Examples with AbstractObservationProcess dr.oldevomodel.MSSD.AbstractObservationProcess used on opensource projects

Example 1 with AbstractObservationProcess

use of dr.oldevomodel.MSSD.AbstractObservationProcess in project beast-mcmc by beast-dev.

the class ALSTreeLikelihoodParser method parseXMLObject.

public Object parseXMLObject(XMLObject xo) throws XMLParseException {
    boolean useAmbiguities = false;
    boolean storePartials = true;
    if (xo.hasAttribute(TreeLikelihoodParser.USE_AMBIGUITIES)) {
        useAmbiguities = xo.getBooleanAttribute(TreeLikelihoodParser.USE_AMBIGUITIES);
    }
    if (xo.hasAttribute(TreeLikelihoodParser.STORE_PARTIALS)) {
        storePartials = xo.getBooleanAttribute(TreeLikelihoodParser.STORE_PARTIALS);
    }
    boolean integrateGainRate = xo.getBooleanAttribute(INTEGRATE_GAIN_RATE);
    //AbstractObservationProcess observationProcess = (AbstractObservationProcess) xo.getChild(AbstractObservationProcess.class);
    PatternList patternList = (PatternList) xo.getChild(PatternList.class);
    TreeModel treeModel = (TreeModel) xo.getChild(TreeModel.class);
    SiteModel siteModel = (SiteModel) xo.getChild(SiteModel.class);
    BranchRateModel branchRateModel = (BranchRateModel) xo.getChild(BranchRateModel.class);
    Parameter mu = ((MutationDeathModel) siteModel.getSubstitutionModel()).getDeathParameter();
    Parameter lam;
    if (!integrateGainRate) {
        lam = (Parameter) xo.getElementFirstChild(IMMIGRATION_RATE);
    } else {
        lam = new Parameter.Default("gainRate", 1.0, 0.001, 1.999);
    }
    AbstractObservationProcess observationProcess = null;
    Logger.getLogger("dr.evolution").info("\n ---------------------------------\nCreating ALSTreeLikelihood model.");
    for (int i = 0; i < xo.getChildCount(); ++i) {
        Object cxo = xo.getChild(i);
        if (cxo instanceof XMLObject && ((XMLObject) cxo).getName().equals(OBSERVATION_PROCESS)) {
            if (((XMLObject) cxo).getStringAttribute(OBSERVATION_TYPE).equals("singleTip")) {
                String taxonName = ((XMLObject) cxo).getStringAttribute(OBSERVATION_TAXON);
                Taxon taxon = treeModel.getTaxon(treeModel.getTaxonIndex(taxonName));
                observationProcess = new SingleTipObservationProcess(treeModel, patternList, siteModel, branchRateModel, mu, lam, taxon);
                Logger.getLogger("dr.evolution").info("All traits are assumed extant in " + taxonName);
            } else {
                // "anyTip" observation process
                observationProcess = new AnyTipObservationProcess(ANY_TIP, treeModel, patternList, siteModel, branchRateModel, mu, lam);
                Logger.getLogger("dr.evolution").info("Observed traits are assumed to be extant in at least one tip node.");
            }
            observationProcess.setIntegrateGainRate(integrateGainRate);
        }
    }
    Logger.getLogger("dr.evolution").info("\tIf you publish results using Acquisition-Loss-Mutation (ALS) Model likelihood, please reference Alekseyenko, Lee and Suchard (2008) Syst. Biol 57: 772-784.\n---------------------------------\n");
    boolean forceRescaling = xo.getAttribute(FORCE_RESCALING, false);
    return new ALSTreeLikelihood(observationProcess, patternList, treeModel, siteModel, branchRateModel, useAmbiguities, storePartials, forceRescaling);
}

Example 2 with AbstractObservationProcess

use of dr.oldevomodel.MSSD.AbstractObservationProcess in project beast-mcmc by beast-dev.

the class ALSTreeLikelihoodParser method parseXMLObject.

public Object parseXMLObject(XMLObject xo) throws XMLParseException {
    boolean useAmbiguities = false;
    boolean storePartials = true;
    if (xo.hasAttribute(TreeLikelihoodParser.USE_AMBIGUITIES)) {
        useAmbiguities = xo.getBooleanAttribute(TreeLikelihoodParser.USE_AMBIGUITIES);
    }
    if (xo.hasAttribute(TreeLikelihoodParser.STORE_PARTIALS)) {
        storePartials = xo.getBooleanAttribute(TreeLikelihoodParser.STORE_PARTIALS);
    }
    boolean integrateGainRate = xo.getBooleanAttribute(INTEGRATE_GAIN_RATE);
    //AbstractObservationProcess observationProcess = (AbstractObservationProcess) xo.getChild(AbstractObservationProcess.class);
    PatternList patternList = (PatternList) xo.getChild(PatternList.class);
    TreeModel treeModel = (TreeModel) xo.getChild(TreeModel.class);
    SiteModel siteModel = (SiteModel) xo.getChild(SiteModel.class);
    BranchRateModel branchRateModel = (BranchRateModel) xo.getChild(BranchRateModel.class);
    Parameter mu = ((MutationDeathModel) siteModel.getSubstitutionModel()).getDeathParameter();
    Parameter lam;
    if (!integrateGainRate) {
        lam = (Parameter) xo.getElementFirstChild(IMMIGRATION_RATE);
    } else {
        lam = new Parameter.Default("gainRate", 1.0, 0.001, 1.999);
    }
    AbstractObservationProcess observationProcess = null;
    Logger.getLogger("dr.evolution").info("\n ---------------------------------\nCreating ALSTreeLikelihood model.");
    for (int i = 0; i < xo.getChildCount(); ++i) {
        Object cxo = xo.getChild(i);
        if (cxo instanceof XMLObject && ((XMLObject) cxo).getName().equals(OBSERVATION_PROCESS)) {
            if (((XMLObject) cxo).getStringAttribute(OBSERVATION_TYPE).equals("singleTip")) {
                String taxonName = ((XMLObject) cxo).getStringAttribute(OBSERVATION_TAXON);
                Taxon taxon = treeModel.getTaxon(treeModel.getTaxonIndex(taxonName));
                observationProcess = new SingleTipObservationProcess(treeModel, patternList, siteModel, branchRateModel, mu, lam, taxon);
                Logger.getLogger("dr.evolution").info("All traits are assumed extant in " + taxonName);
            } else {
                // "anyTip" observation process
                observationProcess = new AnyTipObservationProcess(ANY_TIP, treeModel, patternList, siteModel, branchRateModel, mu, lam);
                Logger.getLogger("dr.evolution").info("Observed traits are assumed to be extant in at least one tip node.");
            }
            observationProcess.setIntegrateGainRate(integrateGainRate);
        }
    }
    Logger.getLogger("dr.evolution").info("\tIf you publish results using Acquisition-Loss-Mutation (ALS) Model likelihood, please reference Alekseyenko, Lee and Suchard (2008) Syst. Biol 57: 772-784.\n---------------------------------\n");
    boolean forceRescaling = xo.getAttribute(FORCE_RESCALING, false);
    return new ALSTreeLikelihood(observationProcess, patternList, treeModel, siteModel, branchRateModel, useAmbiguities, storePartials, forceRescaling);
}