# DRAFT NIST SP 800-90B (January 2016) Section 5

#

# Estimating the Min-Entropy of IID Sources

#

# NOTE: this software is made available with no guarantee - implied or otherwise -

# of correctness or completeness. See user guide for full disclaimer.

#

# Tim Hall

# tim.hall@nist.gov

#

# Kerry McKay

# kerry.mckay@nist.gov

#

# February 2016

import time

import sys

from util90b import get_parser, to_dataset

from permutation_tests import permutation_test

from chi_square_tests import pass_chi_square_tests

from mostCommonValue import most_common

from LRS import lenLRS

##################

# main program

##################

if __name__ == '__main__':

start_time = time.time()

# get command line arguments

args = get_parser('IID').parse_args()

datafile = args.datafile

bits_per_symbol = int(args.bits_per_symbol)

verbose = bool(args.verbose)

with open(datafile, 'rb') as file:

# Read in raw bytes and convert to list of output symbols

bytes_in = bytearray(file.read())

dataset = to_dataset(bytes_in, bits_per_symbol)

k = len(set(dataset))

if verbose:

# print file and dataset details

print ("Read in file %s, %d bytes long." % (datafile, len(bytes_in)))

print ("Dataset: %d %d-bit symbols, %d symbols in alphabet." % (len(dataset), bits_per_symbol, k))

print ("Output symbol values: min = %d, max = %d\n" % (min(dataset), max(dataset)))

#######################################

# STEP 1: Determine if Dataset is IID #

#######################################

# determine if dataset is IID using shuffle and Chi-square tests

passed_permutation_tests = permutation_test(dataset, verbose)

if passed_permutation_tests:

if verbose:

print ("** Passed IID permutation tests")

else:

if verbose:

print ("** Failed IID permutation tests")

print ("IID = False")

sys.exit(0)

# run chi-square tests on dataset

if pass_chi_square_tests(dataset, verbose):

if verbose:

print ("** Passed chi square tests")

else:

if verbose:

print ("** Failed chi square tests")

print ("IID = False")

sys.exit(0)

# run LRS test

if lenLRS(dataset, verbose):

if verbose:

print ("** Passed LRS test")

print ("\nIID = True")

else:

print ("** Failed LRS test")

print ("IID = False")

sys.exit(0)

############################################

# STEP 2: Calculate min-entropy of dataset #

############################################

pmax, minH = most_common(dataset)

print("min-entropy = %g" % (minH))

print("\nDon't forget to run the sanity check on a restart dataset using H_I = %g" % minH )