Description Usage Arguments Aesthetics Computed variables See Also Examples
ggplot2 can not draw true 3d surfaces, but you can use geom_contour
and geom_tile()
to visualise 3d surfaces in 2d. To be a valid
surface, the data must contain only a single row for each unique combination
of the variables mapped to the x
and y
aesthetics. Contouring
tends to work best when x
and y
form a (roughly) evenly
spaced grid. If your data is not evenly spaced, you may want to interpolate
to a grid before visualising.
1 2 3 4 5 6 7 8 | geom_contour(mapping = NULL, data = NULL, stat = "contour",
position = "identity", ..., lineend = "butt", linejoin = "round",
linemitre = 10, na.rm = FALSE, show.legend = NA,
inherit.aes = TRUE)
stat_contour(mapping = NULL, data = NULL, geom = "contour",
position = "identity", ..., 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, as a string. |
position |
Position adjustment, either as a string, or the result of a call to a position adjustment function. |
... |
Other arguments passed on to |
lineend |
Line end style (round, butt, square). |
linejoin |
Line join style (round, mitre, bevel). |
linemitre |
Line mitre limit (number greater than 1). |
na.rm |
If |
show.legend |
logical. Should this layer be included in the legends?
|
inherit.aes |
If |
geom |
The geometric object to use display the data |
geom_contour()
understands the following aesthetics (required aesthetics are in bold):
x
y
alpha
colour
group
linetype
size
weight
Learn more about setting these aesthetics in vignette("ggplot2-specs")
.
height of contour
height of contour, scaled to maximum of 1
contour piece (an integer)
geom_density_2d()
: 2d density contours
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | #' # Basic plot
v <- ggplot(faithfuld, aes(waiting, eruptions, z = density))
v + geom_contour()
# Or compute from raw data
ggplot(faithful, aes(waiting, eruptions)) +
geom_density_2d()
# Setting bins creates evenly spaced contours in the range of the data
v + geom_contour(bins = 2)
v + geom_contour(bins = 10)
# Setting binwidth does the same thing, parameterised by the distance
# between contours
v + geom_contour(binwidth = 0.01)
v + geom_contour(binwidth = 0.001)
# Other parameters
v + geom_contour(aes(colour = stat(level)))
v + geom_contour(colour = "red")
v + geom_raster(aes(fill = density)) +
geom_contour(colour = "white")
|
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