## File: sampling_games.Rd

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r-cran-tidygraph 1.2.0-1
 123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102 % Generated by roxygen2: do not edit by hand % Please edit documentation in R/play.R \name{sampling_games} \alias{sampling_games} \alias{play_degree} \alias{play_dotprod} \alias{play_fitness} \alias{play_fitness_power} \alias{play_erdos_renyi} \alias{play_geometry} \title{Graph games based on direct sampling} \usage{ play_degree(out_degree, in_degree = NULL, method = "simple") play_dotprod(position, directed = TRUE) play_fitness(m, out_fit, in_fit = NULL, loops = FALSE, multiple = FALSE) play_fitness_power( n, m, out_exp, in_exp = -1, loops = FALSE, multiple = FALSE, correct = TRUE ) play_erdos_renyi(n, p, m, directed = TRUE, loops = FALSE) play_geometry(n, radius, torus = FALSE) } \arguments{ \item{out_degree, in_degree}{The degrees of each node in the graph} \item{method}{The algorithm to use for the generation. Either \code{'simple'}, \code{'vl'}, or \code{'simple.no.multiple'}} \item{position}{The latent position of each node by column.} \item{directed}{Should the resulting graph be directed} \item{m}{The number of edges in the graph} \item{out_fit, in_fit}{The fitness of each node} \item{loops}{Are loop edges allowed} \item{multiple}{Are multiple edges allowed} \item{n}{The number of nodes in the graph.} \item{out_exp, in_exp}{Power law exponent of degree distribution} \item{correct}{Use finite size correction} \item{p}{The probabilty of an edge occuring} \item{radius}{The radius within which vertices are connected} \item{torus}{Should the vertices be distributed on a torus instead of a plane} } \value{ A tbl_graph object } \description{ This set of graph games creates graphs directly through sampling of different attributes, topologies, etc. The nature of their algorithm is described in detail at the linked igraph documentation. } \section{Functions}{ \itemize{ \item \code{play_degree}: Create graphs based on the given node degrees. See \code{\link[igraph:sample_degseq]{igraph::sample_degseq()}} \item \code{play_dotprod}: Create graphs with link probability given by the dot product of the latent position of termintating nodes. See \code{\link[igraph:sample_dot_product]{igraph::sample_dot_product()}} \item \code{play_fitness}: Create graphs where edge probabilities are proportional to terminal node fitness scores. See \code{\link[igraph:sample_fitness]{igraph::sample_fitness()}} \item \code{play_fitness_power}: Create graphs with an expected power-law degree distribution. See \code{\link[igraph:sample_fitness_pl]{igraph::sample_fitness_pl()}} \item \code{play_erdos_renyi}: Create graphs with a fixed edge probability or count. See \code{\link[igraph:sample_gnp]{igraph::sample_gnp()}} and \code{\link[igraph:sample_gnm]{igraph::sample_gnm()}} \item \code{play_geometry}: Create graphs by positioning nodes on a plane or torus and connecting nearby ones. See \code{\link[igraph:sample_grg]{igraph::sample_grg()}} }} \examples{ plot(play_erdos_renyi(20, 0.3)) } \seealso{ Other graph games: \code{\link{component_games}}, \code{\link{evolution_games}}, \code{\link{type_games}} } \concept{graph games}