{-# LANGUAGE CPP #-} {-# OPTIONS_GHC -fno-warn-unused-imports -fno-warn-incomplete-patterns #-} ----------------------------------------------------------------------------- {- | Module : Numeric.LinearAlgebra.Tests Copyright : (c) Alberto Ruiz 2007-9 License : GPL-style Maintainer : Alberto Ruiz (aruiz at um dot es) Stability : provisional Portability : portable Some tests. -} module Numeric.LinearAlgebra.Tests( -- module Numeric.LinearAlgebra.Tests.Instances, -- module Numeric.LinearAlgebra.Tests.Properties, qCheck, runTests, runBenchmarks --, runBigTests ) where import Data.Packed.Random import Numeric.LinearAlgebra import Numeric.LinearAlgebra.LAPACK import Numeric.LinearAlgebra.Tests.Instances import Numeric.LinearAlgebra.Tests.Properties import Test.HUnit hiding ((~:),test,Testable,State) import System.Info import Data.List(foldl1') import Numeric.GSL import Prelude hiding ((^)) import qualified Prelude import System.CPUTime import Text.Printf import Data.Packed.Development(unsafeFromForeignPtr,unsafeToForeignPtr) import Control.Arrow((***)) import Debug.Trace #include "Tests/quickCheckCompat.h" debug x = trace (show x) x a ^ b = a Prelude.^ (b :: Int) utest str b = TestCase $ assertBool str b a ~~ b = fromList a |~| fromList b feye n = flipud (ident n) :: Matrix Double ----------------------------------------------------------- detTest1 = det m == 26 && det mc == 38 :+ (-3) && det (feye 2) == -1 where m = (3><3) [ 1, 2, 3 , 4, 5, 7 , 2, 8, 4 :: Double ] mc = (3><3) [ 1, 2, 3 , 4, 5, 7 , 2, 8, i ] detTest2 = inv1 |~| inv2 && [det1] ~~ [det2] where m = complex (feye 6) inv1 = inv m det1 = det m (inv2,(lda,sa)) = invlndet m det2 = sa * exp lda -------------------------------------------------------------------- polyEval cs x = foldr (\c ac->ac*x+c) 0 cs polySolveProp p = length p <2 || last p == 0|| 1E-8 > maximum (map magnitude $ map (polyEval (map (:+0) p)) (polySolve p)) --------------------------------------------------------------------- quad f a b = fst $ integrateQAGS 1E-9 100 f a b -- A multiple integral can be easily defined using partial application quad2 f a b g1 g2 = quad h a b where h x = quad (f x) (g1 x) (g2 x) volSphere r = 8 * quad2 (\x y -> sqrt (r*r-x*x-y*y)) 0 r (const 0) (\x->sqrt (r*r-x*x)) --------------------------------------------------------------------- derivTest = abs (d (\x-> x * d (\y-> x+y) 1) 1 - 1) < 1E-10 where d f x = fst $ derivCentral 0.01 f x --------------------------------------------------------------------- -- besselTest = utest "bessel_J0_e" ( abs (r-expected) < e ) -- where (r,e) = bessel_J0_e 5.0 -- expected = -0.17759677131433830434739701 -- exponentialTest = utest "exp_e10_e" ( abs (v*10^e - expected) < 4E-2 ) -- where (v,e,_err) = exp_e10_e 30.0 -- expected = exp 30.0 --------------------------------------------------------------------- nd1 = (3><3) [ 1/2, 1/4, 1/4 , 0/1, 1/2, 1/4 , 1/2, 1/4, 1/2 :: Double] nd2 = (2><2) [1, 0, 1, 1:: Complex Double] expmTest1 = expm nd1 :~14~: (3><3) [ 1.762110887278176 , 0.478085470590435 , 0.478085470590435 , 0.104719410945666 , 1.709751181805343 , 0.425725765117601 , 0.851451530235203 , 0.530445176063267 , 1.814470592751009 ] expmTest2 = expm nd2 :~15~: (2><2) [ 2.718281828459045 , 0.000000000000000 , 2.718281828459045 , 2.718281828459045 ] --------------------------------------------------------------------- minimizationTest = TestList [ utest "minimization conjugatefr" (minim1 f df [5,7] ~~ [1,2]) , utest "minimization nmsimplex2" (minim2 f [5,7] `elem` [24,25]) ] where