public static void CoordinateDescentAlgCommonHyperGraphOneAlpha(Graph graph)
{
StreamReader nodetype = new StreamReader(filepath + "_typeo.txt");
StreamReader threshold = new StreamReader(filepath + "_tu.txt");
List <double> thresh = new List <double>();
for (int i = 0; i < graph.numV; i++)
{
thresh.Add(double.Parse(threshold.ReadLine()));
}
List <int> type = new List <int>();
for (int i = 0; i < graph.numV; i++)
{
int flag = int.Parse(nodetype.ReadLine());
if (flag == 0)
{
type.Add(0);
}
else if (flag == 1)
{
type.Add(2);
}
else
{
type.Add(1);
}
}
List <double> d = new List <double> {
0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0
};
List <double> cu = new List <double>();
for (int i = 0; i < graph.numV; i++)
{
double t = thresh[i];
double p = 0.0;
if (type[i] == 1)
{
p = System.Math.Pow(t, 0.5);
}
else if (type[i] == 2)
{
p = t;
}
else
{
p = 1 - System.Math.Pow(1 - t, 0.5);
}
foreach (double point in d)
{
if (point < p)
{
continue;
}
cu.Add(point);
break;
}
}
int mh = 0;
if (filepath.Contains("Wiki"))
{
mh = 250000;
}
else if (filepath.Contains("CA"))
{
mh = 2000000;
}
else if (filepath.Contains("dblp"))
{
mh = 20000000;
}
else
{
mh = 40000000;
}
double alpha = 1.0; // Step of c of searching the best discount in th Unified Discount Algorithm
while (alpha <= 1.0)
{
Bipartite bg = new Bipartite(filepath, alpha, graph.numV);
double b = 10.0;
while (b <= 10.0)
// Build a random hyper graph with mH random hyper edges.
{
StreamReader initial = new StreamReader(filepath + "_ini100.txt");
List <int> seed = new List <int>();
for (int i = 0; i < 100; i++)
{
seed.Add(int.Parse(initial.ReadLine()));
}
DateTime Hyper_start = DateTime.Now;
ICModel icm = new ICModel(alpha);
CoordinateDescent cd = new CoordinateDescent(graph, bg, seed, 0.0, type, 20, alpha, mh);
double bused = 0.0;
while (bused <= b)
{
int flag = seed[0];
double maxE = 0.0;
List <int> bestseed = new List <int>();
List <double> bestallo = new List <double>();
foreach (int u in seed)
{
List <int> nrlist = graph.newreach(new List <int> {
u
}, cd.x);
double b2cub1 = 5 * cu[u];
if (b2cub1 >= 0.5 && nrlist.Count >= 1)
{
Tuple <List <int>, List <double>, double> result1 = cd.bestone(nrlist, b2cub1);
if (result1.Item3 / cu[u] >= maxE / cu[flag])
{
maxE = result1.Item3;
flag = u;
bestseed = new List <int>();
foreach (int point in result1.Item1)
{
bestseed.Add(point);
}
bestallo = new List <double>();
foreach (double resource in result1.Item2)
{
bestallo.Add(resource);
}
}
}
if (b2cub1 >= 1.0 && nrlist.Count >= 2)
{
Tuple <List <int>, List <double>, double> result2 = cd.besttwo(nrlist, b2cub1);
if (result2.Item3 / cu[u] >= maxE / cu[flag])
{
maxE = result2.Item3;
flag = u;
bestseed = new List <int>();
foreach (int point in result2.Item1)
{
bestseed.Add(point);
}
bestallo = new List <double>();
foreach (double resource in result2.Item2)
{
bestallo.Add(resource);
}
}
}
if (b2cub1 >= 1.5 && nrlist.Count >= 3)
{
Tuple <List <int>, List <double>, double> result3 = cd.bestone(nrlist, b2cub1);
if (result3.Item3 / cu[u] >= maxE / cu[flag])
