Examples with DiscreteSampler org.apache.commons.rng.sampling.distribution.DiscreteSampler used on opensource projects

Example 1 with DiscreteSampler

use of org.apache.commons.rng.sampling.distribution.DiscreteSampler in project GDSC-SMLM by aherbert.

the class BinomialFitterTest method createData.

private static int[] createData(UniformRandomProvider rg, int n, double p, boolean zeroTruncated) {
    final BinomialDistribution bd = new BinomialDistribution(null, n, p);
    final DiscreteSampler sampler = new InverseTransformDiscreteSampler(rg, pvalue -> bd.inverseCumulativeProbability(pvalue));
    final int[] data = new int[2000];
    if (zeroTruncated) {
        if (p <= 0) {
            throw new RuntimeException("p must be positive");
        }
        for (int i = 0; i < data.length; i++) {
            int count;
            do {
                count = sampler.sample();
            } while (count == 0);
            data[i] = count;
        }
    } else {
        for (int i = 0; i < data.length; i++) {
            data[i] = sampler.sample();
        }
    }
    return data;
}

Example 2 with DiscreteSampler

use of org.apache.commons.rng.sampling.distribution.DiscreteSampler in project GDSC-SMLM by aherbert.

the class ScmosLikelihoodWrapperTest method createData.

private static Object createData(RandomSeed source) {
    final int n = maxx * maxx;
    final SCcmosLikelihoodWrapperTestData data = new SCcmosLikelihoodWrapperTestData();
    data.var = new float[n];
    data.gain = new float[n];
    data.offset = new float[n];
    data.sd = new float[n];
    final UniformRandomProvider rg = RngUtils.create(source.getSeed());
    final DiscreteSampler pd = GdscSmlmTestUtils.createPoissonSampler(rg, O);
    final SharedStateContinuousSampler gs = SamplerUtils.createGaussianSampler(rg, G, G_SD);
    final ContinuousSampler ed = SamplerUtils.createExponentialSampler(rg, VAR);
    for (int i = 0; i < n; i++) {
        data.offset[i] = pd.sample();
        data.var[i] = (float) ed.sample();
        data.sd[i] = (float) Math.sqrt(data.var[i]);
        data.gain[i] = (float) gs.sample();
    }
    return data;
}

Example 3 with DiscreteSampler

use of org.apache.commons.rng.sampling.distribution.DiscreteSampler in project GDSC-SMLM by aherbert.

the class CmosAnalysis method simulate.

private void simulate() throws IOException {
    // Create the offset, variance and gain for each pixel
    final int n = settings.size * settings.size;
    final float[] pixelOffset = new float[n];
    final float[] pixelVariance = new float[n];
    final float[] pixelGain = new float[n];
    IJ.showStatus("Creating random per-pixel readout");
    final long start = System.currentTimeMillis();
    final UniformRandomProvider rg = UniformRandomProviders.create();
    final DiscreteSampler pd = PoissonSamplerUtils.createPoissonSampler(rg, settings.offset);
    final ContinuousSampler ed = SamplerUtils.createExponentialSampler(rg, settings.variance);
    final SharedStateContinuousSampler gauss = SamplerUtils.createGaussianSampler(rg, settings.gain, settings.gainStdDev);
    Ticker ticker = ImageJUtils.createTicker(n, 0);
    for (int i = 0; i < n; i++) {
        // Q. Should these be clipped to a sensible range?
        pixelOffset[i] = pd.sample();
        pixelVariance[i] = (float) ed.sample();
        pixelGain[i] = (float) gauss.sample();
        ticker.tick();
    }
    IJ.showProgress(1);
    // Save to the directory as a stack
    final ImageStack simulationStack = new ImageStack(settings.size, settings.size);
    simulationStack.addSlice("Offset", pixelOffset);
    simulationStack.addSlice("Variance", pixelVariance);
    simulationStack.addSlice("Gain", pixelGain);
    simulationImp = new ImagePlus("PerPixel", simulationStack);
    // Only the info property is saved to the TIFF file
    simulationImp.setProperty("Info", String.format("Offset=%s; Variance=%s; Gain=%s +/- %s", MathUtils.rounded(settings.offset), MathUtils.rounded(settings.variance), MathUtils.rounded(settings.gain), MathUtils.rounded(settings.gainStdDev)));
    IJ.save(simulationImp, new File(settings.directory, "perPixelSimulation.tif").getPath());
    // Create thread pool and workers
    final int threadCount = getThreads();
    final ExecutorService executor = Executors.newFixedThreadPool(threadCount);
    final LocalList<Future<?>> futures = new LocalList<>(numberOfThreads);
    // Simulate the exposure input.
    final int[] photons = settings.getPhotons();
    // For saving stacks
    final int blockSize = 10;
    int numberPerThread = (int) Math.ceil((double) settings.frames / numberOfThreads);
    // Convert to fit the block size
    numberPerThread = (int) Math.ceil((double) numberPerThread / blockSize) * blockSize;
    final Pcg32 rng = Pcg32.xshrs(start);
    // Note the bias is increased by 3-fold so add 2 to the length
    ticker = Ticker.createStarted(new ImageJTrackProgress(true), (long) (photons.length + 2) * settings.frames, threadCount > 1);
    for (final int p : photons) {
        ImageJUtils.showStatus(() -> "Simulating " + TextUtils.pleural(p, "photon"));
        // Create the directory
        final Path out = Paths.get(settings.directory, String.format("photon%03d", p));
        Files.createDirectories(out);
        // Increase frames for bias image
        final int frames = settings.frames * (p == 0 ? 3 : 1);
        for (int from = 0; from < frames; ) {
            final int to = Math.min(from + numberPerThread, frames);
            futures.add(executor.submit(new SimulationWorker(ticker, rng.split(), out.toString(), simulationStack, from, to, blockSize, p)));
            from = to;
        }
        ConcurrencyUtils.waitForCompletionUnchecked(futures);
        futures.clear();
    }
    final String msg = "Simulation time = " + TextUtils.millisToString(System.currentTimeMillis() - start);
    IJ.showStatus(msg);
    ImageJUtils.clearSlowProgress();
    executor.shutdown();
    ImageJUtils.log(msg);
}