Divide one numpy array by another only where both arrays are non-zero

Question

What's the easiest, most Pythonic way to divide one numpy array by another (of the same shape, element-wise) only where both arrays are non-zero?

Where either the divisor or dividend is zero, the corresponding element in the output array should be zero. (This is the default output when the divisor is zero, but np.nan is the default output when the dividend is zero.)

Answer 1

This still tries to divide by 0, but it gives the correct result:

np.where(b==0, 0, a/b)

To avoid doing the divide-by-zero, you can do:

m = b!=0
c = np.zeros_like(a)
np.place(c, m, a[m]/b[m])

Answer 2

I would do it in two lines:

z = x/y
z[y == 0] = 0

As you said, if only the element in x is 0, z will already be 0 at that position. So let NumPy handle that, and then fix up the places where y is 0 by using NumPy's boolean indexing.