Python NumPy add() Function

Numpy add() Function:

The numpy add function computes the sum of the two arrays. It computes the addition of two arrays, say l1 and l2, element by element. The numpy.add() function is a universal function, which means that it accepts several parameters that allow you to optimize its work based on the algorithm’s specifics.

Syntax:

numpy.add(l1, l2, out=None)

Parameters:

l1 and l2: (Required)

Required. The arrays that will be added must be specified. They must be broadcastable to a common shape if l1.shape!= l2.shape

out:

This is optional. It is the location where the result will be saved. It must have a shape that the inputs broadcast to if it is provided. If None or not given, a newly allocated array is returned.

Return Value:

The addition between l1 and l2 is returned by the add function. The nd-add() array’s method can be a scalar. It is determined by the l1 and l2 variables. Numpy is used if l1 and l2 are both scalar. A scalar value will be returned by add(). Otherwise, an nd-array will be returned.

NumPy add() Function in Python

Approach:

Import NumPy module using the import keyword.
Pass some random list as an argument to the array() function to create an array.
Store it in a variable.
Create some sample arrays of different shapes to test the add() function.
Pass the first array and some random number to add() function of NumPy module and print the result.
Here it adds the second argument for each element of the array.
Print the result array.
Pass the first array and second array to add() function of NumPy module and print the result.
Here it adds the second array elements for the first array element.
Print the result array.
Similarly, test it with other arrays of different shapes.
The Exit of the Program.

Below is the implementation:

# Import NumPy module using the import keyword.
import numpy as np
# Pass some random list as an argument to the array() function to create an array.
# Store it in a variable.
arry1 = np.array([[30, 60], [90, 120], [150, 180]])
# Create some sample arrays of different shapes to test the add() function.
arry2 = np.array([[10, 20]])
arry3 = np.array([[100], [200], [300]])
arry4 = np.array([[55, 65], [75, 85], [95, 105]])
# Pass the first array and some random number to add() function of NumPy module and print the result.
# Here it adds the second argument for each element of the array.
print('Adding random number say 10 to the first array : ')
print('Adding 10 to first array gives :\n', np.add(arry1, 10))
# Print the result array.
# Pass the first array and second array to add() function of NumPy module and print the result.
# Here it adds the second array elements for the first array element.
# Print the result array.
print('Adding first array and second array : ')
print(np.add(arry1, arry2))
# Similarly, test it with other arrays of different shapes.
print('Adding first array and third array : ')
print(np.add(arry1, arry3))
print('Adding first array and fourth array : ')
print(np.add(arry1, arry4))

Output:

Adding random number say 3 to the first array : 
Adding 10 to first array gives :
[[ 40 70]
[100 130]
[160 190]]
Adding first array and second array : 
[[ 40 80]
[100 140]
[160 200]]
Adding first array and third array : 
[[130 160]
[290 320]
[450 480]]
Adding first array and fourth array : 
[[ 85 125]
[165 205]
[245 285]]

NumPy add() Function in Python

Related