diff --git a/src/eva2/OptimizerFactory.java b/src/eva2/OptimizerFactory.java index 1a571feb..05664556 100644 --- a/src/eva2/OptimizerFactory.java +++ b/src/eva2/OptimizerFactory.java @@ -132,8 +132,8 @@ public class OptimizerFactory { de.setProblem(problem); de.getPopulation().setTargetSize(popsize); de.setDEType(DETypeEnum.DE2_CurrentToBest); - de.setF(f); - de.setK(CR); + de.setDifferentialWeight(f); + de.setCrossoverRate(CR); de.setLambda(lambda); de.addPopulationChangedEventListener(listener); de.init(); @@ -1476,8 +1476,8 @@ public class OptimizerFactory { AbstractOptimizationProblem problem) { DifferentialEvolution de = new DifferentialEvolution(); de.setDEType(DETypeEnum.DE2_CurrentToBest); // this sets current-to-best - de.setF(0.8); - de.setK(0.6); + de.setDifferentialWeight(0.8); + de.setCrossoverRate(0.6); de.setLambda(0.6); de.setMt(0.05); // this is not really employed for currentToBest return makeParams(de, 50, problem, randSeed, getTerminator()); diff --git a/src/eva2/gui/EvAModuleButtonPanelMaker.java b/src/eva2/gui/EvAModuleButtonPanelMaker.java index c848332d..3e70641d 100644 --- a/src/eva2/gui/EvAModuleButtonPanelMaker.java +++ b/src/eva2/gui/EvAModuleButtonPanelMaker.java @@ -85,7 +85,7 @@ public class EvAModuleButtonPanelMaker implements OptimizationStateListener, Ser public void actionPerformed(ActionEvent event) { try { // this means user break - moduleAdapter.stopOpt(); + moduleAdapter.stopOptimization(); } catch (Exception ee) { LOGGER.log(Level.WARNING, "Error while stopping job.", ee); } @@ -137,7 +137,7 @@ public class EvAModuleButtonPanelMaker implements OptimizationStateListener, Ser public void onUserStart() { try { - moduleAdapter.startOpt(); + moduleAdapter.startOptimization(); stopButton.setEnabled(true); runButton.setEnabled(false); postProcessButton.setEnabled(false); diff --git a/src/eva2/gui/Main.java b/src/eva2/gui/Main.java index da54173a..5b66372e 100644 --- a/src/eva2/gui/Main.java +++ b/src/eva2/gui/Main.java @@ -36,39 +36,21 @@ public class Main extends JFrame implements OptimizationStateListener { * Generated serial version identifier. */ private static final long serialVersionUID = 8232856334379977970L; - private final int splashScreenTime = 2500; + private final int splashScreenTime; private boolean clientInited = false; - private JExtDesktopPaneToolBar desktopToolBar; private JDesktopPane desktopPane; private JPanel configurationPane; - private JSplitPane horizontalSplit; - private Runnable initRnbl = null; + private Runnable initRunnable = null; - //private EvAComAdapter comAdapter; - private transient JMenuBar menuBar; - private transient JExtMenu menuHelp; - private transient JExtMenu menuSelHosts; - private transient JExtMenu menuModule; - private transient JExtMenu menuOptions; - private JPanel statusBar; private transient JProgressBar progressBar; // Option private ExtAction actPreferences; private ExtAction actQuit; - // LogPanel - private LoggingPanel logPanel; private static final Logger LOGGER = Logger.getLogger(Main.class.getName()); - // Module: - private ExtAction actModuleLoad; - // Hosts: - private ExtAction actHost; - private ExtAction actAvailableHost; - private ExtAction actKillHost; - private ExtAction actKillAllHosts; private ModuleAdapter currentModuleAdapter = null; // Help: @@ -78,13 +60,10 @@ public class Main extends JFrame implements OptimizationStateListener { // if not null, the module is loaded automatically and no other can be selected private String useDefaultModule = null; //"Genetic_Optimization"; - private boolean showLoadModules = false; private boolean localMode = false; // measuring optimization runtime private long startTime = 0; - // remember the module in use - private transient String currentModule = null; private boolean withGUI = true; private boolean withTreeView = false; private EvATabbedFrameMaker frameMaker = null; @@ -103,11 +82,7 @@ public class Main extends JFrame implements OptimizationStateListener { } public boolean removeOptimizationStateListener(OptimizationStateListener l) { - if (superListenerList != null) { - return superListenerList.remove(l); - } else { - return false; - } + return superListenerList != null && superListenerList.remove(l); } /** @@ -177,8 +152,8 @@ public class Main extends JFrame implements OptimizationStateListener { * @param noGui * @see #Main(String, String, boolean, boolean) */ - public Main(final String hostName, InterfaceOptimizationParameters goParams, boolean autorun, boolean noSplash, boolean noGui) { - this(hostName, null, null, goParams, autorun, noSplash, noGui, false); + public Main(final String hostName, InterfaceOptimizationParameters optimizationParameters, boolean autorun, boolean noSplash, boolean noGui) { + this(hostName, null, null, optimizationParameters, autorun, noSplash, noGui, false); } /** @@ -231,11 +206,11 @@ public class Main extends JFrame implements OptimizationStateListener { } } - currentModule = null; comAdapter = EvAComAdapter.getInstance(); - SwingUtilities.invokeLater(initRnbl = new Runnable() { + splashScreenTime = 2500; + SwingUtilities.invokeLater(initRunnable = new Runnable() { @Override public void run() { @@ -263,7 +238,7 @@ public class Main extends JFrame implements OptimizationStateListener { if (withGUI) { frameMaker.onUserStart(); } else { - currentModuleAdapter.startOpt(); + currentModuleAdapter.startOptimization(); } } // close splash screen @@ -283,12 +258,12 @@ public class Main extends JFrame implements OptimizationStateListener { * as it returns, the Main GUI is fully initialized. */ public void awaitClientInitialized() { - if (initRnbl != null) { - synchronized (initRnbl) { + if (initRunnable != null) { + synchronized (initRunnable) { if (!clientInited) { try { - initRnbl.wait(); - initRnbl = null; + initRunnable.wait(); + initRunnable = null; } catch (InterruptedException e) { e.printStackTrace(); } @@ -310,7 +285,7 @@ public class Main extends JFrame implements OptimizationStateListener { */ public boolean startOptimization() { if (currentModuleAdapter != null) { - currentModuleAdapter.startOpt(); + currentModuleAdapter.startOptimization(); return true; } else { return false; @@ -371,7 +346,7 @@ public class Main extends JFrame implements OptimizationStateListener { desktopPane = new JExtDesktopPane(); JEFrameRegister.getInstance().setDesktopPane(desktopPane); /* Creates desktopPane ToolBar to show tiling buttons */ - desktopToolBar = new JExtDesktopPaneToolBar((JExtDesktopPane) desktopPane); + JExtDesktopPaneToolBar desktopToolBar = new JExtDesktopPaneToolBar((JExtDesktopPane) desktopPane); /* Pane to hold ToolBar + DesktopPane */ JPanel desktopPanel = new JPanel(new GridBagLayout()); @@ -397,15 +372,11 @@ public class Main extends JFrame implements OptimizationStateListener { System.out.println("Error" + e.getMessage()); } - logPanel = new LoggingPanel(LOGGER); + LoggingPanel logPanel = new LoggingPanel(LOGGER); logPanel.setBorder(BorderFactory.createEmptyBorder(5, 5, 5, 5)); - if (EvAInfo.propShowModules() != null) { - showLoadModules = true; - } else { - showLoadModules = false; // may be set to true again if default module couldnt be loaded - } + boolean showLoadModules = EvAInfo.propShowModules() != null; createActions(); setSize(800, 600); @@ -424,7 +395,7 @@ public class Main extends JFrame implements OptimizationStateListener { add(configurationPane, gbConstraints); /* SplitPane for desktopPanel and loggingPanel */ - horizontalSplit = new JSplitPane(JSplitPane.VERTICAL_SPLIT, true); + JSplitPane horizontalSplit = new JSplitPane(JSplitPane.VERTICAL_SPLIT, true); horizontalSplit.setTopComponent(desktopPanel); horizontalSplit.setBottomComponent(logPanel); horizontalSplit.setDividerLocation(0.25); @@ -442,7 +413,7 @@ public class Main extends JFrame implements OptimizationStateListener { add(horizontalSplit, gbConstraints); /* StatusBar of the main frame */ - statusBar = new JPanel(new FlowLayout(FlowLayout.RIGHT)); + JPanel statusBar = new JPanel(new FlowLayout(FlowLayout.RIGHT)); JPanel statusBarControls = new JPanel(); statusBarControls.setLayout(new BoxLayout(statusBarControls, BoxLayout.LINE_AXIS)); @@ -504,9 +475,7 @@ public class Main extends JFrame implements OptimizationStateListener { } } }); - } - if (withGUI) { LOGGER.log(Level.INFO, "Working directory is: {0}", System.getProperty("user.dir")); LOGGER.log(Level.INFO, "Class path is: {0}", System.getProperty("java.class.path", ".")); @@ -754,12 +723,12 @@ public class Main extends JFrame implements OptimizationStateListener { * Create the