Shortcut version of stat_slabinterval() with geom_interval() for
creating multiple-interval plots.
Roughly equivalent to:
stat_slabinterval(
aes(
colour = after_stat(level),
size = NULL
),
geom = "interval",
show_point = FALSE,
.width = c(0.5, 0.8, 0.95),
show_slab = FALSE,
show.legend = NA
)Usage
stat_interval(
mapping = NULL,
data = NULL,
geom = "interval",
position = "identity",
...,
.width = c(0.5, 0.8, 0.95),
point_interval = "median_qi",
orientation = NA,
na.rm = FALSE,
show.legend = NA,
inherit.aes = TRUE
)Arguments
- mapping
Set of aesthetic mappings created by
aes(). If specified andinherit.aes = TRUE(the default), it is combined with the default mapping at the top level of the plot. You must supplymappingif there is no plot mapping.- data
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 toggplot().A
data.frame, or other object, will override the plot data. All objects will be fortified to produce a data frame. Seefortify()for which variables will be created.A
functionwill be called with a single argument, the plot data. The return value must be adata.frame, and will be used as the layer data. Afunctioncan be created from aformula(e.g.~ head(.x, 10)).- geom
Use to override the default connection between
stat_interval()andgeom_interval()- position
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, likecolour = "red"orlinewidth = 3(see Aesthetics, below). They may also be parameters to the paired geom/stat. When paired with the default geom,geom_interval(), these include:interval_size_rangeA length-2 numeric vector. This geom scales the raw size aesthetic values when drawing interval and point sizes, as they tend to be too thick when using the default settings of
scale_size_continuous(), which give sizes with a range ofc(1, 6). Theinterval_size_domainvalue indicates the input domain of raw size values (typically this should be equal to the value of therangeargument of thescale_size_continuous()function), andinterval_size_rangeindicates the desired output range of the size values (the min and max of the actual sizes used to draw intervals). Most of the time it is not recommended to change the value of this argument, as it may result in strange scaling of legends; this argument is a holdover from earlier versions that did not have size aesthetics targeting the point and interval separately. If you want to adjust the size of the interval or points separately, you can also use thelinewidthorpoint_sizeaesthetics; see sub-geometry-scales.interval_size_domainA length-2 numeric vector giving the minimum and maximum of the values of the
sizeandlinewidthaesthetics that will be translated into actual sizes for intervals drawn according tointerval_size_range(see the documentation for that argument.)arrowgrid::arrow()giving the arrow heads to use on the interval, orNULLfor no arrows.
- .width
The
.widthargument passed topoint_interval: a vector of probabilities to use that determine the widths of the resulting intervals. If multiple probabilities are provided, multiple intervals per group are generated, each with a different probability interval (and value of the corresponding.widthandlevelgenerated variables).- point_interval
A function from the
point_interval()family (e.g.,median_qi,mean_qi,mode_hdi, etc), or a string giving the name of a function from that family (e.g.,"median_qi","mean_qi","mode_hdi", etc; if a string, the caller's environment is searched for the function, followed by the ggdist environment). This function determines the point summary (typically mean, median, or mode) and interval type (quantile interval,qi; highest-density interval,hdi; or highest-density continuous interval,hdci). Output will be converted to the appropriatex- ory-based aesthetics depending on the value oforientation. See thepoint_interval()family of functions for more information.- orientation
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 theyaesthetic to identify different groups. For each group, uses thex,xmin,xmax, andthicknessaesthetics to draw points, intervals, and slabs."vertical"(or"x"): draw vertically, using thexaesthetic to identify different groups. For each group, uses they,ymin,ymax, andthicknessaesthetics 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"(ggdist had anorientationparameter before base ggplot did, hence the discrepancy).- na.rm
If
FALSE, the default, missing values are removed with a warning. IfTRUE, missing values are silently removed.- show.legend
Should this layer be included in the legends? Default is
c(size = FALSE), unlike most geoms, to match its common use cases.FALSEhides all legends,TRUEshows all legends, andNAshows only those that are mapped (the default for most geoms).- inherit.aes
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().
Value
A ggplot2::Stat representing a multiple-interval geometry which can
be added to a ggplot() object.
Details
To visualize sample data, such as a data distribution, samples from a
bootstrap distribution, or a Bayesian posterior, you can supply samples to
the x or y aesthetic.
To visualize analytical distributions, you can use the xdist or ydist
aesthetic. For historical reasons, you can also use dist to specify the distribution, though
this is not recommended as it does not work as well with orientation detection.
These aesthetics can be used as follows:
xdist,ydist, anddistcan be any distribution object from the distributional package (dist_normal(),dist_beta(), etc) or can be aposterior::rvar()object. Since these functions are vectorized, other columns can be passed directly to them in anaes()specification; e.g.aes(dist = dist_normal(mu, sigma))will work ifmuandsigmaare columns in the input data frame.distcan be a character vector giving the distribution name. Then thearg1, ...arg9aesthetics (orargsas 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 thepnorm(),qnorm(), anddnorm()functions for Normal distributions.See the
parse_dist()function for a useful way to generatedistandargsvalues from human-readable distribution specs (like"normal(0,1)"). Such specs are also produced by other packages (like thebrms::get_priorfunction in brms); thus,parse_dist()combined with the stats described here can help you visualize the output of those functions.