{
maxE = result3.Item3;
flag = u;
bestseed = new List <int>();
foreach (int point in result3.Item1)
{
bestseed.Add(point);
}
bestallo = new List <double>();
foreach (double resource in result3.Item2)
{
bestallo.Add(resource);
}
}
}
}
if (bused + cu[flag] > b)
{
break;
}
bused += cu[flag];
seed.Remove(flag);
List <int> maxnr = graph.newreach(new List <int> {
flag
}, cd.x);
for (int u = 0; u < bestseed.Count; u++)
{
if (bused + bestallo[u] > b)
{
break;
}
cd.ChangeAllocation(bestseed[u], bestallo[u]);
cd.x.Add(bestseed[u]);
bused += bestallo[u];
}
Console.WriteLine("newreach:" + Convert.ToString(cd.C.Sum()) + "total:" + Convert.ToString(bused));
}
DateTime Hyper_end = DateTime.Now;
double Hyper_time = (Hyper_end - Hyper_start).TotalMilliseconds;
Hyper_start = DateTime.Now;
List <double> prob = new List <double>();
foreach (int u in cd.x)
{
prob.Add(cd.SeedProb(u, cd.C[u]));
}
Tuple <double, double> results = icm.InfluenceSpread(graph, cd.x, prob, 200);
Hyper_end = DateTime.Now;
FileStream outfile = new FileStream(filepath + "_8o.txt", FileMode.Append);
StreamWriter writer = new StreamWriter(outfile);
writer.Write("Choose time:" + Hyper_time + "\t");
Hyper_time = (Hyper_end - Hyper_start).TotalMilliseconds;
string mem = Convert.ToString(Process.GetCurrentProcess().WorkingSet64 / 8 / 1024 / 1024);
writer.Write("Propagation time:" + Hyper_time + "\t");
writer.Write("a:" + alpha + "\tb:" + b + "\tave:" + results.Item1 + "\tstd:" + results.Item2 + "\tmemory:" + mem + "\n");
writer.Flush();
writer.Close();
b += 10.0;
}
alpha += 0.2;
}
}
public static void CoordinateDescentAlgCommonHyperGraphOneAlpha(Graph graph)
{
StreamReader nodetype = new StreamReader(filepath + "_typeo.txt");
StreamReader threshold = new StreamReader(filepath + "_tu.txt");
List <double> thresh = new List <double>();
for (int i = 0; i < graph.numV; i++)
{
thresh.Add(double.Parse(threshold.ReadLine()));
}
List <int> type = new List <int>();
for (int i = 0; i < graph.numV; i++)
{
int flag = int.Parse(nodetype.ReadLine());
if (flag == 0)
{
type.Add(0);
}
else if (flag == 1)
{
type.Add(2);
}
else
{
type.Add(1);
}
}
List <double> d = new List <double> {
0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0
};
List <double> cu = new List <double>();
for (int i = 0; i < graph.numV; i++)
{
//cu.Add(1.0);
double t = thresh[i];
double p = 0.0;
if (type[i] == 1)
{
p = System.Math.Pow(t, 0.5);
}
else if (type[i] == 2)
{
p = t;
}
else
{
p = 1 - System.Math.Pow(1 - t, 0.5);
}
foreach (double point in d)
{
if (point < p)
{
continue;
}
cu.Add(point);
break;
}
}
int mh = 0;
if (filepath.Contains("Wiki"))
{
mh = 250000;
}
else if (filepath.Contains("CA"))
{
mh = 2000000;
}
else if (filepath.Contains("dblp"))
{
mh = 20000000;
}
else
{
mh = 40000000;
}
double alpha = 0.6; // Step of c of searching the best discount in th Unified Discount Algorithm
while (alpha <= 1.0)
{
Bipartite bg = new Bipartite(filepath, alpha, graph.numV);
double b = 10.0;
double ratio = 3.0;
while (b <= 50.0)
// Build a random hyper graph with mH random hyper edges.
