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< > BotCompany Repo | #1026090 // EditDistance (Ukkonen-optimized Levenshtein)

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/*******************************************************************************
 * Copyright (c) 2010-2019 Haifeng Li
 *
 * Smile is free software: you can redistribute it and/or modify
 * it under the terms of the GNU Lesser General Public License as
 * published by the Free Software Foundation, either version 3 of
 * the License, or (at your option) any later version.
 *
 * Smile is distributed in the hope that it will be useful,
 * but WITHOUT ANY WARRANTY; without even the implied warranty of
 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 * GNU Lesser General Public License for more details.
 *
 * You should have received a copy of the GNU Lesser General Public License
 * along with Smile.  If not, see <https://www.gnu.org/licenses/>.
 *******************************************************************************/

/**
 * The Edit distance between two strings is a metric for measuring the amount
 * of difference between two sequences. The Levenshtein distance between two
 * strings is given by the minimum number of operations needed to transform one
 * string into the other, where an operation is an insertion, deletion, or
 * substitution of a single character. A generalization of the Levenshtein
 * distance (Damerau-Levenshtein distance) allows the transposition of two
 * characters as an operation.
 * <p>
 * Given two strings x and y of length m and n (suppose n &ge; m), this
 * implementation takes O(ne) time and O(mn) space by an extended Ukkonen's
 * algorithm in case of unit cost, where e is the edit distance between x and y.
 * Thus this algorithm is output sensitive. The smaller the distance, the faster
 * it runs.
 * <p>
 * For weighted cost, this implements the regular dynamic programming algorithm,
 * which takes O(mn) time and O(m) space.
 *
 * @author Haifeng Li
 */
final sclass EditDistance /*implements Metric<String>*/ {
  /**
   * Weight matrix for weighted Levenshtein distance.
   */
  private IIntArray2D weight;

  /**
   * Radius of Sakoe-Chiba band
   */
  private double r = -1;

  /**
   * Calculate Damerau or basic Levenshitein distance.
   */
  private boolean damerau = false;

  /**
   * Cost matrix. Because Java automatically initialize arrays, it
   * takes O(mn) to declare this cost matrix every time before
   * calculate edit distance. But the whole point of Berghel & Roach
   * algorithm is to calculate fewer cells than O(mn). Therefore,
   * we create this cost matrix here. Therefore, the methods using
   * this cost matrix is not multi-thread safe.
   */
  private IIntArray2D FKP;

  /**
   * The lambda to calculate FKP array.
   */
  private BRF brf;


  /**
   * Constructor. Multi-thread safe Levenshtein distance.
   */
  public EditDistance() {
      this(false);
  }

  /**
   * Constructor. Multi-thread safe Damerau-Levenshtein distance.
   * @param damerau if true, calculate Damerau-Levenshtein distance
   *                instead of plain Levenshtein distance.
   */
  public EditDistance(boolean damerau) {
      this.damerau = damerau;
  }

  /**
   * Constructor. Highly efficient Levenshtein distance but not multi-thread safe.
   * @param maxStringLength the maximum length of strings that will be
   * feed to this algorithm.
   */
  public EditDistance(int maxStringLength) {
      this(maxStringLength, false);
  }

  /**
   * Constructor. Highly efficient Damerau-Levenshtein distance but not multi-thread safe.
   * @param maxStringLength the maximum length of strings that will be
   *                        feed to this algorithm.
   * @param damerau if true, calculate Damerau-Levenshtein distance
   *                instead of plain Levenshtein distance.
   */
  public EditDistance(int maxStringLength, boolean damerau) {
      this.damerau = damerau;
      FKP = new IntArray2D(2*maxStringLength+1, maxStringLength+2);
      brf = damerau ? new DamerauBRF() : new LevenshteinBRF();
  }

  /**
   * Constructor. Weighted Levenshtein distance without path
   * constraints. Only insertion, deletion, and substitution operations are
   * supported.
   */
  public EditDistance(int[][] weight) {
      this(weight, -1);
  }

