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Example 31 with BayesPm

use of edu.cmu.tetrad.bayes.BayesPm in project tetrad by cmu-phil.

the class TestGeneralBootstrapTest method testFCId.

@Test
public void testFCId() {
    double structurePrior = 1, samplePrior = 1;
    int depth = -1;
    int maxPathLength = -1;
    int numVars = 20;
    int edgesPerNode = 2;
    int numLatentConfounders = 4;
    int numCases = 50;
    int numBootstrapSamples = 5;
    boolean verbose = true;
    long seed = 123;
    Graph dag = makeDiscreteDAG(numVars, numLatentConfounders, edgesPerNode);
    DagToPag dagToPag = new DagToPag(dag);
    Graph truePag = dagToPag.convert();
    System.out.println("Truth PAG_of_the_true_DAG Graph:");
    System.out.println(truePag.toString());
    BayesPm pm = new BayesPm(dag, 2, 3);
    BayesIm im = new MlBayesIm(pm, MlBayesIm.RANDOM);
    DataSet data = im.simulateData(numCases, seed, false);
    Parameters parameters = new Parameters();
    parameters.set("structurePrior", structurePrior);
    parameters.set("samplePrior", samplePrior);
    parameters.set("depth", depth);
    parameters.set("maxPathLength", maxPathLength);
    parameters.set("numPatternsToStore", 0);
    parameters.set("verbose", verbose);
    IndependenceWrapper test = new ChiSquare();
    Algorithm algorithm = new Fci(test);
    GeneralBootstrapTest bootstrapTest = new GeneralBootstrapTest(data, algorithm, numBootstrapSamples);
    bootstrapTest.setVerbose(verbose);
    bootstrapTest.setParameters(parameters);
    bootstrapTest.setEdgeEnsemble(BootstrapEdgeEnsemble.Highest);
    Graph resultGraph = bootstrapTest.search();
    System.out.println("Estimated Bootstrapped PAG_of_the_true_DAG Graph:");
    System.out.println(resultGraph.toString());
    // Adjacency Confusion Matrix
    int[][] adjAr = GeneralBootstrapTest.getAdjConfusionMatrix(truePag, resultGraph);
    printAdjConfusionMatrix(adjAr);
    // Edge Type Confusion Matrix
    int[][] edgeAr = GeneralBootstrapTest.getEdgeTypeConfusionMatrix(truePag, resultGraph);
    printEdgeTypeConfusionMatrix(edgeAr);
}
Also used : MlBayesIm(edu.cmu.tetrad.bayes.MlBayesIm) Parameters(edu.cmu.tetrad.util.Parameters) ChiSquare(edu.cmu.tetrad.algcomparison.independence.ChiSquare) GeneralBootstrapTest(edu.pitt.dbmi.algo.bootstrap.GeneralBootstrapTest) DataSet(edu.cmu.tetrad.data.DataSet) Algorithm(edu.cmu.tetrad.algcomparison.algorithm.Algorithm) Fci(edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Fci) IndependenceWrapper(edu.cmu.tetrad.algcomparison.independence.IndependenceWrapper) Graph(edu.cmu.tetrad.graph.Graph) DagToPag(edu.cmu.tetrad.search.DagToPag) BayesIm(edu.cmu.tetrad.bayes.BayesIm) MlBayesIm(edu.cmu.tetrad.bayes.MlBayesIm) BayesPm(edu.cmu.tetrad.bayes.BayesPm) Test(org.junit.Test) GeneralBootstrapTest(edu.pitt.dbmi.algo.bootstrap.GeneralBootstrapTest)

Example 32 with BayesPm

use of edu.cmu.tetrad.bayes.BayesPm in project tetrad by cmu-phil.

the class TestGeneralBootstrapTest method testFGESd.

