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;
}
}