# 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._average_linkage.
Average linkage distance
"""
from ._levenshtein import Levenshtein
from ._token_distance import _TokenDistance
__all__ = ['AverageLinkage']
[docs]class AverageLinkage(_TokenDistance):
r"""Average linkage distance.
For two lists of tokens X and Y, average linkage distance
:cite:`Deza:2016` is
.. math::
dist_{AverageLinkage}(X, Y) =
\frac{\sum_{i \in X} \sum_{j \in Y} dist(X_i, Y_j)}{|X| \cdot |Y|}
.. versionadded:: 0.4.0
"""
def __init__(self, tokenizer=None, metric=None, **kwargs):
"""Initialize AverageLinkage instance.
Parameters
----------
tokenizer : _Tokenizer
A tokenizer instance from the :py:mod:`abydos.tokenizer` package
metric : _Distance
A string distance measure class for use in the ``soft`` and
``fuzzy`` variants. (Defaults to Levenshtein distance)
**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(AverageLinkage, self).__init__(tokenizer=tokenizer, **kwargs)
if metric is None:
self._metric = Levenshtein()
else:
self._metric = metric
[docs] def dist(self, src, tar):
"""Return the average linkage distance 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
average linkage distance
Examples
--------
>>> cmp = AverageLinkage()
>>> cmp.dist('cat', 'hat')
0.8125
>>> cmp.dist('Niall', 'Neil')
0.8333333333333334
>>> cmp.dist('aluminum', 'Catalan')
0.9166666666666666
>>> cmp.dist('ATCG', 'TAGC')
0.8
.. versionadded:: 0.4.0
"""
if not src and not tar:
return 0.0
src = self.params['tokenizer'].tokenize(src).get_list()
tar = self.params['tokenizer'].tokenize(tar).get_list()
if not src or not tar:
return 1.0
num = 0.0
den = len(src) * len(tar)
for term_src in src:
for term_tar in tar:
num += self._metric.dist(term_src, term_tar)
return num / den
if __name__ == '__main__':
import doctest
doctest.testmod()