/* * EllipticalSliceOperatorParser.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.distribution.MultivariateNormalDistributionModel; import dr.inference.model.CompoundParameter; import dr.inference.model.Parameter; import dr.inference.operators.EllipticalSliceOperator; import dr.inference.operators.MCMCOperator; import dr.math.distributions.GaussianProcessRandomGenerator; import dr.math.distributions.MultivariateNormalDistribution; import dr.xml.*; /** */ public class EllipticalSliceOperatorParser extends AbstractXMLObjectParser { public static final String ELLIPTICAL_SLICE_SAMPLER = "ellipticalSliceSampler"; public static final String SIGNAL_CONSTITUENT_PARAMETERS = "signalConstituentParameters"; public static final String BRACKET_ANGLE = "bracketAngle"; public static final String TRANSLATION_INVARIANT = "translationInvariant"; public static final String ROTATION_INVARIANT = "rotationInvariant"; public static final String DRAW_BY_ROW = "drawByRow"; // TODO What is this? public String getParserName() { return ELLIPTICAL_SLICE_SAMPLER; } public Object parseXMLObject(XMLObject xo) throws XMLParseException { final double weight = xo.getDoubleAttribute(MCMCOperator.WEIGHT); final Parameter variable = (Parameter) xo.getChild(Parameter.class); boolean drawByRowTemp=false; if(xo.hasAttribute(DRAW_BY_ROW)) drawByRowTemp=xo.getBooleanAttribute(DRAW_BY_ROW); final boolean drawByRow=drawByRowTemp; boolean signal = xo.getAttribute(SIGNAL_CONSTITUENT_PARAMETERS, true); if (!signal && !(variable instanceof CompoundParameter)) signal = true; double bracketAngle = xo.getAttribute(BRACKET_ANGLE, 0.0); boolean translationInvariant = xo.getAttribute(TRANSLATION_INVARIANT, false); boolean rotationInvariant = xo.getAttribute(ROTATION_INVARIANT, false); GaussianProcessRandomGenerator gaussianProcess = (GaussianProcessRandomGenerator) xo.getChild(GaussianProcessRandomGenerator.class); if (gaussianProcess == null) { final MultivariateDistributionLikelihood likelihood = (MultivariateDistributionLikelihood) xo.getChild(MultivariateDistributionLikelihood.class); if (!(likelihood.getDistribution() instanceof GaussianProcessRandomGenerator)) { throw new XMLParseException("Elliptical slice sampling only works for multivariate normally distributed random variables"); } if(likelihood.getDistribution() instanceof MultivariateNormalDistribution) gaussianProcess = (MultivariateNormalDistribution) likelihood.getDistribution(); if(likelihood.getDistribution() instanceof MultivariateNormalDistributionModel) gaussianProcess = (MultivariateNormalDistributionModel) likelihood.getDistribution(); } EllipticalSliceOperator operator = new EllipticalSliceOperator(variable, gaussianProcess, drawByRow, signal, bracketAngle, translationInvariant, rotationInvariant); operator.setWeight(weight); return operator; } //************************************************************************ // AbstractXMLObjectParser implementation //************************************************************************ public String getParserDescription() { return "An elliptical slice sampler for parameters with Gaussian priors."; } public Class getReturnType() { return EllipticalSliceOperator.class; } public XMLSyntaxRule[] getSyntaxRules() { return rules; } private final XMLSyntaxRule[] rules = { AttributeRule.newDoubleRule(MCMCOperator.WEIGHT), AttributeRule.newBooleanRule(SIGNAL_CONSTITUENT_PARAMETERS, true), AttributeRule.newDoubleRule(BRACKET_ANGLE, true), AttributeRule.newBooleanRule(TRANSLATION_INVARIANT, true), AttributeRule.newBooleanRule(ROTATION_INVARIANT, true), new ElementRule(Parameter.class), new XORRule( new ElementRule(GaussianProcessRandomGenerator.class), new ElementRule(MultivariateDistributionLikelihood.class) ), AttributeRule.newBooleanRule(DRAW_BY_ROW, true), // new ElementRule(MultivariateNormalDistribution.class), }; }