R 浮点数子集和问题的递归函数

我为的创建了一个递归函数

f（s，x）

，当从值集

x

中拾取元素时，该函数能够生成所有唯一的组合，这些组合的总和为目标和

---

例如，假设

x可以在减法中使用
round
，并设置小数点

f <- function(s, x, xhead = head(x,1), r = c()) {
  if (s == 0) {
    return(list(r))
  } else {
    x <- sort(x,decreasing = T)
    return(unlist(lapply(x[x<=min(xhead,s)], function(k) f(round(s-k, 4), x[x<= round(s-k, 4)], min(k,head(x[x<= round(s-k, 4)],1)), c(r,k))),recursive = F)) 
  }
}

f(s/10,x/10)

谢谢！所以使用
round
来消除减法过程中的不精确性？那么我想它应该取决于
x
> f(s,x)
[[1]]
[1] 10

[[2]]
[1] 8 2

[[3]]
[1] 4 4 2

[[4]]
[1] 4 2 2 2

[[5]]
[1] 2 2 2 2 2

> f(s/10,x/10)
[[1]]
[1] 1

> Map(function(v) v/10, f(s,x))
[[1]]
[1] 1

[[2]]
[1] 0.8 0.2

[[3]]
[1] 0.4 0.4 0.2

[[4]]
[1] 0.4 0.2 0.2 0.2

[[5]]
[1] 0.2 0.2 0.2 0.2 0.2

f <- function(s, x, xhead = head(x,1), r = c()) {
  if (s == 0) {
    return(list(r))
  } else {
    x <- sort(x,decreasing = T)
    return(unlist(lapply(x[x<=min(xhead,s)], function(k) f(round(s-k, 4), x[x<= round(s-k, 4)], min(k,head(x[x<= round(s-k, 4)],1)), c(r,k))),recursive = F)) 
  }
}

f(s/10,x/10)

[[1]]
[1] 1

[[2]]
[1] 0.8 0.2

[[3]]
[1] 0.4 0.4 0.2

[[4]]
[1] 0.4 0.2 0.2 0.2

[[5]]
[1] 0.2 0.2 0.2 0.2 0.2