Package | Description |
---|---|
cern.colt.matrix.tdouble.algo |
Linear Algebraic matrix computations operating on
DoubleMatrix2D
and DoubleMatrix1D . |
cern.jet.random.tdouble |
Large variety of probability distributions featuring high performance generation
of random numbers, CDF's and PDF's.
|
cern.jet.random.tdouble.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.
|
cern.jet.random.tdouble.sampling |
Samples (picks) random subsets of data sequences.
|
cern.jet.stat.tdouble.quantile |
Scalable algorithms and data structures to compute approximate quantiles over very large data sequences.
|
hep.aida.tdouble.bin |
Multisets (bags) with efficient statistics operations defined upon; This package
requires the Colt distribution.
|
Modifier and Type | Method and Description |
---|---|
static DoubleMatrix1D |
DoubleStatistic.viewSample(DoubleMatrix1D matrix,
double fraction,
DoubleRandomEngine randomGenerator)
Constructs and returns a sampling view with a size of
round(matrix.size() * fraction).
|
static DoubleMatrix2D |
DoubleStatistic.viewSample(DoubleMatrix2D matrix,
double rowFraction,
double columnFraction,
DoubleRandomEngine randomGenerator)
Constructs and returns a sampling view with
round(matrix.rows() * rowFraction) rows and
round(matrix.columns() * columnFraction) columns.
|
static DoubleMatrix3D |
DoubleStatistic.viewSample(DoubleMatrix3D matrix,
double sliceFraction,
double rowFraction,
double columnFraction,
DoubleRandomEngine 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.
|
Modifier and Type | Method and Description |
---|---|
static DoubleRandomEngine |
AbstractDoubleDistribution.makeDefaultGenerator()
Constructs and returns a new uniform random number generation engine
seeded with the current time.
|
Modifier and Type | Method and Description |
---|---|
static double |
Distributions.nextBurr1(double r,
int nr,
DoubleRandomEngine randomGenerator)
Returns a random number from the Burr II, VII, VIII, X Distributions.
|
static double |
Distributions.nextBurr2(double r,
double k,
int nr,
DoubleRandomEngine randomGenerator)
Returns a random number from the Burr III, IV, V, VI, IX, XII
distributions.
|
static double |
Distributions.nextCauchy(DoubleRandomEngine randomGenerator)
Returns a cauchy distributed random number from the standard Cauchy
distribution C(0,1).
|
static double |
Distributions.nextErlang(double variance,
double mean,
DoubleRandomEngine randomGenerator)
Returns an erlang distributed random number with the given variance and
mean.
|
static int |
Distributions.nextGeometric(double p,
DoubleRandomEngine randomGenerator)
Returns a discrete geometric distributed random number; Definition.
|
static double |
Distributions.nextLambda(double l3,
double l4,
DoubleRandomEngine randomGenerator)
Returns a lambda distributed random number with parameters l3 and l4.
|
static double |
Distributions.nextLaplace(DoubleRandomEngine randomGenerator)
Returns a Laplace (Double Exponential) distributed random number from the
standard Laplace distribution L(0,1).
|
static double |
Distributions.nextLogistic(DoubleRandomEngine randomGenerator)
Returns a random number from the standard Logistic distribution Log(0,1).
|
static double |
Distributions.nextPowLaw(double alpha,
double cut,
DoubleRandomEngine randomGenerator)
Returns a power-law distributed random number with the given exponent and
lower cutoff.
|
static double |
Distributions.nextTriangular(DoubleRandomEngine randomGenerator)
Returns a random number from the standard Triangular distribution in
(-1,1).
|
static double |
Distributions.nextWeibull(double alpha,
double beta,
DoubleRandomEngine randomGenerator)
Returns a weibull distributed random number.
|
static int |
Distributions.nextZipfInt(double z,
DoubleRandomEngine randomGenerator)
Returns a zipfian distributed random number with the given skew.
|
static void |
DoubleUniform.staticSetRandomEngine(DoubleRandomEngine randomGenerator)
Sets the uniform random number generation engine shared by all
static methods.
|
Constructor and Description |
---|
Beta(double alpha,
double beta,
DoubleRandomEngine randomGenerator)
Constructs a Beta distribution.
|
Binomial(int n,
double p,
DoubleRandomEngine randomGenerator)
Constructs a binomial distribution.
|
BreitWigner(double mean,
double gamma,
double cut,
DoubleRandomEngine randomGenerator)
Constructs a BreitWigner distribution.
|
BreitWignerMeanSquare(double mean,
double gamma,
double cut,
DoubleRandomEngine randomGenerator)
Constructs a mean-squared BreitWigner distribution.
|
ChiSquare(double freedom,
DoubleRandomEngine randomGenerator)
Constructs a ChiSquare distribution.
|
DoubleUniform(double min,
double max,
DoubleRandomEngine randomGenerator)
Constructs a uniform distribution with the given minimum and maximum.
|
DoubleUniform(DoubleRandomEngine randomGenerator)
Constructs a uniform distribution with min=0.0 and
max=1.0.
|
Empirical(double[] pdf,
int interpolationType,
DoubleRandomEngine randomGenerator)
Constructs an Empirical distribution.
