Combined point + multiple interval geoms with default aesthetics designed for use with output from point_interval(). Wrapper around geom_slabinterval().

geom_pointinterval(
mapping = NULL,
data = NULL,
stat = "identity",
position = "identity",
...,
side = "both",
orientation = NA,
show_slab = FALSE,
show.legend = c(size = FALSE)
)

## Arguments

mapping 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. The position adjustment to use for overlapping points on this layer. Setting this equal to "dodge" can be useful if you have overlapping intervals. Arguments passed on to geom_slabinterval scaleWhat 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. justificationJustification 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. normalizeHow to normalize heights of functions input to the thickness aesthetic. If "all" (the default), normalize so that the maximum height across all data is 1; if "panels", normalize within panels so that the maximum height in each panel is 1; if "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; if "groups", normalize within values of the opposite axis and within groups so that the maximum height in each group is 1; if "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). interval_size_domainThe minimum and maximum of the values of the size aesthetic that will be translated into actual sizes for intervals drawn according to interval_size_range (see the documentation for that argument.) interval_size_range(Deprecated). 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 of c(1, 6). The interval_size_domain value indicates the input domain of raw size values (typically this should be equal to the value of the range argument of the scale_size_continuous() function), and interval_size_range indicates 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 instead use the interval_size or point_size aesthetics; see scales. fatten_pointA multiplicative factor used to adjust the size of the point relative to the size of the thickest interval line. If you wish to specify point sizes directly, you can also use the point_size aesthetic and scale_point_size_continuous() or scale_point_size_discrete(); sizes specified with that aesthetic will not be adjusted using fatten_point. show_pointShould the point portion of the geom be drawn? Default TRUE. show_intervalShould the interval portion of the geom be drawn? Default TRUE. na.rmIf FALSE, the default, missing values are removed with a warning. If TRUE, missing values are silently removed. inherit.aesIf 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(). Which side to draw 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). Whether this geom is drawn horizontally ("horizontal") or vertically ("vertical"). The default, NA, automatically detects the orientation based on how the aesthetics are assigned, and should generally do an okay job at this. When horizontal (resp. vertical), the geom uses the y (resp. x) aesthetic to identify different groups, then for each group uses the x (resp. y) aesthetic and the thickness aesthetic to draw a function as an slab, and draws points and intervals horizontally (resp. vertically) using the xmin, x, and xmax (resp. ymin, y, and ymax) aesthetics. 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 ggplot did, and I think the tidybayes naming scheme is more intuitive: "x" and "y" are not orientations and their mapping to orientations is, in my opinion, backwards; but the base ggplot naming scheme is allowed for compatibility). Should the slab portion of the geom be drawn? Default TRUE. Should this layer be included in the legends? Default is c(size = FALSE), unlike most geoms, to match its common use cases. FALSE hides all legends, TRUE shows all legends, and NA shows only those that are mapped (the default for most geoms).

## Value

A ggplot2::Geom representing a point+multiple uncertainty interval geometry which can be added to a ggplot() object.

## Details

These geoms are wrappers around geom_slabinterval() with defaults designed to produce points+interval plots. These geoms set some default aesthetics equal to the .lower, .upper, and .width columns generated by the point_interval family of functions, making them often more convenient than vanilla geom_pointrange() when used with functions like median_qi(), mean_qi(), mode_hdi(), etc.

Specifically, geom_pointinterval acts as if its default aesthetics are aes(size = -.width).

## Aesthetics

These geoms support the following aesthetics:

• x

• y

• datatype

• alpha

• colour

• linetype

• fill

• shape

• stroke

• point_colour

• point_fill

• point_alpha

• point_size

• size

• interval_colour

• interval_alpha

• interval_size

• interval_linetype

• slab_size

• slab_colour

• slab_fill

• slab_alpha

• slab_linetype

• ymin

• ymax

• xmin

• xmax

• width

• height

• thickness

• group

See examples of some of these aesthetics in action in vignette("slabinterval"). Learn more about the sub-geom aesthetics (like interval_color) in the scales documentation. Learn more about basic ggplot aesthetics in vignette("ggplot2-specs").

See geom_slabinterval() for the geom that these geoms wrap. All parameters of that geom are available to these geoms.

See stat_pointinterval() for the stat version, intended for use on samples from a distribution. See geom_interval() for a similar stat intended for intervals without point summaries. See stat_sample_slabinterval() for a variety of other stats that combine intervals with densities and CDFs. See geom_slabinterval() for the geom that these geoms wrap. All parameters of that geom are available to these geoms.

Matthew Kay

## Examples


library(dplyr)
library(ggplot2)

data(RankCorr_u_tau, package = "ggdist")

# orientation is detected automatically based on
# use of xmin/xmax or ymin/ymax

RankCorr_u_tau %>%
group_by(i) %>%
median_qi(.width = c(.8, .95)) %>%
ggplot(aes(y = i, x = u_tau, xmin = .lower, xmax = .upper)) +
geom_pointinterval()

RankCorr_u_tau %>%
group_by(i) %>%
median_qi(.width = c(.8, .95)) %>%
ggplot(aes(x = i, y = u_tau, ymin = .lower, ymax = .upper)) +
geom_pointinterval()