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

Example 61 with DoubleArrayList

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

the class QuantileBin1D method splitApproximately.

/**
 *Divides (rebins) a copy of the receiver at the given <i>interval boundaries</i> into bins and returns these bins, such that each bin <i>approximately</i> reflects the data elements of its range.
 *
 *For each interval boundary of the axis (including -infinity and +infinity), computes the percentage (quantile inverse) of elements less than the boundary.
 *Then lets {@link #splitApproximately(DoubleArrayList,int)} do the real work.
 *
 *@param axis an axis defining interval boundaries.
 *@param resolution a measure of accuracy; the desired number of subintervals per interval.
 */
public synchronized MightyStaticBin1D[] splitApproximately(hep.aida.IAxis axis, int k) {
    DoubleArrayList percentages = new DoubleArrayList(new hep.aida.ref.Converter().edges(axis));
    percentages.beforeInsert(0, Double.NEGATIVE_INFINITY);
    percentages.add(Double.POSITIVE_INFINITY);
    for (int i = percentages.size(); --i >= 0; ) {
        percentages.set(i, quantileInverse(percentages.get(i)));
    }
    return splitApproximately(percentages, k);
}

Example 62 with DoubleArrayList

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

the class StatUtils method expScore.

public static double expScore(double[] _f) {
    // _f = DataUtils.standardizeData(_f);
    DoubleArrayList f = new DoubleArrayList(_f);
    for (int k = 0; k < _f.length; k++) {
        f.set(k, Math.exp(f.get(k)));
    }
    double expected = Descriptive.mean(f);
    return Math.log(expected);
// double diff = logExpected - 0.5;
// return Math.abs(diff);
}

Example 63 with DoubleArrayList

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

the class StatUtils method logCoshScore.

public static double logCoshScore(double[] _f) {
    _f = standardizeData(_f);
    DoubleArrayList f = new DoubleArrayList(_f);
    for (int k = 0; k < _f.length; k++) {
        double v = Math.log(Math.cosh((f.get(k))));
        f.set(k, v);
    }
    double expected = Descriptive.mean(f);
    double diff = expected - logCoshExp;
    return diff * diff;
}

Example 64 with DoubleArrayList

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

the class TestMeasurementSimulator method testChipToChipError.

/**
 * Turn on chip to chip 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 for Gene2:t1, Gene3:t1, and
 * Gene1:t2 are 0.3.
 */
public void testChipToChipError() {
    setDefaultParameters();
    // The following parameters are set to non-default values for
    // this test.
    this.simulator.setDishDishVariability(0.0001);
    this.simulator.setNumSamplesPerDish(1000);
    this.simulator.setSampleSampleVariability(0.0001);
    this.simulator.setChipChipVariability(0.3);
    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));
    DoubleArrayList doubleArrayList2 = new DoubleArrayList(measuredData[1][1]);
    double sum2 = Descriptive.sum(doubleArrayList2);
    double sumOfSquares2 = Descriptive.sumOfSquares(doubleArrayList2);
    double gene1time2sd = Descriptive.standardDeviation(Descriptive.variance(measuredData[1][1].length, sum2, sumOfSquares2));
    assertEquals(0.3, gene2time1sd, 0.02);
    assertEquals(0.3, gene3time1sd, 0.02);
    assertEquals(0.3, gene1time2sd, 0.02);
}

Example 65 with DoubleArrayList

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

the class TestMeasurementSimulator method testTranscriptionError.

/**
 * Save out the raw data using default parameters and make sure that
 * Gene1:t2 has the specified standard deviation. Should be 0.05. (Gene1 has
 * only itself as parent.)
 */
public void testTranscriptionError() {
    // Raw data is saved for this simulation.
    setDefaultParameters();
    this.simulator.setRawDataSaved(true);
    this.simulator.setMeasuredDataSaved(false);
    // Simulate the data.
    this.simulator.simulate(this.history);
    double[][][] rawData = this.simulator.getRawData();
    // (Test the dimensions.)
    // # variables.
    assertEquals(3, rawData.length);
    // # time steps.
    assertEquals(4, rawData[0].length);
    // # cells / dish
    assertEquals(10000, rawData[0][0].length);
    // The test is to see whether Gene 1 at time step 2 has a
    // standard deviation of 0.05. Of course the gene and time
    // step numbers need to be 0-indexed.
    DoubleArrayList doubleArrayList = new DoubleArrayList(rawData[0][1]);
    double sum = Descriptive.sum(doubleArrayList);
    double sumOfSquares = Descriptive.sumOfSquares(doubleArrayList);
    double stdev = Descriptive.standardDeviation(Descriptive.variance(rawData[0][1].length, sum, sumOfSquares));
    assertEquals(0.05, stdev, 0.01);
}