Source code for abydos.distance._clement

# 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
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# Abydos is distributed in the hope that it will be useful,
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Clement similarity

from ._token_distance import _TokenDistance

__all__ = ['Clement']

[docs]class Clement(_TokenDistance): r"""Clement similarity. For two sets X and Y and a population N, Clement similarity :cite:`Clement:1976` is defined as .. math:: sim_{Clement}(X, Y) = \frac{|X \cap Y|}{|X|}\Big(1-\frac{|X|}{|N|}\Big) + \frac{|(N \setminus X) \setminus Y|}{|N \setminus X|} \Big(1-\frac{|N \setminus X|}{|N|}\Big) In :ref:`2x2 confusion table terms <confusion_table>`, where a+b+c+d=n, this is .. math:: sim_{Clement} = \frac{a}{a+b}\Big(1 - \frac{a+b}{n}\Big) + \frac{d}{c+d}\Big(1 - \frac{c+d}{n}\Big) .. versionadded:: 0.4.0 """ def __init__( self, alphabet=None, tokenizer=None, intersection_type='crisp', **kwargs ): """Initialize Clement 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(Clement, self).__init__( alphabet=alphabet, tokenizer=tokenizer, intersection_type=intersection_type, **kwargs )
[docs] def sim(self, src, tar): """Return the Clement 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 Clement similarity Examples -------- >>> cmp = Clement() >>> cmp.sim('cat', 'hat') 0.5025379382522239 >>> cmp.sim('Niall', 'Neil') 0.33840586363079933 >>> cmp.sim('aluminum', 'Catalan') 0.12119877280918714 >>> cmp.sim('ATCG', 'TAGC') 0.006336616803332366 .. 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() n = self._population_unique_card() score = 0.0 if a + b: score += (a / (a + b)) * (1 - (a + b) / n) if c + d: score += (d / (c + d)) * (1 - (c + d) / n) return score
if __name__ == '__main__': import doctest doctest.testmod()