Example usage for org.apache.commons.math.stat.descriptive StatisticalSummary getStandardDeviation

Introduction

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

Prototype

double getStandardDeviation();

Source Link

Document

Returns the standard deviation of the available values.

Usage

From source file:org.datacleaner.beans.NumberAnalyzer.java

@Override
public NumberAnalyzerResult getResult() {
    CrosstabDimension measureDimension = new CrosstabDimension(DIMENSION_MEASURE);
    measureDimension.addCategory(MEASURE_ROW_COUNT);
    measureDimension.addCategory(MEASURE_NULL_COUNT);
    measureDimension.addCategory(MEASURE_HIGHEST_VALUE);
    measureDimension.addCategory(MEASURE_LOWEST_VALUE);
    measureDimension.addCategory(MEASURE_SUM);
    measureDimension.addCategory(MEASURE_MEAN);
    measureDimension.addCategory(MEASURE_GEOMETRIC_MEAN);
    measureDimension.addCategory(MEASURE_STANDARD_DEVIATION);
    measureDimension.addCategory(MEASURE_VARIANCE);
    measureDimension.addCategory(MEASURE_SECOND_MOMENT);
    measureDimension.addCategory(MEASURE_SUM_OF_SQUARES);

    if (descriptiveStatistics) {
        measureDimension.addCategory(MEASURE_MEDIAN);
        measureDimension.addCategory(MEASURE_PERCENTILE25);
        measureDimension.addCategory(MEASURE_PERCENTILE75);
        measureDimension.addCategory(MEASURE_SKEWNESS);
        measureDimension.addCategory(MEASURE_KURTOSIS);
    }/*from  w  w  w . j a  va2 s .  co  m*/

    CrosstabDimension columnDimension = new CrosstabDimension(DIMENSION_COLUMN);
    for (InputColumn<? extends Number> column : _columns) {
        columnDimension.addCategory(column.getName());
    }

    Crosstab<Number> crosstab = new Crosstab<Number>(Number.class, columnDimension, measureDimension);
    for (InputColumn<? extends Number> column : _columns) {
        CrosstabNavigator<Number> nav = crosstab.navigate().where(columnDimension, column.getName());
        NumberAnalyzerColumnDelegate delegate = _columnDelegates.get(column);

        StatisticalSummary s = delegate.getStatistics();
        int nullCount = delegate.getNullCount();

        nav.where(measureDimension, MEASURE_NULL_COUNT).put(nullCount);

        if (nullCount > 0) {
            addAttachment(nav, delegate.getNullAnnotation(), column);
        }

        int numRows = delegate.getNumRows();
        nav.where(measureDimension, MEASURE_ROW_COUNT).put(numRows);

        long nonNullCount = s.getN();

        if (nonNullCount > 0) {
            final double highestValue = s.getMax();
            final double lowestValue = s.getMin();
            final double sum = s.getSum();
            final double mean = s.getMean();
            final double standardDeviation = s.getStandardDeviation();
            final double variance = s.getVariance();

            final double geometricMean;
            final double secondMoment;
            final double sumOfSquares;
            if (descriptiveStatistics) {
                final DescriptiveStatistics descriptiveStats = (DescriptiveStatistics) s;
                geometricMean = descriptiveStats.getGeometricMean();
                sumOfSquares = descriptiveStats.getSumsq();
                secondMoment = new SecondMoment().evaluate(descriptiveStats.getValues());
            } else {
                final SummaryStatistics summaryStats = (SummaryStatistics) s;
                geometricMean = summaryStats.getGeometricMean();
                secondMoment = summaryStats.getSecondMoment();
                sumOfSquares = summaryStats.getSumsq();
            }

            nav.where(measureDimension, MEASURE_HIGHEST_VALUE).put(highestValue);
            addAttachment(nav, delegate.getMaxAnnotation(), column);

            nav.where(measureDimension, MEASURE_LOWEST_VALUE).put(lowestValue);
            addAttachment(nav, delegate.getMinAnnotation(), column);

            nav.where(measureDimension, MEASURE_SUM).put(sum);
            nav.where(measureDimension, MEASURE_MEAN).put(mean);
            nav.where(measureDimension, MEASURE_GEOMETRIC_MEAN).put(geometricMean);
            nav.where(measureDimension, MEASURE_STANDARD_DEVIATION).put(standardDeviation);
            nav.where(measureDimension, MEASURE_VARIANCE).put(variance);
            nav.where(measureDimension, MEASURE_SUM_OF_SQUARES).put(sumOfSquares);
            nav.where(measureDimension, MEASURE_SECOND_MOMENT).put(secondMoment);

            if (descriptiveStatistics) {
                final DescriptiveStatistics descriptiveStatistics = (DescriptiveStatistics) s;
                final double kurtosis = descriptiveStatistics.getKurtosis();
                final double skewness = descriptiveStatistics.getSkewness();
                final double median = descriptiveStatistics.getPercentile(50.0);
                final double percentile25 = descriptiveStatistics.getPercentile(25.0);
                final double percentile75 = descriptiveStatistics.getPercentile(75.0);

                nav.where(measureDimension, MEASURE_MEDIAN).put(median);
                nav.where(measureDimension, MEASURE_PERCENTILE25).put(percentile25);
                nav.where(measureDimension, MEASURE_PERCENTILE75).put(percentile75);
                nav.where(measureDimension, MEASURE_SKEWNESS).put(skewness);
                nav.where(measureDimension, MEASURE_KURTOSIS).put(kurtosis);
            }
        }
    }
    return new NumberAnalyzerResult(_columns, crosstab);
}

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From source file:org.datacleaner.beans.NumberAnalyzerResultReducer.java

@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();
    }// w ww.j av  a  2 s .c om

    logger.warn("Encountered non-reduceable measure '{}'. Slave values are: {}", measure, slaveValues);
    return null;
}

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