Add parentheses (#4059)

R/aes.r

@@ -217,10 +217,10 @@ is_position_aes <- function(vars) {
 #' 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
-#' `aes_string` easy to program with.
+#' (`aes_q()` is an alias to `aes_()`). This makes `aes_()` and
+#' `aes_string()` easy to program with.
 #'
-#' `aes_string` and `aes_` are particularly useful when writing
+#' `aes_string()` and `aes_()` are particularly useful when writing
 #' functions that create plots because you can use strings or quoted
 #' names/calls to define the aesthetic mappings, rather than having to use
 #' [substitute()] to generate a call to `aes()`.

R/autolayer.r

@@ -1,6 +1,6 @@
 #' Create a ggplot layer appropriate to a particular data type
 #'
-#' `autolayer` uses ggplot2 to draw a particular layer for an object of a
+#' `autolayer()` uses ggplot2 to draw a particular layer for an object of a
 #' particular class in a single command. This defines the S3 generic that
 #' other classes and packages can extend.
 #'

R/autoplot.r

@@ -1,6 +1,6 @@
 #' Create a complete ggplot appropriate to a particular data type
 #'
-#' `autoplot` uses ggplot2 to draw a particular plot for an object of a
+#' `autoplot()` uses ggplot2 to draw a particular plot for an object of a
 #' particular class in a single command. This defines the S3 generic that
 #' other classes and packages can extend.
 #'

R/axis-secondary.R

@@ -24,12 +24,12 @@
 #' the axis on the plot. Usually this is [guide_axis()].
 #'
 #' @details
-#' `sec_axis` is used to create the specifications for a secondary axis.
+#' `sec_axis()` is used to create the specifications for a secondary axis.
 #' Except for the `trans` argument any of the arguments can be set to
 #' `derive()` which would result in the secondary axis inheriting the
 #' settings from the primary axis.
 #'
-#' `dup_axis` is provide as a shorthand for creating a secondary axis that
+#' `dup_axis()` is provide as a shorthand for creating a secondary axis that
 #' is a duplication of the primary axis, effectively mirroring the primary axis.
 #'
 #' As of v3.1, date and datetime scales have limited secondary axis capabilities.

R/coord-map.r

@@ -1,6 +1,6 @@
 #' Map projections
 #'
-#' `coord_map` projects a portion of the earth, which is approximately
+#' `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
@@ -15,7 +15,7 @@
 #' 0. For regions that span only a few degrees and are not too close to the
 #' poles, setting the aspect ratio of the plot to the appropriate lat/lon ratio
 #' approximates the usual mercator projection. This is what
-#' `coord_quickmap` does, and is much faster (particularly for complex
+#' `coord_quickmap()` does, and is much faster (particularly for complex
 #' plots like [geom_tile()]) at the expense of correctness.
 #'
 #' @param projection projection to use, see

R/coord-transform.r

@@ -1,6 +1,6 @@
 #' Transformed Cartesian coordinate system
 #'
-#' `coord_trans` is different to scale transformations in that it occurs after
+#' `coord_trans()` is different to scale transformations in that it occurs after
 #' statistical transformation and will affect the visual appearance of geoms - there is
 #' no guarantee that straight lines will continue to be straight.
 #'

R/facet-wrap.r

@@ -3,7 +3,7 @@ NULL
 
 #' Wrap a 1d ribbon of panels into 2d
 #'
-#' `facet_wrap` wraps a 1d sequence of panels into 2d. This is generally
+#' `facet_wrap()` wraps a 1d sequence of panels into 2d. This is generally
 #' a better use of screen space than [facet_grid()] because most
 #' displays are roughly rectangular.
 #'

R/geom-.r

@@ -14,7 +14,7 @@ NULL
 #' Compared to `Stat` and `Position`, `Geom` is a little
 #' different because the execution of the setup and compute functions is
 #' split up. `setup_data` runs before position adjustments, and
-#' `draw_layer` is not run until render time, much later. This
+#' `draw_layer()` is not run until render time, much later. This
 #' means there is no `setup_params` because it's hard to communicate
 #' the changes.
 #'

