internal ExactPhraseScorer(Weight weight, PhraseQuery.PostingsAndFreq[] postings, Similarity.SimScorer docScorer)
: base(weight)
{
this.docScorer = docScorer;
chunkStates = new ChunkState[postings.Length];
endMinus1 = postings.Length - 1;
// min(cost)
cost = postings[0].postings.GetCost();
for (int i = 0; i < postings.Length; i++)
{
// Coarse optimization: advance(target) is fairly
// costly, so, if the relative freq of the 2nd
// rarest term is not that much (> 1/5th) rarer than
// the first term, then we just use .nextDoc() when
// ANDing. this buys ~15% gain for phrases where
// freq of rarest 2 terms is close:
bool useAdvance = postings[i].docFreq > 5 * postings[0].docFreq;
chunkStates[i] = new ChunkState(postings[i].postings, -postings[i].position, useAdvance);
if (i > 0 && postings[i].postings.NextDoc() == DocIdSetIterator.NO_MORE_DOCS)
{
noDocs = true;
return;
}
}
}
internal SloppyPhraseScorer(Weight weight, PhraseQuery.PostingsAndFreq[] postings, int slop, Similarity.SimScorer docScorer)
: base(weight)
{
this.docScorer = docScorer;
this.slop = slop;
this.numPostings = postings == null ? 0 : postings.Length;
pq = new PhraseQueue(postings.Length);
// min(cost)
cost = postings[0].postings.GetCost();
// convert tps to a list of phrase positions.
// note: phrase-position differs from term-position in that its position
// reflects the phrase offset: pp.pos = tp.pos - offset.
// this allows to easily identify a matching (exact) phrase
// when all PhrasePositions have exactly the same position.
if (postings.Length > 0)
{
min = new PhrasePositions(postings[0].postings, postings[0].position, 0, postings[0].terms);
max = min;
max.doc = -1;
for (int i = 1; i < postings.Length; i++)
{
PhrasePositions pp = new PhrasePositions(postings[i].postings, postings[i].position, i, postings[i].terms);
max.next = pp;
max = pp;
max.doc = -1;
}
max.next = min; // make it cyclic for easier manipulation
}
}
public override Explanation Explain(AtomicReaderContext context, int doc)
{
PayloadNearSpanScorer scorer = (PayloadNearSpanScorer)GetScorer(context, (context.AtomicReader).LiveDocs);
if (scorer != null)
{
int newDoc = scorer.Advance(doc);
if (newDoc == doc)
{
float freq = scorer.Freq;
Similarity.SimScorer docScorer = m_similarity.GetSimScorer(m_stats, context);
Explanation expl = new Explanation();
expl.Description = "weight(" + Query + " in " + doc + ") [" + m_similarity.GetType().Name + "], result of:";
Explanation scoreExplanation = docScorer.Explain(doc, new Explanation(freq, "phraseFreq=" + freq));
expl.AddDetail(scoreExplanation);
expl.Value = scoreExplanation.Value;
string field = ((SpanQuery)Query).Field;
// now the payloads part
Explanation payloadExpl = outerInstance.m_function.Explain(doc, field, scorer.payloadsSeen, scorer.m_payloadScore);
// combined
ComplexExplanation result = new ComplexExplanation();
result.AddDetail(expl);
result.AddDetail(payloadExpl);
result.Value = expl.Value * payloadExpl.Value;
result.Description = "PayloadNearQuery, product of:";
return(result);
}
}
return(new ComplexExplanation(false, 0.0f, "no matching term"));
}
protected internal SpanScorer(Spans spans, Weight weight, Similarity.SimScorer docScorer)
: base(weight)
{
this.m_docScorer = docScorer;
this.m_spans = spans;
m_doc = -1;
m_more = spans.Next();
}
public override Explanation Explain(AtomicReaderContext context, int doc)
{
PayloadTermSpanScorer scorer = (PayloadTermSpanScorer)Scorer(context, (context.AtomicReader).LiveDocs);
if (scorer != null)
{
int newDoc = scorer.Advance(doc);
if (newDoc == doc)
{
float freq = scorer.SloppyFreq();
Similarity.SimScorer docScorer = Similarity.DoSimScorer(Stats, context);
