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.Value;
// 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;
}
public TermWeight(TermQuery enclosingInstance, Searcher searcher)
{
InitBlock(enclosingInstance);
this.similarity = Enclosing_Instance.GetSimilarity(searcher);
idfExp = similarity.IdfExplain(Enclosing_Instance.term, searcher);
idf = idfExp.Idf;
}
internal MatchAllScorer(MatchAllDocsQuery enclosingInstance, IndexReader reader, Similarity similarity, Weight w, byte[] norms):base(similarity)
{
InitBlock(enclosingInstance);
this.termDocs = reader.TermDocs(null);
score = w.Value;
this.norms = norms;
}
/// <summary> Construct a <c>TermScorer</c>.
///
/// </summary>
/// <param name="weight">The weight of the <c>Term</c> in the query.
/// </param>
/// <param name="td">An iterator over the documents matching the <c>Term</c>.
/// </param>
/// <param name="similarity">The <c>Similarity</c> implementation to be used for score
/// computations.
/// </param>
/// <param name="norms">The field norms of the document fields for the <c>Term</c>.
/// </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.Value;
for (int i = 0; i < SCORE_CACHE_SIZE; i++)
scoreCache[i] = Similarity.Tf(i) * weightValue;
}
public ConjunctionScorer(Similarity similarity, params Scorer[] scorers):base(similarity)
{
this.scorers = scorers;
coord = similarity.Coord(scorers.Length, scorers.Length);
for (int i = 0; i < scorers.Length; i++)
{
if (scorers[i].NextDoc() == NO_MORE_DOCS)
{
// If even one of the sub-scorers does not have any documents, this
// scorer should not attempt to do any more work.
lastDoc = NO_MORE_DOCS;
return ;
}
}
// Sort the array the first time...
// We don't need to sort the array in any future calls because we know
// it will already start off sorted (all scorers on same doc).
// note that this comparator is not consistent with equals!
System.Array.Sort(scorers, (a, b) => a.DocID() - b.DocID());
// NOTE: doNext() must be called before the re-sorting of the array later on.
// The reason is this: assume there are 5 scorers, whose first docs are 1,
// 2, 3, 5, 5 respectively. Sorting (above) leaves the array as is. Calling
// doNext() here advances all the first scorers to 5 (or a larger doc ID
// they all agree on).
// However, if we re-sort before doNext() is called, the order will be 5, 3,
// 2, 1, 5 and then doNext() will stop immediately, since the first scorer's
// docs equals the last one. So the invariant that after calling doNext()
// all scorers are on the same doc ID is broken.);
if (DoNext() == NO_MORE_DOCS)
{
// The scorers did not agree on any document.
lastDoc = NO_MORE_DOCS;
return ;
}
// If first-time skip distance is any predictor of
// scorer sparseness, then we should always try to skip first on
// those scorers.
// Keep last scorer in it's last place (it will be the first
// to be skipped on), but reverse all of the others so that
// they will be skipped on in order of original high skip.
