// compute scale factor
private void computeFactor() {
// scale mean rate to 1.0 or separate parameter
double treeRate = 0.0;
double treeTime = 0.0;
// normalizeBranchRateTo = 1.0;
for (int i = 0; i < treeModel.getNodeCount(); i++) {
NodeRef node = treeModel.getNode(i);
if (!treeModel.isRoot(node)) {
// d int rateCategory = (int)
// Math.round(rateCategories.getNodeValue(treeModel, node));
// d treeRate += rates[rateCategory] * treeModel.getBranchLength(node);
treeTime += treeModel.getBranchLength(node);
// d System.out.println("rates and time\t" + rates[rateCategory] + "\t" +
// treeModel.getBranchLength(node));
}
}
// treeRate /= treeTime;
scaleFactor = normalizeBranchRateTo / (treeRate / treeTime);
System.out.println("scaleFactor\t\t\t\t\t" + scaleFactor);
}
public void forwardIBD() {
int numNodes = treeModel.getNodeCount();
int stateCount = substitutionModel.getStateCount();
getDiagonalRates(diag);
for (int nodeId = 0; nodeId < numNodes; ++nodeId) {
NodeRef node = treeModel.getNode(nodeId);
NodeRef parent = treeModel.getParent(node);
if (parent == null) { // handle the root
} else if (treeModel.isExternal(node)) { // Handle the tip
double branchTime =
branchRateModel.getBranchRate(treeModel, node)
* (treeModel.getNodeHeight(parent) - treeModel.getNodeHeight(node));
for (int state = 0; state < stateCount; ++state) {
ibdForward[nodeId][state] = Math.exp(-diag[state] * branchTime);
}
} else { // Handle internal node
double branchTime =
branchRateModel.getBranchRate(treeModel, node)
* (treeModel.getNodeHeight(parent) - treeModel.getNodeHeight(node));
int childCount = treeModel.getChildCount(node);
for (int state = 0; state < stateCount; ++state) {
ibdForward[nodeId][state] = 0;
for (int child = 0; child < childCount; ++child) {
int childNodeId = treeModel.getChild(node, child).getNumber();
ibdForward[nodeId][state] += ibdForward[childNodeId][state];
}
ibdForward[nodeId][state] *= Math.exp(-diag[state] * branchTime);
}
}
}
}
public void backwardIBD(NodeRef node) {
int stateCount = substitutionModel.getStateCount();
if (node == null) {
node = treeModel.getRoot();
int nodeId = node.getNumber();
for (int state = 0; state < stateCount; ++state) {
ibdBackward[nodeId][state] = 0;
}
}
getDiagonalRates(diag);
int childCount = treeModel.getChildCount(node);
int nodeId = node.getNumber();
for (int child = 0; child < childCount; ++child) {
NodeRef childNode = treeModel.getChild(node, child);
int childNodeId = childNode.getNumber();
double branchTime =
branchRateModel.getBranchRate(treeModel, childNode)
* (treeModel.getNodeHeight(node) - treeModel.getNodeHeight(childNode));
for (int state = 0; state < stateCount; ++state) {
ibdBackward[childNodeId][state] = ibdBackward[nodeId][state];
for (int sibling = 0; sibling < childCount; ++sibling) {
if (sibling != child) {
int siblingId = treeModel.getChild(node, sibling).getNumber();
ibdBackward[childNodeId][state] += ibdForward[siblingId][state];
}
}
ibdBackward[childNodeId][state] *= Math.exp(-diag[state] * branchTime);
}
}
for (int child = 0; child < childCount; ++child) {
NodeRef childNode = treeModel.getChild(node, child);
backwardIBD(childNode);
}
}
public void expectedIBD() {
int stateCount = substitutionModel.getStateCount();
int nodeCount = treeModel.getNodeCount();
if (ibdweights == null) {
ibdweights = new double[treeModel.getExternalNodeCount()];
ibdForward = new double[nodeCount][stateCount];
ibdBackward = new double[nodeCount][stateCount];
diag = new double[stateCount];
}
double[] freq = substitutionModel.getFrequencyModel().getFrequencies();
forwardIBD();
backwardIBD(null);
int numTips = treeModel.getExternalNodeCount();
for (int i = 0; i < numTips; ++i) {
ibdweights[i] = 0;
for (int j = 0; j < stateCount; ++j) {
