generalbgh/algorithms-for-computing-line-estimators
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algorithms-for-computing-line-estimators
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refactor, import und export bei evaluation.

This commit is contained in:
Armin Wolf 2017-09-19 13:34:06 +02:00
parent 813155347d
commit 646150d2d6
33 changed files with 388 additions and 210 deletions
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77
LinearRegressionTool/pom.xml
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@ -5,8 +5,9 @@
<modelVersion>4.0.0</modelVersion>
<groupId>wwu</groupId>
<artifactId>masterarbeit</artifactId>
<version>1.0-SNAPSHOT</version>
<artifactId>Masterarbeit</artifactId>
<version>1.0</version>
<build>
<plugins>
<plugin>
@ -17,6 +18,52 @@
<target>1.8</target>
</configuration>
</plugin>
<!-- Maven Assembly Plugin -->
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-assembly-plugin</artifactId>
<version>2.4.1</version>
<configuration>
<!-- get all project dependencies -->
<descriptorRefs>
<descriptorRef>jar-with-dependencies</descriptorRef>
</descriptorRefs>
<!-- MainClass in mainfest make a executable jar -->
<archive>
<manifest>
<mainClass>App</mainClass>
</manifest>
</archive>
</configuration>
<executions>
<execution>
<id>make-assembly</id>
<!-- bind to the packaging phase -->
<phase>package</phase>
<goals>
<goal>single</goal>
</goals>
</execution>
</executions>
</plugin>
<plugin>
<groupId>com.googlecode.mavennatives</groupId>
<artifactId>maven-nativedependencies-plugin</artifactId>
<version>0.0.7</version>
<executions>
<execution>
<id>unpacknatives</id>
<phase>generate-resources</phase>
<goals>
<goal>copy</goal>
</goals>
</execution>
</executions>
</plugin>
</plugins>
</build>
@ -49,5 +96,31 @@
<artifactId>JTattoo</artifactId>
<version>1.6.11</version>
</dependency>
<!-- OpenCV -->
<dependency>
<groupId>org</groupId>
<artifactId>opencv</artifactId>
<version>2.4.13</version>
<systemPath>${project.basedir}/src/main/resources/libs/opencv-2413.jar</systemPath>
</dependency>
<dependency>
<groupId>org</groupId>
<artifactId>opencv</artifactId>
<version>2.4.13</version>
<scope>system</scope>
<type>dll</type>
<systemPath>${project.basedir}/src/main/resources/libs/x64/opencv_java2413.dll</systemPath>
<classifier>native-all</classifier>
</dependency>
<!-- https://mvnrepository.com/artifact/org.apache.commons/commons-io -->
<dependency>
<groupId>org.apache.commons</groupId>
<artifactId>commons-io</artifactId>
<version>1.3.2</version>
</dependency>
</dependencies>
</project>

37
LinearRegressionTool/src/main/java/App.java
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@ -1,12 +1,16 @@
import model.LineModel;
import org.apache.commons.io.IOUtils;
import org.opencv.core.Core;
import presenter.Presenter;
import presenter.evaluation.PictureProcessor;
import view.MainFrame;
import javax.swing.*;
import java.awt.*;
import java.lang.reflect.InvocationTargetException;
import java.io.File;
import java.io.FileOutputStream;
import java.io.InputStream;
import java.io.OutputStream;
/**
* Implementierung verschiedener Algorithmen zur Berechnung von Ausgleichsgeraden.
@ -17,7 +21,33 @@ import java.lang.reflect.InvocationTargetException;
*/
public class App {
static {System.loadLibrary(Core.NATIVE_LIBRARY_NAME);}
private static void loadLibrary() {
try {
InputStream in = null;
File fileOut = null;
String osName = System.getProperty("os.name");
int bitness = Integer.parseInt(System.getProperty("sun.arch.data.model"));
if(bitness == 32){
in = App.class.getResourceAsStream("/libs/x86/opencv_java2413.dll");
fileOut = File.createTempFile("tmp", ".dll");
}
else if (bitness == 64){
in = App.class.getResourceAsStream("/libs/x64/opencv_java2413.dll");
fileOut = File.createTempFile("tmp", ".dll");
}
OutputStream out = new FileOutputStream(fileOut);
IOUtils.copy(in, out);
in.close();
out.close();
System.load(fileOut.toString());
} catch (Exception e) {
throw new RuntimeException("Failed to load opencv native library", e);
}
}
private static void setUIFont(javax.swing.plaf.FontUIResource f) {
java.util.Enumeration<Object> keys = UIManager.getDefaults().keys();
@ -51,6 +81,7 @@ public class App {
}
public static void main(String[] args) {
loadLibrary();
final Presenter presenter = new Presenter(new LineModel(), null);

