Draw a function as a continuous curve

Computes and draws a function as a continuous curve. This makes it easy to superimpose a function on top of an existing plot. The function is called with a grid of evenly spaced values along the x axis, and the results are drawn (by default) with a line.

geom_function(
  mapping = NULL,
  data = NULL,
  stat = "function",
  position = "identity",
  ...,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)

stat_function(
  mapping = NULL,
  data = NULL,
  geom = "function",
  position = "identity",
  ...,
  fun,
  xlim = NULL,
  n = 101,
  args = list(),
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = 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: Ignored by stat_function(), do not use.
stat: The statistical transformation to use on the data for this layer, as a string.
position: Position adjustment, either as a string, or the result of a call to a position adjustment function.
...: 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.
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().
geom: The geometric object to use display the data
fun: Function to use. Either 1) an anonymous function in the base or rlang formula syntax (see rlang::as_function()) or 2) a quoted or character name referencing a function; see examples. Must be vectorised.
xlim: Optionally, restrict the range of the function to this range.
n: Number of points to interpolate along the x axis.
args: List of additional arguments passed on to the function defined by fun.

Aesthetics

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

x
y
alpha
colour
group
linetype
size

Learn more about setting these aesthetics in vignette("ggplot2-specs").

Computed variables

stat_function() computes the following variables:

x: x values along a grid
y: value of the function evaluated at corresponding x

Examples


# geom_function() is useful for overlaying functions
set.seed(1492)
ggplot(data.frame(x = rnorm(100)), aes(x)) +
  geom_density() +
  geom_function(fun = dnorm, colour = "red")


# To plot functions without data, specify range of x-axis
base <-
  ggplot() +
  xlim(-5, 5)

base + geom_function(fun = dnorm)


base + geom_function(fun = dnorm, args = list(mean = 2, sd = .5))


# The underlying mechanics evaluate the function at discrete points
# and connect the points with lines
base + stat_function(fun = dnorm, geom = "point")


base + stat_function(fun = dnorm, geom = "point", n = 20)


base + geom_function(fun = dnorm, n = 20)


# Two functions on the same plot
base +
  geom_function(aes(colour = "normal"), fun = dnorm) +
  geom_function(aes(colour = "t, df = 1"), fun = dt, args = list(df = 1))


# Using a custom anonymous function
base + geom_function(fun = function(x) 0.5*exp(-abs(x)))


base + geom_function(fun = ~ 0.5*exp(-abs(.x)))


# Using a custom named function
f <- function(x) 0.5*exp(-abs(x))

base + geom_function(fun = f)

Arguments

Aesthetics

Computed variables

See also

Examples