示例#1
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void scn::GetDiameterAndAverageDistance(size_t &Diamter,double &APL,UGraph::pGraph graph)
{
   size_t sum = 0;
   size_t count = 0;
   size_t diameter = 0;
   std::unordered_map<size_t,size_t> distance;
   for(auto node = graph->begin(); node != graph->end(); node++)
   {
      RunSPFA(graph,*node,distance);
      //add distance except NaF
      for(auto iter = distance.begin(); iter != distance.end(); iter++)
      {
	     if(iter->first == *node)
	     continue;
		 if(iter->second < Graph::NaF)
	     {
	       sum += iter->second;
	       count++;
	       if(iter->second > diameter)
		  diameter = iter->second;
	    }
      }
   }
   //return make_pair(diameter, double(sum) / count);
   Diamter=diameter;
   APL=double(sum) / count;
}
示例#2
0
double scn::ComputeAverageDegree(UGraph::pGraph graph)
{
   double sum = 0;
   for(auto node = graph->begin(); node != graph->end(); node++)
   {
      sum += node->GetDegree();
   }
   return sum / graph->GetNumberOfNodes();
}
示例#3
0
double scn::GetBetweennessCentrality(UGraph::pGraph graph,size_t indexOfNode)
{
   double sum = 0;
   for(auto node1 = graph->begin(); node1 != graph->end(); node1++)
   {
      if(*node1 == indexOfNode)
	 continue;

      for(auto node2 = graph->begin(); node2 != graph->end(); node2++)
      {
	 if(*node2 == indexOfNode || node1 == node2)
	    continue;
	 //compute
	 auto result = GetNumberOfShortestPath(graph,*node1, *node2, indexOfNode);
	 sum += static_cast<double>(result.second) / 
	    static_cast<double>(result.first);
      }
   }
   return sum;
}
示例#4
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double scn::GetHideInfo(UGraph::pGraph graph,size_t indexOfNode)
{
   double sum = 0;
   for(auto node = graph->begin(); node != graph->end(); node++)
   {
      if(*node == indexOfNode)
	 continue;

      sum += GetSearchInfo(graph,*node, indexOfNode);
   }
   return sum / static_cast<double>(graph->GetNumberOfNodes());
}
示例#5
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size_t scn::GetDiameter(UGraph::pGraph graph)
{
   //auto& distance = distance_sssp;
   std::unordered_map<size_t,size_t> distance;
   size_t diameter = 0;
   distance.clear();
   for(auto node = graph->begin(); node != graph->end(); node++)
   {
      RunSPFA(graph,*node,distance);
      //search for the max distance except NaF
      
      for(auto other = graph->begin(); other != graph->end(); other++)
      {
	 if(distance[*other] > diameter && distance[*other] < Graph::NaF)
	 {
	    diameter = distance[*other];
	 }
      }
   }
   return diameter;
}
示例#6
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void scn::RunDjikstra(UGraph::pGraph graph,size_t indexOfSource,std::unordered_map<size_t,size_t> &distance)
{
   //auto& distance = distance_sssp;//using distance_sssp eariler
   assert(graph->HasNode(indexOfSource));
   //init
   //distance.reserve(graph->GetNumberOfNodes());
   for(auto node = graph->begin(); node != graph->end(); node++)
   {
      distance[*node] = Graph::NaF;
   }
   distance[indexOfSource] = 0;

   list<size_t> queue;
   //fill index of nodes into queue
   for(size_t i = 0; i < graph->GetNumberOfNodes(); i++)
   {
      queue.push_back(i);
   }
   //begin
   size_t next_distance;
   while(!queue.empty())
   {
      //get min one
      auto min = min_element(queue.begin(), queue.end(), 
			     [&](const size_t &one, const size_t &two)->bool
			     {
				if(distance[one] < distance[two])
				   return true;
				else
				   return false;
			     });
      auto node = graph->find(*min);  

