到目前为止，我发现使用iterpc生成排列是最快的方法。示例用法可以是：
library(iterpc)
set.seed(143)
dat <- sample(LETTERS[1:4], 10, replace = TRUE)
np_multiset(table(dat), length(dat))
# [1] 18900
I <- iterpc(table(dat), order=TRUE)
out <- getall(I)
getnext(I)
# [1] A A A A B B C C D D
# Levels: A B C D
getcurrent(I)
# [1] A A A A B B C C D D
# Levels: A B C D
得到的矩阵为18900×10，在单个矩阵中为large to be stored。在getnext(I, 1000)的帮助下，我可以获得1000个块的排列，并在此基础上工作。但是，所有这些排列都是带有标签的。有没有办法以随机顺序从序列中取样1000而不是顺序？
预期输出:(但是，没有生成所有排列out）
Isam <- sample(18900, 10)
# [1] 15746 18026 17881 18687 7513 1975 5575 2845 1275 10207
out[Isam,]
# [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
# [1,] "B" "A" "A" "A" "D" "C" "C" "B" "A" "D"
# [2,] "B" "D" "A" "A" "C" "D" "A" "C" "B" "A"
# [3,] "B" "A" "A" "B" "C" "A" "A" "D" "C" "D"
# [4,] "A" "C" "A" "C" "D" "B" "A" "B" "A" "D"
# [5,] "C" "D" "A" "A" "A" "C" "B" "B" "D" "A"
# [6,] "A" "B" "A" "D" "A" "D" "A" "B" "C" "C"
# [7,] "B" "A" "A" "D" "B" "C" "C" "A" "A" "D"
# [8,] "A" "A" "D" "C" "B" "D" "A" "A" "C" "B"
# [9,] "D" "C" "A" "C" "D" "B" "A" "B" "A" "A"
# [10,] "C" "D" "D" "A" "A" "A" "C" "B" "B" "A"