// select a node according to degrees
public Integer SelectNode_PA() throws IOException {
HashMap<Integer, Double> node_degree = new HashMap<Integer, Double>();
for (int n : G.vertexSet()) {
node_degree.put(n, (double) G.degreeOf(n));
}
RandomProb rp = new RandomProb<Integer>();
Integer selected_node = (Integer) (rp.randomPro(node_degree));
return selected_node;
}
public static void main(String[] args) throws IOException {
System.out.println("Enter parameters: N p_w p_r steps:");
try {
BufferedReader reader = new BufferedReader(new InputStreamReader(System.in));
String paras[] = reader.readLine().split(" ");
N = Integer.parseInt(paras[0]);
p_w = Float.parseFloat(paras[1]);
p_r = Float.parseFloat(paras[2]);
steps = Integer.parseInt(paras[3]);
} catch (IOException e) {
System.out.println("Error reading from user");
}
long start = System.currentTimeMillis();
int simulations = 1;
for (int t = 1; t <= simulations; t++) {
// Initialization, generate an empty network of N nodes
EIM dynamic = new EIM();
G = new SimpleWeightedGraph<Integer, DefaultWeightedEdge>(DefaultWeightedEdge.class);
for (int i = 0; i < N; i++) G.addVertex(i);
String para = "EIM_" + Integer.toString(t);
String folder = "files/" + "Networks" + "/";
File f = new File(folder);
if (f.exists() == false) {
f.mkdirs();
}
// distribution of social space
socialposition = dynamic.uniform(N);
for (int s = 0; s < steps; s++) {
int v = random.nextInt(N);
// LA process - weighted random walk + link with social distance
dynamic.localattach(v);
// GA process
// no edges, create one random link
if (G.edgesOf(v).size() == 0) {
dynamic.globalattach(v);
} else {
float prob = random.nextFloat();
if (prob < p_r) dynamic.globalattach(v);
}
// ND process
int d = random.nextInt(N);
if (G.edgesOf(d).size() > 0) {
float prob = random.nextFloat();
if (prob < p_d) {
Set<DefaultWeightedEdge> edges = new HashSet(G.edgesOf(d));
G.removeAllEdges(edges);
}
}
if (s % 100000 == 0) {
System.out.print("Steps:" + Integer.toString(s) + " ");
System.out.print("Edges:");
System.out.print(G.edgeSet().size() + " ");
System.out.println(
"Avg_degree: "
+ Float.toString((float) G.edgeSet().size() * 2 / G.vertexSet().size()));
}
}
// delete isolate nodes
ArrayList<Integer> nodelist = new ArrayList<Integer>();
for (int node : G.vertexSet()) nodelist.add(node);
for (int node : nodelist) {
if (G.degreeOf(node) == 0) G.removeVertex(node);
}
System.out.print("Nodes:");
System.out.println(G.vertexSet().size());
System.out.print("Edges:");
System.out.println(G.edgeSet().size());
// get largest connected component
Statistics stat = new Statistics();
Graph G_LCC = stat.largestConnectedComponent(G);
ExportGraph export = new ExportGraph();
export.exportWPairs((SimpleWeightedGraph<Integer, DefaultWeightedEdge>) G_LCC, para, folder);
System.out.print("Nodes in LCC:");
System.out.println(G_LCC.vertexSet().size());
System.out.print("Edges in LCC:");
System.out.println(G_LCC.edgeSet().size());
System.out.println("Avg_degree: " + Double.toString(stat.avg_degree(G_LCC)));
System.out.println("Avg_clustering: " + Double.toString(stat.avg_clustering(G_LCC)));
System.out.println(
"Degree assortativity: " + Double.toString(stat.assortativityCoefficient(G_LCC)));
}
long elapsedTimeMillis = System.currentTimeMillis() - start;
float elapsedTimeHour = elapsedTimeMillis / (60 * 60 * 1000F);
System.out.print("Elapsed time: ");
System.out.print(elapsedTimeHour);
System.out.println(" hours.");
}
