Module org.apache.lucene.core

Package org.apache.lucene.search.similarities

Class MultiSimilarity.MultiSimScorer

java.lang.Object

org.apache.lucene.search.similarities.Similarity.SimScorer

org.apache.lucene.search.similarities.MultiSimilarity.MultiSimScorer

Enclosing class:

MultiSimilarity

static class MultiSimilarity.MultiSimScorer
extends Similarity.SimScorer

Field Summary

Fields

Modifier and Type	Field	Description
private final Similarity.SimScorer[]	subScorers

Constructor Summary

Constructors

Constructor	Description
MultiSimScorer(Similarity.SimScorer[] subScorers)

Method Summary

Modifier and Type	Method	Description
Explanation	explain(Explanation freq, long norm)	Explain the score for a single document
float	score(float freq, long norm)	Score a single document.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Details

subScorers

private final Similarity.SimScorer[] subScorers

Constructor Details

MultiSimScorer

MultiSimScorer(Similarity.SimScorer[] subScorers)

Method Details

score

public float score(float freq,
 long norm)

Description copied from class: Similarity.SimScorer

Score a single document. freq is the document-term sloppy frequency and must be finite and positive. norm is the encoded normalization factor as computed by Similarity.computeNorm(FieldInvertState) at index time, or 1 if norms are disabled. norm is never 0.

Score must not decrease when freq increases, ie. if freq1 > freq2, then score(freq1, norm) >= score(freq2, norm) for any value of norm that may be produced by Similarity.computeNorm(FieldInvertState).

Score must not increase when the unsigned norm increases, ie. if Long.compareUnsigned(norm1, norm2) > 0 then score(freq, norm1) <= score(freq, norm2) for any legal freq.

As a consequence, the maximum score that this scorer can produce is bound by score(Float.MAX_VALUE, 1).

Specified by:

score in class Similarity.SimScorer

Parameters:

freq - sloppy term frequency, must be finite and positive

norm - encoded normalization factor or 1 if norms are disabled

Returns:

document's score

explain

public Explanation explain(Explanation freq,
 long norm)

Description copied from class: Similarity.SimScorer

Explain the score for a single document

Overrides:

explain in class Similarity.SimScorer

Parameters:

freq - Explanation of how the sloppy term frequency was computed

norm - encoded normalization factor, as returned by Similarity.computeNorm(org.apache.lucene.index.FieldInvertState), or 1 if norms are disabled

Returns:

document's score