Examples with TreeDataLikelihood dr.evomodel.treedatalikelihood.TreeDataLikelihood used on opensource projects

Example 6 with TreeDataLikelihood

use of dr.evomodel.treedatalikelihood.TreeDataLikelihood in project beast-mcmc by beast-dev.

the class NodeHeightGradientParser method parseXMLObject.

public Object parseXMLObject(XMLObject xo) throws XMLParseException {
    String traitName = xo.getAttribute(TRAIT_NAME, DEFAULT_TRAIT_NAME);
    final TreeDataLikelihood treeDataLikelihood = (TreeDataLikelihood) xo.getChild(TreeDataLikelihood.class);
    BranchRateModel branchRateModel = treeDataLikelihood.getBranchRateModel();
    if (branchRateModel instanceof DefaultBranchRateModel || branchRateModel instanceof ArbitraryBranchRates) {
        Parameter branchRates = null;
        if (branchRateModel instanceof ArbitraryBranchRates) {
            branchRates = ((ArbitraryBranchRates) branchRateModel).getRateParameter();
        }
        DataLikelihoodDelegate delegate = treeDataLikelihood.getDataLikelihoodDelegate();
        if (delegate instanceof ContinuousDataLikelihoodDelegate) {
            throw new XMLParseException("Not yet implemented! ");
        } else if (delegate instanceof BeagleDataLikelihoodDelegate) {
            BeagleDataLikelihoodDelegate beagleData = (BeagleDataLikelihoodDelegate) delegate;
            return new NodeHeightGradientForDiscreteTrait(traitName, treeDataLikelihood, beagleData, branchRates);
        } else {
            throw new XMLParseException("Unknown likelihood delegate type");
        }
    } else {
        throw new XMLParseException("Only implemented for an arbitrary rates model");
    }
}

Example 7 with TreeDataLikelihood

use of dr.evomodel.treedatalikelihood.TreeDataLikelihood in project beast-mcmc by beast-dev.

the class PrecisionGradientParser method parseXMLObject.

@Override
public Object parseXMLObject(XMLObject xo) throws XMLParseException {
    String traitName = xo.getAttribute(TRAIT_NAME, DEFAULT_TRAIT_NAME);
    MatrixParameterInterface parameter = (MatrixParameterInterface) xo.getChild(MatrixParameterInterface.class);
    TreeDataLikelihood treeDataLikelihood = (TreeDataLikelihood) xo.getChild(TreeDataLikelihood.class);
    GradientWrtPrecisionProvider gradientWrtPrecisionProvider;
    ConjugateWishartStatisticsProvider wishartStatistics = (ConjugateWishartStatisticsProvider) xo.getChild(ConjugateWishartStatisticsProvider.class);
    if (wishartStatistics != null) {
        gradientWrtPrecisionProvider = new GradientWrtPrecisionProvider.WishartGradientWrtPrecisionProvider(wishartStatistics);
    } else {
        int dim = treeDataLikelihood.getDataLikelihoodDelegate().getTraitDim();
        Tree tree = treeDataLikelihood.getTree();
        DataLikelihoodDelegate delegate = treeDataLikelihood.getDataLikelihoodDelegate();
        ContinuousDataLikelihoodDelegate continuousData = (ContinuousDataLikelihoodDelegate) delegate;
        ModelExtensionProvider.NormalExtensionProvider extensionProvider = (ModelExtensionProvider.NormalExtensionProvider) xo.getChild(ModelExtensionProvider.NormalExtensionProvider.class);
        ContinuousTraitGradientForBranch traitGradient;
        if (extensionProvider != null) {
            traitGradient = new ContinuousTraitGradientForBranch.SamplingVarianceGradient(dim, tree, continuousData, extensionProvider);
        } else {
            traitGradient = new ContinuousTraitGradientForBranch.ContinuousProcessParameterGradient(dim, tree, continuousData, new ArrayList<>(Arrays.asList(ContinuousTraitGradientForBranch.ContinuousProcessParameterGradient.DerivationParameter.WRT_VARIANCE)));
        }
        BranchSpecificGradient branchSpecificGradient = new BranchSpecificGradient(traitName, treeDataLikelihood, continuousData, traitGradient, parameter);
        gradientWrtPrecisionProvider = new GradientWrtPrecisionProvider.BranchSpecificGradientWrtPrecisionProvider(branchSpecificGradient);
    }
    ParameterMode parameterMode = parseParameterMode(xo);
    return parameterMode.factory(gradientWrtPrecisionProvider, treeDataLikelihood, parameter);
}

Example 8 with TreeDataLikelihood

use of dr.evomodel.treedatalikelihood.TreeDataLikelihood in project beast-mcmc by beast-dev.

the class GaussianProcessFromTreeParser method parseXMLObject.

