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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 you 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 = 1, 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)
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.
layer
. These are
often aesthetics, used to set an aesthetic to a fixed value, like
color = "red"
or size = 3
. They may also be parameters
to the paired geom/stat.FALSE
, the default, missing values are removed with
a warning. If TRUE
, missing values are silently removed.NA
, the default, includes if any aesthetics are mapped.
FALSE
never includes, and TRUE
always includes.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_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()
# 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 = ..level..))
v + geom_contour(colour = "red")
v + geom_raster(aes(fill = density)) +
geom_contour(colour = "white")
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