Hmm, is insertWith' new? If I remember right, I think the stack overflows were happening because Map.insertWith isn't strict enough. Otherwise I think the code is the same. But I would expect intTable to be faster, since it uses IntMap, and there's no IntMap.insertWith' as of 6.6.1 (though it may be easy enough to add one).

Chad

On 10/17/07, Thomas Hartman < thomas.hartman@db.com> wrote:

Since I'm interested in the stack overflow issue, and getting acquainted with quickcheck, I thought I would take this opportunity to compare your ordTable with some code Yitzchak Gale posted earlier, against Ham's original problem.

As far as I can tell, they're the same. They work on lists up to 100000 element lists of strings, but on 10^6 size lists I lose patience waiting for them to finish.

Is there a more scientific way of figuring out if one version is better than the other by using, say profiling tools?

Or by reasoning about the code?

t.

****************************************

import Data.List
import qualified Data.Map as M
import Control.Arrow
import Test.QuickCheck
import Test.GenTestData
import System.Random

{-
Is there a library function to take a list of Strings and return a list of
ints showing how many times each String occurs in the list.

So for example:

["egg", "egg", "cheese"] would return [2,1]
-}

testYitzGale n = do
  l <- rgenBndStrRow (10,10) (10^n,10^n)  -- 100000 strings, strings are 10 chars long, works. craps out on 10^6.
  m <- return $ freqFold l    
  putStrLn $ "map items: " ++ ( show $ M.size m )

testCScherer n = do
  l <- rgenBndStrRow (10,10) (10^n,10^n)  -- same limitations as yitz gale code.
  m <- return $ ordTable l    
  putStrLn $ "items: " ++ ( show $ length m )


-- slow for big lists
--freqArr = Prelude.map ( last &&& length ) . group . sort

-- yitz gale code. same as chad scherer code? it's simpler to understand, but is it as fast?
freqFold :: [[Char]] -> M.Map [Char] Int
freqFold = foldl' g M.empty
  where g accum x = M.insertWith' (+) x 1 accum
-- c scherer code. insists on ord. far as I can tell, same speed as yitz.
ordTable :: (Ord a) => [a] -> [(a,Int)]
ordTable xs = M.assocs $! foldl' f M.empty xs
    where f m x = let  m' = M.insertWith (+) x 1 m
                       Just v = M.lookup x m'
                  in v `seq` m'


l = ["egg","egg","cheese"]

-- other quickcheck stuff
--prop_unchanged_by_reverse = \l -> ( freqArr (l :: [[Char]]) ) == ( freqArr $ reverse l )
--prop_freqArr_eq_freqFold = \l -> ( freqArr (l :: [[Char]]) == (freqFold l))
--test1 = quickCheck prop_unchanged_by_reverse
--test2 = quickCheck prop_freqArr_eq_freqFold

--------------- generate test data:
genBndStrRow (minCols,maxCols) (minStrLen, maxStrLen) = rgen ( genBndLoL (minStrLen, maxStrLen) (minCols,maxCols) )

gen gen = do
  sg <- newStdGen
  return $ generate 10000 sg gen

-- generator for a list with length between min and max
genBndList :: Arbitrary a => (Int, Int) -> Gen [a]
genBndList (min,max) = do
  len <- choose (min,max)
  vector len


-- lists of lists
--genBndLoL :: (Int, Int) -> (Int, Int) -> Gen [[a]]
genBndLoL (min1,max1) (min2,max2) = do
  len1 <- choose (min1,max1)
  len2 <- choose (min2,max2)
  vec2 len1 len2

--vec2 :: Arbitrary a => Int -> Int -> Gen [[a]]
vec2 n m = sequence [ vector m | i <- [1..n] ]