infomap.community: Infomap community finding

In igraph/rigraph: Network Analysis and Visualization

Infomap community finding

Description

infomap.community() was renamed to cluster_infomap() to create a more consistent API.

Usage

infomap.community(
  graph,
  e.weights = NULL,
  v.weights = NULL,
  nb.trials = 10,
  modularity = TRUE
)

Arguments

graph	The input graph. Edge directions will be taken into account.
e.weights	If not NULL, then a numeric vector of edge weights. The length must match the number of edges in the graph. By default the ‘weight’ edge attribute is used as weights. If it is not present, then all edges are considered to have the same weight. Larger edge weights correspond to stronger connections.
v.weights	If not NULL, then a numeric vector of vertex weights. The length must match the number of vertices in the graph. By default the ‘weight’ vertex attribute is used as weights. If it is not present, then all vertices are considered to have the same weight. A larger vertex weight means a larger probability that the random surfer jumps to that vertex.
nb.trials	The number of attempts to partition the network (can be any integer value equal or larger than 1).
modularity	Logical scalar, whether to calculate the modularity score of the detected community structure.

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