Source code for abydos.distance._fossum

# 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
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"""abydos.distance._fossum.

Fossum similarity
"""

from ._token_distance import _TokenDistance

__all__ = ['Fossum']


[docs]class Fossum(_TokenDistance): r"""Fossum similarity. For two sets X and Y and a population N, the Fossum similarity :cite:`Fossum:1966` is .. math:: sim_{Fossum}(X, Y) = \frac{|N| \cdot \Big(|X \cap Y|-\frac{1}{2}\Big)^2}{|X| \cdot |Y|} In :ref:`2x2 confusion table terms <confusion_table>`, where a+b+c+d=n, this is .. math:: sim_{Fossum} = \frac{n(a-\frac{1}{2})^2}{(a+b)(a+c)} .. versionadded:: 0.4.0 """ def __init__( self, alphabet=None, tokenizer=None, intersection_type='crisp', **kwargs ): """Initialize Fossum 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(Fossum, self).__init__( alphabet=alphabet, tokenizer=tokenizer, intersection_type=intersection_type, **kwargs )
[docs] def sim_score(self, src, tar): """Return the Fossum 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 Fossum similarity Examples -------- >>> cmp = Fossum() >>> cmp.sim_score('cat', 'hat') 110.25 >>> cmp.sim_score('Niall', 'Neil') 58.8 >>> cmp.sim_score('aluminum', 'Catalan') 2.7256944444444446 >>> cmp.sim_score('ATCG', 'TAGC') 7.84 .. versionadded:: 0.4.0 """ self._tokenize(src, tar) n = self._population_unique_card() a = self._intersection_card() apb = max(1.0, self._src_card()) apc = max(1.0, self._tar_card()) num = n * (a - 0.5) ** 2 if num: return num / (apb * apc) return 0.0
[docs] def sim(self, src, tar): """Return the normalized Fossum 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 Normalized Fossum similarity Examples -------- >>> cmp = Fossum() >>> cmp.sim('cat', 'hat') 0.1836734693877551 >>> cmp.sim('Niall', 'Neil') 0.08925619834710742 >>> cmp.sim('aluminum', 'Catalan') 0.0038927335640138415 >>> cmp.sim('ATCG', 'TAGC') 0.01234567901234568 .. versionadded:: 0.4.0 """ num = self.sim_score(src, tar) if num: return num / max( self.sim_score(src, src), self.sim_score(tar, tar) ) return 0.0
if __name__ == '__main__': import doctest doctest.testmod()