/*
* MultivariateNormalGibbsOperatorParser.java
*
* Copyright (c) 2002-2015 Alexei Drummond, Andrew Rambaut and Marc Suchard
*
* This file is part of BEAST.
* See the NOTICE file distributed with this work for additional
* information regarding copyright ownership and licensing.
*
* BEAST is free software; you can redistribute it and/or modify
* it under the terms of the GNU Lesser General Public License as
* published by the Free Software Foundation; either version 2
* of the License, or (at your option) any later version.
*
* BEAST is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU Lesser General Public License for more details.
*
* You should have received a copy of the GNU Lesser General Public
* License along with BEAST; if not, write to the
* Free Software Foundation, Inc., 51 Franklin St, Fifth Floor,
* Boston, MA 02110-1301 USA
*/
package dr.inferencexml.operators;
import dr.inference.distribution.MultivariateDistributionLikelihood;
import dr.inference.operators.MultivariateNormalGibbsOperator;
import dr.math.matrixAlgebra.IllegalDimension;
import dr.xml.*;
/**
* Created with IntelliJ IDEA.
* User: max
* Date: 2/21/14
* Time: 2:20 PM
* To change this template use File | Settings | File Templates.
*/
public class MultivariateNormalGibbsOperatorParser extends AbstractXMLObjectParser {
public static final String MVN_GIBBS_SAMPLER="MultivariateNormalGibbsOperator";
public static final String PRIOR="prior";
public static final String LIKELIHOOD="likelihood";
public static final String WEIGHT="weight";
@Override
public Object parseXMLObject(XMLObject xo) throws XMLParseException {
MultivariateDistributionLikelihood prior= (MultivariateDistributionLikelihood) xo.getChild(PRIOR).getChild(MultivariateDistributionLikelihood.class);
MultivariateDistributionLikelihood likelihood= (MultivariateDistributionLikelihood) xo.getChild(LIKELIHOOD).getChild(MultivariateDistributionLikelihood.class);
// CompoundParameter data = (CompoundParameter) xo.getChild(CompoundParameter.class);
String weightTemp= (String) xo.getAttribute(WEIGHT);
Double weight=Double.parseDouble(weightTemp);
//TODO check that it gives the right likelihood and the MVN distributions are conformable
// if (!(prior.getDistribution() instanceof MultivariateNormalDistributionModel)) {
// throw new XMLParseException("Only a Wishart distribution is conjugate for Gibbs sampling");
// }
//
// // Make sure precMatrix is square and dim(precMatrix) = dim(parameter)
// if (precMatrix.getColumnDimension() != precMatrix.getRowDimension()) {
// throw new XMLParseException("The variance matrix is not square or of wrong dimension");
// }
try {
return new MultivariateNormalGibbsOperator(likelihood, prior, weight); //To change body of implemented methods use File | Settings | File Templates.
} catch (IllegalDimension illegalDimension) {
illegalDimension.printStackTrace(); //To change body of catch statement use File | Settings | File Templates.
}
return null;
}
@Override
public XMLSyntaxRule[] getSyntaxRules() {
return rules;
}
private XMLSyntaxRule[] rules = new XMLSyntaxRule[]{
new ElementRule(PRIOR, new XMLSyntaxRule[]{new ElementRule(MultivariateDistributionLikelihood.class)}),
new ElementRule(LIKELIHOOD, new XMLSyntaxRule[]{new ElementRule(MultivariateDistributionLikelihood.class)}),
// new ElementRule(CompoundParameter.class),
AttributeRule.newDoubleRule(WEIGHT),
};
@Override
public String getParserDescription() {
return "Multivariate Normal Gibbs Sampler"; //To change body of implemented methods use File | Settings | File Templates.
}
@Override
public Class getReturnType() {
return MultivariateNormalGibbsOperator.class; //To change body of implemented methods use File | Settings | File Templates.
}
@Override
public String getParserName() {
return MVN_GIBBS_SAMPLER; //To change body of implemented methods use File | Settings | File Templates.
}
}