Example usage for org.apache.commons.math3.stat.descriptive SummaryStatistics getStandardDeviation

Introduction

In this page you can find the example usage for org.apache.commons.math3.stat.descriptive SummaryStatistics getStandardDeviation.

Prototype

public double getStandardDeviation() 

Source Link

Document

Returns the standard deviation of the values that have been added.

Usage

From source file:org.cloudsimplus.testbeds.heuristics.DatacenterBrokerHeuristicRunner.java

@Override
protected void printFinalResults(String metricName, SummaryStatistics stats) {
    System.out.printf("\n# %s for %d simulation runs\n", metricName, getNumberOfSimulationRuns());

    if (!simulationRunsAndNumberOfBatchesAreCompatible()) {
        System.out.println(/*w  ww.j a v a  2  s. c  o  m*/
                "\tBatch means method was not be applied because the number of simulation runs is not greater than the number of batches.");
    }
    System.out.printf("\tRound-robin solution used by DatacenterBrokerSimple - Cost: %.2f\n",
            roundRobinSolution.getCost());

    if (getNumberOfSimulationRuns() > 1) {
        System.out.printf("\tHeuristic solutions - Mean cost: %.2f Std. Dev.: %.2f\n", stats.getMean(),
                stats.getStandardDeviation());
        showConfidenceInterval(stats);
        System.out.printf(
                "\n\tThe mean cost of heuristic solutions represent %.2f%% of the Round-robin mapping used by the DatacenterBrokerSimple\n",
                heuristicSolutionCostPercentageOfRoundRobinSolution(stats.getMean()));
        System.out.printf("Experiment execution mean time: %.2f seconds\n", runtimeStats.getMean());
    }
}

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From source file:org.cloudsimplus.testbeds.linuxscheduler.CloudletSchedulerRunner.java

@Override
protected void printFinalResults(String metricName, SummaryStatistics stats) {
    System.out.printf("Results for metric %s\n", metricName);
    System.out.printf("  Mean Number of Cloudlets:         %.2f\n",
            cloudletsNumber.stream().mapToDouble(n -> n).average().orElse(0.0));
    System.out.printf("  Cloudlet Completion Time Avg:     %.2f | Std dev:      %.2f\n", stats.getMean(),
            stats.getStandardDeviation());
    System.out.printf("  Cloudlet Completion Min Avg Time: %.2f | Max avg time: %.2f\n", stats.getMin(),
            stats.getMax());//from   w ww . ja  va  2 s.c o  m
    System.out.println();
}

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From source file:org.hoidla.window.WindowUtils.java

/**
 * Identifies outliers/*  w  ww  .j  av a  2 s. co  m*/
 * @param data
 * @param outlierThresholdFactor
 * @param pattern
 * @return indexes outlying data points
 */
public static List<Integer> removeOutliers(double[] data, int outlierThresholdFactor, double[] pattern) {
    if (null != pattern && data.length != pattern.length) {
        throw new IllegalArgumentException("data and pattern need to be of same size");
    }

    //stats
    SummaryStatistics stats = new SummaryStatistics();
    for (double value : data) {
        stats.addValue(value);
    }
    double mean = stats.getMean();
    double stdDev = stats.getStandardDeviation();

    //thresholds
    double upThreshold = mean + outlierThresholdFactor * stdDev;
    double loThreshold = mean - outlierThresholdFactor * stdDev;

    //detect outliers
    List<Integer> outliers = new ArrayList<Integer>();
    int i = 0;
    for (double value : data) {
        if (value > upThreshold || value < loThreshold) {
            //replace with pattern value so that there is no net effect
            if (null != pattern) {
                data[i] = pattern[i];
            }
            outliers.add(i);
        }
        ++i;
    }

    return outliers;
}

---

From source file:org.lightjason.agentspeak.action.buildin.math.statistic.EStatisticValue.java

/**
 * returns a statistic value/*  ww w .  ja  v a  2 s  .c  om*/
 *
 * @param p_statistic statistic object
 * @return statistic value
 */
public final double value(final SummaryStatistics p_statistic) {
    switch (this) {
    case GEOMETRICMEAN:
        return p_statistic.getGeometricMean();

    case MAX:
        return p_statistic.getMax();

    case MIN:
        return p_statistic.getMin();

    case COUNT:
        return p_statistic.getN();

    case POPULATIONVARIANCE:
        return p_statistic.getPopulationVariance();

    case QUADRATICMEAN:
        return p_statistic.getQuadraticMean();

    case SECONDMOMENT:
        return p_statistic.getSecondMoment();

    case STANDARDDEVIATION:
        return p_statistic.getStandardDeviation();

    case SUM:
        return p_statistic.getSum();

    case SUMLOG:
        return p_statistic.getSumOfLogs();

    case SUMSQUARE:
        return p_statistic.getSumsq();

    case VARIANCE:
        return p_statistic.getVariance();

    case MEAN:
        return p_statistic.getMean();

    default:
        throw new CIllegalStateException(
                org.lightjason.agentspeak.common.CCommon.languagestring(this, "unknown", this));
    }
}

