Source code for abydos.distance._unknown_l

# Copyright 2019-2020 by Christopher C. Little.
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"""abydos.distance._unknown_l.

Unknown L similarity
"""

from ._token_distance import _TokenDistance

__all__ = ['UnknownL']


[docs]class UnknownL(_TokenDistance): r"""Unknown L similarity. For two sets X and Y and a population N, Unknown L similarity, which :cite:`SequentiX:2018` attributes to "Roux" but could not be located, is .. math:: sim_{UnknownL}(X, Y) = \frac{|X \cap Y| + |(N \setminus X) \setminus Y|} {min(|X \setminus Y|, |Y \setminus X|) + min(|N|-|X \setminus Y|, |N|-|Y \setminus X|)} In :ref:`2x2 confusion table terms <confusion_table>`, where a+b+c+d=n, this is .. math:: sim_{UnknownL} = \frac{a+d}{min(b, c) + min(n-b, n-c)} .. versionadded:: 0.4.0 """ def __init__( self, alphabet=None, tokenizer=None, intersection_type='crisp', **kwargs ): """Initialize UnknownL 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(UnknownL, self).__init__( alphabet=alphabet, tokenizer=tokenizer, intersection_type=intersection_type, **kwargs )
[docs] def sim(self, src, tar): """Return the Unknown L 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 Unknown L similarity Examples -------- >>> cmp = UnknownL() >>> cmp.sim('cat', 'hat') 0.9948979591836735 >>> cmp.sim('Niall', 'Neil') 0.9923371647509579 >>> cmp.sim('aluminum', 'Catalan') 0.9821428571428571 >>> cmp.sim('ATCG', 'TAGC') 0.9872448979591837 .. versionadded:: 0.4.0 """ self._tokenize(src, tar) if not self._src_card() or not self._tar_card(): return 1.0 a = self._intersection_card() b = self._src_only_card() c = self._tar_only_card() d = self._total_complement_card() n = self._population_unique_card() return (a + d) / (min(b, c) + min(n - b, n - c))
if __name__ == '__main__': import doctest doctest.testmod()