Examples with CompoundParameter dr.inference.model.CompoundParameter used on opensource projects

Example 1 with CompoundParameter

use of dr.inference.model.CompoundParameter in project beast-mcmc by beast-dev.

the class EllipticalSliceOperatorParser method parseXMLObject.

public Object parseXMLObject(XMLObject xo) throws XMLParseException {
    final double weight = xo.getDoubleAttribute(MCMCOperator.WEIGHT);
    final Parameter variable = (Parameter) xo.getChild(Parameter.class);
    boolean drawByRowTemp = false;
    if (xo.hasAttribute(DRAW_BY_ROW))
        drawByRowTemp = xo.getBooleanAttribute(DRAW_BY_ROW);
    final boolean drawByRow = drawByRowTemp;
    boolean signal = xo.getAttribute(SIGNAL_CONSTITUENT_PARAMETERS, true);
    if (!signal && !(variable instanceof CompoundParameter))
        signal = true;
    double bracketAngle = xo.getAttribute(BRACKET_ANGLE, 0.0);
    boolean translationInvariant = xo.getAttribute(TRANSLATION_INVARIANT, false);
    boolean rotationInvariant = xo.getAttribute(ROTATION_INVARIANT, false);
    GaussianProcessRandomGenerator gaussianProcess = (GaussianProcessRandomGenerator) xo.getChild(GaussianProcessRandomGenerator.class);
    if (gaussianProcess == null) {
        final MultivariateDistributionLikelihood likelihood = (MultivariateDistributionLikelihood) xo.getChild(MultivariateDistributionLikelihood.class);
        if (!(likelihood.getDistribution() instanceof GaussianProcessRandomGenerator)) {
            throw new XMLParseException("Elliptical slice sampling only works for multivariate normally distributed random variables");
        }
        if (likelihood.getDistribution() instanceof MultivariateNormalDistribution)
            gaussianProcess = (MultivariateNormalDistribution) likelihood.getDistribution();
        if (likelihood.getDistribution() instanceof MultivariateNormalDistributionModel)
            gaussianProcess = (MultivariateNormalDistributionModel) likelihood.getDistribution();
    }
    EllipticalSliceOperator operator = new EllipticalSliceOperator(variable, gaussianProcess, drawByRow, signal, bracketAngle, translationInvariant, rotationInvariant);
    operator.setWeight(weight);
    return operator;
}

Example 2 with CompoundParameter

use of dr.inference.model.CompoundParameter in project beast-mcmc by beast-dev.

the class ARGAddRemoveOperatorTest method getSchedule.

public static OperatorSchedule getSchedule(ARGModel arg) {
    CompoundParameter rootHeight = (CompoundParameter) arg.createNodeHeightsParameter(true, false, false);
    CompoundParameter internalHeights = (CompoundParameter) arg.createNodeHeightsParameter(false, true, false);
    //CompoundParameter allInternalNodeHeights = (CompoundParameter) arg.createNodeHeightsParameter(true, true, false);
    //        CompoundParameter rates = (CompoundParameter) arg.createNodeRatesParameter(false, true, true);
    //        ARGAddRemoveEventOperator operator1 = new ARGAddRemoveEventOperator(arg, 5, 0.5,
    //                CoercionMode.COERCION_ON, internalHeights, allInternalNodeHeights, rates, 0.9, null,-1);
    ScaleOperator operator2 = new ScaleOperator(rootHeight, 0.75, CoercionMode.COERCION_ON, 5);
    ScaleOperator operator3 = new ScaleOperator(internalHeights, 0.75, CoercionMode.COERCION_ON, 10);
    OperatorSchedule schedule = new SimpleOperatorSchedule();
    //        schedule.addOperator(operator1);
    schedule.addOperator(operator2);
    schedule.addOperator(operator3);
    return schedule;
//		<scaleOperator id="rootOperator" scaleFactor="0.5"
//			weight="10">
//			<parameter idref="argModel.rootHeight" />
//		</scaleOperator>
//
//		<scaleOperator scaleFactor="0.95" weight="10">
//			<parameter idref="argModel.internalNodeHeights" />
//		</scaleOperator>
//            <ARGEventOperator weight="5" addProbability="0.5"
//			autoOptimize="false">
//			<argTreeModel idref="argModel" />
//			<internalNodes>
//				<parameter idref="argModel.internalNodeHeights" />
//			</internalNodes>
//			<internalNodesPlusRoot>
//				<parameter idref="argModel.allInternalNodeHeights" />
//			</internalNodesPlusRoot>
//			<nodeRates>
//				<parameter idref="argModel.rates" />
//			</nodeRates>
//		</ARGEventOperator>
}

