# compute_node_metric: Compute graph-theoretic metrics from a graph at the node... In graph4lg: Build Graphs for Landscape Genetics Analysis

 compute_node_metric R Documentation

## 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.

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.