4
LinearRegressionTool/src/main/java/model/LineModel.java
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@ -1,11 +1,7 @@
package model;
import sun.awt.image.ImageWatched;
import java.util.ArrayList;
import java.util.Collections;
import java.util.LinkedList;
import java.util.List;
/**
* Implementierung verschiedener Algorithmen zur Berechnung von Ausgleichsgeraden.

4
LinearRegressionTool/src/main/java/presenter/AbstractPresenter.java
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@ -1,9 +1,7 @@
package presenter;
import model.Interval;
import model.LineModel;
import presenter.algorithms.util.IntersectionComputer;
import presenter.algorithms.util.IntersectionCounter;
import presenter.evaluation.EvaluateAlgorithms;
import view.MainFrame;
@ -161,8 +159,6 @@ public abstract class AbstractPresenter implements Observer {
}
public void calculateIntersections() {
try {
Thread thread = new Thread(() -> {

39
LinearRegressionTool/src/main/java/presenter/Presenter.java
View File

@ -118,9 +118,9 @@ public class Presenter extends AbstractPresenter{
public void startImport(File file) {
if (importThread == null || !importThread.isAlive()) {
importThread = new Thread(() -> {
DataImporter importer = new DataImporter(file, this);
DataImporter importer = new DataImporter(file);
importer.addObserver(this);
importer.run();
getModel().setLines(importer.run());
});
importThread.start();
try {
@ -147,13 +147,28 @@ public class Presenter extends AbstractPresenter{
}
}
public void startExport(File file) {
if (exportThread == null || !exportThread.isAlive()) {
exportThread = new Thread(() -> {
DataExporter exporter = new DataExporter(getModel(), file);
DataExporter exporter = new DataExporter(getModel().getLines(), file);
exporter.addObserver(this);
exporter.export();
});
exportThread.start();
try {
exportThread.join();
} catch (InterruptedException e) {
e.printStackTrace();
}
}
}
public void startDatasetExportEvaluation(File file) {
if (exportThread == null || !exportThread.isAlive()) {
exportThread = new Thread(() -> {
DataExporter exporter = new DataExporter(getEval().getData(), file);
exporter.addObserver(this);
exporter.export();
});
@ -214,4 +229,20 @@ public class Presenter extends AbstractPresenter{
evalThread.start();
}
}
public void startEvaluation(int typ, int n, int alg, File file) {
if (evalThread == null || !evalThread.isAlive()) {
evalThread = new Thread(() -> {
try {
setEval(new EvaluateAlgorithms(typ, n, alg, file));
getEval().addObserver(this);
getEval().run();
} catch (InterruptedException e) {
e.printStackTrace();
}
});
evalThread.start();
}
}
}

1
LinearRegressionTool/src/main/java/presenter/algorithms/naiv/NaivLeastMedianOfSquaresEstimator.java
View File

@ -61,7 +61,6 @@ public class NaivLeastMedianOfSquaresEstimator implements Algorithm {
}
private Double f(Double a, Double b) {
ArrayList<Double> res = new ArrayList<>();
for (Point p : set) {

1
LinearRegressionTool/src/main/java/presenter/algorithms/util/FastElementSelector.java
View File

@ -1,6 +1,5 @@
package presenter.algorithms.util;
import java.util.ArrayList;
import java.util.Collections;
import java.util.List;
import java.util.Random;

