# Copyright (C) 2018 Sebastian Sosa, Ivan Puga-Gonzalez, Hu Feng He, Xiaohua Xie, Cédric Sueur
#
# This file is part of Animal Network Toolkit Software (ANTs).
#
# ANT is free software: you can redistribute it and/or modify it
# under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 2 of the License, or
# (at your option) any later version.
#
# ANT is distributed in the hope that it will be useful, but
# WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#' @title Symetric Laplacian centrality
#' @description Calculate the symetric version of the Laplacian centrality for each verteces.
#' @param M a square adjacency matrix.
#' @param df a data frame of same length of the input matrix.
#' @param dfid an integer indicating the column of individual ids in argument \emph{df}
#' @param binary a boolean indicating if the binary version of the laplacian centrality has to be computed.
#' @details Laplacian centrality is the drop in the Laplacian energy of the graph when the vertex is removed.
#' This version uses the degrees (for the binary version ) or the strength (for the weigthed version) to calculate laplacian centrality.
#' @author Sebastian Sosa, Ivan Puga-Gonzalez.
#' @references REF laplacian !!!!!!!!!!!!!!!!
#' @references Sosa, S. (2018). Social Network Analysis, \emph{in}: Encyclopedia of Animal Cognition and Behavior. Springer.
#' @keywords internal
met.lp.single <- function(M, df = NULL, dfid = NULL, binary = FALSE) {
# Compute network metric
if(binary) {
result <- met.lpcB(M)
}
else {
result <- met.lpcW(M)
}
# If argument df is null
if (is.null(df)) {
# Colnames or argument M as names of the vector
attr(result, "names") <- colnames(M)
return(result)
}
else {
if (is.data.frame(df) == FALSE) {
stop("Argument df must be a data frame")
}
# If argument dfid is not null
if (!is.null(dfid)) {
if (is.null(colnames(M))) {
stop("Argument M doesn't have column names")
}
# Order data frame according to argument dfid
col.id <- df.col.findId(df, dfid)
if(binary){
df <- merge.met(vec = result, names = colnames(M), df = df, dfid = col.id, met = "lpB")
}
else{
df <- merge.met(vec = result, names = colnames(M), df = df, dfid = col.id, met = "lp")
}
return(df)
}else{
# Add vector of network metrics in a new colum
if(binary){
df$lpB <- result
}
else{
df$lp <- met.lpcW(M)
}
return(df)
}
}
}
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