# Copyright 2014-2020 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._mra.
The Match Rating Algorithm's distance measure
"""
from ._distance import _Distance
from ..phonetic import MRA as MRAPhonetic # noqa: N811
__all__ = ['MRA']
[docs]
class MRA(_Distance):
"""Match Rating Algorithm comparison rating.
The Western Airlines Surname Match Rating Algorithm comparison rating, as
presented on page 18 of :cite:`Moore:1977`.
.. versionadded:: 0.3.6
"""
_phonetic_alg = MRAPhonetic()
[docs]
def dist_abs(self, src: str, tar: str) -> float:
"""Return the MRA comparison rating of two strings.
Parameters
----------
src : str
Source string for comparison
tar : str
Target string for comparison
Returns
-------
int
MRA comparison rating
Examples
--------
>>> cmp = MRA()
>>> cmp.dist_abs('cat', 'hat')
5
>>> cmp.dist_abs('Niall', 'Neil')
6
>>> cmp.dist_abs('aluminum', 'Catalan')
0
>>> cmp.dist_abs('ATCG', 'TAGC')
5
.. versionadded:: 0.1.0
.. versionchanged:: 0.3.6
Encapsulated in class
"""
if src == tar:
return 6
if src == '' or tar == '':
return 0
src_tok = list(self._phonetic_alg.encode(src))
tar_tok = list(self._phonetic_alg.encode(tar))
if abs(len(src_tok) - len(tar_tok)) > 2:
return 0
length_sum = len(src_tok) + len(tar_tok)
if length_sum < 5:
min_rating = 5
elif length_sum < 8:
min_rating = 4
elif length_sum < 12:
min_rating = 3
else:
min_rating = 2
for _ in range(2):
new_src = []
new_tar = []
minlen = min(len(src_tok), len(tar_tok))
for i in range(minlen):
if src_tok[i] != tar_tok[i]:
new_src.append(src_tok[i])
new_tar.append(tar_tok[i])
src_tok = new_src + src_tok[minlen:]
tar_tok = new_tar + tar_tok[minlen:]
src_tok.reverse()
tar_tok.reverse()
similarity = 6 - max(len(src_tok), len(tar_tok))
if similarity >= min_rating:
return similarity
return 0
[docs]
def sim(self, src: str, tar: str) -> float:
"""Return the normalized MRA similarity of two strings.
This is the MRA normalized to :math:`[0, 1]`, given that MRA itself is
constrained to the range :math:`[0, 6]`.
Parameters
----------
src : str
Source string for comparison
tar : str
Target string for comparison
Returns
-------
float
Normalized MRA similarity
Examples
--------
>>> cmp = MRA()
>>> cmp.sim('cat', 'hat')
0.8333333333333334
>>> cmp.sim('Niall', 'Neil')
1.0
>>> cmp.sim('aluminum', 'Catalan')
0.0
>>> cmp.sim('ATCG', 'TAGC')
0.8333333333333334
.. versionadded:: 0.1.0
.. versionchanged:: 0.3.6
Encapsulated in class
"""
return self.dist_abs(src, tar) / 6
if __name__ == '__main__':
import doctest
doctest.testmod()