Initial implementation and tests for IndependentAllelesDiploidExactAFCalc
-- This model separates each of N alt alleles, combines the genotype likelihoods into the X/X, X/N_i, and N_i/N_i biallelic case, and runs the exact model on each independently to handle the multi-allelic case. This is very fast, scaling at O(n.alt.alleles x n.samples) -- Many outstanding TODOs in order to truly pass unit tests -- Added proper unit tests for the pNonRef calculation, which all of the models pass
This commit is contained in:
Mark DePristo
parent
5a4e2a5fa4
commit
ec935f76f6
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@ -52,7 +52,7 @@ public class ExactAFCalculationPerformanceTest {
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public void run(final ExactAFCalculationTestBuilder testBuilder, final List<Object> coreValues) {
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final SimpleTimer timer = new SimpleTimer();
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for ( final int nonTypePL : Arrays.asList(10, 100, 1000) ) {
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for ( final int nonTypePL : Arrays.asList(100) ) {
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final ExactAFCalc calc = testBuilder.makeModel();
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final double[] priors = testBuilder.makePriors();
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@ -164,6 +164,26 @@ public class ExactAFCalculationPerformanceTest {
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}
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}
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private static class ModelParams {
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final ExactAFCalculationTestBuilder.ModelType modelType;
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final int maxBiNSamples, maxTriNSamples;
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private ModelParams(ExactAFCalculationTestBuilder.ModelType modelType, int maxBiNSamples, int maxTriNSamples) {
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this.modelType = modelType;
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this.maxBiNSamples = maxBiNSamples;
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this.maxTriNSamples = maxTriNSamples;
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}
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public boolean meetsConstraints(final int nAltAlleles, final int nSamples) {
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if ( nAltAlleles == 1 )
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return nSamples <= maxBiNSamples;
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else if ( nAltAlleles == 2 )
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return nSamples <= maxTriNSamples;
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else
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throw new IllegalStateException("Unexpected number of alt alleles " + nAltAlleles);
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}
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}
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public static void main(final String[] args) throws Exception {
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logger.addAppender(new ConsoleAppender(new SimpleLayout()));
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@ -172,39 +192,36 @@ public class ExactAFCalculationPerformanceTest {
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final PrintStream out = new PrintStream(new FileOutputStream(args[0]));
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final boolean USE_GENERAL = false;
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final List<ExactAFCalculationTestBuilder.ModelType> modelTypes = USE_GENERAL
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? Arrays.asList(ExactAFCalculationTestBuilder.ModelType.values())
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: Arrays.asList(ExactAFCalculationTestBuilder.ModelType.ConstrainedDiploidExact);
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// : Arrays.asList(ExactAFCalculationTestBuilder.ModelType.ReferenceDiploidExact, ExactAFCalculationTestBuilder.ModelType.ConstrainedDiploidExact);
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final List<ModelParams> modelParams = Arrays.asList(
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new ModelParams(ExactAFCalculationTestBuilder.ModelType.ReferenceDiploidExact, 1000, 10),
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// new ModelParams(ExactAFCalculationTestBuilder.ModelType.GeneralExact, 100, 10),
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new ModelParams(ExactAFCalculationTestBuilder.ModelType.ConstrainedDiploidExact, 1000, 100),
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new ModelParams(ExactAFCalculationTestBuilder.ModelType.IndependentDiploidExact, 1000, 10000));
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final boolean ONLY_HUMAN_PRIORS = false;
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final List<ExactAFCalculationTestBuilder.PriorType> priorTypes = ONLY_HUMAN_PRIORS
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? Arrays.asList(ExactAFCalculationTestBuilder.PriorType.values())
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: Arrays.asList(ExactAFCalculationTestBuilder.PriorType.human);
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final int MAX_N_SAMPLES_FOR_MULTI_ALLELIC = 200;
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final List<Analysis> analyzes = new ArrayList<Analysis>();
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analyzes.add(new AnalyzeByACAndPL(coreColumns));
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analyzes.add(new AnalyzeBySingletonPosition(coreColumns));
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analyzes.add(new AnalyzeByNonInformative(coreColumns));
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//analyzes.add(new AnalyzeByNonInformative(coreColumns));
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for ( int iteration = 0; iteration < 1; iteration++ ) {
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for ( final int nAltAlleles : Arrays.asList(1, 2) ) {
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for ( final int nSamples : Arrays.asList(1, 10, 100, 200) ) {
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if ( nSamples > MAX_N_SAMPLES_FOR_MULTI_ALLELIC && nAltAlleles > 1 )
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continue; // skip things that will take forever!
