Update stat_ecdf to work either on the x or the y aesthetic. (#4005)

* Update stat_ecdf to work either on the x or the y aesthetic, whatever is provided.

* Undo breaking change of renaming the stats result and go back to y.

* Add bullet to NEWS.md

* Fix typo in comments.

* Improve comment.

* Document

Co-authored-by: GitHub Actions <actions@github.com>

Author: jgjl

NEWS.md

@@ -1,5 +1,7 @@
 # ggplot2 (development version)
 
+* Extended `stat_ecdf()` to calculate the cdf from either x or y instead from y only (@jgjl, #4005).
+
 * Fixed a bug in `labeller()` so that `.default` is passed to `as_labeller()`
   when labellers are specified by naming faceting variables. (@waltersom, #4031)
 

R/stat-ecdf.r

@@ -7,6 +7,11 @@
 #' The downside is that it requires more training to accurately interpret,
 #' and the underlying visual tasks are somewhat more challenging.
 #'
+#' The statistic relies on the aesthetics assignment to guess which variable to
+#' use as the input and which to use as the output. Either x or y must be provided
+#' and one of them must be unused. The ECDF will be calculated on the given aesthetic
+#' and will be output on the unused one.
+#'
 #' @inheritParams layer
 #' @inheritParams geom_point
 #' @param na.rm If `FALSE` (the default), removes missing values with
@@ -17,7 +22,6 @@
 #'   and (Inf, 1)
 #' @section Computed variables:
 #' \describe{
-#'   \item{x}{x in data}
 #'   \item{y}{cumulative density corresponding x}
 #' }
 #' @export
@@ -67,7 +71,24 @@ stat_ecdf <- function(mapping = NULL, data = NULL,
 #' @usage NULL
 #' @export
 StatEcdf <- ggproto("StatEcdf", Stat,
-  compute_group = function(data, scales, n = NULL, pad = TRUE) {
+  required_aes = c("x|y"),
+
+  default_aes = aes(y = after_stat(y)),
+
+  setup_params = function(data, params) {
+    params$flipped_aes <- has_flipped_aes(data, params, main_is_orthogonal = FALSE, main_is_continuous = TRUE)
+
+    has_x <- !(is.null(data$x) && is.null(params$x))
+    has_y <- !(is.null(data$y) && is.null(params$y))
+    if (!has_x && !has_y) {
+      abort("stat_ecdf() requires an x or y aesthetic.")
+    }
+
+    params
+  },
+
+  compute_group = function(data, scales, n = NULL, pad = TRUE, flipped_aes = FALSE) {
+    data <- flip_data(data, flipped_aes)
     # If n is NULL, use raw values; otherwise interpolate
     if (is.null(n)) {
       x <- unique(data$x)
@@ -78,13 +99,11 @@ StatEcdf <- ggproto("StatEcdf", Stat,
     if (pad) {
       x <- c(-Inf, x, Inf)
     }
-    y <- ecdf(data$x)(x)
-
-    new_data_frame(list(x = x, y = y), n = length(x))
-  },
-
-  default_aes = aes(y = after_stat(y)),
+    data_ecdf <- ecdf(data$x)(x)
 
-  required_aes = c("x")
+    df_ecdf <- new_data_frame(list(x = x, y = data_ecdf), n = length(x))
+    df_ecdf$flipped_aes <- flipped_aes
+    flip_data(df_ecdf, flipped_aes)
+  }
 )
 

man/stat_ecdf.Rd

@@ -0,0 +1,16 @@
+context("stat_ecdf")
+
+test_that("stat_ecdf works in both directions", {
+  p <- ggplot(mpg, aes(hwy)) + stat_ecdf()
+  x <- layer_data(p)
+  expect_false(x$flipped_aes[1])
+
+  p <- ggplot(mpg, aes(y = hwy)) + stat_ecdf()
+  y <- layer_data(p)
+  expect_true(y$flipped_aes[1])
+
+  x$flipped_aes <- NULL
+  y$flipped_aes <- NULL
+  expect_identical(x, flip_data(y, TRUE)[,names(x)])
+})
+