aivika-4.0: Simulation/Aivika/Process/Random.hs
-- |
-- Module : Simulation.Aivika.Process.Random
-- Copyright : Copyright (c) 2009-2015, David Sorokin <david.sorokin@gmail.com>
-- License : BSD3
-- Maintainer : David Sorokin <david.sorokin@gmail.com>
-- Stability : experimental
-- Tested with: GHC 7.8.3
--
-- 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_,
randomNormalProcess,
randomNormalProcess_,
randomExponentialProcess,
randomExponentialProcess_,
randomErlangProcess,
randomErlangProcess_,
randomPoissonProcess,
randomPoissonProcess_,
randomBinomialProcess,
randomBinomialProcess_) where
import Control.Monad
import Control.Monad.Trans
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 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 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