Merge branch 'main' into v3.4.1-rc

Author: thomasp85

.github/ISSUE_TEMPLATE/bug_report.md

@@ -0,0 +1,35 @@
+---
+name: Bug report
+about: Submit a bug report to help us improve ggplot2
+---
+
+### Tips for a helpful bug report:
+
+* If you have a question, please don't use this form. Instead, ask on <https://stackoverflow.com/> or <https://community.rstudio.com/>.
+
+* Please include a **minimal reproducible example**, a reprex, to demonstrate the bug.
+If you've never heard of a reprex, please read ["Make a reprex"](https://www.tidyverse.org/help/#reprex).
+Do not include session info unless it is explicitly asked for.
+
+* If you can, use one of the built-in datasets or a small toy dataset that exposes the bug.
+If for some reason, the bug only occurs on your original data, try to limit the number of rows that are necessary to expose the bug. 
+Share such data by copying `dput()` output rather than an external file.
+
+* Unless the bug is about the theme, labels, scales or other plot decoration: please omit these from the code.
+    
+* Please check whether somebody has reported the same problem in the [issues](https://github.com/tidyverse/ggplot2/issues).
+
+Delete these instructions once you have read them.
+
+---
+
+I found a problem with ...
+
+I expected ...
+
+Here is the code to reproduce the bug:
+
+```r
+# copy your code to the clipboard and run:
+reprex::reprex()
+```

.github/ISSUE_TEMPLATE/config.yml

@@ -0,0 +1,4 @@
+contact_links:
+  - name: Help or discussion
+    url: https://community.rstudio.com/
+    about: "Check out options for getting help on the RStudio Community."

.github/ISSUE_TEMPLATE/feature_request.md

@@ -0,0 +1,30 @@
+---
+name: "Feature Request"
+about: Suggest a change or new feature in ggplot2
+---
+
+### Tips for a helpful feature request:
+
+* If you have a question, please don't use this form. Instead, ask on <https://stackoverflow.com/> or <https://community.rstudio.com/>.
+
+* See the [contributing guidelines](https://github.com/tidyverse/ggplot2/blob/main/CONTRIBUTING.md).
+
+* ggplot2 is a mature package that is unlikely to adopt new functionality that can be covered by its extension mechanisms.
+Improvements to its current functionality or to infrastructure are considered in scope for feature requests.
+
+* Please motivate the need for change, if applicable with a **minimal reproducible** example (reprex).
+If you've never heard of a reprex, please read ["Make a reprex"](https://www.tidyverse.org/help/#reprex).
+Do not include session info unless it is explicitly asked for.
+
+Delete this instructions once you've read them.
+
+---
+
+In situations when ...
+
+I would like to be able to ...
+
+```r
+# copy your code to the clipboard and run:
+reprex::reprex()
+```

.github/workflows/R-CMD-check.yaml

@@ -59,7 +59,7 @@ jobs:
 
       - uses: r-lib/actions/setup-r-dependencies@v2
         with:
-          cache-version: 2
+          cache-version: 3
           extra-packages: >
             any::rcmdcheck,
             Hmisc=?ignore-before-r=3.6.0,

DESCRIPTION

@@ -80,7 +80,7 @@ Config/testthat/edition: 3
 Encoding: UTF-8
 LazyData: true
 Roxygen: list(markdown = TRUE)
-RoxygenNote: 7.2.1
+RoxygenNote: 7.2.3
 Collate: 
     'ggproto.r'
     'ggplot-global.R'

ISSUE_TEMPLATE.md

@@ -132,8 +132,10 @@ S3method(scale_type,Date)
 S3method(scale_type,POSIXt)
 S3method(scale_type,character)
 S3method(scale_type,default)
+S3method(scale_type,double)
 S3method(scale_type,factor)
 S3method(scale_type,hms)
+S3method(scale_type,integer)
 S3method(scale_type,list)
 S3method(scale_type,logical)
 S3method(scale_type,numeric)
@@ -316,6 +318,7 @@ export(coord_trans)
 export(cut_interval)
 export(cut_number)
 export(cut_width)
+export(datetime_scale)
 export(derive)
 export(discrete_scale)
 export(draw_key_abline)

