39 lines
1.2 KiB
Python
39 lines
1.2 KiB
Python
from scipy.stats import fisher_exact
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def fisher_excat_upper(
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correct_pattern_count: int, number_of_pattern: int, p_threshold: float = 5.0 / 100.0
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) -> float:
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error_pattern_count = int(number_of_pattern - correct_pattern_count)
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bound = 100.0
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for u in range(0, correct_pattern_count):
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z = int(error_pattern_count + u)
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_, pvalue = fisher_exact(
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[[correct_pattern_count, error_pattern_count], [number_of_pattern - z, z]],
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alternative="greater",
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)
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if bool(pvalue > p_threshold) is False:
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bound = u * 100.0 / number_of_pattern
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break
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return bound
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def fisher_excat_lower(
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correct_pattern_count: int, number_of_pattern: int, p_threshold: float = 5.0 / 100.0
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) -> float:
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error_pattern_count = int(number_of_pattern - correct_pattern_count)
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bound = 0.0
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for u in range(0, error_pattern_count):
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z = int(error_pattern_count - u)
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_, pvalue = fisher_exact(
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[[correct_pattern_count, error_pattern_count], [number_of_pattern - z, z]],
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alternative="less",
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)
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if bool(pvalue > p_threshold) is False:
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bound = u * 100.0 / number_of_pattern
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break
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return bound
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