Copyright	(c) Adam Scibior 2015-2020
License	MIT
Maintainer	leonhard.markert@tweag.io
Stability	experimental
Portability	GHC
Safe Haskell	None
Language	Haskell2010

Control.Monad.Bayes.Free

Description

FreeSampler is a free monad transformer over random sampling.

Synopsis

data FreeSampler m a
hoist :: (Monad m, Monad n) => (forall x. m x -> n x) -> FreeSampler m a -> FreeSampler n a
interpret :: MonadSample m => FreeSampler m a -> m a
withRandomness :: Monad m => [Double] -> FreeSampler m a -> m a
withPartialRandomness :: MonadSample m => [Double] -> FreeSampler m a -> m (a, [Double])
runWith :: MonadSample m => [Double] -> FreeSampler Identity a -> m (a, [Double])

Documentation

data FreeSampler m a Source #

Free monad transformer over random sampling.

Uses the Church-encoded version of the free monad for efficiency.

Instances

Instances details

MonadTrans FreeSampler Source #
Instance details Defined in Control.Monad.Bayes.Free Methods lift :: Monad m => m a -> FreeSampler m a #
Monad (FreeSampler m) Source #
Instance details Defined in Control.Monad.Bayes.Free Methods (>>=) :: FreeSampler m a -> (a -> FreeSampler m b) -> FreeSampler m b # (>>) :: FreeSampler m a -> FreeSampler m b -> FreeSampler m b # return :: a -> FreeSampler m a #
Functor (FreeSampler m) Source #
Instance details Defined in Control.Monad.Bayes.Free Methods fmap :: (a -> b) -> FreeSampler m a -> FreeSampler m b # (<$) :: a -> FreeSampler m b -> FreeSampler m a #
Applicative (FreeSampler m) Source #
Instance details Defined in Control.Monad.Bayes.Free Methods pure :: a -> FreeSampler m a # (<>) :: FreeSampler m (a -> b) -> FreeSampler m a -> FreeSampler m b # liftA2 :: (a -> b -> c) -> FreeSampler m a -> FreeSampler m b -> FreeSampler m c # (>) :: FreeSampler m a -> FreeSampler m b -> FreeSampler m b # (<*) :: FreeSampler m a -> FreeSampler m b -> FreeSampler m a #
Monad m => MonadSample (FreeSampler m) Source #
Instance details Defined in Control.Monad.Bayes.Free Methods random :: FreeSampler m Double Source # uniform :: Double -> Double -> FreeSampler m Double Source # normal :: Double -> Double -> FreeSampler m Double Source # gamma :: Double -> Double -> FreeSampler m Double Source # beta :: Double -> Double -> FreeSampler m Double Source # bernoulli :: Double -> FreeSampler m Bool Source # categorical :: Vector v Double => v Double -> FreeSampler m Int Source # logCategorical :: (Vector v (Log Double), Vector v Double) => v (Log Double) -> FreeSampler m Int Source # uniformD :: [a] -> FreeSampler m a Source # geometric :: Double -> FreeSampler m Int Source # poisson :: Double -> FreeSampler m Int Source # dirichlet :: Vector v Double => v Double -> FreeSampler m (v Double) Source #

hoist :: (Monad m, Monad n) => (forall x. m x -> n x) -> FreeSampler m a -> FreeSampler n a Source #

Hoist FreeSampler through a monad transform.

interpret :: MonadSample m => FreeSampler m a -> m a Source #

Execute random sampling in the transformed monad.

withRandomness :: Monad m => [Double] -> FreeSampler m a -> m a Source #

Execute computation with supplied values for random choices.

withPartialRandomness :: MonadSample m => [Double] -> FreeSampler m a -> m (a, [Double]) Source #

Execute computation with supplied values for a subset of random choices. Return the output value and a record of all random choices used, whether taken as input or drawn using the transformed monad.

runWith :: MonadSample m => [Double] -> FreeSampler Identity a -> m (a, [Double]) Source #

Like withPartialRandomness, but use an arbitrary sampling monad.