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.
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
)
Set of aesthetic mappings created by aes()
. If specified and
inherit.aes = TRUE
(the default), it is combined with the default mapping
at the top level of the plot. You must supply mapping
if there is no plot
mapping.
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. A function
can be created
from a formula
(e.g. ~ head(.x, 10)
).
The statistical transformation to use on the data for this layer.
When using a geom_*()
function to construct a layer, the stat
argument can be used the override the default coupling between geoms and
stats. The stat
argument accepts the following:
A Stat
ggproto subclass, for example StatCount
.
A string naming the stat. To give the stat as a string, strip the
function name of the stat_
prefix. For example, to use stat_count()
,
give the stat as "count"
.
For more information and other ways to specify the stat, see the layer stat documentation.
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 position
argument accepts the following:
The result of calling a position function, such as position_jitter()
.
This method allows for passing extra arguments to the position.
A string naming the position adjustment. To give the position as a
string, strip the function name of the position_
prefix. For example,
to use position_jitter()
, give the position as "jitter"
.
For more information and other ways to specify the position, see the layer position documentation.
Other arguments passed on to layer()
's params
argument. These
arguments broadly fall into one of 4 categories below. Notably, further
arguments to the position
argument, or aesthetics that are required
can not be passed through ...
. Unknown arguments that are not part
of the 4 categories below are ignored.
Static aesthetics that are not mapped to a scale, but are at a fixed
value and apply to the layer as a whole. For example, colour = "red"
or linewidth = 3
. The geom's documentation has an Aesthetics
section that lists the available options. The 'required' aesthetics
cannot be passed on to the params
. Please note that while passing
unmapped aesthetics as vectors is technically possible, the order and
required length is not guaranteed to be parallel to the input data.
When constructing a layer using
a stat_*()
function, the ...
argument can be used to pass on
parameters to the geom
part of the layer. An example of this is
stat_density(geom = "area", outline.type = "both")
. The geom's
documentation lists which parameters it can accept.
Inversely, when constructing a layer using a
geom_*()
function, the ...
argument can be used to pass on parameters
to the stat
part of the layer. An example of this is
geom_area(stat = "density", adjust = 0.5)
. The stat's documentation
lists which parameters it can accept.
The key_glyph
argument of layer()
may also be passed on through
...
. This can be one of the functions described as
key glyphs, to change the display of the layer in the legend.
Number of contour bins. Overridden by breaks
.
The width of the contour bins. Overridden by bins
.
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
and bins
. By default, this is a vector of length
ten with pretty()
breaks.
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 to display the data for this layer.
When using a stat_*()
function to construct a layer, the geom
argument
can be used to override the default coupling between stats and geoms. The
geom
argument accepts the following:
A Geom
ggproto subclass, for example GeomPoint
.
A string naming the geom. To give the geom as a string, strip the
function name of the geom_
prefix. For example, to use geom_point()
,
give the geom as "point"
.
For more information and other ways to specify the geom, see the layer geom documentation.
geom_contour()
understands the following aesthetics (required aesthetics are in bold):
x
y
alpha
colour
group
linetype
linewidth
weight
Learn more about setting these aesthetics in vignette("ggplot2-specs")
.
geom_contour_filled()
understands the following aesthetics (required aesthetics are in bold):
x
y
alpha
colour
fill
group
linetype
linewidth
subgroup
Learn more about setting these aesthetics in vignette("ggplot2-specs")
.
stat_contour()
understands the following aesthetics (required aesthetics are in bold):
x
y
z
group
order
Learn more about setting these aesthetics in vignette("ggplot2-specs")
.
stat_contour_filled()
understands the following aesthetics (required aesthetics are in bold):
x
y
z
fill
group
order
Learn more about setting these aesthetics in vignette("ggplot2-specs")
.
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).
z
After contouring, the z values of individual data points are no longer available.
geom_density_2d()
: 2d density contours
# 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")
# }
Run the code above in your browser using DataLab