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.
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
)A graph object of class dgr_graph.
The dimension of the starting lattice.
The size of the lattice across each dimension.
The neighborhood where the lattice nodes are to be connected.
The rewiring probability.
A logical value (default is FALSE) that governs whether loops
are allowed to be created.
A logical value (default is FALSE) that governs whether
multiple edges are allowed to be created.
An optional string that describes the entity type for all the nodes to be added.
A logical value where setting to TRUE ascribes node IDs to the
label and FALSE yields a blank label.
An optional string for providing a relationship label to all edges to be added.
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).
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).
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.
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.
Supplying a value sets a random seed of the
Mersenne-Twister implementation.
A graph object of class dgr_graph.
# 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()
#> [1] 50
# Get a count of edges
smallworld_graph %>% count_edges()
#> [1] 50