R/geom-ribbon.r

@@ -2,7 +2,7 @@
 #'
 #' For each x value, `geom_ribbon()` displays a y interval defined
 #' by `ymin` and `ymax`. `geom_area()` is a special case of
-#' `geom_ribbon`, where the `ymin` is fixed to 0 and `y` is used instead
+#' `geom_ribbon()`, where the `ymin` is fixed to 0 and `y` is used instead
 #' of `ymax`.
 #'
 #' An area plot is the continuous analogue of a stacked bar chart (see

R/geom-segment.r

@@ -1,6 +1,6 @@
 #' Line segments and curves
 #'
-#' `geom_segment` draws a straight line between points (x, y) and
+#' `geom_segment()` draws a straight line between points (x, y) and
 #' (xend, yend). `geom_curve` draws a curved line. See the underlying
 #' drawing function [grid::curveGrob()] for the parameters that
 #' control the curve.

R/geom-tile.r

@@ -1,9 +1,9 @@
 #' Rectangles
 #'
-#' `geom_rect` and `geom_tile` do the same thing, but are
-#' parameterised differently: `geom_rect` uses the locations of the four
+#' `geom_rect()` and `geom_tile()` do the same thing, but are
+#' 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`,
+#' `geom_tile()` uses the center of the tile and its size (`x`,
 #' `y`, `width`, `height`). `geom_raster` is a high
 #' performance special case for when all the tiles are the same size.
 #'

R/position-dodge.r

@@ -1,10 +1,10 @@
 #' Dodge overlapping objects side-to-side
 #'
 #' Dodging preserves the vertical position of an geom while adjusting the
-#' horizontal position. `position_dodge` requires the grouping variable to be
-#' be specified in the global or `geom_*` layer. Unlike `position_dodge`,
-#' `position_dodge2` works without a grouping variable in a layer.
-#' `position_dodge2` works with bars and rectangles, but is
+#' horizontal position. `position_dodge()` requires the grouping variable to be
+#' be specified in the global or `geom_*` layer. Unlike `position_dodge()`,
+#' `position_dodge2()` works without a grouping variable in a layer.
+#' `position_dodge2()` works with bars and rectangles, but is
 #' particulary useful for arranging box plots, which
 #' can have variable widths.
 #'

R/position-nudge.R

@@ -1,6 +1,6 @@
 #' Nudge points a fixed distance
 #'
-#' `position_nudge` is generally useful for adjusting the position of
+#' `position_nudge()` is generally useful for adjusting the position of
 #' items on discrete scales by a small amount. Nudging is built in to
 #' [geom_text()] because it's so useful for moving labels a small
 #' distance from what they're labelling.

R/quick-plot.r

@@ -1,6 +1,6 @@
 #' Quick plot
 #'
-#' `qplot` is a shortcut designed to be familiar if you're used to base
+#' `qplot()` is a shortcut designed to be familiar if you're used to base
 #' [plot()]. It's a convenient wrapper for creating a number of
 #' different types of plots using a consistent calling scheme. It's great
 #' for allowing you to produce plots quickly, but I highly recommend

R/scale-alpha.r

@@ -2,7 +2,7 @@
 #'
 #' Alpha-transparency scales are not tremendously useful, but can be a
 #' convenient way to visually down-weight less important observations.
-#' `scale_alpha` is an alias for `scale_alpha_continuous` since
+#' `scale_alpha()` is an alias for `scale_alpha_continuous()` since
 #' that is the most common use of alpha, and it saves a bit of typing.
 #'
 #' @param ... Other arguments passed on to [continuous_scale()], [binned_scale],

R/scale-discrete-.r

@@ -1,6 +1,6 @@
 #' Position scales for discrete data
 #'
-#' `scale_x_discrete` and `scale_y_discrete` are used to set the values for
+#' `scale_x_discrete()` and `scale_y_discrete()` are used to set the values for
 #' discrete x and y scale aesthetics. For simple manipulation of scale labels
 #' and limits, you may wish to use [labs()] and [lims()] instead.
 #'

