137 lines
		
	
	
		
			3.8 KiB
		
	
	
	
		
			JavaScript
		
	
	
	
	
	
			
		
		
	
	
			137 lines
		
	
	
		
			3.8 KiB
		
	
	
	
		
			JavaScript
		
	
	
	
	
	
(function() {
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  'use strict';
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  var collator;
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  try {
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    collator = (typeof Intl !== "undefined" && typeof Intl.Collator !== "undefined") ? Intl.Collator("generic", { sensitivity: "base" }) : null;
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  } catch (err){
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    console.log("Collator could not be initialized and wouldn't be used");
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  }
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  // arrays to re-use
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  var prevRow = [],
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    str2Char = [];
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  /**
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   * Based on the algorithm at http://en.wikipedia.org/wiki/Levenshtein_distance.
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   */
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  var Levenshtein = {
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    /**
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     * Calculate levenshtein distance of the two strings.
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     *
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     * @param str1 String the first string.
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     * @param str2 String the second string.
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     * @param [options] Additional options.
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     * @param [options.useCollator] Use `Intl.Collator` for locale-sensitive string comparison.
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     * @return Integer the levenshtein distance (0 and above).
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     */
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    get: function(str1, str2, options) {
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      var useCollator = (options && collator && options.useCollator);
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      var str1Len = str1.length,
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        str2Len = str2.length;
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      // base cases
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      if (str1Len === 0) return str2Len;
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      if (str2Len === 0) return str1Len;
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      // two rows
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      var curCol, nextCol, i, j, tmp;
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      // initialise previous row
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      for (i=0; i<str2Len; ++i) {
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        prevRow[i] = i;
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        str2Char[i] = str2.charCodeAt(i);
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      }
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      prevRow[str2Len] = str2Len;
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      var strCmp;
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      if (useCollator) {
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        // calculate current row distance from previous row using collator
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        for (i = 0; i < str1Len; ++i) {
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          nextCol = i + 1;
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          for (j = 0; j < str2Len; ++j) {
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            curCol = nextCol;
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            // substution
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            strCmp = 0 === collator.compare(str1.charAt(i), String.fromCharCode(str2Char[j]));
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            nextCol = prevRow[j] + (strCmp ? 0 : 1);
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            // insertion
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            tmp = curCol + 1;
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            if (nextCol > tmp) {
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              nextCol = tmp;
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            }
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            // deletion
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            tmp = prevRow[j + 1] + 1;
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            if (nextCol > tmp) {
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              nextCol = tmp;
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            }
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            // copy current col value into previous (in preparation for next iteration)
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            prevRow[j] = curCol;
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          }
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          // copy last col value into previous (in preparation for next iteration)
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          prevRow[j] = nextCol;
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        }
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      }
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      else {
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        // calculate current row distance from previous row without collator
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        for (i = 0; i < str1Len; ++i) {
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          nextCol = i + 1;
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          for (j = 0; j < str2Len; ++j) {
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            curCol = nextCol;
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            // substution
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            strCmp = str1.charCodeAt(i) === str2Char[j];
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            nextCol = prevRow[j] + (strCmp ? 0 : 1);
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            // insertion
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            tmp = curCol + 1;
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            if (nextCol > tmp) {
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              nextCol = tmp;
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            }
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            // deletion
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            tmp = prevRow[j + 1] + 1;
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            if (nextCol > tmp) {
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              nextCol = tmp;
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            }
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            // copy current col value into previous (in preparation for next iteration)
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            prevRow[j] = curCol;
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          }
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          // copy last col value into previous (in preparation for next iteration)
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          prevRow[j] = nextCol;
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        }
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      }
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      return nextCol;
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    }
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  };
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  // amd
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  if (typeof define !== "undefined" && define !== null && define.amd) {
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    define(function() {
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      return Levenshtein;
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    });
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  }
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  // commonjs
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  else if (typeof module !== "undefined" && module !== null && typeof exports !== "undefined" && module.exports === exports) {
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    module.exports = Levenshtein;
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  }
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  // web worker
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  else if (typeof self !== "undefined" && typeof self.postMessage === 'function' && typeof self.importScripts === 'function') {
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    self.Levenshtein = Levenshtein;
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  }
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  // browser main thread
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  else if (typeof window !== "undefined" && window !== null) {
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    window.Levenshtein = Levenshtein;
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  }
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}());
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