# Source code for abydos.distance._baulieu_v

# Copyright 2019-2020 by Christopher C. Little.
# This file is part of Abydos.
#
# Abydos is free software: you can redistribute it and/or modify
# 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._baulieu_v.

Baulieu V distance
"""

from ._token_distance import _TokenDistance

__all__ = ['BaulieuV']

[docs]class BaulieuV(_TokenDistance):
r"""Baulieu V distance.

For two sets X and Y and a population N, Baulieu V distance
:cite:Baulieu:1997 is

.. math::

dist_{BaulieuV}(X, Y) = \frac{|X \setminus Y| + |Y \setminus X| +
1}{|X \cap Y| + |X \setminus Y| + |Y \setminus X| + 1}

This is Baulieu's 23rd dissimilarity coefficient. This coefficient fails
Baulieu's (P2) property, that :math:D(a,0,0,0) = 0. Rather,
:math:D(a,0,0,0) > 0, but
:math:\lim_{a \to \infty} D(a,0,0,0) = 0.

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

.. math::

dist_{BaulieuV} = \frac{b+c+1}{a+b+c+1}

"""

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

"""
super(BaulieuV, self).__init__(
alphabet=alphabet,
tokenizer=tokenizer,
intersection_type=intersection_type,
**kwargs
)

[docs]    def dist(self, src, tar):
"""Return the Baulieu V distance 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
Baulieu V distance

Examples
--------
>>> cmp = BaulieuV()
>>> cmp.dist('cat', 'hat')
0.7142857142857143
>>> cmp.dist('Niall', 'Neil')
0.8
>>> cmp.dist('aluminum', 'Catalan')
0.9411764705882353
>>> cmp.dist('ATCG', 'TAGC')
1.0

"""
self._tokenize(src, tar)

a = self._intersection_card()
b = self._src_only_card()
c = self._tar_only_card()

return (b + c + 1) / (a + b + c + 1)

if __name__ == '__main__':
import doctest

doctest.testmod()