ibdweights[i] += ibdBackward[i][j] * freq[j];
}
}
}
private boolean eligibleForMove(NodeRef node, TreeModel tree, BranchMapModel branchMap) {
// to be eligible for this move, the node's parent and grandparent, or parent and other child,
// must be in the same partition (so removing the parent has no effect on the remaining links of
// the TT),
// and the node and its parent must be in different partitions (such that the move does not
// disconnect anything)
return ((tree.getParent(tree.getParent(node)) != null
&& branchMap.get(tree.getParent(node).getNumber())
== branchMap.get(tree.getParent(tree.getParent(node)).getNumber()))
|| branchMap.get(tree.getParent(node).getNumber())
== branchMap.get(getOtherChild(tree, tree.getParent(node), node).getNumber()))
&& branchMap.get(tree.getParent(node).getNumber()) != branchMap.get(node.getNumber());
}
private void setup() {
DataType dataType = baseSubstitutionModel.getDataType();
FrequencyModel freqModel = baseSubstitutionModel.getFrequencyModel();
Parameter kappaParameter = new Parameter.Default("kappa", 1, baseSubstitutionModel.getKappa());
substitutionModels = new LinkedList<SubstitutionModel>();
branchAssignmentMap = new LinkedHashMap<NodeRef, Integer>();
int branchClass = 0;
for (NodeRef node : treeModel.getNodes()) {
if (!treeModel.isRoot(node)) {
double nodeHeight = treeModel.getNodeHeight(node);
double parentHeight = treeModel.getNodeHeight(treeModel.getParent(node));
double time = 0.5 * (parentHeight + nodeHeight);
double baseOmega = baseSubstitutionModel.getOmega();
double fixed = baseOmega * time;
double epsilon =
(Math.log(1 - random.nextDouble())
/ (-rate)); // Math.exp((random.nextGaussian() * stdev + mean));
double value = fixed + epsilon;
Parameter omegaParameter = new Parameter.Default("omega", 1, value);
GY94CodonModel gy94 =
new GY94CodonModel((Codons) dataType, omegaParameter, kappaParameter, freqModel);
substitutionModels.add(gy94);
branchAssignmentMap.put(node, branchClass);
branchClass++;
} // END: root check
} // END: nodes loop
} // END: setup
public static void checkTree(TreeModel treeModel) {
// todo Should only be run if there exists a zero-length interval
// TreeModel treeModel = (TreeModel) tree;
for (int i = 0; i < treeModel.getInternalNodeCount(); i++) {
NodeRef node = treeModel.getInternalNode(i);
if (node != treeModel.getRoot()) {
double parentHeight = treeModel.getNodeHeight(treeModel.getParent(node));
double childHeight0 = treeModel.getNodeHeight(treeModel.getChild(node, 0));
double childHeight1 = treeModel.getNodeHeight(treeModel.getChild(node, 1));
double maxChild = childHeight0;
if (childHeight1 > maxChild) maxChild = childHeight1;
double newHeight = maxChild + MathUtils.nextDouble() * (parentHeight - maxChild);
treeModel.setNodeHeight(node, newHeight);
}
}
treeModel.pushTreeChangedEvent();
}
public void proposeTree() throws OperatorFailedException {
TreeModel tree = c2cLikelihood.getTreeModel();
BranchMapModel branchMap = c2cLikelihood.getBranchMap();
NodeRef i;
double oldMinAge, newMinAge, newRange, oldRange, newAge, q;
// choose a random node avoiding root, and nodes that are ineligible for this move because they
// have nowhere to
// go
final int nodeCount = tree.getNodeCount();
do {
i = tree.getNode(MathUtils.nextInt(nodeCount));
} while (tree.getRoot() == i || !eligibleForMove(i, tree, branchMap));
final NodeRef iP = tree.getParent(i);
// this one can go anywhere
NodeRef j = tree.getNode(MathUtils.nextInt(tree.getNodeCount()));
NodeRef k = tree.getParent(j);
while ((k != null && tree.getNodeHeight(k) <= tree.getNodeHeight(i)) || (i == j)) {
j = tree.getNode(MathUtils.nextInt(tree.getNodeCount()));
k = tree.getParent(j);
}
if (iP == tree.getRoot() || j == tree.getRoot()) {
