Examples with UniformRandomProvider org.apache.commons.rng.UniformRandomProvider used on opensource projects

Example 46 with UniformRandomProvider

use of org.apache.commons.rng.UniformRandomProvider in project GDSC-SMLM by aherbert.

the class AbstractFilterTest method getIntSpeedData.

/**
 * Create random int data.
 *
 * @param seed the seed
 * @param size the number of datasets
 * @return the array list of random data
 */
ArrayList<int[]> getIntSpeedData(RandomSeed seed, int size) {
    final FloatData data = (FloatData) ConcurrentHashMap.computeIfAbsent(seed, AbstractFilterTest::createSpeedData);
    final ArrayList<float[]> dataSet = data.dataSet;
    if (dataSet.size() < size) {
        final UniformRandomProvider rg = data.rg;
        synchronized (dataSet) {
            while (dataSet.size() < size) {
                dataSet.add(createData(rg, primes[0], primes[0]));
            }
        }
    }
    final ArrayList<int[]> dataSet2 = new ArrayList<>(size);
    for (int i = 0; i < size; i++) {
        final float[] f = dataSet.get(i);
        final int[] d = new int[f.length];
        for (int j = 0; j < d.length; j++) {
            d[j] = (int) (4096 * f[j]);
        }
        dataSet2.add(d);
    }
    return dataSet2;
}

Example 47 with UniformRandomProvider

use of org.apache.commons.rng.UniformRandomProvider in project GDSC-SMLM by aherbert.

the class AbstractFilterTest method getSpeedData.

/**
 * Create random float data.
 *
 * @param seed the seed
 * @param size the number of datasets
 * @return the array list of random data
 */
ArrayList<float[]> getSpeedData(RandomSeed seed, int size) {
    final FloatData data = (FloatData) ConcurrentHashMap.computeIfAbsent(seed, AbstractFilterTest::createSpeedData);
    final ArrayList<float[]> dataSet = data.dataSet;
    if (dataSet.size() < size) {
        final UniformRandomProvider rg = data.rg;
        synchronized (dataSet) {
            while (dataSet.size() < size) {
                dataSet.add(createData(rg, primes[0], primes[0]));
            }
        }
    }
    final ArrayList<float[]> dataSet2 = new ArrayList<>(size);
    for (int i = 0; i < size; i++) {
        dataSet2.add(dataSet.get(i).clone());
    }
    return dataSet2;
}

Example 48 with UniformRandomProvider

use of org.apache.commons.rng.UniformRandomProvider in project GDSC-SMLM by aherbert.

the class AverageFilterTest method checkIsCorrect.

private static void checkIsCorrect(RandomSeed seed, DataFilter filter) {
    final UniformRandomProvider rg = RngUtils.create(seed.getSeed());
    for (final int width : primes) {
        for (final int height : primes) {
            for (final float boxSize : boxSizes) {
                for (final boolean internal : checkInternal) {
                    averageIsCorrect(rg, width, height, boxSize, internal, filter);
                    if (filter.isInterpolated) {
                        averageIsCorrect(rg, width, height, boxSize - 0.3f, internal, filter);
                        averageIsCorrect(rg, width, height, boxSize - 0.6f, internal, filter);
                    }
                }
            }
        }
    }
}

Example 49 with UniformRandomProvider

use of org.apache.commons.rng.UniformRandomProvider in project GDSC-SMLM by aherbert.

the class NormaliserTest method nonNormaliserCanCopyToOutDataWithBorder.

