
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.
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)
The data to be displayed in this layer. There are three options:
If NULL
, the default, the data is inherited from the plot
data as specified in the call to ggplot()
.
A data.frame
, or other object, will override the plot
data. All objects will be fortified to produce a data frame. See
fortify()
for which variables will be created.
A function
will be called with a single argument,
the plot data. The return value must be a data.frame
, and
will be used as the layer data.
The statistical transformation to use on the data for this layer, as a string.
Position adjustment, either as a string, or the result of a call to a position adjustment function.
Other arguments passed on to layer()
. These are
often aesthetics, used to set an aesthetic to a fixed value, like
colour = "red"
or size = 3
. They may also be parameters
to the paired geom/stat.
Line end style (round, butt, square).
Line join style (round, mitre, bevel).
Line mitre limit (number greater than 1).
If FALSE
, the default, missing values are removed with
a warning. If TRUE
, missing values are silently removed.
logical. Should this layer be included in the legends?
NA
, the default, includes if any aesthetics are mapped.
FALSE
never includes, and TRUE
always includes.
It can also be a named logical vector to finely select the aesthetics to
display.
If FALSE
, overrides the default aesthetics,
rather than combining with them. This is most useful for helper functions
that define both data and aesthetics and shouldn't inherit behaviour from
the default plot specification, e.g. borders()
.
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
# NOT RUN {
#' # 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()
# }
# NOT RUN {
# 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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