throw new OperatorFailedException("Root changes not allowed!");
}
if (k == iP || j == iP || k == i) throw new OperatorFailedException("move failed");
final NodeRef CiP = getOtherChild(tree, iP, i);
NodeRef PiP = tree.getParent(iP);
newMinAge = Math.max(tree.getNodeHeight(i), tree.getNodeHeight(j));
newRange = tree.getNodeHeight(k) - newMinAge;
newAge = newMinAge + (MathUtils.nextDouble() * newRange);
oldMinAge = Math.max(tree.getNodeHeight(i), tree.getNodeHeight(CiP));
oldRange = tree.getNodeHeight(PiP) - oldMinAge;
q = newRange / Math.abs(oldRange);
// need to account for the random repainting of iP
if (branchMap.get(PiP.getNumber()) != branchMap.get(CiP.getNumber())) {
q *= 0.5;
}
if (branchMap.get(k.getNumber()) != branchMap.get(j.getNumber())) {
q *= 2;
}
tree.beginTreeEdit();
if (j == tree.getRoot()) {
// 1. remove edges <iP, CiP>
tree.removeChild(iP, CiP);
tree.removeChild(PiP, iP);
// 2. add edges <k, iP>, <iP, j>, <PiP, CiP>
tree.addChild(iP, j);
tree.addChild(PiP, CiP);
// iP is the new root
tree.setRoot(iP);
} else if (iP == tree.getRoot()) {
// 1. remove edges <k, j>, <iP, CiP>, <PiP, iP>
tree.removeChild(k, j);
tree.removeChild(iP, CiP);
// 2. add edges <k, iP>, <iP, j>, <PiP, CiP>
tree.addChild(iP, j);
tree.addChild(k, iP);
// CiP is the new root
tree.setRoot(CiP);
} else {
// 1. remove edges <k, j>, <iP, CiP>, <PiP, iP>
tree.removeChild(k, j);
tree.removeChild(iP, CiP);
tree.removeChild(PiP, iP);
// 2. add edges <k, iP>, <iP, j>, <PiP, CiP>
tree.addChild(iP, j);
tree.addChild(k, iP);
tree.addChild(PiP, CiP);
}
tree.setNodeHeight(iP, newAge);
tree.endTreeEdit();
//
logq = Math.log(q);
// repaint the parent to match either its new parent or its new child (50% chance of each).
if (MathUtils.nextInt(2) == 0) {
branchMap.set(iP.getNumber(), branchMap.get(k.getNumber()), true);
} else {
branchMap.set(iP.getNumber(), branchMap.get(j.getNumber()), true);
}
if (DEBUG) {
c2cLikelihood.checkPartitions();
}
}
protected BeagleTreeLikelihood createTreeLikelihood(
PatternList patternList, //
TreeModel treeModel, //
BranchModel branchModel, //
GammaSiteRateModel siteRateModel, //
BranchRateModel branchRateModel, //
TipStatesModel tipStatesModel, //
boolean useAmbiguities, //
PartialsRescalingScheme scalingScheme, //
Map<
Set<String>, //
Parameter>
partialsRestrictions, //
XMLObject xo //
) throws XMLParseException {
boolean integrateGainRate = xo.getBooleanAttribute(INTEGRATE_GAIN_RATE);
useAmbiguities = true; // TODO No effect
if (scalingScheme != PartialsRescalingScheme.NONE) {
throw new XMLParseException(
"No rescaling scheme is currently support by the mutation-death model " + xo.getId());
}
Parameter mu = ((MutationDeathModel) siteRateModel.getSubstitutionModel()).getDeathParameter();
Parameter lam;
if (!integrateGainRate) {
lam = (Parameter) xo.getElementFirstChild(IMMIGRATION_RATE);
} else {
lam = new Parameter.Default("gainRate", 1.0, 0.001, 1.999);
}
AbstractObservationProcess observationProcess = null;
Logger.getLogger("dr.evolution")
.info("\n ---------------------------------\nCreating a BEAGLE ALSTreeLikelihood model.");
for (int i = 0; i < xo.getChildCount(); ++i) {
Object cxo = xo.getChild(i);
if (cxo instanceof XMLObject && ((XMLObject) cxo).getName().equals(OBSERVATION_PROCESS)) {
if (((XMLObject) cxo).getStringAttribute(OBSERVATION_TYPE).equals("singleTip")) {
String taxonName = ((XMLObject) cxo).getStringAttribute(OBSERVATION_TAXON);
Taxon taxon = treeModel.getTaxon(treeModel.getTaxonIndex(taxonName));
observationProcess =
new SingleTipObservationProcess(
treeModel, patternList, siteRateModel, branchRateModel, mu, lam, taxon);
Logger.getLogger("dr.evolution").info("All traits are assumed extant in " + taxonName);
} else { // "anyTip" observation process
