#' Identifies all R / L interactions
#'
#' This function will map all RL interactions
#'
#' @param input the input graph analysis object
#' @param select the communities to select
#' @param expand if true will expand to grab all communities that share an edge with the input community
#' @export
#' @details
#' This will use the calc_agg_bulk results to ID networks
#' @examples
#' ex_sc_example <- id_rl(input = ex_sc_example)
extract_communities <- function(input, select, expand = TRUE){
members <- input$Clusters_Results$membership
keep <- c()
for (i in 1:length(select)) {
int <- select[i]
ind <- which(members == int)
keep <- c(keep, ind)
}
if(expand == TRUE){
keep2 <- unlist(adjacent_vertices(input$igraph_Network, keep, mode = "all"))
select2 <- unique(members[keep2])
keep <- c()
for (i in 1:length(select2)) {
int <- select2[i]
ind <- which(members == int)
keep <- c(keep, ind)
}
}
subgraph <- induced_subgraph(input$igraph_Network, keep)
ind2 <- match(names(V(subgraph)), names(V(input$igraph_Network)))
l <- input$layout[ind2,]
results <- vector(mode = "list", length = 2)
results[[1]] <- subgraph
results[[2]] <- l
names(results) <- c("igraph_Network", "layout")
return(results)
}
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