gt: 						if (bAdjacencyMatrix[iNode][iNode3]) {
context: /*
   *   This program is free software: you can redistribute it and/or modify
   *   it under the terms of the GNU General Public License as published by
   *   the Free Software Foundation, either version 3 of the License, or
   *   (at your option) any later version.
   *
   *   This program is distributed in the hope that it will be useful,
   *   but WITHOUT ANY WARRANTY; without even the implied warranty of
   *   MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
   *   GNU General Public License for more details.
   *
   *   You should have received a copy of the GNU General Public License
   *   along with this program.  If not, see <http://www.gnu.org/licenses/>.
   */
  
  /*
   *    MarginCalculator.java
   *    Copyright (C) 2007-2012 University of Waikato, Hamilton, New Zealand
   *
   */
  
  package weka.classifiers.bayes.net;
  
  import weka.classifiers.bayes.BayesNet;
  import weka.core.RevisionHandler;
  import weka.core.RevisionUtils;
  
  import java.io.Serializable;
  import java.util.HashSet;
  import java.util.Iterator;
  import java.util.Set;
  import java.util.Vector;
  
  
  public class MarginCalculator implements Serializable, RevisionHandler {
  	  /** for serialization */
  	  private static final long serialVersionUID = 650278019241175534L;
  
  	  boolean m_debug = false;
  	  public JunctionTreeNode m_root = null;
  	JunctionTreeNode [] jtNodes;
  
  	public int getNode(String sNodeName) {
      	int iNode = 0;
      	while (iNode < m_root.m_bayesNet.m_Instances.numAttributes()) {
      		if (m_root.m_bayesNet.m_Instances.attribute(iNode).name().equals(sNodeName)) {
      			return iNode;
      		}
  	    	iNode++; 
      	}
      	//throw new Exception("Could not find node [[" + sNodeName + "]]");
      	return -1;
  	}
  	public String toXMLBIF03() {return m_root.m_bayesNet.toXMLBIF03();}
  	
  	/**
  	 * Calc marginal distributions of nodes in Bayesian network
  	 *	 Note that a connected network is assumed. 
  	 *	 Unconnected networks may give unexpected results.
  	 * @param bayesNet
  	 */
  	public void calcMargins(BayesNet bayesNet) throws Exception {
  		//System.out.println(bayesNet.toString());
  		boolean[][] bAdjacencyMatrix = moralize(bayesNet);
  		process(bAdjacencyMatrix, bayesNet);
  	} // calcMargins
  
  	public void calcFullMargins(BayesNet bayesNet) throws Exception {
  		//System.out.println(bayesNet.toString());
  		int nNodes = bayesNet.getNrOfNodes();
  		boolean[][] bAdjacencyMatrix = new boolean[nNodes][nNodes];
  		for (int iNode = 0; iNode < nNodes; iNode++) {
  			for (int iNode2 = 0; iNode2 < nNodes; iNode2++) {
  				bAdjacencyMatrix[iNode][iNode2] = true;
  			}
  		}
  		process(bAdjacencyMatrix, bayesNet);
  	} // calcMargins
  	
  	
  	public void process(boolean[][] bAdjacencyMatrix, BayesNet bayesNet) throws Exception {
  		int[] order = getMaxCardOrder(bAdjacencyMatrix);
  		bAdjacencyMatrix = fillIn(order, bAdjacencyMatrix);
  		order = getMaxCardOrder(bAdjacencyMatrix);
  		Set [] cliques = getCliques(order, bAdjacencyMatrix);
  		Set [] separators = getSeparators(order, cliques);
  		int [] parentCliques = getCliqueTree(order, cliques, separators);
  		// report cliques
  		int nNodes = bAdjacencyMatrix.length;
  		if (m_debug) {
  		for (int i = 0; i < nNodes; i++) {
  			int iNode = order[i];
  			if (cliques[iNode] != null) {
  				System.out.print("Clique " + iNode + " (");
  				Iterator nodes = cliques[iNode].iterator();
  				while (nodes.hasNext()) {
  					int iNode2 = (Integer) nodes.next();
  					System.out.print(iNode2 + " " + bayesNet.getNodeName(iNode2));
  					if (nodes.hasNext()) {
  						System.out.print(",");
  					}
  				}
  				System.out.print(") S(");
  				nodes = separators[iNode].iterator();
  				while (nodes.hasNext()) {
  					int iNode2 = (Integer) nodes.next();
  					System.out.print(iNode2 + " " + bayesNet.getNodeName(iNode2));
  					if (nodes.hasNext()) {
  						System.out.print(",");
  					}
  				}
  				System.out.println(") parent clique " + parentCliques[iNode]);
  			}		
  		}
  		}
  				
