Commons Math example source code file (WeibullDistributionImpl.java)

This example Commons Math source code file (WeibullDistributionImpl.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

abstractcontinuousdistribution, default_inverse_absolute_accuracy, default_inverse_absolute_accuracy, deprecated, deprecated, io, override, override, serializable, weibulldistribution, weibulldistributionimpl, weibulldistributionimpl

The Commons Math WeibullDistributionImpl.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.MathRuntimeException;

/**
 * Default implementation of
 * {@link org.apache.commons.math.distribution.WeibullDistribution}.
 *
 * @since 1.1
 * @version $Revision: 925812 $ $Date: 2010-03-21 11:49:31 -0400 (Sun, 21 Mar 2010) $
 */
public class WeibullDistributionImpl extends AbstractContinuousDistribution
        implements WeibullDistribution, Serializable {

    /**
     * Default inverse cumulative probability accuracy
     * @since 2.1
     */
    public static final double DEFAULT_INVERSE_ABSOLUTE_ACCURACY = 1e-9;

    /** Serializable version identifier */
    private static final long serialVersionUID = 8589540077390120676L;

    /** The shape parameter. */
    private double shape;

    /** The scale parameter. */
    private double scale;

    /** Inverse cumulative probability accuracy */
    private final double solverAbsoluteAccuracy;

    /**
     * Creates weibull distribution with the given shape and scale and a
     * location equal to zero.
     * @param alpha the shape parameter.
     * @param beta the scale parameter.
     */
    public WeibullDistributionImpl(double alpha, double beta){
        this(alpha, beta, DEFAULT_INVERSE_ABSOLUTE_ACCURACY);
    }

    /**
     * Creates weibull distribution with the given shape, scale and inverse
     * cumulative probability accuracy and a location equal to zero.
     * @param alpha the shape parameter.
     * @param beta the scale parameter.
     * @param inverseCumAccuracy the maximum absolute error in inverse cumulative probability estimates
     * (defaults to {@link #DEFAULT_INVERSE_ABSOLUTE_ACCURACY})
     * @since 2.1
     */
    public WeibullDistributionImpl(double alpha, double beta, double inverseCumAccuracy){
        super();
        setShapeInternal(alpha);
        setScaleInternal(beta);
        solverAbsoluteAccuracy = inverseCumAccuracy;
    }

    /**
     * For this distribution, X, this method returns P(X < <code>x).
     * @param x the value at which the CDF is evaluated.
     * @return CDF evaluted at <code>x.
     */
    public double cumulativeProbability(double x) {
        double ret;
        if (x <= 0.0) {
            ret = 0.0;
        } else {
            ret = 1.0 - Math.exp(-Math.pow(x / scale, shape));
        }
        return ret;
    }

    /**
     * Access the shape parameter.
     * @return the shape parameter.
     */
    public double getShape() {
        return shape;
    }

    /**
     * Access the scale parameter.
     * @return the scale parameter.
     */
    public double getScale() {
        return scale;
    }

    /**
     * Returns the probability density for a particular point.
     *
     * @param x The point at which the density should be computed.
     * @return The pdf at point x.
     * @since 2.1
     */
    @Override
    public double density(double x) {
        if (x < 0) {
            return 0;
        }

        final double xscale = x / scale;
        final double xscalepow = Math.pow(xscale, shape - 1);

        /*
         * Math.pow(x / scale, shape) =
         * Math.pow(xscale, shape) =
         * Math.pow(xscale, shape - 1) * xscale
         */
        final double xscalepowshape = xscalepow * xscale;

        return (shape / scale) * xscalepow * Math.exp(-xscalepowshape);
    }

    /**
     * For this distribution, X, this method returns the critical point x, such
     * that P(X < x) = <code>p.
     * <p>
     * Returns <code>Double.NEGATIVE_INFINITY for p=0 and
     * <code>Double.POSITIVE_INFINITY for p=1.

     *
     * @param p the desired probability
     * @return x, such that P(X < x) = <code>p
     * @throws IllegalArgumentException if <code>p is not a valid
     *         probability.
     */
    @Override
    public double inverseCumulativeProbability(double p) {
        double ret;
        if (p < 0.0 || p > 1.0) {
            throw MathRuntimeException.createIllegalArgumentException(
                  "{0} out of [{1}, {2}] range", p, 0.0, 1.0);
        } else if (p == 0) {
            ret = 0.0;
        } else  if (p == 1) {
            ret = Double.POSITIVE_INFINITY;
        } else {
            ret = scale * Math.pow(-Math.log(1.0 - p), 1.0 / shape);
        }
        return ret;
    }

    /**
     * Modify the shape parameter.
     * @param alpha the new shape parameter value.
     * @deprecated as of 2.1 (class will become immutable in 3.0)
     */
    @Deprecated
    public void setShape(double alpha) {
        setShapeInternal(alpha);
    }
    /**
     * Modify the shape parameter.
     * @param alpha the new shape parameter value.
     */
    private void setShapeInternal(double alpha) {
        if (alpha <= 0.0) {
            throw MathRuntimeException.createIllegalArgumentException(
                  "shape must be positive ({0})",
                  alpha);
        }
        this.shape = alpha;
    }

    /**
     * Modify the scale parameter.
     * @param beta the new scale parameter value.
     * @deprecated as of 2.1 (class will become immutable in 3.0)
     */
    @Deprecated
    public void setScale(double beta) {
        setScaleInternal(beta);
    }
    /**
     * Modify the scale parameter.
     * @param beta the new scale parameter value.
     */
    private void setScaleInternal(double beta) {
        if (beta <= 0.0) {
            throw MathRuntimeException.createIllegalArgumentException(
                  "scale must be positive ({0})",
                  beta);
        }
        this.scale = beta;
    }

    /**
     * Access the domain value lower bound, based on <code>p, used to
     * bracket a CDF 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
     */
    @Override
    protected double getDomainLowerBound(double p) {
        return 0.0;
    }

    /**
     * Access the domain value upper bound, based on <code>p, used to
     * bracket a CDF 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
     */
    @Override
    protected double getDomainUpperBound(double p) {
        return Double.MAX_VALUE;
    }

    /**
     * Access the initial domain value, based on <code>p, used to
     * bracket a CDF root.  This method is used by
     * {@link #inverseCumulativeProbability(double)} to find critical values.
     *
     * @param p the desired probability for the critical value
     * @return initial domain value
     */
    @Override
    protected double getInitialDomain(double p) {
        // use median
        return Math.pow(scale * Math.log(2.0), 1.0 / shape);
    }

    /**
     * Return the absolute accuracy setting of the solver used to estimate
     * inverse cumulative probabilities.
     *
     * @return the solver absolute accuracy
     * @since 2.1
     */
    @Override
    protected double getSolverAbsoluteAccuracy() {
        return solverAbsoluteAccuracy;
    }
}