-- Hoogle documentation, generated by Haddock
-- See Hoogle, http://www.haskell.org/hoogle/


-- | Numerical computation in native Haskell
--   
--   Currently it provides iterative linear solvers, matrix decompositions,
--   eigenvalue computations and related utilities. Please see README.md
--   for details
@package sparse-linear-algebra
@version 0.2.0.2

module Numeric.LinearAlgebra.Sparse.IntMap

-- | <h6>=== IntMap-of-IntMap (IM2) stuff</h6>
insertIM2 :: Key -> Key -> a -> IntMap (IntMap a) -> IntMap (IntMap a)
lookupIM2 :: Key -> Key -> IntMap (IntMap a) -> Maybe a
fromListIM2 :: Foldable t => t (Key, Key, a) -> IntMap (IntMap a) -> IntMap (IntMap a)

-- | folding
ifoldlIM2' :: (Key -> Key -> a -> b -> b) -> b -> IntMap (IntMap a) -> b
ifoldlIM2 :: (Key -> Key -> t -> IntMap a -> IntMap a) -> IntMap (IntMap t) -> IntMap a
foldlIM2 :: (a -> b -> b) -> b -> IntMap (IntMap a) -> b
transposeIM2 :: IntMap (IntMap a) -> IntMap (IntMap a)

-- | filtering
ifilterIM2 :: (Key -> Key -> a -> Bool) -> IntMap (IntMap a) -> IntMap (IntMap a)
filterSubdiag :: IntMap (IntMap a) -> IntMap (IntMap a)
countSubdiagonalNZ :: IntMap (IntMap a) -> Int
subdiagIndices :: IntMap (IntMap a) -> [(Key, Key)]
rpairs :: (a, [b]) -> [(a, b)]

-- | mapping
mapIM2 :: (a -> b) -> IntMap (IntMap a) -> IntMap (IntMap b)
imapIM2 :: (Key -> Key -> a -> b) -> IntMap (IntMap a) -> IntMap (IntMap b)
mapKeysIM2 :: (Key -> Key) -> (Key -> Key) -> IntMap (IntMap a) -> IntMap (IntMap a)
mapColumnIM2 :: (b -> b) -> IntMap (IntMap b) -> Int -> IntMap (IntMap b)

module Numeric.LinearAlgebra.Sparse
class Functor f => Additive f

-- | Ring zero element
zero :: (Additive f, Num a) => f a

-- | Ring +
(^+^) :: (Additive f, Num a) => f a -> f a -> f a

-- | negate the values in a functor
negated :: (Num a, Functor f) => f a -> f a

-- | subtract two Additive objects
(^-^) :: (Additive f, Num a) => f a -> f a -> f a
class Additive f => VectorSpace f

-- | multiplication by a scalar
(.*) :: (VectorSpace f, Num a) => a -> f a -> f a

-- | linear interpolation
lerp :: (VectorSpace f, Num a) => a -> f a -> f a -> f a
class VectorSpace f => Hilbert f

-- | inner product
dot :: (Hilbert f, Num a) => f a -> f a -> a
class Hilbert f => Normed f
norm :: (Normed f, Floating a, Eq a) => a -> f a -> a

-- | Squared 2-norm
normSq :: (Hilbert f, Num a) => f a -> a

-- | L1 norm
norm1 :: (Foldable t, Num a, Functor t) => t a -> a

-- | Euclidean norm
norm2 :: (Hilbert f, Floating a) => f a -> a

-- | Lp norm (p &gt; 0)
normP :: (Foldable t, Functor t, Floating a) => a -> t a -> a

-- | Infinity-norm
normInfty :: (Foldable t, Ord a) => t a -> a

-- | Normalize w.r.t. p-norm (p finite)
normalize :: (Normed f, Floating a, Eq a) => a -> f a -> f a

-- | Lp inner product (p &gt; 0)
dotLp :: (Set t, Foldable t, Floating a) => a -> t a -> t a -> a

-- | Reciprocal
reciprocal :: (Functor f, Fractional b) => f b -> f b

-- | Scale
scale :: (Num b, Functor f) => b -> f b -> f b
class Additive f => FiniteDim f where type FDSize f :: * where {
    type family FDSize f :: *;
}
dim :: FiniteDim f => f a -> FDSize f

