# 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._henderson_heron.
Henderson-Heron dissimilarity
"""
from math import factorial
from ._token_distance import _TokenDistance
__all__ = ['HendersonHeron']
[docs]class HendersonHeron(_TokenDistance):
r"""Henderson-Heron dissimilarity.
For two sets X and Y and a population N, Henderson-Heron dissimilarity
:cite:`Henderson:1977` is:
.. math:
sim_{Henderson-Heron}(X, Y) = \frac{|X|! |Y|! (|N| - |X|)!
(|N|- |Y|)!}{|N|! |X \cap Y|! (|X| - |X \cap Y|)!
(|Y| - |Y \cap X|)! (|N| - |X| - |Y| + |X \cap Y|)!}
.. versionadded:: 0.4.1
"""
def __init__(self, **kwargs):
"""Initialize HendersonHeron instance.
Parameters
----------
**kwargs
Arbitrary keyword arguments
.. versionadded:: 0.4.1
"""
super(HendersonHeron, self).__init__(**kwargs)
[docs] def dist(self, src, tar):
"""Return the Henderson-Heron dissimilarity of two strings.
Parameters
----------
src : str
Source string for comparison
tar : str
Target string for comparison
Returns
-------
float
Henderson-Heron dissimilarity
Examples
--------
>>> cmp = HendersonHeron()
>>> cmp.dist('cat', 'hat')
0.00011668873858680838
>>> cmp.dist('Niall', 'Neil')
0.00048123075776606097
>>> cmp.dist('aluminum', 'Catalan')
0.08534181060514882
>>> cmp.dist('ATCG', 'TAGC')
0.9684367974410505
.. versionadded:: 0.4.1
"""
self._tokenize(src, tar)
a = self._intersection_card()
ab = self._src_card()
ac = self._tar_card()
n = self._population_unique_card()
return (
factorial(ab)
* factorial(ac)
* factorial(n - ab)
* factorial(n - ac)
/ (
factorial(n)
* factorial(a)
* factorial(ab - a)
* factorial(ac - a)
* factorial((n - ac - ab + a))
)
)
if __name__ == '__main__':
import doctest
doctest.testmod()