Source code for abydos.distance._baulieu_iii

# Copyright 2019-2020 by Christopher C. Little.
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Baulieu III distance

from ._token_distance import _TokenDistance

__all__ = ['BaulieuIII']

[docs]class BaulieuIII(_TokenDistance): r"""Baulieu III distance. For two sets X and Y and a population N, Baulieu III distance :cite:`Baulieu:1989` is .. math:: sim_{BaulieuIII}(X, Y) = \frac{|N|^2 - 4(|X \cap Y| \cdot |(N \setminus X) \setminus Y| - |X \setminus Y| \cdot |Y \setminus X|)}{2 \cdot |N|^2} This is based on Baulieu's 20th dissimilarity coefficient. In :ref:`2x2 confusion table terms <confusion_table>`, where a+b+c+d=n, this is .. math:: sim_{BaulieuIII} = \frac{n^2 - 4(ad-bc)}{2n^2} Notes ----- It should be noted that this is *based on* Baulieu's 20th dissimilarity coefficient. This distance is exactly half Baulieu's 20th dissimilarity. According to :cite:`Baulieu:1989`, the 20th dissimilarity should be a value in the range [0.0, 1.0], meeting the article's (P1) property, but the formula given ranges [0.0, 2.0], so dividing by 2 corrects the formula to meet the article's expectations. .. versionadded:: 0.4.0 """ def __init__( self, alphabet=None, tokenizer=None, intersection_type='crisp', **kwargs ): """Initialize BaulieuIII 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(BaulieuIII, self).__init__( alphabet=alphabet, tokenizer=tokenizer, intersection_type=intersection_type, **kwargs )
[docs] def dist(self, src, tar): """Return the Baulieu III 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 III distance Examples -------- >>> cmp = BaulieuIII() >>> cmp.dist('cat', 'hat') 0.4949500208246564 >>> cmp.dist('Niall', 'Neil') 0.4949955747605165 >>> cmp.dist('aluminum', 'Catalan') 0.49768591017891195 >>> cmp.dist('ATCG', 'TAGC') 0.5000813463140358 .. versionadded:: 0.4.0 """ 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() num = n * n - 4 * (a * d - b * c) if num == 0: return 0.0 return num / (2 * n * n)
if __name__ == '__main__': import doctest doctest.testmod()