How to use

getStandardDeviation

method

in

org.apache.commons.math.stat.descriptive.StatisticalSummary

@Override
protected Serializable reduceValues(final List<Object> slaveValues, final String column, final String measure,
    final Collection<? extends NumberAnalyzerResult> results, final Class<?> valueClass) {
  if (SUM_MEASURES.contains(measure)) {
    return sum(slaveValues);
  } else if (NumberAnalyzer.MEASURE_HIGHEST_VALUE.equals(measure)) {
    return maximum(slaveValues);
  } else if (NumberAnalyzer.MEASURE_LOWEST_VALUE.equals(measure)) {
    return minimum(slaveValues);
  } else if (NumberAnalyzer.MEASURE_MEAN.equals(measure)) {
    final StatisticalSummary summary = getSummary(column, results);
    return summary.getMean();
  } else if (NumberAnalyzer.MEASURE_STANDARD_DEVIATION.equals(measure)) {
    final StatisticalSummary summary = getSummary(column, results);
    return summary.getStandardDeviation();
  } else if (NumberAnalyzer.MEASURE_VARIANCE.equals(measure)) {
    final StatisticalSummary summary = getSummary(column, results);
    return summary.getVariance();
  }
  logger.warn("Encountered non-reduceable measure '{}'. Slave values are: {}", measure, slaveValues);
  return null;
}

@Override
protected Serializable reduceValues(List<Object> slaveValues, String column, String measure,
    Collection<? extends NumberAnalyzerResult> results, Class<?> valueClass) {
  if (SUM_MEASURES.contains(measure)) {
    return sum(slaveValues);
  } else if (NumberAnalyzer.MEASURE_HIGHEST_VALUE.equals(measure)) {
    return maximum(slaveValues);
  } else if (NumberAnalyzer.MEASURE_LOWEST_VALUE.equals(measure)) {
    return minimum(slaveValues);
  } else if (NumberAnalyzer.MEASURE_MEAN.equals(measure)) {
    StatisticalSummary summary = getSummary(column, results);
    return summary.getMean();
  } else if (NumberAnalyzer.MEASURE_STANDARD_DEVIATION.equals(measure)) {
    StatisticalSummary summary = getSummary(column, results);
    return summary.getStandardDeviation();
  } else if (NumberAnalyzer.MEASURE_VARIANCE.equals(measure)) {
    StatisticalSummary summary = getSummary(column, results);
    return summary.getVariance();
  }
  
  logger.warn("Encountered non-reduceable measure '{}'. Slave values are: {}", measure, slaveValues);
  return null;
}

/**
 * Computes the empirical distribution using values from the file
 * in <code>valuesFileURL</code> and <code>binCount</code> bins.
 * <p>
 * <code>valuesFileURL</code> must exist and be readable by this process
 * at runtime.</p>
 * <p>
 * This method must be called before using <code>getNext()</code>
 * with <code>mode = DIGEST_MODE</code></p>
 *
 * @param binCount the number of bins used in computing the empirical
 * distribution
 * @throws IOException if an error occurs reading the input file
 */
public void computeDistribution(int binCount)
    throws IOException {
  empiricalDistribution = new EmpiricalDistributionImpl(binCount);
  empiricalDistribution.load(valuesFileURL);
  mu = empiricalDistribution.getSampleStats().getMean();
  sigma = empiricalDistribution.getSampleStats().getStandardDeviation();
}

/**
 * Computes the empirical distribution using values from the file
 * in <code>valuesFileURL</code> and <code>binCount</code> bins.
 * <p>
 * <code>valuesFileURL</code> must exist and be readable by this process
 * at runtime.</p>
 * <p>
 * This method must be called before using <code>getNext()</code>
 * with <code>mode = DIGEST_MODE</code></p>
 *
 * @param binCount the number of bins used in computing the empirical
 * distribution
 * @throws IOException if an error occurs reading the input file
 */
public void computeDistribution(int binCount)
    throws IOException {
  empiricalDistribution = new EmpiricalDistributionImpl(binCount);
  empiricalDistribution.load(valuesFileURL);
  mu = empiricalDistribution.getSampleStats().getMean();
  sigma = empiricalDistribution.getSampleStats().getStandardDeviation();
}

/**
 * Computes the empirical distribution using values from the file
 * in <code>valuesFileURL</code> and <code>binCount</code> bins.
 * <p>
 * <code>valuesFileURL</code> must exist and be readable by this process
 * at runtime.</p>
 * <p>
 * This method must be called before using <code>getNext()</code>
 * with <code>mode = DIGEST_MODE</code></p>
 *
 * @param binCount the number of bins used in computing the empirical
 * distribution
 * @throws IOException if an error occurs reading the input file
 */
public void computeDistribution(int binCount)
    throws IOException {
  empiricalDistribution = new EmpiricalDistributionImpl(binCount);
  empiricalDistribution.load(valuesFileURL);
  mu = empiricalDistribution.getSampleStats().getMean();
  sigma = empiricalDistribution.getSampleStats().getStandardDeviation();
}

final double sum = s.getSum();
final double mean = s.getMean();
final double standardDeviation = s.getStandardDeviation();
final double variance = s.getVariance();

final double sum = s.getSum();
final double mean = s.getMean();
final double standardDeviation = s.getStandardDeviation();
final double variance = s.getVariance();