/*
* Licensed to the Apache Software Foundation (ASF) under one or more
* contributor license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright ownership.
* The ASF licenses this file to You under the Apache License, Version 2.0
* (the "License"); you may not use this file except in compliance with
* the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
using System;
using TermDocs = Lucene.Net.Index.TermDocs;
namespace Lucene.Net.Search
{
/// Expert: A Scorer
for documents matching a Term
.
sealed public class TermScorer : Scorer
{
private Weight weight;
private TermDocs termDocs;
private byte[] norms;
private float weightValue;
private int doc;
private int[] docs = new int[32]; // buffered doc numbers
private int[] freqs = new int[32]; // buffered term freqs
private int pointer;
private int pointerMax;
private const int SCORE_CACHE_SIZE = 32;
private float[] scoreCache = new float[SCORE_CACHE_SIZE];
/// Construct a TermScorer
.
/// The weight of the Term
in the query.
///
/// An iterator over the documents matching the Term
.
///
/// The Similarity implementation to be used for score computations.
///
/// The field norms of the document fields for the Term
.
///
public TermScorer(Weight weight, TermDocs td, Similarity similarity, byte[] norms) : base(similarity)
{
this.weight = weight;
this.termDocs = td;
this.norms = norms;
this.weightValue = weight.GetValue();
for (int i = 0; i < SCORE_CACHE_SIZE; i++)
scoreCache[i] = GetSimilarity().Tf(i) * weightValue;
}
public override void Score(HitCollector hc)
{
Next();
Score(hc, System.Int32.MaxValue);
}
protected internal override bool Score(HitCollector c, int end)
{
Similarity similarity = GetSimilarity(); // cache sim in local
float[] normDecoder = Similarity.GetNormDecoder();
while (doc < end)
{
// for docs in window
int f = freqs[pointer];
float score = f < SCORE_CACHE_SIZE ? scoreCache[f] : similarity.Tf(f) * weightValue; // cache miss
score *= normDecoder[norms[doc] & 0xFF]; // normalize for field
c.Collect(doc, score); // collect score
if (++pointer >= pointerMax)
{
pointerMax = termDocs.Read(docs, freqs); // refill buffers
if (pointerMax != 0)
{
pointer = 0;
}
else
{
termDocs.Close(); // close stream
doc = System.Int32.MaxValue; // set to sentinel value
return false;
}
}
doc = docs[pointer];
}
return true;
}
/// Returns the current document number matching the query.
/// Initially invalid, until {@link #next()} is called the first time.
///
public override int Doc()
{
return doc;
}
/// Advances to the next document matching the query.
///
The iterator over the matching documents is buffered using
/// {@link TermDocs#Read(int[],int[])}.
///
/// true iff there is another document matching the query.
///
public override bool Next()
{
pointer++;
if (pointer >= pointerMax)
{
pointerMax = termDocs.Read(docs, freqs); // refill buffer
if (pointerMax != 0)
{
pointer = 0;
}
else
{
termDocs.Close(); // close stream
doc = System.Int32.MaxValue; // set to sentinel value
return false;
}
}
doc = docs[pointer];
return true;
}
public override float Score()
{
int f = freqs[pointer];
float raw = f < SCORE_CACHE_SIZE ? scoreCache[f] : GetSimilarity().Tf(f) * weightValue; // cache miss
return raw * Similarity.DecodeNorm(norms[doc]); // normalize for field
}
/// Skips to the first match beyond the current whose document number is
/// greater than or equal to a given target.
///
The implementation uses {@link TermDocs#SkipTo(int)}.
///
/// The target document number.
///
/// true iff there is such a match.
///
public override bool SkipTo(int target)
{
// first scan in cache
for (pointer++; pointer < pointerMax; pointer++)
{
if (docs[pointer] >= target)
{
doc = docs[pointer];
return true;
}
}
// not found in cache, seek underlying stream
bool result = termDocs.SkipTo(target);
if (result)
{
pointerMax = 1;
pointer = 0;
docs[pointer] = doc = termDocs.Doc();
freqs[pointer] = termDocs.Freq();
}
else
{
doc = System.Int32.MaxValue;
}
return result;
}
/// Returns an explanation of the score for a document.
///
When this method is used, the {@link #next()} method
/// and the {@link #Score(HitCollector)} method should not be used.
///
/// The document number for the explanation.
///
public override Explanation Explain(int doc)
{
TermQuery query = (TermQuery) weight.GetQuery();
Explanation tfExplanation = new Explanation();
int tf = 0;
while (pointer < pointerMax)
{
if (docs[pointer] == doc)
tf = freqs[pointer];
pointer++;
}
if (tf == 0)
{
if (termDocs.SkipTo(doc))
{
if (termDocs.Doc() == doc)
{
tf = termDocs.Freq();
}
}
}
termDocs.Close();
tfExplanation.SetValue(GetSimilarity().Tf(tf));
tfExplanation.SetDescription("tf(termFreq(" + query.GetTerm() + ")=" + tf + ")");
return tfExplanation;
}
/// Returns a string representation of this TermScorer
.
public override System.String ToString()
{
return "scorer(" + weight + ")";
}
}
}