com.analog.lyric.dimple.factorfunctions.Poisson.java Source code

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/*******************************************************************************
*   Copyright 2014 Analog Devices, Inc.
*
*   Licensed under the Apache License, Version 2.0 (the "License");
*   you may not use this file except in compliance with the License.
*   You may obtain a copy of the License at
*
*       http://www.apache.org/licenses/LICENSE-2.0
*
*   Unless required by applicable law or agreed to in writing, software
*   distributed under the License is distributed on an "AS IS" BASIS,
*   WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
*   See the License for the specific language governing permissions and
*   limitations under the License.
********************************************************************************/

package com.analog.lyric.dimple.factorfunctions;

import java.util.Map;

import org.eclipse.jdt.annotation.Nullable;

import com.analog.lyric.dimple.exceptions.DimpleException;
import com.analog.lyric.dimple.factorfunctions.core.FactorFunctionUtilities;
import com.analog.lyric.dimple.factorfunctions.core.IParametricFactorFunction;
import com.analog.lyric.dimple.factorfunctions.core.UnaryFactorFunction;
import com.analog.lyric.dimple.model.values.Value;

/**
 * @since 0.06
 * @author Jake
 * 
 * Poisson distribution corresponding to p(k|lambda), where k is the observed number of counts
 * and lambda is the rate parameter.
 * 
 * The conjugate prior for lambda is the Gamma distribution
 * Depending on the solver, it may or may not be necessary to use a
 * conjugate prior (for the Gibbs solver, for example, it is not).
 * 
 * The variables in the argument are as follows:
 * 
 * 1) lambda: the rate parameter
 * 2) k: the observed number of counts
 * 
 * The rate parameter may optionally be specified as constants in the constructor.
 * In this case, it is not included in the list of arguments.
 */
public class Poisson extends UnaryFactorFunction implements IParametricFactorFunction {
    private static final long serialVersionUID = 1L;

    protected double _lambda;
    protected double _logLambda;
    protected boolean _lambdaParameterConstant = false;
    private int _firstDirectedToIndex = 1;

    /*---------------
     * Construction
     */

    public Poisson() {
        super((String) null);
    } // For variable lambda

    public Poisson(double lambda) // For fixed lambda
    {
        this();
        if (lambda <= 0)
            throw new DimpleException("lambda must be greater than zero.");
        _lambda = lambda;
        _logLambda = Math.log(lambda);
        _lambdaParameterConstant = true;
        _firstDirectedToIndex = 0;
    }

    /**
     * Constructs a Poisson distribution with fixed lambda parameter.
     * @param parameters If this contains an entry under the key "lambda", that will be used for the
     * corresponding parameter otherwise it will default to 1.0.
     * @since 0.07
     */
    public Poisson(Map<String, Object> parameters) {
        this((double) getOrDefault(parameters, "lambda", 1.0));
    }

    protected Poisson(Poisson other) {
        super(other);
        _lambda = other._lambda;
        _logLambda = other._logLambda;
        _lambdaParameterConstant = other._lambdaParameterConstant;
        _firstDirectedToIndex = other._firstDirectedToIndex;
    }

    @Override
    public Poisson clone() {
        return new Poisson(this);
    }

    /*----------------
     * IDatum methods
     */

    @Override
    public boolean objectEquals(@Nullable Object other) {
        if (this == other) {
            return true;
        }

        if (other instanceof Poisson) {
            Poisson that = (Poisson) other;
            return _lambdaParameterConstant == that._lambdaParameterConstant && _lambda == that._lambda
                    && _firstDirectedToIndex == that._firstDirectedToIndex;
        }

        return false;
    }

    /*------------------------
     * FactorFunction methods
     */

    @Override
    public final double evalEnergy(Value[] arguments) {
        int index = 0;

        // First argument of the factor: lambda
        if (!_lambdaParameterConstant) {
            _lambda = arguments[index++].getDouble();
            if (_lambda < 0)
                return Double.POSITIVE_INFINITY;
            _logLambda = Math.log(_lambda);
        }

        // Second argument of the factor: k
        final int k = arguments[index++].getInt();
        final double negativeLogFactorialK = -org.apache.commons.math3.special.Gamma.logGamma(k + 1);

        if (_lambda > 0)
            return -(-_lambda + k * _logLambda + negativeLogFactorialK);
        else if (_lambda == 0 && k != 0)
            return Double.POSITIVE_INFINITY;
        else if (_lambda == 0 && k == 0)
            return 0;
        return Double.POSITIVE_INFINITY;
    }

    @Override
    public final boolean isDirected() {
        return true;
    }

    @Override
    public final int[] getDirectedToIndices(int numEdges) {
        return FactorFunctionUtilities.getListOfIndices(_firstDirectedToIndex, numEdges - 1);
    }

    /*-----------------------------------
     * IParametricFactorFunction methods
     */

    @Override
    public int copyParametersInto(Map<String, Object> parameters) {
        if (_lambdaParameterConstant) {
            parameters.put("lambda", _lambda);
            return 1;
        }
        return 0;
    }

    @Override
    public @Nullable Object getParameter(String parameterName) {
        if (_lambdaParameterConstant) {
            switch (parameterName) {
            case "lambda":
                return _lambda;
            }
        }
        return null;
    }

    @Override
    public boolean hasConstantParameters() {
        return _lambdaParameterConstant;
    }

    /*-------------------------
     * Factor-specific methods
     */

    public final boolean hasConstantLambdaParameter() {
        return _lambdaParameterConstant;
    }

    public final double getLambda() {
        return _lambda;
    }
}