Source code for abydos.distance._minkowski

# -*- coding: utf-8 -*-

# Copyright 2018 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
# 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.minkowski.

The distance.minkowski module implements Minkowski token-based distances:

    - Minkowski distance & similarity
    - Manhattan distance & similarity
    - Euclidean distance & similarity
    - Chebyshev distance
"""

from __future__ import division, unicode_literals

from numbers import Number

from ._util import _get_qgrams


__all__ = [
    'chebyshev',
    'dist_euclidean',
    'dist_manhattan',
    'dist_minkowski',
    'euclidean',
    'manhattan',
    'minkowski',
    'sim_euclidean',
    'sim_manhattan',
    'sim_minkowski',
]


[docs]def minkowski(src, tar, qval=2, pval=1, normalized=False, alphabet=None): """Return the Minkowski distance (:math:`L^p-norm`) of two strings. The Minkowski distance :cite:`Minkowski:1910` is a distance metric in :math:`L^p-space`. :param str src: source string (or QGrams/Counter objects) for comparison :param str tar: target string (or QGrams/Counter objects) for comparison :param int qval: the length of each q-gram; 0 for non-q-gram version :param int or float pval: the :math:`p`-value of the :math:`L^p`-space. :param bool normalized: normalizes to [0, 1] if True :param collection or int alphabet: the values or size of the alphabet :returns: the Minkowski distance :rtype: float >>> minkowski('cat', 'hat') 4.0 >>> minkowski('Niall', 'Neil') 7.0 >>> minkowski('Colin', 'Cuilen') 9.0 >>> minkowski('ATCG', 'TAGC') 10.0 """ q_src, q_tar = _get_qgrams(src, tar, qval) diffs = ((q_src - q_tar) + (q_tar - q_src)).values() normalizer = 1 if normalized: totals = (q_src + q_tar).values() if alphabet is not None: # noinspection PyTypeChecker normalizer = ( alphabet if isinstance(alphabet, Number) else len(alphabet) ) elif pval == 0: normalizer = len(totals) else: normalizer = sum(_ ** pval for _ in totals) ** (1 / pval) if len(diffs) == 0: return 0.0 if pval == float('inf'): # Chebyshev distance return max(diffs) / normalizer if pval == 0: # This is the l_0 "norm" as developed by David Donoho return len(diffs) / normalizer return sum(_ ** pval for _ in diffs) ** (1 / pval) / normalizer
[docs]def dist_minkowski(src, tar, qval=2, pval=1, alphabet=None): """Return normalized Minkowski distance of two strings. The normalized Minkowski distance :cite:`Minkowski:1910` is a distance metric in :math:`L^p-space`, normalized to [0, 1]. :param str src: source string (or QGrams/Counter objects) for comparison :param str tar: target string (or QGrams/Counter objects) for comparison :param int qval: the length of each q-gram; 0 for non-q-gram version :param int or float pval: the :math:`p`-value of the :math:`L^p`-space. :param collection or int alphabet: the values or size of the alphabet :returns: the normalized Minkowski distance :rtype: float >>> dist_minkowski('cat', 'hat') 0.5 >>> round(dist_minkowski('Niall', 'Neil'), 12) 0.636363636364 >>> round(dist_minkowski('Colin', 'Cuilen'), 12) 0.692307692308 >>> dist_minkowski('ATCG', 'TAGC') 1.0 """ return minkowski(src, tar, qval, pval, True, alphabet)
[docs]def sim_minkowski(src, tar, qval=2, pval=1, alphabet=None): """Return normalized Minkowski similarity of two strings. Minkowski similarity is the complement of Minkowski distance: :math:`sim_{Minkowski} = 1 - dist_{Minkowski}`. :param str src: source string (or QGrams/Counter objects) for comparison :param str tar: target string (or QGrams/Counter objects) for comparison :param int qval: the length of each q-gram; 0 for non-q-gram version :param int or float pval: the :math:`p`-value of the :math:`L^p`-space. :param collection or int alphabet: the values or size of the alphabet :returns: the normalized Minkowski similarity :rtype: float >>> sim_minkowski('cat', 'hat') 0.5 >>> round(sim_minkowski('Niall', 'Neil'), 12) 0.363636363636 >>> round(sim_minkowski('Colin', 'Cuilen'), 12) 0.307692307692 >>> sim_minkowski('ATCG', 'TAGC') 0.0 """ return 1 - minkowski(src, tar, qval, pval, True, alphabet)
[docs]def manhattan(src, tar, qval=2, normalized=False, alphabet=None): """Return the Manhattan distance between two strings. Manhattan distance is the city-block or taxi-cab distance, equivalent to Minkowski distance in :math:`L^1`-space. :param str src: source string (or QGrams/Counter objects) for comparison :param str tar: target string (or QGrams/Counter objects) for comparison :param int qval: the length of each q-gram; 0 for non-q-gram version :param normalized: normalizes to [0, 1] if True :param collection or int alphabet: the values or size of the alphabet :returns: the Manhattan distance :rtype: float >>> manhattan('cat', 'hat') 4.0 >>> manhattan('Niall', 'Neil') 7.0 >>> manhattan('Colin', 'Cuilen') 9.0 >>> manhattan('ATCG', 'TAGC') 10.0 """ return minkowski(src, tar, qval, 1, normalized, alphabet)
