package test.dr.evomodel.branchratemodel;
import dr.evolution.alignment.SitePatterns;
import dr.evolution.datatype.Nucleotides;
import dr.evolution.util.TaxonList;
import dr.evomodel.branchratemodel.DiscretizedBranchRates;
import dr.evomodel.coalescent.CoalescentLikelihood;
import dr.evomodel.coalescent.ConstantPopulationModel;
import dr.evomodel.operators.ExchangeOperator;
import dr.evomodel.operators.SubtreeSlideOperator;
import dr.evomodel.operators.WilsonBalding;
import dr.evomodel.sitemodel.GammaSiteModel;
import dr.evomodel.substmodel.FrequencyModel;
import dr.evomodel.substmodel.HKY;
import dr.evomodel.tree.RateCovarianceStatistic;
import dr.evomodel.tree.RateStatistic;
import dr.evomodel.treelikelihood.TreeLikelihood;
import dr.evomodelxml.coalescent.ConstantPopulationModelParser;
import dr.evomodelxml.sitemodel.GammaSiteModelParser;
import dr.evomodelxml.substmodel.HKYParser;
import dr.evomodelxml.tree.RateStatisticParser;
import dr.evomodelxml.treelikelihood.TreeLikelihoodParser;
import dr.inference.distribution.ExponentialDistributionModel;
import dr.inference.distribution.LogNormalDistributionModel;
import dr.inference.distribution.ParametricDistributionModel;
import dr.inference.loggers.ArrayLogFormatter;
import dr.inference.loggers.MCLogger;
import dr.inference.loggers.TabDelimitedFormatter;
import dr.inference.mcmc.MCMC;
import dr.inference.mcmc.MCMCOptions;
import dr.inference.model.CompoundLikelihood;
import dr.inference.model.Likelihood;
import dr.inference.model.Parameter;
import dr.inference.operators.*;
import dr.inference.trace.ArrayTraceList;
import dr.inference.trace.Trace;
import dr.inference.trace.TraceCorrelation;
import dr.inferencexml.distribution.DistributionModelParser;
import dr.inferencexml.distribution.LogNormalDistributionModelParser;
import dr.inferencexml.model.CompoundLikelihoodParser;
import dr.math.MathUtils;
import junit.framework.Test;
import junit.framework.TestSuite;
import test.dr.inference.trace.TraceCorrelationAssert;
import java.util.ArrayList;
import java.util.List;
/**
* @author Walter Xie
* convert testUncorrelatedRelaxedClock.xml in the folder /example
*/
public class UncorrelatedRelaxedClockTest extends TraceCorrelationAssert {
private Parameter meanParam;
private Parameter stdevParam;
public UncorrelatedRelaxedClockTest(String name) {
super(name);
}
public void setUp() throws Exception {
super.setUp();
MathUtils.setSeed(666);
createAlignment(DENGUE4_TAXON_SEQUENCE, Nucleotides.INSTANCE);
}
public void testLogNormal() throws Exception {
meanParam = new Parameter.Default(LogNormalDistributionModelParser.MEAN, 2.3E-5, 0, 100.0);
stdevParam = new Parameter.Default(LogNormalDistributionModelParser.STDEV, 0.1, 0, 10.0);
ParametricDistributionModel distributionModel = new LogNormalDistributionModel(meanParam, stdevParam, 0.0, true, false); // meanInRealSpace="true"
ArrayTraceList traceList = UncorrelatedRelaxedClock(distributionModel);
// <expectation name="posterior" value="-3927.81"/>
// <expectation name="ucld.mean" value="8.28472E-4"/>
// <expectation name="ucld.stdev" value="0.17435"/>
// <expectation name="meanRate" value="8.09909E-4"/>
// <expectation name="coefficientOfVariation" value="0.15982"/>
// <expectation name="covariance" value="-3.81803E-2"/>
// <expectation name="constant.popSize" value="37.3524"/>
// <expectation name="hky.kappa" value="18.3053"/>
// <expectation name="treeModel.rootHeight" value="69.2953"/>
// <expectation name="treeLikelihood" value="-3855.78"/>
// <expectation name="skyline" value="-72.0313"/> ???
