Source code for abydos.distance._chord

# 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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#
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# GNU General Public License for more details.
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"""abydos.distance._chord.

Chord distance
"""

from ._token_distance import _TokenDistance

__all__ = ['Chord']


[docs]class Chord(_TokenDistance): r"""Chord distance. For two sets X and Y drawn from an alphabet S, the chord distance :cite:`Orloci:1967` is .. math:: sim_{chord}(X, Y) = \sqrt{\sum_{i \in S}\Big(\frac{X_i}{\sqrt{\sum_{j \in X} X_j^2}} - \frac{Y_i}{\sqrt{\sum_{j \in Y} Y_j^2}}\Big)^2} .. versionadded:: 0.4.0 """ def __init__(self, tokenizer=None, intersection_type='crisp', **kwargs): """Initialize Chord instance. Parameters ---------- 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(Chord, self).__init__( tokenizer=tokenizer, intersection_type=intersection_type, **kwargs )
[docs] def dist_abs(self, src, tar): """Return the Chord 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 Chord distance Examples -------- >>> cmp = Chord() >>> cmp.dist_abs('cat', 'hat') 1.0 >>> cmp.dist_abs('Niall', 'Neil') 1.126811100699571 >>> cmp.dist_abs('aluminum', 'Catalan') 1.336712116966249 >>> cmp.dist_abs('ATCG', 'TAGC') 1.414213562373095 .. versionadded:: 0.4.0 """ self._tokenize(src, tar) alphabet = self._total().keys() den1 = max( 1, sum(val * val for val in self._src_tokens.values()) ** 0.5 ) den2 = max( 1, sum(val * val for val in self._tar_tokens.values()) ** 0.5 ) return round( sum( (self._src_tokens[i] / den1 - self._tar_tokens[i] / den2) ** 2 for i in alphabet ) ** 0.5, 15, )
[docs] def dist(self, src, tar): """Return the normalized Chord 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 chord distance Examples -------- >>> cmp = Chord() >>> cmp.dist('cat', 'hat') 0.707106781186547 >>> cmp.dist('Niall', 'Neil') 0.796775770420944 >>> cmp.dist('aluminum', 'Catalan') 0.94519820240106 >>> cmp.dist('ATCG', 'TAGC') 1.0 .. versionadded:: 0.4.0 """ return round(self.dist_abs(src, tar) / (2 ** 0.5), 15)
if __name__ == '__main__': import doctest doctest.testmod()