#' @title Vertically dodge position
#' @param height numeric, height of vertical dodge, Default: NULL
#' @examples
#'
#' if(interactive()){
#'
#' dat <- data.frame(
#' trt = c(LETTERS[1:5], "D"),
#' l = c(20, 40, 10, 30, 50, 40),
#' r = c(70, 50, 30, 60, 80, 70)
#' )
#'
#' ggplot(dat, aes(y=trt, x=l, xend=r)) +
#' geom_dumbbell(size=3, color="#e3e2e1",
#' colour_x = "#5b8124", colour_xend = "#bad744",
#' dot_guide=TRUE, dot_guide_size=0.25,
#' position=position_dodgev(height=0.8)) +
#' labs(x=NULL, y=NULL, title="ggplot2 geom_dumbbell with dot guide") +
#' theme_minimal() +
#' theme(panel.grid.major.x=element_line(size=0.05))
#'
#' }
#'
#' @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
#' @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$height, "position_dodgev", pos_dodgev, check.height = FALSE)
}
)
pos_dodgev <- function(df, height) {
n <- length(unique(df$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
}
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")
}
}
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