  		jtNodes = getJunctionTree(cliques, separators, parentCliques, order, bayesNet);
  		m_root = null;
  		for (int iNode = 0; iNode < nNodes; iNode++) {
  			if (parentCliques[iNode] < 0 && jtNodes[iNode] != null) {
  				m_root = jtNodes[iNode];
  				break;
  			}
  		}
  		m_Margins = new double[nNodes][];
  		initialize(jtNodes, order, cliques, separators, parentCliques);
  		
  		// sanity check
  		for (int i = 0; i < nNodes; i++) {
  			int iNode = order[i];
  			if (cliques[iNode] != null) {
  				if (parentCliques[iNode] == -1 && separators[iNode].size() > 0) {
  					throw new Exception("Something wrong in clique tree");
  				}
  			}
  		}
  		if (m_debug) {
  			//System.out.println(m_root.toString());
  		}
  	} // process
  		
  	void initialize(JunctionTreeNode [] jtNodes, int [] order, Set [] cliques, Set [] separators, int [] parentCliques) {
  		int nNodes = order.length;
  		for (int i = nNodes - 1; i >= 0; i--) {
  			int iNode = order[i];
  			if (jtNodes[iNode]!=null) {
  				jtNodes[iNode].initializeUp();
  			}
  		}	
  		for (int i = 0; i < nNodes; i++) {
  			int iNode = order[i];
  			if (jtNodes[iNode]!=null) {
  				jtNodes[iNode].initializeDown(false);
  			}
  		}	
  	} // initialize
  	
  	JunctionTreeNode [] getJunctionTree(Set [] cliques, Set [] separators, int [] parentCliques, int [] order, BayesNet bayesNet) {
  		int nNodes = order.length;
  		JunctionTreeNode root = null;
  		JunctionTreeNode [] jtns = new JunctionTreeNode[nNodes]; 
  		boolean [] bDone = new boolean[nNodes];
  		// create junction tree nodes
  		for (int i = 0; i < nNodes; i++) {
  			int iNode = order[i];
  			if (cliques[iNode] != null) {
  				jtns[iNode] = new JunctionTreeNode(cliques[iNode], bayesNet, bDone);
  			}
  		}
  		// create junction tree separators
  		for (int i = 0; i < nNodes; i++) {
  			int iNode = order[i];
  			if (cliques[iNode] != null) {
  				JunctionTreeNode parent = null;
  				if (parentCliques[iNode] > 0) {
  					parent = jtns[parentCliques[iNode]];
  					JunctionTreeSeparator jts = new JunctionTreeSeparator(separators[iNode], bayesNet, jtns[iNode], parent);
  					jtns[iNode].setParentSeparator(jts);
  					jtns[parentCliques[iNode]].addChildClique(jtns[iNode]);
  				} else {
  					root = jtns[iNode];	
  				}
  			}
  		}
  		return jtns;
  	} // getJunctionTree
  	
  	public class JunctionTreeSeparator implements Serializable, RevisionHandler {
  	  
  		  private static final long serialVersionUID = 6502780192411755343L;
  		int [] m_nNodes;
  		int m_nCardinality;
  		double [] m_fiParent;
  		double [] m_fiChild;
  		JunctionTreeNode m_parentNode;
  		JunctionTreeNode m_childNode;
  		BayesNet m_bayesNet;
  		
  		JunctionTreeSeparator(Set separator, BayesNet bayesNet, JunctionTreeNode childNode, JunctionTreeNode parentNode) {
  			//////////////////////
  			// initialize node set
  			m_nNodes = new int[separator.size()];
  			int iPos = 0;
  			m_nCardinality = 1;
  			for(Iterator nodes = separator.iterator(); nodes.hasNext();) {
  				int iNode = (Integer) nodes.next();
  				m_nNodes[iPos++] = iNode;
  				m_nCardinality *= bayesNet.getCardinality(iNode);
  			}
  			m_parentNode = parentNode;
  			m_childNode = childNode;
  			m_bayesNet = bayesNet;
  		} // c'tor
  		
