You could also call table() on the columns of the input matrix, first converting them to factors with levels 1:max. Then add together the upper and lower triangles of the table if order is not important. E.g., f2 <- function (mat) { maxMat <- max(mat) stopifnot(is.matrix(mat), all(mat %in% seq_len(maxMat))) L <- split(factor(mat, levels = seq_len(maxMat)), col(mat)) Table <- do.call(table, unname(L)) ignoreOrder <- function(M) { stopifnot(length(dim(M)) == 2) lower <- lower.tri(M, diag = FALSE) upper <- upper.tri(M, diag = FALSE) M[lower] <- M[lower] + t(M)[lower] M[upper] <- t(M)[upper] M } ignoreOrder(Table) }
> mat <- structure(c(5, 6, 5, 5, 4, 3, 6, 7, 4, 7, 5, 5, 5, 5, 6, 5, 5, 4, 3, 6, 7, 4, 7, 5, 5, 5, 6, 5, 4, 5, 5, 7, 5, 6, 3, 5, 6, 7, 6, 6, 5, 4, 5, 5, 7, 5, 6, 3, 5, 6, 7, 6), .Dim = c(26L, 2L)) > f2(mat) 1 2 3 4 5 6 7 1 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 3 0 0 0 2 0 0 2 4 0 0 2 0 4 0 0 5 0 0 0 4 2 10 4 6 0 0 0 0 10 0 2 7 0 0 2 0 4 2 0 Bill Dunlap TIBCO Software wdunlap tibco.com On Wed, Oct 7, 2015 at 6:09 AM, Boris Steipe <boris.ste...@utoronto.ca> wrote: > Still not sure I understand. But here is what I think you might mean: > > # Your data > mat <- structure(c(5, 6, 5, 5, 4, 3, 6, 7, 4, 7, 5, 5, 5, 5, 6, 5, 5, > 4, 3, 6, 7, 4, 7, 5, 5, 5, 6, 5, 4, 5, 5, 7, 5, 6, 3, 5, 6, 7, > 6, 6, 5, 4, 5, 5, 7, 5, 6, 3, 5, 6, 7, 6), .Dim = c(26L, 2L)) > > # Create a square matrix with enough space to have an element for each pair. > Since > # order is not important, only the upper triangle is used. If the matrix is > # large and sparse, a different approach might be needed. > freq <- matrix(numeric(max(mat) * max(mat)), nrow = max(mat), ncol = > max(mat)) > > # Loop over your input > for (i in 1:nrow(mat)) { > # Sort the elements of a row by size. > x <- sort(mat[i,]) > # Increment the corresponding element of the frequency matrix > freq[x[1], x[2]] <- freq[x[1], x[2]] + 1 > } > > freq > > > Cheers, > B. > > > > > > On Oct 7, 2015, at 1:17 AM, Hermann Norpois <hnorp...@gmail.com> wrote: > >> Ok, this was misleading. And was not that important. My result matrix should >> look like this: >> >> 1 2 3 4 5 6 7 ... >> 1 p1 p2 >> 2 p >> 3 >> 4 >> >> p1 etc are the frequencies of the combinations >> >> 1 and 2 for instance do not appear in my example. So the values would be >> zero. Actually, this part is not too important. I would be happy enough to >> solve the challenge with the frequencies of the pairs. >> Thanks Hermann >> >> 2015-10-07 2:40 GMT+02:00 Boris Steipe <boris.ste...@utoronto.ca>: >> Since order is not important to you, you can order your pairs (e.g. >> decreasing) before compiling the frequencies. >> But I don't understand the second part about values "that do not appear in >> the matrix". Do you mean you want to assess all combinations? If that's the >> case I would think about a hash table or other indexed data structure, >> rather than iterating through a matrix. >> >> >> B. >> >> >> >> On Oct 6, 2015, at 4:59 PM, Hermann Norpois <hnorp...@gmail.com> wrote: >> >> > Hello, >> > >> > I have a matrix mat (see dput(mat)) >> > >> >> mat >> > [,1] [,2] >> > [1,] 5 6 >> > [2,] 6 5 >> > [3,] 5 4 >> > [4,] 5 5 >> > .... >> > >> > I want the frequencies of the pairs in a new matrix, whereas the >> > combination 5 and 6 is the same as 6 and 5 (see the first two rows of mat). >> > In other words: What is the probability of each combination (each row) >> > ignoring the order in the combination. As a result I would like to have a >> > matrix that includes rows and cols 0, 1, 2 ... max (mat) that do not appear >> > in my matrix. >> > >> > dput (mat) >> > structure(c(5, 6, 5, 5, 4, 3, 6, 7, 4, 7, 5, 5, 5, 5, 6, 5, 5, >> > 4, 3, 6, 7, 4, 7, 5, 5, 5, 6, 5, 4, 5, 5, 7, 5, 6, 3, 5, 6, 7, >> > 6, 6, 5, 4, 5, 5, 7, 5, 6, 3, 5, 6, 7, 6), .Dim = c(26L, 2L)) >> > >> > Thanks >> > Hermann >> > >> > [[alternative HTML version deleted]] >> > >> > ______________________________________________ >> > R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see >> > https://stat.ethz.ch/mailman/listinfo/r-help >> > PLEASE do read the posting guide >> > http://www.R-project.org/posting-guide.html >> > and provide commented, minimal, self-contained, reproducible code. >> >> ______________________________________________ >> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see >> https://stat.ethz.ch/mailman/listinfo/r-help >> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html >> and provide commented, minimal, self-contained, reproducible code. >> > > ______________________________________________ > R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.