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{-# LANGUAGE FlexibleContexts, FlexibleInstances #-}
{-# LANGUAGE RecordWildCards #-}
module Internal.CG(
cgSolve, cgSolve',
CGState(..), R, V
) where
import Internal.Vector
import Internal.Matrix
import Internal.Numeric
import Internal.Element
import Internal.IO
import Internal.Container
import Internal.Sparse
import Numeric.Vector()
import Internal.Algorithms(linearSolveLS, linearSolve, relativeError, pnorm, NormType(..))
import Control.Arrow((***))
{-
import Util.Misc(debug, debugMat)
(//) :: Show a => a -> String -> a
infix 0 // -- , ///
a // b = debug b id a
(///) :: V -> String -> V
infix 0 ///
v /// b = debugMat b 2 asRow v
-}
type V = Vector R
data CGState = CGState
{ cgp :: Vector R -- ^ conjugate gradient
, cgr :: Vector R -- ^ residual
, cgr2 :: R -- ^ squared norm of residual
, cgx :: Vector R -- ^ current solution
, cgdx :: R -- ^ normalized size of correction
}
cg :: Bool -> (V -> V) -> (V -> V) -> CGState -> CGState
cg sym at a (CGState p r r2 x _) = CGState p' r' r'2 x' rdx
where
ap1 = a p
ap | sym = ap1
| otherwise = at ap1
pap | sym = p <.> ap1
| otherwise = norm2 ap1 ** 2
alpha = r2 / pap
dx = scale alpha p
x' = x + dx
r' = r - scale alpha ap
r'2 = r' <.> r'
beta = r'2 / r2
p' = r' + scale beta p
rdx = norm2 dx / max 1 (norm2 x)
conjugrad
:: Bool -> GMatrix -> V -> V -> R -> R -> [CGState]
conjugrad sym a b = solveG sym (tr a !#>) (a !#>) (cg sym) b
solveG
:: Bool
-> (V -> V) -> (V -> V)
-> ((V -> V) -> (V -> V) -> CGState -> CGState)
-> V
-> V
-> R -> R
-> [CGState]
solveG sym mat ma meth rawb x0' ϵb ϵx
= takeUntil ok . iterate (meth mat ma) $ CGState p0 r0 r20 x0 1
where
a = if sym then ma else mat . ma
b = if sym then rawb else mat rawb
x0 = if x0' == 0 then konst 0 (dim b) else x0'
r0 = b - a x0
r20 = r0 <.> r0
p0 = r0
nb2 = b <.> b
ok CGState {..}
= cgr2 <nb2*ϵb**2
|| cgdx < ϵx
takeUntil :: (a -> Bool) -> [a] -> [a]
takeUntil q xs = a++ take 1 b
where
(a,b) = break q xs
-- | Solve a sparse linear system using the conjugate gradient method with default parameters.
cgSolve
:: Bool -- ^ is symmetric
-> GMatrix -- ^ coefficient matrix
-> Vector R -- ^ right-hand side
-> Vector R -- ^ solution
cgSolve sym a b = cgx $ last $ cgSolve' sym 1E-4 1E-3 n a b 0
where
n = max 10 (round $ sqrt (fromIntegral (dim b) :: Double))
-- | Solve a sparse linear system using the conjugate gradient method with default parameters.
cgSolve'
:: Bool -- ^ symmetric
-> R -- ^ relative tolerance for the residual (e.g. 1E-4)
-> R -- ^ relative tolerance for δx (e.g. 1E-3)
-> Int -- ^ maximum number of iterations
-> GMatrix -- ^ coefficient matrix
-> Vector R -- ^ initial solution
-> Vector R -- ^ right-hand side
-> [CGState] -- ^ solution
cgSolve' sym er es n a b x = take n $ conjugrad sym a b x er es
--------------------------------------------------------------------------------
instance Testable GMatrix
where
checkT _ = (ok,info)
where
sma = convo2 20 3
x1 = vect [1..20]
x2 = vect [1..40]
sm = mkSparse sma
dm = toDense sma
s1 = sm !#> x1
d1 = dm #> x1
s2 = tr sm !#> x2
d2 = tr dm #> x2
sdia = mkDiagR 40 20 (vect [1..10])
s3 = sdia !#> x1
s4 = tr sdia !#> x2
ddia = diagRect 0 (vect [1..10]) 40 20
d3 = ddia #> x1
d4 = tr ddia #> x2
v = testb 40
s5 = cgSolve False sm v
d5 = denseSolve dm v
symassoc = [((0,0),1.0),((1,1),2.0),((0,1),0.5),((1,0),0.5)]
b = vect [3,4]
d6 = flatten $ linearSolve (toDense symassoc) (asColumn b)
s6 = cgSolve True (mkSparse symassoc) b
info = do
print sm
disp (toDense sma)
print s1; print d1
print s2; print d2
print s3; print d3
print s4; print d4
print s5; print d5
print $ relativeError (pnorm Infinity) s5 d5
print s6; print d6
print $ relativeError (pnorm Infinity) s6 d6
ok = s1==d1
&& s2==d2
&& s3==d3
&& s4==d4
&& relativeError (pnorm Infinity) s5 d5 < 1E-10
&& relativeError (pnorm Infinity) s6 d6 < 1E-10
disp = putStr . dispf 2
vect = fromList :: [Double] -> Vector Double
convomat :: Int -> Int -> AssocMatrix
convomat n k = [ ((i,j `mod` n),1) | i<-[0..n-1], j <- [i..i+k-1]]
convo2 :: Int -> Int -> AssocMatrix
convo2 n k = m1 ++ m2
where
m1 = convomat n k
m2 = map (((+n) *** id) *** id) m1
testb n = vect $ take n $ cycle ([0..10]++[9,8..1])
denseSolve a = flatten . linearSolveLS a . asColumn
-- mkDiag v = mkDiagR (dim v) (dim v) v
|
