/* * 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. } }