I am working with a large set of combinations. I would like a way to eliminate a portion of them, such that all combinations where the elements are close together (where close is set by me) are eliminated. (Note, it may take a second or two, it's rather large).
Let's make an example:
library(gtools)
support<-matrix(seq(0,1,by=0.1), ncol=1)
support.n<-as.matrix(permutations(length(support), 3,support))
But now I would like to eliminate all rows where any 2 combinations are "close" (say, within +/-0.2 of each other, inclusive). That is to say, how do I convert:
...
[964,] 1.0 0.7 0.0
[965,] 1.0 0.7 0.1
[966,] 1.0 0.7 0.2
[967,] 1.0 0.7 0.3
[968,] 1.0 0.7 0.4
[969,] 1.0 0.7 0.5
[970,] 1.0 0.7 0.6
[971,] 1.0 0.7 0.8
[972,] 1.0 0.7 0.9
[973,] 1.0 0.8 0.0
[974,] 1.0 0.8 0.1
[975,] 1.0 0.8 0.2
[976,] 1.0 0.8 0.3
[977,] 1.0 0.8 0.4
[978,] 1.0 0.8 0.5
[979,] 1.0 0.8 0.6
[980,] 1.0 0.8 0.7
[981,] 1.0 0.8 0.9
[982,] 1.0 0.9 0.0
[983,] 1.0 0.9 0.1
[984,] 1.0 0.9 0.2
[985,] 1.0 0.9 0.3
[986,] 1.0 0.9 0.4
[987,] 1.0 0.9 0.5
[988,] 1.0 0.9 0.6
[989,] 1.0 0.9 0.7
[990,] 1.0 0.9 0.8
into the much thinner:
....
[964,] 1.0 0.7 0.0
[965,] 1.0 0.7 0.1
[966,] 1.0 0.7 0.2
[967,] 1.0 0.7 0.3
[968,] 1.0 0.7 0.4
[969,] 1.0 0.7 0.5
where the row names are incorrect since I didn't calculate out what happens to them. I have been looking at the commands any(x), and some various which() type commands but can't seem to get the magic to happen.
This should work for you. x is an alias for each row of support.n, each pair combination is created from the row elements and the minimum absolute difference between each pair is checked against 0.2. It returns a TRUE/FALSE which is then used to subset support.n -
support.n[
apply(
support.n,
1,
function(x)
min(
abs(
diff(
combn(
x,
2
)
)
)
)
) > 0.2,
]