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| 1 | +/* |
| 2 | + * Licensed to the Apache Software Foundation (ASF) under one or more |
| 3 | + * contributor license agreements. See the NOTICE file distributed with |
| 4 | + * this work for additional information regarding copyright ownership. |
| 5 | + * The ASF licenses this file to You under the Apache License, Version 2.0 |
| 6 | + * (the "License"); you may not use this file except in compliance with |
| 7 | + * the License. You may obtain a copy of the License at |
| 8 | + * |
| 9 | + * https://www.apache.org/licenses/LICENSE-2.0 |
| 10 | + * |
| 11 | + * Unless required by applicable law or agreed to in writing, software |
| 12 | + * distributed under the License is distributed on an "AS IS" BASIS, |
| 13 | + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
| 14 | + * See the License for the specific language governing permissions and |
| 15 | + * limitations under the License. |
| 16 | + */ |
| 17 | +package org.apache.commons.text.similarity; |
| 18 | + |
| 19 | +/** |
| 20 | + * An algorithm for measuring the difference between two character sequences using the |
| 21 | + * <a href="https://en.wikipedia.org/wiki/Damerau%E2%80%93Levenshtein_distance">Damerau-Levenshtein Distance</a>. |
| 22 | + * |
| 23 | + * <p> |
| 24 | + * This is the number of changes needed to change one sequence into another, where each change is a single character |
| 25 | + * modification (deletion, insertion, substitution, or transposition of two adjacent characters). |
| 26 | + * </p> |
| 27 | + * |
| 28 | + * @see <a href="https://en.wikipedia.org/wiki/Damerau%E2%80%93Levenshtein_distance">Damerau-Levenshtein Distance on Wikipedia</a> |
| 29 | + * @since 1.15.0 |
| 30 | + */ |
| 31 | +public class DamerauLevenshteinDistance implements EditDistance<Integer> { |
| 32 | + |
| 33 | + /** |
| 34 | + * Utility function to ensure distance is valid according to threshold. |
| 35 | + * |
| 36 | + * @param distance The distance value |
| 37 | + * @param threshold The threshold value |
| 38 | + * @return The distance value, or {@code -1} if distance is greater than threshold |
| 39 | + */ |
| 40 | + private static int clampDistance(final int distance, final int threshold) { |
| 41 | + return distance > threshold ? -1 : distance; |
| 42 | + } |
| 43 | + |
| 44 | + /** |
| 45 | + * Finds the Damerau-Levenshtein distance between two CharSequences if it's less than or equal to a given threshold. |
| 46 | + * |
| 47 | + * @param left the first SimilarityInput, must not be null. |
| 48 | + * @param right the second SimilarityInput, must not be null. |
| 49 | + * @param threshold the target threshold, must not be negative. |
| 50 | + * @return result distance, or -1 if distance exceeds threshold |
| 51 | + */ |
| 52 | + private static <E> int limitedCompare(SimilarityInput<E> left, SimilarityInput<E> right, final int threshold) { |
| 53 | + if (left == null || right == null) { |
| 54 | + throw new IllegalArgumentException("Left/right inputs must not be null"); |
| 55 | + } |
| 56 | + |
| 57 | + if (threshold < 0) { |
| 58 | + throw new IllegalArgumentException("Threshold can not be negative"); |
| 59 | + } |
| 60 | + |
| 61 | + // Implementation based on https://en.wikipedia.org/wiki/Damerau%E2%80%93Levenshtein_distance#Optimal_string_alignment_distance |
| 62 | + |
| 63 | + int leftLength = left.length(); |
| 64 | + int rightLength = right.length(); |
| 65 | + |
| 66 | + if (leftLength == 0) { |
| 67 | + return clampDistance(rightLength, threshold); |
| 68 | + } |
| 69 | + |
| 70 | + if (rightLength == 0) { |
| 71 | + return clampDistance(leftLength, threshold); |
| 72 | + } |
| 73 | + |
