mmpp2par.java

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/**    
 * Copyright (C) 2006, Laboratorio di Valutazione delle Prestazioni - Politecnico di Milano

 * This program 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 2 of the License, or
 * (at your option) any later version.

 * This program 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 this program; if not, write to the Free Software
 * Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA  02110-1301  USA
 */
 
package jmt.engine.random;

import jmt.common.exception.IncorrectDistributionParameterException;


/**
*
* This is the parameter that should be passed to the Hyper Exponential
* distribution.
*
* <br><br>Copyright (c) 2006
* <br>Politecnico di Milano - dipartimento di Elettronica e Informazione
* @author Giuliano Casale
*
*/


public class MMPP2Par extends Parameter {

	private double mean;
	private double var;
	private double r0;
	private double r1;
	private double lambda1;
	private double lambda2;
	protected ExponentialPar expParam1;
	protected ExponentialPar expParam2;

	public MMPP2Par(Double lambda0, Double lambda1, Double r0, Double r1)
	        throws IncorrectDistributionParameterException {
		this.r0 = r0.doubleValue();
		this.r1 = r1.doubleValue();
		this.lambda1 = lambda0.doubleValue();
		this.lambda2 = lambda1.doubleValue();
		testParameters();
		this.mean = 0;
		this.var = 0;
		// creates 2 ExponentialPar objects
		expParam1 = new ExponentialPar(1/this.lambda1);
		expParam2 = new ExponentialPar(1/this.lambda2);
	}

	/**
	 * Tests the parameters for the constructor requiring p, lambda1 and lambda2.
	 *
	 * @throws IncorrectDistributionParameterException if p is not betwen zero and one or if lambda1 and labda2 are not both greater than zero.
	 *
	 */
	private void testParameters()
	        throws IncorrectDistributionParameterException {
		if (r1 <= 0 || r1 >= 1)
			throw new IncorrectDistributionParameterException("Error: must be 0 < r1 < 1");
		if (r0 <= 0 || r0 >= 1)
			throw new IncorrectDistributionParameterException("Error: must be 0 < r0 < 1");
		if (lambda1 < 0)
			throw new IncorrectDistributionParameterException("Error: lambda1 must be >= 0");
		if (lambda2 < 0)
			throw new IncorrectDistributionParameterException("Error: lambda2 must be >= 0");
	}

	/**
	 * It verify if the parameter is correct. For the hyper exponential
	 * distribution, the parameter is right if the mean calculated is gtz,
	 * the variance is gtz, p probability is betwen 0 and 1 and both the lambda value are gtz.
	 *
	 * @return boolean, indicating wether the parameter is correct or not.
	 *
	 */

	public boolean check() {
		if ((r0 <= 0 || r0 >= 1) || (r1 <= 0 || r1 >= 1) || (lambda1 < 0) || (lambda2 < 0)) {
			return false;
		} else {
			return true;
		}
	}

	public double getR0() {
		return r0;
	}

	public double getR1() {
		return r1;
	}

	/**
	 * it returns the value of lambda1.
	 * It returns the value of the parameter lambda1, the parameter lamda for the
	 * first exponential distribution created by the hyper exponential parameter.
	 *
	 * @return double with lambda1 the value of lambda for the 1st exponential distribution.
	 *
	 */

	public double getLambda1() {
		return lambda1;
	}

	/**
	 * it returns the value of lambda2.
	 * It returns the value of the parameter lambda2, the parameter lamda for the
	 * second exponential distribution created by the hyper exponential parameter.
	 *
	 * @return double with lambda2 the value of lambda for the 2nd exponential distribution.
	 *
	 */

	public double getLambda2() {
		return lambda2;
	}

	/**
	 * it returns the mean of the distribution.
	 * It returns the value of the mean of the hyper exponential distribution which
	 * is provided by the user or evaluated according to other data.
	 *
	 * @return double with the mean of the hyper exponential distribution.
	 *
	 */
	public double getMean() {
		return mean;
	}

	/**
	 * it returns the variance of the distribution.
	 * It returns the value of the variance of the hyper exponential distribution which
	 * is provided by the user or evaluated according to other data.
	 *
	 * @return double with the variance of the hyper exponential distribution.
	 *
	 */

	public double getVar() {
		return var;
	}

	/**
	 * it returns the parameter of the 1st exponential.
	 * It returns the parameter used to create the first of the exponential
	 * distribution used by the hyper exponential distribution.
	 *
	 * @return exponentialPar with expParam1, the parameter of the 1st exponential distribution.
	 *
	 */

	public ExponentialPar getExpParam1() {
		return expParam1;
	}

	/**
	 * it returns the parameter of the 2nd exponential.
	 * It returns the parameter used to create the second of the exponential
	 * distribution used by the hyper exponential distribution.
	 *
	 * @return exponentialPar with expParam2, the parameter of the 2nd exponential distribution.
	 *
	 */

	public ExponentialPar getExpParam2() {
		return expParam2;
	}

} // end HyperExpPar