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;
}
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();
}
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;
}
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());
}
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;
}
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);
}
}
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;
});
}
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;
}
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;
}
}
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);
}
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);
}
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;
}
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));
}
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());
}
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;
}