Examples with MlBayesIm edu.cmu.tetrad.bayes.MlBayesIm used on opensource projects

Example 1 with MlBayesIm

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

the class TestBayesIm method testCopyConstructor.

@Test
public void testCopyConstructor() {
    Graph graph = GraphConverter.convert("X1-->X2,X1-->X3,X2-->X4,X3-->X4");
    Dag dag = new Dag(graph);
    BayesPm bayesPm = new BayesPm(dag);
    BayesIm bayesIm = new MlBayesIm(bayesPm, MlBayesIm.RANDOM);
    BayesIm bayesIm2 = new MlBayesIm(bayesIm);
    assertEquals(bayesIm, bayesIm2);
}

Example 2 with MlBayesIm

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

the class TestBayesIm method testAddRemoveParent.

/**
 * Tests whether the BayesIm does the right thing in a very simple case
 * where nodes are added or removed from the graph. Start with graph a -> b,
 * parameterizing with two values for each node. Construct and fill in
 * probability tables in BayesIm. Then add edge c -> b "manually." This
 * should create a table of values for c that is unspecified, and it should
 * double up the rows from b. Then remove the node c. Now the table for b
 * should be completely unspecified.
 */
@Test
public void testAddRemoveParent() {
    Node a = new GraphNode("a");
    Node b = new GraphNode("b");
    Graph dag = new EdgeListGraph();
    dag.addNode(a);
    dag.addNode(b);
    dag.addDirectedEdge(a, b);
    BayesPm bayesPm = new BayesPm(dag);
    BayesIm bayesIm = new MlBayesIm(bayesPm, MlBayesIm.RANDOM);
    BayesIm bayesIm2 = new MlBayesIm(bayesPm, bayesIm, MlBayesIm.MANUAL);
    assertEquals(bayesIm, bayesIm2);
    Node c = new GraphNode("c");
    dag.addNode(c);
    dag.addDirectedEdge(c, b);
    BayesPm bayesPm3 = new BayesPm(dag, bayesPm);
    BayesIm bayesIm3 = new MlBayesIm(bayesPm3, bayesIm2, MlBayesIm.MANUAL);
    // Make sure the rows got repeated.
    // assertTrue(rowsEqual(bayesIm3, bayesIm3.getNodeIndex(b), 0, 1));
    // assertTrue(!rowsEqual(bayesIm3, bayesIm3.getNodeIndex(b), 1, 2));
    // assertTrue(rowsEqual(bayesIm3, bayesIm3.getNodeIndex(b), 2, 3));
    // Make sure the 'c' node got ?'s.
    assertTrue(rowUnspecified(bayesIm3, bayesIm3.getNodeIndex(c), 0));
    dag.removeNode(c);
    BayesPm bayesPm4 = new BayesPm(dag, bayesPm3);
    BayesIm bayesIm4 = new MlBayesIm(bayesPm4, bayesIm3, MlBayesIm.MANUAL);
    // Make sure the 'b' node has 2 rows of '?'s'.
    assertTrue(bayesIm4.getNumRows(bayesIm4.getNodeIndex(b)) == 2);
    assertTrue(rowUnspecified(bayesIm4, bayesIm4.getNodeIndex(b), 0));
    assertTrue(rowUnspecified(bayesIm4, bayesIm4.getNodeIndex(b), 1));
}

Example 3 with MlBayesIm

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

the class TestBayesIm method testConstructManual.

@Test
public void testConstructManual() {
    Graph graph = GraphConverter.convert("X1-->X2,X1-->X3,X2-->X4,X3-->X4");
    Graph dag = new Dag(graph);
    BayesPm bayesPm = new BayesPm(dag);
    BayesIm bayesIm = new MlBayesIm(bayesPm);
    Graph dag1 = bayesIm.getBayesPm().getDag();
    Graph dag2 = GraphUtils.replaceNodes(dag1, graph.getNodes());
    assertEquals(dag2, graph);
}

Example 4 with MlBayesIm

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

the class TestCellProbabilities method testCreateUsingBayesIm.

@Test
public void testCreateUsingBayesIm() {
    RandomUtil.getInstance().setSeed(4828385834L);
    Graph graph = GraphConverter.convert("X1-->X2,X1-->X3,X2-->X4,X3-->X4");
    Dag dag = new Dag(graph);
    BayesPm bayesPm = new BayesPm(dag);
    BayesIm bayesIm = new MlBayesIm(bayesPm, MlBayesIm.RANDOM);
    StoredCellProbs cellProbs = StoredCellProbs.createCellTable(bayesIm);
    double prob = cellProbs.getCellProb(new int[] { 0, 0, 0, 0 });
    assertEquals(0.0058, prob, 0.0001);
}

Example 5 with MlBayesIm

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

the class TestDataLoadersRoundtrip method testDiscreteRoundtrip.

@Test
public void testDiscreteRoundtrip() {
    setUp();
    try {
        for (int i = 0; i < 1; i++) {
            List<Node> nodes = new ArrayList<>();
            for (int j = 0; j < 5; j++) {
                nodes.add(new ContinuousVariable("X" + (j + 1)));
            }
            Graph randomGraph = new Dag(GraphUtils.randomGraph(nodes, 0, 8, 30, 15, 15, false));
            Dag dag = new Dag(randomGraph);
            BayesPm bayesPm1 = new BayesPm(dag);
            MlBayesIm bayesIm1 = new MlBayesIm(bayesPm1, MlBayesIm.RANDOM);
            DataSet dataSet = bayesIm1.simulateData(10, false);
            new File("target/test_data").mkdir();
            FileWriter fileWriter = new FileWriter("target/test_data/roundtrip.dat");
            Writer writer = new PrintWriter(fileWriter);
            DataWriter.writeRectangularData(dataSet, writer, '\t');
            writer.close();
            File file = new File("target/test_data/roundtrip.dat");
            DataReader reader = new DataReader();
            reader.setKnownVariables(dataSet.getVariables());
            DataSet _dataSet = reader.parseTabular(file);
            assertTrue(dataSet.equals(_dataSet));
        }
    } catch (IOException e) {
        e.printStackTrace();
        fail(e.getMessage());
    }
}