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Example 16 with GammaSiteModel

use of dr.oldevomodel.sitemodel.GammaSiteModel in project beast-mcmc by beast-dev.

the class GammaSiteModelParser method parseXMLObject.

public Object parseXMLObject(XMLObject xo) throws XMLParseException {
    SubstitutionModel substitutionModel = (SubstitutionModel) xo.getElementFirstChild(SUBSTITUTION_MODEL);
    String msg = "";
    Parameter muParam = null;
    if (xo.hasChildNamed(SUBSTITUTION_RATE)) {
        muParam = (Parameter) xo.getElementFirstChild(SUBSTITUTION_RATE);
        msg += "\n  with initial substitution rate = " + muParam.getParameterValue(0);
    } else if (xo.hasChildNamed(MUTATION_RATE)) {
        muParam = (Parameter) xo.getElementFirstChild(MUTATION_RATE);
        msg += "\n  with initial substitution rate = " + muParam.getParameterValue(0);
    } else if (xo.hasChildNamed(RELATIVE_RATE)) {
        muParam = (Parameter) xo.getElementFirstChild(RELATIVE_RATE);
        msg += "\n  with initial relative rate = " + muParam.getParameterValue(0);
    }
    Parameter shapeParam = null;
    int catCount = 4;
    if (xo.hasChildNamed(GAMMA_SHAPE)) {
        final XMLObject cxo = xo.getChild(GAMMA_SHAPE);
        catCount = cxo.getIntegerAttribute(GAMMA_CATEGORIES);
        shapeParam = (Parameter) cxo.getChild(Parameter.class);
        msg += "\n  " + catCount + " category discrete gamma with initial shape = " + shapeParam.getParameterValue(0);
    }
    Parameter invarParam = null;
    if (xo.hasChildNamed(PROPORTION_INVARIANT)) {
        invarParam = (Parameter) xo.getElementFirstChild(PROPORTION_INVARIANT);
        msg += "\n  initial proportion of invariant sites = " + invarParam.getParameterValue(0);
    }
    Logger.getLogger("dr.evomodel").info("Creating site model." + (msg.length() > 0 ? msg : ""));
    return new GammaSiteModel(substitutionModel, muParam, shapeParam, catCount, invarParam);
}
Also used : GammaSiteModel(dr.oldevomodel.sitemodel.GammaSiteModel) Parameter(dr.inference.model.Parameter) SubstitutionModel(dr.oldevomodel.substmodel.SubstitutionModel)

Example 17 with GammaSiteModel

use of dr.oldevomodel.sitemodel.GammaSiteModel in project beast-mcmc by beast-dev.

the class MsatFullLikelihoodTest method setUpExample3.

private void setUpExample3() throws Exception {
    //taxa
    ArrayList<Taxon> taxonList3 = new ArrayList<Taxon>();
    Collections.addAll(taxonList3, new Taxon("taxon1"), new Taxon("taxon2"), new Taxon("taxon3"), new Taxon("taxon4"), new Taxon("taxon5"), new Taxon("taxon6"), new Taxon("taxon7"));
    Taxa taxa3 = new Taxa(taxonList3);
    //msat datatype
    Microsatellite msat = new Microsatellite(1, 4);
    Patterns msatPatterns = new Patterns(msat, taxa3);
    //pattern in the correct code form.
    msatPatterns.addPattern(new int[] { 0, 3, 1, 2, 3, 0, 1 });
    //create tree
    NewickImporter importer = new NewickImporter("(((taxon1:0.3,taxon2:0.3):0.6,taxon3:0.9):0.9,((taxon4:0.5,taxon5:0.5):0.3,(taxon6:0.7,taxon7:0.7):0.1):1.0);");
    Tree tree = importer.importTree(null);
    //treeModel
    TreeModel treeModel = new TreeModel(tree);
    //msatsubstModel
    AsymmetricQuadraticModel aqm3 = new AsymmetricQuadraticModel(msat, null);
    //siteModel
    GammaSiteModel siteModel = new GammaSiteModel(aqm3);
    //treeLikelihood
    treeLikelihood3 = new TreeLikelihood(msatPatterns, treeModel, siteModel, null, null, false, false, true, false, false);
}
Also used : Taxa(dr.evolution.util.Taxa) Microsatellite(dr.evolution.datatype.Microsatellite) TreeModel(dr.evomodel.tree.TreeModel) GammaSiteModel(dr.oldevomodel.sitemodel.GammaSiteModel) Taxon(dr.evolution.util.Taxon) NewickImporter(dr.evolution.io.NewickImporter) ArrayList(java.util.ArrayList) AsymmetricQuadraticModel(dr.oldevomodel.substmodel.AsymmetricQuadraticModel) TreeLikelihood(dr.oldevomodel.treelikelihood.TreeLikelihood) Tree(dr.evolution.tree.Tree) Patterns(dr.evolution.alignment.Patterns)

