diff --git a/src/main/java/fr/univlille/sae/classification/utils/ViewUtil.java b/src/main/java/fr/univlille/sae/classification/utils/ViewUtil.java
index 8613467602476d7429b0085881ba871cfac2c9dd..2ae6f8ef46d06a72f0da156f1c350c180a2f7b57 100644
--- a/src/main/java/fr/univlille/sae/classification/utils/ViewUtil.java
+++ b/src/main/java/fr/univlille/sae/classification/utils/ViewUtil.java
@@ -77,8 +77,8 @@ public class ViewUtil {
String[] colorsString = colors.keySet().toArray(new String[0]);
for(int i = 0 ; i < colorsString.length ; i+= 7) {
- for(int j = 0 ; i+j < colorsString.length && j < i+7 ; j++) {
- if(j%7 == 0 && i != 0 ) {
+ for (int j = 0; i + j < colorsString.length && j < i + 7; j++) {
+ if (j % 7 == 0 && i != 0) {
legend.getChildren().add(line);
line = new HBox();
line.setSpacing(10);
@@ -86,28 +86,28 @@ public class ViewUtil {
}
tempHBox = new HBox();
- label = new Label(colorsString[i+j]);
+ label = new Label(colorsString[i + j]);
rectangle = new Rectangle(10, 10);
- rectangle.setFill(colors.get(colorsString[i+j]));
+ rectangle.setFill(colors.get(colorsString[i + j]));
tempHBox.getChildren().addAll(rectangle, label);
line.getChildren().add(tempHBox);
-
- if(colorsString.length < 7) legend.getChildren().add(line);
+ }}
+ if (colorsString.length < 7) legend.getChildren().add(line);
/**
- for(String s : colors.keySet()) {
- Circle c = new Circle(5);
- c.setFill(colors.get(s));
- label = new Label(s);
- tempHBox = new HBox();
- tempHBox.getChildren().addAll(c, label);
-
- hbox.getChildren().add(tempHBox);
- }
+ for(String s : colors.keySet()) {
+ Circle c = new Circle(5);
+ c.setFill(colors.get(s));
+ label = new Label(s);
+ tempHBox = new HBox();
+ tempHBox.getChildren().addAll(c, label);
+
+ hbox.getChildren().add(tempHBox);
+ }
*/
- return legend;
- }
+ return legend;
+ }
-}
+ }
diff --git a/src/test/java/fr/univlille/sae/classification/knn/distance/DistanceEuclidienneNormaliseeTest.java b/src/test/java/fr/univlille/sae/classification/knn/distance/DistanceEuclidienneNormaliseeTest.java
new file mode 100644
index 0000000000000000000000000000000000000000..63314320f48ea293bd7ba74e072aaddbc486b9a9
--- /dev/null
+++ b/src/test/java/fr/univlille/sae/classification/knn/distance/DistanceEuclidienneNormaliseeTest.java
@@ -0,0 +1,341 @@
+package fr.univlille.sae.classification.knn.distance;
+
+import static org.junit.jupiter.api.Assertions.*;
+
+import fr.univlille.sae.classification.knn.MethodKNN;
+import javafx.scene.paint.Color;
+import org.junit.jupiter.api.BeforeAll;
+import org.junit.jupiter.api.Test;
+import fr.univlille.sae.classification.model.LoadableData;
+
+public class DistanceEuclidienneNormaliseeTest {
+
+ @BeforeAll
+ public static void setupMethodKNN() {
+ MethodKNN.minData = new double[]{0.0, 2.0, 4.0};
+ MethodKNN.amplitude = new double[]{10.0, 3.0, 2.0}; // Assurez-vous que toutes les amplitudes sont non nulles
+ }
+
+ @Test
+ public void testDistanceMatchingAttributes() {
+ LoadableData data1 = new LoadableData() {
+ @Override
+ public String getClassification() {
+ return "";
+ }
+
+ @Override
+ public void setClassification(String classification) {
+
+ }
+
+ @Override
+ public String[] getAttributesName() {
+ return new String[0];
+ }
+
+ @Override
+ public Color getColor() {
+ return null;
+ }
+
+ @Override
+ public double getDataType(String axes) {
