stat_filledcontour: filled contour stat for ggplot2

In abnormally-distributed/cvreg: Cross Validation and Robust Estimation Utilities

Description

filled contour stat for ggplot2

Usage

stat_filledcontour(
  mapping = NULL,
  data = NULL,
  geom = "raster",
  position = "identity",
  show.legend = NA,
  inherit.aes = TRUE,
  interpolate = TRUE,
  ...
)

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.
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)).
position	Position adjustment, either as a string, or the result of a call to a position adjustment function.
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().
interpolate	If TRUE interpolate linearly, if FALSE (the default) don't interpolate.
...	Other arguments passed on to layer(). These are often aesthetics, used to set an aesthetic to a fixed value, like colour = "red" or size = 3. They may also be parameters to the paired geom/stat.

Examples

ggplot(iris, aes(x = Sepal.Length, y = Petal.Length)) +
   stat_filledcontour(aes(fill=stat(z))) +
   scale_fill_viridis_c()

abnormally-distributed/cvreg documentation built on May 3, 2020, 3:45 p.m.