binarize: Binarize Edge Weights

In cograph: Analysis and Visualization of Complex Networks

Binarize Edge Weights

Description

Replaces every surviving weight with 1, dropping edges at or below the threshold. The network equivalent of sna::event2dichot().

Usage

binarize(
  x,
  threshold = 0,
  absolute = TRUE,
  signed = FALSE,
  keep_isolates = TRUE,
  keep_format = FALSE,
  directed = NULL
)

Arguments

x	Network input.
threshold	Numeric. Edges whose weight exceeds this value are kept and set to 1. Default 0, which keeps every existing edge.
absolute	Logical. Compare abs(weight). Default TRUE, so a correlation network keeps its strong negative edges.
signed	Logical. If TRUE, negative edges become -1 rather than 1, preserving the sign of the association. Default FALSE.
keep_isolates	Logical. Keep nodes that end up with no edges? Default TRUE.
keep_format	Logical. Return the input format when TRUE.
directed	Logical or NULL. If NULL (default), auto-detect.

Value

A cograph_network whose weights are all 1 (or, when signed = TRUE, 1 for a positive edge and -1 for a negative one), or the input format when keep_format = TRUE. Nodes left without edges are kept and reported in a cograph_isolates_created warning, unless keep_isolates = FALSE.

References

Butts, C. T. (2008). Social network analysis with sna. Journal of Statistical Software, 24(6), 1–51.

See Also

threshold_edges, normalize_weights

Examples

adj <- matrix(c(0, .5, .8, 0,
                .5, 0, .3, .6,
                .8, .3, 0, .4,
                 0, .6, .4, 0), 4, 4, byrow = TRUE)
rownames(adj) <- colnames(adj) <- c("A", "B", "C", "D")

binarize(adj, threshold = 0.45)

cograph documentation built on Sept. 30, 2026, 5:08 p.m.