Package | Description |
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cern.colt.matrix.doublealgo |
Double matrix algorithms such as print formatting, sorting, partitioning and statistics.
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cern.jet.random |
Large variety of probability distributions featuring high performance generation
of random numbers, CDF's and PDF's.
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cern.jet.random.engine |
Engines generating strong uniformly distributed pseudo-random numbers;
Needed by all JET probability distributions since they rely on uniform random numbers to generate random numbers from their own distribution.
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cern.jet.random.sampling |
Samples (picks) random subsets of data sequences.
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cern.jet.stat.quantile |
Scalable algorithms and data structures to compute approximate quantiles over very large data sequences.
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Modifier and Type | Method and Description |
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static DoubleMatrix1D |
Statistic.viewSample(DoubleMatrix1D matrix,
double fraction,
RandomEngine randomGenerator)
Constructs and returns a sampling view with a size of round(matrix.size() * fraction).
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static DoubleMatrix2D |
Statistic.viewSample(DoubleMatrix2D matrix,
double rowFraction,
double columnFraction,
RandomEngine randomGenerator)
Constructs and returns a sampling view with round(matrix.rows() * rowFraction) rows and round(matrix.columns() * columnFraction) columns.
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static DoubleMatrix3D |
Statistic.viewSample(DoubleMatrix3D matrix,
double sliceFraction,
double rowFraction,
double columnFraction,
RandomEngine randomGenerator)
Constructs and returns a sampling view with round(matrix.slices() * sliceFraction) slices and round(matrix.rows() * rowFraction) rows and round(matrix.columns() * columnFraction) columns.
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Modifier and Type | Field and Description |
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protected RandomEngine |
Benchmark.randomGenerator |
protected RandomEngine |
AbstractDistribution.randomGenerator |
Modifier and Type | Method and Description |
---|---|
protected RandomEngine |
AbstractDistribution.getRandomGenerator()
Returns the used uniform random number generator;
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static RandomEngine |
AbstractDistribution.makeDefaultGenerator()
Constructs and returns a new uniform random number generation engine seeded with the current time.
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Modifier and Type | Method and Description |
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protected double |
Beta.b00(double a,
double b,
RandomEngine randomGenerator) |
protected double |
Beta.b01(double a,
double b,
RandomEngine randomGenerator) |
protected double |
Beta.b1prs(double p,
double q,
RandomEngine randomGenerator) |
protected long |
Zeta.generateZeta(double ro,
double pk,
RandomEngine randomGenerator)
Returns a zeta distributed random number.
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protected int |
HyperGeometric.hmdu(int N,
int M,
int n,
RandomEngine randomGenerator)
Returns a random number from the distribution.
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protected int |
HyperGeometric.hprs(int N,
int M,
int n,
RandomEngine randomGenerator)
Returns a random number from the distribution.
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static double |
Distributions.nextBurr1(double r,
int nr,
RandomEngine randomGenerator)
Returns a random number from the Burr II, VII, VIII, X Distributions.
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static double |
Distributions.nextBurr2(double r,
double k,
int nr,
RandomEngine randomGenerator)
Returns a random number from the Burr III, IV, V, VI, IX, XII distributions.
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static double |
Distributions.nextCauchy(RandomEngine randomGenerator)
Returns a cauchy distributed random number from the standard Cauchy distribution C(0,1).
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static double |
Distributions.nextErlang(double variance,
double mean,
RandomEngine randomGenerator)
Returns an erlang distributed random number with the given variance and mean.
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static int |
Distributions.nextGeometric(double p,
RandomEngine randomGenerator)
Returns a discrete geometric distributed random number; Definition.
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protected int |
HyperGeometric.nextInt(int N,
int M,
int n,
RandomEngine randomGenerator)
Returns a random number from the distribution; bypasses the internal state.
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static double |
Distributions.nextLambda(double l3,
double l4,
RandomEngine randomGenerator)
Returns a lambda distributed random number with parameters l3 and l4.
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static double |
Distributions.nextLaplace(RandomEngine randomGenerator)
Returns a Laplace (Double Exponential) distributed random number from the standard Laplace distribution L(0,1).
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static double |
Distributions.nextLogistic(RandomEngine randomGenerator)
Returns a random number from the standard Logistic distribution Log(0,1).
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static double |
Distributions.nextPowLaw(double alpha,
double cut,
RandomEngine randomGenerator)
Returns a power-law distributed random number with the given exponent and lower cutoff.
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static double |
Distributions.nextTriangular(RandomEngine randomGenerator)
Returns a random number from the standard Triangular distribution in (-1,1).
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static double |
Distributions.nextWeibull(double alpha,
double beta,
RandomEngine randomGenerator)
Returns a weibull distributed random number.
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static int |
Distributions.nextZipfInt(double z,
RandomEngine randomGenerator)
Returns a zipfian distributed random number with the given skew.
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protected void |
Normal.setRandomGenerator(RandomEngine randomGenerator)
Sets the uniform random generator internally used.
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protected void |
AbstractDistribution.setRandomGenerator(RandomEngine randomGenerator)
Sets the uniform random generator internally used.
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static void |
Uniform.staticSetRandomEngine(RandomEngine randomGenerator)
Sets the uniform random number generation engine shared by all static methods.