Example 3 with CompoundParameter

use of dr.inference.model.CompoundParameter in project beast-mcmc by beast-dev.

the class ContinuousDataLikelihoodParser method parseXMLObject.

public Object parseXMLObject(XMLObject xo) throws XMLParseException {
    TreeModel treeModel = (TreeModel) xo.getChild(TreeModel.class);
    MultivariateDiffusionModel diffusionModel = (MultivariateDiffusionModel) xo.getChild(MultivariateDiffusionModel.class);
    BranchRateModel rateModel = (BranchRateModel) xo.getChild(BranchRateModel.class);
    TreeTraitParserUtilities utilities = new TreeTraitParserUtilities();
    String traitName = TreeTraitParserUtilities.DEFAULT_TRAIT_NAME;
    TreeTraitParserUtilities.TraitsAndMissingIndices returnValue = utilities.parseTraitsFromTaxonAttributes(xo, traitName, treeModel, true);
    CompoundParameter traitParameter = returnValue.traitParameter;
    List<Integer> missingIndices = returnValue.missingIndices;
    Parameter sampleMissingParameter = returnValue.sampleMissingParameter;
    traitName = returnValue.traitName;
    final int dim = diffusionModel.getPrecisionmatrix().length;
    PrecisionType precisionType = PrecisionType.SCALAR;
    if (missingIndices.size() > 0 && !xo.getAttribute(FORCE_COMPLETELY_MISSING, false)) {
        precisionType = PrecisionType.FULL;
    }
    System.err.println("Using precisionType == " + precisionType + " for data model.");
    ContinuousTraitDataModel dataModel = new ContinuousTraitDataModel(traitName, traitParameter, missingIndices, dim, precisionType);
    ConjugateRootTraitPrior rootPrior = ConjugateRootTraitPrior.parseConjugateRootTraitPrior(xo, dim);
    boolean useTreeLength = xo.getAttribute(USE_TREE_LENGTH, false);
    boolean scaleByTime = xo.getAttribute(SCALE_BY_TIME, false);
    if (rateModel == null) {
        rateModel = new DefaultBranchRateModel();
    }
    ContinuousRateTransformation rateTransformation = new ContinuousRateTransformation.Default(treeModel, scaleByTime, useTreeLength);
    ContinuousDataLikelihoodDelegate delegate = new ContinuousDataLikelihoodDelegate(treeModel, diffusionModel, dataModel, rootPrior, rateTransformation, rateModel);
    TreeDataLikelihood treeDataLikelihood = new TreeDataLikelihood(delegate, treeModel, rateModel);
    boolean reconstructTraits = xo.getAttribute(RECONSTRUCT_TRAITS, true);
    if (reconstructTraits) {
        if (missingIndices.size() == 0) {
            ProcessSimulationDelegate simulationDelegate = new ProcessSimulationDelegate.ConditionalOnTipsRealizedDelegate(traitName, treeModel, diffusionModel, dataModel, rootPrior, rateTransformation, rateModel, delegate);
            TreeTraitProvider traitProvider = new ProcessSimulation(traitName, treeDataLikelihood, simulationDelegate);
            treeDataLikelihood.addTraits(traitProvider.getTreeTraits());
        } else {
            ProcessSimulationDelegate simulationDelegate = delegate.getPrecisionType() == PrecisionType.SCALAR ? new ProcessSimulationDelegate.ConditionalOnTipsRealizedDelegate(traitName, treeModel, diffusionModel, dataModel, rootPrior, rateTransformation, rateModel, delegate) : new ProcessSimulationDelegate.MultivariateConditionalOnTipsRealizedDelegate(traitName, treeModel, diffusionModel, dataModel, rootPrior, rateTransformation, rateModel, delegate);
            TreeTraitProvider traitProvider = new ProcessSimulation(traitName, treeDataLikelihood, simulationDelegate);
            treeDataLikelihood.addTraits(traitProvider.getTreeTraits());
            ProcessSimulationDelegate fullConditionalDelegate = new ProcessSimulationDelegate.TipRealizedValuesViaFullConditionalDelegate(traitName, treeModel, diffusionModel, dataModel, rootPrior, rateTransformation, rateModel, delegate);
            treeDataLikelihood.addTraits(new ProcessSimulation(("fc." + traitName), treeDataLikelihood, fullConditionalDelegate).getTreeTraits());
        //                String partialTraitName = getPartiallyMissingTraitName(traitName);
        //
        //                ProcessSimulationDelegate parialSimulationDelegate = new ProcessSimulationDelegate.ConditionalOnPartiallyMissingTipsDelegate(partialTraitName,
        //                        treeModel, diffusionModel, dataModel, rootPrior, rateTransformation, rateModel, delegate);
        //
        //                TreeTraitProvider partialTraitProvider = new ProcessSimulation(partialTraitName,
        //                        treeDataLikelihood, parialSimulationDelegate);
        //
        //                treeDataLikelihood.addTraits(partialTraitProvider.getTreeTraits());
        }
    }
    return treeDataLikelihood;
}

