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Example 1 with SimpleAlignment

use of dr.evolution.alignment.SimpleAlignment in project beast-mcmc by beast-dev.

the class BeastImporter method readAlignment.

private Alignment readAlignment(Element e, TaxonList taxa) throws Importer.ImportException {
    SimpleAlignment alignment = new SimpleAlignment();
    List children = e.getChildren();
    for (Object aChildren : children) {
        Element child = (Element) aChildren;
        if (child.getName().equalsIgnoreCase(SequenceParser.SEQUENCE)) {
            alignment.addSequence(readSequence(child, taxa));
        }
    }
    return alignment;
}
Also used : SimpleAlignment(dr.evolution.alignment.SimpleAlignment) Element(org.jdom.Element) List(java.util.List)

Example 2 with SimpleAlignment

use of dr.evolution.alignment.SimpleAlignment in project beast-mcmc by beast-dev.

the class AncestralSequenceAnnotator method processTree.

private Tree processTree(Tree tree) {
    // Remake tree to fix node ordering - Marc
    GammaSiteRateModel siteModel = loadSiteModel(tree);
    SimpleAlignment alignment = new SimpleAlignment();
    alignment.setDataType(siteModel.getSubstitutionModel().getDataType());
    if (siteModel.getSubstitutionModel().getDataType().getClass().equals(Codons.class)) {
        //System.out.println("trololo");
        alignment.setDataType(Nucleotides.INSTANCE);
    }
    //System.out.println("BOO BOO " + siteModel.getSubstitutionModel().getDataType().getClass().getName()+"\t" + Codons.UNIVERSAL.getClass().getName() + "\t" + alignment.getDataType().getClass().getName());
    // Get sequences
    String[] sequence = new String[tree.getNodeCount()];
    for (int i = 0; i < tree.getNodeCount(); i++) {
        NodeRef node = tree.getNode(i);
        sequence[i] = (String) tree.getNodeAttribute(node, SEQ_STRING);
        if (tree.isExternal(node)) {
            Taxon taxon = tree.getNodeTaxon(node);
            alignment.addSequence(new Sequence(taxon, sequence[i]));
        //System.out.println("seq " + sequence[i]);
        }
    }
    // Make evolutionary model
    BranchRateModel rateModel = new StrictClockBranchRates(new Parameter.Default(1.0));
    FlexibleTree flexTree;
    if (siteModel.getSubstitutionModel().getDataType().getClass().equals(Codons.class)) {
        ConvertAlignment convertAlignment = new ConvertAlignment(siteModel.getSubstitutionModel().getDataType(), ((Codons) siteModel.getSubstitutionModel().getDataType()).getGeneticCode(), alignment);
        flexTree = sampleTree(tree, convertAlignment, siteModel, rateModel);
    //flexTree = sampleTree(tree, alignment, siteModel, rateModel);
    } else {
        flexTree = sampleTree(tree, alignment, siteModel, rateModel);
    }
    introduceGaps(flexTree, tree);
    return flexTree;
}
Also used : Taxon(dr.evolution.util.Taxon) GammaSiteRateModel(dr.evomodel.siteratemodel.GammaSiteRateModel) Sequence(dr.evolution.sequence.Sequence) StrictClockBranchRates(dr.evomodel.branchratemodel.StrictClockBranchRates) SimpleAlignment(dr.evolution.alignment.SimpleAlignment) BranchRateModel(dr.evomodel.branchratemodel.BranchRateModel) ConvertAlignment(dr.evolution.alignment.ConvertAlignment) Parameter(dr.inference.model.Parameter)

Example 3 with SimpleAlignment

use of dr.evolution.alignment.SimpleAlignment in project beast-mcmc by beast-dev.

the class DataLikelihoodTester2 method main.