  		/** marginalize junciontTreeNode node over all nodes outside the separator set
  		 * of the parent clique
  		 *
  		 */
  		public void updateFromParent() {
  			double [] fis = update(m_parentNode); 
  			if (fis == null) {
  				m_fiParent = null;
  			} else {
  				m_fiParent = fis;
  				// normalize
  				double sum = 0;
  				for (int iPos = 0; iPos < m_nCardinality; iPos++) {
  					sum += m_fiParent[iPos];
  				}
  				for (int iPos = 0; iPos < m_nCardinality; iPos++) {
  					m_fiParent[iPos] /= sum;
  				}
  			}
  		} // updateFromParent
  
  		/** marginalize junciontTreeNode node over all nodes outside the separator set
  		 * of the child clique
  		 *
  		 */
  		public void updateFromChild() {
  			double [] fis = update(m_childNode); 
  			if (fis == null) {
  				m_fiChild = null;
  			} else {
  				m_fiChild = fis;
  				// normalize
  				double sum = 0;
  				for (int iPos = 0; iPos < m_nCardinality; iPos++) {
  					sum += m_fiChild[iPos];
  				}
  				for (int iPos = 0; iPos < m_nCardinality; iPos++) {
  					m_fiChild[iPos] /= sum;
  				}
  			}
  		} // updateFromChild
  		
  		/** marginalize junciontTreeNode node over all nodes outside the separator set
  		 * 
  		 * @param node one of the neighboring junciont tree nodes of this separator
  		 */
  		public double [] update(JunctionTreeNode node) {
  			if (node.m_P == null) {
  				return null;
  			}
  			double [] fi = new double[m_nCardinality];
  
  			int [] values = new int[node.m_nNodes.length];
  			int [] order = new int[m_bayesNet.getNrOfNodes()];
  			for (int iNode = 0; iNode < node.m_nNodes.length; iNode++) {
  				order[node.m_nNodes[iNode]] = iNode;
  			}
  			// fill in the values
  			for (int iPos = 0; iPos < node.m_nCardinality; iPos++) {
  				int iNodeCPT = getCPT(node.m_nNodes, node.m_nNodes.length, values, order, m_bayesNet);
  				int iSepCPT =  getCPT(m_nNodes, m_nNodes.length, values, order, m_bayesNet);
  				fi[iSepCPT] += node.m_P[iNodeCPT];
  				// update values
  				int i = 0;
  				values[i]++;
  				while (i < node.m_nNodes.length && values[i] == m_bayesNet.getCardinality(node.m_nNodes[i])) {
  					values[i] = 0;
  					i++;
  					if (i < node.m_nNodes.length) {
  						values[i]++;
  					}
  				}
  			}
  			return fi;
  		} // update
  		  
  		/**
  		 * Returns the revision string.
  		 * 
  		 * @return		the revision
  		 */
  		public String getRevision() {
  		  return RevisionUtils.extract("$Revision: 8064 $");
  		}
  
  	} // class JunctionTreeSeparator
  
  	public class JunctionTreeNode implements Serializable, RevisionHandler {
  	  
  		  private static final long serialVersionUID = 650278019241175536L;
  		/** reference Bayes net for information about variables like name, cardinality, etc.
  		 * but not for relations between nodes **/
  		BayesNet m_bayesNet;
  		/** nodes of the Bayes net in this junction node **/
  		public int [] m_nNodes;
  		/** cardinality of the instances of variables in this junction node **/
  		int m_nCardinality;
  		/** potentials for first network **/
  		double [] m_fi;
  
  		/** distribution over this junction node according to first Bayes network **/
  		double [] m_P;
  
  
  		double [][] m_MarginalP;		
  
