Examples with EmpiricalRateMatrix dr.evomodel.substmodel.EmpiricalRateMatrix used on opensource projects

Example 1 with EmpiricalRateMatrix

use of dr.evomodel.substmodel.EmpiricalRateMatrix in project beast-mcmc by beast-dev.

the class BeagleSeqSimTest method simulateAminoAcid.

// END: simulateThreePartitions
static void simulateAminoAcid() {
    try {
        System.out.println("Test case 4: simulateAminoAcid");
        MathUtils.setSeed(666);
        int sequenceLength = 10;
        ArrayList<Partition> partitionsList = new ArrayList<Partition>();
        // create tree
        NewickImporter importer = new NewickImporter("(SimSeq1:73.7468,(SimSeq2:25.256989999999995,SimSeq3:45.256989999999995):18.48981);");
        Tree tree = importer.importTree(null);
        TreeModel treeModel = new TreeModel(tree);
        // create site model
        GammaSiteRateModel siteRateModel = new GammaSiteRateModel("siteModel");
        // create branch rate model
        BranchRateModel branchRateModel = new DefaultBranchRateModel();
        // create Frequency Model
        Parameter freqs = new Parameter.Default(new double[] { 0.05, 0.05, 0.05, 0.05, 0.05, 0.05, 0.05, 0.05, 0.05, 0.05, 0.05, 0.05, 0.05, 0.05, 0.05, 0.05, 0.05, 0.05, 0.05, 0.05 });
        FrequencyModel freqModel = new FrequencyModel(AminoAcids.INSTANCE, freqs);
        // create substitution model
        EmpiricalRateMatrix rateMatrix = Blosum62.INSTANCE;
        EmpiricalAminoAcidModel empiricalAminoAcidModel = new EmpiricalAminoAcidModel(rateMatrix, freqModel);
        HomogeneousBranchModel substitutionModel = new HomogeneousBranchModel(empiricalAminoAcidModel);
        // create partition
        Partition partition1 = new //
        Partition(//
        treeModel, //
        substitutionModel, //
        siteRateModel, //
        branchRateModel, //
        freqModel, // from
        0, // to
        sequenceLength - 1, // every
        1);
        partitionsList.add(partition1);
        // feed to sequence simulator and generate data
        BeagleSequenceSimulator simulator = new BeagleSequenceSimulator(partitionsList);
        System.out.println(simulator.simulate(simulateInPar, false).toString());
    } catch (Exception e) {
        e.printStackTrace();
        System.exit(-1);
    }
// END: try-catch
}

Example 2 with EmpiricalRateMatrix

use of dr.evomodel.substmodel.EmpiricalRateMatrix in project beast-mcmc by beast-dev.

the class PartitionData method createBranchModel.

