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using System;
using Smile;
// Tutorial6 creates a dynamic Bayesian network (DBN),
// performs the inference, then saves the model to disk.
namespace SmileNetTutorial
{
class Tutorial6
{
public static void Run()
{
Console.WriteLine("Starting Tutorial6...");
Network net = new Network();
int loc = CreateCptNode(
net, "Location", "Location",
new String[] { "Pittsburgh", "Sahara" },
160, 360);
int rain = CreateCptNode(
net, "Rain", "Rain",
new String[] { "true", "false" },
380, 240);
int umb = CreateCptNode(
net, "Umbrella", "Umbrella",
new String[] { "true", "false" },
300, 100);
net.SetNodeTemporalType(rain, Network.NodeTemporalType.Plate);
net.SetNodeTemporalType(umb, Network.NodeTemporalType.Plate);
net.AddArc(loc, rain);
net.AddTemporalArc(rain, rain, 1);
net.AddArc(rain, umb);
double[] rainDef = new double[]
{
0.7, // P(Rain=true |Location=Pittsburgh)
0.3, // P(Rain=false|Location=Pittsburgh)
0.01, // P(Rain=true |Location=Sahara)
0.99 // P(Rain=false|Location=Sahara)
};
net.SetNodeDefinition(rain, rainDef);
double[] rainDefTemporal = new double[]
{
0.7, // P(Rain=true |Location=Pittsburgh,Rain[t-1]=true)
0.3, // P(Rain=false|Location=Pittsburgh,Rain[t-1]=true)
0.3, // P(Rain=true |Location=Pittsburgh,Rain[t-1]=false)
0.7, // P(Rain=false|Location=Pittsburgh,Rain[t-1]=false)
0.001, // P(Rain=true |Location=Sahara,Rain[t-1]=true)
0.999, // P(Rain=false|Location=Sahara,Rain[t-1]=true)
0.01, // P(Rain=true |Location=Sahara,Rain[t-1]=false)
0.99 // P(Rain=false|Location=Sahara,Rain[t-1]=false)
};
net.SetNodeTemporalDefinition(rain, 1, rainDefTemporal);
double[] umbDef = new double[]
{
0.9, // P(Umbrella=true |Rain=true)
0.1, // P(Umbrella=false|Rain=true)
0.2, // P(Umbrella=true |Rain=false)
0.8 // P(Umbrella=false|Rain=false)
};
net.SetNodeDefinition(umb, umbDef);
net.SetSliceCount(5);
Console.WriteLine("Performing update without evidence.");
UpdateAndShowTemporalResults(net);
Console.WriteLine(
"Setting Umbrella[t=1] to true and Umbrella[t=3] to false.");
net.SetTemporalEvidence(umb, 1, 0);
net.SetTemporalEvidence(umb, 3, 1);
UpdateAndShowTemporalResults(net);
net.WriteFile("tutorial6.xdsl");
Console.WriteLine(
"Tutorial6 complete: Network written to tutorial6.xdsl");
}
private static void UpdateAndShowTemporalResults(Network net)
{
net.UpdateBeliefs();
int sliceCount = net.GetSliceCount();
for (int h = net.GetFirstNode(); h >= 0; h = net.GetNextNode(h))
{
if (net.GetNodeTemporalType(h) ==
Network.NodeTemporalType.Plate)
{
int outcomeCount = net.GetOutcomeCount(h);
Console.WriteLine(
"Temporal beliefs for {0}:", net.GetNodeId(h));
double[] v = net.GetNodeValue(h);
for (int sliceIdx = 0; sliceIdx < sliceCount; sliceIdx++)
{
Console.Write("\tt={0}:", sliceIdx);
for (int i = 0; i < outcomeCount; i++)
{
Console.Write(
" {0}", v[sliceIdx * outcomeCount + i]);
}
Console.WriteLine();
}
}
}
Console.WriteLine();
}
private static int CreateCptNode(
Network net, String id, String name,
String[] outcomes, int xPos, int yPos)
{
int handle = net.AddNode(Network.NodeType.Cpt, id);
net.SetNodeName(handle, name);
net.SetNodePosition(handle, xPos, yPos, 85, 55);
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;
}
}
}