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:io.hops.experiments.results.compiler.RawBMResultAggregator.java

public static RawBMResults processSlaveResponses(Collection<Object> responses,
        RawBenchmarkCommand.Request request, Configuration args) {
    DescriptiveStatistics successfulOps = new DescriptiveStatistics();
    DescriptiveStatistics failedOps = new DescriptiveStatistics();
    DescriptiveStatistics speed = new DescriptiveStatistics();
    DescriptiveStatistics duration = new DescriptiveStatistics();
    DescriptiveStatistics noOfAliveNNs = new DescriptiveStatistics();
    for (Object obj : responses) {
        if (!(obj instanceof RawBenchmarkCommand.Response) || (obj instanceof RawBenchmarkCommand.Response
                && ((RawBenchmarkCommand.Response) obj).getPhase() != request.getPhase())) {
            throw new IllegalStateException("Wrong response received from the client");
        } else {//from  w w  w. j av a 2  s  . c o  m
            RawBenchmarkCommand.Response response = (RawBenchmarkCommand.Response) obj;
            successfulOps.addValue(response.getTotalSuccessfulOps());
            failedOps.addValue(response.getTotalFailedOps());
            speed.addValue(response.getOpsPerSec());
            duration.addValue(response.getRunTime());
            noOfAliveNNs.addValue(response.getNnCount());
        }
    }

    RawBMResults result = new RawBMResults(args.getNamenodeCount(), (int) Math.floor(noOfAliveNNs.getMean()),
            args.getNdbNodesCount(), request.getPhase(),
            (successfulOps.getSum() / ((duration.getMean() / 1000))), (duration.getMean() / 1000),
            (successfulOps.getSum()), (failedOps.getSum()));
    return result;
}

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From source file:azkaban.metric.inmemoryemitter.InMemoryMetricEmitter.java

/**
 * filter snapshots using statistically significant points only
 * @param selectedLists list of snapshots
 *///from   w w w.  j ava2 s. c om
private void statBasedSelectMetricHistory(final LinkedList<InMemoryHistoryNode> selectedLists)
        throws ClassCastException {
    logger.debug("selecting snapshots which are far away from mean value");
    DescriptiveStatistics descStats = getDescriptiveStatistics(selectedLists);
    Double mean = descStats.getMean();
    Double std = descStats.getStandardDeviation();

    Iterator<InMemoryHistoryNode> ite = selectedLists.iterator();
    while (ite.hasNext()) {
        InMemoryHistoryNode currentNode = ite.next();
        double value = ((Number) currentNode.getValue()).doubleValue();
        // remove all elements which lies in 95% value band
        if (value < mean + standardDeviationFactor * std && value > mean - standardDeviationFactor * std) {
            ite.remove();
        }
    }
}

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From source file:io.atomix.cluster.impl.PhiAccrualFailureDetector.java

/**
 * Computes the phi value from the given samples.
 * <p>//from w w w.j  a va 2  s .  c om
 * The original phi value in Hayashibara's paper is calculated based on a normal distribution.
 * Here, we calculate it based on an exponential distribution.
 *
 * @param samples       the samples from which to compute phi
 * @param lastHeartbeat the last heartbeat
 * @param currentTime   the current time
 * @return phi
 */
private double computePhi(DescriptiveStatistics samples, long lastHeartbeat, long currentTime) {
    long size = samples.getN();
    long t = currentTime - lastHeartbeat;
    return (size > 0) ? phiFactor * t / samples.getMean() : 100;
}

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

public void exportResults(Path outputDir, ResultExporter exporter) throws IOException {
    Function<Double, String> format = number -> String.format(Locale.US, "%.3f", number);
    exporter.export(outputDir.resolve("TimeStatistics.txt"),
            analysisStatistics.entrySet().stream().map(entry -> {
                DescriptiveStatistics stats = entry.getValue();
                return new String[] { entry.getKey(), format.apply(stats.getMin()),
                        format.apply(stats.getStandardDeviation()), format.apply(stats.getMean()),
                        format.apply(stats.getMax()) };
            }));/*from   w w  w .j av a  2  s  . c  om*/
    exporter.export(outputDir.resolve("StmtCountTimes.txt"),
            analysisTimes.stream()
                    .map(entry -> new String[] { entry.analysisName, entry.contextType.getFullName(),
                            Integer.toString(entry.numStmts), format.apply(entry.time) }));
}

