Merge branch 'main' into geomsf-updateshape

Author: thomasp85

NEWS.md

@@ -1,6 +1,7 @@
 # ggplot2 (development version)
 
 * geom_sf now accepts shape names (@sierrajohnson, #5808)
+* Added `gg` class to `labs()` (@phispu, #5553).
 * Missing values from discrete palettes are no longer translated 
   (@teunbrand, #5929).
 * Fixed bug in `facet_grid(margins = TRUE)` when using expresssions 

R/geom-smooth.R

@@ -9,7 +9,7 @@
 #' `predictdf()` generic and its methods.  For most methods the standard
 #' error bounds are computed using the [predict()] method -- the
 #' exceptions are `loess()`, which uses a t-based approximation, and
-#' `glm()`, where the normal confidence interval is constructed on the link
+#' `glm()`, where the normal confidence band is constructed on the link
 #' scale and then back-transformed to the response scale.
 #'
 #' @eval rd_orientation()

R/labeller.R

@@ -83,6 +83,9 @@
 #' # Interpreting the labels as plotmath expressions
 #' p + facet_grid(. ~ cyl2)
 #' p + facet_grid(. ~ cyl2, labeller = label_parsed)
+#'
+#' # Include optional argument in label function
+#' p + facet_grid(. ~ cyl, labeller = function(x) label_both(x, sep = "="))
 #' }
 #' @name labellers
 NULL
@@ -320,7 +323,7 @@ as_labeller <- function(x, default = label_value, multi_line = TRUE) {
 #'
 #' This function makes it easy to assign different labellers to
 #' different factors. The labeller can be a function or it can be a
-#' named character vectors that will serve as a lookup table.
+#' named character vector that will serve as a lookup table.
 #'
 #' In case of functions, if the labeller has class `labeller`, it
 #' is directly applied on the data frame of labels. Otherwise, it is

R/labels.R

@@ -139,7 +139,7 @@ labs <- function(..., title = waiver(), subtitle = waiver(), caption = waiver(),
   args <- args[!duplicated(names(args))]
   args <- rename_aes(args)
 
-  structure(args, class = "labels")
+  structure(args, class = c("labels", "gg"))
 }
 
 #' @rdname labs

R/layer.R

@@ -58,7 +58,9 @@
 #'   `NA`, the default, includes if any aesthetics are mapped.
 #'   `FALSE` never includes, and `TRUE` always includes.
 #'   It can also be a named logical vector to finely select the aesthetics to
-#'   display.
+#'   display. To include legend keys for all levels, even 
+#'   when no data exists, use `TRUE`.  If `NA`, all levels are shown in legend, 
+#'   but unobserved levels are omitted.
 #' @param inherit.aes If `FALSE`, overrides the default aesthetics,
 #'   rather than combining with them. This is most useful for helper functions
 #'   that define both data and aesthetics and shouldn't inherit behaviour from

R/stat-density.R

@@ -242,6 +242,7 @@ reflect_density <- function(dens, bounds, from, to) {
 precompute_bw = function(x, bw = "nrd0") {
   bw <- bw[1]
   if (is.character(bw)) {
+    bw <- to_lower_ascii(bw)
     bw <- arg_match0(bw, c("nrd0", "nrd", "ucv", "bcv", "sj", "sj-ste", "sj-dpi"))
     bw <- switch(
       to_lower_ascii(bw),

R/stat-smooth.R

@@ -18,15 +18,15 @@
 #'   `y ~ poly(x, 2)`, `y ~ log(x)`. `NULL` by default, in which case
 #'   `method = NULL` implies `formula = y ~ x` when there are fewer than 1,000
 #'   observations and `formula = y ~ s(x, bs = "cs")` otherwise.
-#' @param se Display confidence interval around smooth? (`TRUE` by default, see
+#' @param se Display confidence band around smooth? (`TRUE` by default, see
 #'   `level` to control.)
 #' @param fullrange If `TRUE`, the smoothing line gets expanded to the range of the plot,
 #'   potentially beyond the data. This does not extend the line into any additional padding
 #'   created by `expansion`.
 #' @param xseq A numeric vector of values at which the smoother is evaluated.
 #'   When `NULL` (default), `xseq` is internally evaluated as a sequence of `n`
 #'   equally spaced points for continuous data.
-#' @param level Level of confidence interval to use (0.95 by default).
+#' @param level Level of confidence band to use (0.95 by default).
 #' @param span Controls the amount of smoothing for the default loess smoother.
 #'   Smaller numbers produce wigglier lines, larger numbers produce smoother
 #'   lines. Only used with loess, i.e. when `method = "loess"`,
@@ -40,8 +40,8 @@
 #'   .details = "`stat_smooth()` provides the following variables, some of
 #'   which depend on the orientation:",
 #'   "y|x" = "Predicted value.",
-#'   "ymin|xmin" = "Lower pointwise confidence interval around the mean.",
-#'   "ymax|xmax" = "Upper pointwise confidence interval around the mean.",
+#'   "ymin|xmin" = "Lower pointwise confidence band around the mean.",
+#'   "ymax|xmax" = "Upper pointwise confidence band around the mean.",
 #'   "se" = "Standard error."
 #' )
 #' @export

R/utilities-break.R

@@ -24,6 +24,9 @@
 #' table(cut_width(runif(1000), 0.1, center = 0))
 #' table(cut_width(runif(1000), 0.1, labels = FALSE))
 cut_interval <- function(x, n = NULL, length = NULL, ...) {
+  if ((!is.null(n) && !is.null(length)) || (is.null(n) && is.null(length))) {
+    cli::cli_abort("Specify exactly one of {.var n} and {.var length}.")
+  }
   cut(x, breaks(x, "width", n, length), include.lowest = TRUE, ...)
 }