public static void main(String[] args) {
    // turn off logging to avoid screen noise...
    Logger logger = Logger.getLogger("dr");
    logger.setUseParentHandlers(false);
    SimpleAlignment alignment = createAlignment(sequences, Nucleotides.INSTANCE);
    TreeModel treeModel;
    try {
        treeModel = createSpecifiedTree("((human:0.1,chimp:0.1):0.1,gorilla:0.2)");
    } catch (Exception e) {
        throw new RuntimeException("Unable to parse Newick tree");
    }
    System.out.print("\nTest BeagleTreeLikelihood (kappa = 1): ");
    //substitutionModel
    Parameter freqs = new Parameter.Default(new double[] { 0.25, 0.25, 0.25, 0.25 });
    Parameter kappa = new Parameter.Default(HKYParser.KAPPA, 1.0, 0, 100);
    FrequencyModel f = new FrequencyModel(Nucleotides.INSTANCE, freqs);
    HKY hky = new HKY(kappa, f);
    //siteModel
    double alpha = 0.5;
    GammaSiteRateModel siteRateModel = new GammaSiteRateModel("gammaModel", alpha, 4);
    //        GammaSiteRateModel siteRateModel = new GammaSiteRateModel("siteRateModel");
    siteRateModel.setSubstitutionModel(hky);
    Parameter mu = new Parameter.Default(GammaSiteModelParser.SUBSTITUTION_RATE, 1.0, 0, Double.POSITIVE_INFINITY);
    siteRateModel.setRelativeRateParameter(mu);
    FrequencyModel f2 = new FrequencyModel(Nucleotides.INSTANCE, freqs);
    Parameter kappa2 = new Parameter.Default(HKYParser.KAPPA, 10.0, 0, 100);
    HKY hky2 = new HKY(kappa2, f2);
    GammaSiteRateModel siteRateModel2 = new GammaSiteRateModel("gammaModel", alpha, 4);
    siteRateModel2.setSubstitutionModel(hky2);
    siteRateModel2.setRelativeRateParameter(mu);
    //treeLikelihood
    SitePatterns patterns = new SitePatterns(alignment, null, 0, -1, 1, true);
    BranchModel branchModel = new HomogeneousBranchModel(siteRateModel.getSubstitutionModel(), siteRateModel.getSubstitutionModel().getFrequencyModel());
    BranchModel branchModel2 = new HomogeneousBranchModel(siteRateModel2.getSubstitutionModel(), siteRateModel2.getSubstitutionModel().getFrequencyModel());
    BranchRateModel branchRateModel = new DefaultBranchRateModel();
    BeagleTreeLikelihood treeLikelihood = new BeagleTreeLikelihood(patterns, treeModel, branchModel, siteRateModel, branchRateModel, null, false, PartialsRescalingScheme.AUTO, true);
    double logLikelihood = treeLikelihood.getLogLikelihood();
    System.out.println("logLikelihood = " + logLikelihood);
    System.out.print("\nTest BeagleDataLikelihoodDelegate (kappa = 1): ");
    BeagleDataLikelihoodDelegate dataLikelihoodDelegate = new BeagleDataLikelihoodDelegate(treeModel, patterns, branchModel, siteRateModel, false, PartialsRescalingScheme.NONE, false);
    TreeDataLikelihood treeDataLikelihood = new TreeDataLikelihood(dataLikelihoodDelegate, treeModel, branchRateModel);
    logLikelihood = treeDataLikelihood.getLogLikelihood();
    System.out.println("logLikelihood = " + logLikelihood);
    hky.setKappa(5.0);
    System.out.print("\nTest BeagleDataLikelihoodDelegate (kappa = 5): ");
    logLikelihood = treeDataLikelihood.getLogLikelihood();
    System.out.println("logLikelihood = " + logLikelihood);
    System.out.print("\nTest BeagleDataLikelihoodDelegate (kappa = 10): ");
    dataLikelihoodDelegate = new BeagleDataLikelihoodDelegate(treeModel, patterns, branchModel2, siteRateModel2, false, PartialsRescalingScheme.NONE, false);
    treeDataLikelihood = new TreeDataLikelihood(dataLikelihoodDelegate, treeModel, branchRateModel);
    logLikelihood = treeDataLikelihood.getLogLikelihood();
