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# Copyright 2014-2020 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._gotoh. |
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Gotoh score |
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""" |
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from typing import Any, Callable, Optional, cast |
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from numpy import float_ as np_float |
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from numpy import zeros as np_zeros |
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from ._needleman_wunsch import NeedlemanWunsch |
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__all__ = ['Gotoh'] |
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class Gotoh(NeedlemanWunsch): |
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"""Gotoh score. |
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The Gotoh score :cite:`Gotoh:1982` is essentially Needleman-Wunsch with |
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affine gap penalties. |
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.. versionadded:: 0.3.6 |
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""" |
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def __init__( |
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self, |
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gap_open: float = 1, |
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gap_ext: float = 0.4, |
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sim_func: Optional[Callable[[str, str], float]] = None, |
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**kwargs: Any |
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) -> None: |
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"""Initialize Gotoh instance. |
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Parameters |
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---------- |
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gap_open : float |
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The cost of an open alignment gap (1 by default) |
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gap_ext : float |
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The cost of an alignment gap extension (0.4 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(Gotoh, self).__init__(**kwargs) |
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self._gap_open = gap_open |
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self._gap_ext = gap_ext |
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self._sim_func = cast( |
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Callable[[str, str], float], |
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NeedlemanWunsch.sim_matrix if sim_func is None else sim_func, |
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) # type: Callable[[str, str], float] |
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def sim_score(self, src: str, tar: str) -> float: |
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"""Return the Gotoh 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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Gotoh score |
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Examples |
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-------- |
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>>> cmp = Gotoh() |
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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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>>> round(cmp.sim_score('aluminum', 'Catalan'), 12) |
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-0.4 |
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>>> cmp.sim_score('cat', 'hat') |
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2.0 |
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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_float) |
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p_mat = np_zeros((len(src) + 1, len(tar) + 1), dtype=np_float) |
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q_mat = np_zeros((len(src) + 1, len(tar) + 1), dtype=np_float) |
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d_mat[0, 0] = 0 |
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p_mat[0, 0] = float('-inf') |
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q_mat[0, 0] = float('-inf') |
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for i in range(1, len(src) + 1): |
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d_mat[i, 0] = float('-inf') |
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p_mat[i, 0] = -self._gap_open - self._gap_ext * (i - 1) |
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q_mat[i, 0] = float('-inf') |
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if len(tar) > 1: |
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q_mat[i, 1] = -self._gap_open |
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for j in range(1, len(tar) + 1): |
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d_mat[0, j] = float('-inf') |
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p_mat[0, j] = float('-inf') |
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if len(src) > 1: |
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p_mat[1, j] = -self._gap_open |
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q_mat[0, j] = -self._gap_open - self._gap_ext * (j - 1) |
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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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sim_val = self._sim_func(src[i - 1], tar[j - 1]) |
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d_mat[i, j] = max( |
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d_mat[i - 1, j - 1] + sim_val, |
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p_mat[i - 1, j - 1] + sim_val, |
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q_mat[i - 1, j - 1] + sim_val, |
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) |
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p_mat[i, j] = max( |
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d_mat[i - 1, j] - self._gap_open, |
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p_mat[i - 1, j] - self._gap_ext, |
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) |
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q_mat[i, j] = max( |
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d_mat[i, j - 1] - self._gap_open, |
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q_mat[i, j - 1] - self._gap_ext, |
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) |
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i, j = (n - 1 for n in d_mat.shape) |
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return cast(float, max(d_mat[i, j], p_mat[i, j], q_mat[i, j])) |
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def sim(self, src: str, tar: str) -> float: |
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"""Return the normalized Gotoh 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 Gotoh score |
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Examples |
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-------- |
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>>> cmp = Gotoh() |
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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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if __name__ == '__main__': |
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import doctest |
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doctest.testmod() |
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chrislit /
abydos
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