compute_node_metric: Compute graph-theoretic metrics from a graph at the node...

In graph4lg: Build Graphs for Landscape Genetics Analysis

Compute graph-theoretic metrics from a graph at the node level

Description

The function computes graph-theoretic metric values at the node level.

Usage

compute_node_metric(
  graph,
  metrics = c("deg", "close", "btw", "str", "siw", "miw"),
  weight = TRUE
)

Arguments

graph	An object of class igraph. Its nodes must have names.
metrics	Character vector specifying the graph-theoretic metrics computed at the node-level in the graphs Graph-theoretic metrics can be: Degree (metrics = c("deg", ...)) Closeness centrality index (metrics = c("close",...)) Betweenness centrality index (metrics = c("btw",...)) Strength (sum of the weights of the links connected to a node) (metrics = c("str",...)) Sum of the inverse weights of the links connected to a node (metrics = c("siw", ...), default) Mean of the inverse weights of the links connected to a node (metrics = c("miw", ...)) By default, the vector metrics includes all these metrics.
weight	Logical which indicates whether the links are weighted during the calculation of the centrality indices betweenness and closeness. (default: weight = TRUE). Link weights are interpreted as distances when computing the shortest paths. They should then be inversely proportional to the strength of the relationship between nodes (e.g. to fluxes).

Value

A data.frame with the node names and the metrics computed.

Author(s)

P. Savary

Examples

data(data_ex_genind)
mat_gen <- mat_gen_dist(x = data_ex_genind, dist = "DPS")
graph <- gen_graph_thr(mat_w = mat_gen, mat_thr = mat_gen,
                            thr = 0.8)
res_met <- compute_node_metric(graph)

graph4lg documentation built on Feb. 16, 2023, 5:43 p.m.