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.
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. IfNULL
, the legend title will be omitted.- breaks
One of:
NULL
for no breakswaiver()
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 labelswaiver()
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 thenormalize
parameter togeom_slabinterval()
)? The default isFALSE
: ifscale_thickness_shared()
is in use, the geom-specificnormalize
parameter is ignored (this is achieved by flagging values as already normalized by wrapping them inthickness()
). Set this toTRUE
to allow geoms to also apply their own normalization. Note that if you set renormalize toTRUE
, subguides created via thesubguide
parameter togeom_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 withNA
.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::pal_area()
).minor_breaks
One of:
NULL
for no minor breakswaiver()
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()
. UseNULL
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()
). Therescaler
is ignored by position scales, which always usescales::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 theexpand
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.
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 withscales::new_transform()
.trans
position
For position scales, The position of the axis.
left
orright
for y axes,top
orbottom
for x axes.call
The
call
used to construct the scale for reporting messages.super
The super class to use for the constructed scale
- x
An object (typically a
numeric()
) to be converted to athickness()
object.- lower
The original lower bounds of thickness values before scaling.
- upper
The original upper bounds of thickness values before scaling.
Value
A ggplot2::Scale representing a scale for the thickness
aesthetic for ggdist
geoms. Can be added to a ggplot()
object.
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
).
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()
.
See also
The thickness
aesthetic of geom_slabinterval()
.
Other ggdist scales:
scale_colour_ramp
,
scale_side_mirrored()
,
sub-geometry-scales
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()