Examples with SequenceErrorModel dr.evomodel.tipstatesmodel.SequenceErrorModel used on opensource projects

Example 1 with SequenceErrorModel

use of dr.evomodel.tipstatesmodel.SequenceErrorModel in project beast-mcmc by beast-dev.

the class SequenceErrorModelParser method parseXMLObject.

public Object parseXMLObject(XMLObject xo) throws XMLParseException {
    SequenceErrorModel.ErrorType errorType = SequenceErrorModel.ErrorType.ALL_SUBSTITUTIONS;
    if (xo.hasAttribute(TYPE)) {
        if (xo.getStringAttribute(TYPE).equalsIgnoreCase("transitions")) {
            errorType = SequenceErrorModel.ErrorType.TRANSITIONS_ONLY;
        } else if (!xo.getStringAttribute(TYPE).equalsIgnoreCase("all")) {
            throw new XMLParseException("unrecognized option for attribute, 'type': " + xo.getStringAttribute(TYPE));
        }
    }
    Parameter baseDamageRateParameter = null;
    if (xo.hasChildNamed(BASE_ERROR_RATE)) {
        baseDamageRateParameter = (Parameter) xo.getElementFirstChild(BASE_ERROR_RATE);
    }
    Parameter ageRelatedRateParameter = null;
    if (xo.hasChildNamed(AGE_RELATED_RATE)) {
        ageRelatedRateParameter = (Parameter) xo.getElementFirstChild(AGE_RELATED_RATE);
    }
    if (baseDamageRateParameter == null && ageRelatedRateParameter == null) {
        throw new XMLParseException("You must specify one or other or both of " + BASE_ERROR_RATE + " and " + AGE_RELATED_RATE + " parameters");
    }
    Parameter indicatorParameter = null;
    if (xo.hasChildNamed(INDICATORS)) {
        indicatorParameter = (Parameter) xo.getElementFirstChild(INDICATORS);
    }
    TaxonList includeTaxa = null;
    TaxonList excludeTaxa = null;
    if (xo.hasChildNamed(INCLUDE)) {
        includeTaxa = (TaxonList) xo.getElementFirstChild(INCLUDE);
    }
    if (xo.hasChildNamed(EXCLUDE)) {
        excludeTaxa = (TaxonList) xo.getElementFirstChild(EXCLUDE);
    }
    SequenceErrorModel aDNADamageModel = new SequenceErrorModel(includeTaxa, excludeTaxa, errorType, baseDamageRateParameter, ageRelatedRateParameter, indicatorParameter);
    Logger.getLogger("dr.evomodel").info("Using sequence error model, assuming errors cause " + (errorType == SequenceErrorModel.ErrorType.TRANSITIONS_ONLY ? "transitions only." : "any substitution."));
    return aDNADamageModel;
}

Example 2 with SequenceErrorModel

use of dr.evomodel.tipstatesmodel.SequenceErrorModel 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);
    TreeIntervals intervalList = new TreeIntervals(treeModel, null, null);
    CoalescentLikelihood coalescent = new CoalescentLikelihood(intervalList, 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 = ((DefaultTreeModel) treeModel).createNodeHeightsParameter(true, true, false);
    operator = new UpDownOperator(new Scalable[] { new Scalable.Default(rateParameter) }, new Scalable[] { new Scalable.Default(allInternalHeights) }, 0.75, 3.0, AdaptationMode.ADAPTATION_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 = ((DefaultTreeModel) treeModel).getRootHeightParameter();
    rootHeight.setId(TREE_HEIGHT);
    operator = new ScaleOperator(rootHeight, 0.75);
    operator.setWeight(3.0);
    schedule.addOperator(operator);
    Parameter internalHeights = ((DefaultTreeModel) treeModel).createNodeHeightsParameter(false, true, false);
    operator = new UniformOperator(internalHeights, 30.0);
    schedule.addOperator(operator);
    operator = new SubtreeSlideOperator(((DefaultTreeModel) treeModel), 15.0, 49643.2699171139, true, false, false, false, AdaptationMode.ADAPTATION_ON, AdaptableMCMCOperator.DEFAULT_ADAPTATION_TARGET);
    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, AdaptationMode.ADAPTATION_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);
}