{
StreamReader initial = new StreamReader(filepath + "_ini100.txt");
List <int> seed = new List <int>();
for (int i = 0; i < 100; i++)
{
seed.Add(int.Parse(initial.ReadLine()));
}
DateTime Hyper_start = DateTime.Now;
ICModel icm = new ICModel(alpha);
CoordinateDescent cd = new CoordinateDescent(graph, bg, seed, 0.0, type, 20, alpha, mh);
double bused = 0.0;
while (bused <= b)
{
int flag = seed[0];
double maxE = 0.0;
int circumstance = 0;
List <int> seedset = new List <int>();
foreach (int u in seed)
{
List <int> nrlist = graph.newreach(new List <int> {
u
}, cd.x);
double b2cub1 = ratio * cu[u];
Tuple <List <int>, double> choose = cd.gs(b2cub1, nrlist);
if (choose.Item2 / cu[u] >= maxE / cu[flag])
{
maxE = choose.Item2;
flag = u;
seedset = new List <int>();
foreach (int point in choose.Item1)
{
seedset.Add(point);
}
circumstance = 1;
}
b2cub1 = b2cub1 >= 1.0 ? 1.0 : b2cub1;
foreach (int v in nrlist)
{
double nowE = cd.singlepointgain(v, b2cub1);
if (nowE / cu[v] >= maxE / cu[flag])
{
maxE = nowE;
flag = u;
seedset = new List <int> {
v
};
circumstance = 2;
}
}
}
if (bused + cu[flag] > b)
{
break;
}
bused += cu[flag];
seed.Remove(flag);
List <int> maxnr = graph.newreach(new List <int> {
flag
}, cd.x);
if (circumstance <= 2)
{
foreach (int u in seedset)
{
double allocation = 0.0;
if (type[u] == 1)
{
allocation = 1.0;
}
else
{
allocation = 0.5;
}
//allocation = 1.0;
if (bused + allocation > b)
{
break;
}
cd.ChangeAllocation(u, allocation);
cd.x.Add(u);
Console.Write(Convert.ToString(u) + " ");
bused += allocation;
}
}
else
{
double allocation = cu[flag] * ratio;
allocation = allocation >= 1.0 ? 1.0 : allocation;
if (bused + allocation > b)
{
break;
}
cd.ChangeAllocation(seedset[0], allocation);
cd.x.Add(seedset[0]);
Console.Write(Convert.ToString(seedset[0]) + " ");
bused += allocation;
}
Console.WriteLine("newreach:" + Convert.ToString(cd.C.Sum()) + "total:" + Convert.ToString(bused));
}
DateTime Hyper_end = DateTime.Now;
double Hyper_time = (Hyper_end - Hyper_start).TotalMilliseconds;
Console.WriteLine(cd.x.Count);
Hyper_start = DateTime.Now;
List <double> prob = new List <double>();
foreach (int u in cd.x)
{
prob.Add(cd.SeedProb(u, cd.C[u]));
}
Tuple <double, double> results = icm.InfluenceSpread(graph, cd.x, prob, 200);
Hyper_end = DateTime.Now;
FileStream outfile = new FileStream(filepath + "_7o.txt", FileMode.Append);
StreamWriter writer = new StreamWriter(outfile);
writer.Write("Choose time:" + Hyper_time + "\t");
Hyper_time = (Hyper_end - Hyper_start).TotalMilliseconds;
string mem = Convert.ToString(Process.GetCurrentProcess().WorkingSet64 / 8 / 1024 / 1024);
writer.Write("Propagation time:" + Hyper_time + "\t");
writer.Write("a:" + alpha + "\tb:" + b + "\tave:" + results.Item1 + "\tstd:" + results.Item2 + "\tmemory:" + mem + "\n");
writer.Flush();
writer.Close();
b += 10.0;
}
alpha += 0.2;
}
}
public static void CoordinateDescentAlgCommonHyperGraphOneAlpha(Graph graph)
{
StreamReader initial = new StreamReader(filepath + "_ini100.txt");
StreamReader nodetype = new StreamReader(filepath + "_typeo.txt");
List <int> type = new List <int>();
for (int i = 0; i < graph.numV; i++)
{
int flag = int.Parse(nodetype.ReadLine());
if (flag == 0)
{
type.Add(0);
}
else if (flag == 1)
{
type.Add(2);
}
else
{
type.Add(1);
}
}
List <int> seed = new List <int>();
for (int i = 0; i < 100; i++)
{
seed.Add(int.Parse(initial.ReadLine()));
}
int mh = 0;
if (filepath.Contains("Wiki"))
{
mh = 250000;
}
else if (filepath.Contains("CA"))
{
mh = 2000000;
}
else if (filepath.Contains("dblp"))
{
mh = 20000000;
}
else
{
mh = 40000000;
}
double alpha = 0.6; // Step of c of searching the best discount in th Unified Discount Algorithm
while (alpha <= 0.6)
{
Bipartite bg = new Bipartite(filepath, alpha, graph.numV);
int b1 = 5;
while (b1 <= 5)
// Build a random hyper graph with mH random hyper edges.
