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.

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)

out_degree, in_degree | The degrees of each node in the graph |
---|---|

method | The algorithm to use for the generation. Either |

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 |

A tbl_graph object

`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_erdos_renyi`

: Create graphs with a fixed edge probability or count. See`igraph::sample_gnp()`

and`igraph::sample_gnm()`

`play_geometry`

: Create graphs by positioning nodes on a plane or torus and connecting nearby ones. See`igraph::sample_grg()`

Other graph games: `component_games`

,
`evolution_games`

, `type_games`