-- | unary dimension-checking bracket
withDim :: (FiniteDim f, Show e) => f a -> (FDSize f -> f a -> Bool) -> (f a -> c) -> String -> (f a -> e) -> c

-- | binary dimension-checking bracket
withDim2 :: (FiniteDim f, FiniteDim g, Show e) => f a -> g b -> (FDSize f -> FDSize g -> f a -> g b -> Bool) -> (f a -> g b -> c) -> String -> (f a -> g b -> e) -> c
class Additive f => HasData f a where type HDData f a :: * where {
    type family HDData f a :: *;
}
dat :: HasData f a => f a -> HDData f a
class (FiniteDim f, HasData f a) => Sparse f a
spy :: (Sparse f a, Fractional b) => f a -> b
class Functor f => Set f

-- | union binary lift : apply function on _union_ of two Sets
liftU2 :: Set f => (a -> a -> a) -> f a -> f a -> f a

-- | intersection binary lift : apply function on _intersection_ of two
--   Sets
liftI2 :: Set f => (a -> b -> c) -> f a -> f b -> f c
data SpVector a
SV :: Int -> IntMap a -> SpVector a
[svDim] :: SpVector a -> Int
[svData] :: SpVector a -> IntMap a

-- | SpVector sparsity
spySV :: Fractional b => SpVector a -> b

-- | empty sparse vector (length n, no entries)
zeroSV :: Int -> SpVector a

-- | singleton sparse vector (length 1)
singletonSV :: a -> SpVector a

-- | create a sparse vector from an association list while discarding all
--   zero entries
mkSpVector :: (Num a, Eq a) => Int -> IntMap a -> SpVector a

-- | ", from logically dense array (consecutive indices)
mkSpVectorD :: (Num a, Eq a) => Int -> [a] -> SpVector a
mkSpVector1 :: Int -> IntMap a -> SpVector a

-- | Create new sparse vector, assumin 0-based, contiguous indexing
fromListDenseSV :: Int -> [a] -> SpVector a

-- | DENSE vector of `1`s
onesSV :: Num a => Int -> SpVector a

-- | DENSE vector of `0`s
zerosSV :: Num a => Int -> SpVector a

-- | insert element <tt>x</tt> at index <tt>i</tt> in a preexisting
--   SpVector
insertSpVector :: Int -> a -> SpVector a -> SpVector a
fromListSV :: Int -> [(Int, a)] -> SpVector a
toListSV :: SpVector a -> [(Key, a)]

-- | To dense list (default = 0)
toDenseListSV :: Num b => SpVector b -> [b]

-- | lookup an index in a SpVector (returns 0 if lookup fails)
lookupDenseSV :: Num a => Key -> SpVector a -> a

-- | Tail elements
tailSV :: SpVector a -> SpVector a

-- | Head element
headSV :: Num a => SpVector a -> a

-- | concatenate two sparse vectors
concatSV :: SpVector a -> SpVector a -> SpVector a

-- | promote a SV to SM
svToSM :: SpVector a -> SpMatrix a
outerProdSV :: Num a => SpVector a -> SpVector a -> SpMatrix a
(><) :: Num a => SpVector a -> SpVector a -> SpMatrix a
data SpMatrix a
SM :: (Rows, Cols) -> IntMap (IntMap a) -> SpMatrix a
[smDim] :: SpMatrix a -> (Rows, Cols)
[smData] :: SpMatrix a -> IntMap (IntMap a)

-- | Componentwise tuple operations TODO : use semilattice properties
--   instead
maxTup :: Ord t => (t, t) -> (t, t) -> (t, t)

-- | Componentwise tuple operations TODO : use semilattice properties
--   instead
minTup :: Ord t => (t, t) -> (t, t) -> (t, t)

-- | Empty matrix of size d
emptySpMatrix :: (Int, Int) -> SpMatrix a

-- | Zero SpMatrix of size (m, n)
zeroSM :: Int -> Int -> SpMatrix a
mkDiagonal :: Int -> [a] -> SpMatrix a
eye :: Num a => Int -> SpMatrix a
mkSubDiagonal :: Int -> Int -> [a] -> SpMatrix a

