Java Explanation.setDescription方法代码示例

import org.apache.lucene.search.Explanation; //导入方法依赖的package包/类
@Override
protected void explain(Explanation expl, BasicStats stats, int doc,
    float freq, float docLen) {
  if (stats.getTotalBoost() != 1.0f) {
    expl.addDetail(new Explanation(stats.getTotalBoost(), "boost"));
  }

  expl.addDetail(new Explanation(mu, "mu"));
  Explanation weightExpl = new Explanation();
  weightExpl.setValue((float)Math.log(1 + freq /
      (mu * ((LMStats)stats).getCollectionProbability())));
  weightExpl.setDescription("term weight");
  expl.addDetail(weightExpl);
  expl.addDetail(new Explanation(
      (float)Math.log(mu / (docLen + mu)), "document norm"));
  super.explain(expl, stats, doc, freq, docLen);
}
 

import org.apache.lucene.search.Explanation; //导入方法依赖的package包/类
@Override
public Explanation explain(AtomicReaderContext context, int doc) throws IOException {
  PayloadNearSpanScorer scorer = (PayloadNearSpanScorer) scorer(context, context.reader().getLiveDocs());
  if (scorer != null) {
    int newDoc = scorer.advance(doc);
    if (newDoc == doc) {
      float freq = scorer.freq();
      SimScorer docScorer = similarity.simScorer(stats, context);
      Explanation expl = new Explanation();
      expl.setDescription("weight("+getQuery()+" in "+doc+") [" + similarity.getClass().getSimpleName() + "], result of:");
      Explanation scoreExplanation = docScorer.explain(doc, new Explanation(freq, "phraseFreq=" + freq));
      expl.addDetail(scoreExplanation);
      expl.setValue(scoreExplanation.getValue());
      String field = ((SpanQuery)getQuery()).getField();
      // now the payloads part
      Explanation payloadExpl = function.explain(doc, field, scorer.payloadsSeen, scorer.payloadScore);
      // combined
      ComplexExplanation result = new ComplexExplanation();
      result.addDetail(expl);
      result.addDetail(payloadExpl);
      result.setValue(expl.getValue() * payloadExpl.getValue());
      result.setDescription("PayloadNearQuery, product of:");
      return result;
    }
  }
  
  return new ComplexExplanation(false, 0.0f, "no matching term");
}
 

import org.apache.lucene.search.Explanation; //导入方法依赖的package包/类
@Override
public Explanation explain(AtomicReaderContext context, int doc) throws IOException {
  PayloadTermSpanScorer scorer = (PayloadTermSpanScorer) scorer(context, context.reader().getLiveDocs());
  if (scorer != null) {
    int newDoc = scorer.advance(doc);
    if (newDoc == doc) {
      float freq = scorer.sloppyFreq();
      SimScorer docScorer = similarity.simScorer(stats, context);
      Explanation expl = new Explanation();
      expl.setDescription("weight("+getQuery()+" in "+doc+") [" + similarity.getClass().getSimpleName() + "], result of:");
      Explanation scoreExplanation = docScorer.explain(doc, new Explanation(freq, "phraseFreq=" + freq));
      expl.addDetail(scoreExplanation);
      expl.setValue(scoreExplanation.getValue());
      // now the payloads part
      // QUESTION: Is there a way to avoid this skipTo call? We need to know
      // whether to load the payload or not
      // GSI: I suppose we could toString the payload, but I don't think that
      // would be a good idea
      String field = ((SpanQuery)getQuery()).getField();
      Explanation payloadExpl = function.explain(doc, field, scorer.payloadsSeen, scorer.payloadScore);
      payloadExpl.setValue(scorer.getPayloadScore());
      // combined
      ComplexExplanation result = new ComplexExplanation();
      if (includeSpanScore) {
        result.addDetail(expl);
        result.addDetail(payloadExpl);
        result.setValue(expl.getValue() * payloadExpl.getValue());
        result.setDescription("btq, product of:");
      } else {
        result.addDetail(payloadExpl);
        result.setValue(payloadExpl.getValue());
        result.setDescription("btq(includeSpanScore=false), result of:");
      }
      result.setMatch(true); // LUCENE-1303
      return result;
    }
  }
  
  return new ComplexExplanation(false, 0.0f, "no matching term");
}
 

import org.apache.lucene.search.Explanation; //导入方法依赖的package包/类
/**
 * Returns an explanation for the score.
 * <p>Most basic models use the number of documents and the total term
 * frequency to compute Inf<sub>1</sub>. This method provides a generic
 * explanation for such models. Subclasses that use other statistics must
 * override this method.</p>
 */
public Explanation explain(BasicStats stats, float tfn) {
  Explanation result = new Explanation();
  result.setDescription(getClass().getSimpleName() + ", computed from: ");
  result.setValue(score(stats, tfn));
  result.addDetail(new Explanation(tfn, "tfn"));
  result.addDetail(
      new Explanation(stats.getNumberOfDocuments(), "numberOfDocuments"));
  result.addDetail(
      new Explanation(stats.getTotalTermFreq(), "totalTermFreq"));
  return result;
}
 

