Tests an die Verwendung von Bytes angepasst
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@ -8,28 +8,31 @@ from scipy.special import gammaincc as gammaincc
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class TotOnline:
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@staticmethod
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def total_failure_test(binary_data: str, pattern_length=10):
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length_of_binary_data = len(binary_data)
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@staticmethod
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def total_failure_test(binary_data: bytes, pattern_length=10):
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length_of_binary_data = len(binary_data) * 8
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# Convert bytes to binary string representation
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binary_data_str = ''
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for byte in binary_data:
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binary_data_str += format(byte, '08b')
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# Augment the n-bit sequence to create n overlapping m-bit sequences by appending m-1 bits
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# from the beginning of the sequence to the end of the sequence.
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binary_data += binary_data[:pattern_length + 1:]
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binary_data_str += binary_data_str[:pattern_length + 1]
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# Get max length one patterns for m, m-1, m-2
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max_pattern = ''
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for i in range(pattern_length + 2):
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max_pattern += '1'
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max_pattern = '1' * (pattern_length + 2)
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# Keep track of each pattern's frequency (how often it appears)
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vobs_01 = zeros(int(max_pattern[0:pattern_length:], 2) + 1)
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vobs_02 = zeros(int(max_pattern[0:pattern_length + 1:], 2) + 1)
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vobs_01 = zeros(int(max_pattern[0:pattern_length], 2) + 1)
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vobs_02 = zeros(int(max_pattern[0:pattern_length + 1], 2) + 1)
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for i in range(length_of_binary_data):
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# Work out what pattern is observed
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vobs_01[int(binary_data[i:i + pattern_length:], 2)] += 1
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vobs_02[int(binary_data[i:i + pattern_length + 1:], 2)] += 1
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vobs_01[int(binary_data_str[i:i + pattern_length], 2)] += 1
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vobs_02[int(binary_data_str[i:i + pattern_length + 1], 2)] += 1
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# Calculate the test statistics and p values
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vObs = [vobs_01, vobs_02]
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@ -49,70 +52,67 @@ class TotOnline:
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return p_value, (p_value >= 0.01)
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@staticmethod
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def monobit_test(binary_data: str):
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def monobit_test(binary_data: bytes):
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length_of_bit_string = len(binary_data) * 8
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length_of_bit_string = len(binary_data)
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# Variable for S(n)
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# Variable for S(n)
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count = 0
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# Iterate each bit in the string and compute for S(n)
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for bit in binary_data:
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if bit == 48:
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# If bit is 0, then -1 from the S(n)
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count -= 1
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elif bit == 49:
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# If bit is 1, then +1 to the S(n)
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count += 1
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# Compute the test statistic
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# Iterate each bit in the byte sequence and compute for S(n)
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for byte in binary_data:
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for bit in range(8):
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if (byte >> (7 - bit)) & 1 == 0:
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# If bit is 0, then -1 from the S(n)
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count -= 1
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else:
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# If bit is 1, then +1 to the S(n)
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count += 1
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# Compute the test statistic
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sObs = count / sqrt(length_of_bit_string)
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# Compute p-Value
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# Compute p-Value
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p_value = erfc(fabs(sObs) / sqrt(2))
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# return a p_value and randomness result
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# return a p_value and randomness result
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return p_value, (p_value >= 0.01)
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@staticmethod
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def block_frequency_test(binary_data: str, block_size=128):
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length_of_bit_string = len(binary_data)
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def block_frequency_test(binary_data: bytes, block_size=128):
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length_of_bit_string = len(binary_data) * 8
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if length_of_bit_string < block_size:
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block_size = length_of_bit_string
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# Compute the number of blocks based on the input given. Discard the remainder
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number_of_blocks = floor(length_of_bit_string / block_size)
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# Compute the number of blocks based on the input given. Discard the remainder
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number_of_blocks = length_of_bit_string // block_size
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if number_of_blocks == 1:
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# For block size M=1, this test degenerates to test 1, the Frequency (Monobit) test.
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return TotOnline.monobit_test(binary_data[0:block_size])
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# Initialized variables
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block_start = 0
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block_end = block_size
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# Initialize variables
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proportion_sum = 0.0
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# Create a for loop to process each block
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for counter in range(number_of_blocks):
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# Partition the input sequence and get the data for block
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block_start = counter * block_size // 8
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block_end = block_start + block_size // 8
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block_data = binary_data[block_start:block_end]
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# Determine the proportion 蟺i of ones in each M-bit
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# Determine the proportion πi of ones in each M-bit
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one_count = 0
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for bit in block_data:
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if bit == 49:
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one_count += 1
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# compute π
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pi = one_count / block_size
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for byte in block_data:
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for bit in range(8):
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if (byte >> (7 - bit)) & 1 == 1:
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one_count += 1
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# Compute π
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pi = one_count / (block_size * 8) * 8
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# Compute Σ(πi -½)^2.
