hmm-hmatrix 0.0.2 → 0.1

raw patch · 6 files changed

+27/−31 lines, 6 filesPVP ok

version bump matches the API change (PVP)

API changes (from Hackage documentation)

Files

• Changes.md +3/−0
• hmm-hmatrix.cabal +4/−2
• src/Math/HiddenMarkovModel.hs +3/−6
• src/Math/HiddenMarkovModel/Distribution.hs +13/−14
• src/Math/HiddenMarkovModel/Normalized.hs +1/−2
• src/Math/HiddenMarkovModel/Private.hs +3/−7

@@ -0,0 +1,3 @@+## 0.1++* `Distribution.Estimate` turned into a multi-parameter type class.

@@ -1,5 +1,5 @@ Name:                hmm-hmatrix-Version:             0.0.2+Version:             0.1 Synopsis:            Hidden Markov Models using HMatrix primitives Description:   Hidden Markov Models implemented using HMatrix data types and operations.@@ -37,9 +37,11 @@ Category:            Math Build-Type:          Simple Cabal-Version:       >=1.10+Extra-Source-Files:+  Changes.md  Source-Repository this-  Tag:         0.0.2+  Tag:         0.1   Type:        darcs   Location:    http://hub.darcs.net/thielema/hmm-hmatrix 

@@ -116,8 +116,7 @@ Contribute a manually labeled emission sequence to a HMM training. -} trainSupervised ::-   (Distr.Estimate tdistr, Distr.Distribution tdistr ~ distr,-    Distr.Trained distr ~ tdistr,+   (Distr.Estimate tdistr distr,     Distr.Probability distr ~ prob, Distr.Emission distr ~ emission) =>    Int -> NonEmpty.T [] (State, emission) -> Trained tdistr prob trainSupervised n xs =@@ -133,8 +132,7 @@        }  finishTraining ::-   (Distr.Estimate tdistr, Distr.Distribution tdistr ~ distr,-    Distr.Trained distr ~ tdistr, Distr.Probability distr ~ prob) =>+   (Distr.Estimate tdistr distr, Distr.Probability distr ~ prob) =>    Trained tdistr prob -> T distr prob finishTraining hmm =    Cons {@@ -146,8 +144,7 @@    }  trainMany ::-   (Distr.Estimate tdistr, Distr.Distribution tdistr ~ distr,-    Distr.Trained distr ~ tdistr, Distr.Probability distr ~ prob,+   (Distr.Estimate tdistr distr, Distr.Probability distr ~ prob,     Foldable f) =>    (trainingData -> Trained tdistr prob) ->    NonEmpty.T f trainingData -> T distr prob