  /**
   * Constructor. Weighted Levenshtein distance with
   * Sakoe-Chiba band, which improve computational cost. Only
   * insertion, deletion, and substitution operations are supported.
   * @param radius the window width of Sakoe-Chiba band in terms of percentage of sequence length.
   */
  public EditDistance(int[][] weight, double radius) {
      this.weight = new IntArray2D(weight);
      this.r = radius;
  }

  @Override
  public String toString() {
      if (damerau) {
          if (weight != null)
              return String.format("Damerau-Levenshtein Distance(radius = %d, weight = %s)", r, weight.toString());
          else
              return "Damerau-Levenshtein Distance";
      } else {
          if (weight != null)
              return String.format("Levenshtein Distance(radius = %d, weight = %s)", r, weight.toString());
          else
              return  "Levenshtein Distance";
      }
  }

  /**
   * Edit distance between two strings. O(mn) time and O(n) space for weighted
   * edit distance. O(ne) time and O(mn) space for unit cost edit distance.
   * For weighted edit distance, this method is multi-thread safe. However,
   * it is NOT multi-thread safe for unit cost edit distance.
   */
  public double d(String x, String y) {
      if (weight != null)
          return weightedEdit(x, y);
      else if (FKP == null || x.length() == 1 || y.length() == 1)
          return damerau ? damerau(x, y) : levenshtein(x, y);
      else
          return br(x, y);
  }

  /**
   * Edit distance between two strings. O(mn) time and O(n) space for weighted
   * edit distance. O(ne) time and O(mn) space for unit cost edit distance.
   * For weighted edit distance, this method is multi-thread safe. However,
   * it is NOT multi-thread safe for unit cost edit distance.
   */
  public double d(char[] x, char[] y) {
      if (weight != null)
          return weightedEdit(x, y);
      else if (FKP == null || x.length == 1 || y.length == 1)
          return damerau ? damerau(x, y) : levenshtein(x, y);
      else
          return br(x, y);
  }

  /**
   * Weighted edit distance.
   */
  private double weightedEdit(char[] x, char[] y) {
      // switch parameters to use the shorter one as y to save space.
      if (x.length < y.length) {
          char[] swap = x;
          x = y;
          y = swap;
      }

      int radius = (int) Math.round(r * Math.max(x.length, y.length));

      double[][] d = new double[2][y.length + 1];

      d[0][0] = 0.0;
      for (int j = 1; j <= y.length; j++) {
          d[0][j] = d[0][j - 1] + weight.get(0, y[j]);
      }

      for (int i = 1; i <= x.length; i++) {
          d[1][0] = d[0][0] + weight.get(x[i], 0);

          int start = 1;
          int end = y.length;

          if (radius > 0) {
              start = i - radius;
              if (start > 1)
                  d[1][start - 1] = Double.POSITIVE_INFINITY;
              else
                  start = 1;

              end = i + radius;
              if (end < y.length)
                  d[1][end+1] = Double.POSITIVE_INFINITY;
              else
                  end = y.length;
          }

          for (int j = start; j <= end; j++) {
              double cost = weight.get(x[i - 1], y[j - 1]);
              d[1][j] = min3(
                      d[0][j] + weight.get(x[i - 1], 0), // deletion
                      d[1][j - 1] + weight.get(0, y[j - 1]), // insertion
                      d[0][j - 1] + cost); // substitution
          }

          double[] swap = d[0];
          d[0] = d[1];
          d[1] = swap;
      }

      return d[0][y.length];
  }

  /**
   * Weighted edit distance.
   */
  private double weightedEdit(String x, String y) {
      // switch parameters to use the shorter one as y to save space.
      if (x.length() < y.length()) {
          String swap = x;
          x = y;
          y = swap;
      }

      int radius = (int) Math.round(r * Math.max(x.length(), y.length()));

      double[][] d = new double[2][y.length() + 1];

      d[0][0] = 0.0;
      for (int j = 1; j <= y.length(); j++) {
          d[0][j] = d[0][j - 1] + weight.get(0, y.charAt(j));
      }

      for (int i = 1; i <= x.length(); i++) {
          d[1][0] = d[0][0] + weight.get(x.charAt(i), 0);

          int start = 1;
          int end = y.length();

