paths(graph, source, target)
graph.adhesion(graph)edge.connectivity it can be NULL, see details below.edge.connectivity it can be NULL, see details below.source and
target) is the minimum number of edges needed to remove to
eliminate all (directed) paths from source to target.
edge.connectivity calculates this quantity if both the
source and target arguments are given (and not
NULL). The edge connectivity of a graph is the minimum of the edge
connectivity of every (ordered) pair of vertices in the graph.
edge.connectivity calculates this quantity if neither the
source nor the target arguments are given (ie. they are
both NULL).
A set of edge disjoint paths between two vertices is a set of paths between them containing no common edges. The maximum number of edge disjoint paths between two vertices is the same as their edge connectivity.
The adhesion of a graph is the minimum number of edges needed to remove to obtain a graph which is not strongly connected. This is the same as the edge connectivity of the graph.
The three functions documented on this page calculate similar
properties, more precisely the most general is
edge.connectivity, the others are included only for having more
descriptive function names.
graph.maxflow, vertex.connectivity,
vertex.disjoint.paths, graph.cohesiong <- barabasi.game(100, m=1)
g2 <- barabasi.game(100, m=5)
edge.connectivity(g, 99, 0)
edge.connectivity(g2, 99, 0)
edge.disjoint.paths(g2, 99, 0)
g <- erdos.renyi.game(50, 5/50)
g <- as.directed(g)
g <- subgraph(g, subcomponent(g, 1))
graph.adhesion(g)Run the code above in your browser using DataLab