Source code for abydos.distance._clark

# Copyright 2019-2020 by Christopher C. Little.
# This file is part of Abydos.
#
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"""abydos.distance._clark.

Clark's coefficient of divergence
"""

from ._token_distance import _TokenDistance

__all__ = ['Clark']


[docs]class Clark(_TokenDistance): r"""Clark's coefficient of divergence. For two sets X and Y and a population N, Clark's coefficient of divergence :cite:`Clark:1952` is: .. math:: dist_{Clark}(X, Y) = \sqrt{\frac{\sum_{i=0}^{|N|} \big(\frac{x_i-y_i}{x_i+y_i}\big)^2}{|N|}} .. versionadded:: 0.4.1 """ def __init__(self, **kwargs): """Initialize Clark instance. Parameters ---------- **kwargs Arbitrary keyword arguments .. versionadded:: 0.4.1 """ super(Clark, self).__init__(**kwargs)
[docs] def dist(self, src, tar): """Return Clark's coefficient of divergence of two strings. Parameters ---------- src : str Source string for comparison tar : str Target string for comparison Returns ------- float Clark's coefficient of divergence Examples -------- >>> cmp = Clark() >>> cmp.dist('cat', 'hat') 0.816496580927726 >>> cmp.dist('Niall', 'Neil') 0.8819171036881969 >>> cmp.dist('aluminum', 'Catalan') 0.9660917830792959 >>> cmp.dist('ATCG', 'TAGC') 1.0 .. versionadded:: 0.4.1 """ if src == tar: return 0.0 self._tokenize(src, tar) src_tok = self._src_tokens tar_tok = self._tar_tokens alphabet = set(src_tok.keys() | tar_tok.keys()) return ( sum( ((src_tok[ltr] - tar_tok[ltr]) / (src_tok[ltr] + tar_tok[ltr])) ** 2 for ltr in alphabet ) / len(alphabet) ) ** 0.5
if __name__ == '__main__': import doctest doctest.testmod()