A bipartite graph is projected into two one-mode networks
bipartite_projection(
graph,
types = NULL,
multiplicity = TRUE,
probe1 = NULL,
which = c("both", "true", "false"),
remove.type = TRUE
)
bipartite_projection_size(graph, types = NULL)The input graph. It can be directed, but edge directions are ignored during the computation.
An optional vertex type vector to use instead of the
‘type’ vertex attribute. You must supply this argument if the
graph has no ‘type’ vertex attribute.
If TRUE, then igraph keeps the multiplicity of
the edges as an edge attribute called ‘weight’.
E.g. if there is an A-C-B and also an A-D-B
triple in the bipartite graph (but no more X, such that A-X-B is also in the
graph), then the multiplicity of the A-B edge in the projection will be 2.
This argument can be used to specify the order of the
projections in the resulting list. If given, then it is considered as a
vertex id (or a symbolic vertex name); the projection containing this vertex
will be the first one in the result list. This argument is ignored if only
one projection is requested in argument which.
A character scalar to specify which projection(s) to calculate. The default is to calculate both.
Logical scalar, whether to remove the type vertex
attribute from the projections. This makes sense because these graphs are
not bipartite any more. However if you want to combine them with each other
(or other bipartite graphs), then it is worth keeping this attribute. By
default it will be removed.
A list of two undirected graphs. See details above.
Bipartite graphs have a type vertex attribute in igraph, this is
boolean and FALSE for the vertices of the first kind and TRUE
for vertices of the second kind.
bipartite_projection_size() calculates the number of vertices and edges
in the two projections of the bipartite graphs, without calculating the
projections themselves. This is useful to check how much memory the
projections would need if you have a large bipartite graph.
bipartite_projection() calculates the actual projections. You can use
the probe1 argument to specify the order of the projections in the
result. By default vertex type FALSE is the first and TRUE is
the second.
bipartite_projection() keeps vertex attributes.
Bipartite graphs
bipartite_mapping(),
is_bipartite(),
make_bipartite_graph()
## Projection of a full bipartite graph is a full graph
g <- make_full_bipartite_graph(10, 5)
proj <- bipartite_projection(g)
isomorphic(proj[[1]], make_full_graph(10))
#> [1] TRUE
isomorphic(proj[[2]], make_full_graph(5))
#> [1] TRUE
## The projection keeps the vertex attributes
M <- matrix(0, nrow = 5, ncol = 3)
rownames(M) <- c("Alice", "Bob", "Cecil", "Dan", "Ethel")
colnames(M) <- c("Party", "Skiing", "Badminton")
M[] <- sample(0:1, length(M), replace = TRUE)
M
#> Party Skiing Badminton
#> Alice 0 1 1
#> Bob 1 1 0
#> Cecil 0 0 0
#> Dan 1 1 0
#> Ethel 1 0 0
g2 <- graph_from_biadjacency_matrix(M)
g2$name <- "Event network"
proj2 <- bipartite_projection(g2)
print(proj2[[1]], g = TRUE, e = TRUE)
#> IGRAPH 9aacda9 UNW- 5 5 -- Event network
#> + attr: name (g/c), name (v/c), weight (e/n)
#> + edges from 9aacda9 (vertex names):
#> [1] Alice--Bob Alice--Dan Bob --Dan Bob --Ethel Dan --Ethel
print(proj2[[2]], g = TRUE, e = TRUE)
#> IGRAPH ea9b7f0 UNW- 3 2 -- Event network
#> + attr: name (g/c), name (v/c), weight (e/n)
#> + edges from ea9b7f0 (vertex names):
#> [1] Party --Skiing Skiing--Badminton