fastgreedy.community: Community structure via greedy optimization of modularity

In igraph/rigraph: Network Analysis and Visualization

Community structure via greedy optimization of modularity

Description

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
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 or NA. If it is NULL and the input graph has a ‘weight’ edge attribute, then that attribute will be used. If NULL and no such attribute is present, then the edges will have equal weights. Set this to NA 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.

igraph/rigraph documentation built on May 19, 2024, 6:19 a.m.