module Numeric.MaxEnt.ConjugateGradient where
import Numeric.Optimization.Algorithms.HagerZhang05
import qualified Data.Vector.Unboxed as U
import qualified Data.Vector.Storable as S
import Numeric.AD
import GHC.IO (unsafePerformIO)
import Data.Traversable
import Numeric.AD.Types
import Numeric.AD.Internal.Classes
import Data.List (transpose)
dot :: Num a => [a] -> [a] -> a
dot x y = sum . zipWith (*) x $ y
sumMap :: Num b => (a -> b) -> [a] -> b
sumMap f = sum . map f
sumWith :: Num c => (a -> b -> c) -> [a] -> [b] -> c
sumWith f xs = sum . zipWith f xs
toFunction :: (forall a. RealFloat a => [a] -> a) -> Function Simple
toFunction f = VFunction (f . U.toList)
toGradient :: (forall a. RealFloat a => [a] -> a) -> Gradient Simple
toGradient f = VGradient (U.fromList . grad f . U.toList)
toDoubleF :: (forall a. RealFloat a => [a] -> a) -> [Double] -> Double
toDoubleF f x = f x
squaredGrad :: Num a
=> (forall s. Mode s => [AD s a] -> AD s a) -> [a] -> a
squaredGrad f vs = sumMap (\x -> x*x) (grad f vs)
solve :: Double
-> Int
-> (forall a. RealFloat a => [a] -> a)
-> Either (Result, Statistics) [Double]
solve percision count obj = result where
guess = U.fromList $ replicate
count ((1.0 :: Double) / (fromIntegral count))
result = case unsafePerformIO (optimize (defaultParameters { printFinal = False }) percision guess
(toFunction obj)
(toGradient obj)
Nothing) of
(vs, ToleranceStatisfied, _) -> Right . S.toList $ vs
(_, x, y) -> Left (x, y)