-- | Add to existing SpMatrix using data from list (row, col, value)
fromListSM' :: Foldable t => t (IxRow, IxCol, a) -> SpMatrix a -> SpMatrix a

-- | Create new SpMatrix using data from list (row, col, value)
fromListSM :: Foldable t => (Int, Int) -> t (IxRow, IxCol, a) -> SpMatrix a

-- | Create new SpMatrix assuming contiguous, 0-based indexing of elements
fromListDenseSM :: Int -> [a] -> SpMatrix a

-- | Populate list with SpMatrix contents and populate missing entries with
--   0
toDenseListSM :: Num t => SpMatrix t -> [(IxRow, IxCol, t)]

-- | Insert an element in a preexisting Spmatrix at the specified indices
insertSpMatrix :: IxRow -> IxCol -> a -> SpMatrix a -> SpMatrix a
lookupSM :: SpMatrix a -> IxRow -> IxCol -> Maybe a

-- | Looks up an element in the matrix with a default (if the element is
--   not found, zero is returned)
lookupWD_SM :: Num a => SpMatrix a -> (IxRow, IxCol) -> a

-- | Zero-default lookup, infix form
--   
--   Looks up an element in the matrix with a default (if the element is
--   not found, zero is returned)
(@@) :: Num a => SpMatrix a -> (IxRow, IxCol) -> a
lookupWD_IM :: Num a => IntMap (IntMap a) -> (IxRow, IxCol) -> a
matScale :: Num a => a -> SpMatrix a -> SpMatrix a
normFrobenius :: SpMatrix Double -> Double
type Rows = Int
type Cols = Int
type IxRow = Int
type IxCol = Int

-- | Are the supplied indices within matrix bounds?
validIxSM :: SpMatrix a -> (Int, Int) -> Bool

-- | Is the matrix square?
isSquareSM :: SpMatrix a -> Bool

-- | Is the matrix diagonal?
isDiagonalSM :: SpMatrix a -> Bool

-- | is the matrix orthogonal? i.e. Q^t ## Q == I
isOrthogonalSM :: SpMatrix Double -> Bool

-- | Data in internal representation (do not export)
immSM :: SpMatrix t -> IntMap (IntMap t)

-- | (Number of rows, Number of columns)
dimSM :: SpMatrix t -> (Rows, Cols)

-- | Number of rows times number of columns
nelSM :: SpMatrix t -> Int

-- | Number of rows
nrows :: SpMatrix a -> Rows

-- | Number of columns
ncols :: SpMatrix a -> Cols
data SMInfo
SMInfo :: Int -> Double -> SMInfo
[smNz] :: SMInfo -> Int
[smSpy] :: SMInfo -> Double
infoSM :: SpMatrix a -> SMInfo
nzSM :: SpMatrix a -> Int
spySM :: Fractional b => SpMatrix a -> b
nzRow :: SpMatrix a -> Key -> Int
bwMinSM :: SpMatrix a -> Int
bwMaxSM :: SpMatrix a -> Int
bwBoundsSM :: SpMatrix a -> (Int, Int)

-- | Extract a submatrix given the specified index bounds
extractSubmatrixSM :: SpMatrix a -> (IxRow, IxCol) -> (IxRow, IxCol) -> SpMatrix a

-- | Demote (n x 1) or (1 x n) SpMatrix to SpVector
toSV :: SpMatrix a -> SpVector a
extractColSM :: SpMatrix a -> IxCol -> SpMatrix a

-- | ", and place into SpVector
extractCol :: SpMatrix a -> IxCol -> SpVector a
extractRowSM :: SpMatrix a -> IxRow -> SpMatrix a

-- | ", and place into SpVector
extractRow :: SpMatrix a -> IxRow -> SpVector a

-- | Vertical stacking
vertStackSM :: SpMatrix a -> SpMatrix a -> SpMatrix a

-- | Vertical stacking
(-=-) :: SpMatrix a -> SpMatrix a -> SpMatrix a

-- | Horizontal stacking
horizStackSM :: SpMatrix a -> SpMatrix a -> SpMatrix a

-- | Horizontal stacking
(-||-) :: SpMatrix a -> SpMatrix a -> SpMatrix a

-- | Left fold over SpMatrix
foldlSM :: (a -> b -> b) -> b -> SpMatrix a -> b

-- | Indexed left fold over SpMatrix
ifoldlSM :: (Key -> Key -> a -> b -> b) -> b -> SpMatrix a -> b