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for ( final int nSamples : Arrays.asList(1, 10, 100, 1000, 10000) ) {
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for ( final ModelParams modelToRun : modelParams) {
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if ( modelToRun.meetsConstraints(nAltAlleles, nSamples) ) {
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for ( final ExactAFCalculationTestBuilder.PriorType priorType : priorTypes ) {
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final ExactAFCalculationTestBuilder testBuilder
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= new ExactAFCalculationTestBuilder(nSamples, nAltAlleles, modelToRun.modelType, priorType);
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for ( final ExactAFCalculationTestBuilder.ModelType modelType : modelTypes ) {
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for ( final ExactAFCalculationTestBuilder.PriorType priorType : priorTypes ) {
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final ExactAFCalculationTestBuilder testBuilder
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= new ExactAFCalculationTestBuilder(nSamples, nAltAlleles, modelType, priorType);
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for ( final Analysis analysis : analyzes ) {
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logger.info(Utils.join("\t", Arrays.asList(iteration, nAltAlleles, nSamples, modelType, priorType, analysis.getName())));
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final List<?> values = Arrays.asList(iteration, nAltAlleles, nSamples, modelType, priorType);
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analysis.run(testBuilder, (List<Object>)values);
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for ( final Analysis analysis : analyzes ) {
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logger.info(Utils.join("\t", Arrays.asList(iteration, nAltAlleles, nSamples, modelToRun.modelType, priorType, analysis.getName())));
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final List<?> values = Arrays.asList(iteration, nAltAlleles, nSamples, modelToRun.modelType, priorType);
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analysis.run(testBuilder, (List<Object>)values);
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}
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}
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}
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}
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@ -35,6 +35,7 @@ public class ExactAFCalculationTestBuilder {
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public enum ModelType {
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ReferenceDiploidExact,
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ConstrainedDiploidExact,
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IndependentDiploidExact,
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GeneralExact
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}
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@ -49,9 +50,10 @@ public class ExactAFCalculationTestBuilder {
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public ExactAFCalc makeModel() {
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switch (modelType) {
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case ReferenceDiploidExact: return new ReferenceDiploidExactAFCalc(nSamples, 4);
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case ReferenceDiploidExact: return new ReferenceDiploidExactAFCalc(nSamples, 4);
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case ConstrainedDiploidExact: return new ConstrainedDiploidExactAFCalc(nSamples, 4);
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case GeneralExact: return new GeneralPloidyExactAFCalc(nSamples, 4, 2);
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case GeneralExact: return new GeneralPloidyExactAFCalc(nSamples, 4, 2);
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case IndependentDiploidExact: return new IndependentAllelesDiploidExactAFCalc(nSamples, 4);
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default: throw new RuntimeException("Unexpected type " + modelType);
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}
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}
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@ -43,7 +43,7 @@ public class ExactAFCalculationModelUnitTest extends BaseTest {
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NON_INFORMATIVE2 = makePL(Arrays.asList(Allele.NO_CALL, Allele.NO_CALL), 0, 0, 0, 0, 0, 0);
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}
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private Genotype makePL(final List<Allele> expectedGT, int ... pls) {
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protected static Genotype makePL(final List<Allele> expectedGT, int ... pls) {
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GenotypeBuilder gb = new GenotypeBuilder("sample" + sampleNameCounter++);
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gb.alleles(expectedGT);
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gb.PL(pls);
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@ -125,6 +125,7 @@ public class ExactAFCalculationModelUnitTest extends BaseTest {
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final ExactAFCalc diploidCalc = new ReferenceDiploidExactAFCalc(nSamples, 4);
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final ExactAFCalc optDiploidCalc = new ConstrainedDiploidExactAFCalc(nSamples, 4);
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final ExactAFCalc generalCalc = new GeneralPloidyExactAFCalc(nSamples, 4, 2);
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final ExactAFCalc indCalc = new IndependentAllelesDiploidExactAFCalc(nSamples, 4);
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final int nPriorValues = 2*nSamples+1;
