Update documentation

R/plotResponse.R

@@ -13,10 +13,17 @@
 #' marginal curves.
 #' @param rug logical. If `TRUE` it adds the rug plot for the presence and
 #' absence/background locations, available only for continuous variables.
-#' @param color The colour of the curve, default is "red".
-#'
-#' @details Note that fun is not a character argument, you must use `mean` and
-#' not `"mean"`.
+#' @param color The color of the curve, default is "red".
+#'
+#' @details
+#' * Note that `fun` is not a character argument, you must use `mean` and not
+#' `"mean"`.
+#' * If you want to modify the plot, first you have to assign the output of the
+#' function to a variable, and then you have two options:
+#' + Modify the `ggplot` object by editing the theme or adding additional
+#' elements
+#' + Get the data with `ggplot2::ggplot_build()` and then build your own
+#' plot (see examples)
 #'
 #' @return A \link[ggplot2]{ggplot} object.
 #' @export
@@ -26,8 +33,7 @@
 #' @author Sergio Vignali
 #'
 #' @examples
-#' \donttest{
-#' # Acquire environmental variables
+#' \donttest{# Acquire environmental variables
 #' files <- list.files(path = file.path(system.file(package = "dismo"), "ex"),
 #' pattern = "grd",
 #' full.names = TRUE)
@@ -77,6 +83,23 @@
 #' type = "logistic",
 #' color = "green")
 #'
+#' # Modify plot
+#' # Change y axes limits
+#' my_plot <- plotResponse(model,
+#' var = "bio1",
+#' type = "cloglog")
+#' my_plot +
+#' ggplot2::scale_y_continuous(limits = c(0, 1))
+#'
+#' # Get the data and create your own plot:
+#' df <- ggplot2::ggplot_build(my_plot)$data[[1]]
+#' plot(df$x, df$y,
+#' type = "l",
+#' lwd = 3,
+#' col = "blue",
+#' xlab = "bio1",
+#' ylab = "cloglog output")
+#'
 #' # Train a model with cross validation
 #' folds <- randomFolds(data,
 #' k = 4,
@@ -97,8 +120,7 @@
 #' plotResponse(model,
 #' var = "biome",
 #' type = "logistic",
-#' color = "green")
-#' }
+#' color = "green")}
 plotResponse <- function(model,
  var,
  type = NULL,