Examples with GraphNode edu.cmu.tetrad.graph.GraphNode used on opensource projects

Example 36 with GraphNode

use of edu.cmu.tetrad.graph.GraphNode in project tetrad by cmu-phil.

the class TestUpdaterJointMarginal method testEstimate1.

@Test
public void testEstimate1() {
    Dag graph = new Dag();
    Node L1 = new GraphNode("L1");
    Node X1 = new GraphNode("X1");
    Node X2 = new GraphNode("X2");
    Node X3 = new GraphNode("X3");
    L1.setNodeType(NodeType.MEASURED);
    X1.setNodeType(NodeType.MEASURED);
    X2.setNodeType(NodeType.MEASURED);
    X3.setNodeType(NodeType.MEASURED);
    graph.addNode(L1);
    graph.addNode(X1);
    graph.addNode(X2);
    graph.addNode(X3);
    graph.addDirectedEdge(L1, X1);
    graph.addDirectedEdge(L1, X2);
    graph.addDirectedEdge(L1, X3);
    BayesPm bayesPm = new BayesPm(graph);
    bayesPm.setNumCategories(L1, 2);
    bayesPm.setNumCategories(X1, 2);
    bayesPm.setNumCategories(X2, 2);
    bayesPm.setNumCategories(X3, 2);
    BayesIm estimatedIm = new MlBayesIm(bayesPm);
    Node l1Node = graph.getNode("L1");
    // int l1Index = bayesImMixed.getNodeIndex(l1Node);
    int l1Index = estimatedIm.getNodeIndex(l1Node);
    Node x1Node = graph.getNode("X1");
    // int x1Index = bayesImMixed.getNodeIndex(x1Node);
    int x1Index = estimatedIm.getNodeIndex(x1Node);
    Node x2Node = graph.getNode("X2");
    // int x2Index = bayesImMixed.getNodeIndex(x2Node);
    int x2Index = estimatedIm.getNodeIndex(x2Node);
    Node x3Node = graph.getNode("X3");
    // int x3Index = bayesImMixed.getNodeIndex(x3Node);
    int x3Index = estimatedIm.getNodeIndex(x3Node);
    // bayesImMixed.setProbability(l1Index, 0, 0, 0.5);
    // bayesImMixed.setProbability(l1Index, 0, 1, 0.5);
    estimatedIm.setProbability(l1Index, 0, 0, 0.5);
    estimatedIm.setProbability(l1Index, 0, 1, 0.5);
    // bayesImMixed.setProbability(x1Index, 0, 0, 0.33333);
    // bayesImMixed.setProbability(x1Index, 0, 1, 0.66667);
    estimatedIm.setProbability(x1Index, 0, 0, // p(x1 = 0 | l1 = 0)
    0.33333);
    estimatedIm.setProbability(x1Index, 0, 1, // p(x1 = 1 | l1 = 0)
    0.66667);
    estimatedIm.setProbability(x1Index, 1, 0, // p(x1 = 0 | l1 = 1)
    0.66667);
    estimatedIm.setProbability(x1Index, 1, 1, // p(x1 = 1 | l1 = 1)
    0.33333);
    // bayesImMixed.setProbability(x2Index, 1, 0, 0.66667);
    // bayesImMixed.setProbability(x2Index, 1, 1, 0.33333);
    estimatedIm.setProbability(x2Index, 1, 0, // p(x2 = 0 | l1 = 1)
    0.66667);
    estimatedIm.setProbability(x2Index, 1, 1, // p(x2 = 1 | l1 = 1)
    0.33333);
    estimatedIm.setProbability(x2Index, 0, 0, // p(x2 = 0 | l1 = 0)
    0.33333);
    estimatedIm.setProbability(x2Index, 0, 1, // p(x2 = 1 | l1 = 0)
    0.66667);
    // bayesImMixed.setProbability(x3Index, 1, 0, 0.66667);
    // bayesImMixed.setProbability(x3Index, 1, 1, 0.33333);
    estimatedIm.setProbability(x3Index, 1, 0, // p(x3 = 0 | l1 = 1)
    0.66667);
    estimatedIm.setProbability(x3Index, 1, 1, // p(x3 = 1 | l1 = 1)
    0.33333);
    estimatedIm.setProbability(x3Index, 0, 0, // p(x3 = 0 | l1 = 0)
    0.33333);
    estimatedIm.setProbability(x3Index, 0, 1, // p(x3 = 1 | l1 = 0)
    0.66667);
    Evidence evidence = Evidence.tautology(estimatedIm);
    evidence.getProposition().setCategory(x1Index, 0);
    evidence.getProposition().setCategory(x2Index, 0);
    evidence.getProposition().setCategory(x3Index, 0);
    RowSummingExactUpdater rseu = new RowSummingExactUpdater(estimatedIm);
    rseu.setEvidence(evidence);
    int[] vars1 = { l1Index };
    int[] vals1 = { 0 };
    double p1 = rseu.getJointMarginal(vars1, vals1);
    assertEquals(0.1111, p1, 0.0001);
    int[] vars2 = { l1Index, x1Index };
    int[] vals2 = { 0, 0 };
    double p2 = rseu.getJointMarginal(vars2, vals2);
    assertEquals(0.1111, p2, 0.0001);
    int[] vals3 = { 1, 0 };
    double p3 = rseu.getJointMarginal(vars2, vals3);
    assertEquals(0.8888, p3, 0.0001);
}

Example 37 with GraphNode

use of edu.cmu.tetrad.graph.GraphNode in project tetrad by cmu-phil.

the class TestModelGenerator method testGenerate.

