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Bagplots

Source: R/geom-bagplot.r
geom_bagplot.Rd

Render bagplots from tagged data comprising medians, hulls, contours, and outlier specifications.

Usage

geom_bagplot(
  mapping = NULL,
  data = NULL,
  stat = "bagplot",
  position = "identity",
  ...,
  bag.linewidth = sync(),
  bag.linetype = sync(),
  bag.colour = "black",
  bag.color = NULL,
  bag.fill = sync(),
  bag.alpha = NA,
  median.shape = 21L,
  median.stroke = sync(),
  median.size = 5,
  median.colour = sync(),
  median.color = NULL,
  median.fill = "white",
  median.alpha = NA,
  fence.linewidth = 0.25,
  fence.linetype = 0L,
  fence.colour = sync(),
  fence.color = NULL,
  fence.fill = sync(),
  fence.alpha = 0.25,
  outlier.shape = sync(),
  outlier.stroke = sync(),
  outlier.size = sync(),
  outlier.colour = sync(),
  outlier.color = NULL,
  outlier.fill = NA,
  outlier.alpha = NA,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)

Arguments

mapping

Set of aesthetic mappings created by 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.

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 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)).

stat

The statistical transformation to use on the data for this layer. When using a geom_*() function to construct a layer, the stat argument can be used the override the default coupling between geoms and stats. The stat argument accepts the following:

  • A Stat ggproto subclass, for example StatCount.

  • A string naming the stat. To give the stat as a string, strip the function name of the stat_ prefix. For example, to use stat_count(), give the stat as "count".

  • For more information and other ways to specify the stat, see the layer stat documentation.

position

A position adjustment to use on the data for this layer. This can be used in various ways, including to prevent overplotting and improving the display. The position argument accepts the following:

  • The result of calling a position function, such as position_jitter(). This method allows for passing extra arguments to the position.

  • A string naming the position adjustment. To give the position as a string, strip the function name of the position_ prefix. For example, to use position_jitter(), give the position as "jitter".

  • For more information and other ways to specify the position, see the layer position documentation.

...

Additional arguments passed to ggplot2::layer().

bag.linetype, bag.linewidth, bag.colour, bag.color, bag.fill, bag.alpha

Default aesthetics for bags. Set to sync() to inherit from the data's aesthetics or to NULL to use the data's aesthetics.

median.shape, median.stroke, median.size, median.colour, median.color, median.fill, median.alpha

Default aesthetics for medians. Set to sync() to inherit from the data's aesthetics or to NULL to use the data's aesthetics.

fence.linetype, fence.linewidth, fence.colour, fence.color, fence.fill, fence.alpha

Default aesthetics for fences. Set to sync() to inherit from the data's aesthetics or to NULL to use the data's aesthetics.

outlier.shape, outlier.stroke, outlier.size, outlier.colour, outlier.color, outlier.fill, outlier.alpha

Default aesthetics for outliers. Set to sync() to inherit from the data's aesthetics or to NULL to use the data's aesthetics.

na.rm

Passed to ggplot2::layer().

show.legend

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.

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 ggproto layer.

Details

geom_bagplot() is designed to pair with stat_bagplot(), analogously to the pairing of ggplot2::geom_boxplot() with ggplot2::stat_boxplot().

Because the optional components are more expensive to compute in this setting, they are controlled by parameters passed to the stat. Auxiliary aesthetics like median.colour are available that override auxiliary defaults, and these in turn override the standard defaults. Auxiliary defaults also take effect when auxiliary aesthetics are passed NULL, so that stat_bagplot() and geom_bagplot() have the same default behavior. Pass sync() (instead of NULL, as in ggplot2::geom_boxplot()) to synchronize an auxiliary aesthetic with its standard counterpart.

WARNING: The trade-off between precision and runtime is greater for depth estimation than for density estimation. At the resolution of the default \(100 \times 100\) grid, basic examples may vary noticeably when starting from different random seeds.

Biplot layers

ggbiplot() uses ggplot2::fortify() internally to produce a single data frame with a .matrix column distinguishing the subjects ("rows") and variables ("cols"). The stat layers stat_rows() and stat_cols() simply filter the data frame to one of these two.

The geom layers geom_rows_*() and geom_cols_*() call the corresponding stat in order to render plot elements for the corresponding factor matrix. geom_dims_*() selects a default matrix based on common practice, e.g. points for rows and arrows for columns.

Aesthetics

geom_bagplot() understands the following aesthetics (required aesthetics are in bold):

  • x

  • y

  • component

  • linewidth

  • linetype

  • colour

  • fill

  • alpha

  • shape

  • stroke

  • size

  • group

See also

Other geom layers: geom_axis(), geom_interpolation(), geom_isoline(), geom_lineranges(), geom_origin(), geom_rule(), geom_text_radiate(), geom_vector()

Examples

# Motor Trends base plot with factorized cylinder counts
p <- mtcars |> 
  transform(cyl = factor(cyl)) |> 
  ggplot(aes(x = wt, y = disp)) +
  theme_bw()
# basic bagplot
p + geom_bagplot()

# group by cylinder count
p + geom_bagplot(
  fraction = 0.4, coef = 1.2,
  aes(fill = cyl, linetype = cyl, color = cyl)
)

# using normally unmapped aesthetics
p + geom_bagplot(
  fraction = 0.4, coef = 1.2,
  aes(fill = cyl, linetype = cyl, color = cyl),
  median.color = "black",
  fence.linetype = sync(), fence.colour = "black",
  outlier.shape = "asterisk", outlier.colour = "black"
)