This meta-geom supports drawing combinations of functions (as slabs, aka ridge plots or joy plots), points, and intervals. It acts as a meta-geom for many other tidybayes geoms that are wrappers around this geom, including eye plots, half-eye plots, CCDF barplots, and point+multiple interval plots, and supports both horizontal and vertical orientations, dodging (via the position argument), and relative justification of slabs with their corresponding intervals.

  mapping = NULL,
  data = NULL,
  stat = "identity",
  position = "identity",
  side = c("topright", "top", "right", "bottomleft", "bottom", "left", "topleft",
    "bottomright", "both"),
  scale = 0.9,
  orientation = NA,
  justification = NULL,
  normalize = c("all", "panels", "xy", "groups", "none"),
  interval_size_domain = c(1, 6),
  interval_size_range = c(0.6, 1.4),
  fatten_point = 1.8,
  show_slab = TRUE,
  show_point = TRUE,
  show_interval = TRUE,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE

  mapping = NULL,
  data = NULL,
  stat = "identity",
  position = "identity",
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE



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.


Other arguments passed to layer().


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).


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.


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).


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.


How 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).


The 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.)


(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.


A 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.


Should the slab portion of the geom be drawn? Default TRUE.


Should the point portion of the geom be drawn? Default TRUE.


Should the interval portion of the geom be drawn? Default TRUE.


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().


A ggplot2::Geom representing a slab or combined slab+interval geometry which can be added to a ggplot() object.


geom_slabinterval is a flexible meta-geom that you can use directly or through a variety of "shortcut" geoms that represent useful combinations of the various parameters of this geom. In many cases you will want to use the shortcut geoms instead as they create more useful mnemonic primitives, such as eye plots, half-eye plots, point+interval plots, or CCDF barplots.

The slab portion of the geom is much like a ridge or "joy" plot: it represents the value of a function scaled to fit between values on the x or y access (depending on the value of orientation). Values of the functions are specified using the thickness aesthetic and are scaled to fit into scale times the distance between points on the relevant axis. E.g., if orientation is "horizontal", scale is 0.9, and y is a discrete variable, then the thickness aesthetic specifies the value of some function of x that is drawn for every y value and scaled to fit into 0.9 times the distance between points on the y axis.

For the interval portion of the geom, x and y aesthetics specify the location of the point and ymin/ymax or xmin/xmax (depending on the value of orientation specifying the endpoints of the interval. A scaling factor for interval line width and point size is applied through the interval_size_domain, interval_size_range, and fatten_point parameters. These scaling factors are designed to give multiple uncertainty intervals reasonable scaling at the default settings for scale_size_continuous().

As a combination geom, this geom expects a datatype aesthetic specifying which part of the geom a given row in the input data corresponds to: "slab" or "interval". However, specifying this aesthetic manually is typically only necessary if you use this geom directly; the numerous wrapper geoms will usually set this aesthetic for you as needed, and their use is recommended unless you have a very custom use case.

Wrapper geoms and stats include:

Typically, the geom_* versions are meant for use with already-summarized data (such as intervals) and the stat_* versions are summarize the data themselves (usually draws from a distribution) to produce the geom.


These geoms support the following aesthetics:

  • x

  • y

  • datatype

  • alpha

  • colour

  • colour_ramp

  • 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

  • fill_ramp

  • 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 also

See geom_lineribbon() for a combination geom designed for fit curves plus probability bands. See stat_sample_slabinterval() and stat_dist_slabinterval() for families of stats built on top of this geom for common use cases (like stat_halfeye()). See vignette("slabinterval") for a variety of examples of use.


Matthew Kay


# geom_slabinterval() is typically not that useful on its own. # See vignette("slabinterval") for a variety of examples of the use of its # shortcut geoms and stats, which are more useful than using # geom_slabinterval() directly.