observationProcess =
new AnyTipObservationProcess(
ANY_TIP, treeModel, patternList, siteRateModel, branchRateModel, mu, lam);
Logger.getLogger("dr.evolution")
.info("Observed traits are assumed to be extant in at least one tip node.");
}
observationProcess.setIntegrateGainRate(integrateGainRate);
}
}
Logger.getLogger("dr.evolution")
.info(
"\tIf you publish results using Acquisition-Loss-Mutation (ALS) Model likelihood, please reference Alekseyenko, Lee and Suchard (2008) Syst. Biol 57: 772-784.\n---------------------------------\n");
return new ALSBeagleTreeLikelihood(
observationProcess,
patternList,
treeModel,
branchModel,
siteRateModel,
branchRateModel,
tipStatesModel,
useAmbiguities,
scalingScheme,
partialsRestrictions);
}
public MixtureModelBranchRates(
TreeModel tree,
Parameter rateCategoryQuantilesParameter,
ParametricDistributionModel[] models,
Parameter distributionIndexParameter,
boolean useQuantilesForRates,
boolean normalize,
double normalizeBranchRateTo) {
super(MixtureModelBranchRatesParser.MIXTURE_MODEL_BRANCH_RATES);
this.useQuantilesForRates = useQuantilesForRates;
this.rateCategoryQuantiles =
new TreeParameterModel(tree, rateCategoryQuantilesParameter, false);
rates = new double[tree.getNodeCount()];
this.normalize = normalize;
this.treeModel = tree;
this.distributionModels = models;
this.normalizeBranchRateTo = normalizeBranchRateTo;
this.tree = new SimpleTree(tree);
this.distributionIndexParameter = distributionIndexParameter;
addVariable(this.distributionIndexParameter);
// Force the boundaries of rateCategoryParameter to match the category count
// d Parameter.DefaultBounds bound = new Parameter.DefaultBounds(categoryCount - 1, 0,
// rateCategoryParameter.getDimension());
// d rateCategoryParameter.addBounds(bound);
// rateCategoryQuantilesParameter.;
Parameter.DefaultBounds bound =
new Parameter.DefaultBounds(1.0, 0.0, rateCategoryQuantilesParameter.getDimension());
rateCategoryQuantilesParameter.addBounds(bound);
Parameter.DefaultBounds bound2 = new Parameter.DefaultBounds(models.length, 0.0, 1);
distributionIndexParameter.addBounds(bound2);
distributionIndexParameter.setParameterValue(0, 0);
// Parameter distributionIndexParameter;
for (ParametricDistributionModel distributionModel : distributionModels) {
addModel(distributionModel);
}
// AR - commented out: changes to the tree are handled by model changed events fired by
// rateCategories
// addModel(tree);
// d addModel(rateCategories);
addModel(rateCategoryQuantiles);
// addModel(treeModel); // Maybe
// AR - commented out: changes to rateCategoryParameter are handled by model changed events
// fired by rateCategories
// addVariable(rateCategoryParameter);
if (normalize) {
tree.addModelListener(
new ModelListener() {
public void modelChangedEvent(Model model, Object object, int index) {
computeFactor();
}
public void modelRestored(Model model) {
computeFactor();
}
});
}
setupRates();
}
public NewBeagleTreeLikelihood(
PatternList patternList,
TreeModel treeModel,
BranchModel branchModel,
SiteModel siteModel,
BranchRateModel branchRateModel,
TipStatesModel tipStatesModel,
boolean useAmbiguities,
PartialsRescalingScheme rescalingScheme,
Map<Set<String>, Parameter> partialsRestrictions) {
super(BeagleTreeLikelihoodParser.TREE_LIKELIHOOD, patternList, treeModel);
try {
final Logger logger = Logger.getLogger("dr.evomodel");
logger.info("Using BEAGLE TreeLikelihood");
this.siteModel = siteModel;
addModel(this.siteModel);
this.branchModel = branchModel;
addModel(this.branchModel);
if (branchRateModel != null) {
this.branchRateModel = branchRateModel;
logger.info(" Branch rate model used: " + branchRateModel.getModelName());
} else {
this.branchRateModel = new DefaultBranchRateModel();
