I wish to generate the unique sequences of elements in a list where some elements are not unique in R
sequence <- c(1,0,1,0)
e.g:
result<-function(sequence)
result:
seq1 seq2 seq3 seq4 seq5 seq6
1 1 1 0 0 0 1
2 0 1 0 1 1 0
3 1 0 1 0 1 0
4 0 0 1 1 0 1
notice that all sequences contain every element from the original sequence, such that the sum of the sequence is always 2
gtools returns "too few different elements"
result <- gtools::permutations(4, 4, coseq)
I am not finding any SO post that directly solve this, but instead allow element repeats:Creating combination of sequences
achievable with expand.grid and different lengths of sequences.
EDIT: The above is a minimal example, ideally it would work on the sequence:
sequence = c(0, 1, 0, 1, 0, 1, 0, 1, 1, 0, 1, 0, 0, 1, 1, 1)
It is somewhat important that the solution does not generate duplicates that are then subsequently removed, since a longer sequence, say 20 or 30 will be very computationally demanding if duplicates are generated.
There are a couple of packages specifically built for this.
First the arrangements package:
## sequence is a bad name as it is a base R function so we use s instead
s <- c(1,0,1,0)
arrangements::permutations(unique(s), length(s), freq = table(s))
[,1] [,2] [,3] [,4]
[1,] 1 1 0 0
[2,] 1 0 1 0
[3,] 1 0 0 1
[4,] 0 1 1 0
[5,] 0 1 0 1
[6,] 0 0 1 1
Next, we have RcppAlgos (I am the author):
RcppAlgos::permuteGeneral(unique(s), length(s), freqs = table(s))
[,1] [,2] [,3] [,4]
[1,] 1 1 0 0
[2,] 1 0 1 0
[3,] 1 0 0 1
[4,] 0 1 1 0
[5,] 0 1 0 1
[6,] 0 0 1 1
They are both very efficient as well. To give you an idea, for the actual need by the OP, the other methods will fail (I think there is a limit on the number of rows for a matrix ... 2^31 - 1, not sure though) or take a very long time as they will have to generate 16! ~= 2.092e+13 permutations before any further processing. However, with these two packages, the return is instant:
## actual example needed by OP
sBig <- c(0, 1, 0, 1, 0, 1, 0, 1, 1, 0, 1, 0, 0, 1, 1, 1)
system.time(a <- arrangements::permutations(unique(sBig), length(sBig), freq = table(sBig)))
user system elapsed
0.001 0.001 0.002
system.time(b <- RcppAlgos::permuteGeneral(unique(sBig), length(sBig), freqs = table(sBig)))
user system elapsed
0.001 0.001 0.002
identical(a, b)
[1] TRUE
dim(a)
[1] 11440 16
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