Examples with IndTestScore edu.cmu.tetrad.search.IndTestScore used on opensource projects

Example 1 with IndTestScore

use of edu.cmu.tetrad.search.IndTestScore in project tetrad by cmu-phil.

the class TestAutisticClassification method testForBiwei.

// @Test
public void testForBiwei() {
    Parameters parameters = new Parameters();
    parameters.set("penaltyDiscount", 2);
    parameters.set("depth", -1);
    parameters.set("numRuns", 10);
    parameters.set("randomSelectionSize", 1);
    parameters.set("Structure", "Placeholder");
    FaskGraphs files = new FaskGraphs("/Users/jdramsey/Downloads/USM_ABIDE", new Parameters());
    List<DataSet> datasets = files.getDatasets();
    List<String> filenames = files.getFilenames();
    for (int i = 0; i < datasets.size(); i++) {
        DataSet dataSet = datasets.get(i);
        SemBicScore score = new SemBicScore(new CovarianceMatrixOnTheFly(dataSet));
        Fas fas = new Fas(new IndTestScore(score));
        Graph graph = fas.search();
        System.out.println(graph);
        List<Node> nodes = graph.getNodes();
        StringBuilder b = new StringBuilder();
        for (int j = 0; j < nodes.size(); j++) {
            for (int k = 0; k < nodes.size(); k++) {
                if (graph.isAdjacentTo(nodes.get(j), nodes.get(k))) {
                    b.append("1 ");
                } else {
                    b.append("0 ");
                }
            }
            b.append("\n");
        }
        try {
            File dir = new File("/Users/jdramsey/Downloads/biwei/USM_ABIDE");
            dir.mkdirs();
            File file = new File(dir, filenames.get(i) + ".graph.txt");
            PrintStream out = new PrintStream(file);
            out.println(b);
            out.close();
        } catch (FileNotFoundException e) {
            e.printStackTrace();
        }
    }
}

Example 2 with IndTestScore

use of edu.cmu.tetrad.search.IndTestScore in project tetrad by cmu-phil.

the class TsImages method search.

@Override
public Graph search(List<DataModel> dataSets, Parameters parameters) {
    List<DataModel> dataModels = new ArrayList<>();
    for (DataModel dataSet : dataSets) {
        dataModels.add(dataSet);
    }
    TsGFci search;
    if (score instanceof SemBicScore) {
        SemBicScoreImages gesScore = new SemBicScoreImages(dataModels);
        gesScore.setPenaltyDiscount(parameters.getDouble("penaltyDiscount"));
        IndependenceTest test = new IndTestScore(gesScore);
        search = new TsGFci(test, gesScore);
    } else if (score instanceof BdeuScore) {
        double samplePrior = parameters.getDouble("samplePrior", 1);
        double structurePrior = parameters.getDouble("structurePrior", 1);
        BdeuScoreImages score = new BdeuScoreImages(dataModels);
        score.setSamplePrior(samplePrior);
        score.setStructurePrior(structurePrior);
        IndependenceTest test = new IndTestScore(score);
        search = new TsGFci(test, score);
    } else {
        throw new IllegalStateException("Sorry, data must either be all continuous or all discrete.");
    }
    IKnowledge knowledge = dataModels.get(0).getKnowledge();
    search.setKnowledge(knowledge);
    return search.search();
}

Example 3 with IndTestScore

use of edu.cmu.tetrad.search.IndTestScore in project tetrad by cmu-phil.

the class Pcd method search.

