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numpy.exp () in Python

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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:

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