洗牌向量 - sample() 的所有可能结果? [英] Shuffling a vector - all possible outcomes of sample()?

问题描述

我有一个包含五个项目的向量.

I have a vector with five items.

my_vec <- c("a","b","a","c","d")

如果我想将这些值重新排列成一个新的向量(shuffle)，我可以使用 sample():

If I want to re-arrange those values into a new vector (shuffle), I could use sample():

shuffled_vec <- sample(my_vec)

简单 - 但 sample() 函数只给了我一种可能的洗牌.如果我想知道所有可能的改组组合怎么办?各种combn"函数似乎没有帮助，expand.grid() 给了我所有可能的组合 with 替换，当我需要它时没有替换.执行此操作的最有效方法是什么?

Easy - but the sample() function only gives me one possible shuffle. What if I want to know all possible shuffling combinations? The various "combn" functions don't seem to help, and expand.grid() gives me every possible combination with replacement, when I need it without replacement. What's the most efficient way to do this?

请注意，在我的向量中，我有两次值a" - 因此，在返回的混洗向量集合中，它们都应该在集合中包含两次a".

Note that in my vector, I have the value "a" twice - therefore, in the set of shuffled vectors returned, they all should each have "a" twice in the set.

推荐答案

我认为来自组合包的 permn 可以满足您的需求

I think permn from the combinat package does what you want

library(combinat)
permn(my_vec)

一个较小的例子

> x
[1] "a" "a" "b"
> permn(x)
[[1]]
[1] "a" "a" "b"

[[2]]
[1] "a" "b" "a"

[[3]]
[1] "b" "a" "a"

[[4]]
[1] "b" "a" "a"

[[5]]
[1] "a" "b" "a"

[[6]]
[1] "a" "a" "b"

如果重复是一个问题，你可以做类似的事情来摆脱重复

If the duplicates are a problem you could do something similar to this to get rid of duplicates

strsplit(unique(sapply(permn(my_vec), paste, collapse = ",")), ",")

或者可能是删除重复项的更好方法...

Or probably a better approach to removing duplicates...

dat <- do.call(rbind, permn(my_vec))
dat[duplicated(dat),]

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