| // Copyright 2011 Google Inc. All Rights Reserved. |
| // |
| // Licensed under the Apache License, Version 2.0 (the "License"); |
| // you may not use this file except in compliance with the License. |
| // You may obtain a copy of the License at |
| // |
| // http://www.apache.org/licenses/LICENSE-2.0 |
| // |
| // Unless required by applicable law or agreed to in writing, software |
| // distributed under the License is distributed on an "AS IS" BASIS, |
| // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
| // See the License for the specific language governing permissions and |
| // limitations under the License. |
| |
| #include "edit_distance.h" |
| |
| #include <algorithm> |
| #include <vector> |
| |
| int EditDistance(const StringPiece& s1, |
| const StringPiece& s2, |
| bool allow_replacements, |
| int max_edit_distance) { |
| // The algorithm implemented below is the "classic" |
| // dynamic-programming algorithm for computing the Levenshtein |
| // distance, which is described here: |
| // |
| // http://en.wikipedia.org/wiki/Levenshtein_distance |
| // |
| // Although the algorithm is typically described using an m x n |
| // array, only one row plus one element are used at a time, so this |
| // implementation just keeps one vector for the row. To update one entry, |
| // only the entries to the left, top, and top-left are needed. The left |
| // entry is in row[x-1], the top entry is what's in row[x] from the last |
| // iteration, and the top-left entry is stored in previous. |
| int m = s1.len_; |
| int n = s2.len_; |
| |
| vector<int> row(n + 1); |
| for (int i = 1; i <= n; ++i) |
| row[i] = i; |
| |
| for (int y = 1; y <= m; ++y) { |
| row[0] = y; |
| int best_this_row = row[0]; |
| |
| int previous = y - 1; |
| for (int x = 1; x <= n; ++x) { |
| int old_row = row[x]; |
| if (allow_replacements) { |
| row[x] = min(previous + (s1.str_[y - 1] == s2.str_[x - 1] ? 0 : 1), |
| min(row[x - 1], row[x]) + 1); |
| } |
| else { |
| if (s1.str_[y - 1] == s2.str_[x - 1]) |
| row[x] = previous; |
| else |
| row[x] = min(row[x - 1], row[x]) + 1; |
| } |
| previous = old_row; |
| best_this_row = min(best_this_row, row[x]); |
| } |
| |
| if (max_edit_distance && best_this_row > max_edit_distance) |
| return max_edit_distance + 1; |
| } |
| |
| return row[n]; |
| } |