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# -*- coding: utf-8 -*- |
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# Copyright 2014-2018 by Christopher C. Little. |
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# This file is part of Abydos. |
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# |
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# Abydos is free software: you can redistribute it and/or modify |
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# it under the terms of the GNU General Public License as published by |
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# the Free Software Foundation, either version 3 of the License, or |
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# (at your option) any later version. |
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# |
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# Abydos is distributed in the hope that it will be useful, |
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# but WITHOUT ANY WARRANTY; without even the implied warranty of |
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# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the |
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# GNU General Public License for more details. |
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# |
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# You should have received a copy of the GNU General Public License |
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# along with Abydos. If not, see <http://www.gnu.org/licenses/>. |
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"""abydos.distance._needleman_wunsch. |
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Needleman-Wunsch score |
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""" |
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from __future__ import ( |
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absolute_import, |
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division, |
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print_function, |
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unicode_literals, |
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) |
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from deprecation import deprecated |
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from numpy import float32 as np_float32 |
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from numpy import zeros as np_zeros |
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from six.moves import range |
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from ._distance import _Distance |
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from ._ident import sim_ident |
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from .. import __version__ |
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__all__ = ['NeedlemanWunsch', 'needleman_wunsch'] |
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class NeedlemanWunsch(_Distance): |
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"""Needleman-Wunsch score. |
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The Needleman-Wunsch score :cite:`Needleman:1970` is a standard edit |
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distance measure. |
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.. versionadded:: 0.3.6 |
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""" |
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@staticmethod |
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def sim_matrix( |
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src, |
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tar, |
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mat=None, |
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mismatch_cost=0, |
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match_cost=1, |
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symmetric=True, |
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alphabet=None, |
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): |
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"""Return the matrix similarity of two strings. |
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With the default parameters, this is identical to sim_ident. |
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It is possible for sim_matrix to return values outside of the range |
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:math:`[0, 1]`, if values outside that range are present in mat, |
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mismatch_cost, or match_cost. |
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Parameters |
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---------- |
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src : str |
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Source string for comparison |
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tar : str |
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Target string for comparison |
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mat : dict |
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A dict mapping tuples to costs; the tuples are (src, tar) pairs of |
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symbols from the alphabet parameter |
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mismatch_cost : float |
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The value returned if (src, tar) is absent from mat when src does |
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not equal tar |
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match_cost : float |
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The value returned if (src, tar) is absent from mat when src equals |
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tar |
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symmetric : bool |
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True if the cost of src not matching tar is identical to the cost |
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of tar not matching src; in this case, the values in mat need only |
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contain (src, tar) or (tar, src), not both |
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alphabet : str |
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A collection of tokens from which src and tar are drawn; if this is |
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defined a ValueError is raised if either tar or src is not found in |
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alphabet |
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Returns |
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------- |
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float |
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Matrix similarity |
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Raises |
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------ |
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ValueError |
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src value not in alphabet |
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ValueError |
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tar value not in alphabet |
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Examples |
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-------- |
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>>> NeedlemanWunsch.sim_matrix('cat', 'hat') |
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0 |
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>>> NeedlemanWunsch.sim_matrix('hat', 'hat') |
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1 |
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.. versionadded:: 0.1.0 |
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.. versionchanged:: 0.3.6 |
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Encapsulated in class |
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""" |
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if alphabet: |
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alphabet = tuple(alphabet) |
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for i in src: |
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if i not in alphabet: |
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raise ValueError('src value not in alphabet') |
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for i in tar: |
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if i not in alphabet: |
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raise ValueError('tar value not in alphabet') |
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if src == tar: |
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if mat and (src, src) in mat: |
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return mat[(src, src)] |
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return match_cost |
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if mat and (src, tar) in mat: |
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return mat[(src, tar)] |
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elif symmetric and mat and (tar, src) in mat: |
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return mat[(tar, src)] |
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return mismatch_cost |
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def __init__(self, gap_cost=1, sim_func=None, **kwargs): |
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"""Initialize NeedlemanWunsch instance. |
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Parameters |
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---------- |
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gap_cost : float |
