# 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._unknown_k.
Unknown K distance
"""
from ._token_distance import _TokenDistance
__all__ = ['UnknownK']
[docs]class UnknownK(_TokenDistance):
r"""Unknown K distance.
For two sets X and Y and a population N, Unknown K distance, which
:cite:`SequentiX:2018` attributes to "Excoffier" but could not be
located, is
.. math::
dist_{UnknownK}(X, Y) =
|N| \cdot (1 - \frac{|X \cap Y|}{|N|})
In :ref:`2x2 confusion table terms <confusion_table>`, where a+b+c+d=n,
this is
.. math::
dist_{UnknownK} =
n \cdot (1 - \frac{a}{n})
.. versionadded:: 0.4.0
"""
def __init__(
self,
alphabet=None,
tokenizer=None,
intersection_type='crisp',
**kwargs
):
"""Initialize UnknownK 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(UnknownK, self).__init__(
alphabet=alphabet,
tokenizer=tokenizer,
intersection_type=intersection_type,
**kwargs
)
[docs] def dist_abs(self, src, tar):
"""Return the Unknown K 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
Unknown K distance
Examples
--------
>>> cmp = UnknownK()
>>> cmp.dist_abs('cat', 'hat')
782.0
>>> cmp.dist_abs('Niall', 'Neil')
782.0
>>> cmp.dist_abs('aluminum', 'Catalan')
784.0
>>> cmp.dist_abs('ATCG', 'TAGC')
784.0
.. versionadded:: 0.4.0
"""
self._tokenize(src, tar)
a = self._intersection_card()
n = self._population_unique_card()
if not n:
return 0.0
return n * (1 - a / n)
[docs] def dist(self, src, tar):
"""Return the normalized Unknown K 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
Normalized Unknown K distance
Examples
--------
>>> cmp = UnknownK()
>>> cmp.dist('cat', 'hat')
0.9974489795918368
>>> cmp.dist('Niall', 'Neil')
0.9974489795918368
>>> cmp.dist('aluminum', 'Catalan')
0.9987261146496815
>>> cmp.dist('ATCG', 'TAGC')
1.0
.. versionadded:: 0.4.0
"""
score = self.dist_abs(src, tar)
norm = self._population_unique_card()
if score:
return score / norm
return 0.0
if __name__ == '__main__':
import doctest
doctest.testmod()