Package org.drools.beliefs.graph

Examples of org.drools.beliefs.graph.GraphNode

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    @Test
    public void testEliminationCandidate1() {
        Graph<BayesVariable> graph = new BayesNetwork();

        GraphNode x0 = addNode(graph);
        GraphNode x1 = addNode(graph);
        GraphNode x2 = addNode(graph);
        GraphNode x3 = addNode(graph);
        GraphNode x4 = addNode(graph);

        connectParentToChildren(x1, x2, x3, x4);

        JunctionTreeBuilder jtBuilder = new JunctionTreeBuilder( graph );
        jtBuilder.moralize();
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    }

    @Test
    public void testEliminationCandidate2() {
        Graph graph = new BayesNetwork();
        GraphNode x0 = addNode(graph);
        GraphNode x1 = addNode(graph);
        GraphNode x2 = addNode(graph);
        GraphNode x3 = addNode(graph);
        GraphNode x4 = addNode(graph);

        connectParentToChildren(x1, x2, x3, x4);
        connectParentToChildren(x3, x4);

        JunctionTreeBuilder jtBuilder = new JunctionTreeBuilder( graph );
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    @Test
    public void testCreateClique() {
        Graph<BayesVariable> graph = new BayesNetwork();

        GraphNode dX0 = addNode(graph);
        GraphNode dX1 = addNode(graph);
        GraphNode dX2 = addNode(graph);
        GraphNode dX3 = addNode(graph);
        GraphNode dX4 = addNode(graph);
        GraphNode dX5 = addNode(graph);

        connectParentToChildren(dX1, dX2, dX3, dX4);

        JunctionTreeBuilder jtBuilder = new JunctionTreeBuilder( graph );
        // do not moralize, as we want to test just the clique creation through elimination of the provided vertices
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    @Test
    public void testPriorityQueueWithMinimalNewEdges() {
        Graph<BayesVariable> graph = new BayesNetwork();

        GraphNode x0 = addNode(graph);
        GraphNode x1 = addNode(graph);
        GraphNode x2 = addNode(graph);
        GraphNode x3 = addNode(graph);
        GraphNode x4 = addNode(graph);

        GraphNode x5 = addNode(graph);
        GraphNode x6 = addNode(graph);
        GraphNode x7 = addNode(graph);
        GraphNode x8 = addNode(graph);

        GraphNode x9 = addNode(graph);
        GraphNode x10 = addNode(graph);
        GraphNode x11 = addNode(graph);
        GraphNode x12 = addNode(graph);

        // 3 new edges
        connectParentToChildren(x2, x1);
        connectParentToChildren(x3, x1);
        connectParentToChildren(x4, x1);
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    @Test
    public void testPriorityQueueWithMaximalCliqueWeight() {
        Graph<BayesVariable> graph = new BayesNetwork();

        GraphNode x0 = addNode(graph);
        GraphNode x1 = addNode(graph);
        GraphNode x2 = addNode(graph);
        GraphNode x3 = addNode(graph);
        GraphNode x4 = addNode(graph);
        GraphNode x5 = addNode(graph);
        GraphNode x6 = addNode(graph);
        GraphNode x7 = addNode(graph);
        GraphNode x8 = addNode(graph);
        GraphNode x9 = addNode(graph);
        GraphNode x10 = addNode(graph);
        GraphNode x11 = addNode(graph);
        GraphNode x12 = addNode(graph);

        connectParentToChildren(x2, x1);
        connectParentToChildren(x3, x1);
        connectParentToChildren(x4, x1);
        x1.setContent(new BayesVariable<String>("x1", x0.getId(), new String[]{"a", "b"}, new double[][]{{0.1, 0.1}}));
        x2.setContent(new BayesVariable<String>("x2", x0.getId(), new String[]{"a", "b"}, new double[][]{{0.1, 0.1}}));
        x3.setContent(new BayesVariable<String>("x3", x0.getId(), new String[]{"a", "b"}, new double[][]{{0.1, 0.1}}));
        x4.setContent(new BayesVariable<String>("x4", x0.getId(), new String[]{"a", "b"}, new double[][]{{0.1, 0.1}}));

        connectParentToChildren(x6, x5);
        connectParentToChildren(x7, x5);
        connectParentToChildren(x8, x5);
        x5.setContent(new BayesVariable<String>("x5", x0.getId(), new String[]{"a", "b", "c"}, new double[][]{{0.1, 0.1, 0.1}}));
        x6.setContent(new BayesVariable<String>("x6", x0.getId(), new String[]{"a", "b", "c"}, new double[][]{{0.1, 0.1, 0.1}}));
        x7.setContent(new BayesVariable<String>("x7", x0.getId(), new String[]{"a", "b", "c"}, new double[][]{{0.1, 0.1, 0.1}}));
        x8.setContent(new BayesVariable<String>("x8", x0.getId(), new String[]{"a", "b", "c"}, new double[][]{{0.1, 0.1, 0.1}}));


        connectParentToChildren(x10, x9);
        connectParentToChildren(x11, x9);
        connectParentToChildren(x12, x9);
        x9.setContent(new BayesVariable<String>("x9", x0.getId(), new String[]{"a"}, new double[][]{{0.1}}));
        x10.setContent(new BayesVariable<String>("x10", x0.getId(), new String[]{"a"}, new double[][]{{0.1}}));
        x11.setContent(new BayesVariable<String>("x11", x0.getId(), new String[]{"a", "b"}, new double[][]{{0.1, 0.1}}));
        x12.setContent(new BayesVariable<String>("x12", x0.getId(), new String[]{"a", "b"}, new double[][]{{0.1, 0.1}}));