+ return 0;
+ }
+
+ @Override
+ public double[] getAttributes() {
+ return new double[]{2.0, 3.0, 6.0};
+ }
+
+ @Override
+ public String[] getStringAttributes() {
+ return new String[]{"A", "B"};
+ }
+ };
+
+ LoadableData data2 = new LoadableData() {
+ @Override
+ public String getClassification() {
+ return "";
+ }
+
+ @Override
+ public void setClassification(String classification) {
+
+ }
+
+ @Override
+ public String[] getAttributesName() {
+ return new String[0];
+ }
+
+ @Override
+ public Color getColor() {
+ return null;
+ }
+
+ @Override
+ public double getDataType(String axes) {
+ return 0;
+ }
+
+ @Override
+ public double[] getAttributes() {
+ return new double[]{8.0, 5.0, 8.0};
+ }
+
+ @Override
+ public String[] getStringAttributes() {
+ return new String[]{"A", "B"};
+ }
+ };
+
+ DistanceEuclidienneNormalisee distance = new DistanceEuclidienneNormalisee();
+ double result = distance.distance(data1, data2);
+ assertEquals(1.2093, result, 0.0001);
+ }
+
+ @Test
+ public void testDistanceDifferentStringAttributes() {
+ LoadableData data1 = new LoadableData() {
+ @Override
+ public String getClassification() {
+ return "";
+ }
+
+ @Override
+ public void setClassification(String classification) {
+
+ }
+
+ @Override
+ public String[] getAttributesName() {
+ return new String[0];
+ }
+
+ @Override
+ public Color getColor() {
+ return null;
+ }
+
+ @Override
+ public double getDataType(String axes) {
+ return 0;
+ }
+
+ @Override
+ public double[] getAttributes() {
+ return new double[]{2.0, 3.0, 6.0};
+ }
+
+ @Override
+ public String[] getStringAttributes() {
+ return new String[]{"A", "B"};
+ }
+ };
+
+ LoadableData data2 = new LoadableData() {
+ @Override
+ public String getClassification() {
+ return "";
+ }
+
+ @Override
+ public void setClassification(String classification) {
+
+ }
+
+ @Override
+ public String[] getAttributesName() {
+ return new String[0];
+ }
+
+ @Override
+ public Color getColor() {
+ return null;
+ }
+
+ @Override
+ public double getDataType(String axes) {
+ return 0;
+ }
+
+ @Override
+ public double[] getAttributes() {
+ return new double[]{8.0, 5.0, 8.0};
+ }
+
+ @Override
+ public String[] getStringAttributes() {
+ return new String[]{"A", "C"};
+ }
+ };
+
+ DistanceEuclidienneNormalisee distance = new DistanceEuclidienneNormalisee();
+ double result = distance.distance(data1, data2);
+ assertEquals(1.6093, result, 0.0001);
+ }
+
+ @Test
+ public void testDistanceDifferentAttributeLengths() {
+ LoadableData data1 = new LoadableData() {
+ @Override
+ public String getClassification() {
+ return "";
+ }
+
+ @Override
+ public void setClassification(String classification) {
+
+ }
+
+ @Override
+ public String[] getAttributesName() {
+ return new String[0];
+ }
+
+ @Override
+ public Color getColor() {
+ return null;
+ }
+
+ @Override
+ public double getDataType(String axes) {
+ return 0;
+ }
+
+ @Override
+ public double[] getAttributes() {
+ return new double[]{2.0, 3.0};
+ }
+
+ @Override
+ public String[] getStringAttributes() {
+ return new String[]{"A"};
+ }
+ };
+
+ LoadableData data2 = new LoadableData() {
+ @Override
+ public String getClassification() {
+ return "";
+ }
+
+ @Override
+ public void setClassification(String classification) {
+
+ }
+
+ @Override
+ public String[] getAttributesName() {
