{-# LANGUAGE FlexibleContexts #-} {-# LANGUAGE FlexibleInstances #-} {-# LANGUAGE ScopedTypeVariables #-} {-# OPTIONS_GHC -fno-warn-redundant-constraints #-} module Data.GenValidity.Utils ( -- ** Helper functions for implementing generators upTo, genSplit, genSplit3, genSplit4, genSplit5, genSplit6, genSplit7, genSplit8, arbPartition, shuffle, genListLength, genListOf, genNonEmptyOf, -- ** Helper functions for implementing shrinking functions shrinkTuple, shrinkT2, shrinkT3, shrinkT4, genIntX, genWordX, genFloat, genDouble, genFloatX, genInteger, ) where import Control.Monad (forM, replicateM) import Data.List.NonEmpty (NonEmpty (..)) import qualified Data.List.NonEmpty as NE import Data.Ratio import GHC.Float (castWord32ToFloat, castWord64ToDouble) import System.Random import Test.QuickCheck hiding (Fixed) -- | 'upTo' generates an integer between 0 (inclusive) and 'n'. upTo :: Int -> Gen Int upTo n | n <= 0 = pure 0 | otherwise = choose (0, n) -- | 'genSplit a' generates a tuple '(b, c)' such that 'b + c' equals 'a'. genSplit :: Int -> Gen (Int, Int) genSplit n | n < 0 = pure (0, 0) | otherwise = do i <- choose (0, n) let j = n - i pure (i, j) -- | 'genSplit3 a' generates a triple '(b, c, d)' such that 'b + c + d' equals 'a'. genSplit3 :: Int -> Gen (Int, Int, Int) genSplit3 n | n < 0 = pure (0, 0, 0) | otherwise = do (a, z) <- genSplit n (b, c) <- genSplit z return (a, b, c) -- | 'genSplit4 a' generates a quadruple '(b, c, d, e)' such that 'b + c + d + e' equals 'a'. genSplit4 :: Int -> Gen (Int, Int, Int, Int) genSplit4 n | n < 0 = pure (0, 0, 0, 0) | otherwise = do (y, z) <- genSplit n (a, b) <- genSplit y (c, d) <- genSplit z return (a, b, c, d) -- | 'genSplit5 a' generates a quintuple '(b, c, d, e, f)' such that 'b + c + d + e + f' equals 'a'. genSplit5 :: Int -> Gen (Int, Int, Int, Int, Int) genSplit5 n | n < 0 = pure (0, 0, 0, 0, 0) | otherwise = do (y, z) <- genSplit n (a, b, c) <- genSplit3 y (d, e) <- genSplit z return (a, b, c, d, e) -- | 'genSplit6 a' generates a sextuple '(b, c, d, e, f, g)' such that 'b + c + d + e + f + g' equals 'a'. genSplit6 :: Int -> Gen (Int, Int, Int, Int, Int, Int) genSplit6 n | n < 0 = pure (0, 0, 0, 0, 0, 0) | otherwise = do (y, z) <- genSplit n (a, b, c) <- genSplit3 y (d, e, f) <- genSplit3 z return (a, b, c, d, e, f) -- | 'genSplit7 a' generates a septtuple '(b, c, d, e, f, g)' such that 'b + c + d + e + f + g' equals 'a'. genSplit7 :: Int -> Gen (Int, Int, Int, Int, Int, Int, Int) genSplit7 n | n < 0 = pure (0, 0, 0, 0, 0, 0, 0) | otherwise = do (y, z) <- genSplit n (a, b, c) <- genSplit3 y (d, e, f, g) <- genSplit4 z return (a, b, c, d, e, f, g) -- | 'genSplit8 a' generates a octtuple '(b, c, d, e, f, g, h)' such that 'b + c + d + e + f + g + h' equals 'a'. genSplit8 :: Int -> Gen (Int, Int, Int, Int, Int, Int, Int, Int) genSplit8 n | n < 0 = pure (0, 0, 0, 0, 0, 0, 0, 0) | otherwise = do (y, z) <- genSplit n (a, b, c, d) <- genSplit4 y (e, f, g, h) <- genSplit4 z return (a, b, c, d, e, f, g, h) -- | 'arbPartition n' generates a list 'ls' such that 'sum ls' equals 'n', approximately. arbPartition :: Int -> Gen [Int] arbPartition 0 = pure [] arbPartition i = genListLengthWithSize i >>= go i where go :: Int -> Int -> Gen [Int] go size len = do us <- replicateM len $ choose (0, 1) let invs = map (invE 0.25) us -- Rescale the sizes to (approximately) sum to the given size. pure $ map (round . (* (fromIntegral size / sum invs))) invs -- Use an exponential distribution for generating the -- sizes in the partition. invE :: Double -> Double -> Double invE lambda u = (- log (1 - u)) / lambda genNonEmptyOf :: Gen a -> Gen (NonEmpty a) genNonEmptyOf gen = do l <- genListOf gen case NE.nonEmpty l of Nothing -> scale (+ 1) $ genNonEmptyOf gen Just ne -> pure ne -- Uses 'genListLengthWithSize' with the size parameter genListLength :: Gen Int genListLength = sized genListLengthWithSize -- Generate a list length with the given size genListLengthWithSize :: Int -> Gen Int genListLengthWithSize maxLen = round . invT (fromIntegral maxLen) <$> choose (0, 1) where -- Use a triangle distribution for generating the -- length of the list -- with minimum length '0', mode length '2' -- and given max length. invT :: Double -> Double -> Double invT m u = let a = 0 b = m c = 2 fc = (c - a) / (b - a) in if u < fc then a + sqrt (u * (b - a) * (c - a)) else b - sqrt ((1 - u) * (b - a) * (b - c)) -- | A version of @listOf@ that