import org.apache.lucene.search.Explanation; //导入方法依赖的package包/类
@Override
public final Explanation explain(BasicStats stats, float tfn) {
  Explanation result = new Explanation();
  result.setDescription(getClass().getSimpleName() + ", computed from: ");
  result.setValue(score(stats, tfn));
  result.addDetail(new Explanation(tfn, "tfn"));
  result.addDetail(
      new Explanation(stats.getNumberOfDocuments(), "numberOfDocuments"));
  result.addDetail(
      new Explanation(stats.getDocFreq(), "docFreq"));
  return result;
}
 

import org.apache.lucene.search.Explanation; //导入方法依赖的package包/类
@Override
public final Explanation explain(BasicStats stats, float tfn) {
  Explanation result = new Explanation();
  result.setDescription(getClass().getSimpleName() + ", computed from: ");
  result.setValue(score(stats, tfn));
  result.addDetail(new Explanation(tfn, "tfn"));
  result.addDetail(new Explanation(stats.getTotalTermFreq(), "totalTermFreq"));
  result.addDetail(new Explanation(stats.getDocFreq(), "docFreq"));
  return result;
}
 

import org.apache.lucene.search.Explanation; //导入方法依赖的package包/类
/**
 * Computes a score factor for a phrase.
 * 
 * <p>
 * The default implementation sums the idf factor for
 * each term in the phrase.
 * 
 * @param collectionStats collection-level statistics
 * @param termStats term-level statistics for the terms in the phrase
 * @return an Explain object that includes both an idf 
 *         score factor for the phrase and an explanation 
 *         for each term.
 */
public Explanation idfExplain(CollectionStatistics collectionStats, TermStatistics termStats[]) {
  final long max = collectionStats.maxDoc();
  float idf = 0.0f;
  final Explanation exp = new Explanation();
  exp.setDescription("idf(), sum of:");
  for (final TermStatistics stat : termStats ) {
    final long df = stat.docFreq();
    final float termIdf = idf(df, max);
    exp.addDetail(new Explanation(termIdf, "idf(docFreq=" + df + ", maxDocs=" + max + ")"));
    idf += termIdf;
  }
  exp.setValue(idf);
  return exp;
}
 

import org.apache.lucene.search.Explanation; //导入方法依赖的package包/类
private Explanation explainScore(int doc, Explanation freq, BM25Stats stats, NumericDocValues norms) {
  Explanation result = new Explanation();
  result.setDescription("score(doc="+doc+",freq="+freq+"), product of:");
  
  Explanation boostExpl = new Explanation(stats.queryBoost * stats.topLevelBoost, "boost");
  if (boostExpl.getValue() != 1.0f)
    result.addDetail(boostExpl);
  
  result.addDetail(stats.idf);

  Explanation tfNormExpl = new Explanation();
  tfNormExpl.setDescription("tfNorm, computed from:");
  tfNormExpl.addDetail(freq);
  tfNormExpl.addDetail(new Explanation(k1, "parameter k1"));
  if (norms == null) {
    tfNormExpl.addDetail(new Explanation(0, "parameter b (norms omitted for field)"));
    tfNormExpl.setValue((freq.getValue() * (k1 + 1)) / (freq.getValue() + k1));
  } else {
    float doclen = decodeNormValue((byte)norms.get(doc));
    tfNormExpl.addDetail(new Explanation(b, "parameter b"));
    tfNormExpl.addDetail(new Explanation(stats.avgdl, "avgFieldLength"));
    tfNormExpl.addDetail(new Explanation(doclen, "fieldLength"));
    tfNormExpl.setValue((freq.getValue() * (k1 + 1)) / (freq.getValue() + k1 * (1 - b + b * doclen/stats.avgdl)));
  }
  result.addDetail(tfNormExpl);
  result.setValue(boostExpl.getValue() * stats.idf.getValue() * tfNormExpl.getValue());
  return result;
}
 

import org.apache.lucene.search.Explanation; //导入方法依赖的package包/类
@Override
public final Explanation explain(BasicStats stats, float tfn) {
  Explanation result = new Explanation();
  result.setDescription(getClass().getSimpleName() + ", computed from: ");
  result.setValue(score(stats, tfn));
  result.addDetail(new Explanation(tfn, "tfn"));
  return result;
}
 

import org.apache.lucene.search.Explanation; //导入方法依赖的package包/类
@Override
public final Explanation explain(BasicStats stats) {
  Explanation result = new Explanation();
  result.setDescription(getClass().getSimpleName() + ", computed from: ");
  result.setValue(lambda(stats));
  result.addDetail(
      new Explanation(stats.getDocFreq(), "docFreq"));
  result.addDetail(
      new Explanation(stats.getNumberOfDocuments(), "numberOfDocuments"));
  return result;
}
 