Explanation expl = new Explanation();
expl.Description = "weight(" + Query + " in " + doc + ") [" + Similarity.GetType().Name + "], result of:";
Explanation scoreExplanation = docScorer.Explain(doc, new Explanation(freq, "phraseFreq=" + freq));
expl.AddDetail(scoreExplanation);
expl.Value = scoreExplanation.Value;
// now the payloads part
// QUESTION: Is there a way to avoid this skipTo call? We need to know
// whether to load the payload or not
// GSI: I suppose we could toString the payload, but I don't think that
// would be a good idea
string field = ((SpanQuery)Query).Field;
Explanation payloadExpl = OuterInstance.Function.Explain(doc, field, scorer.PayloadsSeen, scorer.PayloadScore_Renamed);
payloadExpl.Value = scorer.PayloadScore;
// combined
ComplexExplanation result = new ComplexExplanation();
if (OuterInstance.IncludeSpanScore)
{
result.AddDetail(expl);
result.AddDetail(payloadExpl);
result.Value = expl.Value * payloadExpl.Value;
result.Description = "btq, product of:";
}
else
{
result.AddDetail(payloadExpl);
result.Value = payloadExpl.Value;
result.Description = "btq(includeSpanScore=false), result of:";
}
result.Match = true; // LUCENE-1303
return(result);
}
}
return(new ComplexExplanation(false, 0.0f, "no matching term"));
}
public override Explanation Explain(AtomicReaderContext context, int doc)
{
SpanScorer scorer = (SpanScorer)GetScorer(context, context.AtomicReader.LiveDocs);
if (scorer != null)
{
int newDoc = scorer.Advance(doc);
if (newDoc == doc)
{
float freq = scorer.SloppyFreq;
Similarity.SimScorer docScorer = m_similarity.GetSimScorer(m_stats, context);
ComplexExplanation result = new ComplexExplanation();
result.Description = "weight(" + Query + " in " + doc + ") [" + m_similarity.GetType().Name + "], result of:";
Explanation scoreExplanation = docScorer.Explain(doc, new Explanation(freq, "phraseFreq=" + freq));
result.AddDetail(scoreExplanation);
result.Value = scoreExplanation.Value;
result.Match = true;
return(result);
}
}
return(new ComplexExplanation(false, 0.0f, "no matching term"));
}
public PayloadTermSpanScorer(PayloadTermQuery.PayloadTermWeight outerInstance, TermSpans spans, Weight weight, Similarity.SimScorer docScorer)
: base(spans, weight, docScorer)
{
this.OuterInstance = outerInstance;
TermSpans = spans;
}
protected internal PayloadNearSpanScorer(PayloadNearQuery outerInstance, Spans spans, Weight weight, Similarity similarity, Similarity.SimScorer docScorer)
: base(spans, weight, docScorer)
{
this.outerInstance = outerInstance;
this.spans = spans;
}
#pragma warning disable IDE0060 // Remove unused parameter
protected internal PayloadNearSpanScorer(PayloadNearQuery outerInstance, Spans spans, Weight weight, Similarity similarity, Similarity.SimScorer docScorer)
#pragma warning restore IDE0060 // Remove unused parameter
: base(spans, weight, docScorer)
{
this.outerInstance = outerInstance;
this.spans = spans;
}
internal JustCompileSpanScorer(Spans spans, Weight weight, Similarity.SimScorer docScorer)
: base(spans, weight, docScorer)
{
}
/// <summary>
/// Construct a <see cref="TermScorer"/>.
/// </summary>
/// <param name="weight">
/// The weight of the <see cref="Index.Term"/> in the query. </param>
/// <param name="td">
/// An iterator over the documents matching the <see cref="Index.Term"/>. </param>
/// <param name="docScorer">
/// The <see cref="Similarity.SimScorer"/> implementation
/// to be used for score computations. </param>
internal TermScorer(Weight weight, DocsEnum td, Similarity.SimScorer docScorer)
: base(weight)
{
this.docScorer = docScorer;
this.docsEnum = td;
}
