import Linear.Vector
import Normed
-import NumericPrelude hiding ((*), abs)
-import qualified NumericPrelude as NP ((*))
+import NumericPrelude hiding ( (*), abs )
+import qualified NumericPrelude as NP ( (*) )
+import qualified Algebra.Absolute as Absolute ( C )
+import Algebra.Absolute ( abs )
+import qualified Algebra.Additive as Additive
import qualified Algebra.Algebraic as Algebraic
import Algebra.Algebraic (root)
-import qualified Algebra.Additive as Additive
import qualified Algebra.Ring as Ring
import qualified Algebra.Module as Module
import qualified Algebra.RealRing as RealRing
-- | Returns True if the given matrix is upper-triangular, and False
--- otherwise.
+-- otherwise. The parameter @epsilon@ lets the caller choose a
+-- tolerance.
--
-- Examples:
--
--- >>> let m = fromList [[1,0],[1,1]] :: Mat2 Int
+-- >>> let m = fromList [[1,1],[1e-12,1]] :: Mat2 Double
-- >>> is_upper_triangular m
-- False
---
--- >>> let m = fromList [[1,2],[0,3]] :: Mat2 Int
--- >>> is_upper_triangular m
+-- >>> is_upper_triangular' 1e-10 m
-- True
--
-is_upper_triangular :: (Eq a, Ring.C a, Arity m, Arity n)
- => Mat m n a -> Bool
-is_upper_triangular m =
+-- TODO:
+--
+-- 1. Don't cheat with lists.
+--
+is_upper_triangular' :: (Ord a, Ring.C a, Absolute.C a, Arity m, Arity n)
+ => a -- ^ The tolerance @epsilon@.
+ -> Mat m n a
+ -> Bool
+is_upper_triangular' epsilon m =
and $ concat results
where
results = [[ test i j | i <- [0..(nrows m)-1]] | j <- [0..(ncols m)-1] ]
test :: Int -> Int -> Bool
test i j
| i <= j = True
- | otherwise = m !!! (i,j) == 0
+ -- use "less than or equal to" so zero is a valid epsilon
+ | otherwise = abs (m !!! (i,j)) <= epsilon
+
+
+-- | Returns True if the given matrix is upper-triangular, and False
+-- otherwise. A specialized version of 'is_upper_triangular\'' with
+-- @epsilon = 0@.
+--
+-- Examples:
+--
+-- >>> let m = fromList [[1,0],[1,1]] :: Mat2 Int
+-- >>> is_upper_triangular m
+-- False
+--
+-- >>> let m = fromList [[1,2],[0,3]] :: Mat2 Int
+-- >>> is_upper_triangular m
+-- True
+--
+-- TODO:
+--
+-- 1. The Ord constraint is too strong here, Eq would suffice.
+--
+is_upper_triangular :: (Ord a, Ring.C a, Absolute.C a, Arity m, Arity n)
+ => Mat m n a -> Bool
+is_upper_triangular = is_upper_triangular' 0
-- | Returns True if the given matrix is lower-triangular, and False
--- otherwise.
+-- otherwise. This is a specialized version of 'is_lower_triangular\''
+-- with @epsilon = 0@.
--
-- Examples:
--
-- >>> is_lower_triangular m
-- False
--
-is_lower_triangular :: (Eq a,
+is_lower_triangular :: (Ord a,
Ring.C a,
+ Absolute.C a,
Arity m,
Arity n)
=> Mat m n a
is_lower_triangular = is_upper_triangular . transpose
+-- | Returns True if the given matrix is lower-triangular, and False
+-- otherwise. The parameter @epsilon@ lets the caller choose a
+-- tolerance.
+--
+-- Examples:
+--
+-- >>> let m = fromList [[1,1e-12],[1,1]] :: Mat2 Double
+-- >>> is_lower_triangular m
+-- False
+-- >>> is_lower_triangular' 1e-12 m
+-- True
+--
+is_lower_triangular' :: (Ord a,
+ Ring.C a,
+ Absolute.C a,
+ Arity m,
+ Arity n)
+ => a -- ^ The tolerance @epsilon@.
