[Haskell-cafe] Problems with Haskell

Sun Oct 18 23:07:23 EDT 2009

Before anything else, I want to point out that I have no intention to confront your community, or denigrate Haskell. A few days ago I answered an email from a Clean programmer on something related to Clean. He was worried that Clean team could give up its good work, and Clean could disappear; therefore, he was thinking about switching to Haskell. Since I thought that my email could be of interest for the Clean community, I posted it in the -- small-- Clean list :-(Clean is not as popular as Haskell). I received a lot of furious and offensive private emails for suggesting the Clean programmer to stick with Clean. However, I also received a very polite, humorous, and illuminating private email from a person who seems to work at Microsoft. His name is Simon Peyton-Jones. He
urged me to post my comments on a Haskell cafe. He also filed one of my comments as a bug in a Haskell bug track. Here is a couple of snippets from his email:

--- I think it's v bad that a straightforward program runs so slowly, and it's certainly true
that this is an area we could pay more attention to.

--- Meanwhile, I'm curious: are the arrays in Philippos's program strict?  Or lazy?  If strict,
that's a pretty big difference.

Therefore, here are my comments, with a lot of code. 

A few months ago I came accross an unpublished article about a novel genetic programming system. The system was coded in Larceny Scheme. I translated it to Clean and to Haskell. Unhappily, I cannot post the program here because it is very large, and the authors of the original Lisp program don't want me to divulge it before they see in in a printed page of a Journal. Therefore, I wrote an empty genetic programming framework, just to compare languages. Comparing Clean and Haskell, I noticed:

1 -- Clean compiler almost never let me do very stupid things, like trying to unbox a tree, or to write in a closed file (I will post an example of this in a near future). For instance, Clean compiler would never swallow something like the code below:

import Control.Monad.ST
import Data.Array.ST
import Data.Array.Base
import System.Random

data Op = AND | OR | NOT;
data Tree= L Double | T Op [Tree]

main = print $ runST
          (do arr <- newArray (1,2000000) (L 0.0) :: ST s  (STArray s Int Tree)                   

              go  arr 2000000 0.0 )

go ::  STArray s Int Tree -> Int -> Double -> ST s Double
go a i acc
  | i < 1 = return acc
  | otherwise=do 
               b <- unsafeRead a i {- readArray a i -}
               writeArray a i (setDouble ((getDouble b)+3.0))
               c <-  readArray a i 
               go  a (i-1) (acc+ (getDouble c))

-- What I really need is a random index in Haskell.

getDouble (L r)= r
getDouble _ = 0.0

setDouble r= L r

2 -- Safety does not cost much in Clean. For instance, removing array boundary check does not seem to affect Clean. I believe that it does not affect Haskell either, but I have not verified this point.

3 -- Haskell seems to loop more often than Clean. For instance, Haskell may loop if I change function mutate to

mutate e (L i) xs = (e, xs)
mutate e t (y:ys) = ins t (rnLen t y, ys) where
  ins (T p (L i:xs)) (0, st)=(T p (e:xs), st)
  ins (T p (t:xs)) (n,(r1:rs)) | n > 0=
    let (T p mt, s2)= ins (T p xs)(n-1, rs)
      in (T p (t:mt), s2)
  ins (T p (t:xs)) (n,(r1:rs))
    | rn 2 r1== 0= (T p (e:xs), rs)
    | rn 2 r1== 1= let (xpr, st)= mutate e t rs
                     in (T p (xpr:xs), st)

This might be a bug in my implementation of show Tree. It would be great if you people could "show" me what I did wrong.

4 -- On the plus side, there are libraries in Haskell that seem to behave better than the Clean equivalent libraries. This could be explained by the fact that there are a lot of people coding Haskell libraries, while Clean team seems to be reluctant in accepting libraries from outsiders. For instance, lethevert made a very important improvement in ObjectIO (changing fonts in edit text field), but it was never incorporated into Clean (yes, I wrote a lot of emails to Clean  team about it). Last year, when I was learning Clean, I discovered that many of my professors and teachers are presbyopic. Therefore, it would be a good policy to use very large fonts for homework. I only succeeded in doing it thanks to lethevert. In the case of the program below, Haskell System.Random library seems to work much better than Clean MersenneTwister.

5 --- Any improvement in the program below will be welcome. The program is already very fast thanks to suggestions I received from the bug track people, and from Peyton-Jones. Function "show" seems to loop if I replace mutate in item 3 for mutate in the code below. 

