public void removeSelection() {
int[] selRows = dataTable.getSelectedRows();
Set<AbstractPartitionData> partitionsToRemove = new HashSet<AbstractPartitionData>();
for (int row : selRows) {
partitionsToRemove.add(options.dataPartitions.get(row));
}
boolean hasIdenticalTaxa =
options.hasIdenticalTaxa(); // need to check this before removing partitions
// TODO: would probably be a good idea to check if the user wants to remove the last partition
options.dataPartitions.removeAll(partitionsToRemove);
if (options.dataPartitions.size() == 0) {
// all data partitions removed so reset the taxa
options.reset();
useStarBEASTCheck.setSelected(false);
frame.setupStarBEAST(false);
frame.statusLabel.setText("");
frame.setAllOptions();
frame.getExportAction().setEnabled(false);
} else if (!hasIdenticalTaxa) {
options.updateTaxonList();
}
dataTableModel.fireTableDataChanged();
fireDataChanged();
}
public void removeSelection() {
int[] selRows = dataTable.getSelectedRows();
Set<PartitionData> partitionsToRemove = new HashSet<PartitionData>();
for (int row : selRows) {
partitionsToRemove.add(options.dataPartitions.get(row));
}
// TODO: would probably be a good idea to check if the user wants to remove the last partition
options.dataPartitions.removeAll(partitionsToRemove);
// if (options.allowDifferentTaxa && options.dataPartitions.size() < 2) {
// uncheckAllowDifferentTaxa();
// }
if (options.getNonTraitsDataList().size() == 0) {
// all data partitions removed so reset the taxa
options.reset();
useStarBEASTCheck.setSelected(false);
frame.statusLabel.setText("");
frame.setAllOptions();
frame.getExportAction().setEnabled(false);
}
dataTableModel.fireTableDataChanged();
fireDataChanged();
}
public void setOptions(BeautiOptions options) {
this.options = options;
resetPanel();
settingOptions = true;
int selRow = partitionTable.getSelectedRow();
partitionTableModel.fireTableDataChanged();
if (options.getDataPartitions().size() > 0) {
if (selRow < 0) {
selRow = 0;
}
partitionTable.getSelectionModel().setSelectionInterval(selRow, selRow);
setCurrentPartition(options.getDataPartitions().get(selRow));
}
AncestralStatesOptionsPanel panel = optionsPanels.get(currentPartition);
if (panel != null) {
panel.setupPanel();
}
settingOptions = false;
validate();
repaint();
}
private void updateOtherFileNames(BeautiOptions options) {
if (options.fileNameStem != null) {
// fileNameStemField.setText(options.fileNameStem);
options.logFileName = options.fileNameStem + ".log";
if (addTxt.isSelected()) options.logFileName = options.logFileName + ".txt";
logFileNameField.setText(options.logFileName);
// if (options.mapTreeFileName == null) {
// mapTreeFileNameField.setText(options.fileNameStem + ".MAP.tree");
// } else {
// mapTreeFileNameField.setText(options.mapTreeFileName);
// }
updateTreeFileNameList();
treeFileNameField.setText(displayTreeList(options.treeFileName));
if (options.substTreeLog) {
substTreeFileNameField.setText(displayTreeList(options.substTreeFileName));
} else {
substTreeFileNameField.setText("");
}
options.operatorAnalysisFileName = options.fileNameStem + ".ops";
if (addTxt.isSelected()) {
options.operatorAnalysisFileName = options.operatorAnalysisFileName + ".txt";
}
operatorAnalaysisFileNameField.setEnabled(options.operatorAnalysis);
if (options.operatorAnalysis) {
operatorAnalaysisFileNameField.setText(options.operatorAnalysisFileName);
} else {
operatorAnalaysisFileNameField.setText("");
}
// mapTreeLogCheck.setEnabled(true);
// mapTreeLogCheck.setSelected(options.mapTreeLog);
// mapTreeFileNameField.setEnabled(options.mapTreeLog);
substTreeLogCheck.setEnabled(true);
substTreeLogCheck.setSelected(options.substTreeLog);
} else {
// fileNameStemField.setText(fileNameStem);
// fileNameStemField.setEnabled(false);
logFileNameField.setText(DEFAULT_FILE_NAME_STEM + ".log");
treeFileNameField.setText(DEFAULT_FILE_NAME_STEM + "." + STARBEASTOptions.TREE_FILE_NAME);
// mapTreeLogCheck.setEnabled(false);
// mapTreeFileNameField.setEnabled(false);
// mapTreeFileNameField.setText("untitled");
substTreeLogCheck.setSelected(false);
substTreeFileNameField.setEnabled(false);
substTreeFileNameField.setText("");
operatorAnalaysisCheck.setSelected(false);
operatorAnalaysisFileNameField.setText("");
}
}
public void setOptions(BeautiOptions options) {
this.options = options;
modelsChanged();
useStarBEASTCheck.setEnabled(
options.getNonTraitsDataList().size() > 0); // single partition is allowed
createImportTraitButton.setEnabled(options.getNonTraitsDataList().size() > 0);
dataTableModel.fireTableDataChanged();
}
public void linkTrees() { // keep previous PartitionTreePrior for reuse
int[] selRows = dataTable.getSelectedRows();
List<AbstractPartitionData> selectedPartitionData = new ArrayList<AbstractPartitionData>();