| 74 | + // Inspired by LevenshteinDistance impl; swap the input strings to consume less memory |
| 75 | + if (rightLength > leftLength) { |
| 76 | + final SimilarityInput<E> tmp = left; |
| 77 | + left = right; |
| 78 | + right = tmp; |
| 79 | + leftLength = rightLength; |
| 80 | + rightLength = right.length(); |
| 81 | + } |
| 82 | + |
| 83 | + // If the difference between the lengths of the strings is greater than the threshold, we must at least do |
| 84 | + // threshold operations so we can return early |
| 85 | + if (leftLength - rightLength > threshold) { |
| 86 | + return -1; |
| 87 | + } |
| 88 | + |
| 89 | + // Use three arrays of minimum possible size to reduce memory usage. This avoids having to create a 2D |
| 90 | + // array of size leftLength * rightLength |
| 91 | + int[] curr = new int[rightLength + 1]; |
| 92 | + int[] prev = new int[rightLength + 1]; |
| 93 | + int[] prevPrev = new int[rightLength + 1]; |
| 94 | + int[] temp; // Temp variable use to shuffle arrays at the end of each iteration |
| 95 | + |
| 96 | + int rightIndex, leftIndex, cost, minCost; |
| 97 | + |
| 98 | + // Changing empty sequence to [0..i] requires i insertions |
| 99 | + for (rightIndex = 0; rightIndex <= rightLength; rightIndex++) { |
| 100 | + prev[rightIndex] = rightIndex; |
| 101 | + } |
| 102 | + |
| 103 | + // Calculate how many operations it takes to change right[0..rightIndex] into left[0..leftIndex] |
| 104 | + // For each iteration |
| 105 | + // - curr[i] contains the cost of changing right[0..i] into left[0..leftIndex] |
| 106 | + // (computed in current iteration) |
| 107 | + // - prev[i] contains the cost of changing right[0..i] into left[0..leftIndex - 1] |
| 108 | + // (computed in previous iteration) |
| 109 | + // - prevPrev[i] contains the cost of changing right[0..i] into left[0..leftIndex - 2] |
| 110 | + // (computed in iteration before previous) |
| 111 | + for (leftIndex = 1; leftIndex <= leftLength; leftIndex++) { |
| 112 | + // For right[0..0] we must insert leftIndex characters, which means the cost is always leftIndex |
| 113 | + curr[0] = leftIndex; |
| 114 | + |
| 115 | + minCost = Integer.MAX_VALUE; |
| 116 | + |
| 117 | + for (rightIndex = 1; rightIndex <= rightLength; rightIndex++) { |
| 118 | + cost = (left.at(leftIndex - 1) == right.at(rightIndex - 1)) ? 0 : 1; |
| 119 | + |
| 120 | + // Select cheapest operation |
| 121 | + curr[rightIndex] = Math.min( |
| 122 | + Math.min( |
| 123 | + prev[rightIndex] + 1, // Delete current character |
| 124 | + curr[rightIndex - 1] + 1 // Insert current character |
| 125 | + ), |
| 126 | + prev[rightIndex - 1] + cost // Replace (or no cost if same character) |
| 127 | + ); |
| 128 | + |
| 129 | + // Check if adjacent characters are the same -> transpose if cheaper |
| 130 | + if (leftIndex > 1 |
| 131 | + && rightIndex > 1 |
| 132 | + && left.at(leftIndex - 1) == right.at(rightIndex - 2) |
| 133 | + && left.at(leftIndex - 2) == right.at(rightIndex - 1)) { |
| 134 | + // Use cost here, to properly handle two subsequent equal letters |
| 135 | + curr[rightIndex] = Math.min(curr[rightIndex], prevPrev[rightIndex - 2] + cost); |
| 136 | + } |
| 137 | + |
| 138 | + minCost = Math.min(curr[rightIndex], minCost); |
| 139 | + } |
| 140 | + |
| 141 | + // If there was no total cost for this entire iteration to transform right to left[0..leftIndex], there |
| 142 | + // can not be a way to do it below threshold. This is because we have no way to reduce the overall cost |
| 143 | + // in later operations. |
| 144 | + if (minCost > threshold) { |
| 145 | + return -1; |
| 146 | + } |
| 147 | + |
| 148 | + // Rotate arrays for next iteration |
| 149 | + temp = prevPrev; |
| 150 | + prevPrev = prev; |
| 151 | + prev = curr; |
| 152 | + curr = temp; |
| 153 | + } |