}
addModel(this.branchRateModel);
this.tipStatesModel = tipStatesModel;
this.categoryCount = this.siteModel.getCategoryCount();
this.tipCount = treeModel.getExternalNodeCount();
internalNodeCount = nodeCount - tipCount;
int compactPartialsCount = tipCount;
if (useAmbiguities) {
// if we are using ambiguities then we don't use tip partials
compactPartialsCount = 0;
}
// one partials buffer for each tip and two for each internal node (for store restore)
partialBufferHelper = new BufferIndexHelper(nodeCount, tipCount);
// one scaling buffer for each internal node plus an extra for the accumulation, then doubled
// for store/restore
scaleBufferHelper = new BufferIndexHelper(getScaleBufferCount(), 0);
// Attempt to get the resource order from the System Property
if (resourceOrder == null) {
resourceOrder = parseSystemPropertyIntegerArray(RESOURCE_ORDER_PROPERTY);
}
if (preferredOrder == null) {
preferredOrder = parseSystemPropertyIntegerArray(PREFERRED_FLAGS_PROPERTY);
}
if (requiredOrder == null) {
requiredOrder = parseSystemPropertyIntegerArray(REQUIRED_FLAGS_PROPERTY);
}
if (scalingOrder == null) {
scalingOrder = parseSystemPropertyStringArray(SCALING_PROPERTY);
}
if (extraBufferOrder == null) {
extraBufferOrder = parseSystemPropertyIntegerArray(EXTRA_BUFFER_COUNT_PROPERTY);
}
int extraBufferCount = -1; // default
if (extraBufferOrder.size() > 0) {
extraBufferCount = extraBufferOrder.get(instanceCount % extraBufferOrder.size());
}
substitutionModelDelegate =
new SubstitutionModelDelegate(treeModel, branchModel, extraBufferCount);
// first set the rescaling scheme to use from the parser
this.rescalingScheme = rescalingScheme;
int[] resourceList = null;
long preferenceFlags = 0;
long requirementFlags = 0;
if (scalingOrder.size() > 0) {
this.rescalingScheme =
PartialsRescalingScheme.parseFromString(
scalingOrder.get(instanceCount % scalingOrder.size()));
}
if (resourceOrder.size() > 0) {
// added the zero on the end so that a CPU is selected if requested resource fails
resourceList = new int[] {resourceOrder.get(instanceCount % resourceOrder.size()), 0};
if (resourceList[0] > 0) {
preferenceFlags |=
BeagleFlag.PROCESSOR_GPU.getMask(); // Add preference weight against CPU
}
}
if (preferredOrder.size() > 0) {
preferenceFlags = preferredOrder.get(instanceCount % preferredOrder.size());
}
if (requiredOrder.size() > 0) {
requirementFlags = requiredOrder.get(instanceCount % requiredOrder.size());
}
// Define default behaviour here
if (this.rescalingScheme == PartialsRescalingScheme.DEFAULT) {
// if GPU: the default is dynamic scaling in BEAST
if (resourceList != null && resourceList[0] > 1) {
this.rescalingScheme = DEFAULT_RESCALING_SCHEME;
} else { // if CPU: just run as fast as possible
// this.rescalingScheme = PartialsRescalingScheme.NONE;
// Dynamic should run as fast as none until first underflow
this.rescalingScheme = DEFAULT_RESCALING_SCHEME;
}
}
if (this.rescalingScheme == PartialsRescalingScheme.AUTO) {
preferenceFlags |= BeagleFlag.SCALING_AUTO.getMask();
useAutoScaling = true;
} else {
// preferenceFlags |= BeagleFlag.SCALING_MANUAL.getMask();
}
String r = System.getProperty(RESCALE_FREQUENCY_PROPERTY);
if (r != null) {
rescalingFrequency = Integer.parseInt(r);
if (rescalingFrequency < 1) {
rescalingFrequency = RESCALE_FREQUENCY;
}
}
if (preferenceFlags == 0 && resourceList == null) { // else determine dataset characteristics
if (stateCount == 4 && patternList.getPatternCount() < 10000) // TODO determine good cut-off
preferenceFlags |= BeagleFlag.PROCESSOR_CPU.getMask();
}
if (BeagleFlag.VECTOR_SSE.isSet(preferenceFlags) && stateCount != 4) {
// @todo SSE doesn't seem to work for larger state spaces so for now we override the
// SSE option.
