Use this if you are using igraph from R
These functions find all, the largest or all the maximal cliques in an undirected graph. The size of the largest clique can also be calculated.
cliques(graph, min = 0, max = 0) max_cliques(graph, min = NULL, max = NULL, subset = NULL, file = NULL)
The input graph, directed graphs will be considered as undirected ones, multiple edges and loops are ignored.
Numeric constant, lower limit on the size of the cliques to find.
Numeric constant, upper limit on the size of the cliques to find.
cliques find all complete subgraphs in the input graph, obeying the
size limitations given in the
largest_cliques finds all largest cliques in the input graph. A
clique is largest if there is no other clique including more vertices.
max_cliques finds all maximal cliques in the input graph. A
clique is maximal if it cannot be extended to a larger clique. The largest
cliques are always maximal, but a maximal clique is not necessarily the
count_max_cliques counts the maximal cliques.
clique_num calculates the size of the largest clique(s).
clique_size_counts returns a numeric vector representing a histogram
of clique sizes, between the given minimum and maximum clique size.
return a list containing numeric vectors of vertex ids. Each list element is
a clique, i.e. a vertex sequence of class
NULL, invisibly, if its
argument is not
NULL. The output is written to the specified file in
count_max_cliques return an integer
clique_size_counts returns a numeric vector with the clique sizes such that
the i-th item belongs to cliques of size i. Trailing zeros are currently
truncated, but this might change in future versions.
For maximal cliques the following algorithm is implemented: David Eppstein, Maarten Loffler, Darren Strash: Listing All Maximal Cliques in Sparse Graphs in Near-optimal Time. https://arxiv.org/abs/1006.5440
# this usually contains cliques of size six g <- sample_gnp(100, 0.3) clique_num(g) cliques(g, min=6) largest_cliques(g) # To have a bit less maximal cliques, about 100-200 usually g <- sample_gnp(100, 0.03) max_cliques(g)