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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.compression. |
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The distance.compression module implements compression distance measures. |
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""" |
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from __future__ import division, unicode_literals |
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import bz2 |
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import zlib |
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from ._distance import Distance |
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from ..compression import Arithmetic, BWT, RLE |
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try: |
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import lzma |
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except ImportError: # pragma: no cover |
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# If the system lacks the lzma library, that's fine, but lzma compression |
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# similarity won't be supported. |
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lzma = None |
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__all__ = [ |
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'NCDzlib', |
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'dist_ncd_zlib', |
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'sim_ncd_zlib', |
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'NCDbz2', |
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'dist_ncd_bz2', |
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'sim_ncd_bz2', |
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'NCDlzma', |
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'dist_ncd_lzma', |
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'sim_ncd_lzma', |
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'NCDbwtrle', |
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'dist_ncd_bwtrle', |
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'sim_ncd_bwtrle', |
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'NCDrle', |
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'dist_ncd_rle', |
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'sim_ncd_rle', |
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'NCDarith', |
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'dist_ncd_arith', |
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'sim_ncd_arith', |
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] |
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class NCDarith(Distance): |
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"""Normalized Compression Distance using Arithmetic Coding. |
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Normalized compression distance (NCD) :cite:`Cilibrasi:2005`. |
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""" |
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_coder = None |
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def __init__(self): |
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"""Initialize the arithmetic coder object.""" |
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self._coder = Arithmetic() |
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def dist(self, src, tar, probs=None): |
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"""Return the NCD between two strings using arithmetic coding. |
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Args: |
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src (str): Source string for comparison |
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tar (str): Target string for comparison |
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probs (dict): A dictionary trained with :py:meth:`Arithmetic.train` |
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Returns: |
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float: Compression distance |
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Examples: |
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>>> cmp = NCDarith() |
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>>> cmp.dist('cat', 'hat') |
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0.5454545454545454 |
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>>> cmp.dist('Niall', 'Neil') |
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0.6875 |
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>>> cmp.dist('aluminum', 'Catalan') |
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0.8275862068965517 |
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>>> cmp.dist('ATCG', 'TAGC') |
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0.6923076923076923 |
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""" |
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if src == tar: |
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return 0.0 |
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if probs is None: |
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# lacking a reasonable dictionary, train on the strings themselves |
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self._coder.train(src + tar) |
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else: |
