Layer Similarity

Computes similarity between two network layers.

Usage

layer_similarity(
  A1,
  A2,
  method = c("jaccard", "overlap", "hamming", "cosine", "pearson")
)

lsim(A1, A2, method = c("jaccard", "overlap", "hamming", "cosine", "pearson"))

Arguments

A1

First adjacency matrix

A2

Second adjacency matrix, with the same dimensions as A1

method

Comparison method: "jaccard" (default), "overlap", "hamming", "cosine" or "pearson"

Value

A single numeric value. All methods except "hamming" return a similarity, where higher values mean more alike layers. "hamming" returns a distance, the number of matrix cells whose edge presence differs between the two layers. Lower values then mean more alike layers, and the value is not bounded by 1. NA is returned when the denominator is undefined ("jaccard" with no edges in either layer, "overlap" with an empty layer, "cosine" with an all-zero layer).

Details

"jaccard", "overlap" and "hamming" compare edge presence (A > 0) and ignore weights. "cosine" and "pearson" are computed on the cell values, diagonal included. Matrices of different dimensions raise an error.

Examples

layer_similarity(regulation_net, t(regulation_net), method = "cosine")
#> [1] 0.1197053