/* 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.types;
import cc.mallet.util.Maths;
import cc.mallet.util.Randoms;
/**
* Univariate Gaussian factor.
* $Id: UniNormalFactor.java,v 1.1 2007/10/22 21:37:44 mccallum Exp $
*/
public class UniNormalFactor extends AbstractFactor {
private Variable var;
private double mean;
private double variance;
public UniNormalFactor (Variable var, double mean, double variance)
{
super (new HashVarSet (new Variable[] { var }));
if (!var.isContinuous ()) throw new IllegalArgumentException ();
if (variance <= 0) throw new IllegalArgumentException ();
this.var = var;
this.mean = mean;
this.variance = variance;
}
//
protected Factor extractMaxInternal (VarSet varSet)
{
throw new UnsupportedOperationException ();
}
public double value (Assignment assn)
{
double x = assn.getDouble (var);
return 1/Math.sqrt(2*Math.PI*variance) * Math.exp (-1/(2.0 * variance) * (x - mean)*(x-mean));
}
protected double lookupValueInternal (int i)
{
throw new UnsupportedOperationException ();
}
protected Factor marginalizeInternal (VarSet varsToKeep)
{
if (varsToKeep.contains (var)) {
return duplicate ();
} else {
return new ConstantFactor (1.0);
}
}
public Factor normalize ()
{
return this;
}
public Assignment sample (Randoms r)
{
double val = r.nextGaussian (mean, variance);
return new Assignment (var, val);
}
public boolean almostEquals (Factor p, double epsilon)
{
return equals (p);
}
public Factor duplicate ()
{
return new UniNormalFactor (var, mean, variance);
}
public boolean isNaN ()
{
return Double.isNaN (mean) || Double.isNaN (variance);
}
public String dumpToString ()
{
return toString ();
}
public String toString ()
{
return "[NormalFactor "+var+" "+mean+" ... " +variance+" ]";
}
public Factor slice (Assignment assn)
{
if (assn.containsVar (var)) {
return new ConstantFactor (value (assn));
} else return duplicate ();
}
public void multiplyBy (Factor f)
{
if (f instanceof ConstantFactor) {
double val = f.value (new Assignment());
// NormalFactor must be normalized right now...
if (Maths.almostEquals (val, 1.0)) {
return; // ok, it's an identity factor
}
}
throw new UnsupportedOperationException ("Can't multiply NormalFactor by "+f);
}
public void divideBy (Factor f)
{
if (f instanceof ConstantFactor) {
double val = f.value (new Assignment());
// NormalFactor must be normalized right now...
if (Maths.almostEquals (val, 1.0)) {
return; // ok, it's an identity factor
}
}
throw new UnsupportedOperationException ("Can't divide NormalFactor by "+f);
}
}