Merge branch 'ProgressThread_2' into 'master'

Progress thread 2

See merge request !4

src/mustic/gui/ClassificationImage.java

-package mustic.gui;
-
-import java.lang.management.ManagementFactory;
-import java.util.ArrayList;
-
-import javax.swing.ImageIcon;
-import javax.swing.WindowConstants;
-
-import jcl.Classification;
-import jcl.data.attribute.AttributeMultiDimSequence;
-import jcl.learning.methods.multistrategy.samarah4.comm.ClassificationSAM4;
-import mustic.gui.panels.ImageResultPanel;
-import mustic.io.ImageData;
-import mustic.models.gui.ClassificationModel;
-import mustic.models.gui.panels.ResultPanel;
-import net.infonode.tabbedpanel.Tab;
-import net.infonode.tabbedpanel.TabbedPanel;
-
-public class ClassificationImage extends ClassificationModel {
-	/**	 */
-	private static final long serialVersionUID = 1L;
-
-
-	/** */
-	public ArrayList<Classification> results = new ArrayList<Classification>();
-
-	/**
-	 * 
-	 * @param aRawImage
-	 * @param data
-	 * @param title
-	 */
-	public ClassificationImage(DataSession session, String title) {
-		super(session, title, false);
-	}
-
-	public ClassificationImage(DataSession session, String title, boolean justData) {
-		super(session, title, justData);
-	}
-
-	/**
-	 * 
-	 */
-	@Override
-	public void addResult(Classification result, String title) {
-		this.addResult(result, title, this.tabbedPane);
-	}
-
-	@Override
-	synchronized public void addResult(Classification result, String title,
-			TabbedPanel pane) {
-		ResultPanel rpanel = null;
-		if (data instanceof ImageData) {
-			rpanel = new ImageResultPanel(session, result, this, ((ImageData) data));
-		} else {
-			rpanel = new ResultPanel(result, this);
-		}
-		rpanel.setName(title);
-		resultPanels.add(rpanel);
-		
-		Tab t1 = ClassificationModel.createTab(title, new ImageIcon(getClass()
-				.getResource("/icons/actions/document-open-result.png")), //$NON-NLS-1$
-				rpanel, true);
-
-		pane.addTab(t1);
-		t1.setSelected(true);
-	}
-
-	@Override
-	public void doOperationAfterClassification(Classification result) {
-		if (!result.isHybrid() && !(result instanceof ClassificationSAM4)) {
-			if (result.getTimeExec() != 0)
-				result.setTimeExec(ManagementFactory.getThreadMXBean()
-						.getCurrentThreadCpuTime());
-			this.results.add(result);
-			this.addResult(result, Messages.getString("ClassificationImage.1") + ResultPanel.nbResult++); //$NON-NLS-1$
-			ResultPanel irp = (ResultPanel) this.tabbedPane.getTabAt(
-					this.tabbedPane.getTabCount() - 1).getContentComponent();
-			irp.historique.addInfosln(Messages.getString("ClassificationImage.2")); //$NON-NLS-1$
-			if (result.getData().getOneDataObject().getAttribute(0) instanceof AttributeMultiDimSequence) {
-				irp.historique.addInfosln(Messages.getString("ClassificationImage.3")); //$NON-NLS-1$
-				if (result.getData().getDataFilesName().size() > 0) {
-					irp.historique.addInfosln(result.getData().getDataFilesName().get(0));
-				}
-			} else
-				irp.historique.addInfosln(Messages.getString("ClassificationImage.4") //$NON-NLS-1$
-						+ result.getData().getDataName() + "\n"); //$NON-NLS-1$
-
-			if (result.getLearningMethod() != null)
-				irp.historique.addInfosln(result.getLearningMethod()
-						.getParameters().toString());
-
-			if (result.getTimeExec() != 0) {
-				long exec = result.getTimeExec();
-				irp.historique.addInfosln(Messages.getString("ClassificationImage.6") //$NON-NLS-1$
-						+ (exec / 1.0E9) + "s"); //$NON-NLS-1$
-			}
-		}
-	}
-
-}
+package mustic.gui;
+
+import java.lang.management.ManagementFactory;