          if (radius > 0) {
              start = i - radius;
              if (start > 1)
                  d[1][start - 1] = Double.POSITIVE_INFINITY;
              else
                  start = 1;

              end = i + radius;
              if (end < y.length())
                  d[1][end+1] = Double.POSITIVE_INFINITY;
              else
                  end = y.length();
          }

          for (int j = start; j <= end; j++) {
              double cost = weight.get(x.charAt(i - 1), y.charAt(j - 1));
              d[1][j] = min3(
                      d[0][j] + weight.get(x.charAt(i - 1), 0), // deletion
                      d[1][j - 1] + weight.get(0, y.charAt(j - 1)), // insertion
                      d[0][j - 1] + cost); // substitution
          }

          double[] swap = d[0];
          d[0] = d[1];
          d[1] = swap;
      }

      return d[0][y.length()];
  }

  /**
   * Berghel & Roach's extended Ukkonen's algorithm.
   */
  private int br(char[] x, char[] y) {
      if (x.length > y.length) {
          char[] swap = x;
          x = y;
          y = swap;
      }

      final int m = x.length;
      final int n = y.length;

      int ZERO_K = n;

      if (n+2 > FKP.ncols())
          FKP = new IntArray2D(2*n+1, n+2);

      for (int k = -ZERO_K; k < 0; k++) {
          int p = -k - 1;
          FKP.set(k + ZERO_K, p + 1, Math.abs(k) - 1);
          FKP.set(k + ZERO_K, p, Integer.MIN_VALUE);
      }

      FKP.set(ZERO_K, 0, -1);

      for (int k = 1; k <= ZERO_K; k++) {
          int p = k - 1;
          FKP.set(k + ZERO_K, p + 1, -1);
          FKP.set(k + ZERO_K, p, Integer.MIN_VALUE);
      }

      int p = n - m - 1;

      do {
          p++;

          for (int i = (p - (n-m))/2; i >= 1; i--) {
              brf.f(x, y, FKP, ZERO_K, n-m+i, p-i);
          }

          for (int i = (n-m+p)/2; i >= 1; i--) {
              brf.f(x, y, FKP, ZERO_K, n-m-i, p-i);
          }

          brf.f(x, y, FKP, ZERO_K, n - m, p);
      } while (FKP.get((n - m) + ZERO_K, p) != m);

      return p - 1;
  }

  /**
   * Berghel & Roach's extended Ukkonen's algorithm.
   */
  private int br(String x, String y) {
      if (x.length() > y.length()) {
          String swap = x;
          x = y;
          y = swap;
      }

      final int m = x.length();
      final int n = y.length();

      int ZERO_K = n;

      if (n+3 > FKP.ncols())
          FKP = new IntArray2D(2*n+1, n+3);

      for (int k = -ZERO_K; k < 0; k++) {
          int p = -k - 1;
          FKP.set(k + ZERO_K, p + 1, Math.abs(k) - 1);
          FKP.set(k + ZERO_K, p, Integer.MIN_VALUE);
      }

      FKP.set(ZERO_K, 0, -1);

      for (int k = 1; k <= ZERO_K; k++) {
          int p = k - 1;
          FKP.set(k + ZERO_K, p + 1, -1);
          FKP.set(k + ZERO_K, p, Integer.MIN_VALUE);
      }

      int p = n - m - 1;

      do {
          p++;

          for (int i = (p - (n-m))/2; i >= 1; i--) {
              brf.f(x, y, FKP, ZERO_K, n-m+i, p-i);
          }

          for (int i = (n-m+p)/2; i >= 1; i--) {
              brf.f(x, y, FKP, ZERO_K, n-m-i, p-i);
          }

          brf.f(x, y, FKP, ZERO_K, n - m, p);
      } while (FKP.get((n - m) + ZERO_K, p) != m);

      return p - 1;
  }

  private static class LevenshteinBRF implements BRF {
      @Override
      public void f(char[] x, char[] y, IIntArray2D FKP, int ZERO_K, int k, int p) {
          int t = max3(FKP.get(k + ZERO_K, p) + 1, FKP.get(k - 1 + ZERO_K, p), FKP.get(k + 1 + ZERO_K, p) + 1);
          int mnk = Math.min(x.length, y.length - k);

