# 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_i.
Kent & Foster I similarity
"""
from ._token_distance import _TokenDistance
__all__ = ['KentFosterI']
[docs]class KentFosterI(_TokenDistance):
r"""Kent & Foster I similarity.
For two sets X and Y and a population N, Kent & Foster I similarity
:cite:`Kent:1977`, :math:`K_{occ}`, is
.. math::
sim_{KentFosterI}(X, Y) =
\frac{|X \cap Y| - \frac{|X|\cdot|Y|}{|X \cup Y|}}
{|X \cap Y| - \frac{|X|\cdot|Y|}{|X \cup 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 occurrence reliability measure.
In :ref:`2x2 confusion table terms <confusion_table>`, where a+b+c+d=n,
this is
.. math::
sim_{KentFosterI} =
\frac{a-\frac{(a+b)(a+c)}{a+b+c}}{a-\frac{(a+b)(a+c)}{a+b+c}+b+c}
.. versionadded:: 0.4.0
"""
def __init__(
self,
alphabet=None,
tokenizer=None,
intersection_type='crisp',
**kwargs
):
"""Initialize KentFosterI 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(KentFosterI, self).__init__(
alphabet=alphabet,
tokenizer=tokenizer,
intersection_type=intersection_type,
**kwargs
)
[docs] def sim_score(self, src, tar):
"""Return the Kent & Foster I 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 I similarity
Examples
--------
>>> cmp = KentFosterI()
>>> cmp.sim_score('cat', 'hat')
-0.19999999999999996
>>> cmp.sim_score('Niall', 'Neil')
-0.23529411764705888
>>> cmp.sim_score('aluminum', 'Catalan')
-0.30434782608695654
>>> cmp.sim_score('ATCG', 'TAGC')
-0.3333333333333333
.. versionadded:: 0.4.0
"""
self._tokenize(src, tar)
a = self._intersection_card()
b = self._src_only_card()
c = self._tar_only_card()
num = (a + b) * (a + c)
if not num:
bigterm = a
else:
bigterm = a - (num / (a + b + c))
if bigterm:
return bigterm / (bigterm + b + c)
return 0.0
[docs] def sim(self, src, tar):
"""Return the normalized Kent & Foster I 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 I similarity
Examples
--------
>>> cmp = KentFosterI()
>>> cmp.sim('cat', 'hat')
0.8
>>> cmp.sim('Niall', 'Neil')
0.7647058823529411
>>> cmp.sim('aluminum', 'Catalan')
0.6956521739130435
>>> cmp.sim('ATCG', 'TAGC')
0.6666666666666667
.. versionadded:: 0.4.0
"""
return 1.0 + self.sim_score(src, tar)
if __name__ == '__main__':
import doctest
doctest.testmod()