numpy.exp2() in Python (original) (raw)

Last Updated : 29 Nov, 2018

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

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)

Output :

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

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

Code 2 : Graphical representation

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 = "*" )

plt.plot(out_array, y, color = 'red' , marker = "o" )

plt.title( "numpy.exp2()" )

plt.xlabel( "X" )

plt.ylabel( "Y" )

plt.show()

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

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

Similar Reads