Examples with ContinuousVariable edu.cmu.tetrad.data.ContinuousVariable used on opensource projects

Example 56 with ContinuousVariable

use of edu.cmu.tetrad.data.ContinuousVariable in project tetrad by cmu-phil.

the class DescriptiveStats method generateDescriptiveStats.

/**
 * Constructs a readable table of normality test results
 */
public static String generateDescriptiveStats(DataSet dataSet, Node variable) {
    NumberFormat nf = NumberFormatUtil.getInstance().getNumberFormat();
    int col = dataSet.getColumn(variable);
    double[] data = new double[dataSet.getNumRows()];
    boolean continuous = false;
    if (variable instanceof ContinuousVariable) {
        continuous = true;
        for (int i = 0; i < dataSet.getNumRows(); i++) {
            data[i] = dataSet.getDouble(i, col);
        }
    } else {
        try {
            for (int i = 0; i < dataSet.getNumRows(); i++) {
                DiscreteVariable var = (DiscreteVariable) variable;
                String category = var.getCategory(dataSet.getInt(i, col));
                int value = Integer.parseInt(category);
                data[i] = value;
            }
        } catch (NumberFormatException e) {
            return "Not a numerical discrete column.";
        }
    }
    String result = "Descriptive Statistics for: " + variable.getName() + "\n";
    result += "------------------------------------\n\n";
    double[] normalValues = normalParams(data);
    result += "Sample Size:\t\t" + dataSet.getNumRows() + "\n";
    result += "Mean:\t\t\t" + nf.format(normalValues[0]) + "\nStandard Deviation:\t" + nf.format(normalValues[1]) + "\nVariance:\t\t" + nf.format(normalValues[2]) + "\n";
    result += "Skewness:\t\t" + nf.format(StatUtils.skewness(data)) + "\n";
    result += "Excess Kurtosis:\t" + nf.format(StatUtils.kurtosis(data)) + "\n";
    if (continuous) {
        result += "SE Mean:\t\t" + nf.format(standardErrorMean(normalValues[1], dataSet.getNumRows())) + "\n";
    }
    double[] median = median(data);
    result += "Median:\t\t\t" + nf.format(median[0]) + "\n";
    if (continuous) {
        result += "Minimum Value:\t\t" + nf.format(median[1]) + "\nMaximum Value:\t\t" + nf.format(median[2]);
    }
    return result;
}

Example 57 with ContinuousVariable

use of edu.cmu.tetrad.data.ContinuousVariable in project tetrad by cmu-phil.

the class LogisticRegressionRunner method serializableInstance.

/**
 * Generates a simple exemplar of this class to test serialization.
 *
 * @see TetradSerializableUtils
 */
public static LogisticRegressionRunner serializableInstance() {
    List<Node> variables = new LinkedList<>();
    ContinuousVariable var1 = new ContinuousVariable("X");
    ContinuousVariable var2 = new ContinuousVariable("Y");
    variables.add(var1);
    variables.add(var2);
    DataSet dataSet = new ColtDataSet(3, variables);
    double[] col1data = new double[] { 0.0, 1.0, 2.0 };
    double[] col2data = new double[] { 2.3, 4.3, 2.5 };
    for (int i = 0; i < 3; i++) {
        dataSet.setDouble(i, 0, col1data[i]);
        dataSet.setDouble(i, 1, col2data[i]);
    }
    DataWrapper dataWrapper = new DataWrapper(dataSet);
    return new LogisticRegressionRunner(dataWrapper, new Parameters());
}

Example 58 with ContinuousVariable

use of edu.cmu.tetrad.data.ContinuousVariable in project tetrad by cmu-phil.

the class DataConvertUtils method toNodes.

public static List<Node> toNodes(List<String> variables) {
    List<Node> nodes = new LinkedList<>();
    variables.forEach(variable -> {
        nodes.add(new ContinuousVariable(variable));
    });
    return nodes;
}

Example 59 with ContinuousVariable

use of edu.cmu.tetrad.data.ContinuousVariable in project tetrad by cmu-phil.

the class TestEdgeListGraphSingleConnections method testSequence3.

@Test
public void testSequence3() {
    List<Node> nodes = new ArrayList<>();
    for (int i1 = 0; i1 < 50; i1++) {
        nodes.add(new ContinuousVariable("X" + (i1 + 1)));
    }
    Graph graph = new Dag(GraphUtils.randomGraph(nodes, 0, 50, 30, 15, 15, false));
    Node node1 = graph.getNodes().get(0);
    Node node2 = graph.getNodes().get(1);
    List<Node> cond = new ArrayList<>();
    for (int i = 2; i < 5; i++) {
        cond.add(graph.getNodes().get(i));
    }
    boolean dsep = graph.isDSeparatedFrom(node1, node2, cond);
}

Example 60 with ContinuousVariable

use of edu.cmu.tetrad.data.ContinuousVariable in project tetrad by cmu-phil.

the class TestFas method test1.

@Test
public void test1() {
    int numVars = 10;
    double edgesPerNode = 1.0;
    List<Node> vars = new ArrayList<>();
    for (int i = 0; i < numVars; i++) {
        vars.add(new ContinuousVariable("X" + i));
    }
    Graph graph = GraphUtils.randomGraphRandomForwardEdges(vars, 0, (int) (numVars * edgesPerNode), 30, 15, 15, false, true);
    IndependenceTest test = new IndTestDSep(graph);
    Graph fasGraph = new FasStableConcurrent(test).search();
    Graph pcGraph = new Pc(test).search();
    assertEquals(fasGraph, GraphUtils.undirectedGraph(pcGraph));
}