diff --git a/src/algoritmos/DominatingSeed.java b/src/algoritmos/DominatingSeed.java
index bc4d4810ffec78ca1dd519d770a37042882b4243..f62ac8b089049f200f4adcfd3b84ce3ea3bced31 100644
--- a/src/algoritmos/DominatingSeed.java
+++ b/src/algoritmos/DominatingSeed.java
@@ -31,6 +31,7 @@ public class DominatingSeed implements SeedChooser<Actor> {
MinDominatingSet ds = new MinDominatingSet();
minSet = ds.fastGreedy(grafo);
+
System.out.println("|DS| = " + minSet.size());
if (minSet.size() < k) {
System.out.println("Erro: o cojunto domintante é menor que K");
@@ -66,7 +67,50 @@ public class DominatingSeed implements SeedChooser<Actor> {
return semente;
}
-
+
+ public HashSet<Actor> escolher2(int k) {
+ HashSet<Actor> semente = new HashSet<Actor>();
+ HashSet<Actor> minSet = new HashSet<Actor>();
+
+ MinDominatingSet ds = new MinDominatingSet();
+ minSet = ds.fastGreedy2(grafo);
+
+ System.out.println("|DS| = " + minSet.size());
+ if (minSet.size() < k) {
+ System.out.println("Erro: o cojunto domintante é menor que K");
+ return null;
+ }
+
+ // create priority queue of all nodes, with marginal gain delta +inf
+ PriorityQueue<MarginalGain> fila = priorityQueueOfGains(minSet);
+
+ double MaxSpread = 0;
+
+ while (semente.size() < k) {
+ // set all gains invalid
+ for (MarginalGain mg : fila) {
+ mg.setValid(false);
+ }
+
+ while (true) {
+ MarginalGain max = fila.poll();
+ if (max.isValid() == true) {
+ semente.add(max.getVertice());
+ MaxSpread = MaxSpread + max.getGain();
+ break;
+ } else {
+ double sigma = cascata(max.getVertice(), semente);
+ double delta = sigma - MaxSpread;
+ max.setGain(delta);
+ max.setValid(true);
+ fila.add(max);
+ }
+ }
+ }
+
+ return semente;
+ }
+
public HashSet<Actor> escolherGreedy(int k) {
HashSet<Actor> semente = new HashSet<Actor>();
HashSet<Actor> minSet = new HashSet<Actor>();
@@ -120,7 +164,7 @@ public class DominatingSeed implements SeedChooser<Actor> {
vertices[i++] = a;
Random rand = new Random();
- while (rSet.size() < vSet.size()/4) {
+ while (rSet.size() < vSet.size() / 3) {
rSet.add(vertices[rand.nextInt(vertices.length)]);
}
@@ -183,31 +227,36 @@ public class DominatingSeed implements SeedChooser<Actor> {
}
public static void main(String[] args) {
- DirectedSocialNetwork g = new SocialNetworkGenerate()
- .gerarGrafo(800, 2.5);
- HashSet<Actor> seed = new DominatingSeed(g).escolherGreedy(15);
-
- HashSet<Actor> ativos = g.indepCascadeDiffusion(seed);
+ DirectedSocialNetwork g = new SocialNetworkGenerate().gerarGrafo(2000,
+ 2.5);
+ long startTime = 0;
+ startTime = System.nanoTime();
+ HashSet<Actor> seed = new DominatingSeed(g).escolher2(15);
+ System.out.println("Tempo: " + (System.nanoTime() - startTime) / 1000);
+
+ HashSet<Actor> ativos = g.indepCascadeDiffusion(seed);
System.out.println("|V(G)| = " + g.vertexSet().size());
- System.out.println("|S| = " + seed.size());
- System.out.println("|A| = "+ativos.size());
- g.deactivate(ativos);
-// g.activate(seed);
-// g.visualize();
-
- HashSet<Actor> seed2 = new DominatingSeed(g).escolher(15);
-
- HashSet<Actor> ativos2 = g.indepCascadeDiffusion(seed2);
- System.out.println("\n|S| = " + seed2.size());
- System.out.println("|A| = "+ativos2.size());
- g.deactivate(ativos2);
-
- HashSet<Actor> seed3 = new DominatingSeed(g).escolherRandom(15);
-
- HashSet<Actor> ativos3 = g.indepCascadeDiffusion(seed3);
- System.out.println("\n|S| = " + seed3.size());
- System.out.println("|A| = "+ativos3.size());
