Engadidas cabeceiras de licencia e actualizada documentación

codigo/expliclas-api/src/main/java/brunolopez/expliclas/builder/BuilderManager.java

+/*
+ * Copyright (C) 2018 Bruno López Trigo
+ * 
+ * This program is free software; you can redistribute it and/or
+ * modify it under the terms of the GNU General Public License
+ * as published by the Free Software Foundation; either version 2
+ * of the License, or (at your option) any later version.
+
+ * This program is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ * GNU General Public License for more details.
+
+ * You should have received a copy of the GNU General Public License
+ * along with this program; if not, write to the Free Software
+ * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301, USA.
+ */
+
 package brunolopez.expliclas.builder;
 
 import brunolopez.expliclas.exceptions.ConflictEx;
@@ -7,7 +25,10 @@ import brunolopez.expliclas.models.DatasetConfig;
 import brunolopez.expliclas.models.Instance;
 
 public interface BuilderManager {
-    
-    public DatasetConfig buildModels(String token, String datasetName, String model, String[] options) throws ConflictEx, FormatEx, NotFoundEx;
-    public double classifyFURIA(String token, String datasetName, String[] options, Instance instance) throws FormatEx, NotFoundEx;
+
+	public DatasetConfig buildModels(String token, String datasetName, String model, String[] options)
+			throws ConflictEx, FormatEx, NotFoundEx;
+
+	public double classifyFURIA(String token, String datasetName, String[] options, Instance instance)
+			throws FormatEx, NotFoundEx;
 }

codigo/expliclas-api/src/main/java/brunolopez/expliclas/builder/BuilderManagerImpl.java

+/*
+ * Copyright (C) 2018 Bruno López Trigo
+ * 
+ * This program is free software; you can redistribute it and/or
+ * modify it under the terms of the GNU General Public License
+ * as published by the Free Software Foundation; either version 2
+ * of the License, or (at your option) any later version.
+
+ * This program is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ * GNU General Public License for more details.
+
+ * You should have received a copy of the GNU General Public License
+ * along with this program; if not, write to the Free Software
+ * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301, USA.
+ */
+
 package brunolopez.expliclas.builder;
 
 import java.io.File;
@@ -156,15 +174,15 @@ public class BuilderManagerImpl implements BuilderManager {
 			double distance;
 
 			// Genera la configuración del experto
-			
+
 			for (int i = 0; i < instancesLRN.numAttributes(); i++) {
 				log.println("              " + instancesLRN.attribute(i).name());
 				if (i != (instancesLRN.numAttributes() - 1)) {
-					
-					/* 
+
+					/*
 					 * 
 					 * Para el caso de los atributos numéricos dividir el atributo en 3 intervalos
-					 * idénticos con etiquetas (Low, Medium, High) 
+					 * idénticos con etiquetas (Low, Medium, High)
 					 * 
 					 */
 					if (instancesLRN.attribute(i).isNumeric()) {
@@ -182,11 +200,11 @@ public class BuilderManagerImpl implements BuilderManager {
 								new Interval(minMax[0] + distance, minMax[0] + 2 * distance), 1));
 						config.getAttributes().get(i).getProperties()
 								.add(new NumericProperty("High", new Interval(minMax[0] + 2 * distance, minMax[1]), 2));
-					} 
-					/* 
+					}
+					/*
 					 * 
-					 * Para el caso de los atributos categóricos las etiquetas son los posibles valores
-					 * del atributo
+					 * Para el caso de los atributos categóricos las etiquetas son los posibles
+					 * valores del atributo
 					 * 
 					 */
 					else {
@@ -202,7 +220,7 @@ public class BuilderManagerImpl implements BuilderManager {
 			}
 
 			// Añadir a la configuración los consecuentes o clases del problema
-			
+
 			for (int i = 0; i < instancesLRN.classAttribute().numValues(); i++) {
 
 				config.getConsequents().add(new Consequent((i + 1), instancesLRN.classAttribute().value(i),
@@ -233,7 +251,6 @@ public class BuilderManagerImpl implements BuilderManager {
 
 			Evaluation evalLRN = new Evaluation(instancesLRN, null);
 
-
 			/*
 			 * 
 			 * Evaluar el modelo usando un 10 cross-validation por defecto
@@ -312,7 +329,7 @@ public class BuilderManagerImpl implements BuilderManager {
 	/*
 	 * 
 	 * Construye el modelo de clasificación de WEKA para FURIA para clasificar una
-	 * instancia concreta. Este método se utiliza para clasificar cuando se produce 
+	 * instancia concreta. Este método se utiliza para clasificar cuando se produce
 	 * stretching, vote for the most frequent class o abstain.
 	 * 
 	 */
@@ -351,7 +368,8 @@ public class BuilderManagerImpl implements BuilderManager {
 				}
 			}
 