        JunctionTreeBuilder jtBuilder = new JunctionTreeBuilder( graph );
        //jtBuilder.moralize(); // don't moralize, as we want to force a simpler construction for required edges, for the purposes of testing

        PriorityQueue<EliminationCandidate> p = new PriorityQueue<EliminationCandidate>(graph.size());
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    @Test
    public void testIterativeEliminationUsingEdgeAndWeight() {
        Graph<BayesVariable> graph = new BayesNetwork();

        GraphNode x0 = addNode(graph);
        GraphNode x1 = addNode(graph);
        GraphNode x2 = addNode(graph);
        GraphNode x3 = addNode(graph);
        GraphNode x4 = addNode(graph);

        GraphNode x5 = addNode(graph);
        GraphNode x6 = addNode(graph);

        //          *
        //        / | \
        //       *  | *
        //       |  | |
        //       *  | *
        //        \  /
        //         *

        connectParentToChildren(x1, x2);
        connectParentToChildren(x1, x3);
        connectParentToChildren(x1, x6);

        connectParentToChildren(x2, x4);
        connectParentToChildren(x3, x5);

        connectParentToChildren(x4, x6);
        connectParentToChildren(x5, x6);

        // need to ensure x5 followed by x4 are removed first
        x1.setContent(new BayesVariable<String>("x1", x0.getId(), new String[]{"a", "b", "c", "d", "e", "f"}, new double[][]{{0.1, 0.1, 0.1, 0.1, 0.1, 0.1}}));
        x2.setContent(new BayesVariable<String>("x2", x0.getId(), new String[]{"a", "b"}, new double[][]{{0.1, 0.1}}));
        x3.setContent(new BayesVariable<String>("x3", x0.getId(), new String[]{"a", "b"}, new double[][]{{0.1, 0.1}}));
        x4.setContent(new BayesVariable<String>("x4", x0.getId(), new String[]{"a", "b"}, new double[][]{{0.1, 0.1}}));
        x5.setContent(new BayesVariable<String>("x5", x0.getId(), new String[]{"a"}, new double[][]{{0.1 }}));
        x6.setContent(new BayesVariable<String>("x6", x0.getId(), new String[]{"a", "b"}, new double[][]{{0.1, 0.1}}));


        JunctionTreeBuilder jtBuilder = new JunctionTreeBuilder( graph );
        //jtBuilder.moralize(); // don't moralize, as we want to force a simpler construction for vertex elimination order and updates

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    @Test
    public void testTriangulate1() {
        Graph<BayesVariable> graph = new BayesNetwork();

        GraphNode x0 = addNode(graph);
        GraphNode x1 = addNode(graph);
        GraphNode x2 = addNode(graph);
        GraphNode x3 = addNode(graph);
        GraphNode x4 = addNode(graph);

        GraphNode x5 = addNode(graph);
        GraphNode x6 = addNode(graph);

        //          *
        //        / | \
        //       *  | *
        //       |  | |
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    @Test
    public void testTriangulate2() {
        Graph<BayesVariable> graph = new BayesNetwork();

        GraphNode x0 = addNode(graph);
        GraphNode x1 = addNode(graph);
        GraphNode x2 = addNode(graph);
        GraphNode x3 = addNode(graph);
        GraphNode x4 = addNode(graph);

        GraphNode x5 = addNode(graph);
        GraphNode x6 = addNode(graph);

        //            *
        //           /
        //          *
        //        /  \
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    }

    @Test
    public void testSepSetCompareWithDifferentMass() {
        Graph<BayesVariable> graph = new BayesNetwork();
        GraphNode x0 = addNode(graph);
        GraphNode x1 = addNode(graph);
        GraphNode x2 = addNode(graph);
        GraphNode x3 = addNode(graph);
        GraphNode x4 = addNode(graph);
        GraphNode x5 = addNode(graph);
        GraphNode x6 = addNode(graph);


        OpenBitSet OpenBitSet1_1 = bitSet("00001110");
        OpenBitSet OpenBitSet1_2 = bitSet("01101100");
        SeparatorSet s1 = new SeparatorSet( OpenBitSet1_1, 0, OpenBitSet1_2, 0, graph);
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    }

    @Test
    public void testSepSetCompareWithDifferentCost() {
        Graph<BayesVariable> graph = new BayesNetwork();
        GraphNode x0 = addNode(graph);
        GraphNode x1 = addNode(graph);
        GraphNode x2 = addNode(graph);
        GraphNode x3 = addNode(graph);
        GraphNode x4 = addNode(graph);
        GraphNode x5 = addNode(graph);
        GraphNode x6 = addNode(graph);

        x1.setContent(new BayesVariable<String>("x1", x0.getId(), new String[]{"a"}, new double[][]{{0.1 }}));
        x2.setContent(new BayesVariable<String>("x2", x0.getId(), new String[]{"a", "b"}, new double[][]{{0.1, 0.1}}));
        x3.setContent(new BayesVariable<String>("x3", x0.getId(), new String[]{"a", "b"}, new double[][]{{0.1, 0.1}}));
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Related Classes of org.drools.beliefs.graph.GraphNode

  • org.drools.beliefs.bayes.BayesAbsorbtionTest
  • org.drools.beliefs.bayes.BayesInstance
  • org.drools.beliefs.bayes.BayesProjectionTest
  • org.drools.beliefs.bayes.JunctionTreeBuilder
  • org.drools.beliefs.bayes.JunctionTreeBuilderTest
  • org.drools.beliefs.bayes.JunctionTreeTest
  • org.drools.beliefs.bayes.MarginalizerTest
  • org.drools.beliefs.bayes.PassMessageTest
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