[R] generalization of tabulate()

[Gabor Grothendieck]

Using the generalized inner product defined in this post:

   https://www.stat.math.ethz.ch/pipermail/r-help/2006-July/109311.html

try this:

   cbind(S, d = rowSums(inner(S, obs, identical)))


On Fri, Oct 16, 2009 at 4:29 AM, Robin Hankin <rksh1 at cam.ac.uk> wrote:
> Hi
>
> I want a generalization of tabulate() which works on rows of a matrix.
> Suppose I have an integer matrix 'observation':
>
>> observation
>
> y1 y2 y3
> 1 4 0
> 1 4 0
> 2 0 3
> 4 1 0
> 0 5 0
> 0 1 4
> 2 0 3
>
> Each row corresponds to a (multivariate) observation.  Note that the
> first two rows are identical: this means that data "c(1,4,0)" was
> observed twice.
>
> Now suppose I can list the sample space:
>
>> S
>         [1,] 5 0 0
> [2,] 4 1 0
> [3,] 3 2 0
> [4,] 2 3 0
> [5,] 1 4 0
> [6,] 0 5 0
> [7,] 4 0 1
> [8,] 3 1 1
> [9,] 2 2 1
> [10,] 1 3 1
> [11,] 0 4 1
> [12,] 3 0 2
> [13,] 2 1 2
> [14,] 1 2 2
> [15,] 0 3 2
> [16,] 2 0 3
> [17,] 1 1 3
> [18,] 0 2 3
> [19,] 1 0 4
> [20,] 0 1 4
> [21,] 0 0 5
>
> (thus each row corresponds to a point in my sample space).
>
> Now what I need to do is to construct a new matrix, which uses the
> 'observation' matrix above, which is a sort of table:
>
>> desired
>
>     y1 y2 y3 d
> [1,] 5 0 0 0
> [2,] 4 1 0 1
> [3,] 3 2 0 0
> [4,] 2 3 0 0
> [5,] 1 4 0 2
> [6,] 0 5 0 1
> [7,] 4 0 1 0
> [8,] 3 1 1 0
> [9,] 2 2 1 0
> [10,] 1 3 1 0
> [11,] 0 4 1 0
> [12,] 3 0 2 0
> [13,] 2 1 2 0
> [14,] 1 2 2 0
> [15,] 0 3 2 0
> [16,] 2 0 3 2
> [17,] 1 1 3 0
> [18,] 0 2 3 0
> [19,] 1 0 4 0
> [20,] 0 1 4 1
> [21,] 0 0 5 0
>
>
> Thus the 'd' column counts the number of times that each row occurs in
> variable 'observation'.  So desired[5,4]=2 because the observation
> corresponding to desired[5,1:3] (viz c(1,4,0)) occurred twice.  And
> desired[1,4]=0 because the observation corresponding to desired[1,1:3]
> (viz c(5,0,0)) did not occur once (it was not observed).
>
> In my application I have dim(S) ~= c(5,4e6).
>
> I've tried merge(), stack(),  reshape(), but the best I can do
> is the (derisory):
>
> require(partitions)
>
>
> obs <- matrix(as.integer(c(
>               1, 4, 0,
>               1, 4, 0,
>               2, 0, 3,
>               4, 1, 0,
>               0, 5, 0,
>               0, 1, 4,
>               2, 0, 3
>               )),ncol=3,byrow=TRUE)
>
> S <- t(compositions(5,3))
> d <- rep(0,nrow(S))
>
>
> for(i in seq_len(nrow(obs))){
>  for(j in seq_len(nrow(S))){
>   if(all(obs[i,,drop=TRUE] == S[j,,drop=TRUE])){
>     d[j] <- d[j]+1
>   }
>  }
> }
>
> S <- cbind(S,d)
>
>
> Anyone got anything better before I try C?
>
>
> --
> Robin K. S. Hankin
> Uncertainty Analyst
> University of Cambridge
> 19 Silver Street
> Cambridge CB3 9EP
> 01223-764877
>
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