Add more parens

R/aes.r

@@ -214,7 +214,7 @@ is_position_aes <- function(vars) {
 #'
 #' Aesthetic mappings describe how variables in the data are mapped to visual
 #' properties (aesthetics) of geoms. [aes()] uses non-standard
-#' evaluation to capture the variable names. `aes_` and `aes_string`
+#' evaluation to capture the variable names. `aes_()` and `aes_string()`
 #' require you to explicitly quote the inputs either with `""` for
 #' `aes_string()`, or with `quote` or `~` for `aes_()`.
 #' (`aes_q()` is an alias to `aes_()`). This makes `aes_()` and

R/annotation-custom.r

@@ -17,7 +17,7 @@ NULL
 #' @param ymin,ymax y location (in data coordinates) giving vertical
 #'   location of raster
 #' @export
-#' @note `annotation_custom` expects the grob to fill the entire viewport
+#' @note `annotation_custom()` expects the grob to fill the entire viewport
 #' defined by xmin, xmax, ymin, ymax. Grobs with a different (absolute) size
 #' will be center-justified in that region.
 #' Inf values can be used to fill the full plot panel (see examples).

R/annotation-logticks.r

@@ -18,7 +18,7 @@
 #'   long tick marks. In base 10, these are the "1" (or "10") ticks.
 #' @param scaled is the data already log-scaled? This should be `TRUE`
 #'   (default) when the data is already transformed with `log10()` or when
-#'   using `scale_y_log10`. It should be `FALSE` when using
+#'   using `scale_y_log10()`. It should be `FALSE` when using
 #'   `coord_trans(y = "log10")`.
 #' @param colour Colour of the tick marks.
 #' @param size Thickness of tick marks, in mm.

R/coord-.r

@@ -1,6 +1,6 @@
 #' @section Coordinate systems:
 #'
-#' All `coord_*` functions (like `coord_trans`) return a `Coord*`
+#' All `coord_*()` functions (like `coord_trans()`) return a `Coord*`
 #' object (like `CoordTrans`).
 #'
 #' Each of the `Coord*` objects is a [ggproto()] object,

R/coord-map.r

@@ -3,7 +3,7 @@
 #' `coord_map()` projects a portion of the earth, which is approximately
 #' spherical, onto a flat 2D plane using any projection defined by the
 #' `mapproj` package. Map projections do not, in general, preserve straight
-#' lines, so this requires considerable computation. `coord_quickmap` is a
+#' lines, so this requires considerable computation. `coord_quickmap()` is a
 #' quick approximation that does preserve straight lines. It works best for
 #' smaller areas closer to the equator.
 #'

R/facet-.r

@@ -31,7 +31,7 @@ NULL
 #'   turn and is expected to supply a `PANEL` column mapping each row to a
 #'   panel defined in the layout. Additionally this method can also add or
 #'   subtract data points as needed e.g. in the case of adding margins to
-#'   `facet_grid`.
+#'   `facet_grid()`.
 #'
 #'   - `draw_panels`: This is where the panels are assembled into a
 #'   `gtable` object. The method receives, among others, a list of grobs
@@ -494,8 +494,8 @@ max_width <- function(grobs, value_only = FALSE) {
 #' Find panels in a gtable
 #'
 #' These functions help detect the placement of panels in a gtable, if they are
-#' named with "panel" in the beginning. `find_panel` returns the extend of
-#' the panel area, while `panel_cols` and `panel_rows` returns the
+#' named with "panel" in the beginning. `find_panel()` returns the extend of
+#' the panel area, while `panel_cols()` and `panel_rows()` returns the
 #' columns and rows that contains panels respectively.
 #'
 #' @param table A gtable

R/facet-wrap.r

@@ -393,7 +393,7 @@ FacetWrap <- ggproto("FacetWrap", Facet,
 #'
 #' Cleans up the input to be an integer greater than or equal to one, or
 #' `NULL`. Intended to be used on the `nrow` and `ncol`
-#' arguments of `facet_wrap`.
+#' arguments of `facet_wrap()`.
 #' @param n Hopefully an integer greater than or equal to one, or `NULL`,
 #' though other inputs are handled.
 #' @return An integer greater than or equal to one, or `NULL`.

