bioregion (version 1.1.1)

netclu_greedy: Community structure detection via greedy optimization of modularity

Description

This function finds communities in a (un)weighted undirected network via greedy optimization of modularity.

Usage

netclu_greedy(
  net,
  weight = TRUE,
  cut_weight = 0,
  index = names(net)[3],
  bipartite = FALSE,
  site_col = 1,
  species_col = 2,
  return_node_type = "both",
  algorithm_in_output = TRUE
)

Value

A list of class bioregion.clusters with five slots:

1. name: character containing the name of the algorithm

2. args: list of input arguments as provided by the user

3. inputs: list of characteristics of the clustering process

4. algorithm: list of all objects associated with the clustering procedure, such as original cluster objects (only if algorithm_in_output = TRUE)

5. clusters: data.frame containing the clustering results

In the algorithm slot, if algorithm_in_output = TRUE, users can find the output of cluster_fast_greedy.

Arguments

net

the output object from similarity() or dissimilarity_to_similarity(). If a data.frame is used, the first two columns represent pairs of sites (or any pair of nodes), and the next column(s) are the similarity indices.

weight

a boolean indicating if the weights should be considered if there are more than two columns.

cut_weight

a minimal weight value. If weight is TRUE, the links between sites with a weight strictly lower than this value will not be considered (O by default).

index

name or number of the column to use as weight. By default, the third column name of net is used.

bipartite

a boolean indicating if the network is bipartite (see Details).

site_col

name or number for the column of site nodes (i.e. primary nodes).

species_col

name or number for the column of species nodes (i.e. feature nodes).

return_node_type

a character indicating what types of nodes (site, species or both) should be returned in the output (return_node_type = "both" by default).

algorithm_in_output

a boolean indicating if the original output of cluster_fast_greedy should be returned in the output (TRUE by default, see Value).

Author

Maxime Lenormand (), Pierre Denelle () and Boris Leroy ()

Details

This function is based on the fast greedy modularity optimization algorithm Clauset2004bioregion as implemented in the igraph package (cluster_fast_greedy).

References

Clauset2004bioregion

Examples

comat <- matrix(sample(1000, 50), 5, 10)
rownames(comat) <- paste0("Site", 1:5)
colnames(comat) <- paste0("Species", 1:10)

net <- similarity(comat, metric = "Simpson")
com <- netclu_greedy(net)

net_bip <- mat_to_net(comat, weight = TRUE)
clust2 <- netclu_greedy(net_bip, bipartite = TRUE)