probable

Build Status

Simple random value generation for haskell, using an efficient random generator and minimizing system calls. But the library also lets you work with distributions over a finite set, adapting code from Eric Kidd's posts, and all the usual distributions covered in the statistics package.

You can see how it looks in examples, or below. You can view the documentation for 0.1 here.

Example

Simple example of random generation for your types, using probable.

module Main where
import Control.Applicative
import Control.Monad
import Math.Probable
import qualified Data.Vector.Unboxed as VU
data Person = Person 
 { age :: Int
 , weight :: Double
 , salary :: Int
 } deriving (Eq, Show)
person :: RandT IO Person
person = 
 Person <$> intIn (1, 100)
 <*> doubleIn (2, 130)
 <*> intIn (500, 10000)
randomPersons :: Int -> IO [Person]
randomPersons n = mwc $ listOf n person
randomDoubles :: Int -> IO (VU.Vector Double)
randomDoubles n = mwc $ vectorOf n double
main :: IO ()
main = do
	randomPersons 10 >>= mapM_ print
	randomDoubles 10 >>= VU.mapM_ print

Distributions over finite sets, conditional probabilities and random sampling.

module Main where
import Math.Probable
import qualified Data.Vector as V
data Book = Interesting 
		 | Boring
	deriving (Eq, Show)
bookPrior :: Finite d => d Book
bookPrior = weighted [ (Interesting, 0.2) 
					 , (Boring, 0.8) 
					 ]
twoBooks :: Finite d => d (Book, Book)
twoBooks = do
	book1 <- bookPrior
	book2 <- bookPrior
	return (book1, book2)
sampleBooks :: RandT IO (V.Vector Book)
sampleBooks = vectorOf 10 bookPrior
oneInteresting :: Fin (Book, Book)
oneInteresting = bayes $ do
	(b1, b2) <- twoBooks
	condition (b1 == Interesting || b2 == Interesting)
	return (b1, b2)
main :: IO ()
main = do
	print $ exact bookPrior
	mwc sampleBooks >>= print
	print $ exact twoBooks
	print $ exact oneInteresting

Contact

This library is written and maintained by Alp Mestanogullari.

Feel free to contact me for any feedback, comment, suggestion, bug report and what not.