将点和线添加到R中的3D散点图

时间：2023-02-05 14:57:43

I want to visualize concentration ellipsoids in 3d scatter plot in respect of principal components (principal components as axes of these ellipsoids). I used function scatter3d with option ellipsoid = TRUE

我想在三维散点图中显示关于主成分(主要成分作为这些椭球的轴)的浓度椭球。我使用函数scatter3d和选项ellipsoid = TRUE

data3d <- iris[which(iris$Species == "versicolor"), ]

library(car)
library(rgl)
scatter3d(x = data3d[,1], y = data3d[,2], z = data3d[,3],
      surface=FALSE, grid = TRUE, ellipsoid = TRUE,
      axis.col = c("black", "black", "black"), axis.scales = FALSE,
      xlab = "X1", ylab = "X2", zlab = "X3",  surface.col = "blue",
      revolution=0, ellipsoid.alpha = 0.0, level=0.7, point.col = "yellow", add=TRUE)

to draw this plot:

画这个情节:

将点和线添加到R中的3D散点图

Then I was trying to add "mean point" using

然后我试图添加“平均点”使用

points3d(mean(data3d[,1]), mean(data3d[,2]), mean(data3d[,3]), col="red", size=20)

but this point is not in the place it's supposed to be (in the center of ellipsoid): 将点和线添加到R中的3D散点图

但这一点不在它应该的位置(在椭圆体的中心):

and I'm wondering why and how can I rescale it (?). And another question, which will arise after this how can I add axes of this ellipsoid to the plot?

我想知道为什么以及如何重新缩放它(?)。还有一个问题,在此之后会出现如何将这个椭圆体的轴添加到图中?

1 个解决方案

#1

Looking at car:::scatter3d.default shows that the coordinates are internally scaled by the min and max of each dimension; the following code scales before plotting:

看车::: scatter3d.default显示坐标在内部按每个维度的最小值和最大值缩放;以下代码在绘图之前进行缩放:

sc <- function(x,orig) {
    d <- diff(range(orig))
    m <- min(orig)
    (x-m)/d
}
msc <- function(x) {
    sc(mean(x),x)
}

points3d(msc(data3d[,1]),
         msc(data3d[,2]),
         msc(data3d[,3]), col="red", size=20)

#1

Looking at car:::scatter3d.default shows that the coordinates are internally scaled by the min and max of each dimension; the following code scales before plotting:

看车::: scatter3d.default显示坐标在内部按每个维度的最小值和最大值缩放;以下代码在绘图之前进行缩放:

sc <- function(x,orig) {
    d <- diff(range(orig))
    m <- min(orig)
    (x-m)/d
}
msc <- function(x) {
    sc(mean(x),x)
}

points3d(msc(data3d[,1]),
         msc(data3d[,2]),
         msc(data3d[,3]), col="red", size=20)
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