Example usage for org.apache.commons.math3.stat.descriptive DescriptiveStatistics getMean

Introduction

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

Prototype

public double getMean() 

Source Link

Document

Returns the <a href="http://www.xycoon.com/arithmetic_mean.htm"> arithmetic mean </a> of the available values

Usage

From source file:org.mskcc.cbio.portal.scripts.ImportProteinArrayData.java

private double[] convertToZscores(String[] strs) {
    double[] data = new double[strs.length - 1];
    boolean nan = false;
    for (int i = 1; i < strs.length; i++) { // ignore the first column
        try {//w  w  w.  j  ava  2  s.  c  om
            data[i - 1] = Double.parseDouble(strs[i]);
        } catch (Exception e) {
            data[i - 1] = Double.NaN;
            nan = true;
        }
    }

    DescriptiveStatistics ds = new DescriptiveStatistics(nan ? copyWithNoNaN(data) : data);
    double mean = ds.getMean();
    double std = ds.getStandardDeviation();

    for (int i = 0; i < data.length; i++) {
        if (!Double.isNaN(data[i])) {
            data[i] = (data[i] - mean) / std;
        }
    }
    return data;
}

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From source file:org.obiba.magma.math.summary.ContinuousVariableSummaryTest.java

@Test
public void test_compute_integerType() {
    Variable mockVariable = Variable.Builder.newVariable("mock", IntegerType.get(), "mock").build();
    ContinuousVariableSummary summary = computeFromTable(mockVariable,
            Values.asValues(IntegerType.get(), 1, 2, 3));
    DescriptiveStatistics descriptiveStats = summary.getDescriptiveStats();
    assertThat(descriptiveStats.getMin()).isEqualTo(1.0);
    assertThat(descriptiveStats.getMax()).isEqualTo(3.0);
    assertThat(descriptiveStats.getMean()).isEqualTo(2.0);
    assertThat(descriptiveStats.getN()).isEqualTo(3l);
}

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From source file:org.obiba.magma.math.summary.ContinuousVariableSummaryTest.java

@Test
public void test_compute_integerTypeWithNull() {
    Variable mockVariable = Variable.Builder.newVariable("mock", IntegerType.get(), "mock").build();
    ContinuousVariableSummary summary = computeFromTable(mockVariable,
            Values.asValues(IntegerType.get(), 1, 2, 3, null, null));
    DescriptiveStatistics descriptiveStats = summary.getDescriptiveStats();
    assertThat(descriptiveStats.getMin()).isEqualTo(1.0);
    assertThat(descriptiveStats.getMax()).isEqualTo(3.0);
    assertThat(descriptiveStats.getMean()).isEqualTo(2.0);
    assertThat(descriptiveStats.getN()).isEqualTo(3l);
}

---

From source file:org.obiba.magma.math.summary.ContinuousVariableSummaryTest.java

@Test
public void test_compute_integerTypeMissingCategories() {
    Variable mockVariable = Variable.Builder.newVariable("mock", IntegerType.get(), "mock")
            .addCategory("888", "", true).addCategory("999", "", true).build();
    ContinuousVariableSummary summary = computeFromTable(mockVariable,
            Values.asValues(IntegerType.get(), 1, 2, 3, 888, 999));
    DescriptiveStatistics descriptiveStats = summary.getDescriptiveStats();
    assertThat(descriptiveStats.getMin()).isEqualTo(1.0);
    assertThat(descriptiveStats.getMax()).isEqualTo(3.0);
    assertThat(descriptiveStats.getMean()).isEqualTo(2.0);
    assertThat(descriptiveStats.getN()).isEqualTo(3l);
}

---

From source file:org.obiba.opal.web.magma.Dtos.java

@SuppressWarnings({ "OverlyLongMethod", "PMD.NcssMethodCount" })
public static Math.ContinuousSummaryDto.Builder asDto(ContinuousVariableSummary summary) {
    DescriptiveStatistics descriptiveStats = summary.getDescriptiveStats();

    Math.DescriptiveStatsDto.Builder descriptiveBuilder = Math.DescriptiveStatsDto.newBuilder()
            .setN(descriptiveStats.getN()).addAllPercentiles(summary.getPercentiles());

    if (isNumeric(descriptiveStats.getMin()))
        descriptiveBuilder.setMin(descriptiveStats.getMin());
    if (isNumeric(descriptiveStats.getMax()))
        descriptiveBuilder.setMax(descriptiveStats.getMax());
    if (isNumeric(descriptiveStats.getMean()))
        descriptiveBuilder.setMean(descriptiveStats.getMean());
    if (isNumeric(descriptiveStats.getSum()))
        descriptiveBuilder.setSum(descriptiveStats.getSum());
    if (isNumeric(descriptiveStats.getSumsq()))
        descriptiveBuilder.setSumsq(descriptiveStats.getSumsq());
    if (isNumeric(descriptiveStats.getStandardDeviation())) {
        descriptiveBuilder.setStdDev(descriptiveStats.getStandardDeviation());
    }//  www .ja  va  2s.c om
    if (isNumeric(descriptiveStats.getVariance()))
        descriptiveBuilder.setVariance(descriptiveStats.getVariance());
    if (isNumeric(descriptiveStats.getSkewness()))
        descriptiveBuilder.setSkewness(descriptiveStats.getSkewness());
    if (isNumeric(descriptiveStats.getGeometricMean())) {
        descriptiveBuilder.setGeometricMean(descriptiveStats.getGeometricMean());
    }
    if (isNumeric(descriptiveStats.getKurtosis()))
        descriptiveBuilder.setKurtosis(descriptiveStats.getKurtosis());
    double median = descriptiveStats.apply(new Median());
    if (isNumeric(median))
        descriptiveBuilder.setMedian(median);
    if (isNumeric(descriptiveStats.getVariance()))
        descriptiveBuilder.setVariance(descriptiveStats.getVariance());

