numpy.exp () in Python



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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