main menu and add actions. */ private void buildMenu() { - menuBar = new JMenuBar(); + JMenuBar menuBar = new JMenuBar(); setJMenuBar(menuBar); - menuModule = new JExtMenu("&Module"); + JExtMenu menuModule = new JExtMenu("&Module"); //menuModule.add(actModuleLoad); - menuSelHosts = new JExtMenu("&Select Hosts"); + JExtMenu menuSelHosts = new JExtMenu("&Select Hosts"); //menuSelHosts.setToolTipText("Select a host for the server application"); //menuSelHosts.add(actHost); //menuSelHosts.add(actAvailableHost); @@ -767,13 +736,13 @@ public class Main extends JFrame implements OptimizationStateListener { //menuSelHosts.add(actKillHost); //menuSelHosts.add(actKillAllHosts); - menuHelp = new JExtMenu("&Help"); + JExtMenu menuHelp = new JExtMenu("&Help"); menuHelp.add(actHelp); menuHelp.addSeparator(); menuHelp.add(actAbout); menuHelp.add(actLicense); - menuOptions = new JExtMenu("&Options"); + JExtMenu menuOptions = new JExtMenu("&Options"); menuOptions.add(actPreferences); //menuOptions.add(menuSelHosts); menuOptions.addSeparator(); @@ -797,7 +766,7 @@ public class Main extends JFrame implements OptimizationStateListener { public InterfaceOptimizationParameters getGOParameters() { if (currentModuleAdapter != null) { if (currentModuleAdapter instanceof AbstractModuleAdapter) { - return ((AbstractModuleAdapter) currentModuleAdapter).getGOParameters(); + return ((AbstractModuleAdapter) currentModuleAdapter).getOptimizationParameters(); } } return null; @@ -816,12 +785,8 @@ public class Main extends JFrame implements OptimizationStateListener { * * @return */ - public boolean isOptRunning() { - if ((currentModuleAdapter != null) && (currentModuleAdapter instanceof AbstractModuleAdapter)) { - return ((AbstractModuleAdapter) currentModuleAdapter).isOptRunning(); - } else { - return false; - } + public boolean isOptimizationRunning() { + return (currentModuleAdapter != null) && (currentModuleAdapter instanceof AbstractModuleAdapter) && ((AbstractModuleAdapter) currentModuleAdapter).isOptRunning(); } private void loadSpecificModule(String selectedModule, InterfaceOptimizationParameters goParams) { @@ -838,10 +803,7 @@ public class Main extends JFrame implements OptimizationStateListener { URL baseDir = getClass().getClassLoader().getResource(""); String cp = System.getProperty("java.class.path", "."); String dir = (baseDir == null) ? System.getProperty("user.dir") : baseDir.getPath(); - // System.err.println("Working dir: " + dir); - /*if (baseDir == null) { - throw new RuntimeException("Cannot launch EvA2 due to an access restriction. If you are using Java Web Start, please download the application and try again."); - }*/ + if (!cp.contains(dir)) { // this was added due to matlab not adding base dir to base path... System.err.println("classpath does not contain base directory!"); @@ -852,10 +814,9 @@ public class Main extends JFrame implements OptimizationStateListener { loadSpecificModule(selectedModule, goParams); // end recursive call! handle with care! return; } - showLoadModules = true; } else { newModuleAdapter.setConnection(!localMode); - newModuleAdapter.addOptimizationStateListener((OptimizationStateListener) this); + newModuleAdapter.addOptimizationStateListener(this); try { if (withGUI) { // this (or rather: EvAModuleButtonPanelMaker) is where the start button etc come from! @@ -864,7 +825,6 @@ public class Main extends JFrame implements OptimizationStateListener { /* This is the left TabPane on the main frame */ JPanel moduleContainer = frameMaker.makePanel(); - boolean wasVisible = configurationPane.isVisible(); configurationPane.setVisible(false); configurationPane.removeAll(); @@ -873,7 +833,7 @@ public class Main extends JFrame implements OptimizationStateListener { /* ToDo: Find a way to properly add the TreeView to the GOPanel */ if (withTreeView && (newModuleAdapter instanceof AbstractModuleAdapter)) { JComponent tree = null; - tree = getEvATreeView(frameMaker.getGOPanel(), "OptimizationParameters", ((AbstractModuleAdapter) newModuleAdapter).getGOParameters()); + tree = getEvATreeView(frameMaker.getGOPanel(), "OptimizationParameters", ((AbstractModuleAdapter) newModuleAdapter).getOptimizationParameters()); gbConstraints.gridx = 0; gbConstraints.gridy = 0; gbConstraints.fill = GridBagConstraints.BOTH; @@ -896,29 +856,17 @@ public class Main extends JFrame implements OptimizationStateListener { gbConstraints2.gridx = 0; gbConstraints2.gridy = 0; gbConstraints2.fill = GridBagConstraints.VERTICAL; - //gbConstraints2.gridheight = GridBagConstraints.REMAINDER; gbConstraints2.weighty = 1.0; configurationPane.add(moduleContainer, gbConstraints2); configurationPane.validate(); } - currentModule = selectedModule; + } catch (Exception e) { - currentModule = null; LOGGER.log(Level.SEVERE, "Error while newModulAdapter.getModulFrame(): " + e.getMessage(), e); EVAERROR.EXIT("Error while newModulAdapter.getModulFrame(): " + e.getMessage()); } -// try { TODO whats this? -// newModuleAdapter.setConnection(true); -// } catch (Exception e) { -// e.printStackTrace(); -// m_LogPanel.logMessage("Error while m_ComAdapter.AddRMIPlotListener Host: " + e.getMessage()); -// EVAERROR.EXIT("Error while m_ComAdapter.AddRMIPlotListener: " + e.getMessage()); -// } - // set mode (rmi or not) - // ModuladapterListe adden -// m_ModuleAdapterList.add(newModuleAdapter); currentModuleAdapter = newModuleAdapter; } } @@ -927,6 +875,7 @@ public class Main extends JFrame implements OptimizationStateListener { * Create a tree view of an object based on EvATreeNode. It is encapsulated * in a JScrollPane. * + * @param goPanel * @param title * @param object * @return diff --git a/src/eva2/gui/editor/GenericObjectEditor.java b/src/eva2/gui/editor/GenericObjectEditor.java index b5217894..d72339f1 100644 --- a/src/eva2/gui/editor/GenericObjectEditor.java +++ b/src/eva2/gui/editor/GenericObjectEditor.java @@ -144,10 +144,10 @@ public class GenericObjectEditor implements PropertyEditor { try { BeanInfo bi = Introspector.getBeanInfo(cls); PropertyDescriptor[] props = bi.getPropertyDescriptors(); - for (int i = 0; i < props.length; i++) { - if ((props[i].getName().equals(property))) { - if (expertValue != props[i].isExpert()) { - props[i].setExpert(expertValue); + for (PropertyDescriptor prop : props) { + if ((prop.getName().equals(property))) { + if (expertValue != prop.isExpert()) { + prop.setExpert(expertValue); } } } @@ -174,10 +174,10 @@ public class GenericObjectEditor implements PropertyEditor { try { BeanInfo bi = Introspector.getBeanInfo(cls); PropertyDescriptor[] props = bi.getPropertyDescriptors(); - for (int i = 0; i < props.length; i++) { - if ((props[i].getName().equals(property))) { - if (hide != props[i].isHidden()) { - props[i].setHidden(hide); + for (PropertyDescriptor prop : props) { + if ((prop.getName().equals(property))) { + if (hide != prop.isHidden()) { + prop.setHidden(hide); } return true; } @@ -305,7 +305,6 @@ public class GenericObjectEditor implements PropertyEditor { */ @Override public void setValue(Object o) { - //System.err.println("setValue()" + m_ClassType.toString()); if (o == null || classType == null) { logger.log(Level.WARNING, "No ClassType set up for GenericObjectEditor!"); @@ -315,15 +314,14 @@ public class GenericObjectEditor implements PropertyEditor { if (classType.isPrimitive()) { System.err.println("setValue object not of correct type! Expected " + classType.getName() + ", got " + o.getClass().getName()); System.err.println("setting primitive type"); - setObject((Object) o); - //throw new NullPointerException("ASDF"); + setObject(o); } else { System.err.println("setValue object not of correct type! Expected " + classType.getName() + ", got " + o.getClass().getName()); } return; } - setObject((Object) o); + setObject(o); if (editorComponent != null) { editorComponent.updateChooser(); } diff --git a/src/eva2/gui/editor/GenericStringListSelectionEditor.java b/src/eva2/gui/editor/GenericStringListSelectionEditor.java deleted file mode 100644 index 52126706..00000000 --- a/src/eva2/gui/editor/GenericStringListSelectionEditor.java +++ /dev/null @@ -1,66 +0,0 @@ -//package eva2.gui; -// -// -//import javax.swing.*; -// -//import eva2.optimization.individuals.codings.gp.AbstractGPNode; -//import eva2.optimization.individuals.codings.gp.GPArea; -// -//import java.beans.PropertyEditor; -//import java.beans.PropertyChangeSupport; -//import java.beans.PropertyChangeListener; -//import java.awt.