random-fu-multivariate 0.1.1.1 → 0.1.2.0

raw patch · 2 files changed

+1/−111 lines, 2 filesPVP: major bump suggested

API removals or changes: PVP suggests a major version bump

API changes (from Hackage documentation)

Files

• random-fu-multivariate.cabal +1/−2
• src/Data/Random/Distribution/MultiNormal.hs +0/−109

@@ -1,5 +1,5 @@ name:                random-fu-multivariate-version:             0.1.1.1+version:             0.1.2.0 synopsis:            Multivariate distributions for random-fu description:         Please see README.md homepage:            https://github.com/fpco/random-fu-multivariate@@ -23,7 +23,6 @@   hs-source-dirs:    src   exposed-modules:   Data.Random.Distribution.MultivariateNormal                    , Data.Random.Distribution.Static.MultivariateNormal-                   , Data.Random.Distribution.MultiNormal   ghc-options:       -Wall   build-depends:     base >= 4.7 && < 5                    , random-fu

@@ -1,109 +0,0 @@------------------------------------------------------------------- An implementation of multivariate normal distributions -------------------------------------------------------------------{--Written by: Dominic Steinitz, Jacob West-Last modified: 2016-07-27--Summary: Multivariate normal distributions are necessary for Kalman-filters and smoothers.  However, strictly speaking, the functionality-provided here should exist elsewhere, perhaps in the package:-random-fu.--}--------------------------------- File header pragmas --------------------------------{-# LANGUAGE RecordWildCards #-}       -- Used by multiNormalRV, multiNormalConstant-                                       -- and multiNormalQuadraticForm-{-# LANGUAGE MultiParamTypeClasses #-} -- Necessary for Distribution instance-{-# LANGUAGE FlexibleInstances #-}     -- Necessary for Show instance-{-# LANGUAGE TypeFamilies #-}          -- Necessary for MultiNormal definition------------------------------ Module / Exports -----------------------------module Data.Random.Distribution.MultiNormal-       (-         MultiNormal(..)-       , inv-       )-       where-------------------- Imports --------------------import Control.Monad (replicateM, when)-import Data.Maybe (fromMaybe, fromJust)-import Data.Random-import GHC.TypeLits-import Numeric.LinearAlgebra.Static--import qualified Numeric.LinearAlgebra as LA------------------------------ Helper Functions ------------------------------- Matrix inverse: for some reason, this isn't built into the--- static interface; warning: no error handling---- WARNING: Needs better error handling-inv :: KnownNat n => Sq n -> Sq n-inv = fromMaybe (error "Failed attempting to invert non-invertible matrix.") .-      flip linSolve eye---------------------------------------------- Multivariate Normal Distrubtions ----------------------------------------------- This probably belongs elsewhere, maybe Data.Random, but that would--- create a dependence on Numric.LinearAlgebra which I believe is not--- there now and may be undesirable.--data family MultiNormal k :: *-data instance KnownNat n => MultiNormal (R n) =-  MultiNormal { mu :: (R n), cov :: (Sym n) }----- Show Instance ----instance KnownNat n => Show (MultiNormal (R n)) where-  show MultiNormal {..} = "Normal " ++ show mu ++ " " ++ show cov----- Distribution Instance ----instance KnownNat n => Distribution MultiNormal (R n) where-  rvar = multiNormalRV---- WARNING: Needs better error handling-multiNormalRV :: KnownNat n => MultiNormal (R n) -> RVarT m (R n)-multiNormalRV MultiNormal {..} = do-  let (vals, vecs) = eigensystem cov-  when (any (<0) (LA.toList $ unwrap vals))-    (error "Covariance matrix is not positive semi-definite.")--  let lSqrt = diag (fromJust . create $ LA.cmap sqrt (extract vals))-      bigA  = tr vecs <> lSqrt-  -  gnoise <- replicateM (size mu) (rvarT StdNormal)-  return $ mu + bigA #> (vector gnoise)----- PDF Instance ----instance KnownNat n => PDF MultiNormal (R n) where-  pdf    = multiNormalPDF-  logPdf = multiNormalLogPDF--multiNormalPDF :: KnownNat n => MultiNormal (R n) -> R n -> Double-multiNormalPDF mn pt =-  multiNormalConstant mn * exp (multiNormalQuadraticForm mn pt)--multiNormalLogPDF :: KnownNat n => MultiNormal (R n) -> R n -> Double-multiNormalLogPDF mn pt =-  multiNormalConstant mn + multiNormalQuadraticForm mn pt--multiNormalConstant :: KnownNat n => MultiNormal (R n) -> Double-multiNormalConstant MultiNormal {..} = recip . sqrt $ (2*pi)^n * detCov-  where-    n = size mu-    detCov = LA.det . extract . unSym $ cov--multiNormalQuadraticForm :: KnownNat n => MultiNormal (R n) -> R n -> Double-multiNormalQuadraticForm MultiNormal {..} pt = (diff LA.<.> invCov LA.#> diff) / (-2)-  where-    diff = extract (mu - pt)-    invCov = extract . inv . unSym $ cov