CODEWITHSUNDEEP
pythonnumpyscipy
sam
sam

Reputation: 19164

multidimensional array multiplication in numpy

I have 2 multidimensional arrays. I want to multiply those arrays.

My both arrays have shape : 

shape : (3, 100)

I want to convert matlab code : 

sum(q1.*q2)

to 

np.dot(q1, q2)

gives me output : 

ValueError: objects are not aligned

Upvotes: 1

Views: 2342

Answers (2)

Jaime
Jaime

Reputation: 67417

My installation of Octave, when asked to do

sum(a .* b)

with a and b having shape (3, 100), returns an array of shape (1, 100). The exact equivalent in numpy would be:

np.sum(a * b, axis=0)

which returns an array of shape (100,), or if you want to keep the dimensions of size 1:

np.sum(a * b, axis=0, keepdims=True)

You can get the same result, possibly faster, using np.einsum:

np.einsum('ij,ij->j', a, b)

Upvotes: 1

Abhijit
Abhijit

Reputation: 63707

Use Matrix element wise product * instead of dot product

Here is a sample run with a reduced dimension

Implementation 

A = np.random.randint(5,size=(3,4))
B = np.random.randint(5,size=(3,4))
result = A * B

Demo

>>> A
array([[4, 1, 3, 0],
       [2, 0, 2, 2],
       [0, 1, 1, 1]])
>>> B
array([[1, 3, 0, 2],
       [3, 4, 1, 2],
       [3, 0, 4, 3]])
>>> A * B
array([[4, 3, 0, 0],
       [6, 0, 2, 4],
       [0, 0, 4, 3]])

Upvotes: 2

Related Questions