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#' @inheritParams layer
#' @inheritParams geom_point
#' @inheritParams stat_density
#' @param scale if "area" (default), all violins have the same area (before trimming
#' the tails). If "count", areas are scaled proportionally to the number of
#' observations. If "width", all violins have the same maximum width.
#' @section Computed variables:
#' \describe{
#' \item{density}{density estimate}
#' \item{scaled}{density estimate, scaled to maximum of 1}
#' \item{count}{density * number of points - probably useless for violin plots}
#' \item{violinwidth}{density scaled for the violin plot, according to area, counts
#' or to a constant maximum width}
#' \item{n}{number of points}
#' \item{width}{width of violin bounding box}
#' }
#' @seealso [geom_violin()] for examples, and [stat_density()]
#' for examples with data along the x axis.
#' @export
#' @rdname geom_violin
stat_ydensity <- function(mapping = NULL, data = NULL,
geom = "violin", position = "dodge",
...,
bw = "nrd0",
adjust = 1,
kernel = "gaussian",
trim = TRUE,
scale = "area",
na.rm = FALSE,
orientation = NA,
show.legend = NA,
inherit.aes = TRUE) {
scale <- match.arg(scale, c("area", "count", "width"))
layer(
data = data,
mapping = mapping,
stat = StatYdensity,
geom = geom,
position = position,
show.legend = show.legend,
inherit.aes = inherit.aes,
params = list(
bw = bw,
adjust = adjust,
kernel = kernel,
trim = trim,
scale = scale,
na.rm = na.rm,
...
)
)
}
#' @rdname ggplot2-ggproto
#' @format NULL
#' @usage NULL
#' @export
StatYdensity <- ggproto("StatYdensity", Stat,
required_aes = c("x", "y"),
non_missing_aes = "weight",
setup_params = function(data, params) {
params$flipped_aes <- has_flipped_aes(data, params, main_is_orthogonal = TRUE, group_has_equal = TRUE)
params
},
extra_params = c("na.rm", "orientation"),
compute_group = function(data, scales, width = NULL, bw = "nrd0", adjust = 1,
kernel = "gaussian", trim = TRUE, na.rm = FALSE, flipped_aes = FALSE) {
if (nrow(data) < 3) return(new_data_frame())
range <- range(data$y, na.rm = TRUE)
modifier <- if (trim) 0 else 3
bw <- calc_bw(data$y, bw)
dens <- compute_density(data$y, data$w, from = range[1] - modifier*bw, to = range[2] + modifier*bw,
bw = bw, adjust = adjust, kernel = kernel)
dens$y <- dens$x
dens$x <- mean(range(data$x))
# Compute width if x has multiple values
if (length(unique(data$x)) > 1) {
width <- diff(range(data$x)) * 0.9
}
dens$width <- width
dens
},
compute_panel = function(self, data, scales, width = NULL, bw = "nrd0", adjust = 1,
kernel = "gaussian", trim = TRUE, na.rm = FALSE,
scale = "area", flipped_aes = FALSE) {
data <- flip_data(data, flipped_aes)
data <- ggproto_parent(Stat, self)$compute_panel(
data, scales, width = width, bw = bw, adjust = adjust, kernel = kernel,
trim = trim, na.rm = na.rm
)
# choose how violins are scaled relative to each other
data$violinwidth <- switch(scale,
# area : keep the original densities but scale them to a max width of 1
# for plotting purposes only
area = data$density / max(data$density),
# count: use the original densities scaled to a maximum of 1 (as above)
# and then scale them according to the number of observations
count = data$density / max(data$density) * data$n / max(data$n),
# width: constant width (density scaled to a maximum of 1)
width = data$scaled
)
data$flipped_aes <- flipped_aes
flip_data(data, flipped_aes)
}
)
calc_bw <- function(x, bw) {
if (is.character(bw)) {
if (length(x) < 2)
abort("need at least 2 points to select a bandwidth automatically")
bw <- switch(
to_lower_ascii(bw),
nrd0 = stats::bw.nrd0(x),
nrd = stats::bw.nrd(x),
ucv = stats::bw.ucv(x),
bcv = stats::bw.bcv(x),
sj = ,
`sj-ste` = stats::bw.SJ(x, method = "ste"),
`sj-dpi` = stats::bw.SJ(x, method = "dpi"),
abort("unknown bandwidth rule")
)
}
bw
}
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