maxent-0.7: src/Numeric/MaxEnt/ConjugateGradient.hs
{-# LANGUAGE Rank2Types #-}
--------------------------------------------------------------------------------
-- This module is updated to work with version 4.* of `Numeric.AD`, but it is
-- now provides funcationality only to `Numeric.MaxEnt.Linear`. Formerly,
-- `Numeric.MaxEnt.Moment` used the `minimize` function defined here, but I
-- rewrote that module to use the `general` function defined in
-- `Numeric.MaxEnt.General`, which in turn uses `maximize` from the
-- `Numeric.AD.Lagrangian`.
--
-- I intend to rewrite `Numeric.MaxEnt.Linear` so that it no longer relies on
-- this module either, with would leave it unused. -- E.P.
--------------------------------------------------------------------------------
module Numeric.MaxEnt.ConjugateGradient where
import Control.Arrow (second)
import qualified Data.Vector.Unboxed as U
import qualified Data.Vector.Storable as S
import GHC.IO (unsafePerformIO)
import Numeric.Optimization.Algorithms.HagerZhang05
import Numeric.AD
dot :: Num a => [a] -> [a] -> a
dot xs ys = sum $ zipWith (*) xs ys
sumMap :: Num b => (a -> b) -> [a] -> b
sumMap f = sum . map f
sumWith :: Num c => (a -> b -> c) -> [a] -> [b] -> c
sumWith f xs ys = sum $ zipWith f xs ys
minimize :: Double
-> Int
-> (forall a. (Floating a) => [a] -> a)
-> Either (Result, Statistics) (S.Vector Double)
minimize tolerance count obj = result where
guess = U.fromList $ 1 : replicate (count - 1) 0
result = case unsafePerformIO $
optimize
(defaultParameters { printFinal = False,
--printParams = True,
--maxit = 10000,
--verbosity = VeryVerbose,
initialStep = Just 0.1
--lineSearch = ApproximateWolfe,
--debugTol = Just 0.01,
--nanRho = 1.3,
--estimateError = RelativeEpsilon 0.1
--lbfgs = False
})
tolerance
guess
(VFunction (obj . U.toList))
(VGradient (U.fromList . grad obj . U.toList))
(Just $ VCombined (second U.fromList . grad' obj . U.toList)) of
(vs, ToleranceStatisfied, _) -> Right vs
(_, x, y) -> Left (x, y)