Examples with SemPm edu.cmu.tetrad.sem.SemPm used on opensource projects

Example 26 with SemPm

use of edu.cmu.tetrad.sem.SemPm in project tetrad by cmu-phil.

the class TestPurify method test1.

@Test
public void test1() {
    RandomUtil.getInstance().setSeed(48290483L);
    SemGraph graph = new SemGraph();
    Node l1 = new GraphNode("L1");
    l1.setNodeType(NodeType.LATENT);
    Node l2 = new GraphNode("L2");
    l2.setNodeType(NodeType.LATENT);
    Node l3 = new GraphNode("L3");
    l3.setNodeType(NodeType.LATENT);
    Node x1 = new GraphNode("X1");
    Node x2 = new GraphNode("X2");
    Node x3 = new GraphNode("X3");
    Node x4 = new GraphNode("X4");
    Node x4b = new GraphNode("X4b");
    Node x5 = new GraphNode("X5");
    Node x6 = new GraphNode("X6");
    Node x7 = new GraphNode("X7");
    Node x8 = new GraphNode("X8");
    Node x8b = new GraphNode("X8b");
    Node x9 = new GraphNode("X9");
    Node x10 = new GraphNode("X10");
    Node x11 = new GraphNode("X11");
    Node x12 = new GraphNode("X12");
    Node x12b = new GraphNode("X12b");
    graph.addNode(l1);
    graph.addNode(l2);
    graph.addNode(l3);
    graph.addNode(x1);
    graph.addNode(x2);
    graph.addNode(x3);
    graph.addNode(x4);
    graph.addNode(x4b);
    graph.addNode(x5);
    graph.addNode(x6);
    graph.addNode(x7);
    graph.addNode(x8);
    graph.addNode(x8b);
    graph.addNode(x9);
    graph.addNode(x10);
    graph.addNode(x11);
    graph.addNode(x12);
    graph.addNode(x12b);
    graph.addDirectedEdge(l1, x1);
    graph.addDirectedEdge(l1, x2);
    graph.addDirectedEdge(l1, x3);
    graph.addDirectedEdge(l1, x4);
    graph.addDirectedEdge(l1, x4b);
    graph.addDirectedEdge(l1, x5);
    graph.addDirectedEdge(l2, x5);
    graph.addDirectedEdge(l2, x6);
    graph.addDirectedEdge(l2, x7);
    graph.addDirectedEdge(l2, x8);
    graph.addDirectedEdge(l2, x8b);
    graph.addDirectedEdge(l3, x9);
    graph.addDirectedEdge(l3, x10);
    graph.addDirectedEdge(l3, x11);
    graph.addDirectedEdge(l3, x12);
    graph.addDirectedEdge(l3, x12b);
    graph.addDirectedEdge(x1, x4);
    SemPm pm = new SemPm(graph);
    SemIm im = new SemIm(pm);
    DataSet data = im.simulateData(1000, false);
    List<List<Node>> partition = new ArrayList<>();
    List<Node> cluster1 = new ArrayList<>();
    cluster1.add(x1);
    cluster1.add(x2);
    cluster1.add(x3);
    cluster1.add(x4);
    cluster1.add(x4b);
    cluster1.add(x5);
    List<Node> cluster2 = new ArrayList<>();
    cluster2.add(x5);
    cluster2.add(x6);
    cluster2.add(x7);
    cluster2.add(x8);
    cluster2.add(x8b);
    List<Node> cluster3 = new ArrayList<>();
    cluster3.add(x9);
    cluster3.add(x10);
    cluster3.add(x11);
    cluster3.add(x12);
    cluster3.add(x12b);
    partition.add(cluster1);
    partition.add(cluster2);
    partition.add(cluster3);
    TetradTest test = new ContinuousTetradTest(data, TestType.TETRAD_WISHART, 0.05);
    IPurify purify = new PurifyTetradBased2(test);
    purify.setTrueGraph(graph);
    List<List<Node>> partition2 = purify.purify(partition);
    assertEquals(3, partition2.get(0).size());
    assertEquals(2, partition2.get(1).size());
    assertEquals(5, partition2.get(2).size());
}

Example 27 with SemPm

use of edu.cmu.tetrad.sem.SemPm in project tetrad by cmu-phil.

the class TestRicf method test2.

@Test
public void test2() {
    List<Node> nodes = new ArrayList<>();
    for (int i = 0; i < 10; i++) {
        nodes.add(new ContinuousVariable("X" + (i + 1)));
    }
    Graph graph = new Dag(GraphUtils.randomGraph(nodes, 0, 10, 30, 15, 15, false));
    SemPm pm = new SemPm(graph);
    SemIm im = new SemIm(pm);
    DataSet data = im.simulateData(1000, false);
    CovarianceMatrix cov = new CovarianceMatrix(data);
    Ricf.RicfResult result = new Ricf().ricf(new SemGraph(graph), cov, 0.001);
    result.getBhat();
}

Example 28 with SemPm

use of edu.cmu.tetrad.sem.SemPm in project tetrad by cmu-phil.

the class TestRicf method test4.