+ -> Mat m n a
+ -> Bool
+is_lower_triangular' epsilon = (is_upper_triangular' epsilon) . transpose
+
+
-- | Returns True if the given matrix is triangular, and False
-- otherwise.
--
-- >>> is_triangular m
-- False
--
-is_triangular :: (Eq a,
+is_triangular :: (Ord a,
Ring.C a,
+ Absolute.C a,
Arity m,
Arity n)
=> Mat m n a
instance (Eq a, Ring.C a) => Determined (Mat (S Z) (S Z)) a where
determinant (Mat rows) = (V.head . V.head) rows
-instance (Eq a,
+instance (Ord a,
Ring.C a,
+ Absolute.C a,
Arity n,
Determined (Mat (S n) (S n)) a)
=> Determined (Mat (S (S n)) (S (S n))) a where
import qualified Algebra.Algebraic as Algebraic ( C )
import Data.Vector.Fixed ( ifoldl )
import Data.Vector.Fixed.Cont ( Arity )
+import Debug.Trace
import NumericPrelude hiding ( (*) )
import Linear.Matrix (
--
-- Examples (Watkins, p. 193):
--
--- >>> import Linear.Matrix ( Mat2, fromList )
+-- >>> import Normed ( Normed(..) )
+-- >>> import Linear.Vector ( Vec2, Vec3 )
+-- >>> import Linear.Matrix ( Mat2, Mat3, fromList, frobenius_norm )
+-- >>> import qualified Data.Vector.Fixed as V ( map )
+--
-- >>> let m = givens_rotator 0 1 1 1 :: Mat2 Double
-- >>> let m2 = fromList [[1, -1],[1, 1]] :: Mat2 Double
-- >>> m == (1 / (sqrt 2) :: Double) *> m2
-- True
--
-givens_rotator :: forall m a. (Ring.C a, Algebraic.C a, Arity m)
+-- >>> let m = fromList [[2,3],[5,7]] :: Mat2 Double
+-- >>> let rot = givens_rotator 0 1 2.0 5.0 :: Mat2 Double
+-- >>> ((transpose rot) * m) !!! (1,0) < 1e-12
+-- True
+-- >>> let (Mat rows) = rot
+-- >>> let (Mat cols) = transpose rot
+-- >>> V.map norm rows :: Vec2 Double
+-- fromList [1.0,1.0]
+-- >>> V.map norm cols :: Vec2 Double
+-- fromList [1.0,1.0]
+--
+-- >>> let m = fromList [[12,-51,4],[6,167,-68],[-4,24,-41]] :: Mat3 Double
+-- >>> let rot = givens_rotator 1 2 6 (-4) :: Mat3 Double
+-- >>> let ex_rot_r1 = [1,0,0] :: [Double]
+-- >>> let ex_rot_r2 = [0,0.83205,-0.55470] :: [Double]
+-- >>> let ex_rot_r3 = [0, 0.55470, 0.83205] :: [Double]
+-- >>> let ex_rot = fromList [ex_rot_r1, ex_rot_r2, ex_rot_r3] :: Mat3 Double
+-- >>> frobenius_norm ((transpose rot) - ex_rot) < 1e-4
+-- True
+-- >>> ((transpose rot) * m) !!! (2,0) == 0
+-- True
+-- >>> let (Mat rows) = rot
+-- >>> let (Mat cols) = transpose rot
+-- >>> V.map norm rows :: Vec3 Double
+-- fromList [1.0,1.0,1.0]
+-- >>> V.map norm cols :: Vec3 Double
+-- fromList [1.0,1.0,1.0]
+--
+givens_rotator :: forall m a. (Eq a, Ring.C a, Algebraic.C a, Arity m)
=> Int -> Int -> a -> a -> Mat m m a
givens_rotator i j xi xj =
construct f
where
xnorm = sqrt $ xi^2 + xj^2
- c = xi / xnorm
- s = xj / xnorm
+ c = if xnorm == (fromInteger 0) then (fromInteger 1) else xi / xnorm
+ s = if xnorm == (fromInteger 0) then (fromInteger 0) else xj / xnorm
f :: Int -> Int -> a
f y z
-- factorization. We keep the pair updated by multiplying @q@ and
-- @r@ by the new rotator (or its transpose).
