/*
 * 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 $Revision$ $Date$
 */
public class WeibullDistributionImpl extends AbstractContinuousDistribution
		implements WeibullDistribution, Serializable {

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

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

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

	/**
	 * 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) {
		super();
		setShape(alpha);
		setScale(beta);
	}

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

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

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

	/**
	 * For this distribution, X, this method returns the critical point x, such
	 * that P(X &lt; x) = <code>p</code>.
	 * <p>
	 * Returns <code>Double.NEGATIVE_INFINITY</code> for p=0 and
	 * <code>Double.POSITIVE_INFINITY</code> for p=1.
	 * </p>
	 *
	 * @param p
	 *            the desired probability
	 * @return x, such that P(X &lt; x) = <code>p</code>
	 * @throws IllegalArgumentException
	 *             if <code>p</code> 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 = getScale() * Math.pow(-Math.log(1.0 - p), 1.0 / getShape());
		}
		return ret;
	}

	/**
	 * Modify the shape parameter.
	 * 
	 * @param alpha
	 *            the new shape parameter value.
	 */
	public void setShape(double alpha) {
		if (alpha <= 0.0) {
			throw MathRuntimeException.createIllegalArgumentException("shape must be positive ({0})", alpha);
		}
		this.alpha = alpha;
	}

	/**
	 * Modify the scale parameter.
	 * 
	 * @param beta
	 *            the new scale parameter value.
	 */
	public void setScale(double beta) {
		if (beta <= 0.0) {
			throw MathRuntimeException.createIllegalArgumentException("scale must be positive ({0})", beta);
		}
		this.beta = beta;
	}

	/**
	 * Access the domain value lower bound, based on <code>p</code>, 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 &lt; <i>lower bound</i>) &lt;
	 *         <code>p</code>
	 */
	@Override
	protected double getDomainLowerBound(double p) {
		return 0.0;
	}

	/**
	 * Access the domain value upper bound, based on <code>p</code>, 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 &lt; <i>upper bound</i>) &gt;
	 *         <code>p</code>
	 */
	@Override
	protected double getDomainUpperBound(double p) {
		return Double.MAX_VALUE;
	}

	/**
	 * Access the initial domain value, based on <code>p</code>, 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(getScale() * Math.log(2.0), 1.0 / getShape());
	}
}
