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)
NULL, the default, the data is inherited from the plot
data as specified in the call to
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.
function will be called with a single argument,
the plot data. The return value must be a
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), removes missing values with a warning. If
TRUEsilently removes missing values.
NA, the default, includes if any aesthetics are mapped.
FALSEnever includes, and
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.
geom_contourunderstands the following aesthetics (required aesthetics are in bold):
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")