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

Example 6 with Normal

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

the class FunctionTimerSample method main.

// For Atlas: http://localhost:7101/api/v1/graph?q=name,ftimer,:eq,:dist-avg,name,timer,:eq,:dist-avg,1,:axis&s=e-5m&l=0
public static void main(String[] args) {
    MeterRegistry registry = SampleConfig.myMonitoringSystem();
    Timer timer = Timer.builder("timer").publishPercentiles(0.5, 0.95).register(registry);
    Object placeholder = new Object();
    AtomicLong totalTimeNanos = new AtomicLong(0);
    AtomicLong totalCount = new AtomicLong(0);
    FunctionTimer.builder("ftimer", placeholder, p -> totalCount.get(), p -> totalTimeNanos.get(), TimeUnit.NANOSECONDS).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);
            totalCount.incrementAndGet();
            totalTimeNanos.addAndGet((long) TimeUtils.millisToUnit(latencyForThisSecond.get(), TimeUnit.NANOSECONDS));
        }
    }).blockLast();
}

Example 7 with Normal

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

the class LongTaskTimerSample method main.

public static void main(String[] args) {
    MeterRegistry registry = SampleConfig.myMonitoringSystem();
    LongTaskTimer timer = registry.more().longTaskTimer("longTaskTimer");
    RandomEngine r = new MersenneTwister64(0);
    Normal incomingRequests = new Normal(0, 1, r);
    Normal duration = new Normal(30, 50, r);
    AtomicInteger latencyForThisSecond = new AtomicInteger(duration.nextInt());
    Flux.interval(Duration.ofSeconds(1)).doOnEach(d -> latencyForThisSecond.set(duration.nextInt())).subscribe();
    final Map<LongTaskTimer.Sample, CountDownLatch> tasks = new ConcurrentHashMap<>();
    // the potential for an "incoming request" every 10 ms
    Flux.interval(Duration.ofSeconds(1)).doOnEach(d -> {
        if (incomingRequests.nextDouble() + 0.4 > 0 && tasks.isEmpty()) {
            int taskDur;
            while ((taskDur = duration.nextInt()) < 0) ;
            synchronized (tasks) {
                tasks.put(timer.start(), new CountDownLatch(taskDur));
            }
        }
        synchronized (tasks) {
            for (Map.Entry<LongTaskTimer.Sample, CountDownLatch> e : tasks.entrySet()) {
                e.getValue().countDown();
                if (e.getValue().getCount() == 0) {
                    e.getKey().stop();
                    tasks.remove(e.getKey());
                }
            }
        }
    }).blockLast();
}

Example 8 with Normal

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

the class SimulatedEndpointInstrumentation method main.

public static void main(String[] args) {
    MeterRegistry registry = SampleConfig.myMonitoringSystem();
    Timer e1Success = Timer.builder("http.server.requests").tags("uri", "/api/bar").tags("response", "200").publishPercentiles(0.5, 0.95).register(registry);
    Timer e2Success = Timer.builder("http.server.requests").tags("uri", "/api/foo").tags("response", "200").publishPercentiles(0.5, 0.95).register(registry);
    Timer e1Fail = Timer.builder("http.server.requests").tags("uri", "/api/bar").tags("response", "500").publishPercentiles(0.5, 0.95).register(registry);
    Timer e2Fail = Timer.builder("http.server.requests").tags("uri", "/api/foo").tags("response", "500").publishPercentiles(0.5, 0.95).register(registry);
    RandomEngine r = new MersenneTwister64(0);
    Normal incomingRequests = new Normal(0, 1, r);
    Normal successOrFail = new Normal(0, 1, r);
    Normal duration = new Normal(250, 50, r);
    Normal duration2 = new Normal(250, 50, r);
    AtomicInteger latencyForThisSecond = new AtomicInteger(duration.nextInt());
    Flux.interval(Duration.ofSeconds(1)).doOnEach(d -> latencyForThisSecond.set(duration.nextInt())).subscribe();
    AtomicInteger latencyForThisSecond2 = new AtomicInteger(duration2.nextInt());
    Flux.interval(Duration.ofSeconds(1)).doOnEach(d -> latencyForThisSecond2.set(duration2.nextInt())).subscribe();
    // the potential for an "incoming request" every 10 ms
    Flux.interval(Duration.ofMillis(10)).doOnEach(d -> {
        // are we going to receive a request for /api/foo?
        if (incomingRequests.nextDouble() + 0.4 > 0) {
            if (successOrFail.nextDouble() + 0.8 > 0) {
                // pretend the request took some amount of time, such that the time is
                // distributed normally with a mean of 250ms
                e1Success.record(latencyForThisSecond.get(), TimeUnit.MILLISECONDS);
            } else {
                e1Fail.record(latencyForThisSecond.get(), TimeUnit.MILLISECONDS);
            }
        }
    }).subscribe();
    // the potential for an "incoming request" every 1 ms
    Flux.interval(Duration.ofMillis(1)).doOnEach(d -> {
        // are we going to receive a request for /api/bar?
        if (incomingRequests.nextDouble() + 0.4 > 0) {
            if (successOrFail.nextDouble() + 0.8 > 0) {
                // pretend the request took some amount of time, such that the time is
                // distributed normally with a mean of 250ms
                e2Success.record(latencyForThisSecond2.get(), TimeUnit.MILLISECONDS);
            } else {
                e2Fail.record(latencyForThisSecond2.get(), TimeUnit.MILLISECONDS);
            }
        }
    }).blockLast();
}