NAMESPACE

@@ -1,5 +1,14 @@
 # ggplot2 (development version)
 
+* Fixed bug in `coord_sf()` where graticule lines didn't obey 
+  `panel.grid.major`'s linewidth setting (@teunbrand, #5179)
+* The `datetime_scale()` scale constructor is now exported for use in extension
+  packages (@teunbrand, #4701).
+* `geom_text()` drops observations where `angle = NA` instead of throwing an
+  error (@teunbrand, #2757).
+* `update_geom_defaults()` and `update_stat_defaults()` now return properly 
+  classed objects and have updated docs (@dkahle, #5146)
+  
 # ggplot2 3.4.1
 This is a small release focusing on fixing regressions in the 3.4.0 release
 and minor polishes.

NEWS.md

@@ -305,7 +305,7 @@ CoordSf <- ggproto("CoordSf", CoordCartesian,
     } else {
       line_gp <- gpar(
         col = el$colour,
-        lwd = len0_null(el$size*.pt),
+        lwd = len0_null(el$linewidth * .pt),
         lty = el$linetype
       )
       grobs <- c(

R/coord-sf.R

@@ -7,14 +7,38 @@
 #' @keywords internal
 #' @export
 #' @examples
-#' update_geom_defaults("point", list(colour = "darkblue"))
+#'
+#' # updating a geom's default aesthetic settings
+#' # example: change geom_point()'s default color
+#' GeomPoint$default_aes
+#' update_geom_defaults("point", aes(color = "red"))
+#' GeomPoint$default_aes
 #' ggplot(mtcars, aes(mpg, wt)) + geom_point()
-#' update_geom_defaults("point", list(colour = "black"))
+#'
+#' # reset default
+#' update_geom_defaults("point", aes(color = "black"))
+#'
+#'
+#' # updating a stat's default aesthetic settings
+#' # example: change stat_bin()'s default y-axis to the density scale
+#' StatBin$default_aes
+#' update_stat_defaults("bin", aes(y = after_stat(density)))
+#' StatBin$default_aes
+#' ggplot(data.frame(x = rnorm(1e3)), aes(x)) +
+#'   geom_histogram() +
+#'   geom_function(fun = dnorm, color = "red")
+#'
+#' # reset default
+#' update_stat_defaults("bin", aes(y = after_stat(count)))
+#'
 #' @rdname update_defaults
 update_geom_defaults <- function(geom, new) {
   g <- check_subclass(geom, "Geom", env = parent.frame())
   old <- g$default_aes
-  g$default_aes <- defaults(rename_aes(new), old)
+  new <- rename_aes(new)
+  new_names_order <- unique(c(names(old), names(new)))
+  new <- defaults(new, old)[new_names_order]
+  g$default_aes[names(new)] <- new
   invisible()
 }
 
@@ -23,6 +47,9 @@ update_geom_defaults <- function(geom, new) {
 update_stat_defaults <- function(stat, new) {
   g <- check_subclass(stat, "Stat", env = parent.frame())
   old <- g$default_aes
-  g$default_aes <- defaults(rename_aes(new), old)
+  new <- rename_aes(new)
+  new_names_order <- unique(c(names(old), names(new)))
+  new <- defaults(new, old)[new_names_order]
+  g$default_aes[names(new)] <- new
   invisible()
 }

R/geom-defaults.r

@@ -145,7 +145,7 @@
 #' df <- data.frame(
 #'   x = c(1, 1, 2, 2, 1.5),
 #'   y = c(1, 2, 1, 2, 1.5),
-#'   text = c("bottom-left", "bottom-right", "top-left", "top-right", "center")
+#'   text = c("bottom-left", "top-left", "bottom-right", "top-right", "center")
 #' )
 #' ggplot(df, aes(x, y)) +
 #'   geom_text(aes(label = text))
@@ -198,6 +198,8 @@ geom_text <- function(mapping = NULL, data = NULL,
 GeomText <- ggproto("GeomText", Geom,
   required_aes = c("x", "y", "label"),
 
