X-Git-Url: http://gitweb.michael.orlitzky.com/?a=blobdiff_plain;f=src%2FRoots%2FSimple.hs;h=3237d60217aeb9e94bafe6983cf8f6a5dd353727;hb=c5da1efa77844ae6159dfc781ed886fdffbbf4d1;hp=2689163dbbe263ab0bb291958c652576a5797279;hpb=b55c792bd9e2d439c5f1aebae160c92941a87e4e;p=numerical-analysis.git diff --git a/src/Roots/Simple.hs b/src/Roots/Simple.hs index 2689163..3237d60 100644 --- a/src/Roots/Simple.hs +++ b/src/Roots/Simple.hs @@ -11,6 +11,8 @@ where import Data.List (find) +import Vector + import qualified Roots.Fast as F -- | Does the (continuous) function @f@ have a root on the interval @@ -77,6 +79,15 @@ bisect f a b epsilon = -- | The sequence x_{n} of values obtained by applying Newton's method -- on the function @f@ and initial guess @x0@. +-- +-- Examples: +-- +-- Atkinson, p. 60. +-- >>> let f x = x^6 - x - 1 +-- >>> let f' x = 6*x^5 - 1 +-- >>> tail $ take 4 $ newton_iterations f f' 2 +-- [1.6806282722513088,1.4307389882390624,1.2549709561094362] +-- newton_iterations :: (Fractional a, Ord a) => (a -> a) -- ^ The function @f@ whose root we seek -> (a -> a) -- ^ The derivative of @f@ @@ -92,14 +103,35 @@ newton_iterations f f' x0 = -- | Use Newton's method to find a root of @f@ near the initial guess -- @x0@. If your guess is bad, this will recurse forever! +-- +-- Examples: +-- +-- Atkinson, p. 60. +-- +-- >>> let f x = x^6 - x - 1 +-- >>> let f' x = 6*x^5 - 1 +-- >>> let Just root = newtons_method f f' (1/1000000) 2 +-- >>> root +-- 1.1347241385002211 +-- >>> abs (f root) < 1/100000 +-- True +-- +-- >>> import Data.Number.BigFloat +-- >>> let eps = 1/(10^20) :: BigFloat Prec50 +-- >>> let Just root = newtons_method f f' eps 2 +-- >>> root +-- 1.13472413840151949260544605450647284028100785303643e0 +-- >>> abs (f root) < eps +-- True +-- newtons_method :: (Fractional a, Ord a) => (a -> a) -- ^ The function @f@ whose root we seek -> (a -> a) -- ^ The derivative of @f@ -> a -- ^ The tolerance epsilon -> a -- ^ Initial guess, x-naught -> Maybe a -newtons_method f f' epsilon x0 - = find (\x -> abs (f x) < epsilon) x_n +newtons_method f f' epsilon x0 = + find (\x -> abs (f x) < epsilon) x_n where x_n = newton_iterations f f' x0 @@ -180,3 +212,54 @@ secant_method f epsilon x0 x1 = find (\x -> abs (f x) < epsilon) x_n where x_n = secant_iterations f x0 x1 + + + +-- | Find a fixed point of the function @f@ with the search starting +-- at x0. We delegate to the version that returns the number of +-- iterations and simply discard the number of iterations. +-- +fixed_point :: (Vector a, RealFrac b) + => (a -> a) -- ^ The function @f@ to iterate. + -> b -- ^ The tolerance, @epsilon@. + -> a -- ^ The initial value @x0@. + -> a -- ^ The fixed point. +fixed_point f epsilon x0 = + snd $ F.fixed_point_with_iterations f epsilon x0 + + +-- | Return the number of iterations required to find a fixed point of +-- the function @f@ with the search starting at x0 and tolerance +-- @epsilon@. We delegate to the version that returns the number of +-- iterations and simply discard the fixed point. +fixed_point_iteration_count :: (Vector a, RealFrac b) + => (a -> a) -- ^ The function @f@ to iterate. + -> b -- ^ The tolerance, @epsilon@. + -> a -- ^ The initial value @x0@. + -> Int -- ^ The fixed point. +fixed_point_iteration_count f epsilon x0 = + fst $ F.fixed_point_with_iterations f epsilon x0 + + +-- | Returns a list of ratios, +-- +-- ||x^{*} - x_{n+1}|| / ||x^{*} - x_{n}||^{p} +-- +-- of fixed point iterations for the function @f@ with initial guess +-- @x0@ and @p@ some positive power. +-- +-- This is used to determine the rate of convergence. +-- +fixed_point_error_ratios :: (Vector a, RealFrac b) + => (a -> a) -- ^ The function @f@ to iterate. + -> a -- ^ The initial value @x0@. + -> a -- ^ The true solution, @x_star@. + -> Integer -- ^ The power @p@. + -> [b] -- ^ The resulting sequence of x_{n}. +fixed_point_error_ratios f x0 x_star p = + zipWith (/) en_plus_one en_exp + where + xn = F.fixed_point_iterations f x0 + en = map (\x -> norm (x_star - x)) xn + en_plus_one = tail en + en_exp = map (^p) en