Example 4 with CompoundParameter

use of dr.inference.model.CompoundParameter in project beast-mcmc by beast-dev.

the class LeafTraitExtractorParser method parseXMLObject.

@Override
public Object parseXMLObject(XMLObject xo) throws XMLParseException {
    TreeModel model = (TreeModel) xo.getChild(TreeModel.class);
    final CompoundParameter allTraits = (CompoundParameter) xo.getChild(CompoundParameter.class);
    String taxonString = (String) xo.getAttribute(TreeModelParser.TAXON);
    final int leafIndex = model.getTaxonIndex(taxonString);
    if (leafIndex == -1) {
        throw new XMLParseException("Unable to find taxon '" + taxonString + "' in trees.");
    }
    final Parameter leafTrait = allTraits.getParameter(leafIndex);
    boolean setBounds = xo.getAttribute(SET_BOUNDS, true);
    if (setBounds) {
        Parameter.DefaultBounds bound = new Parameter.DefaultBounds(Double.MAX_VALUE, -Double.MAX_VALUE, leafTrait.getDimension());
        leafTrait.addBounds(bound);
    }
    return leafTrait;
}

Example 5 with CompoundParameter

use of dr.inference.model.CompoundParameter in project beast-mcmc by beast-dev.

the class PartitionedTreeModelParser method parseXMLObject.

