% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/geom_bkde2d.r
\name{geom_bkde2d}
\alias{geom_bkde2d}
\alias{stat_bkde2d}
\title{Contours from a 2d density estimate.}
\usage{
geom_bkde2d(mapping = NULL, data = NULL, stat = "bkde2d",
  position = "identity", bandwidth = NULL, range.x = NULL,
  lineend = "butt", contour = TRUE, linejoin = "round", linemitre = 1,
  na.rm = FALSE, show.legend = NA, inherit.aes = TRUE, ...)

stat_bkde2d(mapping = NULL, data = NULL, geom = "density2d",
  position = "identity", contour = TRUE, bandwidth = NULL,
  grid_size = c(51, 51), range.x = NULL, truncate = TRUE, na.rm = FALSE,
  show.legend = NA, inherit.aes = TRUE, ...)
}
\arguments{
\item{mapping}{Set of aesthetic mappings created by \code{\link{aes}} or
\code{\link{aes_}}. If specified and \code{inherit.aes = TRUE} (the
default), is combined with the default mapping at the top level of the
plot. You only need to supply \code{mapping} if there isn't a mapping
defined for the plot.}

\item{data}{A data frame. If specified, overrides the default data frame
defined at the top level of the plot.}

\item{stat}{The statistical transformation to use on the data for this
layer, as a string.}

\item{position}{Position adjustment, either as a string, or the result of
a call to a position adjustment function.}

\item{bandwidth}{the kernel bandwidth smoothing parameter. see
\code{\link[KernSmooth]{bkde2D}} for details. If \code{NULL},
it will be computed for you but will most likely not yield optimal
results. see \code{\link[KernSmooth]{bkde2D}} for details}

\item{range.x}{a list containing two vectors, where each vector contains the
minimum and maximum values of x at which to compute the estimate for
each direction. see \code{\link[KernSmooth]{bkde2D}} for details}

\item{lineend}{Line end style (round, butt, square)}

\item{contour}{If \code{TRUE}, contour the results of the 2d density
estimation}

\item{linejoin}{Line join style (round, mitre, bevel)}

\item{linemitre}{Line mitre limit (number greater than 1)}

\item{na.rm}{If \code{FALSE} (the default), removes missing values with
a warning.  If \code{TRUE} silently removes missing values.}

\item{show.legend}{logical. Should this layer be included in the legends?
\code{NA}, the default, includes if any aesthetics are mapped.
\code{FALSE} never includes, and \code{TRUE} always includes.}

\item{inherit.aes}{If \code{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. \code{\link{borders}}.}

\item{...}{other arguments passed on to \code{\link{layer}}. There are
  three types of arguments you can use here:

  \itemize{
  \item Aesthetics: to set an aesthetic to a fixed value, like
     \code{color = "red"} or \code{size = 3}.
  \item Other arguments to the layer, for example you override the
    default \code{stat} associated with the layer.
  \item Other arguments passed on to the stat.
  }}

\item{truncate}{logical flag: if TRUE, data with x values outside the range
specified by range.x are ignored. see \code{\link[KernSmooth]{bkde2D}}
for details}

\item{gridsize}{vector containing the number of equally spaced points in each
direction over which the density is to be estimated. see
\code{\link[KernSmooth]{bkde2D}} for details}
}
\description{
Contours from a 2d density estimate.

Perform a 2D kernel density estimation using \code{bkde2D} and display the
results with contours. This can be useful for dealing with overplotting
}
\section{Computed variables}{

Same as \code{\link{stat_contour}}
}
\examples{
m <- ggplot(faithful, aes(x = eruptions, y = waiting)) +
       geom_point() +
       xlim(0.5, 6) +
       ylim(40, 110)

m + geom_bkde2d(bandwidth=c(0.5, 5))

m + stat_bkde2d(bandwidth=c(0.5, 5), aes(fill = ..level..), geom = "polygon")

# If you map an aesthetic to a categorical variable, you will get a
# set of contours for each value of that variable
set.seed(4393)
dsmall <- diamonds[sample(nrow(diamonds), 1000), ]
d <- ggplot(dsmall, aes(x, y)) +
       geom_bkde2d(bandwidth=c(0.5, 0.5), aes(colour = cut))
d

# If we turn contouring off, we can use use geoms like tiles:
d + stat_bkde2d(bandwidth=c(0.5, 0.5), geom = "raster",
                aes(fill = ..density..), contour = FALSE)

# Or points:
d + stat_bkde2d(bandwidth=c(0.5, 0.5), geom = "point",
                aes(size = ..density..),  contour = FALSE)
}
\seealso{
\code{\link{geom_contour}} for contour drawing geom,
 \code{\link{stat_sum}} for another way of dealing with overplotting
}