Optimisations et améliorations

res/data/error_iris.csv

+"sepal.length","sepal.width","petal.length","petal.width","variety"
+"abc","xyz","pqr","uvw","Setosa"
+"def","lmn","stu","ijk","Setosa"
+"ghi","opq","vwx","rst","Setosa"
+"jkl","mno","yza","bcd","Setosa"
+"qrs","tuv","efg","hij","Setosa"
\ No newline at end of file

res/stages/main-stage.fxml

 <?xml version="1.0" encoding="UTF-8"?>
 
-<?import javafx.geometry.Insets?>
-<?import javafx.scene.Scene?>
-<?import javafx.scene.chart.NumberAxis?>
-<?import javafx.scene.chart.ScatterChart?>
-<?import javafx.scene.control.Button?>
-<?import javafx.scene.control.Label?>
-<?import javafx.scene.control.ListView?>
-<?import javafx.scene.image.Image?>
-<?import javafx.scene.image.ImageView?>
-<?import javafx.scene.layout.AnchorPane?>
-<?import javafx.scene.layout.HBox?>
-<?import javafx.scene.layout.VBox?>
-<?import javafx.scene.text.Font?>
-<?import javafx.stage.Stage?>
+<?import javafx.geometry.*?>
+<?import javafx.scene.*?>
+<?import javafx.scene.chart.*?>
+<?import javafx.scene.control.*?>
+<?import javafx.scene.image.*?>
+<?import javafx.scene.layout.*?>
+<?import javafx.scene.text.*?>
+<?import javafx.stage.*?>
 
-<Stage fx:id="stage" xmlns="http://javafx.com/javafx/21" xmlns:fx="http://javafx.com/fxml/1" fx:controller="fr.univlille.sae.classification.controller.MainStageController">
+<Stage fx:id="stage" xmlns="http://javafx.com/javafx/17.0.2-ea" xmlns:fx="http://javafx.com/fxml/1" fx:controller="fr.univlille.sae.classification.controller.MainStageController">
     <scene>
         <Scene>
             <AnchorPane prefHeight="535.0" prefWidth="922.0">
@@ -43,7 +37,7 @@
                                                  <NumberAxis fx:id="ordAxe" prefHeight="354.0" prefWidth="54.0" side="LEFT" stylesheets="@../css/style.css" />
                                                </yAxis>
                                              </ScatterChart>
-                                             <Label fx:id="AxesSelected" alignment="CENTER" layoutX="73.0" layoutY="152.0" prefHeight="38.0" prefWidth="600.0">
+                                             <Label fx:id="AxesSelected" alignment="CENTER" layoutX="-2.0" layoutY="3.0" prefHeight="380.0" prefWidth="682.0">
                                                 <font>
                                                    <Font size="21.0" />
                                                 </font>

src/main/java/fr/univlille/sae/classification/controller/AddDataController.java

@@ -90,6 +90,7 @@ public class AddDataController {
                 else if (attrValue instanceof Boolean) {
                     ChoiceBox<String> choiceBox = new ChoiceBox<>();
                     choiceBox.getItems().addAll("VRAI", "FAUX");
+                    choiceBox.setValue("VRAI");
                     hbox.getChildren().add(choiceBox);
                     components.add(choiceBox);
                 }
@@ -124,6 +125,7 @@ public class AddDataController {
                 return null;
             }).toArray();
 
+            System.out.println(Arrays.toString(values));
             ClassificationModel.getClassificationModel().ajouterDonnee(values);
         }catch (IllegalArgumentException e){
             Alert alert = new Alert(Alert.AlertType.ERROR);

src/main/java/fr/univlille/sae/classification/controller/KNNController.java

@@ -8,9 +8,11 @@ import fr.univlille.sae.classification.model.LoadableData;
 import javafx.collections.ObservableList;
 import javafx.concurrent.Task;
 import javafx.fxml.FXML;
+import javafx.geometry.Pos;
 import javafx.scene.Scene;
 import javafx.scene.control.*;
 import javafx.scene.layout.HBox;
+import javafx.scene.layout.VBox;
 import javafx.stage.Stage;
 
 import java.util.ArrayList;
@@ -59,13 +61,10 @@ public class KNNController {
         }else {
             // Calcul du K Optimal:
 
-            HBox hBox = new HBox();
-
 
             Task<Scene> knnTask = new Task<>() {
                 @Override
                 protected Scene call() throws Exception {
-                    System.out.println("Call call()");
                     updateProgress(0, 3);
                     updateMessage("Préparation des données ");
 
@@ -104,30 +103,32 @@ public class KNNController {
                     return scene;
                 }
             };
-
+            VBox vBox = new VBox();
             ProgressBar pBar = new ProgressBar();
             pBar.progressProperty().bind(knnTask.progressProperty());
             Label statusLabel = new Label();
             statusLabel.textProperty().bind(knnTask.messageProperty());
 
