public static double AverageWidth = 0.0; // Average Width each iteration
public static void InitializeKmeans(double[][] PointPositionINPUT, ParallelOptions _parallelOptionsINPUT, string FileName, int ClusterPosition, int FirstClusterValue, int StartingPosition,
int Ncent_GlobalINPUT, int MaxNcent_GlobalINPUT, int Ncent_Global_ParallelINPUT, int ParameterVectorDimensionINPUT, double CenterChangeINPUT, int IterationCutINPUT)
{
Kmeans.PointPosition = PointPositionINPUT;
Kmeans._parallelOptions = _parallelOptionsINPUT;
Kmeans.Ncent_Global = Ncent_GlobalINPUT;
Kmeans.MaxNcent_Global = MaxNcent_GlobalINPUT;
Kmeans.Ncent_Global_Parallel = Ncent_Global_ParallelINPUT;
Kmeans.KmeansCenterChangeCut = CenterChangeINPUT;
Kmeans.KmeansIterationCut = IterationCutINPUT;
Kmeans.ParameterVectorDimension = ParameterVectorDimensionINPUT;
Kmeans.SetParallelCenterDecomposition();
Kmeans.InitialPointAssignment = new int[DAVectorUtility.PointCount_Process];
if (FileName.Length == 0)
{
return;
}
// Read Initial Assignments
DAVectorUtility.SALSAPrint(0, "Kmeans Read File " + FileName + " Points " + DAVectorUtility.PointCount_Global.ToString() + " Starting at position "
+ StartingPosition.ToString() + " Dimension " + Kmeans.ParameterVectorDimension.ToString() + " Cluster Position " + ClusterPosition.ToString() + " Initial value " + FirstClusterValue.ToString());
Kmeans.ReadDataFromFile(FileName, ClusterPosition, FirstClusterValue, StartingPosition);
} // End InitializeKmeans
} // End SetupKmeans
public static void RunKmeans(double[][] ClusterCenterINPUT, int[] ClusterSizeINPUT, double[] ClusteRadiusINPUT,
out int Ncent_GlobalFINAL, out double AverageWidthFINAL)
{
ArrayList KeepPCfractions = new ArrayList(200);
ArrayList KeepCCfractions = new ArrayList(200);
// Inherit Solution arrays
Kmeans.ClusterCenter = ClusterCenterINPUT;
Kmeans.ClusterSize = ClusterSizeINPUT;
Kmeans.ClusterRadius = ClusteRadiusINPUT;
Kmeans.ClusterWidth = new double[Kmeans.MaxNcent_Global];
// Set up TriangleInequality
KmeansTriangleInequality.SetExternalFunctions(GetClusterRadius, GetClusterCenters, FindClusterCenters);
KmeansTriangleInequality.InitializeTriangleInequality(Kmeans.PointPosition, Kmeans._parallelOptions, Kmeans.ClusterCenter,
Kmeans.Ncent_Global, Kmeans.MaxNcent_Global, Kmeans.Ncent_Global_Parallel, Kmeans.ParameterVectorDimension);
DAVectorUtility.SALSAPrint(0, "Start Kmeans ****** Number of Centers " + Kmeans.Ncent_Global.ToString() + " Max Number of Centers " + Kmeans.MaxNcent_Global.ToString()
+ " Center Limit for Parallelism " + Kmeans.Ncent_Global_Parallel.ToString() + " Vector Dimension " + Kmeans.ParameterVectorDimension.ToString());
Kmeans.FindClusterCenters(true, Kmeans.InitialPointAssignment, null, null);
Kmeans.CountKmeansIterations = 0;
bool StartStop = false;
int CountStops = 0;
while (Kmeans.CountKmeansIterations < Kmeans.KmeansIterationCut)
{
double save1 = KmeansTriangleInequality.NumberFullDistancesCalculatedCC;
double save2 = KmeansTriangleInequality.NumberFullDistancesCalculatedPC;
KmeansTriangleInequality.NextIteration();
