Uses of Interface
org.hipparchus.random.RandomGenerator
Package
Description
Clustering algorithms.
Implementations of multivariate distributions.
This package provides optimization algorithms that do not require derivatives.
One-dimensional optimization algorithms.
Random number and random data generators.
Various examples.
Generic univariate and multivariate summary statistic objects.
Summary statistics based on ranks.
Statistical methods for fitting distributions.
Classes providing rank transformations.
Convenience routines and common data structures used throughout the Hipparchus library.
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Uses of RandomGenerator in org.hipparchus.clustering
Modifier and TypeMethodDescriptionFuzzyKMeansClusterer.getRandomGenerator()
Returns the random generator this instance will use.KMeansPlusPlusClusterer.getRandomGenerator()
Returns the random generator this instance will use.ModifierConstructorDescriptionFuzzyKMeansClusterer
(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
Modifier and TypeFieldDescriptionprotected final RandomGenerator
AbstractMultivariateRealDistribution.random
RNG instance used to generate samples from the distribution.ModifierConstructorDescriptionprotected
AbstractMultivariateRealDistribution
(RandomGenerator rng, int n) Simple constructor.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
ModifierConstructorDescriptionCMAESOptimizer
(int maxIterations, double stopFitness, boolean isActiveCMA, int diagonalOnly, int checkFeasableCount, RandomGenerator random, boolean generateStatistics, ConvergenceChecker<PointValuePair> checker) Simple constructor. -
Uses of RandomGenerator in org.hipparchus.optim.univariate
ModifierConstructorDescriptionMultiStartUnivariateOptimizer
(UnivariateOptimizer optimizer, int starts, RandomGenerator generator) Create a multi-start optimizer from a single-start optimizer. -
Uses of RandomGenerator in org.hipparchus.random
Modifier and TypeClassDescriptionclass
This abstract class implements the WELL class of pseudo-random number generator from François Panneton, Pierre L'Ecuyer and Makoto Matsumoto.class
A fast cryptographic pseudo-random number generator.class
ARandomGenerator
adapter that delegates the random number generation to the standardRandom
class.class
This class implements a powerful pseudo-random number generator developed by Makoto Matsumoto and Takuji Nishimura during 1996-1997.class
Extension ofRandom
wrapping aRandomGenerator
.class
A class for generating random data.class
AnyRandomGenerator
implementation can be thread-safe if it is used through an instance of this class.class
This class implements the WELL1024a pseudo-random number generator from François Panneton, Pierre L'Ecuyer and Makoto Matsumoto.class
This class implements the WELL19937a pseudo-random number generator from François Panneton, Pierre L'Ecuyer and Makoto Matsumoto.class
This class implements the WELL19937c pseudo-random number generator from François Panneton, Pierre L'Ecuyer and Makoto Matsumoto.class
This class implements the WELL44497a pseudo-random number generator from François Panneton, Pierre L'Ecuyer and Makoto Matsumoto.class
This class implements the WELL44497b pseudo-random number generator from François Panneton, Pierre L'Ecuyer and Makoto Matsumoto.class
This class implements the WELL512a pseudo-random number generator from François Panneton, Pierre L'Ecuyer and Makoto Matsumoto.Modifier and TypeMethodDescriptionprotected RandomGenerator
RandomDataGenerator.delegate()
Returns the backing delegate instance that methods are forwarded to.Modifier and TypeMethodDescriptionstatic Random
RandomAdaptor.of
(RandomGenerator randomGenerator) Factory method to create aRandom
using the suppliedRandomGenerator
.static RandomDataGenerator
RandomDataGenerator.of
(RandomGenerator randomGenerator) Factory method to create aRandomData
instance using the suppliedRandomGenerator
.ModifierConstructorDescriptionGaussianRandomGenerator
(RandomGenerator generator) Create a new generator.GaussMarkovGenerator
(double tau, double stationarySigma, 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.Creates a synchronized wrapper for the givenRandomGenerator
instance.UniformRandomGenerator
(RandomGenerator generator) Create a new generator.UnitSphereRandomVectorGenerator
(int dimension, RandomGenerator rand) Simple constructor. -
Uses of RandomGenerator in org.hipparchus.samples
Modifier and TypeMethodDescriptionstatic Vector2D
ClusterAlgorithmComparison.generateNoiseVector
(RandomGenerator randomGenerator, double noise) Generate a random vector.ClusterAlgorithmComparison.makeBlobs
(int samples, int centers, double clusterStd, double min, double max, boolean shuffle, RandomGenerator random) Make blobs patterns.ClusterAlgorithmComparison.makeCircles
(int samples, boolean shuffle, double noise, double factor, RandomGenerator random) Make circles patterns.ClusterAlgorithmComparison.makeMoons
(int samples, boolean shuffle, double noise, RandomGenerator random) Make Moons patterns. -
Uses of RandomGenerator in org.hipparchus.stat.descriptive
Modifier and TypeMethodDescriptionStreamingStatistics.StreamingStatisticsBuilder.percentiles
(double epsilonBound, RandomGenerator generator) Sets the computePercentiles setting of the factory.ModifierConstructorDescriptionStreamingStatistics
(double epsilon, RandomGenerator randomGenerator) Construct a new StreamingStatistics instance, maintaining all statistics other than percentiles and with/without percentiles per the arguments. -
Uses of RandomGenerator in org.hipparchus.stat.descriptive.rank
ModifierConstructorDescriptionRandomPercentile
(double epsilon, RandomGenerator randomGenerator) Constructs aRandomPercentile
with quantile estimation errorepsilon
usingrandomGenerator
as its source of random data.RandomPercentile
(RandomGenerator randomGenerator) Constructs aRandomPercentile
with default estimation error usingrandomGenerator
as its source of random data. -
Uses of RandomGenerator in org.hipparchus.stat.fitting
ModifierConstructorDescriptionEmpiricalDistribution
(int binCount, RandomGenerator generator) Creates a new EmpiricalDistribution with the specified bin count using the providedRandomGenerator
as the source of random data.EmpiricalDistribution
(RandomGenerator generator) Creates a new EmpiricalDistribution with default bin count using the providedRandomGenerator
as the source of random data. -
Uses of RandomGenerator in org.hipparchus.stat.ranking
ModifierConstructorDescriptionNaturalRanking
(RandomGenerator randomGenerator) Create a NaturalRanking with TiesStrategy.RANDOM and the given RandomGenerator as the source of random data.NaturalRanking
(NaNStrategy nanStrategy, RandomGenerator randomGenerator) Create a NaturalRanking with the given NaNStrategy, TiesStrategy.RANDOM and the given source of random data. -
Uses of RandomGenerator in org.hipparchus.util
Modifier and TypeMethodDescriptionstatic 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.