R/fortify.r

@@ -1,7 +1,7 @@
 #' Fortify a model with data.
 #'
 #' Rather than using this function, I now recommend using the \pkg{broom}
-#' package, which implements a much wider range of methods. `fortify`
+#' package, which implements a much wider range of methods. `fortify()`
 #' may be deprecated in the future.
 #'
 #' @seealso [fortify.lm()]

R/geom-.r

@@ -3,7 +3,7 @@ NULL
 
 #' @section Geoms:
 #'
-#' All `geom_*` functions (like `geom_point`) return a layer that
+#' All `geom_*()` functions (like `geom_point()`) return a layer that
 #' contains a `Geom*` object (like `GeomPoint`). The `Geom*`
 #' object is responsible for rendering the data in the plot.
 #'

R/geom-bin2d.r

@@ -11,7 +11,7 @@
 #' @inheritParams layer
 #' @inheritParams geom_point
 #' @param geom,stat Use to override the default connection between
-#'   `geom_bin2d` and `stat_bin2d`.
+#'   `geom_bin2d()` and `stat_bin2d()`.
 #' @seealso [stat_binhex()] for hexagonal binning
 #' @examples
 #' d <- ggplot(diamonds, aes(x, y)) + xlim(4, 10) + ylim(4, 10)

R/geom-boxplot.r

@@ -32,7 +32,7 @@
 #' @inheritParams layer
 #' @inheritParams geom_bar
 #' @param geom,stat Use to override the default connection between
-#'   `geom_boxplot` and `stat_boxplot`.
+#'   `geom_boxplot()` and `stat_boxplot()`.
 #' @param outlier.colour,outlier.color,outlier.fill,outlier.shape,outlier.size,outlier.stroke,outlier.alpha
 #'   Default aesthetics for outliers. Set to `NULL` to inherit from the
 #'   aesthetics used for the box.

R/geom-count.r

@@ -6,7 +6,7 @@
 #'
 #' @eval rd_aesthetics("geom", "point")
 #' @param geom,stat Use to override the default connection between
-#'   `geom_count` and `stat_sum`.
+#'   `geom_count()` and `stat_sum()`.
 #' @seealso For continuous `x` and `y`, use [geom_bin2d()].
 #' @inheritParams layer
 #' @inheritParams geom_point

R/geom-density.r

@@ -14,7 +14,7 @@
 #' @inheritParams geom_bar
 #' @inheritParams geom_ribbon
 #' @param geom,stat Use to override the default connection between
-#'   `geom_density` and `stat_density`.
+#'   `geom_density()` and `stat_density()`.
 #' @export
 #' @examples
 #' ggplot(diamonds, aes(carat)) +

R/geom-density2d.r

@@ -12,7 +12,7 @@
 #'  how contours are drawn; [geom_bin2d()] for another way of dealing with
 #'  overplotting.
 #' @param geom,stat Use to override the default connection between
-#'   `geom_density_2d` and `stat_density_2d`.
+#'   `geom_density_2d()` and `stat_density_2d()`.
 #' @inheritParams layer
 #' @inheritParams geom_point
 #' @inheritParams geom_path

R/geom-hex.r

@@ -7,8 +7,8 @@
 #'
 #' @eval rd_aesthetics("geom", "hex")
 #' @seealso [stat_bin2d()] for rectangular binning
-#' @param geom,stat Override the default connection between `geom_hex` and
-#'   `stat_binhex.`
+#' @param geom,stat Override the default connection between `geom_hex()` and
+#'   `stat_binhex()`.
 #' @export
 #' @inheritParams layer
 #' @inheritParams geom_point