    System.out.println("logLikelihood = " + logLikelihood);
    hky2.setKappa(11.0);
    System.out.print("\nTest BeagleDataLikelihoodDelegate (kappa = 11): ");
    logLikelihood = treeDataLikelihood.getLogLikelihood();
    System.out.println("logLikelihood = " + logLikelihood);
    hky.setKappa(1.0);
    hky2.setKappa(10.0);
    MultiPartitionDataLikelihoodDelegate multiPartitionDataLikelihoodDelegate;
    System.out.print("\nTest MultiPartitionDataLikelihoodDelegate 1 partition (kappa = 1):");
    multiPartitionDataLikelihoodDelegate = new MultiPartitionDataLikelihoodDelegate(treeModel, Collections.singletonList((PatternList) patterns), Collections.singletonList((BranchModel) branchModel), Collections.singletonList((SiteRateModel) siteRateModel), true, PartialsRescalingScheme.NONE, false);
    treeDataLikelihood = new TreeDataLikelihood(multiPartitionDataLikelihoodDelegate, treeModel, branchRateModel);
    logLikelihood = treeDataLikelihood.getLogLikelihood();
    System.out.println("logLikelihood = " + logLikelihood);
    hky.setKappa(5.0);
    System.out.print("\nTest MultiPartitionDataLikelihoodDelegate 1 partition (kappa = 5):");
    logLikelihood = treeDataLikelihood.getLogLikelihood();
    System.out.println("logLikelihood = " + logLikelihood);
    hky.setKappa(1.0);
    System.out.print("\nTest MultiPartitionDataLikelihoodDelegate 1 partition (kappa = 10):");
    multiPartitionDataLikelihoodDelegate = new MultiPartitionDataLikelihoodDelegate(treeModel, Collections.singletonList((PatternList) patterns), Collections.singletonList((BranchModel) branchModel2), Collections.singletonList((SiteRateModel) siteRateModel2), true, PartialsRescalingScheme.NONE, false);
    treeDataLikelihood = new TreeDataLikelihood(multiPartitionDataLikelihoodDelegate, treeModel, branchRateModel);
    logLikelihood = treeDataLikelihood.getLogLikelihood();
    System.out.println("logLikelihood = " + logLikelihood);
    System.out.print("\nTest MultiPartitionDataLikelihoodDelegate 2 partitions (kappa = 1, 10): ");
    List<PatternList> patternLists = new ArrayList<PatternList>();
    patternLists.add(patterns);
    patternLists.add(patterns);
    List<SiteRateModel> siteRateModels = new ArrayList<SiteRateModel>();
    siteRateModels.add(siteRateModel);
    siteRateModels.add(siteRateModel2);
    List<BranchModel> branchModels = new ArrayList<BranchModel>();
    branchModels.add(branchModel);
    branchModels.add(branchModel2);
    multiPartitionDataLikelihoodDelegate = new MultiPartitionDataLikelihoodDelegate(treeModel, patternLists, branchModels, siteRateModels, true, PartialsRescalingScheme.NONE, false);
    treeDataLikelihood = new TreeDataLikelihood(multiPartitionDataLikelihoodDelegate, treeModel, branchRateModel);
    logLikelihood = treeDataLikelihood.getLogLikelihood();
    System.out.println("logLikelihood = " + logLikelihood + " (NOT OK: this is 2x the logLikelihood of the 2nd partition)\n\n");
    System.exit(0);
    //START ADDITIONAL TEST #1 - Guy Baele
    System.out.println("-- Test #1 SiteRateModels -- ");
    //alpha in partition 1 reject followed by alpha in partition 2 reject
    System.out.print("Adjust alpha in partition 1: ");
    siteRateModel.setAlpha(0.4);
    logLikelihood = treeDataLikelihood.getLogLikelihood();
    System.out.println("logLikelihood = " + logLikelihood);
    System.out.print("Return alpha in partition 1 to original value: ");
    siteRateModel.setAlpha(0.5);
    logLikelihood = treeDataLikelihood.getLogLikelihood();
    System.out.println("logLikelihood = " + logLikelihood + " (i.e. reject: OK)\n");
