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Remove apache, gson, cli, reflection dependencies for slimmer EvA2

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package.
This commit is contained in:
Fabian Becker
2014-11-02 14:03:23 +01:00
parent 89402e0b05
commit edaa58bd5a
6 changed files with 10 additions and 755 deletions
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21
pom.xml
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@@ -27,27 +27,6 @@
<artifactId>javahelp</artifactId>
<version>2.0.05</version>
</dependency>
<dependency>
<groupId>org.apache.commons</groupId>
<artifactId>commons-math3</artifactId>
<version>3.1.1</version>
</dependency>
<dependency>
<groupId>commons-cli</groupId>
<artifactId>commons-cli</artifactId>
<version>1.2</version>
</dependency>
<dependency>
<groupId>com.google.code.gson</groupId>
<artifactId>gson</artifactId>
<version>2.3</version>
<scope>compile</scope>
</dependency>
<dependency>
<groupId>org.reflections</groupId>
<artifactId>reflections</artifactId>
<version>0.9.9</version>
</dependency>
</dependencies>

712
src/eva2/cli/Main.java
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@@ -1,719 +1,15 @@
package eva2.cli;
import com.google.gson.*;
import eva2.OptimizerFactory;
import eva2.optimization.OptimizationStateListener;
import eva2.optimization.enums.DEType;
import eva2.optimization.enums.PSOTopology;
import eva2.optimization.population.InterfacePopulationChangedEventListener;
import eva2.optimization.modules.OptimizationParameters;
import eva2.optimization.operator.crossover.CrossoverESDefault;
import eva2.optimization.operator.crossover.InterfaceCrossover;
import eva2.optimization.operator.mutation.InterfaceMutation;
import eva2.optimization.operator.mutation.MutateDefault;
import eva2.optimization.operator.selection.InterfaceSelection;
import eva2.optimization.operator.selection.SelectXProbRouletteWheel;
import eva2.optimization.operator.terminators.CombinedTerminator;
import eva2.optimization.operator.terminators.FitnessValueTerminator;
import eva2.optimization.population.Population;
import eva2.problems.AbstractProblemDouble;
import eva2.problems.AbstractProblemDoubleOffset;
import eva2.optimization.strategies.DifferentialEvolution;
import eva2.optimization.strategies.InterfaceOptimizer;
import org.apache.commons.cli.*;
import org.reflections.Reflections;
import java.lang.reflect.Modifier;
import java.util.Arrays;
import java.util.Map;
import java.util.Set;
import java.util.TreeMap;
import java.util.logging.Level;
import java.util.logging.Logger;
import eva2.optimization.go.InterfaceOptimizationParameters;
/**
* Main Class for the EvA2 Command Line Interface
*
* The command line interface features a limited subset of the EvA2
* optimization suite since it's difficult to parameterize all available
* classes in EvA2 from the command line.
* Supported Features:
* - Select all optimization problems that implement InterfaceOptimizationProblem
* - Select all optimizers that implement InterfaceOptimizer
* * Not all optimizers are configurable on the command line and will run
* with default parameters.
* * Optimizers can use the @Description / @Parameter annotations to specify
* parameters for CLI
* - Configure default parameters
* * Population size
* * Number of optimization runs (multi-runs)
* - Termination:
* * Not configurable!
* * Default: EvaluationTerminator(20000)
* Created by becker on 01.11.2014.
*/
public class Main implements OptimizationStateListener, InterfacePopulationChangedEventListener {
private static Logger LOGGER = Logger.getLogger(Main.class.getName());
private int populationSize = 20;
private int numberOfRuns = 1;
private int dimension = 30;
private long seed = System.currentTimeMillis();
private AbstractProblemDoubleOffset problem;
private InterfaceOptimizer optimizer;
private InterfaceMutation mutator;
private InterfaceCrossover crossover;
private InterfaceSelection selection;
private JsonObject jsonObject;
private JsonArray optimizationRuns;
private JsonArray generationsArray;
private double[] fBias = { -4.5000000e+002, -4.5000000e+002, -4.5000000e+002, -4.5000000e+002, -3.1000000e+002,
3.9000000e+002, -1.8000000e+002, -1.4000000e+002, -3.3000000e+002, -3.3000000e+002, 9.0000000e+001,
-4.6000000e+002, -1.3000000e+002, -3.0000000e+002, 1.2000000e+002, 1.2000000e+002, 1.2000000e+002,
1.0000000e+001, 1.0000000e+001, 1.0000000e+001, 3.6000000e+002, 3.6000000e+002, 3.6000000e+002,
2.6000000e+002, 2.6000000e+002};
/**
* Creates a set of default options used in all optimizations.