Example 9 with Normal

use of cern.jet.random.Normal in project processdash by dtuma.

the class LognormalConfidenceInterval method generateBootstrapSamples.

private double[] generateBootstrapSamples() {
    RandomEngine u = new MersenneTwister();
    Normal normal = new Normal(0, 1, u);
    ChiSquare chisquare = new ChiSquare(numSamples - 1, u);
    int bootstrapSize = Settings.getInt("logCI.bootstrapSize", 2000);
    double[] samples = new double[bootstrapSize];
    for (int i = bootstrapSize; i-- > 0; ) samples[i] = generateBootstrapSample(normal, chisquare, numSamples, logstd);
    Arrays.sort(samples);
    return samples;
}

Example 10 with Normal

use of cern.jet.random.Normal in project Gemma by PavlidisLab.

the class ComBat method plot.

/**
 * Make diagnostic plots.
 * FIXME: As in the original ComBat, this only graphs the first batch's statistics. In principle we can (and perhaps
 * should) examine these plots for all the batches.
 *
 * @param filePrefix file prefix
 */
public void plot(String filePrefix) {
    if (this.gammaHat == null)
        throw new IllegalArgumentException("You must call 'run' first");
    /*
         * View the distribution of gammaHat, which we assume will have a normal distribution
         */
    DoubleMatrix1D ghr = gammaHat.viewRow(0);
    int NUM_HIST_BINS = 100;
    Histogram gammaHatHist = new Histogram("GammaHat", NUM_HIST_BINS, ghr);
    XYSeries ghplot = gammaHatHist.plot();
    Normal rn = new Normal(this.gammaBar.get(0), Math.sqrt(this.t2.get(0)), new MersenneTwister());
    Histogram ghtheoryT = new Histogram("Gamma", NUM_HIST_BINS, gammaHatHist.min(), gammaHatHist.max());
    for (int i = 0; i < 10000; i++) {
        double n = rn.nextDouble();
        ghtheoryT.fill(n);
    }
    XYSeries ghtheory = ghtheoryT.plot();
    File tmpfile;
    try {
        tmpfile = File.createTempFile(filePrefix + ".gammahat.histogram.", ".png");
        ComBat.log.info(tmpfile);
    } catch (IOException e) {
        throw new RuntimeException(e);
    }
    try (OutputStream os = new FileOutputStream(tmpfile)) {
        this.writePlot(os, ghplot, ghtheory);
        /*
             * View the distribution of deltaHat, which we assume has an inverse gamma distribution
             */
        DoubleMatrix1D dhr = deltaHat.viewRow(0);
        Histogram deltaHatHist = new Histogram("DeltaHat", NUM_HIST_BINS, dhr);
        XYSeries dhplot = deltaHatHist.plot();
        Gamma g = new Gamma(aPrior.get(0), bPrior.get(0), new MersenneTwister());
        Histogram deltaHatT = new Histogram("Delta", NUM_HIST_BINS, deltaHatHist.min(), deltaHatHist.max());
        for (int i = 0; i < 10000; i++) {
            double invg = 1.0 / g.nextDouble();
            deltaHatT.fill(invg);
        }
        XYSeries dhtheory = deltaHatT.plot();
        tmpfile = File.createTempFile(filePrefix + ".deltahat.histogram.", ".png");
        ComBat.log.info(tmpfile);
        try (OutputStream os2 = new FileOutputStream(tmpfile)) {
            this.writePlot(os2, dhplot, dhtheory);
        }
    } catch (IOException e) {
        throw new RuntimeException(e);
    }
}