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

Example 91 with Parameter

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

the class MicrosatelliteFullAncestryImportanceSamplingOperatorParser method parseXMLObject.

public Object parseXMLObject(XMLObject xo) throws XMLParseException {
    final double weight = xo.getDoubleAttribute(MCMCOperator.WEIGHT);
    final Parameter parameter = (Parameter) xo.getChild(Parameter.class);
    final MicrosatelliteSamplerTreeModel msatSamplerTreeModel = (MicrosatelliteSamplerTreeModel) xo.getChild(MicrosatelliteSamplerTreeModel.class);
    final MicrosatelliteModel msatModel = (MicrosatelliteModel) xo.getChild(MicrosatelliteModel.class);
    final BranchRateModel branchRateModel = (BranchRateModel) xo.getChild(BranchRateModel.class);
    return new MicrosatelliteFullAncestryImportanceSamplingOperator(parameter, msatSamplerTreeModel, msatModel, branchRateModel, weight);
}

Example 92 with Parameter

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

the class MomentDistributionModelParser method parseXMLObject.

@Override
public Object parseXMLObject(XMLObject xo) throws XMLParseException {
    Parameter mean = (Parameter) xo.getChild(MEAN).getChild(0);
    Parameter prec = (Parameter) xo.getChild(PREC).getChild(0);
    Parameter cutoff = null;
    if (xo.getChild(CUTOFF) != null) {
        cutoff = (Parameter) xo.getChild(CUTOFF).getChild(0);
    }
    Parameter data = (Parameter) xo.getChild(DATA).getChild(0);
    return new MomentDistributionModel(mean, prec, cutoff, data);
}

Example 93 with Parameter

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

the class MultivariateNormalDistributionModelParser method parseXMLObject.

public Object parseXMLObject(XMLObject xo) throws XMLParseException {
    XMLObject cxo = xo.getChild(MultivariateDistributionLikelihood.MVN_MEAN);
    Parameter mean = (Parameter) cxo.getChild(Parameter.class);
    cxo = xo.getChild(MultivariateDistributionLikelihood.MVN_PRECISION);
    MatrixParameter precision = (MatrixParameter) cxo.getChild(MatrixParameter.class);
    if (mean.getDimension() != precision.getRowDimension() || mean.getDimension() != precision.getColumnDimension())
        throw new XMLParseException("Mean and precision have wrong dimensions in " + xo.getName() + " element");
    return new MultivariateNormalDistributionModel(mean, precision);
}

Example 94 with Parameter

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

the class MultivariateOUModelParser method parseXMLObject.

public Object parseXMLObject(XMLObject xo) throws XMLParseException {
    SubstitutionModel substitutionModel = (SubstitutionModel) xo.getChild(SubstitutionModel.class);
    Parameter effectParameter = (Parameter) ((XMLObject) xo.getChild(DATA)).getChild(Parameter.class);
    Parameter timesParameter = (Parameter) ((XMLObject) xo.getChild(TIME)).getChild(Parameter.class);
    Parameter designParameter = (Parameter) ((XMLObject) xo.getChild(DESIGN)).getChild(Parameter.class);
    MatrixParameter gammaParameter = (MatrixParameter) xo.getChild(MatrixParameter.class);
    if (effectParameter.getDimension() != timesParameter.getDimension() || effectParameter.getDimension() != designParameter.getDimension()) {
        //				System.err.println("dim(design) "+designParameter.getDimension());
        throw new XMLParseException("dim(" + effectParameter.getStatisticName() + ") != dim(" + timesParameter.getStatisticName() + ") != dim(" + designParameter.getStatisticName() + ") in " + xo.getName() + " element");
    }
    MultivariateOUModel glm = new MultivariateOUModel(substitutionModel, effectParameter, gammaParameter, timesParameter.getParameterValues(), designParameter.getParameterValues());
    addIndependentParameters(xo, glm, effectParameter);
    return glm;
}

Example 95 with Parameter

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

the class MultivariateOUModelParser method addIndependentParameters.

public void addIndependentParameters(XMLObject xo, GeneralizedLinearModel glm, Parameter dependentParam) throws XMLParseException {
    int totalCount = xo.getChildCount();
    for (int i = 0; i < totalCount; i++) {
        if (xo.getChildName(i).compareTo(GeneralizedLinearModelParser.INDEPENDENT_VARIABLES) == 0) {
            XMLObject cxo = (XMLObject) xo.getChild(i);
            Parameter independentParam = (Parameter) cxo.getChild(Parameter.class);
            DesignMatrix designMatrix = (DesignMatrix) cxo.getChild(DesignMatrix.class);
            checkDimensions(independentParam, dependentParam, designMatrix);
            glm.addIndependentParameter(independentParam, designMatrix, null);
        }
    }
}