Use this if you are using igraph from R
sample_bipartite {igraph}  R Documentation 
Generate bipartite graphs using the ErdosRenyi model
sample_bipartite(
n1,
n2,
type = c("gnp", "gnm"),
p,
m,
directed = FALSE,
mode = c("out", "in", "all")
)
bipartite(...)
n1 
Integer scalar, the number of bottom vertices. 
n2 
Integer scalar, the number of top vertices. 
type 
Character scalar, the type of the graph, ‘gnp’ creates a

p 
Real scalar, connection probability for 
m 
Integer scalar, the number of edges for 
directed 
Logical scalar, whether to create a directed graph. See also
the 
mode 
Character scalar, specifies how to direct the edges in directed graphs. If it is ‘out’, then directed edges point from bottom vertices to top vertices. If it is ‘in’, edges point from top vertices to bottom vertices. ‘out’ and ‘in’ do not generate mutual edges. If this argument is ‘all’, then each edge direction is considered independently and mutual edges might be generated. This argument is ignored for undirected graphs. 
... 
Passed to 
Similarly to unipartite (onemode) networks, we can define the G(n,p)
, and
G(n,m)
graph classes for bipartite graphs, via their generating process.
In G(n,p)
every possible edge between top and bottom vertices is realized
with probability p
, independently of the rest of the edges. In G(n,m)
, we
uniformly choose m
edges to realize.
A bipartite igraph graph.
Gabor Csardi csardi.gabor@gmail.com
sample_gnp
for the unipartite version.
## empty graph
sample_bipartite(10, 5, p=0)
## full graph
sample_bipartite(10, 5, p=1)
## random bipartite graph
sample_bipartite(10, 5, p=.1)
## directed bipartite graph, G(n,m)
sample_bipartite(10, 5, type="Gnm", m=20, directed=TRUE, mode="all")