private int maxDocs = 200; // max to cache
internal Hits(Searcher s, Query q, Filter f)
{
query = q;
searcher = s;
filter = f;
GetMoreDocs(50); // retrieve 100 initially
}
public TermWeight(TermQuery enclosingInstance, Searcher searcher)
{
InitBlock(enclosingInstance);
this.searcher = searcher;
}
protected internal override Weight CreateWeight(Searcher searcher)
{
return(new TermWeight(this, searcher));
}
public TermWeight(TermQuery enclosingInstance, Searcher searcher)
{
InitBlock(enclosingInstance);
this.searcher = searcher;
}
/// <summary> Returns a Weight that applies the filter to the enclosed query's Weight.
/// This is accomplished by overriding the Scorer returned by the Weight.
/// </summary>
protected internal override Weight CreateWeight(Searcher searcher)
{
Weight weight = query.CreateWeight(searcher);
return new AnonymousClassWeight(weight, searcher, this);
}
public BooleanWeight(BooleanQuery enclosingInstance, Searcher searcher)
{
InitBlock(enclosingInstance);
this.searcher = searcher;
for (int i = 0; i < Enclosing_Instance.clauses.Count; i++)
{
BooleanClause c = (BooleanClause) Enclosing_Instance.clauses[i];
weights.Add(c.query.CreateWeight(searcher));
}
}
/// <summary>Expert: Constructs an appropriate Weight implementation for this query.
///
/// <p>Only implemented by primitive queries, which re-write to themselves.
/// </summary>
protected internal virtual Weight CreateWeight(Searcher searcher)
{
throw new System.NotSupportedException();
}
/// <summary>Expert: Constructs an initializes a Weight for a top-level query. </summary>
public virtual Weight Weight(Searcher searcher)
{
Query query = searcher.Rewrite(this);
Weight weight = query.CreateWeight(searcher);
float sum = weight.SumOfSquaredWeights();
float norm = GetSimilarity(searcher).QueryNorm(sum);
weight.Normalize(norm);
return weight;
}
/// <summary> Returns a Weight that applies the filter to the enclosed query's Weight.
/// This is accomplished by overriding the Scorer returned by the Weight.
/// </summary>
protected internal override Weight CreateWeight(Searcher searcher)
{
Weight weight = query.CreateWeight(searcher);
return(new AnonymousClassWeight(weight, searcher, this));
}
/// <summary>Expert: Returns the Similarity implementation to be used for this query.
/// Subclasses may override this method to specify their own Similarity
/// implementation, perhaps one that delegates through that of the Searcher.
/// By default the Searcher's Similarity implementation is returned.
/// </summary>
public virtual Similarity GetSimilarity(Searcher searcher)
{
return searcher.GetSimilarity();
}
/// <summary>Expert: Constructs an appropriate Weight implementation for this query.
///
/// <p>Only implemented by primitive queries, which re-write to themselves.
/// </summary>
protected internal virtual Weight CreateWeight(Searcher searcher)
{
throw new System.NotSupportedException();
}
public PhraseWeight(PhraseQuery enclosingInstance, Searcher searcher)
{
InitBlock(enclosingInstance);
this.searcher = searcher;
}
/// <summary>Computes a score factor for a phrase.
///
/// <p>The default implementation sums the {@link #Idf(Term,Searcher)} factor
/// for each term in the phrase.
///
/// </summary>
/// <param name="terms">the terms in the phrase
/// </param>
/// <param name="searcher">the document collection being searched
/// </param>
/// <returns> a score factor for the phrase
/// </returns>
public virtual float Idf(System.Collections.ICollection terms, Searcher searcher)
{
float idf = 0.0f;
System.Collections.IEnumerator i = terms.GetEnumerator();
while (i.MoveNext())
{
idf += Idf((Term) i.Current, searcher);
}
return idf;
}
/// <summary>Computes a score factor for a simple term.
///
/// <p>The default implementation is:<pre>
/// return idf(searcher.docFreq(term), searcher.maxDoc());
/// </pre>
///
/// Note that {@link Searcher#MaxDoc()} is used instead of
/// {@link Monodoc.Lucene.Net.Index.IndexReader#NumDocs()} because it is proportional to
/// {@link Searcher#DocFreq(Term)} , i.e., when one is inaccurate,
/// so is the other, and in the same direction.
///
/// </summary>
/// <param name="term">the term in question
/// </param>
/// <param name="searcher">the document collection being searched
/// </param>
/// <returns> a score factor for the term
/// </returns>
public virtual float Idf(Term term, Searcher searcher)
{
return Idf(searcher.DocFreq(term), searcher.MaxDoc());
}
public PhrasePrefixWeight(PhrasePrefixQuery enclosingInstance, Searcher searcher)
{
InitBlock(enclosingInstance);
this.searcher = searcher;
}
/// <summary>Computes a score factor for a simple term.
///
/// <p>The default implementation is:<pre>
/// return idf(searcher.docFreq(term), searcher.maxDoc());
/// </pre>
///
/// Note that {@link Searcher#MaxDoc()} is used instead of
/// {@link Monodoc.Lucene.Net.Index.IndexReader#NumDocs()} because it is proportional to
/// {@link Searcher#DocFreq(Term)} , i.e., when one is inaccurate,
/// so is the other, and in the same direction.
///
/// </summary>
/// <param name="term">the term in question
/// </param>
/// <param name="searcher">the document collection being searched
/// </param>
/// <returns> a score factor for the term
/// </returns>
public virtual float Idf(Term term, Searcher searcher)
{
return(Idf(searcher.DocFreq(term), searcher.MaxDoc()));
}
protected internal override Weight CreateWeight(Searcher searcher)
{
if (termArrays.Count == 1)
{
// optimize one-term case
Term[] terms = (Term[]) termArrays[0];
BooleanQuery boq = new BooleanQuery();
for (int i = 0; i < terms.Length; i++)
{
boq.Add(new TermQuery(terms[i]), false, false);
}
boq.SetBoost(GetBoost());
return boq.CreateWeight(searcher);
}
return new PhrasePrefixWeight(this, searcher);
}
protected internal override Weight CreateWeight(Searcher searcher)
{
if (terms.Count == 1)
{
// optimize one-term case
Term term = (Term) terms[0];
Query termQuery = new TermQuery(term);
termQuery.SetBoost(GetBoost());
return termQuery.CreateWeight(searcher);
}
return new PhraseWeight(this, searcher);
}
protected internal override Weight CreateWeight(Searcher searcher)
{
return new BooleanWeight(this, searcher);
}
/// <summary>Expert: Returns the Similarity implementation to be used for this query.
/// Subclasses may override this method to specify their own Similarity
/// implementation, perhaps one that delegates through that of the Searcher.
/// By default the Searcher's Similarity implementation is returned.
/// </summary>
public virtual Similarity GetSimilarity(Searcher searcher)
{
return(searcher.GetSimilarity());
}
