numpy.logaddexp() in Python

Syntax : numpy.logaddexp(arr1, arr2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, ufunc ‘logaddexp’) Parameters : arr1 : [array_like] Input array. arr2 : [array_like] 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] True value means to calculate the universal functions(ufunc) at that position, False value means to leave the value in the output alone. **kwargs : allows you to pass keyword variable length of argument to a function. It is used when we want to handle named argument in a function. Return : [ndarray or scalar] It returns Logarithm of exp(arr1) + exp(arr2). This is a scalar if both arr1 and arr2 are scalars.

# Python3 code demonstrate logaddexp() function

# importing numpy
import numpy as np

in_num1 = 2
in_num2 = 3
print ("Input  number1 : ", in_num1)
print ("Input  number2 : ", in_num2)

out_num = np.logaddexp(in_num1, in_num2)
print ("Output number : ", out_num)

Input  number1 :  2
Input  number2 :  3
Output number :  3.31326168752

# Python3 code demonstrate logaddexp() function

# importing numpy
import numpy as np

in_arr1 = [2, 3, 8] 
in_arr2 = [1, 2, 3]
print ("Input array1 : ", in_arr1) 
print ("Input array2 : ", in_arr2)
  
out_arr = np.logaddexp(in_arr1, in_arr2) 
print ("Output array : ", out_arr) 

Input array1 :  [2, 3, 8]
Input array2 :  [1, 2, 3]
Output array :  [ 2.31326169  3.31326169  8.00671535]

jana_sayantan

Follow

Improve

Article Tags :

• Python
• Python-numpy
• Python numpy-Mathematical Function

Practice Tags :

• python