/// <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()); }