Source code for abydos.distance._fidelity

# 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
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
# Abydos is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# GNU General Public License for more details.
# You should have received a copy of the GNU General Public License
# along with Abydos. If not, see <>.



from ._token_distance import _TokenDistance

__all__ = ['Fidelity']

[docs]class Fidelity(_TokenDistance): r"""Fidelity. For two multisets X and Y drawn from an alphabet S, fidelity is .. math:: sim_{Fidelity}(X, Y) = \Bigg( \sum_{i \in S} \sqrt{|\frac{A_i}{|A|} \cdot \frac{B_i}{|B|}|} \Bigg)^2 .. versionadded:: 0.4.0 """ def __init__(self, tokenizer=None, **kwargs): """Initialize Fidelity 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(Fidelity, self).__init__(tokenizer=tokenizer, **kwargs)
[docs] def sim(self, src, tar): """Return the fidelity 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 fidelity Examples -------- >>> cmp = Fidelity() >>> cmp.sim('cat', 'hat') 0.25 >>> cmp.sim('Niall', 'Neil') 0.1333333333333333 >>> cmp.sim('aluminum', 'Catalan') 0.013888888888888888 >>> cmp.sim('ATCG', 'TAGC') 0.0 .. versionadded:: 0.4.0 """ self._tokenize(src, tar) alphabet = self._total().keys() src_mag = max(1, sum(self._src_tokens.values())) tar_mag = max(1, sum(self._tar_tokens.values())) return ( sum( ( abs( self._src_tokens[tok] / src_mag * self._tar_tokens[tok] / tar_mag ) ) ** 0.5 for tok in alphabet ) ** 2 )
if __name__ == '__main__': import doctest doctest.testmod()