Data.Markov.HMarkov

Generate Markov sequences from vectors. The main entry points are: buildProc creates a MarkovProcess from a vector of training elements, a starting element, and a StdGen runUntil runs a MarkovProcess until a termination condition is met, and returns the resulting sequence

Data structures

Map of frequencies

data MarkovMap a

Map of frequencies

Constructors

MarkovMap

Fields

• _idx :: Vector a

  Index of elements

• _mMap :: Vector (Vector Double)

  Map of frequencies

Instances

Show a => Show (MarkovMap a)

Methods

showsPrec :: Int -> MarkovMap a -> ShowS

show :: MarkovMap a -> String

showList :: [MarkovMap a] -> ShowS

Complete process

data MarkovProcess m a

State-compatible wrapper around a trained MarkovMap, which includes a StdGen and the most recently-generated element, or the starting element if the process hasn't been run yet

Constructors

MarkovProcess

Fields

• _pMap :: MarkovMap a

  Wrapped MarkovMap

• _g :: StdGen
• _lastT :: a

  Most recently generated element (or starting element)

• _acc :: m a

  MonadPlus of already-generated elements

Instances

(Show (m a), Show a) => Show (MarkovProcess m a)

Methods

showsPrec :: Int -> MarkovProcess m a -> ShowS

show :: MarkovProcess m a -> String

showList :: [MarkovProcess m a] -> ShowS

Construction helpers

buildMap :: Eq a => Vector a -> MarkovMap a

Build a MarkovMap from a vector of elements

buildProc :: (Eq a, MonadPlus m) => Vector a -> a -> StdGen -> MarkovProcess m a

Build a MarkovProcess from a vector of elements, a starting element, and a source of randomness NOTE: the starting element should be a member of the training vector

Run processes

runMarkov :: (Eq a, MonadPlus m) => MarkovProcess m a -> (m a, MarkovProcess m a)

Run a MarkovProcess once, generating a new element that is appended to the accumulator

runUntil :: (Eq a, MonadPlus m) => (m a -> Bool) -> MarkovProcess m a -> m a

Run a MarkovProcess continually until a termination condition is met, returning the accumulator