massiv-1.0.5.0: src/Data/Massiv/Array/Ops/Sort.hs
{-# LANGUAGE BangPatterns #-}
{-# LANGUAGE ExplicitForAll #-}
{-# LANGUAGE FlexibleContexts #-}
{-# LANGUAGE MonoLocalBinds #-}
-- |
-- Module : Data.Massiv.Array.Ops.Sort
-- Copyright : (c) Alexey Kuleshevich 2018-2022
-- License : BSD3
-- Maintainer : Alexey Kuleshevich <lehins@yandex.ru>
-- Stability : experimental
-- Portability : non-portable
module Data.Massiv.Array.Ops.Sort (
tally,
quicksort,
quicksortBy,
quicksortByM,
quicksortAs,
quicksortAsBy,
quicksortAsByM,
quicksortM_,
quicksortByM_,
unsafeUnstablePartitionRegionM,
) where
import Control.Monad (when)
import Control.Monad.IO.Unlift
import Control.Monad.Primitive
import Control.Scheduler
import Data.Bits (countLeadingZeros)
import Data.Massiv.Array.Delayed.Stream
import Data.Massiv.Array.Mutable
import Data.Massiv.Array.Ops.Transform
import Data.Massiv.Core.Common
import Data.Massiv.Vector (scatMaybes, sunfoldrN)
import Data.Word (Word64)
import System.IO.Unsafe
-- | Count number of occurrences of each element in the array. Results will be
-- sorted in ascending order of the element.
--
-- ==== __Example__
--
-- >>> import Data.Massiv.Array as A
-- >>> xs = fromList Seq [2, 4, 3, 2, 4, 5, 2, 1] :: Array P Ix1 Int
-- >>> xs
-- Array P Seq (Sz1 8)
-- [ 2, 4, 3, 2, 4, 5, 2, 1 ]
-- >>> tally xs
-- Array DS Seq (Sz1 5)
-- [ (1,1), (2,3), (3,1), (4,2), (5,1) ]
--
-- @since 0.4.4
tally :: (Manifest r e, Load r ix e, Ord e) => Array r ix e -> Vector DS (e, Int)
tally arr
| isEmpty arr = setComp (getComp arr) empty
| otherwise = scatMaybes $ sunfoldrN (liftSz2 (+) sz oneSz) count (0, 0, sorted ! 0)
where
sz@(Sz k) = size sorted
count (!i, !n, !prev)
| i < k =
let !e' = unsafeLinearIndex sorted i
in if prev == e'
then Just (Nothing, (i + 1, n + 1, prev))
else Just (Just (prev, n), (i + 1, 1, e'))
| otherwise = Just (Just (prev, n), (i + 1, n, prev))
{-# INLINE count #-}
sorted = quicksort $ flatten arr
{-# INLINE tally #-}
-- | Partition a segment of a vector. Starting and ending indices are unchecked.
--
-- @since 1.0.0
unsafeUnstablePartitionRegionM
:: forall r e m
. (Manifest r e, PrimMonad m)
=> MVector (PrimState m) r e
-> (e -> m Bool)
-> Ix1
-- ^ Start index of the region
-> Ix1
-- ^ End index of the region
-> m Ix1
unsafeUnstablePartitionRegionM marr f start end = fromLeft start (end + 1)
where
fromLeft i j
| i == j = pure i
| otherwise = do
e <- f =<< unsafeLinearRead marr i
if e
then fromLeft (i + 1) j
else fromRight i (j - 1)
fromRight i j
| i == j = pure i
| otherwise = do
x <- unsafeLinearRead marr j
e <- f x
if e
then do
unsafeLinearWrite marr j =<< unsafeLinearRead marr i
unsafeLinearWrite marr i x
fromLeft (i + 1) j
else fromRight i (j - 1)
{-# INLINE unsafeUnstablePartitionRegionM #-}
-- | Same as `quicksort` except it accepts any array that is computable.
--
-- @since 1.0.2
quicksortAs
:: (Load r Ix1 e, Manifest r' e, Ord e) => r' -> Vector r e -> Vector r' e
quicksortAs _ arr = unsafePerformIO $ withLoadMArray_ arr quicksortM_
{-# INLINE quicksortAs #-}
-- | Same as `quicksortBy` except it accepts any array that is computable.
--
-- @since 1.0.2
quicksortAsBy
:: (Load r Ix1 e, Manifest r' e) => r' -> (e -> e -> Ordering) -> Vector r e -> Vector r' e
quicksortAsBy _ f arr =
unsafePerformIO $ withLoadMArray_ arr (quicksortByM_ (\x y -> pure $ f x y))
{-# INLINE quicksortAsBy #-}
-- | Same as `quicksortByM` except it accepts any array that is computable.