    System.out.print("Adjust alpha in partition 2: ");
    siteRateModel2.setAlpha(0.35);
    logLikelihood = treeDataLikelihood.getLogLikelihood();
    System.out.println("logLikelihood = " + logLikelihood);
    System.out.print("Return alpha in partition 2 to original value: ");
    siteRateModel2.setAlpha(0.5);
    logLikelihood = treeDataLikelihood.getLogLikelihood();
    System.out.println("logLikelihood = " + logLikelihood + " (i.e. reject: OK)\n");
    //alpha in partition 1 accept followed by alpha in partition 2 accept
    System.out.print("Adjust alpha in partition 1: ");
    siteRateModel.setAlpha(0.4);
    logLikelihood = treeDataLikelihood.getLogLikelihood();
    System.out.println("logLikelihood = " + logLikelihood);
    System.out.print("Adjust alpha in partition 2: ");
    siteRateModel2.setAlpha(0.35);
    logLikelihood = treeDataLikelihood.getLogLikelihood();
    System.out.println("logLikelihood = " + logLikelihood + " (NOT OK: same logLikelihood as only setting alpha in partition 2)");
    System.out.print("Return alpha in partition 1 to original value: ");
    siteRateModel.setAlpha(0.5);
    logLikelihood = treeDataLikelihood.getLogLikelihood();
    System.out.println("logLikelihood = " + logLikelihood + " (NOT OK: alpha in partition 2 has not been returned to original value yet)");
    System.out.print("Return alpha in partition 2 to original value: ");
    siteRateModel2.setAlpha(0.5);
    logLikelihood = treeDataLikelihood.getLogLikelihood();
    System.out.println("logLikelihood = " + logLikelihood + "\n");
    //adjusting alphas in both partitions without explicitly calling getLogLikelihood() in between
    System.out.print("Adjust both alphas in partitions 1 and 2: ");
    siteRateModel.setAlpha(0.4);
    siteRateModel2.setAlpha(0.35);
    logLikelihood = treeDataLikelihood.getLogLikelihood();
    System.out.println("logLikelihood = " + logLikelihood);
    System.out.print("Return alpha in partition 2 to original value: ");
    siteRateModel2.setAlpha(0.5);
    logLikelihood = treeDataLikelihood.getLogLikelihood();
    System.out.println("logLikelihood = " + logLikelihood + " (NOT OK: alpha in partition 1 has not been returned to original value yet)");
    System.out.print("Return alpha in partition 1 to original value: ");
    siteRateModel.setAlpha(0.5);
    logLikelihood = treeDataLikelihood.getLogLikelihood();
    System.out.println("logLikelihood = " + logLikelihood + "\n\n");
    //END ADDITIONAL TEST - Guy Baele
    //START ADDITIONAL TEST #2 - Guy Baele
    System.out.println("-- Test #2 SiteRateModels -- ");
    logLikelihood = treeDataLikelihood.getLogLikelihood();
    System.out.println("logLikelihood = " + logLikelihood);
    //1 siteRateModel shared across 2 partitions
    siteRateModels = new ArrayList<SiteRateModel>();
    siteRateModels.add(siteRateModel);
    multiPartitionDataLikelihoodDelegate = new MultiPartitionDataLikelihoodDelegate(treeModel, patternLists, branchModels, siteRateModels, true, PartialsRescalingScheme.NONE, false);
    treeDataLikelihood = new TreeDataLikelihood(multiPartitionDataLikelihoodDelegate, treeModel, branchRateModel);
    logLikelihood = treeDataLikelihood.getLogLikelihood();
    System.out.println("logLikelihood = " + logLikelihood + "\n");
    System.out.print("Adjust alpha in shared siteRateModel: ");
    siteRateModel.setAlpha(0.4);
    logLikelihood = treeDataLikelihood.getLogLikelihood();
    System.out.println("logLikelihood = " + logLikelihood + " (NOT OK: same logLikelihood as only adjusted alpha for partition 1)");