|
EmpiricalWalker(double[] pdf,
int interpolationType,
DoubleRandomEngine randomGenerator)
Constructs an Empirical distribution.
|
Exponential(double lambda,
DoubleRandomEngine randomGenerator)
Constructs a Negative Exponential distribution.
|
ExponentialPower(double tau,
DoubleRandomEngine randomGenerator)
Constructs an Exponential Power distribution.
|
Gamma(double alpha,
double lambda,
DoubleRandomEngine randomGenerator)
Constructs a Gamma distribution.
|
Hyperbolic(double alpha,
double beta,
DoubleRandomEngine randomGenerator)
Constructs a Beta distribution.
|
HyperGeometric(int N,
int s,
int n,
DoubleRandomEngine randomGenerator)
Constructs a HyperGeometric distribution.
|
Logarithmic(double p,
DoubleRandomEngine randomGenerator)
Constructs a Logarithmic distribution.
|
NegativeBinomial(int n,
double p,
DoubleRandomEngine randomGenerator)
Constructs a Negative Binomial distribution.
|
Normal(double mean,
double standardDeviation,
DoubleRandomEngine randomGenerator)
Constructs a normal (gauss) distribution.
|
Poisson(double mean,
DoubleRandomEngine randomGenerator)
Constructs a poisson distribution.
|
PoissonSlow(double mean,
DoubleRandomEngine randomGenerator)
Constructs a poisson distribution.
|
StudentT(double freedom,
DoubleRandomEngine randomGenerator)
Constructs a StudentT distribution.
|
VonMises(double freedom,
DoubleRandomEngine randomGenerator)
Constructs a Von Mises distribution.
|
Zeta(double ro,
double pk,
DoubleRandomEngine randomGenerator)
Constructs a Zeta distribution.
|
Modifier and Type | Class and Description |
---|---|
class |
DoubleMersenneTwister
MersenneTwister (MT19937) is one of the strongest uniform pseudo-random
number generators known so far; at the same time it is quick.
|
class |
DRand
Quick medium quality uniform pseudo-random number generator.
|
class |
MersenneTwister64
Same as MersenneTwister except that method raw() returns 64
bit random numbers instead of 32 bit random numbers.
|
Modifier and Type | Method and Description |
---|---|
static DoubleRandomEngine |
DoubleRandomEngine.makeDefault()
Constructs and returns a new uniform random number engine seeded with the
current time.
|
Modifier and Type | Method and Description |
---|---|
DoubleRandomEngine |
DoubleRandomSamplingAssistant.getRandomGenerator()
Returns the used random generator.
|
Modifier and Type | Method and Description |
---|---|
static void |
DoubleRandomSampler.sample(long n,
long N,
int count,
long low,
long[] values,
int fromIndex,
DoubleRandomEngine randomGenerator)
Efficiently computes a sorted random set of count elements from
the interval [low,low+N-1].
|
Constructor and Description |
---|
DoubleRandomSampler(long n,
long N,
long low,
DoubleRandomEngine randomGenerator)
Constructs a random sampler that computes and delivers sorted random sets
in blocks.
|
DoubleRandomSamplingAssistant(long n,
long N,
DoubleRandomEngine randomGenerator)
Constructs a random sampler that samples n random elements from
an input sequence of N elements.
|
WeightedDoubleRandomSampler(int weight,
DoubleRandomEngine randomGenerator)
Chooses exactly one random element from successive blocks of
weight input elements each.
|
Modifier and Type | Method and Description |
---|---|
static DoubleQuantileFinder |
DoubleQuantileFinderFactory.newDoubleQuantileFinder(boolean known_N,
long N,
double epsilon,
double delta,
int quantiles,
DoubleRandomEngine generator)
Returns a quantile finder that minimizes the amount of memory needed
under the user provided constraints.
|
Modifier and Type | Method and Description |
---|---|
void |
DynamicDoubleBin1D.sample(int n,
boolean withReplacement,
DoubleRandomEngine randomGenerator,
DoubleBuffer buffer)
Uniformly samples (chooses) n random elements with or without
replacement from the contained elements and adds them to the given
buffer.
|
DynamicDoubleBin1D |
DynamicDoubleBin1D.sampleBootstrap(DynamicDoubleBin1D other,
int resamples,
DoubleRandomEngine randomGenerator,
DoubleBinBinFunction1D function)
Generic bootstrap resampling.
|
Constructor and Description |
---|
QuantileDoubleBin1D(boolean known_N,
long N,
double epsilon,
double delta,
int quantiles,
DoubleRandomEngine randomGenerator)
Equivalent to
new QuantileBin1D(known_N, N, epsilon, delta, quantiles, randomGenerator, false, false, 2)
.
|
QuantileDoubleBin1D(boolean known_N,
long N,
double epsilon,
double delta,
int quantiles,
DoubleRandomEngine randomGenerator,
boolean hasSumOfLogarithms,
boolean hasSumOfInversions,
int maxOrderForSumOfPowers)
Constructs and returns an empty bin that, under the given constraints,
minimizes the amount of memory needed.
|
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