Extra Coordinate Systems, 'Geoms', Statistical Transformations, Scales and Fonts for 'ggplot2'
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#' Vertically dodge position
#' @rdname position-dodgev
#' @author @@ggstance authors
#' @note position-dodgev(): unmodified from lionel-/ggstance/R/position-dodgev.R 73f521384ae8ea277db5f7d5a2854004aa18f947
#' @export
position_dodgev <- function(height = NULL) {
ggplot2::ggproto(NULL, PositionDodgev, height = height)
}
#' @rdname position-dodgev
#' @author @@ggstance authors
#' @note PositionDodgev(): based on from lionel-/ggstance/R/position-dodgev.R 73f521384ae8ea277db5f7d5a2854004aa18f947
#' @format NULL
#' @usage NULL
#' @export
PositionDodgev <- ggplot2::ggproto("PositionDodgev", ggplot2::Position,
required_aes = "y",
height = NULL,
setup_params = function(self, data) {
if (is.null(data$ymin) && is.null(data$ymax) && is.null(self$height)) {
warning("Height not defined. Set with `position_dodgev(height = ?)`",
call. = FALSE)
}
list(height = self$height)
},
compute_panel = function(data, params, scales) {
collidev(data, params$height, "position_dodgev", pos_dodgev, check.height = FALSE)
}
)
#' @rdname position-dodgev
#' @author @@ggstance authors
#' @note pos_dodgev(): unmodified from lionel-/ggstance/R/position-dodgev.R 73f521384ae8ea277db5f7d5a2854004aa18f947
pos_dodgev <- function(df, height) {
n <- length(unique(df$group))
if (n == 1) return(df)
if (!all(c("ymin", "ymax") %in% names(df))) {
df$ymin <- df$y
df$ymax <- df$y
}
d_height <- max(df$ymax - df$ymin)
# df <- data.frame(n = c(2:5, 10, 26), div = c(4, 3, 2.666666, 2.5, 2.2, 2.1))
# ggplot(df, aes(n, div)) + geom_point()
# Have a new group index from 1 to number of groups.
# This might be needed if the group numbers in this set don't include all of 1:n
groupidx <- match(df$group, sort(unique(df$group)))
# Find the center for each group, then use that to calculate ymin and lmax
df$y <- df$y + height * ((groupidx - 0.5) / n - .5)
df$ymin <- df$y - d_height / n / 2
df$ymax <- df$y + d_height / n / 2
df
}
#' @rdname position-dodgev
#' @author @@ggstance authors
#' @note collidev(): based on lionel-/ggstance/R/position.R 73f521384ae8ea277db5f7d5a2854004aa18f947
collidev <- function(data, height = NULL, name, strategy, ..., check.height = TRUE, reverse = FALSE) {
# Determine height
if (!is.null(height)) {
# Width set manually
if (!(all(c("ymin", "ymax") %in% names(data)))) {
data$ymin <- data$y - height / 2
data$ymax <- data$y + height / 2
}
} else {
if (!(all(c("ymin", "ymax") %in% names(data)))) {
data$ymin <- data$y
data$ymax <- data$y
}
# Width determined from data, must be floating point constant
heights <- unique(data$ymax - data$ymin)
heights <- heights[!is.na(heights)]
# # Suppress warning message since it's not reliable
# if (!zero_range(range(heights))) {
# warning(name, " requires constant height: output may be incorrect",
# call. = FALSE)
# }
height <- heights[1]
}
# Reorder by x position, then on group. The default stacking order reverses
# the group in order to match the legend order.
if (reverse) {
data <- data[order(data$ymin, data$group), ]
} else {
data <- data[order(data$ymin, -data$group), ]
}
# Check for overlap
intervals <- as.numeric(t(unique(data[c("ymin", "ymax")])))
intervals <- intervals[!is.na(intervals)]
if (length(unique(intervals)) > 1 & any(diff(scale(intervals)) < -1e-6)) {
warning(name, " requires non-overlapping y intervals", call. = FALSE)
# This is where the algorithm from [L. Wilkinson. Dot plots.
# The American Statistician, 1999.] should be used
}
data$group <- seq_len(nrow(data)) ## reset grouping
if (!is.null(data$xmax)) {
plyr::ddply(data, "ymin", strategy, ..., height = height)
} else if (!is.null(data$x)) {
data$xmax <- data$x
data <- plyr::ddply(data, "ymin", strategy, ..., height = height)
data$x <- data$xmax
data$yend <- data$y ## ALLOW FOR A YEND COLUMN
data
} else {
stop("Neither x nor xmax defined")
}
}