/* * ExponentialBranchLengthTreePrior.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.oldevomodel.MSSD; import dr.evolution.tree.TreeUtils; import dr.evomodel.tree.TreeModel; import dr.inference.model.AbstractModelLikelihood; import dr.inference.model.Model; import dr.inference.model.Parameter; import dr.inference.model.Variable; import dr.math.GammaFunction; /** * Package: alsDefaultPrior * Description: * <p/> * <p/> * Created by * Alexander V. Alekseyenko (alexander.alekseyenko@gmail.com) * Date: Mar 14, 2008 * Time: 12:47:07 PM */ public class ExponentialBranchLengthTreePrior extends AbstractModelLikelihood { TreeModel treeModel; public ExponentialBranchLengthTreePrior(TreeModel treeModel) { super(null); this.treeModel = treeModel; } protected void handleModelChangedEvent(Model model, Object object, int index) { //AUTOGENERATED METHOD IMPLEMENTATION } /** * This method is called whenever a parameter is changed. * <p/> * It is strongly recommended that the model component sets a "dirty" flag and does no * further calculations. Recalculation is typically done when the model component is asked for * some information that requires them. This mechanism is 'lazy' so that this method * can be safely called multiple times with minimal computational cost. */ protected final void handleVariableChangedEvent(Variable variable, int index, Parameter.ChangeType type) { //AUTOGENERATED METHOD IMPLEMENTATION } /** * Additional state information, outside of the sub-model is stored by this call. */ protected void storeState() { //AUTOGENERATED METHOD IMPLEMENTATION } /** * After this call the model is guaranteed to have returned its extra state information to * the values coinciding with the last storeState call. * Sub-models are handled automatically and do not need to be considered in this method. */ protected void restoreState() { //AUTOGENERATED METHOD IMPLEMENTATION } /** * This call specifies that the current state is accept. Most models will not need to do anything. * Sub-models are handled automatically and do not need to be considered in this method. */ protected void acceptState() { //AUTOGENERATED METHOD IMPLEMENTATION } /** * Get the model. * * @return the model. */ public Model getModel() { return this; //AUTOGENERATED METHOD IMPLEMENTATION } /** * Get the log likelihood. * * @return the log likelihood. */ public double getLogLikelihood() { return calculateLogLikelihood(); } public double calculateLogLikelihood() { int L = treeModel.getNodeCount(); double totalTreeTime = TreeUtils.getTreeLength(treeModel, treeModel.getRoot()); // if(ctmcScale != null){ // // double ab=ctmcScale.getParameterValue(0); // return GammaFunction.lnGamma(L)-Math.log(mu*lam)-(L-1)*Math.log(totalTreeTime)-0.5*Math.log(ab)-ab*totalTreeTime; // }else{ // No Markov Chain for this model return GammaFunction.lnGamma(L) - (L - 1) * Math.log(totalTreeTime); } /** * Forces a complete recalculation of the likelihood next time getLikelihood is called */ public void makeDirty() { //AUTOGENERATED METHOD IMPLEMENTATION } }