-
-            hBox.getChildren().addAll(statusLabel, pBar);
+            vBox.alignmentProperty().setValue(Pos.CENTER);
+            vBox.getChildren().addAll( pBar, statusLabel);
             Stage stageLoad = new Stage();
-            Scene scene = new Scene(hBox);
+            Scene scene = new Scene(vBox);
+            stageLoad.setTitle("Alogirhme K-NN");
+            stageLoad.setMinWidth(300);
 
             stageLoad.setScene(scene);
             stageLoad.show();
 
             Stage stageFinished = new Stage();
-
+            stageFinished.setTitle("Algorithme K-NN - results");
             knnTask.setOnSucceeded(e -> {
                 stageLoad.close();
                 stageFinished.setScene(knnTask.getValue());
                 stageFinished.show();
 
             });
-            knnTask.run();
-            //new Thread(knnTask).start();
+
+            new Thread(knnTask).start();
 
 
 

src/main/java/fr/univlille/sae/classification/controller/LoadDataController.java

 package fr.univlille.sae.classification.controller;
 
+import com.opencsv.exceptions.CsvException;
+import com.opencsv.exceptions.CsvRequiredFieldEmptyException;
 import fr.univlille.sae.classification.model.ClassificationModel;
 import fr.univlille.sae.classification.model.DataType;
 import javafx.fxml.FXML;
@@ -34,6 +36,7 @@ public class LoadDataController {
     @FXML
     public void initialize() {
         fileType.getItems().addAll(DataType.values());
+        fileType.setValue(DataType.values()[0]);
     }
 
     /**
@@ -72,7 +75,15 @@ public class LoadDataController {
         }
 
         ClassificationModel.getClassificationModel().setType(typeChoisi);
+        try {
             ClassificationModel.getClassificationModel().loadData(file);
+        }catch (RuntimeException | CsvRequiredFieldEmptyException e) {
+            Alert alert = new Alert(Alert.AlertType.ERROR);
+            alert.initOwner(stage);
+            alert.setHeaderText(e.toString());
+            alert.setContentText("Le chargement du fichier à echoué, veuillez reessayer !");
+            alert.showAndWait();
+        }
         stage.close();
     }
 }

src/main/java/fr/univlille/sae/classification/knn/MethodKNN.java

 package fr.univlille.sae.classification.knn;
 
+import com.opencsv.exceptions.CsvRequiredFieldEmptyException;
 import fr.univlille.sae.classification.knn.distance.*;
 import fr.univlille.sae.classification.model.ClassificationModel;
 import fr.univlille.sae.classification.model.DataType;
@@ -11,6 +12,8 @@ import java.util.*;
 
 public class MethodKNN {
 
+    // name,attack,base_egg_steps,capture_rate,defense,experience_growth,hp,sp_attack,sp_defense,type1,type2,speed,is_legendary
+    // Test,45,5800,240.0,50,800000,65,55,65,normal,flying,1.5,False
 
     private static final Random random = new Random();
 
@@ -131,6 +134,7 @@ public class MethodKNN {
             // On estime la classe chaque donnée de test, et on verifie si l'algo a bon
             for(LoadableData l : testData) {
                 totalTry++;
+                System.out.println(l);
                 String baseClass = l.getClassification();
                 //  System.out.println("Base class : " + baseClass);
                 //  System.out.println("Base data: " + l);
@@ -150,30 +154,28 @@ public class MethodKNN {
         return taux/(1/testPart);
     }
 
-    public static void main(String[] args) {
+    public static void main(String[] args) throws CsvRequiredFieldEmptyException {
 
         //Test de la robustesse et du meillleur K
 
         ClassificationModel model = ClassificationModel.getClassificationModel();
 
-        model.setType(DataType.IRIS);
-        model.loadData(new File(path+"data/iris.csv"));
+        model.setType(DataType.POKEMON);
+        model.loadData(new File(path+"data/pokemon_train.csv"));
         MethodKNN.updateModel(model.getDatas());
         System.out.println();
 
         List<LoadableData> datas = ClassificationModel.getClassificationModel().getDatas();
-        // On mélange les données pour tester sur differentes variétes car le fichier de base est trié.
-        Collections.shuffle(datas);
 
         for(int i = 0; i<1; i++) {
             System.out.println("Search best k");
 
             // On cherche le meilleure K
-            int bestK = MethodKNN.bestK(datas, new DistanceManhattanNormalisee());
+            int bestK = MethodKNN.bestK(datas, new DistanceEuclidienneNormalisee());
             System.out.println(bestK);
 
             // Puis on clacul la robustesse avec le K trouvé
-            System.out.println(MethodKNN.robustesse( datas, bestK, new DistanceManhattanNormalisee(), 0.2));
+            System.out.println(MethodKNN.robustesse( datas, bestK, new DistanceEuclidienneNormalisee(), 0.2));
 
