-- | -- Module : Simulation.Aivika.Processor.Random -- Copyright : Copyright (c) 2009-2015, David Sorokin -- License : BSD3 -- Maintainer : David Sorokin -- Stability : experimental -- Tested with: GHC 7.10.1 -- -- This module defines some useful random processors that -- hold the current process for the corresponding time interval, -- when processing every input element. -- module Simulation.Aivika.Processor.Random (randomUniformProcessor, randomUniformIntProcessor, randomTriangularProcessor, randomNormalProcessor, randomLogNormalProcessor, randomExponentialProcessor, randomErlangProcessor, randomPoissonProcessor, randomBinomialProcessor, randomGammaProcessor, randomBetaProcessor, randomWeibullProcessor, randomDiscreteProcessor) where import Simulation.Aivika.Generator import Simulation.Aivika.Process import Simulation.Aivika.Process.Random import Simulation.Aivika.Processor -- | When processing every input element, hold the process -- for a random time interval distributed uniformly. randomUniformProcessor :: Double -- ^ the minimum time interval -> Double -- ^ the maximum time interval -> Processor a a randomUniformProcessor min max = withinProcessor $ randomUniformProcess_ min max -- | When processing every input element, hold the process -- for a random time interval distributed uniformly. randomUniformIntProcessor :: Int -- ^ the minimum time interval -> Int -- ^ the maximum time interval -> Processor a a randomUniformIntProcessor min max = withinProcessor $ randomUniformIntProcess_ min max -- | When processing every input element, hold the process -- for a random time interval having the triangular distribution. randomTriangularProcessor :: Double -- ^ the minimum time interval -> Double -- ^ the median of the time interval -> Double -- ^ the maximum time interval -> Processor a a randomTriangularProcessor min median max = withinProcessor $ randomTriangularProcess_ min median max -- | When processing every input element, hold the process -- for a random time interval distributed normally. randomNormalProcessor :: Double -- ^ the mean time interval -> Double -- ^ the time interval deviation -> Processor a a randomNormalProcessor mu nu = withinProcessor $ randomNormalProcess_ mu nu -- | When processing every input element, hold the process -- for a random time interval having the lognormal distribution. randomLogNormalProcessor :: Double -- ^ the mean for a normal distribution -- which this distribution is derived from -> Double -- ^ the deviation for a normal distribution -- which this distribution is derived from -> Processor a a randomLogNormalProcessor mu nu = withinProcessor $ randomLogNormalProcess_ mu nu -- | When processing every input element, hold the process -- for a random time interval distributed exponentially -- with the specified mean (the reciprocal of the rate). randomExponentialProcessor :: Double -- ^ the mean time interval (the reciprocal of the rate) -> Processor a a randomExponentialProcessor mu = withinProcessor $ randomExponentialProcess_ mu -- | When processing every input element, hold the process -- for a random time interval having the Erlang distribution with -- the specified scale (the reciprocal of the rate) and shape parameters. randomErlangProcessor :: Double -- ^ the scale (the reciprocal of the rate) -> Int -- ^ the shape -> Processor a a randomErlangProcessor beta m = withinProcessor $ randomErlangProcess_ beta m -- | When processing every input element, hold the process -- for a random time interval having the Poisson distribution -- with the specified mean. randomPoissonProcessor :: Double -- ^ the mean time interval -> Processor a a randomPoissonProcessor mu = withinProcessor $ randomPoissonProcess_ mu -- | When processing every input element, hold the process -- for a random time interval having the binomial distribution -- with the specified probability and trials. randomBinomialProcessor :: Double -- ^ the probability -> Int -- ^ the number of trials -> Processor a a randomBinomialProcessor prob trials = withinProcessor $ randomBinomialProcess_ prob trials -- | When processing every input element, hold the process -- for a random time interval having the Gamma distribution -- with the specified shape and scale. randomGammaProcessor :: Double -- ^ the shape -> Double -- ^ the scale (a reciprocal of the rate) -> Processor a a randomGammaProcessor kappa theta = withinProcessor $ randomGammaProcess_ kappa theta -- | When processing every input element, hold the process -- for a random time interval having the Beta distribution -- with the specified shape parameters (alpha and beta). randomBetaProcessor :: Double -- ^ shape (alpha) -> Double -- ^ shape (beta) -> Processor a a randomBetaProcessor alpha beta = withinProcessor $ randomBetaProcess_ alpha beta -- | When processing every input element, hold the process -- for a random time interval having the Weibull distribution -- with the specified shape and scale. randomWeibullProcessor :: Double -- ^ shape -> Double -- ^ scale -> Processor a a randomWeibullProcessor alpha beta = withinProcessor $ randomWeibullProcess_ alpha beta -- | When processing every input element, hold the process -- for a random time interval having the specified discrete distribution. randomDiscreteProcessor :: DiscretePDF Double -- ^ the discrete probability density function -> Processor a a randomDiscreteProcessor dpdf = withinProcessor $ randomDiscreteProcess_ dpdf