/*
* Copyright (C) 2002-2009 Alexei Drummond and Andrew Rambaut
*
* 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.app.beauti.generator;
import dr.app.beauti.components.ComponentFactory;
import dr.app.beauti.options.*;
import dr.app.beauti.types.ClockType;
import dr.app.beauti.util.XMLWriter;
import dr.evomodel.branchratemodel.BranchRateModel;
import dr.evomodel.clock.RateEvolutionLikelihood;
import dr.evomodel.tree.TreeModel;
import dr.evomodelxml.branchratemodel.DiscretizedBranchRatesParser;
import dr.evomodelxml.branchratemodel.RandomLocalClockModelParser;
import dr.evomodelxml.branchratemodel.StrictClockBranchRatesParser;
import dr.evomodelxml.clock.ACLikelihoodParser;
import dr.evomodelxml.tree.RateCovarianceStatisticParser;
import dr.evomodelxml.tree.RateStatisticParser;
import dr.evomodelxml.tree.TreeModelParser;
import dr.inference.distribution.ExponentialDistributionModel;
import dr.inference.model.ParameterParser;
import dr.inferencexml.distribution.LogNormalDistributionModelParser;
import dr.inferencexml.model.CompoundParameterParser;
import dr.inferencexml.model.SumStatisticParser;
import dr.util.Attribute;
import dr.xml.XMLParser;
import java.util.List;
/**
* @author Alexei Drummond
* @author Andrew Rambaut
*/
public class BranchRatesModelGenerator extends Generator {
public BranchRatesModelGenerator(BeautiOptions options, ComponentFactory[] components) {
super(options, components);
}
/**
* Write the relaxed clock branch rates block.
*
* @param model PartitionClockModel
* @param writer the writer
*/
public void writeBranchRatesModel(PartitionClockModel model, XMLWriter writer) {
setModelPrefix(model.getPrefix());
Attribute[] attributes;
int categoryCount = 0;
String treePrefix;
List<PartitionTreeModel> activeTrees = options.getPartitionTreeModels(options.getDataPartitions(model));
switch (model.getClockType()) {
case STRICT_CLOCK:
writer.writeComment("The strict clock (Uniform rates across branches)");
writer.writeOpenTag(
StrictClockBranchRatesParser.STRICT_CLOCK_BRANCH_RATES,
new Attribute[]{new Attribute.Default<String>(XMLParser.ID, modelPrefix + BranchRateModel.BRANCH_RATES)}
);
writeParameter("rate", "clock.rate", model, writer);
writer.writeCloseTag(StrictClockBranchRatesParser.STRICT_CLOCK_BRANCH_RATES);
break;
case UNCORRELATED:
writer.writeComment("The uncorrelated relaxed clock (Drummond, Ho, Phillips & Rambaut (2006) PLoS Biology 4, e88 )");
for (PartitionTreeModel tree : activeTrees) {
treePrefix = tree.getPrefix();
PartitionClockModelTreeModelLink clockTree = options.getPartitionClockTreeLink(model, tree);
if (clockTree == null) {
throw new IllegalArgumentException("Cannot find PartitionClockTreeLink, given clock model = " + model.getName()
+ ", tree model = " + tree.getName());
}
//if (options.isFixedSubstitutionRate()) {
// attributes = new Attribute[]{
// new Attribute.Default<String>(XMLParser.ID, BranchRateModel.BRANCH_RATES),
// new Attribute.Default<Double>(DiscretizedBranchRatesParser.NORMALIZED_MEAN, options.getMeanSubstitutionRate())
// };
//} else {