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Constructor and Description |
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Beta(double alpha,
double beta,
RandomEngine randomGenerator)
Constructs a Beta distribution.
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Binomial(int n,
double p,
RandomEngine randomGenerator)
Constructs a binomial distribution.
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BreitWigner(double mean,
double gamma,
double cut,
RandomEngine randomGenerator)
Constructs a BreitWigner distribution.
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BreitWignerMeanSquare(double mean,
double gamma,
double cut,
RandomEngine randomGenerator)
Constructs a mean-squared BreitWigner distribution.
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ChiSquare(double freedom,
RandomEngine randomGenerator)
Constructs a ChiSquare distribution.
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Empirical(double[] pdf,
int interpolationType,
RandomEngine randomGenerator)
Constructs an Empirical distribution.
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EmpiricalWalker(double[] pdf,
int interpolationType,
RandomEngine randomGenerator)
Constructs an Empirical distribution.
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Exponential(double lambda,
RandomEngine randomGenerator)
Constructs a Negative Exponential distribution.
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ExponentialPower(double tau,
RandomEngine randomGenerator)
Constructs an Exponential Power distribution.
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Gamma(double alpha,
double lambda,
RandomEngine randomGenerator)
Constructs a Gamma distribution.
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Hyperbolic(double alpha,
double beta,
RandomEngine randomGenerator)
Constructs a Beta distribution.
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HyperGeometric(int N,
int s,
int n,
RandomEngine randomGenerator)
Constructs a HyperGeometric distribution.
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Logarithmic(double p,
RandomEngine randomGenerator)
Constructs a Logarithmic distribution.
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NegativeBinomial(int n,
double p,
RandomEngine randomGenerator)
Constructs a Negative Binomial distribution.
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Normal(double mean,
double standardDeviation,
RandomEngine randomGenerator)
Constructs a normal (gauss) distribution.
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Poisson(double mean,
RandomEngine randomGenerator)
Constructs a poisson distribution.
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PoissonSlow(double mean,
RandomEngine randomGenerator)
Constructs a poisson distribution.
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StudentT(double freedom,
RandomEngine randomGenerator)
Constructs a StudentT distribution.
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Uniform(double min,
double max,
RandomEngine randomGenerator)
Constructs a uniform distribution with the given minimum and maximum.
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Uniform(RandomEngine randomGenerator)
Constructs a uniform distribution with min=0.0 and max=1.0.
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VonMises(double freedom,
RandomEngine randomGenerator)
Constructs a Von Mises distribution.
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Zeta(double ro,
double pk,
RandomEngine randomGenerator)
Constructs a Zeta distribution.
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Modifier and Type | Class and Description |
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class |
DRand
Quick medium quality uniform pseudo-random number generator.
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class |
MersenneTwister
MersenneTwister (MT19937) is one of the strongest uniform pseudo-random number generators known so far; at the same time it is quick.
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class |
MersenneTwister64
Same as MersenneTwister except that method raw() returns 64 bit random numbers instead of 32 bit random numbers.
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Modifier and Type | Method and Description |
---|---|
static RandomEngine |
RandomEngine.makeDefault()
Constructs and returns a new uniform random number engine seeded with the current time.
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Modifier and Type | Method and Description |
---|---|
static void |
Benchmark.test(int size,
RandomEngine randomEngine)
Prints the first size random numbers generated by the given engine.
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Modifier and Type | Method and Description |
---|---|
RandomEngine |
RandomSamplingAssistant.getRandomGenerator()
Returns the used random generator.
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Modifier and Type | Method and Description |
---|---|
protected static void |
RandomSampler.rejectMethodD(long n,
long N,
int count,
long low,
long[] values,
int fromIndex,
RandomEngine randomGenerator)
Efficiently computes a sorted random set of count elements from the interval [low,low+N-1].
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static void |
RandomSampler.sample(long n,
long N,
int count,
long low,
long[] values,
int fromIndex,
RandomEngine randomGenerator)
Efficiently computes a sorted random set of count elements from the interval [low,low+N-1].
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protected static void |
RandomSampler.sampleMethodA(long n,
long N,
int count,
long low,
long[] values,
int fromIndex,
RandomEngine randomGenerator)
Computes a sorted random set of count elements from the interval [low,low+N-1].
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protected static void |
RandomSampler.sampleMethodD(long n,
long N,
int count,
long low,
long[] values,
int fromIndex,
RandomEngine randomGenerator)
Efficiently computes a sorted random set of count elements from the interval [low,low+N-1].
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Constructor and Description |
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RandomSampler(long n,
long N,
long low,
RandomEngine randomGenerator)
Constructs a random sampler that computes and delivers sorted random sets in blocks.
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RandomSamplingAssistant(long n,
long N,
RandomEngine randomGenerator)
Constructs a random sampler that samples n random elements from an input sequence of N elements.
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WeightedRandomSampler(int weight,
RandomEngine randomGenerator)
Chooses exactly one random element from successive blocks of weight input elements each.
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Modifier and Type | Method and Description |
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static DoubleQuantileFinder |
QuantileFinderFactory.newDoubleQuantileFinder(boolean known_N,
long N,
double epsilon,
double delta,
int quantiles,
RandomEngine generator)
Returns a quantile finder that minimizes the amount of memory needed under the user provided constraints.
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