use of dr.inference.trace.TraceCorrelation in project beast-mcmc by beast-dev.
the class RLYModelTest method randomLocalYuleTester.
private void randomLocalYuleTester(TreeModel treeModel, Parameter I, Parameter b, OperatorSchedule schedule) {
MCMC mcmc = new MCMC("mcmc1");
MCMCOptions options = new MCMCOptions(1000000);
TreeLengthStatistic tls = new TreeLengthStatistic(TL, treeModel);
TreeHeightStatistic rootHeight = new TreeHeightStatistic(TREE_HEIGHT, treeModel);
Parameter m = new Parameter.Default("m", 1.0, 0.0, Double.MAX_VALUE);
SpeciationModel speciationModel = new RandomLocalYuleModel(b, I, m, false, Units.Type.YEARS, 4);
Likelihood likelihood = new SpeciationLikelihood(treeModel, speciationModel, "randomYule.like");
ArrayLogFormatter formatter = new ArrayLogFormatter(false);
MCLogger[] loggers = new MCLogger[2];
loggers[0] = new MCLogger(formatter, 100, false);
loggers[0].add(likelihood);
loggers[0].add(rootHeight);
loggers[0].add(tls);
loggers[0].add(I);
loggers[1] = new MCLogger(new TabDelimitedFormatter(System.out), 100000, false);
loggers[1].add(likelihood);
loggers[1].add(rootHeight);
loggers[1].add(tls);
loggers[1].add(I);
mcmc.setShowOperatorAnalysis(true);
mcmc.init(options, likelihood, schedule, loggers);
mcmc.run();
List<Trace> traces = formatter.getTraces();
ArrayTraceList traceList = new ArrayTraceList("yuleModelTest", traces, 0);
for (int i = 1; i < traces.size(); i++) {
traceList.analyseTrace(i);
}
TraceCorrelation tlStats = traceList.getCorrelationStatistics(traceList.getTraceIndex("root." + birthRateIndicator));
System.out.println("mean = " + tlStats.getMean());
System.out.println("expected mean = 0.5");
assertExpectation("root." + birthRateIndicator, tlStats, 0.5);
}
use of dr.inference.trace.TraceCorrelation in project beast-mcmc by beast-dev.
the class YuleModelTest method yuleTester.
// public void testYuleWithWideExchange() {
//
// TreeModel treeModel = new TreeModel("treeModel", tree);
// Doesn't compile...
// yuleTester(treeModel, ExchangeOperatorTest.getWideExchangeSchedule(treeModel));
// }
private void yuleTester(TreeModel treeModel, OperatorSchedule schedule) {
MCMC mcmc = new MCMC("mcmc1");
MCMCOptions options = new MCMCOptions(1000000);
TreeLengthStatistic tls = new TreeLengthStatistic(TL, treeModel);
TreeHeightStatistic rootHeight = new TreeHeightStatistic(TREE_HEIGHT, treeModel);
Parameter b = new Parameter.Default("b", 2.0, 0.0, Double.MAX_VALUE);
Parameter d = new Parameter.Default("d", 0.0, 0.0, Double.MAX_VALUE);
SpeciationModel speciationModel = new BirthDeathGernhard08Model(b, d, null, BirthDeathGernhard08Model.TreeType.TIMESONLY, Units.Type.YEARS);
Likelihood likelihood = new SpeciationLikelihood(treeModel, speciationModel, "yule.like");
ArrayLogFormatter formatter = new ArrayLogFormatter(false);
MCLogger[] loggers = new MCLogger[2];
loggers[0] = new MCLogger(formatter, 100, false);
loggers[0].add(likelihood);
loggers[0].add(rootHeight);
loggers[0].add(tls);
loggers[1] = new MCLogger(new TabDelimitedFormatter(System.out), 100000, false);
loggers[1].add(likelihood);
loggers[1].add(rootHeight);
loggers[1].add(tls);
mcmc.setShowOperatorAnalysis(true);
mcmc.init(options, likelihood, schedule, loggers);
mcmc.run();
List<Trace> traces = formatter.getTraces();
ArrayTraceList traceList = new ArrayTraceList("yuleModelTest", traces, 0);
for (int i = 1; i < traces.size(); i++) {
traceList.analyseTrace(i);
}
// expectation of root height for 4 tips and lambda = 2
// rootHeight = 0.541666
// TL = 1.5
TraceCorrelation tlStats = traceList.getCorrelationStatistics(traceList.getTraceIndex(TL));
assertExpectation(TL, tlStats, 1.5);
TraceCorrelation treeHeightStats = traceList.getCorrelationStatistics(traceList.getTraceIndex(TREE_HEIGHT));
assertExpectation(TREE_HEIGHT, treeHeightStats, 0.5416666);
}
use of dr.inference.trace.TraceCorrelation in project beast-mcmc by beast-dev.
