numpy.add() in Python



numpy.add() in Python

numpy.add() function is used when we want to compute the addition of two array. It add arguments element-wise. If shape of two arrays are not same, that is arr1.shape != arr2.shape, they must be broadcastable to a common shape (which may be the shape of one or the other).

Syntax : numpy.add(arr1, arr2, /, out=None, *, where=True, casting=’same_kind’, order=’K’, dtype=None, subok=True[, signature, extobj], ufunc ‘add’)

 

Parameters :
arr1 : [array_like or scalar] Input array.
arr2 : [array_like or scalar] Input array.
out : [ndarray, optional] A location into which the result is stored.
-> If provided, it must have a shape that the inputs broadcast to.
-> If not provided or None, a freshly-allocated array is returned.
where : [array_like, optional] Values of True indicate to calculate the ufunc at that position, values of False indicate to leave the value in the output alone.
**kwargs :Allows to pass keyword variable length of argument to a function. Used when we want to handle named argument in a function.

Return : [ndarray or scalar] The sum of arr1 and arr2, element-wise. Returns a scalar if both arr1 and arr2 are scalars.

Code #1 : Working

# Python program explaining
# numpy.add() function
# when inputs are scalar
 
import numpy as geek
in_num1 = 10
in_num2 = 15
 
print ("1st Input  number : ", in_num1)
print ("2nd Input  number : ", in_num2)
   
out_num = geek.add(in_num1, in_num2) 
print ("output number after addition  : ", out_num) 

Output :

1st Input  number :  10
2nd Input  number :  15
output number after addition  :  25

Code #2 :

# Python program explaining
# numpy.add() function
# when inputs are array
 
import numpy as geek
 
in_arr1 = geek.array([[2, -7, 5], [-6, 2, 0]])
in_arr2 = geek.array([[5, 8, -5], [3, 6, 9]])
  
print ("1st Input array : ", in_arr1) 
print ("2nd Input array : ", in_arr2) 
   
out_arr = geek.add(in_arr1, in_arr2) 
print ("output added array : ", out_arr) 

Output :

1st Input array :  [[ 2 -7  5]
 [-6  2  0]]
2nd Input array :  [[ 5  8 -5]
 [ 3  6  9]]
output added array :  [[ 7  1  0]
 [-3  8  9]]

Last Updated on March 1, 2022 by admin

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