33
LinearRegressionTool/src/main/java/presenter/evaluation/EvaluateAlgorithms.java
View File

@ -4,15 +4,17 @@ import model.Interval;
import model.Line;
import model.LineModel;
import model.Point;
import presenter.algorithms.advanced.LeastMedianOfSquaresEstimator;
import presenter.algorithms.advanced.RepeatedMedianEstimator;
import presenter.algorithms.advanced.TheilSenEstimator;
import presenter.algorithms.naiv.NaivLeastMedianOfSquaresEstimator;
import presenter.algorithms.naiv.NaivRepeatedMedianEstimator;
import presenter.algorithms.naiv.NaivTheilSenEstimator;
import presenter.algorithms.util.IntersectionCounter;
import presenter.algorithms.advanced.LeastMedianOfSquaresEstimator;
import presenter.algorithms.advanced.RepeatedMedianEstimator;
import presenter.algorithms.advanced.TheilSenEstimator;
import presenter.generator.DatasetGenerator;
import presenter.io.DataImporter;
import java.io.File;
import java.util.ArrayList;
import java.util.LinkedList;
import java.util.Observable;
@ -96,6 +98,30 @@ public class EvaluateAlgorithms extends Observable {
tsP = new ArrayList<>(arrangement.getNodes());
}
public EvaluateAlgorithms(int type, int n, int alg, File file) {
this.arrangement = new LineModel();
DataImporter importer = new DataImporter(file);
this.arrangement.setLines(importer.run());
this.type = type;
this.iterations = n;
this.alg = alg;
IntersectionCounter counter = new IntersectionCounter();
counter.run(arrangement.getLines(), new Interval(-99999, 99999));
counter.calculateIntersectionAbscissas(arrangement);
lmsL = new LinkedList<>(arrangement.getLines());
rmL = new LinkedList<>(arrangement.getLines());
tsL = new LinkedList<>(arrangement.getLines());
lmsP = new ArrayList<>(arrangement.getNodes());
tsP = new ArrayList<>(arrangement.getNodes());
}
public void run() throws InterruptedException {
setChanged();
String[] msg = {"eval-dataset-generated"};
@ -358,7 +384,6 @@ public class EvaluateAlgorithms extends Observable {
}
public ArrayList<String> getScaleDependentMeasure(final LinkedList<Line> lines, final Double m, final Double b) {
ScaleDependentMeasure scaleDependentMeasure = new ScaleDependentMeasure(lines, m, b);
ArrayList<String> ret = new ArrayList<>();

4
LinearRegressionTool/src/main/java/presenter/evaluation/PictureProcessor.java
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@ -1,8 +1,8 @@
package presenter.evaluation;
import jdk.nashorn.internal.scripts.JD;
import model.Line;
import org.opencv.core.*;
import org.opencv.highgui.*;
import org.opencv.highgui.Highgui;
import org.opencv.imgproc.Imgproc;
import presenter.Presenter;

11
LinearRegressionTool/src/main/java/presenter/io/DataExporter.java
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@ -1,12 +1,13 @@
package presenter.io;
import com.opencsv.CSVWriter;
import model.Line;
import model.LineModel;
import com.opencsv.CSVWriter;
import java.io.File;
import java.io.FileWriter;
import java.io.IOException;
import java.util.LinkedList;
import java.util.Observable;
/**
@ -18,12 +19,12 @@ import java.util.Observable;
*/
public class DataExporter extends Observable {
private LineModel lineModel;
private LinkedList<Line> lines;
private File file;
public DataExporter(LineModel model, File file) {
public DataExporter(LinkedList<Line> lines, File file) {
this.file = file;
this.lineModel = model;
this.lines = lines;
}
public void export() {
@ -33,7 +34,7 @@ public class DataExporter extends Observable {
writer = new CSVWriter(new FileWriter(file), ',');
// feed in your array (or convert your data to an array)
String[] entries = new String[3];
for (Line line : lineModel.getLines()) {
for (Line line : lines) {
entries[0] = line.getId();
entries[1] = line.getM().toString();
Double tmp = (-1) * line.getB();

