random-variates 0.1.5.0 → 0.1.5.1

raw patch · 4 files changed

+10/−15 lines, 4 filesPVP ok

version bump matches the API change (PVP)

API changes (from Hackage documentation)

Files

random-variates.cabal +1/−1
src/Stochastic/Distributions/Continuous.hs +2/−5
src/Stochastic/Distributions/Discrete.hs +5/−7
src/Stochastic/Uniform.hs +2/−2

random-variates.cabal view

@@ -2,7 +2,7 @@ -- documentation, see http://haskell.org/cabal/users-guide/  name:                random-variates-version:             0.1.5.0+version:             0.1.5.1 synopsis:            "Uniform RNG => Non-Uniform RNGs" description:         "Collection of transforms uniform random number generators (RNGs) into any of a dozen common RNGs. Each presenting several common interfaces. Additionally Empirical distributions can be sampled from and tested (chi-squared) against theoretical distributions."    license:             MIT

src/Stochastic/Distributions/Continuous.hs view

@@ -66,8 +66,6 @@ intWordDbl :: Int -> Double intWordDbl x = fromRational $ toRational ((fromInteger $ toInteger x) :: Word) -randomN :: forall a . forall b . (RandomGen a, Random b) => Int -> a -> ([b], a)-randomN n = genTake (random) n  expTransform :: Double -> Double -> Double expTransform y x = -(log $ x) / y@@ -78,13 +76,12 @@   entropy (Sample (Normal mean dev m) u) = (entropy u) + (fromMaybe 0 (fmap (\_->1) m))      rand (Sample (Exponential y) u) =-    mapTuple (expTransform y) (Sample $ Exponential y) (random u)+    mapTuple (expTransform y) (Sample $ Exponential y) (rand u)   rand (Sample (Normal mean dev m) uni) = f m     where       f (Just x) = (x, (Sample (Normal mean dev Nothing) uni'))       f Nothing  = (y, (Sample (Normal mean dev (Just z)) uni'))-      (vs, uni') = randomN 2 uni-      [u1, u2] = map (id) vs+      ([u1, u2], uni') = rands 2 uni       from_u g = mean + dev * (sqrt (-2 * (log u1))) * ( g (2 * pi * u2) )       y = from_u (sin)       z = from_u (cos)

src/Stochastic/Distributions/Discrete.hs view

@@ -85,8 +85,6 @@         sub             = create (k-1)         (j, pmfj, cdfj) = head sub -nextN :: forall a . RandomGen a => Int -> a -> ([Int], a)-nextN n = genTake (next) n  instance DiscreteSample Sample where   entropy (Sample _ u) = entropy u@@ -96,13 +94,13 @@     (\u ->        length $ filter (pred u) cache  )     (Sample $ Binomial n p cache)-    (random g0)+    (C.rand g0)     where pred u (k, pmf, cdf) = cdf < u   rand (Sample (Geometric p) g0) =     mapTuple     ((\u -> ceiling $ (log u) / (log (1-p))))     (Sample $ Geometric p)-    (random g0)+    (C.rand g0)   rand (Sample (Poisson y) g0) =     let f (x, g1) = (C.expTransform y x, g1) in     mapTuple@@ -113,19 +111,19 @@     mapTuple     (\x -> if (x >= p) then 1 else 0)      (Sample $ Bernoulli p)-    (random g0)+    (C.rand g0)   rand (Sample (ZipF n slope cache) u0) =      mapTuple     (\u ->       1 + (length $ filter (pred u) cache))      (Sample $ ZipF n slope cache)-    (random u0)+    (C.rand u0)     where pred u (k, pmf, cdf) = cdf < u   rand (Sample (Uniform a b) g0) =     mapTuple     (\x -> truncate (toDbl (b - a) * x + toDbl a))     (Sample $ Uniform a b)-    (random g0)+    (C.rand g0)  instance DiscreteDistribution Sample where   cdf  (Sample d _) = cdf  d

src/Stochastic/Uniform.hs view

@@ -15,7 +15,7 @@ import Data.Typeable import Control.Exception(throw, Exception) import Data.Int-+import GHC.Stack(errorWithStackTrace) import System.Random(RandomGen(..))  data UniformRandom = XorShift128Plus Word64 Word64 Integer@@ -53,7 +53,7 @@  instance RandomGen UniformRandom where   next (XorShift128Plus high low entropy) -    | entropy == 0 = throw EntropyExhausted+    | entropy == 0 = errorWithStackTrace "Entropy Exausted"     | otherwise    = final      where       -- eagerly evaluate this function, retain no intermediaries or we might blow the stack