R/comm.str.R

In NetworkToolbox: Methods and Measures for Brain, Cognitive, and Psychometric Network Analysis

#' Community Strength/Degree Centrality
#' @description Computes the community
#' \code{\link[NetworkToolbox]{strength}}/\code{\link[NetworkToolbox]{degree}}
#' centrality measure of each community in a network \code{} or computes the
#' \code{\link[NetworkToolbox]{strength}}/\code{\link[NetworkToolbox]{degree}}
#' centrality measure of each community's connections to the other communities 
#' 
#' @param A An adjacency matrix of network data
#' 
#' @param comm A vector corresponding to the
#' community each node belongs to
#' 
#' @param weighted Is the network weighted?
#' Defaults to \code{TRUE}.
#' Set to \code{FALSE} for weighted measures
#' 
#' @param measure Type of measure to compute:
#' 
#' \itemize{
#' 
#' \item{\code{"within"}}
#' {Computes the community strength or degree of nodes within
#' its own community}
#' 
#' \item{\code{"between"}}
#' {Computes the community strength or degree of nodes outside
#' of its own community}
#' 
#' }
#' 
#' @return A vector of community strength/degree centrality values for each specified
#' community in the network
#' (larger values suggest more central positioning)
#' 
#' @examples
#' # Pearson's correlation only for CRAN checks
#' A <- TMFG(neoOpen, normal = FALSE)$A
#' 
#' comm <- igraph::walktrap.community(convert2igraph(abs(A)))$membership
#' 
#' #Strength
#' within.ns <- comm.str(A, comm, measure = "within")
#' between.ns <- comm.str(A, comm, measure = "between")
#' 
#' #Degree
#' within.deg <- comm.str(A, comm, weighted = FALSE, measure = "within")
#' between.deg <- comm.str(A, comm, weighted = FALSE, measure = "between")
#'
#' @author Alexander Christensen <alexpaulchristensen@gmail.com>
#' 
#' @export
#Community Strength/Degree Centrality
comm.str <- function (A, comm, weighted = TRUE,
                      measure = c("within","between"))
{
    if(is.null(comm))
    {stop("comm must be input")}
    
    if(missing(measure))
    {measure <- "between"
    }else{measure <- match.arg(measure)}
    
    comm <- as.vector(comm)
    
    if(ncol(A)!=length(comm))
    {stop("length of comm does not match nodes in matrix")}
    
    uniq <- unique(comm)
    len <- length(uniq)
    
    remove <- matrix(0,nrow=len,ncol=1)
    
    for(j in 1:len)
    {
        rem <- which(comm==uniq[j])
        
        if(length(rem)!=1)
        {
            if(measure == "within")
            {
                if(weighted)
                {remove[j,] <- sum(colSums(A[,rem]))
                }else{remove[j,] <- sum(colSums(binarize(A)[,rem]))}
            }else if(measure == "between")
            {
                if(weighted)
                {remove[j,] <- sum(colSums(A[,-rem]))
                }else{remove[j,] <- sum(colSums(binarize(A)[,-rem]))}
            }
            
            
        }else{remove[j,] <- 0}
    }
    
    norm <- as.vector(round(remove,3))
    
    names(norm) <- uniq
    
    res <- norm[sort(names(norm))]
    
    return(res)
}
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