geom_polygonraster {ggh4x} | R Documentation |
geom_polygonraster
takes data that describes a raster with pixels of
the same size and reparametrises the data as a polygon. This allows for more
flexible transformations of the data, but comes at an efficiency cost.
geom_polygonraster( mapping = NULL, data = NULL, stat = "identity", position = position_lineartrans(), ..., hjust = 0.5, vjust = 0.5, 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, either as a |
position |
Position adjustment, either as a string naming the adjustment
(e.g. |
... |
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. |
na.rm |
If |
show.legend |
logical. Should this layer be included in the legends?
|
inherit.aes |
If |
For each pixel in a raster, makes a vertex for each of the four
corner points. These coordinates can then by transformed by
coord
-functions such as ggplot2::coord_polar()
or
position
-functions such as
position_lineartrans()
. Currently substitutes group
aesthetics right before drawing in favour of pixel identifiers.
A Layer ggproto object.
geom_raster()
understands the following aesthetics (required
aesthetics are in bold):
x
y
fill
alpha
group
# Combining with coord_polar() ggplot(faithfuld, aes(waiting, eruptions)) + geom_polygonraster(aes(fill = density)) + coord_polar() # Combining with linear transformations df <- data.frame(x = row(volcano)[TRUE], y = col(volcano)[TRUE], z = volcano[TRUE]) ggplot(df, aes(x, y, fill = z)) + geom_polygonraster(position = position_lineartrans(angle = 30, shear = c(1, 0)))