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

Example 31 with SemPm

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

the class TestPc method printStats.

private double[] printStats(String[] algorithms, int t, boolean directed, int numRuns, double alpha, double penaltyDiscount, int numMeasures, int numLatents, double edgeFactor) {
    NumberFormat nf = new DecimalFormat("0.00");
    double sumArrowPrecision = 0.0;
    double sumTailPrecision = 0.0;
    double sumBidirectedPrecision = 0.0;
    int numArrows = 0;
    int numTails = 0;
    int numBidirected = 0;
    int count = 0;
    int totalElapsed = 0;
    int countAP = 0;
    int countTP = 0;
    int countBP = 0;
    for (int i = 0; i < numRuns; i++) {
        int numEdges = (int) (edgeFactor * (numMeasures + numLatents));
        List<Node> nodes = new ArrayList<>();
        List<String> names = new ArrayList<>();
        for (int r = 0; r < numMeasures + numLatents; r++) {
            String name = "X" + (r + 1);
            nodes.add(new ContinuousVariable(name));
            names.add(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);
        IndTestFisherZ test = new IndTestFisherZ(data, alpha);
        SemBicScore score = new SemBicScore(new CovarianceMatrixOnTheFly(data));
        score.setPenaltyDiscount(penaltyDiscount);
        GraphSearch search;
        switch(t) {
            case 0:
                search = new Pc(test);
                break;
            case 1:
                search = new Cpc(test);
                break;
            case 2:
                search = new Fges(score);
                break;
            case 3:
                search = new Fci(test);
                break;
            case 4:
                search = new GFci(test, score);
                break;
            case 5:
                search = new Rfci(test);
                break;
            case 6:
                search = new Cfci(test);
                break;
            default:
                throw new IllegalStateException();
        }
        long start = System.currentTimeMillis();
        Graph out = search.search();
        long stop = System.currentTimeMillis();
        long elapsed = stop - start;
        totalElapsed += elapsed;
        out = GraphUtils.replaceNodes(out, dag.getNodes());
        int arrowsTp = 0;
        int arrowsFp = 0;
        int tailsTp = 0;
        int tailsFp = 0;
        int bidirectedTp = 0;
        int bidirectedFp = 0;
        for (Edge edge : out.getEdges()) {
            if (directed && !(edge.isDirected() || Edges.isBidirectedEdge(edge))) {
                continue;
            }
            if (edge.getEndpoint1() == Endpoint.ARROW) {
                if (!dag.isAncestorOf(edge.getNode1(), edge.getNode2()) && dag.existsTrek(edge.getNode1(), edge.getNode2())) {
                    arrowsTp++;
                } else {
                    arrowsFp++;
                }
                numArrows++;
            }
            if (edge.getEndpoint2() == Endpoint.ARROW) {
                if (!dag.isAncestorOf(edge.getNode2(), edge.getNode1()) && dag.existsTrek(edge.getNode1(), edge.getNode2())) {
                    arrowsTp++;
                } else {
                    arrowsFp++;
                }
                numArrows++;
            }
            if (edge.getEndpoint1() == Endpoint.TAIL) {
                if (dag.existsDirectedPathFromTo(edge.getNode1(), edge.getNode2())) {
                    tailsTp++;
                } else {
                    tailsFp++;
                }
                numTails++;
            }
            if (edge.getEndpoint2() == Endpoint.TAIL) {
                if (dag.existsDirectedPathFromTo(edge.getNode2(), edge.getNode1())) {
                    tailsTp++;
                } else {
                    tailsFp++;
                }
                numTails++;
            }
            if (Edges.isBidirectedEdge(edge)) {
                if (!dag.isAncestorOf(edge.getNode1(), edge.getNode2()) && !dag.isAncestorOf(edge.getNode2(), edge.getNode1()) && dag.existsTrek(edge.getNode1(), edge.getNode2())) {
                    bidirectedTp++;
                } else {
                    bidirectedFp++;
                }
                numBidirected++;
            }
        }
        double arrowPrecision = arrowsTp / (double) (arrowsTp + arrowsFp);
        double tailPrecision = tailsTp / (double) (tailsTp + tailsFp);
        double bidirectedPrecision = bidirectedTp / (double) (bidirectedTp + bidirectedFp);
        if (!Double.isNaN(arrowPrecision)) {
            sumArrowPrecision += arrowPrecision;
            countAP++;
        }
        if (!Double.isNaN(tailPrecision)) {
            sumTailPrecision += tailPrecision;
            countTP++;
        }
        if (!Double.isNaN(bidirectedPrecision)) {
            sumBidirectedPrecision += bidirectedPrecision;
            countBP++;
        }
        count++;
    }
    double avgArrowPrecision = sumArrowPrecision / (double) countAP;
    double avgTailPrecision = sumTailPrecision / (double) countTP;
    double avgBidirectedPrecision = sumBidirectedPrecision / (double) countBP;
    double avgNumArrows = numArrows / (double) count;
    double avgNumTails = numTails / (double) count;
    double avgNumBidirected = numBidirected / (double) count;
    double avgElapsed = totalElapsed / (double) numRuns;
    // double avgRatioPrecisionToElapsed = avgArrowPrecision / avgElapsed;
    double[] ret = new double[] { avgArrowPrecision, avgTailPrecision, avgBidirectedPrecision, avgNumArrows, avgNumTails, avgNumBidirected, // minimize
    -avgElapsed // avgRatioPrecisionToElapsed
    };
    System.out.println();
    NumberFormat nf2 = new DecimalFormat("0.0000");
    System.out.println(algorithms[t] + " arrow precision " + nf.format(avgArrowPrecision));
    System.out.println(algorithms[t] + " tail precision " + nf.format(avgTailPrecision));
    System.out.println(algorithms[t] + " bidirected precision " + nf.format(avgBidirectedPrecision));
    System.out.println(algorithms[t] + " avg num arrow " + nf.format(avgNumArrows));
    System.out.println(algorithms[t] + " avg num tails " + nf.format(avgNumTails));
    System.out.println(algorithms[t] + " avg num bidirected " + nf.format(avgNumBidirected));
    System.out.println(algorithms[t] + " avg elapsed " + nf.format(avgElapsed));
    return ret;
}

