Source code for abydos.distance._dice

# Copyright 2014-2020 by Christopher C. Little.
# This file is part of Abydos.
#
# Abydos is free software: you can redistribute it and/or modify
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"""abydos.distance._dice.

Sørensen–Dice coefficient & distance
"""

from deprecation import deprecated

from ._tversky import Tversky
from .. import __version__

__all__ = ['Dice', 'dist_dice', 'sim_dice']


[docs]class Dice(Tversky): r"""Sørensen–Dice coefficient. For two sets X and Y, the Sørensen–Dice coefficient :cite:`Dice:1945,Sorensen:1948,Czekanowski:1909,Motyka:1950` is .. math:: sim_{Dice}(X, Y) = \frac{2 \cdot |X \cap Y|}{|X| + |Y|} This is the complement of Bray & Curtis dissimilarity :cite:`Bray:1957`, also known as the Lance & Williams dissimilarity :cite:`Lance:1967`. This is identical to the Tanimoto similarity coefficient :cite:`Tanimoto:1958` and the Tversky index :cite:`Tversky:1977` for :math:`\alpha = \beta = 0.5`. In the Ruby text library this is identified as White similarity, after :cite:`White:Nd`. In :ref:`2x2 confusion table terms <confusion_table>`, where a+b+c+d=n, this is .. math:: sim_{Dice} = \frac{2a}{2a+b+c} Notes ----- In terms of a confusion matrix, this is equivalent to :math:`F_1` score :py:meth:`ConfusionTable.f1_score`. The multiset variant is termed Gleason similarity :cite:`Gleason:1920`. .. versionadded:: 0.3.6 """ def __init__(self, tokenizer=None, intersection_type='crisp', **kwargs): """Initialize Dice 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(Dice, self).__init__( alpha=0.5, beta=0.5, bias=None, tokenizer=tokenizer, intersection_type=intersection_type, **kwargs )
[docs] def sim(self, src, tar): """Return the Sørensen–Dice coefficient 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 Sørensen–Dice similarity Examples -------- >>> cmp = Dice() >>> cmp.sim('cat', 'hat') 0.5 >>> cmp.sim('Niall', 'Neil') 0.36363636363636365 >>> cmp.sim('aluminum', 'Catalan') 0.11764705882352941 >>> cmp.sim('ATCG', 'TAGC') 0.0 .. versionadded:: 0.1.0 .. versionchanged:: 0.3.6 Encapsulated in class """ return super(Dice, self).sim(src, tar)
[docs]@deprecated( deprecated_in='0.4.0', removed_in='0.6.0', current_version=__version__, details='Use the Dice.sim method instead.', ) def sim_dice(src, tar, qval=2): """Return the Sørensen–Dice coefficient of two strings. This is a wrapper for :py:meth:`Dice.sim`. Parameters ---------- src : str Source string (or QGrams/Counter objects) for comparison tar : str Target string (or QGrams/Counter objects) for comparison qval : int The length of each q-gram Returns ------- float Sørensen–Dice similarity Examples -------- >>> sim_dice('cat', 'hat') 0.5 >>> sim_dice('Niall', 'Neil') 0.36363636363636365 >>> sim_dice('aluminum', 'Catalan') 0.11764705882352941 >>> sim_dice('ATCG', 'TAGC') 0.0 .. versionadded:: 0.1.0 """ return Dice(qval=qval).sim(src, tar)
[docs]@deprecated( deprecated_in='0.4.0', removed_in='0.6.0', current_version=__version__, details='Use the Dice.dist method instead.', ) def dist_dice(src, tar, qval=2): """Return the Sørensen–Dice distance between two strings. This is a wrapper for :py:meth:`Dice.dist`. Parameters ---------- src : str Source string (or QGrams/Counter objects) for comparison tar : str Target string (or QGrams/Counter objects) for comparison qval : int The length of each q-gram Returns ------- float Sørensen–Dice distance Examples -------- >>> dist_dice('cat', 'hat') 0.5 >>> dist_dice('Niall', 'Neil') 0.6363636363636364 >>> dist_dice('aluminum', 'Catalan') 0.8823529411764706 >>> dist_dice('ATCG', 'TAGC') 1.0 .. versionadded:: 0.1.0 """ return Dice(qval=qval).dist(src, tar)
if __name__ == '__main__': import doctest doctest.testmod()