package de.ugoe.cs.quest.usageprofiles;
import java.util.ArrayList;
import java.util.Collection;
import java.util.List;
import de.ugoe.cs.quest.eventcore.Event;
import de.ugoe.cs.quest.usageprofiles.HighOrderMarkovModel;
import java.util.Random;
import org.junit.*;
import static org.junit.Assert.*;
/**
* The class HighOrderMarkovModelTest
contains tests for the class
* {@link HighOrderMarkovModel}
.
*
* @author Steffen Herbold
* @version 1.0
*/
public class HighOrderMarkovModelTest {
Collection>> sequences;
@Test
public void testHighOrderMarkovModel_1() throws Exception {
int maxOrder = 1;
Random r = new Random();
HighOrderMarkovModel result = new HighOrderMarkovModel(maxOrder, r);
assertNotNull(result);
assertEquals(r, result.r);
assertEquals(maxOrder + 1, result.trieOrder);
}
@Test
public void testHighOrderMarkovModel_2() throws Exception {
int maxOrder = 0;
Random r = new Random();
HighOrderMarkovModel result = new HighOrderMarkovModel(maxOrder, r);
assertNotNull(result);
assertEquals(r, result.r);
assertEquals(maxOrder + 1, result.trieOrder);
}
@Test(expected = java.security.InvalidParameterException.class)
public void testHighOrderMarkovModel_3() throws Exception {
int maxOrder = 1;
Random r = null;
new HighOrderMarkovModel(maxOrder, r);
}
@Test(expected = java.security.InvalidParameterException.class)
public void testHighOrderMarkovModel_4() throws Exception {
int maxOrder = -1;
Random r = new Random();
new HighOrderMarkovModel(maxOrder, r);
}
@Test
public void testGetProbability_1() throws Exception {
int markovOrder = 1;
HighOrderMarkovModel fixture = new HighOrderMarkovModel(markovOrder,
new Random());
fixture.train(sequences);
List> context = new ArrayList>();
context.add(new Event("a"));
Event symbol = new Event("b");
double result = fixture.getProbability(context, symbol);
assertEquals(2.0d / 5.0, result, 0.0001);
}
@Test
public void testGetProbability_2() throws Exception {
int markovOrder = 1;
HighOrderMarkovModel fixture = new HighOrderMarkovModel(markovOrder,
new Random());
fixture.train(sequences);
List> context = new ArrayList>();
context.add(new Event("a"));
Event symbol = new Event("r");
double result = fixture.getProbability(context, symbol);
assertEquals(0.0d / 5.0, result, 0.0001);
}
@Test
public void testGetProbability_3() throws Exception {
int markovOrder = 1;
HighOrderMarkovModel fixture = new HighOrderMarkovModel(markovOrder,
new Random());
fixture.train(sequences);
List> context = new ArrayList>();
context.add(new Event("a"));
Event symbol = new Event("c");
double result = fixture.getProbability(context, symbol);
assertEquals(1.0d / 5.0, result, 0.0001);
}
@Test
public void testGetProbability_4() throws Exception {
int markovOrder = 1;
HighOrderMarkovModel fixture = new HighOrderMarkovModel(markovOrder,
new Random());
fixture.train(sequences);
List> context = new ArrayList>();
context.add(Event.STARTEVENT);
context.add(new Event("a"));
Event symbol = new Event("b");
double result = fixture.getProbability(context, symbol);
assertEquals(2.0d / 5.0, result, 0.0001);
}
@Test
public void testGetProbability_5() throws Exception {
int markovOrder = 2;
HighOrderMarkovModel fixture = new HighOrderMarkovModel(markovOrder,
new Random());
fixture.train(sequences);
List> context = new ArrayList>();
context.add(Event.STARTEVENT);
context.add(new Event("a"));
Event symbol = new Event("b");
double result = fixture.getProbability(context, symbol);
assertEquals(1.0d, result, 0.0001);
}
@Test
public void testGetProbability_6() throws Exception {
int markovOrder = 2;
HighOrderMarkovModel fixture = new HighOrderMarkovModel(markovOrder,
new Random());
fixture.train(sequences);
List> context = new ArrayList>();
context.add(Event.STARTEVENT);
context.add(new Event("b"));
Event symbol = new Event("b");
double result = fixture.getProbability(context, symbol);
assertEquals(0.0d, result, 0.0001);
}
@Test
public void testGetProbability_7() throws Exception {
int markovOrder = 0;
HighOrderMarkovModel fixture = new HighOrderMarkovModel(markovOrder,
new Random());
fixture.train(sequences);
List> context = new ArrayList>();
context.add(Event.STARTEVENT);
context.add(new Event("b"));
Event symbol = new Event("a");
double result = fixture.getProbability(context, symbol);
assertEquals(5.0d / 13.0, result, 0.0001);
}
@Test(expected = java.security.InvalidParameterException.class)
public void testGetProbability_8() throws Exception {
int markovOrder = 0;
HighOrderMarkovModel fixture = new HighOrderMarkovModel(markovOrder,
new Random());
fixture.train(sequences);
List> context = new ArrayList>();
context.add(Event.STARTEVENT);
context.add(new Event("b"));
Event symbol = null;
fixture.getProbability(context, symbol);
}
@Test(expected = java.security.InvalidParameterException.class)
public void testGetProbability_9() throws Exception {
int markovOrder = 0;
HighOrderMarkovModel fixture = new HighOrderMarkovModel(markovOrder,
new Random());
fixture.train(sequences);
List> context = null;
Event symbol = new Event("b");
fixture.getProbability(context, symbol);
}
@Before
public void setUp() throws Exception {
List> sequence = new ArrayList>();
sequence.add(new Event("a"));
sequence.add(new Event("b"));
sequence.add(new Event("r"));
sequence.add(new Event("a"));
sequence.add(new Event("c"));
sequence.add(new Event("a"));
sequence.add(new Event("d"));
sequence.add(new Event("a"));
sequence.add(new Event("b"));
sequence.add(new Event("r"));
sequence.add(new Event("a"));
sequences = new ArrayList>>();
sequences.add(sequence);
}
public static void main(String[] args) {
new org.junit.runner.JUnitCore().run(HighOrderMarkovModelTest.class);
}
}