*
* @return Options Default options used for optimizations
*/
private Options createDefaultCommandLineOptions() {
Options opt = new Options();
opt.addOption(OptionBuilder
.withLongOpt("optimizer")
.withDescription("Optimizer")
.hasArg()
.create("op")
);
opt.addOption("ps", "popsize", true, "Population size");
opt.addOption("n", "runs", true, "Number of runs to perform");
opt.addOption("s", "seed", true, "Random seed");
// Those two only make sense when used in an algorithm with mutation/crossover
opt.addOption("pc", true, "Crossover Probability");
opt.addOption("pm", true, "Mutation Probability");
opt.addOption("mutator", true, "Mutator Operator");
opt.addOption("crossover", true, "Crossover Operator");
opt.addOption("selection", true, "Selection Operator");
opt.addOption(OptionBuilder
.withLongOpt("help")
.withDescription("Shows this help message or specific help for [optimizer]")
.hasOptionalArgs(1)
.create('h')
);
opt.addOption(OptionBuilder
.withLongOpt("problem")
.withDescription("Select Optimization Problem to optimize.")
.hasArg()
.create('p')
);
opt.addOption("dim", true, "Problem Dimension");
return opt;
}
@Override
public void performedStop() {
LOGGER.info("Optimization stopped.");
}
@Override
public void performedStart(String infoString) {
LOGGER.info("Optimization started.");
}
@Override
public void performedRestart(String infoString) {
LOGGER.info("Optimization restarted.");
}
@Override
public void updateProgress(int percent, String msg) {
printProgressBar(percent);
}
public static void printProgressBar(int percent) {
StringBuilder bar = new StringBuilder("[");
for (int i = 0; i < 50; i++) {
if (i < (percent / 2)) {
bar.append("=");
} else if (i == (percent / 2)) {
bar.append(">");
} else {
bar.append(" ");
}
}
bar.append("] " + percent + "% ");
System.out.print("\r" + bar.toString());
}
public static Map<String, Class<? extends InterfaceOptimizer>> createOptimizerList() {
Map<String, Class<? extends InterfaceOptimizer>> optimizerList = new TreeMap<>();
Reflections reflections = new Reflections("eva2.optimization.strategies");
Set<Class<? extends InterfaceOptimizer>> optimizers = reflections.getSubTypesOf(InterfaceOptimizer.class);
for (Class<? extends InterfaceOptimizer> optimizer : optimizers) {
// We only want instantiable classes
if (optimizer.isInterface() || Modifier.isAbstract(optimizer.getModifiers())) {
continue;
}
optimizerList.put(optimizer.getSimpleName(), optimizer);
}
return optimizerList;
}
public static Map<String, Class<? extends AbstractProblemDoubleOffset>> createProblemList() {
Map<String, Class<? extends AbstractProblemDoubleOffset>> problemList = new TreeMap<>();
Reflections reflections = new Reflections("eva2.problems");
Set<Class<? extends AbstractProblemDoubleOffset>> problems = reflections.getSubTypesOf(AbstractProblemDoubleOffset.class);
for (Class<? extends AbstractProblemDoubleOffset> problem : problems) {
// We only want instantiable classes
if (problem.isInterface() || Modifier.isAbstract(problem.getModifiers())) {
continue;
}
problemList.put(problem.getSimpleName(), problem);
}
return problemList;
}
public static Map<String, Class<? extends InterfaceMutation>> createMutatorList() {
