abydos/distance/_baroni_urbani_buser_i.py
# 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.
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# 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._baroni_urbani_buser_i.
Baroni-Urbani & Buser I similarity
"""
from typing import Any, Counter as TCounter, Optional, Sequence, Set, Union
from ._token_distance import _TokenDistance
from ..tokenizer import _Tokenizer
__all__ = ['BaroniUrbaniBuserI']
class BaroniUrbaniBuserI(_TokenDistance):
r"""Baroni-Urbani & Buser I similarity.
For two sets X and Y and a population N, the Baroni-Urbani & Buser I
similarity :cite:`BaroniUrbani:1976` is
.. math::
sim_{BaroniUrbaniBuserI}(X, Y) =
\frac{\sqrt{|X \cap Y| \cdot |(N \setminus X) \setminus Y|} +
|X \cap Y|}
{\sqrt{|X \cap Y| \cdot |(N \setminus X) \setminus Y|} +
|X \cap Y| + |X \setminus Y| + |Y \setminus X|}
This is the second, but more 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::
sim_{BaroniUrbaniBuserI} =
\frac{\sqrt{ad}+a}{\sqrt{ad}+a+b+c}
.. versionadded:: 0.4.0
"""
def __init__(
self,
alphabet: Optional[
Union[TCounter[str], Sequence[str], Set[str], int]
] = None,
tokenizer: Optional[_Tokenizer] = None,
intersection_type: str = 'crisp',
**kwargs: Any
) -> None:
"""Initialize BaroniUrbaniBuserI 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(BaroniUrbaniBuserI, self).__init__(
alphabet=alphabet,
tokenizer=tokenizer,
intersection_type=intersection_type,
**kwargs
)
def sim(self, src: str, tar: str) -> float:
"""Return the Baroni-Urbani & Buser 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
Baroni-Urbani & Buser I similarity
Examples
--------
>>> cmp = BaroniUrbaniBuserI()
>>> cmp.sim('cat', 'hat')
0.9119837740878104
>>> cmp.sim('Niall', 'Neil')
0.8552823175014205
>>> cmp.sim('aluminum', 'Catalan')
0.656992712054851
>>> cmp.sim('ATCG', 'TAGC')
0.0
.. 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) / ((a * d) ** 0.5 + a + b + c)
if __name__ == '__main__':
import doctest
doctest.testmod()