    siteRateModel.setAlpha(0.5);
    logLikelihood = treeDataLikelihood.getLogLikelihood();
    System.out.println("logLikelihood = " + logLikelihood + "\n\n");
    //END ADDITIONAL TEST - Guy Baele
    //START ADDITIONAL TEST #3 - Guy Baele
    System.out.println("-- Test #3 SiteRateModels -- ");
    siteRateModel = new GammaSiteRateModel("gammaModel");
    siteRateModel.setSubstitutionModel(hky);
    siteRateModel.setRelativeRateParameter(mu);
    siteRateModel2 = new GammaSiteRateModel("gammaModel2");
    siteRateModel2.setSubstitutionModel(hky2);
    siteRateModel2.setRelativeRateParameter(mu);
    siteRateModels = new ArrayList<SiteRateModel>();
    siteRateModels.add(siteRateModel);
    siteRateModels.add(siteRateModel2);
    multiPartitionDataLikelihoodDelegate = new MultiPartitionDataLikelihoodDelegate(treeModel, patternLists, branchModels, siteRateModels, true, PartialsRescalingScheme.NONE, false);
    treeDataLikelihood = new TreeDataLikelihood(multiPartitionDataLikelihoodDelegate, treeModel, branchRateModel);
    logLikelihood = treeDataLikelihood.getLogLikelihood();
    System.out.println("logLikelihood = " + logLikelihood + "\n");
    System.out.print("Adjust kappa in partition 1: ");
    hky.setKappa(5.0);
    logLikelihood = treeDataLikelihood.getLogLikelihood();
    System.out.println("logLikelihood = " + logLikelihood + " (NOT OK: logLikelihood has not changed?)");
    System.out.print("Return kappa in partition 1 to original value: ");
    hky.setKappa(1.0);
    logLikelihood = treeDataLikelihood.getLogLikelihood();
    System.out.println("logLikelihood = " + logLikelihood + "\n");
    System.out.print("Adjust kappa in partition 2: ");
    hky2.setKappa(11.0);
    logLikelihood = treeDataLikelihood.getLogLikelihood();
    System.out.println("logLikelihood = " + logLikelihood);
    System.out.print("Return kappa in partition 2 to original value: ");
    hky2.setKappa(10.0);
    logLikelihood = treeDataLikelihood.getLogLikelihood();
    System.out.println("logLikelihood = " + logLikelihood + " (i.e. reject: OK)\n\n");
    //END ADDITIONAL TEST - Guy Baele
    //START ADDITIONAL TEST #4 - Guy Baele
    System.out.println("-- Test #4 SiteRateModels -- ");
    SimpleAlignment secondAlignment = createAlignment(moreSequences, Nucleotides.INSTANCE);
    SitePatterns morePatterns = new SitePatterns(secondAlignment, null, 0, -1, 1, true);
    BeagleDataLikelihoodDelegate dataLikelihoodDelegateOne = new BeagleDataLikelihoodDelegate(treeModel, patterns, branchModel, siteRateModel, false, PartialsRescalingScheme.NONE, false);
    TreeDataLikelihood treeDataLikelihoodOne = new TreeDataLikelihood(dataLikelihoodDelegateOne, treeModel, branchRateModel);
    logLikelihood = treeDataLikelihoodOne.getLogLikelihood();
    System.out.println("\nBeagleDataLikelihoodDelegate logLikelihood partition 1 (kappa = 1) = " + logLikelihood);
    hky.setKappa(10.0);
    logLikelihood = treeDataLikelihoodOne.getLogLikelihood();
    System.out.println("BeagleDataLikelihoodDelegate logLikelihood partition 1 (kappa = 10) = " + logLikelihood);
    hky.setKappa(1.0);
    BeagleDataLikelihoodDelegate dataLikelihoodDelegateTwo = new BeagleDataLikelihoodDelegate(treeModel, morePatterns, branchModel2, siteRateModel2, false, PartialsRescalingScheme.NONE, false);
    TreeDataLikelihood treeDataLikelihoodTwo = new TreeDataLikelihood(dataLikelihoodDelegateTwo, treeModel, branchRateModel);
    logLikelihood = treeDataLikelihoodTwo.getLogLikelihood();