for (int row : selRows) {
AbstractPartitionData partition = options.dataPartitions.get(row);
if (!selectedPartitionData.contains(partition)) selectedPartitionData.add(partition);
}
if (selectedPartitionData.size() > 1) {
if (!options.hasIdenticalTaxa(selectedPartitionData)) {
String errMsg = "To share a tree, partitions need to have identical taxa.";
if (selectedPartitionData.get(0).getDataType().getType() == DataType.MICRO_SAT)
errMsg += "\nThe data must be all diploid or all haploid when you want to link the tree.";
JOptionPane.showMessageDialog(
this, errMsg, "Illegal Configuration", JOptionPane.ERROR_MESSAGE);
return;
}
}
Object[] treeArray = options.getPartitionTreeModels(selectedPartitionData).toArray();
if (selectTreeDialog == null) {
selectTreeDialog = new SelectTreeDialog(frame);
}
int result = selectTreeDialog.showDialog(treeArray);
if (result != JOptionPane.CANCEL_OPTION) {
PartitionTreeModel model = selectTreeDialog.getTree();
if (selectTreeDialog.getMakeCopy()) {
model.setName(selectTreeDialog.getName());
}
PartitionTreePrior prior = model.getPartitionTreePrior();
options.linkTreePriors(prior);
for (AbstractPartitionData partition : selectedPartitionData) {
partition.setPartitionTreeModel(model);
}
for (Taxa taxa :
options.taxonSets) { // Issue 454: all the taxon sets are deleted when link/unlink tree
PartitionTreeModel prevModel = options.taxonSetsTreeModel.get(taxa);
if (prevModel != model) options.taxonSetsTreeModel.put(taxa, model);
}
}
modelsChanged();
fireDataChanged();
repaint();
}
public void linkModels() {
int[] selRows = dataTable.getSelectedRows();
List<AbstractPartitionData> selectedPartitionData = new ArrayList<AbstractPartitionData>();
DataType dateType = null;
for (int row : selRows) {
AbstractPartitionData partition = options.dataPartitions.get(row);
if (dateType == null) {
dateType = partition.getDataType();
} else {
if (partition.getDataType() != dateType) {
JOptionPane.showMessageDialog(
this,
"Can only link the models for data partitions \n"
+ "of the same data type (e.g., nucleotides)",
"Unable to link models",
JOptionPane.ERROR_MESSAGE);
return;
}
}
if (!selectedPartitionData.contains(partition)) selectedPartitionData.add(partition);
}
Object[] modelArray = options.getPartitionSubstitutionModels(selectedPartitionData).toArray();
if (selectModelDialog == null) {
selectModelDialog = new SelectModelDialog(frame);
}
int result = selectModelDialog.showDialog(modelArray);
if (result != JOptionPane.CANCEL_OPTION) {
PartitionSubstitutionModel model = selectModelDialog.getModel();
if (selectModelDialog.getMakeCopy()) {
model.setName(selectModelDialog.getName());
}
for (AbstractPartitionData partition : selectedPartitionData) {
partition.setPartitionSubstitutionModel(model);
}
}
if (options.getPartitionSubstitutionModels(Microsatellite.INSTANCE).size() <= 1) {
options.shareMicroSat = true;
}
modelsChanged();
fireDataChanged();
repaint();
}
public void linkTrees() { // keep previous PartitionTreePrior for reuse
int[] selRows = dataTable.getSelectedRows();
List<PartitionData> selectedPartitionData = new ArrayList<PartitionData>();
for (int row : selRows) {
PartitionData partition = options.dataPartitions.get(row);
if (!selectedPartitionData.contains(partition)) selectedPartitionData.add(partition);
}
if (options.allowDifferentTaxa) { // BEAST cannot handle multi <taxa> ref for 1 tree
if (selectedPartitionData.size() > 1) {
if (!options.validateDiffTaxa(selectedPartitionData)) {
JOptionPane.showMessageDialog(
this,
"To accommodate different taxa for each partition trees cannot be linked.",
"Illegal Configuration",
JOptionPane.ERROR_MESSAGE);
return;
}
}
}
Object[] treeArray = options.getPartitionTreeModels(selectedPartitionData).toArray();
if (selectTreeDialog == null) {
selectTreeDialog = new SelectTreeDialog(frame);
}
int result = selectTreeDialog.showDialog(treeArray);
if (result != JOptionPane.CANCEL_OPTION) {
PartitionTreeModel model = selectTreeDialog.getTree();
if (selectTreeDialog.getMakeCopy()) {
model.setName(selectTreeDialog.getName());
}
PartitionTreePrior prior = model.getPartitionTreePrior();
options.linkTreePriors(prior);
for (PartitionData partition : selectedPartitionData) {
partition.setPartitionTreeModel(model);
}
}
modelsChanged();
fireDataChanged();
options.taxonSets.clear();
options.taxonSetsMono.clear();
repaint();
}
private void selectionChanged() {
if (settingOptions) return;
int selRow = partitionTable.getSelectedRow();
if (selRow >= options.getDataPartitions().size()) {
selRow = 0;
partitionTable.getSelectionModel().setSelectionInterval(selRow, selRow);
}
if (selRow >= 0) {
setCurrentPartition(options.getDataPartitions().get(selRow));
// frame.modelSelectionChanged(!isUsed(selRow));
}
}
public void linkClocks() { // keep previous PartitionTreePrior for reuse