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self._coder.set_probs(probs) |
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src_comp = self._coder.encode(src)[1] |
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tar_comp = self._coder.encode(tar)[1] |
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concat_comp = self._coder.encode(src + tar)[1] |
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concat_comp2 = self._coder.encode(tar + src)[1] |
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return ( |
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min(concat_comp, concat_comp2) - min(src_comp, tar_comp) |
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) / max(src_comp, tar_comp) |
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def dist_ncd_arith(src, tar, probs=None): |
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"""Return the NCD between two strings using arithmetic coding. |
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This is a wrapper for :py:meth:`NCDarith.dist`. |
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Args: |
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src (str): Source string for comparison |
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tar (str): Target string for comparison |
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probs (dict): A dictionary trained with :py:meth:`Arithmetic.train` |
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Returns: |
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float: Compression distance |
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Examples: |
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>>> dist_ncd_arith('cat', 'hat') |
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0.5454545454545454 |
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>>> dist_ncd_arith('Niall', 'Neil') |
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0.6875 |
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>>> dist_ncd_arith('aluminum', 'Catalan') |
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0.8275862068965517 |
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>>> dist_ncd_arith('ATCG', 'TAGC') |
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0.6923076923076923 |
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""" |
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return NCDarith().dist(src, tar, probs) |
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def sim_ncd_arith(src, tar, probs=None): |
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"""Return the NCD similarity between two strings using arithmetic coding. |
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This is a wrapper for :py:meth:`NCDarith.sim`. |
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Args: |
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src (str): Source string for comparison |
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tar (str): Target string for comparison |
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probs (dict): A dictionary trained with :py:meth:`Arithmetic.train` |
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Returns: |
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float: Compression similarity |
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Examples: |
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>>> sim_ncd_arith('cat', 'hat') |
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0.4545454545454546 |
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>>> sim_ncd_arith('Niall', 'Neil') |
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0.3125 |
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>>> sim_ncd_arith('aluminum', 'Catalan') |
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0.1724137931034483 |
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>>> sim_ncd_arith('ATCG', 'TAGC') |
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0.3076923076923077 |
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""" |
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return NCDarith().sim(src, tar, probs) |
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class NCDrle(Distance): |
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"""Normalized Compression Distance using RLE. |
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Normalized compression distance (NCD) :cite:`Cilibrasi:2005`. |
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""" |
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_rle = RLE() |
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def dist(self, src, tar): |
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"""Return the NCD between two strings using RLE. |
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Args: |
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src (str): Source string for comparison |
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tar (str): Target string for comparison |
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Returns: |
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float: Compression distance |
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Examples: |
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>>> cmp = NCDrle() |
