Source code for abydos.distance._positional_q_gram_overlap

# Copyright 2019-2020 by Christopher C. Little.
# This file is part of Abydos.
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# Abydos is free software: you can redistribute it and/or modify
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"""abydos.distance._positional_q_gram_overlap.

Positional Q-Gram Overlap coefficient
"""

from collections import defaultdict

from ._distance import _Distance
from ..tokenizer import QGrams, WhitespaceTokenizer

__all__ = ['PositionalQGramOverlap']


[docs]class PositionalQGramOverlap(_Distance): r"""Positional Q-Gram Overlap coefficient. Positional Q-Gram Overlap coefficient :cite:`Gravano:2001,Christen:2006` .. versionadded:: 0.4.0 """ def __init__(self, max_dist=1, tokenizer=None, **kwargs): """Initialize PositionalQGramOverlap instance. Parameters ---------- max_dist : int The maximum positional distance between to q-grams to count as a match. tokenizer : _Tokenizer A tokenizer instance from the :py:mod:`abydos.tokenizer` package **kwargs Arbitrary keyword arguments Other Parameters ---------------- qval : int The length of each q-gram. Using this parameter and tokenizer=None will cause the instance to use the QGram tokenizer with this q value. .. versionadded:: 0.4.0 """ super(PositionalQGramOverlap, self).__init__( tokenizer=tokenizer, **kwargs ) self._max_dist = max_dist qval = 2 if 'qval' not in self.params else self.params['qval'] self.params['tokenizer'] = ( tokenizer if tokenizer is not None else WhitespaceTokenizer() if qval == 0 else QGrams(qval=qval, start_stop='$#', skip=0, scaler=None) )
[docs] def sim(self, src, tar): """Return the Positional Q-Gram Overlap coefficient of two strings. Parameters ---------- src : str Source string for comparison tar : str Target string for comparison Returns ------- float Positional Q-Gram Overlap coefficient Examples -------- >>> cmp = PositionalQGramOverlap() >>> cmp.sim('cat', 'hat') 0.5 >>> cmp.sim('Niall', 'Neil') 0.4 >>> cmp.sim('aluminum', 'Catalan') 0.0 >>> cmp.sim('ATCG', 'TAGC') 0.0 .. versionadded:: 0.4.0 """ if src == tar: return 1.0 if not src or not tar: return 0.0 src_list = self.params['tokenizer'].tokenize(src).get_list() tar_list = self.params['tokenizer'].tokenize(tar).get_list() src_pos = defaultdict(list) tar_pos = defaultdict(list) intersection = 0 for pos in range(len(src_list)): src_pos[src_list[pos]].append(pos) for pos in range(len(tar_list)): tar_pos[tar_list[pos]].append(pos) src_matched = [] tar_matched = [] for tok in src_pos: if tok in tar_pos: for sp in src_pos[tok]: for tp in tar_pos[tok]: if ( abs(sp - tp) <= self._max_dist and sp not in src_matched and tp not in tar_matched ): intersection += 1 src_matched.append(sp) tar_matched.append(tp) denom = min(len(src_list), len(tar_list)) return intersection / denom
if __name__ == '__main__': import doctest doctest.testmod()