Example 18 with GammaSiteModel

use of dr.oldevomodel.sitemodel.GammaSiteModel in project beast-mcmc by beast-dev.

the class SequenceLikelihoodTest method computeSitePatternLikelihoods.

protected double[] computeSitePatternLikelihoods(SitePatterns patterns) {
    // Sub model
    Parameter freqs = new Parameter.Default(alignment.getStateFrequencies());
    Parameter kappa = new Parameter.Default(HKYParser.KAPPA, 29.739445, 0, 100);
    FrequencyModel f = new FrequencyModel(Nucleotides.INSTANCE, freqs);
    HKY hky = new HKY(kappa, f);
    //siteModel
    GammaSiteModel siteModel = new GammaSiteModel(hky);
    Parameter mu = new Parameter.Default(GammaSiteModelParser.MUTATION_RATE, 1.0, 0, Double.POSITIVE_INFINITY);
    siteModel.setMutationRateParameter(mu);
    //treeLikelihood
    TreeLikelihood treeLikelihood = new TreeLikelihood(patterns, treeModel, siteModel, null, null, false, false, true, false, false);
    return treeLikelihood.getPatternLogLikelihoods();
}
Also used : FrequencyModel(dr.oldevomodel.substmodel.FrequencyModel) GammaSiteModel(dr.oldevomodel.sitemodel.GammaSiteModel) HKY(dr.oldevomodel.substmodel.HKY) TreeLikelihood(dr.oldevomodel.treelikelihood.TreeLikelihood) Parameter(dr.inference.model.Parameter)

Example 19 with GammaSiteModel

use of dr.oldevomodel.sitemodel.GammaSiteModel in project beast-mcmc by beast-dev.

the class MCMCTest method testMCMC.