R/scale-shape.r

@@ -1,11 +1,11 @@
 #' Scales for shapes, aka glyphs
 #'
-#' `scale_shape` maps discrete variables to six easily discernible shapes.
+#' `scale_shape()` maps discrete variables to six easily discernible shapes.
 #' If you have more than six levels, you will get a warning message, and the
 #' seventh and subsequence levels will not appear on the plot. Use
 #' [scale_shape_manual()] to supply your own values. You can not map
 #' a continuous variable to shape unless `scale_shape_binned()` is used. Still,
-#' as shape has no inherent order, this use is not advised..
+#' as shape has no inherent order, this use is not advised.
 #'
 #' @param solid Should the shapes be solid, `TRUE`, or hollow,
 #' `FALSE`?

R/scale-size.r

@@ -1,12 +1,12 @@
 #' Scales for area or radius
 #'
-#' `scale_size` scales area, `scale_radius` scales radius. The size
+#' `scale_size()` scales area, `scale_radius()` scales radius. The size
 #' aesthetic is most commonly used for points and text, and humans perceive
 #' the area of points (not their radius), so this provides for optimal
-#' perception. `scale_size_area` ensures that a value of 0 is mapped
-#' to a size of 0. `scale_size_binned` is a binned version of `scale_size` that
+#' perception. `scale_size_area()` ensures that a value of 0 is mapped
+#' to a size of 0. `scale_size_binned()` is a binned version of `scale_size()` that
 #' scales by area (but does not ensure 0 equals an area of zero). For a binned
-#' equivalent of `scale_size_area` use `scale_size_binned_area`.
+#' equivalent of `scale_size_area()` use `scale_size_binned_area()`.
 #'
 #' @name scale_size
 #' @inheritParams continuous_scale

R/stat-qq.r

@@ -1,7 +1,7 @@
 #' A quantile-quantile plot
 #'
-#' `geom_qq` and `stat_qq` produce quantile-quantile plots. `geom_qq_line` and
-#' `stat_qq_line` compute the slope and intercept of the line connecting the
+#' `geom_qq()` and `stat_qq()` produce quantile-quantile plots. `geom_qq_line()` and
+#' `stat_qq_line()` compute the slope and intercept of the line connecting the
 #' points at specified quartiles of the theoretical and sample distributions.
 #'
 #' @eval rd_aesthetics("stat", "qq")

R/stat-summary-2d.r

@@ -1,7 +1,7 @@
 #' Bin and summarise in 2d (rectangle & hexagons)
 #'
-#' `stat_summary_2d` is a 2d variation of [stat_summary()].
-#' `stat_summary_hex` is a hexagonal variation of
+#' `stat_summary_2d()` is a 2d variation of [stat_summary()].
+#' `stat_summary_hex()` is a hexagonal variation of
 #' [stat_summary_2d()]. The data are divided into bins defined
 #' by `x` and `y`, and then the values of `z` in each cell is
 #' are summarised with `fun`.

R/stat-summary.r

@@ -1,6 +1,6 @@
 #' Summarise y values at unique/binned x
 #'
-#' `stat_summary` operates on unique `x` or `y`; `stat_summary_bin`
+#' `stat_summary()` operates on unique `x` or `y`; `stat_summary_bin()`
 #' operates on binned `x` or `y`. They are more flexible versions of
 #' [stat_bin()]: instead of just counting, they can compute any
 #' aggregate.

R/utilities-break.r

@@ -1,8 +1,8 @@
 #' Discretise numeric data into categorical
 #'
-#' `cut_interval` makes `n` groups with equal range, `cut_number`
+#' `cut_interval()` makes `n` groups with equal range, `cut_number()`
 #' makes `n` groups with (approximately) equal numbers of observations;
-#' `cut_width` makes groups of width `width`.
+#' `cut_width()` makes groups of width `width`.
 #'
 #' @author Randall Prium contributed most of the implementation of
 #' `cut_width`.