-			// Especificamos que la instancia es del mismo tipo que las instancias de entrenamiento
+			// Especificamos que la instancia es del mismo tipo que las instancias de
+			// entrenamiento
 			wekaInstance.setDataset(instancesLRN);
 			// Especificamos una clase cualquiera de salida (en este caso la primera)
 			wekaInstance.setClassValue(instancesLRN.instance(0).classValue());

codigo/expliclas-api/src/main/java/brunolopez/expliclas/classifiers/ClassifierManager.java

+/*
+ * Copyright (C) 2018 Bruno López Trigo
+ * 
+ * This program is free software; you can redistribute it and/or
+ * modify it under the terms of the GNU General Public License
+ * as published by the Free Software Foundation; either version 2
+ * of the License, or (at your option) any later version.
+
+ * This program is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ * GNU General Public License for more details.
+
+ * You should have received a copy of the GNU General Public License
+ * along with this program; if not, write to the Free Software
+ * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301, USA.
+ */
+
 package brunolopez.expliclas.classifiers;
 
 import brunolopez.expliclas.exceptions.ConflictEx;

codigo/expliclas-api/src/main/java/brunolopez/expliclas/classifiers/MatrixBuilder.java

+/*
+ * Copyright (C) 2018 Bruno López Trigo
+ * 
+ * This program is free software; you can redistribute it and/or
+ * modify it under the terms of the GNU General Public License
+ * as published by the Free Software Foundation; either version 2
+ * of the License, or (at your option) any later version.
+
+ * This program is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ * GNU General Public License for more details.
+
+ * You should have received a copy of the GNU General Public License
+ * along with this program; if not, write to the Free Software
+ * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301, USA.
+ */
+
 package brunolopez.expliclas.classifiers;
 
 import java.io.BufferedReader;
@@ -22,116 +40,119 @@ import brunolopez.expliclas.utils.MapperJSON;
  */
 public class MatrixBuilder {
 
