Examples with UniformRealDistribution org.apache.commons.math3.distribution.UniformRealDistribution used on opensource projects

Example 6 with UniformRealDistribution

use of org.apache.commons.math3.distribution.UniformRealDistribution in project vcell by virtualcell.

the class BrownianDynamics2DSolver method initializeUniform.

public void initializeUniform(boolean fluorescent) {
    // 
    // initialize to a uniform distribution
    // 
    UniformRealDistribution uniformX = new UniformRealDistribution(simulationRng, origin.getX(), origin.getX() + extent.getX());
    UniformRealDistribution uniformY = new UniformRealDistribution(simulationRng, origin.getY(), origin.getY() + extent.getY());
    for (int i = 0; i < numParticles; i++) {
        particleX[i] = uniformX.sample();
        particleY[i] = uniformY.sample();
        bFluorescent[i] = fluorescent;
    }
    currTime = 0.0;
}

Example 7 with UniformRealDistribution

use of org.apache.commons.math3.distribution.UniformRealDistribution in project druid by druid-io.

the class BenchmarkColumnValueGenerator method initDistribution.

private void initDistribution() {
    BenchmarkColumnSchema.ValueDistribution distributionType = schema.getDistributionType();
    ValueType type = schema.getType();
    List<Object> enumeratedValues = schema.getEnumeratedValues();
    List<Double> enumeratedProbabilities = schema.getEnumeratedProbabilities();
    List<Pair<Object, Double>> probabilities = new ArrayList<>();
    switch(distributionType) {
        case SEQUENTIAL:
            // not random, just cycle through numbers from start to end, or cycle through enumerated values if provided
            distribution = new SequentialDistribution(schema.getStartInt(), schema.getEndInt(), schema.getEnumeratedValues());
            break;
        case UNIFORM:
            distribution = new UniformRealDistribution(schema.getStartDouble(), schema.getEndDouble());
            break;
        case DISCRETE_UNIFORM:
            if (enumeratedValues == null) {
                enumeratedValues = new ArrayList<>();
                for (int i = schema.getStartInt(); i < schema.getEndInt(); i++) {
                    Object val = convertType(i, type);
                    enumeratedValues.add(val);
                }
            }
            // give them all equal probability, the library will normalize probabilities to sum to 1.0
            for (int i = 0; i < enumeratedValues.size(); i++) {
                probabilities.add(new Pair<>(enumeratedValues.get(i), 0.1));
            }
            distribution = new EnumeratedTreeDistribution<>(probabilities);
            break;
        case NORMAL:
            distribution = new NormalDistribution(schema.getMean(), schema.getStandardDeviation());
            break;
        case ROUNDED_NORMAL:
            NormalDistribution normalDist = new NormalDistribution(schema.getMean(), schema.getStandardDeviation());
            distribution = new RealRoundingDistribution(normalDist);
            break;
        case ZIPF:
            int cardinality;
            if (enumeratedValues == null) {
                Integer startInt = schema.getStartInt();
                cardinality = schema.getEndInt() - startInt;
                ZipfDistribution zipf = new ZipfDistribution(cardinality, schema.getZipfExponent());
                for (int i = 0; i < cardinality; i++) {
                    probabilities.add(new Pair<>((Object) (i + startInt), zipf.probability(i)));
                }
            } else {
                cardinality = enumeratedValues.size();
                ZipfDistribution zipf = new ZipfDistribution(enumeratedValues.size(), schema.getZipfExponent());
                for (int i = 0; i < cardinality; i++) {
                    probabilities.add(new Pair<>(enumeratedValues.get(i), zipf.probability(i)));
                }
            }
            distribution = new EnumeratedTreeDistribution<>(probabilities);
            break;
        case ENUMERATED:
            for (int i = 0; i < enumeratedValues.size(); i++) {
                probabilities.add(new Pair<>(enumeratedValues.get(i), enumeratedProbabilities.get(i)));
            }
            distribution = new EnumeratedTreeDistribution<>(probabilities);
            break;
        default:
            throw new UnsupportedOperationException("Unknown distribution type: " + distributionType);
    }
    if (distribution instanceof AbstractIntegerDistribution) {
        ((AbstractIntegerDistribution) distribution).reseedRandomGenerator(seed);
    } else if (distribution instanceof AbstractRealDistribution) {
        ((AbstractRealDistribution) distribution).reseedRandomGenerator(seed);
    } else if (distribution instanceof EnumeratedDistribution) {
        ((EnumeratedDistribution) distribution).reseedRandomGenerator(seed);
    }
}

