Java tutorial
/* * GammaDistributionModel.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.inference.distribution; import dr.inference.model.AbstractModel; import dr.inference.model.Model; import dr.inference.model.Parameter; import dr.inference.model.Variable; import dr.math.UnivariateFunction; import dr.math.distributions.GammaDistribution; import org.apache.commons.math.MathException; import org.apache.commons.math.distribution.GammaDistributionImpl; import org.w3c.dom.Document; import org.w3c.dom.Element; /** * A class that acts as a model for gamma distributed data. * * @author Andrew Rambaut * @author Alexei Drummond * @version $Id: GammaDistributionModel.java,v 1.6 2005/05/24 20:25:59 rambaut Exp $ */ public class GammaDistributionModel extends AbstractModel implements ParametricDistributionModel { public enum GammaParameterizationType { ShapeScale, ShapeRate, ShapeMean, OneParameter } public static final String GAMMA_DISTRIBUTION_MODEL = "gammaDistributionModel"; public static final String ONE_P_GAMMA_DISTRIBUTION_MODEL = "onePGammaDistributionModel"; /** * Construct a gamma distribution model with a default shape scale parameterization. */ public GammaDistributionModel(Variable<Double> shape, Variable<Double> scale) { this(GammaParameterizationType.ShapeScale, shape, scale, 0.0); } /** * Construct a one parameter gamma distribution model. */ public GammaDistributionModel(Variable<Double> shape) { this(GammaParameterizationType.OneParameter, shape, null, 0.0); } /** * Construct a gamma distribution model. */ public GammaDistributionModel(GammaParameterizationType parameterization, Variable<Double> shape, Variable<Double> parameter2, double offset) { super(GAMMA_DISTRIBUTION_MODEL); this.offset = offset; this.parameterization = parameterization; this.shape = shape; addVariable(shape); shape.addBounds(new Parameter.DefaultBounds(Double.POSITIVE_INFINITY, 0.0, 1)); switch (parameterization) { case ShapeScale: this.scale = parameter2; addVariable(scale); scale.addBounds(new Parameter.DefaultBounds(Double.POSITIVE_INFINITY, 0.0, 1)); rate = null; mean = null; break; case ShapeRate: this.rate = parameter2; addVariable(rate); rate.addBounds(new Parameter.DefaultBounds(Double.POSITIVE_INFINITY, 0.0, 1)); scale = null; mean = null; break; case ShapeMean: this.mean = parameter2; addVariable(mean); mean.addBounds(new Parameter.DefaultBounds(Double.POSITIVE_INFINITY, 0.0, 1)); scale = null; rate = null; break; case OneParameter: scale = null; rate = null; mean = null; break; default: throw new IllegalArgumentException("Unknown parameterization type"); } } // ***************************************************************** // Interface Distribution // ***************************************************************** public double pdf(double x) { if (x < offset) return 0.0; return GammaDistribution.pdf(x - offset, getShape(), getScale()); } public double logPdf(double x) { if (x < offset) return Double.NEGATIVE_INFINITY; return GammaDistribution.logPdf(x - offset, getShape(), getScale()); } public double cdf(double x) { if (x < offset) return 0.0; return GammaDistribution.cdf(x - offset, getShape(), getScale()); } public double quantile(double y) { try { return (new GammaDistributionImpl(getShape(), getScale())).inverseCumulativeProbability(y) + offset; } catch (MathException e) { return Double.NaN; } } public double mean() { return GammaDistribution.mean(getShape(), getScale()) + offset; } public double variance() { return GammaDistribution.variance(getShape(), getScale()); } public final UnivariateFunction getProbabilityDensityFunction() { return pdfFunction; } private final UnivariateFunction pdfFunction = new UnivariateFunction() { public final double evaluate(double x) { return pdf(x); } public final double getLowerBound() { return offset; } public final double getUpperBound() { return Double.POSITIVE_INFINITY; } }; // ***************************************************************** // Interface Model // ***************************************************************** public void handleModelChangedEvent(Model model, Object object, int index) { // no intermediates need to be recalculated... } protected final void handleVariableChangedEvent(Variable variable, int index, Parameter.ChangeType type) { // no intermediates need to be recalculated... } protected void storeState() { } // no additional state needs storing protected void restoreState() { } // no additional state needs restoring protected void acceptState() { } // no additional state needs accepting // ************************************************************** // XMLElement IMPLEMENTATION // ************************************************************** public Element createElement(Document document) { throw new RuntimeException("Not implemented!"); } public double getShape() { return shape.getValue(0); } public double getScale() { switch (parameterization) { case ShapeScale: return scale.getValue(0); case ShapeRate: return (1.0 / rate.getValue(0)); case ShapeMean: return (mean.getValue(0) / getShape()); case OneParameter: return (1.0 / getShape()); default: throw new IllegalArgumentException("Unknown parameterization type"); } } // ***************************************************************** // Interface DensityModel // ***************************************************************** @Override public double logPdf(double[] x) { return logPdf(x[0]); } @Override public Variable<Double> getLocationVariable() { throw new UnsupportedOperationException("Not implemented"); } // ************************************************************** // Private instance variables // ************************************************************** private final GammaParameterizationType parameterization; private final Variable<Double> shape; private final Variable<Double> scale; private final Variable<Double> rate; private final Variable<Double> mean; private final double offset; }