I have a problem where I have a sparse matrix of a specific size, 4000 x 4000. The problem also has a tri-diagonal structure such that I know which elements of the sparse matrix will be non-zero. It is blocks of 4 x 4 along the main diagonal, and the first of-diagonals.
My issue is that I have to compute the 4 x 4 block iteratively, and store them in the matrix as I compute them.
A = spalloc(4000,4000,4*4*1000*3);
for i = 1:1000
idx = (1:8)+4(i-1);
A(idx,idx) = A(idx,idx) + Ri;
Exactly how the matrix that is added, Ri, depend on the interation is a bit complicated to explain. It depends on an outside process, but it has the following structure
Ri = [G B; B.' C];
Ri = [D E; E.' F];
Which one it is in each iteration depends on a random process that is (and has to be) randomly sampled in each iteration.
From what I have read about sparse matrices in Matlab, it appears to be important how sparse matrices are constructed, where a bad way may take much longer than a better way. So, does anyone known the best way to do this?