Examples with Normal cern.jet.random.Normal used on opensource projects

Example 1 with Normal

use of cern.jet.random.Normal in project stream-lib by addthis.

the class QDigestTest method testComprehensiveOnMixture.

@Test
public void testComprehensiveOnMixture() {
    RandomEngine r = new MersenneTwister64(0);
    Normal[] dists = new Normal[] { new Normal(100, 50, r), new Normal(150, 20, r), new Normal(500, 300, r), new Normal(10000, 10000, r), new Normal(1200, 300, r) };
    for (int numSamples : new int[] { 1, 10, 100, 1000, 10000 }) {
        long[][] samples = new long[dists.length][];
        for (int i = 0; i < dists.length; ++i) {
            samples[i] = new long[numSamples];
            for (int j = 0; j < samples[i].length; ++j) {
                samples[i][j] = (long) Math.max(0, dists[i].nextDouble());
            }
        }
        double compressionFactor = 1000;
        int logCapacity = 1;
        long max = 0;
        for (long[] s : samples) {
            for (long x : s) max = Math.max(max, x);
        }
        for (double scale = 1; scale < max; scale *= 2, logCapacity++) {
            ;
        }
        double eps = logCapacity / compressionFactor;
        QDigest[] digests = new QDigest[dists.length];
        for (int i = 0; i < digests.length; ++i) {
            digests[i] = new QDigest(compressionFactor);
            for (long x : samples[i]) {
                digests[i].offer(x);
            }
            assertEquals(samples[i].length, digests[i].computeActualSize());
        }
        int numTotal = 0;
        for (int i = 0; i < digests.length; ++i) {
            for (double q = 0; q <= 1; q += 0.01) {
                long res = digests[i].getQuantile(q);
                double[] actualRank = actualRankOf(res, samples[i]);
                assertTrue(actualRank[0] + " .. " + actualRank[1] + " outside error bound for  " + q, q >= actualRank[0] - eps && q <= actualRank[1] + eps);
            }
            // Test the same on the union of all distributions up to i-th
            numTotal += samples[i].length;
            long[] total = new long[numTotal];
            int offset = 0;
            QDigest totalDigest = new QDigest(compressionFactor);
            long expectedSize = 0;
            for (int j = 0; j <= i; ++j) {
                System.arraycopy(samples[j], 0, total, offset, samples[j].length);
                offset += samples[j].length;
                totalDigest = QDigest.unionOf(totalDigest, digests[j]);
                expectedSize += samples[j].length;
            }
            assertEquals(expectedSize, totalDigest.computeActualSize());
            for (double q = 0; q <= 1; q += 0.01) {
                long res = totalDigest.getQuantile(q);
                double[] actualRank = actualRankOf(res, total);
                assertTrue(actualRank[0] + " .. " + actualRank[1] + " outside error bound for  " + q, q >= actualRank[0] - eps && q <= actualRank[1] + eps);
            }
        }
    }
}

Example 2 with Normal

use of cern.jet.random.Normal in project tetrad by cmu-phil.

the class NormalityTests method kolmogorovSmirnov.

/**
 * Calculates the Kolmogorov-Smirnov statistics for a variable
 *
 * @param dataSet relevant data set
 * @param variable continuous variable whose normality is in question
 *
 * @return Kolmogorov-Smirnov statistics: index 0 is the D_n value, 1-5 are the critical values at alpha = .2, .15. .10, .05, and .01 respectively.
 */
public static double[] kolmogorovSmirnov(DataSet dataSet, ContinuousVariable variable) {
    int n = dataSet.getNumRows();
    int columnIndex = dataSet.getColumn(variable);
    Normal idealDistribution = getNormal(dataSet, variable);
    double[] ks = new double[6];
    // get all critical values
    for (int i = 1; i < 6; i++) {
        ks[i] = estimateKSCriticalValue(i, n);
    }
    double[] _data = dataSet.getDoubleData().getColumn(columnIndex).toArray();
    List<Double> _leaveOutMissing = new ArrayList<>();
    for (int i = 0; i < _data.length; i++) {
        if (!Double.isNaN(_data[i])) {
            _leaveOutMissing.add(_data[i]);
        }
    }
    double[] data = new double[_leaveOutMissing.size()];
    for (int i = 0; i < _leaveOutMissing.size(); i++) data[i] = _leaveOutMissing.get(i);
    Arrays.sort(data);
    // sortVariable(dataSet, variable);
    // d = sup x |Fn(X) - i / n| -- the greatest distance between the ideal cdf and the edf
    double d = 0.0;
    for (int i = 1; i <= n; i++) {
        // double x = dataSet.getDouble(i - 1, columnIndex);
        double x = data[i - 1];
        // System.out.println("****" + x);
        // double valueAtQuantile = QQPlot.findQuantile((i + 1) / (dataSet.getNumRows() + 1.0), dataSet.getDouble(0, columnIndex), dataSet.getDouble(n - 1, columnIndex), idealDistribution, .0001, 0, 50);
        double idealValue = idealDistribution.cdf(x);
        // System.out.println(idealValue);
        // System.out.println((double)i / n);
        double difference = Math.abs(idealValue - ((double) i / n));
        if (difference > d) {
            // System.out.println("$$$$$" + difference);
            d = difference;
        }
    }
    ks[0] = d;
    return ks;
}

