stability greyscale, font size, panel labels

R/stability_test.R

@@ -7,33 +7,39 @@
 #' @param var_name The column name containing the variable to be analyzed. Defaults to "tprate".
 #' @param ld_name The column name containing the leadtimes. Defaults to "leadtime".
 #' @param lab The x-label. Defaults to the variable name (var_name).
+#' @param fontsize The font size. Defaults to 11.
+#' @param greyscale Boolean. Use grey scale? Defaults to TRUE.
 #'
 #' @return a plot showing the empirical probability density distribution for each leadtime
 #' @source Evaluation explained in more detail in Kelder et al. 2020
 #' @source Colorblind friendly palette  http://www.cookbook-r.com/Graphs/Colors_(ggplot2)/#a-colorblind-friendly-palette
 #' @export
-Model_stability_density <- function(ensemble, var_name = "tprate", ld_name = "leadtime", lab = var_name) {
-  # I select five colors and put black at the end.
-  cbPalette <- c("#E69F00", "#56B4E9", "#009E73", "#F0E442", "#D55E00", "#000000") # , "#0072B2", "#CC79A7")
-  ### The Leadtime column has to be a factor for a grouped plot
+Model_stability_density <- function(ensemble, var_name = "tprate", ld_name = "leadtime", lab = var_name, fontsize = 11, greyscale = TRUE) {
+  # I select colors of grey scale, n= number of lead times
+  ensemble_length <- length(ensemble[[ld_name]])
+  leadtime_length <- sum(ensemble[[ld_name]] == 2)
+  if (greyscale == TRUE) {
+    cbPalette <- grey.colors(n = ensemble_length/leadtime_length)
+  }else{
+    cbPalette <- c("#E69F00", "#56B4E9", "#009E73", "#F0E442", "#D55E00", "#000000") # , "#0072B2", "#CC79A7")
+  }
+
+    ### Change the leadtime column into a factor for a grouped plot
   ensemble[[ld_name]] <- as.factor(ensemble[[ld_name]])
 
   p1 <-
     ggplot2::ggplot(
       data = ensemble,
       mapping = ggplot2::aes_(
         x = as.name(var_name), colour = as.name(ld_name))) +
-    # ggplot2::ggtitle("UK") +
     ggplot2::labs(x = lab, y = "Density") +
     ggplot2::geom_line(stat = "density") +
     ggplot2::theme_classic() +
     ggplot2::theme(legend.position = "none") +
-    ggplot2::scale_colour_manual(values = cbPalette) #+
-  # theme(
-  #   text = element_text(size = 11),
-  #   axis.text = element_text(size = 11),
-  #   plot.title = element_text(hjust = 0.5)
-  # )
+    ggplot2::scale_colour_manual(values = cbPalette) +
+    ggplot2::theme(text = ggplot2::element_text(size = fontsize),
+                   axis.text = ggplot2::element_text(size = fontsize)
+                   )
 
   return(p1)
 }
@@ -50,13 +56,15 @@ Model_stability_density <- function(ensemble, var_name = "tprate", ld_name = "le
 #' @param var_name The column name containing the variable to be analyzed. Defaults to "tprate".
 #' @param ld_name The column name containing the leadtimes. Defaults to "leadtime".
 #' @param lab The y-label. Defaults to the variable name (var_name).
+#' @param fontsize The font size. Defaults to 11.
+#' @param greyscale Boolean. Use grey scale? Defaults to TRUE.
 #'
 #' @return a plot with the empirical return values of the pooled ensemble including confidence intervals.
 #' Individual lead times are plotted on top.
 #' @source Evaluation explaned in more detail in Kelder et al. 2020
 #' @source Colorblind friendly palette  http://www.cookbook-r.com/Graphs/Colors_(ggplot2)/#a-colorblind-friendly-palette
 #' @export
-Model_stability_boot <- function(ensemble, var_name = "tprate", ld_name = "leadtime", lab = var_name) {
+Model_stability_boot <- function(ensemble, var_name = "tprate", ld_name = "leadtime", lab = var_name, fontsize = 11, greyscale = TRUE) {
   #Define necessary global variables
   ci_2.5 <- ci_97.5 <- quantiles_all <- rps_all <- NULL
 
@@ -97,24 +105,24 @@ Model_stability_boot <- function(ensemble, var_name = "tprate", ld_name = "leadt
   df_quantiles$ci_97.5 <- ci_rvs[2, ]
 
