R/stat_dist_slabinterval.R
stat_dist_slabinterval.Rd
Stats for computing distribution functions (densities or CDFs) + intervals for use with
geom_slabinterval()
. Uses the dist
aesthetic to specify a distribution using
objects from the distributional package,
or using distribution names and arg1
, ... arg9
aesthetics (or args
as a list column)
to specify distribution arguments. See Details.
stat_dist_slabinterval( mapping = NULL, data = NULL, geom = "slabinterval", position = "identity", ..., slab_type = c("pdf", "cdf", "ccdf"), p_limits = c(NA, NA), outline_bars = FALSE, orientation = NA, limits = NULL, n = 501, .width = c(0.66, 0.95), show_slab = TRUE, show_interval = TRUE, na.rm = FALSE, show.legend = c(size = FALSE), inherit.aes = TRUE ) stat_dist_halfeye(...) stat_dist_eye( mapping = NULL, data = NULL, geom = "slabinterval", position = "identity", ..., show.legend = c(size = FALSE), inherit.aes = TRUE ) stat_dist_ccdfinterval( mapping = NULL, data = NULL, geom = "slabinterval", position = "identity", ..., slab_type = "ccdf", normalize = "none", show.legend = c(size = FALSE), inherit.aes = TRUE ) stat_dist_cdfinterval(..., slab_type = "cdf", normalize = "none") stat_dist_gradientinterval( mapping = NULL, data = NULL, geom = "slabinterval", position = "identity", ..., show.legend = c(size = FALSE, slab_alpha = FALSE), inherit.aes = TRUE ) stat_dist_pointinterval(..., show_slab = FALSE) stat_dist_interval( mapping = NULL, data = NULL, geom = "interval", position = "identity", ..., show_slab = FALSE, show_point = FALSE, show.legend = NA, inherit.aes = TRUE ) stat_dist_slab( mapping = NULL, data = NULL, geom = "slab", position = "identity", ..., show.legend = NA, inherit.aes = TRUE )
mapping  Set of aesthetic mappings created by 

data  The data to be displayed in this layer. There are three options: If A A 
geom  Use to override the default connection between

position  Position adjustment, either as a string, or the result of a call to a position adjustment function. 
...  Other arguments passed to 
slab_type  The type of slab function to calculate: probability density (or mass) function ( 
p_limits  Probability limits (as a vector of size 2) used to determine the lower and upper
limits of the slab. E.g., if this is 
outline_bars  For discrete distributions (whose slabs are drawn as histograms), determines
if outlines in between the bars are drawn when the 
orientation  Whether this geom is drawn horizontally ( 
limits  Manuallyspecified limits for the slab, as a vector of length two. These limits are combined with those
computed based on 
n  Number of points at which to evaluate 
.width  The 
show_slab  Should the slab portion of the geom be drawn? Default 
show_interval  Should the interval portion of the geom be drawn? Default 
na.rm  If 
show.legend  Should this layer be included in the legends? Default is 
inherit.aes  If 
normalize  How to normalize heights of functions input to the 
show_point  Should the point portion of the geom be drawn? Default 
A ggplot2::Stat representing a slab or combined slab+interval geometry which can
be added to a ggplot()
object.
A highly configurable stat for generating a variety of plots that combine a "slab" that describes a distribution plus an interval. Several "shortcut" stats are provided which combine multiple options to create useful geoms, particularly eye plots (a combination of a violin plot and interval), halfeye plots (a density plus interval), and CCDF bar plots (a complementary CDF plus interval).
The shortcut stat names follow the pattern stat_dist_[name]
.
Stats include:
stat_dist_eye
: Eye plots (violin + interval)
stat_dist_halfeye
: Halfeye plots (density + interval)
stat_dist_ccdfinterval
: CCDF bar plots (CCDF + interval)
stat_dist_cdfinterval
: CDF bar plots (CDF + interval)
stat_dist_gradientinterval
: Density gradient + interval plots
stat_dist_pointinterval
: Point + interval plots
stat_dist_interval
: Interval plots
These stats expect a dist
aesthetic to specify a distribution. This aesthetic
can be used in one of two ways:
dist
can be any distribution object from the distributional
package, such as dist_normal()
, dist_beta()
, etc. Since these functions are vectorized,
other columns can be passed directly to them in an aes()
specification; e.g.
aes(dist = dist_normal(mu, sigma))
will work if mu
and sigma
are columns in the
input data frame.
dist
can be a character vector giving the distribution name. Then the arg1
, ... arg9
aesthetics (or args
as a list column) specify distribution arguments. Distribution names
should correspond to R functions that have "p"
, "q"
, and "d"
functions; e.g. "norm"
is a valid distribution name because R defines the pnorm()
, qnorm()
, and dnorm()
functions for Normal distributions.
See the parse_dist()
function for a useful way to generate dist
and args
values from humanreadable distribution specs (like "normal(0,1)"
). Such specs are also
produced by other packages (like the brms::get_prior
function in brms); thus,
parse_dist()
combined with the stats described here can help you visualize the output
of those functions.
The following variables are computed by this stat and made available for
use in aesthetic specifications (aes()
) using the stat()
or after_stat()
functions:
x
or y
: For slabs, the input values to the slab function.