takes size into account more accurately. -- -- This generator distributes the size that is is given among the values -- in the list that it generates. genListOf :: Gen a -> Gen [a] genListOf func = sized $ \n -> do pars <- arbPartition n forM pars $ \i -> resize i func shrinkTuple :: (a -> [a]) -> (b -> [b]) -> (a, b) -> [(a, b)] shrinkTuple sa sb (a, b) = ((,) <$> sa a <*> sb b) ++ [(a', b) | a' <- sa a] ++ [(a, b') | b' <- sb b] -- | Turn a shrinking function into a function that shrinks tuples. shrinkT2 :: (a -> [a]) -> (a, a) -> [(a, a)] shrinkT2 s (a, b) = (,) <$> s a <*> s b -- | Turn a shrinking function into a function that shrinks triples. shrinkT3 :: (a -> [a]) -> (a, a, a) -> [(a, a, a)] shrinkT3 s (a, b, c) = (,,) <$> s a <*> s b <*> s c -- | Turn a shrinking function into a function that shrinks quadruples. shrinkT4 :: (a -> [a]) -> (a, a, a, a) -> [(a, a, a, a)] shrinkT4 s (a, b, c, d) = (,,,) <$> s a <*> s b <*> s c <*> s d -- | Generate Int, Int8, Int16, Int32 and Int64 values smartly. -- -- * Some at the border -- * Some around zero -- * Mostly uniformly genIntX :: forall a. (Integral a, Bounded a, Random a) => Gen a genIntX = frequency [ (1, extreme), (1, small), (8, uniformInt) ] where extreme :: Gen a extreme = sized $ \s -> oneof [ choose (maxBound - fromIntegral s, maxBound), choose (minBound, minBound + fromIntegral s) ] small :: Gen a small = sized $ \s -> choose (- fromIntegral s, fromIntegral s) uniformInt :: Gen a uniformInt = choose (minBound, maxBound) -- | Generate Word, Word8, Word16, Word32 and Word64 values smartly. -- -- * Some at the border -- * Some around zero -- * Mostly uniformly genWordX :: forall a. (Integral a, Bounded a, Random a) => Gen a genWordX = frequency [ (1, extreme), (1, small), (8, uniformWord) ] where extreme :: Gen a extreme = sized $ \s -> choose (maxBound - fromIntegral s, maxBound) small :: Gen a small = sized $ \s -> choose (0, fromIntegral s) uniformWord :: Gen a uniformWord = choose (minBound, maxBound) -- | See 'genFloatX' genFloat :: Gen Float genFloat = genFloatX castWord32ToFloat -- | See 'genFloatX' genDouble :: Gen Double genDouble = genFloatX castWord64ToDouble -- | Generate floating point numbers smartly: -- -- * Some denormalised -- * Some around zero -- * Some around the bounds -- * Some by encoding an Integer and an Int to a floating point number. -- * Some accross the entire range -- * Mostly uniformly via the bitrepresentation -- -- The function parameter is to go from the bitrepresentation to the floating point value. genFloatX :: forall a w. (Read a, RealFloat a, Bounded w, Random w) => (w -> a) -> Gen a genFloatX func = frequency [ (1, denormalised), (1, small), (1, aroundBounds), (1, uniformViaEncoding), (6, reallyUniform) ] where denormalised :: Gen a denormalised = elements [ read "NaN", read "Infinity", read "-Infinity", read "-0" ] -- This is what Quickcheck does, -- but inlined so QuickCheck cannot change -- it behind the scenes in the future. small :: Gen a small = sized $ \n -> do let n' = toInteger n let precision = 9999999999999 :: Integer b <- choose (1, precision) a <- choose ((- n') * b, n' * b) pure (fromRational (a % b)) upperSignificand :: Integer upperSignificand = floatRadix (0.0 :: a) ^ floatDigits (0.0 :: a) lowerSignificand :: Integer lowerSignificand = (- upperSignificand) (lowerExponent, upperExponent) = floatRange (0.0 :: a) aroundBounds :: Gen a aroundBounds = do s <- sized $ \n -> oneof [ choose (lowerSignificand, lowerSignificand + fromIntegral n), choose (upperSignificand - fromIntegral n, upperSignificand) ] e <- sized $ \n -> oneof [ choose (lowerExponent, lowerExponent + n), choose (upperExponent - n, upperExponent) ] pure $ encodeFloat s e uniformViaEncoding :: Gen a uniformViaEncoding = do s <- choose (lowerSignificand, upperSignificand) e <- choose $ floatRange (0.0 :: a) pure $ encodeFloat s e -- Not really uniform, but good enough reallyUniform :: Gen a reallyUniform = func <$> choose (minBound, maxBound) genInteger :: Gen Integer genInteger = sized $ \s -> oneof $ (if s >= 10 then (genBiggerInteger :) else id) [ genIntSizedInteger, small ] where small = sized $ \s -> choose (- toInteger s, toInteger s) genIntSizedInteger = toInteger <$> (genIntX :: Gen Int) genBiggerInteger = sized $ \s -> do (a, b, c) <- genSplit3 s ai <- resize a genIntSizedInteger bi <- resize b genInteger ci <- resize c genIntSizedInteger pure $ ai * bi + ci