-    private BufferedReader reader;
-    private final FileManager fmanager;
-
-    public MatrixBuilder(File input) throws FileNotFoundException {
-        this.reader = new BufferedReader(new FileReader(input));
-        this.fmanager = new FileManager();
-    }
-
-    /*
-     * 
-     * Construcción de la matriz de cross-validation, se limita a la lectura
-     * del modelo de WEKA
-     * 
-     */
-    public Matrix readMatrix() throws IOException {
-        String line = "";
-
-        ArrayList<Integer> row = new ArrayList<>();
-
-        Matrix m = new Matrix();
-
-        while (!line.startsWith("=== Confusion")) {
-            line = this.reader.readLine();
-        }
-
-        for (int i = 0; i < 2; i++) {
-            this.reader.readLine();
-        }
-
-        line = this.reader.readLine().split(" \\| ")[0].trim();
-
-        while (line != null && !line.isEmpty()) {
-
-            for (String s : line.split("\\s+")) {
-                row.add(Integer.parseInt(s));
-            }
-
-            m.addRow(row);
-            row.clear();
-
-            line = this.reader.readLine();
-            if (line != null) {
-                line = line.split(" \\| ")[0].trim();
-            }
-
-        }
-
-        this.reader.close();
-
-        m.setPrecision();
-
-        return m;
-
-    }
-
-    /*
-     * 
-     * Construcción de la matriz de confusión de entrenamiento y test, requiere de la lectura
-     * de los archivos de predicciones
-     * 
-     */
-    public Matrix buildMatrixInstances(String token, String name, String algorithm, String type, boolean abstain) throws NotFoundEx, IOException, FormatEx {
-
-        File predictions;
-        File configFile;
-        MapperJSON mapper = new MapperJSON();
-        Position p;
-        Matrix m;
-
-        try {
-            configFile = this.fmanager.getConfig(token, name, "en");
-            DatasetConfig config = mapper.readConfigJSON(configFile);
-
-            // Se obtienen las predicciones
-            if (type.equals("train")) {
-                predictions = this.fmanager.getPredictions(token, name, algorithm);
-            } else {
-                predictions = this.fmanager.getPredictionsTest(token, name, algorithm);
-            }
-            
-            // Se crea una matriz, indicando se tiene columna de abstenciones o no
-            m = new Matrix(config.getConsequents().size(), abstain);
-            
-            this.reader = new BufferedReader(new FileReader(predictions));
-            String line = reader.readLine();
-            int instance = 1;
-            
-            while (line != null) {
-            	// Si la predicción es "NaN" entonces hay una abstención
-            	if(line.split(" ")[1].equals("NaN")) {
-            		p = new Position((int) Float.parseFloat(line.split(" ")[0]), config.getConsequents().size());
-            	} else {
-            		p = new Position((int) Float.parseFloat(line.split(" ")[0]), (int) Float.parseFloat(line.split(" ")[1]));
-            	}
-            	// Si la predicción es incorrecta se añade a la lista de instancias confundidas la instancia
-            	if (p.getRow() != p.getColumn()) {
-                    m.addConfused(p, instance);
-                }
-            	// Se incrementa en la matriz la posición correspondiente a la predicción
-                m.increment(p.getRow(), p.getColumn());
-                line = reader.readLine();
-                instance++;
-            }
-        } catch (Exception ex) {
-            throw new FormatEx("Something went wrong building " + type + " matrix");
-        }
-
-        m.setPrecision();
-        
-        return m;
-
-    }
+	private BufferedReader reader;
+	private final FileManager fmanager;
+
+	public MatrixBuilder(File input) throws FileNotFoundException {
+		this.reader = new BufferedReader(new FileReader(input));
+		this.fmanager = new FileManager();
+	}
+
+	/*
+	 * 
+	 * Construcción de la matriz de cross-validation, se limita a la lectura del
+	 * modelo de WEKA
+	 * 
+	 */
+	public Matrix readMatrix() throws IOException {
+		String line = "";
+
+		ArrayList<Integer> row = new ArrayList<>();
+
+		Matrix m = new Matrix();
+
+		while (!line.startsWith("=== Confusion")) {
+			line = this.reader.readLine();
+		}
+
+		for (int i = 0; i < 2; i++) {
+			this.reader.readLine();
+		}
+
+		line = this.reader.readLine().split(" \\| ")[0].trim();
+
+		while (line != null && !line.isEmpty()) {
+
+			for (String s : line.split("\\s+")) {
+				row.add(Integer.parseInt(s));
+			}
+
+			m.addRow(row);
+			row.clear();
+
+			line = this.reader.readLine();
+			if (line != null) {
+				line = line.split(" \\| ")[0].trim();
+			}
+
+		}
+
+		this.reader.close();
+
+		m.setPrecision();
+
+		return m;
+
+	}
+
+	/*
+	 * 
+	 * Construcción de la matriz de confusión de entrenamiento y test, requiere de
+	 * la lectura de los archivos de predicciones
+	 * 
+	 */
+	public Matrix buildMatrixInstances(String token, String name, String algorithm, String type, boolean abstain)
+			throws NotFoundEx, IOException, FormatEx {
+
+		File predictions;
+		File configFile;
+		MapperJSON mapper = new MapperJSON();
+		Position p;
+		Matrix m;
+
+		try {
+			configFile = this.fmanager.getConfig(token, name, "en");
+			DatasetConfig config = mapper.readConfigJSON(configFile);
+
+			// Se obtienen las predicciones
+			if (type.equals("train")) {
+				predictions = this.fmanager.getPredictions(token, name, algorithm);
+			} else {
+				predictions = this.fmanager.getPredictionsTest(token, name, algorithm);
+			}
+
+			// Se crea una matriz, indicando se tiene columna de abstenciones o no
+			m = new Matrix(config.getConsequents().size(), abstain);
+
+			this.reader = new BufferedReader(new FileReader(predictions));
+			String line = reader.readLine();
+			int instance = 1;
+
+			while (line != null) {
+				// Si la predicción es "NaN" entonces hay una abstención
+				if (line.split(" ")[1].equals("NaN")) {
+					p = new Position((int) Float.parseFloat(line.split(" ")[0]), config.getConsequents().size());
+				} else {
+					p = new Position((int) Float.parseFloat(line.split(" ")[0]),
+							(int) Float.parseFloat(line.split(" ")[1]));
+				}
+				// Si la predicción es incorrecta se añade a la lista de instancias confundidas
+				// la instancia
+				if (p.getRow() != p.getColumn()) {
+					m.addConfused(p, instance);
+				}
+				// Se incrementa en la matriz la posición correspondiente a la predicción
+				m.increment(p.getRow(), p.getColumn());
+				line = reader.readLine();
+				instance++;
+			}
+		} catch (Exception ex) {
+			throw new FormatEx("Something went wrong building " + type + " matrix");
+		}
+
+		m.setPrecision();
+
+		return m;
+
+	}
 }

codigo/expliclas-api/src/main/java/brunolopez/expliclas/classifiers/RuleBuilder.java

