aivika-transformers-4.5: Simulation/Aivika/Trans/Process/Random.hs
-- |
-- Module : Simulation.Aivika.Trans.Process.Random
-- Copyright : Copyright (c) 2009-2016, David Sorokin <david.sorokin@gmail.com>
-- License : BSD3
-- Maintainer : David Sorokin <david.sorokin@gmail.com>
-- Stability : experimental
-- Tested with: GHC 8.0.1
--
-- 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.Trans.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.Trans.DES
import Simulation.Aivika.Trans.Generator
import Simulation.Aivika.Trans.Parameter
import Simulation.Aivika.Trans.Parameter.Random
import Simulation.Aivika.Trans.Process
-- | Hold the process for a random time interval distributed uniformly.
randomUniformProcess :: MonadDES m
=> Double
-- ^ the minimum time interval
-> Double
-- ^ the maximum time interval
-> Process m Double
-- ^ a computation of the time interval
-- for which the process was actually held
{-# INLINABLE randomUniformProcess #-}
randomUniformProcess min max =
do t <- liftParameter $ randomUniform min max
holdProcess t
return t
-- | Hold the process for a random time interval distributed uniformly.
randomUniformProcess_ :: MonadDES m
=> Double
-- ^ the minimum time interval
-> Double
-- ^ the maximum time interval
-> Process m ()
{-# INLINABLE randomUniformProcess_ #-}
randomUniformProcess_ min max =
do t <- liftParameter $ randomUniform min max
holdProcess t
-- | Hold the process for a random time interval distributed uniformly.
randomUniformIntProcess :: MonadDES m
=> Int
-- ^ the minimum time interval
-> Int
-- ^ the maximum time interval
-> Process m Int
-- ^ a computation of the time interval
-- for which the process was actually held
{-# INLINABLE randomUniformIntProcess #-}
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_ :: MonadDES m
=> Int
-- ^ the minimum time interval
-> Int
-- ^ the maximum time interval
-> Process m ()
{-# INLINABLE randomUniformIntProcess_ #-}
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 :: MonadDES m
=> Double
-- ^ the minimum time interval
-> Double
-- ^ a median of the time interval
-> Double
-- ^ the maximum time interval
-> Process m Double
-- ^ a computation of the time interval
-- for which the process was actually held
{-# INLINABLE randomTriangularProcess #-}
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_ :: MonadDES m
=> Double
-- ^ the minimum time interval
-> Double
-- ^ a median of the time interval
-> Double
-- ^ the maximum time interval
-> Process m ()
{-# INLINABLE randomTriangularProcess_ #-}
randomTriangularProcess_ min median max =
do t <- liftParameter $ randomTriangular min median max
holdProcess t
-- | Hold the process for a random time interval distributed normally.
randomNormalProcess :: MonadDES m
=> Double
-- ^ the mean time interval
-> Double
-- ^ the time interval deviation
-> Process m Double
-- ^ a computation of the time interval
-- for which the process was actually held
{-# INLINABLE randomNormalProcess #-}
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_ :: MonadDES m
=> Double
-- ^ the mean time interval
-> Double
-- ^ the time interval deviation
-> Process m ()
{-# INLINABLE randomNormalProcess_ #-}
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 :: MonadDES m
=> 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 m Double
-- ^ a computation of the time interval
-- for which the process was actually held
{-# INLINABLE randomLogNormalProcess #-}
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_ :: MonadDES m
=> 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 m ()
{-# INLINABLE randomLogNormalProcess_ #-}
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 :: MonadDES m
=> Double
-- ^ the mean time interval (the reciprocal of the rate)
-> Process m Double
-- ^ a computation of the time interval
-- for which the process was actually held
{-# INLINABLE randomExponentialProcess #-}
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_ :: MonadDES m
=> Double
-- ^ the mean time interval (the reciprocal of the rate)
-> Process m ()
{-# INLINABLE randomExponentialProcess_ #-}
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 :: MonadDES m
=> Double
-- ^ the scale (the reciprocal of the rate)
-> Int
-- ^ the shape
-> Process m Double
-- ^ a computation of the time interval
-- for which the process was actually held
{-# INLINABLE randomErlangProcess #-}
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_ :: MonadDES m
=> Double
-- ^ the scale (the reciprocal of the rate)
-> Int
-- ^ the shape
-> Process m ()
{-# INLINABLE randomErlangProcess_ #-}
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 :: MonadDES m
=> Double
-- ^ the mean time interval
-> Process m Int
-- ^ a computation of the time interval
-- for which the process was actually held
{-# INLINABLE randomPoissonProcess #-}
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_ :: MonadDES m
=> Double
-- ^ the mean time interval
-> Process m ()
{-# INLINABLE randomPoissonProcess_ #-}
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 :: MonadDES m
=> Double
-- ^ the probability
-> Int
-- ^ the number of trials
-> Process m Int
-- ^ a computation of the time interval
-- for which the process was actually held
{-# INLINABLE randomBinomialProcess #-}
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_ :: MonadDES m
=>Double
-- ^ the probability
-> Int
-- ^ the number of trials
-> Process m ()
{-# INLINABLE randomBinomialProcess_ #-}
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 :: MonadDES m
=> Double
-- ^ the shape
-> Double
-- ^ the scale (a reciprocal of the rate)
-> Process m Double
-- ^ a computation of the time interval
-- for which the process was actually held
{-# INLINABLE randomGammaProcess #-}
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_ :: MonadDES m
=> Double
-- ^ the shape
-> Double
-- ^ the scale (a reciprocal of the rate)
-> Process m ()
{-# INLINABLE randomGammaProcess_ #-}
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 :: MonadDES m
=> Double
-- ^ the shape (alpha)
-> Double
-- ^ the shape (beta)
-> Process m Double
-- ^ a computation of the time interval
-- for which the process was actually held
{-# INLINABLE randomBetaProcess #-}
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_ :: MonadDES m
=> Double
-- ^ the shape (alpha)
-> Double
-- ^ the shape (beta)
-> Process m ()
{-# INLINABLE randomBetaProcess_ #-}
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 :: MonadDES m
=> Double
-- ^ the shape
-> Double
-- ^ the scale
-> Process m Double
-- ^ a computation of the time interval
-- for which the process was actually held
{-# INLINABLE randomWeibullProcess #-}
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_ :: MonadDES m
=> Double
-- ^ the shape
-> Double
-- ^ the scale
-> Process m ()
{-# INLINABLE randomWeibullProcess_ #-}
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 :: MonadDES m
=> DiscretePDF Double
-- ^ the discrete probability density function
-> Process m Double
-- ^ a computation of the time interval
-- for which the process was actually held
{-# INLINABLE randomDiscreteProcess #-}
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_ :: MonadDES m
=> DiscretePDF Double
-- ^ the discrete probability density function
-> Process m ()
{-# INLINABLE randomDiscreteProcess_ #-}
randomDiscreteProcess_ dpdf =
do t <- liftParameter $ randomDiscrete dpdf
holdProcess t