louvainStep: Run a single step of the Louvain algorithm

In yishaishimoni/phenoClust: Find clusters by network modularity

Description

In each step each node in the network is moved to a neighboring cluster (or moved to a new cluster including only itself) if it increases the modularity.

Usage

  louvainStep(G, C, O, Q = modularity(G, C), verbose = TRUE)

Arguments

G	a symmetric N-by-N numeric matrix representing the weights of edges between the N nodes
C	a numeric vector of length N with cluster assignments
O	a vecotor indicating the order by which the nodes are evaluated
Q	the initial modularity value, since the method evaluates only the change in modularity so as not to calculate the modularity each time. If no initial value is provided, the current modularity value is calculated.
verbose	a boolean vaue indicating whether to print progress messages and a progression bar (default=TRUE)

Value

a list containing the a vector of length N (clusters) with cluster assignments that maximizes modularity, and the new modularity (newQ)

yishaishimoni/phenoClust documentation built on May 4, 2019, 5:28 p.m.