commit7ec04d202b0c61148daa08f42f5a95681563bf17parenta38bbed1f53565f05dffc83dfada02a2ebe04e61Author:Jared Tobin <jared@jtobin.ca>Date:Wed, 6 Apr 2016 17:00:44 +0700 Documentation.Diffstat:

M | lib/Numeric/MCMC/Flat.hs | | | 54 | +++++++++++++++++++++++++++++++++++++++++++++++++++++- |

1 file changed, 53 insertions(+), 1 deletion(-)diff --git a/lib/Numeric/MCMC/Flat.hs b/lib/Numeric/MCMC/Flat.hs@@ -1,14 +1,35 @@ {-# OPTIONS_GHC -fno-warn-type-defaults #-} {-# LANGUAGE RecordWildCards #-} +-- | +-- Module: Numeric.MCMC.Flat +-- Copyright: (c) 2016 Jared Tobin +-- License: MIT +-- +-- Maintainer: Jared Tobin <jared@jtobin.ca> +-- Stability: unstable +-- Portability: ghc +-- +-- This is the 'affine invariant ensemble' or AIEMCMC algorithm described in +-- Goodman and Weare, 2010. It is a reasonably efficient and hassle-free +-- sampler, requiring no mucking with tuning parameters or local proposal +-- distributions. +-- +-- The 'mcmc' function streams a trace to stdout to be processed elsewhere, +-- while the `flat` transition can be used for more flexible purposes, +-- such as working with samples in memory. +-- +-- See <http://msp.org/camcos/2010/5-1/camcos-v5-n1-p04-p.pdf> for the definitive +-- reference of the algorithm. + module Numeric.MCMC.Flat ( mcmc , flat , Particle , Ensemble + , Chain , module Sampling.Types - , Chain , MWC.create , MWC.createSystemRandom , MWC.withSystemRandom @@ -93,6 +114,8 @@ execute target e0 e1 n = do return $ V.fromList result +-- | The 'flat' transition operator for driving a Markov chain over a space +-- of ensembles. flat :: PrimMonad m => Transition m Chain @@ -114,6 +137,34 @@ chain = loop where yield next loop next prng +-- | Trace 'n' iterations of a Markov chain and stream them to stdout. +-- +-- Note that the Markov chain is defined over the space of ensembles, so +-- you'll need to provide an ensemble of particles for the start location. +-- +-- >>> import Numeric.MCMC.Flat +-- >>> import Data.Vector (Vector, toList, fromList) +-- >>> :{ +-- >>> let rosenbrock xs = negate (5 *(x1 - x0 ^ 2) ^ 2 + 0.05 * (1 - x0) ^ 2) +-- where [x0, x1] = toList xs +-- >>> :} +-- >>> :{ +-- >>> let ensemble = fromList [ +-- >>> fromList [negate 1.0, negate 1.0] +-- >>> , fromList [negate 1.0, 1.0] +-- >>> , fromList [1.0, negate 1.0] +-- >>> , fromList [1.0, 1.0] +-- >>> ] +-- >>> :} +-- >>> withSystemRandom . asGenIO $ mcmc 2 ensemble rosenbrock +-- -1.0,-1.0 +-- -1.0,1.0 +-- 1.0,-1.0 +-- 0.7049046915549257,0.7049046915549257 +-- -0.843493377618159,-0.843493377618159 +-- -1.1655594505975082,1.1655594505975082 +-- 0.5466534497342876,-0.9615123448709006 +-- 0.7049046915549257,0.7049046915549257 mcmc :: Int -> Ensemble -> (Particle -> Double) -> Gen RealWorld -> IO () mcmc n chainPosition target gen = runEffect $ chain Chain {..} gen @@ -122,6 +173,7 @@ mcmc n chainPosition target gen = runEffect $ where chainTarget = Target target Nothing +-- A parallel map with the specified granularity. parMapChunk :: NFData b => Int -> (a -> b) -> [a] -> Par [b] parMapChunk n f xs = concat <$> parMap (map f) (chunk n xs) where chunk _ [] = []