Time series aggregation efficiency

Question

I commonly need to summarize a time series with irregular timing with a given aggregation function (i.e., sum, average, etc.). However, the current solution that I have seem

Answer 1

Well I have a solution that is almost as quick as the mex but only using matlab. The logic is the same as most of the above, creating a dummy 2D matrix but instead of using @eq I initialize a logical array from the start.

Elapsed time for mine is 0.172975 seconds. Elapsed time for Divakar 0.289122 seconds.

function aggArray = aggregate(array, group, collapseFn)
    [m,~] = size(array);
    n = max(group);
    D = false(m,n); 
    row = (1:m)';
    idx = m*(group(:) - 1) + row;
    D(idx) = true;
    out = zeros(m,size(array,2));
    for ii = 1:n
        out(ii,:) = collapseFn(array(D(:,ii),:),1);
    end
end