-
+ // System.out.println("|S| = " + seed.size());
+ System.out.println("|A| = " + ativos.size());
+ g.deactivate(ativos);
+ // g.activate(seed);
+ // g.visualize();
+
+ startTime = System.nanoTime();
+ HashSet<Actor> seed2 = new DominatingSeed(g).escolher(15);
+ System.out.println("Tempo: " + (System.nanoTime() - startTime) / 1000);
+
+ HashSet<Actor> ativos2 = g.indepCascadeDiffusion(seed2);
+// System.out.println("\n|S| = " + seed2.size());
+ System.out.println("|A| = " + ativos2.size());
+ g.deactivate(ativos2);
+
+// HashSet<Actor> seed3 = new DominatingSeed(g).escolherRandom(15);
+//
+// HashSet<Actor> ativos3 = g.indepCascadeDiffusion(seed3);
+//// System.out.println("\n|S| = " + seed3.size());
+// System.out.println("|A| = "+ativos3.size());
+
}
}
diff --git a/src/algoritmos/MinDominatingSet.java b/src/algoritmos/MinDominatingSet.java
index 42d942df1b9aebc1157af2d27372f1739adb2610..b217840828b6e0f9a4c8a5284c859d5d031b6b3c 100644
--- a/src/algoritmos/MinDominatingSet.java
+++ b/src/algoritmos/MinDominatingSet.java
@@ -108,16 +108,45 @@ public class MinDominatingSet {
}
Set<Actor> dominados = new HashSet<>();
-
while (dominados.size() < n) {
+
Actor v = heapMinMax.removeLast();
- dominados.add(v);
Set<Actor> vizinhos = grafo.outNeighborsOf(v);
if (dominados.addAll(vizinhos)) {
dominante.add(v);
}
+ dominados.add(v);
+ }
+ return dominante;
+ }
+
+ public HashSet<Actor> fastGreedy2(DirectedSocialNetwork grafo) {
+ int n = grafo.vertexSet().size();
+
+ // DS <-- {}
+ HashSet<Actor> dominante = new HashSet<>();
+
+ // compare os vertices pelo grau
+ ComparaPorGrau comp = new ComparaPorGrau(grafo);
+
+ MinMaxPriorityQueue<Actor> fila = null;
+ fila = MinMaxPriorityQueue.orderedBy(comp).maximumSize(n)
+ .create();
+ for (Actor v : grafo.vertexSet()) {
+ fila.add(v);
+ }
+
+ Set<Actor> dominados = new HashSet<>();
+ while (!fila.isEmpty()) {
+ Actor v = fila.removeLast();
+ Set<Actor> vizinhos = grafo.outNeighborsOf(v);
+
+ if (dominados.addAll(vizinhos)) {
+ dominante.add(v);
+ }else
+ dominados.add(v);
}
return dominante;
}
@@ -125,7 +154,7 @@ public class MinDominatingSet {
public static void main(String[] args) {
DirectedSocialNetwork g = new SocialNetworkGenerate().gerarGrafo(
- 100, 2.5);
+ 5000, 2.5);
System.out.println("|V(G)| = " + g.vertexSet().size());
System.out.println("|E(G)| = " + g.edgeSet().size());
@@ -139,10 +168,10 @@ public class MinDominatingSet {
startTime = System.nanoTime();
HashSet<Actor> ds = (HashSet<Actor>) minDom.greedy(g);
System.out.println("Tempo: "+(System.nanoTime() - startTime)/1000);
- System.out.println("|DS|- GreedyPlus: " + ds.size());
+ System.out.println("|DS|- vRegularGreedy: " + ds.size());
System.out.println("\nspread: "+g.espectedSpread(ds, true));
- g.activate(ds);
- g.visualize();
+// g.activate(ds);
+// g.visualize();
startTime = System.nanoTime();
HashSet<Actor> ds2 = (HashSet<Actor>) minDom.regularGreedy(g);
@@ -159,13 +188,12 @@ public class MinDominatingSet {
HashSet<Actor> ds3 = minDom.fastGreedy(g);
// System.out.println("Tempo: "+(System.nanoTime() - startTime)/1000);
System.out.println("\n\n|DS|- FastGreedy: " + ds3.size());
- System.out.println("Vertices dominantes:");
// for (Actor v : ds3) {
// System.out.print(v.toString()+" ");
// }
System.out.println("\nspread: "+g.espectedSpread(ds3, true));
- g.activate(ds3);
- g.visualize();
+// g.activate(ds3);
+// g.visualize();
// HashSet<Actor> seed = new LazyGreedy(g).escolher(ds3.size());
