Package | Description |
---|---|
fr.cnes.sirius.patrius.math.distribution | |
fr.cnes.sirius.patrius.math.genetics | |
fr.cnes.sirius.patrius.math.optim.nonlinear.scalar.noderiv | |
fr.cnes.sirius.patrius.math.optim.univariate | |
fr.cnes.sirius.patrius.math.random |
Random number and random data generators.
|
fr.cnes.sirius.patrius.math.stat.ranking |
Modifier and Type | Field and Description |
---|---|
protected RandomGenerator |
AbstractIntegerDistribution.random
RNG instance used to generate samples from the distribution.
|
protected RandomGenerator |
AbstractRealDistribution.random
RNG instance used to generate samples from the distribution.
|
protected RandomGenerator |
AbstractMultivariateRealDistribution.random
RNG instance used to generate samples from the distribution.
|
Constructor and Description |
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AbstractIntegerDistribution(RandomGenerator rng) |
AbstractMultivariateRealDistribution(RandomGenerator rng,
int n) |
AbstractRealDistribution(RandomGenerator rng) |
BetaDistribution(RandomGenerator rng,
double alphaIn,
double betaIn,
double inverseCumAccuracy)
Creates a β distribution.
|
BinomialDistribution(RandomGenerator rng,
int trials,
double p)
Creates a binomial distribution.
|
CauchyDistribution(RandomGenerator rng,
double medianIn,
double scaleIn,
double inverseCumAccuracy)
Creates a Cauchy distribution.
|
ChiSquaredDistribution(RandomGenerator rng,
double degreesOfFreedom,
double inverseCumAccuracy)
Create a Chi-Squared distribution with the given degrees of freedom and
inverse cumulative probability accuracy.
|
ExponentialDistribution(RandomGenerator rng,
double meanIn,
double inverseCumAccuracy)
Creates an exponential distribution.
|
FDistribution(RandomGenerator rng,
double numeratorDegreesOfFreedomIn,
double denominatorDegreesOfFreedomIn,
double inverseCumAccuracy)
Creates an F distribution.
|
GammaDistribution(RandomGenerator rng,
double shapeIn,
double scaleIn,
double inverseCumAccuracy)
Creates a Gamma distribution.
|
HypergeometricDistribution(RandomGenerator rngIn,
int populationSizeIn,
int numberOfSuccessesIn,
int sampleSizeIn)
Creates a new hypergeometric distribution.
|
LogNormalDistribution(RandomGenerator rng,
double scaleIn,
double shapeIn,
double inverseCumAccuracy)
Creates a log-normal distribution.
|
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[] meansIn,
double[][] covariances)
Creates a multivariate normal distribution with the given mean vector and
covariance matrix.
|
NormalDistribution(RandomGenerator rng,
double meanIn,
double sd,
double inverseCumAccuracy)
Creates a normal distribution.
|
PascalDistribution(RandomGenerator rng,
int r,
double p)
Create a Pascal distribution with the given number of successes and
probability of success.
|
PoissonDistribution(RandomGenerator rng,
double p,
double epsilonIn,
int maxIterationsIn)
Creates a new Poisson distribution with specified mean, convergence
criterion and maximum number of iterations.
|
TDistribution(RandomGenerator rng,
double degreesOfFreedomIn,
double inverseCumAccuracy)
Creates a t distribution.
|
TriangularDistribution(RandomGenerator rng,
double aIn,
double cIn,
double bIn)
Creates a triangular distribution.
|
UniformIntegerDistribution(RandomGenerator rng,
int lowerIn,
int upperIn)
Creates a new uniform integer distribution using the given lower and
upper bounds (both inclusive).
|
UniformRealDistribution(RandomGenerator rng,
double lowerIn,
double upperIn,
double inverseCumAccuracy)
Creates a uniform distribution.
|
WeibullDistribution(RandomGenerator rng,
double alpha,
double beta,
double inverseCumAccuracy)
Creates a Weibull distribution.
|
ZipfDistribution(RandomGenerator rng,
int numberOfElementsIn,
double exponentIn)
Creates a Zipf distribution.
|
Modifier and Type | Method and Description |
---|---|
static RandomGenerator |
GeneticAlgorithm.getRandomGenerator()
Returns the (static) random generator.
|
Modifier and Type | Method and Description |
---|---|
static void |
GeneticAlgorithm.setRandomGenerator(RandomGenerator random)
Set the (static) random generator.
|
Constructor and Description |
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CMAESOptimizer(int maxIterationsIn,
double stopFitnessIn,
boolean isActiveCMAIn,
int diagonalOnlyIn,
int checkFeasableCountIn,
RandomGenerator randomIn,
boolean generateStatisticsIn,
ConvergenceChecker<PointValuePair> checker) |
Constructor and Description |
---|
MultiStartUnivariateOptimizer(UnivariateOptimizer optimizerIn,
int startsIn,
RandomGenerator generatorIn)
Create a multi-start optimizer from a single-start optimizer.
|
Modifier and Type | Class and Description |
---|---|
class |
AbstractRandomGenerator
Abstract class implementing the
RandomGenerator interface. |
class |
AbstractWell
This abstract class implements the WELL class of pseudo-random number generator
from François Panneton, Pierre L'Ecuyer and Makoto Matsumoto.
|
class |
BitsStreamGenerator
Base class for random number generators that generates bits streams.
|
class |
ISAACRandom
ISAAC: a fast cryptographic pseudo-random number generator
ISAAC (Indirection, Shift, Accumulate, Add, and Count) generates 32-bit random numbers. |
class |
JDKRandomGenerator
Extension of
java.util.Random to implement RandomGenerator . |
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
java.util.Random wrapping a RandomGenerator . |
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.
|
Modifier and Type | Method and Description |
---|---|
RandomGenerator |
RandomDataGenerator.getRan()
Returns the RandomGenerator used to generate non-secure random data.
|
Modifier and Type | Method and Description |
---|---|
static Random |
RandomAdaptor.createAdaptor(RandomGenerator randomGenerator)
Factory method to create a
Random using the supplied RandomGenerator . |
Constructor and Description |
---|
EmpiricalDistribution(int binCountIn,
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. |
GaussianRandomGenerator(RandomGenerator generatorIn)
Create a new generator.
|
RandomAdaptor(RandomGenerator randomGeneratorIn)
Construct a RandomAdaptor wrapping the supplied RandomGenerator.
|
RandomDataGenerator(RandomGenerator randIn)
Construct a RandomDataGenerator using the supplied
RandomGenerator as
the source of (non-secure) random data. |
StableRandomGenerator(RandomGenerator generatorIn,
double alphaIn,
double betaIn)
Create a new generator.
|
SynchronizedRandomGenerator(RandomGenerator rng)
Creates a synchronized wrapper for the given
RandomGenerator instance. |
UniformRandomGenerator(RandomGenerator generatorIn)
Create a new generator.
|
UnitSphereRandomVectorGenerator(int dimensionIn,
RandomGenerator randIn) |
ValueServer(RandomGenerator generator)
Construct a ValueServer instance using a RandomGenerator as its source
of random data.
|
Constructor and Description |
---|
NaturalRanking(NaNStrategy nanStrategyIn,
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.
|
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