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R 中具有限制的组合数

[英]Number of combinations with restrictions in R

Dear R and stats community,亲爱的 R 和统计社区,

How many combinations are possible to select 3 objects from a total of 9 objects in a way that 3 selected objects do not repeat themselves in one external characteristic?从总共 9 个对象中选择 3 个对象,以使 3 个所选对象不会在一个外部特征中重复自己,有多少种组合可能?

In my example, three selected specimens must always differ in their species attribute.在我的示例中,三个选定的样本在物种属性上必须始终不同。 That is, in the selection of 3, there should always be one representative of species A, one of species B and one of species C, and the order within this selection does not matter.也就是说,在选择3中,应该总是有一个代表物种A,一个代表物种B,一个代表物种C,并且这个选择中的顺序无关紧要。

> mydata <- data.frame(specimens = paste("s", 1:9, sep = ""), species = LETTERS[1:3])
> mydata
  specimens species
1        s1       A
2        s2       B
3        s3       C
4        s4       A
5        s5       B
6        s6       C
7        s7       A
8        s8       B
9        s9       C

How many combinations are there?有多少组合? I know how to count the combinations of ANY set of three objects with eg arrangements::ncombinations(9,3) or choose(9,3) .我知道如何计算任何一组三个对象的组合,例如arrangements::ncombinations(9,3)choose(9,3)

I have seen that one way for generating combinations that allows pasting a custom function which could help in selecting combinations with required properties.我已经看到了一种生成组合的方法,它允许粘贴自定义函数,这有助于选择具有所需属性的组合。

library(utils)
combn(mydata$specimens, 3, FUN)

I am not able to design such a function by myself.我无法自己设计这样的功能。 One of the unsuccessful trials is失败的试验之一是

library(utils)
outp <- combn(as.character(mydata$specimens), 3, function(x) !duplicated(mydata$species))
> outp[, 1:10]
       [,1]  [,2]  [,3]  [,4]  [,5]  [,6]  [,7]  [,8]  [,9] [,10]
 [1,]  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE
 [2,]  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE
 [3,]  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE
 [4,] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
 [5,] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
 [6,] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
 [7,] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
 [8,] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
 [9,] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE

Thanks in advance for your help.在此先感谢您的帮助。

There has to be an A, a B and a C. There are 3 possible As.必须有 A、B 和 C。有 3 种可能的 As。 Each of these must appear with one of the Bs, so there are 3 * 3 = 9 possible pairs of As and Bs.这些中的每一个都必须与一个 B 一起出现,因此有 3 * 3 = 9 对可能的 As 和 B。 Each of these pairs can be grouped with one of the 3 Cs, so there are 3 * 3 * 3 = 27 possible combinations.这些对中的每一对都可以与 3 个 C 中的一个组合在一起,因此有 3 * 3 * 3 = 27 种可能的组合。

You can see them all using this one-liner:您可以使用此单线查看它们:

expand.grid(split(mydata$specimens, mydata$species))
#>     A  B  C
#> 1  s1 s2 s3
#> 2  s4 s2 s3
#> 3  s7 s2 s3
#> 4  s1 s5 s3
#> 5  s4 s5 s3
#> 6  s7 s5 s3
#> 7  s1 s8 s3
#> 8  s4 s8 s3
#> 9  s7 s8 s3
#> 10 s1 s2 s6
#> 11 s4 s2 s6
#> 12 s7 s2 s6
#> 13 s1 s5 s6
#> 14 s4 s5 s6
#> 15 s7 s5 s6
#> 16 s1 s8 s6
#> 17 s4 s8 s6
#> 18 s7 s8 s6
#> 19 s1 s2 s9
#> 20 s4 s2 s9
#> 21 s7 s2 s9
#> 22 s1 s5 s9
#> 23 s4 s5 s9
#> 24 s7 s5 s9
#> 25 s1 s8 s9
#> 26 s4 s8 s9
#> 27 s7 s8 s9

You can try interaction over split like below您可以尝试通过split interaction ,如下所示

> levels(interaction(with(mydata, split(specimens,species))))
 [1] "s1.s2.s3" "s4.s2.s3" "s7.s2.s3" "s1.s5.s3" "s4.s5.s3" "s7.s5.s3"
 [7] "s1.s8.s3" "s4.s8.s3" "s7.s8.s3" "s1.s2.s6" "s4.s2.s6" "s7.s2.s6"
[13] "s1.s5.s6" "s4.s5.s6" "s7.s5.s6" "s1.s8.s6" "s4.s8.s6" "s7.s8.s6"
[19] "s1.s2.s9" "s4.s2.s9" "s7.s2.s9" "s1.s5.s9" "s4.s5.s9" "s7.s5.s9"
[25] "s1.s8.s9" "s4.s8.s9" "s7.s8.s9"

which shows you all combinations of component specimens from different species它向您展示了来自不同species的组件specimens所有组合

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