----------------------------------------------------------------------------- -- | -- Module : DSP.Matrix.LU -- Copyright : (c) Matthew Donadio 2003 -- License : GPL -- -- Maintainer : m.p.donadio@ieee.org -- Stability : experimental -- Portability : portable -- -- Module implementing LU decomposition and related functions -- ----------------------------------------------------------------------------- module Matrix.Complex.LU (psolve, lu, lu_solve, improve, inverse, lu_det, solve, det) where import Data.Array import Complex import Matrix.Complex.Pivot -- | LU decomposition via Crout's Algorithm -- TODO: modify for partial pivoting / permutation matrix -- TODO: add singularity check -- I am sure these are in G&VL, but the two cases of function f below are -- formulas (2.3.13) and (2.3.12) from NRIC with some variable renaming lu :: Array (Int,Int) (Complex Double) -- ^ A -> Array (Int,Int) (Complex Double) -- ^ LU(A) lu a = a' where a' = array bnds [ ((i,j), luij i j) | (i,j) <- range bnds ] luij i j | i>j = (a!(i,j) - sum [ a'!(i,k) * a'!(k,j) | k <- [1 ..(j-1)] ]) / a'!(j,j) | i<=j = a!(i,j) - sum [ a'!(i,k) * a'!(k,j) | k <- [1 ..(i-1)] ] bnds = bounds a -- | Solution to Ax=b via LU decomposition -- forward is forumla (2.3.6) in NRIC, but remebering that a11=1 -- backward is forumla (2.3.7) in NRIC lu_solve :: Array (Int,Int) (Complex Double) -- ^ LU(A) -> Array Int (Complex Double) -- ^ b -> Array Int (Complex Double) -- ^ x lu_solve a b = x where x = array (1,n) ([(n,xn)] ++ [ (i, backward i) | i <- (reverse [1..(n-1)]) ]) y = array (1,n) ([(1,y1)] ++ [ (i, forward i) | i <- [2..n] ]) y1 = b!1 forward i = (b!i - sum [ a!(i,j) * y!j | j <- [1..(i-1)] ]) xn = y!n / a!(n,n) backward i = (y!i - sum [ a!(i,j) * x!j | j <- [(i+1)..n] ]) / a!(i,i) ((_,_),(n,_)) = bounds a -- | Improve a solution to Ax=b via LU decomposition -- formula (2.7.4) from NRIC improve :: Array (Int,Int) (Complex Double) -- ^ A -> Array (Int,Int) (Complex Double) -- ^ LU(A) -> Array Int (Complex Double) -- ^ b -> Array Int (Complex Double) -- ^ x -> Array Int (Complex Double) -- ^ x' improve a a_lu b x = array (1,n) [ (i, x!i - err!i) | i <- [1..n] ] where err = lu_solve a_lu rhs rhs = array (1,n) [ (i, sum [ a!(i,j) * x!j | j <- [1..n] ] - b!i) | i <- [1..n] ] ((_,_),(n,_)) = bounds a -- | Matrix inversion via LU decomposition -- Section (2.4) from NRIC -- TODO: build in improve inverse :: Array (Int,Int) (Complex Double) -- ^ A -> Array (Int,Int) (Complex Double) -- ^ A^-1 inverse a = a' where a' = array (bounds a) (arrange (makecols (lu a)) 1) makecol i n = array (1,n) [ (j, (\i j->if i == j then 1.0 else 0.0) i j) | j <- [1..n] ] makecols a = [ lu_solve a (makecol i n) | i <- [1..n] ] ((_,_),(n,_)) = bounds a arrange [] _ = [] arrange (m:ms) j = (flatten m j) ++ (arrange ms (j+1)) flatten m j = map (\(i,x) -> ((i,j),x)) (assocs m) -- | Determinant of a matrix via LU decomposition -- Formula (2.5.1) from NRIC lu_det :: Array (Int,Int) (Complex Double) -- ^ LU(A) -> (Complex Double) -- ^ det(A) lu_det a = product [ a!(i,i) | i <- [ 1 .. n] ] where ((_,_),(n,_)) = bounds a -- | LU solver using original matrix solve :: Array (Int,Int) (Complex Double) -- ^ A -> Array Int (Complex Double) -- ^ b -> Array Int (Complex Double) -- ^ x solve a b = (lu_solve . lu) a b psolve :: Array (Int,Int) (Complex Double) -- ^ A -> Array Int (Complex Double) -- ^ b -> Array Int (Complex Double) -- ^ x psolve a b = (lu_solve . lu) (mswap pv a) (vswap pv b) where pv = permute a -- | determinant using original matrix det :: Array (Int,Int) (Complex Double) -- ^ A -> (Complex Double) -- ^ det(A) det a = (lu_det . lu) a ------------------------------------------------------------------------------- -- tests ------------------------------------------------------------------------------- {- a = array ((1,1),(3,3)) [ ((1,1), 1.0), ((1,2), 2.0), ((1,3), 3.0), ((2,1), 2.0), ((2,2), 5.0), ((2,3), 3.0), ((3,1), 1.0), ((3,2), 0.0), ((3,3), 8.0) ] a' = array ((1,1),(3,3)) [ ((1,1), -40.0), ((1,2), 16.0), ((1,3), 9.0), ((2,1), 13.0), ((2,2), -5.0), ((2,3), -3.0), ((3,1), 5.0), ((3,2), -2.0), ((3,3), -1.0) ] a_lu = lu a b = array (1,3) [ (1, 1.0), (2, 2.0), (3, 5.0) ] x = lu_solve a_lu b x' = improve a a_lu b x x'' = improve a a_lu b x' verify = a' == inverse a && -- tests lu, lu_solve, and inverse det a == -1 && -- tests lu_det x == x' && -- tests improve x' == x'' -}