public TermWeight(TermQuery enclosingInstance, Searcher searcher)
{
InitBlock(enclosingInstance);
this.similarity = Enclosing_Instance.GetSimilarity(searcher);
idfExp = similarity.IdfExplain(Enclosing_Instance.term, searcher);
idf = idfExp.GetIdf();
}
public SpanWeight(SpanQuery query, Searcher searcher)
{
this.similarity = query.GetSimilarity(searcher);
this.query = query;
terms = new System.Collections.Hashtable();
query.ExtractTerms(terms);
idfExp = similarity.idfExplain(new System.Collections.ArrayList(terms.Values), searcher);
idf = idfExp.GetIdf();
}
public /*internal*/ bool debugCheckedForDeletions = false; // for test purposes.
internal Hits(Searcher s, Query q, Filter f)
{
weight = q.Weight(s);
searcher = s;
filter = f;
nDeletions = CountDeletions(s);
GetMoreDocs(50); // retrieve 100 initially
lengthAtStart = length;
}
public MultiPhraseWeight(MultiPhraseQuery enclosingInstance, Searcher searcher)
{
InitBlock(enclosingInstance);
this.similarity = Enclosing_Instance.GetSimilarity(searcher);
// compute idf
System.Collections.IEnumerator i = Enclosing_Instance.termArrays.GetEnumerator();
while (i.MoveNext())
{
Term[] terms = (Term[]) i.Current;
for (int j = 0; j < terms.Length; j++)
{
idf += Enclosing_Instance.GetSimilarity(searcher).Idf(terms[j], searcher);
}
}
}
public override Weight CreateWeight(Searcher searcher)
{
return(new MatchAllDocsWeight(this, searcher));
}
public override Weight CreateWeight(Searcher searcher)
{
return(new BooleanWeight(this, searcher));
}
/// <summary> Expert: Constructs an appropriate Weight implementation for this query.
///
/// <p/>
/// Only implemented by primitive queries, which re-write to themselves.
/// </summary>
public virtual Weight CreateWeight(Searcher searcher)
{
throw new System.NotSupportedException();
}
public virtual float Idf(Term term, Searcher searcher)
{
return(Idf(searcher.DocFreq(term), searcher.MaxDoc()));
}
/// <summary> Expert: Constructs and 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);
if (float.IsInfinity(norm) || float.IsNaN(norm))
norm = 1.0f;
weight.Normalize(norm);
return weight;
}
public ConstantWeight(ConstantScoreQuery enclosingInstance, Searcher searcher)
{
InitBlock(enclosingInstance);
this.similarity = Enclosing_Instance.GetSimilarity(searcher);
}
/// <summary> Computes a score factor for a simple term and returns an explanation
/// for that score factor.
///
/// <p/>
/// The default implementation uses:
///
/// <pre>
/// idf(searcher.docFreq(term), searcher.maxDoc());
/// </pre>
///
/// Note that {@link Searcher#MaxDoc()} is used instead of
/// {@link Mono.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> an IDFExplain object that includes both an idf score factor
/// and an explanation for the term.
/// </returns>
/// <throws> IOException </throws>
public virtual IDFExplanation IdfExplain(Term term, Searcher searcher)
{
if (SupportedMethods.overridesTermIDF)
{
float idf = Idf(term, searcher);
return new AnonymousClassIDFExplanation(idf, this);
}
int df = searcher.DocFreq(term);
int max = searcher.MaxDoc();
float idf2 = Idf(df, max);
return new AnonymousClassIDFExplanation1(df, max, idf2, this);
}
/// <summary> Expert: Constructs an appropriate Weight implementation for this query.
///
/// <p/>
/// Only implemented by primitive queries, which re-write to themselves.
/// </summary>
public virtual Weight CreateWeight(Searcher searcher)
{
throw new System.NotSupportedException();
}
public 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);
}
/// <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());
}
public override Weight CreateWeight(Searcher searcher)
{
return(new MultiPhraseWeight(this, searcher));
}
public override Weight CreateWeight(Searcher searcher)
{
return(new TermWeight(this, searcher));
}
/// <summary> Computes a score factor for a phrase.
///
/// <p/>
/// The default implementation sums the idf 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> an IDFExplain object that includes both an idf
/// score factor for the phrase and an explanation
/// for each term.