@Test
public void testFGESd() {
    double structurePrior = 1, samplePrior = 1;
    boolean faithfulnessAssumed = false;
    int maxDegree = -1;
    int numVars = 20;
    int edgesPerNode = 2;
    int numLatentConfounders = 0;
    int numCases = 50;
    int numBootstrapSamples = 5;
    boolean verbose = true;
    long seed = 123;
    Graph dag = makeDiscreteDAG(numVars, numLatentConfounders, edgesPerNode);
    System.out.println("Truth Graph:");
    System.out.println(dag.toString());
    BayesPm pm = new BayesPm(dag, 2, 3);
    BayesIm im = new MlBayesIm(pm, MlBayesIm.RANDOM);
    DataSet data = im.simulateData(numCases, seed, false);
    Parameters parameters = new Parameters();
    parameters.set("structurePrior", structurePrior);
    parameters.set("samplePrior", samplePrior);
    parameters.set("faithfulnessAssumed", faithfulnessAssumed);
    parameters.set("maxDegree", maxDegree);
    parameters.set("numPatternsToStore", 0);
    parameters.set("verbose", verbose);
    ScoreWrapper score = new BdeuScore();
    Algorithm algorithm = new Fges(score);
    GeneralBootstrapTest bootstrapTest = new GeneralBootstrapTest(data, algorithm, numBootstrapSamples);
    bootstrapTest.setVerbose(verbose);
    bootstrapTest.setParameters(parameters);
    bootstrapTest.setEdgeEnsemble(BootstrapEdgeEnsemble.Highest);
    Graph resultGraph = bootstrapTest.search();
    System.out.println("Estimated Graph:");
    System.out.println(resultGraph.toString());
    // Adjacency Confusion Matrix
    int[][] adjAr = GeneralBootstrapTest.getAdjConfusionMatrix(dag, resultGraph);
    printAdjConfusionMatrix(adjAr);
    // Edge Type Confusion Matrix
    int[][] edgeAr = GeneralBootstrapTest.getEdgeTypeConfusionMatrix(dag, resultGraph);
    printEdgeTypeConfusionMatrix(edgeAr);
}
Also used : MlBayesIm(edu.cmu.tetrad.bayes.MlBayesIm) Parameters(edu.cmu.tetrad.util.Parameters) GeneralBootstrapTest(edu.pitt.dbmi.algo.bootstrap.GeneralBootstrapTest) DataSet(edu.cmu.tetrad.data.DataSet) ScoreWrapper(edu.cmu.tetrad.algcomparison.score.ScoreWrapper) Algorithm(edu.cmu.tetrad.algcomparison.algorithm.Algorithm) Fges(edu.cmu.tetrad.algcomparison.algorithm.oracle.pattern.Fges) Graph(edu.cmu.tetrad.graph.Graph) BayesIm(edu.cmu.tetrad.bayes.BayesIm) MlBayesIm(edu.cmu.tetrad.bayes.MlBayesIm) BdeuScore(edu.cmu.tetrad.algcomparison.score.BdeuScore) BayesPm(edu.cmu.tetrad.bayes.BayesPm) Test(org.junit.Test) GeneralBootstrapTest(edu.pitt.dbmi.algo.bootstrap.GeneralBootstrapTest)

Example 33 with BayesPm

use of edu.cmu.tetrad.bayes.BayesPm in project tetrad by cmu-phil.

the class TestGeneralBootstrapTest method testGFCId.

@Test
public void testGFCId() {
    double structurePrior = 1, samplePrior = 1;
    boolean faithfulnessAssumed = false;
    int maxDegree = -1;
    int numVars = 20;
    int edgesPerNode = 2;
    int numLatentConfounders = 4;
    int numCases = 50;
    int numBootstrapSamples = 5;
    boolean verbose = true;
    long seed = 123;
    Graph dag = makeDiscreteDAG(numVars, numLatentConfounders, edgesPerNode);
    DagToPag dagToPag = new DagToPag(dag);
    Graph truePag = dagToPag.convert();
    System.out.println("Truth PAG_of_the_true_DAG Graph:");
    System.out.println(truePag.toString());
    BayesPm pm = new BayesPm(dag, 2, 3);
    BayesIm im = new MlBayesIm(pm, MlBayesIm.RANDOM);
    DataSet data = im.simulateData(numCases, seed, false);
    Parameters parameters = new Parameters();
    parameters.set("structurePrior", structurePrior);
    parameters.set("samplePrior", samplePrior);
    parameters.set("faithfulnessAssumed", faithfulnessAssumed);
    parameters.set("maxDegree", maxDegree);
    parameters.set("numPatternsToStore", 0);
    parameters.set("verbose", verbose);
    ScoreWrapper score = new BdeuScore();
    IndependenceWrapper test = new ChiSquare();
    Algorithm algorithm = new Gfci(test, score);
    GeneralBootstrapTest bootstrapTest = new GeneralBootstrapTest(data, algorithm, numBootstrapSamples);
    bootstrapTest.setVerbose(verbose);
    bootstrapTest.setParameters(parameters);
    bootstrapTest.setEdgeEnsemble(BootstrapEdgeEnsemble.Highest);
    Graph resultGraph = bootstrapTest.search();
    System.out.println("Estimated Bootstrapped PAG_of_the_true_DAG Graph:");
    System.out.println(resultGraph.toString());
    // Adjacency Confusion Matrix
    int[][] adjAr = GeneralBootstrapTest.getAdjConfusionMatrix(truePag, resultGraph);
    printAdjConfusionMatrix(adjAr);
    // Edge Type Confusion Matrix
    int[][] edgeAr = GeneralBootstrapTest.getEdgeTypeConfusionMatrix(truePag, resultGraph);
    printEdgeTypeConfusionMatrix(edgeAr);
}
Also used : MlBayesIm(edu.cmu.tetrad.bayes.MlBayesIm) Parameters(edu.cmu.tetrad.util.Parameters) ChiSquare(edu.cmu.tetrad.algcomparison.independence.ChiSquare) GeneralBootstrapTest(edu.pitt.dbmi.algo.bootstrap.GeneralBootstrapTest) Gfci(edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Gfci) DataSet(edu.cmu.tetrad.data.DataSet) ScoreWrapper(edu.cmu.tetrad.algcomparison.score.ScoreWrapper) Algorithm(edu.cmu.tetrad.algcomparison.algorithm.Algorithm) IndependenceWrapper(edu.cmu.tetrad.algcomparison.independence.IndependenceWrapper) Graph(edu.cmu.tetrad.graph.Graph) DagToPag(edu.cmu.tetrad.search.DagToPag) BayesIm(edu.cmu.tetrad.bayes.BayesIm) MlBayesIm(edu.cmu.tetrad.bayes.MlBayesIm) BdeuScore(edu.cmu.tetrad.algcomparison.score.BdeuScore) BayesPm(edu.cmu.tetrad.bayes.BayesPm) Test(org.junit.Test) GeneralBootstrapTest(edu.pitt.dbmi.algo.bootstrap.GeneralBootstrapTest)