// System.out.println("\nVertices Influentes: "+seed.size());
diff --git a/src/geradores/GeradorGrafoPowerLaw.java b/src/geradores/GeradorGrafoPowerLaw.java
index 969d7704e9b4a78561f09aa0ae4bea769f86c815..c7668d1cd14a4b9a4f37454ecf12e0a207b141a8 100644
--- a/src/geradores/GeradorGrafoPowerLaw.java
+++ b/src/geradores/GeradorGrafoPowerLaw.java
@@ -43,7 +43,7 @@ public class GeradorGrafoPowerLaw {
boolean direcionado) {
//Devido a futura remoção dos vertices isolados
if (direcionado) {
- n = (int) (n + n * 0.17);
+ n = (int) (n + n * 0.7);
}else
n = (int) (n + n * 0.5);
@@ -135,7 +135,7 @@ public class GeradorGrafoPowerLaw {
int n, double beta, boolean direcionado) {
if (direcionado) {
- n = (int) (n + n * 0.17);
+ n = (int) (n + n * 0.65);
}else
n = (int) (n + n * 0.5);
diff --git a/src/geradores/GeradorModeloGRG.java b/src/geradores/GeradorModeloGRG.java
index 2c847ee138c32bcb62350eb7ea3046c095e83fce..6d2f57629c9a3593c1c871d684e02dd570919773 100644
--- a/src/geradores/GeradorModeloGRG.java
+++ b/src/geradores/GeradorModeloGRG.java
@@ -122,7 +122,7 @@ public class GeradorModeloGRG {
if (Math.random() < p){
DefaultWeightedEdge e;
e = g.addEdge(vertices.get(i), vertices.get(j));
- g.setEdgeWeight(e, Math.random());
+ g.setEdgeWeight(e, peso());
}
}
}
@@ -135,7 +135,7 @@ public class GeradorModeloGRG {
if (Math.random() < p){
DefaultWeightedEdge e;
e = g.addEdge(vertices.get(i), vertices.get(j));
- g.setEdgeWeight(e, Math.random());
+ g.setEdgeWeight(e, peso());
}
}
}
@@ -143,4 +143,16 @@ public class GeradorModeloGRG {
}
return g;
}
+
+ public double peso() {
+
+ // int p = (int) (Math.random() * 3);
+ // double[] choice = { 0.2, 0.04, 0.008 };
+ // return choice[p];
+
+ // uniform IC model
+// return (double)10/100;
+// return 0.025;
+ return (Math.random())/4;
+ }
}
diff --git a/src/geradores/SocialNetworkGenerate.java b/src/geradores/SocialNetworkGenerate.java
index effd8c09331162ca494104627f4404287ba1d842..0f0d715dd6d78a078043e38253f5c94501e0baa8 100644
--- a/src/geradores/SocialNetworkGenerate.java
+++ b/src/geradores/SocialNetworkGenerate.java
@@ -20,6 +20,7 @@ import org.jgrapht.WeightedGraph;
import org.jgrapht.graph.DefaultEdge;
import org.jgrapht.graph.DefaultWeightedEdge;
+import plot.Histograma;
import util.ComponentesConexos;
public class SocialNetworkGenerate {
@@ -65,6 +66,18 @@ public class SocialNetworkGenerate {
return g;
}
+
+ public DirectedSocialNetwork gerarGrafoInteiro(int n, double beta,
+ boolean direcionado, boolean comPeso) {
+
+ WeightedGraph<Actor, DefaultWeightedEdge> grafo;
+ grafo = new GeradorGrafoPowerLaw().gerarComPesos(n, beta,
+ direcionado);
+
+ g = asDirectedSocialNetwork(grafo);
+
+ return g;
+ }
// Por padrão a rede resultante é direcionada e com pesos
public DirectedSocialNetwork gerarModeloIC(int n, double beta) {
@@ -114,5 +127,17 @@ public class SocialNetworkGenerate {
return sn;
}
-
+
+ public static void main(String[] args) {
+// DirectedSocialNetwork g = new SocialNetworkGenerate().gerarGrafo(50000, 2.5);
+ DirectedSocialNetwork g = new SocialNetworkGenerate().gerarGrafoInteiro(30000, 2.5, true, true);
+ System.out.println("|V(G)|"+g.vertexSet().size());
+ System.out.println("|E(G)|"+g.edgeSet().size());
+ Histograma histograma = new Histograma();
+ try {
+ histograma.plotarGraficos(histograma.gerarHistograma(g));
+ } catch (IOException e) {
+ e.printStackTrace();
+ }
+ }
}
