/*
* 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 Juola
*
*/
public class PearsonCorrelationDistanceTest {
/**
* Test method for {@link com.jgaap.distances.PearsonCorrelationDistance#distance(com.jgaap.util.EventSet, com.jgaap.util.EventSet)}.
*/
@Test
public void testDistance() {
// n.b. data from testset 2 from http://davidmlane.com/hyperstat/A56626.html
// test 1 : identical distributions
EventSet es1 = new EventSet();
EventSet es2 = new EventSet();
Vector<Event> test1 = new Vector<Event>();
test1.add(new Event("alpha", null));
test1.add(new Event("beta", null));
test1.add(new Event("beta", null));
test1.add(new Event("gamma", null));
test1.add(new Event("gamma", null));
test1.add(new Event("gamma", null));
es1.addEvents(test1);
es2.addEvents(test1);
assertTrue(new PearsonCorrelationDistance().distance(new EventMap(es1), new EventMap(es2)) == 0);
// test 2 : identical probabilities but different distributions
es1=new EventSet();
es2=new EventSet();
test1 = new Vector<Event>();
Vector<Event> test2 = new Vector<Event>();
test1.add(new Event("A", null));
test1.add(new Event("B", null));
test1.add(new Event("B", null));
test1.add(new Event("C", null));
test1.add(new Event("D", null));
test1.add(new Event("E", null));
test2.add(new Event("A", null));
test2.add(new Event("A", null));
test2.add(new Event("B", null));
test2.add(new Event("B", null));
test2.add(new Event("B", null));
test2.add(new Event("B", null));
test2.add(new Event("C", null));
test2.add(new Event("C", null));
test2.add(new Event("D", null));
test2.add(new Event("D", null));
test2.add(new Event("E", null));
test2.add(new Event("E", null));
es1.addEvents(test1);
es2.addEvents(test2);
double result = new PearsonCorrelationDistance().distance(new EventMap(es1), new EventMap(es2));
//System.out.println(result);
assertTrue(DistanceTestHelper.inRange(result, 0.0, 0.0000000001));
// test 3 : Perfect anticorrelation
es1=new EventSet();
es2=new EventSet();
test1 = new Vector<Event>();
test2 = new Vector<Event>();
test1.add(new Event("A", null));
test1.add(new Event("A", null));
test1.add(new Event("A", null));
test1.add(new Event("B", null));
test1.add(new Event("B", null));
test1.add(new Event("C", null));
test2.add(new Event("C", null));
test2.add(new Event("C", null));
test2.add(new Event("C", null));
test2.add(new Event("B", null));
test2.add(new Event("B", null));
test2.add(new Event("A", null));
es1.addEvents(test1);
es2.addEvents(test2);
result = new PearsonCorrelationDistance().distance(new EventMap(es1), new EventMap(es2));
//System.out.println(result);
assertTrue(DistanceTestHelper.inRange(result, 2.0, 0.0000000001));
// test 4 : non-trivial calculation
es1=new EventSet();
es2=new EventSet();
test1 = new Vector<Event>();
test2 = new Vector<Event>();
test1.add(new Event("A", null));
test1.add(new Event("B", null));
test1.add(new Event("B", null));
test1.add(new Event("C", null));
test1.add(new Event("C", null));
test1.add(new Event("C", null));
test2.add(new Event("A", null));
test2.add(new Event("A", null));
test2.add(new Event("B", null));
test2.add(new Event("B", null));
test2.add(new Event("B", null));
test2.add(new Event("B", null));
test2.add(new Event("B", null));
test2.add(new Event("C", null));
test2.add(new Event("C", null));
test2.add(new Event("C", null));
test2.add(new Event("C", null));
test2.add(new Event("C", null));
test2.add(new Event("C", null));
es1.addEvents(test1);
es2.addEvents(test2);
result = new PearsonCorrelationDistance().distance(new EventMap(es1), new EventMap(es2));
System.out.println(result);
assertTrue(DistanceTestHelper.inRange(result, 1-0.9608, 0.001));
// test 5 : edge case (NaN)
es1=new EventSet();
es2=new EventSet();
test1 = new Vector<Event>();
test2 = new Vector<Event>();
test1.add(new Event("A", null));
test1.add(new Event("B", null));
test1.add(new Event("C", null));
test2.add(new Event("A", null));
test2.add(new Event("B", null));
test2.add(new Event("B", null));
test2.add(new Event("C", null));
test2.add(new Event("C", null));
test2.add(new Event("C", null));
es1.addEvents(test1);
es2.addEvents(test2);
result = new PearsonCorrelationDistance().distance(new EventMap(es1), new EventMap(es2));
System.out.println(result);
assertTrue(DistanceTestHelper.inRange(result, 1.0, 0.001));
// test 6 : edge case (point mass)
es1=new EventSet();
es2=new EventSet();
test1 = new Vector<Event>();
test2 = new Vector<Event>();
test1.add(new Event("A", null));
test1.add(new Event("B", null));
test1.add(new Event("C", null));
test2.add(new Event("A", null));
test2.add(new Event("A", null));
test2.add(new Event("B", null));
test2.add(new Event("B", null));
test2.add(new Event("C", null));
test2.add(new Event("C", null));
es1.addEvents(test1);
es2.addEvents(test2);
result = new PearsonCorrelationDistance().distance(new EventMap(es1), new EventMap(es2));
System.out.println(result);
assertTrue(DistanceTestHelper.inRange(result, 0.0, 0.001));
}
}