+import java.text.SimpleDateFormat;
+import java.util.ArrayList;
+import java.util.Date;
+import java.util.Iterator;
+
+import javax.swing.ImageIcon;
+import javax.swing.WindowConstants;
+
+import jcl.Classification;
+import jcl.data.attribute.AttributeMultiDimSequence;
+import jcl.learning.methods.multistrategy.samarah4.comm.ClassificationSAM4;
+import mustic.gui.panels.ImageResultPanel;
+import mustic.io.ImageData;
+import mustic.models.gui.ClassificationModel;
+import mustic.models.gui.panels.ResultPanel;
+import net.infonode.tabbedpanel.Tab;
+import net.infonode.tabbedpanel.TabbedPanel;
+
+public class ClassificationImage extends ClassificationModel {
+	/**	 */
+	private static final long serialVersionUID = 1L;
+
+
+	/** */
+	public ArrayList<Classification> results = new ArrayList<Classification>();
+
+	/**
+	 * 
+	 * @param aRawImage
+	 * @param data
+	 * @param title
+	 */
+	public ClassificationImage(DataSession session, String title) {
+		super(session, title, false);
+	}
+
+	public ClassificationImage(DataSession session, String title, boolean justData) {
+		super(session, title, justData);
+	}
+
+	@Override
+	public void addResult(Classification result, String title) {
+		this.addResult(result, title, this.tabbedPane);
+	}
+
+	@Override
+	synchronized public void addResult(Classification result, String title,
+			TabbedPanel pane) {
+		ResultPanel rpanel = null;
+		if (data instanceof ImageData) {
+			rpanel = new ImageResultPanel(session, result, this, ((ImageData) data));
+		} else {
+			rpanel = new ResultPanel(result, this);
+		}
+		rpanel.setName(title);
+		resultPanels.add(rpanel);
+		Tab t1 = ClassificationModel.createTab(title, new ImageIcon(getClass()
+				.getResource("/icons/actions/document-open-result.png")), //$NON-NLS-1$
+				rpanel, true);
+		pane.addTab(t1);
+		t1.setSelected(true);
+	}
+
+	@Override
+	public void doOperationAfterClassification(Classification result) {
+		// Monitoring the operation status
+		result.setStatus("Step "+ (result.getProgressableList().size()+1) + "/" + (result.getProgressableList().size()+1) + " : Displaying");
+		
+		if (!result.isHybrid() && !(result instanceof ClassificationSAM4)) {
+			if (result.getTimeExec() != 0)
+				result.setTimeExec(ManagementFactory.getThreadMXBean()
+						.getCurrentThreadCpuTime());
+			this.results.add(result);
+			this.addResult(result, Messages.getString("ClassificationImage.1") + ResultPanel.nbResult++); //$NON-NLS-1$
+			ResultPanel irp = (ResultPanel) this.tabbedPane.getTabAt(
+					this.tabbedPane.getTabCount() - 1).getContentComponent();
+			irp.historique.addInfosln(Messages.getString("ClassificationImage.2")); //$NON-NLS-1$
+			if (result.getData().getOneDataObject().getAttribute(0) instanceof AttributeMultiDimSequence) {
+				irp.historique.addInfosln(Messages.getString("ClassificationImage.3")); //$NON-NLS-1$
+				if (result.getData().getDataFilesName().size() > 0) {
+					irp.historique.addInfosln(result.getData().getDataFilesName().get(0));
+				}
+			} else
+				irp.historique.addInfosln(Messages.getString("ClassificationImage.4") //$NON-NLS-1$
+						+ result.getData().getDataName() + "\n"); //$NON-NLS-1$
+
+			if (result.getLearningMethod() != null)
+				irp.historique.addInfosln(result.getLearningMethod()
+						.getParameters().toString());
+
+			if (result.getTimeExec() != 0) {
+				long exec = result.getTimeExec();
+				irp.historique.addInfosln(Messages.getString("ClassificationImage.6") //$NON-NLS-1$
+						+ (exec / 1.0E9) + "s"); //$NON-NLS-1$
+			}
+
+		}
+	}
+
+}