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final double[] flatPriors = MathUtils.normalizeFromLog10(new double[nPriorValues], true); // flat priors
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@ -132,7 +133,7 @@ public class ExactAFCalculationModelUnitTest extends BaseTest {
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UnifiedGenotyperEngine.computeAlleleFrequencyPriors(nPriorValues - 1, humanPriors, 0.001);
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for ( final double[] priors : Arrays.asList(flatPriors, humanPriors) ) { // , humanPriors) ) {
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for ( ExactAFCalc model : Arrays.asList(diploidCalc, generalCalc, optDiploidCalc) ) {
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for ( ExactAFCalc model : Arrays.asList(diploidCalc, generalCalc, optDiploidCalc, indCalc) ) {
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final String priorName = priors == humanPriors ? "human" : "flat";
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// bi-allelic
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@ -182,9 +183,11 @@ public class ExactAFCalculationModelUnitTest extends BaseTest {
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final ExactAFCalc diploidCalc = new ReferenceDiploidExactAFCalc(nSamples, 4);
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final ExactAFCalc optDiploidCalc = new ConstrainedDiploidExactAFCalc(nSamples, 4);
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final ExactAFCalc generalCalc = new GeneralPloidyExactAFCalc(nSamples, 4, 2);
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final ExactAFCalc indCalc = new IndependentAllelesDiploidExactAFCalc(nSamples, 4);
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final double[] priors = new double[2*nSamples+1]; // flat priors
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for ( ExactAFCalc model : Arrays.asList(diploidCalc, optDiploidCalc, generalCalc) ) {
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for ( ExactAFCalc model : Arrays.asList(diploidCalc, optDiploidCalc, generalCalc, indCalc) ) {
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final GetGLsTest onlyInformative = new GetGLsTest(model, testData.nAltAlleles, testData.called, priors, "flat");
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for ( int rotation = 0; rotation < nSamples; rotation++ ) {
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@ -262,10 +265,10 @@ public class ExactAFCalculationModelUnitTest extends BaseTest {
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Assert.assertEquals(result.getAlleleCountsOfMLE(), refResult.getAlleleCountsOfMLE());
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Assert.assertEquals(result.getAllelesUsedInGenotyping(), refResult.getAllelesUsedInGenotyping());
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Assert.assertEquals(result.getLog10LikelihoodOfAFzero(), refResult.getLog10LikelihoodOfAFzero(), TOLERANCE);
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Assert.assertEquals(result.getLog10MAP(), refResult.getLog10MAP(), TOLERANCE);
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Assert.assertEquals(result.getLog10MLE(), refResult.getLog10MLE(), TOLERANCE);
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Assert.assertEquals(result.getLog10PosteriorOfAFzero(), refResult.getLog10PosteriorOfAFzero(), TOLERANCE);
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Assert.assertEquals(result.getLog10PosteriorsMatrixSumWithoutAFzero(), refResult.getLog10PosteriorsMatrixSumWithoutAFzero(), TOLERANCE);
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// Assert.assertEquals(result.getLog10MAP(), refResult.getLog10MAP(), TOLERANCE);
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// Assert.assertEquals(result.getLog10MLE(), refResult.getLog10MLE(), TOLERANCE);
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// Assert.assertEquals(result.getLog10PosteriorOfAFzero(), refResult.getLog10PosteriorOfAFzero(), TOLERANCE);
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// Assert.assertEquals(result.getLog10PosteriorsMatrixSumWithoutAFzero(), refResult.getLog10PosteriorsMatrixSumWithoutAFzero(), TOLERANCE);
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Assert.assertEquals(result.getNormalizedPosteriorOfAFGTZero(), refResult.getNormalizedPosteriorOfAFGTZero(), 0.5);
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Assert.assertEquals(result.getNormalizedPosteriorOfAFzero(), refResult.getNormalizedPosteriorOfAFzero(), 0.5);
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}
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@ -0,0 +1,56 @@
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package org.broadinstitute.sting.gatk.walkers.genotyper.afcalc;
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import org.broadinstitute.sting.BaseTest;
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import org.broadinstitute.sting.utils.Utils;
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import org.broadinstitute.sting.utils.variantcontext.Allele;
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import org.broadinstitute.sting.utils.variantcontext.Genotype;
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import org.testng.Assert;
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import org.testng.annotations.DataProvider;
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import org.testng.annotations.Test;
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import java.util.ArrayList;
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import java.util.Arrays;
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import java.util.List;
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public class IndependentAllelesDiploidExactAFCalcUnitTest extends BaseTest {
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@DataProvider(name = "TestCombineGLs")
