rhine-bayes 1.7 → 1.8

raw patch · 2 files changed

+20/−14 lines, 2 filesdep ~basedep ~rhinedep ~rhine-glossPVP ok

version bump matches the API change (PVP)

Dependency ranges changed: base, rhine, rhine-gloss

API changes (from Hackage documentation)

Files

• rhine-bayes.cabal +5/−4
• src/FRP/Rhine/Bayes.hs +15/−10

@@ -1,6 +1,6 @@ cabal-version: 2.2 name: rhine-bayes-version: 1.7+version: 1.8 synopsis: monad-bayes backend for Rhine description:   This package provides a backend to the @monad-bayes@ library,@@ -30,11 +30,11 @@ common opts   build-depends:     automaton,-    base >=4.16 && <4.22,+    base >=4.18 && <4.22,     log-domain >=0.12,     mmorph ^>=1.2,     monad-bayes ^>=1.3.0.5,-    rhine ^>=1.7,+    rhine ^>=1.8,     transformers >=0.5,    default-extensions:@@ -50,6 +50,7 @@     RankNTypes     ScopedTypeVariables     TupleSections+    TypeApplications     TypeFamilies     TypeOperators @@ -71,7 +72,7 @@   hs-source-dirs: app   build-depends:     rhine-bayes,-    rhine-gloss ^>=1.7,+    rhine-gloss ^>=1.8,     time,    ghc-options:

@@ -1,16 +1,17 @@+{-# OPTIONS_GHC -fno-warn-orphans #-}+ module FRP.Rhine.Bayes where  -- transformers import Control.Monad.Trans.Reader (ReaderT (..)) --- log-domain-import Numeric.Log hiding (sum)- -- monad-bayes import Control.Monad.Bayes.Class import Control.Monad.Bayes.Population+import Control.Monad.Bayes.Sampler.Strict (SamplerT (..))  -- automaton+import Data.Automaton.Schedule (MonadSchedule (..)) import qualified Data.Automaton.Trans.Reader as AutomatonReader  -- rhine-bayes@@ -19,6 +20,10 @@ -- rhine import FRP.Rhine +-- | 'SamplerT' is a newtype over 'ReaderT', so it inherits 'MonadSchedule' via 'hoistS'.+instance (Monad m, MonadSchedule m) => MonadSchedule (SamplerT g m) where+  schedule = fmap (hoistS runSamplerT) >>> schedule >>> hoistS SamplerT+ -- * Inference methods  -- | Run the Sequential Monte Carlo algorithm continuously on a 'ClSF'.@@ -102,11 +107,11 @@ wienerVaryingLogDomain = wienerVarying >>> arr Exp  {- | Inhomogeneous Poisson point process, as described in:-  https://en.wikipedia.org/wiki/Poisson_point_process#Inhomogeneous_Poisson_point_process+ https://en.wikipedia.org/wiki/Poisson_point_process#Inhomogeneous_Poisson_point_process -  * The input is the inverse of the current rate or intensity.-    It corresponds to the average duration between two events.-  * The output is the number of events since the last tick.+ * The input is the inverse of the current rate or intensity.+   It corresponds to the average duration between two events.+ * The output is the number of events since the last tick. -} poissonInhomogeneous ::   (MonadDistribution m, Real (Diff td), Fractional (Diff td)) =>@@ -123,7 +128,7 @@  {- | The Gamma process, https://en.wikipedia.org/wiki/Gamma_process. -  The live input corresponds to inverse shape parameter, which is variance over mean.+ The live input corresponds to inverse shape parameter, which is variance over mean. -} gammaInhomogeneous ::   (MonadDistribution m, Real (Diff td), Fractional (Diff td), Floating (Diff td)) =>@@ -136,8 +141,8 @@  {- | The inhomogeneous Bernoulli process, https://en.wikipedia.org/wiki/Bernoulli_process -  Throws a coin to a given probability at each tick.-  The live input is the probability.+ Throws a coin to a given probability at each tick.+ The live input is the probability. -} bernoulliInhomogeneous :: (MonadDistribution m) => BehaviourF m td Double Bool bernoulliInhomogeneous = arrMCl bernoulli