src/mustic/gui/MainFrame.java

@@ -3967,7 +3967,7 @@ public class MainFrame extends JFrame {
 			        true);
 		
 		
-					t = new ClassificationThread(classif, classificationImage.getProgressBar(), 
+					t = new ClassificationThread(classif, classificationImage.getProgressBar(),classificationImage.getStatusBar(), 
 							classificationImage, null, false, null);
 					t.start();
 					try {

src/mustic/gui/panels/ImageResultPanel.java

@@ -4,6 +4,8 @@ import java.awt.*;
 import java.awt.event.*;
 import java.awt.image.*;
 import java.io.*;
+import java.text.SimpleDateFormat;
+import java.util.Date;
 import java.util.Observable;
 import java.util.Observer;
 import java.util.Vector;
@@ -201,7 +203,6 @@ public class ImageResultPanel extends ResultPanel implements TreeSelectionListen
 				imgData.getHeight(), result.getClusterMap(false), this.result.getClusters());
 		this.classPanel.addTreeSelectionListener(this);
 
-		
 		if (imgData.getRawImages() != null && imgData.getRawImages().size() > 0) {
 			this.viewer = new ClusteringImageViewer(new GDALPyramidImageViewer(
 					imgData.getRawImages().get(0), true), this.clusterMap);

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

@@ -695,8 +695,7 @@ public class ClassifierPanel extends JPanel {
 				if (this.timeCheckBox.isSelected()) {
 					classification.setTimeExec(1);
 				}
-
-				new ClassificationThread(classification, classificationImage.getProgressBar(), 
+				new ClassificationThread(classification, classificationImage.getProgressBar(),classificationImage.getStatusBar(), 
 						classificationImage, this.rmiServer, false, null).start();
 				try {
 					dataSession.associatedFrame.setMaximum(true);
@@ -717,6 +716,7 @@ public class ClassifierPanel extends JPanel {
 
 				// On lance le thread de classif
 				new ClassificationThread(classification, ((ClassificationModel) this.container_).getProgressBar(),
+						((ClassificationModel) this.container_).getStatusBar(),
 				        (ClassificationModel) this.container_, this.rmiServer, false, null).start();
 
 			}

src/mustic/gui/panels/data/DataConstructPanel.java

@@ -124,32 +124,37 @@ public class DataConstructPanel extends JPanel implements ToUpdateObject {
 	}
 
 	private void generateData() {
-		ImageData data = null;
-		
-		if (sourcePanel.isSequenceMaskSelected() && sample instanceof ImageSampler 
-				&& imageSessions != null) {
-			List<Mask> maskSequence = new ArrayList<Mask>();
-			boolean containsAtLeastOne = false;
-			for (ImageSession session : imageSessions) {
-				Mask m = session.getRawImage().getMask();
-				maskSequence.add(m);
-				if (m != null) {
-					containsAtLeastOne = true;
+		new Thread() {
+			@Override
+			public void run() {
+				ImageData data = null;
+				
+				if (sourcePanel.isSequenceMaskSelected() && sample instanceof ImageSampler 
+						&& imageSessions != null) {
+					List<Mask> maskSequence = new ArrayList<Mask>();
+					boolean containsAtLeastOne = false;
+					for (ImageSession session : imageSessions) {
+						Mask m = session.getRawImage().getMask();
+						maskSequence.add(m);
+						if (m != null) {
+							containsAtLeastOne = true;
+						}
+					}
+					if (containsAtLeastOne) {
+						((ImageSampler) sample).setMaskSequence(maskSequence);
+					}
 				}
+				if (filesPaths.size() > 1) {
+					data = new ImageData(sample, filesPaths);
+				} else {
+					data = new ImageData(sample, filesPaths.get(0));
+				}
+				MainFrame.getInstance().createDataSession(data);
+				
+				DataConstructFrame.getInstance().updateDataConstructPanel();
+				DataConstructFrame.getInstance().dispose();
 			}
-			if (containsAtLeastOne) {
-				((ImageSampler) sample).setMaskSequence(maskSequence);
-			}
-		}
-		if (filesPaths.size() > 1) {
-			data = new ImageData(sample, filesPaths);
-		} else {
-			data = new ImageData(sample, filesPaths.get(0));
-		}
-		MainFrame.getInstance().createDataSession(data);
-		
-		DataConstructFrame.getInstance().updateDataConstructPanel();
-		DataConstructFrame.getInstance().dispose();
+		}.start();
 	}
 	
 	public void updateSamplingSelectionPanel() {

src/mustic/gui/panels/data/DataPanel.java

@@ -137,7 +137,8 @@ public class DataPanel extends JPanel implements ChangeListener {
 		this.data = _data;
 