diff --git a/src/readgraph/GraphReader.java b/src/readgraph/GraphReader.java
index a53d2ef484fe48d6cca05be6eb7489bcea15ee97..94f5531302fc91e50b62951957a44ddbc5f74fb3 100644
--- a/src/readgraph/GraphReader.java
+++ b/src/readgraph/GraphReader.java
@@ -63,7 +63,7 @@ public class GraphReader {
DefaultWeightedEdge e;
e = g.addEdge(vertices[v1], vertices[v2]);
if (e != null) {
- g.setEdgeWeight(e, trivalencyModel());
+ g.setEdgeWeight(e, peso());
}
}
}
@@ -79,18 +79,17 @@ public class GraphReader {
/**
* Sorteia um valor aleatório
- *
- * @return um número entre {0.2, 0.04, 0.008}
*/
- public double trivalencyModel() {
+ public double peso() {
// int p = (int) (Math.random() * 3);
// double[] choice = { 0.2, 0.04, 0.008 };
// return choice[p];
// uniform IC model
- return (double)10/100;
-// return Math.random();
+// return (double)10/100;
+// return 0.025;
+ return Math.random()/4;
}
public DirectedSocialNetwork readEpinions() {
diff --git a/src/simulacao/Simulacao.java b/src/simulacao/Simulacao.java
index ffed98f1fd8ae526286274aad68b0c9f18fccf37..f21f4db1912f124037618fcd61ac92a98986dbd1 100644
--- a/src/simulacao/Simulacao.java
+++ b/src/simulacao/Simulacao.java
@@ -4,8 +4,11 @@ import java.text.DateFormat;
import java.text.SimpleDateFormat;
import java.util.Date;
import java.util.HashSet;
+
import javax.media.j3d.PhysicalBody;
+import org.jgrapht.graph.DefaultWeightedEdge;
+
import plot.MeuPlot;
import readgraph.GraphReader;
import algoritmos.ArticulationSeed;
@@ -75,16 +78,102 @@ public class Simulacao {
outDir);
}
- private static void simularArtificial() {
- DirectedSocialNetwork g;
- g = new SocialNetworkGenerate().gerarGrafo(30000, 2.8);
- System.out.println("|V(G)| = " + g.vertexSet().size());
- System.out.println("|E(G)| = " + g.edgeSet().size());
-
- String outDir = "'plots/tex/";
-
- new Simulacao().simularIC(g, outDir);
+ public static void simularRandomGraphIC(int n, String outDir) {
+ double[] tamSemente = { 10, 20, 30, 40, 50 };
+ double[] sigma1 = new double[5], tempo1 = new double[5];
+ double[] sigma2 = new double[5], tempo2 = new double[5];
+ double[] sigma3 = new double[5], tempo3 = new double[5];
+ double[] sigma4 = new double[5], tempo4 = new double[5];
+ int k, repeticoes = 10;
+
+ double[] ssigma1 = new double[5], stempo1 = new double[5];
+ double[] ssigma2 = new double[5], stempo2 = new double[5];
+ double[] ssigma3 = new double[5], stempo3 = new double[5];
+ double[] ssigma4 = new double[5], stempo4 = new double[5];
+
+ for (int j = 0; j < repeticoes; j++) {
+ System.out.println("Grafo "+j);
+ DirectedSocialNetwork g;
+ g = new SocialNetworkGenerate().gerarGrafo(n * 1000, 2.5);
+ System.out.println("|V(G)| = " + g.vertexSet().size());
+ System.out.println("|E(G)| = " + g.edgeSet().size());
+ System.out.println();
+
+ long excutionTime = 0;
+ for (int i = 0; i < tamSemente.length; i++) {
+ k = (int) tamSemente[i];
+ System.out.println("\nTestando para k = " + k);
+
+ excutionTime = System.currentTimeMillis() * -1;
+ HashSet<Actor> seed1 = new DominatingSeed(g).escolher(k);
+ excutionTime += System.currentTimeMillis();
+ tempo1[i] = (excutionTime / 1000.0f);
+ sigma1[i] = g.espectedSpread(seed1, true);
+ System.out.println("DominatingSeed: sigma = " + sigma1[i]
+ + ", tempo = " + tempo1[i] + " segundos");
+ ssigma1[i] += sigma1[i];
+ stempo1[i] += tempo1[i];
+
+ /*excutionTime = System.currentTimeMillis() * -1;
+ HashSet<Actor> seed2 = new LazyGreedy(g).escolher(k);
