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

Example 36 with SemPm

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

the class TestMatrixUtils method testImpiedCovar.

@Test
public void testImpiedCovar() {
    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);
    TetradMatrix err = im.getErrCovar();
    TetradMatrix coef = im.getEdgeCoef();
    TetradMatrix implied = MatrixUtils.impliedCovar(coef, err);
    assertTrue(MatrixUtils.isPositiveDefinite(implied));
    TetradMatrix corr = MatrixUtils.convertCovToCorr(new TetradMatrix(implied));
    assertTrue(MatrixUtils.isPositiveDefinite(corr));
}

Example 37 with SemPm

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

the class TestMimbuild2 method test1.

@Test
public void test1() {
    RandomUtil.getInstance().setSeed(49283494L);
    for (int r = 0; r < 1; r++) {
        Graph mim = DataGraphUtils.randomSingleFactorModel(5, 5, 6, 0, 0, 0);
        Graph mimStructure = structure(mim);
        Parameters params = new Parameters();
        params.set("coefLow", .5);
        params.set("coefHigh", 1.5);
        SemPm pm = new SemPm(mim);
        SemIm im = new SemIm(pm, params);
        DataSet data = im.simulateData(300, false);
        String algorithm = "FOFC";
        Graph searchGraph;
        List<List<Node>> partition;
        if (algorithm.equals("FOFC")) {
            FindOneFactorClusters fofc = new FindOneFactorClusters(data, TestType.TETRAD_WISHART, FindOneFactorClusters.Algorithm.GAP, 0.001);
            searchGraph = fofc.search();
            partition = fofc.getClusters();
        } else if (algorithm.equals("BPC")) {
            TestType testType = TestType.TETRAD_WISHART;
            TestType purifyType = TestType.TETRAD_BASED;
            BuildPureClusters bpc = new BuildPureClusters(data, 0.001, testType, purifyType);
            searchGraph = bpc.search();
            partition = MimUtils.convertToClusters2(searchGraph);
        } else {
            throw new IllegalStateException();
        }
        List<String> latentVarList = reidentifyVariables(mim, data, partition, 2);
        // System.out.println(partition);
        // System.out.println(latentVarList);
        // 
        // System.out.println("True\n" + mimStructure);
        Graph mimbuildStructure;
        for (int mimbuildMethod : new int[] { 2 }) {
            if (mimbuildMethod == 2) {
                Mimbuild2 mimbuild = new Mimbuild2();
                mimbuild.setAlpha(0.001);
                mimbuild.setMinClusterSize(3);
                mimbuildStructure = mimbuild.search(partition, latentVarList, new CovarianceMatrix(data));
                int shd = SearchGraphUtils.structuralHammingDistance(mimStructure, mimbuildStructure);
                assertEquals(7, shd);
            } else if (mimbuildMethod == 3) {
                // System.out.println("Mimbuild Trek\n");
                MimbuildTrek mimbuild = new MimbuildTrek();
                mimbuild.setAlpha(0.1);
                mimbuild.setMinClusterSize(3);
                mimbuildStructure = mimbuild.search(partition, latentVarList, new CovarianceMatrix(data));
                // ICovarianceMatrix latentcov = mimbuild.getLatentsCov();
                // System.out.println("\nCovariance over the latents");
                // System.out.println(latentcov);
                // System.out.println("Estimated\n" + mimbuildStructure);
                int shd = SearchGraphUtils.structuralHammingDistance(mimStructure, mimbuildStructure);
                // System.out.println("SHD = " + shd);
                // System.out.println();
                assertEquals(3, shd);
            } else {
                throw new IllegalStateException();
            }
        }
    }
}

Example 38 with SemPm

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

the class SemPmWrapper method setSemPm.

private void setSemPm(SemPm oldSemPm) {
    try {
        SemPm pm = (SemPm) new MarshalledObject(oldSemPm).get();
        setSemPm(pm);
    } catch (IOException e) {
        e.printStackTrace();
    } catch (ClassNotFoundException e) {
        e.printStackTrace();
    }
}

Example 39 with SemPm

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

the class PurifyScoreBased method gaussianEM.

private double gaussianEM(SemGraph semdag, SemIm initialSemIm) {
    double score, newScore = -Double.MAX_VALUE, bestScore = -Double.MAX_VALUE;
    SemPm semPm = new SemPm(semdag);
    semdag.setShowErrorTerms(true);
    for (int p = 0; p < numObserved; p++) {
        for (int q = 0; q < numObserved; q++) {
            this.bestCyy[p][q] = this.Cyy[p][q];
        }
        if (this.Cyz != null) {
            for (int q = 0; q < numLatent; q++) {
                this.bestCyz[p][q] = this.Cyz[p][q];
            }
        }
    }
    if (this.Czz != null) {
        for (int p = 0; p < numLatent; p++) {
            for (int q = 0; q < numLatent; q++) {
                this.bestCzz[p][q] = this.Czz[p][q];
            }
        }
    }
    initializeGaussianEM(semdag);
    for (int i = 0; i < 3; i++) {
        System.out.println("--Trial " + i);
        SemIm semIm;
        if (i == 0 && initialSemIm != null) {
            semIm = initialSemIm;
        } else {
            semIm = new SemIm(semPm);
            semIm.setCovMatrix(this.covarianceMatrix);
        }
        do {
            score = newScore;
            gaussianExpectation(semIm);
            newScore = gaussianMaximization(semIm);
            if (newScore == -Double.MAX_VALUE) {
                break;
            }
        } while (Math.abs(score - newScore) > 1.E-3);
        System.out.println(newScore);
        if (newScore > bestScore && !Double.isInfinite(newScore)) {
            bestScore = newScore;
            for (int p = 0; p < numObserved; p++) {
                for (int q = 0; q < numObserved; q++) {
                    this.bestCyy[p][q] = this.Cyy[p][q];
                }
                for (int q = 0; q < numLatent; q++) {
                    this.bestCyz[p][q] = this.Cyz[p][q];
                }
            }
            for (int p = 0; p < numLatent; p++) {
                for (int q = 0; q < numLatent; q++) {
                    this.bestCzz[p][q] = this.Czz[p][q];
                }
            }
        }
    }
    for (int p = 0; p < numObserved; p++) {
        for (int q = 0; q < numObserved; q++) {
            this.Cyy[p][q] = this.bestCyy[p][q];
        }
        for (int q = 0; q < numLatent; q++) {
            this.Cyz[p][q] = this.bestCyz[p][q];
        }
    }
    for (int p = 0; p < numLatent; p++) {
        for (int q = 0; q < numLatent; q++) {
            this.Czz[p][q] = this.bestCzz[p][q];
        }
    }
    if (Double.isInfinite(bestScore)) {
        System.out.println("* * Warning: Heywood case in this step");
        return -Double.MAX_VALUE;
    }
    // System.exit(0);
    return bestScore;
}

Example 40 with SemPm

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

the class PurifyScoreBased method scoreCandidate.

private double scoreCandidate() {
    SemGraph graph = updatedGraph();
    initializeGaussianEM(graph);
    SemPm semPm = new SemPm(graph);
    SemIm semIm = new SemIm(semPm, covarianceMatrix);
    gaussianMaximization(semIm);
    try {
        System.out.println("trunk ll = " + semIm.getTruncLL());
        return -semIm.getTruncLL() - 0.5 * semIm.getNumFreeParams() * Math.log(covarianceMatrix.getSampleSize());
    } catch (IllegalArgumentException e) {
        return -Double.MAX_VALUE;
    }
}