Uses of Interface
org.hipparchus.random.RandomGenerator

Packages that use RandomGenerator

Package	Description
org.hipparchus.clustering	Clustering algorithms.
org.hipparchus.distribution.multivariate	Implementations of multivariate distributions.
org.hipparchus.optim.nonlinear.scalar.noderiv	This package provides optimization algorithms that do not require derivatives.
org.hipparchus.optim.univariate	One-dimensional optimization algorithms.
org.hipparchus.random	Random number and random data generators.
org.hipparchus.samples	Various examples.
org.hipparchus.stat.descriptive.rank	Summary statistics based on ranks.
org.hipparchus.stat.fitting	Statistical methods for fitting distributions.
org.hipparchus.stat.ranking	Classes providing rank transformations.
org.hipparchus.util	Convenience routines and common data structures used throughout the Hipparchus library.

Uses of RandomGenerator in org.hipparchus.clustering

Methods in org.hipparchus.clustering that return RandomGenerator

Modifier and Type	Method and Description
RandomGenerator	FuzzyKMeansClusterer.getRandomGenerator() Returns the random generator this instance will use.
RandomGenerator	KMeansPlusPlusClusterer.getRandomGenerator() Returns the random generator this instance will use.

Constructors in org.hipparchus.clustering with parameters of type RandomGenerator

Constructor and Description
FuzzyKMeansClusterer(int k, double fuzziness, int maxIterations, DistanceMeasure measure, double epsilon, RandomGenerator random) Creates a new instance of a FuzzyKMeansClusterer.
KMeansPlusPlusClusterer(int k, int maxIterations, DistanceMeasure measure, RandomGenerator random) Build a clusterer.
KMeansPlusPlusClusterer(int k, int maxIterations, DistanceMeasure measure, RandomGenerator random, KMeansPlusPlusClusterer.EmptyClusterStrategy emptyStrategy) Build a clusterer.

Uses of RandomGenerator in org.hipparchus.distribution.multivariate

Fields in org.hipparchus.distribution.multivariate declared as RandomGenerator

Modifier and Type	Field and Description
protected RandomGenerator	AbstractMultivariateRealDistribution.random RNG instance used to generate samples from the distribution.

Constructors in org.hipparchus.distribution.multivariate with parameters of type RandomGenerator

Constructor and Description
AbstractMultivariateRealDistribution(RandomGenerator rng, int n)
MixtureMultivariateNormalDistribution(RandomGenerator rng, List<Pair<Double,MultivariateNormalDistribution>> components) Creates a mixture model from a list of distributions and their associated weights.
MixtureMultivariateRealDistribution(RandomGenerator rng, List<Pair<Double,T>> components) Creates a mixture model from a list of distributions and their associated weights.
MultivariateNormalDistribution(RandomGenerator rng, double[] means, double[][] covariances) Creates a multivariate normal distribution with the given mean vector and covariance matrix.
MultivariateNormalDistribution(RandomGenerator rng, double[] means, double[][] covariances, double singularMatrixCheckTolerance) Creates a multivariate normal distribution with the given mean vector and covariance matrix.

Uses of RandomGenerator in org.hipparchus.optim.nonlinear.scalar.noderiv

Constructors in org.hipparchus.optim.nonlinear.scalar.noderiv with parameters of type RandomGenerator

Constructor and Description
CMAESOptimizer(int maxIterations, double stopFitness, boolean isActiveCMA, int diagonalOnly, int checkFeasableCount, RandomGenerator random, boolean generateStatistics, ConvergenceChecker<PointValuePair> checker)

Uses of RandomGenerator in org.hipparchus.optim.univariate

Constructors in org.hipparchus.optim.univariate with parameters of type RandomGenerator

Constructor and Description
MultiStartUnivariateOptimizer(UnivariateOptimizer optimizer, int starts, RandomGenerator generator) Create a multi-start optimizer from a single-start optimizer.