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>>> cmp.dist('cat', 'hat') |
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1.0 |
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>>> cmp.dist('Niall', 'Neil') |
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1.0 |
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>>> cmp.dist('aluminum', 'Catalan') |
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1.0 |
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>>> cmp.dist('ATCG', 'TAGC') |
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1.0 |
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""" |
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if src == tar: |
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return 0.0 |
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src_comp = self._rle.encode(src) |
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tar_comp = self._rle.encode(tar) |
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concat_comp = self._rle.encode(src + tar) |
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concat_comp2 = self._rle.encode(tar + src) |
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return ( |
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min(len(concat_comp), len(concat_comp2)) |
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- min(len(src_comp), len(tar_comp)) |
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) / max(len(src_comp), len(tar_comp)) |
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def dist_ncd_rle(src, tar): |
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"""Return the NCD between two strings using RLE. |
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This is a wrapper for :py:meth:`NCDrle.dist`. |
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Args: |
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src (str): Source string for comparison |
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tar (str): Target string for comparison |
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Returns: |
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float: Compression distance |
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Examples: |
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>>> dist_ncd_rle('cat', 'hat') |
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1.0 |
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>>> dist_ncd_rle('Niall', 'Neil') |
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1.0 |
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>>> dist_ncd_rle('aluminum', 'Catalan') |
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1.0 |
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>>> dist_ncd_rle('ATCG', 'TAGC') |
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1.0 |
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""" |
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return NCDrle().dist(src, tar) |
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def sim_ncd_rle(src, tar): |
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"""Return the NCD similarity between two strings using RLE. |
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This is a wrapper for :py:meth:`NCDrle.sim`. |
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Args: |
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src (str): Source string for comparison |
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tar (str): Target string for comparison |
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Returns: |
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float: Compression similarity |
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Examples: |
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>>> sim_ncd_rle('cat', 'hat') |
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0.0 |
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>>> sim_ncd_rle('Niall', 'Neil') |
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0.0 |
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>>> sim_ncd_rle('aluminum', 'Catalan') |
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0.0 |
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>>> sim_ncd_rle('ATCG', 'TAGC') |
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0.0 |
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""" |
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return NCDrle().sim(src, tar) |
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class NCDbwtrle(NCDrle): |
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"""Normalized Compression Distance using BWT plus RLE. |
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Normalized compression distance (NCD) :cite:`Cilibrasi:2005`. |
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""" |
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_bwt = BWT() |
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def dist(self, src, tar): |
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"""Return the NCD between two strings using BWT plus RLE. |
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Args: |
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src (str): Source string for comparison |
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tar (str): Target string for comparison |