[docs]def dist_manhattan(src, tar, qval=2, alphabet=None): """Return the normalized Manhattan distance between two strings. The normalized Manhattan distance is a distance metric in :math:`L^1-space`, normalized to [0, 1]. This is identical to Canberra distance. :param str src: source string (or QGrams/Counter objects) for comparison :param str tar: target string (or QGrams/Counter objects) for comparison :param int qval: the length of each q-gram; 0 for non-q-gram version :param collection or int alphabet: the values or size of the alphabet :returns: the normalized Manhattan distance :rtype: float >>> dist_manhattan('cat', 'hat') 0.5 >>> round(dist_manhattan('Niall', 'Neil'), 12) 0.636363636364 >>> round(dist_manhattan('Colin', 'Cuilen'), 12) 0.692307692308 >>> dist_manhattan('ATCG', 'TAGC') 1.0 """ return manhattan(src, tar, qval, True, alphabet)
[docs]def sim_manhattan(src, tar, qval=2, alphabet=None): """Return the normalized Manhattan similarity of two strings. Manhattan similarity is the complement of Manhattan distance: :math:`sim_{Manhattan} = 1 - dist_{Manhattan}`. :param str src: source string (or QGrams/Counter objects) for comparison :param str tar: target string (or QGrams/Counter objects) for comparison :param int qval: the length of each q-gram; 0 for non-q-gram version :param collection or int alphabet: the values or size of the alphabet :returns: the normalized Manhattan similarity :rtype: float >>> sim_manhattan('cat', 'hat') 0.5 >>> round(sim_manhattan('Niall', 'Neil'), 12) 0.363636363636 >>> round(sim_manhattan('Colin', 'Cuilen'), 12) 0.307692307692 >>> sim_manhattan('ATCG', 'TAGC') 0.0 """ return 1 - manhattan(src, tar, qval, True, alphabet)
[docs]def euclidean(src, tar, qval=2, normalized=False, alphabet=None): """Return the Euclidean distance between two strings. Euclidean distance is the straigh-line or as-the-crow-flies distance, equivalent to Minkowski distance in :math:`L^2`-space. :param str src: source string (or QGrams/Counter objects) for comparison :param str tar: target string (or QGrams/Counter objects) for comparison :param int qval: the length of each q-gram; 0 for non-q-gram version :param normalized: normalizes to [0, 1] if True :param collection or int alphabet: the values or size of the alphabet :returns: the Euclidean distance :rtype: float >>> euclidean('cat', 'hat') 2.0 >>> round(euclidean('Niall', 'Neil'), 12) 2.645751311065 >>> euclidean('Colin', 'Cuilen') 3.0 >>> round(euclidean('ATCG', 'TAGC'), 12) 3.162277660168 """ return minkowski(src, tar, qval, 2, normalized, alphabet)
[docs]def dist_euclidean(src, tar, qval=2, alphabet=None): """Return the normalized Euclidean distance between two strings. The normalized Euclidean distance is a distance metric in :math:`L^2-space`, normalized to [0, 1]. :param str src: source string (or QGrams/Counter objects) for comparison :param str tar: target string (or QGrams/Counter objects) for comparison :param int qval: the length of each q-gram; 0 for non-q-gram version :param collection or int alphabet: the values or size of the alphabet :returns: the normalized Euclidean distance :rtype: float >>> round(dist_euclidean('cat', 'hat'), 12) 0.57735026919 >>> round(dist_euclidean('Niall', 'Neil'), 12) 0.683130051064 >>> round(dist_euclidean('Colin', 'Cuilen'), 12) 0.727606875109 >>> dist_euclidean('ATCG', 'TAGC') 1.0 """ return euclidean(src, tar, qval, True, alphabet)
[docs]def sim_euclidean(src, tar, qval=2, alphabet=None): """Return the normalized Euclidean similarity of two strings. Euclidean similarity is the complement of Euclidean distance: :math:`sim_{Euclidean} = 1 - dist_{Euclidean}`. :param str src: source string (or QGrams/Counter objects) for comparison :param str tar: target string (or QGrams/Counter objects) for comparison :param int qval: the length of each q-gram; 0 for non-q-gram version :param collection or int alphabet: the values or size of the alphabet :returns: the normalized Euclidean similarity :rtype: float >>> round(sim_euclidean('cat', 'hat'), 12) 0.42264973081 >>> round(sim_euclidean('Niall', 'Neil'), 12) 0.316869948936 >>> round(sim_euclidean('Colin', 'Cuilen'), 12) 0.272393124891 >>> sim_euclidean('ATCG', 'TAGC') 0.0 """ return 1 - euclidean(src, tar, qval, True, alphabet)
[docs]def chebyshev(src, tar, qval=2, normalized=False, alphabet=None): r"""Return the Chebyshev distance between two strings. Euclidean distance is the chessboard distance, equivalent to Minkowski distance in :math:`L^\infty-space`. :param str src: source string (or QGrams/Counter objects) for comparison :param str tar: target string (or QGrams/Counter objects) for comparison :param int qval: the length of each q-gram; 0 for non-q-gram version :param normalized: normalizes to [0, 1] if True :param collection or int alphabet: the values or size of the alphabet :returns: the Chebyshev distance :rtype: float >>> chebyshev('cat', 'hat') 1.0 >>> chebyshev('Niall', 'Neil') 1.0 >>> chebyshev('Colin', 'Cuilen') 1.0 >>> chebyshev('ATCG', 'TAGC') 1.0 >>> chebyshev('ATCG', 'TAGC', qval=1) 0.0 >>> chebyshev('ATCGATTCGGAATTTC', 'TAGCATAATCGCCG', qval=1) 3.0 """ return minkowski(src, tar, qval, float('inf'), normalized, alphabet)
if __name__ == '__main__': import doctest doctest.testmod()