#' @include stat-.r
NULL
#' Lines: horizontal, vertical, and specified by slope and intercept.
#'
#' These paired geoms and stats add straight lines to a plot, either
#' horizontal, vertical or specified by slope and intercept. These are useful
#' for annotating plots.
#'
#' These geoms act slightly different to other geoms. You can supply the
#' parameters in two ways: either as arguments to the layer function,
#' or via aesthetics. If you use arguments, e.g.
#' \code{geom_abline(intercept = 0, slope = 1)}, then behind the scenes
#' the geom makes a new data frame containing just the data you've supplied.
#' That means that the lines will be the same in all facets; if you want them
#' to vary across facets, construct the data frame yourself and use aesthetics.
#'
#' Unlike most other geoms, these geoms do not inherit aesthetics from the plot
#' default, because they do not understand x and y aesthetics which are
#' commonly set in the plot. They also do not affect the x and y scales.
#'
#' @section Aesthetics:
#' These geoms are drawn using with \code{\link{geom_line}} so support the
#' same aesthetics: alpha, colour, linetype and size. They also each have
#' aesthetics that control the position of the line:
#'
#' \itemize{
#' \item \code{geom_vline}: \code{xintercept}
#' \item \code{geom_hline}: \code{yintercept}
#' \item \code{geom_abline}: \code{slope} and \code{intercept}
#' }
#'
#' @seealso See \code{\link{geom_segment}} for a more general approach to
#' adding straight line segments to a plot.
#' @inheritParams layer
#' @inheritParams geom_point
#' @param xintercept,yintercept,slope,intercept Parameters that control the
#' position of the line. If these are set, \code{data}, \code{mapping} and
#' \code{show.legend} are overridden
#' @export
#' @examples
#' p <- ggplot(mtcars, aes(wt, mpg)) + geom_point()
#'
#' # Fixed values
#' p + geom_vline(xintercept = 5)
#' p + geom_vline(xintercept = 1:5)
#' p + geom_hline(yintercept = 20)
#'
#' p + geom_abline() # Can't see it - outside the range of the data
#' p + geom_abline(intercept = 20)
#'
#' # Calculate slope and intercept of line of best fit
#' coef(lm(mpg ~ wt, data = mtcars))
#' p + geom_abline(intercept = 37, slope = -5)
#' # But this is easier to do with geom_smooth:
#' p + geom_smooth(method = "lm", se = FALSE)
#'
#' # To show different lines in different facets, use aesthetics
#' p <- ggplot(mtcars, aes(mpg, wt)) +
#' geom_point() +
#' facet_wrap(~ cyl)
#'
#' mean_wt <- data.frame(cyl = c(4, 6, 8), wt = c(2.28, 3.11, 4.00))
#' p + geom_hline(aes(yintercept = wt), mean_wt)
#'
#' # You can also control other aesthetics
#' ggplot(mtcars, aes(mpg, wt, colour = wt)) +
#' geom_point() +
#' geom_hline(aes(yintercept = wt, colour = wt), mean_wt) +
#' facet_wrap(~ cyl)
geom_abline <- function(mapping = NULL, data = NULL,
...,
slope,
intercept,
na.rm = FALSE,
show.legend = NA) {
# If nothing set, default to y = x
if (missing(mapping) && missing(slope) && missing(intercept)) {
slope <- 1
intercept <- 0
}
# Act like an annotation
if (!missing(slope) || !missing(intercept)) {
if (missing(slope)) slope <- 1
if (missing(intercept)) intercept <- 0
data <- data.frame(intercept = intercept, slope = slope)
mapping <- aes(intercept = intercept, slope = slope)
show.legend <- FALSE
}
layer(
data = data,
mapping = mapping,
stat = StatIdentity,
geom = GeomAbline,
position = PositionIdentity,
show.legend = show.legend,
inherit.aes = FALSE,
params = list(
na.rm = na.rm,
...
)
)
}
#' @rdname animint2-gganimintproto
#' @format NULL
#' @usage NULL
#' @export
GeomAbline <- gganimintproto("GeomAbline", Geom,
draw_panel = function(data, panel_scales, coord) {
ranges <- coord$range(panel_scales)
data$x <- ranges$x[1]
data$xend <- ranges$x[2]
data$y <- ranges$x[1] * data$slope + data$intercept
data$yend <- ranges$x[2] * data$slope + data$intercept
GeomSegment$draw_panel(unique(data), panel_scales, coord)
},
pre_process = function(g, g.data, ranges) {
range.mats <- list()
for(xy in c("x","y")){
range.mats[[xy]] <- do.call(rbind, lapply(ranges, "[[", paste0(xy, ".range")))[g.data$PANEL,,drop=FALSE]
}
suffix.list <- c("","end")
for(idx in seq_along(suffix.list)){
suffix <- suffix.list[[idx]]
maybe.x <- range.mats$x[,idx]
maybe.y <- maybe.x*g.data$slope+g.data$intercept
inv <- function(y)(y-g.data$intercept)/g.data$slope
g.data[[paste0("x",suffix)]] <- ifelse(
maybe.y < range.mats$y[,1], inv(range.mats$y[,1]), ifelse(
maybe.y > range.mats$y[,2], inv(range.mats$y[,2]), maybe.x))
g.data[[paste0("y",suffix)]] <- ifelse(
maybe.y < range.mats$y[,1], range.mats$y[,1], ifelse(
maybe.y > range.mats$y[,2], range.mats$y[,2], maybe.y))
}
## ggplot2 defaults to adding a group aes for ablines!
## Remove it since it is meaningless.
g$aes <- g$aes[names(g$aes)!="group"]
g.data <- g.data[! names(g.data) %in% c("slope", "intercept")]
g$geom <- "segment"
return(list(g = g, g.data = g.data))
},
default_aes = aes(colour = "black", size = 0.5, linetype = 1, alpha = NA),
required_aes = c("slope", "intercept"),
draw_key = draw_key_abline
)
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