 		JPanel container = buildBody();		
-		JScrollPane sp = new JScrollPane(container);
+//		JScrollPane sp = new JScrollPane(container);
+		JPanel sp = container;//no scroll bars for better visibility
 		JPanel dataPane = new JPanel(new BorderLayout());
 //		dataPane.setSize(700, 500);
 		dataPane.setPreferredSize(new Dimension(700,500));

src/mustic/io/ImageData.java

@@ -13,6 +13,7 @@ import jcl.data.sampling.Sampler;
 import jcl.utils.exceptions.MethodNotImplementedException;
 import mustic.gui.ImageSession;
 import mustic.gui.MainFrame;
+import mustic.models.thread.ProgressThreadJCL;
 import mustic.utils.jclAdapters.ImageSampler;
 
 /**
@@ -108,7 +109,7 @@ public class ImageData extends SimpleData implements Serializable {
 		// Pierre
 
 		if (MainFrame.DEBUG_MODE == true)
-			System.out.println(" JJJ Création de dataObject[] à partir d'une image " + this.hashCode());
+			System.out.println(" Création de dataObject[] à partir d'une image " + this.hashCode());
 
 		// double[][][] buffer = image.getData();//image.load(0, 0,
 		// image.getWidth(), image.getHeight());
@@ -225,7 +226,7 @@ public class ImageData extends SimpleData implements Serializable {
 	
 	/**
 	 * <p>
-	 * Construcor from an already built set of DataObject of a sampler,
+	 * Constructor from an already built set of DataObject of a sampler,
 	 * the path is only used to gather the image informations
 	 * </p>
 	 * 
@@ -240,9 +241,7 @@ public class ImageData extends SimpleData implements Serializable {
 		if (MainFrame.DEBUG_MODE) {
 			System.out.println(">> ImageData(Sampler,String) <<");
 		}
-		
-		MainFrame.getProgressStatus().setMessage("loading sampler...");
-		
+				
 		this.rawImages.add(path);
 
 		long startTime = System.currentTimeMillis();
@@ -269,7 +268,8 @@ public class ImageData extends SimpleData implements Serializable {
 		dimensions[0] = rawImages.get(0).width;
 		dimensions[1] = rawImages.get(0).height;
 
-//		new ProgressThreadJCL(sampler, MainFrame.getProgressBar(), MainFrame.getProgressStatus()).start();
+		new ProgressThreadJCL(sampler, MainFrame.getProgressBar(), MainFrame.getProgressStatus()).start();
+		
 		if (mask != null) {
 			currentView = sampler.getDataObjects(mask);
 		} else {
@@ -294,7 +294,7 @@ public class ImageData extends SimpleData implements Serializable {
 	
 	/**
 	 * <p>
-	 * Construcor from an already built set of DataObject of a sampler,
+	 * Constructor from an already built set of DataObject of a sampler,
 	 * the path is only used to gather the image informations
 	 * </p>
 	 * 
@@ -322,6 +322,7 @@ public class ImageData extends SimpleData implements Serializable {
 	 * 			a mask to apply to the sampler
 	 */
 	public ImageData(Sampler sampler, Vector<RawImage> images, Mask mask) {
+
 		for(RawImage s : images) {
 			this.rawImages.add(s);
 		}

src/mustic/models/gui/ClassificationFrame.java

@@ -44,7 +44,6 @@ public class ClassificationFrame extends ClassificationModel {
 		ResultPanel rp = new ResultPanel(result, this);
 		rp.setName(name);
 		resultPanels.add(rp);
-
 		Tab tabResult = ClassificationModel.createTab(
 				result.getName(),
 				new ImageIcon(getClass().getResource(

src/mustic/models/gui/ClassificationModel.java

@@ -33,6 +33,7 @@ import mustic.models.gui.panels.HybridClassificationMonitor;
 import mustic.models.gui.panels.MaclawClassificationMonitor;
 import mustic.models.gui.panels.ResultPanel;
 import mustic.models.gui.widgets.ClassificationManager;
+import mustic.utils.tools.ProgressStatus;
 import net.infonode.tabbedpanel.Tab;
 import net.infonode.tabbedpanel.TabDragEvent;
 import net.infonode.tabbedpanel.TabEvent;
@@ -289,6 +290,10 @@ public abstract class ClassificationModel extends JPanel {
 	public JProgressBar getProgressBar() {
 		return MainFrame.getProgressBar();
 	}
+	
+	public ProgressStatus getStatusBar() {
+		return MainFrame.getProgressStatus();
+	}
 