int[] selRows = dataTable.getSelectedRows();
List<PartitionData> selectedPartitionData = new ArrayList<PartitionData>();
for (int row : selRows) {
PartitionData partition = options.dataPartitions.get(row);
if (!selectedPartitionData.contains(partition)) selectedPartitionData.add(partition);
}
Object[] modelArray = options.getPartitionClockModels(selectedPartitionData).toArray();
if (selectClockDialog == null) {
selectClockDialog = new SelectClockDialog(frame);
}
int result = selectClockDialog.showDialog(modelArray);
if (result != JOptionPane.CANCEL_OPTION) {
PartitionClockModel model = selectClockDialog.getModel();
if (selectClockDialog.getMakeCopy()) {
model.setName(selectClockDialog.getName());
}
for (PartitionData partition : selectedPartitionData) {
partition.setPartitionClockModel(model);
}
}
modelsChanged();
fireDataChanged();
repaint();
}
public void unlinkTrees() { // reuse previous PartitionTreePrior
int[] selRows = dataTable.getSelectedRows();
for (int row : selRows) {
PartitionData partition = options.dataPartitions.get(row);
PartitionTreeModel model = partition.getPartitionTreeModel();
if (!model.getName().equals(partition.getName())
&& partition.getTraitType() == null) { // not a trait
PartitionTreeModel newTree = new PartitionTreeModel(options, partition);
// this prevents partition not broken, and used for unsharing tree prior only,
// because sharing uses shareSameTreePrior, unsharing uses getPartitionTreePrior
// newTree.setPartitionTreePrior(newPrior); // important
partition.setPartitionTreeModel(newTree);
}
}
options.linkTreePriors(frame.getCurrentPartitionTreePrior());
modelsChanged();
fireDataChanged();
options.taxonSets.clear();
options.taxonSetsMono.clear();
repaint();
}
private void resetPanel() {
if (!options.hasData()) {
currentPartition = null;
optionsPanels.clear();
optionsPanelParent.removeAll();
}
}
public void setOptions(BeautiOptions options) {
this.options = options;
chainLengthField.setValue(options.chainLength);
echoEveryField.setValue(options.echoEvery);
logEveryField.setValue(options.logEvery);
if (options.fileNameStem != null) {
fileNameStemField.setText(options.fileNameStem);
} else {
fileNameStemField.setText(DEFAULT_FILE_NAME_STEM);
fileNameStemField.setEnabled(false);
}
operatorAnalaysisCheck.setSelected(options.operatorAnalysis);
updateOtherFileNames(options);
if (options.contains(Microsatellite.INSTANCE)) {
samplePriorCheckBox.setSelected(false);
samplePriorCheckBox.setVisible(false);
} else {
samplePriorCheckBox.setVisible(true);
samplePriorCheckBox.setSelected(options.samplePriorOnly);
}
optionsPanel.validate();
optionsPanel.repaint();
}
public boolean createFromTraits(List<TraitData> traits) {
int selRow = -1;
if (selectTraitDialog == null) {
selectTraitDialog = new SelectTraitDialog(frame);
}
if (traits == null || traits.size() == 0) {
int result = selectTraitDialog.showDialog(options.traits, null);
if (result != JOptionPane.CANCEL_OPTION) {
TraitData trait = selectTraitDialog.getTrait();
String name = trait.getName();
if (selectTraitDialog.getMakeCopy()) {
name = selectTraitDialog.getName();
}
selRow = options.createPartitionForTraits(name, trait);
} else {
return false;
}
} else {
if (traits.size() > 1) {
// a set of traits have been passed to the function
int result = selectTraitDialog.showDialog(null, null);
if (result != JOptionPane.CANCEL_OPTION) {
String name = selectTraitDialog.getName();
selRow = options.createPartitionForTraits(name, traits);
} else {
return false;
}
} else {
selRow = options.createPartitionForTraits(traits.get(0).getName(), traits);
}
}
modelsChanged();
dataTableModel.fireTableDataChanged();
if (selRow != -1) {
dataTable.getSelectionModel().setSelectionInterval(selRow, selRow);
}
fireDataChanged();
repaint();
return true;
}
private boolean parameterExists(String name) {
for (Parameter parameter : options.selectParameters()) {
if (parameter.getName().equals(name)) {
return true;
}
}
return false;
}
private void modelsChanged() {
TableColumn col = dataTable.getColumnModel().getColumn(5);
col.setCellEditor(new ComboBoxCellEditor());
col = dataTable.getColumnModel().getColumn(6);
col.setCellEditor(new ComboBoxCellEditor());
col = dataTable.getColumnModel().getColumn(7);
col.setCellEditor(
new DefaultCellEditor(new JComboBox(options.getNonTraitPartitionTreeModels().toArray())));
}
private void fireDataChanged() {
// options.updateLinksBetweenPDPCMPSMPTMPTPP();
options.updatePartitionAllLinks();
if (!(options.clockModelOptions.getRateOptionClockModel() == FixRateType.TIP_CALIBRATED
|| options.clockModelOptions.getRateOptionClockModel() == FixRateType.NODE_CALIBRATED
|| options.clockModelOptions.getRateOptionClockModel() == FixRateType.RATE_CALIBRATED)) {
// TODO correct?
