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).

- 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 objectA 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()`

). Also accepts rlang lambda function notation.

- labels
One of:

`NULL`

for no labels`waiver()`

for the default labels computed by the transformation objectA 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 rangeA numeric vector of length two providing limits of the scale. Use

`NA`

to refer to the existing minimum or maximumA 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
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.- 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.- ...
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::area_pal()`

).`minor_breaks`

One of:

`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.`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.`na.value`

Missing values will be replaced with this value.

`trans`

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

`<name>_trans`

(e.g.,`scales::boxcox_trans()`

). You can create your own transformation with`scales::trans_new()`

.`position`

For position scales, The position of the axis.

`left`

or`right`

for y axes,`top`

or`bottom`

for x axes.`super`

The super class to use for the constructed scale

- x
An object (typically a

`numeric()`

) to be converted to a`thickness()`

object.

A ggplot2::Scale representing a scale for the `thickness`

aesthetic for `ggdist`

geoms. Can be added to a `ggplot()`

object.

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`

).

`thickness()`

is used by `scale_thickness_shared()`

to create `numeric()`

-like
objects marked as being in units of slab "thickness". Unlike regular `numeric()`

s,
`thickness()`

values mapped onto the `thickness`

aesthetic are not rescaled by
`scale_thickness_shared()`

or `geom_slabinterval()`

. In most cases `thickness()`

is not useful directly; though it can be used to mark values that should not be
rescaled---see the definitions of `stat_ccdfinterval()`

and `stat_gradientinterval()`

for some usages.

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()`

.

The `thickness`

aesthetic of `geom_slabinterval()`

.

Other ggdist scales:
`scale_colour_ramp`

,
`scale_side_mirrored()`

,
`scales`

```
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()
```