  		
  		JunctionTreeSeparator m_parentSeparator;
  		public void setParentSeparator(JunctionTreeSeparator parentSeparator) {m_parentSeparator = parentSeparator;}
  		public Vector m_children;
  		public void addChildClique(JunctionTreeNode child) {m_children.add(child);}
  
  		public void initializeUp() {
  			m_P = new double[m_nCardinality];
  			for (int iPos = 0; iPos < m_nCardinality; iPos++) {
  				m_P[iPos] = m_fi[iPos];
  			}
  			int [] values = new int[m_nNodes.length];
  			int [] order = new int[m_bayesNet.getNrOfNodes()];
  			for (int iNode = 0; iNode < m_nNodes.length; iNode++) {
  				order[m_nNodes[iNode]] = iNode;
  			}
  			for (Iterator child = m_children.iterator(); child.hasNext(); ) {
  				JunctionTreeNode childNode = (JunctionTreeNode) child.next();
  				JunctionTreeSeparator separator = childNode.m_parentSeparator;
  			// Update the values
  			for (int iPos = 0; iPos < m_nCardinality; iPos++) {
  				int iSepCPT = getCPT(separator.m_nNodes, separator.m_nNodes.length, values, order, m_bayesNet);
  				int iNodeCPT =  getCPT(m_nNodes, m_nNodes.length, values, order, m_bayesNet);
  					m_P[iNodeCPT] *= separator.m_fiChild[iSepCPT];					
  				// update values
  				int i = 0;
  				values[i]++;
  				while (i < m_nNodes.length && values[i] == m_bayesNet.getCardinality(m_nNodes[i])) {
  					values[i] = 0;
  					i++;
  					if (i < m_nNodes.length) {
  						values[i]++;
  					}
  				}
  			}
  			}
  			// normalize
  			double sum = 0;
  			for (int iPos = 0; iPos < m_nCardinality; iPos++) {
  				sum += m_P[iPos];
  			}
  			for (int iPos = 0; iPos < m_nCardinality; iPos++) {
  				m_P[iPos] /= sum;
  			}
  
  			if (m_parentSeparator != null) { // not a root node
  				m_parentSeparator.updateFromChild();
  			}
  		} // initializeUp
  
  		public void initializeDown(boolean recursively) {
  			if (m_parentSeparator == null) { // a root node
  				calcMarginalProbabilities();
  			} else {
  			m_parentSeparator.updateFromParent();
  				int [] values = new int[m_nNodes.length];
  				int [] order = new int[m_bayesNet.getNrOfNodes()];
  				for (int iNode = 0; iNode < m_nNodes.length; iNode++) {
  					order[m_nNodes[iNode]] = iNode;
  				}
  
  				
  				// Update the values
  				for (int iPos = 0; iPos < m_nCardinality; iPos++) {
  					int iSepCPT = getCPT(m_parentSeparator.m_nNodes, m_parentSeparator.m_nNodes.length, values, order, m_bayesNet);
  					int iNodeCPT =  getCPT(m_nNodes, m_nNodes.length, values, order, m_bayesNet);
  					if ( m_parentSeparator.m_fiChild[iSepCPT] > 0) {
  						m_P[iNodeCPT] *= m_parentSeparator.m_fiParent[iSepCPT] / m_parentSeparator.m_fiChild[iSepCPT];
  					} else {
  						m_P[iNodeCPT] = 0;
  					}
  					// update values
  					int i = 0;
  					values[i]++;
  					while (i < m_nNodes.length && values[i] == m_bayesNet.getCardinality(m_nNodes[i])) {
  						values[i] = 0;
  						i++;
  						if (i < m_nNodes.length) {
  							values[i]++;
  						}
  					}
  				}
  				// normalize
  				double sum = 0;
  				for (int iPos = 0; iPos < m_nCardinality; iPos++) {
  					sum += m_P[iPos];
  				}
  				for (int iPos = 0; iPos < m_nCardinality; iPos++) {
  					m_P[iPos] /= sum;
  				}
  				m_parentSeparator.updateFromChild();
  				calcMarginalProbabilities();
  			}
  			if (recursively) {
  				for (Iterator child = m_children.iterator(); child.hasNext(); ) {
  					JunctionTreeNode childNode = (JunctionTreeNode) child.next();
  					childNode.initializeDown(true);
  				}			
  			}
  		} // initializeDown
  		
