/*
* LogNormalDistributionModelParser.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.distribution;
import dr.inference.distribution.LogNormalDistributionModel;
import dr.inference.model.Parameter;
import dr.xml.*;
/**
* Reads a normal distribution model from a DOM Document element.
*/
public class LogNormalDistributionModelParser extends AbstractXMLObjectParser {
public static final String LOGNORMAL_DISTRIBUTION_MODEL = "logNormalDistributionModel";
public static final String MEAN = "mean";
public static final String STDEV = "stdev";
public static final String PRECISION = "precision";
public static final String OFFSET = "offset";
public static final String MEAN_IN_REAL_SPACE = "meanInRealSpace";
public static final String STDEV_IN_REAL_SPACE = "stdevInRealSpace";
public String getParserName() {
return LOGNORMAL_DISTRIBUTION_MODEL;
}
public Object parseXMLObject(XMLObject xo) throws XMLParseException {
Parameter meanParam;
final double offset = xo.getAttribute(OFFSET, 0.0);
final boolean meanInRealSpace = xo.getAttribute(MEAN_IN_REAL_SPACE, false);
final boolean stdevInRealSpace = xo.getAttribute(STDEV_IN_REAL_SPACE, false);
if(!meanInRealSpace && stdevInRealSpace) {
throw new RuntimeException("Cannot parameterise Lognormal model with M and Stdev");
}
{
final XMLObject cxo = xo.getChild(MEAN);
if (cxo.getChild(0) instanceof Parameter) {
meanParam = (Parameter) cxo.getChild(Parameter.class);
} else {
meanParam = new Parameter.Default(cxo.getDoubleChild(0));
}
}
{
final XMLObject cxo = xo.getChild(PRECISION);
if (cxo != null) {
Parameter precParam;
if (cxo.getChild(0) instanceof Parameter) {
precParam = (Parameter) cxo.getChild(Parameter.class);
} else {
precParam = new Parameter.Default(cxo.getDoubleChild(0));
}
return new LogNormalDistributionModel(meanParam, precParam, offset, meanInRealSpace,stdevInRealSpace, false);
}
}
{
final XMLObject cxo = xo.getChild(STDEV);
Parameter stdevParam;
if (cxo.getChild(0) instanceof Parameter) {
stdevParam = (Parameter) cxo.getChild(Parameter.class);
} else {
stdevParam = new Parameter.Default(cxo.getDoubleChild(0));
}
return new LogNormalDistributionModel(meanParam, stdevParam, offset, meanInRealSpace, stdevInRealSpace);
}
}
//************************************************************************
// AbstractXMLObjectParser implementation
//************************************************************************
public XMLSyntaxRule[] getSyntaxRules() {
return rules;
}
private final XMLSyntaxRule[] rules = {
AttributeRule.newBooleanRule(MEAN_IN_REAL_SPACE, true),
AttributeRule.newBooleanRule(STDEV_IN_REAL_SPACE, true),
AttributeRule.newDoubleRule(OFFSET, true),
new ElementRule(MEAN,
new XMLSyntaxRule[]{
new XORRule(
new ElementRule(Parameter.class),
new ElementRule(Double.class)
)}
),
new XORRule(
new ElementRule(STDEV,
new XMLSyntaxRule[]{
new XORRule(
new ElementRule(Parameter.class),
new ElementRule(Double.class)
)}
),
new ElementRule(PRECISION,
new XMLSyntaxRule[]{
new XORRule(
new ElementRule(Parameter.class),
new ElementRule(Double.class)
)}
))
};
public String getParserDescription() {
return "Describes a normal distribution with a given mean and standard deviation " +
"that can be used in a distributionLikelihood element";
}
public Class getReturnType() {
return LogNormalDistributionModel.class;
}
}