Source code for abydos.distance._hellinger

# Copyright 2019-2020 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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#
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"""abydos.distance._hellinger.

Hellinger distance
"""

from ._token_distance import _TokenDistance

__all__ = ['Hellinger']


[docs]class Hellinger(_TokenDistance): r"""Hellinger distance. For two multisets X and Y drawn from an alphabet S, Hellinger distance :cite:`Hellinger:1909` is .. math:: dist_{Hellinger}(X, Y) = \sqrt{2 \cdot \sum_{i \in S} (\sqrt{|A_i|} - \sqrt{|B_i|})^2} .. versionadded:: 0.4.0 """ def __init__(self, tokenizer=None, **kwargs): """Initialize Hellinger instance. Parameters ---------- tokenizer : _Tokenizer A tokenizer instance from the :py:mod:`abydos.tokenizer` package **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. .. versionadded:: 0.4.0 """ super(Hellinger, self).__init__(tokenizer=tokenizer, **kwargs)
[docs] def dist_abs(self, src, tar): """Return the Hellinger 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 Hellinger distance Examples -------- >>> cmp = Hellinger() >>> cmp.dist_abs('cat', 'hat') 2.8284271247461903 >>> cmp.dist_abs('Niall', 'Neil') 3.7416573867739413 >>> cmp.dist_abs('aluminum', 'Catalan') 5.477225575051661 >>> cmp.dist_abs('ATCG', 'TAGC') 4.47213595499958 .. versionadded:: 0.4.0 """ self._tokenize(src, tar) alphabet = self._total().keys() return ( 2 * sum( ( (abs(self._src_tokens[tok])) ** 0.5 - (abs(self._tar_tokens[tok])) ** 0.5 ) ** 2 for tok in alphabet ) ) ** 0.5
[docs] def dist(self, src, tar): """Return the normalized Hellinger 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 Normalized Hellinger distance Examples -------- >>> cmp = Hellinger() >>> cmp.dist('cat', 'hat') 0.8164965809277261 >>> cmp.dist('Niall', 'Neil') 0.881917103688197 >>> cmp.dist('aluminum', 'Catalan') 0.9128709291752769 >>> cmp.dist('ATCG', 'TAGC') 1.0 .. versionadded:: 0.4.0 """ if src == tar: return 0.0 score = self.dist_abs(src, tar) norm = ( 2 * sum( max(self._src_tokens[tok], self._tar_tokens[tok]) ** 2 for tok in self._total().keys() ) ) ** 0.5 return score / norm
if __name__ == '__main__': import doctest doctest.testmod()