Uses of RandomGenerator in org.hipparchus.random

Classes in org.hipparchus.random that implement RandomGenerator

Modifier and Type	Class and Description
class	AbstractWell This abstract class implements the WELL class of pseudo-random number generator from François Panneton, Pierre L'Ecuyer and Makoto Matsumoto.
class	ISAACRandom A fast cryptographic pseudo-random number generator.
class	JDKRandomGenerator A RandomGenerator adapter that delegates the random number generation to the standard Random class.
class	MersenneTwister This class implements a powerful pseudo-random number generator developed by Makoto Matsumoto and Takuji Nishimura during 1996-1997.
class	RandomAdaptor Extension of Random wrapping a RandomGenerator.
class	RandomDataGenerator A class for generating random data.
class	SynchronizedRandomGenerator Any RandomGenerator implementation can be thread-safe if it is used through an instance of this class.
class	Well1024a This class implements the WELL1024a pseudo-random number generator from François Panneton, Pierre L'Ecuyer and Makoto Matsumoto.
class	Well19937a This class implements the WELL19937a pseudo-random number generator from François Panneton, Pierre L'Ecuyer and Makoto Matsumoto.
class	Well19937c This class implements the WELL19937c pseudo-random number generator from François Panneton, Pierre L'Ecuyer and Makoto Matsumoto.
class	Well44497a This class implements the WELL44497a pseudo-random number generator from François Panneton, Pierre L'Ecuyer and Makoto Matsumoto.
class	Well44497b This class implements the WELL44497b pseudo-random number generator from François Panneton, Pierre L'Ecuyer and Makoto Matsumoto.
class	Well512a This class implements the WELL512a pseudo-random number generator from François Panneton, Pierre L'Ecuyer and Makoto Matsumoto.

Methods in org.hipparchus.random that return RandomGenerator

Modifier and Type	Method and Description
protected RandomGenerator	RandomDataGenerator.delegate() Returns the backing delegate instance that methods are forwarded to.

Methods in org.hipparchus.random with parameters of type RandomGenerator

Modifier and Type	Method and Description
static Random	RandomAdaptor.of(RandomGenerator randomGenerator) Factory method to create a Random using the supplied RandomGenerator.
static RandomDataGenerator	RandomDataGenerator.of(RandomGenerator randomGenerator) Factory method to create a RandomData instance using the supplied RandomGenerator.

Constructors in org.hipparchus.random with parameters of type RandomGenerator

Constructor and Description
GaussianRandomGenerator(RandomGenerator generator) Create a new generator.
RandomAdaptor(RandomGenerator randomGenerator) Construct a RandomAdaptor wrapping the supplied RandomGenerator.
StableRandomGenerator(RandomGenerator generator, double alpha, double beta) Create a new generator.
SynchronizedRandomGenerator(RandomGenerator rng) Creates a synchronized wrapper for the given RandomGenerator instance.
UniformRandomGenerator(RandomGenerator generator) Create a new generator.
UnitSphereRandomVectorGenerator(int dimension, RandomGenerator rand)

Uses of RandomGenerator in org.hipparchus.samples

Methods in org.hipparchus.samples with parameters of type RandomGenerator

Modifier and Type	Method and Description
static Vector2D	ClusterAlgorithmComparison.generateNoiseVector(RandomGenerator randomGenerator, double noise)
static List<Vector2D>	ClusterAlgorithmComparison.makeBlobs(int samples, int centers, double clusterStd, double min, double max, boolean shuffle, RandomGenerator random)
static List<Vector2D>	ClusterAlgorithmComparison.makeCircles(int samples, boolean shuffle, double noise, double factor, RandomGenerator random)
static List<Vector2D>	ClusterAlgorithmComparison.makeMoons(int samples, boolean shuffle, double noise, RandomGenerator random)

Uses of RandomGenerator in org.hipparchus.stat.descriptive.rank

Constructors in org.hipparchus.stat.descriptive.rank with parameters of type RandomGenerator

Constructor and Description
RandomPercentile(double epsilon, RandomGenerator randomGenerator) Constructs a RandomPercentile with quantile estimation error epsilon using randomGenerator as its source of random data.
RandomPercentile(RandomGenerator randomGenerator) Constructs a RandomPercentile with default estimation error using randomGenerator as its source of random data.

Uses of RandomGenerator in org.hipparchus.stat.fitting

Constructors in org.hipparchus.stat.fitting with parameters of type RandomGenerator

Constructor and Description
EmpiricalDistribution(int binCount, RandomGenerator generator) Creates a new EmpiricalDistribution with the specified bin count using the provided RandomGenerator as the source of random data.
EmpiricalDistribution(RandomGenerator generator) Creates a new EmpiricalDistribution with default bin count using the provided RandomGenerator as the source of random data.

Uses of RandomGenerator in org.hipparchus.stat.ranking

Constructors in org.hipparchus.stat.ranking with parameters of type RandomGenerator

Constructor and Description
NaturalRanking(NaNStrategy nanStrategy, RandomGenerator randomGenerator) Create a NaturalRanking with the given NaNStrategy, TiesStrategy.RANDOM and the given source of random data.
NaturalRanking(RandomGenerator randomGenerator) Create a NaturalRanking with TiesStrategy.RANDOM and the given RandomGenerator as the source of random data.

Uses of RandomGenerator in org.hipparchus.util

Methods in org.hipparchus.util with parameters of type RandomGenerator

Modifier and Type	Method and Description
static void	MathArrays.shuffle(int[] list, int start, MathArrays.Position pos, RandomGenerator rng) Shuffle the entries of the given array, using the Fisher–Yates algorithm.
static void	MathArrays.shuffle(int[] list, RandomGenerator rng) Shuffle the entries of the given array.