Examples with Taxa dr.evolution.util.Taxa used on opensource projects

Example 36 with Taxa

use of dr.evolution.util.Taxa in project beast-mcmc by beast-dev.

the class MsatSamplingTreeLikelihoodTest method setUp.

public void setUp() throws Exception {
    super.setUp();
    // 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, 6);
    Patterns msatPatterns = new Patterns(msat, taxa3);
    // pattern in the correct code form.
    msatPatterns.addPattern(new int[] { 0, 1, 3, 2, 4, 5, 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 DefaultTreeModel(tree);
    // msatsubstModel
    AsymmetricQuadraticModel eu1 = new AsymmetricQuadraticModel(msat, null);
    // create msatSamplerTreeModel
    Parameter internalVal = new Parameter.Default(new double[] { 2, 3, 4, 2, 1, 5 });
    int[] externalValues = msatPatterns.getPattern(0);
    HashMap<String, Integer> taxaMap = new HashMap<String, Integer>(externalValues.length);
    boolean internalValuesProvided = true;
    for (int i = 0; i < externalValues.length; i++) {
        taxaMap.put(msatPatterns.getTaxonId(i), i);
    }
    MicrosatelliteSamplerTreeModel msatTreeModel = new MicrosatelliteSamplerTreeModel("JUnitTestEx", treeModel, internalVal, msatPatterns, externalValues, taxaMap, internalValuesProvided);
    // create msatSamplerTreeLikelihood
    BranchRateModel branchRateModel = new StrictClockBranchRates(new Parameter.Default(1.0));
    eu1Likelihood = new MicrosatelliteSamplerTreeLikelihood(msatTreeModel, eu1, branchRateModel);
    // eu2
    TwoPhaseModel eu2 = new TwoPhaseModel(msat, null, eu1, new Parameter.Default(0.0), new Parameter.Default(0.4), null, false);
    eu2Likelihood = new MicrosatelliteSamplerTreeLikelihood(msatTreeModel, eu2, branchRateModel);
    // ec1
    LinearBiasModel ec1 = new LinearBiasModel(msat, null, eu1, new Parameter.Default(0.48), new Parameter.Default(0.0), false, false, false);
    ec1Likelihood = new MicrosatelliteSamplerTreeLikelihood(msatTreeModel, ec1, branchRateModel);
    // ec2
    TwoPhaseModel ec2 = new TwoPhaseModel(msat, null, ec1, new Parameter.Default(0.0), new Parameter.Default(0.4), null, false);
    ec2Likelihood = new MicrosatelliteSamplerTreeLikelihood(msatTreeModel, ec2, branchRateModel);
    // el1
    LinearBiasModel el1 = new LinearBiasModel(msat, null, eu1, new Parameter.Default(0.2), new Parameter.Default(-0.018), true, false, false);
    el1Likelihood = new MicrosatelliteSamplerTreeLikelihood(msatTreeModel, el1, branchRateModel);
    AsymmetricQuadraticModel pu1 = new AsymmetricQuadraticModel(msat, null, new Parameter.Default(1.0), new Parameter.Default(0.015), new Parameter.Default(0.0), new Parameter.Default(1.0), new Parameter.Default(0.015), new Parameter.Default(0.0), false);
    pu1Likelihood = new MicrosatelliteSamplerTreeLikelihood(msatTreeModel, pu1, branchRateModel);
    // ec2
    TwoPhaseModel pu2 = new TwoPhaseModel(msat, null, pu1, new Parameter.Default(0.0), new Parameter.Default(0.4), null, false);
    pu2Likelihood = new MicrosatelliteSamplerTreeLikelihood(msatTreeModel, pu2, branchRateModel);
    // ec1
    LinearBiasModel pc1 = new LinearBiasModel(msat, null, pu1, new Parameter.Default(0.48), new Parameter.Default(0.0), false, false, false);
    pc1Likelihood = new MicrosatelliteSamplerTreeLikelihood(msatTreeModel, pc1, branchRateModel);
}

Example 37 with Taxa

use of dr.evolution.util.Taxa in project beast-mcmc by beast-dev.

the class MsatFullLikelihoodTest method setUp.

public void setUp() throws Exception {
    super.setUp();
    // taxa
    ArrayList<Taxon> taxonList1 = new ArrayList<Taxon>();
    Collections.addAll(taxonList1, new Taxon("taxon1"), new Taxon("taxon2"), new Taxon("taxon3"));
    Taxa taxa1 = new Taxa(taxonList1);
    // msat datatype
    Microsatellite msat = new Microsatellite(1, 3);
    Patterns msatPatterns = new Patterns(msat, taxa1);
    // pattern in the correct code form.
    msatPatterns.addPattern(new int[] { 0, 1, 2 });
    // create tree
    NewickImporter importer = new NewickImporter("(taxon1:7.5,(taxon2:5.3,taxon3:5.3):2.2);");
    Tree tree = importer.importTree(null);
    // treeModel
    TreeModel treeModel = new DefaultTreeModel(tree);
    // msatsubstModel
    AsymmetricQuadraticModel aqm1 = new AsymmetricQuadraticModel(msat, null);
    // siteModel
    GammaSiteModel siteModel = new GammaSiteModel(aqm1);
    // treeLikelihood
    treeLikelihood1 = new TreeLikelihood(msatPatterns, treeModel, siteModel, null, null, false, false, true, false, false);
    setUpExample2();
    setUpExample3();
}

