packages feed

classify-frog 0.2.4.1 → 0.2.4.2

raw patch · 5 files changed

+19/−25 lines, 5 filesdep ~comfort-arraydep ~hmm-lapackdep ~lapack

Dependency ranges changed: comfort-array, hmm-lapack, lapack, semigroups

Files

classify-frog.cabal view
@@ -1,5 +1,5 @@ Name:           classify-frog-Version:        0.2.4.1+Version:        0.2.4.2 License:        BSD3 License-File:   LICENSE Author:         Henning Thielemann <haskell@henning-thielemann.de>@@ -42,7 +42,7 @@   model/diclo/hmm-supervised.csv  Source-Repository this-  Tag:         0.2.4.1+  Tag:         0.2.4.2   Type:        darcs   Location:    http://hub.darcs.net/thielema/classify-frog @@ -98,9 +98,9 @@   Hs-Source-Dirs: src    Build-Depends:-    hmm-lapack >=0.3 && <0.4,-    lapack >=0.2 && <0.3,-    comfort-array >=0.2 && <0.3,+    hmm-lapack >=0.4 && <0.5,+    lapack >=0.3 && <0.4,+    comfort-array >=0.4 && <0.5,     text >=1.1 && <1.3,     lazy-csv >=0.5 && <0.6,     tagchup >=0.4 && <0.5,@@ -125,12 +125,11 @@     filemanip >=0.3.6 && <0.4,     pathtype >=0.8 && <0.9,     non-empty >=0.3 && <0.4,-    semigroups >=0.1 && <1.0,     containers >=0.4 && <0.7,     explicit-exception >=0.1.8 && <0.2,     transformers >=0.2 && <0.6,     bifunctors >=5 && <6,-    semigroups >=0.8.4.1 && <0.19,+    semigroups >=0.8.4.1 && <1.0,     utility-ht >=0.0.12 && <0.1,     numeric-prelude >=0.4 && <0.5,     deepseq >=1.3 && <1.5,
src/Feature.hs view
@@ -634,7 +634,7 @@    LabelChain.T Int String _fineFromCoarseIntervalsBand20 _params rate =    LabelChain.fineFromCoarseIntervalsInt-      (case 3::Int of+      (case fromInteger 3 :: Int of          0 -> LabelChain.detectClicksExtrema                  (timeCeil rate (Time 0.01),                   timeCeil rate (Time 0.03))
src/HiddenMarkovModel.hs view
@@ -10,7 +10,6 @@  import qualified Numeric.LAPACK.Matrix as Matrix import qualified Numeric.LAPACK.Vector as Vector-import Numeric.LAPACK.Matrix (ZeroInt) import Numeric.LAPACK.Vector (Vector)  import qualified Data.Array.Comfort.Storable as ComfortArray@@ -154,7 +153,7 @@    (Storable a) => NonEmpty.T SVL.Vector a -> SVL.Vector a flattenStorableVectorLazy (NonEmpty.Cons x xs) = SVL.cons x xs -prepare :: [Named.NonEmptySignal] -> NonEmpty.T [] (Vector ZeroInt Double)+prepare :: [Named.NonEmptySignal] -> NonEmpty.T [] (Vector ShapeInt Double) prepare nxs =    let xs = map Named.body nxs        vecFromList = ComfortArray.map realToFrac . Vector.autoFromList
src/HiddenMarkovModel/Hardwired.hs view
@@ -16,7 +16,6 @@ import qualified Numeric.LAPACK.Matrix.Square as Square import qualified Numeric.LAPACK.Matrix as Matrix import qualified Numeric.LAPACK.Vector as Vector-import Numeric.LAPACK.Matrix (ZeroInt)  import qualified Data.Array.Comfort.Boxed as Array import Data.Array.Comfort.Boxed (Array)@@ -135,21 +134,16 @@  hmmPattern :: Gaussian hmmPattern =-   (HMM.finishTraining $-    Pat.finish statesShape-      (Distr.GaussianTrained $-       Array.fromList statesShape (replicate numberOfStates Nothing) ::-         Distr.GaussianTrained ShapeInt ShapeState Double)-      pattern)-       {HMM.distribution =-          Distr.gaussian $ Array.fromList statesShape $+   HMM.finishTraining $ flip Pat.finish pattern $+      Distr.gaussianTrained $ Array.fromList statesShape $+         map (\(center,cov) -> (1,center,cov)) $             (Vector.autoFromList [1.00], covariance [[0.17]]) :             (Vector.autoFromList [1.60], covariance [[0.60]]) :             (Vector.autoFromList [0.75], covariance [[0.40]]) :             (Vector.autoFromList [1.00], covariance [[0.20]]) :             (Vector.autoFromList [0.60], covariance [[0.30]]) :             (Vector.autoFromList [1.60], covariance [[0.60]]) :-            []}+            []  hmmNamed :: NamedGaussian hmmNamed =@@ -160,13 +154,13 @@    }  -type HermitianMatrix = Hermitian.Hermitian ZeroInt+type HermitianMatrix = Hermitian.Hermitian ShapeInt  covariance :: [[Double]] -> HermitianMatrix Double covariance =    maybe       (Hermitian.autoFromList MatrixShape.RowMajor [])-      (Hermitian.covariance . Matrix.fromRowsNonEmpty) .+      (Hermitian.gramian . Matrix.fromRowsNonEmpty) .    NonEmpty.fetch . map Vector.autoFromList  @@ -176,5 +170,5 @@       HMM.distribution =          let Distr.Gaussian arr = HMM.distribution model          in  Distr.Gaussian $-             fmap (\(center,dev,c) -> (center, Vector.scale k dev, c/k)) arr+             fmap (\(c,center,dev) -> (c/k, center, Matrix.scale k dev)) arr    }
src/Main.hs view
@@ -143,6 +143,8 @@ import System.Path ((</>), (<.>), ) import Text.Printf (printf, ) +import qualified Numeric.LAPACK.Matrix.Array as ArrMatrix+import qualified Numeric.LAPACK.Matrix as Matrix import qualified Numeric.LAPACK.Vector as Vector import qualified Algebra.RealRing as Real import qualified Algebra.Ring as Ring@@ -559,8 +561,8 @@ printModelDifference :: HMM.Gaussian -> HMM.Gaussian -> IO () printModelDifference hmmSup hmmUnsup =    void $ printf "difference between supervised and unsupervised: %f\n" $-      Vector.normInf $-      Vector.sub (HMM0.transition hmmSup) (HMM0.transition hmmUnsup)+      Vector.normInf $ ArrMatrix.toVector $+      Matrix.sub (HMM0.transition hmmSup) (HMM0.transition hmmUnsup)