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Returns: |
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float: Compression distance |
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Examples: |
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>>> cmp = NCDbwtrle() |
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>>> cmp.dist('cat', 'hat') |
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0.75 |
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>>> cmp.dist('Niall', 'Neil') |
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0.8333333333333334 |
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>>> cmp.dist('aluminum', 'Catalan') |
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1.0 |
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>>> cmp.dist('ATCG', 'TAGC') |
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0.8 |
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""" |
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if src == tar: |
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return 0.0 |
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src_comp = self._rle.encode(self._bwt.encode(src)) |
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tar_comp = self._rle.encode(self._bwt.encode(tar)) |
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concat_comp = self._rle.encode(self._bwt.encode(src + tar)) |
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concat_comp2 = self._rle.encode(self._bwt.encode(tar + src)) |
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return ( |
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min(len(concat_comp), len(concat_comp2)) |
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- min(len(src_comp), len(tar_comp)) |
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) / max(len(src_comp), len(tar_comp)) |
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def dist_ncd_bwtrle(src, tar): |
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"""Return the NCD between two strings using BWT plus RLE. |
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This is a wrapper for :py:meth:`NCDbwtrle.dist`. |
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Args: |
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src (str): Source string for comparison |
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tar (str): Target string for comparison |
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Returns: |
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float: Compression distance |
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Examples: |
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>>> dist_ncd_bwtrle('cat', 'hat') |
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0.75 |
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>>> dist_ncd_bwtrle('Niall', 'Neil') |
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0.8333333333333334 |
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>>> dist_ncd_bwtrle('aluminum', 'Catalan') |
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1.0 |
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>>> dist_ncd_bwtrle('ATCG', 'TAGC') |
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0.8 |
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""" |
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return NCDbwtrle().dist(src, tar) |
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def sim_ncd_bwtrle(src, tar): |
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"""Return the NCD similarity between two strings using BWT plus RLE. |
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This is a wrapper for :py:meth:`NCDbwtrle.sim`. |
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Args: |
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src (str): Source string for comparison |
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tar (str): Target string for comparison |
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Returns: |
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float: Compression similarity |
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Examples: |
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>>> sim_ncd_bwtrle('cat', 'hat') |
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0.25 |
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>>> sim_ncd_bwtrle('Niall', 'Neil') |
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0.16666666666666663 |
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>>> sim_ncd_bwtrle('aluminum', 'Catalan') |
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0.0 |
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>>> sim_ncd_bwtrle('ATCG', 'TAGC') |
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0.19999999999999996 |
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""" |
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return NCDbwtrle().sim(src, tar) |
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class NCDzlib(Distance): |
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"""Normalized Compression Distance using zlib compression. |
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Normalized compression distance (NCD) :cite:`Cilibrasi:2005`. |
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""" |
