random-fu 0.2.1.1 → 0.2.2.0

raw patch · 2 files changed

+57/−35 lines, 2 filesPVP: major bump suggested

API removals or changes: PVP suggests a major version bump

API changes (from Hackage documentation)

Files

• random-fu.cabal +3/−1
• src/Data/Random/Distribution/Categorical.hs +54/−34

@@ -1,5 +1,5 @@ name:                   random-fu-version:                0.2.1.1+version:                0.2.2.0 stability:              provisional  cabal-version:          >= 1.6@@ -28,6 +28,8 @@                         comparable to other Haskell libraries, but still                         a fair bit slower than straight C implementations of                          the same algorithms.+                        .+                        Changes in 0.2.2.0: Bug fixes in Data.Random.Distribution.Categorical.                         .                         Changes in 0.2.1.1: Changed some one-field data types                         to newtypes, updated types for GHC 7.4's removal of Eq 

@@ -6,7 +6,8 @@ module Data.Random.Distribution.Categorical     ( Categorical     , categorical, categoricalT-    , fromList, toList+    , weightedCategorical, weightedCategoricalT+    , fromList, toList, totalWeight, numEvents     , fromWeightedList, fromObservations     , mapCategoricalPs, normalizeCategoricalPs     , collectEvents, collectEventsBy@@ -39,6 +40,16 @@ categoricalT :: (Num p, Distribution (Categorical p) a) => [(p,a)] -> RVarT m a categoricalT = rvarT . fromList +-- |Construct a 'Categorical' random variable from a list of probabilities+-- and categories, where the probabilities all sum to 1.+weightedCategorical :: (Fractional p, Eq p, Distribution (Categorical p) a) => [(p,a)] -> RVar a+weightedCategorical = rvar . fromWeightedList++-- |Construct a 'Categorical' random process from a list of probabilities +-- and categories, where the probabilities all sum to 1.+weightedCategoricalT :: (Fractional p, Eq p, Distribution (Categorical p) a) => [(p,a)] -> RVarT m a+weightedCategoricalT = rvarT . fromWeightedList+ -- | Construct a 'Categorical' distribution from a list of weighted categories. {-# INLINE fromList #-} fromList :: (Num p) => [(p,a)] -> Categorical p a@@ -52,6 +63,14 @@         g x [] = [x]         g x@(p0,_) ((p1, y):xs) = x : (p1-p0,y) : xs +totalWeight :: Num p => Categorical p a -> p+totalWeight (Categorical ds)+    | V.null ds = 0+    | otherwise = fst (V.last ds)++numEvents :: Categorical p a -> Int+numEvents (Categorical ds) = V.length ds+ -- |Construct a 'Categorical' distribution from a list of weighted categories,  -- where the weights do not necessarily sum to 1. fromWeightedList :: (Fractional p, Eq p) => [(p,a)] -> Categorical p a@@ -165,44 +184,45 @@     (<*>) = ap  -- |Like 'fmap', but for the probabilities of a categorical distribution.-mapCategoricalPs :: (p -> q) -> Categorical p e -> Categorical q e-mapCategoricalPs f (Categorical ds) = Categorical (V.map (first f) ds)+mapCategoricalPs :: (Num p, Num q) => (p -> q) -> Categorical p e -> Categorical q e+mapCategoricalPs f = fromList . map (first f) . toList  -- |Adjust all the weights of a categorical distribution so that they  -- sum to unity and remove all events whose probability is zero. normalizeCategoricalPs :: (Fractional p, Eq p) => Categorical p e -> Categorical p e-normalizeCategoricalPs orig@(Categorical ds) = -    if V.null ds-        then orig-        else runST $ do-            let n = V.length ds-            lastP       <- newSTRef 0-            nDups       <- newSTRef 0-            normalized  <- V.thaw ds-            -            let skip = modifySTRef' nDups (1+)-                save i p x = do-                    d <- readSTRef nDups-                    MV.write normalized (i-d) (p, x)-            -            sequence_-                [ do-                    let (p,x) = ds V.! i-                    p0 <- readSTRef lastP-                    if p == p0-                        then skip-                        else do-                            save i (p * scale) x-                            writeSTRef lastP $! p-                | i <- [0..n-1]-                ]-            -            -- force last element to 1-            d <- readSTRef nDups-            MV.write normalized (n-d-1) (1,lastX)-            Categorical <$> V.unsafeFreeze (MV.unsafeSlice 0 (n-d) normalized)+normalizeCategoricalPs orig@(Categorical ds)+    | ps == 0   = Categorical V.empty+    | otherwise = runST $ do+        lastP       <- newSTRef 0+        nDups       <- newSTRef 0+        normalized  <- V.thaw ds+        +        let n           = V.length ds+            skip        = modifySTRef' nDups (1+)+            save i p x  = do+                d <- readSTRef nDups+                MV.write normalized (i-d) (p, x)+        +        sequence_+            [ do+                let (p,x) = ds V.! i+                p0 <- readSTRef lastP+                if p == p0+                    then skip+                    else do+                        save i (p * scale) x+                        writeSTRef lastP $! p+            | i <- [0..n-1]+            ]+        +        -- force last element to 1+        d <- readSTRef nDups+        let n' = n-d+        (_,lastX) <- MV.read normalized (n'-1)+        MV.write normalized (n'-1) (1,lastX)+        Categorical <$> V.unsafeFreeze (MV.unsafeSlice 0 n' normalized)     where-        (ps, lastX) = V.last ds+        ps = totalWeight orig         scale = recip ps  -- |strict 'modifySTRef'