+ return new String[0];
+ }
+
+ @Override
+ public Color getColor() {
+ return null;
+ }
+
+ @Override
+ public double getDataType(String axes) {
+ return 0;
+ }
+
+ @Override
+ public double[] getAttributes() {
+ return new double[]{8.0, 5.0, 8.0};
+ }
+
+ @Override
+ public String[] getStringAttributes() {
+ return new String[]{"A"};
+ }
+ };
+
+ DistanceEuclidienneNormalisee distance = new DistanceEuclidienneNormalisee();
+ assertThrows(IllegalArgumentException.class, () -> distance.distance(data1, data2));
+ }
+
+ @Test
+ public void testDistanceDifferentStringAttributeLengths() {
+ LoadableData data1 = new LoadableData() {
+ @Override
+ public String getClassification() {
+ return "";
+ }
+
+ @Override
+ public void setClassification(String classification) {
+
+ }
+
+ @Override
+ public String[] getAttributesName() {
+ return new String[0];
+ }
+
+ @Override
+ public Color getColor() {
+ return null;
+ }
+
+ @Override
+ public double getDataType(String axes) {
+ return 0;
+ }
+
+ @Override
+ public double[] getAttributes() {
+ return new double[]{2.0, 3.0, 6.0};
+ }
+
+ @Override
+ public String[] getStringAttributes() {
+ return new String[]{"A"};
+ }
+ };
+
+ LoadableData data2 = new LoadableData() {
+ @Override
+ public String getClassification() {
+ return "";
+ }
+
+ @Override
+ public void setClassification(String classification) {
+
+ }
+
+ @Override
+ public String[] getAttributesName() {
+ return new String[0];
+ }
+
+ @Override
+ public Color getColor() {
+ return null;
+ }
+
+ @Override
+ public double getDataType(String axes) {
+ return 0;
+ }
+
+ @Override
+ public double[] getAttributes() {
+ return new double[]{8.0, 5.0, 8.0};
+ }
+
+ @Override
+ public String[] getStringAttributes() {
+ return new String[]{"A", "B"};
+ }
+ };
+
+ DistanceEuclidienneNormalisee distance = new DistanceEuclidienneNormalisee();
+ assertThrows(IllegalArgumentException.class, () -> distance.distance(data1, data2));
+ }
+}
+
diff --git a/src/test/java/fr/univlille/sae/classification/knn/distance/DistanceEuclidienneTest.java b/src/test/java/fr/univlille/sae/classification/knn/distance/DistanceEuclidienneTest.java
new file mode 100644
index 0000000000000000000000000000000000000000..808a444b9bfd4eb2f9c0fad86d6963555a4976c1
--- /dev/null
+++ b/src/test/java/fr/univlille/sae/classification/knn/distance/DistanceEuclidienneTest.java
@@ -0,0 +1,340 @@
+package fr.univlille.sae.classification.knn.distance;
+
+import static org.junit.jupiter.api.Assertions.*;
+
+import javafx.scene.paint.Color;
+import org.junit.jupiter.api.Test;
+import fr.univlille.sae.classification.model.LoadableData;
+
+public class DistanceEuclidienneTest {
+
+ @Test
+ public void testDistanceMatchingAttributes() {
+ LoadableData data1 = new LoadableData() {
+ @Override
+ public String getClassification() {
+ return "";
+ }
+
+ @Override
+ public void setClassification(String classification) {
+
+ }
+
+ @Override
+ public String[] getAttributesName() {
+ return new String[0];
+ }
+
+ @Override
+ public Color getColor() {
+ return null;
+ }
+
+ @Override
+ public double getDataType(String axes) {
+ return 0;
+ }
+
+ @Override
+ public double[] getAttributes() {
+ return new double[]{1.0, 2.0, 3.0};
+ }
+
+ @Override
+ public String[] getStringAttributes() {
+ return new String[]{"A", "B"};
+ }
+ };
+
