Select Top N Nodes by Centrality

Select the top N nodes ranked by a centrality measure.

Usage

select_top(
  x,
  n,
  by = "degree",
  ...,
  keep_edges = c("internal", "none"),
  keep_format = FALSE,
  directed = NULL
)

Arguments

x

Network input.

n

Integer. Number of top nodes to select.

by

Character. Centrality measure for ranking: "degree", "indegree", "outdegree", "strength", "instrength", "outstrength", "betweenness", "closeness", "eigenvector", "pagerank", "hub", "authority", "coreness", or the name of any other measure centrality() computes (see list_centralities()). An unknown name raises a cograph_bad_selection error. Default "degree".

...

Additional filter expressions, applied after the top n nodes are selected.

keep_edges

How to handle edges. Default "internal".

keep_format

Logical. Keep input format? Default FALSE.

directed

Logical or NULL. Auto-detect if NULL.

Value

A cograph_network with the top N nodes.

See also

select_nodes, select_component

Examples

select_top(regulation_net, n = 3, by = "pagerank")
#> Cograph network: 3 nodes, 3 edges ( directed )
#> Source: matrix 
#>   Nodes (3): Monitor, Reflect, Create
#>   Edges: 3 / 6 (density: 50.0%)
#>   Weights: [0.150, 0.370]  |  mean: 0.230
#>   Strongest edges:
#>     Monitor -> Create  0.370
#>     Create -> Monitor  0.170
#>     Reflect -> Monitor  0.150
#> Layout: none 
#>   Use as.data.frame() for the edge table, as.data.frame(what = "nodes") for the nodes.