public void testMCMC() {
    // Sub model
    //new double[]{0.25, 0.25, 0.25, 0.25});
    Parameter freqs = new Parameter.Default(alignment.getStateFrequencies());
    Parameter kappa = new Parameter.Default(HKYParser.KAPPA, 1.0, 1.0E-8, Double.POSITIVE_INFINITY);
    FrequencyModel f = new FrequencyModel(Nucleotides.INSTANCE, freqs);
    HKY hky = new HKY(kappa, f);
    //siteModel
    GammaSiteModel siteModel = new GammaSiteModel(hky);
    Parameter mu = new Parameter.Default(GammaSiteModelParser.MUTATION_RATE, 1.0, 0, Double.POSITIVE_INFINITY);
    siteModel.setMutationRateParameter(mu);
    //treeLikelihood
    SitePatterns patterns = new SitePatterns(alignment, null, 0, -1, 1, true);
    TreeLikelihood treeLikelihood = new TreeLikelihood(patterns, treeModel, siteModel, null, null, false, false, true, false, false);
    treeLikelihood.setId(TreeLikelihoodParser.TREE_LIKELIHOOD);
    // Operators
    OperatorSchedule schedule = new SimpleOperatorSchedule();
    MCMCOperator operator = new ScaleOperator(kappa, 0.5);
    operator.setWeight(1.0);
    schedule.addOperator(operator);
    //        Parameter rootParameter = treeModel.createNodeHeightsParameter(true, false, false);
    //        ScaleOperator scaleOperator = new ScaleOperator(rootParameter, 0.75, CoercionMode.COERCION_ON, 1.0);
    Parameter rootHeight = treeModel.getRootHeightParameter();
    rootHeight.setId(TREE_HEIGHT);
    operator = new ScaleOperator(rootHeight, 0.5);
    operator.setWeight(1.0);
    schedule.addOperator(operator);
    Parameter internalHeights = treeModel.createNodeHeightsParameter(false, true, false);
    operator = new UniformOperator(internalHeights, 10.0);
    schedule.addOperator(operator);
    operator = new SubtreeSlideOperator(treeModel, 1, 1, true, false, false, false, CoercionMode.COERCION_ON);
    schedule.addOperator(operator);
    operator = new ExchangeOperator(ExchangeOperator.NARROW, treeModel, 1.0);
    //        operator.doOperation();
    schedule.addOperator(operator);
    operator = new ExchangeOperator(ExchangeOperator.WIDE, treeModel, 1.0);
    //        operator.doOperation();
    schedule.addOperator(operator);
    operator = new WilsonBalding(treeModel, 1.0);
    //        operator.doOperation();
    schedule.addOperator(operator);
    // Log
    ArrayLogFormatter formatter = new ArrayLogFormatter(false);
    MCLogger[] loggers = new MCLogger[2];
    loggers[0] = new MCLogger(formatter, 1000, false);
    loggers[0].add(treeLikelihood);
    loggers[0].add(rootHeight);
    loggers[0].add(kappa);
    loggers[1] = new MCLogger(new TabDelimitedFormatter(System.out), 100000, false);
    loggers[1].add(treeLikelihood);
    loggers[1].add(rootHeight);
    loggers[1].add(kappa);
    // MCMC
    MCMC mcmc = new MCMC("mcmc1");
    MCMCOptions options = new MCMCOptions(10000000);
    mcmc.setShowOperatorAnalysis(true);
    mcmc.init(options, treeLikelihood, schedule, loggers);
    mcmc.run();
    // time
    System.out.println(mcmc.getTimer().toString());
    // Tracer
    List<Trace> traces = formatter.getTraces();
    ArrayTraceList traceList = new ArrayTraceList("MCMCTest", traces, 0);
    for (int i = 1; i < traces.size(); i++) {
        traceList.analyseTrace(i);
    }
    //      <expectation name="likelihood" value="-1815.75"/>
    //		<expectation name="treeModel.rootHeight" value="6.42048E-2"/>
    //		<expectation name="hky.kappa" value="32.8941"/>
    TraceCorrelation likelihoodStats = traceList.getCorrelationStatistics(traceList.getTraceIndex(TreeLikelihoodParser.TREE_LIKELIHOOD));
    assertExpectation(TreeLikelihoodParser.TREE_LIKELIHOOD, likelihoodStats, -1815.75);
    TraceCorrelation treeHeightStats = traceList.getCorrelationStatistics(traceList.getTraceIndex(TREE_HEIGHT));
    assertExpectation(TREE_HEIGHT, treeHeightStats, 6.42048E-2);
    TraceCorrelation kappaStats = traceList.getCorrelationStatistics(traceList.getTraceIndex(HKYParser.KAPPA));
    assertExpectation(HKYParser.KAPPA, kappaStats, 32.8941);
}
Also used : FrequencyModel(dr.oldevomodel.substmodel.FrequencyModel) TreeLikelihood(dr.oldevomodel.treelikelihood.TreeLikelihood) ExchangeOperator(dr.evomodel.operators.ExchangeOperator) MCMC(dr.inference.mcmc.MCMC) SubtreeSlideOperator(dr.evomodel.operators.SubtreeSlideOperator) MCMCOptions(dr.inference.mcmc.MCMCOptions) ArrayLogFormatter(dr.inference.loggers.ArrayLogFormatter) WilsonBalding(dr.evomodel.operators.WilsonBalding) TraceCorrelation(dr.inference.trace.TraceCorrelation) SitePatterns(dr.evolution.alignment.SitePatterns) TabDelimitedFormatter(dr.inference.loggers.TabDelimitedFormatter) Trace(dr.inference.trace.Trace) GammaSiteModel(dr.oldevomodel.sitemodel.GammaSiteModel) ArrayTraceList(dr.inference.trace.ArrayTraceList) HKY(dr.oldevomodel.substmodel.HKY) Parameter(dr.inference.model.Parameter) MCLogger(dr.inference.loggers.MCLogger)

