numeric-prelude-0.4: src/MathObj/Polynomial.hs
{-# LANGUAGE NoImplicitPrelude #-}
{-# LANGUAGE MultiParamTypeClasses #-}
{-# LANGUAGE FlexibleInstances #-}
{- |
Polynomials and rational functions in a single indeterminate.
Polynomials are represented by a list of coefficients.
All non-zero coefficients are listed, but there may be extra '0's at the end.
Usage:
Say you have the ring of 'Integer' numbers
and you want to add a transcendental element @x@,
that is an element, which does not allow for simplifications.
More precisely, for all positive integer exponents @n@
the power @x^n@ cannot be rewritten as a sum of powers with smaller exponents.
The element @x@ must be represented by the polynomial @[0,1]@.
In principle, you can have more than one transcendental element
by using polynomials whose coefficients are polynomials as well.
However, most algorithms on multi-variate polynomials
prefer a different (sparse) representation,
where the ordering of elements is not so fixed.
If you want division, you need "Number.Ratio"s
of polynomials with coefficients from a "Algebra.Field".
You can also compute with an algebraic element,
that is an element which satisfies an algebraic equation like
@x^3-x-1==0@.
Actually, powers of @x@ with exponents above @3@ can be simplified,
since it holds @x^3==x+1@.
You can perform these computations with "Number.ResidueClass" of polynomials,
where the divisor is the polynomial equation that determines @x@.
If the polynomial is irreducible
(in our case @x^3-x-1@ cannot be written as a non-trivial product)
then the residue classes also allow unrestricted division
(except by zero, of course).
That is, using residue classes of polynomials
you can work with roots of polynomial equations
without representing them by radicals
(powers with fractional exponents).
It is well-known, that roots of polynomials of degree above 4
may not be representable by radicals.
-}
module MathObj.Polynomial
(T, fromCoeffs, coeffs, degree,
showsExpressionPrec, const,
evaluate, evaluateCoeffVector, evaluateArgVector,
collinear,
integrate,
compose, fromRoots, reverse,
translate, dilate, shrink, )
where
import qualified MathObj.Polynomial.Core as Core
import qualified Algebra.Differential as Differential
import qualified Algebra.VectorSpace as VectorSpace
import qualified Algebra.Module as Module
import qualified Algebra.Vector as Vector
import qualified Algebra.Field as Field
import qualified Algebra.PrincipalIdealDomain as PID
import qualified Algebra.Units as Units
import qualified Algebra.IntegralDomain as Integral
import qualified Algebra.Ring as Ring
import qualified Algebra.Additive as Additive
import qualified Algebra.ZeroTestable as ZeroTestable
import qualified Algebra.Indexable as Indexable
import Control.Monad (liftM, )
import qualified Data.List as List
import Test.QuickCheck (Arbitrary(arbitrary))
import qualified MathObj.Wrapper.Haskell98 as W98
import NumericPrelude.Base hiding (const, reverse, )
import NumericPrelude.Numeric
import qualified Prelude as P98
newtype T a = Cons {coeffs :: [a]}
{-# INLINE fromCoeffs #-}
fromCoeffs :: [a] -> T a
fromCoeffs = lift0
{-# INLINE lift0 #-}
lift0 :: [a] -> T a
lift0 = Cons
{-# INLINE lift1 #-}
lift1 :: ([a] -> [a]) -> (T a -> T a)
lift1 f (Cons x0) = Cons (f x0)
{-# INLINE lift2 #-}
lift2 :: ([a] -> [a] -> [a]) -> (T a -> T a -> T a)
lift2 f (Cons x0) (Cons x1) = Cons (f x0 x1)
degree :: (ZeroTestable.C a) => T a -> Maybe Int
degree x =
case Core.normalize (coeffs x) of
[] -> Nothing
(_:xs) -> Just $ length xs
{-
Functor instance is e.g. useful for showing polynomials in residue rings.
@fmap (ResidueClass.concrete 7) (polynomial [1,4,4::ResidueClass.T Integer] * polynomial [1,5,6])@
-}
instance Functor T where
fmap f (Cons xs) = Cons (map f xs)
{-# INLINE plusPrec #-}
{-# INLINE appPrec #-}
plusPrec, appPrec :: Int
plusPrec = 6
appPrec = 10
instance (Show a) => Show (T a) where
showsPrec p (Cons xs) =
showParen (p >= appPrec) (showString "Polynomial.fromCoeffs " . shows xs)
{-# INLINE showsExpressionPrec #-}
showsExpressionPrec :: (Show a, ZeroTestable.C a, Additive.C a) =>
Int -> String -> T a -> String -> String
showsExpressionPrec p var poly =
if isZero poly
then showString "0"
else
let terms = filter (not . isZero . fst)
(zip (coeffs poly) monomials)
monomials = id :
showString "*" . showString var :
map (\k -> showString "*" . showString var
. showString "^" . shows k)
[(2::Int)..]
showsTerm x showsMon = showsPrec (plusPrec+1) x . showsMon
in showParen (p > plusPrec)
(foldl (.) id $ List.intersperse (showString " + ") $
map (uncurry showsTerm) terms)
{-# INLINE evaluate #-}
evaluate :: Ring.C a => T a -> a -> a
evaluate (Cons y) x = Core.horner x y
{- |
Here the coefficients are vectors,
for example the coefficients are real and the coefficents are real vectors.