  		
  		/** calculate marginal probabilities for the individual nodes in the clique.
  		 * Store results in m_MarginalP 
  		 */
  		void calcMarginalProbabilities() {			
  			// calculate marginal probabilities
  			int [] values = new int[m_nNodes.length];
  			int [] order = new int[m_bayesNet.getNrOfNodes()];
  			m_MarginalP = new double[m_nNodes.length][];
  			for (int iNode = 0; iNode < m_nNodes.length; iNode++) {
  				order[m_nNodes[iNode]] = iNode;
  				m_MarginalP[iNode]=new double[m_bayesNet.getCardinality(m_nNodes[iNode])];
  			}
  			for (int iPos = 0; iPos < m_nCardinality; iPos++) {
  				int iNodeCPT =  getCPT(m_nNodes, m_nNodes.length, values, order, m_bayesNet);
  				for (int iNode = 0; iNode < m_nNodes.length; iNode++) {
  					m_MarginalP[iNode][values[iNode]] += m_P[iNodeCPT];
  				}
  				// update values
  				int i = 0;
  				values[i]++;
  				while (i < m_nNodes.length && values[i] == m_bayesNet.getCardinality(m_nNodes[i])) {
  					values[i] = 0;
  					i++;
  					if (i < m_nNodes.length) {
  						values[i]++;
  					}
  				}
  			}
  			
  			for (int iNode = 0; iNode < m_nNodes.length; iNode++) {
  				m_Margins[m_nNodes[iNode]] = m_MarginalP[iNode]; 
  			}
  		} // calcMarginalProbabilities
  		
  		public String toString() {
  			StringBuffer buf = new StringBuffer();
  			for (int iNode = 0; iNode < m_nNodes.length; iNode++) {
  				buf.append(m_bayesNet.getNodeName(m_nNodes[iNode]) + ": ");
  				for (int iValue = 0; iValue < m_MarginalP[iNode].length; iValue++) {
  					buf.append(m_MarginalP[iNode][iValue] + " ");
  				}
  				buf.append('\n');
  			}
  			for (Iterator child = m_children.iterator(); child.hasNext(); ) {
  				JunctionTreeNode childNode = (JunctionTreeNode) child.next();
  				buf.append("----------------\n");
  				buf.append(childNode.toString());
  			}			
  			return buf.toString();
  		} // toString
  		
  		void calculatePotentials(BayesNet bayesNet, Set clique, boolean [] bDone) {
  			m_fi = new double[m_nCardinality];
  			
  			int [] values = new int[m_nNodes.length];
  			int [] order = new int[bayesNet.getNrOfNodes()];
  			for (int iNode = 0; iNode < m_nNodes.length; iNode++) {
  				order[m_nNodes[iNode]] = iNode;
  			}
  			// find conditional probabilities that need to be taken in account
  			boolean [] bIsContained = new boolean[m_nNodes.length];
  			for (int iNode = 0; iNode < m_nNodes.length; iNode++) {
  				int nNode = m_nNodes[iNode];
  				bIsContained[iNode] = !bDone[nNode];
  				for (int iParent = 0; iParent < bayesNet.getNrOfParents(nNode); iParent++) {
  					int nParent = bayesNet.getParent(nNode, iParent);
  					if (!clique.contains(nParent)) {
  						bIsContained[iNode] = false;
  					}
  				}
  				if (bIsContained[iNode]) {
  					bDone[nNode] = true;
  					if (m_debug) {
  						System.out.println("adding node " +nNode);
  					}
  				}
  			}			
  
  			// fill in the values
  			for (int iPos = 0; iPos < m_nCardinality; iPos++) {
  				int iCPT = getCPT(m_nNodes, m_nNodes.length, values, order, bayesNet);
  				m_fi[iCPT] = 1.0;
  				for (int iNode = 0; iNode < m_nNodes.length; iNode++) {
  					if (bIsContained[iNode]) {
  						int nNode = m_nNodes[iNode];
  						int [] nNodes = bayesNet.getParentSet(nNode).getParents();
  						int iCPT2 = getCPT(nNodes, bayesNet.getNrOfParents(nNode), values, order, bayesNet);
  						double f = bayesNet.getDistributions()[nNode][iCPT2].getProbability(values[iNode]);
  						m_fi[iCPT] *= f;
  					}
  				}
  				
  				// update values
  				int i = 0;
  				values[i]++;
  				while (i < m_nNodes.length && values[i] == bayesNet.getCardinality(m_nNodes[i])) {
  					values[i] = 0;
  					i++;
  					if (i < m_nNodes.length) {
  						values[i]++;
  					}
  				}
  			}
  		} // calculatePotentials
  
