contour: Contour functions for tidy and geospatial kernel estimates

In eks: Tidy and Geospatial Kernel Smoothing

Contour functions for tidy and geospatial kernel estimates

Description

Contour functions for tidy and geospatial kernel estimates.

Usage

## S3 method for class 'tidy_ks'
contourLevels(x, ..., cont=c(25,50,75))
## S3 method for class 'sf_ks'
contourLevels(x, ..., cont=c(25,50,75))
contour_breaks(data, cont=c(25,50,75), n=3, group=FALSE, type="density")
st_get_contour(x, cont=c(25,50,75), breaks, disjoint=TRUE, digits)

Arguments

x, data	tidy kernel estimate (output from tidy_k*) or geospatial kernel estimate (output from st_k*)
cont	vector of contour levels. Default is c(25,50,75). Used only for level="density", "quantile".
n	number of contour levels. Default is 3. Used only for level="length", "natural".
type	type of contour levels: one of "density", "length", "quantile", "natural". Default is "density".
group	flag to compute contour levels per group. Default is FALSE.
breaks	tibble or vector of contour levels (e.g. output from contour_breaks)
disjoint	flag to compute disjoint contours. Default is TRUE.
digits	number of significant digits in output labels. If missing, default is 4.
...	other parameters (not implemented)

Details

By default, the 5%, 10%, ..., 95% contours are computed for an st_k* output, though a plot of 19 of them would be too crowded. st_get_contour selects a subset of these, as specified by cont. If a contour level in cont does not already exist or if absolute contour levels are specified in breaks, then the corresponding contours are computed. If disjoint=TRUE (default) then the contours are computed as a set of disjoint multipolygons: this allows for plotting without overlapping transparent colours. If disjoint=FALSE then the contours are overlapping and so their colours alpha-mixed, but they strictly satisfy the probabilistic definition, e.g. a 25% contour region is the smallest region that contains 25% of the probability mass defined by the kernel estimate, see geom_contour_ks.

Since these default probability contours are relative contour levels, they aren't suitable for producing a contour plot with fixed contour levels across all groups. It may require trial and error to obtain a single set of contour levels which is appropriate for all groups: one possible choice is provided by contour_breaks.

Value

–The output from contour_breaks is a tibble of the values of the contour breaks. If group=FALSE then a single set of contour breaks is returned. If group=TRUE then a set of contour breaks for each group is returned.

–The output from st_get_contour is an sf object of the contours as multipolygons, with added attributes

estimate	density value or factor with digits s.f.
contlabel	factor of contour probability level
contperc	factor of contour probability level with added %
contregion	factor of contour probability level with added \leq or \geq

These are used to render the contours in the base R base graphics, and via the aesthetics in ggplot.

See Also

geom_contour_ks

Examples

library(ggplot2)
data(crabs, package="MASS")
## tidy data 
crabs2 <- dplyr::select(crabs, FL, CW)
t1 <- tidy_kde(crabs2)
ggplot(t1, aes(x=FL, y=CW)) + geom_contour_filled_ks()

## geospatial data
crabs2s <- sf::st_as_sf(crabs2, coords=c("FL","CW"))
s1 <- st_kde(crabs2s)
s1_cont <- st_get_contour(s1, cont=seq(10,90, by=20))

## base R plot
vc <- function(.) colorspace::sequential_hcl(palette="viridis", n=.)
plot(s1_cont[,"contperc"], pal=vc)

## ggplot
ggplot() + scale_fill_viridis_d() + 
    geom_sf(data=s1_cont, aes(fill=contperc))

eks documentation built on June 8, 2025, 1:29 p.m.