/*
* 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
}
}