Examples with LatentFactorModelPrecisionGibbsOperator dr.inference.operators.factorAnalysis.LatentFactorModelPrecisionGibbsOperator used on opensource projects

Example 1 with LatentFactorModelPrecisionGibbsOperator

use of dr.inference.operators.factorAnalysis.LatentFactorModelPrecisionGibbsOperator in project beast-mcmc by beast-dev.

the class FactorRJMCMCOperatorParser method parseXMLObject.

@Override
public Object parseXMLObject(XMLObject xo) throws XMLParseException {
    // attributes
    double weight = xo.getDoubleAttribute(WEIGHT);
    int chainLength = xo.getIntegerAttribute(CHAIN_LENGTH);
    double sizeParameter = xo.getDoubleAttribute(SIZE_PARAMETER);
    // declaration
    AdaptableSizeFastMatrixParameter factors, loadings, cutoffs, loadingsSparcity;
    // parameters
    if (xo.hasChildNamed(FACTORS))
        factors = (AdaptableSizeFastMatrixParameter) xo.getChild(FACTORS).getChild(AdaptableSizeFastMatrixParameter.class);
    else
        factors = null;
    loadings = (AdaptableSizeFastMatrixParameter) xo.getChild(LOADINGS).getChild(AdaptableSizeFastMatrixParameter.class);
    if (xo.hasChildNamed(CUTOFFS)) {
        cutoffs = (AdaptableSizeFastMatrixParameter) xo.getChild(CUTOFFS).getChild(AdaptableSizeFastMatrixParameter.class);
    } else
        cutoffs = null;
    if (xo.hasChildNamed(LOADINGS_SPARSITY))
        loadingsSparcity = (AdaptableSizeFastMatrixParameter) xo.getChild(LOADINGS_SPARSITY).getChild(AdaptableSizeFastMatrixParameter.class);
    else
        loadingsSparcity = null;
    // models
    DeterminentalPointProcessPrior DPP = null;
    if (xo.getChild(SPARSITY_PRIOR) != null)
        DPP = (DeterminentalPointProcessPrior) xo.getChild(SPARSITY_PRIOR).getChild(DeterminentalPointProcessPrior.class);
    SimpleMCMCOperator NOp = null;
    if (xo.getChild(NEGATION_OPERATOR) != null) {
        NOp = (SimpleMCMCOperator) xo.getChild(NEGATION_OPERATOR).getChild(SimpleMCMCOperator.class);
    }
    AbstractModelLikelihood LFM = (AbstractModelLikelihood) xo.getChild(AbstractModelLikelihood.class);
    RowDimensionPoissonPrior rowPrior = (RowDimensionPoissonPrior) xo.getChild(ROW_PRIOR).getChild(RowDimensionPoissonPrior.class);
    Likelihood loadingsPrior = null;
    if (xo.hasChildNamed(LOADINGS_PRIOR)) {
        loadingsPrior = (Likelihood) xo.getChild(LOADINGS_PRIOR).getChild(Likelihood.class);
    }
    // operators
    SimpleMCMCOperator sparsityOperator = null;
    if (xo.getChild(BitFlipOperator.class) != null)
        sparsityOperator = (BitFlipOperator) xo.getChild(BitFlipOperator.class);
    if (xo.getChild(LoadingsSparsityOperator.class) != null) {
        sparsityOperator = (LoadingsSparsityOperator) xo.getChild(LoadingsSparsityOperator.class);
    }
    SimpleMCMCOperator loadingsOperator = (SimpleMCMCOperator) xo.getChild(LOADINGS_OPERATOR).getChild(SimpleMCMCOperator.class);
    SimpleMCMCOperator factorOperator = null;
    if (xo.getChild(FACTOR_OPERATOR) != null)
        factorOperator = (SimpleMCMCOperator) xo.getChild(FACTOR_OPERATOR).getChild(FactorTreeGibbsOperator.class);
    LatentFactorModelPrecisionGibbsOperator precisionGibbsOperator = null;
    if (xo.getChild(LatentFactorModelPrecisionGibbsOperator.class) != null) {
        System.out.println("here");
        precisionGibbsOperator = (LatentFactorModelPrecisionGibbsOperator) xo.getChild(LatentFactorModelPrecisionGibbsOperator.class);
    }
    return new FactorRJMCMCOperator(weight, sizeParameter, chainLength, factors, loadings, cutoffs, loadingsSparcity, LFM, DPP, loadingsPrior, loadingsOperator, factorOperator, sparsityOperator, NOp, rowPrior, precisionGibbsOperator);
}

Example 2 with LatentFactorModelPrecisionGibbsOperator

use of dr.inference.operators.factorAnalysis.LatentFactorModelPrecisionGibbsOperator in project beast-mcmc by beast-dev.

the class LatentFactorModelPrecisionGibbsOperatorParser method parseXMLObject.

@Override
public Object parseXMLObject(XMLObject xo) throws XMLParseException {
    String weightTemp = (String) xo.getAttribute(WEIGHT);
    double weight = Double.parseDouble(weightTemp);
    LatentFactorModel LFM = (LatentFactorModel) xo.getChild(LatentFactorModel.class);
    DistributionLikelihood prior = (DistributionLikelihood) xo.getChild(DistributionLikelihood.class);
    boolean randomScan = xo.getAttribute(RANDOM_SCAN, true);
    LatentFactorModelPrecisionGibbsOperator lfmOp = new LatentFactorModelPrecisionGibbsOperator(LFM, prior, weight, randomScan);
    if (xo.hasAttribute(PATH_PARAMETER)) {
        System.out.println("WARNING: Setting Path Parameter is intended for debugging purposes only!");
        lfmOp.setPathParameter(xo.getDoubleAttribute(PATH_PARAMETER));
    }
    return lfmOp;
}