   # And plot
-  cbPalette <- c("#E69F00", "#56B4E9", "#009E73", "#F0E442", "#D55E00", "#000000") # , "#0072B2", "#CC79A7")
-  cols <- c("95 % CI" = "black")
+  if (greyscale == TRUE) {
+    cbPalette <- grey.colors(n = ensemble_length/leadtime_length)
+  }else{
+    cbPalette <- c("#E69F00", "#56B4E9", "#009E73", "#F0E442", "#D55E00", "#000000") # , "#0072B2", "#CC79A7")
+  }
   p2 <-
     ggplot2::ggplot(df_quantiles) +
     ggplot2::geom_line(ggplot2::aes(x = rps_all, y = quantiles_all)) +
     ggplot2::geom_line(ggplot2::aes_(x = ~rps_ld, y = ~quantiles_ld, col = as.name(ld_name))) +
-    ggplot2::geom_ribbon(ggplot2::aes(x = rps_all, ymin = ci_2.5, ymax = ci_97.5, fill = "95 % CI"), alpha = 0.1) +
-    # xlim(NA,875)+
+    ggplot2::geom_ribbon(ggplot2::aes(x = rps_all, ymin = ci_2.5, ymax = ci_97.5, fill = "black"), alpha = 0.1) +
     ggplot2::scale_x_log10(limits = c(NA, leadtime_length)) +
-    # scale_x_continuous(trans='log10') +
-    ggplot2::scale_fill_manual(name = "Pooled data", values = cols) +
     ggplot2::scale_colour_manual(values = cbPalette) +
     ggplot2::xlab("Return period (years)") +
     ggplot2::ylab(lab) +
     ggplot2::theme_classic() +
     ggplot2::theme(legend.position = "none",
-                   text = ggplot2::element_text(size = 11),
-                   axis.text = ggplot2::element_text(size = 11)
+                   text = ggplot2::element_text(size = fontsize),
+                   axis.text = ggplot2::element_text(size = fontsize)
     )
   return(p2)
 }
@@ -124,21 +132,24 @@ Model_stability_boot <- function(ensemble, var_name = "tprate", ld_name = "leadt
 #' @param ensemble The UNSEEN ensemble. This function expects an dataframe with variables leadtime, precipitation.
 #' @param var_name The column name containing the variable to be analyzed. Defaults to "tprate".
 #' @param ld_name The column name containing the leadtimes. Defaults to "leadtime".
-#' @param lab The label. Defaults to the variable name (var_name).
+#' @param lab The variable name plotted as x-label (first panel) and y-label (second panel). Defaults to the variable name (var_name).
+#' @param panel_labels The panel labels. Defaults to c("a", "b").
+#' @param fontsize The font size. Defaults to 11.
+#' @param greyscale Boolean. Use grey scale? Defaults to TRUE.
 #'
 #' @return a plot with the empirical return values of the pooled ensemble including confidence intervals.
 #' Individual lead times are plotted on top.
 #' @seealso [Model_stability_density()] [Model_stability_boot()]d
 #' @source Evaluation explaned in more detail in Kelder et al. 2020
 #' @source Colorblind friendly palette  http://www.cookbook-r.com/Graphs/Colors_(ggplot2)/#a-colorblind-friendly-palette
 #' @export
-stability_test <- function(ensemble, var_name = "tprate", ld_name = "leadtime", lab = var_name) {
+stability_test <- function(ensemble, var_name = "tprate", ld_name = "leadtime", lab = var_name, fontsize = 11, greyscale = TRUE, panel_labels = c("a", "b")) {
   #combine plots from function 1 and 2
-  p1 <- Model_stability_density(ensemble = ensemble, var_name = var_name, ld_name = ld_name, lab = lab)
-  p2 <- Model_stability_boot(ensemble = ensemble, var_name = var_name, ld_name = ld_name, lab = lab)
+  p1 <- Model_stability_density(ensemble = ensemble, var_name = var_name, ld_name = ld_name, lab = lab, fontsize = fontsize, greyscale = greyscale)
+  p2 <- Model_stability_boot(ensemble = ensemble, var_name = var_name, ld_name = ld_name, lab = lab, fontsize = fontsize, greyscale = greyscale)
   p_combined <- ggpubr::ggarrange(p1, p2,
-                          labels = c("a", "b"), # , "c", "d"),
-                          hjust = c(-0.5, 1, -0.5, 1),
+                          labels = panel_labels,
+                          # hjust = c(-0.5, 1, -0.5, 1),
                           ncol = 1, nrow = 2,
                           font.label = list(size = 11, color = "black", face = "bold", family = NULL),
                           common.legend = TRUE