scale_thickness: Slab thickness scale (ggplot2 scale)
In ggdist: Visualizations of Distributions and Uncertainty

scale_thickness

R Documentation

Slab thickness scale (ggplot2 scale)

Description

This ggplot2 scale linearly scales all thickness values of geoms that support the thickness aesthetic (such as geom_slabinterval()). It can be used to align the thickness scales across multiple geoms (by default, thickness is normalized on a per-geom level instead of as a global scale). For a comprehensive discussion and examples of slab scaling and normalization, see the thickness scale article.

Usage

scale_thickness_shared(
  name = waiver(),
  breaks = waiver(),
  labels = waiver(),
  limits = function(l) c(min(0, l[[1]]), l[[2]]),
  renormalize = FALSE,
  oob = scales::oob_keep,
  guide = "none",
  expand = c(0, 0),
  ...
)

scale_thickness_identity(..., guide = "none")

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: `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()`).
`renormalize`	<scalar logical> When mapping values to the `thickness` scale, should those values be allowed to be renormalized by geoms (e.g. via the `normalize` parameter to `geom_slabinterval()`)? The default is `FALSE`: if `scale_thickness_shared()` is in use, the geom-specific `normalize` parameter is ignored (this is achieved by flagging values as already normalized by wrapping them in `thickness()`). Set this to `TRUE` to allow geoms to also apply their own normalization. Note that if you set renormalize to `TRUE`, subguides created via the `subguide` parameter to `geom_slabinterval()` will display the scaled values output by this scale, not the original data values.
`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.
`expand`	<numeric> Vector of limit expansion constants of length 2 or 4, following the same format used by the `expand` argument of `continuous_scale()`. The default is not to expand the limits. You can use the convenience function `expansion()` to generate the expansion values; expanding the lower limit is usually not recommended (because with most `thickness` scales the lower limit is the baseline and represents `0`), so a typical usage might be something like `expand = expansion(c(0, 0.05))` to expand the top end of the scale by 5%.
`...`	Arguments passed on to `ggplot2::continuous_scale` `aesthetics` The names of the aesthetics that this scale works with. `scale_name` The name of the scale that should be used for error messages associated with this scale. `palette` A palette function that when called with a numeric vector with values between 0 and 1 returns the corresponding output values (e.g., `scales::pal_area()`). `minor_breaks` One of: `NULL` for no minor breaks `waiver()` for the default breaks (one minor break between each major break) A numeric vector of positions A function that given the limits returns a vector of minor breaks. Also accepts rlang lambda function notation. When the function has two arguments, it will be given the limits and major breaks. `n.breaks` An integer guiding the number of major breaks. The algorithm may choose a slightly different number to ensure nice break labels. Will only have an effect if `breaks = waiver()`. Use `NULL` to use the default number of breaks given by the transformation. `rescaler` A function used to scale the input values to the range [0, 1]. This is always `scales::rescale()`, except for diverging and n colour gradients (i.e., `scale_colour_gradient2()`, `scale_colour_gradientn()`). The `rescaler` is ignored by position scales, which always use `scales::rescale()`. Also accepts rlang lambda function notation. `na.value` Missing values will be replaced with this value. `transform` For continuous scales, the name of a transformation object or the object itself. Built-in transformations include "asn", "atanh", "boxcox", "date", "exp", "hms", "identity", "log", "log10", "log1p", "log2", "logit", "modulus", "probability", "probit", "pseudo_log", "reciprocal", "reverse", "sqrt" and "time". A transformation object bundles together a transform, its inverse, and methods for generating breaks and labels. Transformation objects are defined in the scales package, and are called `⁠transform_<name>⁠`. If transformations require arguments, you can call them from the scales package, e.g. `scales::transform_boxcox(p = 2)`. You can create your own transformation with `scales::new_transform()`. `trans` Deprecated in favour of `transform`. `position` For position scales, The position of the axis. `left` or `right` for y axes, `top` or `bottom` for x axes. `call` The `call` used to construct the scale for reporting messages. `super` The super class to use for the constructed scale

Details

By default, normalization/scaling of slab thicknesses is controlled by geometries, not by a ggplot2 scale function. This allows various functionality not otherwise possible, such as (1) allowing different geometries to have different thickness scales and (2) allowing the user to control at what level of aggregation (panels, groups, the entire plot, etc) thickness scaling is done via the normalize parameter to geom_slabinterval().

However, this default approach has one drawback: two different geoms will always have their own scaling of thickness. scale_thickness_shared() offers an alternative approach: when added to a chart, all geoms will use the same thickness scale, and geom-level normalization (via their normalize parameters) is ignored. This is achieved by "marking" thickness values as already normalized by wrapping them in the thickness() data type (this can be disabled by setting renormalize = TRUE).

Note: while a slightly more typical name for scale_thickness_shared() might be scale_thickness_continuous(), the latter name would cause this scale to be applied to all thickness aesthetics by default according to the rules ggplot2 uses to find default scales. Thus, to retain the usual behavior of stat_slabinterval() (per-geom normalization of thickness), this scale is called scale_thickness_shared().

Value

A ggplot2::Scale representing a scale for the thickness aesthetic for ggdist geoms. Can be added to a ggplot() object.

Author(s)

Matthew Kay

Examples

library(distributional)
library(ggplot2)
library(dplyr)

prior_post = data.frame(
  prior = dist_normal(0, 1),
  posterior = dist_normal(0.1, 0.5)
)

# By default, separate geoms have their own thickness scales, which means
# distributions plotted using two separate geoms will not have their slab
# functions drawn on the same scale (thus here, the two distributions have
# different areas under their density curves):
prior_post %>%
  ggplot() +
  stat_halfeye(aes(xdist = posterior)) +
  stat_slab(aes(xdist = prior), fill = NA, color = "red")

# For this kind of prior/posterior chart, it makes more sense to have the
# densities on the same scale; thus, the areas under both would be the same.
# We can do that using scale_thickness_shared():
prior_post %>%
  ggplot() +
  stat_halfeye(aes(xdist = posterior)) +
  stat_slab(aes(xdist = prior), fill = NA, color = "#e41a1c") +
  scale_thickness_shared()

ggdist documentation built on June 8, 2025, 10:59 a.m.