Example usage for org.apache.commons.math3.stat.descriptive.moment StandardDeviation evaluate

Introduction

In this page you can find the example usage for org.apache.commons.math3.stat.descriptive.moment StandardDeviation evaluate.

Prototype

@Override
public double evaluate(final double[] values) throws MathIllegalArgumentException 

Source Link

Document

Returns the Standard Deviation of the entries in the input array, or Double.NaN if the array is empty.

Usage

From source file:com.musicg.experiment.test.Test1.java

/**
 * @param args/*w  w w  .j  av  a 2 s. c om*/
 */
public static void main(String[] args) {

    String filename = "audio_work/lala.wav";

    // create a wave object
    Wave wave = null;
    try {
        wave = new Wave(filename);
    } catch (IOException e) {
        // TODO Auto-generated catch block
        e.printStackTrace();
    }

    // TimeDomainRepresentations
    int fftSampleSize = 1024;
    int overlapFactor = 1;
    Spectrogram spectrogram = new Spectrogram(wave, fftSampleSize, overlapFactor);

    int fps = spectrogram.getFramesPerSecond();
    double unitFrequency = spectrogram.getUnitFrequency();

    // set boundary
    int highPass = 100;
    int lowerBoundary = (int) (highPass / unitFrequency);
    int lowPass = 4000;
    int upperBoundary = (int) (lowPass / unitFrequency);
    // end set boundary

    double[][] spectrogramData = spectrogram.getNormalizedSpectrogramData();
    double[][] absoluteSpectrogramData = spectrogram.getAbsoluteSpectrogramData();
    double[][] boundedSpectrogramData = new double[spectrogramData.length][];

    // SpectralCentroid sc=new SpectralCentroid();
    StandardDeviation sd = new StandardDeviation();
    ArrayRankDouble arrayRankDouble = new ArrayRankDouble();

    // zrc
    short[] amps = wave.getSampleAmplitudes();
    int numFrame = amps.length / 1024;
    double[] zcrs = new double[numFrame];

    for (int i = 0; i < numFrame; i++) {
        short[] temp = new short[1024];
        System.arraycopy(amps, i * 1024, temp, 0, temp.length);

        int numZC = 0;
        int size = temp.length;

        for (int j = 0; j < size - 1; j++) {
            if ((temp[j] >= 0 && temp[j + 1] < 0) || (temp[j] < 0 && temp[j + 1] >= 0)) {
                numZC++;
            }
        }

        zcrs[i] = numZC;
    }

    // end zcr

    for (int i = 0; i < spectrogramData.length; i++) {
        double[] temp = new double[upperBoundary - lowerBoundary + 1];
        System.arraycopy(spectrogramData[i], lowerBoundary, temp, 0, temp.length);

        int maxIndex = arrayRankDouble.getMaxValueIndex(temp);
        // sc.setValues(temp);

        double sdValue = sd.evaluate(temp);

        System.out.println(i + " " + (double) i / fps + "s\t" + maxIndex + "\t" + sdValue + "\t" + zcrs[i]);
        boundedSpectrogramData[i] = temp;
    }

    // Graphic render
    GraphicRender render = new GraphicRender();
    render.setHorizontalMarker(61);
    render.setVerticalMarker(200);
    render.renderSpectrogramData(boundedSpectrogramData, filename + ".jpg");

    PitchHandler ph = new PitchHandler();

    for (int frame = 0; frame < absoluteSpectrogramData.length; frame++) {

        System.out.print("frame " + frame + ": ");

        double[] temp = new double[upperBoundary - lowerBoundary + 1];

        double sdValue = sd.evaluate(temp);
        double passSd = 0.1;

        if (sdValue < passSd) {
            System.arraycopy(spectrogramData[frame], lowerBoundary, temp, 0, temp.length);
            double maxFrequency = arrayRankDouble.getMaxValueIndex(temp) * unitFrequency;

            double passFrequency = 400;
            int numRobust = 2;