Example 32 with SemPm

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

the class TestStandardizedSem method rtest8.

public void rtest8() {
    // RandomUtil.getInstance().setSeed(2958442283L);
    SemGraph graph = new SemGraph();
    Node x = new ContinuousVariable("X");
    Node y = new ContinuousVariable("Y");
    Node z = new ContinuousVariable("Z");
    graph.addNode(x);
    graph.addNode(y);
    graph.addNode(z);
    graph.addDirectedEdge(x, y);
    graph.addBidirectedEdge(x, y);
    graph.addDirectedEdge(x, z);
    graph.addDirectedEdge(y, z);
    graph.setShowErrorTerms(true);
    SemPm semPm = new SemPm(graph);
    SemIm semIm = new SemIm(semPm);
    StandardizedSemIm sem = new StandardizedSemIm(semIm, StandardizedSemIm.Initialization.CALCULATE_FROM_SEM);
    DataSet data = semIm.simulateDataCholesky(1000, false);
    data = ColtDataSet.makeContinuousData(data.getVariables(), DataUtils.standardizeData(data.getDoubleData()));
    SemEstimator estimator = new SemEstimator(data, semPm);
    semIm = estimator.estimate();
    DataSet data2 = semIm.simulateDataReducedForm(1000, false);
    DataSet data3 = sem.simulateDataReducedForm(1000, false);
    StandardizedSemIm.ParameterRange range2 = sem.getCovarianceRange(x, y);
    double high = range2.getHigh();
    double low = range2.getLow();
    if (high == Double.POSITIVE_INFINITY)
        high = 1000;
    if (low == Double.NEGATIVE_INFINITY)
        low = -1000;
    double coef = low + RandomUtil.getInstance().nextDouble() * (high - low);
    assertTrue(sem.setErrorCovariance(x, y, coef));
    assertTrue(isStandardized(sem));
}

Example 33 with SemPm

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

the class TestStandardizedSem method test5.