 	/**
 	 * <p>

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

@@ -534,7 +534,7 @@ public class ClassifierPanel extends JPanel {
 		System.out.println("DEBUT CLASSIF");
 		/* On lance le thread de classification */
 		new ClassificationThread(classification,
-				this.container_.getProgressBar(), this.container_,
+				this.container_.getProgressBar(),this.container_.getStatusBar(), this.container_,
 				this.rmiServer, false, null).start();
 	}
 

src/mustic/models/thread/ClassificationThread.java

@@ -8,8 +8,10 @@ import jcl.Classification;
 import jcl.clustering.constraints.Constraint;
 import jcl.jcld.RmiServer;
 import jcl.learning.IterativeClassification;
+import jcl.learning.LearningMethod;
 import jcl.learning.methods.multistrategy.samarah4.comm.ClassificationSAM4;
 import mustic.models.gui.ClassificationModel;
+import mustic.utils.tools.ProgressStatus;
 
 /**
  * <p>
@@ -28,6 +30,9 @@ public class ClassificationThread extends Thread {
 
 	/** Barre d'avancement de la classification */
 	private JProgressBar progressBar_;
+	
+	/** Etat d'avancement de la classification */
+	private ProgressStatus statusBar_;
 
 	/** Server Rmi ou deporte le calcul */
 	private RmiServer rmiServer_;
@@ -55,6 +60,13 @@ public class ClassificationThread extends Thread {
 	 * @param constraints
 	 * 			  constraints used for the new iteration
 	 */
+	public ClassificationThread(Classification classification,
+			JProgressBar progressBar, ProgressStatus statusBar, ClassificationModel container,
+			RmiServer rmiServer, boolean newIterationMode, Vector<Constraint> constraints) {
+		this(classification, progressBar, container, rmiServer, newIterationMode, constraints);
+		this.statusBar_ = statusBar;
+	}
+	
 	public ClassificationThread(Classification classification,
 			JProgressBar progressBar, ClassificationModel container,
 			RmiServer rmiServer, boolean newIterationMode, Vector<Constraint> constraints) {
@@ -69,11 +81,10 @@ public class ClassificationThread extends Thread {
 	@Override
 	public void run() {
 		/* Si on a une barre de progression on monitore la classification */
-
-		if (this.rmiServer_ != null && !this.rmiServer_.useRmi())
-			if (this.progressBar_ != null)
-				new ProgressThreadJCL(this.classification_.getLearningMethod(),
-						this.progressBar_).start();
+		if (this.rmiServer_ != null && !this.rmiServer_.useRmi()) &&
+		    this.progressBar_ != null && this.statusBar_ != null) {
+			new ProgressThreadJCL(this.classification_, this.progressBar_,this.statusBar_).start();
+		}
 
 		/* teste si le calcul est a faire avec rmi */
 		if ((this.rmiServer_ != null) && (this.rmiServer_.useRmi())) {

src/mustic/models/thread/ProgressThreadJCL.java

 package mustic.models.thread;
 
+import java.util.Date;
+
 import javax.swing.JProgressBar;
 
 import jcl.utils.Progressable;
@@ -63,11 +65,13 @@ public class ProgressThreadJCL extends Thread {
 		{
 			while (prog != 100) {
 				prog = this.p.getProgress();
-//				status = this.p.getStatus();
+				status = this.p.getStatus();
+//				long time = new Date().getTime();
+//				System.out.println("prog:"+prog+" status:"+status+" time : "+time);
 				this.b.setValue(prog);
 				MainFrame.getProgressStatus().setMessage(status);
 				try {
-					sleep(1000);
+					sleep(200);
 				} catch (Exception ex) {
 					ex.printStackTrace();
 					System.exit(1);
@@ -82,7 +86,7 @@ public class ProgressThreadJCL extends Thread {
 				prog = this.p.getProgress();
 				this.b.setValue(prog);
 				try {
-					sleep(1000);
+					sleep(200);
 				} catch (Exception ex) {
 					ex.printStackTrace();
 					System.exit(1);

src/mustic/utils/image/reader/GDALImageReaderWrapper.java

 package mustic.utils.image.reader;
 
