geom_raster | R Documentation |
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, and no
pattern fills are applied.
geom_raster(
mapping = NULL,
data = NULL,
stat = "identity",
position = "identity",
...,
hjust = 0.5,
vjust = 0.5,
interpolate = FALSE,
na.rm = FALSE,
show.legend = NA,
inherit.aes = TRUE
)
geom_rect(
mapping = NULL,
data = NULL,
stat = "identity",
position = "identity",
...,
linejoin = "mitre",
na.rm = FALSE,
show.legend = NA,
inherit.aes = TRUE
)
geom_tile(
mapping = NULL,
data = NULL,
stat = "identity",
position = "identity",
...,
linejoin = "mitre",
na.rm = FALSE,
show.legend = NA,
inherit.aes = TRUE
)
mapping |
Set of aesthetic mappings created by |
data |
The data to be displayed in this layer. There are three options: If A A |
stat |
The statistical transformation to use on the data for this layer.
When using a
|
position |
A position adjustment to use on the data for this layer. This
can be used in various ways, including to prevent overplotting and
improving the display. The
|
... |
Other arguments passed on to
|
hjust , vjust |
horizontal and vertical justification of the grob. Each justification value should be a number between 0 and 1. Defaults to 0.5 for both, centering each pixel over its data location. |
interpolate |
If |
na.rm |
If |
show.legend |
logical. Should this layer be included in the legends?
|
inherit.aes |
If |
linejoin |
Line join style (round, mitre, bevel). |
geom_rect()
and geom_tile()
's respond differently to scale
transformations due to their parameterisation. In geom_rect()
, the scale
transformation is applied to the corners of the rectangles. In geom_tile()
,
the transformation is applied only to the centres and its size is determined
after transformation.
geom_tile()
understands the following aesthetics (required aesthetics are in bold):
x
y
alpha
colour
fill
group
height
linetype
linewidth
width
Note that geom_raster()
ignores colour
.
Learn more about setting these aesthetics in vignette("ggplot2-specs")
.
# 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")
# 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_bin_2d(aes(fill = after_stat(count)), binwidth = c(3,1))
cars + stat_bin_2d(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"
)
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