f [x,y] = 10*(x-1)^2 + 20*(y-2)^2 + 30 df [x,y] = [20*(x-1), 40*(y-2)] minim1 g dg ini = fst $ minimizeD ConjugateFR 1E-3 30 1E-2 1E-4 g dg ini minim2 g ini = rows $ snd $ minimize NMSimplex2 1E-2 30 [1,1] g ini --------------------------------------------------------------------- rootFindingTest = TestList [ utest "root Hybrids" (fst sol1 ~~ [1,1]) , utest "root Newton" (rows (snd sol2) == 2) ] where sol1 = root Hybrids 1E-7 30 (rosenbrock 1 10) [-10,-5] sol2 = rootJ Newton 1E-7 30 (rosenbrock 1 10) (jacobian 1 10) [-10,-5] rosenbrock a b [x,y] = [ a*(1-x), b*(y-x^2) ] jacobian a b [x,_y] = [ [-a , 0] , [-2*b*x, b] ] --------------------------------------------------------------------- odeTest = utest "ode" (last (toLists sol) ~~ [-1.7588880332411019, 8.364348908711941e-2]) where sol = odeSolveV RK8pd 1E-6 1E-6 0 (l2v $ vanderpol 10) Nothing (fromList [1,0]) ts ts = linspace 101 (0,100) l2v f = \t -> fromList . f t . toList vanderpol mu _t [x,y] = [y, -x + mu * y * (1-x^2) ] --------------------------------------------------------------------- fittingTest = utest "levmar" (ok1 && ok2) where xs = map return [0 .. 39] sigma = 0.1 ys = map return $ toList $ fromList (map (head . expModel [5,0.1,1]) xs) + scalar sigma * (randomVector 0 Gaussian 40) dats = zip xs (zip ys (repeat sigma)) dat = zip xs ys expModel [a,lambda,b] [t] = [a * exp (-lambda * t) + b] expModelDer [a,lambda,_b] [t] = [[exp (-lambda * t), -t * a * exp(-lambda*t) , 1]] sols = fst $ fitModelScaled 1E-4 1E-4 20 (expModel, expModelDer) dats [1,0,0] sol = fst $ fitModel 1E-4 1E-4 20 (expModel, expModelDer) dat [1,0,0] ok1 = and (zipWith f sols [5,0.1,1]) where f (x,d) r = abs (x-r)<2*d ok2 = norm2 (fromList (map fst sols) - fromList sol) < 1E-5 ----------------------------------------------------- mbCholTest = utest "mbCholTest" (ok1 && ok2) where m1 = (2><2) [2,5,5,8 :: Double] m2 = (2><2) [3,5,5,9 :: Complex Double] ok1 = mbCholSH m1 == Nothing ok2 = mbCholSH m2 == Just (chol m2) --------------------------------------------------------------------- randomTestGaussian = c :~1~: snd (meanCov dat) where a = (3><3) [1,2,3, 2,4,0, -2,2,1] m = 3 |> [1,2,3] c = a <> trans a dat = gaussianSample 7 (10^6) m c randomTestUniform = c :~1~: snd (meanCov dat) where c = diag $ 3 |> map ((/12).(^2)) [1,2,3] dat = uniformSample 7 (10^6) [(0,1),(1,3),(3,6)] --------------------------------------------------------------------- rot :: Double -> Matrix Double rot a = (3><3) [ c,0,s , 0,1,0 ,-s,0,c ] where c = cos a s = sin a rotTest = fun (10^5) :~11~: rot 5E4 where fun n = foldl1' (<>) (map rot angles) where angles = toList $ linspace n (0,1) --------------------------------------------------------------------- -- vector <= 0.6.0.2 bug discovered by Patrick Perry -- http://trac.haskell.org/vector/ticket/31 offsetTest = y == y' where x = fromList [0..3 :: Double] y = subVector 1 3 x (f,o,n) = unsafeToForeignPtr y y' = unsafeFromForeignPtr f o n --------------------------------------------------------------------- normsVTest = TestList [ utest "normv2CD" $ norm2PropC v , utest "normv2CF" $ norm2PropC (single v) #ifndef NONORMVTEST , utest "normv2D" $ norm2PropR x , utest "normv2F" $ norm2PropR (single x) #endif , utest "normv1CD" $ norm1 v == 8 , utest "normv1CF" $ norm1 (single v) == 8 , utest "normv1D" $ norm1 x == 6 , utest "normv1F" $ norm1 (single x) == 6 , utest "normvInfCD" $ normInf v == 5 , utest "normvInfCF" $ normInf (single v) == 5 , utest "normvInfD" $ normInf x == 3 , utest "normvInfF" $ normInf (single