R/RcppExports.R

In ionet: Network Analysis for Input-Output Tables

# Generated by using Rcpp::compileAttributes() -> do not edit by hand
# Generator token: 10BE3573-1514-4C36-9D1C-5A225CD40393

#' Betweenness centrality
#'
#' @description
#' Compute the betweenness centrality with auxiliary information based on strongest path
#' (SP).
#'
#' @param adjmat An n-by-n numerical matrix representing the matrix of intermediate
#' transactions in the input-output table.
#'
#' @param gross An n-dimensional numerical vector representing the gross input/output.
#'
#' @param aux An n-dimensional numerical vector representing the node-specific auxiliary
#' information.
#'
#' @param alpha A scalar (default = 1) between 0 and 1, representing the tuning parameter
#' that controls the weights for SP strength and auxiliary information.
#'
#' @param type A character string specifying the type of SP to calculate. Available
#' options: \itemize{
#' \item \code{type = "consumption"} / \code{type = "pull"} (default)
#' \item \code{type = "distribution"} / \code{type = "push"}
#' }
#'
#' @references
#' Xiao, S., Yan, J. and Zhang, P. (2022).
#' Incorporating Auxiliary Information in Betweenness Measure for Input-Output Networks.
#' \emph{Physica A: Statistical Mechanics and its Applications}, 607, 128200.
#'
#' @return A list of betweeness score, associated SPs, SP distance and SP strength.
#'
#' @export
btw <- function(adjmat, gross, aux, alpha = 1, type = "consumption") {
    .Call(`_ionet_btw`, adjmat, gross, aux, alpha, type)
}

#' Dijkstra's algorithm
#'
#' @description
#' Implement the Dijkstra's algorithm to find the shortest paths from the source node to
#' all nodes in the given network.
#'
#' @param adjmat The adjacency matrix of a directed, weighted network.
#'
#' @param src An integer specifying the given source node to find the shortest distance.
#'
#' @references
#' Dijkstra, E. W. (1959).
#' A Note on Two Problems in Connexion with Graphs.
#' \emph{Numerische Mathematik}, 1, 269--271.
#'
#' @return A list of distance and previous node.
#'
#' @export
dijkstra <- function(adjmat, src) {
    .Call(`_ionet_dijkstra`, adjmat, src)
}