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Commons Math example source code file (AbstractIntegerDistribution.java)

This example Commons Math source code file (AbstractIntegerDistribution.java) is included in the DevDaily.com "Java Source Code Warehouse" project. The intent of this project is to help you "Learn Java by Example" TM.

Java - Commons Math tags/keywords

abstractdistribution, abstractintegerdistribution, functionevaluationexception, functionevaluationexception, integerdistribution, io, mathexception, mathexception, out_of_range_point, override, serializable, string, string, wrong_order_endpoints_message, wrong_order_endpoints_message

The Commons Math AbstractIntegerDistribution.java source code

/*
 * Licensed to the Apache Software Foundation (ASF) under one or more
 * contributor license agreements.  See the NOTICE file distributed with
 * this work for additional information regarding copyright ownership.
 * The ASF licenses this file to You 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 org.apache.commons.math.distribution;

import java.io.Serializable;

import org.apache.commons.math.FunctionEvaluationException;
import org.apache.commons.math.MathException;
import org.apache.commons.math.MathRuntimeException;


/**
 * Base class for integer-valued discrete distributions.  Default
 * implementations are provided for some of the methods that do not vary
 * from distribution to distribution.
 *
 * @version $Revision: 920558 $ $Date: 2010-03-08 17:57:32 -0500 (Mon, 08 Mar 2010) $
 */
public abstract class AbstractIntegerDistribution extends AbstractDistribution
    implements IntegerDistribution, Serializable {

    /** Message for endpoints in wrong order. */
    private static final String WRONG_ORDER_ENDPOINTS_MESSAGE =
        "lower endpoint ({0}) must be less than or equal to upper endpoint ({1})";

    /** Message for out of range point. */
    private static final String OUT_OF_RANGE_POINT =
        "{0} out of [{1}, {2}] range";

    /** Serializable version identifier */
    private static final long serialVersionUID = -1146319659338487221L;

    /**
     * Default constructor.
     */
    protected AbstractIntegerDistribution() {
        super();
    }

    /**
     * For a random variable X whose values are distributed according
     * to this distribution, this method returns P(X ? x).  In other words,
     * this method represents the  (cumulative) distribution function, or
     * CDF, for this distribution.
     * <p>
     * If <code>x does not represent an integer value, the CDF is
     * evaluated at the greatest integer less than x.
     *
     * @param x the value at which the distribution function is evaluated.
     * @return cumulative probability that a random variable with this
     * distribution takes a value less than or equal to <code>x
     * @throws MathException if the cumulative probability can not be
     * computed due to convergence or other numerical errors.
     */
    public double cumulativeProbability(double x) throws MathException {
        return cumulativeProbability((int) Math.floor(x));
    }

    /**
     * For a random variable X whose values are distributed according
     * to this distribution, this method returns P(x0 ? X ? x1).
     *
     * @param x0 the (inclusive) lower bound
     * @param x1 the (inclusive) upper bound
     * @return the probability that a random variable with this distribution
     * will take a value between <code>x0 and x1,
     * including the endpoints.
     * @throws MathException if the cumulative probability can not be
     * computed due to convergence or other numerical errors.
     * @throws IllegalArgumentException if <code>x0 > x1
     */
    @Override
    public double cumulativeProbability(double x0, double x1)
        throws MathException {
        if (x0 > x1) {
            throw MathRuntimeException.createIllegalArgumentException(
                  WRONG_ORDER_ENDPOINTS_MESSAGE, x0, x1);
        }
        if (Math.floor(x0) < x0) {
            return cumulativeProbability(((int) Math.floor(x0)) + 1,
               (int) Math.floor(x1)); // don't want to count mass below x0
        } else { // x0 is mathematical integer, so use as is
            return cumulativeProbability((int) Math.floor(x0),
                (int) Math.floor(x1));
        }
    }

    /**
     * For a random variable X whose values are distributed according
     * to this distribution, this method returns P(X ? x).  In other words,
     * this method represents the probability distribution function, or PDF,
     * for this distribution.
     *
     * @param x the value at which the PDF is evaluated.
     * @return PDF for this distribution.
     * @throws MathException if the cumulative probability can not be
     *            computed due to convergence or other numerical errors.
     */
    public abstract double cumulativeProbability(int x) throws MathException;

