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.