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 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++) { //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 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; } }