R: Add a Watts-Strogatz small-world graph

add_smallworld_graph {DiagrammeR}

R Documentation

Add a Watts-Strogatz small-world graph

Description

To an existing graph object, add a graph built according to the Watts-Strogatz small-world model, which uses a lattice along with a rewiring probability to randomly modify edge definitions.

Usage

add_smallworld_graph(graph, dimension, size, neighborhood, p, loops = FALSE,
  multiple = FALSE, type = NULL, label = TRUE, rel = NULL,
  node_aes = NULL, edge_aes = NULL, node_data = NULL, edge_data = NULL,
  set_seed = NULL)

Arguments

`graph`	a graph object of class `dgr_graph`.
`dimension`	the dimension of the starting lattice.
`size`	the size of the lattice across each dimension.
`neighborhood`	the neighborhood where the lattice nodes are to be connected.
`p`	the rewiring probability.
`loops`	a logical value (default is `FALSE`) that governs whether loops are allowed to be created.
`multiple`	a logical value (default is `FALSE`) that governs whether multiple edges are allowed to be created.
`type`	an optional string that describes the entity type for all the nodes to be added.
`label`	a boolean value where setting to `TRUE` ascribes node IDs to the label and `FALSE` yields a blank label.
`rel`	an optional string for providing a relationship label to all edges to be added.
`node_aes`	an optional list of named vectors comprising node aesthetic attributes. The helper function `node_aes()` is strongly recommended for use here as it contains arguments for each of the accepted node aesthetic attributes (e.g., `shape`, `style`, `color`, `fillcolor`).
`edge_aes`	an optional list of named vectors comprising edge aesthetic attributes. The helper function `edge_aes()` is strongly recommended for use here as it contains arguments for each of the accepted edge aesthetic attributes (e.g., `shape`, `style`, `penwidth`, `color`).
`node_data`	an optional list of named vectors comprising node data attributes. The helper function `node_data()` is strongly recommended for use here as it helps bind data specifically to the created nodes.
`edge_data`	an optional list of named vectors comprising edge data attributes. The helper function `edge_data()` is strongly recommended for use here as it helps bind data specifically to the created edges.
`set_seed`	supplying a value sets a random seed of the `Mersenne-Twister` implementation.

Examples

# Create an undirected smallworld
# graph with 100 nodes using
# a probability value of 0.05
smallworld_graph <-
  create_graph(
    directed = FALSE) %>%
  add_smallworld_graph(
    dimension = 1,
    size = 50,
    neighborhood = 1,
    p = 0.05,
    set_seed = 23)

# Get a count of nodes
smallworld_graph %>%
  count_nodes()

# Get a count of edges
smallworld_graph %>%
  count_edges()

[Package DiagrammeR version 1.0.1 Index]