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#' Maximum betweenness centrality.
#' @description Betweenness centrality associates with each node v, the two
#' nodes u, w, for which the shortest path between u and w runs through v, if
#' the tree were re-rooted at node v. Then, we report the node with maximum
#' betweenness centrality.
#' @param phy phylo object or ltable
#' @param normalization "none" or "tips", if tips is chosen, the obtained
#' maximum betweenness is normalized by the total amount of node pair
#' combinations considered, e.g. (n-2)*(n-1), where n is the number of tips.
#' @return Maximum Betweenness
#' @references Chindelevitch, Leonid, et al. "Network science inspires novel
#' tree shape statistics." Plos one 16.12 (2021): e0259877.
#' @export
max_betweenness <- function(phy, normalization = "none") {
normalization <- check_normalization_key(normalization)
check_tree(phy,
require_binary = TRUE,
require_ultrametric = FALSE)
if (inherits(phy, "matrix")) {
betweenness_stat <- calc_max_betweenness_ltable_cpp(phy)
if (normalization == "tips" || normalization == TRUE) {
n <- 2 * length(phy[, 1]) - 1
betweenness_stat <- 2 * betweenness_stat / ((n - 2) * (n - 1))
}
return(betweenness_stat)
}
if (inherits(phy, "phylo")) {
betweenness_stat <- calc_max_betweenness_cpp(phy)
if (normalization == "tips" || normalization == TRUE) {
n <- 1 + length(phy$edge[, 1])
betweenness_stat <- 2 * betweenness_stat / ((n - 2) * (n - 1))
}
return(betweenness_stat)
}
stop("input object has to be phylo or ltable")
}
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