          while (t < mnk && x[t] == y[t + k]) {
              t++;
          }

          FKP.set(k + ZERO_K, p + 1, t);
      }

      @Override
      public void f(String x, String y, IIntArray2D FKP, int ZERO_K, int k, int p) {
          int t = max3(FKP.get(k + ZERO_K, p) + 1, FKP.get(k - 1 + ZERO_K, p), FKP.get(k + 1 + ZERO_K, p) + 1);
          int mnk = Math.min(x.length(), y.length() - k);

          while (t < mnk && x.charAt(t) == y.charAt(t + k)) {
              t++;
          }

          FKP.set(k + ZERO_K, p + 1, t);
      }
  }

  /**
   * Calculate FKP arrays in BR's algorithm with support of transposition operation.
   */
  private static class DamerauBRF implements BRF {
      @Override
      public void f(char[] x, char[] y, IIntArray2D FKP, int ZERO_K, int k, int p) {
          int t = FKP.get(k + ZERO_K, p) + 1;
          int mnk = Math.min(x.length, y.length - k);

          if (t >= 1 && k + t >= 1 && t < mnk) {
              if (x[t - 1] == y[k + t] && x[t] == y[k + t - 1]) {
                  t++;
              }
          }

          t = max3(FKP.get(k - 1 + ZERO_K, p), FKP.get(k + 1 + ZERO_K, p) + 1, t);

          while (t < mnk && x[t] == y[t + k]) {
              t++;
          }

          FKP.set(k + ZERO_K, p + 1, t);
      }

      @Override
      public void f(String x, String y, IIntArray2D FKP, int ZERO_K, int k, int p) {
          int t = FKP.get(k + ZERO_K, p) + 1;
          int mnk = Math.min(x.length(), y.length() - k);

          if (t >= 1 && k + t >= 1 && t < mnk) {
              if (x.charAt(t - 1) == y.charAt(k + t) && x.charAt(t) == y.charAt(k + t - 1)) {
                  t++;
              }
          }

          t = max3(FKP.get(k - 1 + ZERO_K, p), FKP.get(k + 1 + ZERO_K, p) + 1, t);

          while (t < mnk && x.charAt(t) == y.charAt(t + k)) {
              t++;
          }

          FKP.set(k + ZERO_K, p + 1, t);
      }
  }
  
  static interface BRF {
      /**
       * Calculate FKP arrays in BR's algorithm.
       */
      void f(char[] x, char[] y, IIntArray2D FKP, int ZERO_K, int k, int p);
      /**
       * Calculate FKP arrays in BR's algorithm.
       */
      void f(String x, String y, IIntArray2D FKP, int ZERO_K, int k, int p);
  }

    /**
     * Levenshtein distance between two strings allows insertion, deletion,
     * or substitution of characters. O(mn) time and O(n) space.
     * Multi-thread safe.
     */
    public static int levenshtein(String x, String y) {
        // switch parameters to use the shorter one as y to save space.
        if (x.length() < y.length()) {
            String swap = x;
            x = y;
            y = swap;
        }

        int[][] d = new int[2][y.length() + 1];

        for (int j = 0; j <= y.length(); j++) {
            d[0][j] = j;
        }

        for (int i = 1; i <= x.length(); i++) {
            d[1][0] = i;

            for (int j = 1; j <= y.length(); j++) {
                int cost = x.charAt(i - 1) == y.charAt(j - 1) ? 0 : 1;
                d[1][j] = min3(
                        d[0][j] + 1, // deletion
                        d[1][j - 1] + 1, // insertion
                        d[0][j - 1] + cost); // substitution
            }
            int[] swap = d[0];
            d[0] = d[1];
            d[1] = swap;
        }

        return d[0][y.length()];
    }

    /**
     * Levenshtein distance between two strings allows insertion, deletion,
     * or substitution of characters. O(mn) time and O(n) space.
     * Multi-thread safe.
     */
    public static int levenshtein(char[] x, char[] y) {
        // switch parameters to use the shorter one as y to save space.
        if (x.length < y.length) {
            char[] swap = x;
            x = y;
            y = swap;
        }

