-- | -- Module : Simulation.Aivika.Process.Random -- Copyright : Copyright (c) 2009-2015, David Sorokin -- License : BSD3 -- Maintainer : David Sorokin -- Stability : experimental -- Tested with: GHC 7.10.1 -- -- This module defines helper functions, which are useful to hold -- the 'Process' computation for a time interval according to some -- random distribution. -- module Simulation.Aivika.Process.Random (randomUniformProcess, randomUniformProcess_, randomUniformIntProcess, randomUniformIntProcess_, randomTriangularProcess, randomTriangularProcess_, randomNormalProcess, randomNormalProcess_, randomLogNormalProcess, randomLogNormalProcess_, randomExponentialProcess, randomExponentialProcess_, randomErlangProcess, randomErlangProcess_, randomPoissonProcess, randomPoissonProcess_, randomBinomialProcess, randomBinomialProcess_, randomGammaProcess, randomGammaProcess_, randomBetaProcess, randomBetaProcess_, randomWeibullProcess, randomWeibullProcess_, randomDiscreteProcess, randomDiscreteProcess_) where import Control.Monad import Control.Monad.Trans import Simulation.Aivika.Generator import Simulation.Aivika.Parameter import Simulation.Aivika.Parameter.Random import Simulation.Aivika.Process -- | Hold the process for a random time interval distributed uniformly. randomUniformProcess :: Double -- ^ the minimum time interval -> Double -- ^ the maximum time interval -> Process Double -- ^ a computation of the time interval -- for which the process was actually held randomUniformProcess min max = do t <- liftParameter $ randomUniform min max holdProcess t return t -- | Hold the process for a random time interval distributed uniformly. randomUniformProcess_ :: Double -- ^ the minimum time interval -> Double -- ^ the maximum time interval -> Process () randomUniformProcess_ min max = do t <- liftParameter $ randomUniform min max holdProcess t -- | Hold the process for a random time interval distributed uniformly. randomUniformIntProcess :: Int -- ^ the minimum time interval -> Int -- ^ the maximum time interval -> Process Int -- ^ a computation of the time interval -- for which the process was actually held randomUniformIntProcess min max = do t <- liftParameter $ randomUniformInt min max holdProcess $ fromIntegral t return t -- | Hold the process for a random time interval distributed uniformly. randomUniformIntProcess_ :: Int -- ^ the minimum time interval -> Int -- ^ the maximum time interval -> Process () randomUniformIntProcess_ min max = do t <- liftParameter $ randomUniformInt min max holdProcess $ fromIntegral t -- | Hold the process for a random time interval having the triangular distribution. randomTriangularProcess :: Double -- ^ the minimum time interval -> Double -- ^ a median of the time interval -> Double -- ^ the maximum time interval -> Process Double -- ^ a computation of the time interval -- for which the process was actually held randomTriangularProcess min median max = do t <- liftParameter $ randomTriangular min median max holdProcess t return t -- | Hold the process for a random time interval having the triangular distribution. randomTriangularProcess_ :: Double -- ^ the minimum time interval -> Double -- ^ a median of the time interval -> Double -- ^ the maximum time interval -> Process () randomTriangularProcess_ min median max = do t <- liftParameter $ randomTriangular min median max holdProcess t -- | Hold the process for a random time interval distributed normally. randomNormalProcess :: Double -- ^ the mean time interval -> Double -- ^ the time interval deviation -> Process Double -- ^ a computation of the time interval -- for which the process was actually held randomNormalProcess mu nu = do t <- liftParameter $ randomNormal mu nu when (t > 0) $ holdProcess t return t -- | Hold the process for a random time interval distributed normally. randomNormalProcess_ :: Double -- ^ the mean time interval -> Double -- ^ the time interval deviation -> Process () randomNormalProcess_ mu nu = do t <- liftParameter $ randomNormal mu nu when (t > 0) $ holdProcess t -- | Hold the process for a random time interval having the lognormal distribution. randomLogNormalProcess :: 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 -> Process Double -- ^ a computation of the time interval -- for which the process was actually held randomLogNormalProcess mu nu = do t <- liftParameter $ randomLogNormal mu nu holdProcess t return t -- | Hold the process for a random time interval having the lognormal distribution. randomLogNormalProcess_ :: 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 -> Process () randomLogNormalProcess_ mu nu = do t <- liftParameter $ randomLogNormal mu nu holdProcess t -- | Hold the process for a random time interval distributed exponentially -- with the specified mean (the reciprocal of the rate). randomExponentialProcess :: Double -- ^ the mean time interval (the reciprocal of the rate) -> Process Double -- ^ a computation of the time interval -- for which the process was actually held randomExponentialProcess mu = do t <- liftParameter $ randomExponential mu holdProcess t return t -- | Hold the process for a random time interval distributed exponentially -- with the specified mean (the reciprocal of the rate). randomExponentialProcess_ :: Double -- ^ the mean time interval (the reciprocal of the rate) -> Process () randomExponentialProcess_ mu = do t <- liftParameter $ randomExponential mu holdProcess t -- | Hold the process for a random time interval having the Erlang distribution with -- the specified scale (the reciprocal of the rate) and shape parameters. randomErlangProcess :: Double -- ^ the scale (the reciprocal of the rate) -> Int -- ^ the shape -> Process Double -- ^ a computation of the time interval -- for which the process was actually held randomErlangProcess beta m = do t <- liftParameter $ randomErlang beta m holdProcess t return t -- | Hold the process for a random time interval having the Erlang distribution with -- the specified scale (the reciprocal of the rate) and shape parameters. randomErlangProcess_ :: Double -- ^ the scale (the reciprocal of the rate) -> Int -- ^ the shape -> Process () randomErlangProcess_ beta m = do t <- liftParameter $ randomErlang beta m holdProcess t -- | Hold the process for a random time interval having the Poisson distribution with -- the specified mean. randomPoissonProcess :: Double -- ^ the mean time interval -> Process Int -- ^ a computation of the time interval -- for which the process was actually held randomPoissonProcess mu = do t <- liftParameter $ randomPoisson mu holdProcess $ fromIntegral t return t -- | Hold the process for a random time interval having the Poisson distribution with -- the specified mean. randomPoissonProcess_ :: Double -- ^ the mean time interval -> Process () randomPoissonProcess_ mu = do t <- liftParameter $ randomPoisson mu holdProcess $ fromIntegral t -- | Hold the process for a random time interval having the binomial distribution -- with the specified probability and trials. randomBinomialProcess :: Double -- ^ the probability -> Int -- ^ the number of trials -> Process Int -- ^ a computation of the time interval -- for which the process was actually held randomBinomialProcess prob trials = do t <- liftParameter $ randomBinomial prob trials holdProcess $ fromIntegral t return t -- | Hold the process for a random time interval having the binomial distribution -- with the specified probability and trials. randomBinomialProcess_ :: Double -- ^ the probability -> Int -- ^ the number of trials -> Process () randomBinomialProcess_ prob trials = do t <- liftParameter $ randomBinomial prob trials holdProcess $ fromIntegral t -- | Hold the process for a random time interval having the Gamma distribution -- with the specified shape and scale. randomGammaProcess :: Double -- ^ the shape -> Double -- ^ the scale (a reciprocal of the rate) -> Process Double -- ^ a computation of the time interval -- for which the process was actually held randomGammaProcess kappa theta = do t <- liftParameter $ randomGamma kappa theta holdProcess t return t -- | Hold the process for a random time interval having the Gamma distribution -- with the specified shape and scale. randomGammaProcess_ :: Double -- ^ the shape -> Double -- ^ the scale (a reciprocal of the rate) -> Process () randomGammaProcess_ kappa theta = do t <- liftParameter $ randomGamma kappa theta holdProcess t -- | Hold the process for a random time interval having the Beta distribution -- with the specified shape parameters (alpha and beta). randomBetaProcess :: Double -- ^ the shape (alpha) -> Double -- ^ the shape (beta) -> Process Double -- ^ a computation of the time interval -- for which the process was actually held randomBetaProcess alpha beta = do t <- liftParameter $ randomBeta alpha beta holdProcess t return t -- | Hold the process for a random time interval having the Beta distribution -- with the specified shape parameters (alpha and beta). randomBetaProcess_ :: Double -- ^ the shape (alpha) -> Double -- ^ the shape (beta) -> Process () randomBetaProcess_ alpha beta = do t <- liftParameter $ randomBeta alpha beta holdProcess t -- | Hold the process for a random time interval having the Weibull distribution -- with the specified shape and scale. randomWeibullProcess :: Double -- ^ the shape -> Double -- ^ the scale -> Process Double -- ^ a computation of the time interval -- for which the process was actually held randomWeibullProcess alpha beta = do t <- liftParameter $ randomWeibull alpha beta holdProcess t return t -- | Hold the process for a random time interval having the Weibull distribution -- with the specified shape and scale. randomWeibullProcess_ :: Double -- ^ the shape -> Double -- ^ the scale -> Process () randomWeibullProcess_ alpha beta = do t <- liftParameter $ randomWeibull alpha beta holdProcess t -- | Hold the process for a random time interval having the specified discrete distribution. randomDiscreteProcess :: DiscretePDF Double -- ^ the discrete probability density function -> Process Double -- ^ a computation of the time interval -- for which the process was actually held randomDiscreteProcess dpdf = do t <- liftParameter $ randomDiscrete dpdf holdProcess t return t -- | Hold the process for a random time interval having the specified discrete distribution. randomDiscreteProcess_ :: DiscretePDF Double -- ^ the discrete probability density function -> Process () randomDiscreteProcess_ dpdf = do t <- liftParameter $ randomDiscrete dpdf holdProcess t