Examples of org.apache.lucene.search.Scorer

org.apache.lucene.search.Scorer
Expert: Common scoring functionality for different types of queries.
A Scorer iterates over documents matching a query in increasing order of doc Id.

Document scores are computed using a given Similarity implementation.

NOTE: The values Float.Nan, Float.NEGATIVE_INFINITY and Float.POSITIVE_INFINITY are not valid scores. Certain collectors (eg {@link TopScoreDocCollector}) will not properly collect hits with these scores.

   * this causes problems
   */
  public void testSpanNearScorerSkipTo1() throws Exception {
    SpanNearQuery q = makeQuery();
    Weight w = q.createWeight(searcher);
    Scorer s = w.scorer(searcher.getIndexReader());
    assertEquals(true, s.skipTo(1));
    assertEquals(1, s.doc());
  }

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   * this causes problems
   */
  public void testSpanNearScorerExplain() throws Exception {
    SpanNearQuery q = makeQuery();
    Weight w = q.createWeight(searcher);
    Scorer s = w.scorer(searcher.getIndexReader());
    Explanation e = s.explain(1);
    assertTrue("Scorer explanation value for doc#1 isn't positive: "
               + e.toString(),
               0.0f < e.getValue());
  }

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   * time.
   * Should not be used when the queue is empty.
   */
  public final Scorer pop() {
    // assert size > 0;
    Scorer result = topHSD.scorer;
    popNoResult();
    return result;
  }

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    while(iter.hasNext()) {
      Entry entry = (Entry) iter.next();
      Query query = (Query) entry.getKey();
      int limit = ((Integer) entry.getValue()).intValue();
      Weight weight = query.weight(searcher);
      Scorer scorer = weight.scorer(reader);
      while(scorer.next()) {
        final int docID = scorer.doc();
        if (docIDStart + docID >= limit)
          break;
        reader.deleteDocument(docID);
        any = true;
      }

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        // Sort drill-downs by most restrictive first:
        Arrays.sort(dims);


        // TODO: it could be better if we take acceptDocs
        // into account instead of baseScorer?
        Scorer baseScorer = baseWeight.scorer(context, scoreDocsInOrder, false, acceptDocs);


        if (baseScorer == null) {
          return null;
        }

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      // Pass true for "scoresDocsInOrder", because we
      // require in-order scoring, even if caller does not,
      // since we call advance on the valSrcScorers.  Pass
      // false for "topScorer" because we will not invoke
      // score(Collector) on these scorers:
      Scorer subQueryScorer = subQueryWeight.scorer(context, true, false, acceptDocs);
      if (subQueryScorer == null) {
        return null;
      }
      Scorer[] valSrcScorers = new Scorer[valSrcWeights.length];
      for(int i = 0; i < valSrcScorers.length; i++) {

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    @Override
    public Scorer scorer(AtomicReaderContext readerContext, boolean scoreDocsInOrder,
        boolean topScorer, Bits acceptDocs) throws IOException {


      // Pass scoreDocsInOrder true, topScorer false to our sub and the live docs:
      final Scorer childScorer = childWeight.scorer(readerContext, true, false, readerContext.reader().getLiveDocs());


      if (childScorer == null) {
        // No matches
        return null;
      }


      final int firstChildDoc = childScorer.nextDoc();
      if (firstChildDoc == DocIdSetIterator.NO_MORE_DOCS) {
        // No matches
        return null;
      }

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    @Override
    public Scorer scorer(AtomicReaderContext readerContext, boolean scoreDocsInOrder,
        boolean topScorer, Bits acceptDocs) throws IOException {


      // Pass scoreDocsInOrder true, topScorer false to our sub:
      final Scorer parentScorer = parentWeight.scorer(readerContext, true, false, null);


      if (parentScorer == null) {
        // No matches
        return null;
      }

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          return 0.0f;
        }
      };
  
      final Similarity oldSim = searcher.getSimilarity();
      Scorer spanScorer;
      try {
        searcher.setSimilarity(sim);
        SpanNearQuery snq = new SpanNearQuery(
                                new SpanQuery[] {
                                  makeSpanTermQuery("t1"),
                                  makeSpanTermQuery("t2") },
                                slop,
                                ordered);
  
        spanScorer = searcher.createNormalizedWeight(snq).scorer(ctx, true, false, ctx.reader().getLiveDocs());
      } finally {
        searcher.setSimilarity(oldSim);
      }
      if (i == subIndex) {
        assertTrue("first doc", spanScorer.nextDoc() != DocIdSetIterator.NO_MORE_DOCS);
        assertEquals("first doc number", spanScorer.docID() + ctx.docBase, 11);
        float score = spanScorer.score();
        assertTrue("first doc score should be zero, " + score, score == 0.0f);
      }  else {
        assertTrue("no second doc", spanScorer.nextDoc() == DocIdSetIterator.NO_MORE_DOCS);
      }
    }
  }

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            List<Query> filters = rb.getFilters();
            if (filters!=null){
              final ArrayList<DocIdSet> docsets = new ArrayList<DocIdSet>(filters.size());
                for (Query filter : filters){
                  Weight weight = filter.createWeight(rb.req.getSearcher());
                  final Scorer scorer = weight.scorer(reader, false, true);
                  docsets.add(new DocIdSet(){
                @Override
                public DocIdSetIterator iterator() throws IOException {
                  return scorer;
                }

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