DifferentialEvolution 0.0.1 → 0.0.2

raw patch · 2 files changed

+13/−8 lines, 2 files

Files

• DifferentialEvolution.cabal +2/−1
• Numeric/Optimization/Algorithms/DifferentialEvolution.hs +11/−7

@@ -1,5 +1,5 @@ Name:                DifferentialEvolution-Version:             0.0.1+Version:             0.0.2 Category:            Numerical, Optimization, Algorithms  Synopsis:            Global optimization using Differential Evolution Description:         Plain Differential Evolution algorithm for optimizing @@ -24,6 +24,7 @@  License:             MIT License-File:        LICENSE+homepage:            http://yousource.it.jyu.fi/optimization-with-haskell Author:              Ville Tirronen Maintainer:          ville.tirronen@jyu.fi Build-Type:          Simple

@@ -1,11 +1,9 @@ {-# LANGUAGE ScopedTypeVariables, ViewPatterns, BangPatterns, DeriveDataTypeable, RecordWildCards, GeneralizedNewtypeDeriving, MultiParamTypeClasses, RankNTypes, ImpredicativeTypes, TypeFamilies, UndecidableInstances, TemplateHaskell,TypeOperators #-}--- | Module    : Numeric.Optimization.Algorithms.DifferentialEvolution+-- |Module    : Numeric.Optimization.Algorithms.DifferentialEvolution -- Copyright   : (c) 2011 Ville Tirronen -- License     : MIT -- -- Maintainer  : ville.tirronen@jyu.fi--- Stability   : experimental--- Portability : portable -- -- This module implements basic version of Differential Evolution algorithm -- for finding minimum of possibly multimodal and non-differentiable real valued@@ -20,8 +18,6 @@ --   -- >>>de (defaultParams fitness ((VUB.replicate 60 0), (VUB.replicate 60 0))) -- (0.12486060253695,fromList [2.481036288296201e-3, ... ]---- module Numeric.Optimization.Algorithms.DifferentialEvolution(         -- * Basic Types         Vector, Bounds, Fitness, Budget, DeMonad,@@ -53,9 +49,14 @@ -- import Test.QuickCheck hiding (Gen)  +-- |Vector type for storing trial points type Vector  = VUB.Vector Double+-- |Type for storing function domain orthope. (Structure of arrays seems +--   more efficient than array of structures) type Bounds  = (VUB.Vector Double, VUB.Vector Double)+-- |Fitness function type type Fitness = Vector -> Double+-- |Termination condition type. (Currently just a hard limit on evaluation count) type Budget = Int  data DEParams s = DEParams {_gen :: GenST s@@ -262,7 +263,7 @@         return $ VUB.map (\(x,e1,e2,i) -> if x<cr || i == index then e2 else e1)                 $ VUB.zip4 randoms a b (VUB.enumFromN 0 l) --- |Parameters for algorothm execution+-- |Parameters for algorithm execution data DEArgs = DEArgs {                       -- |Mutation strategy                       destrategy :: Strategy@@ -304,10 +305,13 @@ de :: DEArgs -> DeMonad s (Double,Vector) de DEArgs{..} = do     liftST (restore seed) >>= setM gen-    init <- withGen $ \g -> liftST (V.replicateM spop $ uniformVector g dim) +    +    init <- withGen $ \g -> liftST (V.replicateM spop (uniformVector g dim >>= return.scale))      pop =: V.map (fitness &&& id) init     work     where+     (lb,ub) = (fst bounds, snd bounds)+     scale x = VUB.zipWith3 (\l u x -> l+x*(u-l)) lb ub x      strat = strategy destrategy      work = do logPoint ""                e <- getM ec