numpy array division for entropy calculation

I'm trying to create a shannon_entropy function that works on both python 2 and 3. The following code works in python 3, however, the statement to evaluate norm_counts returns a narray equaling 0 on python 2 and returns correctly in python 3.

I've broken down and simplified the code below:

import unittest   

import numpy as np

def shannon_ent(labels, base=256):

    value, counts = np.unique(labels, return_counts=True)    
    sum_counts = counts.sum()

    norm_counts = counts / sum_counts

    print(norm_counts)

    base = e if base is None else base

    logged_counts = np.log(norm_counts)
    logged_base = np.log(base)
    logged = logged_counts/logged_base
    final = -(norm_counts * logged)

    return final.sum()


class function_tests(unittest.TestCase):

    def test_shannon_ent(self):

        chunk = [32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126]
        ent = shannon_ent(chunk)
        print('*** is: {}'.format(ent))

        self.assertEqual(ent, 0.8212319510413685)

if __name__ == '__main__':
    unittest.main()

The following output is given:

Python 2

# python unittest_binGraph.py 
(array([1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
       1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
       1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
       1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
       1, 1, 1]), 95)
[0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]
E
======================================================================
ERROR: test_shannon_ent (__main__.function_tests)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "unittest_binGraph.py", line 39, in test_shannon_ent
    ent = shannon_ent(chunk)
  File "unittest_binGraph.py", line 22, in shannon_ent
    logged_counts = np.log(norm_counts)
FloatingPointError: divide by zero encountered in log

----------------------------------------------------------------------
Ran 1 test in 0.007s

FAILED (errors=1)

Python 3

# python unittest_binGraph.py 
[1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1] 95
[0.01052632 0.01052632 0.01052632 0.01052632 0.01052632 0.01052632
 0.01052632 0.01052632 0.01052632 0.01052632 0.01052632 0.01052632
 0.01052632 0.01052632 0.01052632 0.01052632 0.01052632 0.01052632
 0.01052632 0.01052632 0.01052632 0.01052632 0.01052632 0.01052632
 0.01052632 0.01052632 0.01052632 0.01052632 0.01052632 0.01052632
 0.01052632 0.01052632 0.01052632 0.01052632 0.01052632 0.01052632
 0.01052632 0.01052632 0.01052632 0.01052632 0.01052632 0.01052632
 0.01052632 0.01052632 0.01052632 0.01052632 0.01052632 0.01052632
 0.01052632 0.01052632 0.01052632 0.01052632 0.01052632 0.01052632
 0.01052632 0.01052632 0.01052632 0.01052632 0.01052632 0.01052632
 0.01052632 0.01052632 0.01052632 0.01052632 0.01052632 0.01052632
 0.01052632 0.01052632 0.01052632 0.01052632 0.01052632 0.01052632
 0.01052632 0.01052632 0.01052632 0.01052632 0.01052632 0.01052632
 0.01052632 0.01052632 0.01052632 0.01052632 0.01052632 0.01052632
 0.01052632 0.01052632 0.01052632 0.01052632 0.01052632 0.01052632
 0.01052632 0.01052632 0.01052632 0.01052632 0.01052632]
*** is: 0.8212319510413685
.
----------------------------------------------------------------------
Ran 1 test in 0.007s

OK

Unless someone has a better way to calculate entropy?! I am currently using scripy and statistics modules in the code as well.