      if(distance[*node] < Graph::NaF)
	 next_distance = distance[*node] + 1;
      else
	 next_distance = Graph::NaF;
      //relax neighbors
      for(auto other = node->begin(); other != node->end(); other++)
      {
	 if(distance[*other] > next_distance)
	 {
	    distance[*other] = next_distance;
	 } 
      }
      queue.erase(min);
   }
}
示例#7
0
void scn::GetDegreeDistribution(vector<pair<size_t, size_t>> &pairs,UGraph::pGraph graph)
{
   std::unordered_map<size_t,size_t> distribution;
   for(auto node = graph->begin(); node != graph->end(); node++)
   {
      distribution[node->GetDegree()]++;
   }
   //copy and sort
   pairs.assign(distribution.begin(), distribution.end());
   sort(pairs.begin(), pairs.end(), [&](const pair<size_t, size_t> &one, 
					const pair<size_t, size_t> &two)->bool
	{
	   if(one.first < two.first)
	      return true;
	   else
	      return false;
	});
}
示例#8
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double scn::GetEntropyOfDegreeDist(UGraph::pGraph graph)
{
   //get degree distribution
	std::unordered_map<size_t,size_t> distribution;
   for(auto node = graph->begin(); node != graph->end(); node++)
   {
      distribution[node->GetDegree()]++;
   }
   //compute the entropy
   double sum = 0;
   double pk = 0;
   for(auto iter = distribution.begin(); iter != distribution.end(); iter++)
   {
      pk = static_cast<double>(iter->second) / graph->GetNumberOfNodes();
      sum -= pk * log(pk)/log(2.0);
   }
   return sum;
}
示例#9
0
double scn::GetClusteringCoeff(UGraph::pGraph graph,size_t indexOfNode)
{
   if(indexOfNode == UGraph::NaF)
   {//the whole network
      double coefficient = 0;
      for(auto node = graph->begin(); node != graph->end(); node++)
      {
	 size_t numberOfTriangles = 0;
	 for(auto other1 = node->begin(); other1 != node->end(); other1++)
	 {
	    for(auto other2 = other1 + 1; other2 != node->end(); other2++)
	    {
	       if(graph->HasEdge(*other1, *other2))
		  numberOfTriangles++;
	    }
	 }
	 if(node->GetDegree()>1)
	 {
	 coefficient += 2 * static_cast<double>(numberOfTriangles) /
	    (node->GetDegree() * (node->GetDegree() - 1));
	 }
      }
      return coefficient / graph->GetNumberOfNodes();
   }
   else
   {//one vertex
      auto node = graph->find(indexOfNode);
      double numberOfTriangles = 0;
      for(auto other1 = node->begin(); other1 != node->end(); other1++)
      {
	 for(auto other2 = other1 + 1; other2 != node->end(); other2++)
	 {
	    if(graph->HasEdge(*other1, *other2))
	       numberOfTriangles++;
	 }
      }
	  if(node->GetDegree()>1)
      return 2 * numberOfTriangles / (node->GetDegree() * (node->GetDegree() - 1));
	  else
	  return 0.0;
   }
}
示例#10
0
double scn::GetPearsonCorrCoeff(UGraph::pGraph graph)
{
   size_t sum = 0;
   size_t product = 0;
   size_t square_sum = 0;
   for(auto i = graph->begin(); i != graph->end(); i++)
   {
      for(auto j = i + 1; j != graph->end(); j++)
      {
	 if(graph->HasEdge(*i, *j))
	 {
	    sum += i->GetDegree() + j->GetDegree();
	    product += i->GetDegree() * j->GetDegree();
	    square_sum += i->GetDegree() * i->GetDegree() + j->GetDegree() * j->GetDegree();
	 }
      }
   }
   double tmp = 1.0 / static_cast<double>(graph->GetNumberOfEdges());
   return (tmp * product - (tmp * sum) * (tmp * sum) / 4) /
      (tmp * square_sum / 2 - (tmp * sum) * (tmp * sum) / 4); 
}
示例#11
0
double scn::GetTransitivity(UGraph::pGraph graph)
{
   size_t numberOfTriangles = 0;
   size_t numberOfTriples = 0;
   for(auto node = graph->begin(); node != graph->end(); node++)
   {
      for(auto other1 = node->begin(); other1 != node->end(); other1++)
      {
	 for(auto other2= other1 + 1; other2 != node->end(); other2++)
	 {
	    if(graph->HasEdge(*other1, *other2))
	    {
	       numberOfTriangles++;
	    }
	 }
      }
      numberOfTriples += node->GetDegree() * (node->GetDegree() - 1) / 2;
   }
   return static_cast<double>(numberOfTriangles) / 
      static_cast<double>(numberOfTriples);
}
示例#12
0
double scn::GetGlobalEfficiency(UGraph::pGraph graph)
{
   double sum = 0;
   std::unordered_map<size_t,size_t> distance;
   //auto& distance = distance_sssp;
   distance.clear();
   for(auto node = graph->begin(); node != graph->end(); node++)
   {
      RunSPFA(graph,*node,distance);
      //add distance
      for(auto iter = distance.begin(); iter != distance.end(); iter++)
      {
	 if(iter->first == *node)
	    continue;

