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());
}