preferenceFlags &= ~BeagleFlag.VECTOR_SSE.getMask();
preferenceFlags |= BeagleFlag.VECTOR_NONE.getMask();
if (stateCount > 4 && this.rescalingScheme == PartialsRescalingScheme.DYNAMIC) {
this.rescalingScheme = PartialsRescalingScheme.DELAYED;
}
}
if (!BeagleFlag.PRECISION_SINGLE.isSet(preferenceFlags)) {
// if single precision not explicitly set then prefer double
preferenceFlags |= BeagleFlag.PRECISION_DOUBLE.getMask();
}
if (substitutionModelDelegate.canReturnComplexDiagonalization()) {
requirementFlags |= BeagleFlag.EIGEN_COMPLEX.getMask();
}
instanceCount++;
beagle =
BeagleFactory.loadBeagleInstance(
tipCount,
partialBufferHelper.getBufferCount(),
compactPartialsCount,
stateCount,
patternCount,
substitutionModelDelegate.getEigenBufferCount(),
substitutionModelDelegate.getMatrixBufferCount(),
categoryCount,
scaleBufferHelper.getBufferCount(), // Always allocate; they may become necessary
resourceList,
preferenceFlags,
requirementFlags);
InstanceDetails instanceDetails = beagle.getDetails();
ResourceDetails resourceDetails = null;
if (instanceDetails != null) {
resourceDetails = BeagleFactory.getResourceDetails(instanceDetails.getResourceNumber());
if (resourceDetails != null) {
StringBuilder sb = new StringBuilder(" Using BEAGLE resource ");
sb.append(resourceDetails.getNumber()).append(": ");
sb.append(resourceDetails.getName()).append("\n");
if (resourceDetails.getDescription() != null) {
String[] description = resourceDetails.getDescription().split("\\|");
for (String desc : description) {
if (desc.trim().length() > 0) {
sb.append(" ").append(desc.trim()).append("\n");
}
}
}
sb.append(" with instance flags: ").append(instanceDetails.toString());
logger.info(sb.toString());
} else {
logger.info(
" Error retrieving BEAGLE resource for instance: " + instanceDetails.toString());
}
} else {
logger.info(
" No external BEAGLE resources available, or resource list/requirements not met, using Java implementation");
}
logger.info(
" " + (useAmbiguities ? "Using" : "Ignoring") + " ambiguities in tree likelihood.");
logger.info(" With " + patternList.getPatternCount() + " unique site patterns.");
if (tipStatesModel != null) {
tipStatesModel.setTree(treeModel);
if (tipStatesModel.getModelType() == TipStatesModel.Type.PARTIALS) {
tipPartials = new double[patternCount * stateCount];
} else {
tipStates = new int[patternCount];
}
addModel(tipStatesModel);
}
for (int i = 0; i < tipCount; i++) {
// Find the id of tip i in the patternList
String id = treeModel.getTaxonId(i);
int index = patternList.getTaxonIndex(id);
if (index == -1) {
throw new TaxonList.MissingTaxonException(
"Taxon, "
+ id
+ ", in tree, "
+ treeModel.getId()
+ ", is not found in patternList, "
+ patternList.getId());
} else {
if (tipStatesModel != null) {
// using a tipPartials model.