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The cost of an alignment gap (1 by default) |
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sim_func : function |
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A function that returns the similarity of two characters (identity |
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similarity by default) |
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**kwargs |
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Arbitrary keyword arguments |
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.. versionadded:: 0.4.0 |
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""" |
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super(NeedlemanWunsch, self).__init__(**kwargs) |
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self._gap_cost = gap_cost |
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self._sim_func = sim_func |
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if self._sim_func is None: |
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self._sim_func = NeedlemanWunsch.sim_matrix |
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def sim_score(self, src, tar): |
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"""Return the Needleman-Wunsch score of two strings. |
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Parameters |
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---------- |
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src : str |
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Source string for comparison |
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tar : str |
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Target string for comparison |
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Returns |
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------- |
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float |
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Needleman-Wunsch score |
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Examples |
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-------- |
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>>> cmp = NeedlemanWunsch() |
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>>> cmp.sim_score('cat', 'hat') |
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2.0 |
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>>> cmp.sim_score('Niall', 'Neil') |
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1.0 |
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>>> cmp.sim_score('aluminum', 'Catalan') |
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-1.0 |
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>>> cmp.sim_score('ATCG', 'TAGC') |
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0.0 |
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.. versionadded:: 0.1.0 |
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.. versionchanged:: 0.3.6 |
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Encapsulated in class |
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""" |
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d_mat = np_zeros((len(src) + 1, len(tar) + 1), dtype=np_float32) |
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for i in range(len(src) + 1): |
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d_mat[i, 0] = -(i * self._gap_cost) |
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for j in range(len(tar) + 1): |
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d_mat[0, j] = -(j * self._gap_cost) |
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for i in range(1, len(src) + 1): |
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for j in range(1, len(tar) + 1): |
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match = d_mat[i - 1, j - 1] + self._sim_func( |
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src[i - 1], tar[j - 1] |
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) |
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delete = d_mat[i - 1, j] - self._gap_cost |
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insert = d_mat[i, j - 1] - self._gap_cost |
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d_mat[i, j] = max(match, delete, insert) |
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return d_mat[d_mat.shape[0] - 1, d_mat.shape[1] - 1] |
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def sim(self, src, tar): |
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"""Return the normalized Needleman-Wunsch score of two strings. |
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Parameters |
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---------- |
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src : str |
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Source string for comparison |
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tar : str |
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Target string for comparison |
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Returns |
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------- |
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float |
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Normalized Needleman-Wunsch score |
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Examples |
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-------- |
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>>> cmp = NeedlemanWunsch() |
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>>> cmp.sim('cat', 'hat') |
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0.6666666666666667 |
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>>> cmp.sim('Niall', 'Neil') |
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0.22360679774997896 |
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>>> round(cmp.sim('aluminum', 'Catalan'), 12) |
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0.0 |
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>>> cmp.sim('cat', 'hat') |
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0.6666666666666667 |
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.. versionadded:: 0.4.1 |
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""" |
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if src == tar: |
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return 1.0 |
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return max(0.0, self.sim_score(src, tar)) / ( |
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self.sim_score(src, src) ** 0.5 * self.sim_score(tar, tar) ** 0.5 |
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) |
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@deprecated( |
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deprecated_in='0.4.0', |
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removed_in='0.6.0', |
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current_version=__version__, |
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details='Use the NeedlemanWunsch.dist_abs method instead.', |
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) |
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def needleman_wunsch(src, tar, gap_cost=1, sim_func=sim_ident): |
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"""Return the Needleman-Wunsch score of two strings. |
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This is a wrapper for :py:meth:`NeedlemanWunsch.dist_abs`. |
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Parameters |
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---------- |
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src : str |
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Source string for comparison |
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tar : str |
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Target string for comparison |
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gap_cost : float |
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The cost of an alignment gap (1 by default) |
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sim_func : function |
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A function that returns the similarity of two characters (identity |
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similarity by default) |
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Returns |
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------- |
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float |
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Needleman-Wunsch score |
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Examples |
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-------- |
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>>> needleman_wunsch('cat', 'hat') |
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2.0 |
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>>> needleman_wunsch('Niall', 'Neil') |
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1.0 |
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>>> needleman_wunsch('aluminum', 'Catalan') |
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-1.0 |
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>>> needleman_wunsch('ATCG', 'TAGC') |
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0.0 |
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.. versionadded:: 0.1.0 |
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""" |
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return NeedlemanWunsch(gap_cost, sim_func).sim_score(src, tar) |
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if __name__ == '__main__': |
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import doctest |
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doctest.testmod() |
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chrislit /
abydos