Example 38 with Taxa

use of dr.evolution.util.Taxa in project beast-mcmc by beast-dev.

the class MsatFullLikelihoodTest method setUpExample2.

private void setUpExample2() throws Exception {
    // taxa
    ArrayList<Taxon> taxonList2 = new ArrayList<Taxon>();
    Collections.addAll(taxonList2, new Taxon("taxon1"), new Taxon("taxon2"), new Taxon("taxon3"), new Taxon("taxon4"), new Taxon("taxon5"));
    Taxa taxa2 = new Taxa(taxonList2);
    // msat datatype
    Microsatellite msat = new Microsatellite(1, 3);
    Patterns msatPatterns = new Patterns(msat, taxa2);
    // pattern in the correct code form.
    msatPatterns.addPattern(new int[] { 0, 1, 2, 1, 2 });
    // create tree
    NewickImporter importer = new NewickImporter("(((taxon1:1.5,taxon2:1.5):1.5,(taxon3:2.1,taxon4:2.1):0.9):0.7,taxon5:3.7);");
    Tree tree = importer.importTree(null);
    // treeModel
    TreeModel treeModel = new DefaultTreeModel(tree);
    // msatsubstModel
    AsymmetricQuadraticModel aqm2 = new AsymmetricQuadraticModel(msat, null);
    // siteModel
    GammaSiteModel siteModel = new GammaSiteModel(aqm2);
    // treeLikelihood
    treeLikelihood2 = new TreeLikelihood(msatPatterns, treeModel, siteModel, null, null, false, false, true, false, false);
}

Example 39 with Taxa

use of dr.evolution.util.Taxa in project beast-mcmc by beast-dev.

the class SpeciesSetPanel method setupTaxonSetsComboBox.

protected void setupTaxonSetsComboBox(JComboBox comboBox, List<Taxon> availableTaxa) {
    comboBox.removeAllItems();
    comboBox.addItem(TAXON.toLowerCase() + "...");
    for (Taxa taxa : options.speciesSets) {
        if (taxa != currentTaxonSet) {
            if (isCompatible(taxa, availableTaxa)) {
                comboBox.addItem(taxa);
            }
        }
    }
}

Example 40 with Taxa

use of dr.evolution.util.Taxa in project beast-mcmc by beast-dev.

the class LogGenerator method writeLogToFile.

/**
     * write log to file
     *
     * @param writer                     XMLWriter
     * @param treePriorGenerator         TreePriorGenerator
     * @param clockModelGenerator  ClockModelGenerator
     * @param substitutionModelGenerator SubstitutionModelGenerator
     * @param treeLikelihoodGenerator    TreeLikelihoodGenerator
     */
public void writeLogToFile(XMLWriter writer, TreePriorGenerator treePriorGenerator, ClockModelGenerator clockModelGenerator, SubstitutionModelGenerator substitutionModelGenerator, TreeLikelihoodGenerator treeLikelihoodGenerator) {
    writer.writeComment("write log to file");
    if (options.logFileName == null) {
        options.logFileName = options.fileNameStem + ".log";
    }
    writer.writeOpenTag(LoggerParser.LOG, new Attribute[] { new Attribute.Default<String>(XMLParser.ID, "fileLog"), new Attribute.Default<String>(LoggerParser.LOG_EVERY, options.logEvery + ""), new Attribute.Default<String>(LoggerParser.FILE_NAME, options.logFileName), new Attribute.Default<Boolean>(LoggerParser.ALLOW_OVERWRITE_LOG, options.allowOverwriteLog) });
    if (options.hasData()) {
        writer.writeIDref(CompoundLikelihoodParser.POSTERIOR, "posterior");
    }
    writer.writeIDref(CompoundLikelihoodParser.PRIOR, "prior");
    if (options.hasData()) {
        writer.writeIDref(CompoundLikelihoodParser.LIKELIHOOD, "likelihood");
    }
    if (options.useStarBEAST) {
        // species
        // coalescent prior
        writer.writeIDref(MultiSpeciesCoalescentParser.SPECIES_COALESCENT, TraitData.TRAIT_SPECIES + "." + COALESCENT);
        // prior on population sizes
        //            if (options.speciesTreePrior == TreePriorType.SPECIES_YULE) {
        writer.writeIDref(MixedDistributionLikelihoodParser.DISTRIBUTION_LIKELIHOOD, SPOPS);
        //            } else {
        //                writer.writeIDref(SpeciesTreeBMPrior.STPRIOR, STP);
        //            }
        // prior on species tree
        writer.writeIDref(SpeciationLikelihoodParser.SPECIATION_LIKELIHOOD, SPECIATION_LIKE);
        writer.writeIDref(ParameterParser.PARAMETER, TraitData.TRAIT_SPECIES + "." + options.starBEASTOptions.POP_MEAN);
        writer.writeIDref(ParameterParser.PARAMETER, SpeciesTreeModelParser.SPECIES_TREE + "." + SPLIT_POPS);
        if (options.getPartitionTreePriors().get(0).getNodeHeightPrior() == TreePriorType.SPECIES_BIRTH_DEATH) {
            writer.writeIDref(ParameterParser.PARAMETER, TraitData.TRAIT_SPECIES + "." + BirthDeathModelParser.MEAN_GROWTH_RATE_PARAM_NAME);
            writer.writeIDref(ParameterParser.PARAMETER, TraitData.TRAIT_SPECIES + "." + BirthDeathModelParser.RELATIVE_DEATH_RATE_PARAM_NAME);
        } else if (options.getPartitionTreePriors().get(0).getNodeHeightPrior() == TreePriorType.SPECIES_YULE || options.getPartitionTreePriors().get(0).getNodeHeightPrior() == TreePriorType.SPECIES_YULE_CALIBRATION) {
            writer.writeIDref(ParameterParser.PARAMETER, TraitData.TRAIT_SPECIES + "." + YuleModelParser.YULE + "." + YuleModelParser.BIRTH_RATE);
        } else {
            throw new IllegalArgumentException("Get wrong species tree prior using *BEAST : " + options.getPartitionTreePriors().get(0).getNodeHeightPrior().toString());
        }
        //Species Tree: tmrcaStatistic
        writer.writeIDref(TMRCAStatisticParser.TMRCA_STATISTIC, SpeciesTreeModelParser.SPECIES_TREE + "." + TreeModelParser.ROOT_HEIGHT);
    }
    for (PartitionTreeModel model : options.getPartitionTreeModels()) {
        writer.writeIDref(ParameterParser.PARAMETER, model.getPrefix() + TreeModel.TREE_MODEL + "." + TreeModelParser.ROOT_HEIGHT);
    }
    // @todo check for redundancy with rootHeight - if no tip dates or given as heights (time before present)
    for (PartitionTreeModel model : options.getPartitionTreeModels()) {
        if (model.hasTipCalibrations()) {
            writer.writeIDref(TMRCAStatisticParser.TMRCA_STATISTIC, model.getPrefix() + TreeModel.TREE_MODEL + ".rootAge");
        }
    }
    if (options.useStarBEAST) {
        for (Taxa taxa : options.speciesSets) {
            // make tmrca(tree.name) eay to read in log for Tracer
            writer.writeIDref(TMRCAStatisticParser.TMRCA_STATISTIC, "tmrca(" + taxa.getId() + ")");
        }
    } else {
        for (Taxa taxa : options.taxonSets) {
            // make tmrca(tree.name) eay to read in log for Tracer
            PartitionTreeModel treeModel = options.taxonSetsTreeModel.get(taxa);
            writer.writeIDref(TMRCAStatisticParser.TMRCA_STATISTIC, "tmrca(" + treeModel.getPrefix() + taxa.getId() + ")");
        }
    }
    for (PartitionTreePrior prior : options.getPartitionTreePriors()) {
        treePriorGenerator.writeParameterLog(prior, writer);
    }
    for (PartitionSubstitutionModel model : options.getPartitionSubstitutionModels()) {
        substitutionModelGenerator.writeLog(model, writer);
    }
    for (PartitionClockModel model : options.getPartitionClockModels()) {
        clockModelGenerator.writeLog(model, writer);
    }
    for (PartitionClockModel model : options.getPartitionClockModels()) {
        clockModelGenerator.writeLogStatistic(model, writer);
    }
    generateInsertionPoint(ComponentGenerator.InsertionPoint.IN_FILE_LOG_PARAMETERS, writer);
    treeLikelihoodGenerator.writeTreeLikelihoodReferences(writer);
    clockModelGenerator.writeClockLikelihoodReferences(writer);
    generateInsertionPoint(ComponentGenerator.InsertionPoint.IN_FILE_LOG_LIKELIHOODS, writer);
    // coalescentLikelihood
    for (PartitionTreeModel model : options.getPartitionTreeModels()) {
        PartitionTreePrior prior = model.getPartitionTreePrior();
        treePriorGenerator.writePriorLikelihoodReferenceLog(prior, model, writer);
        writer.writeText("");
    }
    for (PartitionTreePrior prior : options.getPartitionTreePriors()) {
        if (prior.getNodeHeightPrior() == TreePriorType.EXTENDED_SKYLINE) {
            // only 1 coalescent
            writer.writeIDref(CoalescentLikelihoodParser.COALESCENT_LIKELIHOOD, prior.getPrefix() + COALESCENT);
        } else if (prior.getNodeHeightPrior() == TreePriorType.SKYGRID) {
            writer.writeIDref(GMRFSkyrideLikelihoodParser.SKYGRID_LIKELIHOOD, prior.getPrefix() + "skygrid");
        }
    }
    writer.writeCloseTag(LoggerParser.LOG);
    generateInsertionPoint(ComponentGenerator.InsertionPoint.AFTER_FILE_LOG, writer);
}