/*
* ComplexSubstitutionModelParser.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.oldevomodelxml.substmodel;
import dr.evolution.datatype.DataType;
import dr.oldevomodel.substmodel.ComplexSubstitutionModel;
import dr.oldevomodel.substmodel.FrequencyModel;
import dr.oldevomodel.substmodel.SVSComplexSubstitutionModel;
import dr.evoxml.util.DataTypeUtils;
import dr.inference.model.BayesianStochasticSearchVariableSelection;
import dr.inference.model.Parameter;
import dr.xml.*;
import java.util.logging.Logger;
/**
*/
public class ComplexSubstitutionModelParser extends AbstractXMLObjectParser {
public static final String COMPLEX_SUBSTITUTION_MODEL = "complexSubstitutionModel";
public static final String RATES = "rates";
public static final String ROOT_FREQUENCIES = "rootFrequencies";
public static final String INDICATOR = "rateIndicator";
public static final String RANDOMIZE = "randomizeIndicator";
public static final String NORMALIZATION = "normalize";
public static final String MAX_CONDITION_NUMBER = "maxConditionNumber";
public static final String CONNECTED = "mustBeConnected";
public static final String MAX_ITERATIONS = "maxIterations";
public static final String CHECK_CONDITIONING = "checkConditioning";
public String[] getParserNames() {
return new String[]{
getParserName(), "beast_" + getParserName()
};
}
public String getParserName() {
return COMPLEX_SUBSTITUTION_MODEL;
}
public Object parseXMLObject(XMLObject xo) throws XMLParseException {
DataType dataType = DataTypeUtils.getDataType(xo);
if (dataType == null) dataType = (DataType) xo.getChild(DataType.class);
XMLObject cxo = xo.getChild(RATES);
Parameter ratesParameter = (Parameter) cxo.getChild(Parameter.class);
int rateCount = (dataType.getStateCount() - 1) * dataType.getStateCount();
if (ratesParameter.getDimension() != rateCount) {
throw new XMLParseException("Rates parameter in " + getParserName() + " element should have " + (rateCount)
+ " dimensions. However parameter dimension is " + ratesParameter.getDimension());
}
cxo = xo.getChild(ROOT_FREQUENCIES);
FrequencyModel rootFreq = (FrequencyModel) cxo.getChild(FrequencyModel.class);
if (dataType != rootFreq.getDataType()) {
throw new XMLParseException("Data type of " + getParserName() + " element does not match that of its rootFrequencyModel.");
}
Parameter indicators = null;
if (xo.hasChildNamed(INDICATOR)) {
indicators = (Parameter) ((XMLObject) xo.getChild(INDICATOR)).getChild(Parameter.class);
if (ratesParameter.getDimension() != indicators.getDimension())
throw new XMLParseException("Rate parameter dimension must match indicator parameter dimension");
}
StringBuffer sb = new StringBuffer().append("Constructing a complex substitution model using\n")
.append("\tRate parameters: ").append(ratesParameter.getId())
.append("\n").append("\tRoot frequency model: ").append(rootFreq.getId()).append("\n");
ComplexSubstitutionModel model;
if (indicators == null)
model = new ComplexSubstitutionModel(xo.getId(), dataType, rootFreq, ratesParameter);
else {
boolean randomize = xo.getAttribute(RANDOMIZE, false);
boolean connected = xo.getAttribute(CONNECTED, false);
model = new SVSComplexSubstitutionModel(xo.getId(), dataType, rootFreq, ratesParameter, indicators);
if (randomize) {
BayesianStochasticSearchVariableSelection.Utils.randomize(indicators,
dataType.getStateCount(), false);
boolean valid = !Double.isInfinite(model.getLogLikelihood());
if (!valid) {
throw new XMLParseException("Poor tolerance in complex substitution model. Please retry analysis using BEAGLE");
}
}
sb.append("\tBSSVS indicators: ").append(indicators.getId()).append("\n");
sb.append("\tGraph must be connected: ").append(connected).append("\n");
}
boolean doNormalization = xo.getAttribute(NORMALIZATION, true);
model.setNormalization(doNormalization);
sb.append("\tNormalized: ").append(doNormalization).append("\n");
boolean checkConditioning = xo.getAttribute(CHECK_CONDITIONING, true);
model.setCheckConditioning(checkConditioning);
if (checkConditioning) {
double maxConditionNumber = xo.getAttribute(MAX_CONDITION_NUMBER, 1000);
model.setMaxConditionNumber(maxConditionNumber);
sb.append("\tMax. condition number: ").append(maxConditionNumber).append("\n");
}
int maxIterations = xo.getAttribute(MAX_ITERATIONS, 1000);
model.setMaxIterations(maxIterations);
sb.append("\tMax iterations: ").append(maxIterations).append("\n");
sb.append("\t\tPlease cite Edwards, Suchard et al. (2011)\n");
Logger.getLogger("dr.evomodel.substmodel").info(sb.toString());
return model;
}
//************************************************************************
// AbstractXMLObjectParser implementation
//************************************************************************
public String getParserDescription() {
return "A general reversible model of sequence substitution for any data type with stochastic variable selection.";
}
public Class getReturnType() {
return ComplexSubstitutionModelParser.class;
}
public XMLSyntaxRule[] getSyntaxRules() {
return rules;
}
private final XMLSyntaxRule[] rules = {
new XORRule(
new StringAttributeRule(DataType.DATA_TYPE, "The type of sequence data",
DataType.getRegisteredDataTypeNames(), false),
new ElementRule(DataType.class)
),
AttributeRule.newBooleanRule(RANDOMIZE, true),
new ElementRule(ROOT_FREQUENCIES, FrequencyModel.class),
new ElementRule(RATES,
new XMLSyntaxRule[]{
new ElementRule(Parameter.class)}
),
new ElementRule(INDICATOR,
new XMLSyntaxRule[]{
new ElementRule(Parameter.class)
}, true),
AttributeRule.newBooleanRule(NORMALIZATION, true),
AttributeRule.newDoubleRule(MAX_CONDITION_NUMBER, true),
AttributeRule.newBooleanRule(CONNECTED, true),
AttributeRule.newIntegerRule(MAX_ITERATIONS, true),
AttributeRule.newBooleanRule(CHECK_CONDITIONING, true),
};
}