{
DateTime Hyper_start = DateTime.Now;
ICModel icm = new ICModel(alpha);
int count = Convert.ToInt16(1.5 * Convert.ToDouble(b1));
List <int> seed1 = graph.findlarge(seed, count);
CoordinateDescent cd1 = new CoordinateDescent(graph, bg, seed, seed1, 0.66667, type, 50, alpha, mh);
Random random = new Random();
int b2 = 25;
count = Convert.ToInt16(1.5 * Convert.ToDouble(b2));
int i1 = 0;
while (i1 < 5)
{
i1++;
int i = seed1[random.Next(0, seed1.Count)];
if (Math.Abs(1.0 - cd1.C[i]) < GlobalVar.epsilon)
{
continue;
}
int j = seed1[random.Next(0, seed1.Count)];
if ((i == j) || Math.Abs(1.0 - cd1.C[j]) < GlobalVar.epsilon)
{
continue;
}
double bp = cd1.C[i] + cd1.C[j];
double left = (bp - 1 > 0.0) ? (bp - 1) : 0.0;
double right = (bp < 1.0) ? bp : 1.0;
if (left >= right)
{
continue;
}
double sumns = 0.0, sumnsi = 0.0, sumnsj = 0.0, sumnsij = 0.0;
for (int i2 = 0; i2 < 5; i2++)
{
List <int> realize = new List <int>();
foreach (int u in seed1)
{
if ((u == i) || (u == j))
{
continue;
}
if (random.NextDouble() < cd1.SeedProb(u, cd1.C[u]))
{
realize.Add(u);
}
}
List <int> ns = graph.newreach(realize, seed);
List <int> seed2 = graph.findlarge(ns, count);
CoordinateDescent cd2 = new CoordinateDescent(graph, bg, ns, seed2, 0.66667, type, 10, alpha, mh);
List <double> cns = cd2.IterativeMinimize();
double qns = cd2.expectation();
sumns += qns;
realize.Add(i);
ns = graph.newreach(realize, seed);
seed2 = graph.findlarge(ns, count);
cd2 = new CoordinateDescent(graph, bg, ns, seed2, cns, type, 10, alpha, mh);
List <double> cnsi = cd2.IterativeMinimize();
double qnsi = cd2.expectation();
sumnsi += qnsi;
realize.Remove(i); realize.Add(j);
ns = graph.newreach(realize, seed);
seed2 = graph.findlarge(ns, count);
cd2 = new CoordinateDescent(graph, bg, ns, seed2, cns, type, 10, alpha, mh);
List <double> cnsj = cd2.IterativeMinimize();
double qnsj = cd2.expectation();
sumnsj += qnsj;
realize.Add(i);
ns = graph.newreach(realize, seed);
seed2 = graph.findlarge(ns, count);
if (qnsi > qnsj)
{
cd2 = new CoordinateDescent(graph, bg, ns, seed2, cnsi, type, 10, alpha, mh);
}
else
{
cd2 = new CoordinateDescent(graph, bg, ns, seed2, cnsj, type, 10, alpha, mh);
}
List <double> cnsij = cd2.IterativeMinimize();
double qnsij = cd2.expectation();
sumnsij += qnsij;
}
cd1.PairMinimize(i, j, sumnsi - sumns, sumnsi - sumns, sumns + sumnsij - sumnsi - sumnsj, bp, left, right);
}
DateTime Hyper_end = DateTime.Now;
double Hyper_time = (Hyper_end - Hyper_start).TotalMilliseconds;
Hyper_start = DateTime.Now;
seed1 = cd1.Realize();
List <int> nx = graph.newreach(seed1, seed);
List <int> s = graph.findlarge(nx, count);
CoordinateDescent cd = new CoordinateDescent(graph, bg, nx, s, 0.6667, type, 10, alpha, mh);
cd.IterativeMinimize();
List <double> prob = new List <double>();
for (int i = 0; i < nx.Count; i++)
{
prob.Add(cd.SeedProb(nx[i], cd.C[nx[i]]));
}
Tuple <double, double> results = icm.InfluenceSpread(graph, nx, prob, 200);
Hyper_end = DateTime.Now;
FileStream outfile = new FileStream(filepath + "_4o.txt", FileMode.Append);
StreamWriter writer = new StreamWriter(outfile);
writer.Write("Choose time:" + Hyper_time + "\t");
Hyper_time = (Hyper_end - Hyper_start).TotalMilliseconds;
string mem = Convert.ToString(Process.GetCurrentProcess().WorkingSet64 / 8 / 1024 / 1024);
writer.Write("Propagation time:" + Hyper_time + "\t");
writer.Write("a:" + alpha + "\tb:" + (b1 + b2) + "\tave:" + results.Item1 + "\tstd:" + results.Item2 + "\tmemory:" + mem + "\n");
writer.Flush();
writer.Close();
b1 += 2;
}
alpha += 0.0;
}
}
//public static string filepath = "D:/iiot/csharp/im/Wiki-Vote";
public static void Main(string[] args)
{
Graph graph = new Graph(filepath + ".csv");
int mh = 0;
if (filepath.Contains("Wiki"))
{
mh = 250000;
}
else if (filepath.Contains("CA"))
{
mh = 2000000;
}
else if (filepath.Contains("dblp"))
{
mh = 20000000;
}
else
{
mh = 40000000;
}
double alpha = 0.6; // Step of c of searching the best discount in th Unified Discount Algorithm
while (alpha <= 0.6)
{
Bipartite bg = new Bipartite(filepath, alpha, graph.numV);
double b = 10.0;
double ratio = 4.0;
while (b <= 50.0)
// Build a random hyper graph with mH random hyper edges.
