loop-free operations on two-dimensional numpy arrays

April 25, 2023

This may seem a silly question to the community, but I didn’t manage to find an answer online. Imagine one has a situation like this:

area_vector = np.zeros(np.shape(normal))
for i in range(len(area)):
    area_vector[i] = area[i] * normal[i]

normal is a N x 3 array and area a 1D array of size N. As we can see, the loop is essentially an operation over rows of two-dimensional numpy arrays (area_vector and normal).

Is it possible to perform the above calculation in just 1 line (i.e. avoiding the for loop and using numpy’s built-in methods as much as possible)?

Thanks a lot,

>Solution :

Yes

import numpy as np
N = np.random.randint(10, 100)
normal = np.random.random((N, 3))
pressure = np.random.random((N, 1))
area = np.random.random((N, 1))
area_vector = np.zeros(np.shape(normal))
for i in range(len(pressure)):
    area_vector[i] = area[i] * normal[i]

area_vector_alternative = area * normal
print((area_vector_alternative == area_vector).all())

prints