Java 类org.apache.lucene.search.similarities.IBSimilarity 实例源码

public IBSimilarityProvider(String name, Settings settings, Settings indexSettings) {
    super(name);
    Distribution distribution = parseDistribution(settings);
    Lambda lambda = parseLambda(settings);
    Normalization normalization = parseNormalization(settings);
    this.similarity = new IBSimilarity(distribution, lambda, normalization);
}

@Before
public void setupIndex() throws IOException {
    dirUnderTest = newDirectory();
    List<Similarity> sims = Arrays.asList(
            new ClassicSimilarity(),
            new SweetSpotSimilarity(), // extends Classic
            new BM25Similarity(),
            new LMDirichletSimilarity(),
            new BooleanSimilarity(),
            new LMJelinekMercerSimilarity(0.2F),
            new AxiomaticF3LOG(0.5F, 10),
            new DFISimilarity(new IndependenceChiSquared()),
            new DFRSimilarity(new BasicModelBE(), new AfterEffectB(), new NormalizationH1()),
            new IBSimilarity(new DistributionLL(), new LambdaDF(), new NormalizationH3())
        );
    similarity = sims.get(random().nextInt(sims.size()));

    indexWriterUnderTest = new RandomIndexWriter(random(), dirUnderTest, newIndexWriterConfig().setSimilarity(similarity));
    for (int i = 0; i < docs.length; i++) {
        Document doc = new Document();
        doc.add(newStringField("id", "" + i, Field.Store.YES));
        doc.add(newField("field", docs[i], Store.YES));
        indexWriterUnderTest.addDocument(doc);
    }
    indexWriterUnderTest.commit();
    indexWriterUnderTest.forceMerge(1);
    indexWriterUnderTest.flush();


    indexReaderUnderTest = indexWriterUnderTest.getReader();
    searcherUnderTest = newSearcher(indexReaderUnderTest);
    searcherUnderTest.setSimilarity(similarity);
}

/** spl/df/h2 with default parameters */
public void test() throws Exception {
  Similarity sim = getSimilarity("text");
  assertEquals(IBSimilarity.class, sim.getClass());
  IBSimilarity ib = (IBSimilarity) sim;
  assertEquals(DistributionSPL.class, ib.getDistribution().getClass());
  assertEquals(LambdaDF.class, ib.getLambda().getClass());
  assertEquals(NormalizationH2.class, ib.getNormalization().getClass());
}

/** ll/ttf/h3 with parameterized normalization */
public void testParameters() throws Exception {
  Similarity sim = getSimilarity("text_params");
  assertEquals(IBSimilarity.class, sim.getClass());
  IBSimilarity ib = (IBSimilarity) sim;
  assertEquals(DistributionLL.class, ib.getDistribution().getClass());
  assertEquals(LambdaTTF.class, ib.getLambda().getClass());
  assertEquals(NormalizationH3.class, ib.getNormalization().getClass());
  NormalizationH3 norm = (NormalizationH3) ib.getNormalization();
  assertEquals(900f, norm.getMu(), 0.01f);
}

/** spl/df/h2 with default parameters */
public void test() throws Exception {
  Similarity sim = getSimilarity("text");
  assertEquals(IBSimilarity.class, sim.getClass());
  IBSimilarity ib = (IBSimilarity) sim;
  assertEquals(DistributionSPL.class, ib.getDistribution().getClass());
  assertEquals(LambdaDF.class, ib.getLambda().getClass());
  assertEquals(NormalizationH2.class, ib.getNormalization().getClass());
}

/** ll/ttf/h3 with parameterized normalization */
public void testParameters() throws Exception {
  Similarity sim = getSimilarity("text_params");
  assertEquals(IBSimilarity.class, sim.getClass());
  IBSimilarity ib = (IBSimilarity) sim;
  assertEquals(DistributionLL.class, ib.getDistribution().getClass());
  assertEquals(LambdaTTF.class, ib.getLambda().getClass());
  assertEquals(NormalizationH3.class, ib.getNormalization().getClass());
  NormalizationH3 norm = (NormalizationH3) ib.getNormalization();
  assertEquals(900f, norm.getMu(), 0.01f);
}

/** spl/df/h2 with default parameters */
public void test() throws Exception {
  Similarity sim = getSimilarity("text");
  assertEquals(IBSimilarity.class, sim.getClass());
  IBSimilarity ib = (IBSimilarity) sim;
  assertEquals(DistributionSPL.class, ib.getDistribution().getClass());
  assertEquals(LambdaDF.class, ib.getLambda().getClass());
  assertEquals(NormalizationH2.class, ib.getNormalization().getClass());
}

/** ll/ttf/h3 with parameterized normalization */
public void testParameters() throws Exception {
  Similarity sim = getSimilarity("text_params");
  assertEquals(IBSimilarity.class, sim.getClass());
  IBSimilarity ib = (IBSimilarity) sim;
  assertEquals(DistributionLL.class, ib.getDistribution().getClass());
  assertEquals(LambdaTTF.class, ib.getLambda().getClass());
  assertEquals(NormalizationH3.class, ib.getNormalization().getClass());
  NormalizationH3 norm = (NormalizationH3) ib.getNormalization();
  assertEquals(900f, norm.getMu(), 0.01f);
}

@Override
public Similarity getSimilarity() {
  IBSimilarity sim = new IBSimilarity(distribution, lambda, normalization);
  sim.setDiscountOverlaps(discountOverlaps);
  return sim;
}

@Override
public Similarity getSimilarity() {
  IBSimilarity sim = new IBSimilarity(distribution, lambda, normalization);
  sim.setDiscountOverlaps(discountOverlaps);
  return sim;
}

@Override
public Similarity getSimilarity() {
  IBSimilarity sim = new IBSimilarity(distribution, lambda, normalization);
  sim.setDiscountOverlaps(discountOverlaps);
  return sim;
}

@Override
public Similarity getSimilarity() {
  IBSimilarity sim = new IBSimilarity(distribution, lambda, normalization);
  sim.setDiscountOverlaps(discountOverlaps);
  return sim;
}

@Override
public Similarity getSimilarity() {
  IBSimilarity sim = new IBSimilarity(distribution, lambda, normalization);
  sim.setDiscountOverlaps(discountOverlaps);
  return sim;
}