commit ed636761efb39d18a6c01d9d36587d808eda6dc6
parent 46840992f48ad098199b914da1a67838b1bf1a25
Author: Jared Tobin <jared@jtobin.ca>
Date: Sun, 3 Apr 2016 20:13:42 +0700
Update readme and cabal description.
Diffstat:
3 files changed, 71 insertions(+), 12 deletions(-)
diff --git a/README.md b/README.md
@@ -1,4 +1,35 @@
-# flat-mcmc [](http://travis-ci.org/jtobin/flat-mcmc)
+# flat-mcmc [](http://travis-ci.org/jtobin/flat-mcmc)
-Painless general-purpose sampling.
+*flat-mcmc* is a Haskell library for painless, efficient, general-purpose
+sampling from continuous distributions.
+*flat-mcmc* uses an ensemble sampler that is invariant to affine
+transformations of space. It wanders a target probability distribution's
+parameter space as if it had been "flattened" or "unstretched" in some sense,
+allowing many particles to explore it locally and in parallel.
+
+In general this sampler is useful when you want decent performance without
+dealing with any tuning parameters or local proposal distributions.
+
+*flat-mcmc* exports an 'mcmc' function that prints a trace to stdout, as well
+as a 'flat' transition operator that can be used more generally.
+
+``` haskell
+import Numeric.MCMC.Flat
+import Data.Vector (Vector, toList, fromList)
+
+rosenbrock :: Vector Double -> Double
+rosenbrock xs = negate (5 *(x1 - x0 ^ 2) ^ 2 + 0.05 * (1 - x0) ^ 2) where
+ [x0, x1] = toList xs
+
+ensemble :: Ensemble
+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]
+ ]
+
+main :: IO ()
+main = withSystemRandom . asGenIO $ mcmc 25000 ensemble rosenbrock
+```
diff --git a/flat-mcmc.cabal b/flat-mcmc.cabal
@@ -10,8 +10,37 @@ category: Math
build-type: Simple
cabal-version: >=1.10
description:
-
- Painless general-purpose sampling.
+ *flat-mcmc* is a Haskell library for painless, efficient, general-purpose
+ sampling from continuous distributions.
+ .
+ *flat-mcmc* uses an ensemble sampler that is invariant to affine
+ transformations of space. It wanders a target probability distribution's
+ parameter space as if it had been "flattened" or "unstretched" in some sense,
+ allowing many particles to explore it locally and in parallel.
+ .
+ In general this sampler is useful when you want decent performance without
+ dealing with any tuning parameters or local proposal distributions.
+ .
+ *flat-mcmc* exports an 'mcmc' function that prints a trace to stdout, as well
+ as a 'flat' transition operator that can be used more generally.
+ .
+ > import Numeric.MCMC.Flat
+ > import Data.Vector (Vector, toList, fromList)
+ >
+ > rosenbrock :: Vector Double -> Double
+ > rosenbrock xs = negate (5 *(x1 - x0 ^ 2) ^ 2 + 0.05 * (1 - x0) ^ 2) where
+ > [x0, x1] = toList xs
+ >
+ > ensemble :: Ensemble
+ > 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]
+ > ]
+ >
+ > main :: IO ()
+ > main = withSystemRandom . asGenIO $ mcmc 25000 ensemble rosenbrock
Source-repository head
Type: git
diff --git a/test/Rosenbrock.hs b/test/Rosenbrock.hs
@@ -3,19 +3,18 @@
module Main where
import Numeric.MCMC.Flat
-import Data.Vector (Vector)
-import qualified Data.Vector as V (toList, fromList)
+import Data.Vector (Vector, toList, fromList)
rosenbrock :: Vector Double -> Double
rosenbrock xs = negate (5 *(x1 - x0 ^ 2) ^ 2 + 0.05 * (1 - x0) ^ 2) where
- [x0, x1] = V.toList xs
+ [x0, x1] = toList xs
ensemble :: Ensemble
-ensemble = V.fromList [
- V.fromList [negate 1.0, negate 1.0]
- , V.fromList [negate 1.0, 1.0]
- , V.fromList [1.0, negate 1.0]
- , V.fromList [1.0, 1.0]
+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]
]
main :: IO ()
