Description Usage Arguments Value Examples
A single, connected graph is created. The graph is initialized as a ring lattice, and edges are randomly rewired and/or removed. The procedure is similar to the Watts-Strogatz method, but the sampling of edges to modify can be based on the degree of each node.
1 2 3 |
size |
The number of nodes to include in the graph. |
prob_rewire |
The probability of rewiring an edge. |
prob_remove |
The probability of removing an edge. |
weights |
(Optional) Weights used for sampling nodes. See ?rewire_connections_to_node and ?remove_connections_to_node for details. |
neig_size |
The neighborhood size within which the nodes of the ring lattice are connected. The initial degree of each node is 2 * 'neig_size', so long as 'size' >= (1 + 2 * 'neig_size') |
alpha |
A positive value used to parameterize the Beta distribution. |
beta |
A positive value used to parameterize the Beta distribution. |
epsilon |
A small constant added to the sampling probability of each node. |
... |
Additional arguments are ignored. |
An adjacency matrix representing the network structure.
1 2 3 4 5 | # Create a random module structure (an adjacency matrix) for 10 nodes.
adj_mat <- random_module_structure(10)
# A network object can be created using this structure.
module <- create_module_from_adjacency_matrix(adj_mat)
nw <- create_network_from_modules(10, module)
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.