+/*
+ * Copyright (C) 2018 Bruno López Trigo
+ * 
+ * This program is free software; you can redistribute it and/or
+ * modify it under the terms of the GNU General Public License
+ * as published by the Free Software Foundation; either version 2
+ * of the License, or (at your option) any later version.
+
+ * This program is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ * GNU General Public License for more details.
+
+ * You should have received a copy of the GNU General Public License
+ * along with this program; if not, write to the Free Software
+ * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301, USA.
+ */
+
 package brunolopez.expliclas.classifiers;
 
 import java.io.File;
@@ -68,12 +86,12 @@ public class RuleBuilder {
 		Rules rules = new Rules();
 		rules.setOptions(options);
 
-		/* 
+		/*
 		 * 
 		 * Detección de opciones importantes:
 		 * 
-		 * -p: para determinar si la TNorm es producto o mínimo
-		 * -s: para determinar la acción cuando no se activan reglas.
+		 * -p: para determinar si la TNorm es producto o mínimo -s: para determinar la
+		 * acción cuando no se activan reglas.
 		 * 
 		 */
 		for (int i = 0; i < options.length; i++) {
@@ -107,26 +125,26 @@ public class RuleBuilder {
 
 		/*
 		 * 
-		 *  Expresión regular de intervalo numérico
-		 *  
-		 *  Grupo 1: atributo - Grupo 2: valores
-		 *  
+		 * Expresión regular de intervalo numérico
+		 * 
+		 * Grupo 1: atributo - Grupo 2: valores
+		 * 
 		 */
 		Pattern numericInterval = Pattern.compile("^\\((.*)\\sin\\s\\[(.*)\\]\\)$");
 		/*
 		 * 
-		 *  Expresión regular de intervalo categórico
-		 *  
-		 *  Grupo 1: atributo - Grupo 2: valor
-		 *  
+		 * Expresión regular de intervalo categórico
+		 * 
+		 * Grupo 1: atributo - Grupo 2: valor
+		 * 
 		 */
 		Pattern categoricInterval = Pattern.compile("^\\((.*)\\s=\\s(.*)\\)$");
 		/*
 		 * 
-		 *  Expresión regular de intervalo categórico
-		 *  
-		 *  Grupo 1: consecuente - Grupo 2: CF
-		 *  
+		 * Expresión regular de intervalo categórico
+		 * 
+		 * Grupo 1: consecuente - Grupo 2: CF
+		 * 
 		 */
 		Pattern outputClass = Pattern.compile("^.*=(.*)\\s\\(CF\\s=\\s(.*)\\)$");
 
@@ -144,9 +162,9 @@ public class RuleBuilder {
 			rule = new Rule();
 			intervals = line.split(" and ");
 			for (int i = 0; i < intervals.length; i++) {
-				/* 
-				 * Si el intervalo contiene " => " estamos en el último
-				 * por lo tanto separamos el intervalo de la clase de salida
+				/*
+				 * Si el intervalo contiene " => " estamos en el último por lo tanto separamos
+				 * el intervalo de la clase de salida
 				 */
 				if (intervals[i].contains(" => ")) {
 					interval = intervals[i].split(" => ")[0];
@@ -167,9 +185,9 @@ public class RuleBuilder {
 					// Obtenemos los valores
 					values = numericMatch.group(2).split(", ");
 					/*
-					 * Para los casos -inf, el valor es el valor mínimo del atributo.
-					 * Para los casos inf, el valor es el máximo del atributo.
-					 * El resto de casos toman el valor directamente
+					 * Para los casos -inf, el valor es el valor mínimo del atributo. Para los casos
+					 * inf, el valor es el máximo del atributo. El resto de casos toman el valor
+					 * directamente
 					 */
 					if (values[0].equals("-inf")) {
 						component.setFirstFuzzyValue(
@@ -196,21 +214,21 @@ public class RuleBuilder {
 						component.setFourthFuzzyValue(Double.parseDouble(values[3]));
 					}
 					/*
-					 * Si el componente ya existía se realiza la intersección entre ambos componentes
-					 * y se calculan las ecuaciones de las rectas.
+					 * Si el componente ya existía se realiza la intersección entre ambos
+					 * componentes y se calculan las ecuaciones de las rectas.