/* Copyright (C) 2003 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.inference;


import java.io.IOException;
import java.io.ObjectInputStream;
import java.io.ObjectOutputStream;

import cc.mallet.grmm.types.*;

/**
 * Approximate inferencer for graphical models using sampling.
 *  A general inference engine that takes any Sampler engine, and performs
 *  approximate inference using its samples.
 * Created: Mar 28, 2005
 *
 * @author <A HREF="mailto:casutton@cs.umass.edu>casutton@cs.umass.edu</A>
 * @version $Id: SamplingInferencer.java,v 1.1 2007/10/22 21:37:49 mccallum Exp $
 */
public class SamplingInferencer extends AbstractInferencer {

  private int N;

  private Sampler sampler;

  // Could save only sufficient statistics to save on memory
  transient Assignment samples;

  public SamplingInferencer (Sampler sampler, int n)
  {
    this.sampler = sampler;
    N = n;
  }

  public void computeMarginals (FactorGraph mdl)
  {
    samples = sampler.sample (mdl, N);
  }

  public Factor lookupMarginal (Variable var)
  {
    return lookupMarginal (new HashVarSet (new Variable[] { var }));
  }

  // don't try this for large cliques
  public Factor lookupMarginal (VarSet varSet)
  {
    Factor mrgl = samples.marginalize (varSet);
    AbstractTableFactor tbl = mrgl.asTable ();
    tbl.normalize ();
    return tbl;
  }
  
  // Serialization garbage

  private static final long serialVersionUID = 1;
  private static final int CURRENT_SERIAL_VERSION = 1;

  private void writeObject (ObjectOutputStream out) throws IOException
  {
    out.writeInt (CURRENT_SERIAL_VERSION);
    out.writeInt (N);
    out.writeObject (sampler);
  }


  private void readObject (ObjectInputStream in) throws IOException, ClassNotFoundException
  {
    in.readInt ();  // read version
    N = in.readInt ();
    sampler = (Sampler) in.readObject ();
  }

  public String toString ()
  {
    return "(SamplingInferencer: "+sampler+" )";
  }
}