Example 8 with UniformRealDistribution

use of org.apache.commons.math3.distribution.UniformRealDistribution in project GDSC-SMLM by aherbert.

the class CreateData method createPhotonDistribution.

/**
 * Creates the photon distribution.
 *
 * @return A photon distribution loaded from a file of floating-point values with the specified
 *         population mean.
 */
private RealDistribution createPhotonDistribution() {
    if (PHOTON_DISTRIBUTION[PHOTON_CUSTOM].equals(settings.getPhotonDistribution())) {
        // Get the distribution file
        final String filename = ImageJUtils.getFilename("Photon_distribution", settings.getPhotonDistributionFile());
        if (filename != null) {
            settings.setPhotonDistributionFile(filename);
            try (BufferedReader in = new BufferedReader(new UnicodeReader(new FileInputStream(new File(settings.getPhotonDistributionFile())), null))) {
                final StoredDataStatistics stats = new StoredDataStatistics();
                String str = in.readLine();
                double val = 0.0d;
                while (str != null) {
                    val = Double.parseDouble(str);
                    stats.add(val);
                    str = in.readLine();
                }
                if (stats.getSum() > 0) {
                    // Update the statistics to the desired mean.
                    final double scale = settings.getPhotonsPerSecond() / stats.getMean();
                    final double[] values = stats.getValues();
                    for (int i = 0; i < values.length; i++) {
                        values[i] *= scale;
                    }
                    // TODO - Investigate the limits of this distribution.
                    // How far above and below the input data will values be generated.
                    // Create the distribution using the recommended number of bins
                    final int binCount = stats.getN() / 10;
                    final EmpiricalDistribution dist = new EmpiricalDistribution(binCount, new RandomGeneratorAdapter(createRandomGenerator()));
                    dist.load(values);
                    return dist;
                }
            } catch (final IOException | NullArgumentException | NumberFormatException ex) {
            // Ignore
            }
        }
        ImageJUtils.log("Failed to load custom photon distribution from file: %s. Default to fixed.", settings.getPhotonDistributionFile());
    } else if (PHOTON_DISTRIBUTION[PHOTON_UNIFORM].equals(settings.getPhotonDistribution())) {
        if (settings.getPhotonsPerSecond() < settings.getPhotonsPerSecondMaximum()) {
            return new UniformRealDistribution(new RandomGeneratorAdapter(createRandomGenerator()), settings.getPhotonsPerSecond(), settings.getPhotonsPerSecondMaximum());
        }
    } else if (PHOTON_DISTRIBUTION[PHOTON_GAMMA].equals(settings.getPhotonDistribution())) {
        final double scaleParameter = settings.getPhotonsPerSecond() / settings.getPhotonShape();
        return new GammaDistribution(new RandomGeneratorAdapter(createRandomGenerator()), settings.getPhotonShape(), scaleParameter, ExponentialDistribution.DEFAULT_INVERSE_ABSOLUTE_ACCURACY);
    } else if (PHOTON_DISTRIBUTION[PHOTON_CORRELATED].equals(settings.getPhotonDistribution())) {
        // No distribution required
        return null;
    }
    settings.setPhotonDistribution(PHOTON_DISTRIBUTION[PHOTON_FIXED]);
    return null;
}