diff --git a/res/data/error_iris.csv b/res/data/error_iris.csv
new file mode 100644
index 0000000000000000000000000000000000000000..350d1471cdab74a6393233a8413ab6bd45cc5cb7
--- /dev/null
+++ b/res/data/error_iris.csv
@@ -0,0 +1,6 @@
+"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
diff --git a/res/stages/main-stage.fxml b/res/stages/main-stage.fxml
index 37ee5a84d7934efedc54509dd693ece00867c3b5..c2f1a365d2da7440bf55d75c78c8c07b4d89f91c 100644
--- a/res/stages/main-stage.fxml
+++ b/res/stages/main-stage.fxml
@@ -1,21 +1,15 @@
<?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>
diff --git a/src/main/java/fr/univlille/sae/classification/controller/AddDataController.java b/src/main/java/fr/univlille/sae/classification/controller/AddDataController.java
index 21c7e41752c372ff4c8c1e47add3812f136d0e00..9a220bdf4e1c24f8db37dad2a63785c1c25873de 100644
--- a/src/main/java/fr/univlille/sae/classification/controller/AddDataController.java
+++ b/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);
diff --git a/src/main/java/fr/univlille/sae/classification/controller/KNNController.java b/src/main/java/fr/univlille/sae/classification/controller/KNNController.java
index def9b3273b96a1a2870403485fa2466c807f98a0..9529531f653a5bad439030706ea8b5f540701ef9 100644
--- a/src/main/java/fr/univlille/sae/classification/controller/KNNController.java
+++ b/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();
diff --git a/src/main/java/fr/univlille/sae/classification/controller/LoadDataController.java b/src/main/java/fr/univlille/sae/classification/controller/LoadDataController.java
index 014af783059a9eb43473293a24c3d30af44c39c2..4baf15fcc240ad98712f30d4d42a49855513be51 100644
--- a/src/main/java/fr/univlille/sae/classification/controller/LoadDataController.java
+++ b/src/main/java/fr/univlille/sae/classification/controller/LoadDataController.java
@@ -1,5 +1,7 @@
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);
- ClassificationModel.getClassificationModel().loadData(file);
+ 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();
}
}
diff --git a/src/main/java/fr/univlille/sae/classification/knn/MethodKNN.java b/src/main/java/fr/univlille/sae/classification/knn/MethodKNN.java
index ce462a0b5c12e72f1ac2d9de29bed32aee1006a3..d56d4226ec125293d089f7f2056dc5bc112b0607 100644
--- a/src/main/java/fr/univlille/sae/classification/knn/MethodKNN.java
+++ b/src/main/java/fr/univlille/sae/classification/knn/MethodKNN.java
@@ -1,5 +1,6 @@
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));
}
diff --git a/src/main/java/fr/univlille/sae/classification/model/ClassificationModel.java b/src/main/java/fr/univlille/sae/classification/model/ClassificationModel.java
index 0c5291ca16dadd29e930f2346bec1219feb9c5f5..24b491a1c7d370ef20a53c68031cf1bcbeb851da 100644
--- a/src/main/java/fr/univlille/sae/classification/model/ClassificationModel.java
+++ b/src/main/java/fr/univlille/sae/classification/model/ClassificationModel.java
@@ -1,6 +1,8 @@
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() {
diff --git a/src/main/java/fr/univlille/sae/classification/model/Iris.java b/src/main/java/fr/univlille/sae/classification/model/Iris.java
index e034149b6d6ec8a8ce2f950fcb7aaa44e5bfad36..fbf1734713ae37b123b20e4f9f1f06cbfce9fe32 100644
--- a/src/main/java/fr/univlille/sae/classification/model/Iris.java
+++ b/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;
diff --git a/src/main/java/fr/univlille/sae/classification/model/PointFactory.java b/src/main/java/fr/univlille/sae/classification/model/PointFactory.java
index bddf6995eb5e17c5e48b7de573ec1fa00dbac038..27eba5e9a8c138c2bf0ef639b73bfeada563ed68 100644
--- a/src/main/java/fr/univlille/sae/classification/model/PointFactory.java
+++ b/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:
diff --git a/src/main/java/fr/univlille/sae/classification/model/Pokemon.java b/src/main/java/fr/univlille/sae/classification/model/Pokemon.java
index 5a251f7d2e1328a5cf0490bf3bd6c708c9503bd7..7ac5fad96ac847d5199b969014b9c3f852fa4e79 100644
--- a/src/main/java/fr/univlille/sae/classification/model/Pokemon.java
+++ b/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;
- this.type1 = type1;
+ 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
diff --git a/src/main/java/fr/univlille/sae/classification/view/MainStageView.java b/src/main/java/fr/univlille/sae/classification/view/MainStageView.java
index 3c9c13400d3273d647386a4ce8aec774fbaa9c48..39d6cb935722bf87d326a8dd611ede4a49267a0e 100644
--- a/src/main/java/fr/univlille/sae/classification/view/MainStageView.java
+++ b/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);