Matrix multiplication(dot product) - using numpy.ndarray with Example

Overview:

To multiply two matrices A and B the matrices need not be of same shape. For example, a matrix of shape 3x2 and a matrix of shape 2x3 can be multiplied, resulting in a matrix shape of 3 x 3.
Matrix multiplication is not commutative.
Two matrices can be multiplied using the dot() method of numpy.ndarray which returns the dot product of two matrices.

import numpy as np

import random

# Populate a 2 dimensional ndarray with random numbers between 2 to 10

def FillMatrix(matrix_in):

for x in range(0, matrix_in.shape[0]):

for y in range(0, matrix_in.shape[1]):

matrix_in[x][y] = random.randrange(2, 10) + 2

# Create a matrix1

matrix1 = np.ndarray((3,3))

matrix2 = np.ndarray((3,3))

# Dot product of two matrices using ndarray

newmatrix = matrix1.dot(matrix2)

# Print the Matrices

print("Matrix multiplication using numpy ndarray - Matrix 1:")

print("Matrix multiplication using numpy ndarray - Matrix 2:")

print("Matrix multiplication using numpy ndarray - Multiplication results:")

Matrix multiplication using numpy ndarray - Matrix 1:

[[ 10. 5. 4.]

[ 5. 7. 11.]

[ 4. 11. 4.]]

Matrix multiplication using numpy ndarray - Matrix 2:

[[ 6. 11. 6.]

[ 4. 5. 6.]

[ 10. 8. 6.]]

Matrix multiplication using numpy ndarray - Multiplication results:

[[ 120. 167. 114.]

[ 168. 178. 138.]

[ 108.131.114.]]