numpy.exp2() in Python
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)
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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()
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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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