{-# LANGUAGE TypeFamilies, MultiParamTypeClasses #-} -- | -- Module : Simulation.Aivika.Trans.Var.Unboxed -- Copyright : Copyright (c) 2009-2017, 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 an unboxed variable that is bound up with the event queue and -- that keeps the history of changes storing the values in unboxed arrays, which -- allows using the variable in differential and difference equations of -- System Dynamics within hybrid discrete-continuous simulation. -- -- Because of using the arrays, it would usually be a logical mistake to -- use this variable for collecting statistics. In most cases, -- the statistics can actually be collected with a very small footprint -- by updating immutable 'SamplingStats' and 'TimingStats' values in -- a mutable 'Ref' reference. -- module Simulation.Aivika.Trans.Var.Unboxed (MonadVar(..)) where import Data.Array import Simulation.Aivika.Trans.Ref import Simulation.Aivika.Trans.DES import Simulation.Aivika.Trans.Internal.Simulation import Simulation.Aivika.Trans.Internal.Dynamics import Simulation.Aivika.Trans.Internal.Event import Simulation.Aivika.Trans.Signal import Simulation.Aivika.Trans.Statistics -- | A type class of monads within which we can create mutable unboxed variables. class MonadDES m => MonadVar m a where -- | Like the 'Ref' reference but keeps the history of changes in -- different time points. The 'Var' variable is safe to be used in -- the hybrid discrete-continuous simulation. Only this variable can -- be much slower than the reference. -- -- For example, the memoised values of the variable can be used in -- the differential and difference equations of System Dynamics, while -- the variable iself can be updated within the discrete event simulation. -- -- Because of using arrays, it would usually be a logical mistake to use -- the variable for collecting statistics. In most cases, the statistics -- can actually be collected with a very small footprint by updating immutable -- 'SamplingStats' and 'TimingStats' values in a mutable @Ref@ reference. data Var m a -- | Create a new variable. newVar :: a -> Simulation m (Var m a) -- | Read the first actual, i.e. memoised, value of a variable for the requested time -- actuating the current events from the queue if needed. -- -- This computation can be used in the ordinary differential and -- difference equations of System Dynamics. varMemo :: Var m a -> Dynamics m a -- | Read the recent actual value of a variable for the requested time. -- -- This computation is destined to be used within discrete event simulation. readVar :: Var m a -> Event m a -- | Write a new value into the variable. writeVar :: Var m a -> a -> Event m () -- | Mutate the contents of the variable. modifyVar :: Var m a -> (a -> a) -> Event m () -- | Freeze the variable and return in arrays the time points and the corresponding -- first and last values when the variable had changed or had been memoised in -- different time points: (1) the time points are sorted in ascending order; -- (2) the first and last actual values per each time point are provided. -- -- If you need to get all changes including those ones that correspond to the same -- simulation time points then you can use the 'newSignalHistory' function passing -- in the 'varChanged' signal to it and then call function 'readSignalHistory'. freezeVar :: Var m a -> Event m (Array Int Double, Array Int a, Array Int a) -- | Return a signal that notifies about every change of the variable state. varChanged :: Var m a -> Signal m a -- | Return a signal that notifies about every change of the variable state. varChanged_ :: MonadDES m => Var m a -> Signal m ()