R/plot_AHP_decision_tree.R

In RMCDA: Multi-Criteria Decision Analysis

#' Plot decision tree
#'
#' @param A the comparison matrix
#' @param comparing.competitors the list of matrices related to pairwise comparisons of competitors for each criteria
#' @param results results of running AHP on data
#' @param vertex_font font of text on vertex
#' @param edge_font size of the arrows
#' @param asp aspect ratio of the graph
#' @param max_width maximum width
#' @param vertex_size vertex size
#'
#' @return the decision tree plot
#' @importFrom igraph graph_from_edgelist E E<- layout_as_tree
#' @importFrom grDevices palette
#' @importFrom graphics legend
#' @importFrom stats   cor optim runif sd
#' @importFrom utils   combn
#' @importFrom fmsb    radarchart
#' @export AHP.decision.tree.plot
AHP.decision.tree.plot <- function(A, comparing.competitors, results, vertex_font=1.2, edge_font = 1,
                                   asp = 0.8, max_width = 5, vertex_size=50){

  nodes <- c("Choose alternative",rownames(comparing.competitors[[1]]), rownames(A))

  edges <- c()


  for(idx in seq(1, length(rownames(A)), 1)){
    edges <- c(edges, "Choose alternative")
    edges <- c(edges, rownames(A)[idx])
  }

  for(idx in seq(1,length(rownames(comparing.competitors[[1]])), 1)){
    for(idx.prod in seq(1, length(rownames(A)), 1)){
      edges <- c(edges, rownames(A)[idx.prod])
      edges <- c(edges, rownames(comparing.competitors[[1]])[idx])
    }
  }

  edge_list <- matrix(edges, ncol = 2, byrow = TRUE)
  weights <- c(results[[1]][[2]],
               as.vector(results[[3]]))

  g <- graph_from_edgelist(edge_list)

  E(g)$weight <- weights


  edge_widths <- max_width * (weights / max(weights))


  p <- plot(g,
            layout = layout_as_tree(g, root = 1),  # Tree-like layout with root at the top
            vertex.size = vertex_size,  # Adjust node size
            vertex.label.cex = vertex_font,  # Font size for labels
            vertex.label.color = "black",  # Label color
            vertex.color="#9B7EBD",
            edge.arrow.size = edge_font,  # Arrow size
            edge.width = edge_widths*edge_font,  # Edge widths based on weights
            asp = asp,
            main = "AHP Decision Tree with Weighted Edges")
  return(p)
}