Source code for abydos.distance._bisim

# Copyright 2019-2020 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
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#
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# GNU General Public License for more details.
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"""abydos.distance._bisim.

BI-SIM similarity
"""

from numpy import float as np_float
from numpy import zeros as np_zeros

from ._distance import _Distance

__all__ = ['BISIM']


[docs]class BISIM(_Distance): r"""BI-SIM similarity. BI-SIM similarity :cite:`Kondrak:2003` is an n-gram based, edit-distance derived similarity measure. .. versionadded:: 0.4.0 """ def __init__(self, qval=2, **kwargs): """Initialize BISIM instance. Parameters ---------- qval : int The number of characters to consider in each n-gram (q-gram). By default this is 2, hence BI-SIM. But TRI-SIM can be calculated by setting this to 3. **kwargs Arbitrary keyword arguments .. versionadded:: 0.4.0 """ super(BISIM, self).__init__(**kwargs) self._qval = qval
[docs] def sim(self, src, tar): """Return the BI-SIM similarity of two strings. Parameters ---------- src : str Source string for comparison tar : str Target string for comparison Returns ------- float BI-SIM similarity Examples -------- >>> cmp = BISIM() >>> cmp.sim('cat', 'hat') 0.5 >>> cmp.sim('Niall', 'Neil') 0.4 >>> cmp.sim('aluminum', 'Catalan') 0.3125 >>> cmp.sim('ATCG', 'TAGC') 0.375 .. versionadded:: 0.4.0 """ src_len = len(src) tar_len = len(tar) if src == tar: return 1.0 if not src or not tar: return 0.0 def _id(src_pos, tar_pos): s = 0 for i in range(self._qval): s += int(src[src_pos + i] == tar[tar_pos + i]) return s / self._qval src = src[0].swapcase() * (self._qval - 1) + src tar = tar[0].swapcase() * (self._qval - 1) + tar d_mat = np_zeros((src_len + 1, tar_len + 1), dtype=np_float) for i in range(1, src_len + 1): for j in range(1, tar_len + 1): d_mat[i, j] = max( d_mat[i - 1, j - 1] + _id(i - 1, j - 1), # sub/== d_mat[i - 1, j], # ins d_mat[i, j - 1], # del ) return d_mat[src_len, tar_len] / max(src_len, tar_len)
if __name__ == '__main__': import doctest doctest.testmod()