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

Introduction

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

Prototype

public double getMax() 

Source Link

Document

Returns the maximum of the available values

Usage

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

@Spec(name = "linear data - quadraticSmoothness", functional = SmoothnessTest.LinearData.class)
public void testLinearData_quadraticSmoothness(FunctionalContext<List<Tuple>> context) {
    //second order matching as well
    DescriptiveStatistics stats = new Smoothness(2).apply(context.evaluate());
    assertThat(stats.getMin()).isEqualTo(stats.getMax(), Delta.delta(1.e-8)).isEqualTo(0d, Delta.delta(1.e-8));
}

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

@Spec(name = "quadratic data - quadratic smoothness", functional = SmoothnessTest.QuadraticData.class)
public void testQuadraticCase_quadraticSmoothness(FunctionalContext<List<Tuple>> context) {
    //second order matching as well
    DescriptiveStatistics stats = new Smoothness(2).apply(context.evaluate());
    assertThat(stats.getMin()).isEqualTo(stats.getMax(), Delta.delta(1.e-8)).isEqualTo(0d, Delta.delta(1.e-8));
}

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

public void saveMeasurements(String filePrefix) {
    String tag = getTag();/*w w w  .jav  a  2s  . com*/
    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:com.soulgalore.web.pagesavings.reporters.SystemOutReporter.java

public void report(Set<SiteResult> results, Map<String, DescriptiveStatistics> statistics) {

    Double totalPw = 0D;//from w ww  .  j a  v  a 2 s  .com
    Double totalUnique = 0D;
    for (SiteResult siteResult : results) {
        totalPw += siteResult.getTotalSavings() * siteResult.getSite().getPageViews();
        totalUnique += siteResult.getTotalSavings() * siteResult.getSite().getUniqueBrowsers();
        System.out.println("-------------------------------------");
        System.out.println(siteResult.getSite().getUrl() + " saved per page: "
                + humanReadableByteCount(Math.round(siteResult.getTotalSavings()), true) + " pw:"
                + humanReadableByteCount(
                        Math.round(siteResult.getTotalSavings() * siteResult.getSite().getPageViews()), true)
                + " unique:"
                + humanReadableByteCount(
                        Math.round(siteResult.getTotalSavings() * siteResult.getSite().getUniqueBrowsers()),
                        true));
        System.out.println("Total page size:" + siteResult.getTotalSizeBytes() / 1000 + " kb");
        for (RuleResult ruleResult : siteResult.getResults()) {
            System.out.println(ruleResult.getRule() + " " + ruleResult.getSavings() + " kb");
        }

    }

    System.out.println("-------------------------------------");
    System.out.println("Tested " + results.size() + " sites");
    System.out
            .println("total pw:" + humanReadableByteCount(Math.round(totalPw), true) + " or in kb " + totalPw);
    System.out.println("total unique:" + humanReadableByteCount(Math.round(totalUnique), true) + " or in kb "
            + totalUnique);

    for (String rule : statistics.keySet()) {
        DescriptiveStatistics stats = statistics.get(rule);
        System.out.println(rule + " median save:" + stats.getPercentile(50) + "  max save:" + stats.getMax());
    }

    List<SiteResult> toplist = new ArrayList<SiteResult>();
    toplist.addAll(results);
    Collections.sort(toplist);

    System.out.println("-------------------------------------");
    System.out.println("TopList (kb):");

    for (int i = 0; i < (toplist.size() < TOPLIST_ITEMS ? toplist.size() : TOPLIST_ITEMS); i++)
        System.out.println(toplist.get(i).getSite().getUrl() + " "
                + Math.round(toplist.get(i).getTotalSavings() * 100) / 100.0d);

    System.out.println("-------------------------------------");
    System.out.println("BottomList (kb):");

    for (int i = 1; i < (toplist.size() < TOPLIST_ITEMS ? toplist.size() : TOPLIST_ITEMS) + 1; i++)
        System.out.println(toplist.get(toplist.size() - i).getSite().getUrl() + " "
                + Math.round(toplist.get(toplist.size() - i).getTotalSavings() * 100) / 100.0d);

    Collections.sort(toplist, new SavingsPercentageComparator());

    System.out.println("-------------------------------------");
    System.out.println("TopList %:");
    for (int i = 0; i < (toplist.size() < TOPLIST_ITEMS ? toplist.size() : TOPLIST_ITEMS); i++)
        System.out.println(toplist.get(i).getSite().getUrl() + " "
                + Math.round(toplist.get(i).getSavingsPercentage() * 100) / 100.0d);

