ggplot2 can not draw true 3D surfaces, but you can use geom_contour()
,
geom_contour_filled()
, and geom_tile()
to visualise 3D surfaces in 2D.
These functions require regular data, where the x
and y
coordinates
form an equally spaced grid, and each combination of x
and y
appears
once. Missing values of z
are allowed, but contouring will only work for
grid points where all four corners are non-missing. If you have irregular
data, you'll need to first interpolate on to a grid before visualising,
using interp::interp()
, akima::bilinear()
, or similar.
Usage
geom_contour(
mapping = NULL,
data = NULL,
stat = "contour",
position = "identity",
...,
bins = NULL,
binwidth = NULL,
breaks = NULL,
lineend = "butt",
linejoin = "round",
linemitre = 10,
na.rm = FALSE,
show.legend = NA,
inherit.aes = TRUE
)
geom_contour_filled(
mapping = NULL,
data = NULL,
stat = "contour_filled",
position = "identity",
...,
bins = NULL,
binwidth = NULL,
breaks = NULL,
na.rm = FALSE,
show.legend = NA,
inherit.aes = TRUE
)
stat_contour(
mapping = NULL,
data = NULL,
geom = "contour",
position = "identity",
...,
bins = NULL,
binwidth = NULL,
breaks = NULL,
na.rm = FALSE,
show.legend = NA,
inherit.aes = TRUE
)
stat_contour_filled(
mapping = NULL,
data = NULL,
geom = "contour_filled",
position = "identity",
...,
bins = NULL,
binwidth = NULL,
breaks = NULL,
na.rm = FALSE,
show.legend = NA,
inherit.aes = TRUE
)
Arguments
- mapping
Set of aesthetic mappings created by
aes()
. If specified andinherit.aes = TRUE
(the default), it is combined with the default mapping at the top level of the plot. You must supplymapping
if there is no plot mapping.- data
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 toggplot()
.A
data.frame
, or other object, will override the plot data. All objects will be fortified to produce a data frame. Seefortify()
for which variables will be created.A
function
will be called with a single argument, the plot data. The return value must be adata.frame
, and will be used as the layer data. Afunction
can be created from aformula
(e.g.~ head(.x, 10)
).- stat
The statistical transformation to use on the data for this layer, either as a
ggproto
Geom
subclass or as a string naming the stat stripped of thestat_
prefix (e.g."count"
rather than"stat_count"
)- position
Position adjustment, either as a string naming the adjustment (e.g.
"jitter"
to useposition_jitter
), or the result of a call to a position adjustment function. Use the latter if you need to change the settings of the adjustment.- ...
Other arguments passed on to
layer()
. These are often aesthetics, used to set an aesthetic to a fixed value, likecolour = "red"
orsize = 3
. They may also be parameters to the paired geom/stat.- bins
Number of contour bins. Overridden by
breaks
.- binwidth
The width of the contour bins. Overridden by
bins
.- breaks
One of:
Numeric vector to set the contour breaks
A function that takes the range of the data and binwidth as input and returns breaks as output. A function can be created from a formula (e.g. ~ fullseq(.x, .y)).
Overrides
binwidth
andbins
. By default, this is a vector of length ten withpretty()
breaks.- 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
FALSE
, the default, missing values are removed with a warning. IfTRUE
, missing values are silently removed.- show.legend
logical. Should this layer be included in the legends?
NA
, the default, includes if any aesthetics are mapped.FALSE
never includes, andTRUE
always includes. It can also be a named logical vector to finely select the aesthetics to display.- inherit.aes
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()
.- geom
The geometric object to use to display the data, either as a
ggproto
Geom
subclass or as a string naming the geom stripped of thegeom_
prefix (e.g."point"
rather than"geom_point"
)
Aesthetics
geom_contour()
understands the following aesthetics (required aesthetics are in bold):
Learn more about setting these aesthetics in vignette("ggplot2-specs")
.
geom_contour_filled()
understands the following aesthetics (required aesthetics are in bold):
Learn more about setting these aesthetics in vignette("ggplot2-specs")
.
stat_contour()
understands the following aesthetics (required aesthetics are in bold):
Learn more about setting these aesthetics in vignette("ggplot2-specs")
.
stat_contour_filled()
understands the following aesthetics (required aesthetics are in bold):
Learn more about setting these aesthetics in vignette("ggplot2-specs")
.
Computed variables
These are calculated by the 'stat' part of layers and can be accessed with delayed evaluation. The computed variables differ somewhat for contour lines (computed by stat_contour()
) and contour bands (filled contours, computed by stat_contour_filled()
). The variables nlevel
and piece
are available for both, whereas level_low
, level_high
, and level_mid
are only available for bands. The variable level
is a numeric or a factor depending on whether lines or bands are calculated.
after_stat(level)
Height of contour. For contour lines, this is a numeric vector that represents bin boundaries. For contour bands, this is an ordered factor that represents bin ranges.after_stat(level_low)
,after_stat(level_high)
,after_stat(level_mid)
(contour bands only) Lower and upper bin boundaries for each band, as well as the mid point between boundaries.after_stat(nlevel)
Height of contour, scaled to a maximum of 1.after_stat(piece)
Contour piece (an integer).
Dropped variables
z
After contouring, the z values of individual data points are no longer available.
See also
geom_density_2d()
: 2d density contours
Examples
# 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()
# \donttest{
# use geom_contour_filled() for filled contours
v + geom_contour_filled()
# Setting bins creates evenly spaced contours in the range of the data
v + geom_contour(bins = 3)
v + geom_contour(bins = 5)
# 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 = after_stat(level)))
v + geom_contour(colour = "red")
v + geom_raster(aes(fill = density)) +
geom_contour(colour = "white")
# }