+ LoadableData data2 = new LoadableData() {
+ @Override
+ public String getClassification() {
+ return "";
+ }
+
+ @Override
+ public void setClassification(String classification) {
+
+ }
+
+ @Override
+ public String[] getAttributesName() {
+ return new String[0];
+ }
+
+ @Override
+ public Color getColor() {
+ return null;
+ }
+
+ @Override
+ public double getDataType(String axes) {
+ return 0;
+ }
+
+ @Override
+ public double[] getAttributes() {
+ return new double[]{4.0, 6.0, 3.0};
+ }
+
+ @Override
+ public String[] getStringAttributes() {
+ return new String[]{"A", "B"};
+ }
+ };
+
+ DistanceEuclidienne distance = new DistanceEuclidienne();
+ double result = distance.distance(data1, data2);
+
+ assertEquals(5.0, result, 0.0001); // Distance euclidienne entre les deux points
+ }
+
+ @Test
+ public void testDistanceDifferentStringAttributes() {
+ LoadableData data1 = new LoadableData() {
+ @Override
+ public String getClassification() {
+ return "";
+ }
+
+ @Override
+ public void setClassification(String classification) {
+
+ }
+
+ @Override
+ public String[] getAttributesName() {
+ return new String[0];
+ }
+
+ @Override
+ public Color getColor() {
+ return null;
+ }
+
+ @Override
+ public double getDataType(String axes) {
+ return 0;
+ }
+
+ @Override
+ public double[] getAttributes() {
+ return new double[]{1.0, 2.0, 3.0};
+ }
+
+ @Override
+ public String[] getStringAttributes() {
+ return new String[]{"A", "B"};
+ }
+ };
+
+ LoadableData data2 = new LoadableData() {
+ @Override
+ public String getClassification() {
+ return "";
+ }
+
+ @Override
+ public void setClassification(String classification) {
+
+ }
+
+ @Override
+ public String[] getAttributesName() {
+ return new String[0];
+ }
+
+ @Override
+ public Color getColor() {
+ return null;
+ }
+
+ @Override
+ public double getDataType(String axes) {
+ return 0;
+ }
+
+ @Override
+ public double[] getAttributes() {
+ return new double[]{1.0, 2.0, 3.0};
+ }
+
+ @Override
+ public String[] getStringAttributes() {
+ return new String[]{"A", "C"};
+ }
+ };
+
+ DistanceEuclidienne distance = new DistanceEuclidienne();
+ double result = distance.distance(data1, data2);
+
+ assertEquals(1.0, result, 0.0001); // Une différence dans les attributs string
+ }
+
+ @Test
+ public void testDistanceDifferentAttributeLengths() {
+ LoadableData data1 = new LoadableData() {
+ @Override
+ public String getClassification() {
+ return "";
+ }
+
+ @Override
+ public void setClassification(String classification) {
+
+ }
+
+ @Override
+ public String[] getAttributesName() {
+ return new String[0];
+ }
+
+ @Override
+ public Color getColor() {
+ return null;
+ }
+
+ @Override
+ public double getDataType(String axes) {
+ return 0;
+ }
+
+ @Override
+ public double[] getAttributes() {
+ return new double[]{1.0, 2.0};
+ }
+
+ @Override
+ public String[] getStringAttributes() {
+ return new String[]{"A"};
+ }
+ };
+
+ LoadableData data2 = new LoadableData() {
+ @Override
+ public String getClassification() {
+ return "";
+ }
+
+ @Override
+ public void setClassification(String classification) {
+
+ }
+
+ @Override
+ public String[] getAttributesName() {
+ return new String[0];
+ }
+
+ @Override
+ public Color getColor() {
+ return null;
+ }
+
+ @Override
+ public double getDataType(String axes) {
+ return 0;
+ }
+
+ @Override