R/geom-histogram.r

@@ -17,7 +17,7 @@
 #' one change at a time. You may need to look at a few options to uncover
 #' the full story behind your data.
 #'
-#' In addition to `geom_histogram`, you can create a histogram plot by using
+#' In addition to `geom_histogram()`, you can create a histogram plot by using
 #' `scale_x_binned()` with [geom_bar()]. This method by default plots tick marks
 #' in between each bar.
 #'
@@ -43,8 +43,8 @@
 #' ggplot(diamonds, aes(y = carat)) +
 #'   geom_histogram()
 #'
-#' # For histograms with tick marks between each bin, use `geom_bar` with
-#' # `scale_x_binned`.
+#' # For histograms with tick marks between each bin, use `geom_bar()` with
+#' # `scale_x_binned()`.
 #' ggplot(diamonds, aes(carat)) +
 #'   geom_bar() +
 #'   scale_x_binned()

R/geom-path.r

@@ -22,7 +22,7 @@
 #'  [geom_polygon()]: Filled paths (polygons);
 #'  [geom_segment()]: Line segments
 #' @section Missing value handling:
-#' `geom_path()`, `geom_line()`, and `geom_step` handle `NA` as follows:
+#' `geom_path()`, `geom_line()`, and `geom_step()` handle `NA` as follows:
 #'
 #' * If an `NA` occurs in the middle of a line, it breaks the line. No warning
 #'   is shown, regardless of whether `na.rm` is `TRUE` or `FALSE`.

R/geom-quantile.r

@@ -11,7 +11,7 @@
 #' @param method.args List of additional arguments passed on to the modelling
 #'   function defined by `method`.
 #' @param geom,stat Use to override the default connection between
-#'   `geom_quantile` and `stat_quantile`.
+#'   `geom_quantile()` and `stat_quantile()`.
 #' @examples
 #' m <- ggplot(mpg, aes(displ, 1 / hwy)) + geom_point()
 #' m + geom_quantile()

R/geom-segment.r

@@ -1,11 +1,11 @@
 #' Line segments and curves
 #'
 #' `geom_segment()` draws a straight line between points (x, y) and
-#' (xend, yend). `geom_curve` draws a curved line. See the underlying
+#' (xend, yend). `geom_curve()` draws a curved line. See the underlying
 #' drawing function [grid::curveGrob()] for the parameters that
 #' control the curve.
 #'
-#' Both geoms draw a single segment/curve per case. See `geom_path` if you
+#' Both geoms draw a single segment/curve per case. See `geom_path()` if you
 #' need to connect points across multiple cases.
 #'
 #' @eval rd_aesthetics("geom", "segment")

R/geom-tile.r

@@ -4,7 +4,7 @@
 #' parameterised differently: `geom_rect()` uses the locations of the four
 #' corners (`xmin`, `xmax`, `ymin` and `ymax`), while
 #' `geom_tile()` uses the center of the tile and its size (`x`,
-#' `y`, `width`, `height`). `geom_raster` is a high
+#' `y`, `width`, `height`). `geom_raster()` is a high
 #' performance special case for when all the tiles are the same size.
 #'
 #' @eval rd_aesthetics("geom", "tile")

R/geom-violin.r

@@ -15,7 +15,7 @@
 #' @param trim If `TRUE` (default), trim the tails of the violins
 #'   to the range of the data. If `FALSE`, don't trim the tails.
 #' @param geom,stat Use to override the default connection between
-#'   `geom_violin` and `stat_ydensity`.
+#'   `geom_violin()` and `stat_ydensity()`.
 #' @export
 #' @references Hintze, J. L., Nelson, R. D. (1998) Violin Plots: A Box
 #' Plot-Density Trace Synergism. The American Statistician 52, 181-184.

