{-# LANGUAGE MultiParamTypeClasses, FlexibleInstances, UndecidableInstances #-} ----------------------------------------------------------------------------- -- | -- Module : Control.Monad.MC.GSL -- Copyright : Copyright (c) , Patrick Perry -- License : BSD3 -- Maintainer : Patrick Perry -- Stability : experimental -- module Control.Monad.MC.GSL ( -- * The Monte Carlo monad MC, runMC, evalMC, execMC, unsafeInterleaveMC, -- * The Monte Carlo monad transformer MCT, runMCT, evalMCT, execMCT, liftMCT, unsafeInterleaveMCT, -- | Pure random number generator creation RNG, mt19937, -- | Random distributions uniform, uniformInt, normal, poisson, ) where import Control.Monad ( liftM, MonadPlus(..) ) import Control.Monad.Cont ( MonadCont(..) ) import Control.Monad.Error ( MonadError(..) ) import Control.Monad.Reader ( MonadReader(..) ) import Control.Monad.State ( MonadState(..) ) import Control.Monad.Writer ( MonadWriter(..) ) import Control.Monad.Trans ( MonadTrans(..), MonadIO(..) ) import Data.Word import System.IO.Unsafe ( unsafePerformIO ) import GSL.Random.Gen hiding ( mt19937 ) import qualified GSL.Random.Gen as Gen import GSL.Random.Dist -- | A Monte Carlo monad with an internal random number generator. newtype MC a = MC (RNG -> (a,RNG)) -- | Run this Monte Carlo monad with the given initial random number generator, -- getting the result and the new random number generator. runMC :: MC a -> RNG -> (a, RNG) runMC (MC g) r = let r' = unsafePerformIO $ cloneRNG r in r' `seq` g r' {-# NOINLINE runMC #-} -- | Evaluate this Monte Carlo monad and throw away the final random number -- generator. Very much like @fst@ composed with @runMC@. evalMC :: MC a -> RNG -> a evalMC g r = fst $ runMC g r -- | Exicute this Monte Carlo monad and return the final random number -- generator. Very much like @snd@ composed with @runMC@. execMC :: MC a -> RNG -> RNG execMC g r = snd $ runMC g r -- | Get the baton from the Monte Carlo monad without performing any -- computations. Useful but dangerous. unsafeInterleaveMC :: MC a -> MC a unsafeInterleaveMC (MC m) = MC $ \r -> let (a,_) = m r in (a,r) instance Functor MC where fmap f (MC m) = MC $ \r -> let (a,r') = m r in (f a, r') instance Monad MC where return a = MC $ \r -> (a,r) (MC m) >>= k = MC $ \r -> let (a, r') = m r (MC m') = k a in m' r' instance MonadState RNG MC where get = MC $ getHelp put r' = MC $ putHelp r' getHelp :: RNG -> (RNG,RNG) getHelp r = unsafePerformIO $ do r' <- cloneRNG r r' `seq` return (r',r) {-# NOINLINE getHelp #-} putHelp :: RNG -> RNG -> ((),RNG) putHelp r' r = unsafePerformIO $ do io <- copyRNG r r' io `seq` return ((),r) {-# NOINLINE putHelp #-} -- | A parameterizable Monte Carlo monad for encapsulating an inner -- monad. newtype MCT m a = MCT (RNG -> m (a,RNG)) -- | Similar to 'runMC'. runMCT :: (Monad m) => MCT m a -> RNG -> m (a,RNG) runMCT (MCT g) r = let r' = unsafePerformIO $ cloneRNG r in r' `seq` g r' {-# NOINLINE runMCT #-} -- | Similar to 'evalMC'. evalMCT :: (Monad m) => MCT m a -> RNG -> m a evalMCT g r = do ~(a,_) <- runMCT g r return a -- | Similar to 'execMC'. execMCT :: (Monad m) => MCT m a -> RNG -> m RNG execMCT g r = do ~(_,r') <- runMCT g r return r' -- | Take a Monte Carlo computations and lift it to an MCT computation. liftMCT :: (Monad m) => MC a -> MCT m a liftMCT (MC m) = MCT $ return . m -- | Similar to 