attributes = new Attribute[]{new Attribute.Default<String>(XMLParser.ID, options.noDuplicatedPrefix(modelPrefix, treePrefix)
+ BranchRateModel.BRANCH_RATES)};
//}
writer.writeOpenTag(DiscretizedBranchRatesParser.DISCRETIZED_BRANCH_RATES, attributes);
// tree
writer.writeIDref(TreeModel.TREE_MODEL, treePrefix + TreeModel.TREE_MODEL);
writer.writeOpenTag("distribution");
switch (model.getClockDistributionType()) {
case LOGNORMAL:
writer.writeOpenTag(LogNormalDistributionModelParser.LOGNORMAL_DISTRIBUTION_MODEL,
new Attribute.Default<String>(LogNormalDistributionModelParser.MEAN_IN_REAL_SPACE, "true"));
if (activeTrees.indexOf(tree) < 1) {
writeParameter("mean", ClockType.UCLD_MEAN, model, writer);
writeParameter("stdev", ClockType.UCLD_STDEV, model, writer);
} else {
writeParameterRef("mean", modelPrefix + ClockType.UCLD_MEAN, writer);
writeParameterRef("stdev", modelPrefix + ClockType.UCLD_STDEV, writer);
}
writer.writeCloseTag(LogNormalDistributionModelParser.LOGNORMAL_DISTRIBUTION_MODEL);
break;
case GAMMA:
throw new UnsupportedOperationException("Uncorrelated gamma model not implemented yet");
// break;
case CAUCHY:
throw new UnsupportedOperationException("Uncorrelated Cauchy model not implemented yet");
// break;
case EXPONENTIAL:
writer.writeOpenTag(ExponentialDistributionModel.EXPONENTIAL_DISTRIBUTION_MODEL);
if (activeTrees.indexOf(tree) < 1) {
writeParameter("mean", ClockType.UCED_MEAN, model, writer);
} else {
writeParameterRef("mean", modelPrefix + ClockType.UCED_MEAN, writer);
}
writer.writeCloseTag(ExponentialDistributionModel.EXPONENTIAL_DISTRIBUTION_MODEL);
break;
}
writer.writeCloseTag("distribution");
writer.writeOpenTag(DiscretizedBranchRatesParser.RATE_CATEGORIES);
// AR - this parameter will now set its dimension automatically when BEAST is run
// if (!options.hasIdenticalTaxa()) {
// for (AbstractPartitionData dataPartition : options.dataPartitions) {
// if (dataPartition.getPartitionClockModel().equals(model)) {
// categoryCount = (dataPartition.getTaxonCount() - 1) * 2;
// }
// }
// } else {
// categoryCount = (options.taxonList.getTaxonCount() - 1) * 2;
// }
// writeParameter(clockTree.getParameter("branchRates.categories"), categoryCount, writer);
writeParameter(clockTree.getParameter("branchRates.categories"), -1, writer);
writer.writeCloseTag(DiscretizedBranchRatesParser.RATE_CATEGORIES);
writer.writeCloseTag(DiscretizedBranchRatesParser.DISCRETIZED_BRANCH_RATES);
writer.writeText("");
writer.writeOpenTag(
RateStatisticParser.RATE_STATISTIC,
new Attribute[]{
new Attribute.Default<String>(XMLParser.ID, options.noDuplicatedPrefix(modelPrefix, treePrefix) + "meanRate"),
new Attribute.Default<String>("name", options.noDuplicatedPrefix(modelPrefix, treePrefix) + "meanRate"),
new Attribute.Default<String>("mode", "mean"),
new Attribute.Default<String>("internal", "true"),
new Attribute.Default<String>("external", "true")
}
);
writer.writeIDref(TreeModel.TREE_MODEL, treePrefix + TreeModel.TREE_MODEL);
writer.writeIDref(DiscretizedBranchRatesParser.DISCRETIZED_BRANCH_RATES, options.noDuplicatedPrefix(modelPrefix, treePrefix)
+ BranchRateModel.BRANCH_RATES);
writer.writeCloseTag(RateStatisticParser.RATE_STATISTIC);