the class StrictClockTest method testStrictClock.
public void testStrictClock() throws Exception {
Parameter popSize = new Parameter.Default(ConstantPopulationModelParser.POPULATION_SIZE, 380.0, 0, 38000.0);
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, 2.3E-5, 0, 100.0);
StrictClockBranchRates branchRateModel = new StrictClockBranchRates(rateParameter);
// Sub model
Parameter freqs = new Parameter.Default(alignment.getStateFrequencies());
Parameter kappa = new Parameter.Default(HKYParser.KAPPA, 1.0, 0, 100.0);
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, branchRateModel, null, 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);
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, 1.0, 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);
// CompoundLikelihood
List<Likelihood> likelihoods = new ArrayList<Likelihood>();
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, 500, false);
loggers[0].add(posterior);
loggers[0].add(treeLikelihood);
loggers[0].add(rootHeight);
loggers[0].add(rateParameter);
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);
loggers[1].add(coalescent);
// 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("RandomLocalClockTest", traces, 0);
for (int i = 1; i < traces.size(); i++) {
traceList.analyseTrace(i);
}
// <expectation name="posterior" value="-3928.71"/>
// <expectation name="clock.rate" value="8.04835E-4"/>
// <expectation name="constant.popSize" value="37.3762"/>
// <expectation name="hky.kappa" value="18.2782"/>
// <expectation name="treeModel.rootHeight" value="69.0580"/>
// <expectation name="treeLikelihood" value="-3856.59"/>
// <expectation name="coalescent" value="-72.1285"/>
TraceCorrelation likelihoodStats = traceList.getCorrelationStatistics(traceList.getTraceIndex(CompoundLikelihoodParser.POSTERIOR));
assertExpectation(CompoundLikelihoodParser.POSTERIOR, likelihoodStats, -3928.71);
likelihoodStats = traceList.getCorrelationStatistics(traceList.getTraceIndex(TreeLikelihoodParser.TREE_LIKELIHOOD));
assertExpectation(TreeLikelihoodParser.TREE_LIKELIHOOD, likelihoodStats, -3856.59);
TraceCorrelation treeHeightStats = traceList.getCorrelationStatistics(traceList.getTraceIndex(TREE_HEIGHT));
assertExpectation(TREE_HEIGHT, treeHeightStats, 69.0580);
TraceCorrelation kappaStats = traceList.getCorrelationStatistics(traceList.getTraceIndex(HKYParser.KAPPA));
assertExpectation(HKYParser.KAPPA, kappaStats, 18.2782);
TraceCorrelation rateStats = traceList.getCorrelationStatistics(traceList.getTraceIndex(StrictClockBranchRates.RATE));
assertExpectation(StrictClockBranchRates.RATE, rateStats, 8.04835E-4);
TraceCorrelation popStats = traceList.getCorrelationStatistics(traceList.getTraceIndex(ConstantPopulationModelParser.POPULATION_SIZE));
assertExpectation(ConstantPopulationModelParser.POPULATION_SIZE, popStats, 37.3762);
TraceCorrelation coalescentStats = traceList.getCorrelationStatistics(traceList.getTraceIndex("coalescent"));
assertExpectation("coalescent", coalescentStats, -72.1285);
}
use of dr.inference.trace.TraceCorrelation in project beast-mcmc by beast-dev.
the class GeneralSubstitutionModelTest method testGeneralSubstitutionModel.