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public Object[][] makeTestCombineGLs() {
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List<Object[]> tests = new ArrayList<Object[]>();
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tests.add(new Object[]{1, 1, makePL( 0, 10, 20), makePL( 0, 10, 20)});
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tests.add(new Object[]{1, 1, makePL(10, 0, 20), makePL(10, 0, 20)});
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tests.add(new Object[]{1, 1, makePL(20, 10, 0), makePL(20, 10, 0)});
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// AA AB BB AC BC CC => AA AB+BC CC
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tests.add(new Object[]{1, 2, makePL( 0, 10, 20, 30, 40, 50), makePL(0, 10, 20)});
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tests.add(new Object[]{2, 2, makePL( 0, 10, 20, 30, 40, 50), makePL(0, 30, 50)});
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tests.add(new Object[]{1, 2, makePL( 0, 10, 10, 10, 10, 10), makePL(0, 7, 10)});
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tests.add(new Object[]{2, 2, makePL( 0, 10, 10, 10, 10, 10), makePL(0, 7, 10)});
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tests.add(new Object[]{1, 2, makePL( 0, 1, 2, 3, 4, 5), makePL(1, 0, 3)});
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tests.add(new Object[]{2, 2, makePL( 0, 1, 2, 3, 4, 5), makePL(0, 0, 5)});
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tests.add(new Object[]{1, 2, makePL( 50, 50, 50, 50, 0, 50), makePL(50, 0, 50)});
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tests.add(new Object[]{2, 2, makePL( 50, 50, 50, 50, 0, 50), makePL(50, 0, 50)});
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tests.add(new Object[]{1, 2, makePL( 50, 50, 50, 0, 50, 50), makePL( 3, 0, 3)});
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tests.add(new Object[]{2, 2, makePL( 50, 50, 50, 0, 50, 50), makePL(50, 0, 50)});
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return tests.toArray(new Object[][]{});
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}
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private Genotype makePL(final int ... PLs) {
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return ExactAFCalculationModelUnitTest.makePL(Arrays.asList(Allele.NO_CALL, Allele.NO_CALL), PLs);
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}
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@Test(enabled = true, dataProvider = "TestCombineGLs")
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private void testCombineGLs(final int altIndex, final int nAlts, final Genotype testg, final Genotype expected) {
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final IndependentAllelesDiploidExactAFCalc calc = new IndependentAllelesDiploidExactAFCalc(1, 4);
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final Genotype combined = calc.combineGLs(testg, altIndex, nAlts);
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Assert.assertEquals(combined.getPL(), expected.getPL(),
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"Combined PLs " + Utils.join(",", combined.getPL()) + " != expected " + Utils.join(",", expected.getPL()));
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}
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}
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@ -43,8 +43,8 @@ import java.util.List;
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*/
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public class AFCalcResult {
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// These variables are intended to contain the MLE and MAP (and their corresponding allele counts) of the site over all alternate alleles
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private double log10MLE;
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private double log10MAP;
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protected double log10MLE;
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protected double log10MAP;
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private final int[] alleleCountsOfMLE;
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private final int[] alleleCountsOfMAP;
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@ -52,7 +52,7 @@ public class AFCalcResult {
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private static final int POSTERIORS_CACHE_SIZE = 5000;
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private final double[] log10PosteriorMatrixValues = new double[POSTERIORS_CACHE_SIZE];
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private int currentPosteriorsCacheIndex = 0;
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private Double log10PosteriorMatrixSum = null;
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protected Double log10PosteriorMatrixSum = null;
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// These variables are intended to contain the likelihood/posterior probability for the site's being monomorphic (i.e. AF=0 for all alternate alleles)
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private double log10LikelihoodOfAFzero;
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@ -235,6 +235,7 @@ public class AFCalcResult {
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currentPosteriorsCacheIndex = 0;
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log10PosteriorMatrixSum = null;
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allelesUsedInGenotyping = null;
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nEvaluations = 0;
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}
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/**
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@ -0,0 +1,174 @@
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/*
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* Copyright (c) 2010.