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_compressor = None |
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369
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1 |
|
def __init__(self, level=zlib.Z_DEFAULT_COMPRESSION): |
370
|
|
|
"""Initialize zlib compressor. |
371
|
|
|
|
372
|
|
|
Args: |
373
|
|
|
level (int): The compression level (0 to 9) |
374
|
|
|
""" |
375
|
1 |
|
self._compressor = zlib.compressobj(level) |
376
|
|
|
|
377
|
1 |
|
def dist(self, src, tar): |
|
|
|
|
378
|
|
|
"""Return the NCD between two strings using zlib compression. |
379
|
|
|
|
380
|
|
|
Args: |
381
|
|
|
src (str): Source string for comparison |
382
|
|
|
tar (str): Target string for comparison |
383
|
|
|
|
384
|
|
|
Returns: |
385
|
|
|
float: Compression distance |
386
|
|
|
|
387
|
|
|
Examples: |
388
|
|
|
>>> cmp = NCDzlib() |
389
|
|
|
>>> cmp.dist('cat', 'hat') |
390
|
|
|
0.3333333333333333 |
391
|
|
|
>>> cmp.dist('Niall', 'Neil') |
392
|
|
|
0.45454545454545453 |
393
|
|
|
>>> cmp.dist('aluminum', 'Catalan') |
394
|
|
|
0.5714285714285714 |
395
|
|
|
>>> cmp.dist('ATCG', 'TAGC') |
396
|
|
|
0.4 |
397
|
|
|
|
398
|
|
|
""" |
399
|
1 |
|
if src == tar: |
400
|
1 |
|
return 0.0 |
401
|
|
|
|
402
|
1 |
|
src = src.encode('utf-8') |
403
|
1 |
|
tar = tar.encode('utf-8') |
404
|
|
|
|
405
|
1 |
|
self._compressor.compress(src) |
406
|
1 |
|
src_comp = self._compressor.flush(zlib.Z_FULL_FLUSH) |
407
|
1 |
|
self._compressor.compress(tar) |
408
|
1 |
|
tar_comp = self._compressor.flush(zlib.Z_FULL_FLUSH) |
409
|
1 |
|
self._compressor.compress(src + tar) |
410
|
1 |
|
concat_comp = self._compressor.flush(zlib.Z_FULL_FLUSH) |
411
|
1 |
|
self._compressor.compress(tar + src) |
412
|
1 |
|
concat_comp2 = self._compressor.flush(zlib.Z_FULL_FLUSH) |
413
|
|
|
|
414
|
1 |
|
return ( |
415
|
|
|
min(len(concat_comp), len(concat_comp2)) |
416
|
|
|
- min(len(src_comp), len(tar_comp)) |
417
|
|
|
) / max(len(src_comp), len(tar_comp)) |
418
|
|
|
|
419
|
|
|
|
420
|
1 |
|
def dist_ncd_zlib(src, tar): |
421
|
|
|
"""Return the NCD between two strings using zlib compression. |
422
|
|
|
|
423
|
|
|
This is a wrapper for :py:meth:`NCDzlib.dist`. |
424
|
|
|
|
425
|
|
|
Args: |
426
|
|
|
src (str): Source string for comparison |
427
|
|
|
tar (str): Target string for comparison |
428
|
|
|
|
429
|
|
|
Returns: |
430
|
|
|
float: Compression distance |
431
|
|
|
|
432
|
|
|
Examples: |
433
|
|
|
>>> dist_ncd_zlib('cat', 'hat') |
434
|
|
|
0.3333333333333333 |
435
|
|
|
>>> dist_ncd_zlib('Niall', 'Neil') |
436
|
|
|
0.45454545454545453 |
437
|
|
|
>>> dist_ncd_zlib('aluminum', 'Catalan') |
438
|
|
|
0.5714285714285714 |
439
|
|
|
>>> dist_ncd_zlib('ATCG', 'TAGC') |
440
|
|
|
0.4 |
441
|
|
|
|
442
|
|
|
""" |
443
|
1 |
|
return NCDzlib().dist(src, tar) |
444
|
|
|
|
445
|
|
|
|
446
|
1 |
|
def sim_ncd_zlib(src, tar): |
447
|
|
|
"""Return the NCD similarity between two strings using zlib compression. |
448
|
|
|
|
449
|
|
|
This is a wrapper for :py:meth:`NCDzlib.sim`. |
450
|
|
|
|
451
|
|
|
Args: |
452
|
|
|
src (str): Source string for comparison |
453
|
|
|
tar (str): Target string for comparison |
454
|
|
|
|
455
|
|
|
Returns: |
456
|
|
|
float: Compression similarity |
457
|
|
|
|
458
|
|
|
Examples: |
459
|
|
|
>>> sim_ncd_zlib('cat', 'hat') |
460
|
|
|
0.6666666666666667 |
461
|
|
|
>>> sim_ncd_zlib('Niall', 'Neil') |
462
|
|
|
0.5454545454545454 |
463
|
|
|
>>> sim_ncd_zlib('aluminum', 'Catalan') |
464
|
|
|
0.4285714285714286 |
465
|
|
|
>>> sim_ncd_zlib('ATCG', 'TAGC') |
466
|
|
|
0.6 |
467
|
|
|
|
468
|
|
|
""" |
469
|
1 |
|
return NCDzlib().sim(src, tar) |
470
|
|
|
|
471
|
|
|
|
472
|
1 |
|
class NCDbz2(Distance): |
|
|
|
|
473
|
|
|
"""Normalized Compression Distance using bz2 compression. |
474
|
|
|
|
475
|
|
|
Normalized compression distance (NCD) :cite:`Cilibrasi:2005`. |
476
|
|
|
""" |
477
|
|
|
|
478
|
1 |
|
_level = 9 |
479
|
|
|
|
480
|
1 |
|
def __init__(self, level=9): |
481
|
|
|
"""Initialize zlib compressor. |
482
|
|
|
|
483
|
|
|
Args: |
484
|
|
|
level (int): The compression level (0 to 9) |
485
|
|
|
""" |
486
|
1 |
|
self._level = level |
487
|
|
|
|
488
|
1 |
|
def dist(self, src, tar): |
|
|
|
|
489
|
|
|
"""Return the NCD between two strings using bz2 compression. |
490
|
|
|
|
491
|
|
|
Args: |
492
|
|
|
src (str): Source string for comparison |
493
|
|
|
tar (str): Target string for comparison |
494
|
|
|
|
495
|
|
|
Returns: |
496
|
|
|
float: Compression distance |
497
|
|
|
|
498
|
|
|
Examples: |
499
|
|
|
>>> cmp = NCDbz2() |
500
|
|
|
>>> cmp.dist('cat', 'hat') |
501
|
|
|
0.06666666666666667 |
502
|
|
|
>>> cmp.dist('Niall', 'Neil') |
503
|
|
|
0.03125 |
504
|
|
|
>>> cmp.dist('aluminum', 'Catalan') |
505
|
|
|
0.17647058823529413 |
506
|
|
|
>>> cmp.dist('ATCG', 'TAGC') |
507
|
|
|
0.03125 |
508
|
|
|
|
509
|
|
|
""" |
510
|
1 |
|
if src == tar: |
511
|
1 |
|
return 0.0 |
512
|
|
|
|
513
|
1 |
|
src = src.encode('utf-8') |
514
|
1 |
|
tar = tar.encode('utf-8') |
515
|
|
|
|
516
|
1 |
|
src_comp = bz2.compress(src, self._level)[10:] |
517
|
1 |
|
tar_comp = bz2.compress(tar, self._level)[10:] |
518
|
1 |
|
concat_comp = bz2.compress(src + tar, self._level)[10:] |
519
|
1 |
|
concat_comp2 = bz2.compress(tar + src, self._level)[10:] |
520
|
|
|
|
521
|
1 |
|
return ( |
