random.graph: Generate A Random Graph/DAG

In rlebron-bioinfo/gnlearn: Genetic Network Learning

Description

This function allows you to generate a random graph/DAG.

Usage

random.graph(
  nodes,
  exp.degree,
  dag = TRUE,
  plot = TRUE,
  algorithm = c("regular", "watts", "er", "power", "bipartite", "barabasi",
    "geometric"),
  to = "igraph",
  ...
)

Arguments

nodes	Number of nodes or vector of node names.
exp.degree	Number of expected degree per node.
dag	Whether the graph should be a DAG or not. Default: TRUE
plot	Whether or not to plot the graph. Default: TRUE
algorithm	Algorithm to be used to generate the graph: 'regular', 'watts', 'er', 'power', 'bipartite', 'barabasi', or 'geometric'. Default: 'regular'
to	Output format ('adjacency', 'edges', 'graph', 'igraph', or 'bnlearn').

Examples

graph <- random.graph(LETTERS[1:15], 3, dag=TRUE)
graph <- random.graph(LETTERS[1:15], 3, dag=FALSE)
graph <- random.graph(15, 3, dag=TRUE)
graph <- random.graph(15, 3, dag=FALSE)

rlebron-bioinfo/gnlearn documentation built on July 25, 2020, 12:38 p.m.