  		JunctionTreeNode(Set clique, BayesNet bayesNet, boolean [] bDone) {
  			m_bayesNet = bayesNet;
  			m_children = new Vector();
  			//////////////////////
  			// initialize node set
  			m_nNodes = new int[clique.size()];
  			int iPos = 0;
  			m_nCardinality = 1;
  			for(Iterator nodes = clique.iterator(); nodes.hasNext();) {
  				int iNode = (Integer) nodes.next();
  				m_nNodes[iPos++] = iNode;
  				m_nCardinality *= bayesNet.getCardinality(iNode);
  			}
  			////////////////////////////////
  			// initialize potential function
  			calculatePotentials(bayesNet, clique, bDone);
         } // JunctionTreeNode c'tor
  
  		/* check whether this junciton tree node contains node nNode
  		 * 
  		 */
  		boolean contains(int nNode) {
  			for (int iNode = 0; iNode < m_nNodes.length; iNode++) {
  				if (m_nNodes[iNode]== nNode){
  					return true;
  				}
  			}
  			return false;
  		} // contains
  		
  		public void setEvidence(int nNode, int iValue) throws Exception {
  			int [] values = new int[m_nNodes.length];
  			int [] order = new int[m_bayesNet.getNrOfNodes()];
  
  			int nNodeIdx = -1;
  			for (int iNode = 0; iNode < m_nNodes.length; iNode++) {
  				order[m_nNodes[iNode]] = iNode;
  				if (m_nNodes[iNode] == nNode) {
  					nNodeIdx = iNode;
  				}
  			}
  			if (nNodeIdx < 0) {
  				throw new Exception("setEvidence: Node " + nNode + " not found in this clique");
  			}
  			for (int iPos = 0; iPos < m_nCardinality; iPos++) {
  				if (values[nNodeIdx] != iValue) {
  					int iNodeCPT =  getCPT(m_nNodes, m_nNodes.length, values, order, m_bayesNet);
  					m_P[iNodeCPT] = 0;
  				}
  				// update values
  				int i = 0;
  				values[i]++;
  				while (i < m_nNodes.length && values[i] == m_bayesNet.getCardinality(m_nNodes[i])) {
  					values[i] = 0;
  					i++;
  					if (i < m_nNodes.length) {
  						values[i]++;
  					}
  				}
  			}		
  			// normalize
  			double sum = 0;
  			for (int iPos = 0; iPos < m_nCardinality; iPos++) {
  				sum += m_P[iPos];
  			}
  			for (int iPos = 0; iPos < m_nCardinality; iPos++) {
  				m_P[iPos] /= sum;
  			}
  			calcMarginalProbabilities();
  			updateEvidence(this);
  		} // setEvidence
  
  		void updateEvidence(JunctionTreeNode source) {
  			if (source != this) {
  				int [] values = new int[m_nNodes.length];
  				int [] order = new int[m_bayesNet.getNrOfNodes()];
  				for (int iNode = 0; iNode < m_nNodes.length; iNode++) {
  					order[m_nNodes[iNode]] = iNode;
  				}
  				int [] nChildNodes = source.m_parentSeparator.m_nNodes;
  				int nNumChildNodes = nChildNodes.length; 
  				for (int iPos = 0; iPos < m_nCardinality; iPos++) {
  					int iNodeCPT =  getCPT(m_nNodes, m_nNodes.length, values, order, m_bayesNet);
  					int iChildCPT =  getCPT(nChildNodes, nNumChildNodes, values, order, m_bayesNet);
  					if (source.m_parentSeparator.m_fiParent[iChildCPT] != 0) {
  						m_P[iNodeCPT] *= source.m_parentSeparator.m_fiChild[iChildCPT]/source.m_parentSeparator.m_fiParent[iChildCPT];
  					} else {
  						m_P[iNodeCPT] = 0;
  					}
  					// update values
  					int i = 0;
  					values[i]++;
  					while (i < m_nNodes.length && values[i] == m_bayesNet.getCardinality(m_nNodes[i])) {
  						values[i] = 0;
  						i++;
  						if (i < m_nNodes.length) {
  							values[i]++;
  						}
  					}
  				}		
  				// normalize
  				double sum = 0;
  				for (int iPos = 0; iPos < m_nCardinality; iPos++) {
  					sum += m_P[iPos];
  				}
  				for (int iPos = 0; iPos < m_nCardinality; iPos++) {
  					m_P[iPos] /= sum;
  				}
  				calcMarginalProbabilities();
  			}
  			for (Iterator child = m_children.iterator(); child.hasNext(); ) {
  				JunctionTreeNode childNode = (JunctionTreeNode) child.next();
  				if (childNode != source) {
  					childNode.initializeDown(true);
  				}
  			}			
  			if (m_parentSeparator != null) {
  				m_parentSeparator.updateFromChild();
  				m_parentSeparator.m_parentNode.updateEvidence(this);
  				m_parentSeparator.updateFromParent();
  			}
  		} // updateEvidence
  
