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📄 estimatedcriteriontest.java

📁 著名的开源仿真软件yale
💻 JAVA
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/* *  YALE - Yet Another Learning Environment *  Copyright (C) 2002, 2003 *      Simon Fischer, Ralf Klinkenberg, Ingo Mierswa,  *          Katharina Morik, Oliver Ritthoff *      Artificial Intelligence Unit *      Computer Science Department *      University of Dortmund *      44221 Dortmund,  Germany *  email: yale@ls8.cs.uni-dortmund.de *  web:   http://yale.cs.uni-dortmund.de/ * *  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., 59 Temple Place, Suite 330, Boston, MA 02111-1307 *  USA. */package edu.udo.cs.yale.operator.performance.test;import edu.udo.cs.yale.operator.performance.*;/** Tests {@link EstimatedPerformance}. * *  @version $Id: EstimatedCriterionTest.java,v 1.4 2003/05/22 11:51:18 fischer Exp $ */public class EstimatedCriterionTest extends CriterionTestCase {    private EstimatedPerformance performance10x08, performance20x04;        public void setUp() throws Exception {	super.setUp();	performance10x08 = new EstimatedPerformance("test_performance", 0.8, 10, false);	performance20x04 = new EstimatedPerformance("test_performance", 0.4, 20, false);    }    public void tearDown() throws Exception {	performance10x08 = performance20x04 = null;	super.tearDown();    }    /** Tests micro and makro average. Since makro average is implemented in      *  {@link PerformanceCriterion}, this does not have to be tested for measured     *  performance criteria. */    public void testAverage() {	performance10x08.buildAverage(performance20x04);	assertEquals("Wrong weighted average", 		     (10*0.8 + 20*0.4) / (10+20),		     performance10x08.getValue(), 		     0.0000001);	assertEquals("Wrong makro average", 		     (0.8 + 0.4) / 2, 		     performance10x08.getMakroAverage(), 		     0.0000001);    }    public void testClone() {	cloneTest("Clone of simple criterion", performance10x08);	performance10x08.buildAverage(performance20x04);	cloneTest("Clone of averaged criterion", performance10x08);    }}

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