Multiplying numpy arrays

Question

I have written a function to multiply two numpy arrays.

def ra(self):
    """Multiply Rotation with initial Values"""
    rva = self.r_array() * self.va_array()
    rva = np.sum(rva, axis=1)  # Sum rows of Matrix
    rva = np.array([[rva[0]],  # Transpose Matrix
                    [rva[1]],
                    [rva[2]]])

where:

• r_array has 3 rows and 3 columns
• va_array has 3 rows and 1 column

I feel like this should be able to be written in one line. However, self.r_array() * self.va_array() always returns a 3 x 3 array.

Any suggestions would be greatly appreciated.

Cheers

Answer 1

Actually the * operator does element-wise multiplication. So you need to use .dot() function to get the desired result.

Example :

import numpy as np

a = np.array([[1,2,3],
    [4,5,6],
    [7,8,9]])

b =  np.array([[1]
    ,[2],
    [3]])
print(a * b)
print(a.dot(b))

output :

[[ 1  2  3]
 [ 8 10 12]
 [21 24 27]]
[[14]
 [32]
 [50]]

Observe that when I have used * operator, every column in a is multiplied with b element-wise

Answer 2

A one liner:

 np.sum(r_array*va_array, axis=1, keepdims=True)

To match r_array@va_array, use va_array.T in the 1liner.