options.clockModelOptions.fixRateOfFirstClockPartition();
}
frame.setDirty();
}
private void updateTreeFileNameList() {
options.treeFileName.clear();
options.substTreeFileName.clear();
String treeFN;
for (PartitionTreeModel tree : options.getPartitionTreeModels()) {
if (options.substTreeLog) {
treeFN =
options.fileNameStem
+ "."
+ tree.getPrefix()
+ "(time)."
+ STARBEASTOptions.TREE_FILE_NAME;
} else {
treeFN =
options.fileNameStem
+ "."
+ tree.getPrefix()
+ STARBEASTOptions.TREE_FILE_NAME; // stem.partitionName.tree
}
if (addTxt.isSelected()) treeFN = treeFN + ".txt";
options.treeFileName.add(treeFN);
if (options.substTreeLog) {
treeFN =
options.fileNameStem
+ "."
+ tree.getPrefix()
+ "(subst)."
+ STARBEASTOptions.TREE_FILE_NAME;
if (addTxt.isSelected()) treeFN = treeFN + ".txt";
options.substTreeFileName.add(treeFN);
}
}
if (options.useStarBEAST) {
treeFN = options.fileNameStem + "." + options.starBEASTOptions.SPECIES_TREE_FILE_NAME;
if (addTxt.isSelected()) treeFN = treeFN + ".txt";
options.treeFileName.add(treeFN);
// TODO: species sub tree
}
}
public void getOptions(BeautiOptions options) {
options.fileNameStem = fileNameStemField.getText();
options.logFileName = logFileNameField.getText();
// options.mapTreeLog = mapTreeLogCheck.isSelected();
// options.mapTreeFileName = mapTreeFileNameField.getText();
options.substTreeLog = substTreeLogCheck.isSelected();
updateTreeFileNameList();
options.operatorAnalysis = operatorAnalaysisCheck.isSelected();
options.operatorAnalysisFileName = operatorAnalaysisFileNameField.getText();
options.samplePriorOnly = samplePriorCheckBox.isSelected();
}
/**
* Write the marginalLikelihoodEstimator, pathSamplingAnalysis and steppingStoneSamplingAnalysis
* blocks.
