NumPy Arithmetic Functions

NumPy arithmetic functions include simple addition, subtraction, multiplication, and division: add(), subtract(), multiply(), and divide().

It is important to note that the arrays must have the same shape or conform to the array broadcasting rules.

Example

import numpy as np

a = np.arange(9, dtype=np.float_).reshape(3, 3)
print('First array:')
print(a)
print('\n')
print('Second array:')
b = np.array([10, 10, 10])
print(b)
print('\n')
print('Adding the two arrays:')
print(np.add(a, b))
print('\n')
print('Subtracting the two arrays:')
print(np.subtract(a, b))
print('\n')
print('Multiplying the two arrays:')
print(np.multiply(a, b))
print('\n')
print('Dividing the two arrays:')
print(np.divide(a, b))

Output:

First array:
[[0. 1. 2.]
 [3. 4. 5.]
 [6. 7. 8.]]

Second array:
[10 10 10]

Adding the two arrays:
[[10. 11. 12.]
 [13. 14. 15.]
 [16. 17. 18.]]

Subtracting the two arrays:
[[-10.  -9.  -8.]
 [ -7.  -6.  -5.]
 [ -4.  -3.  -2.]]

Multiplying the two arrays:
[[ 0. 10. 20.]
 [30. 40. 50.]
 [60. 70. 80.]]

Dividing the two arrays:
[[0.  0.1 0.2]
 [0.3 0.4 0.5]
 [0.6 0.7 0.8]]

Additionally, NumPy includes other important arithmetic functions.

numpy.reciprocal()

The numpy.reciprocal() function returns the element-wise reciprocal of the argument. For example, 1/4 becomes 4/1.

Example

import numpy as np

a = np.array([0.25, 1.33, 1, 100])
print('Our array is:')
print(a)
print('\n')
print('Calling reciprocal function:')
print(np.reciprocal(a))

Output:

Our array is:
[  0.25   1.33   1.   100.  ]

Calling reciprocal function:
[4.        0.7518797 1.        0.01     ]

numpy.power()

The numpy.power() function treats elements in the first input array as base and computes their power with corresponding elements in the second input array.

Example

import numpy as np

a = np.array([10, 100, 1000])
print('Our array is:')
print(a)
print('\n')
print('Calling power function:')
print(np.power(a, 2))
print('\n')
print('Second array:')
b = np.array([1, 2, 3])
print(b)
print('\n')
print('Calling power function again:')
print(np.power(a, b))

Output:

Our array is:
[  10  100 1000]

Calling power function:
[    100   10000 1000000]

Second array:
[1 2 3]

Calling power function again:
[        10      10000 1000000000]

numpy.mod()

The numpy.mod() function computes the remainder of division of the elements in the input array. The numpy.remainder() function produces the same result.

Example

import numpy as np

a = np.array([10, 20, 30])
b = np.array([3, 5, 7])
print('First array:')
print(a)
print('\n')
print('Second array:')
print(b)
print('\n')
print('Calling mod() function:')
print(np.mod(a, b))
print('\n')
print('Calling remainder() function:')
print(np.remainder(a, b))

Output:

First array:
[10 20 30]

Second array:
[3 5 7]

Calling mod() function:
[1 0 2]

Calling remainder() function:
[1 0 2]

Calling the remainder() function: [1 0 2]