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Position scales for continuous distributions

Source: R/scale-continuous-distribution.R
scale_continuous_distribution.Rd

These scales allow for distributions to be passed to the x and y position by mapping distribution objects to continuous aesthetics. These scale can be used similarly to the scale_*_continuous functions, but they do not accept transformations. If you want to transform your scale, you should apply a transformation through the coord_* functions, as they are applied after the stat, so the existing ggplot infastructure can be used. For example, if you would like a log transformation of the x axis, plot + coord_transform(x = "log") would work fine.

Usage

scale_x_continuous_distribution(
  name = waiver(),
  breaks = waiver(),
  labels = waiver(),
  limits = NULL,
  expand = waiver(),
  oob = oob_keep,
  guide = waiver(),
  position = "bottom",
  sec.axis = waiver(),
  ...
)

scale_y_continuous_distribution(
  name = waiver(),
  breaks = waiver(),
  labels = waiver(),
  limits = NULL,
  expand = waiver(),
  oob = scales::oob_keep,
  guide = waiver(),
  position = "left",
  sec.axis = waiver(),
  ...
)

Arguments

name

The name of the scale. Used as the axis or legend title. If waiver(), the default, the name of the scale is taken from the first mapping used for that aesthetic. If NULL, the legend title will be omitted.

breaks

One of:

  • NULL for no breaks

  • waiver() for the default breaks computed by the transformation object

  • A numeric vector of positions

  • A function that takes the limits as input and returns breaks as output (e.g., a function returned by scales::extended_breaks()). Note that for position scales, limits are provided after scale expansion. Also accepts rlang lambda function notation.

labels

One of the options below. Please note that when labels is a vector, it is highly recommended to also set the breaks argument as a vector to protect against unintended mismatches.

  • NULL for no labels

  • waiver() for the default labels computed by the transformation object

  • A character vector giving labels (must be same length as breaks)

  • An expression vector (must be the same length as breaks). See ?plotmath for details.

  • A function that takes the breaks as input and returns labels as output. Also accepts rlang lambda function notation.

limits

One of:

  • NULL to use the default scale range

  • A numeric vector of length two providing limits of the scale. Use NA to refer to the existing minimum or maximum

  • A function that accepts the existing (automatic) limits and returns new limits. Also accepts rlang lambda function notation. Note that setting limits on positional scales will remove data outside of the limits. If the purpose is to zoom, use the limit argument in the coordinate system (see coord_cartesian()).

expand

For position scales, a vector of range expansion constants used to add some padding around the data to ensure that they are placed some distance away from the axes. Use the convenience function expansion() to generate the values for the expand argument. The defaults are to expand the scale by 5% on each side for continuous variables, and by 0.6 units on each side for discrete variables.

oob

One of:

  • Function that handles limits outside of the scale limits (out of bounds). Also accepts rlang lambda function notation.

  • The default (scales::censor()) replaces out of bounds values with NA.

  • scales::squish() for squishing out of bounds values into range.

  • scales::squish_infinite() for squishing infinite values into range.

guide

A function used to create a guide or its name. See guides() for more information.

position

For position scales, The position of the axis. left or right for y axes, top or bottom for x axes.

sec.axis

sec_axis() is used to specify a secondary axis.

...

Other arguments passed on to scale_(x|y)_continuous()

Examples

library(ggplot2)
library(distributional)
set.seed(1997)
point_data <- data.frame(xvar = c(dist_uniform(2,3),
                                  dist_normal(3,2),
                                  dist_exponential(3)),
                         yvar = c(dist_gamma(2,1), 
                                  dist_sample(x = list(rnorm(100, 5, 1))), 
                                  dist_exponential(1)))
ggplot(data = point_data) + 
  geom_point_sample(aes(x=xvar, y=yvar)) +
  scale_x_continuous_distribution(name="Hello, I am a random variable", limits = c(-5, 10)) +
  scale_y_continuous_distribution(name="I am also a random variable")