-- | Count sub-diagonal nonzeros
countSubdiagonalNZSM :: SpMatrix a -> Int

-- | Extract the diagonal as a SpVector (with default 0)
extractDiagonalDSM :: Num a => SpMatrix a -> SpVector a

-- | Filter the index subset that lies below the diagonal (used in the QR
--   decomposition, for example)
subdiagIndicesSM :: SpMatrix a -> [(Key, Key)]
sparsifyIM2 :: IntMap (IntMap Double) -> IntMap (IntMap Double)
sparsifySM :: SpMatrix Double -> SpMatrix Double

-- | Round almost-0 and almost-1 to 0 and 1 respectively
roundZeroOneSM :: SpMatrix Double -> SpMatrix Double

-- | transposeSM, (#^) : Matrix transpose
transposeSM :: SpMatrix a -> SpMatrix a

-- | transposeSM, (#^) : Matrix transpose
(#^) :: SpMatrix a -> SpMatrix a

-- | Matrix-on-vector
matVec :: Num a => SpMatrix a -> SpVector a -> SpVector a

-- | Matrix-on-vector
(#>) :: Num a => SpMatrix a -> SpVector a -> SpVector a

-- | Vector-on-matrix (FIXME : transposes matrix: more costly than
--   <a>matVec</a>, I think)
vecMat :: Num a => SpVector a -> SpMatrix a -> SpVector a

-- | Vector-on-matrix (FIXME : transposes matrix: more costly than
--   <a>matVec</a>, I think)
(<#) :: Num a => SpVector a -> SpMatrix a -> SpVector a
matMat :: Num a => SpMatrix a -> SpMatrix a -> SpMatrix a
(##) :: Num a => SpMatrix a -> SpMatrix a -> SpMatrix a

-- | Removes all elements <tt>x</tt> for which `| x | &lt;= eps`)
matMatSparsified :: SpMatrix Double -> SpMatrix Double -> SpMatrix Double

-- | Removes all elements <tt>x</tt> for which `| x | &lt;= eps`)
(#~#) :: SpMatrix Double -> SpMatrix Double -> SpMatrix Double

-- | A^T B
(#^#) :: SpMatrix Double -> SpMatrix Double -> SpMatrix Double

-- | A B^T
(##^) :: SpMatrix Double -> SpMatrix Double -> SpMatrix Double

-- | uses the R matrix from the QR factorization
conditionNumberSM :: SpMatrix Double -> Double
hhMat :: Num a => a -> SpVector a -> SpMatrix a

-- | a vector <tt>x</tt> uniquely defines an orthogonal plane; the
--   Householder operator reflects any point <tt>v</tt> with respect to
--   this plane: v' = (I - 2 x &gt;&lt; x) v
hhRefl :: SpVector Double -> SpMatrix Double
hypot :: Floating a => a -> a -> a
sign :: (Ord a, Num a) => a -> a

-- | Givens coefficients (using stable algorithm shown in Anderson, Edward
--   (4 December 2000). "Discontinuous Plane Rotations and the Symmetric
--   Eigenvalue Problem". LAPACK Working Note)
givensCoef :: (Ord a, Floating a) => a -> a -> (a, a, a)

-- | Givens method, row version: choose other row index i' s.t. i' is : *
--   below the diagonal * corresponding element is nonzero
--   
--   QR.C1 ) To zero out entry A(i, j) we must find row k such that A(k, j)
--   is non-zero but A has zeros in row k for all columns less than j.
givens :: SpMatrix Double -> IxRow -> IxCol -> SpMatrix Double

-- | Is the <tt>k</tt>th the first nonzero column in the row?
firstNonZeroColumn :: IntMap a -> IxRow -> Bool

-- | Returns a set of rows {k} that satisfy QR.C1
candidateRows :: IntMap (IntMap a) -> IxRow -> IxCol -> Maybe [Key]