Computed Variables
The following variables are computed by this stat and made available for
use in aesthetic specifications (aes()) using the after_stat()
function or the after_stat argument of stage():
xory: For slabs, the input values to the slab function. For intervals, the point summary from the interval function. Whether it isxorydepends onorientationxminorymin: For intervals, the lower end of the interval from the interval function.xmaxorymax: 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]. For slabs, the width of the smallest interval containing that value of the slab.level: For intervals, the interval width as an ordered factor. For slabs, the level of the smallest interval containing that value of the slab.pdf: For slabs, the probability density function (PDF). Ifoptions("ggdist.experimental.slab_data_in_intervals")isTRUE: For intervals, the PDF at the point summary; intervals also havepdf_minandpdf_maxfor the PDF at the lower and upper ends of the interval.cdf: For slabs, the cumulative distribution function. Ifoptions("ggdist.experimental.slab_data_in_intervals")isTRUE: For intervals, the CDF at the point summary; intervals also havecdf_minandcdf_maxfor the CDF at the lower and upper ends of the interval.
Aesthetics
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.
These stats support the following aesthetics:
x: x position of the geometry (when orientation ="vertical"); or sample data to be summarized (whenorientation = "horizontal"with sample data).y: y position of the geometry (when orientation ="horizontal"); or sample data to be summarized (whenorientation = "vertical"with sample data).weight: When using samples (i.e. thexandyaesthetics, notxdistorydist), optional weights to be applied to each draw.xdist: When using analytical distributions, distribution to map on the x axis: a distributional object (e.g.dist_normal()) or aposterior::rvar()object.ydist: When using analytical distributions, distribution to map on the y axis: a distributional object (e.g.dist_normal()) or aposterior::rvar()object.dist: When using analytical distributions, a name of a distribution (e.g."norm"), a distributional object (e.g.dist_normal()), or aposterior::rvar()object. See Details.args: Distribution arguments (argsorarg1, ...arg9). See Details.
In addition, in their default configuration (paired with geom_interval())
the following aesthetics are supported by the underlying geom:
Interval-specific aesthetics
xmin: Left end of the interval sub-geometry (iforientation = "horizontal").xmax: Right end of the interval sub-geometry (iforientation = "horizontal").ymin: Lower end of the interval sub-geometry (iforientation = "vertical").ymax: Upper end of the interval sub-geometry (iforientation = "vertical").
Color aesthetics
colour: (orcolor) The color of the interval and point sub-geometries. Use theslab_color,interval_color, orpoint_coloraesthetics (below) to set sub-geometry colors separately.fill: The fill color of the slab and point sub-geometries. Use theslab_fillorpoint_fillaesthetics (below) to set sub-geometry colors separately.alpha: The opacity of the slab, interval, and point sub-geometries. Use theslab_alpha,interval_alpha, orpoint_alphaaesthetics (below) to set sub-geometry colors separately.colour_ramp: (orcolor_ramp) A secondary scale that modifies thecolorscale to "ramp" to another color. Seescale_colour_ramp()for examples.fill_ramp: A secondary scale that modifies thefillscale to "ramp" to another color. Seescale_fill_ramp()for examples.
Line aesthetics
linewidth: Width of the line used to draw the interval (except withgeom_slab(): then it is the width of the slab). With composite geometries including an interval and slab, useslab_linewidthto set the line width of the slab (see below). For interval, rawlinewidthvalues are transformed according to theinterval_size_domainandinterval_size_rangeparameters of thegeom(see above).size: Determines the size of the point. Iflinewidthis not provided,sizewill also determines the width of the line used to draw the interval (this allows line width and point size to be modified together by setting onlysizeand notlinewidth). Rawsizevalues are transformed according to theinterval_size_domain,interval_size_range, andfatten_pointparameters of thegeom(see above). Use thepoint_sizeaesthetic (below) to set sub-geometry size directly without applying the effects ofinterval_size_domain,interval_size_range, andfatten_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 theslab_linetypeorinterval_linetypeaesthetics (below) to set sub-geometry line types separately.
Interval-specific color and line override aesthetics
interval_colour: (orinterval_color) Override forcolour/color: the color of the interval.interval_alpha: Override foralpha: the opacity of the interval.interval_linetype: Override forlinetype: the line type of the interval.
Deprecated aesthetics
interval_size: Useinterval_linewidth.
Other aesthetics (these work as in standard geoms)
widthheightgroup
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 also
See geom_interval() for the geom underlying this stat.
See stat_slabinterval() for the stat this shortcut is based on.
Other slabinterval stats:
stat_ccdfinterval(),
stat_cdfinterval(),
stat_eye(),
stat_gradientinterval(),
stat_halfeye(),
stat_histinterval(),
stat_pointinterval(),
stat_slab(),
stat_spike()
Examples
library(dplyr)
library(ggplot2)
library(distributional)
theme_set(theme_ggdist())
# ON SAMPLE DATA
set.seed(1234)
df = data.frame(
group = c("a", "b", "c"),
value = rnorm(1500, mean = c(5, 7, 9), sd = c(1, 1.5, 1))
)
df %>%
ggplot(aes(x = value, y = group)) +
stat_interval() +
scale_color_brewer()
# ON ANALYTICAL DISTRIBUTIONS
dist_df = data.frame(
group = c("a", "b", "c"),
mean = c( 5, 7, 8),
sd = c( 1, 1.5, 1)
)
# Vectorized distribution types, like distributional::dist_normal()
# and posterior::rvar(), can be used with the `xdist` / `ydist` aesthetics
dist_df %>%
ggplot(aes(y = group, xdist = dist_normal(mean, sd))) +
stat_interval() +
scale_color_brewer()