    System.out.println("BeagleDataLikelihoodDelegate logLikelihood partition 2 (kappa = 10) = " + logLikelihood + "\n");
    multiPartitionDataLikelihoodDelegate = new MultiPartitionDataLikelihoodDelegate(treeModel, Collections.singletonList((PatternList) patterns), Collections.singletonList((BranchModel) branchModel), Collections.singletonList((SiteRateModel) siteRateModel), true, PartialsRescalingScheme.NONE, false);
    treeDataLikelihood = new TreeDataLikelihood(multiPartitionDataLikelihoodDelegate, treeModel, branchRateModel);
    logLikelihood = treeDataLikelihood.getLogLikelihood();
    System.out.print("Test MultiPartitionDataLikelihoodDelegate 1st partition (kappa = 1):");
    System.out.println("logLikelihood = " + logLikelihood);
    hky.setKappa(10.0);
    logLikelihood = treeDataLikelihood.getLogLikelihood();
    System.out.print("Test MultiPartitionDataLikelihoodDelegate 1st partition (kappa = 10):");
    System.out.println("logLikelihood = " + logLikelihood);
    hky.setKappa(1.0);
    multiPartitionDataLikelihoodDelegate = new MultiPartitionDataLikelihoodDelegate(treeModel, Collections.singletonList((PatternList) morePatterns), Collections.singletonList((BranchModel) branchModel2), Collections.singletonList((SiteRateModel) siteRateModel2), true, PartialsRescalingScheme.NONE, false);
    treeDataLikelihood = new TreeDataLikelihood(multiPartitionDataLikelihoodDelegate, treeModel, branchRateModel);
    logLikelihood = treeDataLikelihood.getLogLikelihood();
    System.out.print("Test MultiPartitionDataLikelihoodDelegate 2nd partition (kappa = 10):");
    System.out.println("logLikelihood = " + logLikelihood + "\n");
    patternLists = new ArrayList<PatternList>();
    patternLists.add(patterns);
    patternLists.add(morePatterns);
    multiPartitionDataLikelihoodDelegate = new MultiPartitionDataLikelihoodDelegate(treeModel, patternLists, branchModels, siteRateModels, true, PartialsRescalingScheme.NONE, false);
    treeDataLikelihood = new TreeDataLikelihood(multiPartitionDataLikelihoodDelegate, treeModel, branchRateModel);
    logLikelihood = treeDataLikelihood.getLogLikelihood();
    System.out.print("Test MultiPartitionDataLikelihoodDelegate 2 partitions (kappa = 1, 10): ");
    System.out.println("logLikelihood = " + logLikelihood + " (NOT OK: should be the sum of both separate logLikelihoods)\nKappa value of partition 2 is used to compute logLikelihood for both partitions?");
//END ADDITIONAL TEST - Guy Baele
}
Also used : FrequencyModel(dr.evomodel.substmodel.FrequencyModel) ArrayList(java.util.ArrayList) PatternList(dr.evolution.alignment.PatternList) Logger(java.util.logging.Logger) HomogeneousBranchModel(dr.evomodel.branchmodel.HomogeneousBranchModel) BranchModel(dr.evomodel.branchmodel.BranchModel) DefaultBranchRateModel(dr.evomodel.branchratemodel.DefaultBranchRateModel) SiteRateModel(dr.evomodel.siteratemodel.SiteRateModel) GammaSiteRateModel(dr.evomodel.siteratemodel.GammaSiteRateModel) TreeModel(dr.evomodel.tree.TreeModel) SimpleAlignment(dr.evolution.alignment.SimpleAlignment) SitePatterns(dr.evolution.alignment.SitePatterns) BeagleTreeLikelihood(dr.evomodel.treelikelihood.BeagleTreeLikelihood) HomogeneousBranchModel(dr.evomodel.branchmodel.HomogeneousBranchModel) GammaSiteRateModel(dr.evomodel.siteratemodel.GammaSiteRateModel) DefaultBranchRateModel(dr.evomodel.branchratemodel.DefaultBranchRateModel) BranchRateModel(dr.evomodel.branchratemodel.BranchRateModel) HKY(dr.evomodel.substmodel.nucleotide.HKY) Parameter(dr.inference.model.Parameter)