    Math.ContinuousSummaryDto.Builder continuousBuilder = Math.ContinuousSummaryDto.newBuilder()
            .addAllDistributionPercentiles(summary.getDistributionPercentiles());
    for (IntervalFrequency.Interval interval : summary.getIntervalFrequencies()) {
        Math.IntervalFrequencyDto.Builder freqBuilder = Math.IntervalFrequencyDto.newBuilder()
                .setFreq(interval.getFreq());
        if (isNumeric(interval.getLower()))
            freqBuilder.setLower(interval.getLower());
        if (isNumeric(interval.getUpper()))
            freqBuilder.setUpper(interval.getUpper());
        if (isNumeric(interval.getDensity()))
            freqBuilder.setDensity(interval.getDensity());
        if (isNumeric(interval.getDensityPct()))
            freqBuilder.setDensityPct(interval.getDensityPct());
        continuousBuilder.addIntervalFrequency(freqBuilder);
    }

    for (ContinuousVariableSummary.Frequency frequency : summary.getFrequencies()) {
        Math.FrequencyDto.Builder freqBuilder = Math.FrequencyDto.newBuilder() //
                .setValue(frequency.getValue()) //
                .setFreq(frequency.getFreq())//
                .setMissing(frequency.isMissing());
        if (isNumeric(frequency.getPct()))
            freqBuilder.setPct(frequency.getPct());
        continuousBuilder.addFrequencies(freqBuilder);
    }

    return continuousBuilder.setSummary(descriptiveBuilder);
}

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From source file:org.onosproject.store.cluster.impl.PhiAccrualFailureDetector.java

private double computePhi(DescriptiveStatistics samples, long tLast, long tNow) {
    long size = samples.getN();
    long t = tNow - tLast;
    return (size > 0) ? PHI_FACTOR * t / samples.getMean() : BOOTSTRAP_PHI_VALUE;
}

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From source file:org.orbisgis.view.toc.actions.cui.legend.stats.Thresholds.java

/**
 * This method ://from   ww w .j ava2s  .c  o m
 * - Feeds the given SortedSet with the mean of the given statistics.
 * - Calls itself recursively on the two subset obtained by dividing the set around its mean, if lev > 0.
 * @param inpStat The input statistics
 * @param toFeed The SortedSet we want to feed
 * @param lev The remaining number of levels we have to process.
 */
private void computeBoxedMeans(DescriptiveStatistics inpStat, SortedSet<Double> toFeed, int lev) {
    double[] input = inpStat.getSortedValues();
    double mean = inpStat.getMean();
    toFeed.add(mean);
    if (lev > 0) {
        int i = Arrays.binarySearch(input, mean);
        int ind = i < 0 ? -i - 1 : i;
        double[] first = Arrays.copyOf(input, ind);
        double[] tail = Arrays.copyOfRange(input, ind, input.length);
        computeBoxedMeans(new DescriptiveStatistics(first), toFeed, lev - 1);
        computeBoxedMeans(new DescriptiveStatistics(tail), toFeed, lev - 1);
    }
}

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From source file:org.uma.jmetal.util.experiment.component.GenerateLatexTablesWithStatistics.java

/**
 * Computes the statistical values//from   w w  w  .ja v a  2s .c  om
 * @param values
 * @return
 */
private Map<String, Double> computeStatistics(List<Double> values) {
    Map<String, Double> results = new HashMap<>();

    DescriptiveStatistics stats = new DescriptiveStatistics();
    for (Double value : values) {
        stats.addValue(value);
    }

    results.put("mean", stats.getMean());
    results.put("median", stats.getPercentile(50.0));
    results.put("stdDeviation", stats.getStandardDeviation());
    results.put("iqr", stats.getPercentile(75) - stats.getPercentile(25));
    results.put("max", stats.getMax());
    results.put("min", stats.getMean());
    results.put("numberOfElements", (double) values.size());

    return results;
}

---

From source file:org.wattdepot.client.http.api.performance.GetDateValueThroughput.java

/**
 * @param stats the DescriptiveStatistics to calculate the mean put time.
 * @return The estimated put rate based upon the time it takes to put a single
 *         measurement./* ww  w .  j  av a2s  .  c o m*/
 */
private Long calculateGetRate(DescriptiveStatistics stats) {
    double putTime = stats.getMean();
    Long ret = null;
    double numPuts = 1.0 / putTime;
    ret = Math.round(numPuts);
    return ret;
}

---

From source file:org.wattdepot.client.http.api.performance.PutThroughput.java

/**
 * @param stats the DescriptiveStatistics to calculate the mean put time.
 * @return The estimated put rate based upon the time it takes to put a single
 *         measurement.// w w w. jav a 2s  . c o  m
 */
private Long calculatePutRate(DescriptiveStatistics stats) {
    double putTime = stats.getMean();
    Long ret = null;
    double numPuts = 1.0 / putTime;
    ret = Math.round(numPuts);
    return ret;
}

---

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