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

Example 6 with DataLikelihoodDelegate

use of dr.evomodel.treedatalikelihood.DataLikelihoodDelegate 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 DataLikelihoodDelegate

use of dr.evomodel.treedatalikelihood.DataLikelihoodDelegate 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 DataLikelihoodDelegate

use of dr.evomodel.treedatalikelihood.DataLikelihoodDelegate 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 9 with DataLikelihoodDelegate

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

the class FullyConjugateTreeTipsPotentialDerivativeParser method parseXMLObject.

@Override
public Object parseXMLObject(XMLObject xo) throws XMLParseException {
    // String name = xo.hasId() ? xo.getId() : FULLY_CONJUGATE_TREE_TIPS_POTENTIAL_DERIVATIVE2;
    String traitName = xo.getAttribute(TRAIT_NAME, DEFAULT_TRAIT_NAME);
    // Object co = xo.getChild(0);
    final FullyConjugateMultivariateTraitLikelihood fcTreeLikelihood = (FullyConjugateMultivariateTraitLikelihood) xo.getChild(FullyConjugateMultivariateTraitLikelihood.class);
    final TreeDataLikelihood treeDataLikelihood = (TreeDataLikelihood) xo.getChild(TreeDataLikelihood.class);
    Parameter mask = null;
    if (xo.hasChildNamed(MASKING)) {
        mask = (Parameter) xo.getElementFirstChild(MASKING);
    }
    if (fcTreeLikelihood != null) {
        return new FullyConjugateTreeTipsPotentialDerivative(fcTreeLikelihood, mask);
    } else if (treeDataLikelihood != null) {
        DataLikelihoodDelegate delegate = treeDataLikelihood.getDataLikelihoodDelegate();
        if (!(delegate instanceof ContinuousDataLikelihoodDelegate)) {
            throw new XMLParseException("May not provide a sequence data likelihood to compute tip trait gradient");
        }
        final ContinuousDataLikelihoodDelegate continuousData = (ContinuousDataLikelihoodDelegate) delegate;
        return new TreeTipGradient(traitName, treeDataLikelihood, continuousData, mask);
    } else {
        throw new XMLParseException("Must provide a tree likelihood");
    }
}

Example 10 with DataLikelihoodDelegate

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

the class TreeDataLikelihoodParser method createTreeDataLikelihood.

protected Likelihood createTreeDataLikelihood(List<PatternList> patternLists, List<BranchModel> branchModels, List<SiteRateModel> siteRateModels, Tree treeModel, BranchRateModel branchRateModel, TipStatesModel tipStatesModel, boolean useAmbiguities, boolean preferGPU, PartialsRescalingScheme scalingScheme, boolean delayRescalingUntilUnderflow, PreOrderSettings settings) throws XMLParseException {
    if (tipStatesModel != null) {
        throw new XMLParseException("Tip State Error models are not supported yet with TreeDataLikelihood");
    }
    List<Taxon> treeTaxa = treeModel.asList();
    List<Taxon> patternTaxa = patternLists.get(0).asList();
    if (!patternTaxa.containsAll(treeTaxa)) {
        throw new XMLParseException("TreeModel " + treeModel.getId() + " contains more taxa (" + treeModel.getExternalNodeCount() + ") than the partition pattern list (" + patternTaxa.size() + ").");
    }
    if (!treeTaxa.containsAll(patternTaxa)) {
        throw new XMLParseException("TreeModel " + treeModel.getId() + " contains fewer taxa (" + treeModel.getExternalNodeCount() + ") than the partition pattern list (" + patternTaxa.size() + ").");
    }
    boolean useBeagle3MultiPartition = false;
    if (patternLists.size() > 1) {
        // will currently recommend true if using GPU, CUDA or OpenCL.
        useBeagle3MultiPartition = MultiPartitionDataLikelihoodDelegate.IS_MULTI_PARTITION_RECOMMENDED();
        if (System.getProperty("USE_BEAGLE3_EXTENSIONS") != null) {
            useBeagle3MultiPartition = Boolean.parseBoolean(System.getProperty("USE_BEAGLE3_EXTENSIONS"));
        }
        if (System.getProperty("beagle.multipartition.extensions") != null && !System.getProperty("beagle.multipartition.extensions").equals("auto")) {
            useBeagle3MultiPartition = Boolean.parseBoolean(System.getProperty("beagle.multipartition.extensions"));
        }
    }
    boolean useJava = Boolean.parseBoolean(System.getProperty("java.only", "false"));
    int threadCount = -1;
    int beagleThreadCount = -1;
    if (System.getProperty(BEAGLE_THREAD_COUNT) != null) {
        beagleThreadCount = Integer.parseInt(System.getProperty(BEAGLE_THREAD_COUNT));
    }
    if (beagleThreadCount == -1) {
        if (System.getProperty(THREAD_COUNT) != null) {
            threadCount = Integer.parseInt(System.getProperty(THREAD_COUNT));
        }
    }
    if (useBeagle3MultiPartition && !useJava) {
        if (beagleThreadCount == -1 && threadCount >= 0) {
            System.setProperty(BEAGLE_THREAD_COUNT, Integer.toString(threadCount));
        }
        try {
            DataLikelihoodDelegate dataLikelihoodDelegate = new MultiPartitionDataLikelihoodDelegate(treeModel, patternLists, branchModels, siteRateModels, useAmbiguities, scalingScheme, delayRescalingUntilUnderflow);
            return new TreeDataLikelihood(dataLikelihoodDelegate, treeModel, branchRateModel);
        } catch (DataLikelihoodDelegate.DelegateTypeException dte) {
            useBeagle3MultiPartition = false;
        }
    }
    // The multipartition data likelihood isn't available so make a set of single partition data likelihoods
    List<Likelihood> treeDataLikelihoods = new ArrayList<Likelihood>();
    // Todo: allow for different number of threads per beagle instance according to pattern counts
    if (beagleThreadCount == -1 && threadCount >= 0) {
        System.setProperty(BEAGLE_THREAD_COUNT, Integer.toString(threadCount / patternLists.size()));
    }
    for (int i = 0; i < patternLists.size(); i++) {
        DataLikelihoodDelegate dataLikelihoodDelegate = new BeagleDataLikelihoodDelegate(treeModel, patternLists.get(i), branchModels.get(i), siteRateModels.get(i), useAmbiguities, preferGPU, scalingScheme, delayRescalingUntilUnderflow, settings);
        treeDataLikelihoods.add(new TreeDataLikelihood(dataLikelihoodDelegate, treeModel, branchRateModel));
    }
    if (treeDataLikelihoods.size() == 1) {
        return treeDataLikelihoods.get(0);
    }
    return new CompoundLikelihood(treeDataLikelihoods);
}