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proportion_sum += pow(pi - 0.5, 2.0)
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# Next Block
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block_start += block_size
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block_end += block_size
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# Compute 4M Σ(πi -½)^2.
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result = 4.0 * block_size * proportion_sum
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@ -122,27 +122,30 @@ class TotOnline:
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return p_value, (p_value >= 0.01)
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@staticmethod
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def run_test(binary_data: str):
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def run_test(binary_data: bytes):
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vObs = 0
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length_of_binary_data = len(binary_data)
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length_of_binary_data = len(binary_data) * 8
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# Predefined tau = 2 / sqrt(n)
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tau = 2 / sqrt(length_of_binary_data)
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# Step 1 - Compute the pre-test proportion πof ones in the input sequence: π = Σjεj / n
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one_count = binary_data.count(49)
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# Step 1 - Compute the pre-test proportion π of ones in the input sequence: π = Σjεj / n
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one_count = 0
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for byte in binary_data:
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for bit in range(8):
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if (byte >> (7 - bit)) & 1 == 1:
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one_count += 1
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pi = one_count / length_of_binary_data
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# Step 2 - If it can be shown that absolute value of (π - 0.5) is greater than or equal to tau
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# Step 2 - If it can be shown that the absolute value of (π - 0.5) is greater than or equal to tau,
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# then the run test need not be performed.
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if abs(pi - 0.5) >= tau:
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return 0.0000
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else:
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# Step 3 - Compute vObs
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for item in range(1, length_of_binary_data):
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if binary_data[item] != binary_data[item - 1]:
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for i in range(1, length_of_binary_data):
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if ((binary_data[i // 8] >> (7 - (i % 8))) & 1) != ((binary_data[(i - 1) // 8] >> (7 - ((i - 1) % 8))) & 1):
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vObs += 1
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vObs += 1
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@ -152,14 +155,10 @@ class TotOnline:
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return p_value, (p_value > 0.01)
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@staticmethod
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def longest_one_block_test(binary_data: str):
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def longest_one_block_test(binary_data: bytes):
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length_of_binary_data = len(binary_data) * 8
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length_of_binary_data = len(binary_data)
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# print('Length of binary string: ', length_of_binary_data)
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# Initialized k, m. n, pi and v_values
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if length_of_binary_data < 128:
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# Not enough data to run this test
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return 0.00000, 'Error: Not enough data to run this test'
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elif length_of_binary_data < 6272:
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k = 3
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@ -172,7 +171,6 @@ class TotOnline:
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v_values = [4, 5, 6, 7, 8, 9]
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pi_values = [0.1174, 0.2430, 0.2493, 0.1752, 0.1027, 0.1124]
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else:
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# If length_of_bit_string > 750000
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k = 6
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m = 10000
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v_values = [10, 11, 12, 13, 14, 15, 16]
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@ -182,28 +180,24 @@ class TotOnline:
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block_start = 0
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block_end = m
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xObs = 0
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# This will initialize an array with a number of 0 you specified.
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frequencies = zeros(k + 1)
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# print('Number of Blocks: ', number_of_blocks)
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for count in range(number_of_blocks):
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block_data = binary_data[block_start:block_end]
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block_data = binary_data[block_start // 8:block_end // 8]
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max_run_count = 0
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run_count = 0
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# This will count the number of ones in the block
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for bit in block_data:
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if bit == 49:
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run_count += 1
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max_run_count = max(max_run_count, run_count)
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else:
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max_run_count = max(max_run_count, run_count)
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run_count = 0
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for byte in block_data:
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for bit in range(7, -1, -1):
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if (byte >> bit) & 1 == 1:
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run_count += 1
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max_run_count = max(max_run_count, run_count)
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else:
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max_run_count = max(max_run_count, run_count)
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run_count = 0
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max(max_run_count, run_count)
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# print('Block Data: ', block_data, '. Run Count: ', max_run_count)
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if max_run_count < v_values[0]:
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frequencies[0] += 1
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for j in range(k):
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block_start += m
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block_end += m
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# print("Frequencies: ", frequencies)
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# Compute xObs
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for count in range(len(frequencies)):
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xObs += pow((frequencies[count] - (number_of_blocks * pi_values[count])), 2.0) / (
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number_of_blocks * pi_values[count])
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p_value = gammaincc(float(k / 2), float(xObs / 2))
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return p_value, (p_value > 0.01)
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