/*
* JGAAP -- a graphical program for stylometric authorship attribution
* Copyright (C) 2009,2011 by Patrick Juola
*
* This program is free software: you can redistribute it and/or modify
* it under the terms of the GNU Affero General Public License as
* published by the Free Software Foundation, either version 3 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 Affero General Public License for more details.
*
* You should have received a copy of the GNU Affero General Public License
* along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
/**
*
*/
package com.jgaap.distances;
import static org.junit.Assert.*;
import java.util.Vector;
import org.junit.Test;
import com.jgaap.util.Event;
import com.jgaap.util.EventMap;
import com.jgaap.util.EventSet;
/**
* @author darrenvescovi
*
*/
public class CrossEntropyDivergenceTest {
/**
* Test method for {@link com.jgaap.distances.CrossEntropyDivergence#divergence(com.jgaap.util.EventSet, com.jgaap.util.EventSet)}.
*/
@Test
public void testDivergence() {
EventSet known1 = new EventSet();
EventSet known2;
Vector<Event> test1 = new Vector<Event>();
test1.add(new Event("mary", null));
test1.add(new Event("had", null));
test1.add(new Event("a", null));
test1.add(new Event("little", null));
test1.add(new Event("lamb", null));
test1.add(new Event("whose", null));
test1.add(new Event("fleece", null));
test1.add(new Event("was", null));
test1.add(new Event("white", null));
test1.add(new Event("as", null));
test1.add(new Event("snow", null));
known1.addEvents(test1);
//known1.setAuthor("Mary");
//Same event set
double Result = new CrossEntropyDivergence().divergence(new EventMap(known1), new EventMap(known1));
//System.out.println(s);
assertTrue(DistanceTestHelper.inRange(Result, 2.3978952, 0.0000001));
//different event sets
test1 = new Vector<Event>();
Vector<Event> test2 = new Vector<Event>();
test1.add(new Event("alpha", null));
test1.add(new Event("beta", null));
known1 = new EventSet();
known1.addEvents(test1);
test2.add(new Event("alpha", null));
test2.add(new Event("alpha", null));
test2.add(new Event("alpha", null));
test2.add(new Event("beta", null));
known2 = new EventSet();
known2.addEvents(test2);
Result = new CrossEntropyDivergence().divergence(new EventMap(known1), new EventMap(known2));
//System.out.println(Result);
assertTrue(DistanceTestHelper.inRange(Result, 0.836988, 0.000001));
//Reversed Event Sets
Result = new CrossEntropyDivergence().divergence(new EventMap(known2), new EventMap(known1));
//System.out.println(Result);
assertTrue(DistanceTestHelper.inRange(Result, 0.693147, 0.000001));
//Test with Smoothing
test2 = new Vector<Event>();
test2.add(new Event("alpha", null));
test2.add(new Event("alpha", null));
test2.add(new Event("beta", null));
test2.add(new Event("gamma", null));
known2 = new EventSet();
known2.addEvents(test2);
//System.out.println("Start Here");
Result = new CrossEntropyDivergence().divergence(new EventMap(known2), new EventMap(known1));
//System.out.println(Result);
assertTrue(DistanceTestHelper.inRange(Result, 0.5198603854199589, 0.000001));
//revese the event sets
Result = new CrossEntropyDivergence().divergence(new EventMap(known1), new EventMap(known2));
//System.out.println(Result);
assertTrue(DistanceTestHelper.inRange(Result, 1.0397207, 0.0000001));
}
}