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

Example 16 with LatentFactorModel

use of dr.inference.model.LatentFactorModel 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;
}

Example 17 with LatentFactorModel

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

the class LoadingsIndependenceOperatorParser method parseXMLObject.

@Override
public Object parseXMLObject(XMLObject xo) throws XMLParseException {
    AdaptationMode mode = AdaptationMode.parseMode(xo);
    String scaleFactorTemp = (String) xo.getAttribute(SCALE_FACTOR);
    double scaleFactor = Double.parseDouble(scaleFactorTemp);
    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);
    // To change body of implemented methods use File | Settings | File Templates.
    return new LoadingsIndependenceOperator(LFM, prior, weight, randomScan, scaleFactor, mode);
}