Avoid Numpy Index For loop

Question

Is there any way to avoid using a second for loop for an operation like this?

for x in range(Size_1):
    for y in range(Size_2):
        k[x,y] = np.sqrt(x+y) - y

Or is there a better way to optimize this? Right now it is incredibly slow for large sizes.

Answer 1

Here's a vectorized solution with broadcasting -

X,Y = np.ogrid[:Size_1,:Size_2]
k_out = np.sqrt(X+Y) - Y