@@ -1,8 +1,9 @@ {-# LANGUAGE TypeFamilies #-} {-# LANGUAGE FlexibleContexts #-}+{-# LANGUAGE MultiParamTypeClasses #-} module Math.HiddenMarkovModel.Distribution (    State(..),-   Emission, Probability, Trained,+   Emission, Probability,    Info(..), Generate(..), EmissionProb(..), Estimate(..),     Discrete(..), DiscreteTrained(..),@@ -62,7 +63,6 @@  type family Probability distr type family Emission distr-type family Trained distr   class@@ -89,16 +89,15 @@    emissionStateProb distr e (State s) = NC.atIndex (emissionProb distr e) s  class-   (EmissionProb (Distribution tdistr),-    Trained (Distribution tdistr) ~ tdistr) =>-      Estimate tdistr where+   (Distribution tdistr ~ distr, Trained distr ~ tdistr, EmissionProb distr) =>+      Estimate tdistr distr where    type Distribution tdistr+   type Trained distr    accumulateEmissions ::-      (Distribution tdistr ~ distr, Probability distr ~ prob) =>-      [[(Emission distr, prob)]] -> tdistr+      (Probability distr ~ prob) => [[(Emission distr, prob)]] -> tdistr    -- could as well be in Semigroup class    combine :: tdistr -> tdistr -> tdistr-   normalize :: (Distribution tdistr ~ distr) => tdistr -> distr+   normalize :: tdistr -> distr   @@ -111,9 +110,7 @@ type instance Probability (Discrete prob symbol) = prob type instance Emission (Discrete prob symbol) = symbol -type instance Trained (Discrete prob symbol) = DiscreteTrained prob symbol - instance (NFData prob, NFData symbol) => NFData (Discrete prob symbol) where    rnf (Discrete m) = rnf m @@ -142,8 +139,9 @@  instance    (NC.Container Vector prob, NC.Product prob, Ord symbol) =>-      Estimate (DiscreteTrained prob symbol) where+      Estimate (DiscreteTrained prob symbol) (Discrete prob symbol) where    type Distribution (DiscreteTrained prob symbol) = Discrete prob symbol+   type Trained (Discrete prob symbol) = DiscreteTrained prob symbol    accumulateEmissions grouped =       let set = Set.toAscList $ foldMap (Set.fromList . map fst) grouped           emi = Map.fromAscList $ zip set [0..]@@ -178,9 +176,7 @@ type instance Probability (Gaussian a) = a type instance Emission (Gaussian a) = Vector a -type instance Trained (Gaussian a) = GaussianTrained a - instance (NFData a, Storable a) => NFData (Gaussian a) where    rnf (Gaussian params) = rnf params @@ -216,8 +212,11 @@          in  c * exp ((-1/2) * NC.dot x0 (cholSolve covarianceChol x0))  -instance (HMatrix.Numeric a, Algo.Field a) => Estimate (GaussianTrained a) where+instance+   (HMatrix.Numeric a, Algo.Field a) =>+      Estimate (GaussianTrained a) (Gaussian a) where    type Distribution (GaussianTrained a) = Gaussian a+   type Trained (Gaussian a) = GaussianTrained a    accumulateEmissions =       let params xs =              let center =

@@ -151,8 +151,7 @@ This is done by the Baum-Welch algorithm. -} trainUnsupervised ::-   (Distr.Estimate tdistr, Distr.Distribution tdistr ~ distr,-    Distr.Trained distr ~ tdistr,+   (Distr.Estimate tdistr distr,     Distr.Probability distr ~ prob, Distr.Emission distr ~ emission) =>    T distr prob -> NonEmpty.T [] emission -> Trained tdistr prob trainUnsupervised hmm xs =

@@ -231,14 +231,12 @@    T distr e -> [Matrix e] -> Matrix e sumTransitions hmm =    List.foldl' NC.add (NC.konst 0 $ LinAlg.size $ transition hmm)---    zero = uncurry LinAlg.zeros $ LinAlg.size $ transition hmm  {- | Baum-Welch algorithm -} trainUnsupervised ::-   (Distr.Estimate tdistr, Distr.Distribution tdistr ~ distr,-    Distr.Trained distr ~ tdistr,+   (Distr.Estimate tdistr distr,     Distr.Probability distr ~ prob, Distr.Emission distr ~ emission) =>    T distr prob -> NonEmpty.T [] emission -> Trained tdistr prob trainUnsupervised hmm xs =@@ -257,8 +255,7 @@   mergeTrained ::-   (Distr.Estimate tdistr, Distr.Distribution tdistr ~ distr,-    Distr.Trained distr ~ tdistr, Distr.Probability distr ~ prob) =>+   (Distr.Estimate tdistr distr, Distr.Probability distr ~ prob) =>    Trained tdistr prob -> Trained tdistr prob -> Trained tdistr prob mergeTrained hmm0 hmm1 =    Trained {@@ -271,8 +268,7 @@    }  instance-   (Distr.Estimate tdistr, Distr.Distribution tdistr ~ distr,-    Distr.Probability distr ~ prob) =>+   (Distr.Estimate tdistr distr, Distr.Probability distr ~ prob) =>       Sg.Semigroup (Trained tdistr prob) where    (<>) = mergeTrained