numpy.log2() in Python

array    : [array_like]Input array or object.
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.

An array with Base-2 logarithmic value of x; 
where x belongs to all elements of input array. 

# Python program explaining
# log2() function
import numpy as np

in_array = [1, 3, 5, 2**8]
print ("Input array : ", in_array)

out_array = np.log2(in_array)
print ("Output array : ", out_array)


print("\nnp.log2(4**4) : ", np.log2(4**4))
print("np.log2(2**8) : ", np.log2(2**8))

Input array :  [1, 3, 5, 256]
Output array :  [ 0.          1.5849625   2.32192809  8.        ]

np.log2(4**4) :  8.0
np.log2(2**8) :  8.0

# Python program showing
# Graphical representation of 
# log2() 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.log2(in_array)

print ("out_array : ", out_array)

plt.plot(in_array, in_array, color = 'blue', marker = "*")

# red for numpy.log2()
plt.plot(out_array, in_array, color = 'red', marker = "o")
plt.title("numpy.log2()")
plt.xlabel("out_array")
plt.ylabel("in_array")
plt.show()  

out_array :  [ 0.          0.26303441  0.48542683  0.67807191  0.84799691  1.        ]