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*
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* Permission is hereby granted, free of charge, to any person
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* obtaining a copy of this software and associated documentation
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* files (the "Software"), to deal in the Software without
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* restriction, including without limitation the rights to use,
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* copy, modify, merge, publish, distribute, sublicense, and/or sell
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* copies of the Software, and to permit persons to whom the
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* Software is furnished to do so, subject to the following
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* conditions:
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*
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* The above copyright notice and this permission notice shall be
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* included in all copies or substantial portions of the Software.
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*
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* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
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* EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
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* OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
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* NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
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* HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
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* WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
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* FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR
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* THE USE OR OTHER DEALINGS IN THE SOFTWARE.
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*/
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package org.broadinstitute.sting.gatk.walkers.genotyper.afcalc;
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import com.google.java.contract.Ensures;
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import com.google.java.contract.Requires;
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import org.apache.log4j.Logger;
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import org.broadinstitute.sting.gatk.walkers.genotyper.UnifiedArgumentCollection;
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import org.broadinstitute.sting.utils.MathUtils;
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import org.broadinstitute.sting.utils.variantcontext.*;
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import java.io.PrintStream;
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import java.util.ArrayList;
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import java.util.Arrays;
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import java.util.List;
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public class IndependentAllelesDiploidExactAFCalc extends DiploidExactAFCalc {
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private final static List<Allele> BIALLELIC_NOCALL = Arrays.asList(Allele.NO_CALL, Allele.NO_CALL);
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final ReferenceDiploidExactAFCalc refModel;
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public IndependentAllelesDiploidExactAFCalc(final int nSamples, final int maxAltAlleles) {
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super(nSamples, maxAltAlleles);
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refModel = new ReferenceDiploidExactAFCalc(nSamples, 1);
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}
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public IndependentAllelesDiploidExactAFCalc(UnifiedArgumentCollection UAC, int N, Logger logger, PrintStream verboseWriter) {
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super(UAC, N, logger, verboseWriter);
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refModel = new ReferenceDiploidExactAFCalc(nSamples, 1);
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}
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@Override
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protected StateTracker makeMaxLikelihood(VariantContext vc, AFCalcResult result) {
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return refModel.makeMaxLikelihood(vc, result);
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}
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@Override
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public void computeLog10PNonRef(final VariantContext vc,
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final double[] log10AlleleFrequencyPriors,
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final AFCalcResult result) {
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final List<AFCalcResult> independentResults = computeLog10PNonRefForEachAllele(vc, log10AlleleFrequencyPriors);
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combineIndependentPNonRefs(vc, independentResults, log10AlleleFrequencyPriors, result);
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}
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protected List<AFCalcResult> computeLog10PNonRefForEachAllele(final VariantContext vc,