x) == 3 ] where v = fromList [1,-2,3:+4] :: Vector (Complex Double) x = fromList [1,2,-3] :: Vector Double #ifndef NONORMVTEST norm2PropR a = norm2 a =~= sqrt (dot a a) #endif norm2PropC a = norm2 a =~= realPart (sqrt (dot a (conj a))) a =~= b = fromList [a] |~| fromList [b] normsMTest = TestList [ utest "norm2mCD" $ pnorm PNorm2 v =~= 8.86164970498005 , utest "norm2mCF" $ pnorm PNorm2 (single v) =~= 8.86164970498005 , utest "norm2mD" $ pnorm PNorm2 x =~= 5.96667765076216 , utest "norm2mF" $ pnorm PNorm2 (single x) =~= 5.96667765076216 , utest "norm1mCD" $ pnorm PNorm1 v == 9 , utest "norm1mCF" $ pnorm PNorm1 (single v) == 9 , utest "norm1mD" $ pnorm PNorm1 x == 7 , utest "norm1mF" $ pnorm PNorm1 (single x) == 7 , utest "normmInfCD" $ pnorm Infinity v == 12 , utest "normmInfCF" $ pnorm Infinity (single v) == 12 , utest "normmInfD" $ pnorm Infinity x == 8 , utest "normmInfF" $ pnorm Infinity (single x) == 8 , utest "normmFroCD" $ pnorm Frobenius v =~= 8.88819441731559 , utest "normmFroCF" $ pnorm Frobenius (single v) =~~= 8.88819441731559 , utest "normmFroD" $ pnorm Frobenius x =~= 6.24499799839840 , utest "normmFroF" $ pnorm Frobenius (single x) =~~= 6.24499799839840 ] where v = (2><2) [1,-2*i,3:+4,7] :: Matrix (Complex Double) x = (2><2) [1,2,-3,5] :: Matrix Double a =~= b = fromList [a] :~10~: fromList [b] a =~~= b = fromList [a] :~5~: fromList [b] --------------------------------------------------------------------- sumprodTest = TestList [ utest "sumCD" $ sumElements z == 6 , utest "sumCF" $ sumElements (single z) == 6 , utest "sumD" $ sumElements v == 6 , utest "sumF" $ sumElements (single v) == 6 , utest "prodCD" $ prodProp z , utest "prodCF" $ prodProp (single z) , utest "prodD" $ prodProp v , utest "prodF" $ prodProp (single v) ] where v = fromList [1,2,3] :: Vector Double z = fromList [1,2-i,3+i] prodProp x = prodElements x == product (toList x) --------------------------------------------------------------------- chainTest = utest "chain" $ foldl1' (<>) ms |~| optimiseMult ms where ms = [ diag (fromList [1,2,3 :: Double]) , konst 3 (3,5) , (5><10) [1 .. ] , konst 5 (10,2) ] --------------------------------------------------------------------- conjuTest m = mapVector conjugate (flatten (trans m)) == flatten (ctrans m) --------------------------------------------------------------------- newtype State s a = State { runState :: s -> (a,s) } instance Monad (State s) where return a = State $ \s -> (a,s) m >>= f = State $ \s -> let (a,s') = runState m s in runState (f a) s' state_get :: State s s state_get = State $ \s -> (s,s) state_put :: s -> State s () state_put s = State $ \_ -> ((),s) evalState :: State s a -> s -> a evalState m s = let (a,s') = runState m s in seq s' a newtype MaybeT m a = MaybeT { runMaybeT :: m (Maybe a) } instance Monad m => Monad (MaybeT m) where return a = MaybeT $ return $ Just a m >>= f = MaybeT $ do res <- runMaybeT m case res of Nothing -> return Nothing Just r -> runMaybeT (f r) fail _ = MaybeT $ return Nothing lift_maybe m = MaybeT $ do res <- m return $ Just res -- | apply a test to successive elements of a vector, evaluates to true iff test passes for all pairs --successive_ :: Storable a => (a -> a -> Bool) -> Vector a -> Bool successive_ t v = maybe False (\_ -> True) $ evalState (runMaybeT (mapVectorM_ stp (subVector 1 (dim v - 1) v))) (v @> 0) where stp e = do ep <- lift_maybe $ state_get if t e ep then lift_maybe $ state_put e else (fail "successive_ test failed") -- | operate on successive elements of a vector and