Levenshtein distance (v17)

Revision 17 of this benchmark created by surdu on

Setup

function levenshtein_distance_a (a, b) {
    if(a.length == 0) return b.length; 
    if(b.length == 0) return a.length; 
  
    var matrix = [];
  
    // increment along the first column of each row
    var i;
    for(i = 0; i <= b.length; i++){
      matrix[i] = [i];
    }
  
    // increment each column in the first row
    var j;
    for(j = 0; j <= a.length; j++){
      matrix[0][j] = j;
    }
  
    // Fill in the rest of the matrix
    for(i = 1; i <= b.length; i++){
      for(j = 1; j <= a.length; j++){
        if(b.charAt(i-1) == a.charAt(j-1)){
          matrix[i][j] = matrix[i-1][j-1];
        } else {
          matrix[i][j] = Math.min(matrix[i-1][j-1] + 1, // substitution
                                  Math.min(matrix[i][j-1] + 1, // insertion
                                           matrix[i-1][j] + 1)); // deletion
        }
      }
    }
  
    return matrix[b.length][a.length];
  }
  
  
  function levenshtein_distance_b (s, t) {
    var d = []; //2d matrix
  
      // Step 1
      var n = s.length;
      var m = t.length;
  
      if (n == 0) return m;
      if (m == 0) return n;
  
      //Create an array of arrays in javascript (a descending loop is quicker)
      for (var i = n; i >= 0; i--) d[i] = [];
  
      // Step 2
      for (var i = n; i >= 0; i--) d[i][0] = i;
      for (var j = m; j >= 0; j--) d[0][j] = j;
  
      // Step 3
      for (var i = 1; i <= n; i++) {
          var s_i = s.charAt(i - 1);
  
          // Step 4
          for (var j = 1; j <= m; j++) {
  
              //Check the jagged ld total so far
              if (i == j && d[i][j] > 4) return n;
  
              var t_j = t.charAt(j - 1);
              var cost = (s_i == t_j) ? 0 : 1; // Step 5
  
              //Calculate the minimum
              var mi = d[i - 1][j] + 1;
              var b = d[i][j - 1] + 1;
              var c = d[i - 1][j - 1] + cost;
  
              if (b < mi) mi = b;
              if (c < mi) mi = c;
  
              d[i][j] = mi; // Step 6
  
              //Damerau transposition
              if (i > 1 && j > 1 && s_i == t.charAt(j - 2) && s.charAt(i - 2) == t_j) {
                  d[i][j] = Math.min(d[i][j], d[i - 2][j - 2] + cost);
              }
          }
      }
  
      // Step 7
      return d[n][m];
  }

Test runner

Ready to run.

Testing in
TestOps/sec
algorithm A
levenshtein_distance_a('frankenstein', 'frankestein')
ready
algorithm B
levenshtein_distance_b('frankenstein', 'frankestein')
ready

Revisions

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