R/layout_spectral.R

In schochastics/graphlayouts: Additional Layout Algorithms for Network Visualizations

#' spectral graph layouts
#' @description Using a set of eigenvectors of matrices associated with a graph as coordinates
#' @name layout_spectral
#' @param g igraph object
#' @param type matrix to be used for spectral decomposition. either 'adjacency' or 'laplacian'
#' @param ev eigenvectors to be used. Either 'smallest' or 'largest'.
#' @details The layout_igraph_* function should not be used directly. It is only used as an argument for plotting with 'igraph'.
#' 'ggraph' natively supports the layout.
#' @author David Schoch
#' @return matrix of xy coordinates
#' @examples
#' library(igraph)
#'
#' g <- sample_gnp(50, 0.2)
#'
#' xy <- layout_with_eigen(g, type = "adjacency", ev = "largest")
#'
#' xy <- layout_with_eigen(g, type = "adjacency", ev = "smallest")
#'
#' xy <- layout_with_eigen(g, type = "laplacian", ev = "largest")
#'
#' xy <- layout_with_eigen(g, type = "laplacian", ev = "smallest")
#' @export

layout_with_eigen <- function(g, type = "laplacian", ev = "smallest") {
    ensure_igraph(g)
    if (!igraph::is_connected(g)) {
        stop("g must be connected")
    }
    if (igraph::is_directed(g)) {
        warning("g is directed. undirected version is used for the layout.")
        g <- igraph::as.undirected(g)
    }
    if (!type %in% c("laplacian", "adjacency")) {
        stop("type must be one of 'laplacian' or 'adjacency'")
    }
    if (!ev %in% c("largest", "smallest")) {
        stop("ev must be one of 'smallest' or 'largest'")
    }
    n <- igraph::vcount(g)
    if (type == "adjacency") {
        A <- igraph::as_adj(g, type = "both")
    } else {
        A <- igraph::laplacian_matrix(g)
    }
    sA <- eigen(A)
    if (ev == "largest") {
        xy <- sA$vectors[, 1:2]
    } else if (ev == "smallest" && type == "adjacency") {
        xy <- sA$vectors[, (n - 1):n]
    } else {
        xy <- sA$vectors[, (n - 2):(n - 1)]
    }
    xy
}