numpy.exp2() in Python

numpy.exp2(array, out = None, where = True, casting = ‘same_kind’, order = ‘K’, dtype = None) :
This mathematical function helps user to calculate 2**x for all x being the array elements.

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 2**x(power of 2) for all x i.e. array elements 

 
Code 1 : Working

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# Python program explaining
# exp2() function
import numpy as np
  
in_array = [1, 3, 5, 4]
print ("Input array : \n", in_array)
  
exp2_values = np.exp2(in_array)
print ("\n2**x values : \n", exp2_values)

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Output :

Input array : 
 [1, 3, 5, 4]

2**x values : 
 [  2.   8.  32.  16.]

 
Code 2 : Graphical representation

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# Python program showing
# Graphical representation of 
# exp2() function
import numpy as np
import matplotlib.pyplot as plt
  
in_array = [1, 2, 3, 4, 5 ,6]
out_array = np.exp2(in_array)
  
print("out_array : ", out_array)
  
y = [1, 2, 3, 4, 5 ,6]
plt.plot(in_array, y, color = 'blue', marker = "*")
  
# red for numpy.exp2()
plt.plot(out_array, y, color = 'red', marker = "o")
plt.title("numpy.exp2()")
plt.xlabel("X")
plt.ylabel("Y")
plt.show()  

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Output :
out_array : [ 2. 4. 8. 16. 32. 64.]

References :
https://docs.scipy.org/doc/numpy-1.13.0/reference/generated/numpy.exp2.html
.



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