Example 20 with GammaSiteModel

use of dr.oldevomodel.sitemodel.GammaSiteModel in project beast-mcmc by beast-dev.

the class PMDTestProblem method testPMD.

public void testPMD() throws Exception {
    Parameter popSize = new Parameter.Default(ConstantPopulationModelParser.POPULATION_SIZE, 496432.69917113904, 0, Double.POSITIVE_INFINITY);
    ConstantPopulationModel constantModel = createRandomInitialTree(popSize);
    CoalescentLikelihood coalescent = new CoalescentLikelihood(treeModel, null, new ArrayList<TaxonList>(), constantModel);
    coalescent.setId("coalescent");
    // clock model
    Parameter rateParameter = new Parameter.Default(StrictClockBranchRates.RATE, 4.0E-7, 0, 100.0);
    StrictClockBranchRates branchRateModel = new StrictClockBranchRates(rateParameter);
    // Sub model
    Parameter freqs = new Parameter.Default(new double[] { 0.25, 0.25, 0.25, 0.25 });
    Parameter kappa = new Parameter.Default(HKYParser.KAPPA, 1.0, 1.0E-8, Double.POSITIVE_INFINITY);
    FrequencyModel f = new FrequencyModel(Nucleotides.INSTANCE, freqs);
    HKY hky = new HKY(kappa, f);
    //siteModel
    GammaSiteModel siteModel = new GammaSiteModel(hky);
    Parameter mu = new Parameter.Default(GammaSiteModelParser.MUTATION_RATE, 1.0, 0, Double.POSITIVE_INFINITY);
    siteModel.setMutationRateParameter(mu);
    // SequenceErrorModel
    Parameter ageRelatedRateParameter = new Parameter.Default(SequenceErrorModelParser.AGE_RELATED_RATE, 4.0E-7, 0, 100.0);
    TipStatesModel aDNADamageModel = new SequenceErrorModel(null, null, SequenceErrorModel.ErrorType.TRANSITIONS_ONLY, null, ageRelatedRateParameter, null);
    //treeLikelihood
    SitePatterns patterns = new SitePatterns(alignment, null, 0, -1, 1, true);
    TreeLikelihood treeLikelihood = new TreeLikelihood(patterns, treeModel, siteModel, branchRateModel, aDNADamageModel, false, false, true, false, false);
    treeLikelihood.setId(TreeLikelihoodParser.TREE_LIKELIHOOD);
    // Operators
    OperatorSchedule schedule = new SimpleOperatorSchedule();
    MCMCOperator operator = new ScaleOperator(kappa, 0.75);
    operator.setWeight(1.0);
    schedule.addOperator(operator);
    operator = new ScaleOperator(rateParameter, 0.75);
    operator.setWeight(3.0);
    schedule.addOperator(operator);
    Parameter allInternalHeights = treeModel.createNodeHeightsParameter(true, true, false);
    operator = new UpDownOperator(new Scalable[] { new Scalable.Default(rateParameter) }, new Scalable[] { new Scalable.Default(allInternalHeights) }, 0.75, 3.0, CoercionMode.COERCION_ON);
    schedule.addOperator(operator);
    operator = new ScaleOperator(popSize, 0.75);
    operator.setWeight(3.0);
    schedule.addOperator(operator);
    operator = new ScaleOperator(ageRelatedRateParameter, 0.75);
    operator.setWeight(3.0);
    schedule.addOperator(operator);
    Parameter rootHeight = treeModel.getRootHeightParameter();
    rootHeight.setId(TREE_HEIGHT);
    operator = new ScaleOperator(rootHeight, 0.75);
    operator.setWeight(3.0);
    schedule.addOperator(operator);
    Parameter internalHeights = treeModel.createNodeHeightsParameter(false, true, false);
    operator = new UniformOperator(internalHeights, 30.0);
    schedule.addOperator(operator);
    operator = new SubtreeSlideOperator(treeModel, 15.0, 49643.2699171139, true, false, false, false, CoercionMode.COERCION_ON);
    schedule.addOperator(operator);
    operator = new ExchangeOperator(ExchangeOperator.NARROW, treeModel, 15.0);
    //        operator.doOperation();
    schedule.addOperator(operator);
    operator = new ExchangeOperator(ExchangeOperator.WIDE, treeModel, 3.0);
    //        operator.doOperation();
    schedule.addOperator(operator);
    operator = new WilsonBalding(treeModel, 3.0);
    //        operator.doOperation();
    schedule.addOperator(operator);
    // ??? correct?
    operator = new DeltaExchangeOperator(freqs, new int[] { 1, 1, 1, 1 }, 0.01, 1.0, false, CoercionMode.COERCION_ON);
    schedule.addOperator(operator);
    //CompoundLikelihood
    OneOnXPrior likelihood1 = new OneOnXPrior();
    likelihood1.addData(popSize);
    OneOnXPrior likelihood2 = new OneOnXPrior();
