public TermWeight(TermQuery enclosingInstance, Searcher searcher)
{
InitBlock(enclosingInstance);
this.similarity = Enclosing_Instance.GetSimilarity(searcher);
idfExp = similarity.IdfExplain(Enclosing_Instance.term, searcher);
idf = idfExp.Idf;
}
public MatchAllDocsWeight(MatchAllDocsQuery enclosingInstance, Searcher searcher)
{
InitBlock(enclosingInstance);
this.similarity = searcher.Similarity;
}
public override Weight CreateWeight(Searcher searcher)
{
return(new BooleanWeight(this, searcher));
}
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:
///
/// <code>
/// idf(searcher.docFreq(term), searcher.MaxDoc);
/// </code>
///
/// Note that <see cref="Searcher.MaxDoc" /> is used instead of
/// <see cref="Lucene.Net.Index.IndexReader.NumDocs()" /> because it is
/// proportional to <see cref="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 Explanation.IDFExplanation IdfExplain(Term term, Searcher searcher)
{
int df = searcher.DocFreq(term);
int max = searcher.MaxDoc;
float idf2 = Idf(df, max);
return new AnonymousClassIDFExplanation1(df, max, idf2, this);
}
/// <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);
}
public override Weight CreateWeight(Searcher searcher)
{
return(new MatchAllDocsWeight(this, searcher));
}
public override Weight CreateWeight(Searcher searcher)
{
return(new ConstantScoreQuery.ConstantWeight(this, searcher));
}
public ConstantWeight(ConstantScoreQuery enclosingInstance, Searcher searcher)
{
InitBlock(enclosingInstance);
this.similarity = Enclosing_Instance.GetSimilarity(searcher);
}
/// <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.GetSumOfSquaredWeights();
float norm = GetSimilarity(searcher).QueryNorm(sum);
if (float.IsInfinity(norm) || float.IsNaN(norm))
norm = 1.0f;
weight.Normalize(norm);
return weight;
}
public override Weight CreateWeight(Searcher searcher)
{
return(new TermWeight(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();
}
/// <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.Similarity;
}
public override Weight CreateWeight(Searcher searcher)
{
if (terms.Count == 1)
{
// optimize one-term case
Term term = terms[0];
Query termQuery = new TermQuery(term);
termQuery.Boost = Boost;
return termQuery.CreateWeight(searcher);
}
return new PhraseWeight(this, searcher);
}
public override Weight CreateWeight(Searcher searcher)
{
return new MatchAllDocsWeight(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.Similarity);
}
} // end of DisjunctionMaxWeight inner class
/* Create the Weight used to score us */
public override Weight CreateWeight(Searcher searcher)
{
return(new DisjunctionMaxWeight(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 MatchAllDocsWeight(MatchAllDocsQuery enclosingInstance, Searcher searcher)
{
InitBlock(enclosingInstance);
this.similarity = searcher.Similarity;
}
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);
}
}
}
public override Weight CreateWeight(Searcher searcher)
{
return new ConstantScoreQuery.ConstantWeight(this, searcher);
}
public override Weight CreateWeight(Searcher searcher)
{
return new MultiPhraseWeight(this, searcher);
}
public override Weight CreateWeight(Searcher searcher)
{
return(new MultiPhraseWeight(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 Explanation.IDFExplanation IdfExplain(ICollection <Term> terms, Searcher searcher)
{
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));
}
/// <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 Explanation.IDFExplanation IdfExplain(ICollection<Term> terms, Searcher searcher)
{
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 TermWeight(this, searcher);
}
