# Source code for abydos.distance._baroni_urbani_buser_ii

# 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,
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# along with Abydos. If not, see <http://www.gnu.org/licenses/>.

"""abydos.distance._baroni_urbani_buser_ii.

Baroni-Urbani & Buser II correlation
"""

from ._token_distance import _TokenDistance

__all__ = ['BaroniUrbaniBuserII']

[docs]class BaroniUrbaniBuserII(_TokenDistance):
r"""Baroni-Urbani & Buser II correlation.

For two sets X and Y and a population N, the Baroni-Urbani & Buser II
correlation :cite:BaroniUrbani:1976 is

.. math::

corr_{BaroniUrbaniBuserII}(X, Y) =
\frac{\sqrt{|X \cap Y| \cdot |(N \setminus X) \setminus Y|} +
|X \cap Y| - |X \setminus Y| - |Y \setminus X|}
{\sqrt{|X \cap Y| \cdot |(N \setminus X) \setminus Y|} +
|X \cap Y| + |X \setminus Y| + |Y \setminus X|}

This is the first, but less commonly used and referenced of the two
similarities proposed by Baroni-Urbani & Buser.

In :ref:2x2 confusion table terms <confusion_table>, where a+b+c+d=n,
this is

.. math::

corr_{BaroniUrbaniBuserII} =
\frac{\sqrt{ad}+a-b-c}{\sqrt{ad}+a+b+c}

.. versionadded:: 0.4.0
"""

def __init__(
self,
alphabet=None,
tokenizer=None,
intersection_type='crisp',
**kwargs
):
"""Initialize BaroniUrbaniBuserII 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(BaroniUrbaniBuserII, self).__init__(
alphabet=alphabet,
tokenizer=tokenizer,
intersection_type=intersection_type,
**kwargs
)

[docs]    def corr(self, src, tar):
"""Return the Baroni-Urbani & Buser II 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
Baroni-Urbani & Buser II correlation

Examples
--------
>>> cmp = BaroniUrbaniBuserII()
>>> cmp.corr('cat', 'hat')
0.8239675481756209
>>> cmp.corr('Niall', 'Neil')
0.7105646350028408
>>> cmp.corr('aluminum', 'Catalan')
0.31398542410970204
>>> cmp.corr('ATCG', 'TAGC')
-1.0

.. 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()
d = self._total_complement_card()

return ((a * d) ** 0.5 + a - b - c) / ((a * d) ** 0.5 + a + b + c)

[docs]    def sim(self, src, tar):
"""Return the Baroni-Urbani & Buser 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
Baroni-Urbani & Buser II similarity

Examples
--------
>>> cmp = BaroniUrbaniBuserII()
>>> cmp.sim('cat', 'hat')
0.9119837740878105
>>> cmp.sim('Niall', 'Neil')
0.8552823175014204
>>> cmp.sim('aluminum', 'Catalan')
0.656992712054851
>>> cmp.sim('ATCG', 'TAGC')
0.0

.. versionadded:: 0.4.0

"""
return (self.corr(src, tar) + 1) / 2

if __name__ == '__main__':
import doctest

doctest.testmod()