int end = scorers.Length - 1;
int max = end >> 1;
for (int i = 0; i < max; i++)
{
Scorer tmp = scorers[i];
int idx = end - i - 1;
scorers[i] = scorers[idx];
scorers[idx] = tmp;
}
}
internal DocumentsWriter(Directory directory, IndexWriter writer, IndexingChain indexingChain)
{
InitBlock();
this.directory = directory;
this.writer = writer;
this.similarity = writer.Similarity;
flushedDocCount = writer.MaxDoc();
consumer = indexingChain.GetChain(this);
if (consumer is DocFieldProcessor)
{
docFieldProcessor = (DocFieldProcessor) consumer;
}
}
public ConstantWeight(ConstantScoreQuery enclosingInstance, Searcher searcher)
{
InitBlock(enclosingInstance);
this.similarity = Enclosing_Instance.GetSimilarity(searcher);
}
public ConstantScorer(ConstantScoreQuery enclosingInstance, Similarity similarity, IndexReader reader, Weight w):base(similarity)
{
InitBlock(enclosingInstance);
theScore = w.Value;
DocIdSet docIdSet = Enclosing_Instance.internalFilter.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;
}
}
}
internal ExactPhraseScorer(Weight weight, TermPositions[] tps, int[] offsets, Similarity similarity, byte[] norms):base(weight, tps, offsets, similarity, norms)
{
}
public override Explanation Explain(IndexReader reader, int doc)
{
Explanation result = new Explanation();
result.Description = "weight(" + Query + " in " + doc + "), product of:";
System.Text.StringBuilder docFreqs = new System.Text.StringBuilder();
System.Text.StringBuilder query = new System.Text.StringBuilder();
query.Append('\"');
docFreqs.Append(idfExp.Explain());
for (int i = 0; i < Enclosing_Instance.terms.Count; i++)
{
if (i != 0)
{
query.Append(" ");
}
Term term = Enclosing_Instance.terms[i];
query.Append(term.Text);
}
query.Append('\"');
Explanation idfExpl = new Explanation(idf, "idf(" + Enclosing_Instance.field + ":" + docFreqs + ")");
// explain query weight
Explanation queryExpl = new Explanation();
queryExpl.Description = "queryWeight(" + Query + "), product of:";
Explanation boostExpl = new Explanation(Enclosing_Instance.Boost, "boost");
if (Enclosing_Instance.Boost != 1.0f)
{
queryExpl.AddDetail(boostExpl);
}
queryExpl.AddDetail(idfExpl);
Explanation queryNormExpl = new Explanation(queryNorm, "queryNorm");
queryExpl.AddDetail(queryNormExpl);
queryExpl.Value = boostExpl.Value * idfExpl.Value * queryNormExpl.Value;
result.AddDetail(queryExpl);
// explain field weight
Explanation fieldExpl = new Explanation();
fieldExpl.Description = "fieldWeight(" + Enclosing_Instance.field + ":" + query + " in " + doc + "), product of:";
PhraseScorer scorer = (PhraseScorer)Scorer(reader, true, false);
if (scorer == null)
{
return(new Explanation(0.0f, "no matching docs"));
}
Explanation tfExplanation = new Explanation();
int d = scorer.Advance(doc);
float phraseFreq = (d == doc) ? scorer.CurrentFreq() : 0.0f;
tfExplanation.Value = similarity.Tf(phraseFreq);
tfExplanation.Description = "tf(phraseFreq=" + phraseFreq + ")";
fieldExpl.AddDetail(tfExplanation);
fieldExpl.AddDetail(idfExpl);
Explanation fieldNormExpl = new Explanation();
byte[] fieldNorms = reader.Norms(Enclosing_Instance.field);
float fieldNorm = fieldNorms != null?Similarity.DecodeNorm(fieldNorms[doc]) : 1.0f;
fieldNormExpl.Value = fieldNorm;
fieldNormExpl.Description = "fieldNorm(field=" + Enclosing_Instance.field + ", doc=" + doc + ")";
fieldExpl.AddDetail(fieldNormExpl);
fieldExpl.Value = tfExplanation.Value * idfExpl.Value * fieldNormExpl.Value;
result.AddDetail(fieldExpl);
// combine them
result.Value = queryExpl.Value * fieldExpl.Value;
if (queryExpl.Value == 1.0f)
{
return(fieldExpl);
}
return(result);
}
