R/plot.updated_graph.R

In graphicalMCP: Graphical Multiple Comparison Procedures

#' S3 plot method for the class `updated_graph`
#'
#' @description
#' Plotting an updated graph is a *very* light wrapper around
#' [plot.initial_graph()], only changing the default vertex color to use gray
#' for deleted hypotheses.
#'
#' @param x An object of class `updated_graph` to plot.
#' @inheritDotParams plot.initial_graph
#'
#' @return An object x of class `updated_graph`, after plotting the updated
#'   graph.
#'
#' @seealso
#'   [plot.initial_graph()] for the plot method for the initial graph.
#'
#' @rdname plot.updated_graph
#'
#' @export
#'
#' @references
#'   Bretz, F., Posch, M., Glimm, E., Klinglmueller, F., Maurer, W., and
#'   Rohmeyer, K. (2011). Graphical approaches for multiple comparison
#'   procedures using weighted Bonferroni, Simes, or parametric tests.
#'   \emph{Biometrical Journal}, 53(6), 894-913.
#'
#' @examples
#' # A graphical multiple comparison procedure with two primary hypotheses (H1
#' # and H2) and two secondary hypotheses (H3 and H4)
#' # See Figure 1 in Bretz et al. (2011).
#' hypotheses <- c(0.5, 0.5, 0, 0)
#' transitions <- rbind(
#'   c(0, 0, 1, 0),
#'   c(0, 0, 0, 1),
#'   c(0, 1, 0, 0),
#'   c(1, 0, 0, 0)
#' )
#' g <- graph_create(hypotheses, transitions)
#'
#' # Delete the second and third hypotheses in the "unordered mode"
#' plot(
#'   graph_update(
#'     g,
#'     c(FALSE, TRUE, TRUE, FALSE)
#'   ),
#'   layout = "grid"
#' )
plot.updated_graph <- function(x, ...) {
  v_colors <- rep("#6baed6", length(x$updated_graph$hypotheses))
  v_colors[x$deleted] <- "#cccccc"

  plot(x$updated_graph, vertex.color = v_colors, ...)

  invisible(x)
}