public BranchModel createBranchModel() {
    BranchModel branchModel = null;
    if (this.substitutionModelIndex == 0) {
        // HKY
        Parameter kappa = new Parameter.Default(1, substitutionParameterValues[0]);
        FrequencyModel frequencyModel = this.createFrequencyModel();
        HKY hky = new HKY(kappa, frequencyModel);
        branchModel = new HomogeneousBranchModel(hky);
    } else if (this.substitutionModelIndex == 1) {
        // GTR
        Parameter ac = new Parameter.Default(1, substitutionParameterValues[1]);
        Parameter ag = new Parameter.Default(1, substitutionParameterValues[2]);
        Parameter at = new Parameter.Default(1, substitutionParameterValues[3]);
        Parameter cg = new Parameter.Default(1, substitutionParameterValues[4]);
        Parameter ct = new Parameter.Default(1, substitutionParameterValues[5]);
        Parameter gt = new Parameter.Default(1, substitutionParameterValues[6]);
        FrequencyModel frequencyModel = this.createFrequencyModel();
        GTR gtr = new GTR(ac, ag, at, cg, ct, gt, frequencyModel);
        branchModel = new HomogeneousBranchModel(gtr);
    } else if (this.substitutionModelIndex == 2) {
        // TN93
        Parameter kappa1 = new Parameter.Default(1, substitutionParameterValues[7]);
        Parameter kappa2 = new Parameter.Default(1, substitutionParameterValues[8]);
        FrequencyModel frequencyModel = this.createFrequencyModel();
        TN93 tn93 = new TN93(kappa1, kappa2, frequencyModel);
        branchModel = new HomogeneousBranchModel(tn93);
    } else if (this.substitutionModelIndex == 3) {
        // Yang Codon Model
        FrequencyModel frequencyModel = this.createFrequencyModel();
        Parameter kappa = new Parameter.Default(1, substitutionParameterValues[9]);
        Parameter omega = new Parameter.Default(1, substitutionParameterValues[10]);
        GY94CodonModel yangCodonModel = new GY94CodonModel(Codons.UNIVERSAL, omega, kappa, frequencyModel);
        branchModel = new HomogeneousBranchModel(yangCodonModel);
    } else if (this.substitutionModelIndex == 4) {
        // MG94CodonModel
        FrequencyModel frequencyModel = this.createFrequencyModel();
        Parameter alpha = new Parameter.Default(1, substitutionParameterValues[11]);
        Parameter beta = new Parameter.Default(1, substitutionParameterValues[12]);
        Parameter kappa = new Parameter.Default(1, substitutionParameterValues[13]);
        MG94HKYCodonModel mg94 = new MG94HKYCodonModel(Codons.UNIVERSAL, alpha, beta, kappa, frequencyModel);
        branchModel = new HomogeneousBranchModel(mg94);
    } else if (this.substitutionModelIndex == 5) {
        // Blosum62
        FrequencyModel frequencyModel = this.createFrequencyModel();
        EmpiricalRateMatrix rateMatrix = Blosum62.INSTANCE;
        EmpiricalAminoAcidModel empiricalAminoAcidModel = new EmpiricalAminoAcidModel(rateMatrix, frequencyModel);
        branchModel = new HomogeneousBranchModel(empiricalAminoAcidModel);
    } else if (this.substitutionModelIndex == 6) {
        // CPREV
        FrequencyModel frequencyModel = this.createFrequencyModel();
        EmpiricalRateMatrix rateMatrix = CPREV.INSTANCE;
        EmpiricalAminoAcidModel empiricalAminoAcidModel = new EmpiricalAminoAcidModel(rateMatrix, frequencyModel);
        branchModel = new HomogeneousBranchModel(empiricalAminoAcidModel);
    } else if (this.substitutionModelIndex == 7) {
        // Dayhoff
        FrequencyModel frequencyModel = this.createFrequencyModel();
        EmpiricalRateMatrix rateMatrix = Dayhoff.INSTANCE;
        EmpiricalAminoAcidModel empiricalAminoAcidModel = new EmpiricalAminoAcidModel(rateMatrix, frequencyModel);
        branchModel = new HomogeneousBranchModel(empiricalAminoAcidModel);
    } else if (this.substitutionModelIndex == 8) {
        // JTT
        FrequencyModel frequencyModel = this.createFrequencyModel();
        EmpiricalRateMatrix rateMatrix = JTT.INSTANCE;
        EmpiricalAminoAcidModel empiricalAminoAcidModel = new EmpiricalAminoAcidModel(rateMatrix, frequencyModel);
        branchModel = new HomogeneousBranchModel(empiricalAminoAcidModel);
    } else if (this.substitutionModelIndex == 9) {
        // LG
        FrequencyModel frequencyModel = this.createFrequencyModel();
        EmpiricalRateMatrix rateMatrix = LG.INSTANCE;
        EmpiricalAminoAcidModel empiricalAminoAcidModel = new EmpiricalAminoAcidModel(rateMatrix, frequencyModel);
        branchModel = new HomogeneousBranchModel(empiricalAminoAcidModel);
    } else if (this.substitutionModelIndex == 10) {
        // MTREV
        FrequencyModel frequencyModel = this.createFrequencyModel();
        EmpiricalRateMatrix rateMatrix = MTREV.INSTANCE;
        EmpiricalAminoAcidModel empiricalAminoAcidModel = new EmpiricalAminoAcidModel(rateMatrix, frequencyModel);
        branchModel = new HomogeneousBranchModel(empiricalAminoAcidModel);
    } else if (this.substitutionModelIndex == 11) {
        // WAG
        FrequencyModel frequencyModel = this.createFrequencyModel();
        EmpiricalRateMatrix rateMatrix = WAG.INSTANCE;
        EmpiricalAminoAcidModel empiricalAminoAcidModel = new EmpiricalAminoAcidModel(rateMatrix, frequencyModel);
        branchModel = new HomogeneousBranchModel(empiricalAminoAcidModel);
    } else {
        System.out.println("Not yet implemented");
    }
    return branchModel;
}

Example 3 with EmpiricalRateMatrix

use of dr.evomodel.substmodel.EmpiricalRateMatrix in project beast-mcmc by beast-dev.

the class EmpiricalAminoAcidModelParser method parseXMLObject.

public Object parseXMLObject(XMLObject xo) throws XMLParseException {
    FrequencyModel freqModel = null;
    if (xo.hasAttribute(FREQUENCIES)) {
        XMLObject cxo = xo.getChild(FREQUENCIES);
        freqModel = (FrequencyModel) cxo.getChild(FrequencyModel.class);
    }
    EmpiricalRateMatrix rateMatrix = null;
    String type = xo.getStringAttribute(TYPE);
    if (type.equals(AminoAcidModelType.BLOSUM_62.getXMLName())) {
        rateMatrix = Blosum62.INSTANCE;
    } else if (type.equals(AminoAcidModelType.DAYHOFF.getXMLName())) {
        rateMatrix = Dayhoff.INSTANCE;
    } else if (type.equals(AminoAcidModelType.JTT.getXMLName())) {
        rateMatrix = JTT.INSTANCE;
    } else if (type.equals(AminoAcidModelType.MT_REV_24.getXMLName())) {
        rateMatrix = MTREV.INSTANCE;
    } else if (type.equals(AminoAcidModelType.CP_REV_45.getXMLName())) {
        rateMatrix = CPREV.INSTANCE;
    } else if (type.equals(AminoAcidModelType.WAG.getXMLName())) {
        rateMatrix = WAG.INSTANCE;
    } else if (type.equals(AminoAcidModelType.LG.getXMLName())) {
        rateMatrix = LG.INSTANCE;
    } else if (type.equals(AminoAcidModelType.FLU.getXMLName())) {
        rateMatrix = FLU.INSTANCE;
    } else {
        throw new XMLParseException("Unrecognized empirical amino acid model: " + type);
    }
    return new EmpiricalAminoAcidModel(rateMatrix, freqModel);
}