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#' Discretized colourbar guide
#'
#' This guide is version of [guide_colourbar()] for binned colour and fill
#' scales. It shows areas between breaks as a single constant colour instead of
#' the gradient known from the colourbar counterpart.
#'
#' @param even.steps Should the rendered size of the bins be equal, or should
#' they be proportional to their length in the data space? Defaults to `TRUE`
#' @param show.limits Logical. Should the limits of the scale be shown with
#' labels and ticks. Default is `NULL` meaning it will take the value from the
#' scale. This argument is ignored if `labels` is given as a vector of
#' values. If one or both of the limits is also given in `breaks` it will be
#' shown irrespective of the value of `show.limits`.
#' @param ticks A logical specifying if tick marks on the colourbar should be
#' visible.
#' @inheritDotParams guide_colourbar -nbin -raster -ticks -available_aes
#'
#' @inheritSection guide_bins Use with discrete scale
#'
#' @return A guide object
#' @export
#'
#' @family guides
#' @examples
#' df <- expand.grid(X1 = 1:10, X2 = 1:10)
#' df$value <- df$X1 * df$X2
#'
#' p <- ggplot(df, aes(X1, X2)) + geom_tile(aes(fill = value))
#'
#' # Coloursteps guide is the default for binned colour scales
#' p + scale_fill_binned()
#'
#' # By default each bin in the guide is the same size irrespectively of how
#' # their sizes relate in data space
#' p + scale_fill_binned(breaks = c(10, 25, 50))
#'
#' # This can be changed with the `even.steps` argument
#' p + scale_fill_binned(
#' breaks = c(10, 25, 50),
#' guide = guide_coloursteps(even.steps = FALSE)
#' )
#'
#' # By default the limits is not shown, but this can be changed
#' p + scale_fill_binned(guide = guide_coloursteps(show.limits = TRUE))
#'
#' # (can also be set in the scale)
#' p + scale_fill_binned(show.limits = TRUE)
#'
guide_coloursteps <- function(even.steps = TRUE, show.limits = NULL, ticks = FALSE, ...) {
guide <- guide_colourbar(raster = FALSE, ticks = ticks, nbin = 100, ...)
guide$even.steps <- even.steps
guide$show.limits <- show.limits
class(guide) <- c('colorsteps', class(guide))
guide
}
#' @export
#' @rdname guide_coloursteps
guide_colorsteps <- guide_coloursteps
#' @export
guide_train.colorsteps <- function(guide, scale, aesthetic = NULL) {
breaks <- scale$get_breaks()
breaks <- breaks[!is.na(breaks)]
show_limits <- guide$show.limits %||% scale$show.limits %||% FALSE
if (show_limits && (is.character(scale$labels) || is.numeric(scale$labels))) {
cli::cli_warn(c(
"{.arg show.limits} is ignored when {.arg labels} are given as a character vector",
"i" = "Either add the limits to {.arg breaks} or provide a function for {.arg labels}"
))
show_limits <- FALSE
}
if (guide$even.steps || !is.numeric(breaks)) {
if (length(breaks) == 0 || all(is.na(breaks))) {
return()
}
if (is.numeric(breaks)) {
limits <- scale$get_limits()
if (!is.numeric(scale$breaks)) {
breaks <- breaks[!breaks %in% limits]
}
all_breaks <- unique0(c(limits[1], breaks, limits[2]))
bin_at <- all_breaks[-1] - diff(all_breaks) / 2
} else {
# If the breaks are not numeric it is used with a discrete scale. We check
# if the breaks follow the allowed format "(<lower>, <upper>]", and if it
# does we convert it into bin specs
if (!guide$even.steps) {
cli::cli_warn("{.code even.steps = FALSE} is not supported when used with a discrete scale")
}
bin_at <- breaks
breaks_num <- as.character(breaks)
breaks_num <- strsplit(gsub("\\(|\\)|\\[|\\]", "", breaks_num), ",\\s?")
breaks_num <- as.numeric(unlist(breaks_num))
if (anyNA(breaks_num)) {
cli::cli_abort(c(
"Breaks not formatted correctly for a bin legend.",
"i" = "Use {.code (<lower>, <upper>]} format to indicate bins"
))
}
all_breaks <- breaks_num[c(1, seq_along(breaks) * 2)]
limits <- all_breaks[c(1, length(all_breaks))]
breaks <- all_breaks[-c(1, length(all_breaks))]
}
ticks <- data_frame(
scale$map(breaks),
.name_repair = ~ aesthetic %||% scale$aesthetics[1]
)
ticks$.value <- seq_along(breaks) - 0.5
ticks$.label <- scale$get_labels(breaks)
guide$nbin <- length(breaks) + 1L
if (breaks[1] %in% limits) {
ticks$.value <- ticks$.value - 1L
ticks[[1]][1] <- NA
guide$nbin <- guide$nbin - 1L
}
if (breaks[length(breaks)] %in% limits) {
ticks[[1]][nrow(ticks)] <- NA
guide$nbin <- guide$nbin - 1L
}
guide$key <- ticks
guide$bar <- data_frame0(
colour = scale$map(bin_at),
value = seq_along(bin_at) - 1,
.size = length(bin_at)
)
if (guide$reverse) {
guide$key <- guide$key[nrow(guide$key):1, ]
guide$bar <- guide$bar[nrow(guide$bar):1, ]
}
guide$hash <- with(guide, hash(list(title, key$.label, bar, name)))
} else {
guide <- NextMethod()
limits <- scale$get_limits()
}
if (show_limits) {
edges <- rescale(c(0, 1), to = guide$bar$value[c(1, nrow(guide$bar))], from = c(0.5, guide$nbin - 0.5) / guide$nbin)
if (guide$reverse) edges <- rev(edges)
guide$key <- guide$key[c(NA, seq_len(nrow(guide$key)), NA), , drop = FALSE]
guide$key$.value[c(1, nrow(guide$key))] <- edges
guide$key$.label[c(1, nrow(guide$key))] <- scale$get_labels(limits)
if (guide$key$.value[1] == guide$key$.value[2]) {
guide$key <- guide$key[-1,]
}
if (guide$key$.value[nrow(guide$key)-1] == guide$key$.value[nrow(guide$key)]) {
guide$key <- guide$key[-nrow(guide$key),]
}
}
guide
}
#' Calculate the default hjust and vjust settings depending on legend
#' direction and position.
#'
#' @noRd
label_just_defaults.colorbar <- function(direction, position) {
if (direction == "horizontal") {
switch(
position,
"top" = list(hjust = 0.5, vjust = 0),
list(hjust = 0.5, vjust = 1)
)
}
else {
switch(
position,
"left" = list(hjust = 1, vjust = 0.5),
list(hjust = 0, vjust = 0.5)
)
}
}
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