Expose argument n from stats::density in the interface of stat_density. (#1661)

* Expose argument n from stats::density in the interface of stat_density.

The argument controls the number of equally spaced points at which the
density is to be estimated. As in stats::density the argument n defaults
to 512. It is exposed through the function interface of stat_density and
can thus also be used from geom_density.

An existent local variable n, which holds the number of values in
the input vector, has been renamed to nx to avoid a name clash.

* Added a note about powers of two being recommended.

Author: hbuschme

NEWS.md

@@ -59,6 +59,7 @@
 * The `theme()` constructor now has named arguments rather than ellipsis. This 
   should make autocomplete substantially more useful.
 
+
 * `position_stack()` and `position_fill()` now sorts the stacking order so it 
   matches the order of the grouping. Use level reordering to alter the stacking 
   order. The default legend and stacking order is now also in line. The default 
@@ -87,6 +88,10 @@
 
 * `stat_ecdf()` respects `pad` argument (#1646).
 
+* `stat_density` now makes argument `n` of the unterlying function
+  `stats::density` ("number of equally spaced points at which the
+  density is to be estimated") accessible. (@hbuschme)
+
 * `x` and `y` scales are now symmetric regarding the list of
   aesthetics they accept: `xmin_final`, `xmax_final`, `xlower`,
   `xmiddle` and `xupper` are now valid `x` aesthetics.

R/stat-density.r

@@ -4,6 +4,9 @@
 #'   \code{\link{density}} for details
 #' @param kernel kernel used for density estimation, see
 #'   \code{\link{density}} for details
+#' @param n number of equally spaced points at which the density is to be
+#'   estimated, should be a power of two, see \code{\link{density}} for
+#'   details
 #' @param trim This parameter only matters if you are displaying multiple
 #'   densities in one plot. If \code{FALSE}, the default, each density is
 #'   computed on the full range of the data. If \code{TRUE}, each density
@@ -25,6 +28,7 @@ stat_density <- function(mapping = NULL, data = NULL,
                          bw = "nrd0",
                          adjust = 1,
                          kernel = "gaussian",
+                         n = 512,
                          trim = FALSE,
                          na.rm = FALSE,
                          show.legend = NA,
@@ -42,6 +46,7 @@ stat_density <- function(mapping = NULL, data = NULL,
       bw = bw,
       adjust = adjust,
       kernel = kernel,
+      n = n,
       trim = trim,
       na.rm = na.rm,
       ...
@@ -58,45 +63,45 @@ StatDensity <- ggproto("StatDensity", Stat,
   default_aes = aes(y = ..density.., fill = NA),
 
   compute_group = function(data, scales, bw = "nrd0", adjust = 1, kernel = "gaussian",
-                           trim = FALSE, na.rm = FALSE) {
+                           n = 512, trim = FALSE, na.rm = FALSE) {
     if (trim) {
       range <- range(data$x, na.rm = TRUE)
     } else {
       range <- scales$x$dimension()
     }
 
     compute_density(data$x, data$weight, from = range[1], to = range[2],
-      bw = bw, adjust = adjust, kernel = kernel)
+      bw = bw, adjust = adjust, kernel = kernel, n = n)
   }
 
 )
 
 compute_density <- function(x, w, from, to, bw = "nrd0", adjust = 1,
-                            kernel = "gaussian") {
-  n <- length(x)
+                            kernel = "gaussian", n = 512) {
+  nx <- length(x)
   if (is.null(w)) {
-    w <- rep(1 / n, n)
+    w <- rep(1 / nx, nx)
   }
 
   # if less than 3 points, spread density evenly over points
-  if (n < 3) {
+  if (nx < 3) {
     return(data.frame(
       x = x,
       density = w / sum(w),
       scaled = w / max(w),
       count = 1,
-      n = n
+      n = nx
     ))
   }
 
   dens <- stats::density(x, weights = w, bw = bw, adjust = adjust,
-    kernel = kernel, from = from, to = to)
+    kernel = kernel, n = n, from = from, to = to)
 
   data.frame(
     x = dens$x,
     density = dens$y,
     scaled =  dens$y / max(dens$y, na.rm = TRUE),
-    count =   dens$y * n,
-    n = n
+    count =   dens$y * nx,
+    n = nx
   )
 }