Shortcut version of geom_slabinterval() for creating slab (ridge) plots.
Roughly equivalent to:
geom_slabinterval(
show_point = FALSE, show_interval = FALSE
)
geom_slab(
mapping = NULL,
data = NULL,
stat = "identity",
position = "identity",
...,
orientation = NA,
normalize = "all",
fill_type = "segments",
na.rm = FALSE,
show.legend = NA,
inherit.aes = TRUE
)A ggplot2::Geom representing a slab (ridge) geometry which can
be added to a ggplot() object.
Set of aesthetic mappings created by aes() or
aes_(). If specified and inherit.aes = TRUE (the
default), it is combined with the default mapping at the top level of the
plot. You must supply mapping if there is no plot mapping.
The data to be displayed in this layer. There are three options:
If NULL, the default, the data is inherited from the plot
data as specified in the call to ggplot().
A data.frame, or other object, will override the plot
data. All objects will be fortified to produce a data frame. See
fortify() for which variables will be created.
A function will be called with a single argument,
the plot data. The return value must be a data.frame, and
will be used as the layer data. A function can be created
from a formula (e.g. ~ head(.x, 10)).
The statistical transformation to use on the data for this layer, as a string.
Position adjustment, either as a string, or the result of a call to a position adjustment function.
Setting this equal to "dodge" (position_dodge()) or "dodgejust" (position_dodgejust()) can be useful if
you have overlapping geometries.
Other arguments passed to layer(). These are often aesthetics, used to set an aesthetic
to a fixed value, like colour = "red" or size = 3 (see Aesthetics, below). They may also be
parameters to the paired geom/stat.
Whether this geom is drawn horizontally or vertically. One of:
NA (default): automatically detect the orientation based on how the aesthetics
are assigned. Automatic detection works most of the time.
"horizontal" (or "y"): draw horizontally, using the y aesthetic to identify different
groups. For each group, uses the x, xmin, xmax, and thickness aesthetics to
draw points, intervals, and slabs.
"vertical" (or "x"): draw vertically, using the x aesthetic to identify different
groups. For each group, uses the y, ymin, ymax, and thickness aesthetics to
draw points, intervals, and slabs.
For compatibility with the base ggplot naming scheme for orientation, "x" can be used as an alias
for "vertical" and "y" as an alias for "horizontal" (tidybayes had an orientation parameter
before base ggplot did, hence the discrepancy).
How to normalize heights of functions input to the thickness aesthetic. One of:
"all": normalize so that the maximum height across all data is 1.
"panels": normalize within panels so that the maximum height in each panel is 1.
"xy": normalize within the x/y axis opposite the orientation of this geom so
that the maximum height at each value of the opposite axis is 1.
"groups": normalize within values of the opposite axis and within each
group so that the maximum height in each group is 1.
"none": values are taken as is with no normalization (this should probably
only be used with functions whose values are in [0,1], such as CDFs).
What type of fill to use when the fill color or alpha varies within a slab. One of:
"segments": breaks up the slab geometry into segments for each unique combination of fill color and
alpha value. This approach is supported by all graphics devices and works well for sharp cutoff values,
but can give ugly results if a large number of unique fill colors are being used (as in gradients,
like in stat_gradientinterval()).
"gradient": a grid::linearGradient() is used to create a smooth gradient fill. This works well for
large numbers of unique fill colors, but requires R >= 4.1 and is not yet supported on all graphics devices.
As of this writing, the png() graphics device with type = "cairo", the svg() device, the pdf()
device, and the ragg::agg_png() devices are known to support this option. On R < 4.1, this option
will fall back to fill_type = "segment" with a message.
"auto": attempts to use fill_type = "gradient" if support for it can be auto-detected. On R >= 4.2,
support for gradients can be auto-detected on some graphics devices; if support is not detected, this
option will fall back to fill_type = "segments" (in case of a false negative, fill_type = "gradient"
can be set explicitly). On R < 4.2, support for gradients cannot be auto-detected, so this will always
fall back to fill_type = "segments", in which case you can set fill_type = "gradient" explicitly
if you are using a graphics device that support gradients.
If FALSE, the default, missing values are removed with a warning. If TRUE, missing
values are silently removed.
logical. Should this layer be included in the legends?
NA, the default, includes if any aesthetics are mapped.
FALSE never includes, and TRUE always includes.
It can also be a named logical vector to finely select the aesthetics to
display.
If FALSE, overrides the default aesthetics,
rather than combining with them. This is most useful for helper functions
that define both data and aesthetics and shouldn't inherit behaviour from
the default plot specification, e.g. borders().
The slab+interval stats and geoms have a wide variety of aesthetics that control
the appearance of their three sub-geometries: the slab, the point, and
the interval.