 
+import javax.swing.SwingWorker;
+
 import org.gdal.gdal.Band;
 import org.gdal.gdal.Dataset;
+import org.gdal.gdal.ProgressCallback;
 import org.gdal.gdal.gdal;
 import org.gdal.gdalconst.gdalconst;
 
 import jcl.utils.exceptions.MethodNotImplementedException;
+import mustic.gui.MainFrame;
+import mustic.utils.tools.ProgressPropertyChangeListener;
 
 /**
  * Reader tool used to access to the data using the gdal library
@@ -291,7 +296,7 @@ public class GDALImageReaderWrapper extends ReaderWrapper {
 		
 	}
 
-	/*
+	/**
 	 * Generates overviews if 
 	 * @param filePath
 	 * 			The image file path
@@ -310,12 +315,74 @@ public class GDALImageReaderWrapper extends ReaderWrapper {
 			//       the factor is the different (just tested for the first band)
 			if ((dataSet.GetRasterBand(1).GetOverviewCount() != overViewIDList.length) ||
 				((dataSet.GetRasterBand(1).GetOverview(0).getXSize() - dataSet.getRasterXSize()/2) > 1)) {
-				dataSet.BuildOverviews(overViewIDList);
-				
+				//Layers are generated in a background process using Swingworker. 
+				//A progress bar is incremented to display loading progress 
+				ImgLoadTask task = new ImgLoadTask(dataSet, overViewIDList);
+				task.addPropertyChangeListener(new ProgressPropertyChangeListener());
+				task.execute();
+				task.get();						
 			}
 		}
 	}
 	
+	/**
+	 * SwingWorker which generates pyramids layers in a background process
+	 * and updates a progress bar
+	 * 
+	 * @author Jean-Noël BALANCHE
+	 *
+	 */
+	static class ImgLoadTask extends SwingWorker<Void,Void> 
+	{
+		 
+		 private int[] overViewIDList = null;
+		 private Dataset dataSet = null;
+		 private int layer = 1;
+		 
+		 /**
+		  * task to generate pyramide layers in a background process
+		  * 
+		  * @param dataSet the dataset where to put the layers
+		  * @param overViewIDList list of layers to generate
+		  */
+		 public ImgLoadTask(Dataset dataSet, int[] overViewIDList) {
+		     //initialize
+			 this.dataSet = dataSet;
+			 this.overViewIDList = overViewIDList;
+		 }
+		
+		 @Override
+		 public Void doInBackground() throws Exception {
+			System.out.println("Nb layers to generate : " + overViewIDList.length);
+			MainFrame.getProgressStatus().setMessage("Generating overview "+layer+" of "+overViewIDList.length);
+			dataSet.BuildOverviews(overViewIDList,new ProgressCallback(){
+	            @Override
+	            public int run(double dfComplete, String message)
+	            {
+	            	/* If BuildOverviews is calling ProgressCallback.run() for each layer : */
+//	            	double totalProgress = layer*100/overViewIDList.length+dfComplete*100/overViewIDList.length;
+//	                setProgress((int) Math.min(totalProgress,100));
+//	            	if(dfComplete*100>=100) {
+//	    				layer++;
+//	    				MainFrame.getProgressStatus().setMessage("Generating overview "+layer+" of "+overViewIDList.length);
+//	                }
+	            	
+	            	/* If BuildOverviews is calling ProgressCallback.run() only one time :*/
+	    			MainFrame.getProgressStatus().setMessage("Generating overview "+layer+" of "+overViewIDList.length);
+	            	setProgress((int) (100 * dfComplete));
+	            	if(dfComplete*100>=layer*100/overViewIDList.length && dfComplete*100<100)