+  non_missing_aes = "angle",
+
   default_aes = aes(
     colour = "black", size = 3.88, angle = 0, hjust = 0.5,
     vjust = 0.5, alpha = NA, family = "", fontface = 1, lineheight = 1.2

R/geom-text.r

@@ -6,26 +6,35 @@
 #' subsequent layers unless specifically overridden.
 #'
 #' `ggplot()` is used to construct the initial plot object,
-#' and is almost always followed by `+` to add component to the
-#' plot. There are three common ways to invoke `ggplot()`:
+#' and is almost always followed by a plus sign (`+`) to add
+#' components to the plot.
 #'
-#' * `ggplot(df, aes(x, y, other aesthetics))`
-#' * `ggplot(df)`
+#' There are three common patterns used to invoke `ggplot()`:
+#'
+#' * `ggplot(data = df, mapping = aes(x, y, other aesthetics))`
+#' * `ggplot(data = df)`
 #' * `ggplot()`
 #'
-#' The first method is recommended if all layers use the same
+#' The first pattern is recommended if all layers use the same
 #' data and the same set of aesthetics, although this method
-#' can also be used to add a layer using data from another
-#' data frame. See the first example below. The second
-#' method specifies the default data frame to use for the plot,
-#' but no aesthetics are defined up front. This is useful when
-#' one data frame is used predominantly as layers are added,
-#' but the aesthetics may vary from one layer to another. The
-#' third method initializes a skeleton `ggplot` object which
-#' is fleshed out as layers are added. This method is useful when
+#' can also be used when adding a layer using data from another
+#' data frame. 
+#'
+#' The second pattern specifies the default data frame to use
+#' for the plot, but no aesthetics are defined up front. This
+#' is useful when one data frame is used predominantly for the
+#' plot, but the aesthetics vary from one layer to another. 
+#'
+#' The third pattern initializes a skeleton `ggplot` object, which
+#' is fleshed out as layers are added. This is useful when
 #' multiple data frames are used to produce different layers, as
 #' is often the case in complex graphics.
 #'
+#' The `data =` and `mapping =` specifications in the arguments are optional
+#' (and are often omitted in practice), so long as the data and the mapping
+#' values are passed into the function in the right order. In the examples
+#' below, however, they are left in place for clarity.
+#'
 #' @param data Default dataset to use for plot. If not already a data.frame,
 #'   will be converted to one by [fortify()]. If not specified,
 #'   must be supplied in each layer added to the plot.
@@ -36,42 +45,61 @@
 #'   evaluation.
 #' @export
 #' @examples
-#' # Generate some sample data, then compute mean and standard deviation
-#' # in each group
+#' # Create a data frame with some sample data, then create a data frame
+#' # containing the mean value for each group in the sample data.
 #' set.seed(1)
-#' df <- data.frame(
-#'   gp = factor(rep(letters[1:3], each = 10)),
-#'   y = rnorm(30)
+#' 
+#' sample_df <- data.frame(
+#'   group = factor(rep(letters[1:3], each = 10)),
+#'   value = rnorm(30)
 #' )
-#' ds <- do.call(rbind, lapply(split(df, df$gp), function(d) {
-#'   data.frame(mean = mean(d$y), sd = sd(d$y), gp = d$gp)
-#' }))
-#'
-#' # The summary data frame ds is used to plot larger red points on top
-#' # of the raw data. Note that we don't need to supply `data` or `mapping`
-#' # in each layer because the defaults from ggplot() are used.
-#' ggplot(df, aes(gp, y)) +
+#' 
+#' group_means_df <- setNames(
+#'   aggregate(value ~ group, sample_df, mean),
+#'   c("group", "group_mean")
+#' )
+#' 
+#' # The following three code blocks create the same graphic, each using one
+#' # of the three patterns specified above. In each graphic, the sample data
