# Copyright (c) 2018 luozhouyang # # Permission is hereby granted, free of charge, to any person obtaining a copy # of this software and associated documentation files (the "Software"), to deal # in the Software without restriction, including without limitation the rights # to use, copy, modify, merge, publish, distribute, sublicense, and/or sell # copies of the Software, and to permit persons to whom the Software is # furnished to do so, subject to the following conditions: # # The above copyright notice and this permission notice shall be included in all # copies or substantial portions of the Software. # # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE # SOFTWARE. from functools import reduce from .string_distance import StringDistance def default_insertion_cost(char): return 1.0 def default_deletion_cost(char): return 1.0 def default_substitution_cost(char_a, char_b): return 1.0 class WeightedLevenshtein(StringDistance): def __init__(self, substitution_cost_fn=default_substitution_cost, insertion_cost_fn=default_insertion_cost, deletion_cost_fn=default_deletion_cost, ): self.substitution_cost_fn = substitution_cost_fn self.insertion_cost_fn = insertion_cost_fn self.deletion_cost_fn = deletion_cost_fn def distance(self, s0, s1): if s0 is None: raise TypeError("Argument s0 is NoneType.") if s1 is None: raise TypeError("Argument s1 is NoneType.") if s0 == s1: return 0.0 if len(s0) == 0: return reduce(lambda cost, char: cost + self.insertion_cost_fn(char), s1, 0) if len(s1) == 0: return reduce(lambda cost, char: cost + self.deletion_cost_fn(char), s0, 0) v0, v1 = [0.0] * (len(s1) + 1), [0.0] * (len(s1) + 1) v0[0] = 0 for i in range(1, len(v0)): v0[i] = v0[i - 1] + self.insertion_cost_fn(s1[i - 1]) for i in range(len(s0)): s0i = s0[i] deletion_cost = self.deletion_cost_fn(s0i) v1[0] = v0[0] + deletion_cost for j in range(len(s1)): s1j = s1[j] cost = 0 if s0i != s1j: cost = self.substitution_cost_fn(s0i, s1j) insertion_cost = self.insertion_cost_fn(s1j) v1[j + 1] = min(v1[j] + insertion_cost, v0[j + 1] + deletion_cost, v0[j] + cost) v0, v1 = v1, v0 return v0[len(s1)]