abydos/distance/_sokal_sneath_ii.py
# Copyright 2018-2020 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._sokal_sneath_ii.
Sokal & Sneath II similarity
"""
from typing import Any, Optional
from ._token_distance import _TokenDistance
from ..tokenizer import _Tokenizer
__all__ = ['SokalSneathII']
class SokalSneathII(_TokenDistance):
r"""Sokal & Sneath II similarity.
For two sets X and Y, Sokal & Sneath II similarity :cite:`Sokal:1963` is
.. math::
sim_{SokalSneathII}(X, Y) =
\frac{|X \cap Y|}
{|X \cap Y| + 2|X \triangle Y|}
This is the second of five "Unnamed coefficients" presented in
:cite:`Sokal:1963`. It corresponds to the "Unmatched pairs carry twice the
weight of matched pairs in the Denominator" with "Negative Matches in
Numerator Excluded".
"Negative Matches in Numerator Included" corresponds to the Rogers &
Tanimoto similarity, :class:`.RogersTanimoto`.
In :ref:`2x2 confusion table terms <confusion_table>`, where a+b+c+d=n,
this is
.. math::
sim_{SokalSneathII} =
\frac{a}{a+2(b+c)}
.. versionadded:: 0.4.0
"""
def __init__(
self,
tokenizer: Optional[_Tokenizer] = None,
intersection_type: str = 'crisp',
**kwargs: Any
) -> None:
"""Initialize SokalSneathII instance.
Parameters
----------
tokenizer : _Tokenizer
A tokenizer instance from the :py:mod:`abydos.tokenizer` package
intersection_type : str
Specifies the intersection type, and set type as a result:
See :ref:`intersection_type <intersection_type>` description in
:py:class:`_TokenDistance` for details.
**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.
metric : _Distance
A string distance measure class for use in the ``soft`` and
``fuzzy`` variants.
threshold : float
A threshold value, similarities above which are counted as
members of the intersection for the ``fuzzy`` variant.
.. versionadded:: 0.4.0
"""
super(SokalSneathII, self).__init__(
tokenizer=tokenizer, intersection_type=intersection_type, **kwargs
)
def sim(self, src: str, tar: str) -> float:
"""Return the Sokal & Sneath II 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
Sokal & Sneath II similarity
Examples
--------
>>> cmp = SokalSneathII()
>>> cmp.sim('cat', 'hat')
0.2
>>> cmp.sim('Niall', 'Neil')
0.125
>>> cmp.sim('aluminum', 'Catalan')
0.03225806451612903
>>> cmp.sim('ATCG', 'TAGC')
0.0
.. versionadded:: 0.4.0
"""
if src == tar:
return 1.0
self._tokenize(src, tar)
a = self._intersection_card()
b = self._src_only_card()
c = self._tar_only_card()
return a / (a + 2 * (b + c))
if __name__ == '__main__':
import doctest
doctest.testmod()