bidirection: Utilities for working with bidirectional layers
In ggplot2: Create Elegant Data Visualisations Using the Grammar of Graphics

bidirection

R Documentation

Utilities for working with bidirectional layers

Description

These functions are what underpins the ability of certain geoms to work automatically in both directions. See the Extending ggplot2 vignette for how they are used when implementing Geom, Stat, and Position classes.

Usage

has_flipped_aes(
  data,
  params = list(),
  main_is_orthogonal = NA,
  range_is_orthogonal = NA,
  group_has_equal = FALSE,
  ambiguous = FALSE,
  main_is_continuous = FALSE,
  main_is_optional = FALSE
)

flip_data(data, flip = NULL)

flipped_names(flip = FALSE)

Arguments

`data`	The layer data
`params`	The parameters of the `Stat`/`Geom`. Only the `orientation` parameter will be used.
`main_is_orthogonal`	If only `x` or `y` are present do they correspond to the main orientation or the reverse. E.g. If `TRUE` and `y` is present it is not flipped. If `NA` this check will be ignored.
`range_is_orthogonal`	If `xmin`/`xmax` or `ymin`/`ymax` is present do they correspond to the main orientation or reverse. If `NA` this check will be ignored.
`group_has_equal`	Is it expected that grouped data has either a single `x` or `y` value that will correspond to the orientation.
`ambiguous`	Is the layer ambiguous in its mapping by nature. If so, it will only be flipped if `params$orientation == "y"`
`main_is_continuous`	If there is a discrete and continuous axis, does the continuous one correspond to the main orientation?
`main_is_optional`	Is the main axis aesthetic optional and, if not given, set to `0`
`flip`	Logical. Is the layer flipped.

Details

has_flipped_aes() is used to sniff out the orientation of the layer from the data. It has a range of arguments that can be used to finetune the sniffing based on what the data should look like. flip_data() will switch the column names of the data so that it looks like x-oriented data. flipped_names() provides a named list of aesthetic names that corresponds to the orientation of the layer.

Value

has_flipped_aes() returns TRUE if it detects a layer in the other orientation and FALSE otherwise. flip_data() will return the input unchanged if flip = FALSE and the data with flipped aesthetic names if flip = TRUE. flipped_names() returns a named list of strings. If flip = FALSE the name of the element will correspond to the element, e.g. flipped_names(FALSE)$x == "x" and if flip = TRUE it will correspond to the flipped name, e.g. flipped_names(FALSE)$x == "y"

Controlling the sniffing

How the layer data should be interpreted depends on its specific features. has_flipped_aes() contains a range of flags for defining what certain features in the data correspond to:

main_is_orthogonal: This argument controls how the existence of only a x or y aesthetic is understood. If TRUE then the existing aesthetic would be then secondary axis. This behaviour is present in stat_ydensity() and stat_boxplot(). If FALSE then the existing aesthetic is the main axis as seen in e.g. stat_bin(), geom_count(), and stat_density().
range_is_orthogonal: This argument controls whether the existence of range-like aesthetics (e.g. xmin and xmax) represents the main or secondary axis. If TRUE then the range is given for the secondary axis as seen in e.g. geom_ribbon() and geom_linerange().
group_has_equal: This argument controls whether to test for equality of all x and y values inside each group and set the main axis to the one where all is equal. This test is only performed if TRUE, and only after less computationally heavy tests has come up empty handed. Examples are stat_boxplot() and stat_ydensity
ambiguous: This argument tells the function that the layer, while bidirectional, doesn't treat each axis differently. It will circumvent any data based guessing and only take hint from the orientation element in params. If this is not present it will fall back to FALSE. Examples are geom_line() and geom_area()
main_is_continuous: This argument controls how the test for discreteness in the scales should be interpreted. If TRUE then the main axis will be the one which is not discrete-like. Conversely, if FALSE the main axis will be the discrete-like one. Examples of TRUE is stat_density() and stat_bin(), while examples of FALSE is stat_ydensity() and stat_boxplot()
main_is_optional: This argument controls the rare case of layers were the main direction is an optional aesthetic. This is only seen in stat_boxplot() where x is set to 0 if not given. If TRUE there will be a check for whether all x or all y are equal to 0