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#' Rectangles
#'
#' `geom_rect()` and `geom_tile()` do the same thing, but are
#' parameterised differently: `geom_rect()` uses the locations of the four
#' corners (`xmin`, `xmax`, `ymin` and `ymax`), while
#' `geom_tile()` uses the center of the tile and its size (`x`,
#' `y`, `width`, `height`). `geom_raster()` is a high
#' performance special case for when all the tiles are the same size.
#'
#' @eval rd_aesthetics("geom", "tile", "Note that `geom_raster()` ignores `colour`.")
#' @inheritParams layer
#' @inheritParams geom_point
#' @inheritParams geom_segment
#' @export
#' @examples
#' # The most common use for rectangles is to draw a surface. You always want
#' # to use geom_raster here because it's so much faster, and produces
#' # smaller output when saving to PDF
#' ggplot(faithfuld, aes(waiting, eruptions)) +
#' geom_raster(aes(fill = density))
#'
#' # Interpolation smooths the surface & is most helpful when rendering images.
#' ggplot(faithfuld, aes(waiting, eruptions)) +
#' geom_raster(aes(fill = density), interpolate = TRUE)
#'
#' # If you want to draw arbitrary rectangles, use geom_tile() or geom_rect()
#' df <- data.frame(
#' x = rep(c(2, 5, 7, 9, 12), 2),
#' y = rep(c(1, 2), each = 5),
#' z = factor(rep(1:5, each = 2)),
#' w = rep(diff(c(0, 4, 6, 8, 10, 14)), 2)
#' )
#' ggplot(df, aes(x, y)) +
#' geom_tile(aes(fill = z), colour = "grey50")
#' ggplot(df, aes(x, y, width = w)) +
#' geom_tile(aes(fill = z), colour = "grey50")
#' ggplot(df, aes(xmin = x - w / 2, xmax = x + w / 2, ymin = y, ymax = y + 1)) +
#' geom_rect(aes(fill = z), colour = "grey50")
#'
#' \donttest{
#' # Justification controls where the cells are anchored
#' df <- expand.grid(x = 0:5, y = 0:5)
#' set.seed(1)
#' df$z <- runif(nrow(df))
#' # default is compatible with geom_tile()
#' ggplot(df, aes(x, y, fill = z)) +
#' geom_raster()
#' # zero padding
#' ggplot(df, aes(x, y, fill = z)) +
#' geom_raster(hjust = 0, vjust = 0)
#'
#' # Inspired by the image-density plots of Ken Knoblauch
#' cars <- ggplot(mtcars, aes(mpg, factor(cyl)))
#' cars + geom_point()
#' cars + stat_bin2d(aes(fill = after_stat(count)), binwidth = c(3,1))
#' cars + stat_bin2d(aes(fill = after_stat(density)), binwidth = c(3,1))
#'
#' cars +
#' stat_density(
#' aes(fill = after_stat(density)),
#' geom = "raster",
#' position = "identity"
#' )
#' cars +
#' stat_density(
#' aes(fill = after_stat(count)),
#' geom = "raster",
#' position = "identity"
#' )
#' }
geom_tile <- function(mapping = NULL, data = NULL,
stat = "identity", position = "identity",
...,
linejoin = "mitre",
na.rm = FALSE,
show.legend = NA,
inherit.aes = TRUE) {
layer(
data = data,
mapping = mapping,
stat = stat,
geom = GeomTile,
position = position,
show.legend = show.legend,
inherit.aes = inherit.aes,
params = list2(
linejoin = linejoin,
na.rm = na.rm,
...
)
)
}
#' @rdname ggplot2-ggproto
#' @format NULL
#' @usage NULL
#' @export
#' @include geom-rect.r
GeomTile <- ggproto("GeomTile", GeomRect,
extra_params = c("na.rm"),
setup_data = function(data, params) {
data$width <- data$width %||% params$width %||% resolution(data$x, FALSE)
data$height <- data$height %||% params$height %||% resolution(data$y, FALSE)
transform(data,
xmin = x - width / 2, xmax = x + width / 2, width = NULL,
ymin = y - height / 2, ymax = y + height / 2, height = NULL
)
},
default_aes = aes(fill = "grey20", colour = NA, linewidth = 0.1, linetype = 1,
alpha = NA, width = NA, height = NA),
required_aes = c("x", "y"),
# These aes columns are created by setup_data(). They need to be listed here so
# that GeomRect$handle_na() properly removes any bars that fall outside the defined
# limits, not just those for which x and y are outside the limits
non_missing_aes = c("xmin", "xmax", "ymin", "ymax"),
draw_key = draw_key_polygon
)
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