            double[] robustFrequencies = new double[numRobust];
            double nthValue = arrayRankDouble.getNthOrderedValue(temp, numRobust, false);
            int count = 0;
            for (int b = lowerBoundary; b <= upperBoundary; b++) {
                if (spectrogramData[frame][b] >= nthValue) {
                    robustFrequencies[count++] = b * unitFrequency;
                    if (count >= numRobust) {
                        break;
                    }
                }
            }

            double passIntensity = 1000;
            double intensity = 0;
            for (int i = 0; i < absoluteSpectrogramData[frame].length; i++) {
                intensity += absoluteSpectrogramData[frame][i];
            }
            intensity /= absoluteSpectrogramData[frame].length;
            System.out.print(" intensity: " + intensity + " pitch: " + maxFrequency);
            if (intensity > passIntensity && maxFrequency > passFrequency) {
                double p = ph.getHarmonicProbability(robustFrequencies);
                System.out.print(" P: " + p);
            }
        }
        System.out.print(" zcr:" + zcrs[frame]);
        System.out.println();
    }
}

---

From source file:com.facebook.presto.operator.aggregation.TestDoubleStdDevAggregation.java

@Override
public Number getExpectedValue(int start, int length) {
    if (length < 2) {
        return null;
    }//from w  w w . ja  va2  s.co  m

    double[] values = new double[length];
    for (int i = 0; i < length; i++) {
        values[i] = start + i;
    }

    StandardDeviation stdDev = new StandardDeviation();
    return stdDev.evaluate(values);
}

---

From source file:com.facebook.presto.operator.aggregation.TestDoubleStdDevPopAggregation.java

@Override
public Number getExpectedValue(int start, int length) {
    if (length == 0) {
        return null;
    }/* www.j a v  a  2 s  .c o m*/

    double[] values = new double[length];
    for (int i = 0; i < length; i++) {
        values[i] = start + i;
    }

    StandardDeviation stdDev = new StandardDeviation(false);
    return stdDev.evaluate(values);
}

---

From source file:com.itemanalysis.psychometrics.kernel.LikelihoodCrossValidation.java

private void computeBounds() {
    StandardDeviation sd = new StandardDeviation();
    this.max = sd.evaluate(x);
}

---

From source file:net.sf.sessionAnalysis.SessionVisitorSessionLengthNanosStatistics.java

public double computeSessionLengthStdDev() {
    double[] lengths = computeLengthVector();
    StandardDeviation stdDevObj = new StandardDeviation();
    return stdDevObj.evaluate(lengths);
}

---

From source file:com.graphhopper.jsprit.core.algorithm.acceptor.SchrimpfInitialThresholdGenerator.java

@Override
public void informAlgorithmStarts(VehicleRoutingProblem problem, VehicleRoutingAlgorithm algorithm,
        Collection<VehicleRoutingProblemSolution> solutions) {
    logger.info("prepare schrimpfAcceptanceFunction, i.e. determine initial threshold");
    double now = System.currentTimeMillis();

    /*/*from w  w w  . j  a  va2 s  . c om*/
       * randomWalk to determine standardDev
     */
    final double[] results = new double[nOfRandomWalks];

    Jsprit.Builder builder = new GreedySchrimpfFactory().createGreedyAlgorithmBuilder(problem);
    builder.setCustomAcceptor(new AcceptNewRemoveFirst(1));
    VehicleRoutingAlgorithm vra = builder.buildAlgorithm();
    vra.setMaxIterations(nOfRandomWalks);
    vra.getAlgorithmListeners().addListener(new IterationEndsListener() {

        @Override
        public void informIterationEnds(int iteration, VehicleRoutingProblem problem,
                Collection<VehicleRoutingProblemSolution> solutions) {
            double result = Solutions.bestOf(solutions).getCost();
            //            logger.info("result={}", result);
            results[iteration - 1] = result;
        }

    });
    vra.searchSolutions();

    StandardDeviation dev = new StandardDeviation();
    double standardDeviation = dev.evaluate(results);
    double initialThreshold = standardDeviation / 2;

    schrimpfAcceptance.setInitialThreshold(initialThreshold);

    logger.info("took {} seconds", ((System.currentTimeMillis() - now) / 1000.0));
    logger.debug("initial threshold: {}", initialThreshold);
    logger.info("---------------------------------------------------------------------");
}