-}
{-# INLINE evaluateCoeffVector #-}
evaluateCoeffVector :: Module.C a v => T v -> a -> v
evaluateCoeffVector (Cons y) x = Core.hornerCoeffVector x y
{- |
Here the argument is a vector,
for example the coefficients are complex numbers or square matrices
and the coefficents are reals.
-}
{-# INLINE evaluateArgVector #-}
evaluateArgVector :: (Module.C a v, Ring.C v) => T a -> v -> v
evaluateArgVector (Cons y) x = Core.hornerArgVector x y
{- |
'compose' is the functional composition of polynomials.
It fulfills
@ eval x . eval y == eval (compose x y) @
-}
-- compose :: Module.C a b => T b -> T a -> T a
-- compose (Cons x) y = Core.horner y (map const x)
{-# INLINE compose #-}
compose :: (Ring.C a) => T a -> T a -> T a
compose (Cons x) y = Core.horner y (map const x)
{-# INLINE const #-}
const :: a -> T a
const x = lift0 [x]
collinear :: (Eq a, Ring.C a) => T a -> T a -> Bool
collinear (Cons x) (Cons y) = Core.collinear x y
instance (Eq a, ZeroTestable.C a) => Eq (T a) where
(Cons x) == (Cons y) = Core.equal x y
instance (Indexable.C a, ZeroTestable.C a) => Indexable.C (T a) where
compare = Indexable.liftCompare coeffs
instance (ZeroTestable.C a) => ZeroTestable.C (T a) where
isZero (Cons x) = isZero x
instance (Additive.C a) => Additive.C (T a) where
(+) = lift2 Core.add
(-) = lift2 Core.sub
zero = lift0 []
negate = lift1 Core.negate
instance Vector.C T where
zero = zero
(<+>) = (+)
(*>) = Vector.functorScale
instance (Module.C a b) => Module.C a (T b) where
(*>) x = lift1 (x *>)
instance (Field.C a, Module.C a b) => VectorSpace.C a (T b)
instance (Ring.C a) => Ring.C (T a) where
one = const one
fromInteger = const . fromInteger
(*) = lift2 Core.mul
{- |
The 'Integral.C' instance is intensionally built
from the 'Field.C' structure of the polynomial coefficients.
If we would use @Integral.C a@ superclass,
then the Euclidean algorithm could not determine
the greatest common divisor of e.g. @[1,1]@ and @[2]@.
-}
instance (ZeroTestable.C a, Field.C a) => Integral.C (T a) where
divMod (Cons x) (Cons y) =
let (d,m) = Core.divMod x y
in (Cons d, Cons m)
instance (ZeroTestable.C a, Field.C a) => Units.C (T a) where
isUnit (Cons []) = False
isUnit (Cons (x0:xs)) = not (isZero x0) && all isZero xs
stdUnit (Cons x) = const (Core.stdUnit x)
stdUnitInv (Cons x) = const (recip (Core.stdUnit x))
{-
Polynomials are a Euclidean domain, so no instance is necessary
(although it might be faster).
-}
instance (ZeroTestable.C a, Field.C a) => PID.C (T a)
instance (Ring.C a) => Differential.C (T a) where
differentiate = lift1 Core.differentiate
{-# INLINE integrate #-}
integrate :: (Field.C a) => a -> T a -> T a
integrate = lift1 . Core.integrate
{-# INLINE fromRoots #-}
fromRoots :: (Ring.C a) => [a] -> T a
fromRoots = Cons . foldl (flip Core.mulLinearFactor) [one]
{-# INLINE reverse #-}
reverse :: Additive.C a => T a -> T a
reverse = lift1 Core.alternate
translate :: Ring.C a => a -> T a -> T a
translate d =
lift1 $ foldr (\c p -> [c] + Core.mulLinearFactor d p) []
shrink :: Ring.C a => a -> T a -> T a
shrink k =
lift1 $ zipWith (*) (iterate (k*) one)
dilate :: Field.C a => a -> T a -> T a
dilate = shrink . Field.recip
instance (Arbitrary a, ZeroTestable.C a) => Arbitrary (T a) where
arbitrary = liftM (fromCoeffs . Core.normalize) arbitrary
-- * Haskell 98 legacy instances
{- |
It is disputable whether polynomials shall be represented by number literals or not.
An advantage is, that one can write
let x = polynomial [0,1]
in (x^2+x+1)*(x-1)
However the output looks much different.
-}
{-# INLINE notImplemented #-}
notImplemented :: String -> a
notImplemented name =
error $ "MathObj.Polynomial: method " ++ name ++ " cannot be implemented"
-- legacy instances for use of numeric literals in GHCi
instance (P98.Num a) => P98.Num (T a) where
fromInteger = const . P98.fromInteger
negate = W98.unliftF1 Additive.negate
(+) = W98.unliftF2 (Additive.+)
(*) = W98.unliftF2 (Ring.*)
abs = notImplemented "abs"
signum = notImplemented "signum"
instance (P98.Fractional a) => P98.Fractional (T a) where
fromRational = const . P98.fromRational
(/) = notImplemented "(/)"