20
LinearRegressionTool/src/main/java/presenter/io/DataImporter.java
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@ -1,14 +1,15 @@
package presenter.io;
import com.opencsv.CSVReader;
import model.Line;
import model.LineModel;
import presenter.Presenter;
import com.opencsv.CSVReader;
import java.io.File;
import java.io.FileNotFoundException;
import java.io.FileReader;
import java.io.IOException;
import java.util.LinkedList;
import java.util.List;
import java.util.Observable;
@ -24,17 +25,10 @@ public class DataImporter extends Observable {
private File file;
private CSVReader reader;
private LineModel model;
private Presenter presenter;
public DataImporter(File file, Presenter presenter) {
this.model = new LineModel();
this.presenter = presenter;
this.presenter.setModel(this.model);
public DataImporter(File file) {
//System.out.println(this.model.getLines().size()+ " die Anzahl der aktuellen Lines.");
this.file = file;
try {
@ -44,8 +38,9 @@ public class DataImporter extends Observable {
}
}
public void run() {
public LinkedList<Line> run() {
LinkedList<Line> list = new LinkedList<>();
try {
List<String[]> lines = reader.readAll();
int counter = 0;
@ -57,8 +52,8 @@ public class DataImporter extends Observable {
Double y = Double.parseDouble(nextLine[2]) * (-1);
Line line = new Line(x, y);
line.setId(counter + "");
if (!this.presenter.getModel().getLines().contains(line)) {
this.presenter.getModel().addLine(line);
if (!list.contains(line)) {
list.add(line);
}
//System.out.format("|\t\t\t\t\t %-11d \t|\t\t\t\t\t %-11f \t|\t\t\t\t\t %-11f \t\t\t\t\t|\n", id,x,y);
setChanged();
@ -74,6 +69,7 @@ public class DataImporter extends Observable {
} catch (InterruptedException e) {
e.printStackTrace();
}
return list;
}
}

5
LinearRegressionTool/src/main/java/view/MainFrame.java
View File

@ -5,7 +5,10 @@ import model.Line;
import presenter.AbstractPresenter;
import presenter.Presenter;
import view.listener.*;
import view.panels.*;
import view.panels.DualityPanel;
import view.panels.EvaluationPanel;
import view.panels.InfoPanel;
import view.panels.PlotPanel;
import view.panels.tabs.LMSPanel;
import view.panels.tabs.RMPanel;
import view.panels.tabs.TSPanel;

10
LinearRegressionTool/src/main/java/view/MenuBar.java
View File

@ -1,7 +1,6 @@
package view;
import presenter.Presenter;
import view.MainFrame;
import view.listener.ExportDataListener;
import view.listener.GenerateDataListener;
import view.listener.ImportDataListener;
@ -9,7 +8,6 @@ import view.listener.PictureImportListener;
import view.panels.AboutPanel;
import javax.swing.*;
import java.awt.*;
/**
* Implementierung verschiedener Algorithmen zur Berechnung von Ausgleichsgeraden.
@ -70,8 +68,12 @@ public class MenuBar {
}
public void addActionListeners() {
this.exitItem.addActionListener(e -> {System.exit(0);});
this.evaluateItem.addActionListener(e -> {view.showEvauluationDialog();});
this.exitItem.addActionListener(e -> {
System.exit(0);
});
this.evaluateItem.addActionListener(e -> {
view.showEvauluationDialog();
});
this.importItem.addActionListener(new ImportDataListener((Presenter) view.getPresenter(), view));
this.exportItem.addActionListener(new ExportDataListener((Presenter) view.getPresenter(), view));
this.generateItem.addActionListener(new GenerateDataListener((Presenter) view.getPresenter()));

