use ggplot2 with kde plots of ks package-CodePudding

I'm using

CodePudding user response：

The first two are straightforward in ggplot. Here's a fully reproducible example:

library(ggplot2)

data <- cbind(rnorm(100), rnorm(100))

d <- ggplot(as.data.frame(data), aes(V1, V2))   
  scale_color_viridis_c()  
  theme_bw()

d   geom_density2d(aes(colour = after_stat(level)), bins = 5)

d   geom_density2d_filled()

EDIT

To specifically use the output of ks::kde(), we need to convert its data from a matrix into long format using reshape2::melt, but then it is still very easy to plot in ggplot:

set.seed(1)

data <- cbind(rnorm(100), rnorm(100))
kd   <- ks::kde(data)

library(ggplot2)

Contour Plot

ggplot(reshape2::melt(kd$estimate))  
  geom_contour(aes(x = Var1, y = Var2, z = value, color = stat(level)),
               bins = 5)  
  scale_color_viridis_c()  
  coord_equal()  
  theme_classic()

Filled contour plot

ggplot(reshape2::melt(kd$estimate))  
  geom_contour_filled(aes(x = Var1, y = Var2, z = value, fill = stat(level)),
               bins = 9)  
  scale_fill_viridis_d()  
  coord_equal()  
  theme_classic()  
  theme(legend.position = "none")

Raster image

ggplot(reshape2::melt(kd$estimate))  
  geom_raster(aes(x = Var1, y = Var2, fill = value))  
  scale_fill_viridis_c()  
  coord_equal()  
  theme_classic()  
  theme(legend.position = "none")

^{Created on 2021-11-12 by the reprex package (v2.0.0)}