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Simplify a Network

Source: R/simplify.R
simplify.Rd

Removes self-loops and (where representable) merges duplicate (multi-)edges, similar to igraph::simplify().

Usage

simplify(x, remove_loops, remove_multiple, edge_attr_comb, ...)

# S3 method for class 'matrix'
simplify(
  x,
  remove_loops = TRUE,
  remove_multiple = TRUE,
  edge_attr_comb = "mean",
  ...
)

# S3 method for class 'cograph_network'
simplify(
  x,
  remove_loops = TRUE,
  remove_multiple = TRUE,
  edge_attr_comb = "mean",
  ...
)

# S3 method for class 'igraph'
simplify(
  x,
  remove_loops = TRUE,
  remove_multiple = TRUE,
  edge_attr_comb = "mean",
  ...
)

# S3 method for class 'tna'
simplify(
  x,
  remove_loops = TRUE,
  remove_multiple = TRUE,
  edge_attr_comb = "mean",
  ...
)

# Default S3 method
simplify(
  x,
  remove_loops = TRUE,
  remove_multiple = TRUE,
  edge_attr_comb = "mean",
  ...
)

Arguments

x

Network input (matrix, cograph_network, igraph, tna object).

remove_loops

Logical. Remove self-loops (diagonal entries)?

remove_multiple

Logical. Merge duplicate edges? No-op for matrix/tna inputs (see Details).

edge_attr_comb

How to combine weights of duplicate edges: "sum", "mean", "max", "min", "first", or a custom function. Ignored for matrix/tna inputs.

...

Additional arguments (currently unused).

Value

The simplified network in the same format as the input.

Details

The extent of simplification depends on the input representation:

  • matrix and tna: edges are stored as an n x n weight matrix. Each cell (i, j) is unique by construction, so duplicate-edge merging is a no-op regardless of remove_multiple / edge_attr_comb; only self-loops (the diagonal) can be removed. Convert to cograph_network or igraph first if you need true duplicate aggregation.

  • cograph_network: duplicate edges in the edge-list are merged via aggregate_duplicate_edges() using edge_attr_comb.

  • igraph: delegates to igraph::simplify().

See also

filter_edges for conditional edge removal, centrality which has its own simplify parameter

Examples

# Matrix with self-loops
mat <- matrix(c(0.5, 0.3, 0, 0.3, 0.2, 0.4, 0, 0.4, 0.1), 3, 3)
rownames(mat) <- colnames(mat) <- c("A", "B", "C")
simplify(mat)
#>     A   B   C
#> A 0.0 0.3 0.0
#> B 0.3 0.0 0.4
#> C 0.0 0.4 0.0

# Edge list with duplicates
edges <- data.frame(from = c(1, 1, 2), to = c(2, 2, 3), weight = c(0.3, 0.7, 0.5))
net <- cograph(edges, layout = NULL)
simplify(net)
#> Cograph network: 3 nodes, 2 edges ( directed )
#> Source: edgelist 
#> Data: data.frame (3 x 3) 
#>   Nodes (3): 1, 2, 3
#> Weights: 0.5 (all equal)
#> Layout: none 
simplify(net, edge_attr_comb = "sum")
#> Cograph network: 3 nodes, 2 edges ( directed )
#> Source: edgelist 
#> Data: data.frame (3 x 3) 
#>   Nodes (3): 1, 2, 3
#> Weights: 0.5 to 1 
#> Layout: none