Move {MASS} to Suggests

DESCRIPTION

@@ -38,7 +38,6 @@ Imports:
     gtable (>= 0.1.1),
     isoband,
     lifecycle (> 1.0.1),
-    MASS,
     rlang (>= 1.1.0),
     scales (>= 1.3.0),
     stats,
@@ -53,6 +52,7 @@ Suggests:
     knitr,
     mapproj,
     maps,
+    MASS,
     mgcv,
     multcomp,
     munsell,

NEWS.md

@@ -1,5 +1,7 @@
 # ggplot2 (development version)
 
+* `geom_errorbarh()` is deprecated in favour of 
+  `geom_errorbar(orientation = "y")` (@teunbrand, #5961).
 * `geom_contour()` should be able to recognise a rotated grid of points 
   (@teunbrand, #4320)
 * `geom_boxplot()` gains additional arguments to style the colour, linetype and

R/stat-density-2d.R

@@ -138,6 +138,7 @@ StatDensity2d <- ggproto("StatDensity2d", Stat,
   contour_type = "lines",
 
   compute_layer = function(self, data, params, layout) {
+    check_installed("MASS", reason = "for calculating 2D density.")
     # first run the regular layer calculation to infer densities
     data <- ggproto_parent(Stat, self)$compute_layer(data, params, layout)
 

R/stat-ellipse.R

@@ -77,6 +77,14 @@ stat_ellipse <- function(mapping = NULL, data = NULL,
 StatEllipse <- ggproto("StatEllipse", Stat,
   required_aes = c("x", "y"),
 
+  setup_params = function(data, params) {
+    params$type <- params$type %||% "t"
+    if (identical(params$type, "t")) {
+      check_installed("MASS", "for calculating ellipses with `type = \"t\"`.")
+    }
+    params
+  },
+
   compute_group = function(data, scales, type = "t", level = 0.95,
                            segments = 51, na.rm = FALSE) {
     calculate_ellipse(data = data, vars = c("x", "y"), type = type,

R/stat-qq.R

@@ -32,8 +32,12 @@
 #' p <- ggplot(df, aes(sample = y))
 #' p + stat_qq() + stat_qq_line()
 #'
-#' # Use fitdistr from MASS to estimate distribution params
-#' params <- as.list(MASS::fitdistr(df$y, "t")$estimate)
+#' # Use fitdistr from MASS to estimate distribution params:
+#' # if (requireNamespace("MASS", quietly = TRUE)) {
+#' #   params <- as.list(MASS::fitdistr(df$y, "t")$estimate)
+#' # }
+#' # Here, we use pre-computed params
+#' params <- list(m = -0.02505057194115, s = 1.122568610124, df = 6.63842653897)
 #' ggplot(df, aes(sample = y)) +
 #'   stat_qq(distribution = qt, dparams = params["df"]) +
 #'   stat_qq_line(distribution = qt, dparams = params["df"])

tests/testthat/test-stat-density2d.R

@@ -1,3 +1,5 @@
+skip_if_not_installed("MASS")
+
 test_that("uses scale limits, not data limits", {
   base <- ggplot(mtcars, aes(wt, mpg)) +
     stat_density_2d() +

tests/testthat/test-stat-ellipsis.R

@@ -1,3 +1,5 @@
+skip_if_not_installed("MASS")
+
 test_that("stat_ellipsis returns correct data format", {
   n_seg <- 40
   d <- data_frame(x = c(1, 1, 4, 4, 4, 3, 3, 1), y = c(1:4, 1:4), id = rep(1:2, each = 4))