Control.Monad.Bayes.Sampler

SamplerIO and SamplerST are instances of MonadSample. Apply a MonadCond transformer to obtain a MonadInfer that can execute probabilistic models.

Documentation

data SamplerIO a

An IO based random sampler using the MWC-Random package.

Instances

Monad SamplerIO

Defined in Control.Monad.Bayes.Sampler

Methods

(>>=) :: SamplerIO a -> (a -> SamplerIO b) -> SamplerIO b

(>>) :: SamplerIO a -> SamplerIO b -> SamplerIO b

return :: a -> SamplerIO a

fail :: String -> SamplerIO a

Functor SamplerIO

Defined in Control.Monad.Bayes.Sampler

Methods

fmap :: (a -> b) -> SamplerIO a -> SamplerIO b

(<$) :: a -> SamplerIO b -> SamplerIO a

Applicative SamplerIO

Defined in Control.Monad.Bayes.Sampler

Methods

pure :: a -> SamplerIO a

(<*>) :: SamplerIO (a -> b) -> SamplerIO a -> SamplerIO b

liftA2 :: (a -> b -> c) -> SamplerIO a -> SamplerIO b -> SamplerIO c

(*>) :: SamplerIO a -> SamplerIO b -> SamplerIO b

(<*) :: SamplerIO a -> SamplerIO b -> SamplerIO a

MonadIO SamplerIO

Defined in Control.Monad.Bayes.Sampler

Methods

liftIO :: IO a -> SamplerIO a

MonadSample SamplerIO

Defined in Control.Monad.Bayes.Sampler

Methods

random :: SamplerIO Double

uniform :: Double -> Double -> SamplerIO Double

normal :: Double -> Double -> SamplerIO Double

gamma :: Double -> Double -> SamplerIO Double

beta :: Double -> Double -> SamplerIO Double

bernoulli :: Double -> SamplerIO Bool

categorical :: Vector v Double => v Double -> SamplerIO Int

logCategorical :: (Vector v (Log Double), Vector v Double) => v (Log Double) -> SamplerIO Int

uniformD :: [a] -> SamplerIO a

geometric :: Double -> SamplerIO Int

poisson :: Double -> SamplerIO Int

dirichlet :: Vector v Double => v Double -> SamplerIO (v Double)

sampleIO :: SamplerIO a -> IO a

Initialize a pseudo-random number generator using randomness supplied by the operating system. For efficiency this operation should be applied at the very end, ideally once per program.

sampleIOfixed :: SamplerIO a -> IO a

Like sampleIO, but with a fixed random seed. Useful for reproducibility.

sampleIOwith :: SamplerIO a -> GenIO -> IO a

Like sampleIO but with a custom pseudo-random number generator.

data Seed

An immutable snapshot of the state of a Gen.

Instances

Eq Seed

Defined in System.Random.MWC

Methods

(==) :: Seed -> Seed -> Bool

(/=) :: Seed -> Seed -> Bool

Show Seed

Defined in System.Random.MWC

Methods

showsPrec :: Int -> Seed -> ShowS

show :: Seed -> String

showList :: [Seed] -> ShowS

newtype SamplerST a

An ST based random sampler using the mwc-random package.

Constructors

SamplerST (forall s. ReaderT (GenST s) (ST s) a)

Instances

Monad SamplerST

Defined in Control.Monad.Bayes.Sampler

Methods

(>>=) :: SamplerST a -> (a -> SamplerST b) -> SamplerST b

(>>) :: SamplerST a -> SamplerST b -> SamplerST b

return :: a -> SamplerST a

fail :: String -> SamplerST a

Functor SamplerST

Defined in Control.Monad.Bayes.Sampler

Methods

fmap :: (a -> b) -> SamplerST a -> SamplerST b

(<$) :: a -> SamplerST b -> SamplerST a

Applicative SamplerST

Defined in Control.Monad.Bayes.Sampler

Methods

pure :: a -> SamplerST a

(<*>) :: SamplerST (a -> b) -> SamplerST a -> SamplerST b

liftA2 :: (a -> b -> c) -> SamplerST a -> SamplerST b -> SamplerST c

(*>) :: SamplerST a -> SamplerST b -> SamplerST b

(<*) :: SamplerST a -> SamplerST b -> SamplerST a

MonadSample SamplerST

Defined in Control.Monad.Bayes.Sampler

Methods

random :: SamplerST Double

uniform :: Double -> Double -> SamplerST Double

normal :: Double -> Double -> SamplerST Double

gamma :: Double -> Double -> SamplerST Double

beta :: Double -> Double -> SamplerST Double

bernoulli :: Double -> SamplerST Bool

categorical :: Vector v Double => v Double -> SamplerST Int

logCategorical :: (Vector v (Log Double), Vector v Double) => v (Log Double) -> SamplerST Int

uniformD :: [a] -> SamplerST a

geometric :: Double -> SamplerST Int

poisson :: Double -> SamplerST Int

dirichlet :: Vector v Double => v Double -> SamplerST (v Double)

runSamplerST :: SamplerST a -> ReaderT (GenST s) (ST s) a

sampleST :: SamplerST a -> State Seed a

Run the sampler with a supplied seed. Note that 'State Seed' is much less efficient than SamplerST for composing computation.

sampleSTfixed :: SamplerST a -> a

Run the sampler with a fixed random seed.