Examples with DataSet edu.cmu.tetrad.data.DataSet used on opensource projects

Example 26 with DataSet

use of edu.cmu.tetrad.data.DataSet in project tetrad by cmu-phil.

the class TestGeneralizedSem method test16.

@Test
public void test16() {
    RandomUtil.getInstance().setSeed(29999483L);
    try {
        Node x1 = new GraphNode("X1");
        Node x2 = new GraphNode("X2");
        Node x3 = new GraphNode("X3");
        Node x4 = new GraphNode("X4");
        Graph g = new EdgeListGraphSingleConnections();
        g.addNode(x1);
        g.addNode(x2);
        g.addNode(x3);
        g.addNode(x4);
        g.addDirectedEdge(x1, x2);
        g.addDirectedEdge(x2, x3);
        g.addDirectedEdge(x3, x4);
        g.addDirectedEdge(x1, x4);
        GeneralizedSemPm pm = new GeneralizedSemPm(g);
        pm.setNodeExpression(x1, "E_X1");
        pm.setNodeExpression(x2, "a1 * X1 + E_X2");
        pm.setNodeExpression(x3, "a2 * X2 + E_X3");
        pm.setNodeExpression(x4, "a3 * X1 + a4 * X3 ^ 2 + E_X4");
        pm.setNodeExpression(pm.getErrorNode(x1), "N(0, c1)");
        pm.setNodeExpression(pm.getErrorNode(x2), "N(0, c2)");
        pm.setNodeExpression(pm.getErrorNode(x3), "N(0, c3)");
        pm.setNodeExpression(pm.getErrorNode(x4), "N(0, c4)");
        // pm.setParameterExpression("c1", "1");
        // pm.setParameterExpression("c2", "1");
        // pm.setParameterExpression("c3", "1");
        // pm.setParameterExpression("c4", "1");
        GeneralizedSemIm im = new GeneralizedSemIm(pm);
        im.setParameterValue("a1", 1);
        im.setParameterValue("a2", 1);
        im.setParameterValue("a3", 1);
        im.setParameterValue("a4", 1);
        im.setParameterValue("c1", 1);
        im.setParameterValue("c2", 1);
        im.setParameterValue("c3", 1);
        im.setParameterValue("c4", 1);
        print("True model: ");
        print(im);
        DataSet data = im.simulateDataRecursive(1000, false);
        GeneralizedSemIm imInit = new GeneralizedSemIm(pm);
        imInit.setParameterValue("a1", .5);
        imInit.setParameterValue("a2", .5);
        imInit.setParameterValue("a3", .5);
        imInit.setParameterValue("a4", .7);
        imInit.setParameterValue("c1", 2);
        imInit.setParameterValue("c2", 2);
        imInit.setParameterValue("c3", 2);
        imInit.setParameterValue("c4", 2);
        GeneralizedSemEstimator estimator = new GeneralizedSemEstimator();
        GeneralizedSemIm estIm = estimator.estimate(pm, data);
        print("\n\n\nEstimated model: ");
        print(estIm);
        print(estimator.getReport());
        double aSquaredStar = estimator.getaSquaredStar();
        assertEquals(50.38, aSquaredStar, 0.01);
    } catch (ParseException e) {
        e.printStackTrace();
    }
}

Example 27 with DataSet

use of edu.cmu.tetrad.data.DataSet in project tetrad by cmu-phil.

the class TestGeneralizedSem method test8.

@Test
public void test8() {
    RandomUtil.getInstance().setSeed(29999483L);
    Node x = new GraphNode("X");
    Node y = new GraphNode("Y");
    List<Node> nodes = new ArrayList<>();
    nodes.add(x);
    nodes.add(y);
    Graph graph = new EdgeListGraphSingleConnections(nodes);
    graph.addDirectedEdge(x, y);
    SemPm spm = new SemPm(graph);
    SemIm sim = new SemIm(spm);
    sim.setEdgeCoef(x, y, 20);
    sim.setErrVar(x, 1);
    sim.setErrVar(y, 1);
    GeneralizedSemPm pm = new GeneralizedSemPm(spm);
    GeneralizedSemIm im = new GeneralizedSemIm(pm, sim);
    print(im);
    try {
        pm.setParameterEstimationInitializationExpression("b1", "U(10, 30)");
        pm.setParameterEstimationInitializationExpression("T1", "U(.1, 3)");
        pm.setParameterEstimationInitializationExpression("T2", "U(.1, 3)");
    } catch (ParseException e) {
        e.printStackTrace();
    }
    DataSet data = im.simulateDataRecursive(1000, false);
    GeneralizedSemEstimator estimator = new GeneralizedSemEstimator();
    GeneralizedSemIm estIm = estimator.estimate(pm, data);
    print(estIm);
    // System.out.println(estimator.getReport());
    double aSquaredStar = estimator.getaSquaredStar();
    assertEquals(0.69, aSquaredStar, 0.01);
}

Example 28 with DataSet

use of edu.cmu.tetrad.data.DataSet in project tetrad by cmu-phil.

the class TestGeneralizedSem method test2.

