Add a G(n, m) Erdos-Renyi graph
To an existing graph object, add a graph built according to the Erdos-Renyi
G(n, m) model. This uses the same constant probability when creating the
fixed number of edges. Thus for n
nodes there will be m
edges and, if the
loops
argument is set as TRUE
, then random loop edges will be part of
m
.
add_gnm_graph( graph, n, m, loops = FALSE, type = NULL, label = TRUE, rel = NULL, node_aes = NULL, edge_aes = NULL, node_data = NULL, edge_data = NULL, set_seed = NULL )
graph |
A graph object of class |
n |
The number of nodes comprising the generated graph. |
m |
The number of edges in the generated graph. |
loops |
A logical value (default is |
type |
An optional string that describes the entity type for all the nodes to be added. |
label |
A boolean value where setting to |
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 |
edge_aes |
An optional list of named vectors comprising edge aesthetic
attributes. The helper function |
node_data |
An optional list of named vectors comprising node data
attributes. The helper function |
edge_data |
An optional list of named vectors comprising edge data
attributes. The helper function |
set_seed |
Supplying a value sets a random seed of the
|
A graph object of class dgr_graph
.
# Create an undirected GNM # graph with 100 nodes and # 120 edges gnm_graph <- create_graph( directed = FALSE) %>% add_gnm_graph( n = 100, m = 120) # Get a count of nodes gnm_graph %>% count_nodes() # Get a count of edges gnm_graph %>% count_edges()
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