private void button2_Click(object sender, EventArgs e)
{
int N = int.Parse(textBox4.Text);
int N_init = int.Parse(textBox6.Text);
int E = int.Parse(textBox3.Text);;
BarabasiAlbertModel g = new BarabasiAlbertModel(N, false, false, N_init, E);
Data.RandomNetwork d = g.Generate();
if (radioButton6.Checked)
{
if (visualize)
{
var graphviz = new GraphvizAlgorithm <int, UndirectedEdge <int> >(d.MGraph);
string output = graphviz.Generate(new FileDotEngine(), "graph");
pictureBox2.ImageLocation = "graph.png";
}
label4.Text = string.Format(@"{0}", d.ClusteringCoefficient());
var degreeDistribuition = d.DegreeDistribuition();
ErdosDistribuitionDegreeChart.Titles.Add(new Title(RandomGraphStrings.DegreeChartTitle));
GenerateDegreeDistribuitionChart(chart1, degreeDistribuition);
}
if (radioButton5.Checked)
{
GenerateAveragePathLengthBarabasiChart(chart7, N, N_init, E);
GenerateClusteringCoefficientChartBarabasi(chart6, N, N_init, E);
}
}
private void button1_Click(object sender, EventArgs e)
{
int N = int.Parse(textBox1.Text);
int k = int.Parse(textBox5.Text);
//int iter = N;
double p = 0.0;
double.TryParse(textBox2.Text, NumberStyles.Any, CultureInfo.InvariantCulture, out p);
WattsStrogatzModel g = new WattsStrogatzModel(N, false, false, p, k);
Data.RandomNetwork d = g.Generate();
if (radioButton4.Checked)
{
if (visualize)
{
var graphviz = new GraphvizAlgorithm <int, UndirectedEdge <int> >(d.MGraph);
string output = graphviz.Generate(new FileDotEngine(), "graph");
pictureBox1.ImageLocation = "graph.png";
}
label4.Text = string.Format(@"{0}", d.ClusteringCoefficient());
var degreeDistribuition = d.DegreeDistribuition();
ErdosDistribuitionDegreeChart.Titles.Add(new Title(RandomGraphStrings.DegreeChartTitle));
GenerateDegreeDistribuitionChart(chart2, degreeDistribuition);
}
if (radioButton3.Checked)
{
GenerateAveragePathLengthWattsChart(chart4, N, k);
GenerateClusteringCoefficientChart(chart3, N, k);
}
}
private void GenerateAveragePathLengthBarabasiChart(Chart chart, int N, int Ninit, int Edges)
{
int iter = 20;
double max = 0;
double[] datax = new double[iter];
double[] datay = new double[iter];
chart.Series.Clear();
chart.Legends.Clear();
chart.Titles.Clear();
chart.ChartAreas.Clear();
BarabasiAlbertModel g;
for (int i = 0; i < iter; i++)
{
g = new BarabasiAlbertModel(N, false, false, Ninit, Edges * i);
Data.RandomNetwork d = g.Generate();
datay[i] = d.AveragePathLength();
datax[i] = (double)i / iter;
if (datay[i] > max)
{
max = datay[i];
}
Console.WriteLine("x : " + datax[i] + ", y : " + datay[i]);
}
ChartSeries(chart, datax, datay, "p = Avg Path Len", iter, N);
ChartAreas(chart, "Graph Avg Path Length", max);
ChartTitle(chart, "");
}
private void GenerateClusteringCoefficientChart(Chart chart, int N, int k)
{
int iter = 20;
double[] datax = new double[iter];
double[] datay = new double[iter];
chart.Series.Clear();
chart.Legends.Clear();
chart.Titles.Clear();
chart.ChartAreas.Clear();
WattsStrogatzModel g;
for (int i = 0; i < iter; i++)
{
//RandomGraph g = new RandomGraph(N, (double)i/iter);
g = new WattsStrogatzModel(N, false, false, (double)i / iter, k);
//ErdösRenyiModel g = new ErdösRenyiModel(N, (double)i / iter);
Data.RandomNetwork d = g.Generate();
datay[i] = d.ClusteringCoefficient();
datax[i] = (double)i / iter;
//Console.WriteLine("x : " + datax[i] + ", y : "+ datay[i]);
}
ChartSeries(chart, datax, datay, "p = Clust. Coeff.", iter, N);
ChartAreas(chart, "Graph Clustering Coefficient", 1);
ChartTitle(chart, "");
}
