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.
out_degree, in_degree: The degrees of each node in the graph
method: The algorithm to use for the generation. Either 'simple', 'vl', or 'simple.no.multiple'
position: The latent position of each node by column.
directed: Should the resulting graph be directed
m: The number of edges in the graph
out_fit, in_fit: The fitness of each node
loops: Are loop edges allowed
multiple: Are multiple edges allowed
n: The number of nodes in the graph.
out_exp, in_exp: Power law exponent of degree distribution
correct: Use finite size correction
p: The probabilty of an edge occuring
radius: The radius within which vertices are connected
torus: Should the vertices be distributed on a torus instead of a plane
Returns
A tbl_graph object
Functions
play_degree(): Create graphs based on the given node degrees. See igraph::sample_degseq()
play_dotprod(): Create graphs with link probability given by the dot product of the latent position of termintating nodes. See igraph::sample_dot_product()
play_fitness(): Create graphs where edge probabilities are proportional to terminal node fitness scores. See igraph::sample_fitness()
play_fitness_power(): Create graphs with an expected power-law degree distribution. See igraph::sample_fitness_pl()
play_gnm(): Create graphs with a fixed edge count. See igraph::sample_gnm()
play_gnp(): Create graphs with a fixed edge probability. See igraph::sample_gnp()
play_geometry(): Create graphs by positioning nodes on a plane or torus and connecting nearby ones. See igraph::sample_grg()
play_erdos_renyi(): Create graphs with a fixed edge probability or count. See igraph::sample_gnp() and igraph::sample_gnm()
Examples
plot(play_erdos_renyi(20,0.3))
See Also
Other graph games: component_games, evolution_games, type_games