writer.writeText("");
writer.writeOpenTag(
RateStatisticParser.RATE_STATISTIC,
new Attribute[]{
new Attribute.Default<String>(XMLParser.ID, options.noDuplicatedPrefix(modelPrefix, treePrefix) + RateStatisticParser.COEFFICIENT_OF_VARIATION),
new Attribute.Default<String>("name", options.noDuplicatedPrefix(modelPrefix, treePrefix) + RateStatisticParser.COEFFICIENT_OF_VARIATION),
new Attribute.Default<String>("mode", RateStatisticParser.COEFFICIENT_OF_VARIATION),
new Attribute.Default<String>("internal", "true"),
new Attribute.Default<String>("external", "true")
}
);
writer.writeIDref(TreeModel.TREE_MODEL, treePrefix + TreeModel.TREE_MODEL);
writer.writeIDref(DiscretizedBranchRatesParser.DISCRETIZED_BRANCH_RATES, options.noDuplicatedPrefix(modelPrefix, treePrefix)
+ BranchRateModel.BRANCH_RATES);
writer.writeCloseTag(RateStatisticParser.RATE_STATISTIC);
writer.writeText("");
writer.writeOpenTag(
RateCovarianceStatisticParser.RATE_COVARIANCE_STATISTIC,
new Attribute[]{
new Attribute.Default<String>(XMLParser.ID, options.noDuplicatedPrefix(modelPrefix, treePrefix) + "covariance"),
new Attribute.Default<String>("name", options.noDuplicatedPrefix(modelPrefix, treePrefix) + "covariance")
}
);
writer.writeIDref(TreeModel.TREE_MODEL, treePrefix + TreeModel.TREE_MODEL);
writer.writeIDref(DiscretizedBranchRatesParser.DISCRETIZED_BRANCH_RATES, options.noDuplicatedPrefix(modelPrefix, treePrefix) + BranchRateModel.BRANCH_RATES);
writer.writeCloseTag(RateCovarianceStatisticParser.RATE_COVARIANCE_STATISTIC);
}
break;
case AUTOCORRELATED:
writer.writeComment("The autocorrelated relaxed clock (Rannala & Yang, 2007)");
for (PartitionTreeModel tree : activeTrees) {
treePrefix = tree.getPrefix();
PartitionClockModelTreeModelLink clockTree = options.getPartitionClockTreeLink(model, tree);
if (clockTree == null) {
throw new IllegalArgumentException("Cannot find PartitionClockTreeLink, given clock model = " + model.getName()
+ ", tree model = " + tree.getName());
}
attributes = new Attribute[]{
new Attribute.Default<String>(XMLParser.ID, options.noDuplicatedPrefix(modelPrefix, treePrefix) + BranchRateModel.BRANCH_RATES),
new Attribute.Default<String>("episodic", "false"),
new Attribute.Default<String>("logspace", "true"),
};
writer.writeOpenTag(ACLikelihoodParser.AC_LIKELIHOOD, attributes);
writer.writeIDref(TreeModel.TREE_MODEL, treePrefix + TreeModel.TREE_MODEL);
if (!model.isEstimatedRate()) { //TODO move to options or panel select method
Parameter para = tree.getParameter(TreeModel.TREE_MODEL + "." + RateEvolutionLikelihood.ROOTRATE);//"treeModel.rootRate"
para.isFixed = true;
para.initial = model.getRate();
}
writer.writeOpenTag(RateEvolutionLikelihood.RATES,
new Attribute[]{
new Attribute.Default<String>(TreeModelParser.ROOT_NODE, "false"),
new Attribute.Default<String>(TreeModelParser.INTERNAL_NODES, "true"),
new Attribute.Default<String>(TreeModelParser.LEAF_NODES, "true")
});
writer.writeTag(ParameterParser.PARAMETER,
new Attribute.Default<String>(XMLParser.ID, options.noDuplicatedPrefix(modelPrefix, treePrefix) + TreeModel.TREE_MODEL + "."
