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

Example 16 with ContinuousVariable

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

the class SemEstimatorWrapper method serializableInstance.

// public SemEstimatorWrapper(DataWrapper dataWrapper,
// SemPmWrapper semPmWrapper,
// SemImWrapper semImWrapper,
// Parameters params) {
// if (dataWrapper == null) {
// throw new NullPointerException();
// }
// 
// if (semPmWrapper == null) {
// throw new NullPointerException();
// }
// 
// if (semImWrapper == null) {
// throw new NullPointerException();
// }
// 
// DataSet dataSet =
// (DataSet) dataWrapper.getSelectedDataModel();
// SemPm semPm = semPmWrapper.getSemPm();
// SemIm semIm = semImWrapper.getSemIm();
// 
// this.semEstimator = new SemEstimator(dataSet, semPm, getOptimizer());
// if (!degreesOfFreedomCheck(semPm)) return;
// this.semEstimator.setTrueSemIm(semIm);
// this.semEstimator.setNumRestarts(getParams().getInt("numRestarts", 1));
// this.semEstimator.estimate();
// 
// this.params = params;
// 
// log();
// }
/**
 * Generates a simple exemplar of this class to test serialization.
 *
 * @see TetradSerializableUtils
 */
public static SemEstimatorWrapper serializableInstance() {
    List<Node> variables = new LinkedList<>();
    ContinuousVariable x = new ContinuousVariable("X");
    variables.add(x);
    DataSet dataSet = new ColtDataSet(10, variables);
    for (int i = 0; i < dataSet.getNumRows(); i++) {
        for (int j = 0; j < dataSet.getNumColumns(); j++) {
            dataSet.setDouble(i, j, RandomUtil.getInstance().nextDouble());
        }
    }
    Dag dag = new Dag();
    dag.addNode(x);
    SemPm pm = new SemPm(dag);
    Parameters params1 = new Parameters();
    return new SemEstimatorWrapper(dataSet, pm, params1);
}

Example 17 with ContinuousVariable

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

the class CovMatrixTable method setVariableName.

private void setVariableName(int index, String name) {
    List variables = getCovMatrix().getVariables();
    for (int i = 0; i < variables.size(); i++) {
        ContinuousVariable _variable = (ContinuousVariable) variables.get(i);
        if (name.equals(_variable.getName())) {
            return;
        }
    }
    ContinuousVariable variable = (ContinuousVariable) variables.get(index);
    variable.setName(name);
}

Example 18 with ContinuousVariable

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

the class IndTestMultinomialLogisticRegressionWald method isIndependentRegression.

private boolean isIndependentRegression(Node x, Node y, List<Node> z) {
    if (!variablesPerNode.containsKey(x)) {
        throw new IllegalArgumentException("Unrecogized node: " + x);
    }
    if (!variablesPerNode.containsKey(y)) {
        throw new IllegalArgumentException("Unrecogized node: " + y);
    }
    for (Node node : z) {
        if (!variablesPerNode.containsKey(node)) {
            throw new IllegalArgumentException("Unrecogized node: " + node);
        }
    }
    List<Node> regressors = new ArrayList<>();
    if (y instanceof ContinuousVariable) {
        regressors.add(internalData.getVariable(y.getName()));
    } else {
        regressors.addAll(variablesPerNode.get(y));
    }
    for (Node _z : z) {
        regressors.addAll(variablesPerNode.get(_z));
    }
    int[] _rows = getNonMissingRows(x, y, z);
    regression.setRows(_rows);
    RegressionResult result;
    try {
        result = regression.regress(x, regressors);
    } catch (Exception e) {
        return false;
    }
    double p = 1;
    if (y instanceof ContinuousVariable) {
        p = result.getP()[1];
    } else {
        for (int i = 0; i < variablesPerNode.get(y).size(); i++) {
            double val = result.getP()[1 + i];
            if (val < p)
                p = val;
        }
    }
    this.lastP = p;
    boolean indep = p > alpha;
    if (indep) {
        TetradLogger.getInstance().log("independencies", SearchLogUtils.independenceFactMsg(x, y, z, p));
    } else {
        TetradLogger.getInstance().log("dependencies", SearchLogUtils.dependenceFactMsg(x, y, z, p));
    }
    return indep;
}

Example 19 with ContinuousVariable

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

the class MGM method runTests1.

