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

Example 16 with Likelihood

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

the class MLLoggerParser method parseXMLObject.

public Object parseXMLObject(XMLObject xo) throws XMLParseException {
    Likelihood likelihood = (Likelihood) xo.getElementFirstChild(LIKELIHOOD);
    // logEvery of zero only displays at the end
    int logEvery = xo.getAttribute(LOG_EVERY, 0);
    final PrintWriter pw = getLogFile(xo, getParserName());
    LogFormatter formatter = new TabDelimitedFormatter(pw);
    MLLogger logger = new MLLogger(likelihood, formatter, logEvery);
    if (xo.hasAttribute(TITLE)) {
        logger.setTitle(xo.getStringAttribute(TITLE));
    }
    for (int i = 0; i < xo.getChildCount(); i++) {
        Object child = xo.getChild(i);
        if (child instanceof Columns) {
            logger.addColumns(((Columns) child).getColumns());
        } else if (child instanceof Loggable) {
            logger.add((Loggable) child);
        } else if (child instanceof Identifiable) {
            logger.addColumn(new LogColumn.Default(((Identifiable) child).getId(), child));
        } else {
            logger.addColumn(new LogColumn.Default(child.getClass().toString(), child));
        }
    }
    return logger;
}

Example 17 with Likelihood

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

the class CompoundLikelihoodParser method parseXMLObject.

public Object parseXMLObject(XMLObject xo) throws XMLParseException {
    // the default is -1 threads (automatic thread pool size) but an XML attribute can override it
    int threads = xo.getAttribute(THREADS, -1);
    // both the XML attribute and a system property can override it
    if (System.getProperty("thread.count") != null) {
        threads = Integer.parseInt(System.getProperty("thread.count"));
        if (threads < -1 || threads > 1000) {
            // put an upper limit here - may be unnecessary?
            threads = -1;
        }
    }
    //        }
    List<Likelihood> likelihoods = new ArrayList<Likelihood>();
    for (int i = 0; i < xo.getChildCount(); i++) {
        final Object child = xo.getChild(i);
        if (child instanceof Likelihood) {
            if (likelihoods.contains(child)) {
                throw new XMLParseException("The likelihood element, '" + ((Likelihood) child).getId() + "', is already present in the likelihood or prior density.");
            }
            likelihoods.add((Likelihood) child);
        //            } else if (child instanceof BeagleBranchLikelihoods){
        //                
        //            	//TODO
        //            	likelihoods.addAll( ((BeagleBranchLikelihoods)child).getBranchLikelihoods());
        } else {
            throw new XMLParseException("An element (" + child + ") which is not a likelihood has been added to a " + COMPOUND_LIKELIHOOD + " element");
        }
    }
    CompoundLikelihood compoundLikelihood;
    if (xo.getName().equalsIgnoreCase(LIKELIHOOD)) {
        compoundLikelihood = new CompoundLikelihood(threads, likelihoods);
        switch(threads) {
            case -1:
                Logger.getLogger("dr.evomodel").info("\nLikelihood computation is using an auto sizing thread pool.");
                break;
            case 0:
                Logger.getLogger("dr.evomodel").info("\nLikelihood computation is using a single thread.");
                break;
            default:
                Logger.getLogger("dr.evomodel").info("\nLikelihood computation is using a pool of " + threads + " threads.");
                break;
        }
    } else {
        compoundLikelihood = new CompoundLikelihood(likelihoods);
    }
    return compoundLikelihood;
}

Example 18 with Likelihood

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

the class BeagleBranchLikelihoodParser method parseXMLObject.

@Override
public Object parseXMLObject(XMLObject xo) throws XMLParseException {
    TreeModel treeModel = (TreeModel) xo.getChild(TreeModel.class);
    // if(xo.hasChildNamed(TreeModel.TREE_MODEL)) {
    //
    // treeModel = (TreeModel) xo.getChild(TreeModel.class);
    // }
    Parameter zParameter = (Parameter) xo.getElementFirstChild(DirichletProcessPriorParser.CATEGORIES);
    List<Likelihood> likelihoods = new ArrayList<Likelihood>();
    XMLObject cxo = (XMLObject) xo.getChild(UNIQUE_LIKELIHOODS);
    for (int i = 0; i < cxo.getChildCount(); i++) {
        Likelihood likelihood = (Likelihood) cxo.getChild(i);
        likelihoods.add(likelihood);
    }
    return null;
//		new BeagleBranchLikelihood(
////				treeModel, likelihoods, zParameter
//				);
}

Example 19 with Likelihood

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

the class DirichletProcessOperatorParser method parseXMLObject.

