minor style fixes

Author: LorenzBuehmann

components-core/src/main/java/org/dllearner/core/AbstractClassExpressionLearningProblem.java

@@ -33,7 +33,9 @@
  * @author Lorenz Buehmann
  *
  */
-public abstract class AbstractClassExpressionLearningProblem<T extends Score>  extends AbstractLearningProblem<T, OWLClassExpression, EvaluatedDescription<T>> implements LearningProblem {
+public abstract class AbstractClassExpressionLearningProblem<T extends Score>
+		extends AbstractLearningProblem<T, OWLClassExpression, EvaluatedDescription<T>>
+		implements LearningProblem {
 
 	protected OWLDataFactory dataFactory = new OWLDataFactoryImpl();
 	@ConfigOption(description = "load examples via class expression selector")

components-core/src/main/java/org/dllearner/core/AbstractLearningProblem.java

@@ -30,7 +30,9 @@
  * @author Jens Lehmann
  *
  */
-public abstract class AbstractLearningProblem<T extends Score, V extends OWLObject, W extends EvaluatedHypothesis<V, T>>  extends AbstractComponent implements LearningProblem {
+public abstract class AbstractLearningProblem<T extends Score, V extends OWLObject, W extends EvaluatedHypothesis<V, T>>
+		extends AbstractComponent
+		implements LearningProblem {
 
 	@ConfigOption(description="The reasoner component variable to use for this Learning Problem")
 	protected AbstractReasonerComponent reasoner;

components-core/src/main/java/org/dllearner/learningproblems/Heuristics.java

@@ -252,7 +252,7 @@ public static double[] getAScoreApproximationStep1(double beta, int nrOfPosExamp
 		// method approximates t * a / |R(A)|
 		double[] interval = Heuristics.getConfidenceInterval95Wald(nrOfSuccessfulInstanceChecks, nrOfInstanceChecks);
 		double diff = beta * (interval[1] - interval[0]);
-		double ret[] = new double[2];
+		double[] ret = new double[2];
 		ret[0] = beta * interval[0] + 0.5*diff;
 		ret[1] = diff;
 		return ret;
@@ -289,7 +289,7 @@ public static double[] getAScoreApproximationStep2(int nrOfPosClassifiedPositive
 		double lowerBorder = Heuristics.getAScore(recallLowerBorder, precisionLowerBorder, beta);
 		double upperBorder = Heuristics.getAScore(recallUpperBorder, precisionUpperBorder, beta);
 		double diff = upperBorder - lowerBorder;
-		double ret[] = new double[2];
+		double[] ret = new double[2];
 		ret[0] = lowerBorder + 0.5*diff;
 		ret[1] = diff;
 		return ret;

components-core/src/main/java/org/dllearner/utilities/examples/ExampleContainer.java

@@ -70,24 +70,14 @@ public int compareTo(@NotNull ExampleContainer e){
 			return 0;
 		}
 
-		boolean equalPosSize = false;
-		boolean equalNegSize = false;
-		
-		if(getPositiveExamples().size() == e.getPositiveExamples().size()){
-			equalPosSize = true;
-		} 
-		if(getNegativeExamples().size() == e.getNegativeExamples().size()){
-			equalNegSize = true;
-		} 
-		
+		boolean equalPosSize = getPositiveExamples().size() == e.getPositiveExamples().size();
+		boolean equalNegSize = getNegativeExamples().size() == e.getNegativeExamples().size();
 
 		if(equalPosSize && !equalNegSize)return 1;
 		if(equalNegSize && !equalPosSize)return -1;
-		if(!equalPosSize && !equalPosSize)return 1;
-		
+		if(!equalPosSize && !equalNegSize)return 1;
 
 		return 1;
-		
 	}
 
 	public SortedSet<OWLIndividual> getNegativeExamples() {
@@ -96,8 +86,4 @@ public SortedSet<OWLIndividual> getNegativeExamples() {
 	public SortedSet<OWLIndividual> getPositiveExamples() {
 		return positiveExamples;
 	}
-	
-	
-	
-
 }