# 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._discounted_hamming.
Relaxed Hamming distance
"""
from ._distance import _Distance
from ..tokenizer import QGrams
__all__ = ['RelaxedHamming']
[docs]class RelaxedHamming(_Distance):
"""Relaxed Hamming distance.
This is a variant of Hamming distance in which positionally close matches
are considered partially matching.
.. versionadded:: 0.4.1
"""
def __init__(self, tokenizer=None, maxdist=2, discount=0.2, **kwargs):
"""Initialize DiscountedHamming instance.
Parameters
----------
tokenizer : _Tokenizer
A tokenizer instance from the :py:mod:`abydos.tokenizer` package
maxdist : int
The maximum distance to consider for discounting.
discount : float
The discount factor multiplied by the distance from the source
string position.
**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:: 0.4.1
"""
super(RelaxedHamming, self).__init__(**kwargs)
self.params['tokenizer'] = tokenizer
if 'qval' in self.params:
self.params['tokenizer'] = QGrams(
qval=self.params['qval'], start_stop='$#', skip=0, scaler=None
)
self._maxdist = maxdist
self._discount = discount
[docs] def dist_abs(self, src, tar):
"""Return the discounted Hamming distance between two strings.
Parameters
----------
src : str
Source string for comparison
tar : str
Target string for comparison
Returns
-------
float
Relaxed Hamming distance
Examples
--------
>>> cmp = RelaxedHamming()
>>> cmp.dist_abs('cat', 'hat')
1.0
>>> cmp.dist_abs('Niall', 'Neil')
1.4
>>> cmp.dist_abs('aluminum', 'Catalan')
6.4
>>> cmp.dist_abs('ATCG', 'TAGC')
0.8
.. versionadded:: 0.4.1
"""
if src == tar:
return 0
if len(src) != len(tar):
replacement_char = 1
while chr(replacement_char) in src or chr(replacement_char) in tar:
replacement_char += 1
replacement_char = chr(replacement_char)
if len(src) < len(tar):
src += replacement_char * (len(tar) - len(src))
else:
tar += replacement_char * (len(src) - len(tar))
if self.params['tokenizer']:
src = self.params['tokenizer'].tokenize(src).get_list()
tar = self.params['tokenizer'].tokenize(tar).get_list()
score = 0
for pos in range(len(src)):
if src[pos] == tar[pos : pos + 1][0]:
continue
try:
diff = (
tar[pos + 1 : pos + self._maxdist + 1].index(src[pos]) + 1
)
except ValueError:
diff = 0
try:
found = (
tar[max(0, pos - self._maxdist) : pos][::-1].index(
src[pos]
)
+ 1
)
except ValueError:
found = 0
if found and diff:
diff = min(diff, found)
elif found:
diff = found
if diff:
score += min(1.0, self._discount * diff)
else:
score += 1.0
return score
[docs] def dist(self, src, tar):
"""Return the normalized relaxed Hamming distance between strings.
Parameters
----------
src : str
Source string for comparison
tar : str
Target string for comparison
Returns
-------
float
Normalized relaxed Hamming distance
Examples
--------
>>> cmp = RelaxedHamming()
>>> round(cmp.dist('cat', 'hat'), 12)
0.333333333333
>>> cmp.dist('Niall', 'Neil')
0.27999999999999997
>>> cmp.dist('aluminum', 'Catalan')
0.8
>>> cmp.dist('ATCG', 'TAGC')
0.2
.. versionadded:: 0.4.1
"""
if src == tar:
return 0.0
score = self.dist_abs(src, tar)
if self.params['tokenizer']:
src = self.params['tokenizer'].tokenize(src).get_list()
tar = self.params['tokenizer'].tokenize(tar).get_list()
return score / max(len(src), len(tar))
if __name__ == '__main__':
import doctest
doctest.testmod()