import org.apache.lucene.search.Explanation; //导入方法依赖的package包/类
/** Returns an explanation for the normalized term frequency.
 * <p>The default normalization methods use the field length of the document
 * and the average field length to compute the normalized term frequency.
 * This method provides a generic explanation for such methods.
 * Subclasses that use other statistics must override this method.</p>
 */
public Explanation explain(BasicStats stats, float tf, float len) {
  Explanation result = new Explanation();
  result.setDescription(getClass().getSimpleName() + ", computed from: ");
  result.setValue(tfn(stats, tf, len));
  result.addDetail(new Explanation(tf, "tf"));
  result.addDetail(
      new Explanation(stats.getAvgFieldLength(), "avgFieldLength"));
  result.addDetail(new Explanation(len, "len"));
  return result;
}
 

import org.apache.lucene.search.Explanation; //导入方法依赖的package包/类
@Override
public final Explanation explain(BasicStats stats) {
  Explanation result = new Explanation();
  result.setDescription(getClass().getSimpleName() + ", computed from: ");
  result.setValue(lambda(stats));
  result.addDetail(
      new Explanation(stats.getTotalTermFreq(), "totalTermFreq"));
  result.addDetail(
      new Explanation(stats.getNumberOfDocuments(), "numberOfDocuments"));
  return result;
}
 

import org.apache.lucene.search.Explanation; //导入方法依赖的package包/类
public Explanation explain(int docId, String field, int numPayloadsSeen, float payloadScore){
  Explanation result = new Explanation();
  result.setDescription(getClass().getSimpleName() + ".docScore()");
  result.setValue(docScore(docId, field, numPayloadsSeen, payloadScore));
  return result;
}
 

import org.apache.lucene.search.Explanation; //导入方法依赖的package包/类
private Explanation explainScore(int doc, Explanation freq, IDFStats stats, NumericDocValues norms) {
  Explanation result = new Explanation();
  result.setDescription("score(doc="+doc+",freq="+freq+"), product of:");

  // explain query weight
  Explanation queryExpl = new Explanation();
  queryExpl.setDescription("queryWeight, product of:");

  Explanation boostExpl = new Explanation(stats.queryBoost, "boost");
  if (stats.queryBoost != 1.0f)
    queryExpl.addDetail(boostExpl);
  queryExpl.addDetail(stats.idf);

  Explanation queryNormExpl = new Explanation(stats.queryNorm,"queryNorm");
  queryExpl.addDetail(queryNormExpl);

  queryExpl.setValue(boostExpl.getValue() *
                     stats.idf.getValue() *
                     queryNormExpl.getValue());

  result.addDetail(queryExpl);

  // explain field weight
  Explanation fieldExpl = new Explanation();
  fieldExpl.setDescription("fieldWeight in "+doc+
                           ", product of:");

  Explanation tfExplanation = new Explanation();
  tfExplanation.setValue(tf(freq.getValue()));
  tfExplanation.setDescription("tf(freq="+freq.getValue()+"), with freq of:");
  tfExplanation.addDetail(freq);
  fieldExpl.addDetail(tfExplanation);
  fieldExpl.addDetail(stats.idf);

  Explanation fieldNormExpl = new Explanation();
  float fieldNorm = norms != null ? decodeNormValue(norms.get(doc)) : 1.0f;
  fieldNormExpl.setValue(fieldNorm);
  fieldNormExpl.setDescription("fieldNorm(doc="+doc+")");
  fieldExpl.addDetail(fieldNormExpl);
  
  fieldExpl.setValue(tfExplanation.getValue() *
                     stats.idf.getValue() *
                     fieldNormExpl.getValue());

  result.addDetail(fieldExpl);
  
  // combine them
  result.setValue(queryExpl.getValue() * fieldExpl.getValue());

  if (queryExpl.getValue() == 1.0f)
    return fieldExpl;

  return result;
}
 

import org.apache.lucene.search.Explanation; //导入方法依赖的package包/类
/**
 * Explains the score. The implementation here provides a basic explanation
 * in the format <em>score(name-of-similarity, doc=doc-id,
 * freq=term-frequency), computed from:</em>, and
 * attaches the score (computed via the {@link #score(BasicStats, float, float)}
 * method) and the explanation for the term frequency. Subclasses content with
 * this format may add additional details in
 * {@link #explain(Explanation, BasicStats, int, float, float)}.
 *  
 * @param stats the corpus level statistics.
 * @param doc the document id.
 * @param freq the term frequency and its explanation.
 * @param docLen the document length.
 * @return the explanation.
 */
protected Explanation explain(
    BasicStats stats, int doc, Explanation freq, float docLen) {
  Explanation result = new Explanation(); 
  result.setValue(score(stats, freq.getValue(), docLen));
  result.setDescription("score(" + getClass().getSimpleName() +
      ", doc=" + doc + ", freq=" + freq.getValue() +"), computed from:");
  result.addDetail(freq);
  
  explain(result, stats, doc, freq.getValue(), docLen);
  
  return result;
}