private static void runTests1() {
    try {
        // DoubleMatrix2D xIn = DoubleFactory2D.dense.make(loadDataSelect("/Users/ajsedgewick/tetrad/test_data", "med_test_C.txt"));
        // DoubleMatrix2D yIn = DoubleFactory2D.dense.make(loadDataSelect("/Users/ajsedgewick/tetrad/test_data", "med_test_D.txt"));
        // String path = MGM.class.getResource("test_data").getPath();
        String path = "/Users/ajsedgewick/tetrad_master/tetrad/tetrad-lib/src/main/java/edu/pitt/csb/mgm/test_data";
        System.out.println(path);
        DoubleMatrix2D xIn = DoubleFactory2D.dense.make(MixedUtils.loadDelim(path, "med_test_C.txt").getDoubleData().toArray());
        DoubleMatrix2D yIn = DoubleFactory2D.dense.make(MixedUtils.loadDelim(path, "med_test_D.txt").getDoubleData().toArray());
        int[] L = new int[24];
        Node[] vars = new Node[48];
        for (int i = 0; i < 24; i++) {
            L[i] = 2;
            vars[i] = new ContinuousVariable("X" + i);
            vars[i + 24] = new DiscreteVariable("Y" + i);
        }
        double lam = .2;
        MGM model = new MGM(xIn, yIn, new ArrayList<>(Arrays.asList(vars)), L, new double[] { lam, lam, lam });
        MGM model2 = new MGM(xIn, yIn, new ArrayList<>(Arrays.asList(vars)), L, new double[] { lam, lam, lam });
        System.out.println("Weights: " + Arrays.toString(model.weights.toArray()));
        DoubleMatrix2D test = xIn.copy();
        DoubleMatrix2D test2 = xIn.copy();
        long t = System.currentTimeMillis();
        for (int i = 0; i < 50000; i++) {
            test2 = xIn.copy();
            test.assign(test2);
        }
        System.out.println("assign Time: " + (System.currentTimeMillis() - t));
        t = System.currentTimeMillis();
        double[][] xArr = xIn.toArray();
        for (int i = 0; i < 50000; i++) {
            if (Thread.currentThread().isInterrupted()) {
                break;
            }
            // test = DoubleFactory2D.dense.make(xArr);
            test2 = xIn.copy();
            test = test2;
        }
        System.out.println("equals Time: " + (System.currentTimeMillis() - t));
        System.out.println("Init nll: " + model.smoothValue(model.params.toMatrix1D()));
        System.out.println("Init reg term: " + model.nonSmoothValue(model.params.toMatrix1D()));
        t = System.currentTimeMillis();
        model.learnEdges(700);
        // model.learn(1e-7, 700);
        System.out.println("Orig Time: " + (System.currentTimeMillis() - t));
        System.out.println("nll: " + model.smoothValue(model.params.toMatrix1D()));
        System.out.println("reg term: " + model.nonSmoothValue(model.params.toMatrix1D()));
        System.out.println("params:\n" + model.params);
        System.out.println("adjMat:\n" + model.adjMatFromMGM());
    } catch (IOException ex) {
        ex.printStackTrace();
    }
}

Example 20 with ContinuousVariable

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

the class ADTreeTest method main.

public static void main(String[] args) throws Exception {
    int columns = 40;
    int numEdges = 40;
    int rows = 500;
    List<Node> variables = new ArrayList<>();
    List<String> varNames = new ArrayList<>();
    for (int i = 0; i < columns; i++) {
        final String name = "X" + (i + 1);
        varNames.add(name);
        variables.add(new ContinuousVariable(name));
    }
    Graph graph = GraphUtils.randomGraphRandomForwardEdges(variables, 0, numEdges, 30, 15, 15, false, true);
    BayesPm pm = new BayesPm(graph);
    BayesIm im = new MlBayesIm(pm, MlBayesIm.RANDOM);
    DataSet data = im.simulateData(rows, false);
    // This implementation uses a DataTable to represent the data
    // The first type parameter is the type for the variables
    // The second type parameter is the type for the values of the variables
    DataTableImpl<Node, Short> dataTable = new DataTableImpl<>(variables);
    for (int i = 0; i < rows; i++) {
        ArrayList<Short> intArray = new ArrayList<>();
        for (int j = 0; j < columns; j++) {
            intArray.add((short) data.getInt(i, j));
        }
        dataTable.addRow(intArray);
    }
    // create the tree
    long start = System.currentTimeMillis();
    ADTree<Node, Short> adTree = new ADTree<>(dataTable);
    System.out.println(String.format("Generated tree in %s millis", System.currentTimeMillis() - start));
    // the query is an arbitrary map of vars and their values
    TreeMap<Node, Short> query = new TreeMap<>();
    query.put(node(pm, "X1"), (short) 1);
    query.put(node(pm, "X5"), (short) 0);
    start = System.currentTimeMillis();
    System.out.println(String.format("Count is %d", adTree.count(query)));
    System.out.println(String.format("Query in %s ms", System.currentTimeMillis() - start));
    query.clear();
    query.put(node(pm, "X1"), (short) 1);
    query.put(node(pm, "X2"), (short) 1);
    query.put(node(pm, "X5"), (short) 0);
    query.put(node(pm, "X10"), (short) 1);
    start = System.currentTimeMillis();
    System.out.println(String.format("Count is %d", adTree.count(query)));
    System.out.println(String.format("Query in %s ms", System.currentTimeMillis() - start));
}