python - Numpy: Subtract 2 numpy arrays row wise -

i have 2 numpy arrays , b below:

a = np.random.randint(0,10,(3,2)) out[124]:  array([[0, 2],        [6, 8],        [0, 4]]) b = np.random.randint(0,10,(2,2)) out[125]:  array([[5, 9],        [2, 4]]) 

i want subtract each row in b each row in , desired output of shape(3,2,2):

array([[[-5, -7],        [-2, -2]],         [[ 1, -1],        [ 4,  4]],         [[-5, -5],        [-2,  0]]]) 

i can using:

print(np.c_[(a - b[0]),(a - b[1])].reshape(3,2,2)) 

but need vectorized solution or built in numpy function this.

just use np.newaxis (which alias none) add singleton dimension a, , let broadcasting rest:

in [45]: a[:, np.newaxis] - b out[45]:  array([[[-5, -7],         [-2, -2]],         [[ 1, -1],         [ 4,  4]],         [[-5, -5],         [-2,  0]]])