522
|
|
|
min(len(concat_comp), len(concat_comp2)) |
523
|
|
|
- min(len(src_comp), len(tar_comp)) |
524
|
|
|
) / max(len(src_comp), len(tar_comp)) |
525
|
|
|
|
526
|
|
|
|
527
|
1 |
|
def dist_ncd_bz2(src, tar): |
528
|
|
|
"""Return the NCD between two strings using bz2 compression. |
529
|
|
|
|
530
|
|
|
This is a wrapper for :py:meth:`NCDbz2.dist`. |
531
|
|
|
|
532
|
|
|
Args: |
533
|
|
|
src (str): Source string for comparison |
534
|
|
|
tar (str): Target string for comparison |
535
|
|
|
|
536
|
|
|
Returns: |
537
|
|
|
float: Compression distance |
538
|
|
|
|
539
|
|
|
Examples: |
540
|
|
|
>>> dist_ncd_bz2('cat', 'hat') |
541
|
|
|
0.06666666666666667 |
542
|
|
|
>>> dist_ncd_bz2('Niall', 'Neil') |
543
|
|
|
0.03125 |
544
|
|
|
>>> dist_ncd_bz2('aluminum', 'Catalan') |
545
|
|
|
0.17647058823529413 |
546
|
|
|
>>> dist_ncd_bz2('ATCG', 'TAGC') |
547
|
|
|
0.03125 |
548
|
|
|
|
549
|
|
|
""" |
550
|
1 |
|
return NCDbz2().dist(src, tar) |
551
|
|
|
|
552
|
|
|
|
553
|
1 |
|
def sim_ncd_bz2(src, tar): |
554
|
|
|
"""Return the NCD similarity between two strings using bz2 compression. |
555
|
|
|
|
556
|
|
|
This is a wrapper for :py:meth:`NCDbz2.sim`. |
557
|
|
|
|
558
|
|
|
Args: |
559
|
|
|
src (str): Source string for comparison |
560
|
|
|
tar (str): Target string for comparison |
561
|
|
|
|
562
|
|
|
Returns: |
563
|
|
|
float: Compression similarity |
564
|
|
|
|
565
|
|
|
Examples: |
566
|
|
|
>>> sim_ncd_bz2('cat', 'hat') |
567
|
|
|
0.9333333333333333 |
568
|
|
|
>>> sim_ncd_bz2('Niall', 'Neil') |
569
|
|
|
0.96875 |
570
|
|
|
>>> sim_ncd_bz2('aluminum', 'Catalan') |
571
|
|
|
0.8235294117647058 |
572
|
|
|
>>> sim_ncd_bz2('ATCG', 'TAGC') |
573
|
|
|
0.96875 |
574
|
|
|
|
575
|
|
|
""" |
576
|
1 |
|
return NCDbz2().sim(src, tar) |
577
|
|
|
|
578
|
|
|
|
579
|
1 |
|
class NCDlzma(Distance): |
|
|
|
|
580
|
|
|
"""Normalized Compression Distance using lzma compression. |
581
|
|
|
|
582
|
|
|
Normalized compression distance (NCD) :cite:`Cilibrasi:2005`. |
583
|
|
|
""" |
584
|
|
|
|
585
|
1 |
|
def dist(self, src, tar): |
|
|
|
|
586
|
|
|
"""Return the NCD between two strings using lzma compression. |
587
|
|
|
|
588
|
|
|
Args: |
589
|
|
|
src (str): Source string for comparison |
590
|
|
|
tar (str): Target string for comparison |
591
|
|
|
|
592
|
|
|
Returns: |
593
|
|
|
float: Compression distance |
594
|
|
|
|
595
|
|
|
Raises: |
596
|
|
|
ValueError: Install the PylibLZMA module in order to use lzma |
597
|
|
|
|
598
|
|
|
Examples: |
599
|
|
|
>>> cmp = NCDlzma() |
600
|
|
|
>>> cmp.dist('cat', 'hat') |
601
|
|
|
0.08695652173913043 |
602
|
|
|
>>> cmp.dist('Niall', 'Neil') |
603
|
|
|
0.16 |
604
|
|
|
>>> cmp.dist('aluminum', 'Catalan') |
605
|
|
|
0.16 |
606
|
|
|
>>> cmp.dist('ATCG', 'TAGC') |
607
|
|
|
0.08695652173913043 |
608
|
|
|
|
609
|
|
|
""" |
610
|
|
|
if src == tar: |
611
|
|
|
return 0.0 |
612
|
|
|
|
613
|
|
|
src = src.encode('utf-8') |
614
|
|
|
tar = tar.encode('utf-8') |
615
|
|
|
|
616
|
|
|
if lzma is not None: |
617
|
|
|
src_comp = lzma.compress(src)[14:] |
618
|
|
|
tar_comp = lzma.compress(tar)[14:] |
619
|
|
|
concat_comp = lzma.compress(src + tar)[14:] |
620
|
|
|
concat_comp2 = lzma.compress(tar + src)[14:] |
621
|
|
|
else: # pragma: no cover |
622
|
|
|
raise ValueError( |
623
|
|
|
'Install the PylibLZMA module in order to use lzma' |
624
|
|
|
) |
625
|
|
|
|
626
|
|
|
return ( |
627
|
|
|
min(len(concat_comp), len(concat_comp2)) |
628
|
|
|
- min(len(src_comp), len(tar_comp)) |
629
|
|
|
) / max(len(src_comp), len(tar_comp)) |
630
|
|
|
|
631
|
|
|
|
632
|
1 |
|
def dist_ncd_lzma(src, tar): |
633
|
|
|
"""Return the NCD between two strings using lzma compression. |
634
|
|
|
|
635
|
|
|
This is a wrapper for :py:meth:`NCDlzma.dist`. |
636
|
|
|
|
637
|
|
|
Args: |
638
|
|
|
src (str): Source string for comparison |
639
|
|
|
tar (str): Target string for comparison |
640
|
|
|
|
641
|
|
|
Returns: |
642
|
|
|
float: Compression distance |
643
|
|
|
|
644
|
|
|
Examples: |
645
|
|
|
>>> dist_ncd_lzma('cat', 'hat') |
646
|
|
|
0.08695652173913043 |
647
|
|
|
>>> dist_ncd_lzma('Niall', 'Neil') |
648
|
|
|
0.16 |
649
|
|
|
>>> dist_ncd_lzma('aluminum', 'Catalan') |
650
|
|
|
0.16 |
651
|
|
|
>>> dist_ncd_lzma('ATCG', 'TAGC') |
652
|
|
|
0.08695652173913043 |
653
|
|
|
|
654
|
|
|
""" |
655
|
|
|
return NCDlzma().dist(src, tar) |
656
|
|
|
|
657
|
|
|
|
658
|
1 |
|
def sim_ncd_lzma(src, tar): |
659
|
|
|
"""Return the NCD similarity between two strings using lzma compression. |
660
|
|
|
|
661
|
|
|
This is a wrapper for :py:meth:`NCDlzma.sim`. |
662
|
|
|
|
663
|
|
|
Args: |
664
|
|
|
src (str): Source string for comparison |
665
|
|
|
tar (str): Target string for comparison |
666
|
|
|
|
667
|
|
|
Returns: |
668
|
|
|
float: Compression similarity |
669
|
|
|
|
670
|
|
|
Examples: |
671
|
|
|
>>> sim_ncd_lzma('cat', 'hat') |
672
|
|
|
0.9130434782608696 |
673
|
|
|
>>> sim_ncd_lzma('Niall', 'Neil') |
674
|
|
|
0.84 |
675
|
|
|
>>> sim_ncd_lzma('aluminum', 'Catalan') |
676
|
|
|
0.84 |
677
|
|
|
>>> sim_ncd_lzma('ATCG', 'TAGC') |
678
|
|
|
0.9130434782608696 |
679
|
|
|
|
680
|
|
|
""" |
681
|
|
|
return NCDlzma().sim(src, tar) |
682
|
|
|
|
683
|
|
|
|
684
|
|
|
if __name__ == '__main__': |
685
|
|
|
import doctest |
686
|
|
|
|
687
|
|
|
doctest.testmod() |
688
|
|
|
|