# Copyright 2019-2020 by Christopher C. Little.
# This file is part of Abydos.
#
# Abydos is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# Abydos is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with Abydos. If not, see <http://www.gnu.org/licenses/>.
"""abydos.distance._fuzzywuzzy_token_set.
FuzzyWuzzy Token Set similarity
"""
from difflib import SequenceMatcher
from ._token_distance import _TokenDistance
from ..tokenizer import RegexpTokenizer
__all__ = ['FuzzyWuzzyTokenSet']
[docs]class FuzzyWuzzyTokenSet(_TokenDistance):
r"""FuzzyWuzzy Token Set similarity.
This follows the FuzzyWuzzy Token Set similarity algorithm
:cite:`Cohen:2011`. Rather than returning an integer in the range [0, 100],
as demonstrated in the blog post, this implementation returns a float in
the range [0.0, 1.0]. Distinct from the
.. versionadded:: 0.4.0
"""
def __init__(self, tokenizer=None, **kwargs):
"""Initialize FuzzyWuzzyTokenSet instance.
Parameters
----------
tokenizer : _Tokenizer
A tokenizer instance from the :py:mod:`abydos.tokenizer` package.
By default, the regexp tokenizer is employed, matching only
letters.
**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
"""
if tokenizer is None:
tokenizer = RegexpTokenizer()
super(FuzzyWuzzyTokenSet, self).__init__(tokenizer=tokenizer, **kwargs)
[docs] def sim(self, src, tar):
"""Return the FuzzyWuzzy Token Set similarity of two strings.
Parameters
----------
src : str
Source string (or QGrams/Counter objects) for comparison
tar : str
Target string (or QGrams/Counter objects) for comparison
Returns
-------
float
FuzzyWuzzy Token Set similarity
Examples
--------
>>> cmp = FuzzyWuzzyTokenSet()
>>> cmp.sim('cat', 'hat')
0.75
>>> cmp.sim('Niall', 'Neil')
0.7272727272727273
>>> cmp.sim('aluminum', 'Catalan')
0.47058823529411764
>>> cmp.sim('ATCG', 'TAGC')
0.6
.. versionadded:: 0.4.0
"""
src = self.params['tokenizer'].tokenize(src).get_set()
tar = self.params['tokenizer'].tokenize(tar).get_set()
intersection = src & tar
src -= intersection
tar -= intersection
intersection = ' '.join(sorted(intersection)) + ' '
src = intersection + ' '.join(sorted(src))
tar = intersection + ' '.join(sorted(tar))
return max(
SequenceMatcher(None, src, intersection).ratio(),
SequenceMatcher(None, intersection, tar).ratio(),
SequenceMatcher(None, src, tar).ratio(),
)
if __name__ == '__main__':
import doctest
doctest.testmod()