The moving sum can be calculated in MATLAB with movsum. However, that function requires that the window be a scalar. Is there a faster way to calculate a moving sum when the window length varies without using a loop?
As it stands, I am working with two equally sized vectors. The first contains values to sum and the second contains window lengths. A for-loop is used to manually extract the required values from the first vector for each ith value (window length) in the second vector. It gets the job done, but it would be great if it could be optimized, as it is being run millions of times.
The window sizes in the second vector span a large enough range (e.g., 50) that it is not faster to pre-calculate moving sums for each window size and simply index into the corresponding pre-calculated vectors while looping.
If this question can be answered, I would also apply it to other moving functions, such as movmax and movmin.
Edited addition in response to Steven Lord's comment:
Yes, that is what I am asking. (Though the vectors are on the order of 100,000 in length with windows up to 500 in size.) Typically, sums are not centered, though. So, it would include the current and previous elements.
The following example should help:
y = [1 2 3 4 2 5 3 7 2 4 5 4 7 6 3 9 5 5 3 6];
s(i) = sum(x((i-y(i)+1):i));
disp(s)
1 3 6 10 9 20 18 35 17 34 45 42 70 69 42 108 75 80 54 105
s_arr(i,:) = movsum(x,[i-1 0]);
disp(s)
1 3 6 10 9 20 18 35 17 34 45 42 70 69 42 108 75 80 54 105