    likelihood2.addData(kappa);
    List<Likelihood> likelihoods = new ArrayList<Likelihood>();
    likelihoods.add(likelihood1);
    likelihoods.add(likelihood2);
    likelihoods.add(coalescent);
    Likelihood prior = new CompoundLikelihood(0, likelihoods);
    prior.setId(CompoundLikelihoodParser.PRIOR);
    likelihoods.clear();
    likelihoods.add(treeLikelihood);
    Likelihood likelihood = new CompoundLikelihood(-1, likelihoods);
    likelihoods.clear();
    likelihoods.add(prior);
    likelihoods.add(likelihood);
    Likelihood posterior = new CompoundLikelihood(0, likelihoods);
    posterior.setId(CompoundLikelihoodParser.POSTERIOR);
    // Log
    ArrayLogFormatter formatter = new ArrayLogFormatter(false);
    MCLogger[] loggers = new MCLogger[2];
    loggers[0] = new MCLogger(formatter, 1000, false);
    loggers[0].add(posterior);
    loggers[0].add(treeLikelihood);
    loggers[0].add(rootHeight);
    loggers[0].add(rateParameter);
    loggers[0].add(ageRelatedRateParameter);
    loggers[0].add(popSize);
    loggers[0].add(kappa);
    loggers[0].add(coalescent);
    loggers[1] = new MCLogger(new TabDelimitedFormatter(System.out), 10000, false);
    loggers[1].add(posterior);
    loggers[1].add(treeLikelihood);
    loggers[1].add(rootHeight);
    loggers[1].add(rateParameter);
    // MCMC
    MCMC mcmc = new MCMC("mcmc1");
    MCMCOptions options = new MCMCOptions(1000000);
    mcmc.setShowOperatorAnalysis(true);
    mcmc.init(options, posterior, schedule, loggers);
    mcmc.run();
    // time
    System.out.println(mcmc.getTimer().toString());
    // Tracer
    List<Trace> traces = formatter.getTraces();
    ArrayTraceList traceList = new ArrayTraceList("PMDTest", traces, 0);
    for (int i = 1; i < traces.size(); i++) {
        traceList.analyseTrace(i);
    }
    //        <expectation name="clock.rate" value="1.5E-7"/>
    //        <expectation name="errorModel.ageRate" value="0.7E-7"/>
    //        <expectation name="hky.kappa" value="10"/>
    TraceCorrelation kappaStats = traceList.getCorrelationStatistics(traceList.getTraceIndex(HKYParser.KAPPA));
    assertExpectation(HKYParser.KAPPA, kappaStats, 10);
    TraceCorrelation rateStats = traceList.getCorrelationStatistics(traceList.getTraceIndex(StrictClockBranchRates.RATE));
    assertExpectation(StrictClockBranchRates.RATE, rateStats, 1.5E-7);
    TraceCorrelation ageRateStats = traceList.getCorrelationStatistics(traceList.getTraceIndex(SequenceErrorModelParser.AGE_RELATED_RATE));
    assertExpectation(SequenceErrorModelParser.AGE_RELATED_RATE, ageRateStats, 0.7E-7);
}
Also used : FrequencyModel(dr.oldevomodel.substmodel.FrequencyModel) OneOnXPrior(dr.inference.model.OneOnXPrior) CompoundLikelihood(dr.inference.model.CompoundLikelihood) Likelihood(dr.inference.model.Likelihood) TreeLikelihood(dr.oldevomodel.treelikelihood.TreeLikelihood) CoalescentLikelihood(dr.evomodel.coalescent.CoalescentLikelihood) TreeLikelihood(dr.oldevomodel.treelikelihood.TreeLikelihood) ExchangeOperator(dr.evomodel.operators.ExchangeOperator) ArrayList(java.util.ArrayList) MCMC(dr.inference.mcmc.MCMC) SubtreeSlideOperator(dr.evomodel.operators.SubtreeSlideOperator) SequenceErrorModel(dr.evomodel.tipstatesmodel.SequenceErrorModel) StrictClockBranchRates(dr.evomodel.branchratemodel.StrictClockBranchRates) CoalescentLikelihood(dr.evomodel.coalescent.CoalescentLikelihood) MCMCOptions(dr.inference.mcmc.MCMCOptions) ArrayLogFormatter(dr.inference.loggers.ArrayLogFormatter) WilsonBalding(dr.evomodel.operators.WilsonBalding) TraceCorrelation(dr.inference.trace.TraceCorrelation) SitePatterns(dr.evolution.alignment.SitePatterns) ConstantPopulationModel(dr.evomodel.coalescent.ConstantPopulationModel) TaxonList(dr.evolution.util.TaxonList) CompoundLikelihood(dr.inference.model.CompoundLikelihood) TabDelimitedFormatter(dr.inference.loggers.TabDelimitedFormatter) TipStatesModel(dr.evomodel.tipstatesmodel.TipStatesModel) Trace(dr.inference.trace.Trace) GammaSiteModel(dr.oldevomodel.sitemodel.GammaSiteModel) ArrayTraceList(dr.inference.trace.ArrayTraceList) HKY(dr.oldevomodel.substmodel.HKY) Parameter(dr.inference.model.Parameter) MCLogger(dr.inference.loggers.MCLogger)

