[FIXED] Numpy calculate product of differences of two matrices against all rows in matrix

Issue

the following is what I want to achieve. Is there a way to do this efficiently with Numpy or other methods in Python? Since my data would be big. I would like to do it more efficiently. Thank you in advance.

import numpy as np
x = np.arange(6).reshape(3,2)
y = np.arange(10).reshape(5,2)
z = np.zeros((len(x), len(y)))

for i in range(len(z)):
    for j in range(len(z[0])):
        z[i,j] = np.prod(x[i] - y[j])

Solution

Just vectorize your code:

z = (x[:,None]-y).prod(axis=-1)

Output:

array([[ 0,  4, 16, 36, 64],
       [ 4,  0,  4, 16, 36],
       [16,  4,  0,  4, 16]])

Intermediate:

(x[:,None]-y).

array([[[ 0,  0],
        [-2, -2],
        [-4, -4],
        [-6, -6],
        [-8, -8]],

       [[ 2,  2],
        [ 0,  0],
        [-2, -2],
        [-4, -4],
        [-6, -6]],

       [[ 4,  4],
        [ 2,  2],
        [ 0,  0],
        [-2, -2],
        [-4, -4]]])

Answered By - mozway