*
* @param writer XMLWriter
*/
public void writeMLE(XMLWriter writer, MarginalLikelihoodEstimationOptions options) {
if (options.performMLE) {
writer.writeComment("Define marginal likelihood estimator (PS/SS) settings");
List<Attribute> attributes = new ArrayList<Attribute>();
// attributes.add(new Attribute.Default<String>(XMLParser.ID, "mcmc"));
attributes.add(
new Attribute.Default<Integer>(
MarginalLikelihoodEstimator.CHAIN_LENGTH, options.mleChainLength));
attributes.add(
new Attribute.Default<Integer>(
MarginalLikelihoodEstimator.PATH_STEPS, options.pathSteps));
attributes.add(
new Attribute.Default<String>(
MarginalLikelihoodEstimator.PATH_SCHEME, options.pathScheme));
if (!options.pathScheme.equals(MarginalLikelihoodEstimator.LINEAR)) {
attributes.add(
new Attribute.Default<Double>(
MarginalLikelihoodEstimator.ALPHA, options.schemeParameter));
}
writer.writeOpenTag(MarginalLikelihoodEstimator.MARGINAL_LIKELIHOOD_ESTIMATOR, attributes);
writer.writeOpenTag("samplers");
writer.writeIDref("mcmc", "mcmc");
writer.writeCloseTag("samplers");
attributes = new ArrayList<Attribute>();
attributes.add(new Attribute.Default<String>(XMLParser.ID, "pathLikelihood"));
writer.writeOpenTag(PathLikelihood.PATH_LIKELIHOOD, attributes);
writer.writeOpenTag(PathLikelihood.SOURCE);
writer.writeIDref(CompoundLikelihoodParser.POSTERIOR, CompoundLikelihoodParser.POSTERIOR);
writer.writeCloseTag(PathLikelihood.SOURCE);
writer.writeOpenTag(PathLikelihood.DESTINATION);
writer.writeIDref(CompoundLikelihoodParser.PRIOR, CompoundLikelihoodParser.PRIOR);
writer.writeCloseTag(PathLikelihood.DESTINATION);
writer.writeCloseTag(PathLikelihood.PATH_LIKELIHOOD);
attributes = new ArrayList<Attribute>();
attributes.add(new Attribute.Default<String>(XMLParser.ID, "MLELog"));
attributes.add(new Attribute.Default<Integer>("logEvery", options.mleLogEvery));
attributes.add(new Attribute.Default<String>("fileName", options.mleFileName));
writer.writeOpenTag("log", attributes);
writer.writeIDref("pathLikelihood", "pathLikelihood");
writer.writeCloseTag("log");
writer.writeCloseTag(MarginalLikelihoodEstimator.MARGINAL_LIKELIHOOD_ESTIMATOR);
writer.writeComment("Path sampling estimator from collected samples");
attributes = new ArrayList<Attribute>();
attributes.add(new Attribute.Default<String>("fileName", options.mleFileName));
writer.writeOpenTag(PathSamplingAnalysis.PATH_SAMPLING_ANALYSIS, attributes);
writer.writeTag(
"likelihoodColumn", new Attribute.Default<String>("name", "pathLikelihood.delta"), true);
writer.writeTag(
"thetaColumn", new Attribute.Default<String>("name", "pathLikelihood.theta"), true);
writer.writeCloseTag(PathSamplingAnalysis.PATH_SAMPLING_ANALYSIS);
writer.writeComment("Stepping-stone sampling estimator from collected samples");
attributes = new ArrayList<Attribute>();
attributes.add(new Attribute.Default<String>("fileName", options.mleFileName));
writer.writeOpenTag(
SteppingStoneSamplingAnalysis.STEPPING_STONE_SAMPLING_ANALYSIS, attributes);
writer.writeTag(
"likelihoodColumn", new Attribute.Default<String>("name", "pathLikelihood.delta"), true);
writer.writeTag(
"thetaColumn", new Attribute.Default<String>("name", "pathLikelihood.theta"), true);
writer.writeCloseTag(SteppingStoneSamplingAnalysis.STEPPING_STONE_SAMPLING_ANALYSIS);
} else if (options.performMLEGSS) {
// First define necessary components for the tree working prior
if (options.choiceTreeWorkingPrior.equals("Product of exponential distributions")) {
// more general product of exponentials needs to be constructed
if (DEBUG) {
System.err.println("productOfExponentials selected: " + options.choiceTreeWorkingPrior);
}
List<Attribute> attributes = new ArrayList<Attribute>();
attributes.add(new Attribute.Default<String>(XMLParser.ID, "exponentials"));
attributes.add(new Attribute.Default<String>("fileName", beautiOptions.logFileName));
attributes.add(
new Attribute.Default<String>("burnin", "" + beautiOptions.chainLength * 0.10));
attributes.add(
new Attribute.Default<String>("parameterColumn", "coalescentEventsStatistic"));
attributes.add(
new Attribute.Default<String>(
"dimension", "" + (beautiOptions.taxonList.getTaxonCount() - 1)));
writer.writeOpenTag(
TreeWorkingPriorParsers.PRODUCT_OF_EXPONENTIALS_POSTERIOR_MEANS_LOESS, attributes);
writer.writeTag(
TreeModel.TREE_MODEL,
new Attribute.Default<String>(XMLParser.ID, TreeModel.TREE_MODEL),
true);
writer.writeCloseTag(TreeWorkingPriorParsers.PRODUCT_OF_EXPONENTIALS_POSTERIOR_MEANS_LOESS);
} else {
// matching coalescent model has to be constructed
// getting the coalescent model
if (DEBUG) {
System.err.println(
"matching coalescent model selected: " + options.choiceTreeWorkingPrior);
System.err.println(beautiOptions.getPartitionTreePriors().get(0).getNodeHeightPrior());
}
/*for (PartitionTreePrior prior : options.getPartitionTreePriors()) {
treePriorGenerator.writeTreePriorModel(prior, writer);
writer.writeText("");
}*/
// TODO: extend for more than 1 coalescent model?