--
-- @since 1.0.2
quicksortAsByM
:: (Load r Ix1 e, Manifest r' e, MonadUnliftIO m)
=> r'
-> (e -> e -> m Ordering)
-> Vector r e
-> m (Vector r' e)
quicksortAsByM _ f arr =
withRunInIO $ \run -> withLoadMArray_ arr (quicksortByM_ (\x y -> run (f x y)))
{-# INLINE quicksortAsByM #-}
-- | This is an implementation of
-- [Quicksort](https://en.wikipedia.org/wiki/Quicksort), which is an efficient,
-- but unstable sort. This implementation uses Median-of-three for pivot
-- choosing, as such it performs very well not only for random values, but also
-- for common edge cases like already sorted, reversed sorted and arrays with
-- many duplicate elements. It will also respect the computation strategy and
-- will result in a nice speed up for systems with multiple CPUs.
--
-- @since 0.3.2
quicksort
:: (Manifest r e, Ord e) => Vector r e -> Vector r e
quicksort arr = unsafePerformIO $ withMArray_ arr quicksortM_
{-# INLINE quicksort #-}
-- | Same as `quicksortBy`, but instead of `Ord` constraint expects a custom `Ordering`.
--
-- @since 0.6.1
quicksortByM
:: (Manifest r e, MonadUnliftIO m) => (e -> e -> m Ordering) -> Vector r e -> m (Vector r e)
quicksortByM f arr = withRunInIO $ \run -> withMArray_ arr (quicksortByM_ (\x y -> run (f x y)))
{-# INLINE quicksortByM #-}
-- | Same as `quicksortBy`, but instead of `Ord` constraint expects a custom `Ordering`.
--
-- @since 0.6.1
quicksortBy :: Manifest r e => (e -> e -> Ordering) -> Vector r e -> Vector r e
quicksortBy f arr =
unsafePerformIO $ withMArray_ arr (quicksortByM_ (\x y -> pure $ f x y))
{-# INLINE quicksortBy #-}
-- | Manifest version of `quicksort`
--
-- @since 0.3.2
quicksortM_
:: (Ord e, Manifest r e, MonadPrimBase s m)
=> Scheduler s ()
-> MVector s r e
-> m ()
quicksortM_ = quicksortInternalM_ (\e1 e2 -> pure $ e1 < e2) (\e1 e2 -> pure $ e1 == e2)
{-# INLINE quicksortM_ #-}
-- | Same as `quicksortM_`, but instead of `Ord` constraint expects a custom `Ordering`.
--
-- @since 0.6.1
quicksortByM_
:: (Manifest r e, MonadPrimBase s m)
=> (e -> e -> m Ordering)
-> Scheduler s ()
-> MVector s r e
-> m ()
quicksortByM_ compareM =
quicksortInternalM_ (\x y -> (LT ==) <$> compareM x y) (\x y -> (EQ ==) <$> compareM x y)
{-# INLINE quicksortByM_ #-}
quicksortInternalM_
:: (Manifest r e, MonadPrimBase s m)
=> (e -> e -> m Bool)
-> (e -> e -> m Bool)
-> Scheduler s ()
-> MVector s r e
-> m ()
quicksortInternalM_ fLT fEQ scheduler marr
| numWorkers scheduler < 2 || depthPar <= 0 = qsortSeq 0 (k - 1)
| otherwise = qsortPar depthPar 0 (k - 1)
where
-- How deep into the search tree should we continue scheduling jobs. Constants below
-- were discovered empirically:
depthPar = min (logNumWorkers + 4) (logSize - 10)
k = unSz (sizeOfMArray marr)
-- We must use log becuase decinding into a tree creates an exponential number of jobs
logNumWorkers = 63 - countLeadingZeros (fromIntegral (numWorkers scheduler) :: Word64)
-- Using many cores on small vectors only makes things slower
logSize = 63 - countLeadingZeros (fromIntegral k :: Word64)
ltSwap i j = do
ei <- unsafeLinearRead marr i
ej <- unsafeLinearRead marr j
lt <- fLT ei ej
if lt
then do
unsafeLinearWrite marr i ej
unsafeLinearWrite marr j ei
pure ei
else pure ej
{-# INLINE ltSwap #-}
getPivot lo hi = do
let !mid = (hi + lo) `div` 2
_ <- ltSwap mid lo
_ <- ltSwap hi lo
ltSwap mid hi
{-# INLINE getPivot #-}
qsortPar !n !lo !hi =
when (lo < hi) $ do
p <- getPivot lo hi
l <- unsafeUnstablePartitionRegionM marr (`fLT` p) lo (hi - 1)
h <- unsafeUnstablePartitionRegionM marr (`fEQ` p) l hi
if n > 0
then do
let !n' = n - 1
scheduleWork scheduler $ qsortPar n' lo (l - 1)
scheduleWork scheduler $ qsortPar n' h hi
else do
qsortSeq lo (l - 1)
qsortSeq h hi
qsortSeq !lo !hi =
when (lo < hi) $ do
p <- getPivot lo hi
l <- unsafeUnstablePartitionRegionM marr (`fLT` p) lo (hi - 1)
h <- unsafeUnstablePartitionRegionM marr (`fEQ` p) l hi
qsortSeq lo (l - 1)
qsortSeq h hi
{-# INLINE quicksortInternalM_ #-}