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from py_stringmatching import utils
from six.moves import xrange
from py_stringmatching.similarity_measure.sequence_similarity_measure import \
SequenceSimilarityMeasure
from py_stringmatching.similarity_measure.cython.cython_jaro import jaro
class Jaro(SequenceSimilarityMeasure):
"""Computes Jaro measure.
The Jaro measure is a type of edit distance, developed mainly to compare short strings,
such as first and last names.
"""
def __init__(self):
super(Jaro, self).__init__()
def get_raw_score(self, string1, string2):
"""Computes the raw Jaro score between two strings.
Args:
string1,string2 (str): Input strings.
Returns:
Jaro similarity score (float).
Raises:
TypeError : If the inputs are not strings or if one of the inputs is None.
Examples:
>>> jaro = Jaro()
>>> jaro.get_raw_score('MARTHA', 'MARHTA')
0.9444444444444445
>>> jaro.get_raw_score('DWAYNE', 'DUANE')
0.8222222222222223
>>> jaro.get_raw_score('DIXON', 'DICKSONX')
0.7666666666666666
"""
# input validations
utils.sim_check_for_none(string1, string2)
# convert input to unicode.
string1 = utils.convert_to_unicode(string1)
string2 = utils.convert_to_unicode(string2)
utils.tok_check_for_string_input(string1, string2)
# if one of the strings is empty return 0
if utils.sim_check_for_empty(string1, string2):
return 0
return jaro(string1, string2)
def get_sim_score(self, string1, string2):
"""Computes the normalized Jaro similarity score between two strings. Simply call get_raw_score.
Args:
string1,string2 (str): Input strings.
Returns:
Normalized Jaro similarity score (float).
Raises:
TypeError : If the inputs are not strings or if one of the inputs is None.
Examples:
>>> jaro = Jaro()
>>> jaro.get_sim_score('MARTHA', 'MARHTA')
0.9444444444444445
>>> jaro.get_sim_score('DWAYNE', 'DUANE')
0.8222222222222223
>>> jaro.get_sim_score('DIXON', 'DICKSONX')
0.7666666666666666
"""
return self.get_raw_score(string1, string2)
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