numpy.exp () in Python

Michael Zippo 18.07.2021

Parameters:

  array:  [array_like] Input array or object whose elements, we need to test.  out:  [ndarray, optional] Output array with same dimensions as Input array, placed with result.  ** 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.  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.

Return:

 An array with exponential of all elements of input array.

Code 1: Working

# Python program explaining
# exp () function

import numpy as np

in_array = [ 1 , 3 , 5 ]

print ( "Input array:" , in_array)

out_array = np.exp (in_array)

print ( "Output array:" , out_array)

Output:

 Input array: [1, 3, 5] Output array: [2.71828183 20.08553692 148.4131591]

Code 2: Graphic representation

       # Show Python program  
  # Graphical view  
  # exp () function  
   import   numpy as np  
   import   matplotlib.pyplot as plt 
    
   in_array   =   [  1  ,   1.2  ,   1.4  ,   1.6  ,   1.8  ,   2  ] 
   out_array   =   np.exp (in_array) 
   
   y   =   [  1  ,   1.2  ,   1.4  ,   1.6  ,   1.8  ,   2  ] 
   plt.plot (in_array, y, color   =   ’blue’  , marker   =   "*"  ) 
    
  # red for numpy.exp ()  
   plt.plot (out_array, y, color   =   ’red’  , marker   =  " o " ) 
   plt.title (  "numpy.exp ()"  ) 
   plt.xlabel (  "X"  ) 
   plt.ylabel (  "Y"  ) 
   plt.show ()

Output:

Links:
https://docs.scipy.org/doc/ numpy-1.13.0 / reference / generated / numpy.exp.html
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numpy.exp () in Python

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