+ public double[] getAttributes() {
+ return new double[]{1.0, 2.0, 3.0};
+ }
+
+ @Override
+ public String[] getStringAttributes() {
+ return new String[]{"A"};
+ }
+ };
+
+ DistanceEuclidienne distance = new DistanceEuclidienne();
+
+ assertThrows(IllegalArgumentException.class, () -> {
+ distance.distance(data1, data2);
+ });
+ }
+
+ @Test
+ public void testDistanceDifferentStringAttributeLengths() {
+ LoadableData data1 = new LoadableData() {
+ @Override
+ public String getClassification() {
+ return "";
+ }
+
+ @Override
+ public void setClassification(String classification) {
+
+ }
+
+ @Override
+ public String[] getAttributesName() {
+ return new String[0];
+ }
+
+ @Override
+ public Color getColor() {
+ return null;
+ }
+
+ @Override
+ public double getDataType(String axes) {
+ return 0;
+ }
+
+ @Override
+ public double[] getAttributes() {
+ return new double[]{1.0, 2.0, 3.0};
+ }
+
+ @Override
+ public String[] getStringAttributes() {
+ return new String[]{"A"};
+ }
+ };
+
+ LoadableData data2 = new LoadableData() {
+ @Override
+ public String getClassification() {
+ return "";
+ }
+
+ @Override
+ public void setClassification(String classification) {
+
+ }
+
+ @Override
+ public String[] getAttributesName() {
+ return new String[0];
+ }
+
+ @Override
+ public Color getColor() {
+ return null;
+ }
+
+ @Override
+ public double getDataType(String axes) {
+ return 0;
+ }
+
+ @Override
+ public double[] getAttributes() {
+ return new double[]{1.0, 2.0, 3.0};
+ }
+
+ @Override
+ public String[] getStringAttributes() {
+ return new String[]{"A", "B"};
+ }
+ };
+
+ DistanceEuclidienne distance = new DistanceEuclidienne();
+
+ assertThrows(IllegalArgumentException.class, () -> {
+ distance.distance(data1, data2);
+ });
+ }
+}
diff --git "a/src/test/java/fr/univlille/sae/classification/knn/distance/DistanceManhattanNormalis\303\251eTest.java" "b/src/test/java/fr/univlille/sae/classification/knn/distance/DistanceManhattanNormalis\303\251eTest.java"
new file mode 100644
index 0000000000000000000000000000000000000000..f9265dea407ae1d348c79cafa95c632a8c39ad09
--- /dev/null
+++ "b/src/test/java/fr/univlille/sae/classification/knn/distance/DistanceManhattanNormalis\303\251eTest.java"
@@ -0,0 +1,91 @@
+package fr.univlille.sae.classification.knn.distance;
+
+import static org.junit.jupiter.api.Assertions.*;
+
+import org.junit.jupiter.api.Test;
+import fr.univlille.sae.classification.model.LoadableData;
+import fr.univlille.sae.classification.knn.MethodKNN;
+import fr.univlille.sae.classification.knn.distance.DistanceManhattanNormalisée;
+import org.junit.jupiter.api.BeforeEach;
+
+public class DistanceManhattanNormaliséeTest {
+
+ private DistanceManhattanNormalisée distanceManhattan;
+
+ @BeforeEach
+ public void setUp() {
+ // Initialisation de l'objet DistanceManhattanNormalisée avant chaque test
+ distanceManhattan = new DistanceManhattanNormalisée();
+
+ // Définition des valeurs de normalisation dans MethodKNN (à ajuster selon votre logique)
+ MethodKNN.minData = new double[] {0.0, 0.0}; // Valeurs minimales pour les attributs
+ MethodKNN.amplitude = new double[] {1.0, 1.0}; // Amplitude pour la normalisation
+ }
+
+ @Test
+ public void testDistanceSimple() {
+ // Création de deux objets LoadableData avec des attributs simples
+ LoadableData data1 = new LoadableData(new double[] {1.0, 2.0});
