org.apache.lucene.search.TermStatistics#docFreq ( )源码实例Demo

@Override
   public final SimWeight computeWeight(CollectionStatistics collectionStats,
				 TermStatistics... termStats)
   {
float N, n, idf, adl;
idf = 1.0f;
N   = collectionStats.maxDoc();
adl = collectionStats.sumTotalTermFreq() / N;

if (termStats.length == 1) {
    n = termStats[0].docFreq();
    idf = log(N/n);
}
else {
    for (final TermStatistics stat : termStats) {
	n = stat.docFreq();
	idf += log(N/n);
    }
}

return new TFIDFWeight(collectionStats.field(), idf, adl);
   }
 

private void writeTermStatistics(TermStatistics termStatistics) throws IOException {
    int docFreq = (int) termStatistics.docFreq();
    assert (docFreq >= -1);
    writePotentiallyNegativeVInt(docFreq);
    long ttf = termStatistics.totalTermFreq();
    assert (ttf >= -1);
    writePotentiallyNegativeVLong(ttf);
}
 

@Override
public Explanation idfExplain(CollectionStatistics collectionStats, TermStatistics termStats) {
  final long df = termStats.docFreq();
  final long max = collectionStats.maxDoc();
  final float idf = idfManager.getIDF(termStats.term().utf8ToString());
  return new Explanation(idf, "idf(docFreq=" + df + ", maxDocs=" + max + ")");
}
 

@Override
public Explanation idfExplain(CollectionStatistics collectionStats, TermStatistics termStats) {
  final long df = termStats.docFreq();
  final long docCount = collectionStats.docCount();
  final float idf = idf(df, docCount);
  return Explanation.match(idf, "idf, computed as log((docCount+1)/(docFreq+1)) + 1 from:",
      Explanation.match(df, "docFreq, number of documents containing term"),
      Explanation.match(docCount, "docCount, total number of documents with field"));
}
 

@Override
   public final SimWeight computeWeight(CollectionStatistics collectionStats,
				 TermStatistics... termStats)
   {
long  N, n;
float idf_, avdl;

idf_ = 1.0f;

N    = collectionStats.docCount();
if (N == -1)
    N = collectionStats.maxDoc();

avdl = collectionStats.sumTotalTermFreq() / N;

if (termStats.length == 1) {
    n    = termStats[0].docFreq();
    idf_ = idf(n, N);
}
else { /* computation for a phrase */
    for (final TermStatistics stat : termStats) {
	n     = stat.docFreq();
	idf_ += idf(n, N);
    }
}

return new TFIDFWeight(collectionStats.field(), idf_, avdl);
   }
 

public TermStats(String field, TermStatistics stats) {
  this.term = field + ":" + stats.term().utf8ToString();
  this.t = new Term(field, stats.term());
  this.docFreq = stats.docFreq();
  this.totalTermFreq = stats.totalTermFreq();
}
 

/**
 * Computes a score factor for a simple term and returns an explanation
 * for that score factor.
 * 
 * <p>
 * The default implementation uses:
 * 
 * <pre class="prettyprint">
 * idf(docFreq, docCount);
 * </pre>
 * 
 * Note that {@link CollectionStatistics#docCount()} is used instead of
 * {@link org.apache.lucene.index.IndexReader#numDocs() IndexReader#numDocs()} because also 
 * {@link TermStatistics#docFreq()} is used, and when the latter 
 * is inaccurate, so is {@link CollectionStatistics#docCount()}, and in the same direction.
 * In addition, {@link CollectionStatistics#docCount()} does not skew when fields are sparse.
 *   
 * @param collectionStats collection-level statistics
 * @param termStats term-level statistics for the term
 * @return an Explain object that includes both an idf score factor 
           and an explanation for the term.
 */
public Explanation idfExplain(CollectionStatistics collectionStats, TermStatistics termStats) {
  final long df = termStats.docFreq();
  final long docCount = collectionStats.docCount();
  final float idf = idf(df, docCount);
  return Explanation.match(idf, "idf, computed as log(1 + (N - n + 0.5) / (n + 0.5)) from:",
      Explanation.match(df, "n, number of documents containing term"),
      Explanation.match(docCount, "N, total number of documents with field"));
}
 

/**
 * Computes a score factor for a simple term and returns an explanation
 * for that score factor.
 * 
 * <p>
 * The default implementation uses:
 * 
 * <pre class="prettyprint">
 * idf(docFreq, docCount);
 * </pre>
 * 
 * Note that {@link CollectionStatistics#docCount()} is used instead of
 * {@link org.apache.lucene.index.IndexReader#numDocs() IndexReader#numDocs()} because also 
 * {@link TermStatistics#docFreq()} is used, and when the latter 
 * is inaccurate, so is {@link CollectionStatistics#docCount()}, and in the same direction.
 * In addition, {@link CollectionStatistics#docCount()} does not skew when fields are sparse.
 *   
 * @param collectionStats collection-level statistics
 * @param termStats term-level statistics for the term
 * @return an Explain object that includes both an idf score factor 
           and an explanation for the term.
 */
public Explanation idfExplain(CollectionStatistics collectionStats, TermStatistics termStats) {
  final long df = termStats.docFreq();
  final long docCount = collectionStats.docCount();
  final float idf = idf(df, docCount);
  return Explanation.match(idf, "idf(docFreq, docCount)", 
      Explanation.match(df, "docFreq, number of documents containing term"),
      Explanation.match(docCount, "docCount, total number of documents with field"));
}
 

/**
 * Computes a score factor for a simple term and returns an explanation
 * for that score factor.
 * 
 * <p>
 * The default implementation uses:
 * 
 * <pre class="prettyprint">
 * idf(docFreq, docCount);
 * </pre>
 * 
 * Note that {@link CollectionStatistics#docCount()} is used instead of
 * {@link org.apache.lucene.index.IndexReader#numDocs() IndexReader#numDocs()} because also 
 * {@link TermStatistics#docFreq()} is used, and when the latter 
 * is inaccurate, so is {@link CollectionStatistics#docCount()}, and in the same direction.
 * In addition, {@link CollectionStatistics#docCount()} does not skew when fields are sparse.
 *   
 * @param collectionStats collection-level statistics
 * @param termStats term-level statistics for the term
 * @return an Explain object that includes both an idf score factor 
           and an explanation for the term.
 */
public Explanation idfExplain(CollectionStatistics collectionStats, TermStatistics termStats) {
  final long df = termStats.docFreq();
  final long docCount = collectionStats.docCount() == -1 ? collectionStats.maxDoc() : collectionStats.docCount();
  final float idf = idf(df, docCount);
  return Explanation.match(idf, "idf(docFreq=" + df + ", docCount=" + docCount + ")");
}
 

/**
 * 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 docCount = collectionStats.docCount() == -1 ? collectionStats.maxDoc() : collectionStats.docCount();
  float idf = 0.0f;
  List<Explanation> details = new ArrayList<>();
  for (final TermStatistics stat : termStats ) {
    final long df = stat.docFreq();
    final float termIdf = idf(df, docCount);
    details.add(Explanation.match(termIdf, "idf(docFreq=" + df + ", docCount=" + docCount + ")"));
    idf += termIdf;
  }
  return Explanation.match(idf, "idf(), sum of:", details);
}