#' Display a smooth density estimate.
#'
#' A kernel density estimate, useful for display the distribution of variables
#' with underlying smoothness.
#'
#' @section Aesthetics:
#' \Sexpr[results=rd,stage=build]{animint2:::rd_aesthetics("geom", "density")}
#'
#' @seealso See \code{\link{geom_histogram}}, \code{\link{geom_freqpoly}} for
#' other methods of displaying continuous distribution.
#' See \code{\link{geom_violin}} for a compact density display.
#' @inheritParams layer
#' @inheritParams geom_point
#' @param geom,stat Use to override the default connection between
#' \code{geom_density} and \code{stat_density}.
#' @export
#' @examples
#' ggplot(diamonds, aes(carat)) +
#' geom_density()
#'
#' ggplot(diamonds, aes(carat)) +
#' geom_density(adjust = 1/5)
#' ggplot(diamonds, aes(carat)) +
#' geom_density(adjust = 5)
#'
#' ggplot(diamonds, aes(depth, colour = cut)) +
#' geom_density() +
#' xlim(55, 70)
#' ggplot(diamonds, aes(depth, fill = cut, colour = cut)) +
#' geom_density(alpha = 0.1) +
#' xlim(55, 70)
#'
#' \donttest{
#' # Stacked density plots: if you want to create a stacked density plot, you
#' # probably want to 'count' (density * n) variable instead of the default
#' # density
#'
#' # Loses marginal densities
#' ggplot(diamonds, aes(carat, fill = cut)) +
#' geom_density(position = "stack")
#' # Preserves marginal densities
#' ggplot(diamonds, aes(carat, ..count.., fill = cut)) +
#' geom_density(position = "stack")
#'
#' # You can use position="fill" to produce a conditional density estimate
#' ggplot(diamonds, aes(carat, ..count.., fill = cut)) +
#' geom_density(position = "fill")
#' }
geom_density <- function(mapping = NULL, data = NULL,
stat = "density", position = "identity",
...,
na.rm = FALSE,
show.legend = NA,
inherit.aes = TRUE) {
layer(
data = data,
mapping = mapping,
stat = stat,
geom = GeomDensity,
position = position,
show.legend = show.legend,
inherit.aes = inherit.aes,
params = list(
na.rm = na.rm,
...
)
)
}
#' @rdname animint2-gganimintproto
#' @format NULL
#' @usage NULL
#' @export
#' @include geom-ribbon.r
GeomDensity <- gganimintproto("GeomDensity", GeomArea,
default_aes = defaults(
aes(fill = NA, weight = 1, colour = "black", alpha = NA),
GeomArea$default_aes
),
pre_process= function(g, g.data, ...) {
g$geom <- "ribbon"
g.data <- g.data[order(g.data$x), ]
return(list(g = g, g.data = g.data))
}
)
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