+ LoadableData data2 = new LoadableData(new double[] {3.0, 5.0});
+
+ // Calcul de la distance manhattan normalisée
+ double result = distanceManhattan.distance(data1, data2);
+
+ // Calcul attendu : (|1.0 - 3.0| / 1.0) + (|2.0 - 5.0| / 1.0)
+ double expected = (Math.abs(1.0 - 3.0) / 1.0) + (Math.abs(2.0 - 5.0) / 1.0);
+
+ // Vérification du résultat
+ assertEquals(expected, result, 0.001);
+ }
+
+ @Test
+ public void testDistanceZero() {
+ // Deux objets avec les mêmes attributs (la distance devrait être 0)
+ LoadableData data1 = new LoadableData(new double[] {1.0, 2.0});
+ LoadableData data2 = new LoadableData(new double[] {1.0, 2.0});
+
+ // Vérification que la distance est bien 0
+ double result = distanceManhattan.distance(data1, data2);
+ assertEquals(0.0, result, 0.001);
+ }
+
+ @Test
+ public void testDistanceAvecValeursExtremes() {
+ // Test avec des valeurs maximales ou minimales (hypothétiques dans ce cas)
+ LoadableData data1 = new LoadableData(new double[] {Double.MAX_VALUE, Double.MIN_VALUE});
+ LoadableData data2 = new LoadableData(new double[] {Double.MIN_VALUE, Double.MAX_VALUE});
+
+ double result = distanceManhattan.distance(data1, data2);
+
+ // Calcul de la distance, ici l'effet de normalisation devrait être pris en compte
+ double expected = (Math.abs(Double.MAX_VALUE - Double.MIN_VALUE) / 1.0) +
+ (Math.abs(Double.MIN_VALUE - Double.MAX_VALUE) / 1.0);
+
+ assertEquals(expected, result, 0.001);
+ }
+
+ @Test
+ public void testDistanceAvecDonneesNulles() {
+ // Test avec des données nulles
+ LoadableData data1 = new LoadableData(new double[] {1.0, 2.0});
+ LoadableData data2 = null;
+
+ try {
+ distanceManhattan.distance(data1, data2);
+ fail("La méthode devrait lever une exception quand l'un des objets est nul");
+ } catch (NullPointerException e) {
+ // Vérification qu'une exception est lancée
+ }
+ }
+
+ @Test
+ public void testDistanceAvecDonneesVides() {
+ // Test avec des données vides (tous les attributs sont 0 ou absents)
+ LoadableData data1 = new LoadableData(new double[] {});
+ LoadableData data2 = new LoadableData(new double[] {});
+
+ // La distance devrait être 0 car il n'y a aucune différence d'attribut
+ double result = distanceManhattan.distance(data1, data2);
+ assertEquals(0.0, result, 0.001);
+ }
+}
diff --git a/src/test/java/fr/univlille/sae/classification/knn/distance/DistanceManhattanTest.java b/src/test/java/fr/univlille/sae/classification/knn/distance/DistanceManhattanTest.java
new file mode 100644
index 0000000000000000000000000000000000000000..ee21bd98dd5e4cd33f9cdca083a1acb020ff2fd0
--- /dev/null
+++ b/src/test/java/fr/univlille/sae/classification/knn/distance/DistanceManhattanTest.java
@@ -0,0 +1,414 @@
+package fr.univlille.sae.classification.knn.distance;
+
+import static org.junit.jupiter.api.Assertions.*;
+
+import javafx.scene.paint.Color;
+import org.junit.jupiter.api.Test;
+import fr.univlille.sae.classification.model.LoadableData;
+
+public class DistanceManhattanTest {
+
+ @Test
+ public void testDistanceMatchingAttributes() {
+ LoadableData data1 = new LoadableData() {
+ @Override
+ public String getClassification() {
+ return "";
+ }
+
+ @Override
+ public void setClassification(String classification) {
+
+ }
+
+ @Override
+ public String[] getAttributesName() {
+ return new String[0];
