Math.HiddenMarkovModel.Example.TrafficLightPrivate

Documentation

>>> import qualified Data.NonEmpty as NonEmpty
>>> import Control.DeepSeq (deepseq)
>>> 
>>> verifyRevelations :: HMM -> [Bool]
>>> verifyRevelations hmm_ =
>>> map (verifyRevelation hmm_) (NonEmpty.flatten labeledSequences)

data Color

Constructors

Red

Yellow

Green

Instances

Enum Color

Defined in Math.HiddenMarkovModel.Example.TrafficLightPrivate

Methods

succ :: Color -> Color

pred :: Color -> Color

toEnum :: Int -> Color

fromEnum :: Color -> Int

enumFrom :: Color -> [Color]

enumFromThen :: Color -> Color -> [Color]

enumFromTo :: Color -> Color -> [Color]

enumFromThenTo :: Color -> Color -> Color -> [Color]

Eq Color

Defined in Math.HiddenMarkovModel.Example.TrafficLightPrivate

Methods

(==) :: Color -> Color -> Bool

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

Ord Color

Defined in Math.HiddenMarkovModel.Example.TrafficLightPrivate

Methods

compare :: Color -> Color -> Ordering

(<) :: Color -> Color -> Bool

(<=) :: Color -> Color -> Bool

(>) :: Color -> Color -> Bool

(>=) :: Color -> Color -> Bool

max :: Color -> Color -> Color

min :: Color -> Color -> Color

Read Color

Defined in Math.HiddenMarkovModel.Example.TrafficLightPrivate

Methods

readsPrec :: Int -> ReadS Color

readList :: ReadS [Color]

readPrec :: ReadPrec Color

readListPrec :: ReadPrec [Color]

Show Color

Defined in Math.HiddenMarkovModel.Example.TrafficLightPrivate

Methods

showsPrec :: Int -> Color -> ShowS

show :: Color -> String

showList :: [Color] -> ShowS

NFData Color

Defined in Math.HiddenMarkovModel.Example.TrafficLightPrivate

Methods

rnf :: Color -> ()

CSVSymbol Color

Using show and read is not always a good choice since they must format and parse Haskell expressions which is not of much use to the outside world.

Defined in Math.HiddenMarkovModel.Example.TrafficLightPrivate

Methods

cellFromSymbol :: Color -> String

symbolFromCell :: String -> Maybe Color

data State

Constructors

StateRed

StateYellowRG

StateGreen

StateYellowGR

Instances

Bounded State

Defined in Math.HiddenMarkovModel.Example.TrafficLightPrivate

Methods

minBound :: State

maxBound :: State

Enum State

Defined in Math.HiddenMarkovModel.Example.TrafficLightPrivate

Methods

succ :: State -> State

pred :: State -> State

toEnum :: Int -> State

fromEnum :: State -> Int

enumFrom :: State -> [State]

enumFromThen :: State -> State -> [State]

enumFromTo :: State -> State -> [State]

enumFromThenTo :: State -> State -> State -> [State]

Eq State

Defined in Math.HiddenMarkovModel.Example.TrafficLightPrivate

Methods

(==) :: State -> State -> Bool

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

Ord State

Defined in Math.HiddenMarkovModel.Example.TrafficLightPrivate

Methods

compare :: State -> State -> Ordering

(<) :: State -> State -> Bool

(<=) :: State -> State -> Bool

(>) :: State -> State -> Bool

(>=) :: State -> State -> Bool

max :: State -> State -> State

min :: State -> State -> State

type StateSet = Enumeration State

stateSet :: StateSet

type HMM = Discrete Color StateSet Double

hmm :: HMM

>>> verifyRevelations hmm
[True,True]

hmmDisturbed :: HMM

>>> verifyRevelations hmmDisturbed
[True,True]

stateVector :: Double -> Double -> Double -> Double -> Vector StateSet Double

red :: (State, Color)

yellowRG :: (State, Color)

green :: (State, Color)

yellowGR :: (State, Color)

labeledSequences :: T [] (T [] (State, Color))

hmmTrainedSupervised :: HMM

Construct a Hidden Markov model by watching a set of manually created sequences of emissions and according states.

>>> verifyRevelations hmmTrainedSupervised
[True,True]

stateSequences :: T [] (T [] Color)

hmmTrainedUnsupervised :: HMM

Construct a Hidden Markov model starting from a known model and a set of sequences that contain only the emissions, but no states.

>>> verifyRevelations hmmTrainedUnsupervised
[True,True]

hmmIterativelyTrained :: HMM

Repeat unsupervised training until convergence.

deepseq hmmIterativelyTrained True

verifyRevelation :: HMM -> T [] (State, Color) -> Bool