Map<String, Class<? extends InterfaceMutation>> mutationList = new TreeMap<>();
Reflections reflections = new Reflections("eva2.optimization.operator.mutation");
Set<Class<? extends InterfaceMutation>> mutators = reflections.getSubTypesOf(InterfaceMutation.class);
for (Class<? extends InterfaceMutation> mutator : mutators) {
// We only want instantiable classes
if (mutator.isInterface() || Modifier.isAbstract(mutator.getModifiers())) {
continue;
}
mutationList.put(mutator.getSimpleName(), mutator);
}
return mutationList;
}
public static Map<String, Class<? extends InterfaceCrossover>> createCrossoverList() {
Map<String, Class<? extends InterfaceCrossover>> crossoverList = new TreeMap<>();
Reflections reflections = new Reflections("eva2.optimization.operator.crossover");
Set<Class<? extends InterfaceCrossover>> crossovers = reflections.getSubTypesOf(InterfaceCrossover.class);
for (Class<? extends InterfaceCrossover> crossover : crossovers) {
// We only want instantiable classes
if (crossover.isInterface() || Modifier.isAbstract(crossover.getModifiers())) {
continue;
}
crossoverList.put(crossover.getSimpleName(), crossover);
}
return crossoverList;
}
public static Map<String, Class<? extends InterfaceSelection>> createSelectionList() {
Map<String, Class<? extends InterfaceSelection>> selectionList = new TreeMap<>();
Reflections reflections = new Reflections("eva2.optimization.operator.selection");
Set<Class<? extends InterfaceSelection>> selections = reflections.getSubTypesOf(InterfaceSelection.class);
for (Class<? extends InterfaceSelection> selection : selections) {
// We only want instantiable classes
if (selection.isInterface() || Modifier.isAbstract(selection.getModifiers())) {
continue;
}
selectionList.put(selection.getSimpleName(), selection);
}
return selectionList;
}
public static void showHelp(Options options) {
HelpFormatter helpFormatter = new HelpFormatter();
helpFormatter.printHelp("java -jar EvA2.jar", "Global Parameters", options, "", true);
}
public class Main {
public static void main(String[] args) {
Main optimizationMain = new Main(args);
optimizationMain.runOptimization();
}
InterfaceOptimizationParameters parameters = OptimizationBuilder.parseArguments(args);
public Main(String[] args) {
int index = Arrays.asList(args).indexOf("--");
String[] programParams = args;
String[] optimizerParams;
if (index >= 0) {
programParams = Arrays.copyOfRange(args, 0, index);
optimizerParams = Arrays.copyOfRange(args, index + 1, args.length);
} else {
optimizerParams = new String[]{};
}
this.jsonObject = new JsonObject();
this.optimizationRuns = new JsonArray();
this.generationsArray = new JsonArray();
/**
* Default command line options only require help or optimizer.
* Later we build extended command line options depending on
* the selected optimizer.
*/
Options defaultOptions = this.createDefaultCommandLineOptions();
/**
* Parse default options.
*/
CommandLineParser cliParser = new BasicParser();
CommandLine commandLine = null;
try {
commandLine = cliParser.parse(defaultOptions, programParams);
} catch (ParseException e) {
showHelp(defaultOptions);
System.exit(-1);
}
/**
* Process help and help sub pages.