        int[][] d = new int[2][y.length + 1];

        for (int j = 0; j <= y.length; j++) {
            d[0][j] = j;
        }

        for (int i = 1; i <= x.length; i++) {
            d[1][0] = i;

            for (int j = 1; j <= y.length; j++) {
                int cost = x[i - 1] == y[j - 1] ? 0 : 1;
                d[1][j] = min3(
                        d[0][j] + 1, // deletion
                        d[1][j - 1] + 1, // insertion
                        d[0][j - 1] + cost); // substitution
            }
            int[] swap = d[0];
            d[0] = d[1];
            d[1] = swap;
        }

        return d[0][y.length];
    }

    /**
     * Damerau-Levenshtein distance between two strings allows insertion,
     * deletion, substitution, or transposition of characters.
     * O(mn) time and O(n) space. Multi-thread safe.
     */
    public static int damerau(String x, String y) {
        // switch parameters to use the shorter one as y to save space.
        if (x.length() < y.length()) {
            String swap = x;
            x = y;
            y = swap;
        }

        int[][] d = new int[3][y.length() + 1];

        for (int j = 0; j <= y.length(); j++) {
            d[1][j] = j;
        }

        for (int i = 1; i <= x.length(); i++) {
            d[2][0] = i;

            for (int j = 1; j <= y.length(); j++) {
                int cost = x.charAt(i-1) == y.charAt(j-1) ? 0 : 1;
                d[2][j] = min3(
                        d[1][j] + 1,       // deletion
                        d[2][j-1] + 1,       // insertion
                        d[1][j-1] + cost); // substitution

                if (i > 1 && j > 1) {
                    if (x.charAt(i-1) == y.charAt(j-2) && x.charAt(i-2) == y.charAt(j-1))
                        d[2][j] = Math.min(d[2][j], d[0][j-2] + cost);   // damerau
                }
            }

            int[] swap = d[0];
            d[0] = d[1];
            d[1] = d[2];
            d[2] = swap;
        }

        return d[1][y.length()];
    }

    /**
     * Damerau-Levenshtein distance between two strings allows insertion,
     * deletion, substitution, or transposition of characters.
     * O(mn) time and O(n) space. Multi-thread safe.
     */
    public static int damerau(char[] x, char[] y) {
        // switch parameters to use the shorter one as y to save space.
        if (x.length < y.length) {
            char[] swap = x;
            x = y;
            y = swap;
        }

        int[][] d = new int[3][y.length + 1];

        for (int j = 0; j <= y.length; j++) {
            d[1][j] = j;
        }

        for (int i = 1; i <= x.length; i++) {
            d[2][0] = i;

            for (int j = 1; j <= y.length; j++) {
                int cost = x[i-1] == y[j-1] ? 0 : 1;
                d[2][j] = min3(
                        d[1][j] + 1,       // deletion
                        d[2][j-1] + 1,       // insertion
                        d[1][j-1] + cost); // substitution

                if (i > 1 && j > 1) {
                    if (x[i-1] == y[j-2] && x[i-2] == y[j-1])
                        d[2][j] = Math.min(d[2][j], d[0][j-2] + cost);   // damerau
                }
            }

            int[] swap = d[0];
            d[0] = d[1];
            d[1] = d[2];
            d[2] = swap;
        }

        return d[1][y.length];
    }
}

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Snippet ID: #1026090
Snippet name: EditDistance (Ukkonen-optimized Levenshtein)
Eternal ID of this version: #1026090/12
Text MD5: 8de66b6e60486cf7a6446e083e8525bd
Transpilation MD5: f930147f105ecf72101cc5439315c298
Author: stefan
Category: javax
Type: JavaX fragment (include)
Public (visible to everyone): Yes
Archived (hidden from active list): No
Created/modified: 2019-11-27 03:02:26
Source code size: 19786 bytes / 630 lines
Pitched / IR pitched: No / No
Views / Downloads: 181 / 543
Version history: 11 change(s)
Referenced in: [show references]