return the resulting vector, whose length 1 less than that of the input --successive :: (Storable a, Storable b) => (a -> a -> b) -> Vector a -> Vector b successive f v = evalState (mapVectorM stp (subVector 1 (dim v - 1) v)) (v @> 0) where stp e = do ep <- state_get state_put e return $ f ep e succTest = utest "successive" $ successive_ (>) (fromList [1 :: Double,2,3,4]) == True && successive_ (>) (fromList [1 :: Double,3,2,4]) == False && successive (+) (fromList [1..10 :: Double]) == 9 |> [3,5,7,9,11,13,15,17,19] --------------------------------------------------------------------- findAssocTest = utest "findAssoc" ok where ok = m1 == m2 m1 = assoc (6,6) 7 $ zip (find (>0) (ident 5 :: Matrix Float)) [10 ..] :: Matrix Double m2 = diagRect 7 (fromList[10..14]) 6 6 --------------------------------------------------------------------- condTest = utest "cond" ok where ok = step v * v == cond v 0 0 0 v v = fromList [-7 .. 7 ] :: Vector Float --------------------------------------------------------------------- conformTest = utest "conform" ok where ok = 1 + row [1,2,3] + col [10,20,30,40] + (4><3) [1..] == (4><3) [13,15,17 ,26,28,30 ,39,41,43 ,52,54,56] row = asRow . fromList col = asColumn . fromList :: [Double] -> Matrix Double --------------------------------------------------------------------- accumTest = utest "accum" ok where x = ident 3 :: Matrix Double ok = accum x (+) [((1,2),7), ((2,2),3)] == (3><3) [1,0,0 ,0,1,7 ,0,0,4] && toList (flatten x) == [1,0,0,0,1,0,0,0,1] --------------------------------------------------------------------- -- | All tests must pass with a maximum dimension of about 20 -- (some tests may fail with bigger sizes due to precision loss). runTests :: Int -- ^ maximum dimension -> IO () runTests n = do setErrorHandlerOff let test p = qCheck n p putStrLn "------ mult Double" test (multProp1 10 . rConsist) test (multProp1 10 . cConsist) test (multProp2 10 . rConsist) test (multProp2 10 . cConsist) putStrLn "------ mult Float" test (multProp1 6 . (single *** single) . rConsist) test (multProp1 6 . (single *** single) . cConsist) test (multProp2 6 . (single *** single) . rConsist) test (multProp2 6 . (single *** single) . cConsist) putStrLn "------ sub-trans" test (subProp . rM) test (subProp . cM) putStrLn "------ ctrans" test (conjuTest . cM) test (conjuTest . zM) putStrLn "------ lu" test (luProp . rM) test (luProp . cM) putStrLn "------ inv (linearSolve)" test (invProp . rSqWC) test (invProp . cSqWC) putStrLn "------ luSolve" test (linearSolveProp (luSolve.luPacked) . rSqWC) test (linearSolveProp (luSolve.luPacked) . cSqWC) putStrLn "------ cholSolve" test (linearSolveProp (cholSolve.chol) . rPosDef) test (linearSolveProp (cholSolve.chol) . cPosDef) putStrLn "------ luSolveLS" test (linearSolveProp linearSolveLS . rSqWC) test (linearSolveProp linearSolveLS . cSqWC) test (linearSolveProp2 linearSolveLS . rConsist) test (linearSolveProp2 linearSolveLS . cConsist) putStrLn "------ pinv (linearSolveSVD)" test (pinvProp . rM) test (pinvProp . cM) putStrLn "------ det" test (detProp . rSqWC) test (detProp . cSqWC) putStrLn "------ svd" test (svdProp1 . rM) test (svdProp1 . cM) test (svdProp1a svdR) test (svdProp1a svdC) test (svdProp1a svdRd) test (svdProp1b svdR) test (svdProp1b svdC) test (svdProp1b svdRd) test (svdProp2 thinSVDR) test (svdProp2 thinSVDC) test (svdProp2 thinSVDRd) test (svdProp2 thinSVDCd) test (svdProp3 . rM) test (svdProp3 . cM) test (svdProp4 . rM) test (svdProp4 . cM) test (svdProp5a) test (svdProp5b) test (svdProp6a) test (svdProp6b) test (svdProp7 . rM) test (svdProp7 . cM) putStrLn "------ svdCd" #ifdef NOZGESDD putStrLn "Omitted" #else test (svdProp1a svdCd) test (svdProp1b svdCd) #endif putStrLn "------ eig" test (eigSHProp . rHer) test (eigSHProp . cHer) test (eigProp . rSq) test (eigProp . cSq) test (eigSHProp2 . rHer) test (eigSHProp2 . cHer) test (eigProp2 . rSq) test (eigProp2 . cSq) putStrLn "------ nullSpace" test (nullspaceProp . rM) test (nullspaceProp . cM) putStrLn "------ qr" test (qrProp . rM) test (qrProp . cM) test (rqProp . rM) test (rqProp . cM) test (rqProp1 . cM) test (rqProp2 . cM) test (rqProp3 . cM) putStrLn "------ hess" test (hessProp . rSq) test (hessProp . cSq) putStrLn "------ schur" test (schurProp2 . rSq) test (schurProp1 . cSq) putStrLn "------ chol" test (cholProp . rPosDef) test (cholProp . cPosDef) putStrLn "------ expm" test (expmDiagProp . complex. rSqWC) test (expmDiagProp . cSqWC) putStrLn "------ fft" test (\v -> ifft (fft v) |~| v) putStrLn "------ vector operations - Double" test (\u -> sin u ^ 2 + cos u ^ 2 |~| (1::RM)) test $ (\u -> sin u ^ 2 + cos u ^ 2 |~| (1::CM)) . liftMatrix makeUnitary test (\u -> sin u ** 2 + cos u ** 2 |~| (1::RM)) test (\u -> cos u * tan u |~| sin (u::RM)) test $ (\u -> cos u * tan u |~| sin (u::CM)) . liftMatrix makeUnitary putStrLn "------ vector operations - Float" test (\u -> sin u ^ 2 + cos u ^ 2 |~~| (1::FM)) test $ (\u -> sin u ^ 2 + cos u ^ 2 |~~| (1::ZM)) . liftMatrix makeUnitary test (\u -> sin u ** 2 + cos u ** 2 |~~| (1::FM)) test (\u -> cos u * tan u |~~| sin (u::FM)) test $ (\u -> cos u * tan u |~~| sin (u::ZM)) . liftMatrix makeUnitary putStrLn "------ read . show" test (\m -> (m::RM) == read (show m)) test (\m -> (m::CM) == read (show m)) test (\m -> toRows (m::RM) == read (show (toRows m))) test (\m -> toRows (m::CM) == read (show (toRows m))) test (\m -> (m::FM) == read (show m)) test (\m -> (m::ZM) == read (show m)) test (\m -> toRows (m::FM) == read (show (toRows m))) test (\m -> toRows (m::ZM) == read (show (toRows m))) putStrLn "------ some unit tests" _ <- runTestTT $ TestList [ utest "1E5 rots" rotTest , utest "det1" detTest1 , utest "invlndet" detTest2 , utest "expm1" (expmTest1) , utest "expm2" (expmTest2) , utest "arith1" $ ((ones (100,100) * 5 + 2)/0.5 - 7)**2 |~| (49 :: RM) , utest "arith2" $ ((scalar (1+i) * ones (100,100) * 5 + 2)/0.5 - 7)**2 |~| ( scalar (140*i-51) :: CM) , utest "arith3" $ exp (scalar i * ones(10,10)*pi) + 1 |~| 0 , utest "<\\>" $ (3><2) [2,0,0,3,1,1::Double] <\> 3|>[4,9,5] |~| 2|>[2,3] -- , utest "gamma" (gamma 5 == 24.0) -- , besselTest -- , exponentialTest , utest "deriv" derivTest , utest "integrate" (abs (volSphere 2.5 - 4/3*pi*2.5^3) < 1E-8) , utest "polySolve" (polySolveProp [1,2,3,4]) , minimizationTest , rootFindingTest , utest "randomGaussian" randomTestGaussian , utest "randomUniform" randomTestUniform , utest "buildVector/Matrix" $ complex (10 |> [0::Double ..]) == buildVector 10 fromIntegral && ident 5 == buildMatrix 5 5 (\(r,c) -> if r==c then 1::Double else 0) , utest "rank" $ rank ((2><3)[1,0,0,1,6*eps,0]) == 1 && rank ((2><3)[1,0,0,1,7*eps,0]) == 2 , utest "block" $ fromBlocks [[ident 3,0],[0,ident 4]] == (ident 7 :: CM) , odeTest , fittingTest , mbCholTest , utest "offset" offsetTest , normsVTest , normsMTest , sumprodTest , chainTest , succTest , findAssocTest , condTest , conformTest , accumTest ] return () -- single precision approximate equality infixl 4 |~~| a |~~| b = a :~6~: b makeUnitary v | realPart n > 1 = v / scalar n | otherwise = v where n = sqrt (conj v <.