/**
* The termCompare method in FuzzyTermEnum uses Levenshtein distance to calculate the distance
* between the given term and the comparing term.
*
* <p>If the minSimilarity is >= 1.0, this uses the maxEdits as the comparison. Otherwise,
* this method uses the following logic to calculate similarity.
*
* <pre>
* similarity = 1 - ((float)distance / (float) (prefixLength + Math.min(textlen, targetlen)));
* </pre>
*
* where distance is the Levenshtein distance for the two words.
*/
@Override
protected final AcceptStatus accept(BytesRef term) {
if (StringHelper.startsWith(term, prefixBytesRef)) {
utf32.copyUTF8Bytes(term);
final int distance =
calcDistance(utf32.ints(), realPrefixLength, utf32.length() - realPrefixLength);
// Integer.MIN_VALUE is the sentinel that Levenshtein stopped early
if (distance == Integer.MIN_VALUE) {
return AcceptStatus.NO;
}
// no need to calc similarity, if raw is true and distance > maxEdits
if (raw == true && distance > maxEdits) {
return AcceptStatus.NO;
}
final float similarity =
calcSimilarity(distance, (utf32.length() - realPrefixLength), text.length);
// if raw is true, then distance must also be <= maxEdits by now
// given the previous if statement
if (raw == true || (raw == false && similarity > minSimilarity)) {
boostAtt.setBoost((similarity - minSimilarity) * scale_factor);
return AcceptStatus.YES;
} else {
return AcceptStatus.NO;
}
} else {
return AcceptStatus.END;
}
}