---

From source file:de.biomedical_imaging.traJ.features.SplineCurveSpatialFeature.java

@Override
/**//from   ww  w  .  j  a  v a2s.  c  o m
 * @return [0] Mean  distance [1] SD  distance 
 */
public double[] evaluate() {
    splinefit = new TrajectorySplineFit(t, nSegments);
    splinefit.calculateSpline();
    if (!splinefit.wasSuccessfull()) {
        return new double[] { Double.NaN, Double.NaN };
    }
    double[] data = new double[t.size()];
    for (int i = 0; i < t.size(); i++) {

        Point2D.Double help = new Point2D.Double(splinefit.getRotatedTrajectory().get(i).x,
                splinefit.getRotatedTrajectory().get(i).y);
        data[i] = help.distance(splinefit.minDistancePointSpline(new Point2D.Double(
                splinefit.getRotatedTrajectory().get(i).x, splinefit.getRotatedTrajectory().get(i).y), 50));
    }
    Mean m = new Mean();
    StandardDeviation sd = new StandardDeviation();
    result = new double[] { m.evaluate(data), sd.evaluate(data) };
    return result;

}

---

From source file:de.biomedical_imaging.traj.math.MomentsCalculator.java

public double calculateNthMoment(int n) {
    Array2DRowRealMatrix gyr = RadiusGyrationTensor2D.getRadiusOfGyrationTensor(t);
    EigenDecomposition eigdec = new EigenDecomposition(gyr);

    Vector2d eigv = new Vector2d(eigdec.getEigenvector(0).getEntry(0), eigdec.getEigenvector(0).getEntry(1));

    double[] projected = new double[t.size()];
    for (int i = 0; i < t.size(); i++) {
        Vector2d pos = new Vector2d(t.get(i).x, t.get(i).y);
        double v = eigv.dot(pos);
        projected[i] = v;//from  w  w w  .  ja  va 2s .  c  om
    }

    Mean m = new Mean();
    StandardDeviation s = new StandardDeviation();
    double mean = m.evaluate(projected);
    double sd = s.evaluate(projected);
    double sumPowN = 0;

    for (int i = 0; i < projected.length; i++) {
        sumPowN += Math.pow((projected[i] - mean) / sd, n);
    }

    double nThMoment = sumPowN / projected.length;

    return nThMoment;
}

---

From source file:com.itemanalysis.psychometrics.kernel.LeastSquaresCrossValidation.java

private void computeBounds() throws Exception {
    StandardDeviation stdev = new StandardDeviation();
    this.sd = stdev.evaluate(x);
    Min min = new Min();
    double from = min.evaluate(x);
    Max max = new Max();
    double to = max.evaluate(x);

}

---

From source file:eagle.security.userprofile.model.kde.UserProfileKDEModeler.java

private void computeStats(RealMatrix m) {
    if (m.getColumnDimension() != this.cmdTypes.length) {
        LOG.error("Please fix the commands list in config file");
    }//from   ww w. j ava  2s.  c o  m

    statistics = new UserCommandStatistics[m.getColumnDimension()];

    for (int i = 0; i < m.getColumnDimension(); i++) {
        UserCommandStatistics stats = new UserCommandStatistics();
        stats.setCommandName(this.cmdTypes[i]);
        RealVector colData = m.getColumnVector(i);
        StandardDeviation deviation = new StandardDeviation();
        double stddev = deviation.evaluate(colData.toArray());

        if (LOG.isDebugEnabled())
            LOG.debug("Stddev is NAN ? " + (Double.isNaN(stddev) ? "yes" : "no"));
        if (stddev <= lowVarianceVal)
            stats.setLowVariant(true);
        else
            stats.setLowVariant(false);

        stats.setStddev(stddev);
        Mean mean = new Mean();
        double mu = mean.evaluate(colData.toArray());
        if (LOG.isDebugEnabled())
            LOG.debug("mu is NAN ? " + (Double.isNaN(mu) ? "yes" : "no"));

        stats.setMean(mu);
        statistics[i] = stats;
    }
}

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