+ }
+
+ @Override
+ public Color getColor() {
+ return null;
+ }
+
+ @Override
+ public double getDataType(String axes) {
+ return 0;
+ }
+
+ @Override
+ public double[] getAttributes() {
+ return new double[]{2.0, 3.0, 6.0};
+ }
+
+ @Override
+ public String[] getStringAttributes() {
+ return new String[]{"A", "B"};
+ }
+ };
+
+ LoadableData data2 = new LoadableData() {
+ @Override
+ public String getClassification() {
+ return "";
+ }
+
+ @Override
+ public void setClassification(String classification) {
+
+ }
+
+ @Override
+ public String[] getAttributesName() {
+ return new String[0];
+ }
+
+ @Override
+ public Color getColor() {
+ return null;
+ }
+
+ @Override
+ public double getDataType(String axes) {
+ return 0;
+ }
+
+ @Override
+ public double[] getAttributes() {
+ return new double[]{5.0, 8.0, 3.0};
+ }
+
+ @Override
+ public String[] getStringAttributes() {
+ return new String[]{"A", "B"};
+ }
+ };
+
+ DistanceManhattan distance = new DistanceManhattan();
+ double result = distance.distance(data1, data2);
+ assertEquals(11.0, result, 0.0001);
+ }
+
+ @Test
+ public void testDistanceWithZeros() {
+ LoadableData data1 = new LoadableData() {
+ @Override
+ public String getClassification() {
+ return "";
+ }
+
+ @Override
+ public void setClassification(String classification) {
+
+ }
+
+ @Override
+ public String[] getAttributesName() {
+ return new String[0];
+ }
+
+ @Override
+ public Color getColor() {
+ return null;
+ }
+
+ @Override
+ public double getDataType(String axes) {
+ return 0;
+ }
+
+ @Override
+ public double[] getAttributes() {
+ return new double[]{0.0, 0.0, 0.0};
+ }
+
+ @Override
+ public String[] getStringAttributes() {
+ return new String[]{"A", "B"};
+ }
+ };
+
+ LoadableData data2 = new LoadableData() {
+ @Override
+ public String getClassification() {
+ return "";
+ }
+
+ @Override
+ public void setClassification(String classification) {
+
+ }
+
+ @Override
+ public String[] getAttributesName() {
+ return new String[0];
+ }
+
+ @Override
+ public Color getColor() {
+ return null;
+ }
+
+ @Override
+ public double getDataType(String axes) {
+ return 0;
+ }
+
+ @Override
+ public double[] getAttributes() {
+ return new double[]{0.0, 0.0, 0.0};
+ }
+
+ @Override
+ public String[] getStringAttributes() {
+ return new String[]{"A", "B"};
+ }
+ };
+
+ DistanceManhattan distance = new DistanceManhattan();
+ double result = distance.distance(data1, data2);
+ assertEquals(0.0, result, 0.0001);
+ }
+
+ @Test
+ public void testDistanceWithNegativeValues() {
+ LoadableData data1 = new LoadableData() {
+ @Override
+ public String getClassification() {
+ return "";
+ }
+
+ @Override
+ public void setClassification(String classification) {
+
+ }
+
+ @Override
+ public String[] getAttributesName() {
+ return new String[0];
+ }
+
+ @Override
+ public Color getColor() {
+ return null;
+ }
+
+ @Override
+ public double getDataType(String axes) {
+ return 0;
+ }
+
+ @Override
+ public double[] getAttributes() {
+ return new double[]{-2.0, -3.0, -6.0};
+ }
+
+ @Override
+ public String[] getStringAttributes() {
+ return new String[]{"A", "B"};
+ }
+ };
+
+ LoadableData data2 = new LoadableData() {
+ @Override
+ public String getClassification() {
+ return "";
+ }
+
+ @Override
+ public void setClassification(String classification) {
+
+ }
+
