nosqlbench/_docs/services/docs/markdown/virtdata-funcref/funcref_distributions.md

CATEGORY distributions

Beta

@see Wikipedia: Beta distribution @see Commons JavaDoc: BetaDistribution

• int -> Beta(double: alpha, double: beta, java.lang.String[]...: mods) -> double
• long -> Beta(double: alpha, double: beta, java.lang.String[]...: mods) -> double

Binomial

@see Wikipedia: Binomial distribution @see Commons JavaDoc: BinomialDistribution

• int -> Binomial(int: trials, double: p, java.lang.String[]...: modslist) -> int
• int -> Binomial(int: trials, double: p, java.lang.String[]...: modslist) -> long
• long -> Binomial(int: trials, double: p, java.lang.String[]...: modslist) -> int
• long -> Binomial(int: trials, double: p, java.lang.String[]...: modslist) -> long

Cauchy

@see Wikipedia: Cauchy_distribution @see Commons Javadoc: CauchyDistribution

• int -> Cauchy(double: median, double: scale, java.lang.String[]...: mods) -> double
• long -> Cauchy(double: median, double: scale, java.lang.String[]...: mods) -> double

ChiSquared

@see Wikipedia: Chi-squared distribution @see Commons JavaDoc: ChiSquaredDistribution

• int -> ChiSquared(double: degreesOfFreedom, java.lang.String[]...: mods) -> double
• long -> ChiSquared(double: degreesOfFreedom, java.lang.String[]...: mods) -> double

CoinFunc

This is a higher-order function which takes an input value, and flips a coin. The first parameter is used as the threshold for choosing a function. If the sample values derived from the input is lower than the threshold value, then the first following function is used, and otherwise the second is used. For example, if the threshold is 0.23, and the input value is hashed and sampled in the unit interval to 0.43, then the second of the two provided functions will be used. The input value does not need to be hashed beforehand, since the user may need to use the full input value before hashing as the input to one or both of the functions. This function will accept either a LongFunction or a {@link Function} or a LongUnaryOperator in either position. If necessary, use {@link java.util.function.ToLongFunction} to adapt other function forms to be compatible with these signatures.

• java.lang.Long -> CoinFunc(double: threshold, java.lang.Object: first, java.lang.Object: second) -> java.lang.Object
  • ex: CoinFunc(0.15,NumberNameToString(),Combinations('A:1:B:23')) - use the first function 15% of the time

ConstantContinuous

Always yields the same value. @see Commons JavaDoc: ConstantContinuousDistribution

• int -> ConstantContinuous(double: value, java.lang.String[]...: mods) -> double
• long -> ConstantContinuous(double: value, java.lang.String[]...: mods) -> double

Enumerated

Creates a probability density given the values and optional weights provided, in "value:weight value:weight ..." form. The weight can be elided for any value to use the default weight of 1.0d. @see Commons JavaDoc: EnumeratedRealDistribution

• int -> Enumerated(java.lang.String: data, java.lang.String[]...: mods) -> double
  • ex: Enumerated('1 2 3 4 5 6') - a fair six-sided die roll
  • ex: Enumerated('1:2.0 2 3 4 5 6') - an unfair six-sided die roll, where 1 has probability mass 2.0, and everything else has only 1.0
• long -> Enumerated(java.lang.String: data, java.lang.String[]...: mods) -> double
  • ex: Enumerated('1 2 3 4 5 6') - a fair 6-sided die
  • ex: Enumerated('1:2.0 2 3 4 5:0.5 6:0.5') - an unfair fair 6-sided die, where ones are twice as likely, and fives and sixes are half as likely

Exponential

@see Wikipedia: Exponential distribution @see Commons JavaDoc: ExponentialDistribution

• int -> Exponential(double: mean, java.lang.String[]...: mods) -> double
• long -> Exponential(double: mean, java.lang.String[]...: mods) -> double

F

@see Wikipedia: F-distribution @see Commons JavaDoc: FDistribution @see Mathworld: F-Distribution

• int -> F(double: numeratorDegreesOfFreedom, double: denominatorDegreesOfFreedom, java.lang.String[]...: mods) -> double
• long -> F(double: numeratorDegreesOfFreedom, double: denominatorDegreesOfFreedom, java.lang.String[]...: mods) -> double

Gamma

@see Wikipedia: Gamma distribution @see Commons JavaDoc: GammaDistribution

• int -> Gamma(double: shape, double: scale, java.lang.String[]...: mods) -> double
• long -> Gamma(double: shape, double: scale, java.lang.String[]...: mods) -> double

Geometric

@see Wikipedia: Geometric distribution @see Commons JavaDoc: GeometricDistribution

• int -> Geometric(double: p, java.lang.String[]...: modslist) -> int
• int -> Geometric(double: p, java.lang.String[]...: modslist) -> long
• long -> Geometric(double: p, java.lang.String[]...: modslist) -> int
• long -> Geometric(double: p, java.lang.String[]...: modslist) -> long

Gumbel

@see Wikipedia: Gumbel distribution @see Commons JavaDoc: GumbelDistribution

• int -> Gumbel(double: mu, double: beta, java.lang.String[]...: mods) -> double
• long -> Gumbel(double: mu, double: beta, java.lang.String[]...: mods) -> double

Hypergeometric

@see Wikipedia: Hypergeometric distribution @see Commons JavaDoc: HypergeometricDistribution

