ARRAYS AND VECTOR OPERATIONS

Listing 2.12 displays the content of array_vector.py that illustrates how to perform vector operations on the elements in a NumPy array.

LISTING 2.12: array_vector.py

import numpy as np

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

print('a:       ', a)
print('b:       ', b)
print('a + b:   ', a+b)
print('a - b:   ', a-b)
print('a * b:   ', a*b)
print('a / b:   ', a/b)
print('b / a:   ', b/a)
print('a.dot(b):',a.dot(b))

Listing 2.12 contains two NumPy arrays called a and b followed by eight print() statements, each of which displays the result of “applying” a different arithmetic operation to the NumPy arrays a and b. The output from launching Listing 2.12 is here:

('a    :   ', array([[1, 2], [3, 4]]))
('b    :   ', array([[5, 6], [7, 8]]))
('a + b:   ', array([[ 6,  8], [10, 12]]))
('a - b:   ', array([[-4...