*; -//import java.awt.event.ActionListener; -//import java.awt.event.ActionEvent; -//import java.util.ArrayList; -// -///** -// * TODO this should be redundant with the new GenericObjectListEditor. -// * -// * Created by IntelliJ IDEA. -// * User: streiche -// * Date: 23.03.2004 -// * Time: 15:03:29 -// * To change this template use File | Settings | File Templates. -// */ -//public class GenericStringListSelectionEditor extends AbstractListSelectionEditor { -// private PropertyStringList m_List; -// -// @Override -// protected int getElementCount() { -// return m_List.getStrings().length; -// } -// -// @Override -// protected String getElementName(int i) { -// return m_List.getStrings()[i]; -// } -// -// @Override -// protected boolean isElementAllowed(int i) { -// return this.m_List.getSelection()[i]; -// } -// -// @Override -// protected boolean performOnAction() { -// for (int i = 0; i < this.m_BlackCheck.length; i++) { -// this.m_List.setSelectionForElement(i, this.m_BlackCheck[i].isSelected()); -// } -// return true; -// } -// -// @Override -// protected boolean setObject(Object o) { -// if (o instanceof PropertyStringList) { -// this.m_List = (PropertyStringList) o; -// return true; -// } else return false; -// } -// -// /** Retruns the current object. -// * @return the current object -// */ -// public Object getValue() { -// return this.m_List; -// } -//} \ No newline at end of file diff --git a/src/eva2/optimization/modules/AbstractModuleAdapter.java b/src/eva2/optimization/modules/AbstractModuleAdapter.java index ccc2fc03..698580c8 100644 --- a/src/eva2/optimization/modules/AbstractModuleAdapter.java +++ b/src/eva2/optimization/modules/AbstractModuleAdapter.java @@ -62,7 +62,7 @@ abstract public class AbstractModuleAdapter implements ModuleAdapter, Serializab * Start optimization on processor. */ @Override - public void startOpt() { + public void startOptimization() { processor.startOpt(); } @@ -70,7 +70,7 @@ abstract public class AbstractModuleAdapter implements ModuleAdapter, Serializab * Restart optimization on processor. */ @Override - public void restartOpt() { + public void restartOptimization() { processor.restartOpt(); } @@ -78,7 +78,7 @@ abstract public class AbstractModuleAdapter implements ModuleAdapter, Serializab * Stop optimization on processor. */ @Override - public void stopOpt() { + public void stopOptimization() { // This means user break processor.stopOpt(); } @@ -108,7 +108,7 @@ abstract public class AbstractModuleAdapter implements ModuleAdapter, Serializab } } - public InterfaceOptimizationParameters getGOParameters() { + public InterfaceOptimizationParameters getOptimizationParameters() { if ((processor != null) && (processor instanceof Processor)) { return ((Processor) processor).getGOParams(); } else { @@ -116,7 +116,7 @@ abstract public class AbstractModuleAdapter implements ModuleAdapter, Serializab } } - public void setGOParameters(InterfaceOptimizationParameters goParams) { + public void setOptimizationParameters(InterfaceOptimizationParameters goParams) { if ((processor != null) && (processor instanceof Processor)) { ((Processor) processor).setGOParams(goParams); } diff --git a/src/eva2/optimization/modules/DEParameters.java b/src/eva2/optimization/modules/DEParameters.java index 02cbbfc0..859af2e2 100644 --- a/src/eva2/optimization/modules/DEParameters.java +++ b/src/eva2/optimization/modules/DEParameters.java @@ -107,15 +107,15 @@ public class DEParameters extends AbstractOptimizationParameters implements Inte * @param f */ public void setF(double f) { - ((DifferentialEvolution) this.optimizer).setF(f); + ((DifferentialEvolution) this.optimizer).setDifferentialWeight(f); } public double getF() { - return ((DifferentialEvolution) this.optimizer).getF(); + return ((DifferentialEvolution) this.optimizer).getDifferentialWeight(); } - public String fTipText() { - return "F is a real and constant factor which controlls the ampllification of the differential variation."; + public String differentialWeightTipText() { + return "F is a real and constant factor which controlls the amplification of the differential variation."; } /** @@ -124,14 +124,14 @@ public class DEParameters extends AbstractOptimizationParameters implements Inte * @param k */ public void setK(double k) { - ((DifferentialEvolution) this.optimizer).setK(k); + ((DifferentialEvolution) this.optimizer).setCrossoverRate(k); } public double getK() { - return ((DifferentialEvolution) this.optimizer).getK(); + return ((DifferentialEvolution) this.optimizer).getCrossoverRate(); } - public String kTipText() { + public String crossoverRateTipText() { return "Probability of alteration through DE1."; } diff --git a/src/eva2/optimization/modules/GenericModuleAdapter.java b/src/eva2/optimization/modules/GenericModuleAdapter.java index 4ff2d45b..e3c77923 100644 --- a/src/eva2/optimization/modules/GenericModuleAdapter.java +++ b/src/eva2/optimization/modules/GenericModuleAdapter.java @@ -140,8 +140,8 @@ public class GenericModuleAdapter extends AbstractModuleAdapter implements Seria } @Override - public void setGOParameters(InterfaceOptimizationParameters goParams) { - super.setGOParameters(goParams); + public void setOptimizationParameters(InterfaceOptimizationParameters goParams) { + super.setOptimizationParameters(goParams); paramPanel.getEditor().setValue(goParams); } } diff --git a/src/eva2/optimization/modules/ModuleAdapter.java b/src/eva2/optimization/modules/ModuleAdapter.java index 9a7e8db4..aa697e29 100644 --- a/src/eva2/optimization/modules/ModuleAdapter.java +++ b/src/eva2/optimization/modules/ModuleAdapter.java @@ -21,7 +21,7 @@ public interface ModuleAdapter extends OptimizationStateListener { EvATabbedFrameMaker getModuleFrame(); - void startOpt(); // called from client + void startOptimization(); // called from client /** * Schedule a certain job to a job list. @@ -30,9 +30,9 @@ public interface ModuleAdapter extends OptimizationStateListener { */ OptimizationJob scheduleJob(); - void restartOpt(); + void restartOptimization(); - void stopOpt(); + void stopOptimization(); //void runScript(); diff --git a/src/eva2/optimization/modules/Processor.java b/src/eva2/optimization/modules/Processor.java index cc6e9814..ab945f20 100644 --- a/src/eva2/optimization/modules/Processor.java +++ b/src/eva2/optimization/modules/Processor.java @@ -32,7 +32,7 @@ import javax.swing.JOptionPane; /** * The Processor may run as a thread permanently (GenericModuleAdapter) and is - * then stopped and started by a switch in startOpt/stopOpt. + * then stopped and started by a switch in startOptimization/stopOptimization. *

* Processor also handles adaptive parameter control by checking for the method * getParamControl in (so far) Optimizer and Problem instances. The return-value @@ -214,7 +214,7 @@ public class Processor extends Thread implements InterfaceProcessor, InterfacePo Population resultPop = null; if (!isOptRunning()) { - System.err.println("warning, this shouldnt happen in processor! Was startOpt called?"); + System.err.println("warning, this shouldnt happen in processor! Was startOptimization called?"); setOptRunning(true); } diff --git a/src/eva2/optimization/operator/postprocess/PostProcess.java b/src/eva2/optimization/operator/postprocess/PostProcess.java index 404f1193..57ba5172 100644 --- a/src/eva2/optimization/operator/postprocess/PostProcess.java +++ b/src/eva2/optimization/operator/postprocess/PostProcess.java @@ -442,14 +442,14 @@ public class PostProcess { gda.initByPopulation(pop, false); int funCallsBefore = pop.getFunctionCalls(); - pop.SetFunctionCalls(baseEvals); + pop.setFunctionCalls(baseEvals); OptimizerRunnable ppRunnable = new OptimizerRunnable(OptimizerFactory.makeParams(gda, pop, problem, 0, term), true); runPP(ppRunnable); // ppRunnable.getStats().createNextGenerationPerformed(gda.getPopulation(), gda, null); int funCallsDone = pop.getFunctionCalls() - baseEvals; - pop.SetFunctionCalls(funCallsBefore); + pop.setFunctionCalls(funCallsBefore); return funCallsDone; } @@ -476,26 +476,16 @@ public class PostProcess { nms.setGenerationCycle(5); nms.initByPopulation(pop, false); int funCallsBefore = pop.getFunctionCalls(); - pop.SetFunctionCalls(baseEvals); + pop.setFunctionCalls(baseEvals); OptimizerRunnable ppRunnable = new OptimizerRunnable(OptimizerFactory.makeParams(nms, pop, problem, 0, term), true); // as nms creates a new population and has already evaluated them, send a signal to stats ppRunnable.getStats().createNextGenerationPerformed(nms.getPopulation(), nms, null); -// if (problem instanceof InterfaceFirstOrderDerivableProblem) { -// double[] x = pop.getBestEAIndividual().getDoublePosition(); -// System.out.println("grads: " + BeanInspector.toString(((InterfaceFirstOrderDerivableProblem)problem).getFirstOrderGradients(x))); -// } - runPP(ppRunnable); -// if (problem instanceof InterfaceFirstOrderDerivableProblem) { -// double[] x = pop.getBestEAIndividual().getDoublePosition(); -// System.out.println("grads: " + BeanInspector.toString(((InterfaceFirstOrderDerivableProblem)problem).getFirstOrderGradients(x))); -// } - int funCallsDone = pop.getFunctionCalls() - baseEvals; - pop.SetFunctionCalls(funCallsBefore); + pop.setFunctionCalls(funCallsBefore); return new Pair(funCallsDone, ppRunnable.wasAborted()); } @@ -529,7 +519,7 @@ public class PostProcess { OptimizationParameters cmaParams = OptimizerFactory.makeParams(es, pop, problem, 0, term); int funCallsBefore = pop.getFunctionCalls(); - pop.SetFunctionCalls(baseEvals); + pop.setFunctionCalls(baseEvals); OptimizerRunnable ppRunnable = new OptimizerRunnable(cmaParams, true); ppRunnable.getStats().createNextGenerationPerformed(cmaParams.getOptimizer().getPopulation(), cmaParams.getOptimizer(), null); @@ -605,7 +595,6 @@ public class PostProcess { } subPop = NelderMeadSimplex.createNMSPopulation(candidates.getEAIndividual(index), absToRelPerturb(perturb, range), range, false); } -// subPop.setSameParams(candidates); return subPop; } @@ -723,7 +712,6 @@ public class PostProcess { for (int i = 0; i < candidates.size(); i++) { // improve each single sub pop subPop = nmPops.get(i); term.init(prob); -// if (TRACE) System.out.println("*** before " + subPop.getBestEAIndividual().getStringRepresentation()); switch (method) { case nelderMead: @@ -744,23 +732,15 @@ public class PostProcess { break; } - // if (TRACE) System.out.println("*** after: " + subPop.getBestEAIndividual().getStringRepresentation()); if (checkRange(subPop.getBestEAIndividual())) { - // and replace corresponding individual (should usually be better) -// if (subPop.getBestEAIndividual().isDominant(candidates.getEAIndividual(i))) { // TODO Multiobjective??? if (subPop.getBestEAIndividual().getFitness(0) < candidates.getEAIndividual(i).getFitness(0)) { -// System.out.println("moved by "+ PhenotypeMetric.dist(candidates.getEAIndividual(i), subPop.getBestEAIndividual())); - subPop.getBestEAIndividual().putData(movedDistanceKey, new Double(PhenotypeMetric.dist(candidates.getEAIndividual(i), subPop.getBestEAIndividual()))); -// subPop.getBestEAIndividual().putData(movedToPositionKey, subPop.getBestEAIndividual().getDoublePosition()); - // ^ this makes no sense here since the new position is returned anyways by replacing the candidate individual + subPop.getBestEAIndividual().putData(movedDistanceKey, PhenotypeMetric.dist(candidates.getEAIndividual(i), subPop.getBestEAIndividual())); candidates.set(i, subPop.getBestEAIndividual()); } } else { // TODO esp. in nelder mead System.err.println("Warning, individual left the problem range during PP!"); } - -// if (TRACE) System.out.println("refined to " + subPop.getBestEAIndividual().getStringRepresentation()); } return stepsPerf; @@ -864,9 +844,7 @@ public class PostProcess { rnbl.getGOParams().setDoPostProcessing(false); rnbl.setVerbosityLevel(StatisticsParameter.VERBOSITY_NONE); ppRunnables.add(rnbl); -// System.err.println("Starting runbl " + rnbl); rnbl.run(); -// System.err.println("Aborted: " + rnbl.wasAborted()); rnbl.getGOParams().setDoPostProcessing(true); ppRunnables.remove(rnbl); } @@ -875,16 +853,15 @@ public class PostProcess { * Stop the post processing thread with the given ID. */ public static void stopPP(int rnblID) { -// System.err.println("Stopping pp " + rnblID); OptimizerRunnable rnbl = getRunnable(rnblID); stopPP(rnbl); } private static OptimizerRunnable getRunnable(int rnblID) { synchronized (ppRunnables) { - for (int i = 0; i < ppRunnables.size(); i++) { - if (rnblID == ppRunnables.get(i).getID()) { - return ppRunnables.get(i); + for (OptimizerRunnable ppRunnable : ppRunnables) { + if (rnblID == ppRunnable.getID()) { + return ppRunnable; } } } @@ -895,7 +872,6 @@ public class PostProcess { * Stop the post processing if its currently running. */ public static void stopPP(OptimizerRunnable rnbl) { -// System.err.println("Stopping rnbl " + rnbl); if (rnbl != null) { synchronized (rnbl) { rnbl.stopOpt(); @@ -954,7 +930,6 @@ public class PostProcess { OptimizerRunnable runnable = OptimizerFactory.getOptRunnable(OptimizerFactory.STD_GA, problem, 100, null); runnable.run(); Population pop = runnable.getGOParams().getOptimizer().getPopulation(); -// System.out.println("no optima found: " + mmp.getNumberOfFoundOptima(pop)); Population found = getFoundOptima(pop, mmp.getRealOptima(), 0.05, true); System.out.println("all found (" + found.size() + "): " + BeanInspector.toString(found)); @@ -963,8 +938,6 @@ public class PostProcess { int evalCnt = 0; while (popD.tail() > 0.001) { i++; -// public static PopDoublePair clusterHC(pop, problem, sigmaCluster, funCalls, keepClusterRatio, mute) { - popD = clusterLocalSearch(PostProcessMethod.hillClimber, popD.head(), problem, 0.01, 1500, 0.1, new MutateESFixedStepSize(0.02)); evalCnt += popD.head().getFunctionCalls(); System.out.println("popsize is " + popD.head().size()); @@ -972,11 +945,6 @@ public class PostProcess { found = getFoundOptima(popD.head(), mmp.getRealOptima(), 0.05, true); System.out.println("found at " + i + " (" + found.size() + "): " + BeanInspector.toString(found)); System.out.println("funcalls: " + evalCnt); -// System.out.println(BeanInspector.toString(pop.getMeanFitness())); - -// System.out.println("no optima found: " + mmp.getNumberOfFoundOptima(pop)); -// System.out.println("best after: " + AbstractEAIndividual.getDefaultStringRepresentation(pop.getBestEAIndividual())); - } /** @@ -999,7 +967,6 @@ public class PostProcess { Population clust = (Population) clusterBest(pop, new ClusteringDensityBased(sigmaCluster, 2), keepClusterRatio, KEEP_LONERS, BEST_RAND).clone(); - //clust.addPopulationChangedEventListener() double[] meanFit = clust.getMeanFitness(); if (TRACE) { @@ -1008,7 +975,7 @@ public class PostProcess { int evalsDone = processSingleCandidates(method, clust, funCalls, sigmaCluster / 2., problem, mute); - clust.SetFunctionCalls(evalsBefore + evalsDone); + clust.setFunctionCalls(evalsBefore + evalsDone); double improvement = EuclideanMetric.euclideanDistance(meanFit, clust.getMeanFitness()); if (TRACE) { @@ -1037,21 +1004,6 @@ public class PostProcess { listener.println("found " + getFoundOptima(solutions, mmkProb.getRealOptima(), epsilon, true).size() + " for epsilon = " + epsilon + ", maxPeakRatio: " + mmkProb.getMaximumPeakRatio(solutions)); } } - } else { - // TODO in this form it may cost a lot of time and cant be stopped, which is bad -// double epsilonPhenoSpace = 0.01, epsilonFitConv = 1e-10, clusterSigma = 0.; -// Population extrOpts; -// for (int k=0; k<3; k++) { -// extrOpts = prob.extractPotentialOptima(solutions, epsilonPhenoSpace, epsilonFitConv, clusterSigma, -1); -// listener.println("estimated number of found optima: " + extrOpts.size() + " with crit. " + epsilonPhenoSpace); -// if (extrOpts.size() > 0) { -// listener.println("fit measures: "); -// int critCnt = extrOpts.getEAIndividual(0).getFitness().length; -// for (int i=0; i List jobs = jobList.getSelectedJobs(); if (jobs.size() == 1) { OptimizationJob job = jobs.get(0); - AbstractOptimizationParameters curParams = (AbstractOptimizationParameters) ((AbstractModuleAdapter) jobList.module).getGOParameters(); + AbstractOptimizationParameters curParams = (AbstractOptimizationParameters) ((AbstractModuleAdapter) jobList.module).getOptimizationParameters(); curParams.setSameParams((AbstractOptimizationParameters) job.getGOParams()); - ((GenericModuleAdapter) jobList.module).setGOParameters(curParams); + ((GenericModuleAdapter) jobList.module).setOptimizationParameters(curParams); ((GenericModuleAdapter) jobList.module).getStatistics().getStatisticsParameter().setMultiRuns(job.getNumRuns()); ((GenericModuleAdapter) jobList.module).getStatistics().getStatisticsParameter().setFieldSelection(job.getFieldSelection(((GenericModuleAdapter) jobList.module).getStatistics().getStatisticsParameter().getFieldSelection())); } else { diff --git a/src/eva2/optimization/strategies/ClusteringHillClimbing.java b/src/eva2/optimization/strategies/ClusteringHillClimbing.java index c167a6b5..46ab9cc6 100644 --- a/src/eva2/optimization/strategies/ClusteringHillClimbing.java +++ b/src/eva2/optimization/strategies/ClusteringHillClimbing.java @@ -200,7 +200,7 @@ public class