private void ProbabilityDependencyAnalysis()
{
Console.Write("Please enter the number of vertecies (Default = 24): ");
if (!int.TryParse(Console.ReadLine(), out this.initialVertexes))
{
this.initialVertexes = 24;
}
Console.Write("Please enter the number of realization (Default = 1): ");
if (!int.TryParse(Console.ReadLine(), out this.realizations))
{
this.realizations = 1;
}
Bounds <double, double> bounds = this.GetProbabilityBounds();
Dictionary <double, ICollection <double> > allResults = new Dictionary <double, ICollection <double> >();
for (var start = bounds.InitialValue; start <= bounds.MaxValue; start += bounds.Step)
{
var networks = new ERNetwork[this.realizations];
var results = new double[this.realizations];
allResults[start] = results;
var prob = start;
Parallel.For(0, this.realizations, new ParallelOptions {
MaxDegreeOfParallelism = this.parallel
}, i =>
{
var param = new Dictionary <GenerationParameter, object>
{
{ GenerationParameter.Probability, prob },
{ GenerationParameter.Vertices, this.initialVertexes }
};
networks[i] = (ERNetwork)AbstractNetwork.CreateNetworkByType(ModelType.ER, $"Prob_{prob}_Run_{i}",
ResearchType.Basic, GenerationType.Random, new Dictionary <ResearchParameter, object> {
}, param, AnalyzeOption.Degeneracy, ContainerMode.Fast);
networks[i].Generate();
networks[i].Analyze();
results[i] = (double)networks[i].NetworkResult.Result[AnalyzeOption.Degeneracy];
});
}
this.SaveProbResearchResult(allResults);
Console.WriteLine("Research is completed. You can start other experiment or close app.");
Console.WriteLine();
}
public void Init()
{
network = new ERNetwork(500, 2000);
}