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package tutorials;
import smile.*;
// Tutorial4 loads the XDSL file file created by Tutorial1
// and adds decision and utility nodes, which transforms
// a Bayesian Network (BN) into an Influence Diagram (ID).
public class Tutorial4 {
public static void run() {
System.out.println("Starting Tutorial4...");
Network net = new Network();
net.readFile("tutorial1.xdsl");
int s = net.getNode("Success");
int i = createNode(net, Network.NodeType.DECISION,
"Invest", "Investment decision",
new String[]{ "Invest", "DoNotInvest" }, 160, 240);
int g = createNode(net, Network.NodeType.UTILITY,
"Gain", "Financial gain", null, 60, 200);
net.addArc(i, g);
net.addArc(s, g);
double[] gainDefinition = new double[] {
10000, // Utility(Invest=I, Success=S)
-5000, // Utility(Invest=I, Success=F)
500, // Utility(Invest=D, Success=S)
500 // Utility(Invest=D, Success=F)
};
net.setNodeDefinition(g, gainDefinition);
net.writeFile("tutorial4.xdsl");
System.out.println(
"Tutorial4 complete: Influence diagram written to tutorial4.xdsl.");
}
private static int createNode(
Network net, int nodeType, String id, String name,
String[] outcomes, int xPos, int yPos) {
int handle = net.addNode(nodeType, id);
net.setNodeName(handle, name);
net.setNodePosition(handle, xPos, yPos, 85, 55);
if (outcomes != null) {
int initialOutcomeCount = net.getOutcomeCount(handle);
for (int i = 0; i < initialOutcomeCount; i ++) {
net.setOutcomeId(handle, i, outcomes[i]);
}
for (int i = initialOutcomeCount; i < outcomes.length; i ++) {
net.addOutcome(handle, outcomes[i]);
}
}
return handle;
}
}