-- | Applies Givens rotation iteratively to zero out sub-diagonal elements
qr :: SpMatrix Double -> (SpMatrix Double, SpMatrix Double)

-- | Givens matrices in order [G1, G2, .. , G_N ]
gmats :: SpMatrix Double -> [SpMatrix Double]
eigsQR :: Int -> SpMatrix Double -> SpVector Double

-- | Cubic-order convergence, but it requires a mildly educated guess on
--   the initial eigenpair
rayleighStep :: SpMatrix Double -> (SpVector Double, Double) -> (SpVector Double, Double)
eigRayleigh :: Int -> SpMatrix Double -> (SpVector Double, Double) -> (SpVector Double, Double)
hhV :: SpVector Double -> (SpVector Double, Double)

-- | numerical tolerance for e.g. solution convergence
eps :: Double

-- | residual of candidate solution x0
residual :: Num a => SpMatrix a -> SpVector a -> SpVector a -> SpVector a
converged :: SpMatrix Double -> SpVector Double -> SpVector Double -> Bool

-- | one step of CGS
cgsStep :: SpMatrix Double -> SpVector Double -> CGS -> CGS
data CGS
CGS :: SpVector Double -> SpVector Double -> SpVector Double -> SpVector Double -> CGS
[_x] :: CGS -> SpVector Double
[_r] :: CGS -> SpVector Double
[_p] :: CGS -> SpVector Double
[_u] :: CGS -> SpVector Double

-- | iterate solver until convergence or until max # of iterations is
--   reached
cgs :: SpMatrix Double -> SpVector Double -> SpVector Double -> SpVector Double -> CGS

-- | one step of BiCGSTAB
bicgstabStep :: SpMatrix Double -> SpVector Double -> BICGSTAB -> BICGSTAB
data BICGSTAB
BICGSTAB :: SpVector Double -> SpVector Double -> SpVector Double -> BICGSTAB
[_xBicgstab] :: BICGSTAB -> SpVector Double
[_rBicgstab] :: BICGSTAB -> SpVector Double
[_pBicgstab] :: BICGSTAB -> SpVector Double

-- | iterate solver until convergence or until max # of iterations is
--   reached
bicgstab :: SpMatrix Double -> SpVector Double -> SpVector Double -> SpVector Double -> BICGSTAB
data LinSolveMethod
CGS_ :: LinSolveMethod
BICGSTAB_ :: LinSolveMethod

-- | Linear solve with _random_ starting vector
linSolveM :: PrimMonad m => LinSolveMethod -> SpMatrix Double -> SpVector Double -> m (SpVector Double)

-- | Linear solve with _deterministic_ starting vector (every component at
--   0.1)
linSolve :: LinSolveMethod -> SpMatrix Double -> SpVector Double -> SpVector Double

-- | &lt;&gt; : linSolve using BiCGSTAB method and by default
(<\>) :: SpMatrix Double -> SpVector Double -> SpVector Double

-- | transform state until a condition is met
modifyUntil :: MonadState s m => (s -> Bool) -> (s -> s) -> m s

-- | Keep a moving window buffer (length 2) of state <tt>x</tt> to assess
--   convergence, stop when either a condition on that list is satisfied or
--   when max # of iterations is reached
loopUntilAcc :: Int -> ([t] -> Bool) -> (t -> t) -> t -> t

-- | Keep a moving window buffer (length 2) of state <tt>x</tt> to assess
--   convergence, stop when either a condition on that list is satisfied or
--   when max # of iterations is reached (runs in State monad)
modifyInspectN :: MonadState s m => Int -> ([s] -> Bool) -> (s -> s) -> m s
meanl :: (Foldable t, Fractional a) => t a -> a
norm2l :: (Foldable t, Functor t, Floating a) => t a -> a
diffSqL :: Floating a => [a] -> a

-- | iterate until convergence is verified or we run out of a fixed
--   iteration budget
untilConverged :: MonadState a m => (a -> SpVector Double) -> (a -> a) -> m a

-- | convergence check (FIXME)
normDiffConverged :: (Foldable t, Functor t) => (a -> SpVector Double) -> t a -> Bool