*/
if (commandLine.hasOption("help")) {
String helpOption = commandLine.getOptionValue("help");
if (helpOption == null) {
showHelp(defaultOptions);
} else {
switch (helpOption) {
case "optimizer":
showOptimizerHelp();
break;
case "problem":
listProblems();
break;
default:
showHelp(defaultOptions);
break;
}
}
System.exit(0);
}
// OK, so we've got valid parameters - let's setup the optimizer and problem
if (commandLine.hasOption("popsize")) {
this.populationSize = Integer.parseInt(commandLine.getOptionValue("popsize"));
}
if (commandLine.hasOption("runs")) {
this.numberOfRuns = Integer.parseInt(commandLine.getOptionValue("runs"));
}
if (commandLine.hasOption("seed")) {
this.seed = Long.parseLong(commandLine.getOptionValue("seed"));
}
if (commandLine.hasOption("dim")) {
this.dimension = Integer.parseInt(commandLine.getOptionValue("dim"));
}
if (commandLine.hasOption("problem")) {
String problemName = commandLine.getOptionValue("problem");
setProblemFromName(problemName);
this.problem.setProblemDimension(this.dimension);
} else {
LOGGER.severe("No problem specified. Please specify a problem with '--problem'.");
System.exit(-1);
}
if (commandLine.hasOption("mutator")) {
String mutatorName = commandLine.getOptionValue("mutator");
try {
setMutatorFromName(mutatorName);
} catch (Exception ex) {
System.out.println(ex.getMessage());
System.exit(-1);
}
} else {
this.mutator = new MutateDefault();
}
if (commandLine.hasOption("crossover")) {
String crossoverName = commandLine.getOptionValue("crossover");
try {
setCrossoverFromName(crossoverName);
} catch (Exception ex) {
System.out.println(ex.getMessage());
System.exit(-1);
}
} else {
this.crossover = new CrossoverESDefault();
}
if (commandLine.hasOption("selection")) {
String selectionName = commandLine.getOptionValue("selection");
try {
setSelectionFromName(selectionName);
} catch (Exception ex) {
System.out.println(ex.getMessage());
System.exit(-1);
}
} else {
this.selection = new SelectXProbRouletteWheel();
}
// Depends on mutator/crossover/selection being set
if (commandLine.hasOption("optimizer")) {
String optimizerName = commandLine.getOptionValue("optimizer");
try {
createOptimizerFromName(optimizerName, optimizerParams);
} catch(Exception ex) {
System.out.println(ex.getMessage());
System.exit(-1);
}
}
this.jsonObject.addProperty("population_size", this.populationSize);
this.jsonObject.addProperty("number_of_runs", this.numberOfRuns);
this.jsonObject.addProperty("dimension", this.dimension);
this.jsonObject.addProperty("seed", this.seed);
JsonObject problemObject = new JsonObject();
problemObject.addProperty("name", this.problem.getName());
problemObject.addProperty("dimension", 30);
this.jsonObject.add("problem", problemObject);
}
private void setMutatorFromName(String mutatorName) {
Map<String, Class<? extends InterfaceMutation>> mutatorList = createMutatorList();
Class<? extends InterfaceMutation> mutator = mutatorList.get(mutatorName);
try {
this.mutator = mutator.newInstance();
} catch (InstantiationException e) {
e.printStackTrace();
} catch (IllegalAccessException e) {
e.printStackTrace();
}
}
private void setCrossoverFromName(String crossoverName) {
Map<String, Class<? extends InterfaceCrossover>> crossoverList = createCrossoverList();
Class<? extends InterfaceCrossover> crossover = crossoverList.get(crossoverName);
try {
this.crossover = crossover.newInstance();
} catch (InstantiationException e) {
e.printStackTrace();
} catch (IllegalAccessException e) {
e.printStackTrace();
}
}
private void setSelectionFromName(String selectionName) {
Map<String, Class<? extends InterfaceSelection>> selectionList = createSelectionList();
Class<? extends InterfaceSelection> selection = selectionList.get(selectionName);
try {
this.selection = selection.newInstance();
} catch (InstantiationException e) {
e.printStackTrace();
} catch (IllegalAccessException e) {
e.printStackTrace();
}
}
/**
* This method will create the various optimizers that are supported on the CLI.
* It's a really messy process since neither Java nor args4j/apache-cli can handle
* complex object parameters. The trick here is that all parameters after the
* double-dash (--) are treated as parameters for the optimization algorithm.
*
* @param optimizerName The name of the optimizer.
* @param optimizerParams The remaining command line parameters.
* @throws Exception
*/
private void createOptimizerFromName(String optimizerName, String[] optimizerParams) throws Exception {
Options opt = new Options();
CommandLineParser cliParser = new BasicParser();
CommandLine commandLine = null;
switch(optimizerName) {
case "DifferentialEvolution": {
opt.addOption("F", true, "Differential Weight");
opt.addOption("CR", true, "Crossover Rate");
opt.addOption("DEType", true, "DE Type ()");
/**
* Parse default options.
