如果我们假设配对点列表，并且您可以相信这些值是有效的（可能不是一个合理的假设，但是可以添加防御措施），看来您可能只需使用 min 和 max 来做到这一点：

If we assume a list of paired points, and that you can trust the values are valid (probably not a fair assumption, but defenses could be added), it seems that you may be able to just do this with min and max:

inputData <-
  list(
    c(1,10)
    , c(7,3)
    , c(4,5)
  )

lapply(inputData, function(x){
  c(max(x), min(x))
})

给予

[[1]]
[1] 10  1

[[2]]
[1] 7 3

[[3]]
[1] 5 4

如果转换为矩阵，则可以从向量获得相同的基本输出/data.frame，然后使用具有相同功能的 apply 按行。矩阵方法可能类似于：

You can get the same basic output from vectors, if you convert to a matrix/data.frame, then use apply by row with the same function. The matrix approach likely looks something like:

matData <-
  do.call(rbind, inputData)

t(apply(matData, 1, function(x){
  c(max(x), min(x))
}))

并给出：

     [,1] [,2]
[1,]   10    1
[2,]    7    3
[3,]    5    4

鉴于更新，我不得不说我同意@Frank，您应该对此处的内容有基本了解，但请使用 pmax 和 pmin 。然后，该函数如下所示（请注意，我将 x 和 y 设置为参数，因为它们似乎是必需的）。

Given the update, I have to say that I agree with @Frank that you should take the basic idea of what I have here, but use pmax and pmin instead. The function then looks like this (note, I am setting x and y as arguments, since they appear to be required).

cb <- function(corrPlot, x, y, rectArgs = list() ){ 
  # ... pass named vector of x and y names 
  # for upper x > y, lower x < y 
  useX <- pmax(x, y)
  useY <- pmin(x,y)

  n <- ncol(corrPlot)
  nms <- colnames(corrPlot)
  colnames(corrPlot) <- if(is.null(nms)) 1:ncol(corrPlot) else nms

  xleft <- match(useX, colnames(corrPlot)) - 0.5
  ybottom <- n - match(useY, colnames(corrPlot)) + 0.5

  lst <- list(xleft=xleft, ybottom=ybottom, xright=xleft+1, ytop=ybottom+1) 
  do.call(rect, c(lst, rectArgs))
}

然后，这似乎按预期工作：

Then, this appears to work as expected:

cb(plt, x=c(1, 3, 4), y=c(10, 7, 5), rectArgs=list(border="red", lwd=3))

正如预期的那样，有三种生成所需对排序的方法，具体取决于它们是成对列表，矩阵/data.frame还是a向量。另一种方法是接受列表或matrix / data.frame作为函数的参数，然后使用 lapply 或 apply 函数，并从中提取所需的值。

As expected, there are three ways to generate the desired pair ordering, depending on whether they come in a list of pairs, a matrix/data.frame, or a vector. The alternative approach would be to accept either a list or a matrix/data.frame as an argument to the function, then use the lapply or apply functions above and extract your required values from those.