gggda (version 0.1.0)

stat_chull: Convex hulls and hull peelings

Description

Restrict planar data to the boundary points of its convex hull, or of nested convex hulls containing specified fractions of points.

Usage

stat_chull(
  mapping = NULL,
  data = NULL,
  geom = "polygon",
  position = "identity",
  show.legend = NA,
  inherit.aes = TRUE,
  ...
)
stat_peel(
  mapping = NULL,
  data = NULL,
  geom = "polygon",
  position = "identity",
  num = NULL,
  by = 1L,
  breaks = c(0.5),
  cut = c("above", "below"),
  show.legend = NA,
  inherit.aes = TRUE,
  ...
)

Value

A ggproto

layer.

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)).

geom

The geometric object to use to display the data for this layer. When using a stat_*() function to construct a layer, the geom argument can be used to override the default coupling between stats and geoms. The geom argument accepts the following:

• A Geom ggproto subclass, for example GeomPoint.

• A string naming the geom. To give the geom as a string, strip the function name of the geom_ prefix. For example, to use geom_point(), give the geom as "point".

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

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().

...

Additional arguments passed to ggplot2::layer().

num

A positive integer; the number of hulls to peel. Pass Inf for all hulls.

by

A positive integer; with what frequency to include consecutive hulls, pairs with num.

breaks

A numeric vector of fractions (between 0 and 1) of the data to contain in each hull; overridden by num.

cut

Character; one of "above" and "below", indicating whether each hull should contain at least or at most breaks of the data, respectively.

Multidimensional position aesthetics

This statistical transformation is compatible with the convenience function aes_coord().

Some transformations (e.g. stat_center()) commute with projection to the lower (1 or 2)-dimensional biplot space. If they detect aesthetics of the form ..coord[0-9]+, then ..coord1 and ..coord2 are converted to x and y while any remaining are ignored.

Other transformations (e.g. stat_spantree()) yield different results in a lower-dimensional biplot when they are computed before versus after projection. If the stat layer detects these aesthetics, then the transformation is performed before projection, and the results in the first two dimensions are returned as x and y.

A small number of transformations (stat_rule()) are incompatible with these aesthetics but will accept aes_coord() without warning.

Computed variables

These are calculated during the statistical transformation and can be accessed with delayed evaluation.

hull

the position of breaks that defines each hull

frac

the value of breaks that defines each hull

prop

the actual proportion of data within each hull

Details

As used in a ggplot2 vignette, stat_chull() restricts a dataset with x and y variables to the points that lie on its convex hull.

Building on this, stat_peel() returns hulls from a convex hull peeling: a subset of sequentially removed hulls containing specified fractions of the data.

References

Barnett V (1976) "The Ordering of Multivariate Data". Journal of the Royal Statistical Society: Series A (General), 139(3): 318--344. tools:::Rd_expr_doi("10.2307/2344839")

See Also

Other stat layers: stat_bagplot(), stat_center(), stat_cone(), stat_depth(), stat_rule(), stat_scale(), stat_spantree()

Examples

ggplot(USJudgeRatings, aes(x = INTG, y = PREP)) +
  geom_point() +
  stat_chull(alpha = .5)
ggplot(USJudgeRatings, aes(x = INTG, y = PREP)) +
  stat_peel(
    aes(alpha = after_stat(hull)),
    breaks = seq(.1, .9, .2)
  )
ggplot(USJudgeRatings, aes(x = INTG, y = PREP)) +
  stat_peel(
    aes(alpha = after_stat(hull)),
    num = 6, by = 2, color = "black"
  )

# specify fractions of points
ggplot(iris, aes(Sepal.Width, Sepal.Length, color = Species)) +
  stat_peel(aes(fill = Species, alpha = after_stat(frac)),
            breaks = seq(.1, .9, .2)) +
  scale_alpha_continuous(trans = scales::reverse_trans()) +
  geom_point()
# specify number of peels
ggplot(iris, aes(Sepal.Width, Sepal.Length, color = Species)) +
  stat_peel(fill = "transparent", num = 3) +
  geom_point()
# mapping to opacity overrides transparency
ggplot(iris, aes(Sepal.Width, Sepal.Length, color = Species)) +
  stat_peel(aes(alpha = after_stat(hull)), fill = "transparent", num = 3) +
  geom_point()