public void testGeneralSubstitutionModel() {
// Sub model
FrequencyModel freqModel = new FrequencyModel(dataType, alignment.getStateFrequencies());
// dimension="5" value="1.0"
Parameter ratesPara = new Parameter.Default(GeneralSubstitutionModelParser.RATES, 5, 1.0);
// relativeTo="5"
GeneralSubstitutionModel generalSubstitutionModel = new GeneralSubstitutionModel(dataType, freqModel, ratesPara, 4);
// siteModel
GammaSiteModel siteModel = new GammaSiteModel(generalSubstitutionModel);
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(ratesPara, 0.5);
operator.setWeight(1.0);
schedule.addOperator(operator);
Parameter rootHeight = ((DefaultTreeModel) treeModel).getRootHeightParameter();
rootHeight.setId(TREE_HEIGHT);
operator = new ScaleOperator(rootHeight, 0.5);
operator.setWeight(1.0);
schedule.addOperator(operator);
Parameter internalHeights = ((DefaultTreeModel) treeModel).createNodeHeightsParameter(false, true, false);
operator = new UniformOperator(internalHeights, 10.0);
schedule.addOperator(operator);
operator = new SubtreeSlideOperator(((DefaultTreeModel) treeModel), 1, 1, true, false, false, false, AdaptationMode.ADAPTATION_ON, AdaptableMCMCOperator.DEFAULT_ADAPTATION_TARGET);
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(ratesPara);
loggers[1] = new MCLogger(new TabDelimitedFormatter(System.out), 100000, false);
loggers[1].add(treeLikelihood);
loggers[1].add(rootHeight);
loggers[1].add(ratesPara);
// 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("GeneralSubstitutionModelTest", 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="rateAC" value="6.08986E-2"/>
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, 0.0640787258170083);
TraceCorrelation rateACStats = traceList.getCorrelationStatistics(traceList.getTraceIndex(GeneralSubstitutionModelParser.RATES + "1"));
assertExpectation(GeneralSubstitutionModelParser.RATES + "1", rateACStats, 0.061071756742081366);
}
use of dr.inference.trace.TraceCorrelation in project beast-mcmc by beast-dev.
the class LognormalPriorTest method testLognormalPrior.
public void testLognormalPrior() {
// ConstantPopulation constant = new ConstantPopulation(Units.Type.YEARS);
// constant.setN0(popSize); // popSize
Parameter popSize = new Parameter.Default(6.0);
popSize.setId(ConstantPopulationModelParser.POPULATION_SIZE);
ConstantPopulationModel demo = new ConstantPopulationModel(popSize, Units.Type.YEARS);
// Likelihood
Likelihood dummyLikelihood = new DummyLikelihood(demo);
// Operators
OperatorSchedule schedule = new SimpleOperatorSchedule();
MCMCOperator operator = new ScaleOperator(popSize, 0.75);
operator.setWeight(1.0);
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(popSize);
loggers[1] = new MCLogger(new TabDelimitedFormatter(System.out), 100000, false);
// loggers[1].add(treeLikelihood);
loggers[1].add(popSize);
// MCMC
MCMC mcmc = new MCMC("mcmc1");
MCMCOptions options = new MCMCOptions(1000000);
// meanInRealSpace="false"
DistributionLikelihood logNormalLikelihood = new DistributionLikelihood(new LogNormalDistribution(1.0, 1.0), 0);
logNormalLikelihood.addData(popSize);
List<Likelihood> likelihoods = new ArrayList<Likelihood>();
likelihoods.add(logNormalLikelihood);
Likelihood prior = new CompoundLikelihood(0, likelihoods);
likelihoods.clear();
likelihoods.add(dummyLikelihood);
Likelihood likelihood = new CompoundLikelihood(-1, likelihoods);
likelihoods.clear();
likelihoods.add(prior);
likelihoods.add(likelihood);
Likelihood posterior = new CompoundLikelihood(0, likelihoods);
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("LognormalPriorTest", traces, 0);
for (int i = 1; i < traces.size(); i++) {
traceList.analyseTrace(i);
}
// <expectation name="param" value="4.48168907"/>
TraceCorrelation popSizeStats = traceList.getCorrelationStatistics(traceList.getTraceIndex(ConstantPopulationModelParser.POPULATION_SIZE));
System.out.println("Expectation of Log-Normal(1,1) is e^(M+S^2/2) = e^(1.5) = " + Math.exp(1.5));
assertExpectation(ConstantPopulationModelParser.POPULATION_SIZE, popSizeStats, Math.exp(1.5));
}
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