Example 34 with BayesPm

use of edu.cmu.tetrad.bayes.BayesPm in project tetrad by cmu-phil.

the class TestHistogram method testHistogram.

@Test
public void testHistogram() {
    RandomUtil.getInstance().setSeed(4829384L);
    List<Node> nodes = new ArrayList<>();
    for (int i = 0; i < 5; i++) {
        nodes.add(new ContinuousVariable("X" + (i + 1)));
    }
    Dag trueGraph = new Dag(GraphUtils.randomGraph(nodes, 0, 5, 30, 15, 15, false));
    int sampleSize = 1000;
    // Continuous
    SemPm semPm = new SemPm(trueGraph);
    SemIm semIm = new SemIm(semPm);
    DataSet data = semIm.simulateData(sampleSize, false);
    Histogram histogram = new Histogram(data);
    histogram.setTarget("X1");
    histogram.setNumBins(20);
    assertEquals(3.76, histogram.getMax(), 0.01);
    assertEquals(-3.83, histogram.getMin(), 0.01);
    assertEquals(1000, histogram.getN());
    histogram.setTarget("X1");
    histogram.setNumBins(10);
    histogram.addConditioningVariable("X3", 0, 1);
    histogram.addConditioningVariable("X4", 0, 1);
    histogram.removeConditioningVariable("X3");
    assertEquals(3.76, histogram.getMax(), 0.01);
    assertEquals(-3.83, histogram.getMin(), 0.01);
    assertEquals(188, histogram.getN());
    double[] arr = histogram.getContinuousData("X2");
    histogram.addConditioningVariable("X2", StatUtils.min(arr), StatUtils.mean(arr));
    // Discrete
    BayesPm bayesPm = new BayesPm(trueGraph);
    BayesIm bayesIm = new MlBayesIm(bayesPm, MlBayesIm.RANDOM);
    DataSet data2 = bayesIm.simulateData(sampleSize, false);
    // For some reason these are giving different
    // values when all of the unit tests are run are
    // once. TODO They produce stable values when
    // this particular test is run repeatedly.
    Histogram histogram2 = new Histogram(data2);
    histogram2.setTarget("X1");
    int[] frequencies1 = histogram2.getFrequencies();
    // assertEquals(928, frequencies1[0]);
    // assertEquals(72, frequencies1[1]);
    histogram2.setTarget("X1");
    histogram2.addConditioningVariable("X2", 0);
    histogram2.addConditioningVariable("X3", 1);
    int[] frequencies = histogram2.getFrequencies();
// assertEquals(377, frequencies[0]);
// assertEquals(28, frequencies[1]);
}
Also used : Histogram(edu.cmu.tetrad.data.Histogram) MlBayesIm(edu.cmu.tetrad.bayes.MlBayesIm) DataSet(edu.cmu.tetrad.data.DataSet) Node(edu.cmu.tetrad.graph.Node) ArrayList(java.util.ArrayList) Dag(edu.cmu.tetrad.graph.Dag) ContinuousVariable(edu.cmu.tetrad.data.ContinuousVariable) BayesIm(edu.cmu.tetrad.bayes.BayesIm) MlBayesIm(edu.cmu.tetrad.bayes.MlBayesIm) SemPm(edu.cmu.tetrad.sem.SemPm) SemIm(edu.cmu.tetrad.sem.SemIm) BayesPm(edu.cmu.tetrad.bayes.BayesPm) Test(org.junit.Test)