{- ghc gp.hs -O2 --make -}
{- Execute:  gp.exe +RTS -sstderr -}
import Control.Monad.ST
import Data.Array.ST
import Data.Array.Base
import System.Random

data Op = AND | OR | NOT;
data Tree= L Int | T Op [Tree]
psz= 20000
thr=4.0
gates= [AND, NOT, OR]

table= [ (False, False, False), (True, False, True),
         (True, True, False), (False, True, True)]

prt NOT= "NOT"
prt OR= "OR"
prt AND= "AND"

instance Show Tree where
    show (L i) = "L"++(show i)
    show (T p xs) = (prt p)++(show xs)

main = do 
   xs <- (rnList (1, 20000)) 
   print  $ runST $ do
      arr <- newArray_ (1,psz)  :: ST s (STArray s Int Tree)
      (arr, xs1) <- gen0 arr psz xs
      g1 <- evolve 30 arr (L 0) xs1; return $ g1 

gen0 a i xs = if i<=0 then return(a,xs) else do 
     (tree, rs) <- return(rndXpr gates 5 xs)
     writeArray a i tree
     gen0 a (i-1)  rs

mutate e (L i) xs = (e, xs)
mutate e t (y:ys) = ins t (rnLen t y, ys) where 
  ins (T p (L i:xs)) (0, st)=(T p (e:xs), st)
  ins (T p (t:xs)) (n,(r1:rs)) | n > 0= 
    let (T p mt, s2)= ins (T p xs)(n-1, rs) 
      in (T p (t:mt), s2)
  ins (T p (t:xs)) (n,(r1:rs)) 
    | rn 2 r1== 0= (T p (e:xs), rs)
    | rn 2 r1== 1= let (xpr, st)= mutate e t rs 
                     in (T p (xpr:xs), st)

fxy NOT r= T NOT [L (rn 2 r)]
fxy AND st = T AND [L 0, L 1]
fxy OR  st = T OR  [L 0, L 1]

rndXpr fs  beastSz xs= loop beastSz xs where
  rth s r= s!!(rn (length s) r)
  loop n (r1:r2:rs)
     | n<1 = (fxy (rth fs r1) r1, rs)
     |otherwise= mutate (fxy (rth fs r1) r2) f1 rs
    where (f1, ys)=  loop (n-1) rs

run (L 0) x y= x -- Interpreter
run (L 1) x y= y
run (T AND xs) x y = and [run c x y  | c <- xs]
run (T OR xs) x y= or [run c x y | c <- xs]
run (T NOT (t:_)) x y= not (run t x y)

rn n r= (abs r) `rem` n

rnLen (T _ s) r= rn (length s) r

rnList :: (Int, Int) -> IO [Int]
rnList r=getStdGen>>=(\x->return(randomRs r x))

frag  (L i)  st = (L i, st)
frag (T p xs) (r1:r2:rs)
  | rn 2 r2==0= (xpr, rs)
  | otherwise= frag xpr rs  
 where xpr= xs!!(rnLen (T p xs) r1) 

crossover e1 e2 rs = ([c2, c1], rs4)  where
   (g1, rs1) = frag e1 rs
   (g2, rs2) = frag e2 rs1
   (c1, rs3) = mutate g1 e2 rs2
   (c2, rs4) = mutate g2 e1 rs3

nGates (L i)= 0.0
nGates (T p xs) = (-0.1) + sum [nGates g | g <- xs]   

fitness tt gt = (ng + 1.0 + sum [ft t | t <- tt]) where
   ng= nGates gt
   ft (out, t1, t2) | run gt t1 t2 == out= 1.0
   ft _ = 0.0

evolve n p b xs | n < 1 = do
   (arr, xs1) <- gen0 p psz xs
   evolve 30 arr b xs1
evolve n p b (r1:r2:rs) = do 
     n1 <- return $ 1+(rn psz r1)
     n2 <- return $ 1+(rn psz r2)
     g1 <- readArray p n1; g2 <- readArray p n2
     ([c1,c2], rs) <- return $ crossover g1 g2 rs
     insrt c1 p 1 psz 
     insrt c2 p 1 psz 
     res <- best 1 b p
     fitn <- return $ fitness table res
     if fitn > thr 
       then return res else evolve (n-1) p res rs 

best i res p | i >= psz= return res
best i fg p= do 
  g <- readArray p i
  if (fitness table fg) > (fitness table g) 
       then best (i+1) fg p else best (i+1) g p 

insrt g v i sz | i >= sz = return ()
insrt g v i sz = do
   a <- readArray v i
   fg <- return $ fitness table g
   fa <- return $ fitness table a
   if fa > fg then insrt g v (i+1) sz
     else do writeArray v i g

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