Package gnu.trove

Examples of gnu.trove.TObjectDoubleIterator.advance()

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  private double GetNeighborhoodEntropy(TObjectDoubleHashMap map) {
    double entropy = 0;
    //    TObjectDoubleIterator ni = neighbors_.iterator();
    TObjectDoubleIterator ni = map.iterator();
    while (ni.hasNext()) {
      ni.advance();
      entropy += -1 * ni.value() *
        Math.log(ni.value()) / Math.log(2);
    }
    return (entropy);
  }
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  // from the node.
  public double GetOutEdgeWeightSum() {
    double sum = 0;
    TObjectDoubleIterator ni = neighbors_.iterator();
    while (ni.hasNext()) {
      ni.advance();
      sum += ni.value();
    }
    return (sum);
  }
 
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  public double GetNormalizationConstant(Graph2 g, double mu1, double mu2, double mu3) {
    double mii = 0;
    double totalNeighWeight = 0;
    TObjectDoubleIterator nIter = neighbors_.iterator();
    while (nIter.hasNext()) {
      nIter.advance();
      totalNeighWeight += this.GetContinuationProbability() * nIter.value();
     
      Vertex2 neigh = g._vertices.get(nIter.key());
      totalNeighWeight += neigh.GetContinuationProbability() *
        neigh.GetNeighborWeight(this.GetName());
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  public double GetLCLPNormalizationConstant(Graph2 g, double mu1, double mu2, double mu3) {
    // sum_{u} W_uv^{2}, where u is the neighbor
    double totalNeighWeightSq = 0;
    TObjectDoubleIterator nIter = neighbors_.iterator();
    while (nIter.hasNext()) {
      nIter.advance();
      Vertex2 neigh = g._vertices.get(nIter.key());
      totalNeighWeightSq += neigh.GetNeighborWeight(this.GetName()) *
        neigh.GetNeighborWeight(this.GetName());
    }
   
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  public double GetNormalizationConstant2(Graph2 g, double mu1, double mu2, double mu3) {
    double mii = 0;
    double totalNeighWeight = 0;
    TObjectDoubleIterator nIter = neighbors_.iterator();
    while (nIter.hasNext()) {
      nIter.advance();
      totalNeighWeight += nIter.value();     
    }
   
    // mu1 x p^{inj} + 0.5 * mu2 x \sum_j (p_{i}^{cont} W_{ij} + p_{j}^{cont} W_{ji}) + mu3
    mii = mu1 * (IsSeedNode() ? 1 : 0) + /*0.5 **/ mu2 * totalNeighWeight + mu3;
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    }

    TObjectDoubleIterator mi = m.iterator();
    double denom = 0;
    while (mi.hasNext()) {
      mi.advance();
      denom += mi.value();
    }
    // assert (denom > 0);

    if (denom > 0) {
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    // assert (denom > 0);

    if (denom > 0) {
      mi = m.iterator();
      while (mi.hasNext()) {
        mi.advance();
        double newVal = mi.value() / denom;
        mi.setValue(newVal);
      }
    }
  }
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  public static ArrayList<ObjectDoublePair> ReverseSortMap(TObjectDoubleHashMap m) {
    ArrayList<ObjectDoublePair> lsps = new ArrayList<ObjectDoublePair>();

    TObjectDoubleIterator mi = m.iterator();
    while (mi.hasNext()) {
      mi.advance();
      lsps.add(new ObjectDoublePair(mi.key(), mi.value()));
    }

    ObjectDoublePairComparator lspComparator = new ObjectDoublePairComparator();
    Collections.sort(lsps, lspComparator);
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      Vertex2 v = this._vertices.get(vName);
      if (v.IsTestNode()) {
        TObjectDoubleIterator labelIter =
            this._labelManager.getLabelScores(v.GetGoldLabel()).iterator();
        while (labelIter.hasNext()) {
          labelIter.advance();
          testLabels.adjustOrPutValue((String) labelIter.key(), 1, 1);
        }
      }
     
      if (v.IsSeedNode()) {
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    for (String vName : this._vertices.keySet()) {
      Vertex2 v = this._vertices.get(vName);
      TObjectDoubleIterator nIter = v.GetNeighbors().iterator();
      while (nIter.hasNext()) {
        nIter.advance();
        String nName = (String) nIter.key();

        // we assume that the currently set distances are distance squares
        double currWeight = v.GetNeighborWeight(nName);
        double sigmaSquarred = Math.pow(sigmaFactor * avgEdgeWeight, 2);
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