beast.inference.distribution.GammaDistributionModel.java Source code

Introduction

Here is the source code for beast.inference.distribution.GammaDistributionModel.java

Source

/*
 * GammaDistributionModel.java
 *
 * BEAST: Bayesian Evolutionary Analysis by Sampling Trees
 * Copyright (C) 2014 BEAST Developers
 *
 * BEAST is free software: you can redistribute it and/or modify it
 * under the terms of the GNU General Public License as published by
 * the Free Software Foundation, either version 3 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 General Public License for more details.
 *
 * You should have received a copy of the GNU General Public License
 * along with BEAST.  If not, see <http://www.gnu.org/licenses/>.
 */

package beast.inference.distribution;

import beast.inference.model.AbstractModel;
import beast.inference.model.Model;
import beast.inference.model.Parameter;
import beast.inference.model.Variable;
import beast.math.UnivariateFunction;
import beast.math.distributions.GammaDistribution;
import beast.xml.XMLObjectParser;
import org.w3c.dom.Document;
import org.w3c.dom.Element;

/**
 * A class that acts as a model for gamma distributed data.
 *
 * @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 static final String GAMMA_DISTRIBUTION_MODEL = "gammaDistributionModel";

    /**
     * Construct a constant mutation rate model.
     */
    public GammaDistributionModel(Variable<Double> shape, Variable<Double> scale) {

        super(GAMMA_DISTRIBUTION_MODEL);

        this.shape = shape;
        this.scale = scale;
        addVariable(shape);
        shape.addBounds(new Parameter.DefaultBounds(Double.POSITIVE_INFINITY, 0.0, 1));
        if (scale != null) {
            addVariable(scale);
            scale.addBounds(new Parameter.DefaultBounds(Double.POSITIVE_INFINITY, 0.0, 1));
        }
    }

    /**
     * Construct a constant mutation rate model.
     */
    public GammaDistributionModel(Variable<Double> shape) {

        super(GAMMA_DISTRIBUTION_MODEL);

        this.shape = shape;
        addVariable(shape);
        shape.addBounds(new Parameter.DefaultBounds(Double.POSITIVE_INFINITY, 0.0, 1));
    }

    // *****************************************************************
    // Interface Distribution
    // *****************************************************************

    public double pdf(double x) {
        return GammaDistribution.pdf(x, getShape(), getScale());
    }

    public double logPdf(double x) {
        return GammaDistribution.logPdf(x, getShape(), getScale());
    }

    public double cdf(double x) {
        return GammaDistribution.cdf(x, getShape(), getScale());
    }

    public double quantile(double y) {
        return (new org.apache.commons.math3.distribution.GammaDistribution(getShape(), getScale()))
                .inverseCumulativeProbability(y);
    }

    public double mean() {
        return GammaDistribution.mean(getShape(), getScale());
    }

    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 0.0;
        }

        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() {
        if (scale == null)
            return (1.0 / getShape());
        return scale.getValue(0);
    }

    // **************************************************************
    // Private instance variables
    // **************************************************************

    private Variable<Double> shape = null;
    private Variable<Double> scale = null;

    public static final XMLObjectParser<GammaDistributionModel> PARSER = new DistributionModelParser<GammaDistributionModel>() {
        public String getParserName() {
            return GammaDistributionModel.GAMMA_DISTRIBUTION_MODEL;
        }

        GammaDistributionModel parseDistributionModel(Parameter[] parameters, double offset) {
            return new GammaDistributionModel(parameters[0], parameters[1]);
        }

        public String[] getParameterNames() {
            return new String[] { SHAPE, SCALE };
        }

        public String getParserDescription() {
            return "A model of a gamma distribution.";
        }

        public boolean allowOffset() {
            return false;
        }

        public Class getReturnType() {
            return GammaDistributionModel.class;
        }
    };
}