| 154 | + |
| 155 | + // Prev contains the value computed in the latest iteration |
| 156 | + return clampDistance(prev[rightLength], threshold); |
| 157 | + } |
| 158 | + |
| 159 | + /** |
| 160 | + * Finds the Damerau-Levenshtein distance between two inputs using optimal string alignment. |
| 161 | + * |
| 162 | + * @param left the first CharSequence, must not be null. |
| 163 | + * @param right the second CharSequence, must not be null. |
| 164 | + * @return result distance. |
| 165 | + * @throws IllegalArgumentException if either CharSequence input is {@code null}. |
| 166 | + */ |
| 167 | + private static <E> int unlimitedCompare(SimilarityInput<E> left, SimilarityInput<E> right) { |
| 168 | + if (left == null || right == null) { |
| 169 | + throw new IllegalArgumentException("Left/right inputs must not be null"); |
| 170 | + } |
| 171 | + |
| 172 | + /* |
| 173 | + * Implementation based on https://en.wikipedia.org/wiki/Damerau%E2%80%93Levenshtein_distance#Optimal_string_alignment_distance |
| 174 | + */ |
| 175 | + |
| 176 | + int leftLength = left.length(); |
| 177 | + int rightLength = right.length(); |
| 178 | + |
| 179 | + if (leftLength == 0) { |
| 180 | + return rightLength; |
| 181 | + } |
| 182 | + |
| 183 | + if (rightLength == 0) { |
| 184 | + return leftLength; |
| 185 | + } |
| 186 | + |
| 187 | + // Inspired by LevenshteinDistance impl; swap the input strings to consume less memory |
| 188 | + if (rightLength > leftLength) { |
| 189 | + final SimilarityInput<E> tmp = left; |
| 190 | + left = right; |
| 191 | + right = tmp; |
| 192 | + leftLength = rightLength; |
| 193 | + rightLength = right.length(); |
| 194 | + } |
| 195 | + |
| 196 | + // Use three arrays of minimum possible size to reduce memory usage. This avoids having to create a 2D |
| 197 | + // array of size leftLength * rightLength |
| 198 | + int[] curr = new int[rightLength + 1]; |
| 199 | + int[] prev = new int[rightLength + 1]; |
| 200 | + int[] prevPrev = new int[rightLength + 1]; |
| 201 | + int[] temp; // Temp variable use to shuffle arrays at the end of each iteration |
| 202 | + |
| 203 | + int rightIndex, leftIndex, cost; |
| 204 | + |
| 205 | + // Changing empty sequence to [0..i] requires i insertions |
| 206 | + for (rightIndex = 0; rightIndex <= rightLength; rightIndex++) { |
| 207 | + prev[rightIndex] = rightIndex; |
| 208 | + } |
| 209 | + |
| 210 | + // Calculate how many operations it takes to change right[0..rightIndex] into left[0..leftIndex] |
| 211 | + // For each iteration |
| 212 | + // - curr[i] contains the cost of changing right[0..i] into left[0..leftIndex] |
| 213 | + // (computed in current iteration) |
| 214 | + // - prev[i] contains the cost of changing right[0..i] into left[0..leftIndex - 1] |
| 215 | + // (computed in previous iteration) |
| 216 | + // - prevPrev[i] contains the cost of changing right[0..i] into left[0..leftIndex - 2] |
| 217 | + // (computed in iteration before previous) |
| 218 | + for (leftIndex = 1; leftIndex <= leftLength; leftIndex++) { |
| 219 | + // For right[0..0] we must insert leftIndex characters, which means the cost is always leftIndex |
| 220 | + curr[0] = leftIndex; |
| 221 | + |
| 222 | + for (rightIndex = 1; rightIndex <= rightLength; rightIndex++) { |
| 223 | + cost = (left.at(leftIndex - 1) == right.at(rightIndex - 1)) ? 0 : 1; |
| 224 | + |
| 225 | + // Select cheapest operation |
| 226 | + curr[rightIndex] = Math.min( |
| 227 | + Math.min( |
| 228 | + prev[rightIndex] + 1, // Delete current character |
| 229 | + curr[rightIndex - 1] + 1 // Insert current character |
| 230 | + ), |
| 231 | + prev[rightIndex - 1] + cost // Replace (or no cost if same character) |
| 232 | + ); |
| 233 | + |
