# 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._kent_foster_ii.
Kent & Foster II similarity
"""
from ._token_distance import _TokenDistance
__all__ = ['KentFosterII']
[docs]class KentFosterII(_TokenDistance):
r"""Kent & Foster II similarity.
For two sets X and Y and a population N, Kent & Foster II similarity
:cite:`Kent:1977`, :math:`K_{nonocc}`, is
.. math::
sim_{KentFosterII}(X, Y) =
\frac{|(N \setminus X) \setminus Y| -
\frac{|X \setminus Y|\cdot|Y \setminus X|}
{|N \setminus (X \cap Y)|}}
{|(N \setminus X) \setminus Y| -
\frac{|X \setminus Y|\cdot|Y \setminus X|}
{|N \setminus (X \cap Y)|} +
|X \setminus Y| + |Y \setminus X|}
Kent & Foster derived this from Cohen's :math:`\kappa` by "subtracting
appropriate chance agreement correction figures from the numerators and
denominators" to arrive at an non-occurrence reliability measure.
In :ref:`2x2 confusion table terms <confusion_table>`, where a+b+c+d=n,
this is
.. math::
sim_{KentFosterII} =
\frac{d-\frac{(b+d)(c+d)}{b+c+d}}{d-\frac{(b+d)(c+d)}{b+c+d}+b+c}
.. versionadded:: 0.4.0
"""
def __init__(
self,
alphabet=None,
tokenizer=None,
intersection_type='crisp',
**kwargs
):
"""Initialize KentFosterII instance.
Parameters
----------
alphabet : Counter, collection, int, or None
This represents the alphabet of possible tokens.
See :ref:`alphabet <alphabet>` description in
:py:class:`_TokenDistance` for details.
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(KentFosterII, self).__init__(
alphabet=alphabet,
tokenizer=tokenizer,
intersection_type=intersection_type,
**kwargs
)
[docs] def sim_score(self, src, tar):
"""Return the Kent & Foster 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
Kent & Foster II similarity
Examples
--------
>>> cmp = KentFosterII()
>>> cmp.sim_score('cat', 'hat')
-0.0012804097311239404
>>> cmp.sim_score('Niall', 'Neil')
-0.002196997436837158
>>> cmp.sim_score('aluminum', 'Catalan')
-0.004784688995214218
>>> cmp.sim_score('ATCG', 'TAGC')
-0.0031989763275758767
.. versionadded:: 0.4.0
"""
self._tokenize(src, tar)
b = self._src_only_card()
c = self._tar_only_card()
d = self._total_complement_card()
num = (b + d) * (c + d)
if not num:
bigterm = d
else:
bigterm = d - (num / (b + c + d))
if bigterm:
return bigterm / (bigterm + b + c)
return 0.0
[docs] def sim(self, src, tar):
"""Return the normalized Kent & Foster 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
Normalized Kent & Foster II similarity
Examples
--------
>>> cmp = KentFosterII()
>>> cmp.sim('cat', 'hat')
0.998719590268876
>>> cmp.sim('Niall', 'Neil')
0.9978030025631628
>>> cmp.sim('aluminum', 'Catalan')
0.9952153110047858
>>> cmp.sim('ATCG', 'TAGC')
0.9968010236724241
.. versionadded:: 0.4.0
"""
return 1.0 + self.sim_score(src, tar)
if __name__ == '__main__':
import doctest
doctest.testmod()