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Basic arithmetic operation

Lesson 7 Chapter 3

Let's first cover the basic arithmetic operations with some examples:

# Import Numpy library
import numpy as np

# Create two arrays
a = np.array([[1,5],[0,8]], dtype=np.float32)
b = np.array([[2,1],[5,2]], dtype=np.float32)
print('a= ', a)
print('b= ', b)

# Elementwise adding
# a + b and np.add(a, b) are the same.
# Check to see if a + b and np.add(a, b) are the same using ``assert``.
# .all() method check if all elements of a matrix is True.
print('a + b= ', a + b)
assert((a + b == np.add(a, b)).all())

# Elementwise subtraction
print('a - b= ', a - b)
assert((a - b == np.subtract(a, b)).all())

# Elementwise multiplication
print('a * b= ', a * b)
assert((a * b == np.multiply(a, b)).all())

# Elementwise division
print('a / b= ',a / b)
assert((a / b == np.divide(a, b)).all())

# Elementwise square
print('a^2= ', np.square(a))
assert((a ** 2 == np.square(a)).all())

a=  [[1. 5.]
	[0. 8.]]
b=  [[2. 1.]
	[5. 2.]]
a + b=  [[ 3.  6.]
	[ 5. 10.]]
a - b=  [[-1.  4.]
	[-5.  6.]]
a * b=  [[ 2.  5.]
	[ 0. 16.]]
a / b=  [[0.5 5. ]
	[0.  4. ]]
a^2=  [[ 1. 25.]
	[ 0. 64.]]
Element-wise summation. In element-wise operations, the operator performs on correspondent elements from matrices.
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