diagonal

Is there a way in Octave to compute and store only the diagonal of a matrix product? Basically like doing: vector = diag(A*B); I don't care about any of the values of A*B except those on the diagonal. The matrix sizes are around 80k x 12 and 12 x 80k , so even if I didn't care about the speed/extra memory it simply wont fit in RAM. Strange, since Octave is a package for huge data sets and diagonals are very important, so it should be possible. The first element in the diagonal is the scalar product of the first row of A with the first column of B. The second element in the diagonal is the

I've got a large nxn matrix and would like to take off-diagonal slices of varying sizes. For example: 1 2 3 4 5 6 1 2 3 4 5 6 1 2 3 4 5 6 1 2 3 4 5 6 1 2 3 4 5 6 1 2 3 4 5 6 I'd like an R function which, when given the matrix and "width of diagonal slice" would return an nxn matrix of just those values. So for the matrix above and, say, 3, I'd get: 1 x x x x x 1 2 x x x x 1 2 3 x x x x 2 3 4 x x x x 3 4 5 x x x x 4 5 6 At the moment I'm using (forgive me) a for loop which is incredibly slow: getDiags<-function(ndiags, cormat){ resmat=matrix(ncol=ncol(cormat),nrow=nrow(cormat)) dimnames(resmat)

I'm looking for a Pythonic way to get all the diagonals of a (square) matrix, represented as a list of lists. Suppose I have the following matrix: matrix = [[-2, 5, 3, 2], [ 9, -6, 5, 1], [ 3, 2, 7, 3], [-1, 8, -4, 8]] Then the large diagonals are easy: l = len(matrix[0]) print [matrix[i][i] for i in range(l)] # [-2, -6, 7, 8] print [matrix[l-1-i][i] for i in range(l-1,-1,-1)] # [ 2, 5, 2, -1] But I have trouble coming up with a way to generate all the diagonals. The output I'm looking for is: [[-2], [9, 5], [3,-6, 3], [-1, 2, 5, 2], [8, 7, 1], [-4, 3], [8], [2], [3,1], [5, 5, 3], [-2, -6, 7,