| 234 | + // Check if adjacent characters are the same -> transpose if cheaper |
| 235 | + if (leftIndex > 1 |
| 236 | + && rightIndex > 1 |
| 237 | + && left.at(leftIndex - 1) == right.at(rightIndex - 2) |
| 238 | + && left.at(leftIndex - 2) == right.at(rightIndex - 1)) { |
| 239 | + // Use cost here, to properly handle two subsequent equal letters |
| 240 | + curr[rightIndex] = Math.min(curr[rightIndex], prevPrev[rightIndex - 2] + cost); |
| 241 | + } |
| 242 | + } |
| 243 | + |
| 244 | + // Rotate arrays for next iteration |
| 245 | + temp = prevPrev; |
| 246 | + prevPrev = prev; |
| 247 | + prev = curr; |
| 248 | + curr = temp; |
| 249 | + } |
| 250 | + |
| 251 | + // Prev contains the value computed in the latest iteration |
| 252 | + return prev[rightLength]; |
| 253 | + } |
| 254 | + |
| 255 | + /** |
| 256 | + * Threshold. |
| 257 | + */ |
| 258 | + private final Integer threshold; |
| 259 | + |
| 260 | + /** |
| 261 | + * Constructs a default instance that uses a version of the algorithm that does not use a threshold parameter. |
| 262 | + */ |
| 263 | + public DamerauLevenshteinDistance() { |
| 264 | + this(null); |
| 265 | + } |
| 266 | + |
| 267 | + /** |
| 268 | + * Constructs a new instance. If the threshold is not null, distance calculations will be limited to a maximum length. |
| 269 | + * If the threshold is null, the unlimited version of the algorithm will be used. |
| 270 | + * |
| 271 | + * @param threshold If this is null then distances calculations will not be limited. This may not be negative. |
| 272 | + */ |
| 273 | + public DamerauLevenshteinDistance(final Integer threshold) { |
| 274 | + if (threshold != null && threshold < 0) { |
| 275 | + throw new IllegalArgumentException("Threshold must not be negative"); |
| 276 | + } |
| 277 | + this.threshold = threshold; |
| 278 | + } |
| 279 | + |
| 280 | + /** |
| 281 | + * Computes the Damerau-Levenshtein distance between two Strings. |
| 282 | + * |
| 283 | + * <p> |
| 284 | + * A higher score indicates a greater distance. |
| 285 | + * </p> |
| 286 | + * |
| 287 | + * @param left the first input, must not be null. |
| 288 | + * @param right the second input, must not be null. |
| 289 | + * @return result distance, or -1 if threshold is exceeded. |
| 290 | + * @throws IllegalArgumentException if either String input {@code null}. |
| 291 | + */ |
| 292 | + @Override |
| 293 | + public Integer apply(final CharSequence left, final CharSequence right) { |
| 294 | + return apply(SimilarityInput.input(left), SimilarityInput.input(right)); |
| 295 | + } |
| 296 | + |
| 297 | + /** |
| 298 | + * Computes the Damerau-Levenshtein distance between two inputs. |
| 299 | + * |
| 300 | + * <p> |
| 301 | + * A higher score indicates a greater distance. |
| 302 | + * </p> |
| 303 | + * |
| 304 | + * @param <E> The type of similarity score unit. |
| 305 | + * @param left the first input, must not be null. |
| 306 | + * @param right the second input, must not be null. |
| 307 | + * @return result distance, or -1 if threshold is exceeded. |
| 308 | + * @throws IllegalArgumentException if either String input {@code null}. |
| 309 | + * @since 1.13.0 |
| 310 | + */ |
| 311 | + public <E> Integer apply(final SimilarityInput<E> left, final SimilarityInput<E> right) { |
| 312 | + if (threshold != null) { |
| 313 | + return limitedCompare(left, right, threshold); |
| 314 | + } |
| 315 | + return unlimitedCompare(left, right); |
| 316 | + } |
| 317 | + |
| 318 | + /** |
| 319 | + * Gets the distance threshold. |
| 320 | + * |
| 321 | + * @return The distance threshold. |
| 322 | + */ |
| 323 | + public Integer getThreshold() { |
| 324 | + return threshold; |
| 325 | + } |
| 326 | +} |
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