+#' # are plotted in the first layer and the group means data frame is used to
+#' # plot larger red points on top of the sample data in the second layer.
+#' 
+#' # Pattern 1
+#' # Both the `data` and `mapping` arguments are passed into the `ggplot()`
+#' # call. Those arguments are omitted in the first `geom_point()` layer
+#' # because they get passed along from the `ggplot()` call. Note that the
+#' # second `geom_point()` layer re-uses the `x = group` aesthetic through
+#' # that mechanism but overrides the y-position aesthetic.
+#' ggplot(data = sample_df, mapping = aes(x = group, y = value)) +
 #'   geom_point() +
-#'   geom_point(data = ds, aes(y = mean), colour = 'red', size = 3)
-#'
-#' # Same plot as above, declaring only the data frame in ggplot().
-#' # Note how the x and y aesthetics must now be declared in
-#' # each geom_point() layer.
-#' ggplot(df) +
-#'   geom_point(aes(gp, y)) +
-#'   geom_point(data = ds, aes(gp, mean), colour = 'red', size = 3)
-#'
-#' # Alternatively we can fully specify the plot in each layer. This
-#' # is not useful here, but can be more clear when working with complex
-#' # mult-dataset graphics
+#'   geom_point(
+#'     mapping = aes(y = group_mean), data = group_means_df,
+#'     colour = 'red', size = 3
+#'   )
+#' 
+#' # Pattern 2
+#' # Same plot as above, passing only the `data` argument into the `ggplot()`
+#' # call. The `mapping` arguments are now required in each `geom_point()`
+#' # layer because there is no `mapping` argument passed along from the
+#' # `ggplot()` call.
+#' ggplot(data = sample_df) +
+#'   geom_point(mapping = aes(x = group, y = value)) +
+#'   geom_point(
+#'     mapping = aes(x = group, y = group_mean), data = group_means_df,
+#'     colour = 'red', size = 3
+#'   )
+#' 
+#' # Pattern 3
+#' # Same plot as above, passing neither the `data` or `mapping` arguments
+#' # into the `ggplot()` call. Both those arguments are now required in
+#' # each `geom_point()` layer. This pattern can be particularly useful when
+#' # creating more complex graphics with many layers using data from multiple
+#' # data frames.
 #' ggplot() +
-#'   geom_point(data = df, aes(gp, y)) +
-#'   geom_point(data = ds, aes(gp, mean), colour = 'red', size = 3) +
-#'   geom_errorbar(
-#'     data = ds,
-#'     aes(gp, mean, ymin = mean - sd, ymax = mean + sd),
-#'     colour = 'red',
-#'     width = 0.4
+#'   geom_point(mapping = aes(x = group, y = value), data = sample_df) +
+#'   geom_point(
+#'     mapping = aes(x = group, y = group_mean), data = group_means_df,
+#'     colour = 'red', size = 3
 #'   )
 ggplot <- function(data = NULL, mapping = aes(), ...,
                    environment = parent.frame()) {

R/plot.r

@@ -275,7 +275,16 @@ scale_y_time <- function(name = waiver(),
   )
 }
 
-## rename to datetime_scale
+#' Date/time scale constructor
+#'
+#' @inheritParams scale_x_datetime
+#' @inheritParams continuous_scale
+#' @param trans For date/time scales, the name of a date/time transformation or
+#'   the object itself. Built-in transformations include "hms", "date" and "time".
+#' @inheritDotParams continuous_scale -aesthetics -trans -palette -breaks -minor_breaks -labels -guide
+#'
+#' @export
+#' @keywords internal
 datetime_scale <- function(aesthetics, trans, palette,
                            breaks = pretty_breaks(), minor_breaks = waiver(),
                            labels = waiver(), date_breaks = waiver(),

R/scale-date.r

@@ -91,5 +91,11 @@ scale_type.Date <- function(x) c("date", "continuous")
 #' @export
 scale_type.numeric <- function(x) "continuous"
 
+#' @export
+scale_type.integer <- function(x) "continuous"
+
+#' @export
+scale_type.double <- function(x) "continuous"
+
 #' @export
 scale_type.hms <- function(x) "time"