*/
try {
commandLine = cliParser.parse(opt, optimizerParams);
} catch (ParseException e) {
showHelp(opt);
System.exit(-1);
}
double f = 0.8, lambda = 0.6, cr = 0.6;
if (commandLine.hasOption("F")) {
f = Double.parseDouble(commandLine.getOptionValue("F"));
}
if (commandLine.hasOption("CR")) {
cr = Double.parseDouble(commandLine.getOptionValue("CR"));
}
this.optimizer = OptimizerFactory.createDifferentialEvolution(this.problem, this.populationSize, f, lambda, cr, this);
if (commandLine.hasOption("DEType")) {
((DifferentialEvolution)this.optimizer).setDEType(
DEType.getFromId(
Integer.parseInt(commandLine.getOptionValue("DEType"))
)
);
}
break;
}
case "GeneticAlgorithm": {
double pm = 0.01, pc = 0.5;
opt.addOption("pm", true, "Mutation Probability");
opt.addOption("pc", true, "Crossover Probability");
/**
* Parse default options.
*/
try {
commandLine = cliParser.parse(opt, optimizerParams);
} catch (ParseException e) {
showHelp(opt);
System.exit(-1);
}
if (commandLine.hasOption("pm")) {
pm = Double.parseDouble(commandLine.getOptionValue("pm"));
}
if (commandLine.hasOption("pc")) {
pc = Double.parseDouble(commandLine.getOptionValue("pc"));
}
this.optimizer = OptimizerFactory.createGeneticAlgorithm(mutator, pm, crossover, pc, selection, this.populationSize, this.problem, this);
break;
}
case "ParticleSwarmOptimization": {
double phi1 = 2.05, phi2 = 2.05, speedLimit = 0.1;
int topoRange = 2;
PSOTopology selectedTopology = PSOTopology.star;
opt.addOption("speedLimit", true, "Speed Limit");
opt.addOption("topology", true, "Particle Swarm Topology (0-7)");
opt.addOption("phi1", true, "Phi 1");
opt.addOption("phi2", true, "Phi 2");
/**
* Parse default options.
*/
try {
commandLine = cliParser.parse(opt, optimizerParams);
} catch (ParseException e) {
showHelp(opt);
System.exit(-1);
}
if (commandLine.hasOption("phi1")) {
phi1 = Double.parseDouble(commandLine.getOptionValue("phi1"));
}
if (commandLine.hasOption("phi2")) {
phi2 = Double.parseDouble(commandLine.getOptionValue("phi2"));
}
if (commandLine.hasOption("topology")) {
selectedTopology = PSOTopology.getFromId(Integer.parseInt(commandLine.getOptionValue("topology")));
}
if (commandLine.hasOption("speedLimit")) {
speedLimit = Double.parseDouble(commandLine.getOptionValue("speedLimit"));
}
this.optimizer = OptimizerFactory.createParticleSwarmOptimization(problem, this.populationSize, phi1, phi2, speedLimit, selectedTopology, topoRange, this);
break;
}
case "EvolutionStrategies": {
double pm, pc;
int mu = 5, lambda = 20;
boolean plusStrategy = false;
opt.addOption("pm", true, "Mutation Probability");
opt.addOption("pc", true, "Crossover Probability");
opt.addOption("mu", true, "Mu");
opt.addOption("lambda", true, "Lambda");
opt.addOption("plusStrategy", true, "Whether to use the plus or comma strategy.");
/**
* Parse default options.