++Kmeans.CountKmeansIterations;
bool WillStop = false;
if (!StartStop)
{
if (Kmeans.AverageCenterChange < Kmeans.AverageRadius * Kmeans.KmeansCenterChangeCut)
{
StartStop = true;
}
}
else
{
++CountStops;
if (CountStops > 10)
{
WillStop = true;
}
}
double tmp1 = (KmeansTriangleInequality.NumberFullDistancesCalculatedCC - save1) / (double)Kmeans.MaxNcent_Global;
double tmp2 = (KmeansTriangleInequality.NumberFullDistancesCalculatedPC - save2) / ((double)Kmeans.MaxNcent_Global * (double)DAVectorUtility.PointCount_Global);
double tmp3 = KmeansTriangleInequality.NumberFullDistancesCalculatedPC / ((double)Kmeans.MaxNcent_Global * (double)(DAVectorUtility.PointCount_Global * Kmeans.CountKmeansIterations));
double tmp4 = (KmeansTriangleInequality.NumberFullDistancesCalculatedPC + KmeansTriangleInequality.NumberFullDistancesCalculatedCC) / ((double)Kmeans.MaxNcent_Global * (double)(DAVectorUtility.PointCount_Global * Kmeans.CountKmeansIterations));
DAVectorUtility.SALSAPrint(0, "Iteration " + Kmeans.CountKmeansIterations.ToString() + " Average Center Change " + Kmeans.AverageCenterChange.ToString("E4")
+ " Average Radius " + Kmeans.AverageRadius.ToString("E4") + " Average Width " + Kmeans.AverageWidth.ToString("E4")
+ " CC calcs per C " + tmp1.ToString("F4") + " PC calcs per P&C " + tmp2.ToString("F6")
+ " Cumul PC / Max " + tmp3.ToString("F6") + " Cumul PC+CC / PC Max " + tmp4.ToString("F6"));
KeepPCfractions.Add(tmp2);
KeepCCfractions.Add(tmp1 / DAVectorUtility.PointCount_Global);
if (((Kmeans.CountKmeansIterations % 10) == 1) || WillStop)
{
string message = " Sizes";
for (int CenterIndex = 0; CenterIndex < Kmeans.Ncent_Global; CenterIndex++)
{
message += " " + Kmeans.ClusterSize[CenterIndex].ToString();
}
DAVectorUtility.SALSAPrint(0, message);
}
if (WillStop)
{
break;
}
}
DAVectorUtility.SALSAPrint(0, "End Kmeans Iterations " + Kmeans.CountKmeansIterations.ToString() + " Iteration Cut " + Kmeans.KmeansIterationCut.ToString() +
" Average Center Change " + Kmeans.AverageCenterChange.ToString("E4") + " Average Radius " + Kmeans.AverageRadius.ToString("E4") +
" Average Width " + Kmeans.AverageWidth.ToString("E4") + " Fractional Cut " + Kmeans.KmeansCenterChangeCut.ToString("F4"));
KmeansTriangleInequality.PrintDiagnostics();
string messagePC = "\nPC Calcs per Point iteration";
string messageCC = "\nCC Calcs per Point iteration";
int numPC = KeepPCfractions.Count;
for (int linecount = 0; linecount < numPC; linecount++)
{
messagePC += " " + ((double)KeepPCfractions[linecount]).ToString("F4") + ",";
messageCC += " " + ((double)KeepCCfractions[linecount]).ToString("F4") + ",";
}
DAVectorUtility.SALSAPrint(0, messagePC);
DAVectorUtility.SALSAPrint(0, messageCC);
Ncent_GlobalFINAL = Kmeans.Ncent_Global;
AverageWidthFINAL = Kmeans.AverageWidth;
// Print Histograms
if (KmeansTriangleInequality.UseTriangleInequality != 0)
{
KmeansTriangleInequality.PlotPointHistograms(Math.Sqrt(AverageWidthFINAL));
KmeansTriangleInequality.PlotCenterHistograms(Math.Sqrt(AverageWidthFINAL));
}
return;
} // End RunKmeans()