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 MatchAllScorer(MatchAllDocsQuery enclosingInstance, IndexReader reader, Similarity similarity, Weight w, byte[] norms) : base(similarity)
{
InitBlock(enclosingInstance);
this.termDocs = reader.TermDocs(null);
score = w.GetValue();
this.norms = norms;
}
internal MatchAllScorer(MatchAllDocsQuery enclosingInstance, IndexReader reader, Similarity similarity, Weight w, byte[] norms):base(similarity)
{
InitBlock(enclosingInstance);
this.termDocs = reader.TermDocs(null);
score = w.GetValue();
this.norms = norms;
}
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;
}
/// <summary> Construct a <code>TermScorer</code>.
///
/// </summary>
/// <param name="weight">The weight of the <code>Term</code> in the query.
/// </param>
/// <param name="td">An iterator over the documents matching the <code>Term</code>.
/// </param>
/// <param name="similarity">The <code>Similarity</code> implementation to be used for score
/// computations.
/// </param>
/// <param name="norms">The field norms of the document fields for the <code>Term</code>.
/// </param>
public /*internal*/ TermScorer(Weight weight, TermDocs td, Similarity similarity, byte[] norms):base(similarity)
{
this.weight = weight;
this.termDocs = td;
this.norms = norms;
this.weightValue = weight.GetValue();
for (int i = 0; i < SCORE_CACHE_SIZE; i++)
scoreCache[i] = GetSimilarity().Tf(i) * weightValue;
}
/// <summary> Construct a <code>TermScorer</code>.
///
/// </summary>
/// <param name="weight">The weight of the <code>Term</code> in the query.
/// </param>
/// <param name="td">An iterator over the documents matching the <code>Term</code>.
/// </param>
/// <param name="similarity">The <code>Similarity</code> implementation to be used for score
/// computations.
/// </param>
/// <param name="norms">The field norms of the document fields for the <code>Term</code>.
/// </param>
public /*internal*/ TermScorer(Weight weight, TermDocs td, Similarity similarity, byte[] norms) : base(similarity)
{
this.weight = weight;
this.termDocs = td;
this.norms = norms;
this.weightValue = weight.GetValue();
for (int i = 0; i < SCORE_CACHE_SIZE; i++)
{
scoreCache[i] = GetSimilarity().Tf(i) * weightValue;
}
}
public ConstantScorer(ConstantScoreQuery enclosingInstance, Similarity similarity, IndexReader reader, Weight w) : base(similarity)
{
InitBlock(enclosingInstance);
theScore = w.GetValue();
DocIdSet docIdSet = Enclosing_Instance.filter.GetDocIdSet(reader);
if (docIdSet == null)
{
docIdSetIterator = DocIdSet.EMPTY_DOCIDSET.Iterator();
}
else
{
DocIdSetIterator iter = docIdSet.Iterator();
if (iter == null)
{
docIdSetIterator = DocIdSet.EMPTY_DOCIDSET.Iterator();
}
else
{
docIdSetIterator = iter;
}
}
}
public ConstantScorer(ConstantScoreQuery enclosingInstance, Similarity similarity, IndexReader reader, Weight w):base(similarity)
{
InitBlock(enclosingInstance);
theScore = w.GetValue();
DocIdSet docIdSet = Enclosing_Instance.filter.GetDocIdSet(reader);
if (docIdSet == null)
{
docIdSetIterator = DocIdSet.EMPTY_DOCIDSET.Iterator();
}
else
{
DocIdSetIterator iter = docIdSet.Iterator();
if (iter == null)
{
docIdSetIterator = DocIdSet.EMPTY_DOCIDSET.Iterator();
}
else
{
docIdSetIterator = iter;
}
}
}