@Test
public void test4() {
    List<Node> nodes1 = new ArrayList<>();
    for (int i1 = 0; i1 < 5; i1++) {
        nodes1.add(new ContinuousVariable("X" + (i1 + 1)));
    }
    Graph g1 = GraphUtils.randomGraph(nodes1, 0, 5, 0, 0, 0, false);
    List<Node> nodes = new ArrayList<>();
    for (int i = 0; i < 5; i++) {
        nodes.add(new ContinuousVariable("X" + (i + 1)));
    }
    Graph g2 = GraphUtils.randomGraph(nodes, 0, 5, 0, 0, 0, false);
    SemPm pm = new SemPm(g1);
    SemIm im = new SemIm(pm);
    DataSet dataset = im.simulateData(1000, false);
    ICovarianceMatrix cov = new CovarianceMatrix(dataset);
    new Ricf().ricf(new SemGraph(g1), cov, 0.001);
    new Ricf().ricf(new SemGraph(g2), cov, 0.001);
}

Example 29 with SemPm

use of edu.cmu.tetrad.sem.SemPm in project tetrad by cmu-phil.

the class TestIndTestWaldLR method testIsIndependent.

@Test
public void testIsIndependent() {
    RandomUtil.getInstance().setSeed(1450705713157L);
    int numPassed = 0;
    for (int i = 0; i < 10; i++) {
        List<Node> nodes = new ArrayList<>();
        for (int i1 = 0; i1 < 10; i1++) {
            nodes.add(new ContinuousVariable("X" + (i1 + 1)));
        }
        Graph graph = GraphUtils.randomGraph(nodes, 0, 10, 3, 3, 3, false);
        SemPm pm = new SemPm(graph);
        SemIm im = new SemIm(pm);
        DataSet data = im.simulateData(1000, false);
        Discretizer discretizer = new Discretizer(data);
        discretizer.setVariablesCopied(true);
        discretizer.equalCounts(data.getVariable(0), 2);
        discretizer.equalCounts(data.getVariable(3), 2);
        data = discretizer.discretize();
        Node x1 = data.getVariable("X1");
        Node x2 = data.getVariable("X2");
        Node x3 = data.getVariable("X3");
        Node x4 = data.getVariable("X4");
        Node x5 = data.getVariable("X5");
        List<Node> cond = new ArrayList<>();
        cond.add(x3);
        cond.add(x4);
        cond.add(x5);
        Node x1Graph = graph.getNode(x1.getName());
        Node x2Graph = graph.getNode(x2.getName());
        List<Node> condGraph = new ArrayList<>();
        for (Node node : cond) {
            condGraph.add(graph.getNode(node.getName()));
        }
        // Using the Wald LR test since it's most up to date.
        IndependenceTest test = new IndTestMultinomialLogisticRegressionWald(data, 0.05, false);
        IndTestDSep dsep = new IndTestDSep(graph);
        boolean correct = test.isIndependent(x2, x1, cond) == dsep.isIndependent(x2Graph, x1Graph, condGraph);
        if (correct) {
            numPassed++;
        }
    }
    // System.out.println(RandomUtil.getInstance().getSeed());
    // Do not always get all 10.
    assertEquals(10, numPassed);
}

Example 30 with SemPm

use of edu.cmu.tetrad.sem.SemPm in project tetrad by cmu-phil.

the class TestLingamPattern method test1.

@Test
public void test1() {
    RandomUtil.getInstance().setSeed(4938492L);
    int sampleSize = 1000;
    List<Node> nodes = new ArrayList<>();
    for (int i = 0; i < 6; i++) {
        nodes.add(new ContinuousVariable("X" + (i + 1)));
    }
    Graph graph = new Dag(GraphUtils.randomGraph(nodes, 0, 6, 4, 4, 4, false));
    List<Distribution> variableDistributions = new ArrayList<>();
    variableDistributions.add(new Normal(0, 1));
    variableDistributions.add(new Normal(0, 1));
    variableDistributions.add(new Normal(0, 1));
    variableDistributions.add(new Uniform(-1, 1));
    variableDistributions.add(new Normal(0, 1));
    variableDistributions.add(new Normal(0, 1));
    SemPm semPm = new SemPm(graph);
    SemIm semIm = new SemIm(semPm);
    DataSet dataSet = simulateDataNonNormal(semIm, sampleSize, variableDistributions);
    Score score = new SemBicScore(new CovarianceMatrixOnTheFly(dataSet));
    Graph estPattern = new Fges(score).search();
    LingamPattern lingam = new LingamPattern(estPattern, dataSet);
    lingam.search();
    double[] pvals = lingam.getPValues();
    double[] expectedPVals = { 0.18, 0.29, 0.88, 0.00, 0.01, 0.58 };
    for (int i = 0; i < pvals.length; i++) {
        assertEquals(expectedPVals[i], pvals[i], 0.01);
    }
}