Package edu.umd.cloud9.util.map

Examples of edu.umd.cloud9.util.map.HMapID$KeyIterator


    assertEquals(m2.length(), 1, 10E-6);
  }

  @Test
  public void testSortedEntries1() {
    HMapID m = new HMapID();

    m.put(1, 5.0);
    m.put(2, 2.0);
    m.put(3, 3.0);
    m.put(4, 3.0);
    m.put(5, 1.0);

    Entry[] e = m.getEntriesSortedByValue();
    assertEquals(5, e.length);

    assertEquals(1, e[0].getKey());
    assertEquals(5.0, e[0].getValue(), 10E-6);
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    assertEquals(1.0, e[4].getValue(), 10E-6);
  }

  @Test
  public void testSortedEntries2() {
    HMapID m = new HMapID();

    m.put(1, 5.0);
    m.put(2, 2.0);
    m.put(3, 3.0);
    m.put(4, 3.0);
    m.put(5, 1.0);

    Entry[] e = m.getEntriesSortedByValue(2);

    assertEquals(2, e.length);

    assertEquals(1, e[0].getKey());
    assertEquals(5.0, e[0].getValue(), 10E-6);
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    assertEquals(3.0, e[1].getValue(), 10E-6);
  }

  @Test
  public void testSortedEntries3() {
    HMapID m = new HMapID();

    m.put(1, 5.0);
    m.put(2, 2.0);

    Entry[] e = m.getEntriesSortedByValue(5);

    assertEquals(2, e.length);

    assertEquals(1, e[0].getKey());
    assertEquals(5.0, e[0].getValue(), 10E-6);
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    assertEquals(2.0, e[1].getValue(), 10E-6);
  }

  @Test
  public void testSortedEntries4() {
    HMapID m = new HMapID();

    Entry[] e = m.getEntriesSortedByValue();
    assertTrue(e == null);
  }
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    assertTrue(e == null);
  }

  @Test
  public void testIncrement() {
    HMapID m = new HMapID();
    assertEquals(0.0, m.get(1), 10E-6);

    m.increment(1, 0.5);
    assertEquals(0.5, m.get(1), 10E-6);

    m.increment(1, 1.0);
    m.increment(2, 0.0);
    m.increment(3, -0.5);

    assertEquals(1.5, m.get(1), 10E-6);
    assertEquals(0.0, m.get(2), 10E-6);
    assertEquals(-0.5, m.get(3), 10E-6);
  }
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  public static void addToTable(int curIndex, TreeSet<PairOfFloatString> topTrans, float cumProb, TTable_monolithic_IFAs table,
      Vocab trgVocab, float cumProbThreshold, HookaStats stats) {
    List<Integer> sortedIndices = new ArrayList<Integer>();
    HMapIF index2ProbMap = new HMapIF();

    float sumOfProbs = 0.0f;    //only extract the top K<15 if the mass prob. exceeds MAX_probThreshold
    while(!topTrans.isEmpty() && sumOfProbs < cumProbThreshold){
      PairOfFloatString e = topTrans.pollLast();
      String term = e.getRightElement();
      float pr = e.getLeftElement()/cumProb;    // normalize
      logger.debug(term+"-->"+pr);
      int trgIndex = trgVocab.addOrGet(term);
      sumOfProbs += e.getLeftElement();         // keep track of unnormalized cumulative prob for determining cutoff
      sortedIndices.add(trgIndex);
      index2ProbMap.put(trgIndex, pr);
    }

    // to enable faster access with binary search, we sort entries by vocabulary index.
    Collections.sort(sortedIndices);
    int numEntries = sortedIndices.size();

    // for statistics only
    stats.update(numEntries, sumOfProbs);

    // write translation list to TTable object
    int[] indices = new int[numEntries];
    float[] probs = new float[numEntries];
    int i=0;
    for(int sortedIndex : sortedIndices){
      indices[i]=sortedIndex;
      probs[i]=index2ProbMap.get(sortedIndex);
      i++;
    }     
    table.set(curIndex, new IndexedFloatArray(indices, probs, true));
  }
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    DocumentVectorSlidingWindow generator = new DocumentVectorSlidingWindow(env, fs);

    //Parse queries, judgemnts and features
    HMapIV<String> parsedQueries = QueryUtility.loadQueries(queryPath);
    HMapIV<int[]> queries = QueryUtility.queryToIntegerCode(env, parsedQueries);
    HMapIF idfs = QueryUtility.loadIdf(env, parsedQueries);
    HMapIF cfs = QueryUtility.loadCf(env, parsedQueries);
    HMapIV<int[]> qrels = QrelUtility.parseQrelsFromTabDelimited(qrelPath);
    Map<String, Feature> featuresMap = FeatureUtility.parseFeatures(featurePath);
    Feature[] features = new Feature[featuresMap.size()];
    int index = 0;
    for(String key: featuresMap.keySet()) {
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    DocumentVectorOnTheFlyIndexing generator = new DocumentVectorOnTheFlyIndexing(env, fs);

    //Parse queries, judgemnts and features
    HMapIV<String> parsedQueries = QueryUtility.loadQueries(queryPath);
    HMapIV<int[]> queries = QueryUtility.queryToIntegerCode(env, parsedQueries);
    HMapIF idfs = QueryUtility.loadIdf(env, parsedQueries);
    HMapIF cfs = QueryUtility.loadCf(env, parsedQueries);
    HMapIV<int[]> qrels = QrelUtility.parseQrelsFromTabDelimited(qrelPath);
    Map<String, Feature> featuresMap = FeatureUtility.parseFeatures(featurePath);
    Feature[] features = new Feature[featuresMap.size()];
    int index = 0;
    for(String key: featuresMap.keySet()) {
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    RankAndFeaturesSmallAdaptive generator = new RankAndFeaturesSmallAdaptive(env, fs);

    //Parse queries and find integer codes for the query terms.
    HMapIV<String> parsedQueries = QueryUtility.loadQueries(queryPath);
    HMapIV<int[]> queries = QueryUtility.queryToIntegerCode(env, parsedQueries);
    HMapIF idfs = QueryUtility.loadIdf(env, parsedQueries);
    HMapIF cfs = QueryUtility.loadCf(env, parsedQueries);
    HMapIV<int[]> qrels = QrelUtility.parseQrelsFromTabDelimited(qrelPath);
    Map<String, Feature> featuresMap = FeatureUtility.parseFeatures(featurePath);
    Feature[] features = new Feature[featuresMap.size()];
    int index = 0;
    for(String key: featuresMap.keySet()) {
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                            (float) env.getDefaultDf(), (float) env.getDefaultCf());
  }

  private void preparePostings(String postingsPath) throws Exception {
    postings = new HMapIV<CompressedPositionalPostings>();
    dfs = new HMapII();
    docLengths = new HMapII();

    FSDataInputStream input = fs.open(new Path(postingsPath));
    int termid = input.readInt();
    while(termid != -1) {
      dfs.put(termid, input.readInt());
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