Examples with RandomUtil edu.cmu.tetrad.util.RandomUtil used on opensource projects

Example 16 with RandomUtil

use of edu.cmu.tetrad.util.RandomUtil in project tetrad by cmu-phil.

the class MlBayesIm method simulateData.

/**
 * Simulates a sample with the given sample size.
 *
 * @param sampleSize the sample size.
 * @param seed       the random number generator seed allows you
 *                   recreate the simulated data by passing in the same
 *                   seed (so you don't have to store the sample data
 * @return the simulated sample as a DataSet.
 */
public DataSet simulateData(int sampleSize, long seed, boolean latentDataSaved) {
    RandomUtil random = RandomUtil.getInstance();
    long _seed = random.getSeed();
    random.setSeed(seed);
    DataSet dataSet = simulateData(sampleSize, latentDataSaved);
    random.revertSeed(_seed);
    return dataSet;
}

Example 17 with RandomUtil

use of edu.cmu.tetrad.util.RandomUtil in project tetrad by cmu-phil.

the class DirichletBayesIm method getRandomWeights.

/**
 * This method chooses random probabilities for a row which add up to 1.0.
 * Random doubles are drawn from a random distribution, and the final row is
 * then normalized.
 *
 * @param size the length of the row.
 * @return an array with randomly distributed probabilities of this length.
 * @see #randomizeRow
 */
private static double[] getRandomWeights(int size) {
    assert size >= 0;
    double[] weights = new double[size];
    double sum = 0.0;
    for (int i = 0; i < size; i++) {
        RandomUtil randomUtil = RandomUtil.getInstance();
        weights[i] = randomUtil.nextDouble();
        sum += weights[i];
    }
    for (int i = 0; i < size; i++) {
        weights[i] /= sum;
    }
    return weights;
}

Example 18 with RandomUtil

use of edu.cmu.tetrad.util.RandomUtil in project tetrad by cmu-phil.

the class MlBayesImObs method simulateData.

public DataSet simulateData(DataSet dataSet, long seed, boolean latentDataSaved) {
    RandomUtil random = RandomUtil.getInstance();
    random.setSeed(seed);
    return simulateDataHelper(dataSet, latentDataSaved);
}

Example 19 with RandomUtil

use of edu.cmu.tetrad.util.RandomUtil in project tetrad by cmu-phil.

the class ApproximateUpdater method getSinglePoint.

private static int[] getSinglePoint(BayesIm bayesIm, int[] tiers) {
    int[] point = new int[bayesIm.getNumNodes()];
    int[] combination = new int[bayesIm.getNumNodes()];
    RandomUtil randomUtil = RandomUtil.getInstance();
    for (int nodeIndex : tiers) {
        double cutoff = randomUtil.nextDouble();
        for (int k = 0; k < bayesIm.getNumParents(nodeIndex); k++) {
            combination[k] = point[bayesIm.getParent(nodeIndex, k)];
        }
        int rowIndex = bayesIm.getRowIndex(nodeIndex, combination);
        double sum = 0.0;
        for (int k = 0; k < bayesIm.getNumColumns(nodeIndex); k++) {
            double probability = bayesIm.getProbability(nodeIndex, rowIndex, k);
            if (Double.isNaN(probability)) {
                throw new IllegalStateException("Some probability " + "values in the BayesIm are not filled in; " + "cannot simulate data to do approximate updating.");
            }
            sum += probability;
            if (sum >= cutoff) {
                point[nodeIndex] = k;
                break;
            }
        }
    }
    return point;
}

Example 20 with RandomUtil

use of edu.cmu.tetrad.util.RandomUtil in project tetrad by cmu-phil.

the class TestColtDataSet method testRemoveColumn.

@Test
public void testRemoveColumn() {
    int rows = 10;
    int cols = 5;
    List<Node> variables = new LinkedList<>();
    for (int i = 0; i < cols; i++) {
        variables.add(new ContinuousVariable("X" + i));
    }
    DataSet dataSet = new ColtDataSet(rows, variables);
    RandomUtil randomUtil = RandomUtil.getInstance();
    for (int i = 0; i < rows; i++) {
        for (int j = 0; j < cols; j++) {
            dataSet.setDouble(i, j, randomUtil.nextDouble());
        }
    }
    int[] _cols = new int[2];
    _cols[0] = 1;
    _cols[1] = 2;
    dataSet.removeCols(_cols);
    List<Node> _variables = new LinkedList<>(variables);
    _variables.remove(2);
    _variables.remove(1);
    assertEquals(dataSet.getVariables(), _variables);
}