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# Main function -----------------------------------------------------------
#' Segregating overlapping ranges
#'
#' @description One-dimensional ranged data in the x-direction is segregated in
#' the y-direction such that no overlap in two-dimensional space occurs. This
#' positioning works best when no relevant information is plotted in the
#' y-direction.
#'
#' @param extend a `numeric` of length 1 indicating how far a range should
#' be extended in total for calculating overlaps. Setting this argument to a
#' positive number leaves some space between ranges in the same bin.
#' @param stepsize a `numeric` of length 1 that determines how much space
#' is added between bins in the y-direction. A positive value grows the bins
#' from bottom to top, while a negative value grows the bins from top to
#' bottom.
#'
#' @export
#'
#' @return A *PositionDisjointRanges* object.
#'
#' @details An object is considered disjoint from a second object when the range
#' between their `xmin` and `xmax` coordinates don't overlap.
#' Objects that overlap are assigned to different bins in the y-direction,
#' whereby lower bins are filled first. This way, information in the
#' x-direction is preserved and different objects can be discerned.
#'
#' Note that this positioning is only particularly useful when y-coordinates
#' do not encode relevant information. Geoms that pair well with this
#' positioning are [`geom_rect()`][ggplot2::geom_tile] and
#' [ggplot2::geom_tile()].
#'
#' This positioning function was inspired by the `disjointBins()`
#' function in the `IRanges` package, but has been written such that it
#' accepts any numeric input next to solely integer input.
#'
#' @seealso The `disjointBins` function the Bioconductor IRanges package.
#'
#' @examples
#' # Even though geom_tile() is parametrised by middle-x values, it is
#' # internally converted to xmin, xmax, ymin, ymax parametrisation so the
#' # positioning still works.
#'
#' ggplot() +
#' geom_tile(aes(x = rnorm(200), y = 0),
#' width = 0.2, height = 0.9,
#' position = position_disjoint_ranges(extend = 0.1))
position_disjoint_ranges <- function(extend = 1, stepsize = 1) {
ggproto(NULL, PositionDisjointRanges, extend = extend, stepsize = stepsize)
}
# ggproto -----------------------------------------------------------------
#' @usage NULL
#' @format NULL
#' @export
#' @rdname ggh4x_extensions
PositionDisjointRanges <- ggplot2::ggproto(
"PositionDisjointRanges",
ggplot2::Position,
extend = NULL,
stepsize = NULL,
required_aes = c("xmin", "xmax", "ymin", "ymax"),
setup_params = function(self, data) {
if (is.null(data$xmin) || is.null(data$xmax)) {
cli::cli_warn(c(
"Undefined ranges in the x-direction.",
i = "Please supply {.field xmin} and {.field xmax}."
))
}
list(extend = self$extend,
stepsize = self$stepsize)
},
compute_panel = function(data, params, scales) {
# Simplify groups to ranges
if (length(unique(data[["group"]])) > 1) {
group <- data$group
ranges <- by(data, data$group, function(dat){
c(min(dat$xmin), max(dat$xmax), dat$group[1])
})
ranges <- do.call(rbind, ranges)
ranges <- setNames(as.data.frame(ranges),
c("xmin", "xmax", "group"))
} else if (all(data[["group"]] == -1)){
ranges <- cbind(data[, c("xmin", "xmax")],
group = row(data)[, 1])
group <- ranges$group
} else {
return(data)
}
# Extend and sort ranges
ranges$xmin <- ranges$xmin - 0.5 * params$extend
ranges$xmax <- ranges$xmax + 0.5 * params$extend
ord <- order(ranges$xmin)
ranges <- ranges[ord, ]
# Perform disjoint bins operation similar to IRanges::disjointBins(), but
# generalized to any ranged numeric data, not just integers.
track_bins <- ranges$xmax[1]
ranges$bin <- c(1, vapply(tail(seq_along(ord), -1), function(i) {
dat <- ranges[i, ]
j <- which(track_bins < dat$xmin)
if (length(j) > 0) {
ans <- j[1]
# If a bin is available, update bin
ends <- track_bins
ends[ans] <- dat$xmax
track_bins <<- ends
} else {
# Else, make new bin
track_bins <<- c(track_bins, dat$xmax)
ans <- length(track_bins)
}
return(ans)
}, integer(1)))
# Transform
map <- match(group, ranges$group)
if (all(c("ymin", "ymax") %in% names(data))) {
data$ymax <- data$ymax + params$stepsize * (ranges$bin[map] - 1)
data$ymin <- data$ymin + params$stepsize * (ranges$bin[map] - 1)
}
return(data)
}
)
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