static void Main(string[] args)
        {
            bool Kmeans        = true;
            bool GasSwitch     = false;
            bool KohonenSwitch = false;

            Thread.CurrentThread.CurrentCulture = new CultureInfo("en-US");
            NeuronGenerator NeuralGenerator = new NeuronGenerator();
            Configuration   Configuration   = new Configuration();
            Pointparser     Parser          = new Pointparser();

            Parser.Filepath = "zestaw1.txt";
            double                InitialXRange             = 2.0;
            double                InitialYRange             = 2.0; //describes initial square (centered at 0,0) from which the neurons are generated
            List <Neuron>         Neurons                   = NeuralGenerator.GetNeurons(Configuration.GetAmountOfNeurons(), InitialXRange, InitialYRange);
            List <Point>          TrainingPointsList        = Parser.Parse();
            KohonenLearning       NeuralNetworkKohonenStyle = new KohonenLearning(Neurons, TrainingPointsList, Configuration);
            NeuralGas             NeuralNetworkGasStyle     = new NeuralGas(Neurons, TrainingPointsList, Configuration, NeuralGenerator);
            VoronoiDiagramContext DiagramContext            = new VoronoiDiagramContext
            {
                Width  = 1366,
                Height = 768,
                MinX   = TrainingPointsList.Min(point => point.XCoordinate) - 0.5,
                MaxX   = TrainingPointsList.Max(point => point.XCoordinate) + 0.5,
                MinY   = TrainingPointsList.Min(point => point.YCoordinate) - 0.5,
                MaxY   = TrainingPointsList.Max(point => point.YCoordinate) + 0.5,
            };

            if (KohonenSwitch)
            {
                for (int i = 0; i < 100; i++)
                {
                    if (i % 10 == 0)
                    {
                        Console.WriteLine("Progress o 10 %");
                    }
                    NeuralNetworkKohonenStyle.Train(i);
                    IEnumerable <Point> Points = NeuralNetworkKohonenStyle.ReturnNeuronsAsPoints();
                    VoronoiDiagram.CreateImage(DiagramContext, Points, TrainingPointsList).Save("Kohonen" + i.ToString("D3") + ".png");
                }
            }
            else if (GasSwitch)
            {
                for (int i = 0; i < 500; i++)
                {
                    if (i % 50 == 0)
                    {
                        Console.WriteLine("Progress o 10 %");
                    }
                    NeuralNetworkGasStyle.Train(i);
                    IEnumerable <Point> Points = NeuralNetworkGasStyle.ReturnNeuronsAsPoints();
                    VoronoiDiagram.CreateImage(DiagramContext, Points, TrainingPointsList).Save("NeuralGas" + i.ToString("D3") + ".png");
                }
            }
            else if (Kmeans)
            {
                KSrednie KMeans = new KSrednie(10, 10, 10, TrainingPointsList, 150);
                Parser.ParseOut(KMeans.Clusterize(DiagramContext));
            }
        }
Exemplo n.º 2
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 public NeuralGas(List <Neuron> ListOfNeurons, List <Point> ListOfPoints, Configuration Configuration, NeuronGenerator Generator)
 {
     this.Neurons = ListOfNeurons;
     this.Points  = ListOfPoints;
     this.SetParams(Configuration);
     this.Errors           = new List <Point>();
     ProximityFunctionType = new ProximityFunction(Metric.Euclidean, Proximity.Gauss).CalculateGasProximity;
     NeuronGen             = new NeuronGenerator();
 }
Exemplo n.º 3
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 public KSrednie(int ClusterCount, double Xrange, double Yrange, List <Point> Points, int Maxiters)
 {
     this.ClusterCount = ClusterCount;
     this.NeurGen      = new NeuronGenerator();
     this.Xrange       = Xrange;
     this.Yrange       = Yrange;
     this.Points       = Points;
     this.Clusters     = new Dictionary <int, List <Point> >();
     for (int i = 0; i < ClusterCount; i++)
     {
         Clusters.Add(i, new List <Point>());
     }
     this.Error    = new List <Point>();
     this.MaxIters = Maxiters;
 }