random_network {SDDE} | R Documentation |
This function allows the user to create random network X and an associated augmented network Y using either the Erdos-Renyi model or the Barabasi-Albert model.
random_network(original_node, additional_node, ngroup, edge_ratio,total_edge, type)
original_node |
the number of nodes in the original network X (default=25) |
additional_node |
the number of additional node in network Y (default=5) |
ngroup |
the number of additional taxa groups in network Y (default=1) |
edge_ratio |
the edge to node ratio (default=between 1 and 5) |
total_edge |
the number of edges in the fixed model |
type |
Either 'erdos' for the Erdos-Renyi model, 'barabasi' for the Barabasi-Albert model, 'watts' for the Watts-Strogatz model or 'fixed' fixed model allowing a defined number of edges |
Return a data.frame containing g1, g2, the total_nodes and the total_edges numbers of network Y and the total_original_nodes number of network X.
## Create a small random_network ## Not run: random_network() ## End(Not run) ## Expected result: # # $g1 # IGRAPH UNW- 25 23 -- Erdos renyi (gnm) graph # + attr: name (g/c), type (g/c), loops (g/l), m (g/n), name (v/c), tax # (v/c), weight (e/n) # # $g2 # IGRAPH UNW- 30 30 -- Erdos renyi (gnm) graph # + attr: name (g/c), type (g/c), loops (g/l), m (g/n), name (v/c), tax # (v/c), weight (e/n) # # $total_nodes # [1] 30 # # $total_edges # [1] 30 # # $total_original_nodes # [1] 25 # ## Create two networks using the Erdos-Renyi model with 100 nodes in network X ## and 10 additional nodes in network Y of 3 types. random_network(100,10,3); ## Create a random networks of 20 +10 additional node using the Barabsi-Albert model ## and compute the corresponding SDDE path types. ## l <- random_network(20,10,ngroup=1,vertex_ratio=1, type='barabasi'); ## complete_network(l$g1, l$g2);