ClusteringHillClimbing implements InterfacePopulationChangedEventLi System.out.println("evalCycle: " + hcEvalCycle + ", evals now: " + evalsNow); } popD = PostProcess.clusterLocalSearch(localSearchMethod, m_Population, (AbstractOptimizationProblem) m_Problem, sigmaClust, evalsNow, 0.5, mutator); - // (m_Population, (AbstractOptimizationProblem)problem, sigmaClust, hcEvalCycle - (m_Population.getFunctionCalls() % hcEvalCycle), 0.5); + // (population, (AbstractOptimizationProblem)problem, sigmaClust, hcEvalCycle - (population.getFunctionCalls() % hcEvalCycle), 0.5); if (popD.head().getFunctionCalls() == funCallsBefore) { System.err.println("Bad case, increasing allowed evaluations!"); evalsNow = Math.max(evalsNow++, (int) (evalsNow * 1.2)); diff --git a/src/eva2/optimization/strategies/DifferentialEvolution.java b/src/eva2/optimization/strategies/DifferentialEvolution.java index ecda403c..3e325d47 100644 --- a/src/eva2/optimization/strategies/DifferentialEvolution.java +++ b/src/eva2/optimization/strategies/DifferentialEvolution.java @@ -32,19 +32,19 @@ import java.util.Vector; */ public class DifferentialEvolution implements InterfaceOptimizer, java.io.Serializable { - protected Population m_Population = new Population(); + protected Population population = new Population(); protected transient Population children = null; - protected AbstractOptimizationProblem m_Problem = new F1Problem(); - private DETypeEnum m_DEType; + protected AbstractOptimizationProblem optimizationProblem = new F1Problem(); + private DETypeEnum DEType; @Parameter(name = "F", description = "Differential Weight") - private double m_F = 0.8; + private double differentialWeight = 0.8; @Parameter(name = "CR", description = "Crossover Rate") - private double m_k = 0.6; // AKA CR + private double crossoverRate = 0.6; // AKA CR @Parameter(name = "Lambda", description = "Lambda") - private double m_Lambda = 0.6; + private double lambda = 0.6; private double m_Mt = 0.05; private int maximumAge = -1; @@ -65,15 +65,15 @@ public class DifferentialEvolution implements InterfaceOptimizer, java.io.Serial */ public DifferentialEvolution() { // sets DE2 as default - m_DEType = DETypeEnum.DE2_CurrentToBest; + DEType = DETypeEnum.DE2_CurrentToBest; } public DifferentialEvolution(int popSize, DETypeEnum type, double f, double k, double lambda, double mt) { - m_Population = new Population(popSize); - m_DEType = type; - m_F = f; - m_k = k; - m_Lambda = lambda; + population = new Population(popSize); + DEType = type; + differentialWeight = f; + crossoverRate = k; + this.lambda = lambda; m_Mt = mt; } @@ -83,13 +83,13 @@ public class DifferentialEvolution implements InterfaceOptimizer, java.io.Serial * @param a */ public DifferentialEvolution(DifferentialEvolution a) { - this.m_DEType = a.m_DEType; - this.m_Population = (Population) a.m_Population.clone(); - this.m_Problem = (AbstractOptimizationProblem) a.m_Problem.clone(); + this.DEType = a.DEType; + this.population = (Population) a.population.clone(); + this.optimizationProblem = (AbstractOptimizationProblem) a.optimizationProblem.clone(); this.m_Identifier = a.m_Identifier; - this.m_F = a.m_F; - this.m_k = a.m_k; - this.m_Lambda = a.m_Lambda; + this.differentialWeight = a.differentialWeight; + this.crossoverRate = a.crossoverRate; + this.lambda = a.lambda; this.m_Mt = a.m_Mt; this.maximumAge = a.maximumAge; @@ -106,9 +106,9 @@ public class DifferentialEvolution implements InterfaceOptimizer, java.io.Serial @Override public void init() { - this.m_Problem.initializePopulation(this.m_Population); -// children = new Population(m_Population.size()); - this.evaluatePopulation(this.m_Population); + this.optimizationProblem.initializePopulation(this.population); +// children = new Population(population.size()); + this.evaluatePopulation(this.population); this.firePropertyChangedEvent(Population.NEXT_GENERATION_PERFORMED); } @@ -124,14 +124,14 @@ public class DifferentialEvolution implements InterfaceOptimizer, java.io.Serial */ @Override public void initByPopulation(Population pop, boolean reset) { - this.m_Population = (Population) pop.clone(); + this.population = (Population) pop.clone(); if (reset) { - this.m_Population.init(); - this.evaluatePopulation(this.m_Population); + this.population.init(); + this.evaluatePopulation(this.population); this.firePropertyChangedEvent(Population.NEXT_GENERATION_PERFORMED); } -// if (reset) this.m_Population.init(); -// else children = new Population(m_Population.size()); +// if (reset) this.population.init(); +// else children = new Population(population.size()); } /** @@ -140,7 +140,7 @@ public class DifferentialEvolution implements InterfaceOptimizer, java.io.Serial * @param population The population that is to be evaluated */ private void evaluatePopulation(Population population) { - this.m_Problem.evaluate(population); + this.optimizationProblem.evaluate(population); population.incrGeneration(); } @@ -266,7 +266,7 @@ public class DifferentialEvolution implements InterfaceOptimizer, java.io.Serial x1 = indy.getDoubleData(); result = new double[x1.length]; - if (m_Problem instanceof AbstractMultiObjectiveOptimizationProblem) { + if (optimizationProblem instanceof AbstractMultiObjectiveOptimizationProblem) { // implements MODE for the multi-objective case: a dominating individual is selected for difference building Population domSet = pop.getDominatingSet((AbstractEAIndividual) indy); if (domSet.size() > 0) { @@ -290,27 +290,6 @@ public class DifferentialEvolution implements InterfaceOptimizer, java.io.Serial return result; } - /** - * This method returns two parents to the original individual - * - * @param pop The population to choose from - * @return the delta vector - */ -// private double[][] chooseRandomParents(Population pop) { -// InterfaceESIndividual indy1, indy2; -// double[][] result = new double[2][]; -// try { -// indy1 = (InterfaceESIndividual)pop.get(RNG.randomInt(0, pop.size()-1)); -// indy2 = (InterfaceESIndividual)pop.get(RNG.randomInt(0, pop.size()-1)); -// } catch (java.lang.ClassCastException e) { -// System.out.println("Differential Evolution currently requires InterfaceESIndividual as basic data type!"); -// return result; -// } -// result[0] = indy1.getDGenotype(); -// result[1] = indy2.getDGenotype(); -// return result; -// } - /** * This method will generate one new individual from the given population * @@ -318,7 +297,6 @@ public class DifferentialEvolution implements InterfaceOptimizer, java.io.Serial * @return AbstractEAIndividual */ public AbstractEAIndividual generateNewIndividual(Population pop, int parentIndex) { -// int firstParentIndex; AbstractEAIndividual indy; InterfaceDataTypeDouble esIndy; @@ -342,7 +320,7 @@ public class DifferentialEvolution implements InterfaceOptimizer, java.io.Serial oX = esIndy.getDoubleData(); vX = oX.clone(); nX = new double[oX.length]; - switch (this.m_DEType) { + switch (this.DEType) { case DE1_Rand_1: { // this is DE1 or DE/rand/1 double[] delta = this.fetchDeltaRandom(pop); @@ -462,25 +440,25 @@ public class DifferentialEvolution implements InterfaceOptimizer, java.io.Serial private double getCurrentK() { if (randomizeFKLambda) { - return RNG.randomDouble(m_k * 0.8, m_k * 1.2); + return RNG.randomDouble(crossoverRate * 0.8, crossoverRate * 1.2); } else { - return m_k; + return crossoverRate; } } private double getCurrentLambda() { if (randomizeFKLambda) { - return RNG.randomDouble(m_Lambda * 0.8, m_Lambda * 1.2); + return RNG.randomDouble(lambda * 0.8, lambda * 1.2); } else { - return m_Lambda; + return lambda; } } private double getCurrentF() { if (randomizeFKLambda) { - return RNG.randomDouble(m_F * 0.8, m_F * 1.2); + return RNG.randomDouble(differentialWeight * 0.8, differentialWeight * 1.2); } else { - return m_F; + return differentialWeight; } } @@ -524,72 +502,69 @@ public class DifferentialEvolution implements InterfaceOptimizer, java.io.Serial * However it may be easier to parallelize. */ public void optimizeGenerational() { -// AbstractEAIndividual indy = null, orig; int parentIndex; - // required for dynamic problems especially -// problem.evaluatePopulationStart(m_Population); if (children == null) { - children = new Population(m_Population.size()); + children = new Population(population.size()); } else { children.clear(); } - for (int i = 0; i < this.m_Population.size(); i++) { + for (int i = 0; i < this.population.size(); i++) { if (cyclePop) { parentIndex = i; } else { - parentIndex = RNG.randomInt(0, this.m_Population.size() - 1); + parentIndex = RNG.randomInt(0, this.population.size() - 