2
LinearRegressionTool/src/main/java/view/listener/ExportDataListener.java
View File

@ -33,7 +33,7 @@ public class ExportDataListener implements ActionListener {
File file = null;
JFileChooser chooser = new JFileChooser(FileSystemView.getFileSystemView().getHomeDirectory());
chooser.setPreferredSize(new Dimension(800, 700));
chooser.setFileFilter(new FileNameExtensionFilter("Comma-Separated Value", "csv", "text"));
chooser.setFileFilter(new FileNameExtensionFilter("Comma-Separated Value, (*.csv)", "csv", "text"));
chooser.setMultiSelectionEnabled(false);
chooser.setFileSelectionMode(JFileChooser.FILES_ONLY);

1
LinearRegressionTool/src/main/java/view/listener/GenerateDataListener.java
View File

@ -2,7 +2,6 @@ package view.listener;
import presenter.Presenter;
import javax.swing.*;
import java.awt.event.ActionEvent;
import java.awt.event.ActionListener;

2
LinearRegressionTool/src/main/java/view/listener/ImportDataListener.java
View File

@ -33,7 +33,7 @@ public class ImportDataListener implements ActionListener {
File file = null;
JFileChooser chooser = new JFileChooser(FileSystemView.getFileSystemView().getHomeDirectory());
chooser.setPreferredSize(new Dimension(800, 700));
chooser.setFileFilter(new FileNameExtensionFilter("Comma-Separated Value", "csv", "text"));
chooser.setFileFilter(new FileNameExtensionFilter("Comma-Separated Value, (*.csv)", "csv", "text"));
chooser.setMultiSelectionEnabled(false);
chooser.setFileSelectionMode(JFileChooser.FILES_ONLY);

47
LinearRegressionTool/src/main/java/view/panels/EvaluationPanel.java
View File

@ -75,7 +75,7 @@ public class EvaluationPanel extends JPanel {
datasetCountLabel = new JLabel("Größe des Datensatzes");
Integer[] choice = {50, 100, 200, 500, 1000, 1500};
datasetCountChoice = new JComboBox(choice);
String[] datatypes = {"Punktwolke", "Gerade", "Kreis und Gerade"};
String[] datatypes = {"Punktwolke", "Gerade", "Kreis und Gerade", "Import von CSV-Datei"};
datasetType = new JComboBox<>(datatypes);
start = new JButton("Start");
@ -191,7 +191,29 @@ public class EvaluationPanel extends JPanel {
alg = checkSelection();
n = (Integer) datasetCountChoice.getSelectedItem();
String datatyp = (String) datasetType.getSelectedItem();
if (datatyp == "Import von CSV-Datei"){
SwingUtilities.invokeLater(() -> {
File file = null;
JFileChooser chooser = new JFileChooser(FileSystemView.getFileSystemView().getHomeDirectory());
chooser.setPreferredSize(new Dimension(800, 700));
chooser.setFileFilter(new FileNameExtensionFilter("Comma-Separated Value, (*.csv)", "csv", "text"));
chooser.setMultiSelectionEnabled(false);
chooser.setFileSelectionMode(JFileChooser.FILES_ONLY);
if (chooser.showOpenDialog(this) == JFileChooser.APPROVE_OPTION) {
//System.out.println ("Datei "+chooser.getSelectedFile()+ " ausgewählt.");
file = chooser.getSelectedFile();
final File input = file;
Thread t = new Thread(() -> ((Presenter) view.getPresenter()).startEvaluation(type, n, alg, input));
t.start();
}
});
} else {
((Presenter) view.getPresenter()).startEvaluation(type, n, alg, datatyp);
}
clearTable.setEnabled(true);
latexExport.setEnabled(true);
exportData.setEnabled(true);
@ -224,7 +246,7 @@ public class EvaluationPanel extends JPanel {
File file = null;
JFileChooser chooser = new JFileChooser(FileSystemView.getFileSystemView().getHomeDirectory());
chooser.setPreferredSize(new Dimension(800, 700));
chooser.setFileFilter(new FileNameExtensionFilter("LaTeX-Datei", "tex", "text"));
chooser.setFileFilter(new FileNameExtensionFilter("LaTeX-Datei, (*.tex)", "tex", "text"));
chooser.setMultiSelectionEnabled(false);
chooser.setFileSelectionMode(JFileChooser.FILES_ONLY);
@ -257,7 +279,26 @@ public class EvaluationPanel extends JPanel {
exportData.addActionListener(e -> {
SwingUtilities.invokeLater(() -> {
JOptionPane.showMessageDialog(this, "Boooooooooooooooooooooooooooooooooooooooooooooooooooooo! :)");
SwingUtilities.invokeLater(() -> {
File file = null;
JFileChooser chooser = new JFileChooser(FileSystemView.getFileSystemView().getHomeDirectory());
chooser.setPreferredSize(new Dimension(800, 700));
chooser.setFileFilter(new FileNameExtensionFilter("Comma-Separated Value, (*.csv)", "csv", "text"));
chooser.setMultiSelectionEnabled(false);
chooser.setFileSelectionMode(JFileChooser.FILES_ONLY);
if (chooser.showOpenDialog(this) == JFileChooser.APPROVE_OPTION) {
//System.out.println ("Datei "+chooser.getSelectedFile()+ " ausgewählt.");
file = chooser.getSelectedFile();
String filename = file.getAbsolutePath().contains(".csv") ? file.getAbsolutePath() : file.getAbsolutePath().concat(".csv");
File withExtension = new File(filename);
final File input = withExtension;
Thread t = new Thread(() ->((Presenter) view.getPresenter()).startDatasetExportEvaluation(input));
t.start();
}
});
});
});