  		/**
  		 * Returns the revision string.
  		 * 
  		 * @return		the revision
  		 */
  		public String getRevision() {
  		  return RevisionUtils.extract("$Revision: 8064 $");
  		}
  		
  	} // class JunctionTreeNode
  
  	int getCPT(int [] nodeSet, int nNodes, int[] values, int[] order, BayesNet bayesNet) {
  		int iCPTnew = 0;
  		for (int iNode = 0; iNode < nNodes; iNode++) {
  			int nNode = nodeSet[iNode];
  			iCPTnew = iCPTnew * bayesNet.getCardinality(nNode);
  			iCPTnew += values[order[nNode]];
  		}
  		return iCPTnew;
  	} // getCPT
  
  	int [] getCliqueTree(int [] order, Set [] cliques, Set [] separators) {
  		int nNodes = order.length;
  		int [] parentCliques = new int[nNodes];
  		//for (int i = nNodes - 1; i >= 0; i--) {
  		for (int i = 0; i < nNodes; i++) {
  			int iNode = order[i];
  			parentCliques[iNode] = -1;
  			if (cliques[iNode] != null && separators[iNode].size() > 0) {
  				//for (int j = nNodes - 1; j > i; j--) {
  				for (int j = 0; j < nNodes; j++) {
  					int iNode2 = order[j];
  					if (iNode!= iNode2 && cliques[iNode2] != null && cliques[iNode2].containsAll(separators[iNode])) {
  						parentCliques[iNode] = iNode2;
  						j = i;
  						j = 0;
  						j = nNodes;
  					}
  				}
  				
  			}
  		}
  		return parentCliques;
  	} // getCliqueTree
  	
  	/** calculate separator sets in clique tree
  	 * 
  	 * @param order: maximum cardinality ordering of the graph
  	 * @param cliques: set of cliques
  	 * @return set of separator sets
  	 */
  	Set [] getSeparators(int [] order, Set [] cliques) {
  		int nNodes = order.length;
  		Set [] separators = new HashSet[nNodes];
  		Set processedNodes = new HashSet(); 
  		//for (int i = nNodes - 1; i >= 0; i--) {
  		for (int i = 0; i < nNodes; i++) {
  			int iNode = order[i];
  			if (cliques[iNode] != null) {
  				Set separator = new HashSet();
  				separator.addAll(cliques[iNode]);
  				separator.retainAll(processedNodes);
  				separators[iNode] = separator;
  				processedNodes.addAll(cliques[iNode]);
  			}
  		}
  		return separators;
  	} // getSeparators
  	
  	/**
  	 * get cliques in a decomposable graph represented by an adjacency matrix
  	 * 
  	 * @param order: maximum cardinality ordering of the graph
  	 * @param bAdjacencyMatrix: decomposable graph
  	 * @return set of cliques
  	 */
  	Set [] getCliques(int[] order, boolean[][] bAdjacencyMatrix) throws Exception {
  		int nNodes = bAdjacencyMatrix.length;
  		Set [] cliques = new HashSet[nNodes];
  		//int[] inverseOrder = new int[nNodes];
  		//for (int iNode = 0; iNode < nNodes; iNode++) {
  			//inverseOrder[order[iNode]] = iNode;
  		//}
  		// consult nodes in reverse order
  		for (int i = nNodes - 1; i >= 0; i--) {
  			int iNode = order[i];
  			if (iNode == 22) {
  				int h = 3;
  				h ++;
  			}
  			Set clique = new HashSet();
  			clique.add(iNode);
  			for (int j = 0; j < i; j++) {
  				int iNode2 = order[j];
  				if (bAdjacencyMatrix[iNode][iNode2]) {
  					clique.add(iNode2);
  				}
  			}
  			