/**
     * @return a tree object based on the XML element it was passed.
     */
public Object parseXMLObject(XMLObject xo) throws XMLParseException {
    Tree tree = (Tree) xo.getChild(Tree.class);
    AbstractOutbreak outbreak = (AbstractOutbreak) xo.getElementFirstChild(OUTBREAK);
    PartitionedTreeModel treeModel;
    if (xo.hasAttribute(STARTING_TT_FILE)) {
        treeModel = new PartitionedTreeModel(xo.getId(), tree, outbreak, xo.getStringAttribute(STARTING_TT_FILE));
    } else {
        treeModel = new PartitionedTreeModel(xo.getId(), tree, outbreak);
    }
    Logger.getLogger("dr.evomodel").info("Creating the partitioned tree model, '" + xo.getId() + "'");
    for (int i = 0; i < xo.getChildCount(); i++) {
        if (xo.getChild(i) instanceof XMLObject) {
            XMLObject cxo = (XMLObject) xo.getChild(i);
            if (cxo.getName().equals(ROOT_HEIGHT)) {
                ParameterParser.replaceParameter(cxo, treeModel.getRootHeightParameter());
            } else if (cxo.getName().equals(LEAF_HEIGHT)) {
                String taxonName;
                if (cxo.hasAttribute(TAXON)) {
                    taxonName = cxo.getStringAttribute(TAXON);
                } else {
                    throw new XMLParseException("taxa element missing from leafHeight element in treeModel element");
                }
                int index = treeModel.getTaxonIndex(taxonName);
                if (index == -1) {
                    throw new XMLParseException("taxon " + taxonName + " not found for leafHeight element in treeModel element");
                }
                NodeRef node = treeModel.getExternalNode(index);
                Parameter newParameter = treeModel.getLeafHeightParameter(node);
                ParameterParser.replaceParameter(cxo, newParameter);
                Taxon taxon = treeModel.getTaxon(index);
                setPrecisionBounds(newParameter, taxon);
            } else if (cxo.getName().equals(LEAF_HEIGHTS)) {
                // get a set of leaf height parameters out as a compound parameter...
                TaxonList taxa = (TaxonList) cxo.getChild(TaxonList.class);
                Parameter offsetParameter = (Parameter) cxo.getChild(Parameter.class);
                CompoundParameter leafHeights = new CompoundParameter("leafHeights");
                for (Taxon taxon : taxa) {
                    int index = treeModel.getTaxonIndex(taxon);
                    if (index == -1) {
                        throw new XMLParseException("taxon " + taxon.getId() + " not found for leafHeight element in treeModel element");
                    }
                    NodeRef node = treeModel.getExternalNode(index);
                    Parameter newParameter = treeModel.getLeafHeightParameter(node);
                    leafHeights.addParameter(newParameter);
                    setPrecisionBounds(newParameter, taxon);
                }
                ParameterParser.replaceParameter(cxo, leafHeights);
            } else if (cxo.getName().equals(NODE_HEIGHTS)) {
                boolean rootNode = cxo.getAttribute(ROOT_NODE, false);
                boolean internalNodes = cxo.getAttribute(INTERNAL_NODES, false);
                boolean leafNodes = cxo.getAttribute(LEAF_NODES, false);
                if (!rootNode && !internalNodes && !leafNodes) {
                    throw new XMLParseException("one or more of root, internal or leaf nodes must be selected for the nodeHeights element");
                }
                ParameterParser.replaceParameter(cxo, treeModel.createNodeHeightsParameter(rootNode, internalNodes, leafNodes));
            } else if (cxo.getName().equals(NODE_RATES)) {
                boolean rootNode = cxo.getAttribute(ROOT_NODE, false);
                boolean internalNodes = cxo.getAttribute(INTERNAL_NODES, false);
                boolean leafNodes = cxo.getAttribute(LEAF_NODES, false);
                double[] initialValues = null;
                if (cxo.hasAttribute(INITIAL_VALUE)) {
                    initialValues = cxo.getDoubleArrayAttribute(INITIAL_VALUE);
                }
                if (!rootNode && !internalNodes && !leafNodes) {
                    throw new XMLParseException("one or more of root, internal or leaf nodes must be selected for the nodeRates element");
                }
                ParameterParser.replaceParameter(cxo, treeModel.createNodeRatesParameter(initialValues, rootNode, internalNodes, leafNodes));
            } else if (cxo.getName().equals(NODE_TRAITS)) {
                boolean rootNode = cxo.getAttribute(ROOT_NODE, false);
                boolean internalNodes = cxo.getAttribute(INTERNAL_NODES, false);
                boolean leafNodes = cxo.getAttribute(LEAF_NODES, false);
                boolean fireTreeEvents = cxo.getAttribute(FIRE_TREE_EVENTS, false);
                String name = cxo.getAttribute(NAME, "trait");
                int dim = cxo.getAttribute(MULTIVARIATE_TRAIT, 1);
                double[] initialValues = null;
                if (cxo.hasAttribute(INITIAL_VALUE)) {
                    initialValues = cxo.getDoubleArrayAttribute(INITIAL_VALUE);
                }
                if (!rootNode && !internalNodes && !leafNodes) {
                    throw new XMLParseException("one or more of root, internal or leaf nodes must be selected for the nodeTraits element");
                }
                ParameterParser.replaceParameter(cxo, treeModel.createNodeTraitsParameter(name, dim, initialValues, rootNode, internalNodes, leafNodes, fireTreeEvents));
            } else if (cxo.getName().equals(LEAF_TRAIT)) {
                String name = cxo.getAttribute(NAME, "trait");
                String taxonName;
                if (cxo.hasAttribute(TAXON)) {
                    taxonName = cxo.getStringAttribute(TAXON);
                } else {
                    throw new XMLParseException("taxa element missing from leafTrait element in treeModel element");
                }
                int index = treeModel.getTaxonIndex(taxonName);
                if (index == -1) {
                    throw new XMLParseException("taxon '" + taxonName + "' not found for leafTrait element in treeModel element");
                }
                NodeRef node = treeModel.getExternalNode(index);
                Parameter parameter = treeModel.getNodeTraitParameter(node, name);
                if (parameter == null)
                    throw new XMLParseException("trait '" + name + "' not found for leafTrait (taxon, " + taxonName + ") element in treeModel element");
                ParameterParser.replaceParameter(cxo, parameter);
            } else {
                if (!cxo.getName().equals(OUTBREAK)) {
                    throw new XMLParseException("illegal child element in " + getParserName() + ": " + cxo.getName());
                }
            }
        } else if (xo.getChild(i) instanceof Tree) {
        // do nothing - already handled
        } else {
            throw new XMLParseException("illegal child element in  " + getParserName() + ": " + xo.getChildName(i) + " " + xo.getChild(i));
        }
    }
    // AR this is doubling up the number of bounds on each node.
    //        treeModel.setupHeightBounds();
    //System.err.println("done constructing treeModel");
    Logger.getLogger("dr.evomodel").info("  initial tree topology = " + TreeUtils.uniqueNewick(treeModel, treeModel.getRoot()));
    Logger.getLogger("dr.evomodel").info("  tree height = " + treeModel.getNodeHeight(treeModel.getRoot()));
    return treeModel;
}