probability 0.2.1 → 0.2.2

raw patch · 7 files changed

+64/−23 lines, 7 filesdep +transformersdep −mtldep ~containersdep ~randomPVP ok

version bump matches the API change (PVP)

Dependencies added: transformers

Dependencies removed: mtl

Dependency ranges changed: containers, random

API changes (from Hackage documentation)

Files

• ToDo +3/−0
• probability.cabal +16/−6
• src/Numeric/Probability/Example/Collection.hs +2/−2
• src/Numeric/Probability/Example/Profession.hs +32/−0
• src/Numeric/Probability/Monad.hs +7/−7
• src/Numeric/Probability/Random.hs +2/−2
• src/Numeric/Probability/Show.hs +2/−6

@@ -1,3 +1,6 @@+the library could benefit from Monad transformers like WriterT and Product, see+   http://www.randomhacks.net/articles/2007/02/21/refactoring-probability-distributions+ Examples:    Election and prognoses 

@@ -1,10 +1,10 @@ Name:               probability-Version:            0.2.1+Version:            0.2.2 License:            BSD3 License-File:       COPYRIGHT Author:             Martin Erwig <erwig@eecs.oregonstate.edu>, Steve Kollmansberger Maintainer:         Henning Thielemann <haskell@henning-thielemann.de>-Homepage:           http://darcs.haskell.org/probability+Homepage:           http://haskell.org/haskellwiki/Probabilistic_Functional_Programming Category:           Math, Monads, Graphics Synopsis:           Probabilistic Functional Programming Description:@@ -14,20 +14,29 @@    but extends the List monad by a measure of probability.    Small interface to R plotting. Tested-With:    GHC==6.4.1, GHC==6.8.2-Cabal-Version:  >=1.2+Cabal-Version:  >=1.6 Build-Type:     Simple- Data-Files:   README   ToDo +Source-Repository head+  type:     darcs+  location: http://darcs.haskell.org/probability/++Source-Repository this+  type:     darcs+  location: http://darcs.haskell.org/probability/+  tag:      0.2.2++ Flag splitBase   description: Choose the new smaller, split-up base package.  Library-  Build-Depends: mtl+  Build-Depends: transformers >=0.0.1 && <0.2   If flag(splitBase)-    Build-Depends: base >= 2, random, containers+    Build-Depends: base >= 2, random >=1.0 && <2, containers >=0.1 && <1   Else     Build-Depends: base >= 1.0 && < 2 @@ -55,6 +64,7 @@     Numeric.Probability.Example.MontyHall     Numeric.Probability.Example.NBoys     Numeric.Probability.Example.Predator+    Numeric.Probability.Example.Profession     Numeric.Probability.Example.Queuing     Numeric.Probability.Example.TreeGrowth   Other-Modules:

@@ -8,8 +8,8 @@ import Numeric.Probability.Percentage (Dist)  import Numeric.Probability.Monad (doWhile, )-import Control.Monad.State-   (StateT(StateT, runStateT), evalStateT, liftM2, replicateM)+import Control.Monad.Trans.State (StateT(StateT, runStateT), evalStateT, )+import Control.Monad (liftM2, replicateM, )  import qualified Data.List as List import System.Random (Random)

@@ -0,0 +1,32 @@+{- |+The newspaper "Sueddeutsche" asked their readers+what professions 16 persons have,+by only showing the photographies of them and three choices.++Their statistics was:+22% readers had  0 to  5 correct answers   (category 0)+75% readers had  6 to 11 correct answers   (category 1)+ 3% readers had 12 to 16 correct answers   (category 2)++Can this statistics be explained with random guessing,+or is there some information in the photographies+that the readers could utilize?++I got 6 correct answers.+-}++module Numeric.Probability.Example.Profession where++import qualified Numeric.Probability.Distribution as Dist+++-- type Probability = Rational+type Probability = Double+type Dist a = Dist.T Probability a++correctAnswers :: Dist Int+correctAnswers = sum $ replicate 16 $ Dist.fromFreqs [(0,2), (1,1)]++categories :: Dist Int+categories =+   Dist.map (\n -> if n<=5 then 0 else if n<=11 then 1 else 2) correctAnswers

@@ -20,9 +20,9 @@ -- | like 'iterate' but returns all intermediate values walk :: (Monad m) => Int -> (a -> m a) -> (a -> m [a]) walk n f =-   let recurse 0 _ = return []-       recurse m x = liftM (x:) (recurse (pred m) =<< f x)-   in  recurse n+   let recourse 0 _ = return []+       recourse m x = liftM (x:) (recourse (pred m) =<< f x)+   in  recourse n   {- |@@ -31,8 +31,8 @@ -} doWhile :: Monad m => (a -> Bool) -> (a -> m a) -> (a -> m a) doWhile p t =-   let recurse x = t x >>= \l -> if p l then recurse l else return l-   in  recurse+   let recourse x = t x >>= \l -> if p l then recourse l else return l+   in  recourse  {- | While loop with a priori check.@@ -40,8 +40,8 @@ -} while :: Monad m => (a -> Bool) -> (a -> m a) -> (a -> m a) while p t =-   let recurse x = if p x then t x >>= recurse else return x-   in  recurse+   let recourse x = if p x then t x >>= recourse else return x+   in  recourse   whileTrace :: Monad m => (a -> m Bool) -> m a -> m [a]

@@ -7,7 +7,7 @@ import qualified System.Random as Random import System.Random (Random, ) -import Control.Monad.State (State(State), evalState, )+import Control.Monad.Trans.State (State, state, evalState, )  import qualified System.IO as IO import Prelude hiding (print)@@ -29,7 +29,7 @@  randomR :: Random.Random a => (a, a) -> T a randomR rng =-   Cons (State (Random.randomR rng))+   Cons (state (Random.randomR rng))  {- | Run random action in 'IO' monad.

@@ -1,16 +1,12 @@ module Numeric.Probability.Show where  showL :: Show a => Int -> a -> String-showL n x = s++rep (n-length s) ' '+showL n x = s ++ replicate (n-length s) ' '             where s=show x  showR :: Show a => Int -> a -> String-showR n x = rep (n-length s) ' '++s+showR n x = replicate (n-length s) ' ' ++ s             where s=show x  --showP :: Float -> String --showP f =  showR 3 (round (f*100))++"%"--rep :: Int -> a -> [a]-rep n x = take n (repeat x)-