+ TreeModelParser.NODE_RATES), true);
writer.writeCloseTag(RateEvolutionLikelihood.RATES);
writer.writeOpenTag(RateEvolutionLikelihood.ROOTRATE,
new Attribute[]{
new Attribute.Default<String>(TreeModelParser.ROOT_NODE, "true"),
new Attribute.Default<String>(TreeModelParser.INTERNAL_NODES, "false"),
new Attribute.Default<String>(TreeModelParser.LEAF_NODES, "false")
});
writer.writeTag(ParameterParser.PARAMETER,
new Attribute.Default<String>(XMLParser.ID, options.noDuplicatedPrefix(modelPrefix, treePrefix) + TreeModel.TREE_MODEL + "."
+ RateEvolutionLikelihood.ROOTRATE), true);
writer.writeCloseTag(RateEvolutionLikelihood.ROOTRATE);
// writeParameterRef("rates", treePrefix + "treeModel.nodeRates", writer);
// writeParameterRef(RateEvolutionLikelihood.ROOTRATE, treePrefix + "treeModel.rootRate", writer);
writeParameter("variance", "branchRates.var", clockTree, writer);
writer.writeCloseTag(ACLikelihoodParser.AC_LIKELIHOOD);
if (model.isEstimatedRate()) {//TODO
writer.writeText("");
writer.writeOpenTag(CompoundParameterParser.COMPOUND_PARAMETER,
new Attribute[]{new Attribute.Default<String>(XMLParser.ID, options.noDuplicatedPrefix(modelPrefix, treePrefix) + TreeModel.TREE_MODEL
+ "." + "allRates")});
writer.writeIDref(ParameterParser.PARAMETER, options.noDuplicatedPrefix(modelPrefix, treePrefix) + TreeModel.TREE_MODEL + "."
+ TreeModelParser.NODE_RATES);
writer.writeIDref(ParameterParser.PARAMETER, options.noDuplicatedPrefix(modelPrefix, treePrefix) + TreeModel.TREE_MODEL + "."
+ RateEvolutionLikelihood.ROOTRATE);
writer.writeCloseTag(CompoundParameterParser.COMPOUND_PARAMETER);
}
writer.writeText("");
writer.writeOpenTag(
RateStatisticParser.RATE_STATISTIC,
new Attribute[]{
new Attribute.Default<String>(XMLParser.ID, options.noDuplicatedPrefix(modelPrefix, treePrefix) + "meanRate"),
new Attribute.Default<String>("name", options.noDuplicatedPrefix(modelPrefix, treePrefix) + "meanRate"),
new Attribute.Default<String>("mode", "mean"),
new Attribute.Default<String>("internal", "true"),
new Attribute.Default<String>("external", "true")
}
);
writer.writeIDref(TreeModel.TREE_MODEL, treePrefix + TreeModel.TREE_MODEL);
writer.writeIDref(ACLikelihoodParser.AC_LIKELIHOOD, modelPrefix + BranchRateModel.BRANCH_RATES);
writer.writeCloseTag(RateStatisticParser.RATE_STATISTIC);
writer.writeText("");
writer.writeOpenTag(
RateStatisticParser.RATE_STATISTIC,
new Attribute[]{
new Attribute.Default<String>(XMLParser.ID, modelPrefix + RateStatisticParser.COEFFICIENT_OF_VARIATION),
new Attribute.Default<String>("name", options.noDuplicatedPrefix(modelPrefix, treePrefix) + RateStatisticParser.COEFFICIENT_OF_VARIATION),
new Attribute.Default<String>("mode", RateStatisticParser.COEFFICIENT_OF_VARIATION),
new Attribute.Default<String>("internal", "true"),
new Attribute.Default<String>("external", "true")
}
);
writer.writeIDref(TreeModel.TREE_MODEL, treePrefix + TreeModel.TREE_MODEL);
writer.writeIDref(ACLikelihoodParser.AC_LIKELIHOOD, modelPrefix + BranchRateModel.BRANCH_RATES);
writer.writeCloseTag(RateStatisticParser.RATE_STATISTIC);
writer.writeText("");
writer.writeOpenTag(
RateCovarianceStatisticParser.RATE_COVARIANCE_STATISTIC,