@Test
public void test5() {
    RandomUtil.getInstance().setSeed(582374923L);
    SemGraph graph = new SemGraph();
    graph.setShowErrorTerms(true);
    Node x1 = new ContinuousVariable("X1");
    Node x2 = new ContinuousVariable("X2");
    Node x3 = new ContinuousVariable("X3");
    graph.addNode(x1);
    graph.addNode(x2);
    graph.addNode(x3);
    graph.setShowErrorTerms(true);
    Node ex1 = graph.getExogenous(x1);
    Node ex2 = graph.getExogenous(x2);
    Node ex3 = graph.getExogenous(x3);
    graph.addDirectedEdge(x1, x3);
    graph.addDirectedEdge(x2, x3);
    // graph.addDirectedEdge(x1, x2);
    // graph.addBidirectedEdge(ex1, ex2);
    SemPm pm = new SemPm(graph);
    SemIm im = new SemIm(pm);
    DataSet dataSet = im.simulateDataRecursive(1000, false);
    TetradMatrix _dataSet = dataSet.getDoubleData();
    _dataSet = DataUtils.standardizeData(_dataSet);
    DataSet dataSetStandardized = ColtDataSet.makeData(dataSet.getVariables(), _dataSet);
    SemEstimator estimator = new SemEstimator(dataSetStandardized, im.getSemPm());
    SemIm imStandardized = estimator.estimate();
    StandardizedSemIm sem = new StandardizedSemIm(im);
    // sem.setErrorCovariance(ex1, ex2, -.24);
    assertTrue(isStandardized(sem));
}

Example 34 with SemPm

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

the class TestStandardizedSem method test2.

@Test
public void test2() {
    RandomUtil.getInstance().setSeed(5729384723L);
    SemGraph graph = new SemGraph();
    Node x1 = new ContinuousVariable("X1");
    Node x2 = new ContinuousVariable("X2");
    Node x3 = new ContinuousVariable("X3");
    Node x4 = new ContinuousVariable("X4");
    Node x5 = new ContinuousVariable("X5");
    graph.addNode(x1);
    graph.addNode(x2);
    graph.addNode(x3);
    graph.addNode(x4);
    graph.addNode(x5);
    graph.setShowErrorTerms(true);
    graph.addDirectedEdge(x1, x2);
    graph.addDirectedEdge(x2, x3);
    graph.addDirectedEdge(x4, x3);
    graph.addDirectedEdge(x2, x4);
    graph.addDirectedEdge(x1, x4);
    graph.addDirectedEdge(x5, x4);
    SemPm pm = new SemPm(graph);
    SemIm im = new SemIm(pm);
    StandardizedSemIm sem = new StandardizedSemIm(im);
    assertTrue(isStandardized(sem));
}

Example 35 with SemPm

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

the class TestStandardizedSem method test6.

@Test
public void test6() {
    // RandomUtil.getInstance().setSeed(582374923L);
    SemGraph graph = new SemGraph();
    graph.setShowErrorTerms(true);
    Node x1 = new ContinuousVariable("X1");
    Node x2 = new ContinuousVariable("X2");
    Node x3 = new ContinuousVariable("X3");
    graph.addNode(x1);
    graph.addNode(x2);
    graph.addNode(x3);
    graph.setShowErrorTerms(true);
    Node ex1 = graph.getExogenous(x1);
    Node ex2 = graph.getExogenous(x2);
    Node ex3 = graph.getExogenous(x3);
    graph.addDirectedEdge(x1, x3);
    graph.addDirectedEdge(x2, x3);
    graph.addDirectedEdge(x1, x2);
    graph.addBidirectedEdge(ex1, ex2);
    // List<List<Node>> treks = DataGraphUtils.treksIncludingBidirected(graph, x1, x3);
    // 
    // for (List<Node> trek : treks) {
    // System.out.println(trek);
    // }
    SemPm pm = new SemPm(graph);
    SemIm im = new SemIm(pm);
    DataSet dataSet = im.simulateDataRecursive(1000, false);
    TetradMatrix _dataSet = dataSet.getDoubleData();
    _dataSet = DataUtils.standardizeData(_dataSet);
    DataSet dataSetStandardized = ColtDataSet.makeData(dataSet.getVariables(), _dataSet);
    SemEstimator estimator = new SemEstimator(dataSetStandardized, im.getSemPm());
    SemIm imStandardized = estimator.estimate();
    StandardizedSemIm sem = new StandardizedSemIm(im);
    assertTrue(isStandardized(sem));
}