package dr.inferencexml.distribution; import dr.inference.distribution.DistributionLikelihood; import dr.inference.distribution.ParametricDistributionModel; import dr.inference.distribution.RandomWalkModel; import dr.inference.model.Parameter; import dr.xml.*; /** * */ public class RandomWalkModelParser extends AbstractXMLObjectParser { public static final String RANDOM_WALK = "randomWalk"; public static final String LOG_SCALE = "logScale"; public String getParserName() { return RANDOM_WALK; } public Object parseXMLObject(XMLObject xo) throws XMLParseException { Parameter data = (Parameter) xo.getChild(Parameter.class); ParametricDistributionModel distribution = (ParametricDistributionModel) xo.getChild(ParametricDistributionModel.class); boolean logScale = false; if (xo.hasAttribute(LOG_SCALE)) logScale = xo.getBooleanAttribute(LOG_SCALE); return new RandomWalkModel(distribution, data, false, logScale); } //************************************************************************ // AbstractXMLObjectParser implementation //************************************************************************ public XMLSyntaxRule[] getSyntaxRules() { return rules; } private XMLSyntaxRule[] rules = new XMLSyntaxRule[]{ AttributeRule.newBooleanRule(LOG_SCALE, true), new ElementRule(Parameter.class), new XORRule( new ElementRule(ParametricDistributionModel.class), new ElementRule(DistributionLikelihood.class) ) }; public String getParserDescription() { return "Describes a first-order random walk. No prior is assumed on the first data element"; } public Class getReturnType() { return RandomWalkModel.class; } }