R/find_all_cpm_com.R

In dendroNetwork: Create Networks of Dendrochronological Series using Pairwise Similarity

#' Finding all CPM communities in a network/graph
#'
#' Function to determine all CPM-communities in a network (or graph)
#'
#' @param graph_input the graph for find all CPM communities in
#' @param n_core this defaults to 0, if a number larger than 1 is given the community detection is performed using parallel computing
#' @returns data frame with at least two columns. The first column are the node names and the further columns represent the CPM-communities, with 1 denoting the membership in a community.
#' @examples
#' data(hol_rom)
#' sim_table_hol <- sim_table(hol_rom)
#' g_hol <- dendro_network(sim_table_hol)
#' hol_com_cpm_all <- find_all_cpm_com(g_hol)
#'
#' @export find_all_cpm_com
#'


find_all_cpm_com <- function(graph_input, n_core = 0) {
  if (!igraph::is_igraph(graph_input)) {
    stop(paste0("Please use an igraph object as input. The current object is an ", class(graph_input), "."))
  }
  if (n_core > 1) {
    for (i in 3:igraph::clique_num(graph_input)) {
      com_cpm <- clique_community_names_par(graph_input, i, n_core)
      if (i == 3) {
        com_cpm_all <- com_cpm
      } else {
        com_cpm_all <- rbind(com_cpm_all, com_cpm)
      }
    }
  } else {
    for (i in 3:igraph::clique_num(graph_input)) {
      com_cpm <- clique_community_names(graph_input, i)
      if (i == 3) {
        com_cpm_all <- com_cpm
      } else {
        com_cpm_all <- rbind(com_cpm_all, com_cpm)
      }
    }
  }
  com_cpm_all <- com_cpm_all |>
    dplyr::count(node, com_name) |>
    tidyr::spread(com_name, n)
  com_cpm_all
}