% Generated by roxygen2 (4.1.1): do not edit by hand % Please edit documentation in R/geom_bkde2d.r \name{geom_bkde2d} \alias{geom_bkde2d} \title{Contours from a 2d density estimate.} \usage{ geom_bkde2d(mapping = NULL, data = NULL, stat = "bkde2d", position = "identity", bandwidth, range.x = NULL, lineend = "butt", contour = TRUE, linejoin = "round", linemitre = 1, 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{lineend}{Line end style (round, butt, square)} \item{linejoin}{Line join style (round, mitre, bevel)} \item{linemitre}{Line mitre limit (number greater than 1)} \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. }} } \description{ Contours from a 2d density estimate. } \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) }