如何使用带有R的persp（）来绘制数据集中的三个变量(How to use persp() with R to graph three variables in a dataset)

如何使用带有R的persp（）来绘制数据集中的三个变量(How to use persp() with R to graph three variables in a dataset)

我有这个数据：

wine <-read.table("http://archive.ics.uci.edu/ml/machine-learning-databases/wine/wine.data",sep=",") attach(wine)

我试图用persp()函数提示变量V2，V3和V4的3D图

我收到此错误：

Error in persp.default(v2, v3, v4) : increasing 'x' and 'y' values expected

虽然我已经使用sort()函数sort()每个变量进行了sort() 。

我该怎么办？

I have this data:

wine <-read.table("http://archive.ics.uci.edu/ml/machine-learning-databases/wine/wine.data",sep=",") attach(wine)

and I am trying to prompt a 3D plot of the variables V2, V3 and V4 with the persp() function

I get this error:

Error in persp.default(v2, v3, v4) : increasing 'x' and 'y' values expected

Although I already sorted each variable with the sort() function.

How should I proceed?

最满意答案

这是一个概念上的错误。 persp用于曲面图，但您的数据仅支持散点图。

对于曲面图，我们需要在x ， y展开的网格上的曲面值。 换句话说，我们在网格上绘制2D函数f(x, y) ： expand.grid(x = sort(x), y = sort(y)) 。 我们需要知道这个函数f和（在几乎所有情况下）使用outer来评估它在这样的网格上。 考虑这个例子：

x <- seq(-10, 10, length = 30) ## already in increasing order y <- x ## already in increasing order f <- function(x, y) {r <- sqrt(x ^ 2 + y ^ 2); 10 * sin(r) / r} z <- outer(x, y, f) ## evaluation on grid; obtain a matrix `z` persp(x, y, z)

另一方面，散点图仅限于(x, y) ：

library(scatterplot3d) scatterplot3d(V2, V3, V4) ## your `wine` data

This is some conceptual mistake. persp is used for surface plot, but your data only support scatter plot.

For a surface plot, we need the surface values on a grid expanded by x, y. In other words, we are plotting a 2D function f(x, y) on a grid: expand.grid(x = sort(x), y = sort(y)). We need to know this function f and (in almost all situation) use outer to evaluate it on such grid. Consider this example:

x <- seq(-10, 10, length = 30) ## already in increasing order y <- x ## already in increasing order f <- function(x, y) {r <- sqrt(x ^ 2 + y ^ 2); 10 * sin(r) / r} z <- outer(x, y, f) ## evaluation on grid; obtain a matrix `z` persp(x, y, z)

Scatter plot on the other hand, is only restricted to (x, y):

library(scatterplot3d) scatterplot3d(V2, V3, V4) ## your `wine` data