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

Example 16 with SemIm

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

the class TestFci method testSearch15.

@Test
public void testSearch15() {
    int numVars = 80;
    int numEdges = 80;
    int sampleSize = 1000;
    boolean latentDataSaved = false;
    int numLatents = 40;
    List<Node> nodes = new ArrayList<>();
    for (int i = 0; i < numVars; i++) {
        nodes.add(new ContinuousVariable("X" + (i + 1)));
    }
    Dag trueGraph = new Dag(GraphUtils.randomGraph(nodes, numLatents, numEdges, 7, 5, 5, false));
    SemPm bayesPm = new SemPm(trueGraph);
    SemIm bayesIm = new SemIm(bayesPm);
    DataSet dataSet = bayesIm.simulateData(sampleSize, latentDataSaved);
    IndependenceTest test = new IndTestFisherZ(dataSet, 0.05);
    Cfci search = new Cfci(test);
    // Run search
    search.search();
}

Example 17 with SemIm

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

the class TestFci method testFciAnc.

// @Test
public void testFciAnc() {
    int numMeasures = 50;
    double edgeFactor = 2.0;
    int numRuns = 10;
    double alpha = 0.01;
    double penaltyDiscount = 4.0;
    int numVarsToMarginalize = 5;
    int numLatents = 10;
    System.out.println("num measures = " + numMeasures);
    System.out.println("edge factor = " + edgeFactor);
    System.out.println("alpha = " + alpha);
    System.out.println("penaltyDiscount = " + penaltyDiscount);
    System.out.println("num runs = " + numRuns);
    System.out.println("num vars to marginalize = " + numVarsToMarginalize);
    System.out.println("num latents = " + numLatents);
    System.out.println();
    for (int i = 0; i < numRuns; i++) {
        int numEdges = (int) (edgeFactor * (numMeasures + numLatents));
        List<Node> nodes = new ArrayList<>();
        for (int r = 0; r < numMeasures + numLatents; r++) {
            String name = "X" + (r + 1);
            nodes.add(new ContinuousVariable(name));
        }
        Graph dag = GraphUtils.randomGraphRandomForwardEdges(nodes, numLatents, numEdges, 10, 10, 10, false);
        SemPm pm = new SemPm(dag);
        SemIm im = new SemIm(pm);
        DataSet data = im.simulateData(1000, false);
        Graph pag = getPag(alpha, penaltyDiscount, data);
        DataSet marginalData = data.copy();
        List<Node> variables = marginalData.getVariables();
        Collections.shuffle(variables);
        for (int m = 0; m < numVarsToMarginalize; m++) {
            marginalData.removeColumn(marginalData.getColumn(variables.get(m)));
        }
        Graph margPag = getPag(alpha, penaltyDiscount, marginalData);
        int ancAnc = 0;
        int ancNanc = 0;
        int nancAnc = 0;
        int nancNanc = 0;
        int ambAnc = 0;
        int ambNanc = 0;
        int totalAncMarg = 0;
        int totalNancMarg = 0;
        for (Node n1 : marginalData.getVariables()) {
            for (Node n2 : marginalData.getVariables()) {
                if (n1 == n2)
                    continue;
                if (ancestral(n1, n2, margPag)) {
                    if (ancestral(n1, n2, pag)) {
                        ancAnc++;
                    } else if (nonAncestral(n1, n2, pag)) {
                        nancAnc++;
                    } else {
                        ambAnc++;
                    }
                    totalAncMarg++;
                } else if (nonAncestral(n1, n2, margPag)) {
                    if (ancestral(n1, n2, pag)) {
                        ancNanc++;
                    } else if (nonAncestral(n1, n2, pag)) {
                        nancNanc++;
                    } else {
                        ambNanc++;
                    }
                    totalNancMarg++;
                }
            }
        }
        // {
        // TextTable table = new TextTable(5, 3);
        // table.setToken(0, 1, "Ancestral");
        // table.setToken(0, 2, "Nonancestral");
        // table.setToken(1, 0, "Ancestral");
        // table.setToken(2, 0, "Nonancestral");
        // table.setToken(3, 0, "Ambiguous");
        // table.setToken(4, 0, "Total");
        // 
        // table.setToken(1, 1, ancAnc + "");
        // table.setToken(2, 1, nancAnc + "");
        // table.setToken(3, 1, ambAnc + "");
        // table.setToken(1, 2, ancNanc + "");
        // table.setToken(2, 2, nancNanc + "");
        // table.setToken(3, 2, ambNanc + "");
        // table.setToken(4, 1, totalAncMarg + "");
        // table.setToken(4, 2, totalNancMarg + "");
        // 
        // System.out.println(table);
        // }
        {
            TextTable table = new TextTable(5, 3);
            table.setToken(0, 1, "Ancestral");
            table.setToken(0, 2, "Nonancestral");
            table.setToken(1, 0, "Ancestral");
            table.setToken(2, 0, "Nonancestral");
            table.setToken(3, 0, "Ambiguous");
            table.setToken(4, 0, "Total");
            NumberFormat nf = new DecimalFormat("0.00");
            table.setToken(1, 1, nf.format(ancAnc / (double) totalAncMarg) + "");
            table.setToken(2, 1, nf.format(nancAnc / (double) totalAncMarg) + "");
            table.setToken(3, 1, nf.format(ambAnc / (double) totalAncMarg) + "");
            table.setToken(1, 2, nf.format(ancNanc / (double) totalNancMarg) + "");
            table.setToken(2, 2, nf.format(nancNanc / (double) totalNancMarg) + "");
            table.setToken(3, 2, nf.format(ambNanc / (double) totalNancMarg) + "");
            table.setToken(4, 1, totalAncMarg + "");
            table.setToken(4, 2, totalNancMarg + "");
            System.out.println(table);
        }
    }
}