TreePriorType nodeHeightPrior =
beautiOptions.getPartitionTreePriors().get(0).getNodeHeightPrior();
switch (nodeHeightPrior) {
case CONSTANT:
writer.writeComment("A working prior for the constant population size model.");
writer.writeOpenTag(
ConstantPopulationModelParser.CONSTANT_POPULATION_MODEL,
new Attribute[] {
new Attribute.Default<String>(XMLParser.ID, modelPrefix + "constantReference"),
new Attribute.Default<String>(
"units", Units.Utils.getDefaultUnitName(beautiOptions.units))
});
writer.writeOpenTag(ConstantPopulationModelParser.POPULATION_SIZE);
writeParameter(
"constantReference.popSize",
"constant.popSize",
beautiOptions.logFileName,
(int) (options.mleChainLength * 0.10),
writer);
writer.writeCloseTag(ConstantPopulationModelParser.POPULATION_SIZE);
writer.writeCloseTag(ConstantPopulationModelParser.CONSTANT_POPULATION_MODEL);
writer.writeComment("A working prior for the coalescent.");
writer.writeOpenTag(
CoalescentLikelihoodParser.COALESCENT_LIKELIHOOD,
new Attribute[] {
new Attribute.Default<String>(XMLParser.ID, modelPrefix + "coalescentReference")
});
writer.writeOpenTag(CoalescentLikelihoodParser.MODEL);
writer.writeIDref(
ConstantPopulationModelParser.CONSTANT_POPULATION_MODEL,
beautiOptions.getPartitionTreePriors().get(0).getPrefix() + "constantReference");
writer.writeCloseTag(CoalescentLikelihoodParser.MODEL);
writer.writeOpenTag(CoalescentLikelihoodParser.POPULATION_TREE);
writer.writeIDref(TreeModel.TREE_MODEL, modelPrefix + TreeModel.TREE_MODEL);
writer.writeCloseTag(CoalescentLikelihoodParser.POPULATION_TREE);
writer.writeCloseTag(CoalescentLikelihoodParser.COALESCENT_LIKELIHOOD);
break;
case EXPONENTIAL:
writer.writeComment("A working prior for the exponential growth model.");
writer.writeOpenTag(
ExponentialGrowthModelParser.EXPONENTIAL_GROWTH_MODEL,
new Attribute[] {
new Attribute.Default<String>(XMLParser.ID, modelPrefix + "exponentialReference"),
new Attribute.Default<String>(
"units", Units.Utils.getDefaultUnitName(beautiOptions.units))
});
writer.writeOpenTag(ExponentialGrowthModelParser.POPULATION_SIZE);
writeParameter(
"exponentialReference.popSize",
"exponential.popSize",
beautiOptions.logFileName,
(int) (options.mleChainLength * 0.10),
writer);
writer.writeCloseTag(ExponentialGrowthModelParser.POPULATION_SIZE);
writer.writeOpenTag(ExponentialGrowthModelParser.GROWTH_RATE);
writeParameter(
"exponentialReference.growthRate",
"exponential.growthRate",
beautiOptions.logFileName,
(int) (options.mleChainLength * 0.10),
writer);
writer.writeCloseTag(ExponentialGrowthModelParser.GROWTH_RATE);
writer.writeCloseTag(ExponentialGrowthModelParser.EXPONENTIAL_GROWTH_MODEL);
writer.writeComment("A working prior for the coalescent.");
writer.writeOpenTag(
CoalescentLikelihoodParser.COALESCENT_LIKELIHOOD,
new Attribute[] {
new Attribute.Default<String>(XMLParser.ID, modelPrefix + "coalescentReference")
});
writer.writeOpenTag(CoalescentLikelihoodParser.MODEL);
writer.writeIDref(
ExponentialGrowthModelParser.EXPONENTIAL_GROWTH_MODEL,
beautiOptions.getPartitionTreePriors().get(0).getPrefix() + "constantReference");
writer.writeCloseTag(CoalescentLikelihoodParser.MODEL);
writer.writeOpenTag(CoalescentLikelihoodParser.POPULATION_TREE);
writer.writeIDref(TreeModel.TREE_MODEL, modelPrefix + TreeModel.TREE_MODEL);
writer.writeCloseTag(CoalescentLikelihoodParser.POPULATION_TREE);
writer.writeCloseTag(CoalescentLikelihoodParser.COALESCENT_LIKELIHOOD);
break;
case LOGISTIC:
writer.writeComment("A working prior for the logistic growth model.");
writer.writeOpenTag(
LogisticGrowthModelParser.LOGISTIC_GROWTH_MODEL,
new Attribute[] {
new Attribute.Default<String>(XMLParser.ID, modelPrefix + "logisticReference"),
new Attribute.Default<String>(
"units", Units.Utils.getDefaultUnitName(beautiOptions.units))
});