/// </returns>
/// <throws> IOException </throws>
public virtual IDFExplanation idfExplain(System.Collections.ICollection terms, Searcher searcher)
{
if (SupportedMethods.overridesCollectionIDF)
{
float idf = Idf(terms, searcher);
return new AnonymousClassIDFExplanation2(idf, this);
}
int max = searcher.MaxDoc();
float idf2 = 0.0f;
System.Text.StringBuilder exp = new System.Text.StringBuilder();
foreach (Term term in terms)
{
int df = searcher.DocFreq(term);
idf2 += Idf(df, max);
exp.Append(" ");
exp.Append(term.Text());
exp.Append("=");
exp.Append(df);
}
float fIdf = idf2;
return new AnonymousClassIDFExplanation3(fIdf, exp, this);
}
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;
}
protected internal System.Collections.ArrayList weights = new System.Collections.ArrayList(); // The Weight's for our subqueries, in 1-1 correspondence with disjuncts
/* Construct the Weight for this Query searched by searcher. Recursively construct subquery weights. */
public DisjunctionMaxWeight(DisjunctionMaxQuery enclosingInstance, Searcher searcher)
{
InitBlock(enclosingInstance);
this.similarity = searcher.GetSimilarity();
for (System.Collections.IEnumerator iter = Enclosing_Instance.disjuncts.GetEnumerator(); iter.MoveNext(); )
{
weights.Add(((Query) iter.Current).CreateWeight(searcher));
}
}
public override Weight CreateWeight(Searcher searcher)
{
return new MultiPhraseWeight(this, searcher);
}
} // end of DisjunctionMaxWeight inner class
/* Create the Weight used to score us */
public override Weight CreateWeight(Searcher searcher)
{
return(new DisjunctionMaxWeight(this, 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>
public override Weight CreateWeight(Searcher searcher)
{
Weight weight = query.CreateWeight(searcher);
Similarity similarity = query.GetSimilarity(searcher);
return new AnonymousClassWeight(weight, similarity, this);
}
/// <summary> Computes a score factor for a phrase.
///
/// <p/>
/// The default implementation sums the idf 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> an IDFExplain object that includes both an idf
/// score factor for the phrase and an explanation
/// for each term.
/// </returns>
/// <throws> IOException </throws>
public virtual IDFExplanation idfExplain(System.Collections.ICollection terms, Searcher searcher)
{
if (SupportedMethods.overridesCollectionIDF)
{
float idf = Idf(terms, searcher);
return(new AnonymousClassIDFExplanation2(idf, this));
}
int max = searcher.MaxDoc();
float idf2 = 0.0f;
System.Text.StringBuilder exp = new System.Text.StringBuilder();
foreach (Term term in terms)
{
int df = searcher.DocFreq(term);
idf2 += Idf(df, max);
exp.Append(" ");
exp.Append(term.Text());
exp.Append("=");
exp.Append(df);
}
float fIdf = idf2;
return(new AnonymousClassIDFExplanation3(fIdf, exp, this));
}
public override Weight CreateWeight(Searcher searcher)
{
return new ValueSourceQuery.ValueSourceWeight(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();
}
public ValueSourceWeight(ValueSourceQuery enclosingInstance, Searcher searcher)
{
InitBlock(enclosingInstance);
this.similarity = Enclosing_Instance.GetSimilarity(searcher);
}
// count # deletions, return -1 if unknown.
private int CountDeletions(Searcher s)
{
int cnt = - 1;
if (s is IndexSearcher)
{
cnt = s.MaxDoc() - ((IndexSearcher) s).GetIndexReader().NumDocs();
}
return cnt;
}
public MatchAllDocsWeight(MatchAllDocsQuery enclosingInstance, Searcher searcher)
{
InitBlock(enclosingInstance);
this.similarity = searcher.GetSimilarity();
}
public override Weight CreateWeight(Searcher searcher)
{
return new MatchAllDocsWeight(this, searcher);
}
// Implement coord disabling.
// Inherit javadoc.
public override Similarity GetSimilarity(Searcher searcher)
{
Similarity result = base.GetSimilarity(searcher);
if (disableCoord)
{
// disable coord as requested
result = new AnonymousClassSimilarityDelegator(this, result);
}
return result;
}
public MatchAllDocsWeight(MatchAllDocsQuery enclosingInstance, Searcher searcher)
{
InitBlock(enclosingInstance);
this.similarity = searcher.GetSimilarity();
}
public BooleanWeight(BooleanQuery enclosingInstance, Searcher searcher)
{
InitBlock(enclosingInstance);
this.similarity = Enclosing_Instance.GetSimilarity(searcher);
weights = new System.Collections.ArrayList(Enclosing_Instance.clauses.Count);
for (int i = 0; i < Enclosing_Instance.clauses.Count; i++)
{
BooleanClause c = (BooleanClause) Enclosing_Instance.clauses[i];
weights.Add(c.GetQuery().CreateWeight(searcher));
}
}
public override Weight CreateWeight(Searcher searcher)
{
return new TermWeight(this, searcher);
}
public override Weight CreateWeight(Searcher searcher)
{
return new BooleanWeight(this, searcher);
}
public override Weight CreateWeight(Searcher searcher)
{
return(new ConstantScoreQuery.ConstantWeight(this, searcher));
}
public override Weight CreateWeight(Searcher searcher)
{
return new ConstantScoreQuery.ConstantWeight(this, searcher);
}
public Result (string Term, Searcher searcher, ScoreDoc[] docs)
{
this.term = Term;
this.searcher = searcher;
this.docs = docs;
}
public ConstantWeight(ConstantScoreQuery enclosingInstance, Searcher searcher)
{
InitBlock(enclosingInstance);
this.similarity = Enclosing_Instance.GetSimilarity(searcher);
}
} // end of DisjunctionMaxWeight inner class
/* Create the Weight used to score us */
public override Weight CreateWeight(Searcher searcher)
{
return new DisjunctionMaxWeight(this, searcher);
}
public virtual float Idf(Term term, Searcher searcher)
{
return Idf(searcher.DocFreq(term), searcher.MaxDoc());
}