Example 35 with BayesPm

use of edu.cmu.tetrad.bayes.BayesPm in project tetrad by cmu-phil.

the class BayesImEditorObs method init.

private void init(BayesIm bayesIm) {
    if (bayesIm == null) {
        throw new NullPointerException("Bayes IM must not be null.");
    }
    BayesPm bayesPm = bayesIm.getBayesPm();
    Graph graph = bayesPm.getDag();
    GraphWorkbench workbench = new GraphWorkbench(graph);
    JMenuBar menuBar = new JMenuBar();
    JMenu file = new JMenu("File");
    menuBar.add(file);
    // file.add(new SaveBayesImXmlAction(this));
    // file.add(new LoadBayesImXmlAction(wrapper, this));
    file.add(new SaveScreenshot(this, true, "Save Screenshot..."));
    file.add(new SaveComponentImage(workbench, "Save Graph Image..."));
    setLayout(new BorderLayout());
    add(menuBar, BorderLayout.NORTH);
    wizard = new BayesImEditorWizardObs(bayesIm, workbench);
    wizard.addPropertyChangeListener(new PropertyChangeListener() {

        public void propertyChange(PropertyChangeEvent evt) {
            if ("editorValueChanged".equals(evt.getPropertyName())) {
                firePropertyChange("modelChanged", null, null);
            }
        }
    });
    JScrollPane workbenchScroll = new JScrollPane(workbench);
    JScrollPane wizardScroll = new JScrollPane(getWizard());
    workbenchScroll.setPreferredSize(new Dimension(450, 450));
    JSplitPane splitPane = new JSplitPane(JSplitPane.HORIZONTAL_SPLIT, workbenchScroll, wizardScroll);
    splitPane.setOneTouchExpandable(true);
    splitPane.setDividerLocation(workbenchScroll.getPreferredSize().width);
    add(splitPane, BorderLayout.CENTER);
    setName("Bayes IM Obs Editor");
    getWizard().addPropertyChangeListener(new PropertyChangeListener() {

        public void propertyChange(PropertyChangeEvent evt) {
            if ("editorClosing".equals(evt.getPropertyName())) {
                firePropertyChange("editorClosing", null, getName());
            }
            if ("closeFrame".equals(evt.getPropertyName())) {
                firePropertyChange("closeFrame", null, null);
                firePropertyChange("editorClosing", true, true);
            }
            if ("modelChanged".equals(evt.getPropertyName())) {
                firePropertyChange("modelChanged", evt.getOldValue(), evt.getNewValue());
            }
        }
    });
}
Also used : PropertyChangeEvent(java.beans.PropertyChangeEvent) PropertyChangeListener(java.beans.PropertyChangeListener) Graph(edu.cmu.tetrad.graph.Graph) GraphWorkbench(edu.cmu.tetradapp.workbench.GraphWorkbench) BayesPm(edu.cmu.tetrad.bayes.BayesPm)

Aggregations

BayesPm (edu.cmu.tetrad.bayes.BayesPm)38 MlBayesIm (edu.cmu.tetrad.bayes.MlBayesIm)23 BayesIm (edu.cmu.tetrad.bayes.BayesIm)18 Test (org.junit.Test)17 Node (edu.cmu.tetrad.graph.Node)14 Graph (edu.cmu.tetrad.graph.Graph)10 DataSet (edu.cmu.tetrad.data.DataSet)6 Dag (edu.cmu.tetrad.graph.Dag)6 DisplayNode (edu.cmu.tetradapp.workbench.DisplayNode)6 ArrayList (java.util.ArrayList)6 List (java.util.List)5 BayesProperties (edu.cmu.tetrad.bayes.BayesProperties)4 LargeScaleSimulation (edu.cmu.tetrad.sem.LargeScaleSimulation)4 Algorithm (edu.cmu.tetrad.algcomparison.algorithm.Algorithm)3 GraphNode (edu.cmu.tetrad.graph.GraphNode)3 Parameters (edu.cmu.tetrad.util.Parameters)3 GeneralBootstrapTest (edu.pitt.dbmi.algo.bootstrap.GeneralBootstrapTest)3 NumberFormat (java.text.NumberFormat)3 RandomGraph (edu.cmu.tetrad.algcomparison.graph.RandomGraph)2 ChiSquare (edu.cmu.tetrad.algcomparison.independence.ChiSquare)2