Example 3 with Normal

use of cern.jet.random.Normal in project micrometer by micrometer-metrics.

the class CounterSample method main.

public static void main(String[] args) {
    MeterRegistry registry = SampleConfig.myMonitoringSystem();
    Counter counter = registry.counter("counter", "method", "actual");
    AtomicInteger n = new AtomicInteger(0);
    registry.more().counter("counter", Tags.of("method", "function"), n);
    RandomEngine r = new MersenneTwister64(0);
    Normal dist = new Normal(0, 1, r);
    Flux.interval(Duration.ofMillis(10)).doOnEach(d -> {
        if (dist.nextDouble() + 0.1 > 0) {
            counter.increment();
            n.incrementAndGet();
        }
    }).blockLast();
}

Example 4 with Normal

use of cern.jet.random.Normal in project micrometer by micrometer-metrics.

the class TimerMaximumThroughputSample method main.

public static void main(String[] args) {
    MeterRegistry registry = SampleConfig.myMonitoringSystem();
    Timer timer = Timer.builder("timer").publishPercentileHistogram().sla(Duration.ofMillis(275), Duration.ofMillis(300), Duration.ofMillis(500)).distributionStatisticExpiry(Duration.ofSeconds(10)).distributionStatisticBufferLength(3).register(registry);
    RandomEngine r = new MersenneTwister64(0);
    Normal duration = new Normal(250, 50, r);
    AtomicInteger latencyForThisSecond = new AtomicInteger(duration.nextInt());
    Flux.interval(Duration.ofSeconds(1)).doOnEach(d -> latencyForThisSecond.set(duration.nextInt())).subscribe();
    Stream<Integer> infiniteStream = Stream.iterate(0, i -> (i + 1) % 1000);
    Flux.fromStream(infiniteStream).parallel(4).runOn(Schedulers.parallel()).doOnEach(d -> timer.record(latencyForThisSecond.get(), TimeUnit.MILLISECONDS)).subscribe();
    Flux.never().blockLast();
}

Example 5 with Normal

use of cern.jet.random.Normal in project micrometer by micrometer-metrics.

the class TimerSample method main.

public static void main(String[] args) {
    MeterRegistry registry = SampleConfig.myMonitoringSystem();
    Timer timer = Timer.builder("timer").publishPercentileHistogram().publishPercentiles(0.5, 0.95, 0.99).sla(Duration.ofMillis(275), Duration.ofMillis(300), Duration.ofMillis(500)).distributionStatisticExpiry(Duration.ofSeconds(10)).distributionStatisticBufferLength(3).register(registry);
    FunctionTimer.builder("ftimer", timer, Timer::count, t -> t.totalTime(TimeUnit.SECONDS), TimeUnit.SECONDS).register(registry);
    RandomEngine r = new MersenneTwister64(0);
    Normal incomingRequests = new Normal(0, 1, r);
    Normal duration = new Normal(250, 50, r);
    AtomicInteger latencyForThisSecond = new AtomicInteger(duration.nextInt());
    Flux.interval(Duration.ofSeconds(1)).doOnEach(d -> latencyForThisSecond.set(duration.nextInt())).subscribe();
    // the potential for an "incoming request" every 10 ms
    Flux.interval(Duration.ofMillis(10)).doOnEach(d -> {
        if (incomingRequests.nextDouble() + 0.4 > 0) {
            // pretend the request took some amount of time, such that the time is
            // distributed normally with a mean of 250ms
            timer.record(latencyForThisSecond.get(), TimeUnit.MILLISECONDS);
        }
    }).blockLast();
}