Examples with DoubleArrayList cern.colt.list.DoubleArrayList used on opensource projects

Example 1 with DoubleArrayList

use of cern.colt.list.DoubleArrayList in project tetrad by cmu-phil.

the class TestMeasurementSimulator method testSampleToSampleError.

/**
 * Turn on sample-to-sample error, turn off all other sources of error,
 * simulate 1 dish of data with 1000 samples per dish, and look to see
 * whether in the aggregated data the standard deviations of Gene2:t1 and
 * Gene3:t1 are 0.2.
 */
public void testSampleToSampleError() {
    setDefaultParameters();
    // The following parameters are set to non-default values for
    // this test.
    this.simulator.setNumSamplesPerDish(1000);
    this.simulator.setSampleSampleVariability(0.2);
    this.simulator.setChipChipVariability(0.0001);
    this.simulator.setPixelDigitalization(0.0001);
    this.simulator.setStepsGenerated(2);
    this.simulator.setNumCellsPerDish(100);
    // Simulate the data.
    this.simulator.simulate(this.history);
    double[][][] measuredData = this.simulator.getMeasuredData();
    // Do the test.
    DoubleArrayList doubleArrayList = new DoubleArrayList(measuredData[1][0]);
    double sum = Descriptive.sum(doubleArrayList);
    double sumOfSquares = Descriptive.sumOfSquares(doubleArrayList);
    double gene2time1sd = Descriptive.standardDeviation(Descriptive.variance(measuredData[1][0].length, sum, sumOfSquares));
    DoubleArrayList doubleArrayList1 = new DoubleArrayList(measuredData[2][0]);
    double sum1 = Descriptive.sum(doubleArrayList1);
    double sumOfSquares1 = Descriptive.sumOfSquares(doubleArrayList1);
    double gene3time1sd = Descriptive.standardDeviation(Descriptive.variance(measuredData[2][0].length, sum1, sumOfSquares1));
    assertEquals(0.2, gene2time1sd, 0.02);
    assertEquals(0.2, gene3time1sd, 0.02);
}

Example 2 with DoubleArrayList

use of cern.colt.list.DoubleArrayList in project tetrad by cmu-phil.

the class TestMeasurementSimulator method testDishToDishVariability.

/**
 * Turn on dish-to-dish variability error, turn off all other sources of
 * error, simulate 100 dishes of data with 1 sample per dish, and look to
 * see whether in the aggregated data Gene2:t1 and Gene3:t1 have standard
 * deviations that are 10% of their respective means.
 */
public void testDishToDishVariability() {
    setDefaultParameters();
    // The following parameters are set to non-default values for
    // this test.
    this.simulator.setNumDishes(100);
    this.simulator.setStepsGenerated(2);
    this.simulator.setNumSamplesPerDish(1);
    this.simulator.setSampleSampleVariability(0.0001);
    this.simulator.setChipChipVariability(0.0001);
    this.simulator.setPixelDigitalization(0.0001);
    this.simulator.setNumCellsPerDish(100);
    // Simulate the data.
    this.simulator.simulate(this.history);
    double[][][] measuredData = this.simulator.getMeasuredData();
    // Do the test.
    DoubleArrayList doubleArrayList = new DoubleArrayList(measuredData[1][0]);
    double sum = Descriptive.sum(doubleArrayList);
    double sumOfSquares = Descriptive.sumOfSquares(doubleArrayList);
    double gene2time1sd = Descriptive.standardDeviation(Descriptive.variance(measuredData[1][0].length, sum, sumOfSquares));
    DoubleArrayList doubleArrayList1 = new DoubleArrayList(measuredData[2][0]);
    double sum1 = Descriptive.sum(doubleArrayList1);
    double sumOfSquares1 = Descriptive.sumOfSquares(doubleArrayList1);
    double gene3time1sd = Descriptive.standardDeviation(Descriptive.variance(measuredData[2][0].length, sum1, sumOfSquares1));
    double gene2time1mean = Descriptive.mean(new DoubleArrayList(measuredData[1][0]));
    double gene3time1mean = Descriptive.mean(new DoubleArrayList(measuredData[2][0]));
    assertEquals(Math.abs(0.1 * gene2time1mean), gene2time1sd, 0.03);
    assertEquals(Math.abs(0.1 * gene3time1mean), gene3time1sd, 0.03);
}

Example 3 with DoubleArrayList

use of cern.colt.list.DoubleArrayList in project beast2 by CompEvol.

the class KernelDensityEstimator2D method bandwidthNRD.

// bandwidth.nrd =
// function (x)
// {
// r <- quantile(x, c(0.25, 0.75))
// h <- (r[2] - r[1])/1.34
// 4 * 1.06 * min(sqrt(var(x)), h) * length(x)^(-1/5)
// }
public double bandwidthNRD(double[] in) {
    DoubleArrayList inList = new DoubleArrayList(in.length);
    for (double d : in) inList.add(d);
    inList.sort();
    final double h = (Descriptive.quantile(inList, 0.75) - Descriptive.quantile(inList, 0.25)) / 1.34;
    return 4 * 1.06 * Math.min(Math.sqrt(DiscreteStatistics.variance(in)), h) * Math.pow(in.length, -0.2);
}

Example 4 with DoubleArrayList

use of cern.colt.list.DoubleArrayList in project tdq-studio-se by Talend.

the class QuantileFinderTest method observedEpsilonsAtPhis.

/**
 * This method was created in VisualAge.
 * @return double[]
 * @param values cern.it.hepodbms.primitivearray.DoubleArrayList
 * @param phis double[]
 */
public static DoubleArrayList observedEpsilonsAtPhis(DoubleArrayList phis, ExactDoubleQuantileFinder exactFinder, DoubleQuantileFinder approxFinder, double desiredEpsilon) {
    DoubleArrayList epsilons = new DoubleArrayList(phis.size());
    for (int i = phis.size(); --i >= 0; ) {
        double epsilon = observedEpsilonAtPhi(phis.get(i), exactFinder, approxFinder);
        epsilons.add(epsilon);
        if (epsilon > desiredEpsilon)
            System.out.println("Real epsilon = " + epsilon + " is larger than desired by " + (epsilon - desiredEpsilon));
    }
    return epsilons;
}

Example 5 with DoubleArrayList

use of cern.colt.list.DoubleArrayList in project tdq-studio-se by Talend.

the class Descriptive method quantiles.

/**
 * Returns the quantiles of the specified percentages.
 * The quantiles need not necessarily be contained in the data sequence, it can be a linear interpolation.
 * @param sortedData the data sequence; <b>must be sorted ascending</b>.
 * @param percentages the percentages for which quantiles are to be computed.
 * Each percentage must be in the interval <tt>[0.0,1.0]</tt>.
 * @return the quantiles.
 */
public static DoubleArrayList quantiles(DoubleArrayList sortedData, DoubleArrayList percentages) {
    int s = percentages.size();
    DoubleArrayList quantiles = new DoubleArrayList(s);
    for (int i = 0; i < s; i++) {
        quantiles.add(quantile(sortedData, percentages.get(i)));
    }
    return quantiles;
}