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# Copyright 2019-2020 by Christopher C. Little. |
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# This file is part of Abydos. |
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# |
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# Abydos is free software: you can redistribute it and/or modify |
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# it under the terms of the GNU General Public License as published by |
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# the Free Software Foundation, either version 3 of the License, or |
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# (at your option) any later version. |
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# |
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# Abydos is distributed in the hope that it will be useful, |
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# but WITHOUT ANY WARRANTY; without even the implied warranty of |
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# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the |
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# GNU General Public License for more details. |
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# |
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# You should have received a copy of the GNU General Public License |
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# along with Abydos. If not, see <http://www.gnu.org/licenses/>. |
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"""abydos.distance._guth. |
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Guth matching algorithm |
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""" |
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from typing import Any, List, Optional, Union |
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from ._distance import _Distance |
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from ..tokenizer import QGrams, _Tokenizer |
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__all__ = ['Guth'] |
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class Guth(_Distance): |
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r"""Guth matching. |
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Guth matching :cite:`Guth:1976` uses a simple positional matching rule list |
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to determine whether two names match. Following the original, the |
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:meth:`.sim_score` method returns only 1.0 for matching or 0.0 for |
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non-matching. |
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1 |
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The :math:`.sim` mathod instead penalizes more distant matches and never |
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outrightly declares two names a non-matching unless no matches can be made |
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in the two strings. |
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Tokens other than single characters can be matched by specifying a |
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tokenizer during initialization or setting the qval parameter. |
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.. versionadded:: 0.4.1 |
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""" |
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def __init__( |
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self, tokenizer: Optional[_Tokenizer] = None, **kwargs: Any |
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) -> None: |
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"""Initialize Guth instance. |
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Parameters |
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---------- |
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tokenizer : _Tokenizer |
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A tokenizer instance from the :py:mod:`abydos.tokenizer` package |
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**kwargs |
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Arbitrary keyword arguments |
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Other Parameters |
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---------------- |
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qval : int |
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The length of each q-gram. Using this parameter and tokenizer=None |
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will cause the instance to use the QGram tokenizer with this |
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q value. |
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.. versionadded:: 0.4.1 |
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""" |
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super(Guth, self).__init__(**kwargs) |
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self.params['tokenizer'] = tokenizer |
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if 'qval' in self.params: |
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self.params['tokenizer'] = QGrams( |
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qval=self.params['qval'], start_stop='$#', skip=0, scaler=None |
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) |
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def _token_at( |
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self, name: Union[List[str], str], pos: int |
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) -> Optional[str]: |
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"""Return the token of name at position pos. |
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Parameters |
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---------- |
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name : str or list |
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A string (or list) from which to return a token |
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pos : int |
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The position of the token to return |
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Returns |
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------- |
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str |
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The requested token or None if the position is invalid |
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.. versionadded:: 0.4.1 |
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""" |
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if pos < 0: |
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return None |
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if pos >= len(name): |
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return None |
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return name[pos] |
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def sim_score(self, src: str, tar: str) -> float: |
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"""Return the Guth matching score of two strings. |
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Parameters |
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---------- |
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src : str |
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Source string for comparison |
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tar : str |
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Target string for comparison |
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Returns |
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------- |
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float |
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Guth matching score (1.0 if matching, otherwise 0.0) |
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Examples |
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-------- |
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>>> cmp = Guth() |
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>>> cmp.sim_score('cat', 'hat') |
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1.0 |
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>>> cmp.sim_score('Niall', 'Neil') |
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1.0 |
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>>> cmp.sim_score('aluminum', 'Catalan') |
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0.0 |
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>>> cmp.sim_score('ATCG', 'TAGC') |
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1.0 |
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.. versionadded:: 0.4.1 |
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""" |
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if src == tar: |
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return 1.0 |
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if not src or not tar: |
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return 0.0 |
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if self.params['tokenizer']: |
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src = self.params['tokenizer'].tokenize(src).get_list() |
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tar = self.params['tokenizer'].tokenize(tar).get_list() |
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for pos in range(len(src)): |
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s = self._token_at(src, pos) |
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if s and s in set(tar[max(0, pos - 1) : pos + 3]): |
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continue |
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t = self._token_at(tar, pos) |
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if t and t in set(src[max(0, pos - 1) : pos + 3]): |
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continue |
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s = self._token_at(src, pos + 1) |
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t = self._token_at(tar, pos + 1) |
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if s and t and s == t: |
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continue |
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s = self._token_at(src, pos + 2) |
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t = self._token_at(tar, pos + 2) |
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if s and t and s == t: |
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continue |
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break |
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else: |
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return 1.0 |
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return 0.0 |
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def sim(self, src: str, tar: str) -> float: |
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"""Return the relative Guth similarity of two strings. |
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This deviates from the algorithm described in :cite:`Guth:1976` in that |
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more distant matches are penalized, so that less similar terms score |
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lower that more similar terms. |
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If no match is found for a particular token in the source string, this |
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does not result in an automatic 0.0 score. Rather, the score is further |
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penalized towards 0.0. |
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Parameters |
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---------- |
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src : str |
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Source string for comparison |
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tar : str |
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Target string for comparison |
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Returns |
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------- |
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float |
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Relative Guth matching score |
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Examples |
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-------- |
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>>> cmp = Guth() |
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>>> cmp.sim('cat', 'hat') |
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0.8666666666666667 |
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>>> cmp.sim('Niall', 'Neil') |
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0.8800000000000001 |
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>>> cmp.sim('aluminum', 'Catalan') |
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0.4 |
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>>> cmp.sim('ATCG', 'TAGC') |
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0.8 |
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.. versionadded:: 0.4.1 |
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""" |
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if src == tar: |
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return 1.0 |
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if not src or not tar: |
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return 0.0 |
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if self.params['tokenizer']: |
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src = self.params['tokenizer'].tokenize(src).get_list() |
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tar = self.params['tokenizer'].tokenize(tar).get_list() |
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score = 0.0 |
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for pos in range(len(src)): |
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s = self._token_at(src, pos) |
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t = self._token_at(tar, pos) |
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if s and t and s == t: |
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score += 1.0 |
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continue |
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t = self._token_at(tar, pos + 1) |
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if s and t and s == t: |
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score += 0.8 |
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continue |
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t = self._token_at(tar, pos + 2) |
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if s and t and s == t: |
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score += 0.6 |
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continue |
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t = self._token_at(tar, pos - 1) |
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if s and t and s == t: |
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score += 0.8 |
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continue |
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s = self._token_at(src, pos - 1) |
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t = self._token_at(tar, pos) |
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if s and t and s == t: |
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score += 0.8 |
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continue |
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s = self._token_at(src, pos + 1) |
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if s and t and s == t: |
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score += 0.8 |
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continue |
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s = self._token_at(src, pos + 2) |
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if s and t and s == t: |
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score += 0.6 |
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continue |
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s = self._token_at(src, pos + 1) |
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t = self._token_at(tar, pos + 1) |
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if s and t and s == t: |
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score += 0.6 |
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continue |
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s = self._token_at(src, pos + 2) |
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t = self._token_at(tar, pos + 2) |
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if s and t and s == t: |
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score += 0.2 |
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continue |
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return score / len(src) |
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if __name__ == '__main__': |
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import doctest |
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doctest.testmod() |
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chrislit /
abydos
