add annotation mismatch warning and refactor tests

protected/gatk-tools-protected/src/main/java/org/broadinstitute/gatk/tools/walkers/variantrecalibration/VariantRecalibrator.java

@@ -279,11 +279,11 @@ public class VariantRecalibrator extends RodWalker<ExpandingArrayList<VariantDat
      *  model Gaussians can be subset by the value in the "Gaussian" column if desired.
      */
     @Argument(fullName="output_model", shortName = "outputModel", doc="If specified, the variant recalibrator will output the VQSR model fit to the file specified by -modelFile or to stdout", required=false)
-    private boolean outputModel = false;
+    private String outputModel = null;
     @Argument(fullName="input_model", shortName = "inputModel", doc="If specified, the variant recalibrator will read the VQSR model from this file path.", required=false)
     private String inputModel = "";
-    @Output(fullName="model_file", shortName = "modelFile", doc="A GATKReport containing the positive and negative model fits", required=false)
+    //@Output(fullName="model_file", shortName = "modelFile", doc="A GATKReport containing the positive and negative model fits", required=false)
-    protected PrintStream modelReport = null;
+    //protected PrintStream modelReport = null;
 
     @Hidden
     @Argument(fullName="replicate", shortName="replicate", doc="Used to debug the random number generation inside the VQSR. Do not use.", required=false)
@@ -370,7 +370,11 @@ public class VariantRecalibrator extends RodWalker<ExpandingArrayList<VariantDat
             final GATKReportTable pmcTable = reportIn.getTable("PositiveModelCovariances");
             final GATKReportTable pmmTable = reportIn.getTable("PositiveModelMeans");
             final GATKReportTable pPMixTable = reportIn.getTable("GoodGaussianPMix");
-            final int numAnnotations = dataManager.getMeanVector().length;
+            final int numAnnotations = dataManager.annotationKeys.size();
+
+            if( numAnnotations != pmmTable.getNumColumns()-1 || numAnnotations != nmmTable.getNumColumns()-1 ) { // -1 because the first column is the gaussian number.
+                throw new UserException.CommandLineException( "Annotations specified on the command line do not match annotations in the model report." );
+            }
 
             goodModel = GMMFromTables(pmmTable, pmcTable, pPMixTable, numAnnotations);
             badModel = GMMFromTables(nmmTable, nmcTable, nPMixTable, numAnnotations);
@@ -534,9 +538,13 @@ public class VariantRecalibrator extends RodWalker<ExpandingArrayList<VariantDat
                 dataManager.dropAggregateData(); // Don't need the aggregate data anymore so let's free up the memory
                 engine.evaluateData(dataManager.getData(), badModel, true);
 
-                if (outputModel) {
+                if (outputModel != null) {
-                    GATKReport report = writeModelReport(goodModel, badModel, USE_ANNOTATIONS);
+                    try (PrintStream modelReporter = new PrintStream(outputModel)) {
-                    report.print(modelReport);
+                        GATKReport report = writeModelReport(goodModel, badModel, USE_ANNOTATIONS);
+                        report.print(modelReporter);
+                    } catch (FileNotFoundException e){
+                        throw new UserException("Could not open output model file:" + outputModel);
+                    }
                 }
 
                 engine.calculateWorstPerformingAnnotation(dataManager.getData(), goodModel, badModel);

protected/gatk-tools-protected/src/test/java/org/broadinstitute/gatk/tools/walkers/variantrecalibration/VariantRecalibratorModelOutputUnitTest.java

@@ -68,17 +68,14 @@ import java.util.Random;
 public class VariantRecalibratorModelOutputUnitTest {
     protected final static Logger logger = Logger.getLogger(VariantRecalibratorModelOutputUnitTest.class);
     private final boolean printTables = true;
+    private final int numAnnotations = 6;
+    private final double shrinkage = 1.0;
+    private final double dirichlet = 0.001;
+    private final double priorCounts = 20.0;
+    private final double epsilon = 1e-6;
 
     @Test
     public void testVQSRModelOutput() {
-        final int numAnnotations = 6;
-        final double shrinkage = 1.0;
-        final double dirichlet = 0.001;
-        final double priorCounts = 20.0;
-        final int numGoodGaussians = 2;
-        final int numBadGaussians = 1;
-        final double epsilon = 1e-6;
-
         Random rand = new Random(12878);
         MultivariateGaussian goodGaussian1 = new MultivariateGaussian(numAnnotations);
         goodGaussian1.initializeRandomMu(rand);
@@ -170,10 +167,53 @@ public class VariantRecalibratorModelOutputUnitTest {
                 Assert.assertEquals(badGaussian1.sigma.get(i,j), (Double)badSigma.get(i,annotationList.get(j)), epsilon);
             }
         }
+    }
+
+
+    @Test
+    public void testVQSRModelInput(){
+        Random rand = new Random(12878);
+        MultivariateGaussian goodGaussian1 = new MultivariateGaussian(numAnnotations);
+        goodGaussian1.initializeRandomMu(rand);
+        goodGaussian1.initializeRandomSigma(rand);
+
+        MultivariateGaussian goodGaussian2 = new MultivariateGaussian(numAnnotations);
+        goodGaussian2.initializeRandomMu(rand);
+        goodGaussian2.initializeRandomSigma(rand);
+
+        MultivariateGaussian badGaussian1 = new MultivariateGaussian(numAnnotations);
+        badGaussian1.initializeRandomMu(rand);
+        badGaussian1.initializeRandomSigma(rand);
+
+        List<MultivariateGaussian> goodGaussianList = new ArrayList<>();
+        goodGaussianList.add(goodGaussian1);
+        goodGaussianList.add(goodGaussian2);
+
+        List<MultivariateGaussian> badGaussianList = new ArrayList<>();
+        badGaussianList.add(badGaussian1);
+
+        GaussianMixtureModel goodModel = new GaussianMixtureModel(goodGaussianList, shrinkage, dirichlet, priorCounts);
+        GaussianMixtureModel badModel = new GaussianMixtureModel(badGaussianList, shrinkage, dirichlet, priorCounts);
+
+        VariantRecalibrator vqsr = new VariantRecalibrator();
+        List<String> annotationList = new ArrayList<>();
+        annotationList.add("QD");
+        annotationList.add("MQ");
+        annotationList.add("FS");
+        annotationList.add("SOR");
+        annotationList.add("ReadPosRankSum");
+        annotationList.add("MQRankSum");
+
+        GATKReport report = vqsr.writeModelReport(goodModel, badModel, annotationList);
 
         // Now test model report reading
-        // Read the gaussian weighting tables
+        // Read all the tables
+        final GATKReportTable badMus = report.getTable("NegativeModelMeans");
+        final GATKReportTable badSigma = report.getTable("NegativeModelCovariances");
         final GATKReportTable nPMixTable = report.getTable("BadGaussianPMix");
+
+        final GATKReportTable goodMus = report.getTable("PositiveModelMeans");
+        final GATKReportTable goodSigma = report.getTable("PositiveModelCovariances");
         final GATKReportTable pPMixTable = report.getTable("GoodGaussianPMix");
 
         GaussianMixtureModel goodModelFromFile = vqsr.GMMFromTables(goodMus, goodSigma, pPMixTable, annotationList.size());
@@ -183,7 +223,6 @@ public class VariantRecalibratorModelOutputUnitTest {
         testGMMsForEquality(badModel, badModelFromFile, epsilon);
     }
 
-
     @Test
     //This is tested separately to avoid setting up a VariantDataManager and populating it with fake data
     public void testAnnotationNormalizationOutput() {