| random_module_structure {SeqNet} | R Documentation |
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.
random_module_structure( size, prob_rewire = 1, prob_remove = 0.5, weights = NULL, neig_size = 3, alpha = 100, beta = 1, epsilon = 10^-5, ... )
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
|
neig_size |
The neighborhood size within which the nodes of the
ring lattice are connected. The initial degree of each node is
|
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.
# 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)