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

private void writeStats(BufferedWriter writer, String transaction, String[] columns, File depthDir, int key)
        throws IOException {

    writer.write(key + " ");

    for (String cache : RESOLVING_CACHES) {
        File cacheDir = new File(depthDir, cache);
        Map<String, DescriptiveStatistics> stats = null;
        Map<String, DescriptiveStatistics> statsResolving = null;
        if (cacheDir.exists()) {
            stats = TransactionStatsAggregator.aggregate(new File(cacheDir, HOPSSTATS), transaction);
        }//from www  . j  a  v  a2s.  c  o  m

        if (isResolvingCache(cache)) {
            statsResolving = TransactionStatsAggregator.aggregate(new File(cacheDir, RESOLVING_CACHE_STATS),
                    "GET");
        }

        if (stats != null) {
            for (String col : columns) {
                DescriptiveStatistics st = stats.get(col);
                writer.write(st.getMin() + " " + st.getMean() + " " + st.getMax() + " ");
            }
        }

        if (statsResolving != null) {
            for (String col : RESOLVING_CACHE_COLUMNS) {
                DescriptiveStatistics st = statsResolving.get(col);
                writer.write(st.getMin() + " " + st.getMean() + " " + st.getMax() + " ");
            }
        }
    }

    writer.newLine();
}

---

From source file:io.yields.math.framework.DomainTest.java

@Explore(name = "Test Variable Distribution", dataProvider = DataProviders.FixedMersenneTwisterDataProvider.class)
@Exploration(name = "Test Function", context = FunctionExplorerContext.class, group = "domain")
public void testVariableDistribution(Explorer<Double> explorer) {

    assertThat(explorer.all().count()).isEqualTo(explorer.valid().count());
    assertThat(explorer.valid().count()).isEqualTo(explorer.valid().count());
    assertThat(explorer.invalid().count()).isEqualTo(0);
    assertThat(explorer.propertyError().count()).isEqualTo(0);

    DescriptiveStatistics stats = new DescriptiveStatistics();
    explorer.all().forEach(result -> stats.addValue(result.getFunctionOutcome().orElse(0d)));

    assertThat(stats.getMean()).isEqualTo(0, delta(0.1));
    assertThat(stats.getMax()).isEqualTo(1, delta(0.1));
    assertThat(stats.getMin()).isEqualTo(-1, delta(0.1));
}

---

From source file:io.yields.math.framework.DomainTest.java

@Explore(name = "Test Variable Distribution with multiple properties", dataProvider = DataProviders.FixedMersenneTwisterDataProvider.class)
@Exploration(name = "Test Function", context = FunctionExplorerMultiplePropertiesContext.class, group = "domain")
public void testVariableDistributionMultipleProperties(Explorer<Double> explorer) {

    assertThat(explorer.all().count()).isEqualTo(explorer.valid().count());
    assertThat(explorer.valid().count()).isEqualTo(explorer.valid().count());
    assertThat(explorer.invalid().count()).isEqualTo(0);
    assertThat(explorer.propertyError().count()).isEqualTo(0);

    DescriptiveStatistics stats = new DescriptiveStatistics();
    explorer.all().forEach(result -> stats.addValue(result.getFunctionOutcome().orElse(0d)));

    assertThat(stats.getMean()).isEqualTo(0, delta(0.1));
    assertThat(stats.getMax()).isEqualTo(1, delta(0.1));
    assertThat(stats.getMin()).isEqualTo(-1, delta(0.1));
}

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From source file:io.realm.datastorebenchmark.DataStoreTest.java

public void saveMeasurements(String filePrefix) {
    String tag = getTag();/* w ww .  j av  a  2  s.co m*/
    try {
        // one file per test with raw data
        for (String key : keys) {
            File file1 = new File(Environment.getExternalStorageDirectory() + "/datastorebenchmark",
                    tag + "_" + key + ".csv");
            FileOutputStream fileOutputStream1 = new FileOutputStream(file1, false);
            List<Long> measurement = measurements.get(key);
            for (int i = 0; i < measurement.size(); i++) {
                fileOutputStream1.write(String.format("%d\n", measurement.get(i).longValue()).getBytes());
            }
            fileOutputStream1.close();
        }