Positional aesthetics
x: x position of the geometry
y: y position of the geometry
Slab-specific aesthetics
thickness: The thickness of the slab at each x value (if orientation = "horizontal") or
y value (if orientation = "vertical") of the slab.
side: Which side to place the slab on. "topright", "top", and "right" are synonyms
which cause the slab to be drawn on the top or the right depending on if orientation is "horizontal"
or "vertical". "bottomleft", "bottom", and "left" are synonyms which cause the slab
to be drawn on the bottom or the left depending on if orientation is "horizontal" or
"vertical". "topleft" causes the slab to be drawn on the top or the left, and "bottomright"
causes the slab to be drawn on the bottom or the right. "both" draws the slab mirrored on both
sides (as in a violin plot).
scale: What proportion of the region allocated to this geom to use to draw the slab. If scale = 1,
slabs that use the maximum range will just touch each other. Default is 0.9 to leave some space.
justification: Justification of the interval relative to the slab, where 0 indicates bottom/left
justification and 1 indicates top/right justification (depending on orientation). If justification
is NULL (the default), then it is set automatically based on the value of side: when side is
"top"/"right" justification is set to 0, when side is "bottom"/"left"
justification is set to 1, and when side is "both" justification is set to 0.5.
datatype: When using composite geoms directly without a stat (e.g. geom_slabinterval()), datatype is used to
indicate which part of the geom a row in the data targets: rows with datatype = "slab" target the
slab portion of the geometry and rows with datatype = "interval" target the interval portion of
the geometry. This is set automatically when using ggdist stats.
Color aesthetics
colour: (or color) The color of the interval and point sub-geometries.
Use the slab_color, interval_color, or point_color aesthetics (below) to
set sub-geometry colors separately.
fill: The fill color of the slab and point sub-geometries. Use the slab_fill
or point_fill aesthetics (below) to set sub-geometry colors separately.
alpha: The opacity of the slab, interval, and point sub-geometries. Use the slab_alpha,
interval_alpha, or point_alpha aesthetics (below) to set sub-geometry colors separately.
colour_ramp: (or color_ramp) A secondary scale that modifies the color
scale to "ramp" to another color. See scale_colour_ramp() for examples.
fill_ramp: A secondary scale that modifies the fill
scale to "ramp" to another color. See scale_fill_ramp() for examples.
Line aesthetics
size: Width of the outline around the slab (if visible). Also determines the width of
the line used to draw the interval and the size of the point, but raw
size values are transformed according to the interval_size_domain, interval_size_range,
and fatten_point parameters of the geom (see above). Use the slab_size,
interval_size, or point_size aesthetics (below) to set sub-geometry line widths separately
(note that when size is set directly using the override aesthetics, interval and point
sizes are not affected by interval_size_domain, interval_size_range, and fatten_point).
stroke: Width of the outline around the point sub-geometry.
linetype: Type of line (e.g., "solid", "dashed", etc) used to draw the interval
and the outline of the slab (if it is visible). Use the slab_linetype or
interval_linetype aesthetics (below) to set sub-geometry line types separately.
Slab-specific color/line override aesthetics
slab_fill: Override for fill: the fill color of the slab.
slab_colour: (or slab_color) Override for colour/color: the outline color of the slab.
slab_alpha: Override for alpha: the opacity of the slab.
slab_size: Override for size: the width of the outline of the slab.
slab_linetype: Override for linetype: the line type of the outline of the slab.
Other aesthetics (these work as in standard geoms)
width
height
group
See examples of some of these aesthetics in action in vignette("slabinterval").
Learn more about the sub-geom override aesthetics (like interval_color) in the
scales documentation. Learn more about basic ggplot aesthetics in
vignette("ggplot2-specs").
See stat_slab() for the stat version, intended for
use on sample data or analytical distributions.
See geom_slabinterval() for the geometry this shortcut is based on.
Other slabinterval geoms:
geom_interval(),
geom_pointinterval()
library(dplyr)
library(ggplot2)
theme_set(theme_ggdist())
# we will manually demonstrate plotting a density with geom_slab(),
# though generally speaking this is easier to do using stat_slab(), which
# will determine sensible limits automatically and correctly adjust
# densities when using scale transformations
df = expand.grid(
mean = 1:3,
input = seq(-2, 6, length.out = 100)
) %>%
mutate(
group = letters[4 - mean],
density = dnorm(input, mean, 1)
)
# orientation is detected automatically based on
# use of x or y
df %>%
ggplot(aes(y = group, x = input, thickness = density)) +
geom_slab()
df %>%
ggplot(aes(x = group, y = input, thickness = density)) +
geom_slab()
# RIDGE PLOTS
# "ridge" plots can be created by increasing the slab height and
# setting the slab color
df %>%
ggplot(aes(y = group, x = input, thickness = density)) +
geom_slab(height = 2, color = "black")
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