{----------------------------------------------------------------------------- reactive-banana ------------------------------------------------------------------------------} {-# LANGUAGE Rank2Types #-} {-# LANGUAGE MultiParamTypeClasses #-} module Reactive.Banana.Combinators ( -- * Synopsis -- | Combinators for building event graphs. -- * Introduction -- $intro1 Event, Behavior, -- $intro2 interpret, -- * Core Combinators module Control.Applicative, module Data.Monoid, never, union, unions, filterE, collect, spill, accumE, apply, stepper, -- $classes -- * Derived Combinators -- ** Filtering filterJust, filterApply, whenE, split, -- ** Accumulation -- $Accumulation. accumB, mapAccum, -- ** Simultaneous event occurrences calm, unionWith, -- ** Apply class Apply(..), ) where import Control.Applicative import Control.Monad import Data.Maybe (isJust, catMaybes) import Data.Monoid (Monoid(..)) import qualified Reactive.Banana.Internal.EventBehavior1 as Prim import Reactive.Banana.Internal.Types2 {----------------------------------------------------------------------------- Introduction ------------------------------------------------------------------------------} {-$intro1 At its core, Functional Reactive Programming (FRP) is about two data types 'Event' and 'Behavior' and the various ways to combine them. -} -- Event -- Behavior {-$intro2 As you can see, both types seem to have a superfluous parameter @t@. The library uses it to rule out certain gross inefficiencies, in particular in connection with dynamic event switching. For basic stuff, you can completely ignore it, except of course for the fact that it will annoy you in your type signatures. While the type synonyms mentioned above are the way you should think about 'Behavior' and 'Event', they are a bit vague for formal manipulation. To remedy this, the library provides a very simple but authoritative model implementation. See "Reactive.Banana.Model" for more. -} {----------------------------------------------------------------------------- Interpetation ------------------------------------------------------------------------------} -- | Interpret an event processing function. -- Useful for testing. interpret :: (forall t. Event t a -> Event t b) -> [[a]] -> IO [[b]] interpret f xs = map toList <$> Prim.interpret (return . unE . f . E) (map Just xs) toList :: Maybe [a] -> [a] toList Nothing = [] toList (Just xs) = xs {----------------------------------------------------------------------------- Core combinators ------------------------------------------------------------------------------} singleton :: a -> [a] singleton x = [x] -- | Event that never occurs. -- Think of it as @never = []@. never :: Event t a never = E $ Prim.mapE singleton Prim.never -- | Merge two event streams of the same type. -- In case of simultaneous occurrences, the left argument comes first. -- Think of it as -- -- > union ((timex,x):xs) ((timey,y):ys) -- > | timex <= timey = (timex,x) : union xs ((timey,y):ys) -- > | timex > timey = (timey,y) : union ((timex,x):xs) ys union :: Event t a -> Event t a -> Event t a union e1 e2 = E $ Prim.unionWith (++) (unE e1) (unE e2) -- | Merge several event streams of the same type. -- -- > unions = foldr union never unions :: [Event t a] -> Event t a unions = foldr union never -- | Allow all event occurrences that are 'Just' values, discard the rest. -- Variant of 'filterE'. filterJust :: Event t (Maybe a) -> Event t a filterJust = E . Prim.filterJust . Prim.mapE (decide . catMaybes) . unE where decide xs = if null xs then Nothing else Just xs -- | Allow all events that fulfill the predicate, discard the rest. -- Think of it as -- -- > filterE p es = [(time,a) | (time,a) <- es, p a] filterE :: (a -> Bool) -> Event t a -> Event t a filterE p = filterJust . fmap (\x -> if p x then Just x else Nothing) -- | Collect simultaneous event occurences. -- The result will never contain an empty list. -- Example: -- -- > collect [(time1, e1), (time1, e2)] = [(time1, [e1,e2])] collect :: Event t a -> Event t [a] collect e = E $ Prim.mapE singleton (unE e) -- | Emit simultaneous event occurrences. -- The first element in the list will be emitted first, and so on. -- -- Up to strictness, we have -- -- > spill . collect = id spill :: Event t [a] -> Event t a spill e = E $ Prim.mapE concat (unE e) -- | Construct a time-varying function from an initial value and -- a stream of new values. Think of it as -- -- > stepper x0 ex = \time -> last (x0 : [x | (timex,x) <- ex, timex < time]) -- -- Note that the smaller-than-sign in the comparision @timex < time@ means -- that the value of the behavior changes \"slightly after\" -- the event occurrences. This allows for recursive definitions. -- -- Also note that in the case of simultaneous occurrences, -- only the last one is kept. stepper :: a -> Event t a -> Behavior t a stepper x e = B $ Prim.stepperB x $ Prim.mapE last $ unE e -- | The 'accumE' function accumulates a stream of events. -- Example: -- -- > accumE "x" [(time1,(++"y")),(time2,(++"z"))] -- > = [(time1,"xy"),(time2,"xyz")] -- -- Note