+ excutionTime += System.currentTimeMillis();
+ tempo2[i] = (excutionTime / 1000.0f);
+ sigma2[i] = g.espectedSpread(seed2, true);
+ System.out.println("LazyGreedy: sigma = " + sigma2[i]
+ + ", tempo = " + tempo2[i] + " segundos");
+ ssigma2[i] += sigma2[i];
+ stempo2[i] += tempo2[i];*/
+
+ excutionTime = System.currentTimeMillis() * -1;
+ HashSet<Actor> seed2 = new DominatingSeed(g).escolher2(k);
+ excutionTime += System.currentTimeMillis();
+ tempo2[i] = (excutionTime / 1000.0f);
+ sigma2[i] = g.espectedSpread(seed2, true);
+ System.out.println("preSelect: sigma = " + sigma2[i]
+ + ", tempo = " + tempo2[i] + " segundos");
+ ssigma2[i] += sigma2[i];
+ stempo2[i] += tempo2[i];
+
+ excutionTime = System.currentTimeMillis() * -1;
+ HashSet<Actor> seed3 = new HightDegree(g).escolher(k);
+ excutionTime += System.currentTimeMillis();
+ tempo3[i] = (excutionTime / 1000.0f);
+ sigma3[i] = g.espectedSpread(seed3, true);
+ System.out.println("HighDegree: sigma = " + sigma3[i]
+ + ", tempo = " + tempo3[i] + " segundos");
+ ssigma3[i] += sigma3[i];
+ stempo3[i] += tempo3[i];
+
+ excutionTime = System.currentTimeMillis() * -1;
+ HashSet<Actor> seed4 = new RandomSeed(g).escolher(k);
+ excutionTime += System.currentTimeMillis();
+ tempo4[i] = (excutionTime / 1000.0f);
+ sigma4[i] = g.espectedSpread(seed4, true);
+ System.out.println("RandomSeed: sigma = " + sigma4[i]
+ + ", tempo = " + tempo4[i] + " segundos");
+ ssigma4[i] += sigma4[i];
+ stempo4[i] += tempo4[i];
+
+ }
+ }
+ // TODO tirar a média das 10 repetiçoes e plotar a media
+ for (int i = 0; i < tamSemente.length; i++) {
+ sigma1[i] = ssigma1[i] / repeticoes;
+ sigma2[i] = ssigma2[i] / repeticoes;
+ sigma3[i] = ssigma3[i] / repeticoes;
+ sigma4[i] = ssigma4[i] / repeticoes;
+
+ tempo1[i] = stempo1[i] / repeticoes;
+ tempo2[i] = stempo2[i] / repeticoes;
+ tempo3[i] = stempo3[i] / repeticoes;
+ tempo4[i] = stempo4[i] / repeticoes;
+ }
+ MeuPlot meuplot = new MeuPlot();
+ meuplot.plotPropagacao(tamSemente, sigma1, sigma2, sigma3, sigma4,
+ outDir);
+ meuplot.plotTempoExecucao(tamSemente, tempo1, tempo2, tempo3, tempo4,
+ outDir);
}
private static void simularPhy() {
@@ -124,17 +213,39 @@ public class Simulacao {
new Simulacao().simularIC(g, outDir);
}
+ private static void simularDblp() {
+ System.out.println("dblp.txt");
+ DirectedSocialNetwork g;
+ g = new GraphReader().readDblp();
+ System.out.println("|V(G)| = " + g.vertexSet().size());
+ System.out.println("|E(G)| = " + g.edgeSet().size());
+
+ String outDir = "'plots/dblp/";
+
+ new Simulacao().simularIC(g, outDir);
+
+ }
+
+ private static void simularArtificial() {
+ int i = 2;
+
+ while (i <= 4) {
+ String outDir = "'plots/rand/"+i+"/";
+ simularRandomGraphIC(i, outDir);
+ System.out.println("\t----------");
+ i = i * 2;
+ }
+ }
+
public static void main(String[] args) {
DateFormat dateFormat = new SimpleDateFormat("dd/MM/yyyy HH:mm:ss");
Date data = new Date();
System.out.println("Data de início: " + dateFormat.format(data));
-// simularArtificial();
-// System.out.println("Data de término: " + dateFormat.format(data));
- simularPhy();
- System.out.println("Data de término: " + dateFormat.format(data));
- simularEpinions();
- System.out.println("Data de término: " + dateFormat.format(data));
- simularHep();
- System.out.println("Data de término: " + dateFormat.format(data));
+ simularArtificial();
+ simularPhy();
+// simularEpinions();
+ simularHep();
+// simularDblp();
}
+
}