{
StreamReader initial = new StreamReader(filepath + "_ini100.txt");
List <int> seed = new List <int>();
List <int> final = new List <int>();
for (int i = 0; i < 100; i++)
{
seed.Add(int.Parse(initial.ReadLine()));
}
DateTime Hyper_start = DateTime.Now;
ICModel icm = new ICModel(alpha);
CoordinateDescent cd = new CoordinateDescent(graph, bg, seed, 0.0, 10, alpha, mh);
double bused = 0.0;
while (bused <= b)
{
int flag = seed[0];
double maxE = 0.0;
List <int> seedset = new List <int>();
foreach (int u in seed)
{
List <int> nrlist = graph.newreach(new List <int> {
u
}, cd.x);
double b2cub1 = ratio;
Tuple <List <int>, double> choose = cd.gs(b2cub1, nrlist);
if (choose.Item2 >= maxE)
{
maxE = choose.Item2;
flag = u;
seedset = new List <int>();
foreach (int point in choose.Item1)
{
seedset.Add(point);
}
}
}
if (bused + 1.0 > b)
{
break;
}
bused += 1.0;
seed.Remove(flag);
foreach (int u in seedset)
{
if (bused + 1.0 > b)
{
break;
}
cd.ChangeAllocation(u, 1.0);
cd.x.Add(u);
final.Add(u);
Console.Write(Convert.ToString(u) + " ");
bused += 1.0;
}
Console.WriteLine("newreach:" + Convert.ToString(cd.C.Sum()) + "total:" + Convert.ToString(bused));
}
DateTime Hyper_end = DateTime.Now;
double Hyper_time = (Hyper_end - Hyper_start).TotalMilliseconds;
Console.WriteLine(final.Count);
Hyper_start = DateTime.Now;
Tuple <double, double> results = icm.InfluenceSpread(graph, final, 20000, 0.7);
Hyper_end = DateTime.Now;
FileStream outfile = new FileStream(filepath + "_9n.txt", FileMode.Append);
StreamWriter writer = new StreamWriter(outfile);
writer.Write("Choose time:" + Hyper_time + "\t");
Hyper_time = (Hyper_end - Hyper_start).TotalMilliseconds;
string mem = Convert.ToString(Process.GetCurrentProcess().WorkingSet64 / 8 / 1024 / 1024);
writer.Write("Propagation time:" + Hyper_time + "\t");
writer.Write("a:" + alpha + "\tb:" + b + "\tave:" + results.Item1 + "\tstd:" + results.Item2 + "\tmemory:" + mem + "\n");
writer.Flush();
writer.Close();
b += 10.0;
}
alpha += 0.2;
}
}
public static void CoordinateDescentAlgCommonHyperGraphOneAlpha(Graph graph)
{
StreamReader nodetype = new StreamReader(filepath + "_typeo.txt");
StreamReader threshold = new StreamReader(filepath + "_tu.txt");
List <double> thresh = new List <double>();
for (int i = 0; i < graph.numV; i++)
{
thresh.Add(double.Parse(threshold.ReadLine()));
}
List <int> type = new List <int>();
for (int i = 0; i < graph.numV; i++)
{
int flag = int.Parse(nodetype.ReadLine());
if (flag == 0)
{
type.Add(0);
}
else if (flag == 1)
{
type.Add(2);
}
else
{
type.Add(1);
}
}
List <double> d = new List <double> {
0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0
};
List <double> cu = new List <double>();
for (int i = 0; i < graph.numV; i++)
{
double t = thresh[i];
double p = 0.0;
if (type[i] == 1)
{
p = System.Math.Pow(t, 0.5);
}
else if (type[i] == 2)
{
p = t;
}
else
{
p = 1 - System.Math.Pow(1 - t, 0.5);
}
foreach (double point in d)
{
if (point < p)
{
continue;
}
cu.Add(point);
break;
}
}
int mh = 0;
if (filepath.Contains("Wiki"))
{
mh = 250000;
}
else if (filepath.Contains("CA"))
{
mh = 2000000;
}
else if (filepath.Contains("dblp"))
{
mh = 20000000;
}
else
{
mh = 40000000;
}
double alpha = 1.0; // Step of c of searching the best discount in th Unified Discount Algorithm
while (alpha <= 1.0)
{
Bipartite bg = new Bipartite(filepath, alpha, graph.numV);
double btotal = 30.0;
List <double> ratio = new List <double> {
1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0
};
while (btotal <= 30.0)
// Build a random hyper graph with mH random hyper edges.