    System.out.println("-------------------------------------");
    System.out.println("BottomList %:");

    for (int i = 1; i < (toplist.size() < TOPLIST_ITEMS ? toplist.size() : TOPLIST_ITEMS) + 1; i++)
        System.out.println(toplist.get(toplist.size() - i).getSite().getUrl() + " "
                + Math.round(toplist.get(toplist.size() - i).getSavingsPercentage() * 100) / 100.0d);

    System.out.println("-------------------------------------");
    System.out.println("TopList most savings:");
    Collections.sort(toplist, new TotalSavingsComparator());
    for (int i = 1; i < (toplist.size() < TOPLIST_ITEMS ? toplist.size() : TOPLIST_ITEMS) + 1; i++)
        System.out
                .println(toplist.get(toplist.size() - i).getSite().getUrl() + " "
                        + humanReadableByteCount(
                                Math.round(toplist.get(toplist.size() - i).getTotalSavings()
                                        * toplist.get(toplist.size() - i).getSite().getUniqueBrowsers()),
                                true));

    System.out.println("-------------------------------------");
    System.out.println("TopList largest sites:");
    Collections.sort(toplist, new PageSizeComparator());
    for (int i = 1; i < (toplist.size() < TOPLIST_ITEMS ? toplist.size() : TOPLIST_ITEMS) + 1; i++)
        System.out.println(toplist.get(toplist.size() - i).getSite().getUrl() + " " + humanReadableByteCount(
                Math.round(toplist.get(toplist.size() - i).getTotalSizeBytes() / 1000), true));

}

---

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

@Spec(name = "quadratic data - first order smoothness", functional = SmoothnessTest.QuadraticData.class)
public void testQuadratic_linearSmoothness(FunctionalContext<List<Tuple>> context) {
    //first order will not match
    DescriptiveStatistics stats = new Smoothness(1).apply(context.evaluate());
    assertThat(stats.getMin()).isGreaterThan(0);
    assertThat(stats.getMax()).isLessThan(1);
    assertThat(stats.getMean()).isLessThan(.5);
}

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From source file:io.hops.leaderElection.experiments.ExperimentDriver.java

public void writeMessageToFile(int numProcesses, DescriptiveStatistics failOverStats,
        DescriptiveStatistics tpStats) throws IOException {
    PrintWriter out = new PrintWriter(new BufferedWriter(new FileWriter("summary.log", true)));
    out.println(numProcesses + " " + tpStats.getN() + " " + tpStats.getMin() + " " + tpStats.getMax() + " "
            + tpStats.getMean() + " " + tpStats.getStandardDeviation() + " "
            + (tpStats.getStandardDeviation() / Math.sqrt(tpStats.getN())) + " " + failOverStats.getN() + " "
            + failOverStats.getMin() + " " + failOverStats.getMax() + " " + failOverStats.getMean() + " "
            + failOverStats.getStandardDeviation() + " "
            + (failOverStats.getStandardDeviation() / Math.sqrt(failOverStats.getN())));
    out.close();// w ww  .  ja v a2 s . co m
}

---

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 ww w. j  a  v  a 2s  .c  om

        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();
}

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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 . j ava  2  s  .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());
}

---

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  a  v  a 2  s .c o m
    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:com.tascape.reactor.report.SuiteResultView.java

private void processMetrics() {
    Map<String, Map<String, Object>> tm = new HashMap<>();
    this.caseMetrics.forEach(row -> {
        String key = row.get(CaseResultMetric.METRIC_GROUP) + "." + row.get(CaseResultMetric.METRIC_NAME);
        Map<String, Object> r = tm.get(key);
        if (r == null) {
            tm.put(key, row);//  w  ww  .j ava  2  s  . c om
            List<Double> values = new ArrayList<>();
            values.add((double) row.get(CaseResultMetric.METRIC_VALUE));
            row.put("values", values);
        } else {
            @SuppressWarnings("unchecked")
            List<Double> values = (List<Double>) r.get("values");
            values.add((double) row.get(CaseResultMetric.METRIC_VALUE));
        }
    });

    tm.values().stream().forEach(row -> {
        @SuppressWarnings("unchecked")
        List<Double> values = (List<Double>) row.get("values");
        if (values.size() > 1) {
            DescriptiveStatistics stats = new DescriptiveStatistics();
            values.forEach(v -> stats.addValue(v));
            row.put("max", stats.getMax());
            row.put("min", stats.getMin());
            row.put("mean", stats.getMean());
            row.put("size", values.size());
        }
    });

    this.caseMetrics = new ArrayList<>(tm.values());
}

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