	 sum += 1.0 / static_cast<double>(iter->second);
      }
   }
   double size = static_cast<double>(graph->GetNumberOfNodes());
   return size * (size - 1) / sum;
}
示例#13
0
double scn::GetRichClubCoeff(UGraph::pGraph graph,size_t degree)
{
   IndexList setOfHighNode;//whose degree is greater than
                           //argument degree
   for(auto node = graph->begin(); node != graph->end(); node++)
   {
      if(node->GetDegree() > degree)
      {
	 setOfHighNode.push_back(*node);
      }
   }
   double sum = 0;
   for(auto one = setOfHighNode.begin(); one != setOfHighNode.end(); one++)
   {
      for(auto two = one + 1; two != setOfHighNode.end(); two++)
      {
	 if(graph->HasEdge(*one, *two))
	    sum++;
      }
   }
   return 2 * sum / static_cast<double>(setOfHighNode.size() * (setOfHighNode.size() - 1));
}
示例#14
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void scn::GetShortestDistanceDistribution(vector<pair<size_t, size_t>> &distribution,UGraph::pGraph graph)
{
   std::unordered_map<size_t,size_t> distance;
   std::unordered_map<size_t,size_t> tempdist;
   for(auto node = graph->begin(); node != graph->end(); node++)
   {
      RunSPFA(graph,*node,distance);
      //add distance except NaF
      for(auto iter = distance.begin(); iter !=distance.end(); iter++)
      {
	 if(iter->first == *node)
	    continue;

	 if(iter->second < Graph::NaF)
	 {
	    tempdist[iter->second]++;
	 }
      }
   }
   distribution.assign(tempdist.begin(),tempdist.end());
   sort(distribution.begin(), distribution.end());
}
示例#15
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void scn::GetClusteringDegreeCorre(pair<double, vector<pair<size_t, double>>> &correlation,UGraph::pGraph graph)
{
   unordered_map<size_t, double> degree_dist, degree_cc;
   //accumulate degree and clustering coefficient
   for(auto node = graph->begin(); node != graph->end(); node++)
   {
      degree_dist[node->GetDegree()]++;
      degree_cc[node->GetDegree()] += GetClusteringCoeff(graph,*node);
   }
   //get average
   double degree_average = 0;//1-order moment of degree
   double degree_sqr_average = 0;//2-order moment of degree
   for(auto iter = degree_dist.begin(); iter != degree_dist.end(); iter++)
   {
      //average clustering coefficient in each degree
      degree_cc[iter->first] /= iter->second;
      //probability of degree
      iter->second /= graph->GetNumberOfNodes();
      //1-order moment of degree
      degree_average += iter->first * iter->second;
      //2-order moment of degree
      degree_sqr_average += iter->first * iter->first * iter->second;
   }
   //compute global clustering degree correlation
   double clustering_degree_corre = 0;
   for(auto iter = degree_dist.begin(); iter != degree_dist.end(); iter++)
   {
      clustering_degree_corre += iter->first * (iter->first - 1) * iter->second
	 * degree_cc[iter->first];
   }
   clustering_degree_corre /= (degree_sqr_average - degree_average);
   //sort and get result
   correlation.second.assign(degree_cc.begin(), degree_cc.end());
   sort(correlation.second.begin(), correlation.second.end());
   correlation.first=clustering_degree_corre;
}