prob density

stat_prob_2d(
  mapping = NULL,
  data = NULL,
  geom = "density_2d",
  position = "identity",
  ...,
  contour = TRUE,
  contour_var = "density",
  n = 100,
  h = NULL,
  adjust = c(1, 1),
  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)).

geom

Use to override the default connection between geom_prob_2d() and stat_prob_2d.

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.

...

Arguments passed on to geom_contour

binwidth

The width of the contour bins. Overridden by bins.

bins

Number of contour bins. Overridden by breaks.

breaks

One of:

Numeric vector to set the contour breaks
A function that takes the range of the data and binwidth as input and returns breaks as output. A function can be created from a formula (e.g. ~ fullseq(.x, .y)).

Overrides binwidth and bins. By default, this is a vector of length ten with pretty() breaks.

contour

If TRUE, contour the results of the 2d density estimation.

contour_var

Character string identifying the variable to contour by. Can be one of "density", "ndensity", or "count". See the section on computed variables for details.

n

Number of grid points in each direction.

h

Bandwidth (vector of length two). If NULL, estimated using MASS::bandwidth.nrd().

adjust

A multiplicative bandwidth adjustment to be used if 'h' is 'NULL'. This makes it possible to adjust the bandwidth while still using the a bandwidth estimator. For example, adjust = 1/2 means use half of the default bandwidth.

na.rm

If FALSE, the default, missing values are removed with a warning. If TRUE, missing values are silently removed.

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().

Examples

library(ggplot2)
 
# Data
n = 200
set.seed(1)
a <- data.frame( x=rnorm(n, 10, 1.9), y=rnorm(n, 10, 1.2) )
b <- data.frame( x=rnorm(n, 14.5, 1.9), y=rnorm(n, 14.5, 1.9) )
c <- data.frame( x=rnorm(n, 9.5, 1.9), y=rnorm(n, 15.5, 1.9) )
data <- rbind(a,b,c)

# Show the area only
ggplot(data, aes(x=x, y=y) ) +
  stat_prob_2d(aes(fill = ..level.., color =..level.. ), geom = "polygon")
#> Warning: The dot-dot notation (`..level..`) was deprecated in ggplot2 3.4.0.
#> ℹ Please use `after_stat(level)` instead.


ggplot(data, aes(x=x, y=y) ) +
  stat_prob_2d(aes(fill = ..level..), geom = "polygon", color = "white")


ggplot(data, aes(x=x, y=y) ) +
  stat_prob_2d(aes(color =..level.. ), geom = "path")