5
LinearRegressionTool/src/main/java/view/panels/tabs/LMSPanel.java
View File

@ -1,10 +1,6 @@
package view.panels.tabs;
import com.sun.istack.internal.Nullable;
import view.panels.PlotPanel;
import javax.swing.*;
import javax.swing.border.TitledBorder;
import java.awt.*;
/**
@ -84,7 +80,6 @@ public class LMSPanel extends TabPanel {
}
@Nullable
public String[] getInput() {
String[] input = new String[3];
input[0] = this.input[0].getText();

5
LinearRegressionTool/src/main/java/view/panels/tabs/RMPanel.java
View File

@ -1,10 +1,6 @@
package view.panels.tabs;
import com.sun.istack.internal.Nullable;
import view.panels.PlotPanel;
import javax.swing.*;
import javax.swing.border.TitledBorder;
import java.awt.*;
/**
@ -77,7 +73,6 @@ public class RMPanel extends TabPanel {
}
@Nullable
public String getInput() {
String input = "";
input = this.input.getText();

4
LinearRegressionTool/src/main/java/view/panels/tabs/TSPanel.java
View File

@ -1,10 +1,6 @@
package view.panels.tabs;
import com.sun.istack.internal.Nullable;
import view.panels.PlotPanel;
import javax.swing.*;
import javax.swing.border.TitledBorder;
import java.awt.*;
/**

16
LinearRegressionTool/src/main/java/view/panels/tabs/TabPanel.java
View File

@ -41,6 +41,14 @@ public abstract class TabPanel extends JPanel{
this.startButton.setFont(new Font("Verdana", Font.PLAIN, 16));
}
protected void addTextfieldAndInput(int row, String name, Double value) {
//muss nicht obligatorisch implementiert werden
}
public PlotPanel getPlotPanel() {
return plotPanel;
}
public void setPlotPanel(PlotPanel plotPanel) {
this.plotPanel = plotPanel;
if (this.centerPanel.getComponents().length > 0)
@ -52,14 +60,6 @@ public abstract class TabPanel extends JPanel{
this.revalidate();
}
protected void addTextfieldAndInput(int row, String name, Double value){
//muss nicht obligatorisch implementiert werden
}
public PlotPanel getPlotPanel() {
return plotPanel;
}
public JButton getStartButton() {
return startButton;
}

0
LinearRegressionTool/libs/opencv-2413.jar → LinearRegressionTool/src/main/resources/libs/opencv-2413.jar
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0
LinearRegressionTool/libs/x64/opencv_java2413.dll → LinearRegressionTool/src/main/resources/libs/x64/opencv_java2413.dll
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