/*
* EmergingEpidemicModel.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.coalescent;
import dr.evolution.coalescent.DemographicFunction;
import dr.evolution.coalescent.ExponentialGrowth;
import dr.evomodel.tree.TreeModel;
import dr.evomodelxml.coalescent.EmergingEpidemicModelParser;
import dr.inference.model.Parameter;
import dr.inference.model.Statistic;
/**
* This class models an exponentially growing (or shrinking) population
* (Parameters: N0=present-day population size; r=growth rate).
* This model is nested with the constant-population size model (r=0).
*
* @author Alexei Drummond
* @author Andrew Rambaut
* @version $Id: ExponentialGrowthModel.java,v 1.14 2005/05/24 20:25:57 rambaut Exp $
*/
public class EmergingEpidemicModel extends DemographicModel {
//
// Public stuff
//
/**
* Construct demographic model with default settings
*/
public EmergingEpidemicModel(Parameter growthRateParameter,
Parameter generationTimeParameter,
Parameter generationShapeParameter,
Parameter offspringDispersionParameter,
TreeModel treeModel,
Type units) {
this(EmergingEpidemicModelParser.EMERGING_EPIDEMIC_MODEL, growthRateParameter, generationTimeParameter, generationShapeParameter, offspringDispersionParameter, treeModel, units);
}
/**
* Construct demographic model with default settings
*/
public EmergingEpidemicModel(String name,
Parameter growthRateParameter,
Parameter generationTimeParameter,
Parameter generationShapeParameter,
Parameter offspringDispersionParameter,
TreeModel treeModel,
Type units) {
super(name);
exponentialGrowth = new ExponentialGrowth(units);
this.growthRateParameter = growthRateParameter;
addVariable(growthRateParameter);
growthRateParameter.addBounds(new Parameter.DefaultBounds(Double.MAX_VALUE, 0.0, 1));
this.generationTimeParameter = generationTimeParameter;
addVariable(generationTimeParameter);
generationTimeParameter.addBounds(new Parameter.DefaultBounds(Double.MAX_VALUE, 0.0, 1));
this.generationShapeParameter = generationShapeParameter;
addVariable(generationShapeParameter);
generationShapeParameter.addBounds(new Parameter.DefaultBounds(Double.MAX_VALUE, 0.0, 1));
this.offspringDispersionParameter = offspringDispersionParameter;
addVariable(offspringDispersionParameter);
offspringDispersionParameter.addBounds(new Parameter.DefaultBounds(Double.MAX_VALUE, 0.0, 1));
this.treeModel = treeModel;
addModel(treeModel);
addStatistic(new N0Statistic("N0"));
addStatistic(new RStatistic("R"));
setUnits(units);
}
// general functions
public DemographicFunction getDemographicFunction() {
exponentialGrowth.setN0(getN0());
exponentialGrowth.setGrowthRate(growthRateParameter.getParameterValue(0));
return exponentialGrowth;
}
public double getR() {
double r = growthRateParameter.getParameterValue(0);
double Tg = generationTimeParameter.getParameterValue(0);
double alpha = generationShapeParameter.getParameterValue(0);
double R = Math.pow(1.0 + ((r * Tg) / alpha), alpha);
return R;
}
public double getN0() {
double R = getR();
double t0 = treeModel.getNodeHeight(treeModel.getRoot());
double r = growthRateParameter.getParameterValue(0);
double Tg = generationTimeParameter.getParameterValue(0);
double k = offspringDispersionParameter.getParameterValue(0);
double N0 = (k * Tg * Math.exp(r * t0)) / (R * (k + R));
return N0;
}
public class N0Statistic extends Statistic.Abstract {
public N0Statistic(String name) {
super(name);
}
public int getDimension() {
return 1;
}
public double getStatisticValue(final int i) {
return getN0();
}
}
public class RStatistic extends Statistic.Abstract {
public RStatistic(String name) {
super(name);
}
public int getDimension() {
return 1;
}
public double getStatisticValue(final int i) {
return getR();
}
}
//
// protected stuff
//
private final Parameter growthRateParameter;
private final Parameter generationTimeParameter;
private final Parameter generationShapeParameter;
private final Parameter offspringDispersionParameter;
private final TreeModel treeModel;
private final ExponentialGrowth exponentialGrowth;
}