/* * 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; }