Example 4 with SimpleAlignment

use of dr.evolution.alignment.SimpleAlignment in project beast-mcmc by beast-dev.

the class DataLikelihoodTester method createAlignment.

private static SimpleAlignment createAlignment(Object[][] taxa_sequence, DataType dataType) {
    SimpleAlignment alignment = new SimpleAlignment();
    alignment.setDataType(dataType);
    //        alignment.setDataType(Nucleotides.INSTANCE);
    // 6, 17
    Taxon[] taxa = new Taxon[taxa_sequence[0].length];
    System.out.println("Taxon len = " + taxa_sequence[0].length);
    System.out.println("Alignment len = " + taxa_sequence[1].length);
    if (taxa_sequence.length > 2)
        System.out.println("Date len = " + taxa_sequence[2].length);
    for (int i = 0; i < taxa_sequence[0].length; i++) {
        taxa[i] = new Taxon(taxa_sequence[0][i].toString());
        if (taxa_sequence.length > 2) {
            Date date = new Date((Double) taxa_sequence[2][i], Units.Type.YEARS, (Boolean) taxa_sequence[3][0]);
            taxa[i].setDate(date);
        }
        //taxonList.addTaxon(taxon);
        Sequence sequence = new Sequence(taxa_sequence[1][i].toString());
        sequence.setTaxon(taxa[i]);
        sequence.setDataType(dataType);
        alignment.addSequence(sequence);
    }
    return alignment;
}
Also used : SimpleAlignment(dr.evolution.alignment.SimpleAlignment) Taxon(dr.evolution.util.Taxon) Sequence(dr.evolution.sequence.Sequence) Date(dr.evolution.util.Date)

Example 5 with SimpleAlignment

use of dr.evolution.alignment.SimpleAlignment in project beast-mcmc by beast-dev.

the class BeagleSeqSimTest method simulateRandomBranchAssignment.