new Attribute[]{
new Attribute.Default<String>(XMLParser.ID, options.noDuplicatedPrefix(modelPrefix, treePrefix) + "covariance"),
new Attribute.Default<String>("name", options.noDuplicatedPrefix(modelPrefix, treePrefix) + "covariance")
}
);
writer.writeIDref(TreeModel.TREE_MODEL, treePrefix + TreeModel.TREE_MODEL);
writer.writeIDref(ACLikelihoodParser.AC_LIKELIHOOD, modelPrefix + BranchRateModel.BRANCH_RATES);
writer.writeCloseTag(RateCovarianceStatisticParser.RATE_COVARIANCE_STATISTIC);
}
break;
case RANDOM_LOCAL_CLOCK: // 1 random local clock CANNOT have different tree models
writer.writeComment("The random local clock model (Drummond & Suchard, 2010)");
if (activeTrees == null || activeTrees.size() != 1) {
throw new IllegalArgumentException("A single random local clock cannot be applied to multiple trees.");
}
treePrefix = activeTrees.get(0).getPrefix();
writer.writeOpenTag(
RandomLocalClockModelParser.LOCAL_BRANCH_RATES,
new Attribute[]{
// 1 random local clock CANNOT have different tree models,
// so use modelPrefix not noDuplicatedPrefix(modelPrefix, treePrefix)
new Attribute.Default<String>(XMLParser.ID, modelPrefix + BranchRateModel.BRANCH_RATES),
new Attribute.Default<String>("ratesAreMultipliers", "false")
}
);
writer.writeIDref(TreeModel.TREE_MODEL, treePrefix + TreeModel.TREE_MODEL);
writer.writeOpenTag("rates");
writer.writeTag(ParameterParser.PARAMETER, new Attribute.Default<String>
(XMLParser.ID, modelPrefix + ClockType.LOCAL_CLOCK + ".relativeRates")
, true);
writer.writeCloseTag("rates");
writer.writeOpenTag("rateIndicator");
writer.writeTag(ParameterParser.PARAMETER, new Attribute.Default<String>
(XMLParser.ID, modelPrefix + ClockType.LOCAL_CLOCK + ".changes")
, true);
writer.writeCloseTag("rateIndicator");
writeParameter("clockRate", "clock.rate", model, writer);
writer.writeCloseTag(RandomLocalClockModelParser.LOCAL_BRANCH_RATES);
writer.writeText("");
writer.writeOpenTag(
SumStatisticParser.SUM_STATISTIC,
new Attribute[]{
new Attribute.Default<String>(XMLParser.ID, modelPrefix + "rateChanges"),
new Attribute.Default<String>("name", modelPrefix + "rateChangeCount"),
new Attribute.Default<String>("elementwise", "true"),
}
);
writer.writeIDref(ParameterParser.PARAMETER, modelPrefix + ClockType.LOCAL_CLOCK + ".changes");
writer.writeCloseTag(SumStatisticParser.SUM_STATISTIC);
writer.writeText("");
writer.writeOpenTag(
RateStatisticParser.RATE_STATISTIC,
new Attribute[]{
new Attribute.Default<String>(XMLParser.ID, options.noDuplicatedPrefix(modelPrefix, treePrefix) + "meanRate"),
new Attribute.Default<String>("name", options.noDuplicatedPrefix(modelPrefix, treePrefix) + "meanRate"),
new Attribute.Default<String>("mode", "mean"),
new Attribute.Default<String>("internal", "true"),
new Attribute.Default<String>("external", "true")
}
);
writer.writeIDref(TreeModel.TREE_MODEL, treePrefix + TreeModel.TREE_MODEL);
writer.writeIDref(RandomLocalClockModelParser.LOCAL_BRANCH_RATES, modelPrefix + BranchRateModel.BRANCH_RATES);
writer.writeCloseTag(RateStatisticParser.RATE_STATISTIC);
writer.writeText("");
writer.writeOpenTag(
RateStatisticParser.RATE_STATISTIC,
new Attribute[]{