{
foreach (double r in ratio)
{
double b1 = btotal / (1.0 + r);
StreamReader initial = new StreamReader(filepath + "_ini100.txt");
List <int> seed = new List <int>();
for (int i = 0; i < 100; i++)
{
seed.Add(int.Parse(initial.ReadLine()));
}
DateTime Hyper_start = DateTime.Now;
ICModel icm = new ICModel(alpha);
CoordinateDescent cd = new CoordinateDescent(graph, bg, seed, 0.0, type, 10, alpha, mh);
double b1used = 0.0;
while (b1used < b1)
{
int flag = seed[0];
double maxE = 0.0;
List <double> maxC = new List <double>();
foreach (int u in seed)
{
List <int> nrlist = graph.newreach(new List <int> {
u
}, cd.x);
double b2cub1 = r * cu[u];
int count = Convert.ToInt16(Math.Ceiling(1.5 * b2cub1));
double init_c = b2cub1 / Convert.ToDouble(count);
List <int> choose = graph.findlarge(nrlist, count);
foreach (int v in choose)
{
cd.ChangeAllocation(v, init_c);
}
cd.initNodes = nrlist;
cd.IterativeMinimize();
double nowE = cd.expectation();
if (nowE / cu[u] >= maxE / cu[flag])
{
flag = u;
maxE = nowE;
maxC = new List <double>();
for (int pos = 0; pos < cd.C.Count; pos++)
{
maxC.Add(cd.C[pos]);
}
}
foreach (int v in nrlist)
{
cd.ChangeAllocation(v, 0.0);
}
}
Console.WriteLine(cd.C.Sum());
b1used += cu[flag];
if (b1used > b1)
{
break;
}
seed.Remove(flag);
List <int> maxnr = graph.newreach(new List <int> {
flag
}, cd.x);
foreach (int u in maxnr)
{
cd.ChangeAllocation(u, maxC[u]);
cd.x.Add(u);
}
}
DateTime Hyper_end = DateTime.Now;
double Hyper_time = (Hyper_end - Hyper_start).TotalMilliseconds;
Hyper_start = DateTime.Now;
List <double> prob = new List <double>();
foreach (int u in cd.x)
{
prob.Add(cd.SeedProb(u, cd.C[u]));
}
Tuple <double, double> results = icm.InfluenceSpread(graph, cd.x, prob, 200);
Hyper_end = DateTime.Now;
FileStream outfile = new FileStream(filepath + "_6o.txt", FileMode.Append);
StreamWriter writer = new StreamWriter(outfile);
writer.Write("Choose time:" + Hyper_time + "\t");
Hyper_time = (Hyper_end - Hyper_start).TotalMilliseconds;
string mem = Convert.ToString(Process.GetCurrentProcess().WorkingSet64 / 8 / 1024 / 1024);
writer.Write("Propagation time:" + Hyper_time + "\t");
writer.Write("a:" + alpha + "\tb:" + btotal + "\tave:" + results.Item1 + "\tstd:" + results.Item2 + "\tmemory:" + mem + "ratio" + Convert.ToString(r) + "\n");
writer.Flush();
writer.Close();
}
btotal += 10.0;
}
alpha += 0.2;
}
}