---

From source file:org.lightjason.agentspeak.action.builtin.math.statistic.EStatisticValue.java

/**
 * returns a statistic value//ww w .j a v a 2s .c o m
 *
 * @param p_statistic statistic object
 * @return statistic value
 */
public final double value(@Nonnull final SummaryStatistics p_statistic) {
    switch (this) {
    case GEOMETRICMEAN:
        return p_statistic.getGeometricMean();

    case MAX:
        return p_statistic.getMax();

    case MIN:
        return p_statistic.getMin();

    case COUNT:
        return p_statistic.getN();

    case POPULATIONVARIANCE:
        return p_statistic.getPopulationVariance();

    case QUADRATICMEAN:
        return p_statistic.getQuadraticMean();

    case SECONDMOMENT:
        return p_statistic.getSecondMoment();

    case STANDARDDEVIATION:
        return p_statistic.getStandardDeviation();

    case SUM:
        return p_statistic.getSum();

    case SUMLOG:
        return p_statistic.getSumOfLogs();

    case SUMSQUARE:
        return p_statistic.getSumsq();

    case VARIANCE:
        return p_statistic.getVariance();

    case MEAN:
        return p_statistic.getMean();

    default:
        throw new CIllegalStateException(
                org.lightjason.agentspeak.common.CCommon.languagestring(this, "unknown", this));
    }
}

---

From source file:org.lpe.common.util.LpeNumericUtils.java

/**
 * Calculates confidence interval width for the given SummaryStatistics and
 * the significance level.//from w  w  w . jav  a  2 s .  c  o  m
 * 
 * @param summaryStatistics
 *            the data
 * @param significance
 *            desired significance level
 * @return the width of the confidence interval around the mean with the
 *         given significance level
 */
public static double getConfidenceIntervalWidth(SummaryStatistics summaryStatistics, double significance) {
    return getConfidenceIntervalWidth(summaryStatistics.getN(), summaryStatistics.getStandardDeviation(),
            significance);
}

---

From source file:org.orbisgis.corejdbc.ReadTable.java

/**
 * Compute numeric stats of the specified table column using a limited input rows. Stats are not done in the sql side.
 * @param connection Available connection
 * @param tableName Table name/*from w  w  w .  j  a  v a2 s. c  o m*/
 * @param columnName Column name
 * @param rowNum Row id
 * @param pm Progress monitor
 * @return An array of attributes {@link STATS}
 * @throws SQLException
 */
public static String[] computeStatsLocal(Connection connection, String tableName, String columnName,
        SortedSet<Integer> rowNum, ProgressMonitor pm) throws SQLException {
    String[] res = new String[STATS.values().length];
    SummaryStatistics stats = new SummaryStatistics();
    try (Statement st = connection.createStatement()) {
        // Cancel select
        PropertyChangeListener listener = EventHandler.create(PropertyChangeListener.class, st, "cancel");
        pm.addPropertyChangeListener(ProgressMonitor.PROP_CANCEL, listener);
        try (ResultSet rs = st.executeQuery(String.format("SELECT %s FROM %s", columnName, tableName))) {
            ProgressMonitor fetchProgress = pm.startTask(rowNum.size());
            while (rs.next() && !pm.isCancelled()) {
                if (rowNum.contains(rs.getRow())) {
                    stats.addValue(rs.getDouble(columnName));
                    fetchProgress.endTask();
                }
            }
        } finally {
            pm.removePropertyChangeListener(listener);
        }
    }
    res[STATS.SUM.ordinal()] = Double.toString(stats.getSum());
    res[STATS.AVG.ordinal()] = Double.toString(stats.getMean());
    res[STATS.COUNT.ordinal()] = Long.toString(stats.getN());
    res[STATS.MIN.ordinal()] = Double.toString(stats.getMin());
    res[STATS.MAX.ordinal()] = Double.toString(stats.getMax());
    res[STATS.STDDEV_SAMP.ordinal()] = Double.toString(stats.getStandardDeviation());
    return res;
}

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From source file:org.orekit.forces.gravity.SolidTidesFieldTest.java

@Test
public void testInterpolationAccuracy() throws OrekitException {

    // The shortest periods are slightly below one half day for the tidal waves
    // considered here. This implies the sampling rate should be fast enough.
    // The tuning parameters we have finally settled correspond to a two hours
    // sample containing 12 points (i.e. one new point is computed every 10 minutes).
    // The observed relative interpolation error with these settings are essentially
    // due to Runge phenomenon at points sampling rate. Plotting the errors shows
    // singular peaks pointing out of merely numerical noise.
    final IERSConventions conventions = IERSConventions.IERS_2010;
    Frame itrf = FramesFactory.getITRF(conventions, true);
    TimeScale utc = TimeScalesFactory.getUTC();
    UT1Scale ut1 = TimeScalesFactory.getUT1(conventions, true);
    NormalizedSphericalHarmonicsProvider gravityField = GravityFieldFactory.getConstantNormalizedProvider(5, 5);

