Let's say I have a matrix x
which contains 10 rows and 2 columns. I want to generate a new matrix M
that contains each unique pair of rows from x
- that is, a new matrix with 55 rows and 4 columns.
E.g.,
x <- matrix (nrow=10, ncol=2, 1:20)
M <- data.frame(matrix(ncol=4, nrow=55))
k <- 1
for (i in 1:nrow(x))
for (j in i:nrow(x))
{
M[k,] <- unlist(cbind (x[i,], x[j,]))
k <- k + 1
}
So, x
is:
[,1] [,2]
[1,] 1 11
[2,] 2 12
[3,] 3 13
[4,] 4 14
[5,] 5 15
[6,] 6 16
[7,] 7 17
[8,] 8 18
[9,] 9 19
[10,] 10 20
And then M
has 4 columns, the first two are one row from x
and the next 2 are another row from x
:
> head(M,10)
X1 X2 X3 X4
1 1 11 1 11
2 1 11 2 12
3 1 11 3 13
4 1 11 4 14
5 1 11 5 15
6 1 11 6 16
7 1 11 7 17
8 1 11 8 18
9 1 11 9 19
10 1 11 10 20
Is there either a faster or simpler (or both) way of doing this in R?
The expand.grid()
function useful for this:
R> GG <- expand.grid(1:10,1:10)
R> GG <- GG[GG[,1]>=GG[,2],] # trim it to your 55 pairs
R> dim(GG)
[1] 55 2
R> head(GG)
Var1 Var2
1 1 1
2 2 1
3 3 1
4 4 1
5 5 1
6 6 1
R>
Now you have the 'n*(n+1)/2' subsets and you can simple index your original matrix.
I'm not quite grokking what you are doing so I'll just throw out something that may, or may not help.
Here's what I think of as the Cartesian product of the two columns:
expand.grid(x[,1],x[,2])
You can also try the "relations" package. Here is the vignette. It should work like this:
relation_table(x %><% x)
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