public Tuple <List <int>, double> gs(double b, List <int> range)
{
HashSet <int> seeds = new HashSet <int>();
List <int> seedSet = new List <int>();
//CELF Algorithm
PriorityQueue <VNode> pq = new PriorityQueue <VNode>(range.Count + 1, new VNodeComparer());
List <bool> update = new List <bool>();
foreach (int u in range)
{
VNode node = new VNode(u, bg.numS);
pq.Push(node);
}
for (int u = 0; u < bg.numV; ++u)
{
update.Add(false);
}
double total_gain = 0.0;
while (b > 0.0 && pq.Count > 0)
{
for (int u = 0; u < bg.numV; ++u)
{
update[u] = false;
}
int next = 0;
double gain = 0;
while (true)
{
VNode node = pq.Pop();
int max_u = node.id;
if (update[max_u])
{
next = max_u;
gain = node.val;
break;
}
else
{
double sum = 0;
foreach (int sid in bg.V2S[max_u])
{
sum += prob_edge[sid];
}
VNode n1 = new VNode(max_u, sum);
pq.Push(n1);
update[max_u] = true;
}
}
b -= 1.0;
total_gain += gain;
ChangeAllocation(next, 1.0);
seeds.Add(next);
seedSet.Add(next);
}
foreach (int point in seedSet)
{
ChangeAllocation(point, 0.0);
}
return(new Tuple <List <int>, double>(seedSet, total_gain * bg.numV / bg.numS));
}
//Given seed probability P, find the best k nodes that can maximize influence spread
public Tuple <List <int>, double> Greedy(int k, List <double> P)
{
HashSet <int> seeds = new HashSet <int> ();
List <int> seedSet = new List <int> ();
List <double> edgeW = new List <double> ();
for (int h = 0; h < numS; ++h)
{
edgeW.Add(1.0);
}
//CELF Algorithm
PriorityQueue <VNode> pq = new PriorityQueue <VNode> (numV + 1, new VNodeComparer());
List <bool> update = new List <bool> ();
for (int u = 0; u < numV; ++u)
{
VNode node = new VNode(u, numS);
pq.Push(node);
update.Add(false);
}
double total_gain = 0.0;
for (int i = 0; i < k; ++i)
{
for (int u = 0; u < numV; ++u)
{
update [u] = false;
}
int next = 0;
double gain = 0;
while (true)
{
VNode node = pq.Pop();
int max_u = node.id;
if (update [max_u])
{
next = max_u;
gain = node.val;
break;
}
else
{
double sum = 0;
if (i == 0)
{
sum = V2S[max_u].Count * P[max_u];
}
else
{
foreach (int sid in V2S[max_u])
{
sum += edgeW[sid] * P[max_u];
}
}
VNode n1 = new VNode(max_u, sum);
pq.Push(n1);
update [max_u] = true;
}
}
total_gain += gain;
foreach (int sid in V2S[next])
{
edgeW [sid] = edgeW [sid] * (1 - P [next]);
}
seeds.Add(next);
seedSet.Add(next);
}
return(new Tuple <List <int>, double> (seedSet, total_gain * numV / numS));
}