在ggtern中绘制kde结果

Question

我正在使用ggtern以三级绘图的形式绘制一个大型数据集(参见下面的示例).

直到某个数据大小,一切都很完美,因为我使用的是geom_density_tern().因为我想要想象一个更加复杂的数据集加载所有它并且用ggplot渲染变得不可能(在内存方面的限制).我想也许可以通过计算单独计算的kde2d矩阵的结果来解决这个问题.那就是我被困住的地方.我想知道是否有可能在ggtern中做到这一点？

在任何情况下,我都添加了一个最小的数据结构和绘图,我现在使用它.

require(ggplot2)
require(ggtern) 

set.seed(1) 

mydata <- data.frame(
        x = runif(100, min = 0.25, max = 0.5),
        y = runif(100, min = 0.1, max = 0.4),
        z = runif(100, min = 0.5, max = 0.7))   

plot <- ggtern() + 
        theme_bw() +
        theme_hidetitles() +
        geom_density_tern(data = mydata,
            aes(x = x, y = y, z = z, alpha = ..level.. ), 
            size = 0.1, linetype = "solid", fill = "blue")+
        geom_point(data = mydata, 
            aes(x = x, y = y, z = z), alpha = 0.8, size = 1)
plot

这些额外的线重现了三元协调系统中的密度图:

library(MASS)
dataTern = transform_tern_to_cart(mydata$x,mydata$y,mydata$z)
dataTernDensity <- kde2d(x=dataTern$x, y=dataTern$y, lims = c(range(0,1), range(0,1)), n = 400) 

image(dataTernDensity$x, dataTernDensity$y, dataTernDensity$z)
points(dataTern$x, dataTern$y, pch = 20, cex = 0.1)
segments(x0 = 0, y0 = 0, x1 = 0.5, y1 = 1, col= "white")
segments(x0 = 0, y0 = 0, x1 = 1, y1 = 0, col= "white")
segments(x0 = 0.5, y0 = 1, x1 = 1, y1 = 0, col= "white")

并获得此图:

在此先感谢您的帮助!

Answer 1

我们可以使用 Stat 中通常在幕后使用的代码来解决这个问题。ggtern 2.0.1几天前，在完全重写软件包以兼容之后，我刚刚发布并在 CRAN 上发布ggplot2 2.0.0，我熟悉了一种可能适合您需求的方法。ggtern 2.0.X顺便说一句，为了满足您的兴趣，可以在此处找到新功能的摘要：

请在下面找到您的问题的解决方案和工作代码，这是在等距对数比空间上计算的密度估计。

#Required Libraries
library(ggtern)
library(ggplot2)
library(compositions)
library(MASS)
library(scales)

set.seed(1) #For Reproduceability
mydata <- data.frame(
  x = runif(100, min = 0.25, max = 0.5),
  y = runif(100, min = 0.1, max = 0.4),
  z = runif(100, min = 0.5, max = 0.7)) 

#VARIABLES
nlevels  = 7
npoints  = 200
expand   = 0.5

#Prepare the data, put on isometric logratio basis
df     = data.frame(acomp(mydata)); colnames(df) = colnames(mydata)
data   = data.frame(ilr(df)); colnames(data) = c('x','y')

#Prepare the Density Estimate Data
h.est  = c(MASS::bandwidth.nrd(data$x), MASS::bandwidth.nrd(data$y))
lims   = c(expand_range(range(data$x),expand),expand_range(range(data$y),expand))
dens   = MASS::kde2d(data$x,data$y,h=h.est,n=npoints,lims=lims)

#-------------------------------------------------------------
#<<<<< Presumably OP has data at this point, 
#      and so the following should achieve solution
#-------------------------------------------------------------

#Generate the contours via ggplot2's non-exported function
lines  = ggplot2:::contour_lines(data.frame(expand.grid(x = dens$x, y = dens$y),
                                            z=as.vector(dens$z),group=1),
                                 breaks=pretty(dens$z,n=nlevels))

#Transform back to ternary space
lines[,names(mydata)] = data.frame(ilrInv(lines[,names(data)]))

#Render the plot
ggtern(data=lines,aes(x,y,z)) +
  theme_dark() + 
  theme_legend_position('topleft') + 
  geom_polygon(aes(group=group,fill=level),colour='grey50') +
  scale_fill_gradient(low='green',high='red') + 
  labs(fill  = "Density",
       title = "Example Manual Contours from Density Estimate Data")