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.
Here's a vectorized solution with broadcasting -
X,Y = np.ogrid[:Size_1,:Size_2]
k_out = np.sqrt(X+Y) - Y
Supplementing Divakar's solution: If Y and X are not new ranges but some preexisting vectors of numbers, use np.ix_:
Y, X = np.array([[1.3, 3.5, 2], [2.0, -1, 1]])
Y, X = np.ix_(Y, X) # does the same as Y = Y[:, None]; X = X[None, :]
out = np.sqrt(Y+X) - X
