/*
* DiffusionLikelihood.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.evolution.continuous;
import dr.math.*;
import dr.evolution.tree.Tree;
import dr.evolution.tree.NodeRef;
/**
*
*
*/
public class DiffusionLikelihood implements UnivariateFunction, MultivariateFunction {
Tree tree;
String traitName;
public DiffusionLikelihood(Tree tree, String traitName) {
this.tree = tree;
this.traitName = traitName;
}
public double optimize(double[] p) {
//
if (p.length > 1) {
p[0] = 1.0;
p[1] = 0.01;
MultivariateMinimum optimizer = new ConjugateDirectionSearch();
//MultivariateMinimum optimizer = new DifferentialEvolution(2,5);
optimizer.optimize(this,p,1e-6, 1e-6);
return -evaluate(p);
} else if (p.length == 1) {
UnivariateMinimum optimizer = new UnivariateMinimum();
p[0] = optimizer.optimize(this,1e-6);
return -evaluate(p[0]);
} else throw new IllegalArgumentException("");
}
/**
* @return the log likelihood of going from start to stop in the given time
*/
public double getLogLikelihood(double distance, double time, double D, double bias) {
// expected variance of distances of given time
double Dtime = D * time;
double d = distance - (bias*time);
//System.out.println("distance=" + unbiasedDistance + " time=" + time);
// the log likelihood of travelling distance d, in time t given diffusion rate D
return -(Math.log(Math.sqrt(Dtime*2*Math.PI))) - ((d*d)/(2*Dtime));
}
public double evaluate(double[] argument) {
double D = argument[0];
double bias = argument[1];
double logLkl = 0.0;
for (int i = 0; i < tree.getNodeCount(); i++) {
NodeRef child = tree.getNode(i);
if (!tree.isRoot(child)) {
NodeRef parent = tree.getParent(child);
Contrastable parentValue = (Contrastable)tree.getNodeAttribute(parent,traitName);
Contrastable childValue = (Contrastable)tree.getNodeAttribute(child,traitName);
double distance = parentValue.getDifference(childValue);
//System.out.println(distance);
logLkl += getLogLikelihood(distance,tree.getBranchLength(child),D, bias);
}
}
return -logLkl;
}
public int getNumArguments() {
return 2;
}
public double getLowerBound(int n) {
if (n == 0) return 1e-12;
return -Double.MAX_VALUE;
}
public double getUpperBound(int n) {
return 2000;
}
public double evaluate(double argument) {
return evaluate(new double[] {argument, 0.0});
}
public double getLowerBound() {
return getLowerBound(0);
}
public double getUpperBound() {
return getUpperBound(0);
}
}