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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.
#' @param drop Whether to discard groups with less than 2 observations
#' (`TRUE`, default) or keep such groups for position adjustment purposes
#' (`FALSE`).
#'
#' @eval rd_computed_vars(
#' density = "Density estimate.",
#' scaled = "Density estimate, scaled to a maximum of 1.",
#' count = "Density * number of points - probably useless for violin
#' plots.",
#' violinwidth = "Density scaled for the violin plot, according to area,
#' counts or to a constant maximum width.",
#' n = "Number of points.",
#' 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",
drop = TRUE,
na.rm = FALSE,
orientation = NA,
show.legend = NA,
inherit.aes = TRUE,
bounds = c(-Inf, Inf)) {
scale <- arg_match0(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 = list2(
bw = bw,
adjust = adjust,
kernel = kernel,
trim = trim,
scale = scale,
drop = drop,
na.rm = na.rm,
bounds = bounds,
...
)
)
}
#' @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$flipped_aes <- has_flipped_aes(data, params, main_is_orthogonal = TRUE, group_has_equal = TRUE)
params
},
extra_params = c("na.rm", "orientation"),
compute_group = function(self, data, scales, width = NULL, bw = "nrd0", adjust = 1,
kernel = "gaussian", trim = TRUE, na.rm = FALSE,
drop = TRUE, flipped_aes = FALSE, bounds = c(-Inf, Inf)) {
if (nrow(data) < 2) {
if (isTRUE(drop)) {
cli::cli_warn(c(
"Groups with fewer than two datapoints have been dropped.",
i = paste0(
"Set {.code drop = FALSE} to consider such groups for position ",
"adjustment purposes."
)))
return(data_frame0())
}
ans <- data_frame0(x = data$x, n = nrow(data))
return(ans)
}
range <- range(data$y, na.rm = TRUE)
modifier <- if (trim) 0 else 3
bw <- calc_bw(data$y, bw)
dens <- compute_density(
data$y, data[["weight"]],
from = range[1] - modifier * bw, to = range[2] + modifier * bw,
bw = bw, adjust = adjust, kernel = kernel, bounds = bounds
)
dens$y <- dens$x
# Compute width if x has multiple values
if (vec_unique_count(data$x) > 1) {
dens$x <- mean(range(data$x))
width <- diff(range(data$x)) * 0.9
} else {
# Explicitly repeat to preserve data$x's mapped_discrete class
dens$x <- vec_rep(data$x[1], nrow(dens))
}
dens$width <- width
dens
},
compute_panel = function(self, data, scales, width = NULL, bw = "nrd0", adjust = 1,
kernel = "gaussian", trim = TRUE, na.rm = FALSE,
scale = "area", flipped_aes = FALSE, drop = TRUE,
bounds = c(-Inf, Inf)) {
data <- flip_data(data, flipped_aes)
data <- ggproto_parent(Stat, self)$compute_panel(
data, scales, width = width, bw = bw, adjust = adjust, kernel = kernel,
trim = trim, na.rm = na.rm, drop = drop, bounds = bounds,
)
if (!drop && any(data$n < 2)) {
cli::cli_warn(
"Cannot compute density for groups with fewer than two datapoints."
)
}
# choose how violins are scaled relative to each other
data$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, na.rm = TRUE),
# 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, na.rm = TRUE) *
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)
},
dropped_aes = "weight"
)
calc_bw <- function(x, bw) {
if (is.character(bw)) {
if (length(x) < 2) {
cli::cli_abort("{.arg x} must contain at least 2 elements 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"),
cli::cli_abort("{.var {bw}} is not a valid bandwidth rule.")
)
}
bw
}
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