        // combined CSV file
        File file = new File(Environment.getExternalStorageDirectory() + "/datastorebenchmark",
                filePrefix + ".csv");
        FileOutputStream fileOutputStream = new FileOutputStream(file, true);
        fileOutputStream.write(String.format("%s;", tag).getBytes());
        for (String key : keys) {
            List<Long> measurement = measurements.get(key);
            double[] doubles = new double[measurement.size()];
            for (int i = 0; i < measurement.size(); i++) {
                doubles[i] = measurement.get(i).doubleValue();
            }
            Collections.sort(measurement);
            DescriptiveStatistics results = new DescriptiveStatistics(doubles);
            fileOutputStream.write(String
                    .format("%e;%e;%e;", results.getMin(), results.getMax(), results.getMean()).getBytes());
        }
        fileOutputStream.write("\n".getBytes());
        fileOutputStream.close();
    } catch (Exception e) {
        e.printStackTrace();
    }
}

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From source file:mase.app.allocation.AllocationProblem.java

@Override
public EvaluationResult[] evaluateSolution(GroupController gc, long seed) {
    AgentController[] acs = gc.getAgentControllers(numAgents);
    RealMatrix distanceMatrix = new Array2DRowRealMatrix(numAgents, types.length);
    for (int i = 0; i < numAgents; i++) {
        AllocationAgent aa = (AllocationAgent) acs[i];
        for (int j = 0; j < types.length; j++) {
            distanceMatrix.setEntry(i, j, DIST.compute(aa.getLocation(), types[j]));
        }/*www.  ja  v  a  2 s  .  c  o  m*/
    }

    DescriptiveStatistics pd = pairDistances(distanceMatrix);

    // fitness
    FitnessResult fr = new FitnessResult(1 - pd.getMean() / FastMath.sqrt(dimensions));

    // individual characterisation -- distance to each type
    List<EvaluationResult> vbrs = new ArrayList<>();
    for (double[] dists : distanceMatrix.getData()) {
        vbrs.add(new VectorBehaviourResult(dists));
    }
    CompoundEvaluationResult ser = new CompoundEvaluationResult(vbrs);

    // aux characterisation -- min, mean, max, sd pair distances
    VectorBehaviourResult aux = new VectorBehaviourResult(pd.getMin(), pd.getMean(), pd.getMax(),
            pd.getStandardDeviation());

    return new EvaluationResult[] { fr, aux, ser };
}

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From source file:io.yields.math.framework.DomainTest.java

@Explore(name = "Multiple Explorations", dataProvider = DataProviders.FixedMersenneTwisterDataProvider.class)
@Exploration(name = "Test Function", context = FunctionExplorerContext.class, group = "domain")
@Exploration(name = "Test Function 2", context = Function2ExplorerContext.class, group = "domain")
public void testMultipleExplorations(List<Explorer<Double>> explorers) {

    for (Explorer<Double> explorer : explorers) {

        assertThat(explorer.all().count()).isEqualTo(explorer.valid().count());
        assertThat(explorer.invalid().count()).isEqualTo(0);
        assertThat(explorer.propertyError().count()).isEqualTo(0);

        DescriptiveStatistics stats = new DescriptiveStatistics();
        explorer.all().forEach(result -> stats.addValue(result.getFunctionOutcome().orElse(0d)));

        assertThat(stats.getMean()).isEqualTo(0, delta(0.1));
        assertThat(stats.getMax()).isEqualTo(1, delta(0.1));
        assertThat(stats.getMin()).isEqualTo(-1, delta(0.1));

    }//from w  ww.j a  v a 2  s.  c om

    // compare 2 explorers
    Explorer<Double> firstExplorer = explorers.get(0);
    Explorer<Double> secondExplorer = explorers.get(1);

    List<PropertyVerifications<Double>> resultsOfFirstExplorer = firstExplorer.all()
            .collect(Collectors.toList());
    List<PropertyVerifications<Double>> resultsOfSecondExplorer = secondExplorer.all()
            .collect(Collectors.toList());

    for (int i = 0; i < resultsOfFirstExplorer.size(); i++) {
        assertThat(resultsOfFirstExplorer.get(i).getFunctionOutcome().orElse(0d))
                .isEqualTo(resultsOfSecondExplorer.get(i).getFunctionOutcome().orElse(0d), delta(2d));
    }

}

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