*/
try {
commandLine = cliParser.parse(opt, optimizerParams);
} catch (ParseException e) {
showHelp(opt);
System.exit(-1);
}
if (commandLine.hasOption("pm")) {
pm = Double.parseDouble(commandLine.getOptionValue("pm"));
} else {
pm = 0.01;
}
if (commandLine.hasOption("pc")) {
pc = Double.parseDouble(commandLine.getOptionValue("pc"));
} else {
pc = 0.9;
}
if (commandLine.hasOption("mu")) {
mu = Integer.parseInt(commandLine.getOptionValue("mu"));
}
if (commandLine.hasOption("lambda")) {
lambda = Integer.parseInt(commandLine.getOptionValue("lambda"));
}
if (commandLine.hasOption("plusStrategy")) {
plusStrategy = Boolean.parseBoolean(commandLine.getOptionValue("plusStrategy"));
}
this.optimizer = OptimizerFactory.createEvolutionStrategy(mu, lambda, plusStrategy, this.mutator, pm, this.crossover, pc, this.selection, problem, this);
break;
}
default:
throw new Exception("Unsupported Optimizer");
}
}
private void setProblemFromName(String problemName) {
Map<String, Class<? extends AbstractProblemDoubleOffset>> problemList = createProblemList();
Class<? extends AbstractProblemDoubleOffset> problem = problemList.get(problemName);
try {
this.problem = problem.newInstance();
} catch (InstantiationException e) {
e.printStackTrace();
} catch (IllegalAccessException e) {
e.printStackTrace();
}
//setCECDefaults(this.problem);
}
private void setCECDefaults(AbstractProblemDouble problem) {
switch(problem.getName()) {
case "F1-Problem": // F1: Shifted Sphere
this.problem.setDefaultRange(100);
this.problem.setYOffset(fBias[0]);
break;
case "F2-Problem": // F6: Shifted Rosenbrock's Function
this.problem.setDefaultRange(100);
this.problem.setYOffset(fBias[5]);
break;
case "F5-Problem": // F2: Schwefel's 1.2
this.problem.setDefaultRange(100);
this.problem.setYOffset(fBias[1]);
break;
case "F6-Problem": // F9: Shifted Rastrigin's Function
this.problem.setDefaultRange(5);
this.problem.setYOffset(fBias[8]);
break;
default:
LOGGER.info("No CEC'05 default parameters for this problem found.");
break;
}
}
/**
* Executes the optimization and outputs a JSON document to the command line
* with the statistics of the optimization run(s).
*/
private void runOptimization() {
for(int i = 0; i < this.numberOfRuns; i++) {
// Terminate after 10000 function evaluations OR after reaching a fitness < 0.1
OptimizerFactory.setEvaluationTerminator(500000);
//OptimizerFactory.setTerminator(new FitnessValueTerminator(new double[]{0.0001}));
OptimizerFactory.addTerminator(new FitnessValueTerminator(new double[]{0.0001}), CombinedTerminator.OR);
LOGGER.log(Level.INFO, "Running {0}", optimizer.getName());
OptimizationParameters params = OptimizerFactory.makeParams(optimizer, this.populationSize, this.problem, this.seed, OptimizerFactory.getTerminator());
double[] result = OptimizerFactory.optimizeToDouble(params);
JsonObject optimizationDetails = new JsonObject();
optimizationDetails.addProperty("total_time", 1.0);
optimizationDetails.addProperty("total_function_calls", optimizer.getPopulation().getFunctionCalls());
optimizationDetails.addProperty("termination_criteria", OptimizerFactory.terminatedBecause());
optimizationDetails.add("generations", this.generationsArray);
JsonArray solutionArray = new JsonArray();
for(double val : result) {
solutionArray.add(new JsonPrimitive(val));
}
optimizationDetails.add("solution", solutionArray);
this.optimizationRuns.add(optimizationDetails);
// Needs to be re-created here.