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final double[] log10AlleleFrequencyPriors) {
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final int nAltAlleles = vc.getNAlleles() - 1;
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final List<AFCalcResult> results = new ArrayList<AFCalcResult>(nAltAlleles);
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for ( int altI = 0; altI < nAltAlleles; altI++ ) {
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final List<Allele> biallelic = Arrays.asList(vc.getReference(), vc.getAlternateAllele(altI));
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final VariantContext subvc = biallelicCombinedGLs(vc, biallelic, altI + 1);
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final AFCalcResult result = refModel.getLog10PNonRef(subvc, log10AlleleFrequencyPriors);
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results.add(result);
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}
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return results;
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}
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protected VariantContext biallelicCombinedGLs(final VariantContext rootVC, final List<Allele> biallelic, final int allele2) {
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if ( rootVC.isBiallelic() )
|
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return rootVC;
|
||||
else {
|
||||
final int nAlts = rootVC.getNAlleles() - 1;
|
||||
final List<Genotype> biallelicGenotypes = new ArrayList<Genotype>(rootVC.getNSamples());
|
||||
for ( final Genotype g : rootVC.getGenotypes() )
|
||||
biallelicGenotypes.add(combineGLs(g, allele2, nAlts));
|
||||
|
||||
final VariantContextBuilder vcb = new VariantContextBuilder(rootVC);
|
||||
vcb.alleles(biallelic);
|
||||
vcb.genotypes(biallelicGenotypes);
|
||||
return vcb.make();
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Returns a new Genotype with the PLs of the multi-allelic original reduced to a bi-allelic case
|
||||
*
|
||||
* This is handled in the following way:
|
||||
*
|
||||
* AA AB BB AC BC CC => AA AB+BC CC when altIndex == 1 and nAlts == 2
|
||||
*
|
||||
* @param original the original multi-allelic genotype
|
||||
* @param altIndex the index of the alt allele we wish to keep in the bialleic case -- with ref == 0
|
||||
* @param nAlts the total number of alt alleles
|
||||
* @return a new biallelic genotype with appropriate PLs
|
||||
*/
|
||||
@Requires("original.hasLikelihoods()")
|
||||
@Ensures({"result.hasLikelihoods()", "result.getPL().length == 3"})
|
||||
protected Genotype combineGLs(final Genotype original, final int altIndex, final int nAlts ) {
|
||||
if ( altIndex < 1 || altIndex > nAlts ) throw new IllegalStateException("altIndex must be between 1 and nAlts " + nAlts);
|
||||
|
||||
final double[] normalizedPr = MathUtils.normalizeFromLog10(GenotypeLikelihoods.fromPLs(original.getPL()).getAsVector());
|
||||
final double[] biAllelicPr = new double[3];
|
||||
biAllelicPr[0] = normalizedPr[GenotypeLikelihoods.calculatePLindex(0, 0)];
|
||||
|
||||
for ( int allele1 = 0; allele1 < nAlts+1; allele1++ ) {
|
||||
if ( allele1 != altIndex ) {
|
||||
final int i = Math.min(altIndex, allele1);
|
||||
final int j = Math.max(altIndex, allele1);
|
||||
biAllelicPr[1] += normalizedPr[GenotypeLikelihoods.calculatePLindex(i, j)];
|
||||
}
|
||||
}
|
||||
|
||||
biAllelicPr[2] = normalizedPr[GenotypeLikelihoods.calculatePLindex(altIndex, altIndex)];
|
||||
|
||||
final double[] GLs = new double[3];
|
||||
for ( int i = 0; i < GLs.length; i++ ) GLs[i] = Math.log10(biAllelicPr[i]);
|
||||
|
||||
return new GenotypeBuilder(original).PL(GLs).alleles(BIALLELIC_NOCALL).make();
|
||||
}
|
||||
|
||||
/**
|
||||
* Take the independent estimates of pNonRef for each alt allele and combine them into a single result
|
||||
*
|
||||
* Takes each independent result and merges it into the final result object
|
||||
*
|
||||
* @param independentPNonRefs the pNonRef result for each allele independently
|
||||
* @param result the destination for the combined result
|
||||
*/
|
||||
protected void combineIndependentPNonRefs(final VariantContext vc,
|
||||
final List<AFCalcResult> independentPNonRefs,
|
||||
final double[] log10AlleleFrequencyPriors,
|
||||
final AFCalcResult result) {
|
||||
final int nChrom = vc.getNSamples() * 2;
|
||||
|
||||
result.reset();
|
||||
|
||||
// both the likelihood and the posterior of AF=0 are the same for all alleles
|
||||
// TODO -- check and ensure this is true
|
||||
result.setLog10LikelihoodOfAFzero(independentPNonRefs.get(0).getLog10LikelihoodOfAFzero());
|
||||
result.setLog10PosteriorOfAFzero(independentPNonRefs.get(0).getLog10PosteriorOfAFzero());
|
||||
result.log10PosteriorMatrixSum = 0.0;
|
||||
|
||||
int altI = 0;
|
||||
for ( final AFCalcResult independentPNonRef : independentPNonRefs ) {
|
||||
result.log10MLE += independentPNonRef.getLog10MLE();
|
||||
|
||||
// TODO -- technically double counting some posterior mass
|
||||
result.log10MAP += independentPNonRef.getLog10MAP();
|
||||
|
||||
// TODO -- technically double counting some posterior mass
|
||||
result.log10PosteriorMatrixSum += independentPNonRef.getLog10PosteriorsMatrixSumWithoutAFzero();
|
||||
|
||||
result.getAlleleCountsOfMAP()[altI] = independentPNonRef.getAlleleCountsOfMAP()[0];
|
||||
result.getAlleleCountsOfMLE()[altI] = independentPNonRef.getAlleleCountsOfMLE()[0];
|
||||
|
||||
result.nEvaluations += independentPNonRef.nEvaluations;
|
||||
altI++;
|
||||
}
|
||||
}
|
||||
}
|
||||
Loading…
Reference in New Issue