geom_contour_ks | R Documentation |
Contour and filled contour plots for tidy kernel estimates for 2-dimensional data.
geom_contour_ks(mapping=NULL, data=NULL, stat="contour_ks",
position="identity", ..., cont=c(25,50,75), contperc=TRUE,
breaks=NULL, digits=NULL, show.legend=NA, inherit.aes=TRUE)
stat_contour_ks(mapping=NULL, data=NULL, geom="contour_ks",
position="identity", ..., show.legend=NA, inherit.aes=TRUE)
geom_contour_filled_ks(mapping=NULL, data=NULL, stat="contour_filled_ks",
position="identity", ..., cont=c(25,50,75), contperc=TRUE,
breaks=NULL, transp_neutral=NULL, digits=NULL, show.legend=NA,
inherit.aes=TRUE)
stat_contour_filled_ks(mapping=NULL, data=NULL, geom="contour_filled_ks",
position="identity", ..., show.legend=NA, inherit.aes=TRUE)
mapping |
Set of aesthetic mappings created by |
data |
The data to be displayed in this layer. There are three options: If A A |
stat |
The statistical transformation to use on the data for this layer, as a string. |
position |
Position adjustment, either as a string, or the result of a call to a position adjustment function. |
... |
Other arguments passed on to |
cont |
Vector of contour probabilities. Default value is |
contperc |
Deprecated. |
transp_neutral |
Flag to set neutral colour in diverging fill scale to be transparent. |
breaks |
Numeric vector to set the contour breaks e.g. output from |
digits |
Number of significant digits in legend keys. Default is 4. |
show.legend |
logical. Should this layer be included in the legends?
|
inherit.aes |
If |
geom |
The geometric object to use display the data. |
These layer functions are modifications of the standard layer functions ggplot2::geom_contour
, geom_contour_filled
and ggplot2::stat_contour
, stat_contour_filled
. Their usage and output are similar, except that they require a tidy kernel estimate as the input, rather than the observations themselves, and that the underlying choice of the contour levels is different. For most cases, geom_contour_ks
is equivalent to geom_contour(stat="contour_ks")
, and likewise for geom_contour_filled_ks
.
The choice of the contour levels are based on probability contours. A 25%
contour region is the smallest region that contains 25% of the
probability mass defined by the kernel estimate. Probability contours offer a more intuitive approach to selecting the contour levels that reveal the pertinent characteristics of the kernel estimates. See Chacon & Duong (2018, Chapter 2.2). They are specified by the cont
parameter: the default value is cont=c(25,50,75)
, which computes the upper quartile, median and lower quartile probability contours. To display legend labels with the percent symbol, contperc=TRUE
is deprecated. The preferred syntax is after_stat(contperc)
in the aesthetic, though for geom_contour_filled_ks
, it is already the default, and can be omitted. See examples below.
Since these probability contours are computed for each group of the grouping variable in data
, then these relative contour levels are different for each group. To produce a contour plot with fixed contour levels across all groups, then these can be supplied in breaks
: a possible choice is provided by contour_breaks
.
Similar output as the standard layer functions ggplot2::geom_contour
, geom_contour_filled
and ggplot2::stat_contour
, stat_contour_filled
.
Chacon, J.E. & Duong, T. (2018) Multivariate Kernel Smoothing and Its Applications. Chapman & Hall/CRC, Boca Raton.
contour_breaks
library(ggplot2)
data(crabs, package="MASS")
crabs2 <- dplyr::select(crabs, FL, CW)
t1 <- tidy_kde(crabs2)
gt <- ggplot(t1, aes(x=FL, y=CW))
gt + geom_contour_filled_ks()
gt + geom_contour_ks(aes(colour=after_stat(contperc)))
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.