Question

I have two equally sized numpy arrays (they happen to be 48×365) where every element is either -1, 0, or 1. I want to compare the two and see how many times they are both the same and how many times they are different while discounting all the times where at least one of the arrays has a zero as no data. For instance:

for x in range(48):
    for y in range(365):
        if array1[x][y] != 0:
            if array2[x][y] != 0:
                if array1[x][y] == array2[x][y]:
                    score = score + 1
                else:
                    score = score - 1
return score

This takes a very long time. I was thinking to take advantage of the fact that multiplying the elements together and summing all the answers may give the same outcome, and I’m looking for a special numpy function to help with that. I’m not really sure what unusual numpy function are out there.

Answer 1

Simpy do not iterate. Iterating over a numpy array defeats the purpose of using the tool.

ans = np.logical_and(
    np.logical_and(array1 != 0, array2 != 0),
    array1 == array2 )

should give the correct solution.