    /**
     * For a random variable X whose values are distributed according
     * to this distribution, this method returns P(X = x). In other words, this
     * method represents the probability mass function,  or PMF, for the distribution.
     * <p>
     * If <code>x does not represent an integer value, 0 is returned.
     *
     * @param x the value at which the probability density function is evaluated
     * @return the value of the probability density function at x
     */
    public double probability(double x) {
        double fl = Math.floor(x);
        if (fl == x) {
            return this.probability((int) x);
        } else {
            return 0;
        }
    }

    /**
    * For a random variable X whose values are distributed according
     * to this distribution, this method returns P(x0 ? X ? x1).
     *
     * @param x0 the inclusive, lower bound
     * @param x1 the inclusive, upper bound
     * @return the cumulative probability.
     * @throws MathException if the cumulative probability can not be
     *            computed due to convergence or other numerical errors.
     * @throws IllegalArgumentException if x0 > x1
     */
    public double cumulativeProbability(int x0, int x1) throws MathException {
        if (x0 > x1) {
            throw MathRuntimeException.createIllegalArgumentException(
                  WRONG_ORDER_ENDPOINTS_MESSAGE, x0, x1);
        }
        return cumulativeProbability(x1) - cumulativeProbability(x0 - 1);
    }

    /**
     * For a random variable X whose values are distributed according
     * to this distribution, this method returns the largest x, such
     * that P(X ? x) ? <code>p.
     *
     * @param p the desired probability
     * @return the largest x such that P(X ? x) <= p
     * @throws MathException if the inverse cumulative probability can not be
     *            computed due to convergence or other numerical errors.
     * @throws IllegalArgumentException if p < 0 or p > 1
     */
    public int inverseCumulativeProbability(final double p) throws MathException{
        if (p < 0.0 || p > 1.0) {
            throw MathRuntimeException.createIllegalArgumentException(
                  OUT_OF_RANGE_POINT, p, 0.0, 1.0);
        }

        // by default, do simple bisection.
        // subclasses can override if there is a better method.
        int x0 = getDomainLowerBound(p);
        int x1 = getDomainUpperBound(p);
        double pm;
        while (x0 < x1) {
            int xm = x0 + (x1 - x0) / 2;
            pm = checkedCumulativeProbability(xm);
            if (pm > p) {
                // update x1
                if (xm == x1) {
                    // this can happen with integer division
                    // simply decrement x1
                    --x1;
                } else {
                    // update x1 normally
                    x1 = xm;
                }
            } else {
                // update x0
                if (xm == x0) {
                    // this can happen with integer division
                    // simply increment x0
                    ++x0;
                } else {
                    // update x0 normally
                    x0 = xm;
                }
            }
        }

        // insure x0 is the correct critical point
        pm = checkedCumulativeProbability(x0);
        while (pm > p) {
            --x0;
            pm = checkedCumulativeProbability(x0);
        }

        return x0;
    }

    /**
     * Computes the cumulative probablity function and checks for NaN values returned.
     * Throws MathException if the value is NaN. Wraps and rethrows any MathException encountered
     * evaluating the cumulative probability function in a FunctionEvaluationException. Throws
     * FunctionEvaluationException of the cumulative probability function returns NaN.
     *
     * @param argument input value
     * @return cumulative probability
     * @throws FunctionEvaluationException if a MathException occurs computing the cumulative probability
     */
    private double checkedCumulativeProbability(int argument) throws FunctionEvaluationException {
        double result = Double.NaN;
        try {
            result = cumulativeProbability(argument);
        } catch (MathException ex) {
            throw new FunctionEvaluationException(ex, argument, ex.getPattern(), ex.getArguments());
        }
        if (Double.isNaN(result)) {
            throw new FunctionEvaluationException(argument,
                "Discrete cumulative probability function returned NaN for argument {0}", argument);
        }
        return result;
    }

    /**
     * Access the domain value lower bound, based on <code>p, used to
     * bracket a PDF root.  This method is used by
     * {@link #inverseCumulativeProbability(double)} to find critical values.
     *
     * @param p the desired probability for the critical value
     * @return domain value lower bound, i.e.
     *         P(X < <i>lower bound) < p
     */
    protected abstract int getDomainLowerBound(double p);

    /**
     * Access the domain value upper bound, based on <code>p, used to
     * bracket a PDF root.  This method is used by
     * {@link #inverseCumulativeProbability(double)} to find critical values.
     *
     * @param p the desired probability for the critical value
     * @return domain value upper bound, i.e.
     *         P(X < <i>upper bound) > p
     */
    protected abstract int getDomainUpperBound(double p);
}

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