问题
I have a matrix, for example, 5x5.
[,1] [,2] [,3] [,4] [,5]
[1,] 22 -2 -2 -2 2
[2,] -2 22 2 2 2
[3,] -2 2 22 2 2
[4,] -2 2 2 22 2
[5,] 2 2 2 2 22.
As you can see, the matrix is symmetric.
Above the main diagonal, there are 4+3+2+1=10 positions, and I find via combn all the possible (permutation) matrices, which have (-2) 3 times in these 10 positions. That means 10!/3!*7!=120 matrices.
But some of them are equivalent.
So,my problem is how to find the non-equivalent matrices from the 120.
I am taking about permutation matrices, because if I pick one of the 120 matrices and I use rmperm, I have as a result one (random) of the 120 matrices.
When I have 5x5 and 6x6 matrices, I don't have problem, because I have developed an algorithm. But now I want to do the same in a 7x7 matrix and more, but the algorithm is very slow, because I have lots of loops.
So, I want with one command, when I pick a matrix from the 120 matrices, to give me ALL the permutations matrices from the 120.
Thanks a lot!
回答1:
Basically what you want is permutation of multiset. The package iterpc will do the job.
> library(iterpc)
> I <- iterpc(c(3,7), ordered=TRUE)
> getlength(I)
[1] 120
> getall(I)
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 1 1 2 2 2 2 2 2 2
[2,] 1 1 2 1 2 2 2 2 2 2
[3,] 1 1 2 2 1 2 2 2 2 2
[4,] 1 1 2 2 2 1 2 2 2 2
[5,] 1 1 2 2 2 2 1 2 2 2
[6,] 1 1 2 2 2 2 2 1 2 2
[7,] 1 1 2 2 2 2 2 2 1 2
[8,] 1 1 2 2 2 2 2 2 2 1
[9,] 1 2 1 1 2 2 2 2 2 2
[10,] 1 2 1 2 1 2 2 2 2 2
[11,] 1 2 1 2 2 1 2 2 2 2
[12,] 1 2 1 2 2 2 1 2 2 2
[13,] 1 2 1 2 2 2 2 1 2 2
[14,] 1 2 1 2 2 2 2 2 1 2
[15,] 1 2 1 2 2 2 2 2 2 1
[16,] 1 2 2 1 1 2 2 2 2 2
[17,] 1 2 2 1 2 1 2 2 2 2
[18,] 1 2 2 1 2 2 1 2 2 2
[19,] 1 2 2 1 2 2 2 1 2 2
[20,] 1 2 2 1 2 2 2 2 1 2
[ reached getOption("max.print") -- omitted 100 rows ]
Each row here is a permutations of 1 and 2. You should replace the 1's by -2.
回答2:
Basically, you're asking for all row/column permutations. For an n x n matrix there are n! (n factorial) permutations of the rows and n! permutations of the columns, for a total of (n!)^2 total row/column permutations (not all of which are necessarily unique).
The first step would be to obtain a sample dataset and get the set of all permutations of the row/column indices (I'm assuming square matrices but it would be easy to extend to the non-square case):
# Sample dataset:
library(sna)
set.seed(100)
(g <- rgraph(3))
# [,1] [,2] [,3]
# [1,] 0 0 1
# [2,] 1 0 0
# [3,] 1 1 0
# All permutations of indices
library(gtools)
(perms <- permutations(nrow(g), nrow(g)))
# [,1] [,2] [,3]
# [1,] 1 2 3
# [2,] 1 3 2
# [3,] 2 1 3
# [4,] 2 3 1
# [5,] 3 1 2
# [6,] 3 2 1
You can compute all pairings of the row/column orderings, which you can use to grab all possible row/column permutations:
pairings <- expand.grid(1:nrow(perms), 1:nrow(perms))
head(pairings)
# Var1 Var2
# 1 1 1
# 2 2 1
# 3 3 1
# 4 4 1
# 5 5 1
# 6 6 1
all.perms <- lapply(1:nrow(pairings), function(x) g[perms[pairings[x,1],], perms[pairings[x,2],]])
head(all.perms)
# [[1]]
# [,1] [,2] [,3]
# [1,] 0 0 1
# [2,] 1 0 0
# [3,] 1 1 0
#
# [[2]]
# [,1] [,2] [,3]
# [1,] 0 0 1
# [2,] 1 1 0
# [3,] 1 0 0
# ...
Finally, you can use unique to grab the elements of all.perms that are unique matrices:
all.unique.perms <- unique(perms)
length(all.unique.perms)
# [1] 18
来源：https://stackoverflow.com/questions/29995794/how-to-find-all-the-possible-permutations-of-a-matrix-in-r