[SOLVED] Multiply a 3D array with a 2D array


I have a 3D numpy array and I want to multiply it with a 2D array, The 3D looks like follows:

C= np.zeros((3, 2, 2))
C[0][0] = [0,0]
C[0][1] = [0,1]
C[1][0] = [1,0]
C[1][1] = [1,1]
C[2][0] = [1,2]
C[2][1] = [2,1]

The 2D array looks like:

V = np.zeros((3,2)) 
V[0][0] = 1
V[0][1] = 2
V[1][0] = 1
V[1][1] = 3
V[2][0] = 4 
V[2][1] = 5

The result R is to be a 2X2 2D array(4 elements in total) R=[[5,8],[13,10]] where:

R[0] = V[0][0]*C[0][0]+V[1][0]*C[1][0]+V[2][0]*C[2][0] = [5,8] (first row of R)

R[1] = V[0][1]*C[0][1]+V[1][1]*C[1][1]+V[2][1]*C[2][1] = [13,10] (second row of R)

This is just an example, How Can I get R using numpy matrix multiplication operation with V and C (with no for loop!). Please help!

Sorry I made some edit later, the comment showed an old example, it should be good now


Your example is confusing. Why do you say your expected result is [[1, 0], [5, 10]] but in your example you also say R should be [[5, 8], [13, 10]]?

I hope this was just a typo on your part because it’s not clear from your example how you’d get from one to the other.

In any case:

(V.T * C.T).sum(axis=2).T


array([[ 5.,  8.],
       [13., 10.]])

Answered By – ddejohn

Answer Checked By – Dawn Plyler (BugsFixing Volunteer)

Leave a Reply

Your email address will not be published. Required fields are marked *