DiagrammeR (version 1.0.0)

add_smallworld_graph: 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

# NOT RUN {
# 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()
# }