new Attribute.Default<String>(XMLParser.ID, options.noDuplicatedPrefix(modelPrefix, treePrefix) + RateStatisticParser.COEFFICIENT_OF_VARIATION),
new Attribute.Default<String>("name", options.noDuplicatedPrefix(modelPrefix, treePrefix) + RateStatisticParser.COEFFICIENT_OF_VARIATION),
new Attribute.Default<String>("mode", RateStatisticParser.COEFFICIENT_OF_VARIATION),
new Attribute.Default<String>("internal", "true"),
new Attribute.Default<String>("external", "true")
}
);
writer.writeIDref(TreeModel.TREE_MODEL, treePrefix + TreeModel.TREE_MODEL);
writer.writeIDref(RandomLocalClockModelParser.LOCAL_BRANCH_RATES, modelPrefix + BranchRateModel.BRANCH_RATES);
writer.writeCloseTag(RateStatisticParser.RATE_STATISTIC);
writer.writeText("");
writer.writeOpenTag(
RateCovarianceStatisticParser.RATE_COVARIANCE_STATISTIC,
new Attribute[]{
new Attribute.Default<String>(XMLParser.ID, options.noDuplicatedPrefix(modelPrefix, treePrefix) + "covariance"),
new Attribute.Default<String>("name", options.noDuplicatedPrefix(modelPrefix, treePrefix) + "covariance")
}
);
writer.writeIDref(TreeModel.TREE_MODEL, treePrefix + TreeModel.TREE_MODEL);
writer.writeIDref(RandomLocalClockModelParser.LOCAL_BRANCH_RATES, modelPrefix + BranchRateModel.BRANCH_RATES);
writer.writeCloseTag(RateCovarianceStatisticParser.RATE_COVARIANCE_STATISTIC);
break;
default:
throw new IllegalArgumentException("Unknown clock model");
}
}
public void writeAllClockRateRefs(PartitionClockModel model, XMLWriter writer) {
writer.writeIDref(ParameterParser.PARAMETER, getClockRateString(model));
}
public String getClockRateString(PartitionClockModel model) {
setModelPrefix(model.getPrefix());
switch (model.getClockType()) {
case STRICT_CLOCK:
case RANDOM_LOCAL_CLOCK:
return modelPrefix + "clock.rate";
case UNCORRELATED:
switch (model.getClockDistributionType()) {
case LOGNORMAL:
return modelPrefix + ClockType.UCLD_MEAN;
case GAMMA:
throw new UnsupportedOperationException("Uncorrelated gamma model not supported yet");
// return modelPrefix + ClockType.UCGD_SCALE;
case CAUCHY:
throw new UnsupportedOperationException("Uncorrelated Cauchy model not supported yet");
// return modelPrefix + ClockType.UCCD_MEAN;
case EXPONENTIAL:
return modelPrefix + ClockType.UCED_MEAN;
}
case AUTOCORRELATED:
//TODO
throw new IllegalArgumentException("Autocorrelated Relaxed Clock, writeAllClockRateRefs(PartitionClockModel model, XMLWriter writer)");
// break;
default:
throw new IllegalArgumentException("Unknown clock model");
}
}
public void writeLog(PartitionClockModel model, XMLWriter writer) {
setModelPrefix(model.getPrefix());
switch (model.getClockType()) {
case STRICT_CLOCK:
case RANDOM_LOCAL_CLOCK:
writer.writeIDref(ParameterParser.PARAMETER, model.getPrefix() + "clock.rate");
break;
case UNCORRELATED:
switch (model.getClockDistributionType()) {
case LOGNORMAL:
writer.writeIDref(ParameterParser.PARAMETER, model.getPrefix() + ClockType.UCLD_MEAN);
writer.writeIDref(ParameterParser.PARAMETER, model.getPrefix() + ClockType.UCLD_STDEV);
break;
case GAMMA:
throw new UnsupportedOperationException("Uncorrelated gamma model not supported yet");
case CAUCHY:
