Examples of cc.mallet.grmm.types.Factor

cc.mallet.grmm.types.Factor
Interface for multivariate discrete probability distributions. All distributions are assumed to be over 0...k. If you want a distribution over some other discrete set, use the @see getAlphabet and @see setAlphabet members. (I thought about having a single Potential interface, for both continuous and discrete, but then all the method parameters were java.lang.Object, and the lack of type safety was both inefficient and disturbing.) Created: Mon Sep 15 14:04:58 2003 @author Charles Sutton @version $Id: Factor.java,v 1.1 2007/10/22 21:37:44 mccallum Exp $

      Assignment assn = unrolled.getAssignment ();
      for (Iterator it = unrolled.unrolledVarSetIterator (); it.hasNext();) {
        ACRF.UnrolledVarSet clique = (ACRF.UnrolledVarSet) it.next();
        System.out.println("Clique "+clique);
        dumpAssnForClique (assn, clique);
        Factor ptl = unrolled.factorOf (clique);
        System.out.println("Value = "+ptl.value (assn));
        System.out.println(ptl);
      }
    }

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  public static void addAllFactors (FactorGraph mdl, List regions)
  {
    for (Iterator it = regions.iterator (); it.hasNext ();) {
      Region region = (Region) it.next ();
      for (Iterator pIt = mdl.factorsIterator (); pIt.hasNext();) {
        Factor ptl = (Factor) pIt.next ();
        if (region.vars.containsAll (ptl.varSet ())) {
          region.factors.add (ptl);
        }
      }
    }
  }

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    public List computeBaseRegions (FactorGraph mdl)
    {
      List regions = new ArrayList (mdl.factors ().size ());
      for (Iterator it = mdl.factorsIterator (); it.hasNext ();) {
        Factor ptl =  (Factor) it.next ();
        regions.add (new Region (ptl));
      }
      removeSubsumedRegions (regions);
      addAllFactors (mdl, regions);
      return regions;

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  {
    Variable[] vars = new Variable[] { new Variable (3), new Variable (3), new Variable (3) };


    Variable[] vars1 = new Variable[]{ vars[0], vars[1] };
    double[] vals1 = new double[] { 0, 0.2, 0.8, 0, 0.7, 0.3, 0, 0.5, 0.5 };
    Factor tbl1 = new TableFactor (vars1, vals1);


    Variable[] vars2 = new Variable[]{ vars[1], vars[2] };
    double[] vals2 = new double[] { 0.2, 0.2, 0.8, 0.7, 0, 0.7, 0.3, 0, 0.5 };
    Factor tbl2 = new TableFactor (vars2, vals2);


    FactorGraph fg = new FactorGraph ();
    fg.multiplyBy (tbl1);
    fg.multiplyBy (tbl2);
    System.out.println (fg.dumpToString ());

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    if (parent == null) {
      throw new UnsupportedOperationException
              ("No parent cluster in " + jt + " for clique " + varSet);
    }


    Factor cpf = jt.getCPF (parent);
    if (logger.isLoggable (Level.FINER)) {
      logger.finer ("Lookup jt marginal: clique " + varSet + " cluster " + parent);
      logger.finest ("  cpf " + cpf);
    }


    Factor marginal = strategy.extractBelief (cpf, varSet);
    marginal.normalize ();


    return marginal;
  }

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  public Factor lookupMarginal (JunctionTree jt, Variable var)
  {
    if (jt == null) { throw new IllegalStateException ("Call computeMarginals() first."); }


    VarSet parent = jt.findParentCluster (var);
    Factor cpf = jt.getCPF (parent);
    if (logger.isLoggable (Level.FINER)) {
      logger.finer ("Lookup jt marginal: var " + var + " cluster " + parent);
      logger.finest (" cpf " + cpf);
    }


    Factor marginal = strategy.extractBelief (cpf, new HashVarSet (new Variable[] { var }));
    marginal.normalize ();


    return marginal;
  }

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