1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74
|
% Generated by roxygen2 (4.1.1): do not edit by hand
% Please edit documentation in R/games.R
\name{sample_bipartite}
\alias{bipartite}
\alias{bipartite.random.game}
\alias{sample_bipartite}
\title{Bipartite random graphs}
\usage{
sample_bipartite(n1, n2, type = c("gnp", "gnm"), p, m, directed = FALSE,
mode = c("out", "in", "all"))
bipartite(...)
}
\arguments{
\item{n1}{Integer scalar, the number of bottom vertices.}
\item{n2}{Integer scalar, the number of top vertices.}
\item{type}{Character scalar, the type of the graph, \sQuote{gnp} creates a
$G(n,p)$ graph, \sQuote{gnm} creates a $G(n,m)$ graph. See details below.}
\item{p}{Real scalar, connection probability for $G(n,p)$ graphs. Should not
be given for $G(n,m)$ graphs.}
\item{m}{Integer scalar, the number of edges for $G(n,p)$ graphs. Should not
be given for $G(n,p)$ graphs.}
\item{directed}{Logical scalar, whether to create a directed graph. See also
the \code{mode} argument.}
\item{mode}{Character scalar, specifies how to direct the edges in directed
graphs. If it is \sQuote{out}, then directed edges point from bottom
vertices to top vertices. If it is \sQuote{in}, edges point from top
vertices to bottom vertices. \sQuote{out} and \sQuote{in} do not generate
mutual edges. If this argument is \sQuote{all}, then each edge direction is
considered independently and mutual edges might be generated. This argument
is ignored for undirected graphs.}
\item{...}{Passed to \code{sample_bipartite}.}
}
\value{
A bipartite igraph graph.
}
\description{
Generate bipartite graphs using the Erdos-Renyi model
}
\details{
Similarly to unipartite (one-mode) 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 probablity $p$, independently of the rest of the edges. In $G(n,m)$, we
uniformly choose $m$ edges to realize.
}
\examples{
## 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")
}
\author{
Gabor Csardi \email{csardi.gabor@gmail.com}
}
\seealso{
\code{\link{sample_gnp}} for the unipartite version.
}
\keyword{graphs}
|