TraceCorrelation likelihoodStats = traceList.getCorrelationStatistics(traceList.getTraceIndex(CompoundLikelihoodParser.POSTERIOR));
assertExpectation(CompoundLikelihoodParser.POSTERIOR, likelihoodStats, -3927.81);
likelihoodStats = traceList.getCorrelationStatistics(traceList.getTraceIndex(TreeLikelihoodParser.TREE_LIKELIHOOD));
assertExpectation(TreeLikelihoodParser.TREE_LIKELIHOOD, likelihoodStats, -3855.78);
TraceCorrelation treeHeightStats = traceList.getCorrelationStatistics(traceList.getTraceIndex(TREE_HEIGHT));
assertExpectation(TREE_HEIGHT, treeHeightStats, 69.2953);
TraceCorrelation kappaStats = traceList.getCorrelationStatistics(traceList.getTraceIndex(HKYParser.KAPPA));
assertExpectation(HKYParser.KAPPA, kappaStats, 18.06518);
TraceCorrelation ucldStats = traceList.getCorrelationStatistics(traceList.getTraceIndex(LogNormalDistributionModelParser.MEAN));
assertExpectation(LogNormalDistributionModelParser.MEAN, ucldStats, 8.0591451486E-4);
ucldStats = traceList.getCorrelationStatistics(traceList.getTraceIndex(LogNormalDistributionModelParser.STDEV));
assertExpectation(LogNormalDistributionModelParser.STDEV, ucldStats, 0.16846023066431434);
TraceCorrelation rateStats = traceList.getCorrelationStatistics(traceList.getTraceIndex("meanRate"));
assertExpectation("meanRate", rateStats, 8.010906E-4);
TraceCorrelation coefficientOfVariationStats = traceList.getCorrelationStatistics(traceList.getTraceIndex(RateStatisticParser.COEFFICIENT_OF_VARIATION));
assertExpectation(RateStatisticParser.COEFFICIENT_OF_VARIATION, coefficientOfVariationStats, 0.15982);
TraceCorrelation covarianceStats = traceList.getCorrelationStatistics(traceList.getTraceIndex("covariance"));
assertExpectation("covariance", covarianceStats, -0.0260333026);
TraceCorrelation popStats = traceList.getCorrelationStatistics(traceList.getTraceIndex(ConstantPopulationModelParser.POPULATION_SIZE));
assertExpectation(ConstantPopulationModelParser.POPULATION_SIZE, popStats, 37.3524);
TraceCorrelation coalescentStats = traceList.getCorrelationStatistics(traceList.getTraceIndex("coalescent"));
assertExpectation("coalescent", coalescentStats, -72.0313);
}
public void testExponential() throws Exception {
meanParam = new Parameter.Default(1.0);
meanParam.setId(DistributionModelParser.MEAN);
stdevParam = null;
ParametricDistributionModel distributionModel = new ExponentialDistributionModel(meanParam); // offset = 0
ArrayTraceList traceList = UncorrelatedRelaxedClock(distributionModel);
TraceCorrelation likelihoodStats = traceList.getCorrelationStatistics(traceList.getTraceIndex(CompoundLikelihoodParser.POSTERIOR));
assertExpectation(CompoundLikelihoodParser.POSTERIOR, likelihoodStats, -3958.7409);
// System.out.println("likelihoodStats = " + likelihoodStats.getMean());
likelihoodStats = traceList.getCorrelationStatistics(traceList.getTraceIndex(TreeLikelihoodParser.TREE_LIKELIHOOD));
assertExpectation(TreeLikelihoodParser.TREE_LIKELIHOOD, likelihoodStats, -3885.26939);
// System.out.println("treelikelihoodStats = " + likelihoodStats.getMean());
TraceCorrelation treeHeightStats = traceList.getCorrelationStatistics(traceList.getTraceIndex(TREE_HEIGHT));
assertExpectation(TREE_HEIGHT, treeHeightStats, 84.3529526);
TraceCorrelation kappaStats = traceList.getCorrelationStatistics(traceList.getTraceIndex(HKYParser.KAPPA));
assertExpectation(HKYParser.KAPPA, kappaStats, 18.38065);
TraceCorrelation ucedStats = traceList.getCorrelationStatistics(traceList.getTraceIndex(DistributionModelParser.MEAN));
assertExpectation(DistributionModelParser.MEAN, ucedStats, 0.0019344134887784579);
// System.out.println("ucedStats = " + ucedStats.getMean());
TraceCorrelation rateStats = traceList.getCorrelationStatistics(traceList.getTraceIndex("meanRate"));
assertExpectation("meanRate", rateStats, 0.0020538802366337084);
// System.out.println("rateStats = " + rateStats.getMean());
TraceCorrelation coefficientOfVariationStats = traceList.getCorrelationStatistics(traceList.getTraceIndex(RateStatisticParser.COEFFICIENT_OF_VARIATION));
assertExpectation(RateStatisticParser.COEFFICIENT_OF_VARIATION, coefficientOfVariationStats, 0.773609960455);
// System.out.println("coefficientOfVariationStats = " + coefficientOfVariationStats.getMean());
TraceCorrelation covarianceStats = traceList.getCorrelationStatistics(traceList.getTraceIndex("covariance"));
assertExpectation("covariance", covarianceStats, -0.07042030641301375);
// System.out.println("covarianceStats = " + covarianceStats.getMean());
TraceCorrelation popStats = traceList.getCorrelationStatistics(traceList.getTraceIndex(ConstantPopulationModelParser.POPULATION_SIZE));
assertExpectation(ConstantPopulationModelParser.POPULATION_SIZE, popStats, 43.4478);
// System.out.println("popStats = " + popStats.getMean());
TraceCorrelation coalescentStats = traceList.getCorrelationStatistics(traceList.getTraceIndex("coalescent"));
assertExpectation("coalescent", coalescentStats, -73.4715);
// System.out.println("coalescentStats = " + coalescentStats.getMean());
}
private ArrayTraceList UncorrelatedRelaxedClock(ParametricDistributionModel distributionModel) throws Exception {
Parameter popSize = new Parameter.Default(ConstantPopulationModelParser.POPULATION_SIZE, 380.0, 0, 38000.0);
ConstantPopulationModel constantModel = createRandomInitialTree(popSize);
CoalescentLikelihood coalescent = new CoalescentLikelihood(treeModel, null, new ArrayList<TaxonList>(), constantModel);
coalescent.setId("coalescent");
// clock model
Parameter rateCategoryParameter = new Parameter.Default(32);
rateCategoryParameter.setId(DiscretizedBranchRates.BRANCH_RATES);
DiscretizedBranchRates branchRateModel = new DiscretizedBranchRates(treeModel, rateCategoryParameter,
distributionModel, 1, false, Double.NaN);
RateStatistic meanRate = new RateStatistic("meanRate", treeModel, branchRateModel, true, true, RateStatisticParser.MEAN);
RateStatistic coefficientOfVariation = new RateStatistic(RateStatisticParser.COEFFICIENT_OF_VARIATION, treeModel, branchRateModel,
true, true, RateStatisticParser.COEFFICIENT_OF_VARIATION);
RateCovarianceStatistic covariance = new RateCovarianceStatistic("covariance", treeModel, branchRateModel);
// 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(meanParam, 0.75);
operator.setWeight(3.0);
schedule.addOperator(operator);
if (stdevParam != null) {
operator = new ScaleOperator(stdevParam, 0.75);
operator.setWeight(3.0);
schedule.addOperator(operator);
}
Parameter allInternalHeights = treeModel.createNodeHeightsParameter(true, true, false);
// whdc
//operator = new UpDownOperator(new Scalable[]{new Scalable.Default(meanParam)},
//new Scalable[] {new Scalable.Default(allInternalHeights)}, 0.75, 3.0, CoercionMode.COERCION_ON);
operator = new UpDownOperator(new Parameter[]{meanParam},
new Parameter[] {allInternalHeights}, 0.75, 3.0, CoercionMode.COERCION_ON);
schedule.addOperator(operator);
operator = new SwapOperator(rateCategoryParameter, 10);
operator.setWeight(1.0);
schedule.addOperator(operator);
operator = new RandomWalkIntegerOperator(rateCategoryParameter, 1, 10.0);
schedule.addOperator(operator);
operator = new UniformIntegerOperator(rateCategoryParameter, (int) (double)rateCategoryParameter.getBounds().getLowerLimit(0),
(int) (double)rateCategoryParameter.getBounds().getUpperLimit(0), 10.0);
schedule.addOperator(operator);
operator = new ScaleOperator(popSize, 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, 38.0, 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);
//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, 10000, false);
loggers[0].add(posterior);
loggers[0].add(treeLikelihood);
loggers[0].add(rootHeight);
loggers[0].add(meanParam);
if (stdevParam != null) loggers[0].add(stdevParam);
loggers[0].add(meanRate);
loggers[0].add(coefficientOfVariation);
loggers[0].add(covariance);
loggers[0].add(popSize);
loggers[0].add(kappa);
loggers[0].add(coalescent);
loggers[1] = new MCLogger(new TabDelimitedFormatter(System.out), 100000, false);
loggers[1].add(posterior);
loggers[1].add(treeLikelihood);
loggers[1].add(rootHeight);
loggers[1].add(meanRate);
loggers[1].add(coalescent);
// MCMC
MCMC mcmc = new MCMC("mcmc1");
MCMCOptions options = new MCMCOptions();
options.setChainLength(10000000);
options.setUseCoercion(true); // autoOptimize = true
options.setCoercionDelay(100);
options.setTemperature(1.0);
options.setFullEvaluationCount(2000);
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);
}
return traceList;
}
public static Test suite() {
return new TestSuite(UncorrelatedRelaxedClockTest.class);
}
}