@Override
public Object parseXMLObject(XMLObject xo) throws XMLParseException {
    DirichletProcessPrior dpp = (DirichletProcessPrior) xo.getChild(DirichletProcessPrior.class);
    Likelihood likelihood = (Likelihood) xo.getElementFirstChild(DATA_LOG_LIKELIHOOD);
    Parameter categoriesParameter = (Parameter) xo.getElementFirstChild(DirichletProcessPriorParser.CATEGORIES);
    CountableRealizationsParameter allParameters = (CountableRealizationsParameter) xo.getChild(CountableRealizationsParameter.class);
    CompoundParameter uniquelyRealizedParameters = (CompoundParameter) xo.getChild(CompoundParameter.class);
    int M = xo.getIntegerAttribute(MH_STEPS);
    final double weight = xo.getDoubleAttribute(MCMCOperator.WEIGHT);
    return new // 
    DirichletProcessOperator(// 
    dpp, //
    categoriesParameter, //
    uniquelyRealizedParameters, //
    allParameters, //
    likelihood, //
    M, //
    weight);
}

Example 20 with Likelihood

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

the class BeastCheckpointer method writeStateToFile.

private boolean writeStateToFile(File file, long state, double lnL, MarkovChain markovChain) {
    OperatorSchedule operatorSchedule = markovChain.getSchedule();
    OutputStream fileOut = null;
    try {
        fileOut = new FileOutputStream(file);
        PrintStream out = new PrintStream(fileOut);
        ArrayList<TreeParameterModel> traitModels = new ArrayList<TreeParameterModel>();
        int[] rngState = MathUtils.getRandomState();
        out.print("rng");
        for (int i = 0; i < rngState.length; i++) {
            out.print("\t");
            out.print(rngState[i]);
        }
        out.println();
        out.print("state\t");
        out.println(state);
        out.print("lnL\t");
        out.println(lnL);
        for (Parameter parameter : Parameter.CONNECTED_PARAMETER_SET) {
            out.print("parameter");
            out.print("\t");
            out.print(parameter.getParameterName());
            out.print("\t");
            out.print(parameter.getDimension());
            for (int dim = 0; dim < parameter.getDimension(); dim++) {
                out.print("\t");
                out.print(parameter.getParameterValue(dim));
            }
            out.println();
        }
        for (int i = 0; i < operatorSchedule.getOperatorCount(); i++) {
            MCMCOperator operator = operatorSchedule.getOperator(i);
            out.print("operator");
            out.print("\t");
            out.print(operator.getOperatorName());
            out.print("\t");
            out.print(operator.getAcceptCount());
            out.print("\t");
            out.print(operator.getRejectCount());
            if (operator instanceof CoercableMCMCOperator) {
                out.print("\t");
                out.print(((CoercableMCMCOperator) operator).getCoercableParameter());
            }
            out.println();
        }
        //check up front if there are any TreeParameterModel objects
        for (Model model : Model.CONNECTED_MODEL_SET) {
            if (model instanceof TreeParameterModel) {
                //System.out.println("\nDetected TreeParameterModel: " + ((TreeParameterModel) model).toString());
                traitModels.add((TreeParameterModel) model);
            }
        }
        for (Model model : Model.CONNECTED_MODEL_SET) {
            if (model instanceof TreeModel) {
                out.print("tree");
                out.print("\t");
                out.println(model.getModelName());
                //replace Newick format by printing general graph structure
                //out.println(((TreeModel) model).getNewick());
                out.println("#node height taxon");
                int nodeCount = ((TreeModel) model).getNodeCount();
                out.println(nodeCount);
                for (int i = 0; i < nodeCount; i++) {
                    out.print(((TreeModel) model).getNode(i).getNumber());
                    out.print("\t");
                    out.print(((TreeModel) model).getNodeHeight(((TreeModel) model).getNode(i)));
                    if (((TreeModel) model).isExternal(((TreeModel) model).getNode(i))) {
                        out.print("\t");
                        out.print(((TreeModel) model).getNodeTaxon(((TreeModel) model).getNode(i)).getId());
                    }
                    out.println();
                }
                out.println("#edges");
                out.println("#child-node parent-node L/R-child traits");
                out.println(nodeCount);
                for (int i = 0; i < nodeCount; i++) {
                    NodeRef parent = ((TreeModel) model).getParent(((TreeModel) model).getNode(i));
                    if (parent != null) {
                        out.print(((TreeModel) model).getNode(i).getNumber());
                        out.print("\t");
                        out.print(((TreeModel) model).getParent(((TreeModel) model).getNode(i)).getNumber());
                        out.print("\t");
                        if ((((TreeModel) model).getChild(parent, 0) == ((TreeModel) model).getNode(i))) {
                            //left child
                            out.print(0);
                        } else if ((((TreeModel) model).getChild(parent, 1) == ((TreeModel) model).getNode(i))) {
                            //right child
                            out.print(1);
                        } else {
                            throw new RuntimeException("Operation currently only supported for nodes with 2 children.");
                        }
                        for (TreeParameterModel tpm : traitModels) {
                            out.print("\t");
                            out.print(tpm.getNodeValue((TreeModel) model, ((TreeModel) model).getNode(i)));
                        }
                        out.println();
                    }
                }
            }
        }
        out.close();
        fileOut.close();
    } catch (IOException ioe) {
        System.err.println("Unable to write file: " + ioe.getMessage());
        return false;
    }
    if (DEBUG) {
        for (Likelihood likelihood : Likelihood.CONNECTED_LIKELIHOOD_SET) {
            System.err.println(likelihood.getId() + ": " + likelihood.getLogLikelihood());
        }
    }
    return true;
}