public TermSpans(TermPositions positions, Term term)
{
this.positions = positions;
this.term = term;
doc = - 1;
}
private float freq; //prhase frequency in current doc as computed by phraseFreq().
internal PhraseScorer(Weight weight, TermPositions[] tps, int[] offsets, Similarity similarity, byte[] norms):base(similarity)
{
this.norms = norms;
this.weight = weight;
this.value_Renamed = weight.GetValue();
// 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.
for (int i = 0; i < tps.Length; i++)
{
PhrasePositions pp = new PhrasePositions(tps[i], offsets[i]);
if (last != null)
{
// add next to end of list
last.next = pp;
}
else
{
first = pp;
}
last = pp;
}
pq = new PhraseQueue(tps.Length); // construct empty pq
first.doc = - 1;
}
internal SloppyPhraseScorer(Weight weight, TermPositions[] tps, int[] offsets, Similarity similarity, int slop, byte[] norms):base(weight, tps, offsets, similarity, norms)
{
this.slop = slop;
}
public override Scorer Scorer(IndexReader reader, bool scoreDocsInOrder, bool topScorer)
{
if (Enclosing_Instance.termArrays.Count == 0)
// optimize zero-term case
return null;
TermPositions[] tps = new TermPositions[Enclosing_Instance.termArrays.Count];
for (int i = 0; i < tps.Length; i++)
{
Term[] terms = (Term[]) Enclosing_Instance.termArrays[i];
TermPositions p;
if (terms.Length > 1)
p = new MultipleTermPositions(reader, terms);
else
p = reader.TermPositions(terms[0]);
if (p == null)
return null;
tps[i] = p;
}
if (Enclosing_Instance.slop == 0)
return new ExactPhraseScorer(this, tps, Enclosing_Instance.GetPositions(), similarity, reader.Norms(Enclosing_Instance.field));
else
return new SloppyPhraseScorer(this, tps, Enclosing_Instance.GetPositions(), similarity, Enclosing_Instance.slop, reader.Norms(Enclosing_Instance.field));
}
public override Scorer Scorer(IndexReader reader, bool scoreDocsInOrder, bool topScorer)
{
if (Enclosing_Instance.terms.Count == 0)
// optimize zero-term case
return null;
TermPositions[] tps = new TermPositions[Enclosing_Instance.terms.Count];
for (int i = 0; i < Enclosing_Instance.terms.Count; i++)
{
TermPositions p = reader.TermPositions((Term) Enclosing_Instance.terms[i]);
if (p == null)
return null;
tps[i] = p;
}
if (Enclosing_Instance.slop == 0)
// optimize exact case
return new ExactPhraseScorer(this, tps, Enclosing_Instance.GetPositions(), similarity, reader.Norms(Enclosing_Instance.field));
else
return new SloppyPhraseScorer(this, tps, Enclosing_Instance.GetPositions(), similarity, Enclosing_Instance.slop, reader.Norms(Enclosing_Instance.field));
}
public PayloadTermSpanScorer(PayloadTermWeight enclosingInstance, TermSpans spans, Weight weight, Similarity similarity, byte[] norms):base(spans, weight, similarity, norms)
{
InitBlock(enclosingInstance);
positions = spans.GetPositions();
}
