以前曾问过这个问题,但仅针对具有非重复元素的向量。我找不到一个简单的解决方案来从具有重复元素的向量中获取所有组合。为了说明,我在下面列出了一个示例。
x <- c('red', 'blue', 'green', 'red', 'green', 'red')
向量x对于“红色”具有3个重复元素,对于“绿色”具有2个重复元素。所有唯一组合的预期结果都是这样。
# unique combinations with one element
'red'
'blue'
'green'
# unique combination with two elements
'red', 'blue' # same as 'blue','red'
'red', 'green'
'red', 'red'
'blue', 'green'
'green', 'green'
# unique combination with three elements
'red', 'blue', 'green'
'red', 'red', 'blue'
'red', 'red', 'green'
'red', 'red', 'red' # This is valid because there are three 'red's
'green', 'green', 'red'
'green', 'green', 'blue'
# more unique combinations with four, five, and six elements
答案 0 :(得分:4)
结合使用combn()
和lapply()
可以解决问题。
x <- c('red', 'blue', 'green', 'red', 'green', 'red')
lapply(1:3, function(y) combn(x, y))
# [[1]]
# [,1] [,2] [,3] [,4] [,5] [,6]
# [1,] "red" "blue" "green" "red" "green" "red"
# [[2]]
# [,1] [,2] [,3] [,4] [,5] [,6] ...
# [1,] "red" "red" "red" "red" "red" "blue" ...
# [2,] "blue" "green" "red" "green" "red" "green" ...
# [[3]]
# [,1] [,2] [,3] [,4] [,5] [,6] ...
# [1,] "red" "red" "red" "red" "red" "red" ...
# [2,] "blue" "blue" "blue" "blue" "green" "green" ...
# [3,] "green" "red" "green" "red" "red" "green" ...
所有唯一组合
lapply(cc, function(y)
y[,!duplicated(apply(y, 2, paste, collapse="."))]
)
[[1]]
[1] "red" "blue" "green"
[[2]]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] "red" "red" "red" "blue" "blue" "green" "green"
[2,] "blue" "green" "red" "green" "red" "red" "green"
[[3]]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] ...
[1,] "red" "red" "red" "red" "red" "red" "blue" ...
[2,] "blue" "blue" "green" "green" "red" "red" "green" ...
[3,] "green" "red" "red" "green" "green" "red" "red" ...
尽管严格说来,它们并不是唯一的组合,因为其中一些是彼此置换的。
正确唯一的组合
lapply(cc, function(y)
y[,!duplicated(apply(y, 2, function(z) paste(sort(z), collapse=".")))]
)
# [[1]]
# [1] "red" "blue" "green"
# [[2]]
# [,1] [,2] [,3] [,4] [,5]
# [1,] "red" "red" "red" "blue" "green"
# [2,] "blue" "green" "red" "green" "green"
# [[3]]
# [,1] [,2] [,3] [,4] [,5] [,6]
# [1,] "red" "red" "red" "red" "red" "blue"
# [2,] "blue" "blue" "green" "green" "red" "green"
# [3,] "green" "red" "red" "green" "red" "green"
答案 1 :(得分:4)
library(DescTools)
x <- c('red', 'blue', 'green', 'red', 'green', 'red')
allSets <- lapply(1:length(x), function(i){
unique(t(apply(CombSet(x,i,repl = F),1,sort)))
})
#[1]]
#[,1] [,2] [,3] [,4] [,5] [,6]
#[1,] "red" "blue" "green" "red" "green" "red"
##[[2]]
#[,1] [,2]
#[1,] "blue" "red"
#[2,] "green" "red"
#[3,] "red" "red"
#[4,] "blue" "green"
#[5,] "green" "green"
#[[3]]
#[,1] [,2] [,3]
#[1,] "blue" "green" "red"
#[2,] "blue" "red" "red"
#[3,] "green" "red" "red"
#[4,] "green" "green" "red"
#[5,] "red" "red" "red"
#[6,] "blue" "green" "green"
#[[4]]
#[,1] [,2] [,3] [,4]
#[1,] "blue" "green" "red" "red"
#[2,] "blue" "green" "green" "red"
#[3,] "blue" "red" "red" "red"
#[4,] "green" "green" "red" "red"
#[5,] "green" "red" "red" "red"
#[[5]]
#[,1] [,2] [,3] [,4] [,5]
#[1,] "blue" "green" "green" "red" "red"
#[2,] "blue" "green" "red" "red" "red"
#[3,] "green" "green" "red" "red" "red"
#[[6]]
#[,1] [,2] [,3] [,4] [,5] [,6]
#[1,] "blue" "green" "green" "red" "red" "red"
答案 2 :(得分:4)
library(arrangements)
combinations(c("red", "blue", "green"), k = 2, freq = c(3, 1, 2))
# [,1] [,2]
# [1,] "red" "red"
# [2,] "red" "blue"
# [3,] "red" "green"
# [4,] "blue" "green"
# [5,] "green" "green"
combinations(c("red", "blue", "green"), k = 3, freq = c(3, 1, 2))
# [,1] [,2] [,3]
# [1,] "red" "red" "red"
# [2,] "red" "red" "blue"
# [3,] "red" "red" "green"
# [4,] "red" "blue" "green"
# [5,] "red" "green" "green"
# [6,] "blue" "green" "green"
如果您不想手动输入频率:
x <- c('red', 'blue', 'green', 'red', 'green', 'red')
tx <- table(x)
combinations(names(tx), k = 2, freq = tx)
# [,1] [,2]
# [1,] "blue" "green"
# [2,] "blue" "red"
# [3,] "green" "green"
# [4,] "green" "red"
# [5,] "red" "red"
或使用RcppAlgos
:
library(RcppAlgos)
comboGeneral(names(tx), m=2, freqs = tx)
# [,1] [,2]
# [1,] "blue" "green"
# [2,] "blue" "red"
# [3,] "green" "green"
# [4,] "green" "red"
# [5,] "red" "red"