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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