@Override
public Graph search(DataModel dataSet, Parameters parameters) {
    if (parameters.getInt("bootstrapSampleSize") < 1) {
        IndTestScore test;
        if (dataSet instanceof ICovarianceMatrix) {
            SemBicScoreDeterministic score = new SemBicScoreDeterministic((ICovarianceMatrix) dataSet);
            score.setPenaltyDiscount(parameters.getDouble("penaltyDiscount"));
            score.setDeterminismThreshold(parameters.getDouble("determinismThreshold"));
            test = new IndTestScore(score);
        } else if (dataSet instanceof DataSet) {
            SemBicScoreDeterministic score = new SemBicScoreDeterministic(new CovarianceMatrix((DataSet) dataSet));
            score.setPenaltyDiscount(parameters.getDouble("penaltyDiscount"));
            score.setDeterminismThreshold(parameters.getDouble("determinismThreshold"));
            test = new IndTestScore(score);
        } else {
            throw new IllegalArgumentException("Expecting a dataset or a covariance matrix.");
        }
        edu.cmu.tetrad.search.Pcd search = new edu.cmu.tetrad.search.Pcd(test);
        search.setDepth(parameters.getInt("depth"));
        search.setKnowledge(knowledge);
        search.setVerbose(parameters.getBoolean("verbose"));
        return search.search();
    } else {
        Pcd algorithm = new Pcd();
        // algorithm.setKnowledge(knowledge);
        DataSet data = (DataSet) dataSet;
        GeneralBootstrapTest search = new GeneralBootstrapTest(data, algorithm, parameters.getInt("bootstrapSampleSize"));
        search.setKnowledge(knowledge);
        BootstrapEdgeEnsemble edgeEnsemble = BootstrapEdgeEnsemble.Highest;
        switch(parameters.getInt("bootstrapEnsemble", 1)) {
            case 0:
                edgeEnsemble = BootstrapEdgeEnsemble.Preserved;
                break;
            case 1:
                edgeEnsemble = BootstrapEdgeEnsemble.Highest;
                break;
            case 2:
                edgeEnsemble = BootstrapEdgeEnsemble.Majority;
        }
        search.setEdgeEnsemble(edgeEnsemble);
        search.setParameters(parameters);
        search.setVerbose(parameters.getBoolean("verbose"));
        return search.search();
    }
}

Example 4 with IndTestScore

use of edu.cmu.tetrad.search.IndTestScore in project tetrad by cmu-phil.

the class SemBicDTest method getTest.

@Override
public IndependenceTest getTest(DataModel dataSet, Parameters parameters) {
    SemBicScoreDeterministic score = new SemBicScoreDeterministic(new CovarianceMatrix((ICovarianceMatrix) dataSet));
    score.setPenaltyDiscount(parameters.getDouble("penaltyDiscount"));
    return new IndTestScore(score, dataSet);
}

Example 5 with IndTestScore

use of edu.cmu.tetrad.search.IndTestScore in project tetrad by cmu-phil.

the class ImagesPcStableMax method search.

@Override
public Graph search(List<DataModel> dataModels, Parameters parameters) {
    if (parameters.getInt("bootstrapSampleSize") < 1) {
        List<DataSet> dataSets = new ArrayList<>();
        for (DataModel dataModel : dataModels) {
            dataSets.add((DataSet) dataModel);
        }
        SemBicScoreImages3 score = new SemBicScoreImages3(dataSets);
        score.setPenaltyDiscount(parameters.getDouble("penaltyDiscount"));
        IndependenceTest test = new IndTestScore(score);
        PcStableMax search = new PcStableMax(test);
        search.setUseHeuristic(parameters.getBoolean("useMaxPOrientationHeuristic"));
        search.setMaxPathLength(parameters.getInt("maxPOrientationMaxPathLength"));
        search.setKnowledge(knowledge);
        search.setDepth(parameters.getInt("depth"));
        return search.search();
    } else {
        ImagesPcStableMax imagesPcStableMax = new ImagesPcStableMax();
        // imagesPcStableMax.setKnowledge(knowledge);
        List<DataSet> datasets = new ArrayList<>();
        for (DataModel dataModel : dataModels) {
            datasets.add((DataSet) dataModel);
        }
        GeneralBootstrapTest search = new GeneralBootstrapTest(datasets, imagesPcStableMax, parameters.getInt("bootstrapSampleSize"));
        search.setKnowledge(knowledge);
        BootstrapEdgeEnsemble edgeEnsemble = BootstrapEdgeEnsemble.Highest;
        switch(parameters.getInt("bootstrapEnsemble", 1)) {
            case 0:
                edgeEnsemble = BootstrapEdgeEnsemble.Preserved;
                break;
            case 1:
                edgeEnsemble = BootstrapEdgeEnsemble.Highest;
                break;
            case 2:
                edgeEnsemble = BootstrapEdgeEnsemble.Majority;
        }
        search.setEdgeEnsemble(edgeEnsemble);
        search.setParameters(parameters);
        search.setVerbose(parameters.getBoolean("verbose"));
        return search.search();
    }
}