/* * UltrametricSpeciationModel.java * * Copyright (c) 2002-2015 Alexei Drummond, Andrew Rambaut and Marc Suchard * * This file is part of BEAST. * See the NOTICE file distributed with this work for additional * information regarding copyright ownership and licensing. * * BEAST is free software; you can redistribute it and/or modify * it under the terms of the GNU Lesser General Public License as * published by the Free Software Foundation; either version 2 * of the License, or (at your option) any later version. * * BEAST is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU Lesser General Public License for more details. * * You should have received a copy of the GNU Lesser General Public * License along with BEAST; if not, write to the * Free Software Foundation, Inc., 51 Franklin St, Fifth Floor, * Boston, MA 02110-1301 USA */ package dr.evomodel.speciation; import dr.evolution.tree.NodeRef; import dr.evolution.tree.Tree; import dr.evolution.util.Taxon; import dr.evolution.util.Units; import java.util.Set; /** * This interface provides methods that describe a speciation model. * * @author Andrew Rambaut * @author Alexei Drummond */ public abstract class UltrametricSpeciationModel extends SpeciationModel implements Units { public UltrametricSpeciationModel(String modelName, Type units) { super(modelName, units); } /** * "fixed" part of likelihood. Guaranteed to be called before any logNodeProbability * calls for one evaluation of the tree. * * @param taxonCount Number of taxa in tree * @return density factor which is not node dependent */ public abstract double logTreeProbability(int taxonCount); /** * Per node part of likelihood. * * @param tree * @param node * @return node contribution to density */ public abstract double logNodeProbability(Tree tree, NodeRef node); public boolean analyticalMarginalOK() { return false; } public double getMarginal(Tree tree, CalibrationPoints calibration) { return calibration.getCorrection(tree, -1); } /** * @return true if calls to logNodeProbability for terminal nodes (tips) are required */ public abstract boolean includeExternalNodesInLikelihoodCalculation(); /** * Generic likelihood calculation * * @param tree * @return log-likelihood of density */ public final double calculateTreeLogLikelihood(Tree tree) { final int taxonCount = tree.getExternalNodeCount(); double logL = logTreeProbability(taxonCount); for (int j = 0; j < tree.getInternalNodeCount(); j++) { logL += logNodeProbability(tree, tree.getInternalNode(j)); } if (includeExternalNodesInLikelihoodCalculation()) { for (int j = 0; j < taxonCount; j++) { logL += logNodeProbability(tree, tree.getExternalNode(j)); } } return logL; } /** * Alternative likelihood calculation that uses recursion over the tree and allows * a list of taxa to exclude * * @param tree the tree * @param exclude a list of taxa to exclude * @return log-likelihood of density */ public double calculateTreeLogLikelihood(Tree tree, Set<Taxon> exclude) { final int taxonCount = tree.getExternalNodeCount() - exclude.size(); double[] lnL = {logTreeProbability(taxonCount)}; calculateNodeLogLikelihood(tree, tree.getRoot(), exclude, lnL); return lnL[0]; } /** * Alternative likelihood calculation that uses recursion over the tree and allows * a list of taxa to exclude * * @param tree the tree * @param node * @param exclude a list of taxa to exclude * @param lnL a reference to the lnL sum * @return the number of included daughter nodes */ private int calculateNodeLogLikelihood(Tree tree, NodeRef node, Set<Taxon> exclude, double[] lnL) { if (tree.isExternal(node)) { if (!exclude.contains(tree.getNodeTaxon(node))) { if (includeExternalNodesInLikelihoodCalculation()) { lnL[0] += logNodeProbability(tree, node); } // this tip is included in the subtree... return 1; } // this tip is excluded from the subtree... return 0; } else { int count = 0; for (int i = 0; i < tree.getChildCount(node); i++) { NodeRef child = tree.getChild(node, i); count += calculateNodeLogLikelihood(tree, child, exclude, lnL); } if (count == 2) { // this node is included in the subtree... lnL[0] += logNodeProbability(tree, node); } // if at least one of the children has included tips then return 1 otherwise 0 return count > 0 ? 1 : 0; } } @Override public double calculateTreeLogLikelihood(Tree tree, CalibrationPoints calibration) { double logL = calculateTreeLogLikelihood(tree); double mar = getMarginal(tree, calibration); logL += mar; return logL; } }