writer.writeOpenTag(LogisticGrowthModelParser.POPULATION_SIZE);
writeParameter(
"logisticReference.popSize",
"logistic.popSize",
beautiOptions.logFileName,
(int) (options.mleChainLength * 0.10),
writer);
writer.writeCloseTag(LogisticGrowthModelParser.POPULATION_SIZE);
writer.writeOpenTag(LogisticGrowthModelParser.GROWTH_RATE);
writeParameter(
"logisticReference.growthRate",
"logistic.growthRate",
beautiOptions.logFileName,
(int) (options.mleChainLength * 0.10),
writer);
writer.writeCloseTag(LogisticGrowthModelParser.GROWTH_RATE);
writer.writeOpenTag(LogisticGrowthModelParser.TIME_50);
writeParameter(
"logisticReference.t50",
"logistic.t50",
beautiOptions.logFileName,
(int) (options.mleChainLength * 0.10),
writer);
writer.writeCloseTag(LogisticGrowthModelParser.TIME_50);
writer.writeCloseTag(LogisticGrowthModelParser.LOGISTIC_GROWTH_MODEL);
writer.writeComment("A working prior for the coalescent.");
writer.writeOpenTag(
CoalescentLikelihoodParser.COALESCENT_LIKELIHOOD,
new Attribute[] {
new Attribute.Default<String>(XMLParser.ID, modelPrefix + "coalescentReference")
});
writer.writeOpenTag(CoalescentLikelihoodParser.MODEL);
writer.writeIDref(
LogisticGrowthModelParser.LOGISTIC_GROWTH_MODEL,
beautiOptions.getPartitionTreePriors().get(0).getPrefix() + "constantReference");
writer.writeCloseTag(CoalescentLikelihoodParser.MODEL);
writer.writeOpenTag(CoalescentLikelihoodParser.POPULATION_TREE);
writer.writeIDref(TreeModel.TREE_MODEL, modelPrefix + TreeModel.TREE_MODEL);
writer.writeCloseTag(CoalescentLikelihoodParser.POPULATION_TREE);
writer.writeCloseTag(CoalescentLikelihoodParser.COALESCENT_LIKELIHOOD);
break;
case EXPANSION:
writer.writeComment("A working prior for the expansion growth model.");
writer.writeOpenTag(
ExpansionModelParser.EXPANSION_MODEL,
new Attribute[] {
new Attribute.Default<String>(XMLParser.ID, modelPrefix + "expansionReference"),
new Attribute.Default<String>(
"units", Units.Utils.getDefaultUnitName(beautiOptions.units))
});
writer.writeOpenTag(ExpansionModelParser.POPULATION_SIZE);
writeParameter(
"expansionReference.popSize",
"expansion.popSize",
beautiOptions.logFileName,
(int) (options.mleChainLength * 0.10),
writer);
writer.writeCloseTag(ExpansionModelParser.POPULATION_SIZE);
writer.writeOpenTag(ExpansionModelParser.GROWTH_RATE);
writeParameter(
"expansionReference.growthRate",
"expansion.growthRate",
beautiOptions.logFileName,
(int) (options.mleChainLength * 0.10),
writer);
writer.writeCloseTag(ExpansionModelParser.GROWTH_RATE);
writer.writeOpenTag(ExpansionModelParser.ANCESTRAL_POPULATION_PROPORTION);
writeParameter(
"expansionReference.ancestralProportion",
"expansion.ancestralProportion",
beautiOptions.logFileName,
(int) (options.mleChainLength * 0.10),
writer);
writer.writeCloseTag(ExpansionModelParser.ANCESTRAL_POPULATION_PROPORTION);
writer.writeCloseTag(ExpansionModelParser.EXPANSION_MODEL);
writer.writeComment("A working prior for the coalescent.");
writer.writeOpenTag(
CoalescentLikelihoodParser.COALESCENT_LIKELIHOOD,
new Attribute[] {
new Attribute.Default<String>(XMLParser.ID, modelPrefix + "coalescentReference")
});
writer.writeOpenTag(CoalescentLikelihoodParser.MODEL);
writer.writeIDref(
ExpansionModelParser.EXPANSION_MODEL,
beautiOptions.getPartitionTreePriors().get(0).getPrefix() + "constantReference");
writer.writeCloseTag(CoalescentLikelihoodParser.MODEL);
writer.writeOpenTag(CoalescentLikelihoodParser.POPULATION_TREE);
writer.writeIDref(TreeModel.TREE_MODEL, modelPrefix + TreeModel.TREE_MODEL);
writer.writeCloseTag(CoalescentLikelihoodParser.POPULATION_TREE);
writer.writeCloseTag(CoalescentLikelihoodParser.COALESCENT_LIKELIHOOD);
break;
default:
// Do not switch to product of exponentials as the coalescentEventsStatistic has not
// been logged
// TODO: show menu that explains mismatch between prior and working prior?