throw new UnsupportedOperationException("Uncorrelated Couchy model not supported yet");
case EXPONENTIAL:
writer.writeIDref(ParameterParser.PARAMETER, model.getPrefix() + ClockType.UCED_MEAN);
break;
}
case AUTOCORRELATED:
// TODO
break;
default:
throw new IllegalArgumentException("Unknown clock model");
}
}
public void writeLogStatistic(PartitionClockModel model, XMLWriter writer) {
setModelPrefix(model.getPrefix());
switch (model.getClockType()) {
case STRICT_CLOCK:
break;
case UNCORRELATED:
for (PartitionTreeModel tree : options.getPartitionTreeModels(options.getDataPartitions(model))) {
writer.writeIDref(RateStatisticParser.RATE_STATISTIC, options.noDuplicatedPrefix(model.getPrefix(), tree.getPrefix()) + "meanRate");
writer.writeIDref(RateStatisticParser.RATE_STATISTIC, options.noDuplicatedPrefix(model.getPrefix(), tree.getPrefix()) + RateStatisticParser.COEFFICIENT_OF_VARIATION);
writer.writeIDref(RateCovarianceStatisticParser.RATE_COVARIANCE_STATISTIC, options.noDuplicatedPrefix(model.getPrefix(), tree.getPrefix()) + "covariance");
}
break;
case AUTOCORRELATED:
// TODO
for (PartitionTreeModel tree : options.getPartitionTreeModels(options.getDataPartitions(model))) {
writer.writeIDref(RateStatisticParser.RATE_STATISTIC, options.noDuplicatedPrefix(model.getPrefix(), tree.getPrefix()) + "meanRate");
writer.writeIDref(RateStatisticParser.RATE_STATISTIC, options.noDuplicatedPrefix(model.getPrefix(), tree.getPrefix()) + RateStatisticParser.COEFFICIENT_OF_VARIATION);
writer.writeIDref(RateCovarianceStatisticParser.RATE_COVARIANCE_STATISTIC, options.noDuplicatedPrefix(model.getPrefix(), tree.getPrefix()) + "covariance");
writer.writeIDref(ParameterParser.PARAMETER, options.noDuplicatedPrefix(model.getPrefix(), tree.getPrefix()) + "branchRates.var");
writer.writeIDref(ParameterParser.PARAMETER, options.noDuplicatedPrefix(model.getPrefix(), tree.getPrefix()) + "treeModel.rootRate");
}
break;
case RANDOM_LOCAL_CLOCK:
writer.writeIDref(SumStatisticParser.SUM_STATISTIC, model.getPrefix() + "rateChanges");
for (PartitionTreeModel tree : options.getPartitionTreeModels(options.getDataPartitions(model))) {
writer.writeIDref(RateStatisticParser.RATE_STATISTIC, options.noDuplicatedPrefix(model.getPrefix(), tree.getPrefix()) + "meanRate");
writer.writeIDref(RateStatisticParser.RATE_STATISTIC, options.noDuplicatedPrefix(model.getPrefix(), tree.getPrefix()) + RateStatisticParser.COEFFICIENT_OF_VARIATION);
writer.writeIDref(RateCovarianceStatisticParser.RATE_COVARIANCE_STATISTIC, options.noDuplicatedPrefix(model.getPrefix(), tree.getPrefix()) + "covariance");
}
break;
default:
throw new IllegalArgumentException("Unknown clock model");
}
}
public void writeClockLikelihoodReferences(XMLWriter writer) {
for (AbstractPartitionData partition : options.dataPartitions) { // Each PD has one TreeLikelihood
PartitionClockModel clockModel = partition.getPartitionClockModel();
if (clockModel != null && clockModel.getClockType() == ClockType.AUTOCORRELATED) {
throw new UnsupportedOperationException("Autocorrelated relaxed clock model not implemented yet");
// writer.writeIDref(ACLikelihoodParser.AC_LIKELIHOOD, clockModel.getPrefix() + BranchRateModel.BRANCH_RATES);
}
}
}
}