         }
 

src/main/java/fr/univlille/sae/classification/model/ClassificationModel.java

 package fr.univlille.sae.classification.model;
 
 import com.opencsv.bean.CsvToBeanBuilder;
+import com.opencsv.exceptions.CsvBadConverterException;
+import com.opencsv.exceptions.CsvRequiredFieldEmptyException;
 import fr.univlille.sae.classification.knn.MethodKNN;
 import fr.univlille.sae.classification.knn.distance.Distance;
 import fr.univlille.sae.classification.knn.distance.DistanceEuclidienne;
@@ -79,7 +81,7 @@ public class ClassificationModel extends Observable {
      * Charge les données à partir d'un fichier CSV.
      * @param file fichier contenant les données à charger.
      */
-    public void loadData(File file) {
+    public void loadData(File file) throws CsvRequiredFieldEmptyException, CsvBadConverterException {
         try {
             this.datas = new CsvToBeanBuilder<LoadableData>(Files.newBufferedReader(file.toPath()))
                     .withSeparator(',')
@@ -137,6 +139,7 @@ public class ClassificationModel extends Observable {
 
     public void setDistance(Distance distance) {
         this.distance = distance;
+        this.kOptimal = 0;
     }
 
     public Distance getDistance() {

src/main/java/fr/univlille/sae/classification/model/Iris.java

@@ -13,13 +13,13 @@ import java.util.Map;
  */
 public class Iris extends LoadableData {
 
-    @CsvBindByName(column = "sepal.length")
+    @CsvBindByName(column = "sepal.length", required = true)
     private double sepalLength;
-    @CsvBindByName(column = "sepal.width")
+    @CsvBindByName(column = "sepal.width", required = true)
     private double sepalWidth;
-    @CsvBindByName(column = "petal.length")
+    @CsvBindByName(column = "petal.length", required = true)
     private double petalLength;
-    @CsvBindByName(column = "petal.width")
+    @CsvBindByName(column = "petal.width", required = true)
     private double petalWidth;
     @CsvBindByName(column = "variety")
     private String variety;

src/main/java/fr/univlille/sae/classification/model/PointFactory.java

@@ -32,7 +32,7 @@ public class PointFactory {
                         data = new Pokemon(coords);
                     }
                     else if (coords.length == 11) {
-                        data = new Pokemon((String) coords[0], (Integer) coords[1], (Integer) coords[2], (Double) coords[3], (Integer) coords[4], (Integer) coords[5], (Integer) coords[6], (Integer) coords[7], (Integer) coords[8], "", "", (Double) coords[9], (Boolean) coords[10]);
+                        data = new Pokemon((String) coords[0], (Integer) coords[1], (Integer) coords[2], (Double) coords[3], (Integer) coords[4], (Integer) coords[5], (Integer) coords[6], (Integer) coords[7], (Integer) coords[8], "undefined", "", (Double) coords[9], (Boolean) coords[10]);
                     }
                     break;
                 default:

src/main/java/fr/univlille/sae/classification/model/Pokemon.java

@@ -49,7 +49,11 @@ public class Pokemon extends LoadableData{
         this.hp = hp;
         this.spAttack = spAttack;
         this.spDefense = spDefense;
+        if(type1 == null || type1.isEmpty()) {
+            this.type1 = "undefined";
+        }else {
             this.type1 = type1;
+        }
         this.type2 = type2;
         this.speed = speed;
         this.isLegendary = isLegendary;
@@ -123,7 +127,7 @@ public class Pokemon extends LoadableData{
 
     @Override
     public String[] getStringAttributes() {
-        return new String[]{name, type2, String.valueOf(isLegendary)};
+        return new String[]{type2, String.valueOf(isLegendary)};
     }
 
     @Override

src/main/java/fr/univlille/sae/classification/view/MainStageView.java

@@ -8,6 +8,7 @@ import fr.univlille.sae.classification.utils.Observer;
 import fr.univlille.sae.classification.utils.ViewUtil;
 import javafx.fxml.FXMLLoader;
 import javafx.scene.Node;
+import javafx.scene.chart.NumberAxis;
 import javafx.scene.chart.ScatterChart;
 import javafx.scene.chart.XYChart;
 import javafx.scene.control.*;
@@ -120,6 +121,17 @@ public class MainStageView extends DataVisualizationView implements Observer {
                     Object xValue = data.getAttributesNames().get(actualX);
                     Object yValue = data.getAttributesNames().get(actualY);
 
+
+
+                    double x = 0;
+                    if(xValue instanceof Number) {
+                        x = ((Number) xValue).doubleValue();
+                    }
+                    double y = 0;
+                    if(yValue instanceof Number) {
+                        y = ((Number) yValue).doubleValue();
+                    }
+                    /**
                     Double x = 0.0;
                     if (xValue instanceof Integer) {
                         x = ((Integer) xValue).doubleValue();
@@ -133,7 +145,7 @@ public class MainStageView extends DataVisualizationView implements Observer {
                     } else if (yValue instanceof Double) {
                         y = (Double) yValue;
                     }
-
+                    **/
                     ScatterChart.Data<Double, Double> dataPoint = new ScatterChart.Data<>(x, y);
 
                     Node nodePoint = ViewUtil.getForm(data, new Circle(5), controller);