Delete a bunch of unused methods

src/main/java/org/broadinstitute/hellbender/tools/copynumber/denoising/SVDDenoisingUtils.java

@@ -35,8 +35,7 @@ public final class SVDDenoisingUtils {
     private static final Logger logger = LogManager.getLogger(SVDDenoisingUtils.class);
 
     private static final double EPSILON = 1E-9;
-    private static final double INV_LN2 = MathUtils.INV_LOG_2;
-    private static final double LN2_EPSILON = Math.log(EPSILON) * INV_LN2;
+    private static final double LN2_EPSILON = Math.log(EPSILON) * MathUtils.INV_LOG_2;
 
     private SVDDenoisingUtils() {}
 
@@ -459,7 +458,8 @@ private static int countNumberPassingFilter(final boolean[] filter) {
 
     private static void transformToFractionalCoverage(final RealMatrix matrix) {
         logger.info("Transforming read counts to fractional coverage...");
-        final double[] sampleSums = MathUtils.rowSums(matrix);
+        final double[] sampleSums = IntStream.range(0, matrix.getRowDimension())
+                .mapToDouble(r -> MathUtils.sum(matrix.getRow(r))).toArray();
         matrix.walkInOptimizedOrder(new DefaultRealMatrixChangingVisitor() {
             @Override
             public double visit(int sampleIndex, int intervalIndex, double value) {
@@ -498,6 +498,6 @@ private static int calculateMaximumZerosCount(final int numTotalCounts,
     }
 
     private static double safeLog2(final double x) {
-        return x < EPSILON ? LN2_EPSILON : Math.log(x) * INV_LN2;
+        return x < EPSILON ? LN2_EPSILON : Math.log(x) * MathUtils.INV_LOG_2;
     }
 }

src/main/java/org/broadinstitute/hellbender/tools/copynumber/gcnv/GermlineCNVIntervalVariantComposer.java

@@ -186,6 +186,6 @@ static int calculateGenotypeQuality(final CopyNumberPosteriorDistribution copyNu
     }
 
     private static int convertLogProbabilityToPhredScore(final double posteriorProbInLogSpace) {
-        return (int) FastMath.floor(-10.0 * posteriorProbInLogSpace * MathUtils.LOG10_OF_E);
+        return (int) FastMath.floor(-10.0 * posteriorProbInLogSpace * MathUtils.LOG10_E);
     }
 }

src/main/java/org/broadinstitute/hellbender/tools/walkers/annotator/AlleleFraction.java

@@ -1,9 +1,7 @@
 package org.broadinstitute.hellbender.tools.walkers.annotator;
 
 import htsjdk.variant.variantcontext.*;
-import htsjdk.variant.vcf.VCFConstants;
 import htsjdk.variant.vcf.VCFFormatHeaderLine;
-import htsjdk.variant.vcf.VCFStandardHeaderLines;
 import org.broadinstitute.barclay.help.DocumentedFeature;
 import org.broadinstitute.hellbender.engine.ReferenceContext;
 import org.broadinstitute.hellbender.utils.MathUtils;
@@ -54,14 +52,14 @@ public void annotate(final ReferenceContext ref,
         for ( final Genotype genotype : genotypes ) {
            if ( genotype.hasAD() ) {
                 final int[] AD = genotype.getAD();
-                final double[] allAlleleFractions = MathUtils.normalizeFromRealSpace(Arrays.stream(AD).mapToDouble(x -> x).toArray());
+                final double[] allAlleleFractions = MathUtils.normalizeSumToOne(Arrays.stream(AD).mapToDouble(x -> x).toArray());
                 gb.attribute(getKeyNames().get(0), Arrays.copyOfRange(allAlleleFractions, 1, allAlleleFractions.length)); //omit the first entry of the array corresponding to the reference
             }
             // if there is no AD value calculate it now using likelihoods
             else if (likelihoods != null) {
                 DepthPerAlleleBySample adCalc = new DepthPerAlleleBySample();
                 final int[] AD = adCalc.annotateWithLikelihoods(vc, g, new LinkedHashSet<>(vc.getAlleles()), likelihoods);
-                final double[] allAlleleFractions = MathUtils.normalizeFromRealSpace(Arrays.stream(AD).mapToDouble(x -> x*1.0).toArray());
+                final double[] allAlleleFractions = MathUtils.normalizeSumToOne(Arrays.stream(AD).mapToDouble(x -> x*1.0).toArray());
                 gb.attribute(getKeyNames().get(0), Arrays.copyOfRange(allAlleleFractions, 1, allAlleleFractions.length)); //omit the first entry of the array corresponding to the reference
             }
         }

src/main/java/org/broadinstitute/hellbender/tools/walkers/genotyper/afcalc/AFCalculationResult.java

