Package org.integratedmodelling.riskwiz.jtree

Examples of org.integratedmodelling.riskwiz.jtree.JTInference.initialize()

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            JTInference inference = new JTInference();

            // JTCompilerDebugger deb = new JTCompilerDebugger();
            // deb.doAll();
            // //   
            inference.initialize(network, new JoinTreeCompiler());
            inference.run();
    
            Set<BNNode> nodes = network.vertexSet();

            for (BNNode node : nodes) {
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        JTInference inference = new JTInference();

        try {
            inference.initialize(bn, new JoinTreeCompiler());
        } catch (Exception e) {
            // TODO Auto-generated catch block
            e.printStackTrace();
        }
        inference.run();
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            JTInference inference = new JTInference();

            // JTCompilerDebugger deb = new JTCompilerDebugger();
            // deb.doAll();
     
            inference.initialize(network, new JoinTreeCompiler());
            inference.run();
      
            Set<BNNode> nodes = network.vertexSet();

            for (BNNode node : nodes) {
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            JTInference inference = new JTInference();

            // JTCompilerDebugger deb = new JTCompilerDebugger();
            // deb.doAll();

            inference.initialize(network, new JoinTreeCompiler());
            inference.run();

            Set<BNNode> nodes = network.vertexSet();

            for (BNNode node : nodes) {
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            BeliefNetwork bn = r.load(new FileInputStream("examples/water.xdsl"));
            // BeliefNetwork bn =rb.load(new FileInputStream("examples/sprinkler.xml"));

            JTInference inference = new JTInference();

            inference.initialize(bn, new JoinTreeCompiler());
            // inference.setObservation("Cloudy", "true");
            inference.run();
       
            for (BNNode n : bn.vertexSet()) {
                System.out.println(n.getName() + ": " + n.getMarginal());
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            }
   
            // run inference
            JTInference inference = new JTInference();

            inference.initialize(network, new JoinTreeCompiler());
            inference.run();

            // output inference results
            System.out.println("Marginals of original network\n");
            for (BNNode node : nodes) {
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            // finally, learn!
            learner.learnFromTable(graphData);
     
            inference = new JTInference();
            inference.initialize(network, new JoinTreeCompiler());
            inference.run();
            // now, show the probabilities again
            // nodes = network.vertexSet();
            System.out.println("CPTs after learning\n");
            nodes = network.vertexSet();
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            }
   
            // run inference
            JTInference inference = new JTInference();

            inference.initialize(network, new JoinTreeCompiler());
            inference.run();

            // output inference results
            System.out.println("Marginals of original network\n");
            for (BNNode node : nodes) {
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            // finally, learn!
            learner.learnFromTable(graphData);
     
            inference = new JTInference();
            inference.initialize(network, new JoinTreeCompiler());
            inference.run();
            // now, show the probabilities again
            // nodes = network.vertexSet();
            System.out.println("CPTs after learning\n");
            nodes = network.vertexSet();
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            JTInference inference = new JTInference();
            JTCompilerDebugger deb = new JTCompilerDebugger();

            deb.doAll();
     
            inference.initialize(network, new JoinTreeCompiler(), deb);
            inference.run();

            // output inference results

            Set<BNNode> nodes = network.vertexSet();
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