46 lines
1.4 KiB
Plaintext
46 lines
1.4 KiB
Plaintext
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from math import fabs as fabs
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from math import sqrt as sqrt
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from scipy.special import erfc as erfc
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import numpy as np
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from scipy import stats
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class StartUPTest:
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@staticmethod
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def monobit_test(binary_data: str):
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length_of_bit_string = len(binary_data)
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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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sObs = count / sqrt(length_of_bit_string)
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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 p_value, (p_value >= 0.01)
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@staticmethod
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def chi_square(binary_data: str):
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observed_frequencies = [binary_data.count(48), binary_data.count(49)]
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expected_probabilities = [0.5, 0.5] # Assuming equal probability for each bit value
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total_observations = len(binary_data)
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expected_frequencies = np.array(expected_probabilities) * total_observations
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chi2_statistic, p_value = stats.chisquare(observed_frequencies, f_exp=expected_frequencies)
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return p_value, p_value >= 0.01, chi2_statistic
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