# Source code for abydos.distance._cosine

# Copyright 2014-2020 by Christopher C. Little.
# This file is part of Abydos.
#
# Abydos is free software: you can redistribute it and/or modify
# 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
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# 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 <http://www.gnu.org/licenses/>.

"""abydos.distance._cosine.

Cosine similarity & distance
"""

from math import sqrt

from deprecation import deprecated

from ._token_distance import _TokenDistance
from .. import __version__

__all__ = ['Cosine', 'dist_cosine', 'sim_cosine']

[docs]class Cosine(_TokenDistance): r"""Cosine similarity. For two sets X and Y, the cosine similarity, Otsuka-Ochiai coefficient, or Ochiai coefficient :cite:Otsuka:1936,Ochiai:1957 is .. math:: sim_{cosine}(X, Y) = \frac{|X \cap Y|}{\sqrt{|X| \cdot |Y|}} In :ref:2x2 confusion table terms <confusion_table>, where a+b+c+d=n, this is .. math:: sim_{cosine} = \frac{a}{\sqrt{(a+b)(a+c)}} Notes ----- This measure is also known as the Fowlkes-Mallows index :cite:Fowlkes:1983 for two classes and G-measure, the geometric mean of precision & recall. .. versionadded:: 0.3.6 """ def __init__(self, tokenizer=None, intersection_type='crisp', **kwargs): """Initialize Cosine 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(Cosine, self).__init__( tokenizer=tokenizer, intersection_type=intersection_type, **kwargs )
[docs] def sim(self, src, tar): r"""Return the cosine 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 Cosine similarity Examples -------- >>> cmp = Cosine() >>> cmp.sim('cat', 'hat') 0.5 >>> cmp.sim('Niall', 'Neil') 0.3651483716701107 >>> cmp.sim('aluminum', 'Catalan') 0.11785113019775793 >>> cmp.sim('ATCG', 'TAGC') 0.0 .. versionadded:: 0.1.0 .. versionchanged:: 0.3.6 Encapsulated in class """ if src == tar: return 1.0 if not src or not tar: return 0.0 self._tokenize(src, tar) num = self._intersection_card() if num: return num / sqrt(self._src_card() * self._tar_card()) return 0.0
[docs]@deprecated( deprecated_in='0.4.0', removed_in='0.6.0', current_version=__version__, details='Use the Cosine.sim method instead.', ) def sim_cosine(src, tar, qval=2): r"""Return the cosine similarity of two strings. This is a wrapper for :py:meth:Cosine.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 Cosine similarity Examples -------- >>> sim_cosine('cat', 'hat') 0.5 >>> sim_cosine('Niall', 'Neil') 0.3651483716701107 >>> sim_cosine('aluminum', 'Catalan') 0.11785113019775793 >>> sim_cosine('ATCG', 'TAGC') 0.0 .. versionadded:: 0.1.0 """ return Cosine(qval=qval).sim(src, tar)
[docs]@deprecated( deprecated_in='0.4.0', removed_in='0.6.0', current_version=__version__, details='Use the Cosine.dist method instead.', ) def dist_cosine(src, tar, qval=2): """Return the cosine distance between two strings. This is a wrapper for :py:meth:Cosine.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 Cosine distance Examples -------- >>> dist_cosine('cat', 'hat') 0.5 >>> dist_cosine('Niall', 'Neil') 0.6348516283298893 >>> dist_cosine('aluminum', 'Catalan') 0.882148869802242 >>> dist_cosine('ATCG', 'TAGC') 1.0 .. versionadded:: 0.1.0 """ return Cosine(qval=qval).dist(src, tar)
if __name__ == '__main__': import doctest doctest.testmod()