/// <summary>
/// Perform an EM clustering on each plate independantely
/// </summary>
/// <param name="CurrentPlateToProcess">the plate to process</param>
/// <param name="ClassNumber">Number of class</param>
private void ClusteringEMSinglePlate(cPlate CurrentPlateToProcess, int ClassNumber, FormForEMInfo WindowEMinfo)
{
weka.core.Instances Ninsts = CurrentPlateToProcess.CreateInstancesWithoutClass();// CreateInstanceWithoutClass(CurrentTable);
weka.clusterers.EM EMCluster = new EM();
EMCluster.setNumClusters(ClassNumber);
EMCluster.setMaxIterations((int)WindowEMinfo.numericUpDownMaxIterations.Value);
EMCluster.setMinStdDev((double)WindowEMinfo.numericUpDownMinStdev.Value);
EMCluster.setSeed((int)WindowEMinfo.numericUpDownSeedNumber.Value);
EMCluster.buildClusterer(Ninsts);
EMCluster.getClusterModelsNumericAtts();
if (EMCluster.numberOfClusters() > cGlobalInfo.ListWellClasses.Count)
{
richTextBoxInfoClustering.AppendText("\n Plate " + CurrentPlateToProcess.GetName() + ", cluster Number: more than " + cGlobalInfo.ListWellClasses.Count + ", clustering not operated.\n");
return;
}
else
richTextBoxInfoClustering.AppendText("\n" + CurrentPlateToProcess.GetName() + ": " + EMCluster.numberOfClusters() + " cluster(s)");
ClusterEvaluation eval = new ClusterEvaluation();
eval.setClusterer(EMCluster);
eval.evaluateClusterer(Ninsts);
CurrentPlateToProcess.AssignClass(eval.getClusterAssignments());
}
/// <summary>
/// Perform an EM clustering on each plate independantely
/// </summary>
/// <param name="CurrentPlateToProcess">the plate to process</param>
/// <param name="ClassNumber">Number of class</param>
private void ClusteringEMSinglePlate(cPlate CurrentPlateToProcess, int ClassNumber, FormForEMInfo WindowEMinfo)
{
weka.core.Instances Ninsts = CurrentPlateToProcess.CreateInstancesWithoutClass();// CreateInstanceWithoutClass(CurrentTable);
if (Ninsts.numInstances() == 0)
{
MessageBox.Show("No active wells !", "Error", MessageBoxButtons.OK, MessageBoxIcon.Error);
return;
}
weka.clusterers.EM EMCluster = new EM();
EMCluster.setNumClusters(ClassNumber);
EMCluster.setMaxIterations((int)WindowEMinfo.numericUpDownMaxIterations.Value);
EMCluster.setMinStdDev((double)WindowEMinfo.numericUpDownMinStdev.Value);
EMCluster.setSeed((int)WindowEMinfo.numericUpDownSeedNumber.Value);
EMCluster.buildClusterer(Ninsts);
EMCluster.getClusterModelsNumericAtts();
if (EMCluster.numberOfClusters() > GlobalInfo.GetNumberofDefinedClass())
{
richTextBoxInfoClustering.AppendText("\n Plate " + CurrentPlateToProcess.Name + ", cluster Number: more than " + GlobalInfo.GetNumberofDefinedClass() + ", clustering not operated.\n");
return;
}
else
richTextBoxInfoClustering.AppendText("\n" + CurrentPlateToProcess.Name + ": " + EMCluster.numberOfClusters() + " cluster(s)");
ClusterEvaluation eval = new ClusterEvaluation();
eval.setClusterer(EMCluster);
eval.evaluateClusterer(Ninsts);
CurrentPlateToProcess.AssignClass(eval.getClusterAssignments());
}
/// <summary>
/// Perform an Hierarchical clustering on each plate independantely
/// </summary>
/// <param name="CurrentPlateToProcess">the plate to process</param>
/// <param name="ClassNumber">Number of class</param>
private void ClusteringHierarchicalSinglePlate(cPlate CurrentPlateToProcess, int ClassNumber)
{
weka.core.Instances Ninsts = CurrentPlateToProcess.CreateInstancesWithoutClass();
weka.clusterers.HierarchicalClusterer HClusterer = new HierarchicalClusterer();
//string OptionDistance = " -A \"weka.core.";
string OptionDistance = " -A \"";
switch (cGlobalInfo.OptionsWindow.comboBoxHierarchicalDistance.SelectedIndex)
{
case 0:
OptionDistance += "EuclideanDistance";
break;
case 1:
OptionDistance += "ManhattanDistance";
break;
case 2:
OptionDistance += "ChebyshevDistance";
break;
default:
break;
}
OptionDistance += " -R first-last\"";
string[] TAGS_LINK_TYPE = { "SINGLE", "COMPLETE", "AVERAGE", "MEAN", "CENTROID", "WARD", "ADJCOMPLETE" };
string WekaOption = "-L " + TAGS_LINK_TYPE[cGlobalInfo.OptionsWindow.comboBoxHierarchicalLinkType.SelectedIndex];// + OptionDistance;
HClusterer.setOptions(weka.core.Utils.splitOptions(WekaOption));
//EuclideanDistance2 Dist2 = new EuclideanDistance2();
//HClusterer.setDistanceFunction(Dist2);
HClusterer.setNumClusters(ClassNumber);
HClusterer.buildClusterer(Ninsts);
richTextBoxInfoClustering.AppendText("\n" + CurrentPlateToProcess.GetName() + ": " + HClusterer.numberOfClusters() + " cluster(s)");
ClusterEvaluation eval = new ClusterEvaluation();
eval.setClusterer(HClusterer);
eval.evaluateClusterer(Ninsts);
CurrentPlateToProcess.AssignClass(eval.getClusterAssignments());
}
/// <summary>
/// Perform an EM clustering on each plate independantely
/// </summary>
/// <param name="CurrentPlateToProcess">the plate to process</param>
/// <param name="ClassNumber">Number of class</param>
private void ClusteringEMSinglePlate(cPlate CurrentPlateToProcess, int ClassNumber)
{
weka.core.Instances Ninsts = CurrentPlateToProcess.CreateInstancesWithoutClass();// CreateInstanceWithoutClass(CurrentTable);
weka.clusterers.EM EMCluster = new EM();
EMCluster.setNumClusters(ClassNumber);
EMCluster.buildClusterer(Ninsts);
EMCluster.getClusterModelsNumericAtts();
if (EMCluster.numberOfClusters() > GlobalInfo.GetNumberofDefinedClass())
{
richTextBoxInfoClustering.AppendText("\n Plate " + CurrentPlateToProcess.Name + ", cluster Number: more than " + GlobalInfo.GetNumberofDefinedClass() + ", clustering not operated.\n");
return;
}
else
richTextBoxInfoClustering.AppendText("\n" + CurrentPlateToProcess.Name + ": " + EMCluster.numberOfClusters() + " cluster(s)");
ClusterEvaluation eval = new ClusterEvaluation();
eval.setClusterer(EMCluster);
eval.evaluateClusterer(Ninsts);
CurrentPlateToProcess.AssignClass(eval.getClusterAssignments());
}