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

Introduction

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

Prototype

public DescriptiveStatistics() 

Source Link

Document

Construct a DescriptiveStatistics instance with an infinite window

Usage

From source file:com.screenslicer.core.util.StringUtil.java

public static void trimLargeItems(int[] stringLengths, List<? extends Object> originals) {
    DescriptiveStatistics stats = new DescriptiveStatistics();
    for (int i = 0; i < stringLengths.length; i++) {
        stats.addValue(stringLengths[i]);
    }/*from w ww. j av a  2  s  . com*/
    double stdDev = stats.getStandardDeviation();
    double mean = stats.getMean();
    List<Object> toRemove = new ArrayList<Object>();
    for (int i = 0; i < stringLengths.length; i++) {
        double diff = stringLengths[i] - mean;
        if (diff / stdDev > 4d) {
            toRemove.add(originals.get(i));
        }
    }
    for (Object obj : toRemove) {
        originals.remove(obj);
    }
}

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From source file:io.hops.experiments.stats.TransactionStatsAggregator.java

public static Map<String, DescriptiveStatistics> aggregate(File statsFile, String headerPattern,
        String transaction, boolean printSummary) throws IOException {
    if (!statsFile.exists())
        return null;

    transaction = transaction.toUpperCase();

    BufferedReader reader = new BufferedReader(new FileReader(statsFile));
    String tx = reader.readLine();
    String[] headers = null;/* w  w w. ja  v a2 s  .c  o  m*/
    Map<Integer, DescriptiveStatistics> statistics = Maps.newHashMap();
    if (tx != null) {
        headers = tx.split(",");
        for (int i = 1; i < headers.length; i++) {
            String h = headers[i].toUpperCase();
            if (h.contains(headerPattern) || headerPattern.equals(ALL)) {
                statistics.put(i, new DescriptiveStatistics());
            }
        }
    }

    int txCount = 0;
    while ((tx = reader.readLine()) != null) {
        if (tx.startsWith(transaction) || transaction.equals(ALL)) {
            txCount++;
            String[] txStats = tx.split(",");
            if (txStats.length == headers.length) {
                for (Map.Entry<Integer, DescriptiveStatistics> e : statistics.entrySet()) {
                    e.getValue().addValue(Double.valueOf(txStats[e.getKey()]));
                }
            }
        }
    }

    reader.close();

    if (headers == null)
        return null;

    if (printSummary) {
        System.out.println("Transaction: " + transaction + " " + txCount);

        List<Integer> keys = new ArrayList<Integer>(statistics.keySet());
        Collections.sort(keys);

        for (Integer i : keys) {
            DescriptiveStatistics stats = statistics.get(i);
            if (stats.getMin() == 0 && stats.getMax() == 0) {
                continue;
            }
            System.out.println(headers[i]);
            System.out.println("Min " + stats.getMin() + " Max " + stats.getMax() + " Avg " + stats.getMean()
                    + " Std " + stats.getStandardDeviation());
        }
    }

    Map<String, DescriptiveStatistics> annotatedStats = Maps.newHashMap();
    for (Map.Entry<Integer, DescriptiveStatistics> e : statistics.entrySet()) {
        annotatedStats.put(headers[e.getKey()].trim(), e.getValue());
    }
    return annotatedStats;
}

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From source file:com.intuit.tank.persistence.databases.BucketDataItemTest.java

/**
 * Run the Date getStartTime() method test.
 * /*  w  w w.j a  va2s . c om*/
 * @throws Exception
 * 
 * @generatedBy CodePro at 9/10/14 10:32 AM
 */
@Test
public void testGetStartTime_1() throws Exception {
    BucketDataItem fixture = new BucketDataItem(1, new Date(), new DescriptiveStatistics());

    Date result = fixture.getStartTime();

    assertNotNull(result);
}

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From source file:fr.inria.eventcloud.benchmarks.performance_tuning.QuadrupleStatsAnalyzer.java

public QuadrupleStatsAnalyzer() {
    this.graphLength = new DescriptiveStatistics();
    this.subjectLength = new DescriptiveStatistics();
    this.predicateLength = new DescriptiveStatistics();
    this.objectLength = new DescriptiveStatistics();

    this.quadsLength = new DescriptiveStatistics();
    // SummaryStatistics
}

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From source file:io.yields.math.concepts.operator.Smoothness.java

@Override
public DescriptiveStatistics apply(Collection<Tuple> tuples) {
    Validate.isTrue(tuples.size() > order);
    //first we normalize the tuples so data fits in the unit square
    List<Tuple> normalizedData = normalize(tuples);
    //calculate error (i.e. distance between tuple y and fitted polynomial
    RealMatrix error = computeDistance(normalizedData);
    //group in stats object
    DescriptiveStatistics stats = new DescriptiveStatistics();
    for (double value : error.getColumn(0)) {
        stats.addValue(Math.abs(value));
    }//ww  w.ja  va2 s .  c  om
    return stats;
}

