Simulation.Aivika.Trans.Dynamics.Random

Tested with: GHC 8.0.1

This module defines the random functions that always return the same values in the integration time points within a single simulation run. The values for another simulation run will be regenerated anew.

For example, the computations returned by these functions can be used in the equations of System Dynamics.

Also it is worth noting that the values are generated in a strong order starting from starttime with step dt. This is how the memo0Dynamics function actually works.

Documentation

memoRandomUniformDynamics

Arguments

:: MonadSD m

=> Dynamics m Double

minimum

-> Dynamics m Double

maximum

-> Simulation m (Dynamics m Double)

Computation that generates random numbers distributed uniformly and memoizes them in the integration time points.

memoRandomUniformIntDynamics

Arguments

:: MonadSD m

=> Dynamics m Int

minimum

-> Dynamics m Int

maximum

-> Simulation m (Dynamics m Int)

Computation that generates random integer numbers distributed uniformly and memoizes them in the integration time points.

memoRandomTriangularDynamics

Arguments

:: MonadSD m

=> Dynamics m Double

minimum

-> Dynamics m Double

median

-> Dynamics m Double

maximum

-> Simulation m (Dynamics m Double)

Computation that generates random numbers from the triangular distribution and memoizes the numbers in the integration time points.

memoRandomNormalDynamics

Arguments

:: MonadSD m

=> Dynamics m Double

mean

-> Dynamics m Double

deviation

-> Simulation m (Dynamics m Double)

Computation that generates random numbers distributed normally and memoizes them in the integration time points.

memoRandomLogNormalDynamics

Arguments

:: MonadSD m

=> Dynamics m Double

the mean of a normal distribution which this distribution is derived from

-> Dynamics m Double

the deviation of a normal distribution which this distribution is derived from

-> Simulation m (Dynamics m Double)

Computation that generates random numbers from the lognormal distribution and memoizes the numbers in the integration time points.

memoRandomExponentialDynamics

Arguments

:: MonadSD m

=> Dynamics m Double

the mean (the reciprocal of the rate)

-> Simulation m (Dynamics m Double)

Computation that generates exponential random numbers with the specified mean (the reciprocal of the rate) and memoizes them in the integration time points.

memoRandomErlangDynamics

Arguments

:: MonadSD m

=> Dynamics m Double

the scale (the reciprocal of the rate)

-> Dynamics m Int

the shape

-> Simulation m (Dynamics m Double)

Computation that generates the Erlang random numbers with the specified scale (the reciprocal of the rate) and integer shape but memoizes them in the integration time points.

memoRandomPoissonDynamics

Arguments

:: MonadSD m

=> Dynamics m Double

the mean

-> Simulation m (Dynamics m Int)

Computation that generats the Poisson random numbers with the specified mean and memoizes them in the integration time points.

memoRandomBinomialDynamics

Arguments

:: MonadSD m

=> Dynamics m Double

the probability

-> Dynamics m Int

the number of trials

-> Simulation m (Dynamics m Int)

Computation that generates binomial random numbers with the specified probability and trials but memoizes them in the integration time points.

memoRandomGammaDynamics

Arguments

:: MonadSD m

=> Dynamics m Double

shape

-> Dynamics m Double

scale (a reciprocal of the rate)

-> Simulation m (Dynamics m Double)

Computation that generates random numbers from the Gamma distribution with the specified shape and scale but memoizes the numbers in the integration time points.

memoRandomBetaDynamics

Arguments

:: MonadSD m

=> Dynamics m Double

shape (alpha)

-> Dynamics m Double

shape (beta)

-> Simulation m (Dynamics m Double)

Computation that generates random numbers from the Beta distribution by the specified shape parameters and memoizes the numbers in the integration time points.

memoRandomWeibullDynamics

Arguments

:: MonadSD m

=> Dynamics m Double

shape

-> Dynamics m Double

scale

-> Simulation m (Dynamics m Double)

Computation that generates random numbers from the Weibull distribution with the specified shape and scale but memoizes the numbers in the integration time points.

memoRandomDiscreteDynamics :: (MonadSD m, MonadMemo m a) => Dynamics m (DiscretePDF a) -> Simulation m (Dynamics m a)

Computation that generates random values from the specified discrete distribution and memoizes the values in the integration time points.