this.generationsArray = new JsonArray();
}
this.jsonObject.add("runs", this.optimizationRuns);
Gson gson = new GsonBuilder().setPrettyPrinting().create();
System.out.println(gson.toJson(this.jsonObject));
}
private static void showOptimizerHelp() {
Map<String, Class<? extends InterfaceOptimizer>> optimizerList = createOptimizerList();
System.out.println("Available Optimizers:");
for (String name : optimizerList.keySet()) {
System.out.printf("%s\n", name);
}
}
private static void listProblems() {
Map<String, Class<? extends AbstractProblemDoubleOffset>> problemList = createProblemList();
System.out.println("Available Problems:");
for (String name : problemList.keySet()) {
System.out.printf("%s\n", name);
}
}
@Override
public void registerPopulationStateChanged(Object source, String name) {
if (name.equals("NextGenerationPerformed")) {
InterfaceOptimizer optimizer = (InterfaceOptimizer)source;
Population population = optimizer.getPopulation();
JsonObject newGeneration = new JsonObject();
newGeneration.addProperty("generation", population.getGeneration());
newGeneration.addProperty("function_calls", population.getFunctionCalls());
JsonArray bestFitness = new JsonArray();
for(double val : population.getBestFitness()) {
bestFitness.add(new JsonPrimitive(val));
}
newGeneration.add("best_fitness", bestFitness);
JsonArray meanFitness = new JsonArray();
for(double val : population.getMeanFitness()) {
meanFitness.add(new JsonPrimitive(val));
}
newGeneration.add("mean_fitness", meanFitness);
//System.out.println(newGeneration.toString());
this.generationsArray.add(newGeneration);
}
}
}

15
src/eva2/cli/NewMain.java
View File

@@ -1,15 +0,0 @@
package eva2.cli;
import eva2.optimization.go.InterfaceOptimizationParameters;
/**
* Created by becker on 01.11.2014.
*/
public class NewMain {
public static void main(String[] args) {
InterfaceOptimizationParameters parameters = OptimizationBuilder.parseArguments(args);
}
}

2
src/eva2/cli/OptimizationBuilder.java
View File

@@ -111,7 +111,7 @@ public final class OptimizationBuilder {
Class<?>[] params = new Class[0];
try {
Constructor constructor = clazz.getConstructor(params);
instance = (T)constructor.newInstance(null);
instance = (T)constructor.newInstance(new Object[]{});
} catch (NoSuchMethodException | InvocationTargetException | InstantiationException | IllegalAccessException ex) {
ex.printStackTrace();
}

13
src/eva2/optimization/statistics/EvAStatisticalEvaluation.java
View File

@@ -6,11 +6,12 @@ import eva2.optimization.enums.StatisticsOnTwoSampledData;
import eva2.tools.ReflectPackage;
import eva2.tools.StringTools;
import eva2.tools.math.Mathematics;
import org.apache.commons.math3.stat.ranking.NaNStrategy;
import org.apache.commons.math3.stat.ranking.TiesStrategy;
import java.text.DecimalFormat;
import java.util.*;
import java.util.ArrayList;
import java.util.Collections;
import java.util.LinkedList;
import java.util.List;
import java.util.logging.Logger;
/**
@@ -257,19 +258,15 @@ public class EvAStatisticalEvaluation {
private static String calculateMannWhitney(String field, OptimizationJob job1, OptimizationJob job2) {
double[] dat1 = job1.getDoubleDataColumn(field);
double[] dat2 = job2.getDoubleDataColumn(field);
org.apache.commons.math3.stat.inference.MannWhitneyUTest mU = new org.apache.commons.math3.stat.inference.MannWhitneyUTest(NaNStrategy.FAILED, TiesStrategy.AVERAGE);
double t = Double.NaN;
if (dat1 != null && dat2 != null) {
return "" + mU.mannWhitneyUTest(dat1, dat2);
/*
Object obj = ReflectPackage.instantiateWithParams("jsc.independentsamples.MannWhitneyTest", new Object[]{dat1, dat2}, null);
if (obj != null) {
Object sp = BeanInspector.callIfAvailable(obj, "getSP", new Object[]{});
t = (Double) sp;
} else {
LOGGER.warning("For the MannWhitney test, the JSC package is required on the class path!");
}*/
}
}
return "" + t;
}

2
src/eva2/tools/Serializer.java
View File

@@ -1,7 +1,5 @@
package eva2.tools;
import com.google.gson.Gson;
import java.io.*;
import java.util.logging.Level;
import java.util.logging.Logger;