rnetcarto: Computes modularity and modularity roles from a network.

In rnetcarto: Fast Network Modularity and Roles Computation by Simulated Annealing (Rgraph C Library Wrapper for R)

Computes modularity and modularity roles from a network.

Description

Compute modularity and modularity roles for graphs using simulated annealing

Usage

netcarto(
  web,
  seed = as.integer(floor(runif(1, 1, 100000001))),
  iterfac = 1,
  coolingfac = 0.995,
  bipartite = FALSE
)

Arguments

web	network either as a square adjacency matrix or a list describing E interactions a->b: the first (resp. second) element is the vector of the labels of a (resp. b), the third (optional) is the vector of interaction weights.
seed	Seed for the random number generator: Must be a positive integer.
iterfac	At each temperature of the simulated annealing (SA), the program performs fN^2 individual-node updates (involving the movement of a single node from one module to another) and fN collective updates (involving the merging of two modules and the split of a module). The number "f" is the iteration factor.
coolingfac	Temperature cooling factor.
bipartite	If True use the bipartite definition of modularity.

Value

A list. The first element is a dataframe with the name, module, z-score, and participation coefficient for each row of the input matrix. The second element is the modularity of this partition.

Examples

# Generate a simple random network
a = matrix(as.integer(runif(100)<.3), ncol=10) 
a[lower.tri(a)] = 0
# Find an optimal partition for modularity using netcarto.
netcarto(a)

rnetcarto documentation built on Jan. 17, 2023, 1:12 a.m.