113 lines
3.2 KiB
Ruby
113 lines
3.2 KiB
Ruby
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# Levenshtein distance algorithm implementation for Ruby, with UTF-8 support
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#
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# Author:: Paul BATTLEY (pbattley @ gmail.com)
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# Version:: 1.3
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# Date:: 2005-04-19
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#
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# == About
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#
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# The Levenshtein distance is a measure of how similar two strings s and t are,
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# calculated as the number of deletions/insertions/substitutions needed to
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# transform s into t. The greater the distance, the more the strings differ.
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#
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# The Levenshtein distance is also sometimes referred to as the
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# easier-to-pronounce-and-spell 'edit distance'.
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#
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# == Revision history
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#
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# * 2005-05-19 1.3 Repairing an oversight, distance can now be called via
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# Levenshtein.distance(s, t)
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# * 2005-05-04 1.2 Now uses just one 1-dimensional array. I think this is as
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# far as optimisation can go.
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# * 2005-05-04 1.1 Now storing only the current and previous rows of the matrix
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# instead of the whole lot.
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#
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# == Licence
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#
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# Copyright (c) 2005 Paul Battley
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#
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# Usage of the works is permitted provided that this instrument is retained
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# with the works, so that any entity that uses the works is notified of this
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# instrument.
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#
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# DISCLAIMER: THE WORKS ARE WITHOUT WARRANTY.
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#
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module Levenshtein
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#
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# Calculate the Levenshtein distance between two strings +str1+ and +str2+.
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# +str1+ and +str2+ should be ASCII or UTF-8.
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#
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def distance(str1, str2)
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s = str1.unpack('U*')
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t = str2.unpack('U*')
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n = s.length
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m = t.length
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return m if (0 == n)
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return n if (0 == m)
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d = (0..m).to_a
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x = nil
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(0...n).each do |i|
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e = i+1
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(0...m).each do |j|
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cost = (s[i] == t[j]) ? 0 : 1
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x = [
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d[j+1] + 1, # insertion
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e + 1, # deletion
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d[j] + cost # substitution
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].min
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d[j] = e
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e = x
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end
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d[m] = x
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end
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return x
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end
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extend self
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end
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if (__FILE__ == $0)
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require 'test/unit'
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class LevenshteinTest < Test::Unit::TestCase
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include Levenshtein
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EXPECTED = [
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# Easy ones
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['test', 'test', 0],
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['test', 'tent', 1],
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['gumbo', 'gambol', 2],
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['kitten', 'sitting', 3],
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# Empty strings
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['foo', '', 3],
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['', '', 0],
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['a', '', 1],
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# UTF-8
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["f\303\266o", 'foo', 1],
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["fran\303\247ais", 'francais', 1],
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["fran\303\247ais", "fran\303\246ais", 1],
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["\347\247\201\343\201\256\345\220\215\345\211\215\343\201\257"<<
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"\343\203\235\343\203\274\343\203\253\343\201\247\343\201\231",
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"\343\201\274\343\201\217\343\201\256\345\220\215\345\211\215\343\201"<<
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"\257\343\203\235\343\203\274\343\203\253\343\201\247\343\201\231",
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2], # Japanese
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# Edge cases
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['a', 'a', 0],
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['0123456789', 'abcdefghijklmnopqrstuvwxyz', 26]
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]
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def test_known_distances
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EXPECTED.each do |a,b,x|
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assert_equal(x, distance(a, b))
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assert_equal(x, distance(b, a))
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end
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end
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end
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end
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