R/ggproto.r

@@ -1,7 +1,7 @@
 #' Create a new ggproto object
 #'
-#' Construct a new object with `ggproto`, test with `is.proto`,
-#' and access parent methods/fields with `ggproto_parent`.
+#' Construct a new object with `ggproto()`, test with `is.ggproto()`,
+#' and access parent methods/fields with `ggproto_parent()`.
 #'
 #' ggproto implements a protype based OO system which blurs the lines between
 #' classes and instances. It is inspired by the proto package, but it has some

R/plot.r

@@ -7,7 +7,7 @@
 #'
 #' `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`:
+#' plot. There are three common ways to invoke `ggplot()`:
 #'
 #' * `ggplot(df, aes(x, y, other aesthetics))`
 #' * `ggplot(df)`

R/position-.r

@@ -1,6 +1,6 @@
 #' @section Positions:
 #'
-#' All `position_*` functions (like `position_dodge`) return a
+#' All `position_*()` functions (like `position_dodge()`) return a
 #' `Position*` object (like `PositionDodge`). The `Position*`
 #' object is responsible for adjusting the position of overlapping geoms.
 #'

R/quick-plot.r

@@ -13,7 +13,7 @@
 #' @param facets faceting formula to use. Picks [facet_wrap()] or
 #'   [facet_grid()] depending on whether the formula is one-
 #'   or two-sided
-#' @param margins See `facet_grid`: display marginal facets?
+#' @param margins See `facet_grid()`: display marginal facets?
 #' @param geom Character vector specifying geom(s) to draw. Defaults to
 #'  "point" if x and y are specified, and "histogram" if only x is specified.
 #' @param stat,position DEPRECATED.

R/save.r

@@ -35,7 +35,7 @@
 #'   If not supplied, uses the size of current graphics device.
 #' @param dpi Plot resolution. Also accepts a string input: "retina" (320),
 #'   "print" (300), or "screen" (72). Applies only to raster output types.
-#' @param limitsize When `TRUE` (the default), `ggsave` will not
+#' @param limitsize When `TRUE` (the default), `ggsave()` will not
 #'   save images larger than 50x50 inches, to prevent the common error of
 #'   specifying dimensions in pixels.
 #' @param ... Other arguments passed on to the graphics device function,

R/scale-type.R

@@ -46,7 +46,7 @@ find_global <- function(name, env, mode = "any") {
 #'
 #' @param x A vector
 #' @return A character vector of scale types. These will be tried in turn
-#'   to find a default scale. For example, if `scale_type` returns
+#'   to find a default scale. For example, if `scale_type()` returns
 #'   `c("foo", "bar")` and the vector is used with the colour aesthetic,
 #'   ggplot2 will first look for `scale_colour_foo` then
 #'   `scale_colour_bar`.

R/stat-.r

@@ -1,6 +1,6 @@
 #' @section Stats:
 #'
-#' All `stat_*` functions (like `stat_bin`) return a layer that
+#' All `stat_*()` functions (like `stat_bin()`) return a layer that
 #' contains a `Stat*` object (like `StatBin`). The `Stat*`
 #' object is responsible for rendering the data in the plot.
 #'

R/stat-count.r

@@ -4,10 +4,10 @@
 #'   \item{prop}{groupwise proportion}
 #' }
 #' @seealso [stat_bin()], which bins data in ranges and counts the
-#'   cases in each range. It differs from `stat_count`, which counts the
+#'   cases in each range. It differs from `stat_count()`, which counts the
 #'   number of cases at each `x` position (without binning into ranges).
 #'   [stat_bin()] requires continuous `x` data, whereas
-#'   `stat_count` can be used for both discrete and continuous `x` data.
+#'   `stat_count()` can be used for both discrete and continuous `x` data.
 #'
 #' @export
 #' @rdname geom_bar

R/stat-qq.r

@@ -12,12 +12,12 @@
 #' @inheritParams layer
 #' @inheritParams geom_point
 #' @section Computed variables:
-#' Variables computed by `stat_qq`:
+#' Variables computed by `stat_qq()`:
 #' \describe{
 #'   \item{sample}{sample quantiles}
 #'   \item{theoretical}{theoretical quantiles}
 #' }
-#' Variables computed by `stat_qq_line`:
+#' Variables computed by `stat_qq_line()`:
 #' \describe{
 #'   \item{x}{x-coordinates of the endpoints of the line segment connecting the
 #'            points at the chosen quantiles of the theoretical and the sample

