public static double CalculateSingle(DistanceMeasurementTypes distanceMeasurement, List <double[]> firstClusterDatapoints, List <double[]> secondClusterDatapoints)
{
double min = double.MaxValue;
for (int i = 0; i < firstClusterDatapoints.Count(); i++)
{
for (int j = 0; j < secondClusterDatapoints.Count(); j++)
{
var firstDatapoint = firstClusterDatapoints[i];
var secondDatapoint = secondClusterDatapoints[j];
var distance = DistanceCalculationHelper.Calculate(distanceMeasurement, firstDatapoint, secondDatapoint);
if (distance < min)
{
min = distance;
}
}
}
return(min);
}
public static double CalculateComplete(DistanceMeasurementTypes distanceMeasurement, List <double[]> firstClusterDatapoints, List <double[]> secondClusterDatapoints)
{
double max = 0;
for (int i = 0; i < firstClusterDatapoints.Count(); i++)
{
for (int j = 0; j < secondClusterDatapoints.Count(); j++)
{
var firstDatapoint = firstClusterDatapoints[i];
var secondDatapoint = secondClusterDatapoints[j];
var distance = DistanceCalculationHelper.Calculate(distanceMeasurement, firstDatapoint, secondDatapoint);
if (distance > max)
{
max = distance;
}
}
}
return(max);
}
public double[,] CalculateSimilarity(List <double[]> data)
{
// Documentation :
// https://r-snippets.readthedocs.io/en/latest/real_analysis/metrics.html
var nbRow = data.Count();
double[,] c = new double[nbRow, nbRow];
for (int i = 0; i < nbRow; i++)
{
var firstVector = data.ElementAt(i);
for (int j = 0; j < nbRow; j++)
{
var secondVector = data.ElementAt(j);
double distance = DistanceCalculationHelper.Calculate(_options.DistanceMeasurement, firstVector, secondVector);
c[i, j] = distance;
}
}
return(c);
}
