Merge pull request #6 from bioclipse/FixedRegressionCOloring

Fixed regression coloring
bioclipse · Apr 2, 2013 · 822bc10 · 822bc10
2 parents 0d317ec + 9091663
commit 822bc10
Show file tree

Hide file tree

Showing 3 changed files with 53 additions and 21 deletions.
diff --git a/plugins/net.bioclipse.ds.common/src/net/bioclipse/ds/matcher/BaseSDFMatcher.java b/plugins/net.bioclipse.ds.common/src/net/bioclipse/ds/matcher/BaseSDFMatcher.java
@@ -256,6 +256,9 @@ public void completeReturn( SDFIndexEditorModel object ) {
 			throw new DSException("Initialization of DB exact match FP cancelled");
 		}
 
+		if (SDFmodel==null){
+			throw new DSException("Could not read SDFModel");
+		}
 		if (SDFmodel.getNumberOfMolecules()<=0){
 			throw new DSException("No molecules could be read in database");
 		}

diff --git a/plugins/net.bioclipse.ds.libsvm/src/net/bioclipse/ds/libsvm/SignaturesLibSVMPrediction.java b/plugins/net.bioclipse.ds.libsvm/src/net/bioclipse/ds/libsvm/SignaturesLibSVMPrediction.java
@@ -124,6 +124,10 @@ public void initialize(IProgressMonitor monitor) throws DSException {
 		String signaturesPath = getFileFromParameter(SIGNATURES_FILE_PARAMETER );
 		startHeight=Integer.parseInt(getParameters().get( SIGNATURES_MIN_HEIGHT ));
 		endHeight=Integer.parseInt(getParameters().get( SIGNATURES_MAX_HEIGHT ));
+		String infoma = getParameters().get( "isInformative" );
+		if (infoma!=null)
+			setInformative(Boolean.parseBoolean(getParameters().get( "isInformative" )));
+
 
 		//These are for regression
 		if ("false".equalsIgnoreCase(getParameters().get( "isClassification" ))){
@@ -288,30 +292,52 @@ public List<? extends ITestResult> predictLibSVM(ICDKMolecule cdkmol,
 		results.add(match);
 
 		//Logic for multi-class results here
-		int intPrediction=(int)prediction;
-		if (classLabels==null){
-			return returnError("No classlabels found in model", "Classlabels are null for model");
-		}
-		String predictedClassLabel = classLabels.get(intPrediction);
+		if (getParameters().get("isClassification").equalsIgnoreCase("true")){
 
-		logger.debug("Prediction result: " + prediction + ", predictedClassLabel=" + predictedClassLabel);
+			int intPrediction=(int)prediction;
+			if (classLabels==null){
+				return returnError("No classlabels found in model", "Classlabels are null for model");
+			}
+			String predictedClassLabel = classLabels.get(intPrediction);
 
-		//If this is higher than posVal in list, set POSITIVE color
-		int posIX = classLabels.indexOf(positiveValue);
-		int negIX = classLabels.indexOf(negativeValue);
-		int predIX = classLabels.indexOf(predictedClassLabel);
+			logger.debug("Prediction result: " + prediction + ", predictedClassLabel=" + predictedClassLabel);
 
-		if (predIX==posIX){
-			match.setClassification( ITestResult.POSITIVE );
-			match.setName("Result: Positive");
-		}
-		else if (predIX==negIX){
-			match.setClassification( ITestResult.NEGATIVE );
-			match.setName("Result: Negative");
-		}
-		else{
-			match.setClassification( ITestResult.INCONCLUSIVE );
-			match.setName("Result: Inconclusive");
+			//If this is higher than posVal in list, set POSITIVE color
+			int posIX = classLabels.indexOf(positiveValue);
+			int negIX = classLabels.indexOf(negativeValue);
+			int predIX = classLabels.indexOf(predictedClassLabel);
+
+			if (predIX==posIX){
+				match.setClassification( ITestResult.POSITIVE );
+				match.setName("Result: Positive");
+			}
+			else if (predIX==negIX){
+				match.setClassification( ITestResult.NEGATIVE );
+				match.setName("Result: Negative");
+			}
+			else{
+				match.setClassification( ITestResult.INCONCLUSIVE );
+				match.setName("Result: Inconclusive");
+			}
+
+		}else{
+			//Regression
+			if (isInformative())
+				match.setClassification( ITestResult.INFORMATIVE );
+			else{
+				if (prediction>regrUpperThreshold && lowIsNegative)
+					match.setClassification( ITestResult.POSITIVE );
+				else if (prediction>regrUpperThreshold && !lowIsNegative)
+					match.setClassification( ITestResult.NEGATIVE );
+				else if (prediction<regrLowerThreshold && lowIsNegative)
+					match.setClassification( ITestResult.NEGATIVE );
+				else if (prediction<regrLowerThreshold && !lowIsNegative)
+					match.setClassification( ITestResult.POSITIVE);
+			}
+
+			//Else, between the two, keep inconclusive
+			match.setName("Result: " + formatter.format(prediction));
+//			return results;
 		}
 
 
@@ -511,6 +537,8 @@ else if (predIX==negIX){
 			match = new ScaledResultMatch("Result: " 
 					+ formatter.format( prediction ), 
 					ITestResult.INFORMATIVE);
+			results.clear();
+			results.add(match);
 
 			int result=ITestResult.INCONCLUSIVE;
 			if (regrLowerThreshold!=null && regrUpperThreshold!=null){

diff --git a/plugins/net.bioclipse.ds.ui/src/net/bioclipse/ds/ui/views/DSView.java b/plugins/net.bioclipse.ds.ui/src/net/bioclipse/ds/ui/views/DSView.java
@@ -1205,6 +1205,7 @@ public void setFocus() {
 
     private void updateView() {
 
+    	if (viewer.getControl().isDisposed()) return;
         viewer.refresh();
 //        viewer.expandToLevel( 1 );
         viewer.expandAll();