ordr (version 0.1.2)

stat_chull: Restrict geometric data to boundary points for its convex hull

Description

As used in a ggplot2 vignette, this stat layer restricts a dataset with x and y variables to the points that lie on its convex hull. The biplot extension restricts each matrix factor to its own hull.

Usage

stat_chull(
  mapping = NULL,
  data = NULL,
  geom = "polygon",
  position = "identity",
  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().

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.

Ordination aesthetics

The convenience function ord_aes() can be used to incorporate all coordinates of the ordination model into a statistical transformation. It maps the coordinates to the custom aesthetics ..coord1, ..coord2, etc.

Some transformations, e.g. stat_center(), are commutative with projection to the 'x' and 'y' coordinates. 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 planar biplot when they are computer before or after projection. If such a stat layer detects these aesthetics, then the lot of them are used in the transformation.

In either case, the stat layer returns a data frame with position aesthetics x and y.

See Also

Other stat layers: stat_center(), stat_cone(), stat_scale(), stat_spantree()

Examples

# correspondence analysis of combined female and male hair and eye color data
HairEyeColor %>%
  rowSums(dims = 2L) %>%
  MASS::corresp(nf = 2L) %>%
  as_tbl_ord() %>%
  augment_ord() %>%
  print() -> hec_ca
# inertia across artificial coordinates (all singular values < 1)
get_inertia(hec_ca)

# in row-principal biplot, row coordinates are weighted averages of columns
hec_ca %>%
  confer_inertia("rows") %>%
  ggbiplot(aes(color = .matrix, fill = .matrix, shape = .matrix)) +
  theme_bw() +
  stat_cols_chull(alpha = .1) +
  geom_cols_point() +
  geom_rows_point() +
  ggtitle("Row-principal CA of hair & eye color")
# in column-principal biplot, column coordinates are weighted averages of rows
hec_ca %>%
  confer_inertia("cols") %>%
  ggbiplot(aes(color = .matrix, fill = .matrix, shape = .matrix)) +
  theme_bw() +
  stat_rows_chull(alpha = .1) +
  geom_rows_point() +
  geom_cols_point() +
  ggtitle("Column-principal CA of hair & eye color")