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JPMML class model evaluator
/*
* Licensed to the Apache Software Foundation (ASF) under one or more
* contributor license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright ownership.
* The ASF licenses this file to You 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.
*/
package org.jpmml.evaluator;
import java.util.Arrays;
class LevenshteinDistanceUtil {
private LevenshteinDistanceUtil(){
}
/**
* Find the Levenshtein distance between two CharSequences if it's less than or
* equal to a given threshold.
*
*
* This implementation follows from Algorithms on Strings, Trees and
* Sequences by Dan Gusfield and Chas Emerick's implementation of the
* Levenshtein distance algorithm from http://www.merriampark.com/ld.htm
*
*
*
* limitedCompare(null, *, *) = IllegalArgumentException
* limitedCompare(*, null, *) = IllegalArgumentException
* limitedCompare(*, *, -1) = IllegalArgumentException
* limitedCompare("","", 0) = 0
* limitedCompare("aaapppp", "", 8) = 7
* limitedCompare("aaapppp", "", 7) = 7
* limitedCompare("aaapppp", "", 6)) = -1
* limitedCompare("elephant", "hippo", 7) = 7
* limitedCompare("elephant", "hippo", 6) = -1
* limitedCompare("hippo", "elephant", 7) = 7
* limitedCompare("hippo", "elephant", 6) = -1
*
*
* @param left the first string, must not be null
* @param right the second string, must not be null
* @param threshold the target threshold, must not be negative
* @return result distance, or -1
*/
static int limitedCompare(CharSequence left, CharSequence right, final boolean caseSensitive, final int threshold) { // NOPMD
if (left == null || right == null) {
throw new IllegalArgumentException("Strings must not be null");
}
if (threshold < 0) {
throw new IllegalArgumentException("Threshold must not be negative");
}
/*
* This implementation only computes the distance if it's less than or
* equal to the threshold value, returning -1 if it's greater. The
* advantage is performance: unbounded distance is O(nm), but a bound of
* k allows us to reduce it to O(km) time by only computing a diagonal
* stripe of width 2k + 1 of the cost table. It is also possible to use
* this to compute the unbounded Levenshtein distance by starting the
* threshold at 1 and doubling each time until the distance is found;
* this is O(dm), where d is the distance.
*
* One subtlety comes from needing to ignore entries on the border of
* our stripe eg. p[] = |#|#|#|* d[] = *|#|#|#| We must ignore the entry
* to the left of the leftmost member We must ignore the entry above the
* rightmost member
*
* Another subtlety comes from our stripe running off the matrix if the
* strings aren't of the same size. Since string s is always swapped to
* be the shorter of the two, the stripe will always run off to the
* upper right instead of the lower left of the matrix.
*
* As a concrete example, suppose s is of length 5, t is of length 7,
* and our threshold is 1. In this case we're going to walk a stripe of
* length 3. The matrix would look like so:
*
*
* 1 2 3 4 5
* 1 |#|#| | | |
* 2 |#|#|#| | |
* 3 | |#|#|#| |
* 4 | | |#|#|#|
* 5 | | | |#|#|
* 6 | | | | |#|
* 7 | | | | | |
*
*
* Note how the stripe leads off the table as there is no possible way
* to turn a string of length 5 into one of length 7 in edit distance of
* 1.
*
* Additionally, this implementation decreases memory usage by using two
* single-dimensional arrays and swapping them back and forth instead of
* allocating an entire n by m matrix. This requires a few minor
* changes, such as immediately returning when it's detected that the
* stripe has run off the matrix and initially filling the arrays with
* large values so that entries we don't compute are ignored.
*
* See Algorithms on Strings, Trees and Sequences by Dan Gusfield for
* some discussion.
*/
int n = left.length(); // length of left
int m = right.length(); // length of right
// if one string is empty, the edit distance is necessarily the length
// of the other
if (n == 0) {
return m <= threshold ? m : -1;
} else if (m == 0) {
return n <= threshold ? n : -1;
}
if (n > m) {
// swap the two strings to consume less memory
final CharSequence tmp = left;
left = right;
right = tmp;
n = m;
m = right.length();
}
int[] p = new int[n + 1]; // 'previous' cost array, horizontally
int[] d = new int[n + 1]; // cost array, horizontally
int[] tempD; // placeholder to assist in swapping p and d
// fill in starting table values
final int boundary = Math.min(n, threshold) + 1;
for (int i = 0; i < boundary; i++) {
p[i] = i;
}
// these fills ensure that the value above the rightmost entry of our
// stripe will be ignored in following loop iterations
Arrays.fill(p, boundary, p.length, Integer.MAX_VALUE);
Arrays.fill(d, Integer.MAX_VALUE);
// iterates through t
for (int j = 1; j <= m; j++) {
final char rightJ = right.charAt(j - 1); // jth character of right
d[0] = j;
// compute stripe indices, constrain to array size
final int min = Math.max(1, j - threshold);
final int max = j > Integer.MAX_VALUE - threshold ? n : Math.min(
n, j + threshold);
// the stripe may lead off of the table if s and t are of different
// sizes
if (min > max) {
return -1;
}
// ignore entry left of leftmost
if (min > 1) {
d[min - 1] = Integer.MAX_VALUE;
}
// iterates through [min, max] in s
for (int i = min; i <= max; i++) {
final char leftI = left.charAt(i - 1);
if (equals(leftI, rightJ, caseSensitive)) {
// diagonally left and up
d[i] = p[i - 1];
} else {
// 1 + minimum of cell to the left, to the top, diagonally
// left and up
d[i] = 1 + Math.min(Math.min(d[i - 1], p[i]), p[i - 1]);
}
}
// copy current distance counts to 'previous row' distance counts
tempD = p;
p = d;
d = tempD;
}
// if p[n] is greater than the threshold, there's no guarantee on it
// being the correct
// distance
if (p[n] <= threshold) {
return p[n];
}
return -1;
}
static
private boolean equals(char left, char right, boolean caseSensitive){
if(left == right){
return true;
} // End if
if(!caseSensitive){
return (Character.toLowerCase(left) == Character.toLowerCase(right)) || (Character.toUpperCase(left) == Character.toUpperCase(right));
}
return false;
}
}