  			//for (int iNode2 = 0; iNode2 < nNodes; iNode2++) {
  				//if (bAdjacencyMatrix[iNode][iNode2] && inverseOrder[iNode2] < inverseOrder[iNode]) {
  					//clique.add(iNode2);
  				//}
  			//}
  			cliques[iNode] = clique;
  		}
  		for (int iNode = 0; iNode < nNodes; iNode++) {
  			for (int iNode2 = 0; iNode2 < nNodes; iNode2++) {
  				if (iNode != iNode2 && cliques[iNode]!= null && cliques[iNode2]!= null && cliques[iNode].containsAll(cliques[iNode2])) {
  					cliques[iNode2] = null;
  				}
  			}
  		}		
  		// sanity check
  		if (m_debug) {
  		int [] nNodeSet = new int[nNodes];
  		for (int iNode = 0; iNode < nNodes; iNode++) {
  			if (cliques[iNode] != null) {
  				Iterator it = cliques[iNode].iterator();
  				int k = 0;
  				while (it.hasNext()) {
  					nNodeSet[k++] = (Integer) it.next();
  				}
  				for (int i = 0; i < cliques[iNode].size(); i++) {
  					for (int j = 0; j < cliques[iNode].size(); j++) {
  						if (i!=j && !bAdjacencyMatrix[nNodeSet[i]][nNodeSet[j]]) {
  							throw new Exception("Non clique" + i + " " + j);
  						}
  					}
  				}
  			}
  		}
  		}
  		return cliques;
  	} // getCliques
  
  	/**
  	 * moralize DAG and calculate
  	 * adjacency matrix representation for a Bayes Network, effecively
  	 * converting the directed acyclic graph to an undirected graph.
  	 * 
  	 * @param bayesNet
  	 *            Bayes Network to process
  	 * @return adjacencies in boolean matrix format
  	 */
  	public boolean[][] moralize(BayesNet bayesNet) {
  		int nNodes = bayesNet.getNrOfNodes();
  		boolean[][] bAdjacencyMatrix = new boolean[nNodes][nNodes];
  		for (int iNode = 0; iNode < nNodes; iNode++) {
  			ParentSet parents = bayesNet.getParentSets()[iNode];
  			moralizeNode(parents, iNode, bAdjacencyMatrix);
  		}
  		return bAdjacencyMatrix;
  	} // moralize
  
  	private void moralizeNode(ParentSet parents, int iNode, boolean[][] bAdjacencyMatrix) {
  		for (int iParent = 0; iParent < parents.getNrOfParents(); iParent++) {
  			int nParent = parents.getParent(iParent);
  			if ( m_debug && !bAdjacencyMatrix[iNode][nParent])
  				System.out.println("Insert " + iNode + "--" + nParent);
  			bAdjacencyMatrix[iNode][nParent] = true;
  			bAdjacencyMatrix[nParent][iNode] = true;
  			for (int iParent2 = iParent + 1; iParent2 < parents.getNrOfParents(); iParent2++) {
  				int nParent2 = parents.getParent(iParent2);
  				if (m_debug && !bAdjacencyMatrix[nParent2][nParent])
  					System.out.println("Mary " + nParent + "--" + nParent2);
  				bAdjacencyMatrix[nParent2][nParent] = true;
  				bAdjacencyMatrix[nParent][nParent2] = true;
  			}
  		}	
  	} // moralizeNode
  	
  	/**
  	 * Apply Tarjan and Yannakakis (1984) fill in algorithm for graph
  	 * triangulation. In reverse order, insert edges between any non-adjacent
  	 * neighbors that are lower numbered in the ordering.
  	 * 
  	 * Side effect: input matrix is used as output
  	 * 
  	 * @param order
  	 *            node ordering
  	 * @param bAdjacencyMatrix
  	 *            boolean matrix representing the graph
  	 * @return boolean matrix representing the graph with fill ins
  	 */
  	public boolean[][] fillIn(int[] order, boolean[][] bAdjacencyMatrix) {
  		int nNodes = bAdjacencyMatrix.length;
  		int[] inverseOrder = new int[nNodes];
  		for (int iNode = 0; iNode < nNodes; iNode++) {
  			inverseOrder[order[iNode]] = iNode;
  		}
  		// consult nodes in reverse order
  		for (int i = nNodes - 1; i >= 0; i--) {
  			int iNode = order[i];
  			// find pairs of neighbors with lower order
  			for (int j = 0; j < i; j++) {
  				int iNode2 = order[j];
  				if (bAdjacencyMatrix[iNode][iNode2]) {
  					for (int k = j+1; k < i; k++) {
  						int iNode3 = order[k];
  