// END: main
static void simulateRandomBranchAssignment() {
    try {
        System.out.println("Test case I dunno which: simulate random branch assignments");
        MathUtils.setSeed(666);
        int sequenceLength = 10;
        ArrayList<Partition> partitionsList = new ArrayList<Partition>();
        File treeFile = new File("/home/filip/Dropbox/BeagleSequenceSimulator/SimTree/SimTree.figtree");
        Tree tree = Utils.importTreeFromFile(treeFile);
        TreeModel treeModel = new TreeModel(tree);
        // create Frequency Model
        Parameter freqs = new Parameter.Default(Utils.UNIFORM_CODON_FREQUENCIES);
        FrequencyModel freqModel = new FrequencyModel(Codons.UNIVERSAL, freqs);
        // create base subst model
        Parameter omegaParameter = new Parameter.Default("omega", 1, 1.0);
        Parameter kappaParameter = new Parameter.Default("kappa", 1, 1.0);
        GY94CodonModel baseSubModel = new GY94CodonModel(Codons.UNIVERSAL, omegaParameter, kappaParameter, freqModel);
        RandomBranchModel substitutionModel = new RandomBranchModel(treeModel, baseSubModel, 0.25, false, -1);
        // create site model
        GammaSiteRateModel siteRateModel = new GammaSiteRateModel("siteModel");
        // create branch rate model
        BranchRateModel branchRateModel = new DefaultBranchRateModel();
        // create partition
        Partition partition1 = new //
        Partition(//
        treeModel, //
        substitutionModel, //
        siteRateModel, //
        branchRateModel, //
        freqModel, // from
        0, // to
        sequenceLength - 1, // every
        1);
        //			Sequence ancestralSequence = new Sequence();
        //			ancestralSequence.appendSequenceString("TCAAGTGAGG");
        //			partition1.setRootSequence(ancestralSequence);
        partitionsList.add(partition1);
        // feed to sequence simulator and generate data
        BeagleSequenceSimulator simulator = new BeagleSequenceSimulator(partitionsList);
        SimpleAlignment alignment = simulator.simulate(simulateInPar, true);
        // alignment.setOutputType(SimpleAlignment.OutputType.NEXUS);
        alignment.setOutputType(SimpleAlignment.OutputType.XML);
        System.out.println(alignment.toString());
    } catch (Exception e) {
        e.printStackTrace();
    }
// END: try-catch
}
Also used : FrequencyModel(dr.evomodel.substmodel.FrequencyModel) Partition(dr.app.beagle.tools.Partition) ArrayList(java.util.ArrayList) GammaSiteRateModel(dr.evomodel.siteratemodel.GammaSiteRateModel) BeagleSequenceSimulator(dr.app.beagle.tools.BeagleSequenceSimulator) ImportException(dr.evolution.io.Importer.ImportException) IOException(java.io.IOException) DefaultBranchRateModel(dr.evomodel.branchratemodel.DefaultBranchRateModel) TreeModel(dr.evomodel.tree.TreeModel) RandomBranchModel(dr.evomodel.branchmodel.RandomBranchModel) SimpleAlignment(dr.evolution.alignment.SimpleAlignment) DefaultBranchRateModel(dr.evomodel.branchratemodel.DefaultBranchRateModel) BranchRateModel(dr.evomodel.branchratemodel.BranchRateModel) Tree(dr.evolution.tree.Tree) Parameter(dr.inference.model.Parameter) GY94CodonModel(dr.evomodel.substmodel.codon.GY94CodonModel) File(java.io.File)

Aggregations

SimpleAlignment (dr.evolution.alignment.SimpleAlignment)28 Sequence (dr.evolution.sequence.Sequence)15 Taxon (dr.evolution.util.Taxon)10 ArrayList (java.util.ArrayList)9 TreeModel (dr.evomodel.tree.TreeModel)7 Parameter (dr.inference.model.Parameter)7 Tree (dr.evolution.tree.Tree)6 BranchRateModel (dr.evomodel.branchratemodel.BranchRateModel)6 GammaSiteRateModel (dr.evomodel.siteratemodel.GammaSiteRateModel)6 BeagleSequenceSimulator (dr.app.beagle.tools.BeagleSequenceSimulator)5 Partition (dr.app.beagle.tools.Partition)5 ImportException (dr.evolution.io.Importer.ImportException)5 FrequencyModel (dr.evomodel.substmodel.FrequencyModel)5 Date (dr.evolution.util.Date)4 HomogeneousBranchModel (dr.evomodel.branchmodel.HomogeneousBranchModel)4 DefaultBranchRateModel (dr.evomodel.branchratemodel.DefaultBranchRateModel)4 HKY (dr.evomodel.substmodel.nucleotide.HKY)4 IOException (java.io.IOException)4 Taxa (dr.evolution.util.Taxa)3 BranchModel (dr.evomodel.branchmodel.BranchModel)3