Aggregations

GammaSiteModel (dr.oldevomodel.sitemodel.GammaSiteModel)28 Parameter (dr.inference.model.Parameter)21 FrequencyModel (dr.oldevomodel.substmodel.FrequencyModel)20 TreeLikelihood (dr.oldevomodel.treelikelihood.TreeLikelihood)20 SitePatterns (dr.evolution.alignment.SitePatterns)15 HKY (dr.oldevomodel.substmodel.HKY)15 ArrayList (java.util.ArrayList)7 TreeModel (dr.evomodel.tree.TreeModel)6 Tree (dr.evolution.tree.Tree)5 Taxa (dr.evolution.util.Taxa)5 ExchangeOperator (dr.evomodel.operators.ExchangeOperator)5 SubtreeSlideOperator (dr.evomodel.operators.SubtreeSlideOperator)5 WilsonBalding (dr.evomodel.operators.WilsonBalding)5 ArrayLogFormatter (dr.inference.loggers.ArrayLogFormatter)5 MCLogger (dr.inference.loggers.MCLogger)5 TabDelimitedFormatter (dr.inference.loggers.TabDelimitedFormatter)5 MCMC (dr.inference.mcmc.MCMC)5 MCMCOptions (dr.inference.mcmc.MCMCOptions)5 ArrayTraceList (dr.inference.trace.ArrayTraceList)5 Trace (dr.inference.trace.Trace)5