@@ -74,10 +74,10 @@ public AFCalculationResult(final int[] alleleCountsOfMLE,
         }
         if ( ! allelesUsedInGenotyping.containsAll(log10pRefByAllele.keySet()) ) {
             throw new IllegalArgumentException("log10pRefByAllele doesn't contain all of the alleles used in genotyping: log10pRefByAllele " + log10pRefByAllele + " but allelesUsedInGenotyping " + allelesUsedInGenotyping);
-        }if ( ! MathUtils.goodLog10ProbVector(log10LikelihoodsOfAC, LOG_10_ARRAY_SIZES, false) ) {
+        }if ( ! MathUtils.isValidLog10ProbabilityVector(log10LikelihoodsOfAC, LOG_10_ARRAY_SIZES, false) ) {
             throw new IllegalArgumentException("log10LikelihoodsOfAC are bad " + Utils.join(",", log10LikelihoodsOfAC));
         }
-        if ( ! MathUtils.goodLog10ProbVector(log10PriorsOfAC, LOG_10_ARRAY_SIZES, false) ) {
+        if ( ! MathUtils.isValidLog10ProbabilityVector(log10PriorsOfAC, LOG_10_ARRAY_SIZES, false) ) {
             throw new IllegalArgumentException("log10priors are bad " + Utils.join(",", log10PriorsOfAC));
         }
 

src/main/java/org/broadinstitute/hellbender/tools/walkers/haplotypecaller/AssemblyResultSet.java

@@ -525,11 +525,27 @@ public SortedSet<VariantContext> getVariationEvents(final int maxMnpDistance) {
     public void regenerateVariationEvents(int maxMnpDistance) {
         final List<Haplotype> haplotypeList = getHaplotypeList();
         EventMap.buildEventMapsForHaplotypes(haplotypeList, fullReferenceWithPadding, paddedReferenceLoc, debug, maxMnpDistance);
-        variationEvents = EventMap.getAllVariantContexts(haplotypeList);
+        variationEvents = getAllVariantContexts(haplotypeList);
         lastMaxMnpDistanceUsed = OptionalInt.of(maxMnpDistance);
         variationPresent = haplotypeList.stream().anyMatch(Haplotype::isNonReference);
     }
 
+    /**
+     * Get all of the VariantContexts in the event maps for all haplotypes, sorted by their start position
+     * @param haplotypes the set of haplotypes to grab the VCs from
+     * @return a sorted set of variant contexts
+     */
+    private static SortedSet<VariantContext> getAllVariantContexts( final List<Haplotype> haplotypes ) {
+        // Using the cigar from each called haplotype figure out what events need to be written out in a VCF file
+        final TreeSet<VariantContext> vcs = new TreeSet<>(Comparator.comparingInt(VariantContext::getStart));
+
+        for( final Haplotype h : haplotypes ) {
+            vcs.addAll(h.getEventMap().getVariantContexts());
+        }
+
+        return vcs;
+    }
+
     public void setDebug(boolean debug) {
         this.debug = debug;
     }

src/main/java/org/broadinstitute/hellbender/tools/walkers/mutect/CreateSomaticPanelOfNormals.java

@@ -201,7 +201,7 @@ private static final double germlineProbability(final double alleleFrequency, fi
         final double[] relativeProbsOfHetHomArtifact = {hetPrior * hetLikelihood + homPrior * homLikelihood, ARTIFACT_PRIOR * artifactLikelihood};
 
         // check for invalid probabilities just in case of finite precision error
-        return MathUtils.sum(relativeProbsOfHetHomArtifact) < 0 ? 0 : MathUtils.normalizeFromRealSpace(relativeProbsOfHetHomArtifact)[0];
+        return MathUtils.sum(relativeProbsOfHetHomArtifact) < 0 ? 0 : MathUtils.normalizeSumToOne(relativeProbsOfHetHomArtifact)[0];
     }
 
     private BetaDistributionShape fitBeta(final List<int[]> altAndRefCounts) {

src/main/java/org/broadinstitute/hellbender/tools/walkers/mutect/SomaticGenotypingEngine.java

@@ -242,7 +242,7 @@ private void addGenotypes(final ReadLikelihoods<Allele> logLikelihoods,
             final double[] flatPriorPseudocounts = new IndexRange(0, logMatrix.numberOfAlleles()).mapToDouble(a -> 1);
             final double[] alleleFractionsPosterior = logMatrix.numberOfReads() == 0 ? flatPriorPseudocounts :
                     SomaticLikelihoodsEngine.alleleFractionsPosterior(getAsRealMatrix(logMatrix), flatPriorPseudocounts);
-            final double[] tumorAlleleFractionsMean = MathUtils.normalizeFromRealSpace(alleleFractionsPosterior);
+            final double[] tumorAlleleFractionsMean = MathUtils.normalizeSumToOne(alleleFractionsPosterior);
 
