use of dr.evomodel.substmodel.nucleotide.TN93 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;
}
use of dr.evomodel.substmodel.nucleotide.TN93 in project beast-mcmc by beast-dev.
the class TN93Test method testTN93.
public void testTN93() {
Parameter kappa1 = new Parameter.Default(5.0);
Parameter kappa2 = new Parameter.Default(2.0);
double[] pi = new double[] { 0.40, 0.20, 0.30, 0.10 };
double time = 0.1;
FrequencyModel freqModel = new FrequencyModel(Nucleotides.INSTANCE, pi);
TN93 tn = new TN93(kappa1, kappa2, freqModel);
EigenDecomposition decomp = tn.getEigenDecomposition();
Vector eval = new Vector(decomp.getEigenValues());
System.out.println("Eval = " + eval);
double[] probs = new double[16];
tn.getTransitionProbabilities(time, probs);
System.out.println("new probs = " + new Vector(probs));
// check against old implementation
dr.oldevomodel.substmodel.FrequencyModel oldFreq = new dr.oldevomodel.substmodel.FrequencyModel(Nucleotides.INSTANCE, pi);
dr.oldevomodel.substmodel.TN93 oldTN = new dr.oldevomodel.substmodel.TN93(kappa1, kappa2, oldFreq);
double[] oldProbs = new double[16];
oldTN.getTransitionProbabilities(time, oldProbs);
System.out.println("old probs = " + new Vector(oldProbs));
assertEquals(probs, oldProbs, 10E-6);
}
use of dr.evomodel.substmodel.nucleotide.TN93 in project beast-mcmc by beast-dev.
the class TN93Parser method parseXMLObject.
public Object parseXMLObject(XMLObject xo) throws XMLParseException {
Parameter kappa1Param = (Parameter) xo.getElementFirstChild(KAPPA1);
Parameter kappa2Param = (Parameter) xo.getElementFirstChild(KAPPA2);
FrequencyModel freqModel = (FrequencyModel) xo.getElementFirstChild(FREQUENCIES);
Logger.getLogger("dr.evomodel").info("\nCreating TN93 substitution model. Initial kappa = " + kappa1Param.getValue(0) + "," + kappa2Param.getValue(0));
return new TN93(kappa1Param, kappa2Param, freqModel);
}
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