@Test
public void test2() {
    RandomUtil.getInstance().setSeed(2999983L);
    int sampleSize = 1000;
    List<Node> variableNodes = new ArrayList<>();
    ContinuousVariable x1 = new ContinuousVariable("X1");
    ContinuousVariable x2 = new ContinuousVariable("X2");
    ContinuousVariable x3 = new ContinuousVariable("X3");
    ContinuousVariable x4 = new ContinuousVariable("X4");
    ContinuousVariable x5 = new ContinuousVariable("X5");
    variableNodes.add(x1);
    variableNodes.add(x2);
    variableNodes.add(x3);
    variableNodes.add(x4);
    variableNodes.add(x5);
    Graph _graph = new EdgeListGraph(variableNodes);
    SemGraph graph = new SemGraph(_graph);
    graph.addDirectedEdge(x1, x3);
    graph.addDirectedEdge(x2, x3);
    graph.addDirectedEdge(x3, x4);
    graph.addDirectedEdge(x2, x4);
    graph.addDirectedEdge(x4, x5);
    graph.addDirectedEdge(x2, x5);
    SemPm semPm = new SemPm(graph);
    SemIm semIm = new SemIm(semPm);
    DataSet dataSet = semIm.simulateData(sampleSize, false);
    print(semPm);
    GeneralizedSemPm _semPm = new GeneralizedSemPm(semPm);
    GeneralizedSemIm _semIm = new GeneralizedSemIm(_semPm, semIm);
    DataSet _dataSet = _semIm.simulateDataMinimizeSurface(sampleSize, false);
    print(_semPm);
    for (int j = 0; j < dataSet.getNumColumns(); j++) {
        double[] col = dataSet.getDoubleData().getColumn(j).toArray();
        double[] _col = _dataSet.getDoubleData().getColumn(j).toArray();
        double mean = StatUtils.mean(col);
        double _mean = StatUtils.mean(_col);
        double variance = StatUtils.variance(col);
        double _variance = StatUtils.variance(_col);
        assertEquals(mean, _mean, 0.3);
        assertEquals(1.0, variance / _variance, .2);
    }
}

Example 29 with DataSet

use of edu.cmu.tetrad.data.DataSet in project tetrad by cmu-phil.

the class TestGeneralizedSem method test11.

@Test
public void test11() {
    RandomUtil.getInstance().setSeed(29999483L);
    try {
        Node x1 = new GraphNode("X1");
        Node x2 = new GraphNode("X2");
        Node x3 = new GraphNode("X3");
        Node x4 = new GraphNode("X4");
        Graph g = new EdgeListGraphSingleConnections();
        g.addNode(x1);
        g.addNode(x2);
        g.addNode(x3);
        g.addNode(x4);
        g.addDirectedEdge(x1, x2);
        g.addDirectedEdge(x2, x3);
        g.addDirectedEdge(x3, x4);
        g.addDirectedEdge(x1, x4);
        GeneralizedSemPm pm = new GeneralizedSemPm(g);
        pm.setNodeExpression(x1, "E_X1");
        pm.setNodeExpression(x2, "a1 * tan(X1) + E_X2");
        pm.setNodeExpression(x3, "a2 * tan(X2) + E_X3");
        pm.setNodeExpression(x4, "a3 * tan(X1) + a4 * tan(X3) ^ 2 + E_X4");
        pm.setNodeExpression(pm.getErrorNode(x1), "N(0, c1)");
        pm.setNodeExpression(pm.getErrorNode(x2), "N(0, c2)");
        pm.setNodeExpression(pm.getErrorNode(x3), "N(0, c3)");
        pm.setNodeExpression(pm.getErrorNode(x4), "N(0, c4)");
        pm.setParameterExpression("c1", "4");
        pm.setParameterExpression("c2", "4");
        pm.setParameterExpression("c3", "4");
        pm.setParameterExpression("c4", "4");
        GeneralizedSemIm im = new GeneralizedSemIm(pm);
        print("True model: ");
        print(im);
        DataSet data = im.simulateDataRecursive(1000, false);
        GeneralizedSemIm imInit = new GeneralizedSemIm(pm);
        imInit.setParameterValue("c1", 8);
        imInit.setParameterValue("c2", 8);
        imInit.setParameterValue("c3", 8);
        imInit.setParameterValue("c4", 8);
        GeneralizedSemEstimator estimator = new GeneralizedSemEstimator();
        GeneralizedSemIm estIm = estimator.estimate(pm, data);
        print("\n\n\nEstimated model: ");
        print(estIm);
        print(estimator.getReport());
        double aSquaredStar = estimator.getaSquaredStar();
        assertEquals(7.07, aSquaredStar, 0.01);
    } catch (ParseException e) {
        e.printStackTrace();
    }
}

Example 30 with DataSet

use of edu.cmu.tetrad.data.DataSet in project tetrad by cmu-phil.

the class TestGeneralizedSem method test7.

@Test
public void test7() {
    RandomUtil.getInstance().setSeed(29999483L);
    List<Node> nodes = new ArrayList<>();
    int numVars = 10;
    for (int i = 0; i < numVars; i++) nodes.add(new ContinuousVariable("X" + (i + 1)));
    Graph graph = GraphUtils.randomGraphRandomForwardEdges(nodes, 0, numVars, 30, 15, 15, false, true);
    GeneralizedSemPm pm = new GeneralizedSemPm(graph);
    GeneralizedSemIm im = new GeneralizedSemIm(pm);
    print(im);
    DataSet data = im.simulateDataRecursive(1000, false);
    GeneralizedSemEstimator estimator = new GeneralizedSemEstimator();
    GeneralizedSemIm estIm = estimator.estimate(pm, data);
    print(estIm);
    print(estimator.getReport());
    double aSquaredStar = estimator.getaSquaredStar();
    assertEquals(0.67, aSquaredStar, 0.01);
}