For intervals, the point summary from the interval function. Whether it is x
or y
depends on orientation
xmin
or ymin
: For intervals, the lower end of the interval from the interval function.
xmax
or ymax
: For intervals, the upper end of the interval from the interval function.
.width
: For intervals, the interval width as a numeric value in [0, 1]
.
level
: For intervals, the interval width as an ordered factor.
f
: For slabs, the output values from the slab function (such as the PDF, CDF, or CCDF),
determined by slab_type
.
pdf
: For slabs, the probability density function.
cdf
: For slabs, the cumulative distribution function.
The slab+interval stat
s and geom
s have a wide variety of aesthetics that control
the appearance of their three subgeometries: the slab, the point, and
the interval.
These stat
s support the following aesthetics:
x
: x position of the geometry (when orientation = "vertical"
); or sample data to be summarized
(when orientation = "horizontal"
) except for stat_dist_
geometries (which use only one of x
or y
at a time along with the dist
aesthetic).
y
: y position of the geometry (when orientation = "horizontal"
); or sample data to be summarized
(when orientation = "vertical"
) except for stat_dist_
geometries (which use only one of x
or y
at a time along with the dist
aesthetic).
dist
: A name of a distribution (e.g. "norm"
) or a distributional object (e.g. dist_normal()
).
See Details.
args
: Distribution arguments (args
or arg1
, ... arg9
). See Details.
In addition, in their default configuration (paired with geom_slabinterval()
) the following aesthetics are supported by the underlying geom:
Slabspecific 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 stat
s.
Intervalspecific aesthetics
xmin
: Left end of the interval subgeometry (if orientation = "horizontal"
).
xmax
: Right end of the interval subgeometry (if orientation = "horizontal"
).
ymin
: Lower end of the interval subgeometry (if orientation = "vertical"
).
ymax
: Upper end of the interval subgeometry (if orientation = "vertical"
).
Pointspecific aesthetics
shape
: Shape type used to draw the point subgeometry.
Color aesthetics
colour
: (or color
) The color of the interval and point subgeometries.
Use the slab_color
, interval_color
, or point_color
aesthetics (below) to
set subgeometry colors separately.
fill
: The fill color of the slab and point subgeometries. Use the slab_fill
or point_fill
aesthetics (below) to set subgeometry colors separately.
alpha
: The opacity of the slab, interval, and point subgeometries. Use the slab_alpha
,
interval_alpha
, or point_alpha
aesthetics (below) to set subgeometry 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
: (or 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 subgeometry 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 subgeometry.
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 subgeometry line types separately.
Slabspecific 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.
Intervalspecific color/line override aesthetics
interval_colour
: (or interval_color
) Override for colour
/color
: the color of the interval.
interval_alpha
: Override for alpha
: the opacity of the interval.
interval_size
: Override for size
: the line width of the interval.
interval_linetype
: Override for linetype
: the line type of the interval.
Pointspecific color/line override aesthetics
point_fill
: Override for fill
: the fill color of the point.
point_colour
: (or point_color
) Override for colour
/color
: the outline color of the point.
point_alpha
: Override for alpha
: the opacity of the point.
point_size
: Override for size
: the size of the point.
Other aesthetics (these work as in standard geom
s)
width
height
group
See examples of some of these aesthetics in action in vignette("slabinterval")
.
Learn more about the subgeom override aesthetics (like interval_color
) in the scales documentation.
Learn more about basic ggplot aesthetics in vignette("ggplot2specs")
.
See geom_slabinterval()
for more information on the geom these stats
use by default and some of the options they have. See stat_sample_slabinterval()
for the versions of these stats that can be used on samples.
See vignette("slabinterval")
for a variety of examples of use.
library(dplyr) library(ggplot2) library(distributional) theme_set(theme_ggdist()) dist_df = tribble( ~group, ~subgroup, ~mean, ~sd, "a", "h", 5, 1, "b", "h", 7, 1.5, "c", "h", 8, 1, "c", "i", 9, 1, "c", "j", 7, 1 ) dist_df %>% ggplot(aes(x = group, dist = "norm", arg1 = mean, arg2 = sd, fill = subgroup)) + stat_dist_eye(position = "dodge")# Using functions from the distributional package (like dist_normal()) with the # dist aesthetic can lead to more compact/expressive specifications dist_df %>% ggplot(aes(x = group, dist = dist_normal(mean, sd), fill = subgroup)) + stat_dist_eye(position = "dodge")# the stat_dist_... family applies a Jacobian adjustment to densities # when plotting on transformed scales in order to plot them correctly. # It determines the Jacobian using symbolic differentiation if possible, # using stats::D(). If symbolic differentation fails, it falls back # to numericDeriv(), which is less reliable; therefore, it is # advisable to use scale transformation functions that are defined in # terms of basic math functions so that their derivatives can be # determined analytically (most of the transformation functions in the # scales package currently have this property). # For example, here is a logNormal distribution plotted on the log # scale, where it will appear Normal: data.frame(dist = "lnorm", logmean = log(10), logsd = 2*log(10)) %>% ggplot(aes(y = 1, dist = dist, arg1 = logmean, arg2 = logsd)) + stat_dist_halfeye() + scale_x_log10(breaks = 10^seq(5,7, by = 2))# see vignette("slabinterval") for many more examples.