// TODO: but show it when the MCM option is wrongfully being selected, don't do anything
// here
}
}
writer.writeComment("Define marginal likelihood estimator (GSS) settings");
List<Attribute> attributes = new ArrayList<Attribute>();
attributes.add(
new Attribute.Default<Integer>(
MarginalLikelihoodEstimator.CHAIN_LENGTH, options.mleChainLength));
attributes.add(
new Attribute.Default<Integer>(
MarginalLikelihoodEstimator.PATH_STEPS, options.pathSteps));
attributes.add(
new Attribute.Default<String>(
MarginalLikelihoodEstimator.PATH_SCHEME, options.pathScheme));
if (!options.pathScheme.equals(MarginalLikelihoodEstimator.LINEAR)) {
attributes.add(
new Attribute.Default<Double>(
MarginalLikelihoodEstimator.ALPHA, options.schemeParameter));
}
writer.writeOpenTag(MarginalLikelihoodEstimator.MARGINAL_LIKELIHOOD_ESTIMATOR, attributes);
writer.writeOpenTag("samplers");
writer.writeIDref("mcmc", "mcmc");
writer.writeCloseTag("samplers");
attributes = new ArrayList<Attribute>();
attributes.add(new Attribute.Default<String>(XMLParser.ID, "pathLikelihood"));
writer.writeOpenTag(PathLikelihood.PATH_LIKELIHOOD, attributes);
writer.writeOpenTag(PathLikelihood.SOURCE);
writer.writeIDref(CompoundLikelihoodParser.POSTERIOR, CompoundLikelihoodParser.POSTERIOR);
writer.writeCloseTag(PathLikelihood.SOURCE);
writer.writeOpenTag(PathLikelihood.DESTINATION);
writer.writeOpenTag(CompoundLikelihoodParser.WORKING_PRIOR);
ArrayList<Parameter> parameters = beautiOptions.selectParameters();
for (Parameter param : parameters) {
if (DEBUG) {
System.err.println(param.toString() + " " + param.priorType.toString());
}
// should leave out those parameters set by the coalescent
if (param.priorType != PriorType.NONE_TREE_PRIOR) {
// TODO: frequencies is multidimensional, is that automatically dealt with?
writer.writeOpenTag(
WorkingPriorParsers.NORMAL_REFERENCE_PRIOR,
new Attribute[] {
new Attribute.Default<String>("fileName", beautiOptions.logFileName),
new Attribute.Default<String>("parameterColumn", param.getName()),
new Attribute.Default<String>("burnin", "" + beautiOptions.chainLength * 0.10)
});
writeParameterIdref(writer, param);
writer.writeCloseTag(WorkingPriorParsers.NORMAL_REFERENCE_PRIOR);
}
}
if (options.choiceTreeWorkingPrior.equals("Product of exponential distributions")) {
writer.writeIDref("productOfExponentialsPosteriorMeansLoess", "exponentials");
} else {
writer.writeIDref(CoalescentLikelihoodParser.COALESCENT_LIKELIHOOD, "coalescentReference");
}
writer.writeCloseTag(CompoundLikelihoodParser.WORKING_PRIOR);
writer.writeCloseTag(PathLikelihood.DESTINATION);
writer.writeCloseTag(PathLikelihood.PATH_LIKELIHOOD);
attributes = new ArrayList<Attribute>();
attributes.add(new Attribute.Default<String>(XMLParser.ID, "MLELog"));
attributes.add(new Attribute.Default<Integer>("logEvery", options.mleLogEvery));
attributes.add(new Attribute.Default<String>("fileName", options.mleFileName));
writer.writeOpenTag("log", attributes);
writer.writeIDref("pathLikelihood", "pathLikelihood");
writer.writeCloseTag("log");
writer.writeCloseTag(MarginalLikelihoodEstimator.MARGINAL_LIKELIHOOD_ESTIMATOR);
writer.writeComment("Generalized stepping-stone sampling estimator from collected samples");
attributes = new ArrayList<Attribute>();
attributes.add(new Attribute.Default<String>("fileName", options.mleFileName));
writer.writeOpenTag(
GeneralizedSteppingStoneSamplingAnalysis.GENERALIZED_STEPPING_STONE_SAMPLING_ANALYSIS,
attributes);
writer.writeTag(
"sourceColumn", new Attribute.Default<String>("name", "pathLikelihood.source"), true);
writer.writeTag(
"destinationColumn",
new Attribute.Default<String>("name", "pathLikelihood.destination"),
true);
writer.writeTag(
"thetaColumn", new Attribute.Default<String>("name", "pathLikelihood.theta"), true);
writer.writeCloseTag(
GeneralizedSteppingStoneSamplingAnalysis.GENERALIZED_STEPPING_STONE_SAMPLING_ANALYSIS);
}
}
private boolean modelExists(String modelName) {
HierarchicalModelComponentOptions comp =
(HierarchicalModelComponentOptions)
options.getComponentOptions(HierarchicalModelComponentOptions.class);
return comp.modelExists(modelName);
}
private void fireDataChanged() {
options.updatePartitionAllLinks();
frame.setDirty();
}