1); } - AbstractEAIndividual indy = generateNewIndividual(m_Population, parentIndex); + AbstractEAIndividual indy = generateNewIndividual(population, parentIndex); children.add(indy); } - children.setGenerationTo(m_Population.getGeneration()); - m_Problem.evaluate(children); + children.setGeneration(population.getGeneration()); + optimizationProblem.evaluate(children); /** * MdP: added a reevalutation mechanism for dynamically changing * problems */ if (isReEvaluate()) { - for (int i = 0; i < this.m_Population.size(); i++) { + for (int i = 0; i < this.population.size(); i++) { - if (((AbstractEAIndividual) m_Population.get(i)).getAge() >= maximumAge) { - this.m_Problem.evaluate(((AbstractEAIndividual) m_Population.get(i))); - ((AbstractEAIndividual) m_Population.get(i)).SetAge(0); - m_Population.incrFunctionCalls(); + if (((AbstractEAIndividual) population.get(i)).getAge() >= maximumAge) { + this.optimizationProblem.evaluate(((AbstractEAIndividual) population.get(i))); + ((AbstractEAIndividual) population.get(i)).SetAge(0); + population.incrFunctionCalls(); } } } - int nextDoomed = getNextDoomed(m_Population, 0); - for (int i = 0; i < this.m_Population.size(); i++) { + int nextDoomed = getNextDoomed(population, 0); + for (int i = 0; i < this.population.size(); i++) { AbstractEAIndividual indy = children.getEAIndividual(i); if (cyclePop) { parentIndex = i; } else { - parentIndex = RNG.randomInt(0, this.m_Population.size() - 1); + parentIndex = RNG.randomInt(0, this.population.size() - 1); } if (nextDoomed >= 0) { // this one is lucky, may replace an 'old' one - m_Population.replaceIndividualAt(nextDoomed, indy); - nextDoomed = getNextDoomed(m_Population, nextDoomed + 1); + population.replaceIndividualAt(nextDoomed, indy); + nextDoomed = getNextDoomed(population, nextDoomed + 1); } else { - if (m_Problem instanceof AbstractMultiObjectiveOptimizationProblem & indy.getFitness().length > 1) { + if (optimizationProblem instanceof AbstractMultiObjectiveOptimizationProblem & indy.getFitness().length > 1) { ReplacementCrowding repl = new ReplacementCrowding(); - repl.insertIndividual(indy, m_Population, null); + repl.insertIndividual(indy, population, null); } else { -// index = RNG.randomInt(0, this.m_Population.size()-1); +// index = RNG.randomInt(0, this.population.size()-1); if (!compareToParent) { - parentIndex = RNG.randomInt(0, this.m_Population.size() - 1); + parentIndex = RNG.randomInt(0, this.population.size() - 1); } - AbstractEAIndividual orig = (AbstractEAIndividual) this.m_Population.get(parentIndex); + AbstractEAIndividual orig = (AbstractEAIndividual) this.population.get(parentIndex); if (indy.isDominatingDebConstraints(orig)) { - this.m_Population.replaceIndividualAt(parentIndex, indy); + this.population.replaceIndividualAt(parentIndex, indy); } } } } - this.m_Population.incrFunctionCallsBy(children.size()); - this.m_Population.incrGeneration(); + this.population.incrFunctionCallsBy(children.size()); + this.population.incrGeneration(); this.firePropertyChangedEvent(Population.NEXT_GENERATION_PERFORMED); } @@ -597,10 +572,10 @@ public class DifferentialEvolution implements InterfaceOptimizer, java.io.Serial AbstractEAIndividual indy = null, orig; int index; - int nextDoomed = getNextDoomed(m_Population, 0); + int nextDoomed = getNextDoomed(population, 0); // required for dynamic problems especially - m_Problem.evaluatePopulationStart(m_Population); + optimizationProblem.evaluatePopulationStart(population); /** @@ -609,96 +584,52 @@ public class DifferentialEvolution implements InterfaceOptimizer, java.io.Serial */ if (isReEvaluate()) { nextDoomed = -1; - for (int i = 0; i < this.m_Population.size(); i++) { + for (int i = 0; i < this.population.size(); i++) { - if (((AbstractEAIndividual) m_Population.get(i)).getAge() >= maximumAge) { - this.m_Problem.evaluate(((AbstractEAIndividual) m_Population.get(i))); - ((AbstractEAIndividual) m_Population.get(i)).SetAge(0); - m_Population.incrFunctionCalls(); + if (((AbstractEAIndividual) population.get(i)).getAge() >= maximumAge) { + this.optimizationProblem.evaluate(((AbstractEAIndividual) population.get(i))); + ((AbstractEAIndividual) population.get(i)).SetAge(0); + population.incrFunctionCalls(); } } } - for (int i = 0; i < this.m_Population.size(); i++) { + for (int i = 0; i < this.population.size(); i++) { if (cyclePop) { index = i; } else { - index = RNG.randomInt(0, this.m_Population.size() - 1); + index = RNG.randomInt(0, this.population.size() - 1); } - indy = generateNewIndividual(m_Population, index); -// if (cyclePop) indy = this.generateNewIndividual(this.m_Population, i); -// else indy = this.generateNewIndividual(this.m_Population, -1); - this.m_Problem.evaluate(indy); - this.m_Population.incrFunctionCalls(); + indy = generateNewIndividual(population, index); + this.optimizationProblem.evaluate(indy); + this.population.incrFunctionCalls(); if (nextDoomed >= 0) { // this one is lucky, may replace an 'old' one - m_Population.replaceIndividualAt(nextDoomed, indy); - nextDoomed = getNextDoomed(m_Population, nextDoomed + 1); + population.replaceIndividualAt(nextDoomed, indy); + nextDoomed = getNextDoomed(population, nextDoomed + 1); } else { - if (m_Problem instanceof AbstractMultiObjectiveOptimizationProblem) { + if (optimizationProblem instanceof AbstractMultiObjectiveOptimizationProblem) { - if (indy.isDominatingDebConstraints(m_Population.getEAIndividual(index))) { //child dominates the parent replace the parent - m_Population.replaceIndividualAt(index, indy); - } else if (!(m_Population.getEAIndividual(index).isDominatingDebConstraints(indy))) { //do nothing if parent dominates the child use crowding if neither one dominates the other one + if (indy.isDominatingDebConstraints(population.getEAIndividual(index))) { //child dominates the parent replace the parent + population.replaceIndividualAt(index, indy); + } else if (!(population.getEAIndividual(index).isDominatingDebConstraints(indy))) { //do nothing if parent dominates the child use crowding if neither one dominates the other one ReplacementNondominatedSortingDistanceCrowding repl = new ReplacementNondominatedSortingDistanceCrowding(); - repl.insertIndividual(indy, m_Population, null); + repl.insertIndividual(indy, population, null); } - // ReplacementCrowding repl = new ReplacementCrowding(); - // repl.insertIndividual(indy, m_Population, null); - - } else { -// index = RNG.randomInt(0, this.m_Population.size()-1); if (!compareToParent) { - index = RNG.randomInt(0, this.m_Population.size() - 1); + index = RNG.randomInt(0, this.population.size() - 1); } - orig = (AbstractEAIndividual) this.m_Population.get(index); + orig = (AbstractEAIndividual) this.population.get(index); if (indy.isDominatingDebConstraints(orig)) { - this.m_Population.replaceIndividualAt(index, indy); + this.population.replaceIndividualAt(index, indy); } } } } -//////// this was a non-steady-state-version -// if (children==null) children = new Population(m_Population.size()); -// for (int i = 0; i < this.m_Population.size(); i++) { -// indy = this.generateNewIndividual(this.m_Population); -// this.problem.evaluate(indy); -// this.m_Population.incrFunctionCalls(); -// children.add(indy); -// } -// int nextDoomed = getNextDoomed(m_Population, 0); -// -// for (int i=0; i= 0) { // kid is lucky, it may replace an 'old' individual -// m_Population.replaceIndividualAt(nextDoomed, indy); -// nextDoomed = getNextDoomed(m_Population, nextDoomed+1); -// } else { // duel with random one -// index = RNG.randomInt(0, this.m_Population.size()-1); -// org = (AbstractEAIndividual)this.m_Population.get(index); -// // if (envHasChanged) this.problem.evaluate(org); -// if (indy.isDominatingDebConstraints(org)) { -// this.m_Population.replaceIndividualAt(index, indy); -// } -// } -// } -// children.clear(); -//////// this was the original version -// for (int i = 0; i < this.m_Population.size(); i++) { -// indy = this.generateNewIndividual(this.m_Population); -// this.problem.evaluate(indy); -// this.m_Population.incrFunctionCalls(); -// index = RNG.randomInt(0, this.m_Population.size()-1); -// org = (AbstractEAIndividual)this.m_Population.get(index); -// if (indy.isDominatingDebConstraints(org)) { -// this.m_Population.remove(index); -// this.m_Population.add(index, indy); -// } -// } - m_Problem.evaluatePopulationEnd(m_Population); - this.m_Population.incrGeneration(); + optimizationProblem.evaluatePopulationEnd(population); + this.population.incrGeneration(); this.firePropertyChangedEvent(Population.NEXT_GENERATION_PERFORMED); } @@ -767,12 +698,12 @@ public class DifferentialEvolution implements InterfaceOptimizer, java.io.Serial */ @Override public void setProblem(InterfaceOptimizationProblem problem) { - this.m_Problem = (AbstractOptimizationProblem) problem; + this.optimizationProblem = (AbstractOptimizationProblem) problem; } @Override public InterfaceOptimizationProblem getProblem() { - return (InterfaceOptimizationProblem) this.m_Problem; + return (InterfaceOptimizationProblem) this.optimizationProblem; } /** @@ -786,8 +717,8 @@ public class DifferentialEvolution implements InterfaceOptimizer, java.io.Serial String result = ""; result += "Differential Evolution:\n"; result += "Optimization Problem: "; - result += this.m_Problem.getStringRepresentationForProblem(this) + "\n"; - result += this.m_Population.getStringRepresentation(); + result += this.optimizationProblem.getStringRepresentationForProblem(this) + "\n"; + result += this.population.getStringRepresentation(); return result; } @@ -838,12 +769,12 @@ public class DifferentialEvolution implements InterfaceOptimizer, java.io.Serial */ @Override public Population getPopulation() { - return this.m_Population; + return this.population; } @Override public void setPopulation(Population pop) { - this.m_Population = pop; + this.population = pop; } public String populationTipText() { @@ -862,15 +793,15 @@ public class DifferentialEvolution implements InterfaceOptimizer, java.io.Serial * * @param f */ - public void setF(double f) { - this.m_F = f; + public void setDifferentialWeight(double f) { + this.differentialWeight = f; } - public double getF() { - return this.m_F; + public double getDifferentialWeight() { + return this.differentialWeight; } - public String fTipText() { + public String differentialWeightTipText() { return "F is a real and constant factor which controls the amplification of the differential variation."; } @@ -880,21 +811,21 @@ public class DifferentialEvolution implements InterfaceOptimizer, java.io.Serial * * @param k */ - public void setK(double k) { + public void setCrossoverRate(double k) { if (k < 0) { k = 0; } if (k > 1) { k = 1; } - this.m_k = k; + this.crossoverRate = k; } - public double getK() { - return this.m_k; + public double getCrossoverRate() { + return this.crossoverRate; } - public String kTipText() { + public String crossoverrateTipText() { return "Probability of alteration through DE (a.k.a. CR, similar to discrete uniform crossover)."; } @@ -905,11 +836,11 @@ public class DifferentialEvolution implements InterfaceOptimizer, java.io.Serial * @param l */ public void setLambda(double l) { - this.m_Lambda = l; + this.lambda = l; } public double getLambda() { - return this.m_Lambda; + return this.lambda; } public String lambdaTipText() { @@ -945,14 +876,14 @@ public class DifferentialEvolution implements InterfaceOptimizer, java.io.Serial * @param s The type. */ public void setDEType(DETypeEnum s) { - this.m_DEType = s; + this.DEType = s; // show mt for trig. DE only GenericObjectEditor.setShowProperty(this.getClass(), "lambda", s == DETypeEnum.DE2_CurrentToBest); GenericObjectEditor.setShowProperty(this.getClass(), "mt", s == DETypeEnum.TrigonometricDE); } public DETypeEnum getDEType() { - return this.m_DEType; + return this.DEType; } public String dETypeTipText() { @@ -1009,17 +940,6 @@ public class DifferentialEvolution implements InterfaceOptimizer, java.io.Serial return "If true, values for k, f, lambda are randomly sampled around +/- 20% of the given values."; } - // public boolean isCyclePop() { -// return cyclePop; -// } -// -// public void setCyclePop(boolean cyclePop) { -// this.cyclePop = cyclePop; -// } -// -// public String cyclePopTipText() { -// return "Use all individuals as parents in cyclic sequence instead of randomly."; -// } public boolean isCompareToParent() { return compareToParent; } @@ -1071,6 +991,6 @@ public class DifferentialEvolution implements InterfaceOptimizer, java.io.Serial } public String reEvaluateTipText() { - return "Reeavulates individuals which are older than maximum age instead of discarding them"; + return "Re-evaluates individuals which are older than maximum age instead of discarding them"; } } \ No newline at end of file diff --git a/src/eva2/optimization/strategies/EvolutionStrategyIPOP.java b/src/eva2/optimization/strategies/EvolutionStrategyIPOP.java index e04a230c..d3b14357 100644 --- a/src/eva2/optimization/strategies/EvolutionStrategyIPOP.java +++ b/src/eva2/optimization/strategies/EvolutionStrategyIPOP.java @@ -88,7 +88,7 @@ public class EvolutionStrategyIPOP extends EvolutionStrategies implements Interf // // first perform the environment selection to select myu parents // parents = selectParents(); // -// // m_Population / parents are of sizes lambda / mu +// // population / parents are of sizes lambda / mu // if (parents.getEAIndividual(0).getMutationOperator() instanceof InterfaceMutationGenerational) { // ((InterfaceMutationGenerational)parents.getEAIndividual(0).getMutationOperator()).adaptAfterSelection(getPopulation(), parents); // } diff --git a/src/eva2/optimization/strategies/HillClimbing.java b/src/eva2/optimization/strategies/HillClimbing.java index 389da065..d7acaea5 100644 --- a/src/eva2/optimization/strategies/HillClimbing.java +++ b/src/eva2/optimization/strategies/HillClimbing.java @@ -92,7 +92,7 @@ public class HillClimbing implements InterfaceOptimizer, java.io.Serializable { this.m_Problem.evaluate(this.m_Population); for (int i = 0; i < this.m_Population.size(); i++) { if (((AbstractEAIndividual) original.get(i)).isDominatingDebConstraints(((AbstractEAIndividual) this.m_Population.get(i)))) { -// this.m_Population.remove(i); +// this.population.remove(i); // throw away mutated one and replace by old one this.m_Population.set(i, original.get(i)); } else { @@ -100,20 +100,20 @@ public class HillClimbing implements InterfaceOptimizer, java.io.Serializable { } } this.m_Population.incrGeneration(); -// for (int i = 0; i < this.m_Population.size(); i++) { -// indy1 = (AbstractEAIndividual) this.m_Population.get(i); +// for (int i = 0; i < this.population.size(); i++) { +// indy1 = (AbstractEAIndividual) this.population.get(i); // indy2 = (AbstractEAIndividual)(indy1).clone(); // indy2.mutate(); // this.problem.evaluate((AbstractEAIndividual) indy2); // //indy2.SetFitness(0, indy2.evaulateAsMiniBits()); -// this.m_Population.incrFunctionCalls(); +// this.population.incrFunctionCalls(); // //if (indy2.getFitness(0) < indy1.getFitness(0)) { // if (indy2.isDominating(indy1)) { -// this.m_Population.remove(i); -// this.m_Population.add(i, indy2); +// this.population.remove(i); +// this.population.add(i, indy2); // } // } -// this.m_Population.incrGeneration(); +// this.population.incrGeneration(); this.firePropertyChangedEvent(Population.NEXT_GENERATION_PERFORMED); } diff --git a/src/eva2/optimization/strategies/IslandModelEA.java b/src/eva2/optimization/strategies/IslandModelEA.java index e2d54c88..a29f8c92 100644 --- a/src/eva2/optimization/strategies/IslandModelEA.java +++ b/src/eva2/optimization/strategies/IslandModelEA.java @@ -88,7 +88,7 @@ public class IslandModelEA implements InterfacePopulationChangedEventListener, I } } -// this.m_Population = new Population(); +// this.population = new Population(); this.m_Population.clear(); this.m_Population.init(); this.m_Optimizer.init(); @@ -284,7 +284,7 @@ public class IslandModelEA implements InterfacePopulationChangedEventListener, I this.m_Population.addPopulation(pop); this.m_Population.incrFunctionCallsBy(pop.getFunctionCalls()); } -// System.out.println("Fitnesscalls :" + this.m_Population.getFunctionCalls()); +// System.out.println("Fitnesscalls :" + this.population.getFunctionCalls()); this.firePropertyChangedEvent(Population.NEXT_GENERATION_PERFORMED, this.m_Optimizer.getPopulation()); double plotValue = (this.m_Problem.getDoublePlotValue(this.m_Population)).doubleValue(); if (this.m_Show) { @@ -366,7 +366,7 @@ public class IslandModelEA implements InterfacePopulationChangedEventListener, I } //result += "=> The Optimization Problem: "; //result += this.problem.getStringRepresentationForProblem(this) +"\n"; - //result += this.m_Population.getStringRepresentation(); + //result += this.population.getStringRepresentation(); return result; } diff --git a/src/eva2/optimization/strategies/MemeticAlgorithm.java b/src/eva2/optimization/strategies/MemeticAlgorithm.java index d1c2935d..fbc41e9c 100644 --- a/src/eva2/optimization/strategies/MemeticAlgorithm.java +++ b/src/eva2/optimization/strategies/MemeticAlgorithm.java @@ -46,7 +46,7 @@ public class MemeticAlgorithm implements InterfaceOptimizer, } public MemeticAlgorithm(MemeticAlgorithm a) { - // this.m_Population = (Population)a.m_Population.clone(); + // this.population = (Population)a.population.clone(); this.m_Problem = (InterfaceLocalSearchable) a.m_Problem.clone(); this.m_GlobalOptimizer = (InterfaceOptimizer) a.m_GlobalOptimizer; this.selectorPlug = (InterfaceSelection) a.selectorPlug; diff --git a/src/eva2/optimization/strategies/MonteCarloSearch.java b/src/eva2/optimization/strategies/MonteCarloSearch.java index 3acad87b..fc9c8390 100644 --- a/src/eva2/optimization/strategies/MonteCarloSearch.java +++ b/src/eva2/optimization/strategies/MonteCarloSearch.java @@ -88,7 +88,7 @@ public class MonteCarloSearch implements InterfaceOptimizer, java.io.Serializabl public void optimize() { Population original = (Population) this.m_Population.clone(); -// this.problem.initializePopulation(this.m_Population); +// this.problem.initializePopulation(this.population); for (int i = 0; i < m_Population.size(); i++) { m_Population.getEAIndividual(i).defaultInit(null); } diff --git a/src/eva2/optimization/strategies/MultiObjectiveCMAES.java b/src/eva2/optimization/strategies/MultiObjectiveCMAES.java index ce88eb1b..0528de7b 100644 --- a/src/eva2/optimization/strategies/MultiObjectiveCMAES.java +++ b/src/eva2/optimization/strategies/MultiObjectiveCMAES.java @@ -178,10 +178,10 @@ public class MultiObjectiveCMAES implements InterfaceOptimizer, Serializable { */ @Override public void init() { - // initByPopulation(m_Population, true); + // initByPopulation(population, true); this.m_Population.setTargetSize(m_lambdamo); this.m_Problem.initializePopulation(this.m_Population); - // children = new Population(m_Population.size()); + // children = new Population(population.size()); this.evaluatePopulation(this.m_Population); this.firePropertyChangedEvent(Population.NEXT_GENERATION_PERFORMED); diff --git a/src/eva2/optimization/strategies/MultiObjectiveEA.java b/src/eva2/optimization/strategies/MultiObjectiveEA.java index 4473d0db..85ac6051 100644 --- a/src/eva2/optimization/strategies/MultiObjectiveEA.java +++ b/src/eva2/optimization/strategies/MultiObjectiveEA.java @@ -211,7 +211,7 @@ public class MultiObjectiveEA implements InterfaceOptimizer, java.io.Serializabl result += this.m_Optimizer.getStringRepresentation() + "\n"; //result += "=> The Optimization Problem: "; //result += this.problem.getStringRepresentationForProblem(this) +"\n"; - //result += this.m_Population.getStringRepresentation(); + //result += this.population.getStringRepresentation(); return result; } diff --git a/src/eva2/optimization/strategies/NelderMeadSimplex.java b/src/eva2/optimization/strategies/NelderMeadSimplex.java index 6546e185..48f28461 100644 --- a/src/eva2/optimization/strategies/NelderMeadSimplex.java +++ b/src/eva2/optimization/strategies/NelderMeadSimplex.java @@ -296,7 +296,7 @@ public class NelderMeadSimplex implements InterfaceOptimizer, Serializable, Inte // Mathematics.projectToRange(x, range); // ((InterfaceDataTypeDouble)ind).setDoubleGenotype(x); // problem.evaluate(ind); -// this.m_Population.incrFunctionCalls(); +// this.population.incrFunctionCalls(); } m_Population.set(m_Population.getIndexOfWorstIndividualNoConstr(fitIndex), ind, fitIndex); } else {//keine Verbesserung gefunden shrink!! @@ -309,7 +309,7 @@ public class NelderMeadSimplex implements InterfaceOptimizer, Serializable, Inte c[i] = 0.5 * c[i] + 0.5 * u_1[i]; } ((InterfaceDataTypeDouble) m_Population.getEAIndividual(j)).setDoubleGenotype(c); -// m_Population.getEAIndividual(j).resetConstraintViolation(); // not a good idea because during evaluation, a stats update may be performed which mustnt see indies which are evaluated, but possible constraints have been reset. +// population.getEAIndividual(j).resetConstraintViolation(); // not a good idea because during evaluation, a stats update may be performed which mustnt see indies which are evaluated, but possible constraints have been reset. } m_Problem.evaluate(m_Population); } diff --git a/src/eva2/optimization/strategies/ParticleFilterOptimization.java b/src/eva2/optimization/strategies/ParticleFilterOptimization.java index 597ab5bd..fe379f5f 100644 --- a/src/eva2/optimization/strategies/ParticleFilterOptimization.java +++ b/src/eva2/optimization/strategies/ParticleFilterOptimization.java @@ -96,8 +96,8 @@ public class ParticleFilterOptimization implements InterfaceOptimizer, java.io.S @Override public void init() { - //System.out.println("popsize is " + m_Population.size()); - //System.out.println("pops targ is " + m_Population.getPopulationSize()); + //System.out.println("popsize is " + population.size()); + //System.out.println("pops targ is " + population.getPopulationSize()); if (initialVelocity <= 0.) { (((AbstractOptimizationProblem) m_Problem).getIndividualTemplate()).setMutationOperator(new MutateESFixedStepSize(mutationSigma)); @@ -264,7 +264,7 @@ public class ParticleFilterOptimization implements InterfaceOptimizer, java.io.S m_Population = evaluatePopulation(nextGeneration); -// collectStatistics(m_Population); +// collectStatistics(population); this.firePropertyChangedEvent(Population.NEXT_GENERATION_PERFORMED); diff --git a/src/eva2/optimization/strategies/ParticleSwarmOptimization.java b/src/eva2/optimization/strategies/ParticleSwarmOptimization.java index bfcdd4be..2c730344 100644 --- a/src/eva2/optimization/strategies/ParticleSwarmOptimization.java +++ b/src/eva2/optimization/strategies/ParticleSwarmOptimization.java @@ -698,7 +698,7 @@ public class ParticleSwarmOptimization implements InterfaceOptimizer, java.io.Se // if (index != 0) return; // double[] bestPosition = (double[])m_BestIndividual.getData(partBestPosKey); -// double[] localBestPos = findNeighbourhoodOptimum(index, m_Population); +// double[] localBestPos = findNeighbourhoodOptimum(index, population); // this.m_Plot.setConnectedPoint(curPosition[0], curPosition[1], index+1); // this.m_Plot.setConnectedPoint(curPosition[0] + curVelocity[0], curPosition[1] + curVelocity[1], index+1); // this.m_Plot.setConnectedPoint(curPosition[0], curPosition[1], index+2); @@ -1355,7 +1355,7 @@ public class ParticleSwarmOptimization implements InterfaceOptimizer, java.io.Se @Override public void optimize() { -// System.out.println(">>> " + m_Population.getStringRepresentation()); +// System.out.println(">>> " + population.getStringRepresentation()); startOptimize(); // Update the individuals @@ -1370,12 +1370,12 @@ public class ParticleSwarmOptimization implements InterfaceOptimizer, java.io.Se // log the best individual of the population logBestIndividual(); -// System.out.println("<<< " + m_Population.getStringRepresentation()); +// System.out.println("<<< " + population.getStringRepresentation()); -// if (doLocalSearch && (m_Population.getGeneration()%localSearchGens==0)) { -//// System.out.println("Local search at gen "+m_Population.getGeneration()); -// Population bestN = m_Population.getBestNIndividuals(Math.max(1,(int)(lsCandidateRatio*m_Population.size()))); -//// Population bestN = m_Population.getSortedNIndividuals(Math.max(1,(int)(lsCandidateRatio*m_Population.size())), false); +// if (doLocalSearch && (population.getGeneration()%localSearchGens==0)) { +//// System.out.println("Local search at gen "+population.getGeneration()); +// Population bestN = population.getBestNIndividuals(Math.max(1,(int)(lsCandidateRatio*population.size()))); +//// Population bestN = population.getSortedNIndividuals(Math.max(1,(int)(lsCandidateRatio*population.size())), false); // Population cands=(Population)bestN.clone(); // int maxSteps=cands.size()*lsStepsPerInd; // int stepsDone = PostProcess.processSingleCandidates(PostProcessMethod.nelderMead, cands, maxSteps, 0.01, (AbstractOptimizationProblem)this.problem, null); @@ -1388,8 +1388,8 @@ public class ParticleSwarmOptimization implements InterfaceOptimizer, java.io.Se // } // if (stepsDone>maxSteps) { //// System.err.println("Warning: more steps performed than alloed in PSO LS: " + stepsDone + " vs. " + maxSteps); -// m_Population.incrFunctionCallsBy(stepsDone); -// } else m_Population.incrFunctionCallsBy(maxSteps); +// population.incrFunctionCallsBy(stepsDone); +// } else population.incrFunctionCallsBy(maxSteps); // } this.firePropertyChangedEvent(Population.NEXT_GENERATION_PERFORMED); @@ -1554,10 +1554,10 @@ public class ParticleSwarmOptimization implements InterfaceOptimizer, java.io.Se // } // for (int i=0; i