/* Copyright (C) 2006 Univ. of Massachusetts Amherst, Computer Science Dept.
This file is part of "MALLET" (MAchine Learning for LanguagE Toolkit).
http://www.cs.umass.edu/~mccallum/mallet
This software is provided under the terms of the Common Public License,
version 1.0, as published by http://www.opensource.org. For further
information, see the file `LICENSE' included with this distribution. */
package cc.mallet.grmm.test;
import junit.framework.TestCase;
import junit.framework.TestSuite;
import gnu.trove.TDoubleArrayList;
import java.io.IOException;
import java.io.BufferedReader;
import java.io.StringReader;
import cc.mallet.grmm.types.*;
import cc.mallet.grmm.util.ModelReader;
import cc.mallet.types.MatrixOps;
import cc.mallet.util.Randoms;
/**
* $Id: TestBetaFactor.java,v 1.1 2007/10/22 21:37:41 mccallum Exp $
*/
public class TestBetaFactor extends TestCase {
public TestBetaFactor (String name)
{
super (name);
}
public void testVarSet ()
{
Variable var = new Variable (Variable.CONTINUOUS);
Factor f = new BetaFactor (var, 0.5, 0.5);
assertEquals (1, f.varSet ().size ());
assertTrue (f.varSet().contains (var));
}
public void testValue ()
{
Variable var = new Variable (Variable.CONTINUOUS);
Factor f = new BetaFactor (var, 1.0, 1.2);
Assignment assn = new Assignment (var, 0.7);
assertEquals (0.94321, f.value(assn), 1e-5);
}
public void testSample ()
{
Variable var = new Variable (Variable.CONTINUOUS);
Randoms r = new Randoms (2343);
Factor f = new BetaFactor (var, 0.7, 0.5);
TDoubleArrayList lst = new TDoubleArrayList ();
for (int i = 0; i < 100000; i++) {
Assignment assn = f.sample (r);
lst.add (assn.getDouble (var));
}
double[] vals = lst.toNativeArray ();
double mean = MatrixOps.mean (vals);
assertEquals (0.7 / (0.5 + 0.7), mean, 0.01);
}
public void testSample2 ()
{
Variable var = new Variable (Variable.CONTINUOUS);
Randoms r = new Randoms (2343);
Factor f = new BetaFactor (var, 0.7, 0.5, 3.0, 8.0);
TDoubleArrayList lst = new TDoubleArrayList ();
for (int i = 0; i < 100000; i++) {
Assignment assn = f.sample (r);
lst.add (assn.getDouble (var));
}
double[] vals = lst.toNativeArray ();
double mean = MatrixOps.mean (vals);
assertEquals (5.92, mean, 0.01);
}
static String mdlstr = "VAR u1 u2 : continuous\n" +
"u1 ~ Beta 0.2 0.7\n" +
"u2 ~ Beta 1.0 0.3\n";
public void testSliceInFg () throws IOException
{
ModelReader reader = new ModelReader ();
FactorGraph fg = reader.readModel (new BufferedReader (new StringReader (TestBetaFactor.mdlstr)));
Variable u1 = fg.findVariable ("u1");
Variable u2 = fg.findVariable ("u2");
Assignment assn = new Assignment (new Variable[] { u1, u2 }, new double[] { 0.25, 0.85 });
FactorGraph fg2 = (FactorGraph) fg.slice (assn);
assertEquals (2, fg2.factors ().size ());
assertEquals (0.59261 * 1.13202, fg2.value (new Assignment ()), 1e-5);
}
/**
* @return a <code>TestSuite</code>
*/
public static TestSuite suite ()
{
return new TestSuite (TestBetaFactor.class);
}
public static void main (String[] args)
{
TestSuite theSuite;
if (args.length > 0) {
theSuite = new TestSuite ();
for (int i = 0; i < args.length; i++) {
theSuite.addTest (new TestBetaFactor (args[i]));
}
} else {
theSuite = (TestSuite) TestBetaFactor.suite ();
}
junit.textui.TestRunner.run (theSuite);
}
}