R/graph.entropy.R

In statGraph: Statistical Methods for Graphs

#' Graph Spectral Entropy
#'
#' \code{graph.entropy} returns the spectral entropy of an undirected graph.
#'
#' @param Graph the undirected graph (igraph object).
#' If \code{Graph} has the  attribute \code{eigenvalues} containing
#' the eigenvalues of \code{Graph}, such values will be used to
#' compute its spectral density.
#'
#' @param ... Other relevant parameters for \code{\link{graph.spectral.density}}.
#'
#' @return A list with class 'statGraph' containing the following components:
#' \item{\code{method:}}{ a string indicating the used method.}
#' \item{\code{info:}}{ a string showing details about the method.}
#' \item{\code{data.name:}}{ a string with the data's name(s).}
#' \item{\code{entropy:}}{ a real number corresponding to the graph spectral entropy.}
#'
#' @keywords spectral_entropy
#'
#' @references
#' Takahashi, D. Y., Sato, J. R., Ferreira, C. E. and Fujita A. (2012)
#' Discriminating Different Classes of Biological Networks by Analyzing the
#' Graph Spectra  Distribution. _PLoS ONE_, *7*, e49949.
#' doi:10.1371/journal.pone.0049949.
#'
#' @examples
#' set.seed(1)
#' G <- igraph::sample_gnp(n=100, p=0.5)
#' entropy <- graph.entropy(Graph = G)
#' entropy
#'
#' @export
graph.entropy <- function(Graph, ...) {
    if (!valid.input(Graph)) {
        stop("The input should be an igraph object!")
    }
    data.name <- deparse(substitute(Graph))
    # compute the entropy
    f <- graph.spectral.density(Graph, ...)

    if (sum(is.na(f)) > 0) {
        return(NA)
    }
    y <- f$y
    valid_idx <- which(y != 0)
    y[valid_idx] <- y[valid_idx] * log(y[valid_idx])
    entropy <- -trapezoidSum(f$x, y)
    # return class
    method_info <- "Spectral Entropy of a Graph"
    output <- list(method = method_info, info = f$info, data.name = data.name, entropy = entropy)
    class(output) <- "statGraph"
    return(output)
}