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package org.ufcspa.simdecs.diagram.bn;

import java.io.File;
import java.util.ArrayList;
import java.util.Vector;

import unbbayes.io.xmlbif.version6.*;
import unbbayes.prs.Node;
import unbbayes.prs.bn.JunctionTreeAlgorithm;
import unbbayes.prs.bn.ProbabilisticNetwork;
import unbbayes.prs.bn.ProbabilisticNode;

import unbbayes.simdecs.PerguntaNodo;

/**
 *
 * @author mchelem
 */
public class BayesianNetwork {
            
    public static ProbabilisticNetwork loadNetwork(String filename) throws Exception {
        ProbabilisticNetwork bayesianNetwork = new ProbabilisticNetwork(null);
        XMLBIFIO.loadXML(new File(filename),bayesianNetwork);        
        return bayesianNetwork;
    } 
    
    /* Testing */
    public static void main(String[] args) throws Exception {
        ProbabilisticNetwork bn = BayesianNetwork.loadNetwork("samples/headache.xml");
        
        // Get bayesian network name
        System.out.println("Network name: "+ bn.getName());
        
        // Get all the nodes
        System.out.println("All nodes: ");
        ArrayList<Node> nodes = bn.getNodes();
        for (Node node: nodes){
            System.out.println("-> " + node.getName());            
        }
        
        // Get node by name and its children
        // To work with probabilistic table, node must be a Probabilistic node
        ProbabilisticNode facialPainNode = (ProbabilisticNode)bn.getNode("facial_pain");
        System.out.println("\nNode: " + facialPainNode.getName());
        
        for (int i = 0; i < facialPainNode.getStatesSize(); i++) {
             System.out.println(facialPainNode.getStateAt(i)+":"+facialPainNode.getMarginalAt(i));
        }
        
        // Fields custo, tempo and pergunta moved to database. 
        // Included here for testing.
	System.out.println("Custo: " + facialPainNode.getCustoEtapa());
	System.out.println("Tempo: " + facialPainNode.getTempoEtapa());
	   
        Vector<PerguntaNodo> perguntas = facialPainNode.getPerguntas();
        for (PerguntaNodo pergunta: perguntas) {
            // Setting questions because it is not set in the saved net
            pergunta.setPergunta("Minha pergunta?");
            System.out.println("Pergunta: " + pergunta.getPergunta());	
	 }
                
        ArrayList<Node> childrenNodes = facialPainNode.getChildren();
        System.out.println("Children:");
        for (Node node: childrenNodes){
            System.out.println("-> " + node.getName());            
        }
        
        // Updating nodes
        // Before updating probabilities, it is required to run the network
        System.out.println("Running Bayesian network:");

        JunctionTreeAlgorithm jt = new JunctionTreeAlgorithm();
        jt.setNet(bn);	    
        jt.run();
        
        ProbabilisticNode holocranialPainNode = (ProbabilisticNode) bn.getNode("holocranial_pain");
        System.out.println("\nNode: " + holocranialPainNode.getName());

        System.out.println("Before updating probability table:");
        for (int i = 0; i < holocranialPainNode.getStatesSize(); i++) {
             System.out.println(holocranialPainNode.getStateAt(i)+":"+holocranialPainNode.getMarginalAt(i));
        }
                
        float likelihood[] = new float[holocranialPainNode.getStatesSize()]; 
        likelihood[0] = 1.0f;
        likelihood[1] = 0.0f;
        holocranialPainNode.addLikeliHood(likelihood);
        
        bn.updateEvidences();
        
        System.out.println("After updating probability table:");        
        for (int i = 0; i < holocranialPainNode.getStatesSize(); i++) {
             System.out.println(holocranialPainNode.getStateAt(i)+":"+holocranialPainNode.getMarginalAt(i));
        }
    }
    
    
}