--
-qr :: forall m n a. (Arity m, Arity n, Algebraic.C a, Ring.C a)
+-- Examples:
+--
+-- >>> import Linear.Matrix
+--
+-- >>> let m = fromList [[1,2],[1,3]] :: Mat2 Double
+-- >>> let (q,r) = qr m
+-- >>> let c = (1 / (sqrt 2 :: Double))
+-- >>> let ex_q = c *> (fromList [[1,-1],[1,1]] :: Mat2 Double)
+-- >>> let ex_r = c *> (fromList [[2,5],[0,1]] :: Mat2 Double)
+-- >>> frobenius_norm (q - ex_q) == 0
+-- True
+-- >>> frobenius_norm (r - ex_r) == 0
+-- True
+-- >>> let m' = q*r
+-- >>> frobenius_norm (m - m') < 1e-10
+-- True
+-- >>> is_upper_triangular' 1e-10 r
+-- True
+--
+-- >>> let m = fromList [[2,3],[5,7]] :: Mat2 Double
+-- >>> let (q,r) = qr m
+-- >>> frobenius_norm (m - (q*r)) < 1e-12
+-- True
+-- >>> is_upper_triangular' 1e-10 r
+-- True
+--
+-- >>> let m = fromList [[12,-51,4],[6,167,-68],[-4,24,-41]] :: Mat3 Double
+-- >>> let (q,r) = qr m
+-- >>> frobenius_norm (m - (q*r)) < 1e-12
+-- True
+-- >>> is_upper_triangular' 1e-10 r
+-- True
+--
+qr :: forall m n a. (Arity m, Arity n, Eq a, Algebraic.C a, Ring.C a, Show a)
=> Mat m n a -> (Mat m m a, Mat m n a)
qr matrix =
ifoldl col_function initial_qr columns
-- | Process the entries in a column, doing basically the same
-- thing as col_dunction does. It updates the QR factorization,
-- maybe, and returns the current one.
- f col_idx (q,r) idx x
- | idx <= col_idx = (q,r) -- leave it alone.
- | otherwise =
- (q*rotator, (transpose rotator)*r)
+ f col_idx (q,r) idx _ -- ignore the current element
+ | idx <= col_idx = (q,r)
+-- trace ("---------------\nidx: " ++ (show idx) ++ ";\ncol_idx: " ++ (show col_idx) ++ "; leaving it alone") (q,r) -- leave it alone.
+ | otherwise = (q*rotator, (transpose rotator)*r)
+-- trace ("---------------\nidx: " ++ (show idx) ++ ";\ncol_idx: " ++ (show col_idx) ++ ";\nupdating Q and R;\nq: " ++ (show q) ++ ";\nr " ++ (show r) ++ ";\nnew q: " ++ (show $ q*rotator) ++ ";\nnew r: " ++ (show $ (transpose rotator)*r) ++ ";\ny: " ++ (show y) ++ ";\nr[i,j]: " ++ (show (r !!! (col_idx, col_idx))))
+-- (q*rotator, (transpose rotator)*r)
where
+ y = r !!! (idx, col_idx)
rotator :: Mat m m a
- rotator = givens_rotator col_idx idx (r !!! (idx, col_idx)) x
+ rotator = givens_rotator col_idx idx (r !!! (col_idx, col_idx)) y