public AnonymousClassIDFExplanation1(int df, int max, float idf, Similarity enclosingInstance)
{
InitBlock(df, max, idf, enclosingInstance);
}
public /*internal*/ BooleanScorer(Similarity similarity, int minNrShouldMatch,
System.Collections.Generic.List<Scorer> optionalScorers, System.Collections.Generic.List<Scorer> prohibitedScorers)
: base(similarity)
{
InitBlock();
this.minNrShouldMatch = minNrShouldMatch;
if (optionalScorers != null && optionalScorers.Count > 0)
{
foreach (Scorer scorer in optionalScorers)
{
maxCoord++;
if (scorer.NextDoc() != NO_MORE_DOCS)
{
scorers = new SubScorer(scorer, false, false, bucketTable.NewCollector(0), scorers);
}
}
}
if (prohibitedScorers != null && prohibitedScorers.Count > 0)
{
foreach(Scorer scorer in prohibitedScorers)
{
int mask = nextMask;
nextMask = nextMask << 1;
prohibitedMask |= mask; // update prohibited mask
if (scorer.NextDoc() != NO_MORE_DOCS)
{
scorers = new SubScorer(scorer, false, true, bucketTable.NewCollector(mask), scorers);
}
}
}
coordFactors = new float[maxCoord];
Similarity sim = Similarity;
for (int i = 0; i < maxCoord; i++)
{
coordFactors[i] = sim.Coord(i, maxCoord - 1);
}
}
public MatchAllDocsWeight(MatchAllDocsQuery enclosingInstance, Searcher searcher)
{
InitBlock(enclosingInstance);
this.similarity = searcher.Similarity;
}
/// <summary>Construct a <see cref="Similarity" /> that delegates all methods to another.</summary>
/// <param name="delegee">the Similarity implementation to delegate to</param>
public SimilarityDelegator(Similarity delegee)
{
this.delegee = delegee;
}
public MultiPhraseWeight(MultiPhraseQuery enclosingInstance, Searcher searcher)
{
InitBlock(enclosingInstance);
this.similarity = Enclosing_Instance.GetSimilarity(searcher);
// compute idf
int maxDoc = searcher.MaxDoc;
foreach (Term[] terms in enclosingInstance.termArrays)
{
foreach (Term term in terms)
{
idf += similarity.Idf(searcher.DocFreq(term), maxDoc);
}
}
}
internal SloppyPhraseScorer(Weight weight, TermPositions[] tps, int[] offsets, Similarity similarity, int slop, byte[] norms):base(weight, tps, offsets, similarity, norms)
{
this.slop = slop;
}
internal void SetSimilarity(Similarity similarity)
{
lock (this)
{
this.similarity = similarity;
for (int i = 0; i < threadStates.Length; i++)
threadStates[i].docState.similarity = similarity;
}
}
public AnonymousClassIDFExplanation3(float fIdf, System.Text.StringBuilder exp, Similarity enclosingInstance)
{
InitBlock(fIdf, exp, enclosingInstance);
}
/// <summary>Expert: Set the Similarity implementation used by this IndexWriter.
/// </summary>
public virtual void SetSimilarity(Similarity similarity)
{
EnsureOpen();
this.similarity = similarity;
docWriter.SetSimilarity(similarity);
}
internal SloppyPhraseScorer(Weight weight, TermPositions[] tps, int[] offsets, Similarity similarity, int slop, byte[] norms) : base(weight, tps, offsets, similarity, norms)
{
this.slop = slop;
}
private void InitBlock(int df, int max, float idf, Similarity enclosingInstance)
{
this.df = df;
this.max = max;
this.idf = idf;
this.enclosingInstance = enclosingInstance;
}
private readonly int maxDoc; // document count
public CachedDfSource(Dictionary<Term,int> dfMap, int maxDoc, Similarity similarity)
{
this.dfMap = dfMap;
this.maxDoc = maxDoc;
Similarity = similarity;
}
private void InitBlock(float fIdf, System.Text.StringBuilder exp, Similarity enclosingInstance)
{
this.fIdf = fIdf;
this.exp = exp;
this.enclosingInstance = enclosingInstance;
}
public ConjunctionScorer(Similarity similarity, System.Collections.Generic.ICollection<Scorer> scorers)
: this(similarity, scorers.ToArray())
{
}