+ @Override
+ public String[] getAttributesName() {
+ return new String[0];
+ }
+
+ @Override
+ public Color getColor() {
+ return null;
+ }
+
+ @Override
+ public double getDataType(String axes) {
+ return 0;
+ }
+
+ @Override
+ public double[] getAttributes() {
+ return new double[]{2.0, 3.0, 6.0};
+ }
+
+ @Override
+ public String[] getStringAttributes() {
+ return new String[]{"A", "B"};
+ }
+ };
+
+ DistanceManhattan distance = new DistanceManhattan();
+ double result = distance.distance(data1, data2);
+ assertEquals(22.0, result, 0.0001);
+ }
+
+ @Test
+ public void testDistanceWithDifferentAttributeLengths() {
+ LoadableData data1 = new LoadableData() {
+ @Override
+ public String getClassification() {
+ return "";
+ }
+
+ @Override
+ public void setClassification(String classification) {
+
+ }
+
+ @Override
+ public String[] getAttributesName() {
+ return new String[0];
+ }
+
+ @Override
+ public Color getColor() {
+ return null;
+ }
+
+ @Override
+ public double getDataType(String axes) {
+ return 0;
+ }
+
+ @Override
+ public double[] getAttributes() {
+ return new double[]{1.0, 2.0};
+ }
+
+ @Override
+ public String[] getStringAttributes() {
+ return new String[]{"A"};
+ }
+ };
+
+ LoadableData data2 = new LoadableData() {
+ @Override
+ public String getClassification() {
+ return "";
+ }
+
+ @Override
+ public void setClassification(String classification) {
+
+ }
+
+ @Override
+ public String[] getAttributesName() {
+ return new String[0];
+ }
+
+ @Override
+ public Color getColor() {
+ return null;
+ }
+
+ @Override
+ public double getDataType(String axes) {
+ return 0;
+ }
+
+ @Override
+ public double[] getAttributes() {
+ return new double[]{3.0};
+ }
+
+ @Override
+ public String[] getStringAttributes() {
+ return new String[]{"A"};
+ }
+ };
+
+ DistanceManhattan distance = new DistanceManhattan();
+ assertThrows(ArrayIndexOutOfBoundsException.class, () -> distance.distance(data1, data2));
+ }
+
+ @Test
+ public void testDistanceEmptyAttributes() {
+ LoadableData data1 = new LoadableData() {
+ @Override
+ public String getClassification() {
+ return "";
+ }
+
+ @Override
+ public void setClassification(String classification) {
+
+ }
+
+ @Override
+ public String[] getAttributesName() {
+ return new String[0];
+ }
+
+ @Override
+ public Color getColor() {
+ return null;
+ }
+
+ @Override
+ public double getDataType(String axes) {
+ return 0;
+ }
+
+ @Override
+ public double[] getAttributes() {
+ return new double[]{};
+ }
+
+ @Override
+ public String[] getStringAttributes() {
+ return new String[]{};
+ }
+ };
+
+ LoadableData data2 = new LoadableData() {
+ @Override
+ public String getClassification() {
+ return "";
+ }
+
+ @Override
+ public void setClassification(String classification) {
+
+ }
+
+ @Override
+ public String[] getAttributesName() {
+ return new String[0];
+ }
+
+ @Override
+ public Color getColor() {
+ return null;
+ }
+
+ @Override
+ public double getDataType(String axes) {
+ return 0;
+ }
+
+ @Override
+ public double[] getAttributes() {
+ return new double[]{};
+ }
+
+ @Override
+ public String[] getStringAttributes() {
+ return new String[]{};
+ }
+ };
+
+ DistanceManhattan distance = new DistanceManhattan();
+ double result = distance.distance(data1, data2);
+ assertEquals(0.0, result, 0.0001);
+ }
+}
\ No newline at end of file