public List <Point> Clusterize(VoronoiDiagramContext Context)
{
Neurons = NeurGen.GetNeurons(ClusterCount, Xrange, Yrange);
foreach (Point Point in Points)
{
double ClosestDistance = double.MaxValue;
int BestSoFar = -1;
for (int i = 0; i < ClusterCount; i++)
{
if (Neurons[i].CalculateDistanceFrom(Point) < ClosestDistance)
{
// Console.WriteLine("Distance from Neuron" + i.ToString() + Neurons[i].CalculateDistanceFrom(Point) );
BestSoFar = i;
ClosestDistance = Neurons[i].CalculateDistanceFrom(Point);
}
}
Clusters[BestSoFar].Add(Point);
//Console.WriteLine("Assigned to: " + BestSoFar.ToString());
}
;
for (int Iteration = 0; Iteration < MaxIters; Iteration++)
{
Point Err = new Point(Iteration, 0.0);
for (int i = 0; i < ClusterCount; i++)
{
{
Double ErrorComponent = 0.0;
Point Mean = CalculateMean(Clusters[i]);
ErrorComponent = Neurons[i].CalculateDistanceFrom(Mean);
Err.YCoordinate += ErrorComponent;
//if(Iteration == 0 || Iteration == 1) Console.WriteLine(i.ToString() + Neurons[i].GetAsPoint().XCoordinate + " " + Neurons[i].GetAsPoint().YCoordinate + " MEAN " + Mean.XCoordinate + " " + Mean.YCoordinate);
Neurons[i].UpdateWeight(Mean.XCoordinate, Mean.YCoordinate);
}
Error.Add(Err);
}
;
//reassign clusters;
for (int i = 0; i < ClusterCount; i++)
{
Clusters[i] = new List <Point>();
}
foreach (Point Point in Points)
{
double ClosestDistance = double.MaxValue;
int BestSoFar = -1;
for (int i = 0; i < ClusterCount; i++)
{
if (Neurons[i].CalculateDistanceFrom(Point) < ClosestDistance)
{
BestSoFar = i;
ClosestDistance = Neurons[i].CalculateDistanceFrom(Point);
}
}
Clusters[BestSoFar].Add(Point);
}
;
List <Point> Voro = new List <Point>();
foreach (Neuron Neuron in Neurons)
{
Voro.Add(Neuron.GetAsPoint());
}
VoronoiDiagram.CreateImage(Context, Voro).Save("KMEANS" + Iteration.ToString() + "Means" + ClusterCount.ToString() + ".png");
}
return(Error);
}
public void NeuronListSort(List <Neuron> Neurons)
{
Neuron Comparer = new Neuron(new double[] { 1.0, 2.0 });
Neurons.Sort();
}
