Finding unique rows in a matrix and summing their weights faster

I am performing the following:

    % a matrix where rows are observations
    A = [1 2;
         4 6;
         1 2;
         9 2;
         4 2;
         6 9];

    % each row has a weight
    W = (1:size(A, 1))';

    % find unique rows
    [uA, ~, icA] = unique(A, 'rows')

    >> 

    uA =

         1     2
         4     2
         4     6
         6     9
         9     2

    icA =

         1
         3
         1
         5
         2
         4

    % what is the combined weight for each unique row?
    wA = zeros(size(uA, 1), 1);
    for i = 1:length(uA)
        wA(i) = sum(W(icA == i));
    end

    % check it works
    wA

    >>

    wA =

         4
         5
         2
         6
         4

    assert(sum(W) == sum(wA), 'sum(W) ~= sum(wA)')

The code works, but the for loop is very slow for a large number of rows. Does anyone know a faster way to do this?

Answer 1

[Andrei Bobrov]

A = [1 2
4 6
1 2
9 2
4 2
6 9];

[aa,cc,cc] = unique(A,'rows');
W = (1:size(A, 1))';
wA = accumarray(cc,W);