@Test
public void testGenerate() {
    Node x1 = new GraphNode("x1");
    Node x2 = new GraphNode("x2");
    Node x3 = new GraphNode("x3");
    Node x4 = new GraphNode("x4");
    Node x5 = new GraphNode("x5");
    // graph = new EdgeListGraph();
    Graph graph = new EdgeListGraph();
    graph.clear();
    // Add and remove some nodes.
    graph.addNode(x1);
    graph.addNode(x2);
    graph.addNode(x3);
    graph.addNode(x4);
    graph.addNode(x5);
    graph.addDirectedEdge(x1, x2);
    graph.addDirectedEdge(x2, x3);
    graph.addDirectedEdge(x3, x4);
    List<Graph> variants1 = ModelGenerator.generate(graph);
    assertEquals(17, variants1.size());
}

Example 38 with GraphNode

use of edu.cmu.tetrad.graph.GraphNode in project tetrad by cmu-phil.

the class TestIndependenceFact method testSimpleCase.

@Test
public void testSimpleCase() {
    Node x = new GraphNode("X");
    Node y = new GraphNode("Y");
    Node w = new GraphNode("W");
    IndependenceFact fact1 = new IndependenceFact(x, y);
    IndependenceFact fact2 = new IndependenceFact(y, x);
    assertEquals(fact1, fact2);
    IndependenceFact fact3 = new IndependenceFact(x, w);
    assertNotEquals(fact1, fact3);
    List<IndependenceFact> facts = new ArrayList<>();
    facts.add(fact1);
    assertTrue(facts.contains(fact2));
}

Example 39 with GraphNode

use of edu.cmu.tetrad.graph.GraphNode in project tetrad by cmu-phil.

the class TestSemProposition method constructGraph1.

private Graph constructGraph1() {
    Graph graph = new EdgeListGraph();
    Node x1 = new GraphNode("X1");
    Node x2 = new GraphNode("X2");
    Node x3 = new GraphNode("X3");
    Node x4 = new GraphNode("X4");
    Node x5 = new GraphNode("X5");
    graph.addNode(x1);
    graph.addNode(x2);
    graph.addNode(x3);
    graph.addNode(x4);
    graph.addNode(x5);
    graph.addDirectedEdge(x1, x2);
    graph.addDirectedEdge(x2, x3);
    graph.addDirectedEdge(x3, x4);
    graph.addDirectedEdge(x1, x4);
    graph.addDirectedEdge(x4, x5);
    return graph;
}

Example 40 with GraphNode

use of edu.cmu.tetrad.graph.GraphNode in project tetrad by cmu-phil.

the class TestCptInvariantUpdater method testUpdate5.

@Test
public void testUpdate5() {
    Node x0Node = new GraphNode("X0");
    Node x1Node = new GraphNode("X1");
    Node x2Node = new GraphNode("X2");
    Node x3Node = new GraphNode("X3");
    Node x4Node = new GraphNode("X4");
    Dag graph = new Dag();
    graph.addNode(x0Node);
    graph.addNode(x1Node);
    graph.addNode(x2Node);
    graph.addNode(x3Node);
    graph.addNode(x4Node);
    graph.addDirectedEdge(x0Node, x1Node);
    graph.addDirectedEdge(x0Node, x2Node);
    graph.addDirectedEdge(x1Node, x3Node);
    graph.addDirectedEdge(x2Node, x3Node);
    graph.addDirectedEdge(x4Node, x0Node);
    graph.addDirectedEdge(x4Node, x2Node);
    BayesPm bayesPm = new BayesPm(graph);
    MlBayesIm bayesIm = new MlBayesIm(bayesPm, MlBayesIm.RANDOM);
    int x1 = bayesIm.getNodeIndex(x1Node);
    int x2 = bayesIm.getNodeIndex(x2Node);
    int x3 = bayesIm.getNodeIndex(x3Node);
    Evidence evidence = Evidence.tautology(bayesIm);
    evidence.getProposition().setCategory(x1, 1);
    evidence.getProposition().setCategory(x2, 0);
    evidence.getNodeIndex("X1");
    BayesUpdater updater1 = new CptInvariantUpdater(bayesIm);
    updater1.setEvidence(evidence);
    BayesUpdater updater2 = new RowSummingExactUpdater(bayesIm);
    updater2.setEvidence(evidence);
    double marginal1 = updater1.getMarginal(x3, 0);
    double marginal2 = updater2.getMarginal(x3, 0);
    assertEquals(marginal1, marginal2, 0.000001);
}