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# Valuegenerator

### Available Value-Generators

So far, we have the following value generators:

• Integer distribution generators:
• BinomialDistributionGenerator Samples from a Binomial distribution with the given number of trials and probability of success.
• EnumeratedIntegerDistributionGenerator Samples from a discrete distribution using the given probability mass function definition.
• HypergeometricDistributionGenerator Samples from a Hypergeometric distribution with the specified population size, number of successes in the population, and sample size.
• PascalDistributionGenerator Samples from a Pascal distribution with the given number of successes and probability of success.
• PoissonDistributionGenerator Samples from a Poisson distribution with specified mean, convergence criterion (optional) and maximum number of iterations (optional).
• UniformIntegerDistributionGenerator Samples from a uniform integer distribution using the given lower and upper bounds (both inclusive).
• ZipfDistributionGenerator Samples from a Zipf distribution with the given number of elements and exponent.
• Real distribution generators:
• BetaDistributionGenerator Samples from a  β-distribution with the given First shape parameter (alpha) and Second shape parameter(beta).
• CauchyDistributionGenerator Samples from a Cauchy distribution using the given median (default=0) and scale (default=0).
• ChiSquaredDistributionGenerator Samples from a Chi-Squared distribution with the given degrees of freedom.
• EmpiricalDistributionGenerator Samples from a Empirical distribution with the specified bin count (optional).
• EnumeratedRealDistributionGenerator Samples from a discrete distribution using the given probability mass function enumeration.
• ExponentialDistributionGenerator Samples from a exponential distribution with the given mean.
• FDistributionGenerator Samples from a F-distribution using the given degrees of freedom.
• GammaDistributionGenerator Samples from a gamma distribution with specified values of the shape and scale parameters.
• LevyDistributionGenerator Samples from a Lévy distribution with the given random generator to be used for sampling, the location, and the scale parameter.
• LogNormalDistributionGenerator Samples from a log-normal distribution using the specified scale (default=0) and shape (default=1).
• NormalDistributionGenerator Samples from a normal distribution using the given mean (default=0) and standard deviation (default=1).
• RayleighDistributionGenerator Samples from a Rayleigh distribution using the given scale.
• TDistributionGenerator Samples from a Student's t-distribution using the given degrees of freedom.
• TriangularDistributionGenerator Samples from a triangular real distribution using the given lower limit, upper limit, and mode.
• UniformRealDistributionGenerator Samples from a uniform real distribution using the given lower and upper bounds (default=[0,1]).
• WeibullDistributionGenerator Samples from a Weibull distribution with the given shape and scale and a location equal to zero.
• MultivariateNormalDistributionGenerator Samples from a multivariate normal distribution using the given means and covariances.
• Evolving generators:
• AlternatingGenerator Generates alternating values.
• IncreaseGenerator Generates increasing values.
• StepIncreaseGenerator
• SineGenerator Generates values from the sine function.
• CosineGenerator Generates values from the cosine function.
• TangentGenerator Generates values from the tangent function.
• DirichletEtaFunctionGenerator Generates values from the Dirichlet eta function using the parameter s.
• TimeGenerator Returns the current time in milliseconds.
• Spatial generators:
• MovingCircleGenerator Generates x/y steps in a circle.
• MovingPolynomialGenerator Generates x/y steps from an arbitrary polynomial.
• WaypointGenerator Generates x/y values from a list of waypoints.
• Switching generators:
• AlternatingDurationSwitchGenerator
• SignGenerator: Generates a value with switching signs.
• SwitchGenerator
• Value generators:
• TimeGenerator Generates current timestamps.
• ConstantValueGenerator Generates a constant value.
• PredifinedValueGenerator Generates a value from a fixed set of value.
• Random generators
• ISAACGenerator
• MersenneTwisterGenerator
• Well1024aGenerator
• Well19937aGenerator
• Well19937cGenerator
• Well44497aGenerator
• Well44497bGenerator
• Well512aGenerator

The distribution generators and their documentation are based on the Apache Commons Math3 implementation

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