package org.apache.lucene.search.spans;
/*
* 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.
*/
import org.apache.lucene.index.AtomicReaderContext;
import org.apache.lucene.index.IndexReaderContext;
import org.apache.lucene.index.Term;
import org.apache.lucene.index.TermContext;
import org.apache.lucene.search.*;
import org.apache.lucene.search.similarities.Similarity;
import org.apache.lucene.search.similarities.Similarity.SimScorer;
import org.apache.lucene.util.Bits;
import java.io.IOException;
import java.util.HashMap;
import java.util.Map;
import java.util.TreeSet;
/**
* Expert-only. Public for use by other weight implementations
*/
public class SpanWeight extends Weight {
protected Similarity similarity;
protected Map<Term,TermContext> termContexts;
protected SpanQuery query;
protected Similarity.SimWeight stats;
public SpanWeight(SpanQuery query, IndexSearcher searcher)
throws IOException {
this.similarity = searcher.getSimilarity();
this.query = query;
termContexts = new HashMap<Term,TermContext>();
TreeSet<Term> terms = new TreeSet<Term>();
query.extractTerms(terms);
final IndexReaderContext context = searcher.getTopReaderContext();
final TermStatistics termStats[] = new TermStatistics[terms.size()];
int i = 0;
for (Term term : terms) {
TermContext state = TermContext.build(context, term);
termStats[i] = searcher.termStatistics(term, state);
termContexts.put(term, state);
i++;
}
final String field = query.getField();
if (field != null) {
stats = similarity.computeWeight(query.getBoost(),
searcher.collectionStatistics(query.getField()),
termStats);
}
}
@Override
public Query getQuery() { return query; }
@Override
public float getValueForNormalization() throws IOException {
return stats == null ? 1.0f : stats.getValueForNormalization();
}
@Override
public void normalize(float queryNorm, float topLevelBoost) {
if (stats != null) {
stats.normalize(queryNorm, topLevelBoost);
}
}
@Override
public Scorer scorer(AtomicReaderContext context, boolean scoreDocsInOrder,
boolean topScorer, Bits acceptDocs) throws IOException {
if (stats == null) {
return null;
} else {
return new SpanScorer(query.getSpans(context, acceptDocs, termContexts), this, similarity.simScorer(stats, context));
}
}
@Override
public Explanation explain(AtomicReaderContext context, int doc) throws IOException {
SpanScorer scorer = (SpanScorer) scorer(context, true, false, context.reader().getLiveDocs());
if (scorer != null) {
int newDoc = scorer.advance(doc);
if (newDoc == doc) {
float freq = scorer.sloppyFreq();
SimScorer docScorer = similarity.simScorer(stats, context);
ComplexExplanation result = new ComplexExplanation();
result.setDescription("weight("+getQuery()+" in "+doc+") [" + similarity.getClass().getSimpleName() + "], result of:");
Explanation scoreExplanation = docScorer.explain(doc, new Explanation(freq, "phraseFreq=" + freq));
result.addDetail(scoreExplanation);
result.setValue(scoreExplanation.getValue());
result.setMatch(true);
return result;
}
}
return new ComplexExplanation(false, 0.0f, "no matching term");
}
}