org.simmetrics.metrics.DamerauLevenshtein Maven / Gradle / Ivy
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* Copyright (C) 2014 - 2015 Simmetrics Authors
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package org.simmetrics.metrics;
import static com.google.common.base.Preconditions.checkArgument;
import static java.lang.Math.max;
import static org.simmetrics.metrics.Math.max;
import static org.simmetrics.metrics.Math.min;
import org.simmetrics.StringDistance;
import org.simmetrics.StringMetric;
/**
* Calculates the Damerau-Levenshtein similarity and distance measure between
* two strings.
*
* Insert/delete, substitute and transpose operations can be weighted. When the
* cost for substitution and/or transposition are zero Damerau-Levenshtein does
* not satisfy the coincidence property.
*
* This class is immutable and thread-safe.
*
* @see Wikipedia
* - Damerau-Levenshtein distance
* @see Levenshtein
*
*/
public final class DamerauLevenshtein implements StringMetric, StringDistance {
private final float maxCost;
private final float insertDelete;
private final float substitute;
private final float transpose;
/**
* Constructs a new Damerau-Levenshtein metric.
*/
public DamerauLevenshtein() {
this(1.0f, 1.0f, 1.0f);
}
/**
* Constructs a new weighted Damerau-Levenshtein metric. When the cost for
* substitution and/or transposition are zero Damerau-Levenshtein does not
* satisfy the coincidence property.
*
* @param insertDelete
* positive non-zero cost of an insert or deletion operation
* @param substitute
* positive cost of a substitute operation
* @param transpose
* positive cost of a transpose operation
*/
public DamerauLevenshtein(float insertDelete, float substitute,
float transpose) {
checkArgument(insertDelete > 0);
checkArgument(substitute >= 0);
checkArgument(transpose >= 0);
this.maxCost = max(insertDelete, substitute, transpose);
this.insertDelete = insertDelete;
this.substitute = substitute;
this.transpose = transpose;
}
@Override
public float compare(final String a, final String b) {
if (a.isEmpty() && b.isEmpty()) {
return 1.0f;
}
return 1.0f - (distance(a, b) / (maxCost * max(a.length(), b.length())));
}
@Override
public float distance(final String s, final String t) {
if (s.isEmpty())
return t.length() * insertDelete;
if (t.isEmpty())
return s.length() * insertDelete;
if (s.equals(t))
return 0;
final int tLength = t.length();
final int sLength = s.length();
float[] swap;
float[] v0 = new float[tLength + 1];
float[] v1 = new float[tLength + 1];
float[] v2 = new float[tLength + 1];
// initialize v1 (the previous row of distances)
// this row is A[0][i]: edit distance for an empty s
// the distance is just the number of characters to delete from t
for (int i = 0; i < v1.length; i++) {
v1[i] = i * insertDelete;
}
for (int i = 0; i < sLength; i++) {
// first element of v2 is A[i+1][0]
// edit distance is delete (i+1) chars from s to match empty t
v2[0] = (i + 1) * insertDelete;
for (int j = 0; j < tLength; j++) {
if (j > 0 && i > 0 && s.charAt(i - 1) == t.charAt(j)
&& s.charAt(i) == t.charAt(j - 1)) {
v2[j + 1] = min(v2[j] + insertDelete, v1[j + 1]
+ insertDelete, v1[j]
+ (s.charAt(i) == t.charAt(j) ? 0.0f : substitute),
v0[j - 1] + transpose);
} else {
v2[j + 1] = min(v2[j] + insertDelete, v1[j + 1]
+ insertDelete, v1[j]
+ (s.charAt(i) == t.charAt(j) ? 0.0f : substitute));
}
}
swap = v0;
v0 = v1;
v1 = v2;
v2 = swap;
}
// latest results was in v2 which was swapped to v1
return v1[tLength];
}
@Override
public String toString() {
return "DamerauLevenshtein [insertDelete=" + insertDelete
+ ", substitute=" + substitute + ", transpose=" + transpose
+ "]";
}
}