"""Fuzzy Wuzzy Partial Ratio Similarity Measure"""
from __future__ import division
from difflib import SequenceMatcher
from py_stringmatching import utils
from py_stringmatching.similarity_measure.sequence_similarity_measure import \
SequenceSimilarityMeasure
[docs]class PartialRatio(SequenceSimilarityMeasure):
"""Computes the Fuzzy Wuzzy partial ratio similarity between two strings.
Fuzzy Wuzzy partial ratio raw score is a measure of the strings similarity as an int in the
range [0, 100]. Given two strings X and Y, let the shorter string (X) be of length m.
It finds the fuzzy wuzzy ratio similarity measure between the shorter string and every
substring of length m of the longer string, and returns the maximum of
those similarity measures. Fuzzy Wuzzy partial ratio sim score is a float in the range [0, 1]
and is obtained by dividing the raw score by 100.
Note:
In the case where either of strings X or Y are empty, we define the Fuzzy Wuzzy ratio similarity
score to be 0.
"""
def __init__(self):
pass
[docs] def get_raw_score(self, string1, string2):
"""
Computes the Fuzzy Wuzzy partial ratio measure raw score between two strings.
This score is in the range [0,100].
Args:
string1,string2 (str): Input strings
Returns:
Partial Ratio measure raw score (int) is returned
Raises:
TypeError: If the inputs are not strings
Examples:
>>> s = PartialRatio()
>>> s.get_raw_score('Robert Rupert', 'Rupert')
100
>>> s.get_raw_score('Sue', 'sue')
67
>>> s.get_raw_score('example', 'samples')
86
References:
* https://pypi.python.org/pypi/fuzzywuzzy
"""
# input validations
utils.sim_check_for_none(string1, string2)
utils.sim_check_for_string_inputs(string1, string2)
# if one of the strings is empty return 0
if utils.sim_check_for_empty(string1, string2):
return 0
string1 = utils.convert_to_unicode(string1)
string2 = utils.convert_to_unicode(string2)
# string1 should be smaller in length than string2. If this is not the case
# then swap string1 and string2
if len(string1) > len(string2):
temp = string1
string1 = string2
string2 = temp
sm = SequenceMatcher(None, string1, string2)
matching_blocks = sm.get_matching_blocks()
scores = []
for block in matching_blocks:
string2_starting_index = 0
if (block[1] - block[0] > 0):
string2_starting_index = block[1] - block[0]
string2_ending_index = string2_starting_index + len(string1)
string2_substr = string2[string2_starting_index:string2_ending_index]
sm2 = SequenceMatcher(None, string1, string2_substr)
similarity_ratio = sm2.ratio()
if similarity_ratio > .995:
return 100
else:
scores.append(similarity_ratio)
return int(round(100 * max(scores)))
[docs] def get_sim_score(self, string1, string2):
"""
Computes the Fuzzy Wuzzy partial ratio similarity score between two strings.
This score is in the range [0,1].
Args:
string1,string2 (str): Input strings
Returns:
Partial Ratio measure similarity score (float) is returned
Raises:
TypeError: If the inputs are not strings
Examples:
>>> s = PartialRatio()
>>> s.get_sim_score('Robert Rupert', 'Rupert')
1.0
>>> s.get_sim_score('Sue', 'sue')
0.67
>>> s.get_sim_score('example', 'samples')
0.86
References:
* https://pypi.python.org/pypi/fuzzywuzzy
"""
# input validations
utils.sim_check_for_none(string1, string2)
utils.sim_check_for_string_inputs(string1, string2)
# if one of the strings is empty return 0
if utils.sim_check_for_empty(string1, string2):
return 0
raw_score = 1.0 * self.get_raw_score(string1, string2)
sim_score = raw_score / 100
return sim_score