that the output events are simultaneous with the input events, -- there is no \"delay\" like in the case of 'accumB'. accumE :: a -> Event t (a -> a) -> Event t a accumE acc = E . mapAccumE acc . Prim.mapE concatenate . unE where concatenate :: [a -> a] -> a -> ([a],a) concatenate fs acc = (tail values, last values) where values = scanl' (flip ($)) acc fs mapAccumE :: s -> Prim.Event (s -> (a,s)) -> Prim.Event a mapAccumE acc = Prim.mapE fst . Prim.accumE (undefined,acc) . Prim.mapE (. snd) -- strict version of scanl scanl' :: (a -> b -> a) -> a -> [b] -> [a] scanl' f x ys = x : case ys of [] -> [] y:ys -> let z = f x y in z `seq` scanl' f z ys -- | Apply a time-varying function to a stream of events. -- Think of it as -- -- > apply bf ex = [(time, bf time x) | (time, x) <- ex] apply :: Behavior t (a -> b) -> Event t a -> Event t b apply bf ex = E $ Prim.applyE (Prim.mapB map $ unB bf) (unE ex) {-$classes /Further combinators that Haddock can't document properly./ > instance Monoid (Event t (a -> a)) This monoid instance is /not/ the straightforward instance that you would obtain from 'never' and 'union'. Instead of just merging event streams, we use 'unionWith' to compose the functions. This is very useful in the context of 'accumE' and 'accumB' where simultaneous event occurrences are best avoided. > instance Applicative (Behavior t) 'Behavior' is an applicative functor. In particular, we have the following functions. > pure :: a -> Behavior t a The constant time-varying value. Think of it as @pure x = \\time -> x@. > (<*>) :: Behavior t (a -> b) -> Behavior t a -> Behavior t b Combine behaviors in applicative style. Think of it as @bf \<*\> bx = \\time -> bf time $ bx time@. -} {- No monoid instance, sorry. instance Monoid (Event t (a -> a)) where mempty = never mappend = unionWith (flip (.)) -} instance Functor (Event t) where fmap f e = E $ Prim.mapE (map f) (unE e) instance Applicative (Behavior t) where pure x = B $ Prim.pureB x bf <*> bx = B $ Prim.applyB (unB bf) (unB bx) instance Functor (Behavior t) where fmap = liftA {----------------------------------------------------------------------------- Derived Combinators ------------------------------------------------------------------------------} {- Unfortunately, we can't make a Num instance because that would require Eq and Show . instance Num a => Num (Behavior t a) where (+) = liftA2 (+) (-) = liftA2 (-) (*) = liftA2 (*) negate = fmap negate abs = fmap abs signum = fmap signum fromInteger = pure . fromInteger -} -- | Allow all events that fulfill the time-varying predicate, discard the rest. -- Generalization of 'filterE'. filterApply :: Behavior t (a -> Bool) -> Event t a -> Event t a filterApply bp = fmap snd . filterE fst . apply ((\p a-> (p a,a)) <$> bp) -- | Allow events only when the behavior is 'True'. -- Variant of 'filterApply'. whenE :: Behavior t Bool -> Event t a -> Event t a whenE bf = filterApply (const <$> bf) -- | Split event occurrences according to a tag. -- The 'Left' values go into the left component while the 'Right' values -- go into the right component of the result. split :: Event t (Either a b) -> (Event t a, Event t b) split e = (filterJust $ fromLeft <$> e, filterJust $ fromRight <$> e) where fromLeft (Left a) = Just a fromLeft (Right b) = Nothing fromRight (Left a) = Nothing fromRight (Right b) = Just b -- | Combine simultaneous event occurrences into a single occurrence. -- -- > unionWith f e1 e2 = fmap (foldr1 f) <$> collect (e1 `union` e2) unionWith :: (a -> a -> a) -> Event t a -> Event t a -> Event t a unionWith f e1 e2 = E $ Prim.unionWith g (unE e1) (unE e2) where g xs ys = singleton $ foldr1 f (xs ++ ys) -- | Keep only the last occurrence when simultaneous occurrences happen. calm :: Event t a -> Event t a calm = fmap last . collect -- $Accumulation. -- Note: all accumulation functions are strict in the accumulated value! -- acc -> (x,acc) is the order used by 'unfoldr' and 'State'. -- | The 'accumB' function is similar to a /strict/ left fold, 'foldl''. -- It starts with an initial value and combines it with incoming events. -- For example, think -- -- > accumB "x" [(time1,(++"y")),(time2,(++"z"))] -- > = stepper "x" [(time1,"xy"),(time2,"xyz")] -- -- Note that the value of the behavior changes \"slightly after\" -- the events occur. This allows for recursive definitions. accumB :: a -> Event t (a -> a) -> Behavior t a -- accumB x (Event e) = behavior $ AccumB x e accumB acc = stepper acc . accumE acc -- | Efficient combination of 'accumE' and 'accumB'. mapAccum :: acc -> Event t (acc -> (x,acc)) -> (Event t x, Behavior t acc) mapAccum acc ef = (fst <$> e, stepper acc (snd <$> e)) where e = accumE (undefined,acc) ((. snd) <$> ef) infixl 4 <@>, <@ -- | Class for overloading the 'apply' function. class (Functor f, Functor g) => Apply f g where -- | Infix operation for the 'apply' function, similar to '<*>' (<@>) :: f (a -> b) -> g a -> g b -- | Convenience function, similar to '<*' (<@) :: f a -> g b -> g a f <@ g = (const <$> f) <@> g instance Apply (Behavior t) (Event t) where (<@>) = apply