> v) -- -- | Some additional tests on big matrices. They take a few minutes. -- runBigTests :: IO () -- runBigTests = undefined -------------------------------------------------------------------------------- -- | Performance measurements. runBenchmarks :: IO () runBenchmarks = do --cholBench solveBench subBench multBench svdBench eigBench putStrLn "" -------------------------------- time msg act = do putStr (msg++" ") t0 <- getCPUTime act `seq` putStr " " t1 <- getCPUTime printf "%6.2f s CPU\n" $ (fromIntegral (t1 - t0) / (10^12 :: Double)) :: IO () return () -------------------------------- manymult n = foldl1' (<>) (map rot2 angles) where angles = toList $ linspace n (0,1) rot2 :: Double -> Matrix Double rot2 a = (3><3) [ c,0,s , 0,1,0 ,-s,0,c ] where c = cos a s = sin a multb n = foldl1' (<>) (replicate (10^6) (ident n :: Matrix Double)) -------------------------------- subBench = do putStrLn "" let g = foldl1' (.) (replicate (10^5) (\v -> subVector 1 (dim v -1) v)) time "0.1M subVector " (g (constant 1 (1+10^5) :: Vector Double) @> 0) let f = foldl1' (.) (replicate (10^5) (fromRows.toRows)) time "subVector-join 3" (f (ident 3 :: Matrix Double) @@>(0,0)) time "subVector-join 10" (f (ident 10 :: Matrix Double) @@>(0,0)) -------------------------------- multBench = do let a = ident 1000 :: Matrix Double let b = ident 2000 :: Matrix Double a `seq` b `seq` putStrLn "" time "product of 1M different 3x3 matrices" (manymult (10^6)) putStrLn "" time "product of 1M constant 1x1 matrices" (multb 1) time "product of 1M constant 3x3 matrices" (multb 3) --time "product of 1M constant 5x5 matrices" (multb 5) time "product of 1M const. 10x10 matrices" (multb 10) --time "product of 1M const. 15x15 matrices" (multb 15) time "product of 1M const. 20x20 matrices" (multb 20) --time "product of 1M const. 25x25 matrices" (multb 25) putStrLn "" time "product (1000 x 1000)<>(1000 x 1000)" (a<>a) time "product (2000 x 2000)<>(2000 x 2000)" (b<>b) -------------------------------- eigBench = do let m = reshape 1000 (randomVector 777 Uniform (1000*1000)) s = m + trans m m `seq` s `seq` putStrLn "" time "eigenvalues symmetric 1000x1000" (eigenvaluesSH' m) time "eigenvectors symmetric 1000x1000" (snd $ eigSH' m) time "eigenvalues general 1000x1000" (eigenvalues m) time "eigenvectors general 1000x1000" (snd $ eig m) -------------------------------- svdBench = do let a = reshape 500 (randomVector 777 Uniform (3000*500)) b = reshape 1000 (randomVector 777 Uniform (1000*1000)) fv (_,_,v) = v@@>(0,0) a `seq` b `seq` putStrLn "" time "singular values 3000x500" (singularValues a) time "thin svd 3000x500" (fv $ thinSVD a) time "full svd 3000x500" (fv $ svd a) time "singular values 1000x1000" (singularValues b) time "full svd 1000x1000" (fv $ svd b) -------------------------------- solveBenchN n = do let x = uniformSample 777 (2*n) (replicate n (-1,1)) a = trans x <> x b = asColumn $ randomVector 666 Uniform n a `seq` b `seq` putStrLn "" time ("svd solve " ++ show n) (linearSolveSVD a b) time (" ls solve " ++ show n) (linearSolveLS a b) time (" solve " ++ show n) (linearSolve a b) time ("cholSolve " ++ show n) (cholSolve (chol a) b) solveBench = do solveBenchN 500 solveBenchN 1000 -- solveBenchN 1500 -------------------------------- cholBenchN n = do let x = uniformSample 777 (2*n) (replicate n (-1,1)) a = trans x <> x a `seq` putStrLn "" time ("chol " ++ show n) (chol a) cholBench = do cholBenchN 1200 cholBenchN 600 cholBenchN 300 -- cholBenchN 150 -- cholBenchN 50