Java Tutorial Code 2: Performing Inference with a Bayesian Network

From DSL

public void InfereceWithBayesianNetwork() {
 try {
   Network net = new Network();
   net.readFile("tutorial_a.xdsl"); 
   
       
   // ---- We want to compute P("Forecast" = Moderate) ----
   // Updating the network:
   net.updateBeliefs();
   
   // Getting the handle of the node "Forecast":
   net.getNode("Forecast");
   
   // Getting the index of the "Moderate" outcome:
   String[] aForecastOutcomeIds = net.getOutcomeIds("Forecast");
   int outcomeIndex;
   for (outcomeIndex = 0; outcomeIndex < aForecastOutcomeIds.length; outcomeIndex++)
     if ("Moderate".equals(aForecastOutcomeIds[outcomeIndex]))
       break;
   
   // Getting the value of the probability:
   double[] aValues = net.getNodeValue("Forecast");
   double P_ForecastIsModerate = aValues[outcomeIndex];
   
   System.out.println("P(\"Forecast\" = Moderate) = "      + P_ForecastIsModerate);
   
   
   // ---- We want to compute P("Success" = Failure | "Forecast" = Good) ----
   // Introducing the evidence in node "Forecast":
   net.setEvidence("Forecast", "Good");
   
   // Updating the network:
   net.updateBeliefs();
   
   // Getting the handle of the node "Success":
   net.getNode("Success");
   
   // Getting the index of the "Failure" outcome:
   String[] aSuccessOutcomeIds = net.getOutcomeIds("Success");
   for (outcomeIndex = 0; outcomeIndex < aSuccessOutcomeIds.length; outcomeIndex++)
     if ("Failure".equals(aSuccessOutcomeIds[outcomeIndex]))
       break;
   
   // Getting the value of the probability:
   aValues = net.getNodeValue("Success");
   double P_SuccIsFailGivenForeIsGood = aValues[outcomeIndex];
   
   System.out.println("P(\"Success\" = Failure | \"Forecast\" = Good) = " + P_SuccIsFailGivenForeIsGood);
   
   // ---- We want to compute P("Success" = Success | "Forecast" = Poor) ----
   // Clearing the evidence in node "Forecast":
   net.clearEvidence("Forecast");
   
   // Introducing the evidence in node "Forecast":
   net.setEvidence("Forecast", "Good");
   
   // Updating the network:
   net.updateBeliefs();
   
   // Getting the index of the "Failure" outcome:
   aSuccessOutcomeIds = net.getOutcomeIds("Success");
   for (outcomeIndex = 0; outcomeIndex < aSuccessOutcomeIds.length; outcomeIndex++)
     if ("Failure".equals(aSuccessOutcomeIds[outcomeIndex]))
       break;
   
   // Getting the value of the probability:
   aValues = net.getNodeValue("Success");
   double P_SuccIsSuccGivenForeIsPoor = aValues[outcomeIndex];
   
   System.out.println("P(\"Success\" = Success | \"Forecast\" = Poor) = " + P_SuccIsSuccGivenForeIsPoor);
 }
 catch (SMILEException e) {
   System.out.println(e.getMessage());
 }
}