Safe Haskell | None |
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- type Square sh = ArrayMatrix (Square sh)
- size :: Square sh a -> sh
- mapSize :: (sh0 -> sh1) -> Square sh0 a -> Square sh1 a
- toFull :: (C vert, C horiz) => Square sh a -> Full vert horiz sh sh a
- toGeneral :: Square sh a -> General sh sh a
- fromGeneral :: Eq sh => General sh sh a -> Square sh a
- fromScalar :: Storable a => a -> Square () a
- toScalar :: Storable a => Square () a -> a
- fromList :: (C sh, Storable a) => sh -> [a] -> Square sh a
- autoFromList :: Storable a => [a] -> Square ShapeInt a
- transpose :: Square sh a -> Square sh a
- adjoint :: (C sh, Floating a) => Square sh a -> Square sh a
- identity :: (C sh, Floating a) => sh -> Square sh a
- identityFrom :: (C sh, Floating a) => Square sh a -> Square sh a
- identityFromWidth :: (C height, C width, Floating a) => General height width a -> Square width a
- identityFromHeight :: (C height, C width, Floating a) => General height width a -> Square height a
- diagonal :: (C sh, Floating a) => Vector sh a -> Square sh a
- takeDiagonal :: (C sh, Floating a) => Square sh a -> Vector sh a
- trace :: (C sh, Floating a) => Square sh a -> a
- stack :: (C vert, C horiz, C sizeA, Eq sizeA, C sizeB, Eq sizeB, Floating a) => Square sizeA a -> Full vert horiz sizeA sizeB a -> Full horiz vert sizeB sizeA a -> Square sizeB a -> Square (sizeA :+: sizeB) a
- (|=|) :: (C vert, C horiz, C sizeA, Eq sizeA, C sizeB, Eq sizeB, Floating a) => (Square sizeA a, Full vert horiz sizeA sizeB a) -> (Full horiz vert sizeB sizeA a, Square sizeB a) -> Square (sizeA :+: sizeB) a
- multiply :: (C sh, Eq sh, Floating a) => Square sh a -> Square sh a -> Square sh a
- square :: (C sh, Floating a) => Square sh a -> Square sh a
- power :: (C sh, Floating a) => Integer -> Square sh a -> Square sh a
- congruence :: (C height, Eq height, C width, Floating a) => Square height a -> General height width a -> Square width a
- congruenceAdjoint :: (C height, C width, Eq width, Floating a) => General height width a -> Square width a -> Square height a
- solve :: (C vert, C horiz, C sh, Eq sh, C nrhs, Floating a) => Square sh a -> Full vert horiz sh nrhs a -> Full vert horiz sh nrhs a
- inverse :: (C sh, Floating a) => Square sh a -> Square sh a
- determinant :: (C sh, Floating a) => Square sh a -> a
- eigenvalues :: (C sh, Floating a) => Square sh a -> Vector sh (ComplexOf a)
- schur :: (C sh, Floating a) => Square sh a -> (Square sh a, Square sh a)
- schurComplex :: (C sh, Real a, Complex a ~ ac) => Square sh ac -> (Square sh ac, Upper sh ac)
- eigensystem :: (C sh, Floating a, ComplexOf a ~ ac) => Square sh a -> (Square sh ac, Vector sh ac, Square sh ac)
- type ComplexOf x = Complex (RealOf x)

# Documentation

type Square sh = ArrayMatrix (Square sh)Source

fromGeneral :: Eq sh => General sh sh a -> Square sh aSource

fromScalar :: Storable a => a -> Square () aSource

autoFromList :: Storable a => [a] -> Square ShapeInt aSource

identityFromWidth :: (C height, C width, Floating a) => General height width a -> Square width aSource

identityFromHeight :: (C height, C width, Floating a) => General height width a -> Square height aSource

stack :: (C vert, C horiz, C sizeA, Eq sizeA, C sizeB, Eq sizeB, Floating a) => Square sizeA a -> Full vert horiz sizeA sizeB a -> Full horiz vert sizeB sizeA a -> Square sizeB a -> Square (sizeA :+: sizeB) aSource

(|=|) :: (C vert, C horiz, C sizeA, Eq sizeA, C sizeB, Eq sizeB, Floating a) => (Square sizeA a, Full vert horiz sizeA sizeB a) -> (Full horiz vert sizeB sizeA a, Square sizeB a) -> Square (sizeA :+: sizeB) aSource

congruence :: (C height, Eq height, C width, Floating a) => Square height a -> General height width a -> Square width aSource

congruence B A = A^H * B * A

The meaning and order of matrix factors of these functions is consistent:

congruenceAdjoint :: (C height, C width, Eq width, Floating a) => General height width a -> Square width a -> Square height aSource

congruenceAdjoint A B = A * B * A^H

solve :: (C vert, C horiz, C sh, Eq sh, C nrhs, Floating a) => Square sh a -> Full vert horiz sh nrhs a -> Full vert horiz sh nrhs aSource

determinant :: (C sh, Floating a) => Square sh a -> aSource

schur :: (C sh, Floating a) => Square sh a -> (Square sh a, Square sh a)Source

If `(q,r) = schur a`

, then `a = q <> r <> adjoint q`

,
where `q`

is unitary (orthogonal)
and `r`

is a right-upper triangular matrix for complex `a`

and a 1x1-or-2x2-block upper triangular matrix for real `a`

.
With `takeDiagonal r`

you get all eigenvalues of `a`

if `a`

is complex
and the real parts of the eigenvalues if `a`

is real.
Complex conjugated eigenvalues of a real matrix `a`

are encoded as 2x2 blocks along the diagonal.

The meaning and order of matrix factors of these functions is consistent:

eigensystem :: (C sh, Floating a, ComplexOf a ~ ac) => Square sh a -> (Square sh ac, Vector sh ac, Square sh ac)Source

(vr,d,vlAdj) = eigensystem a

Counterintuitively, `vr`

contains the right eigenvectors as columns
and `vlAdj`

contains the left conjugated eigenvectors as rows.
The idea is to provide a decomposition of `a`

.
If `a`

is diagonalizable, then `vr`

and `vlAdj`

are almost inverse to each other.
More precisely, `vlAdj <> vr`

is a diagonal matrix,
but not necessarily an identity matrix.
This is because all eigenvectors are normalized to Euclidean norm 1.
With the following scaling, the decomposition becomes perfect:

let scal = takeDiagonal $ vlAdj <> vr a == vr #*\ Vector.divide d scal ##*# vlAdj

If `a`

is non-diagonalizable
then some columns of `vr`

and corresponding rows of `vlAdj`

are left zero
and the above property does not hold.

The meaning and order of result matrices of these functions is consistent: