Examples with Attribute dr.util.Attribute used on opensource projects

Example 16 with Attribute

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

the class TreePriorGenerator method writePriorLikelihood.

/**
     * Write the prior on node heights (coalescent or speciational models)
     *
     * @param model  PartitionTreeModel
     * @param writer the writer
     */
void writePriorLikelihood(PartitionTreeModel model, XMLWriter writer) {
    //tree model prefix
    // only has prefix, if (options.getPartitionTreePriors().size() > 1)
    setModelPrefix(model.getPrefix());
    //    	String priorPrefix = prior.getPrefix();
    PartitionTreePrior prior = model.getPartitionTreePrior();
    TreePriorType treePrior = prior.getNodeHeightPrior();
    switch(treePrior) {
        case YULE:
        case BIRTH_DEATH:
        case BIRTH_DEATH_INCOMPLETE_SAMPLING:
        case BIRTH_DEATH_SERIAL_SAMPLING:
        case BIRTH_DEATH_BASIC_REPRODUCTIVE_NUMBER:
        case YULE_CALIBRATION:
            // generate a speciational process
            writer.writeComment("Generate a speciation likelihood for Yule or Birth Death");
            writer.writeOpenTag(SpeciationLikelihoodParser.SPECIATION_LIKELIHOOD, new Attribute[] { new Attribute.Default<String>(XMLParser.ID, modelPrefix + "speciation") });
            // write pop size socket
            writer.writeOpenTag(SpeciationLikelihoodParser.MODEL);
            writeNodeHeightPriorModelRef(prior, writer);
            writer.writeCloseTag(SpeciationLikelihoodParser.MODEL);
            writer.writeOpenTag(SpeciationLikelihoodParser.TREE);
            writer.writeIDref(TreeModel.TREE_MODEL, modelPrefix + TreeModel.TREE_MODEL);
            writer.writeCloseTag(SpeciationLikelihoodParser.TREE);
            if (treePrior == TreePriorType.YULE_CALIBRATION) {
                if (options.treeModelOptions.isNodeCalibrated(model) == 0) {
                    writer.writeOpenTag(SpeciationLikelihoodParser.CALIBRATION, new Attribute[] { new Attribute.Default<String>(SpeciationLikelihoodParser.CORRECTION, prior.getCalibCorrectionType().toString()) });
                    writer.writeOpenTag(SpeciationLikelihoodParser.POINT);
                    String taxaId;
                    if (options.hasIdenticalTaxa()) {
                        taxaId = TaxaParser.TAXA;
                    } else {
                        taxaId = options.getDataPartitions(model).get(0).getPrefix() + TaxaParser.TAXA;
                    }
                    writer.writeIDref(TaxaParser.TAXA, taxaId);
                    writeDistribution(model.getParameter("treeModel.rootHeight"), true, writer);
                    writer.writeCloseTag(SpeciationLikelihoodParser.POINT);
                    writer.writeCloseTag(SpeciationLikelihoodParser.CALIBRATION);
                } else if (options.treeModelOptions.isNodeCalibrated(model) == 1) {
                    // should be only 1 calibrated internal node with monophyletic for each tree at moment
                    Taxa t = (Taxa) options.getKeysFromValue(options.taxonSetsTreeModel, model).get(0);
                    Parameter nodeCalib = options.getStatistic(t);
                    writer.writeOpenTag(SpeciationLikelihoodParser.CALIBRATION, new Attribute[] { new Attribute.Default<String>(SpeciationLikelihoodParser.CORRECTION, prior.getCalibCorrectionType().toString()) });
                    writer.writeOpenTag(SpeciationLikelihoodParser.POINT);
                    writer.writeIDref(TaxaParser.TAXA, t.getId());
                    writeDistribution(nodeCalib, true, writer);
                    writer.writeCloseTag(SpeciationLikelihoodParser.POINT);
                    writer.writeCloseTag(SpeciationLikelihoodParser.CALIBRATION);
                    if (!options.treeModelOptions.isNodeCalibrated(nodeCalib)) {
                        throw new IllegalArgumentException("Calibrated Yule model requires a calibration to be specified for node, " + nodeCalib.getName() + ".");
                    }
                }
            }
            writer.writeCloseTag(SpeciationLikelihoodParser.SPECIATION_LIKELIHOOD);
            break;
        case SKYLINE:
            // generate a Bayesian skyline plot
            writer.writeComment("Generate a generalizedSkyLineLikelihood for Bayesian Skyline");
            writer.writeOpenTag(BayesianSkylineLikelihoodParser.SKYLINE_LIKELIHOOD, new Attribute[] { new Attribute.Default<String>(XMLParser.ID, modelPrefix + "skyline"), new Attribute.Default<String>("linear", prior.getSkylineModel() == TreePriorParameterizationType.LINEAR_SKYLINE ? "true" : "false") });
            // write pop size socket
            writer.writeOpenTag(BayesianSkylineLikelihoodParser.POPULATION_SIZES);
            if (prior.getSkylineModel() == TreePriorParameterizationType.LINEAR_SKYLINE) {
                writeParameter(prior.getParameter("skyline.popSize"), prior.getSkylineGroupCount() + 1, writer);
            } else {
                writeParameter(prior.getParameter("skyline.popSize"), prior.getSkylineGroupCount(), writer);
            }
            writer.writeCloseTag(BayesianSkylineLikelihoodParser.POPULATION_SIZES);
            // write group size socket
            writer.writeOpenTag(BayesianSkylineLikelihoodParser.GROUP_SIZES);
            writeParameter(prior.getParameter("skyline.groupSize"), prior.getSkylineGroupCount(), writer);
            writer.writeCloseTag(BayesianSkylineLikelihoodParser.GROUP_SIZES);
            writer.writeOpenTag(CoalescentLikelihoodParser.POPULATION_TREE);
            writer.writeIDref(TreeModel.TREE_MODEL, modelPrefix + TreeModel.TREE_MODEL);
            writer.writeCloseTag(CoalescentLikelihoodParser.POPULATION_TREE);
            writer.writeCloseTag(BayesianSkylineLikelihoodParser.SKYLINE_LIKELIHOOD);
            writer.writeText("");
            writeExponentialMarkovLikelihood(prior, writer);
            break;
        case EXTENDED_SKYLINE:
            // different format
            break;
        case GMRF_SKYRIDE:
            writer.writeComment("Generate a gmrfSkyrideLikelihood for GMRF Bayesian Skyride process");
            writer.writeOpenTag(GMRFSkyrideLikelihoodParser.SKYLINE_LIKELIHOOD, new Attribute[] { new Attribute.Default<String>(XMLParser.ID, modelPrefix + "skyride"), new Attribute.Default<String>(GMRFSkyrideLikelihoodParser.TIME_AWARE_SMOOTHING, prior.getSkyrideSmoothing() == TreePriorParameterizationType.TIME_AWARE_SKYRIDE ? "true" : "false"), new Attribute.Default<String>(GMRFSkyrideLikelihoodParser.RANDOMIZE_TREE, //TODO For GMRF, tree model/tree prior combination not implemented by BEAST yet. The validation is in BeastGenerator.checkOptions()
            options.getPartitionTreeModels(prior).get(0).getStartingTreeType() == StartingTreeType.UPGMA ? "true" : "false") });
            int skyrideIntervalCount = options.taxonList.getTaxonCount() - 1;
            writer.writeOpenTag(GMRFSkyrideLikelihoodParser.POPULATION_PARAMETER);
            writer.writeComment("skyride.logPopSize is in log units unlike other popSize");
            writeParameter(prior.getParameter("skyride.logPopSize"), skyrideIntervalCount, writer);
            writer.writeCloseTag(GMRFSkyrideLikelihoodParser.POPULATION_PARAMETER);
            writer.writeOpenTag(GMRFSkyrideLikelihoodParser.GROUP_SIZES);
            writeParameter(prior.getParameter("skyride.groupSize"), skyrideIntervalCount, writer);
            writer.writeCloseTag(GMRFSkyrideLikelihoodParser.GROUP_SIZES);
            writer.writeOpenTag(GMRFSkyrideLikelihoodParser.PRECISION_PARAMETER);
            writeParameter(prior.getParameter("skyride.precision"), 1, writer);
            writer.writeCloseTag(GMRFSkyrideLikelihoodParser.PRECISION_PARAMETER);
            writer.writeOpenTag(GMRFSkyrideLikelihoodParser.POPULATION_TREE);
            writer.writeIDref(TreeModel.TREE_MODEL, modelPrefix + TreeModel.TREE_MODEL);
            writer.writeCloseTag(GMRFSkyrideLikelihoodParser.POPULATION_TREE);
            writer.writeCloseTag(GMRFSkyrideLikelihoodParser.SKYLINE_LIKELIHOOD);
            break;
        case SKYGRID:
            break;
        case SPECIES_YULE:
        case SPECIES_YULE_CALIBRATION:
        case SPECIES_BIRTH_DEATH:
            break;
        default:
            // generate a coalescent process
            writer.writeComment("Generate a coalescent likelihood");
            writer.writeOpenTag(CoalescentLikelihoodParser.COALESCENT_LIKELIHOOD, new Attribute[] { new Attribute.Default<String>(XMLParser.ID, modelPrefix + COALESCENT) });
            writer.writeOpenTag(CoalescentLikelihoodParser.MODEL);
            writeNodeHeightPriorModelRef(prior, writer);
            writer.writeCloseTag(CoalescentLikelihoodParser.MODEL);
            writer.writeOpenTag(CoalescentLikelihoodParser.POPULATION_TREE);
            writer.writeIDref(TreeModel.TREE_MODEL, modelPrefix + TreeModel.TREE_MODEL);
            writer.writeCloseTag(CoalescentLikelihoodParser.POPULATION_TREE);
            writer.writeCloseTag(CoalescentLikelihoodParser.COALESCENT_LIKELIHOOD);
    }
}

Example 17 with Attribute

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

the class TMRCAStatisticsGenerator method writeTMRCAStatistics.

/**
     * Generate tmrca statistics
     *
     * @param writer       the writer
     */
public void writeTMRCAStatistics(XMLWriter writer) {
    List<Taxa> taxonSets;
    Map<Taxa, Boolean> taxonSetsMono;
    if (options.useStarBEAST) {
        taxonSets = options.speciesSets;
        taxonSetsMono = options.speciesSetsMono;
        writer.writeComment("Species Sets");
        writer.writeText("");
        for (Taxa taxa : taxonSets) {
            writer.writeOpenTag(TMRCAStatisticParser.TMRCA_STATISTIC, new Attribute[] { new Attribute.Default<String>(XMLParser.ID, "tmrca(" + taxa.getId() + ")") });
            // make tmrca(tree.name) eay to read in log for Tracer
            writer.writeOpenTag(TMRCAStatisticParser.MRCA);
            writer.writeIDref(TaxaParser.TAXA, taxa.getId());
            writer.writeCloseTag(TMRCAStatisticParser.MRCA);
            writer.writeIDref(SpeciesTreeModelParser.SPECIES_TREE, SP_TREE);
            writer.writeCloseTag(TMRCAStatisticParser.TMRCA_STATISTIC);
            if (taxonSetsMono.get(taxa)) {
                //                    && treeModel.getPartitionTreePrior().getNodeHeightPrior() != TreePriorType.YULE
                //                    && options.getKeysFromValue(options.taxonSetsTreeModel, treeModel).size() > 1) {
                writer.writeOpenTag(MonophylyStatisticParser.MONOPHYLY_STATISTIC, new Attribute[] { new Attribute.Default<String>(XMLParser.ID, "monophyly(" + taxa.getId() + ")") });
                writer.writeOpenTag(MonophylyStatisticParser.MRCA);
                writer.writeIDref(TaxaParser.TAXA, taxa.getId());
                writer.writeCloseTag(MonophylyStatisticParser.MRCA);
                writer.writeIDref(SpeciesTreeModelParser.SPECIES_TREE, SP_TREE);
                writer.writeCloseTag(MonophylyStatisticParser.MONOPHYLY_STATISTIC);
            }
        }
    } else {
        taxonSets = options.taxonSets;
        taxonSetsMono = options.taxonSetsMono;
        writer.writeComment("Taxon Sets");
        writer.writeText("");
        for (Taxa taxa : taxonSets) {
            PartitionTreeModel treeModel = options.taxonSetsTreeModel.get(taxa);
            writer.writeOpenTag(TMRCAStatisticParser.TMRCA_STATISTIC, new Attribute[] { new Attribute.Default<String>(XMLParser.ID, "tmrca(" + treeModel.getPrefix() + taxa.getId() + ")"), new Attribute.Default<Boolean>(TMRCAStatisticParser.STEM, options.taxonSetsIncludeStem.get(taxa)) });
            // make tmrca(tree.name) eay to read in log for Tracer
            writer.writeOpenTag(TMRCAStatisticParser.MRCA);
            writer.writeIDref(TaxaParser.TAXA, taxa.getId());
            writer.writeCloseTag(TMRCAStatisticParser.MRCA);
            writer.writeIDref(TreeModel.TREE_MODEL, treeModel.getPrefix() + TreeModel.TREE_MODEL);
            writer.writeCloseTag(TMRCAStatisticParser.TMRCA_STATISTIC);
            if (taxonSetsMono.get(taxa)) {
                //                    && treeModel.getPartitionTreePrior().getNodeHeightPrior() != TreePriorType.YULE
                //                    && options.getKeysFromValue(options.taxonSetsTreeModel, treeModel).size() > 1) {
                writer.writeOpenTag(MonophylyStatisticParser.MONOPHYLY_STATISTIC, new Attribute[] { new Attribute.Default<String>(XMLParser.ID, "monophyly(" + taxa.getId() + ")") });
                writer.writeOpenTag(MonophylyStatisticParser.MRCA);
                writer.writeIDref(TaxaParser.TAXA, taxa.getId());
                writer.writeCloseTag(MonophylyStatisticParser.MRCA);
                writer.writeIDref(TreeModel.TREE_MODEL, treeModel.getPrefix() + TreeModel.TREE_MODEL);
                writer.writeCloseTag(MonophylyStatisticParser.MONOPHYLY_STATISTIC);
            }
        }
    }
}

Example 18 with Attribute

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

the class TMRCAStatisticsGenerator method writeTaxonSets.

/**
     * Generate additional taxon sets
     *
     * @param writer    the writer
     * @param taxonSets a list of taxa to write
     */
public void writeTaxonSets(XMLWriter writer, List<Taxa> taxonSets) {
    writer.writeText("");
    for (Taxa taxa : taxonSets) {
        writer.writeOpenTag(TaxaParser.TAXA, new Attribute[] { new Attribute.Default<String>(XMLParser.ID, taxa.getId()) });
        for (int j = 0; j < taxa.getTaxonCount(); j++) {
            writer.writeIDref(TaxonParser.TAXON, taxa.getTaxon(j).getId());
        }
        writer.writeCloseTag(TaxaParser.TAXA);
    }
}

Example 19 with Attribute

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

the class TreeLikelihoodGenerator method writeTreeLikelihood.

/**
     * Write the tree likelihood XML block.
     *
     * @param id        the id of the tree likelihood
     * @param num       the likelihood number
     * @param partition the partition to write likelihood block for
     * @param writer    the writer
     */
private void writeTreeLikelihood(String tag, String id, int num, PartitionData partition, XMLWriter writer) {
    PartitionSubstitutionModel substModel = partition.getPartitionSubstitutionModel();
    PartitionTreeModel treeModel = partition.getPartitionTreeModel();
    PartitionClockModel clockModel = partition.getPartitionClockModel();
    writer.writeComment("Likelihood for tree given sequence data");
    String prefix;
    if (num > 0) {
        prefix = partition.getPrefix() + substModel.getPrefixCodon(num);
    } else {
        prefix = partition.getPrefix();
    }
    String idString = prefix + id;
    Attribute[] attributes;
    if (tag.equals(MarkovJumpsTreeLikelihoodParser.MARKOV_JUMP_TREE_LIKELIHOOD)) {
        AncestralStatesComponentOptions ancestralStatesOptions = (AncestralStatesComponentOptions) options.getComponentOptions(AncestralStatesComponentOptions.class);
        boolean saveCompleteHistory = ancestralStatesOptions.isCompleteHistoryLogging(partition);
        attributes = new Attribute[] { new Attribute.Default<String>(XMLParser.ID, idString), new Attribute.Default<Boolean>(TreeLikelihoodParser.USE_AMBIGUITIES, substModel.isUseAmbiguitiesTreeLikelihood()), new Attribute.Default<Boolean>(MarkovJumpsTreeLikelihoodParser.USE_UNIFORMIZATION, true), new Attribute.Default<Integer>(MarkovJumpsTreeLikelihoodParser.NUMBER_OF_SIMULANTS, 1), new Attribute.Default<String>(AncestralStateTreeLikelihoodParser.RECONSTRUCTION_TAG_NAME, prefix + AncestralStateTreeLikelihoodParser.RECONSTRUCTION_TAG), new Attribute.Default<String>(MarkovJumpsTreeLikelihoodParser.SAVE_HISTORY, saveCompleteHistory ? "true" : "false") };
    } else if (tag.equals(TreeLikelihoodParser.ANCESTRAL_TREE_LIKELIHOOD)) {
        attributes = new Attribute[] { new Attribute.Default<String>(XMLParser.ID, idString), new Attribute.Default<Boolean>(TreeLikelihoodParser.USE_AMBIGUITIES, substModel.isUseAmbiguitiesTreeLikelihood()), new Attribute.Default<String>(AncestralStateTreeLikelihoodParser.RECONSTRUCTION_TAG_NAME, prefix + AncestralStateTreeLikelihoodParser.RECONSTRUCTION_TAG) };
    } else {
        attributes = new Attribute[] { new Attribute.Default<String>(XMLParser.ID, idString), new Attribute.Default<Boolean>(TreeLikelihoodParser.USE_AMBIGUITIES, substModel.isUseAmbiguitiesTreeLikelihood()) };
    }
    writer.writeOpenTag(tag, attributes);
    if (!options.samplePriorOnly) {
        if (num > 0) {
            writeCodonPatternsRef(prefix, num, substModel.getCodonPartitionCount(), writer);
        } else {
            writer.writeIDref(SitePatternsParser.PATTERNS, prefix + SitePatternsParser.PATTERNS);
        }
    } else {
        // We just need to use the dummy alignment
        writer.writeIDref(AlignmentParser.ALIGNMENT, partition.getAlignment().getId());
    }
    writer.writeIDref(TreeModel.TREE_MODEL, treeModel.getPrefix() + TreeModel.TREE_MODEL);
    if (num > 0) {
        writer.writeIDref(GammaSiteModel.SITE_MODEL, substModel.getPrefix(num) + SiteModel.SITE_MODEL);
    } else {
        writer.writeIDref(GammaSiteModel.SITE_MODEL, substModel.getPrefix() + SiteModel.SITE_MODEL);
    }
    ClockModelGenerator.writeBranchRatesModelRef(clockModel, writer);
    generateInsertionPoint(ComponentGenerator.InsertionPoint.IN_TREE_LIKELIHOOD, partition, prefix, writer);
    writer.writeCloseTag(tag);
}

Example 20 with Attribute

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

the class STARBEASTGenerator method writeGeneUnderSpecies.

private void writeGeneUnderSpecies(XMLWriter writer) {
    writer.writeComment("Species Tree: Coalescent likelihood for gene trees under species tree");
    // speciesCoalescent id="coalescent"
    writer.writeOpenTag(MultiSpeciesCoalescentParser.SPECIES_COALESCENT, new Attribute[] { new Attribute.Default<String>(XMLParser.ID, TraitData.TRAIT_SPECIES + "." + COALESCENT) });
    writer.writeIDref(TraitData.TRAIT_SPECIES, TraitData.TRAIT_SPECIES);
    writer.writeIDref(SpeciesTreeModelParser.SPECIES_TREE, SP_TREE);
    writer.writeCloseTag(MultiSpeciesCoalescentParser.SPECIES_COALESCENT);
    // exponentialDistributionModel id="pdist"
    //        writer.writeOpenTag(ExponentialDistributionModel.EXPONENTIAL_DISTRIBUTION_MODEL, new Attribute[]{
    //                new Attribute.Default<String>(XMLParser.ID, PDIST)});
    //
    //        writer.writeOpenTag(DistributionModelParser.MEAN);
    //
    //        Parameter para = options.getParameter(TraitGuesser.Traits.TRAIT_SPECIES + "." + options.POP_MEAN);
    //
    //        writer.writeTag(ParameterParser.PARAMETER, new Attribute[]{
    //                new Attribute.Default<String>(XMLParser.ID, TraitGuesser.Traits.TRAIT_SPECIES + "." + options.POP_MEAN),
    //                new Attribute.Default<String>(ParameterParser.VALUE, Double.toString(para.initial))}, true);
    //
    //        writer.writeCloseTag(DistributionModelParser.MEAN);
    //
    //        writer.writeCloseTag(ExponentialDistributionModel.EXPONENTIAL_DISTRIBUTION_MODEL);
    //        if (options.speciesTreePrior == TreePriorType.SPECIES_YULE) {
    writer.writeComment("Species tree prior: gama2 + gamma4");
    writer.writeOpenTag(MixedDistributionLikelihoodParser.DISTRIBUTION_LIKELIHOOD, new Attribute[] { new Attribute.Default<String>(XMLParser.ID, SPOPS) });
    // change exponential + gamma2 into gama2 + gamma4
    // <distribution0>
    writer.writeOpenTag(MixedDistributionLikelihoodParser.DISTRIBUTION0);
    //        writer.writeIDref(ExponentialDistributionModel.EXPONENTIAL_DISTRIBUTION_MODEL, PDIST);
    writer.writeOpenTag(GammaDistributionModel.GAMMA_DISTRIBUTION_MODEL);
    writer.writeOpenTag(DistributionModelParser.SHAPE);
    writer.writeText("2");
    writer.writeCloseTag(DistributionModelParser.SHAPE);
    writer.writeOpenTag(DistributionModelParser.SCALE);
    Parameter para = options.starBEASTOptions.getParameter(TraitData.TRAIT_SPECIES + "." + options.starBEASTOptions.POP_MEAN);
    writeParameter(para, 1, writer);
    writer.writeCloseTag(DistributionModelParser.SCALE);
    writer.writeCloseTag(GammaDistributionModel.GAMMA_DISTRIBUTION_MODEL);
    writer.writeCloseTag(MixedDistributionLikelihoodParser.DISTRIBUTION0);
    // <distribution1>
    writer.writeOpenTag(MixedDistributionLikelihoodParser.DISTRIBUTION1);
    writer.writeOpenTag(GammaDistributionModel.GAMMA_DISTRIBUTION_MODEL);
    writer.writeOpenTag(DistributionModelParser.SHAPE);
    writer.writeText("4");
    writer.writeCloseTag(DistributionModelParser.SHAPE);
    writer.writeOpenTag(DistributionModelParser.SCALE);
    writer.writeIDref(ParameterParser.PARAMETER, TraitData.TRAIT_SPECIES + "." + options.starBEASTOptions.POP_MEAN);
    writer.writeCloseTag(DistributionModelParser.SCALE);
    writer.writeCloseTag(GammaDistributionModel.GAMMA_DISTRIBUTION_MODEL);
    writer.writeCloseTag(MixedDistributionLikelihoodParser.DISTRIBUTION1);
    // <data>
    writer.writeOpenTag(MixedDistributionLikelihoodParser.DATA);
    writer.writeIDref(ParameterParser.PARAMETER, SpeciesTreeModelParser.SPECIES_TREE + "." + SPLIT_POPS);
    writer.writeCloseTag(MixedDistributionLikelihoodParser.DATA);
    // <indicators>
    writer.writeOpenTag(MixedDistributionLikelihoodParser.INDICATORS);
    // Needs special treatment - you have to generate "NS" ones and 2(N-1) zeros, where N is the number of species.
    // N "1", 2(N-1) "0"
    writer.writeTag(ParameterParser.PARAMETER, new Attribute[] { new Attribute.Default<String>(ParameterParser.VALUE, getIndicatorsParaValue()) }, true);
    writer.writeCloseTag(MixedDistributionLikelihoodParser.INDICATORS);
    writer.writeCloseTag(MixedDistributionLikelihoodParser.DISTRIBUTION_LIKELIHOOD);
//        } else {
//            // STPopulationPrior id="stp" log_root="true"
//            writer.writeOpenTag(SpeciesTreeBMPrior.STPRIOR, new Attribute[]{
//                    new Attribute.Default<String>(XMLParser.ID, STP),
//                    new Attribute.Default<String>(SpeciesTreeBMPrior.LOG_ROOT, "true")});
//            writer.writeIDref(SpeciesTreeModelParser.SPECIES_TREE, SP_TREE);
//
//            writer.writeOpenTag(SpeciesTreeBMPrior.TIPS);
//
//            writer.writeIDref(ExponentialDistributionModel.EXPONENTIAL_DISTRIBUTION_MODEL, PDIST);
//
//            writer.writeCloseTag(SpeciesTreeBMPrior.TIPS);
//
//            writer.writeOpenTag(SpeciesTreeBMPrior.STSIGMA);
//
//            writer.writeTag(ParameterParser.PARAMETER, new Attribute[]{
//                    // <parameter id="stsigma" value="1" />
//                    new Attribute.Default<String>(XMLParser.ID, SpeciesTreeBMPrior.STSIGMA.toLowerCase()),
//                    new Attribute.Default<String>(ParameterParser.VALUE, "1")}, true);
//
//            writer.writeCloseTag(SpeciesTreeBMPrior.STSIGMA);
//
//            writer.writeCloseTag(SpeciesTreeBMPrior.STPRIOR);
//        }
}