-- Copyright (c) David Amos, 2008. All rights reserved. {-# OPTIONS_GHC -fglasgow-exts #-} -- |A module providing elementary operations involving scalars, vectors, and matrices -- over a ring or field. Vectors are represented as [a], matrices as [[a]]. -- (No distinction is made between row and column vectors.) -- It is the caller's responsibility to ensure that the lists have the correct number of elements. -- -- The mnemonic for many of the arithmetic operations is that the number of angle brackets -- on each side indicates the dimension of the argument on that side. For example, -- v \<*\>\> m is multiplication of a vector on the left by a matrix on the right. module Math.Algebra.LinearAlgebra where import qualified Data.List as L import Math.Algebra.Field.Base -- not actually used in this module infixr 8 *>, *>> infixr 7 <<*> infixl 7 <.>, <*>, <<*>>, <*>> infixl 6 <+>, <->, <<+>>, <<->> -- The mnemonic for these operations is that the number of angle brackets on each side indicates the dimension of the argument on that side -- vector operations -- |u \<+\> v returns the sum u+v of vectors (<+>) :: (Num a) => [a] -> [a] -> [a] u <+> v = zipWith (+) u v -- |u \<-\> v returns the difference u-v of vectors (<->) :: (Num a) => [a] -> [a] -> [a] u <-> v = zipWith (-) u v -- |k *\> v returns the product k*v of the scalar k and the vector v (*>) :: (Num a) => a -> [a] -> [a] k *> v = map (k*) v -- |u \<.\> v returns the dot product of vectors (also called inner or scalar product) (<.>) :: (Num a) => [a] -> [a] -> a u <.> v = sum (zipWith (*) u v) -- |u \<*\> v returns the tensor product of vectors (also called outer or matrix product) (<*>) :: (Num a) => [a] -> [a] -> [[a]] u <*> v = [ [a*b | b <- v] | a <- u] -- matrix operations -- |a \<\<+\>\> b returns the sum a+b of matrices (<<+>>) :: (Num a) => [[a]] -> [[a]] -> [[a]] a <<+>> b = (zipWith . zipWith) (+) a b -- |a \<\<-\>\> b returns the difference a-b of matrices (<<->>) :: (Num a) => [[a]] -> [[a]] -> [[a]] a <<->> b = (zipWith . zipWith) (-) a b -- |a \<\<*\>\> b returns the product a*b of matrices (<<*>>) :: (Num a) => [[a]] -> [[a]] -> [[a]] a <<*>> b = [ [u <.> v | v <- L.transpose b] | u <- a] -- |k *\> m returns the product k*m of the scalar k and the matrix m (*>>) :: (Num a) => a -> [[a]] -> [[a]] k *>> m = (map . map) (k*) m -- |m \<\<*\> v is multiplication of a vector by a matrix on the left (<<*>) :: (Num a) => [[a]] -> [a] -> [a] m <<*> v = map (<.> v) m -- |v \<*\>\> m is multiplication of a vector by a matrix on the right (<*>>) :: (Num a) => [a] -> [[a]] -> [a] v <*>> m = map (v <.>) (L.transpose m) fMatrix n f = [[f i j | j <- [1..n]] | i <- [1..n]] -- version with indices from zero fMatrix' n f = [[f i j | j <- [0..n-1]] | i <- [0..n-1]] -- idMx n = fMatrix n (\i j -> if i == j then 1 else 0) idMx n = idMxs !! n where idMxs = map snd $ iterate next (0,[]) next (j,m) = (j+1, (1 : replicate j 0) : map (0:) m) -- |iMx n is the n*n identity matrix iMx :: (Num t) => Int -> [[t]] iMx n = idMx n -- |jMx n is the n*n matrix of all 1s jMx :: (Num t) => Int -> [[t]] jMx n = replicate n (replicate n 1) -- |zMx n is the n*n matrix of all 0s zMx :: (Num t) => Int -> [[t]] zMx n = replicate n (replicate n 0) {- -- VECTORS data Vector d k = V [k] deriving (Eq,Ord,Show) instance (IntegerAsType d, Num k) => Num (Vector d k) where V a + V b = V $ a <+> b V a - V b = V $ a <-> b negate (V a) = V $ map negate a fromInteger 0 = V $ replicate d' 0 where d' = fromInteger $ value (undefined :: d) V v <>> M m = V $ v <*>> m M m <<> V v = V $ m <<*> v k |> V v = V $ k *> v -} -- MATRICES {- -- Square matrices of dimension d over field k data Matrix d k = M [[k]] deriving (Eq,Ord,Show) instance (IntegerAsType d, Num k) => Num (Matrix d k) where M a + M b = M $ a <<+>> b M a - M b = M $ a <<->> b negate (M a) = M $ (map . map) negate a M a * M b = M $ a <<*>> b fromInteger 0 = M $ zMx d' where d' = fromInteger $ value (undefined :: d) fromInteger 1 = M $ idMx d' where d' = fromInteger $ value (undefined :: d) instance (IntegerAsType d, Fractional a) => Fractional (Matrix d a) where recip (M a) = case inverse a of Nothing -> error "Matrix.recip: matrix is singular" Just a' -> M a' -} -- |The inverse of a matrix (over a field), if it exists inverse :: (Fractional a) => [[a]] -> Maybe [[a]] inverse m = let d = length m -- the dimension i = idMx d m' = zipWith (++) m i i1 = inverse1 m' i2 = inverse2 i1 in if length i1 == d then Just i2 else Nothing -- given (M|I), use row operations to get to (U|A), where U is upper triangular with 1s on diagonal inverse1 [] = [] inverse1 ((x:xs):rs) = if x /= 0 then let r' = (1/x) *> xs in (1:r') : inverse1 [ys <-> y *> r' | (y:ys) <- rs] else case filter (\r' -> head r' /= 0) rs of [] -> [] -- early termination, which will be detected in calling function r:_ -> inverse1 (((x:xs) <+> r) : rs) -- This is basically row echelon form -- given (U|A), use row operations to get to M^-1 inverse2 [] = [] inverse2 ((1:r):rs) = inverse2' r rs : inverse2 rs where inverse2' xs [] = xs inverse2' (x:xs) ((1:r):rs) = inverse2' (xs <-> x *> r) rs -- This is basically reduced row echelon form xs ! i = xs !! (i-1) -- ie, a 1-based list lookup instead of 0-based rowEchelonForm [] = [] rowEchelonForm ((x:xs):rs) = if x /= 0 then let r' = (1/x) *> xs in (1:r') : map (0:) (rowEchelonForm [ys <-> y *> r' | (y:ys) <- rs]) else case filter (\r' -> head r' /= 0) rs of [] -> map (0:) (rowEchelonForm $ xs : map tail rs) r:_ -> rowEchelonForm (((x:xs) <+> r) : rs) rowEchelonForm zs@([]:_) = zs reducedRowEchelonForm :: (Fractional a) => [[a]] -> [[a]] reducedRowEchelonForm m = reverse $ reduce $ reverse $ rowEchelonForm m where reduce (r:rs) = let r':rs' = reduceStep (r:rs) in r' : reduce rs' -- is this scanl or similar? reduce [] = [] reduceStep ((1:xs):rs) = (1:xs) : [ 0: (ys <-> y *> xs) | y:ys <- rs] reduceStep rs@((0:_):_) = zipWith (:) (map head rs) (reduceStep $ map tail rs) reduceStep rs = rs -- kernel of a matrix -- returns basis for vectors v s.t m <<*> v == 0 kernel m = kernelRRE $ reducedRowEchelonForm m kernelRRE m = let nc = length $ head m -- the number of columns is = findLeadingCols 1 (L.transpose m) -- these are the indices of the columns which have a leading 1 js = [1..nc] L.\\ is freeCols = let m' = take (length is) m -- discard zero rows in zip is $ L.transpose [map (negate . (!j)) m' | j <- js] boundCols = zip js (idMx $ length js) in L.transpose $ map snd $ L.sort $ freeCols ++ boundCols where findLeadingCols i (c@(1:_):cs) = i : findLeadingCols (i+1) (map tail cs) findLeadingCols i (c@(0:_):cs) = findLeadingCols (i+1) cs findLeadingCols _ _ = [] m ^- n = recip m ^ n -- t (M m) = M (L.transpose m) -- |The determinant of a matrix (over a field) det :: (Fractional a) => [[a]] -> a det [[x]] = x det ((x:xs):rs) = if x /= 0 then let r' = (1/x) *> xs in x * det [ys <-> y *> r' | (y:ys) <- rs] else case filter (\r' -> head r' /= 0) rs of [] -> 0 r:_ -> det (((x:xs) <+> r) : rs) {- class IntegerAsType a where value :: a -> Integer data Z instance IntegerAsType Z where value _ = 0 data S a instance IntegerAsType a => IntegerAsType (S a) where value _ = value (undefined :: a) + 1 -}