Example 18 with SemIm

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

the class TestSemProposition method testEvidence.

@Test
public void testEvidence() {
    Graph graph = constructGraph1();
    SemPm semPm = new SemPm(graph);
    SemIm semIm = new SemIm(semPm);
    List nodes = semIm.getVariableNodes();
    SemProposition proposition = SemProposition.tautology(semIm);
    for (int i = 0; i < semIm.getVariableNodes().size(); i++) {
        assertTrue(Double.isNaN(proposition.getValue(i)));
    }
    proposition.setValue(1, 0.5);
    assertEquals(0.5, proposition.getValue(1), 0.0);
    Node node4 = (Node) nodes.get(3);
    proposition.setValue(node4, 0.7);
    assertEquals(0.7, proposition.getValue(node4), 0.0);
}

Example 19 with SemIm

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

the class TestSemVarMeans method testMeansCholesky.

@Test
public void testMeansCholesky() {
    Graph graph = constructGraph1();
    SemPm semPm1 = new SemPm(graph);
    List<Parameter> parameters = semPm1.getParameters();
    for (Parameter p : parameters) {
        p.setInitializedRandomly(false);
    }
    SemIm semIm1 = new SemIm(semPm1);
    double[] means = { 5.0, 4.0, 3.0, 2.0, 1.0 };
    RandomUtil.getInstance().setSeed(-379467L);
    for (int i = 0; i < semIm1.getVariableNodes().size(); i++) {
        Node node = semIm1.getVariableNodes().get(i);
        semIm1.setMean(node, means[i]);
    }
    DataSet dataSet = semIm1.simulateDataCholesky(1000, false);
    SemEstimator semEst = new SemEstimator(dataSet, semPm1);
    semEst.estimate();
    SemIm estSemIm = semEst.getEstimatedSem();
    List<Node> nodes = semPm1.getVariableNodes();
    for (Node node : nodes) {
        double mean = semIm1.getMean(node);
        assertEquals(mean, estSemIm.getMean(node), 0.6);
    }
}

Example 20 with SemIm

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

the class TestSemVarMeans method testMeansReducedForm.

@Test
public void testMeansReducedForm() {
    Graph graph = constructGraph1();
    SemPm semPm1 = new SemPm(graph);
    List<Parameter> parameters = semPm1.getParameters();
    for (Parameter p : parameters) {
        p.setInitializedRandomly(false);
    }
    SemIm semIm1 = new SemIm(semPm1);
    double[] means = { 5.0, 4.0, 3.0, 2.0, 1.0 };
    RandomUtil.getInstance().setSeed(-379467L);
    for (int i = 0; i < semIm1.getVariableNodes().size(); i++) {
        Node node = semIm1.getVariableNodes().get(i);
        semIm1.setMean(node, means[i]);
    }
    DataSet dataSet = semIm1.simulateDataReducedForm(1000, false);
    SemEstimator semEst = new SemEstimator(dataSet, semPm1);
    semEst.estimate();
    SemIm estSemIm = semEst.getEstimatedSem();
    List<Node> nodes = semPm1.getVariableNodes();
    for (Node node : nodes) {
        double mean = semIm1.getMean(node);
        assertEquals(mean, estSemIm.getMean(node), 0.5);
    }
}