@Override
public Object parseXMLObject(XMLObject xo) throws XMLParseException {
    FullyConjugateMultivariateTraitLikelihood traitModel = (FullyConjugateMultivariateTraitLikelihood) xo.getChild(FullyConjugateMultivariateTraitLikelihood.class);
    if (traitModel != null) {
        return new GaussianProcessFromTree(traitModel);
    }
    TreeDataLikelihood treeDataLikelihood = (TreeDataLikelihood) xo.getChild(TreeDataLikelihood.class);
    ContinuousDataLikelihoodDelegate dataDelegate = GibbsSampleMissingTraitsOperator.parseContinuousDataLikelihoodDelegate(xo);
    boolean mask = xo.getAttribute(MASK_TO_MISSING, true);
    TreeTipGaussianProcess process = new TreeTipGaussianProcess(dataDelegate.getDataModel().getModelName(), treeDataLikelihood, dataDelegate, null, true);
    return process;
}

Example 9 with TreeDataLikelihood

use of dr.evomodel.treedatalikelihood.TreeDataLikelihood in project beast-mcmc by beast-dev.

the class AttenuationGradientParser method parseXMLObject.

@Override
public Object parseXMLObject(XMLObject xo) throws XMLParseException {
    String traitName = xo.getAttribute(TRAIT_NAME, DEFAULT_TRAIT_NAME);
    MatrixParameterInterface parameter = (MatrixParameterInterface) xo.getChild(MatrixParameterInterface.class);
    TreeDataLikelihood treeDataLikelihood = (TreeDataLikelihood) xo.getChild(TreeDataLikelihood.class);
    DataLikelihoodDelegate delegate = treeDataLikelihood.getDataLikelihoodDelegate();
    int dim = treeDataLikelihood.getDataLikelihoodDelegate().getTraitDim();
    Tree tree = treeDataLikelihood.getTree();
    ContinuousDataLikelihoodDelegate continuousData = (ContinuousDataLikelihoodDelegate) delegate;
    ContinuousTraitGradientForBranch.ContinuousProcessParameterGradient traitGradient = new ContinuousTraitGradientForBranch.ContinuousProcessParameterGradient(dim, tree, continuousData, new ArrayList<ContinuousTraitGradientForBranch.ContinuousProcessParameterGradient.DerivationParameter>(Arrays.asList(ContinuousTraitGradientForBranch.ContinuousProcessParameterGradient.DerivationParameter.WRT_DIAGONAL_SELECTION_STRENGTH)));
    BranchSpecificGradient branchSpecificGradient = new BranchSpecificGradient(traitName, treeDataLikelihood, continuousData, traitGradient, parameter);
    ParameterMode parameterMode = parseParameterMode(xo);
    return parameterMode.factory(branchSpecificGradient, treeDataLikelihood, parameter);
}

Example 10 with TreeDataLikelihood

use of dr.evomodel.treedatalikelihood.TreeDataLikelihood in project beast-mcmc by beast-dev.

the class BranchRateGradientParser method parseXMLObject.

@Override
public Object parseXMLObject(XMLObject xo) throws XMLParseException {
    String traitName = xo.getAttribute(TRAIT_NAME, DEFAULT_TRAIT_NAME);
    boolean useHessian = xo.getAttribute(USE_HESSIAN, false);
    final Object child = xo.getChild(TreeDataLikelihood.class);
    if (child != null) {
        return parseTreeDataLikelihood((TreeDataLikelihood) child, traitName, useHessian);
    } else {
        CompoundLikelihood compoundLikelihood = (CompoundLikelihood) xo.getChild(CompoundLikelihood.class);
        List<GradientWrtParameterProvider> providers = new ArrayList<>();
        for (Likelihood likelihood : compoundLikelihood.getLikelihoods()) {
            if (!(likelihood instanceof TreeDataLikelihood)) {
                throw new XMLParseException("Unknown likelihood type");
            }
            GradientWrtParameterProvider provider = parseTreeDataLikelihood((TreeDataLikelihood) likelihood, traitName, useHessian);
            providers.add(provider);
        }
        checkBranchRateModels(providers);
        return new SumDerivative(providers);
    }
}