'unsafeInterleaveMC'. unsafeInterleaveMCT :: (Monad m) => MCT m a -> MCT m a unsafeInterleaveMCT (MCT g) = MCT $ \r -> do ~(a,_) <- g r return (a,r) instance (Monad m) => Functor (MCT m) where fmap f (MCT m) = MCT $ \r -> do ~(x, r') <- m r return (f x, r') instance (Monad m) => Monad (MCT m) where return a = MCT $ \r -> return (a,r) (MCT m) >>= k = MCT $ \r -> do ~(a,r') <- m r let (MCT m') = k a m' r' fail str = MCT $ \_ -> fail str instance (MonadPlus m) => MonadPlus (MCT m) where mzero = MCT $ \_ -> mzero (MCT m) `mplus` (MCT n) = MCT $ \r -> let r' = unsafePerformIO $ cloneRNG r in r' `seq` (m r `mplus` n r') instance (Monad m) => MonadState RNG (MCT m) where get = MCT $ return . getHelp put r' = MCT $ return . (putHelp r') instance MonadTrans MCT where lift m = MCT $ \r -> do a <- m return (a,r) instance (MonadCont m) => MonadCont (MCT m) where callCC f = MCT $ \r -> callCC $ \c -> let (MCT m) = (f (\a -> MCT $ \r' -> c (a, r'))) in m r instance (MonadError e m) => MonadError e (MCT m) where throwError = lift . throwError (MCT m) `catchError` h = MCT $ \r -> m r `catchError` \e -> let (MCT m') = h e in m' r instance (MonadIO m) => MonadIO (MCT m) where liftIO = lift . liftIO instance (MonadReader r m) => MonadReader r (MCT m) where ask = lift ask local f (MCT m) = MCT $ \r -> local f (m r) instance (MonadState s m) => MonadState s (MCT m) where get = lift get put = lift . put instance (MonadWriter w m) => MonadWriter w (MCT m) where tell = lift . tell listen (MCT m) = MCT $ \r -> do ~((a,r'),w) <- listen (m r) return ((a,w),r') pass (MCT m) = MCT $ \r -> pass $ do ~((a,f),r') <- m r return ((a,r'),f) -- | Get a Mersenne Twister random number generator seeded with the given -- value. mt19937 :: Word64 -> RNG mt19937 s = unsafePerformIO $ do r <- newRNG Gen.mt19937 setSeed r s return r {-# NOINLINE mt19937 #-} -- | @uniformInt n@ generates an integer uniformly in the range @[0,n-1]@. -- It is an error to call this function with a non-positive value. uniformInt :: Int -> MC Int uniformInt n = MC $ uniformIntHelp n uniformIntHelp :: Int -> RNG -> (Int,RNG) uniformIntHelp n r = unsafePerformIO $ do x <- getUniformInt r n x `seq` return (x,r) -- | @uniform a b@ generates a value uniformly distributed in @[a,b)@. uniform :: Double -> Double -> MC Double uniform a b = MC $ uniformHelp a b uniformHelp :: Double -> Double -> RNG -> (Double,RNG) uniformHelp a b r = unsafePerformIO $ do x <- getFlat r a b x `seq` return (x,r) {-# NOINLINE uniformHelp #-} -- | @normal mu sigma@ generates a Normal random variable with mean -- @mu@ and standard deviation @sigma@. normal :: Double -> Double -> MC Double normal mu sigma = MC $ normalHelp mu sigma normalHelp :: Double -> Double -> RNG -> (Double,RNG) normalHelp mu sigma r = unsafePerformIO $ do x <- liftM (mu +) $ getGaussian r sigma x `seq` return (x,r) {-# NOINLINE normalHelp #-} -- | @poisson mu@ generates a Poisson random variable with mean @mu@. poisson :: Double -> MC Int poisson mu = MC $ poissonHelp mu poissonHelp :: Double -> RNG -> (Int,RNG) poissonHelp mu r = unsafePerformIO $ do x <- getPoisson r mu x `seq` return (x,r) {-# NOINLINE poissonHelp #-} {- unifInt :: (Monad m) => Int -> MCT m Int unifInt n = MCT $ unifInt' n unifInt' :: (Monad m) => Int -> RNG -> m (Int,RNG) unifInt' n r = unsafePerformIO $ do i <- rngUnifInt r n i `seq` (return . return) (i,r) -}