// First set the observed states:
tipStatesModel.setStates(patternList, index, i, id);
if (tipStatesModel.getModelType() == TipStatesModel.Type.PARTIALS) {
// Then set the tip partials as determined by the model:
setPartials(beagle, tipStatesModel, i);
} else {
// or the tip states:
tipStatesModel.getTipStates(i, tipStates);
beagle.setTipStates(i, tipStates);
}
} else {
if (useAmbiguities) {
setPartials(beagle, patternList, index, i);
} else {
setStates(beagle, patternList, index, i);
}
}
}
}
if (patternList instanceof AscertainedSitePatterns) {
ascertainedSitePatterns = true;
}
this.partialsRestrictions = partialsRestrictions;
// hasRestrictedPartials = (partialsRestrictions != null);
if (hasRestrictedPartials) {
numRestrictedPartials = partialsRestrictions.size();
updateRestrictedNodePartials = true;
partialsMap = new Parameter[treeModel.getNodeCount()];
partials = new double[stateCount * patternCount * categoryCount];
} else {
numRestrictedPartials = 0;
updateRestrictedNodePartials = false;
}
beagle.setPatternWeights(patternWeights);
String rescaleMessage = " Using rescaling scheme : " + this.rescalingScheme.getText();
if (this.rescalingScheme == PartialsRescalingScheme.AUTO
&& resourceDetails != null
&& (resourceDetails.getFlags() & BeagleFlag.SCALING_AUTO.getMask()) == 0) {
// If auto scaling in BEAGLE is not supported then do it here
this.rescalingScheme = PartialsRescalingScheme.DYNAMIC;
rescaleMessage =
" Auto rescaling not supported in BEAGLE, using : " + this.rescalingScheme.getText();
}
if (this.rescalingScheme == PartialsRescalingScheme.DYNAMIC) {
rescaleMessage += " (rescaling every " + rescalingFrequency + " evaluations)";
}
logger.info(rescaleMessage);
if (this.rescalingScheme == PartialsRescalingScheme.DYNAMIC) {
everUnderflowed = false; // If false, BEAST does not rescale until first under-/over-flow.
}
updateSubstitutionModel = true;
updateSiteModel = true;
} catch (TaxonList.MissingTaxonException mte) {
throw new RuntimeException(mte.toString());
}
this.useAmbiguities = useAmbiguities;
hasInitialized = true;
}
/** Constructor. */
public CenancestorTreeLikelihood(
PatternList patternList,
TreeModel treeModel,
SiteModel siteModel,
CenancestorBranchRateModel branchRateModel,
TipStatesModel tipStatesModel,
Parameter cenancestorHeight,
Parameter cenancestorBranch,
// Parameter asStatistic,
boolean useAmbiguities,
boolean allowMissingTaxa,
boolean storePartials,
boolean forceJavaCore,
boolean forceRescaling) {
super(CenancestorTreeLikelihoodParser.TREE_LIKELIHOOD, patternList, treeModel);
this.storePartials = storePartials;
nodeCount = treeModel.getNodeCount() + 1;
updateNode = new boolean[nodeCount];
for (int i = 0; i < nodeCount; i++) {
updateNode[i] = true;
}
try {
this.siteModel = siteModel;
addModel(siteModel);
this.frequencyModel = siteModel.getFrequencyModel();
addModel(frequencyModel);
this.tipStatesModel = tipStatesModel;
integrateAcrossCategories = siteModel.integrateAcrossCategories();
this.categoryCount = siteModel.getCategoryCount();
this.cenancestorHeight = cenancestorHeight;
addVariable(cenancestorHeight);
cenancestorHeight.addBounds(
new Parameter.DefaultBounds(
Double.POSITIVE_INFINITY,
0.0,
1)); // TODO The lower bound should be the maximum leaf height
this.cenancestorBranch = cenancestorBranch;
cenancestorBranch.addBounds(
new Parameter.DefaultBounds(
Double.POSITIVE_INFINITY,
0.0,
1)); // TODO The upper bound should be the maximum leaf height
addVariable(cenancestorBranch);
// if (asStatistic == cenancestorHeight){
// this.branchRules=true;
// }
// if (branchRules==true){
updateCenancestorHeight(); // Trying to avoid improper initial values
// }
// else{
// updateCenancestorBranch();
// }
final Logger logger = Logger.getLogger("dr.evomodel");
String coreName = "Java general";
/** TODO: Check if is worthy to implement other datatypes. */
final DataType dataType = patternList.getDataType();
if (dataType instanceof dr.evolution.datatype.TwoStates) {
coreName = "Java cenancestor binary";
cenancestorlikelihoodCore =
new GeneralCenancestorLikelihoodCore(patternList.getStateCount());
} else if (dataType instanceof dr.evolution.datatype.GeneralDataType) {
coreName = "Java cenancestor CNV";
cenancestorlikelihoodCore =
new GeneralCenancestorLikelihoodCore(patternList.getStateCount());
}
/* if (integrateAcrossCategories) {
final DataType dataType = patternList.getDataType();
if (dataType instanceof dr.evolution.datatype.Nucleotides) {
if (!forceJavaCore && NativeNucleotideLikelihoodCore.isAvailable()) {
coreName = "native nucleotide";
likelihoodCore = new NativeNucleotideLikelihoodCore();
} else {
coreName = "Java nucleotide";
likelihoodCore = new NucleotideLikelihoodCore();
}
} else if (dataType instanceof dr.evolution.datatype.AminoAcids) {
if (!forceJavaCore && NativeAminoAcidLikelihoodCore.isAvailable()) {
coreName = "native amino acid";
likelihoodCore = new NativeAminoAcidLikelihoodCore();
} else {
coreName = "Java amino acid";
likelihoodCore = new AminoAcidLikelihoodCore();
}
// The codon core was out of date and did nothing more than the general core...
