-- This library is a way to package up dynamic behavior. It makes it easier to -- dynamically create dynamic components. See the [original release -- notes](/blog/announce/version-0.5.0.elm) on this library to get a feel for how -- it can be used. module Automaton where import Signal (lift,foldp) import List (reverse) import Maybe (Just, Nothing) data Automaton a b = Step (a -> (Automaton a b, b)) -- Run an automaton on a given signal. The automaton steps forward -- whenever the input signal updates. run : Automaton a b -> b -> Signal a -> Signal b run auto base inputs = let step a (Step f, _) = f a in lift (\(x,y) -> y) <| foldp step (auto,base) inputs -- Step an automaton forward once with a given input. step : a -> Automaton a b -> (Automaton a b, b) step a (Step f) = f a -- Compose two automatons, chaining them together. (>>>) : Automaton a b -> Automaton b c -> Automaton a c f >>> g = Step (\a -> let (f', b) = step a f (g', c) = step b g in (f' >>> g', c)) -- Compose two automatons, chaining them together. (<<<) : Automaton b c -> Automaton a b -> Automaton a c g <<< f = f >>> g -- Combine a list of automatons into a single automaton that produces a list. combine : [Automaton a b] -> Automaton a [b] combine autos = Step (\a -> let (autos', bs) = unzip $ map (step a) autos in (combine autos', bs)) -- Create an automaton with no memory. It just applies the given function to -- every input. pure : (a -> b) -> Automaton a b pure f = Step (\x -> (pure f, f x)) -- Create an automaton with state. Requires an initial state and a step -- function to step the state forward. For example, an automaton that counted -- how many steps it has taken would look like this: -- -- count = Automaton a Int -- count = state 0 (\\_ c -> c+1) -- -- It is a stateful automaton. The initial state is zero, and the step function -- increments the state on every step. state : b -> (a -> b -> b) -> Automaton a b state s f = Step (\x -> let s' = f x s in (state s' f, s')) -- Create an automaton with hidden state. Requires an initial state and a -- step function to step the state forward and produce an output. hiddenState : s -> (a -> s -> (s,b)) -> Automaton a b hiddenState s f = Step (\x -> let (s',out) = f x s in (hiddenState s' f, out)) -- Count the number of steps taken. count : Automaton a Int count = state 0 (\_ c -> c + 1) type Queue t = ([t],[t]) empty = ([],[]) enqueue x (en,de) = (x::en, de) dequeue q = case q of ([],[]) -> Nothing (en,[]) -> dequeue ([], reverse en) (en,hd::tl) -> Just (hd, (en,tl)) -- Computes the running average of the last `n` inputs. average : Int -> Automaton Float Float average k = let step n (ns,len,sum) = if len == k then stepFull n (ns,len,sum) else ((enqueue n ns, len+1, sum+n), (sum+n) / (len+1)) stepFull n (ns,len,sum) = case dequeue ns of Nothing -> ((ns,len,sum), 0) Just (m,ns') -> let sum' = sum + n - m in ((enqueue n ns', len, sum'), sum' / len) in hiddenState (empty,0,0) step {-- TODO(evancz): See the following papers for ideas on how to make this library faster and better: - Functional Reactive Programming, Continued - Causal commutative arrows and their optimization Speeding things up is a really low priority. Language features and libraries with nice APIs and are way more important! --}