Examples of gnu.trove.TObjectDoubleIterator

gnu.trove.TObjectDoubleIterator

  }


  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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  // returns the sum of weights of all edges going out
  // 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());
    }
    
    // mu1 x p^{inj} + 0.5 * mu2 x \sum_j (p_{i}^{cont} W_{ij} + p_{j}^{cont} W_{ji}) + mu3

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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());
    }
    
    double denom = mu1 * (IsSeedNode() ? 1 : 0) +

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  // This is used in case of LGC
  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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    // default value, then keep the top scoring k labels as requested
    if (keepTopK != Integer.MAX_VALUE) {
      KeepTopScoringKeys(m, keepTopK);
    }


    TObjectDoubleIterator mi = m.iterator();
    double denom = 0;
    while (mi.hasNext()) {
      mi.advance();
      denom += mi.value();
    }
    // 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 class CollectionUtil2 {


  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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      return (Map2String(m, null));
  }


  public static String Map2String(TObjectDoubleHashMap m, RyanAlphabet a) {
    // String retString = "";
    TObjectDoubleIterator mIter = m.iterator();
    StringBuffer retBuffer = new StringBuffer();
    
    ArrayList<ObjectDoublePair> sortedMap = ReverseSortMap(m);
    int n = sortedMap.size();
    for (int i = 0; i < n; ++i) {

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    TObjectDoubleHashMap<String> seedLabels = new TObjectDoubleHashMap<String>();


    for (String vName : this._vertices.keySet()) {
      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()) {
        Object[] injLabels= this._labelManager.getLabelScores(v.GetInjectedLabelScores()).keys();

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    // get the average edge weight of the graph
    double avgEdgeWeight = GetAverageEdgeWeightSqrt();
    
    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);
        double newWeight = Math.exp((-1.0 * currWeight) / (2 * sigmaSquarred));

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upenn.junto.algorithm.mad_sketch.CollectionUtil2

upenn.junto.algorithm.mad_sketch.Graph2

upenn.junto.algorithm.mad_sketch.Vertex2

java.util.ConcurrentModificationException

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