} else if (dataType instanceof dr.evolution.datatype.Codons) {
if (!forceJavaCore && NativeGeneralLikelihoodCore.isAvailable()) {
coreName = "native general";
likelihoodCore = new NativeGeneralLikelihoodCore(patternList.getStateCount());
} else {
coreName = "Java general";
likelihoodCore = new GeneralLikelihoodCore(patternList.getStateCount());
}
useAmbiguities = true;
} else {
if (!forceJavaCore && NativeGeneralLikelihoodCore.isAvailable()) {
coreName = "native general";
likelihoodCore = new NativeGeneralLikelihoodCore(patternList.getStateCount());
} else {
coreName = "Java general";
likelihoodCore = new GeneralLikelihoodCore(patternList.getStateCount());
}
}
} else {
likelihoodCore = new GeneralLikelihoodCore(patternList.getStateCount());
}*/
{
final String id = getId();
logger.info(
"TreeLikelihood("
+ ((id != null) ? id : treeModel.getId())
+ ") using "
+ coreName
+ " likelihood core");
logger.info(
" " + (useAmbiguities ? "Using" : "Ignoring") + " ambiguities in tree likelihood.");
logger.info(" With " + patternList.getPatternCount() + " unique site patterns.");
}
if (branchRateModel != null) {
this.branchRateModel = branchRateModel;
logger.info("Branch rate model used: " + branchRateModel.getModelName());
} else {
this.branchRateModel = new DefaultCenancestorBranchRateModel();
}
addModel(this.branchRateModel);
probabilities = new double[stateCount * stateCount];
cenancestorlikelihoodCore.initialize(
nodeCount, patternCount, categoryCount, integrateAcrossCategories);
int extNodeCount = treeModel.getExternalNodeCount();
int intNodeCount = treeModel.getInternalNodeCount();
if (tipStatesModel != null) {
tipStatesModel.setTree(treeModel);
tipPartials = new double[patternCount * stateCount];
for (int i = 0; i < extNodeCount; i++) {
// Find the id of tip i in the patternList
String id = treeModel.getTaxonId(i);
int index = patternList.getTaxonIndex(id);
if (index == -1) {
throw new TaxonList.MissingTaxonException(
"Taxon, "
+ id
+ ", in tree, "
+ treeModel.getId()
+ ", is not found in patternList, "
+ patternList.getId());
}
tipStatesModel.setStates(patternList, index, i, id);
cenancestorlikelihoodCore.createNodePartials(i);
}
addModel(tipStatesModel);
} else {
for (int i = 0; i < extNodeCount; i++) {
// Find the id of tip i in the patternList
String id = treeModel.getTaxonId(i);
int index = patternList.getTaxonIndex(id);
if (index == -1) {
if (!allowMissingTaxa) {
throw new TaxonList.MissingTaxonException(
"Taxon, "
+ id
+ ", in tree, "
+ treeModel.getId()
+ ", is not found in patternList, "
+ patternList.getId());
}
if (useAmbiguities) {
setMissingPartials((LikelihoodCore) cenancestorlikelihoodCore, i);
} else {
setMissingStates((LikelihoodCore) cenancestorlikelihoodCore, i);
}
} else {
if (useAmbiguities) {
setPartials(
(LikelihoodCore) cenancestorlikelihoodCore, patternList, categoryCount, index, i);
} else {
setStates((LikelihoodCore) cenancestorlikelihoodCore, patternList, index, i);
}
}
}
}
for (int i = 0; i <= intNodeCount; i++) { // Added one step for the cenancestor
cenancestorlikelihoodCore.createNodePartials(extNodeCount + i);
}
if (forceRescaling) {
cenancestorlikelihoodCore.setUseScaling(true);
logger.info(" Forcing use of partials rescaling.");
}
} catch (TaxonList.MissingTaxonException mte) {
throw new RuntimeException(mte.toString());
}
addStatistic(new SiteLikelihoodsStatistic());
}