             // TODO: We shouldn't always assume that the genotype in the normal is hom ref
             final Allele ref = logMatrix.getAllele(getRefIndex(logMatrix));

src/main/java/org/broadinstitute/hellbender/tools/walkers/mutect/filtering/StrandArtifactFilter.java

@@ -127,8 +127,8 @@ EStep strandArtifactProbability(final double strandArtifactPrior, int forwardCou
         final double reverseLogPrior = Math.log(strandArtifactPrior/2);
         final double noneLogPrior = Math.log(1 - strandArtifactPrior);
 
-        final double[] forwardReverseNoneProbs = MathUtils.normalizeLog10(new double[] {(forwardLogLikelihood + forwardLogPrior) * MathUtils.LOG10_OF_E,
-                (reverseLogLikelihood + reverseLogPrior)* MathUtils.LOG10_OF_E, (noneLogLikelihood + noneLogPrior) * MathUtils.LOG10_OF_E}, false, true);
+        final double[] forwardReverseNoneProbs = MathUtils.normalizeLog10(new double[] {(forwardLogLikelihood + forwardLogPrior) * MathUtils.LOG10_E,
+                (reverseLogLikelihood + reverseLogPrior)* MathUtils.LOG10_E, (noneLogLikelihood + noneLogPrior) * MathUtils.LOG10_E}, false, true);
 
         return new EStep(forwardReverseNoneProbs[0], forwardReverseNoneProbs[1], forwardCount, reverseCount, forwardAltCount, reverseAltCount);
     }

src/main/java/org/broadinstitute/hellbender/tools/walkers/readorientation/LearnReadOrientationModelEngine.java

@@ -292,7 +292,7 @@ public static double[] computeResponsibilities(final Nucleotide refAllele, final
     private static double computeLogPosterior(final int altDepth, final int altF1R2Depth, final int depth,
                                               final double statePrior, final BetaDistributionShape afPseudoCounts,
                                               final BetaDistributionShape f1r2PseudoCounts){
-        Utils.validateArg(MathUtils.isAProbability(statePrior), String.format("statePrior must be a probability but got %f", statePrior));
+        Utils.validateArg(MathUtils.isValidProbability(statePrior), String.format("statePrior must be a probability but got %f", statePrior));
 
         return Math.log(statePrior)
                 + new BetaBinomialDistribution(null, afPseudoCounts.getAlpha(), afPseudoCounts.getBeta(), depth).logProbability(altDepth)

src/main/java/org/broadinstitute/hellbender/utils/Dirichlet.java

@@ -1,11 +1,8 @@
 package org.broadinstitute.hellbender.utils;
 
 import org.apache.commons.math3.special.Gamma;
-import org.apache.commons.math3.util.MathArrays;
 
-import java.util.Arrays;
 import java.util.Collections;
-import java.util.stream.IntStream;
 
 /**
  * The Dirichlet distribution is a distribution on multinomial distributions: if pi is a vector of positive multinomial weights
@@ -53,7 +50,7 @@ public double[] effectiveMultinomialWeights() {
 
     public double[] effectiveLog10MultinomialWeights() {
         final double digammaOfSum = Gamma.digamma(MathUtils.sum(alpha));
-        return MathUtils.applyToArray(alpha, a -> (Gamma.digamma(a) - digammaOfSum) * MathUtils.LOG10_OF_E);
+        return MathUtils.applyToArray(alpha, a -> (Gamma.digamma(a) - digammaOfSum) * MathUtils.LOG10_E);
     }
 
     public double[] effectiveLogMultinomialWeights() {

src/main/java/org/broadinstitute/hellbender/utils/GenotypeUtils.java

@@ -73,7 +73,7 @@ public static GenotypeCounts computeDiploidGenotypeCounts(final VariantContext v
                         varIndex = idxVector[2];
                     }
                 }
-                biallelicLikelihoods = MathUtils.normalizeFromRealSpace(new double[] {normalizedLikelihoods[idxAA], normalizedLikelihoods[hetIndex], normalizedLikelihoods[varIndex]});
+                biallelicLikelihoods = MathUtils.normalizeSumToOne(new double[] {normalizedLikelihoods[idxAA], normalizedLikelihoods[hetIndex], normalizedLikelihoods[varIndex]});
             }
             else {
                 biallelicLikelihoods = normalizedLikelihoods;