Community structure via greedy optimization of modularity
Source:R/community.R
fastgreedy.community.Rd
fastgreedy.community()
was renamed to cluster_fast_greedy()
to create a more
consistent API.
Usage
fastgreedy.community(
graph,
merges = TRUE,
modularity = TRUE,
membership = TRUE,
weights = NULL
)
Arguments
- graph
The input graph. It must be undirected and must not have multi-edges.
- merges
Logical scalar, whether to return the merge matrix.
- modularity
Logical scalar, whether to return a vector containing the modularity after each merge.
- membership
Logical scalar, whether to calculate the membership vector corresponding to the maximum modularity score, considering all possible community structures along the merges.
- weights
The weights of the edges. It must be a positive numeric vector,
NULL
orNA
. If it isNULL
and the input graph has a ‘weight’ edge attribute, then that attribute will be used. IfNULL
and no such attribute is present, then the edges will have equal weights. Set this toNA
if the graph was a ‘weight’ edge attribute, but you don't want to use it for community detection. A larger edge weight means a stronger connection for this function.