---

From source file:cz.cuni.mff.d3s.tools.perfdoc.server.measuring.statistics.Statistics.java

public long computeMean() {
    if (measurementResults.isEmpty()) {
        return -1;
    }//from   w ww.  jav  a 2s .c o  m

    DescriptiveStatistics stats = new DescriptiveStatistics();
    for (Long l : measurementResults) {
        stats.addValue(l);
    }

    return (long) stats.getPercentile(50);
}

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From source file:com.soulgalore.web.pagesavings.googlepagespeed.GooglePageSpeedSavingsCollector.java

@Inject
public GooglePageSpeedSavingsCollector(HTTPBodyFetcher fetcher, SiteResultCollector siteResultCollector,
        @Named("com.soulgalore.web.savings.googlekey") String key) {
    this.fetcher = fetcher;
    this.siteResultCollector = siteResultCollector;
    this.key = key;

    for (String rule : GooglePageSpeedSiteResultCollector.RULES) {
        statistics.put(rule, new DescriptiveStatistics());
    }// ww  w .j a v a  2 s  .  c o  m

}

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From source file:com.caseystella.analytics.outlier.streaming.mad.SketchyMovingMADTest.java

@Test
public void testSketchyMovingMAD() throws IOException {
    Random r = new Random(0);
    List<DataPoint> points = new ArrayList<>();
    DescriptiveStatistics stats = new DescriptiveStatistics();
    DescriptiveStatistics medianStats = new DescriptiveStatistics();
    OutlierConfig config = JSONUtil.INSTANCE.load(madConfig, OutlierConfig.class);
    SketchyMovingMAD madAlgo = ((SketchyMovingMAD) config.getSketchyOutlierAlgorithm()).withConfig(config);
    int i = 0;/*from ww w . j av  a 2s. co  m*/
    for (i = 0; i < 10000; ++i) {
        double val = r.nextDouble() * 1000 - 10000;
        stats.addValue(val);
        DataPoint dp = (new DataPoint(i, val, null, "foo"));
        madAlgo.analyze(dp);
        points.add(dp);
    }
    for (DataPoint dp : points) {
        medianStats.addValue(Math.abs(dp.getValue() - stats.getPercentile(50)));
    }
    double mad = medianStats.getPercentile(50);
    double median = stats.getPercentile(50);
    {
        double val = getValAtModifiedZScore(3.6, mad, median);
        System.out.println("MODERATE => " + val);
        DataPoint dp = (new DataPoint(i++, val, null, "foo"));
        Severity s = madAlgo.analyze(dp).getSeverity();
        Assert.assertTrue(s == Severity.MODERATE_OUTLIER);
    }
    {
        double val = getValAtModifiedZScore(6, mad, median);
        System.out.println("SEVERE => " + val);
        DataPoint dp = (new DataPoint(i++, val, null, "foo"));
        Severity s = madAlgo.analyze(dp).getSeverity();
        Assert.assertTrue(s == Severity.SEVERE_OUTLIER);
    }

    Assert.assertTrue(madAlgo.getMedianDistributions().get("foo").getAmount() <= 110);
    Assert.assertTrue(madAlgo.getMedianDistributions().get("foo").getChunks().size() <= 12);
}

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From source file:cc.redberry.core.tensor.BulkTestsForParser.java

@Test
public void testAllExpressionsInTestDirectory() {
    File testDirectory = new File("src/test");
    Counter c = new Counter(), m = new Counter();
    DescriptiveStatistics statistics = new DescriptiveStatistics();
    testParseRecurrently(testDirectory, c, m, statistics);
    System.out.println("Total number of lines containing parse(..): " + c.counter);
    System.out.println("Total number of matched and parsed lines: " + m.counter);
    System.out.println("Strings statistics: \n\t" + statistics.toString().replace("\n", "\n\t"));
    Assert.assertTrue((c.counter - m.counter) < 2);
}

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From source file:cc.kave.commons.pointsto.evaluation.PointsToSetEvaluation.java

public void run(Path contextsDir) throws IOException {
    StatementCounterVisitor stmtCounterVisitor = new StatementCounterVisitor();
    List<Context> contexts = getSamples(contextsDir).stream()
            .filter(cxt -> cxt.getSST().accept(stmtCounterVisitor, null) > 0).collect(Collectors.toList());
    log("Using %d contexts for evaluation\n", contexts.size());

    PointsToUsageExtractor extractor = new PointsToUsageExtractor();
    for (Context context : contexts) {
        PointstoSetSizeAnalysis analysis = new PointstoSetSizeAnalysis();
        extractor.extract(analysis.compute(context));
        results.addAll(analysis.getSetSizes());
    }/*from www. ja v  a  2s .c o  m*/

    DescriptiveStatistics statistics = new DescriptiveStatistics();
    for (Integer setSize : results) {
        statistics.addValue(setSize.doubleValue());
    }
    log("mean: %.2f\n", statistics.getMean());
    log("stddev: %.2f\n", statistics.getStandardDeviation());
    log("min/max: %.2f/%.2f\n", statistics.getMin(), statistics.getMax());
}

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