• int -> Hypergeometric(int: populationSize, int: numberOfSuccesses, int: sampleSize, java.lang.String[]...: modslist) -> int
• int -> Hypergeometric(int: populationSize, int: numberOfSuccesses, int: sampleSize, java.lang.String[]...: modslist) -> long
• long -> Hypergeometric(int: populationSize, int: numberOfSuccesses, int: sampleSize, java.lang.String[]...: modslist) -> int
• long -> Hypergeometric(int: populationSize, int: numberOfSuccesses, int: sampleSize, java.lang.String[]...: modslist) -> long

Laplace

@see Wikipedia: Laplace distribution @see Commons JavaDoc: LaplaceDistribution

• int -> Laplace(double: mu, double: beta, java.lang.String[]...: mods) -> double
• long -> Laplace(double: mu, double: beta, java.lang.String[]...: mods) -> double

Levy

@see Wikipedia: Lévy distribution @see Commons JavaDoc: LevyDistribution

• int -> Levy(double: mu, double: c, java.lang.String[]...: mods) -> double
• long -> Levy(double: mu, double: c, java.lang.String[]...: mods) -> double

LogNormal

@see Wikipedia: Log-normal distribution @see Commons JavaDoc: LogNormalDistribution

• int -> LogNormal(double: scale, double: shape, java.lang.String[]...: mods) -> double
• long -> LogNormal(double: scale, double: shape, java.lang.String[]...: mods) -> double

Logistic

@see Wikipedia: Logistic distribution @see Commons JavaDoc: LogisticDistribution

• int -> Logistic(double: mu, double: scale, java.lang.String[]...: mods) -> double
• long -> Logistic(double: mu, double: scale, java.lang.String[]...: mods) -> double

Nakagami

@see Wikipedia: Nakagami distribution @see Commons JavaDoc: NakagamiDistribution

• int -> Nakagami(double: mu, double: omega, java.lang.String[]...: mods) -> double
• long -> Nakagami(double: mu, double: omega, java.lang.String[]...: mods) -> double

Normal

@see Wikipedia: Normal distribution @see Commons JavaDoc: NormalDistribution

• int -> Normal(double: mean, double: sd, java.lang.String[]...: mods) -> double
• long -> Normal(double: mean, double: sd, java.lang.String[]...: mods) -> double

Pareto

@see Wikipedia: Pareto distribution @see Commons JavaDoc: ParetoDistribution

• int -> Pareto(double: scale, double: shape, java.lang.String[]...: mods) -> double
• long -> Pareto(double: scale, double: shape, java.lang.String[]...: mods) -> double

Pascal

@see Commons JavaDoc: PascalDistribution @see Wikipedia: Negative binomial distribution

• int -> Pascal(int: r, double: p, java.lang.String[]...: modslist) -> int
• int -> Pascal(int: r, double: p, java.lang.String[]...: modslist) -> long
• long -> Pascal(int: r, double: p, java.lang.String[]...: modslist) -> int
• long -> Pascal(int: r, double: p, java.lang.String[]...: modslist) -> long

Poisson

@see Wikipedia: Poisson distribution @see Commons JavaDoc: PoissonDistribution

• int -> Poisson(double: p, java.lang.String[]...: modslist) -> int
• int -> Poisson(double: p, java.lang.String[]...: modslist) -> long
• long -> Poisson(double: p, java.lang.String[]...: modslist) -> int
• long -> Poisson(double: p, java.lang.String[]...: modslist) -> long

T

@see Wikipedia: Student's t-distribution @see Commons JavaDoc: TDistribution

• int -> T(double: degreesOfFreedom, java.lang.String[]...: mods) -> double
• long -> T(double: degreesOfFreedom, java.lang.String[]...: mods) -> double

Triangular

@see Wikipedia: Triangular distribution @see Commons JavaDoc: TriangularDistribution

• int -> Triangular(double: a, double: c, double: b, java.lang.String[]...: mods) -> double
• long -> Triangular(double: a, double: c, double: b, java.lang.String[]...: mods) -> double

Uniform

@see Wikipedia: Uniform distribution (continuous) @see Commons JavaDoc: UniformContinuousDistribution

• int -> Uniform(double: lower, double: upper, java.lang.String[]...: mods) -> double
• long -> Uniform(double: lower, double: upper, java.lang.String[]...: mods) -> double
• int -> Uniform(int: lower, int: upper, java.lang.String[]...: modslist) -> int
• int -> Uniform(int: lower, int: upper, java.lang.String[]...: modslist) -> long
• long -> Uniform(int: lower, int: upper, java.lang.String[]...: modslist) -> int
• long -> Uniform(int: lower, int: upper, java.lang.String[]...: modslist) -> long

Weibull

@see Wikipedia: Weibull distribution @see Wolfram Mathworld: Weibull Distribution @see Commons Javadoc: WeibullDistribution

• int -> Weibull(double: alpha, double: beta, java.lang.String[]...: mods) -> double
• long -> Weibull(double: alpha, double: beta, java.lang.String[]...: mods) -> double

WeightedFuncs

Allows for easy branching over multiple functions with specific weights.

• long -> WeightedFuncs(java.lang.Object[]...: weightsAndFuncs) -> java.lang.Object

Zipf

@see Wikipedia: Zipf's Law @see Commons JavaDoc: ZipfDistribution

• int -> Zipf(int: numberOfElements, double: exponent, java.lang.String[]...: modslist) -> int
• int -> Zipf(int: numberOfElements, double: exponent, java.lang.String[]...: modslist) -> long
• long -> Zipf(int: numberOfElements, double: exponent, java.lang.String[]...: modslist) -> int
• long -> Zipf(int: numberOfElements, double: exponent, java.lang.String[]...: modslist) -> long