@SeededTest
void nonNormaliserCanCopyToOutDataWithBorder(RandomSeed seed) {
    final UniformRandomProvider rg = RngUtils.create(seed.getSeed());
    for (final int width : primes) {
        for (final int height : primes) {
            final float[] data = createData(rg, width, height);
            for (final int boxSize : boxSizes) {
                // logger.fine(() -> String.format("%dx%d : border=%d", width, height, boxSize);
                // Assume fixed normaliser works
                final FixedNormaliser n = new FixedNormaliser(1);
                final NonNormaliser nn = new NonNormaliser();
                final float[] e = new float[data.length];
                final float[] o = new float[data.length];
                n.normalise(data, e, width, height, boxSize);
                nn.normalise(data, o, width, height, boxSize);
                Assertions.assertArrayEquals(o, e, () -> String.format("%dx%d : border=%d", width, height, boxSize));
            }
        }
    }
}

Example 50 with UniformRandomProvider

use of org.apache.commons.rng.UniformRandomProvider in project GDSC-SMLM by aherbert.

the class TraceExporter method export.

private void export(MemoryPeakResults results) {
    // Copy to allow manipulation
    results = results.copy();
    // Strip results with no trace Id
    results.removeIf(result -> result.getId() <= 0);
    // Sort by ID then time
    results.sort(IdFramePeakResultComparator.INSTANCE);
    // Split traces with big jumps and long tracks into smaller tracks
    results = splitTraces(results);
    results = splitLongTraces(results);
    // Count each ID and remove short traces
    int id = 0;
    int count = 0;
    int tracks = 0;
    int maxLength = 0;
    final TIntHashSet remove = new TIntHashSet();
    for (int i = 0, size = results.size(); i < size; i++) {
        final PeakResult result = results.get(i);
        if (result.getId() != id) {
            if (count < settings.minLength) {
                remove.add(id);
            } else {
                tracks++;
                maxLength = Math.max(maxLength, count);
            }
            count = 0;
            id = result.getId();
        }
        count += getLength(result);
    }
    // Final ID
    if (count < settings.minLength) {
        remove.add(id);
    } else {
        tracks++;
        maxLength = Math.max(maxLength, count);
    }
    if (!remove.isEmpty()) {
        results.removeIf(result -> remove.contains(result.getId()));
        results.sort(IdFramePeakResultComparator.INSTANCE);
    }
    if (settings.wobble > 0) {
        // Just leave any exceptions to trickle up and kill the plugin
        final TypeConverter<DistanceUnit> c = results.getDistanceConverter(DistanceUnit.NM);
        final double w = c.convertBack(settings.wobble);
        final UniformRandomProvider rng = UniformRandomProviders.create();
        final NormalizedGaussianSampler gauss = SamplerUtils.createNormalizedGaussianSampler(rng);
        final boolean is3D = results.is3D();
        results.forEach((PeakResultProcedure) peakResult -> {
            peakResult.setXPosition((float) (peakResult.getXPosition() + w * gauss.sample()));
            peakResult.setYPosition((float) (peakResult.getYPosition() + w * gauss.sample()));
            if (is3D) {
                peakResult.setZPosition((float) (peakResult.getZPosition() + w * gauss.sample()));
            }
        });
    }
    if (settings.format == 2) {
        exportVbSpt(results);
    } else if (settings.format == 1) {
        exportAnaDda(results);
    } else {
        exportSpotOn(results);
    }
    ImageJUtils.log("Exported %s: %s in %s", results.getName(), TextUtils.pleural(results.size(), "localisation"), TextUtils.pleural(tracks, "track"));
    if (settings.showTraceLengths) {
        // We store and index (count-1)
        final int[] h = new int[maxLength];
        id = 0;
        for (int i = 0, size = results.size(); i < size; i++) {
            final PeakResult result = results.get(i);
            if (result.getId() != id) {
                h[count - 1]++;
                count = 0;
                id = result.getId();
            }
            count += getLength(result);
        }
        h[count - 1]++;
        final String title = TITLE + ": " + results.getName();
        final Plot plot = new Plot(title, "Length", "Frequency");
        plot.addPoints(SimpleArrayUtils.newArray(h.length, 1, 1.0f), SimpleArrayUtils.toFloat(h), Plot.BAR);
        plot.setLimits(SimpleArrayUtils.findIndex(h, i -> i != 0), maxLength + 1, 0, Double.NaN);
        ImageJUtils.display(title, plot);
    }
}