Contract Nodes into Groups

Replaces each group of nodes with a single node whose edges aggregate the edges of its members. The operation corresponds to igraph::contract() and tidygraph's to_contracted(), and it is the network form of the aggregation computed by summarize_clusters().

Usage

contract_nodes(
  x,
  groups,
  weight = c("sum", "mean", "max", "min"),
  loops = FALSE,
  keep_format = FALSE,
  directed = NULL
)

Arguments

x

Network input.

groups

Group assignment. Either a vector with one entry per node, in node order, or a named list mapping each group name to node labels. A list must assign every node. Malformed input raises a cograph_bad_selection error.

weight

How to aggregate the weights of the edges that fall between two groups. One of "sum" (default), "mean", "max" or "min". Within-group edges are aggregated the same way when loops = TRUE.

loops

Logical. Keep the within-group edges as self-loops on the contracted node. Default FALSE.

keep_format

Logical. If TRUE, a matrix, igraph, statnet network or tna input is returned in its own format. An edge-list data frame or a qgraph object is returned as a cograph_network with a cograph_no_format_roundtrip warning. Default FALSE returns a cograph_network.

directed

Logical or NULL. Directedness used to read the input. NULL (default) detects it from the input.

Value

A cograph_network with one node per group, labeled by group name, or the input format when keep_format = TRUE. The groups follow the factor levels of a vector (sorted for a character vector) or the order of a list.

See also

summarize_clusters, detect_communities, split_components

Examples

contract_nodes(regulation_net, groups = rep(c("Plan", "Act"), each = 5))
#> Cograph network: 2 nodes, 2 edges ( directed )
#> Source: matrix 
#>   Nodes (2): Act, Plan
#>   Edges: 2 / 2 (density: 100.0%)
#>   Weights: [2.600, 3.480]  |  mean: 3.040
#>   Strongest edges:
#>     Act -> Plan  3.480
#>     Plan -> Act  2.600
#> Layout: none 
#>   Use as.data.frame() for the edge table, as.data.frame(what = "nodes") for the nodes.