/*
* TruncatedNormalDistributionModelParser.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.TruncatedNormalDistributionModel;
import dr.inference.model.Parameter;
import dr.xml.*;
/**
* Reads a normal distribution model from a DOM Document element.
*/
public class TruncatedNormalDistributionModelParser extends AbstractXMLObjectParser {
public static final String TRUNCATED_NORMAL_DISTRIBUTION_MODEL = "truncatedNormalDistributionModel";
public static final String MEAN = "mean";
public static final String STDEV = "stdev";
public static final String MINIMUM = "minimum";
public static final String MAXIMUM = "maximum";
public static final String PREC = "precision";
public String getParserName() {
return TRUNCATED_NORMAL_DISTRIBUTION_MODEL;
}
public Object parseXMLObject(XMLObject xo) throws XMLParseException {
Parameter meanParam;
Parameter stdevParam;
Parameter minParam;
Parameter maxParam;
Parameter precParam;
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));
}
if(xo.hasChildNamed(MINIMUM)){
cxo = xo.getChild(MINIMUM);
if(cxo.getChild(0) instanceof Parameter) {
minParam = (Parameter) cxo.getChild(Parameter.class);
} else {
minParam = new Parameter.Default(cxo.getDoubleChild(0));
}
} else {
minParam = new Parameter.Default(Double.NEGATIVE_INFINITY);
}
if(xo.hasChildNamed(MAXIMUM)){
cxo = xo.getChild(MAXIMUM);
if(cxo.getChild(0) instanceof Parameter) {
maxParam = (Parameter) cxo.getChild(Parameter.class);
} else {
maxParam = new Parameter.Default(cxo.getDoubleChild(0));
}
} else {
maxParam = new Parameter.Default(Double.POSITIVE_INFINITY);
}
if (xo.getChild(STDEV) != null) {
cxo = xo.getChild(STDEV);
if (cxo.getChild(0) instanceof Parameter) {
stdevParam = (Parameter) cxo.getChild(Parameter.class);
} else {
stdevParam = new Parameter.Default(cxo.getDoubleChild(0));
}
return new TruncatedNormalDistributionModel(meanParam, stdevParam, minParam, maxParam);
}
cxo = xo.getChild(PREC);
if (cxo.getChild(0) instanceof Parameter) {
precParam = (Parameter) cxo.getChild(Parameter.class);
} else {
precParam = new Parameter.Default(cxo.getDoubleChild(0));
}
return new TruncatedNormalDistributionModel(meanParam, precParam, minParam, maxParam, true);
}
//************************************************************************
// AbstractXMLObjectParser implementation
//************************************************************************
public XMLSyntaxRule[] getSyntaxRules() {
return rules;
}
private final XMLSyntaxRule[] rules = {
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(PREC,
new XMLSyntaxRule[]{
new XORRule(
new ElementRule(Parameter.class),
new ElementRule(Double.class)
)}
)
),
new OrRule(
new ElementRule(MINIMUM,
new XMLSyntaxRule[]{
new XORRule(
new ElementRule(Parameter.class),
new ElementRule(Double.class)
)}
),
new ElementRule(MAXIMUM,
new XMLSyntaxRule[]{
new XORRule(
new ElementRule(Parameter.class),
new ElementRule(Double.class)
)
}
)
)
};
public String getParserDescription() {
return "Describes a truncated normal distribution with a given mean, standard deviation and minimum or" +
"maximum (or both) values that can be used in a distributionLikelihood element";
}
public Class getReturnType() {
return TruncatedNormalDistributionModel.class;
}
}