work in progess : cleaning of the old distance implementation

src/mustic/gui/panels/ImageResultPanel.java

@@ -1199,12 +1199,6 @@ public class ImageResultPanel extends ResultPanel implements TreeSelectionListen
 							out.closeEntry();
 						}
 
-						out.putNextEntry(new ZipEntry(name + '/' + "ParameterMode.ser"));
-						oos = new ObjectOutputStream(out);
-						oos.writeObject(AttributeMultiDimSequence.getMode());
-						oos.flush();
-						out.closeEntry();
-
 						out.putNextEntry(new ZipEntry(name + '/' + "ParameterSimplify.ser"));
 						oos = new ObjectOutputStream(out);
 						oos.writeObject(AttributeMultiDimSequence.getSimplifyFrom());
@@ -1311,12 +1305,6 @@ public class ImageResultPanel extends ResultPanel implements TreeSelectionListen
 					out.closeEntry();
 				}
 
-				out.putNextEntry(new ZipEntry(name + '/' + "ParameterMode.ser"));
-				oos = new ObjectOutputStream(out);
-				oos.writeObject(AttributeMultiDimSequence.getMode());
-				oos.flush();
-				out.closeEntry();
-
 				out.putNextEntry(new ZipEntry(name + '/' + "ParameterSimplify.ser"));
 				oos = new ObjectOutputStream(out);
 				oos.writeObject(AttributeMultiDimSequence.getSimplifyFrom());

src/mustic/gui/panels/classifier/ClassifierPanel.java

@@ -941,20 +941,22 @@ public class ClassifierPanel extends JPanel {
 
 		ClassificationWeights weights = new GlobalWeights(data);
 		
+		if (this.attributeSelectionPanel != null)
+			weights = this.attributeSelectionPanel.getWeights();
+		
 		DistanceModel model = null;
 		
 		/* generates model */
 		if (this.useNaiveDist) {
 //			AttributeMultiDimSequence.setMode(AttributeMultiDimSequence.EUCLIDIEN);
-			model = DistanceModel.generateNaiveModel(data.getOneDataObject());
+			model = DistanceModel.generateNaiveModel(data.getOneDataObject(), weights);
 		}
 		else {
 //			AttributeMultiDimSequence.setMode(AttributeMultiDimSequence.DTW_BARYCENTRE);
-			model = DistanceModel.generateDefaultModel(data.getOneDataObject());
+			model = DistanceModel.generateDefaultModel(data.getOneDataObject(), weights);
 		}
 
-		if (this.attributeSelectionPanel != null)
-			weights = this.attributeSelectionPanel.getWeights();
+		
 
 		int choice = this.modele.getSelectedApproach();
 
@@ -1042,7 +1044,6 @@ public class ClassifierPanel extends JPanel {
 						else {
 							distanceParameters[th][i] = EmptyDistanceParameter.getInstance();//no parameter for a numerical euclidean distance
 							averageParameters[i] = EmptyAverageParameter.getInstance();
-
 						}
 						i++;
 					}

src/mustic/gui/panels/classifier/components/HybridClassificationPanel.java

@@ -10,7 +10,11 @@ import javax.swing.*;
 import javax.swing.border.TitledBorder;
 
 import jcl.data.Data;
+import jcl.data.attribute.Attribute;
 import jcl.data.attribute.AttributeMultiDimSequence;
+import jcl.data.distance.Distance;
+import jcl.data.distance.DistanceParameter;
+import jcl.data.distance.sequential.DistanceEuclidean;
 import jcl.learning.LearningParameters;
 import jcl.learning.methods.multistrategy.samarah.*;
 import mustic.gui.MainFrame;
@@ -151,7 +155,11 @@ public class HybridClassificationPanel extends JPanel implements AgentListManage
 			else {
 				file += "\t\t<isSimplifySequence>true</isSimplifySequence>\n";
 			}
-			if (AttributeMultiDimSequence.getMode() == AttributeMultiDimSequence.EUCLIDIEN) {
+			for (Distance<Attribute, DistanceParameter> d : agent.getParams().getModel().getDistances()) {
+				if(!(d instanceof DistanceEuclidean)) 
+				
+			}
+			if (AttributeMultiDimSequence.getMode() == AttributeMultiDimSequence.EUCLIDIEN && agent.getParams().getModel()) {
 				file += "\t\t<isUseNaiveDist>true</isUseNaiveDist>\n";
 			}
 			else {

src/mustic/io/ImageData.java

@@ -533,12 +533,6 @@ public class ImageData extends SimpleData implements Serializable {
 	public void setResolution(double resolution) {
 		this.resolution = resolution;
 	}
-	
-	private void setProperties(int mode, int simplifyFrom) {
-		AttributeMultiDimSequence.setMode(mode);
-		AttributeMultiDimSequence.setSimplifyFrom(simplifyFrom);
-
-	}
 
 	/**
 	 * <p>