R/plot_ci.R

In metan: Multi Environment Trials Analysis

#' @title Plot the confidence interval for correlation
#'
#' @description
#' `r badge('stable')`
#'
#'This function plots the 95% confidence interval for Pearson's correlation
#'coefficient generated by the function `corr_ci`.
#'
#' @param object An object generate by the function `corr_ci()`
#' @param fill If `corr_ci()` is computed with the argument `by` use
#'   `fill` to fill the shape by each level of the grouping variable
#'   `by`.
#' @param position.fill The position of shapes and errorbar when `fill` is used.
#'   Defaults to `0.3`.
#' @param x.lab The label of x-axis, set to 'Pairwise combinations'. New
#'   arguments can be inserted as `x.lab = 'my label'`.
#' @param y.lab The label of y-axis, set to 'Pearson's correlation coefficient'
#'   New arguments can be inserted as `y.lab = 'my label'`.
#' @param y.lim The range of x-axis. Default is `NULL`. The same arguments
#'   than `x.lim` can be used.
#' @param y.breaks The breaks to be plotted in the x-axis. Default is
#'   `authomatic breaks`. The same arguments than `x.breaks` can be
#'   used.
#' @param shape The shape point to represent the correlation coefficient.
#'   Default is `21` (circle). Values must be between `21-25`:
#'   `21` (circle), `22` (square), `23` (diamond), `24` (up
#'   triangle), and `25` (low triangle).
#' @param col.shape The color for the shape edge. Set to `black`.
#' @param fill.shape The color to fill the shape. Set to `orange`.
#' @param size.shape The size for the shape point. Set to `2.5`.
#' @param width.errbar The width for the errorbar showing the CI.
#' @param main The title of the plot. Set to `main = FALSE` to ommite the
#'   plot title.
#' @param invert.axis Should the names of the pairwise correlation appear in the
#'   y-axis?
#' @param reorder Logical argument. If `TRUE` (default) the pairwise
#'   combinations are reordered according to the correlation coefficient.
#' @param legend.position The position of the legend when using `fill` argument.
#'   Defaults to `"bottom"`.
#' @param plot_theme The graphical theme of the plot. Default is
#'   `plot_theme = theme_metan()`. For more details, see
#'   [ggplot2::theme()].
#' @return An object of class `gg, ggplot`.
#' @md
#' @export
#' @examples
#' \donttest{
#' library(metan)
#' library(dplyr)
#' # Traits that contains "E"
#' data_ge2 %>%
#'   select(contains('E')) %>%
#'   corr_ci() %>%
#'   plot_ci()
#'
#' # Group by environment
#' # Traits PH, EH, EP, EL, and ED
#' # Select only correlations with PH
#'
#'data_ge2 %>%
#'  corr_ci(PH, EP, EL, ED, CW,
#'          sel.var = "PH",
#'          by = ENV) %>%
#'  plot_ci(fill = ENV)

#'}
plot_ci <- function(object,
                    fill = NULL,
                    position.fill = 0.3,
                    x.lab = NULL,
                    y.lab = NULL,
                    y.lim = NULL,
                    y.breaks = waiver(),
                    shape = 21,
                    col.shape = "black",
                    fill.shape = "orange",
                    size.shape = 2.5,
                    width.errbar = 0.2,
                    main = TRUE,
                    invert.axis = TRUE,
                    reorder = TRUE,
                    legend.position = "bottom",
                    plot_theme = theme_metan()) {
  if (!has_class(object, "tbl_df")) {
    stop("The object must be a 'data.frame' or a 'tbl_df'.")
  }
  if (!any(colnames(object) %in% c("Pair", "Corr"))) {
    stop("It appers that the object was not generate by the function 'coor_ci()'.")
  }
  n <- object[1, which(colnames(object) == "n")]
  x.lab <- ifelse(is.null(x.lab) == F, x.lab, paste0("Pairwise combinations"))
  y.lab <- ifelse(is.null(y.lab) == F, y.lab, paste0("Pearson's correlation coefficient"))
  object %<>% mutate(Pair = paste(V1, V2, sep = " x "))
  if(reorder == TRUE){
    if(!missing(fill)){
      p <-
        ggplot(object, aes(x = reorder(Pair, Corr), y = Corr, fill = {{fill}})) +
        geom_errorbar(aes(ymax = UL,
                          ymin = LL),
                      width = width.errbar,
                      position = position_dodge(width = position.fill)) +
        geom_point(col = col.shape,
                   position = position_dodge(width = position.fill),
                   size = size.shape,
                   shape = shape)
    } else{
      p <-
        ggplot(object, aes(x = reorder(Pair, Corr), y = Corr)) +
          geom_errorbar(aes(ymax = UL,
                            ymin = LL),
                        width = width.errbar) +
        geom_point(col = col.shape,
                   fill = fill.shape,
                   size = size.shape,
                   shape = shape)
    }
  } else{
    if(!missing(fill)){
      p <-
        ggplot(object, aes(x = Pair, y = Corr, fill = {{fill}})) +
        geom_errorbar(aes(ymax = UL,
                          ymin = LL),
                      width = width.errbar,
                      position = position_dodge(width = position.fill)) +
        geom_point(col = col.shape,
                   position = position_dodge(width = position.fill),
                   size = size.shape,
                   shape = shape)
    } else{
      p <-
        ggplot(object, aes(x = Pair, y = Corr)) +
        geom_errorbar(aes(ymax = UL,
                          ymin = LL),
                      width = width.errbar) +
        geom_point(col = col.shape,
                   fill = fill.shape,
                   size = size.shape,
                   shape = shape)

    }
  }
  p <- p + geom_hline(yintercept = 0, linetype = "dashed")
  if (invert.axis == TRUE) {
    p <- p + coord_flip()
  } else {
    p <- p
  }
  p <- p + plot_theme %+replace%
    theme(axis.text = element_text(colour = "black"),
          legend.position = legend.position) +
    labs(x = x.lab, y = y.lab)
  if (main == TRUE) {
    p <- p + ggtitle("95% CI for Pearson's correlation coefficient",
                     subtitle = paste("n = ", n))
  }
  return(p)
}