    SolidTidesField raw = new SolidTidesField(conventions.getLoveNumbers(),
            conventions.getTideFrequencyDependenceFunction(ut1), conventions.getPermanentTide(),
            conventions.getSolidPoleTide(ut1.getEOPHistory()), itrf, gravityField.getAe(), gravityField.getMu(),
            gravityField.getTideSystem(), CelestialBodyFactory.getSun(), CelestialBodyFactory.getMoon());
    int step = 600;
    int nbPoints = 12;
    CachedNormalizedSphericalHarmonicsProvider interpolated = new CachedNormalizedSphericalHarmonicsProvider(
            raw, step, nbPoints, OrekitConfiguration.getCacheSlotsNumber(), 7 * Constants.JULIAN_DAY,
            0.5 * Constants.JULIAN_DAY);

    // the following time range is located around the maximal observed error
    AbsoluteDate start = new AbsoluteDate(2003, 6, 12, utc);
    AbsoluteDate end = start.shiftedBy(3 * Constants.JULIAN_DAY);
    SummaryStatistics stat = new SummaryStatistics();
    for (AbsoluteDate date = start; date.compareTo(end) < 0; date = date.shiftedBy(60)) {
        NormalizedSphericalHarmonics rawHarmonics = raw.onDate(date);
        NormalizedSphericalHarmonics interpolatedHarmonics = interpolated.onDate(date);

        for (int n = 2; n < 5; ++n) {
            for (int m = 0; m <= n; ++m) {

                if (n < 4 || m < 3) {
                    double cnmRaw = rawHarmonics.getNormalizedCnm(n, m);
                    double cnmInterp = interpolatedHarmonics.getNormalizedCnm(n, m);
                    double errorC = (cnmInterp - cnmRaw) / FastMath.abs(cnmRaw);
                    stat.addValue(errorC);

                    if (m > 0) {
                        double snmRaw = rawHarmonics.getNormalizedSnm(n, m);
                        double snmInterp = interpolatedHarmonics.getNormalizedSnm(n, m);
                        double errorS = (snmInterp - snmRaw) / FastMath.abs(snmRaw);
                        stat.addValue(errorS);
                    }// w  w w  .j  a  v a2  s .c  om
                }
            }
        }
    }
    Assert.assertEquals(0.0, stat.getMean(), 2.0e-12);
    Assert.assertTrue(stat.getStandardDeviation() < 2.0e-9);
    Assert.assertTrue(stat.getMin() > -9.0e-8);
    Assert.assertTrue(stat.getMax() < 8.0e-8);

}

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From source file:org.spotter.ext.detection.highmessaging.analyze.Analyzer.java

protected double standardDeviation(List<Double> values) {
    SummaryStatistics stats = new SummaryStatistics();
    for (double val : values) {
        stats.addValue(val);
    }//from  w  ww.j  av  a  2 s.  c  om
    return stats.getStandardDeviation();
}

---

From source file:org.spotter.ext.detection.highmessaging.analyze.LinearAnalyzer.java

@Override
public AnalyzeResult analyze() {
    // Values smoothed
    List<Double> valuesSmoothed = smooth(yValues, smoothingWide);

    // Values smoothed and normalized relative to the first
    List<Double> valuesSmoothedNormalized = normalize(valuesSmoothed, valuesSmoothed.get(0));

    // Check if linear increasing
    List<Double> slopes = new ArrayList<Double>();
    SummaryStatistics statsSlopesSmoothedNormalized = new SummaryStatistics();
    for (int i = 0; i < xValues.size(); i++) {
        double slope = 1;

        if (i != 0) {
            slope = (valuesSmoothedNormalized.get(i) - valuesSmoothedNormalized.get(i - 1))
                    / (xValues.get(i) - xValues.get(i - 1));
        }//from  w w w.j  a  v  a 2  s  . c om

        statsSlopesSmoothedNormalized.addValue(slope);
        slopes.add(slope);
        // System.out.println((slope + "").replaceAll("\\.", ","));
    }

    List<Double> slopesSmoothed = smooth(slopes, 2);

    int outlierCount = 0;
    double lowerBound = statsSlopesSmoothedNormalized.getMean()
            - statsSlopesSmoothedNormalized.getStandardDeviation();
    lowerBound = 0.5;
    for (double val : slopesSmoothed) {
        // System.out.println((val + "").replaceAll("\\.", ","));
        if (lowerBound > val) {
            outlierCount++;
        }
    }

    double pctOutlier = 1D / slopes.size() * outlierCount;
    //      System.out.println(String.format("> Outlier: %d Pct Outlier: %.2f", outlierCount, pctOutlier));

    if (pctOutlier > 1D - pctThreshold) {
        // Too much outside
        return AnalyzeResult.NEGATIVE;
    } else {
        // Alles ok
        return AnalyzeResult.POSITIVE;
    }
}

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