R/theme-current.R

@@ -5,8 +5,8 @@ NULL
 #' Get, set, and modify the active theme
 #'
 #' The current/active theme (see [theme()]) is automatically applied to every
-#' plot you draw. Use `theme_get` to get the current theme, and `theme_set` to
-#' completely override it. `theme_update` and `theme_replace` are shorthands for
+#' plot you draw. Use `theme_get()` to get the current theme, and `theme_set()` to
+#' completely override it. `theme_update()` and `theme_replace()` are shorthands for
 #' changing individual elements.
 #'
 #' @section Adding on to a theme:
@@ -21,9 +21,9 @@ NULL
 #'   theme not specified in e2 will not be present in the resulting theme (i.e.
 #'   NULL). Thus this operator can be used to overwrite an entire theme.
 #'
-#'   `theme_update` uses the `+` operator, so that any unspecified values in the
+#'   `theme_update()` uses the `+` operator, so that any unspecified values in the
 #'   theme element will default to the values they are set in the theme.
-#'   `theme_replace` uses `%+replace%` to completely replace the element, so any
+#'   `theme_replace()` uses `%+replace%` to completely replace the element, so any
 #'   unspecified values will overwrite the current value in the theme with
 #'   `NULL`.
 #'
@@ -37,7 +37,7 @@ NULL
 #'
 #' @param ... named list of theme settings
 #' @param e1,e2 Theme and element to combine
-#' @return `theme_set`, `theme_update`, and `theme_replace`
+#' @return `theme_set()`, `theme_update()`, and `theme_replace()`
 #'   invisibly return the previous theme so you can easily save it, then
 #'   later restore it.
 #' @seealso [+.gg()]

R/theme-defaults.r

@@ -12,37 +12,37 @@
 #' @details
 #' \describe{
 #'
-#' \item{`theme_gray`}{
+#' \item{`theme_gray()`}{
 #' The signature ggplot2 theme with a grey background and white gridlines,
 #' designed to put the data forward yet make comparisons easy.}
 #'
-#' \item{`theme_bw`}{
+#' \item{`theme_bw()`}{
 #' The classic dark-on-light ggplot2 theme. May work better for presentations
 #' displayed with a projector.}
 #'
-#' \item{`theme_linedraw`}{
+#' \item{`theme_linedraw()`}{
 #' A theme with only black lines of various widths on white backgrounds,
-#' reminiscent of a line drawing. Serves a purpose similar to `theme_bw`.
+#' reminiscent of a line drawing. Serves a purpose similar to `theme_bw()`.
 #' Note that this theme has some very thin lines (<< 1 pt) which some journals
 #' may refuse.}
 #'
-#' \item{`theme_light`}{
-#' A theme similar to `theme_linedraw` but with light grey lines and axes,
+#' \item{`theme_light()`}{
+#' A theme similar to `theme_linedraw()` but with light grey lines and axes,
 #' to direct more attention towards the data.}
 #'
-#' \item{`theme_dark`}{
-#' The dark cousin of `theme_light`, with similar line sizes but a dark background. Useful to make thin coloured lines pop out.}
+#' \item{`theme_dark()`}{
+#' The dark cousin of `theme_light()`, with similar line sizes but a dark background. Useful to make thin coloured lines pop out.}
 #'
-#' \item{`theme_minimal`}{
+#' \item{`theme_minimal()`}{
 #' A minimalistic theme with no background annotations.}
 #'
-#' \item{`theme_classic`}{
+#' \item{`theme_classic()`}{
 #' A classic-looking theme, with x and y axis lines and no gridlines.}
 #'
-#' \item{`theme_void`}{
+#' \item{`theme_void()`}{
 #' A completely empty theme.}
 #'
-#' \item{`theme_test`}{
+#' \item{`theme_test()`}{
 #' A theme for visual unit tests. It should ideally never change except
 #' for new features.}
 #'