我希望能够使用O(1)分摊的寻址,其矢量类型根据所需的索引而懒惰地增长.
这可以通过使用配对a MVector (PrimState m) a:a PrimRef m [a]来保持余数,使用标准的双重算法进行amoritzed O(1)访问来实现:
{-# LANGUAGE ExistentialQuantification #-}
module LazyVec where
import Control.Monad.Primitive
import Data.PrimRef
import Data.Vector.Mutable (MVector)
import qualified Data.Vector.Mutable as M
import Data.Vector (fromList, thaw)
import Control.Monad (forM_)
data LazyVec m a = PrimMonad m => LazyVec (MVector (PrimState m) a) (PrimRef m [a])
-- prime the LazyVec with the first n elements
lazyFromListN :: PrimMonad m => Int -> [a] -> m (LazyVec m a)
lazyFromListN n xs = do
let (as,bs) = splitAt n xs
mvec <- thaw $ fromList as
mref <- newPrimRef bs
return $ LazyVec mvec mref
-- look up the i'th element
lazyIndex :: PrimMonad m => Int -> LazyVec m a -> m a
lazyIndex i lv@(LazyVec mvec mref) | i < 0 = error "negative index"
| i < n = M.read mvec i
| otherwise = do
xs <- readPrimRef mref
if null xs
then error "index out of range"
else do
-- expand the mvec by some power of 2
-- so that it includes the i'th index
-- or ends
let n' = n * 2 ^ ( 1 + floor (logBase 2 (toEnum (i `div` n))))
let growth = n' - n
let (as, bs) = splitAt growth xs
M.grow mvec $ if null bs then length as else growth
forM_ (zip [n,n+1..] as) . uncurry $ M.write mvec
writePrimRef mref bs
lazyIndex i lv
where n = M.length mvec
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而且我可以使用我的代码 - 但我宁愿重复使用其他人(对于一个,我没有测试过我的代码).
某些包中是否存在具有这些语义的矢量类型(从可能无限列表中延迟创建,O(1)摊销访问)?
正如 Jake McArthur 在评论中指出的那样:“如果它只是一个函数,那么我建议只使用现有的记忆包之一,例如MemoTrie或data-memocombinators。它们应该会让这一切变得简单。”
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