public static void Run(Random rnd, int size, double edgeProb, int numOfNodes, string resultDir)
{
var globalVectorType = GlobalVectorType.Sum;
var epsilon = new ThresholdEpsilon(10);
var amountOfIterations = 500;
var initMatrix = GenerateMatrix(size, edgeProb, rnd);
var vectorLength = initMatrix.Count;
var fileName = $"SpectralGap_VectorLength_{vectorLength}_Nodes_{numOfNodes}_Iterations_{amountOfIterations}.csv";
var resultPath = Path.Combine(resultDir, fileName);
using (var resultCsvFile = File.CreateText(resultPath))
{
resultCsvFile.AutoFlush = true;
resultCsvFile.WriteLine(AccumaltedResult.Header(numOfNodes));
var multiRunner = MultiRunner.InitAll(SplitTo(initMatrix, size, numOfNodes, rnd), numOfNodes,
vectorLength, globalVectorType,
epsilon, SpectralGapFunction.MonitoredFunction);
multiRunner.OnlySchemes(new MonitoringScheme.Distance(2),
new MonitoringScheme.Value(),
new MonitoringScheme.Vector(),
new MonitoringScheme.Naive(),
new MonitoringScheme.Oracle());
var changes = GenerateChanges(initMatrix, numOfNodes, rnd).Take(amountOfIterations);
multiRunner.RunAll(changes, rnd, false)
.FinishAfter(multiRunner.Runners.Count, r => double.IsNegativeInfinity(r.LowerBound))
.Select(r => r.AsCsvString())
.ForEach((Action <string>)resultCsvFile.WriteLine);
}
Process.Start(resultPath);
}
public static void RunOnData(string graphPath, string resultDir)
{
var globalVectorType = GlobalVectorType.Sum;
var epsilon = new ThresholdEpsilon(10);
var numOfNodes = 2;
var fileName = $"SpectralGap__YoutubeGraph__Nodes_{numOfNodes}.csv";
var resultPath = Path.Combine(resultDir, fileName);
var operations = GraphParsing.ReadGraph(graphPath);
var initGraph = (GraphOperation.InitGraph)operations.First();
var numOfVerices = initGraph.NumOfVertices;
using (var resultCsvFile = File.CreateText(resultPath))
{
}
Process.Start(resultPath);
}
