On 01/15/2013 12:51 AM, Martin Drautzburg wrote:
What would be a good way to represent a Network anyways? I believe the classic approach is a list of nodes and a list vertices. In the simulation I will frequently have to find the process of an input or output and to find the input connected to an output. The node/vertices implementation seems to require scanning lists, which could be slow once I have thousands of processes.
Other than that any pointers to how to construct networks (which go beyond mere graphs) would be much appreciated.
Hello Martin, I guess the exact way depends on what precisely you want to achieve. I'm thinking about two options, hope others will suggest more. Either you try to model it in a pure setting or you go into IO. In a former case you may try to make use of lazy streams, say function of type f :: [a] -> [b] -> [c] is basically your's processing unit which takes two inputs and produces one output. For example, this is an integrator: f1 xs ys = zipWith (+) xs ys summer xs = let ret = f1 xs ys ys = 0 : ret in ret Here you depend on mutually recursive bindings in order to form the loops, so you can't make a dynamic structures this way, I believe. Speaking about IO, you may either go the classic boring way by collecting all the outputs in some mutable data structure and updating them in a loop, or you may try to have some fun with GHC's green threads: import Control.Monad import Control.Concurrent import Control.Concurrent.MVar mkBinaryF f i1 i2 = do ret <- newEmptyMVar let worker = do v1 <- i1 v2 <- i2 res <- f v1 v2 putMVar ret res forkIO $ forever worker return (takeMVar ret) main = do inp2 <- newMVar 0 out <- mkBinaryF (\x y -> return $ x + y) (getLine >>= return . read) (takeMVar inp2) forever $ do v <- out putStrLn $ "out: " ++ show v putMVar inp2 v For a more theoretically backed approach I suggest you to look at CSP. http://www.cs.kent.ac.uk/projects/ofa/chp/ Best wishes, Dmitry