Source code for abydos.distance._gower_legendre

# Copyright 2018-2020 by Christopher C. Little.
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Gower & Legendre similarity

from ._token_distance import _TokenDistance

__all__ = ['GowerLegendre']

[docs]class GowerLegendre(_TokenDistance): r"""Gower & Legendre similarity. For two sets X and Y and a population N, the Gower & Legendre similarity :cite:`Gower:1986` is .. math:: sim_{GowerLegendre}(X, Y) = \frac{|X \cap Y| + |(N \setminus X) \setminus Y|} {|X \cap Y| + |(N \setminus X) \setminus Y| + \theta \cdot |X \triangle Y|} In :ref:`2x2 confusion table terms <confusion_table>`, where a+b+c+d=n, this is .. math:: sim_{GowerLegendre} = \frac{a+d}{a+\theta(b+c)+d} .. versionadded:: 0.4.0 """ def __init__( self, alphabet=None, tokenizer=None, intersection_type='crisp', theta=0.5, **kwargs ): """Initialize GowerLegendre 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. theta : float The weight to place on the symmetric difference. **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 """ self.theta = theta super(GowerLegendre, self).__init__( alphabet=alphabet, tokenizer=tokenizer, intersection_type=intersection_type, **kwargs )
[docs] def sim(self, src, tar): """Return the Gower & Legendre 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 Gower & Legendre similarity Examples -------- >>> cmp = GowerLegendre() >>> cmp.sim('cat', 'hat') 0.9974424552429667 >>> cmp.sim('Niall', 'Neil') 0.9955156950672646 >>> cmp.sim('aluminum', 'Catalan') 0.9903536977491961 >>> cmp.sim('ATCG', 'TAGC') 0.993581514762516 .. versionadded:: 0.4.0 """ if src == tar: return 1.0 self._tokenize(src, tar) apd = self._intersection_card() + self._total_complement_card() bpc = self._src_only_card() + self._tar_only_card() return apd / (apd + self.theta * bpc)
if __name__ == '__main__': import doctest doctest.testmod()