# Source code for abydos.distance._gwet_ac

# 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._gwet_ac.

Gwet's AC correlation
"""

from ._token_distance import _TokenDistance

__all__ = ['GwetAC']

[docs]class GwetAC(_TokenDistance): r"""Gwet's AC correlation. For two sets X and Y and a population N, Gwet's AC correlation :cite:Gwet:2008 is .. math:: corr_{Gwet_{AC}}(X, Y) = AC = \frac{p_o - p_e^{AC}}{1 - p_e^{AC}} where .. math:: \begin{array}{lll} p_o &=&\frac{|X \cap Y| + |(N \setminus X) \setminus Y|}{|N|} p_e^{AC}&=&\frac{1}{2}\Big(\frac{|X|+|Y|}{|N|}\cdot \frac{|X \setminus Y| + |Y \setminus X|}{|N|}\Big) \end{array} In :ref:2x2 confusion table terms <confusion_table>, where a+b+c+d=n, this is .. math:: \begin{array}{lll} p_o&=&\frac{a+d}{n} p_e^{AC}&=&\frac{1}{2}\Big(\frac{2a+b+c}{n}\cdot \frac{2d+b+c}{n}\Big) \end{array} .. versionadded:: 0.4.0 """ def __init__( self, alphabet=None, tokenizer=None, intersection_type='crisp', **kwargs ): """Initialize GwetAC 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(GwetAC, self).__init__( alphabet=alphabet, tokenizer=tokenizer, intersection_type=intersection_type, **kwargs )
[docs] def corr(self, src, tar): """Return the Gwet's AC correlation 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 Gwet's AC correlation Examples -------- >>> cmp = GwetAC() >>> cmp.corr('cat', 'hat') 0.9948456319360438 >>> cmp.corr('Niall', 'Neil') 0.990945276504824 >>> cmp.corr('aluminum', 'Catalan') 0.9804734301840141 >>> cmp.corr('ATCG', 'TAGC') 0.9870811678360627 .. 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() d = self._total_complement_card() n = a + b + c + d po = (a + d) / n q = (2 * a + b + c) / (2 * n) pe = 2 * q * (1 - q) return (po - pe) / (1 - pe)
[docs] def sim(self, src, tar): """Return the Gwet's AC 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 Gwet's AC similarity Examples -------- >>> cmp = GwetAC() >>> cmp.sim('cat', 'hat') 0.9974228159680218 >>> cmp.sim('Niall', 'Neil') 0.995472638252412 >>> cmp.sim('aluminum', 'Catalan') 0.9902367150920071 >>> cmp.sim('ATCG', 'TAGC') 0.9935405839180314 .. versionadded:: 0.4.0 """ return (1.0 + self.corr(src, tar)) / 2.0
if __name__ == '__main__': import doctest doctest.testmod()