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81 lines
2.1 KiB
Python
81 lines
2.1 KiB
Python
"""https://en.wikipedia.org/wiki/Jaro%E2%80%93Winkler_distance"""
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def jaro_winkler(str1: str, str2: str) -> float:
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"""
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Jaro-Winkler distance is a string metric measuring an edit distance between two
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sequences.
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Output value is between 0.0 and 1.0.
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>>> jaro_winkler("martha", "marhta")
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0.9611111111111111
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>>> jaro_winkler("CRATE", "TRACE")
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0.7333333333333334
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>>> jaro_winkler("test", "dbdbdbdb")
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0.0
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>>> jaro_winkler("test", "test")
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1.0
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>>> jaro_winkler("hello world", "HeLLo W0rlD")
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0.6363636363636364
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>>> jaro_winkler("test", "")
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0.0
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>>> jaro_winkler("hello", "world")
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0.4666666666666666
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>>> jaro_winkler("hell**o", "*world")
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0.4365079365079365
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"""
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def get_matched_characters(_str1: str, _str2: str) -> str:
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matched = []
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limit = min(len(_str1), len(_str2)) // 2
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for i, char in enumerate(_str1):
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left = int(max(0, i - limit))
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right = int(min(i + limit + 1, len(_str2)))
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if char in _str2[left:right]:
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matched.append(char)
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_str2 = (
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f"{_str2[0 : _str2.index(char)]} {_str2[_str2.index(char) + 1 :]}"
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)
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return "".join(matched)
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# matching characters
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matching_1 = get_matched_characters(str1, str2)
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matching_2 = get_matched_characters(str2, str1)
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match_count = len(matching_1)
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# transposition
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transpositions = (
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len([(c1, c2) for c1, c2 in zip(matching_1, matching_2) if c1 != c2]) // 2
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)
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if not match_count:
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jaro = 0.0
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else:
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jaro = (
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1
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/ 3
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* (
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match_count / len(str1)
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+ match_count / len(str2)
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+ (match_count - transpositions) / match_count
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)
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)
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# common prefix up to 4 characters
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prefix_len = 0
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for c1, c2 in zip(str1[:4], str2[:4]):
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if c1 == c2:
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prefix_len += 1
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else:
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break
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return jaro + 0.1 * prefix_len * (1 - jaro)
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if __name__ == "__main__":
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import doctest
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doctest.testmod()
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print(jaro_winkler("hello", "world"))
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