-- | run <tt>niter</tt> iterations and append the state <tt>x</tt> to a
--   list <tt>xs</tt>, stop when either the <tt>xs</tt> satisfies a
--   predicate <tt>q</tt> or when the counter reaches 0
runAppendN :: ([t] -> Bool) -> (t -> t) -> Int -> t -> [t]

-- | ", NO convergence check
runAppendN' :: (t -> t) -> Int -> t -> [t]

-- | Rounding rule
almostZero :: Double -> Bool

-- | Rounding rule
almostOne :: Double -> Bool
withDefault :: (t -> Bool) -> t -> t -> t
roundZero :: Double -> Double
roundOne :: Double -> Double
with2Defaults :: (t -> Bool) -> (t -> Bool) -> t -> t -> t -> t

-- | Round to respectively 0 or 1 within some predefined numerical
--   precision eps
roundZeroOne :: Double -> Double

-- | Dense SpMatrix
randMat :: PrimMonad m => Int -> m (SpMatrix Double)

-- | Dense SpVector
randVec :: PrimMonad m => Int -> m (SpVector Double)

-- | Sparse SpMatrix
randSpMat :: Int -> Int -> IO (SpMatrix Double)

-- | Sparse SpVector
randSpVec :: Int -> Int -> IO (SpVector Double)
sizeStr :: SpMatrix a -> String
showNonZero :: (Show a, Num a, Eq a) => a -> String
toDenseRow :: Num a => SpMatrix a -> Key -> [a]
toDenseRowClip :: (Show a, Num a) => SpMatrix a -> Key -> Int -> String
newline :: IO ()
printDenseSM :: (Show t, Num t) => SpMatrix t -> IO ()
toDenseListClip :: (Show a, Num a) => SpVector a -> Int -> String
printDenseSV :: (Show t, Num t) => SpVector t -> IO ()
class PrintDense a
prd :: PrintDense a => a -> IO ()

-- | integer-indexed ziplist
denseIxArray :: [b] -> [(Int, b)]

-- | ", 2d arrays
denseIxArray2 :: Int -> [c] -> [(Int, Int, c)]

-- | foldr over the results of a fmap
foldrMap :: (Foldable t, Functor t) => (a -> b) -> (b -> c -> c) -> c -> t a -> c

-- | strict left fold
foldlStrict :: (a -> b -> a) -> a -> [b] -> a

-- | indexed right fold
ifoldr :: Num i => (a -> b -> b) -> b -> (i -> c -> d -> a) -> c -> [d] -> b
type LB = Int
type UB = Int
inBounds :: LB -> UB -> Int -> Bool
inBounds2 :: (LB, UB) -> (Int, Int) -> Bool
inBounds0 :: UB -> Int -> Bool
inBounds02 :: (UB, UB) -> (Int, Int) -> Bool
instance GHC.Show.Show Numeric.LinearAlgebra.Sparse.LinSolveMethod
instance GHC.Classes.Eq Numeric.LinearAlgebra.Sparse.LinSolveMethod
instance GHC.Classes.Eq Numeric.LinearAlgebra.Sparse.BICGSTAB
instance GHC.Classes.Eq Numeric.LinearAlgebra.Sparse.CGS
instance GHC.Show.Show Numeric.LinearAlgebra.Sparse.SMInfo
instance GHC.Classes.Eq Numeric.LinearAlgebra.Sparse.SMInfo
instance GHC.Classes.Eq a => GHC.Classes.Eq (Numeric.LinearAlgebra.Sparse.SpMatrix a)
instance GHC.Classes.Eq a => GHC.Classes.Eq (Numeric.LinearAlgebra.Sparse.SpVector a)
instance Numeric.LinearAlgebra.Sparse.Set Data.IntMap.Base.IntMap
instance Numeric.LinearAlgebra.Sparse.Additive Data.IntMap.Base.IntMap
instance Numeric.LinearAlgebra.Sparse.VectorSpace Data.IntMap.Base.IntMap
instance Numeric.LinearAlgebra.Sparse.Hilbert Data.IntMap.Base.IntMap
instance Numeric.LinearAlgebra.Sparse.Normed Data.IntMap.Base.IntMap
instance GHC.Base.Functor Numeric.LinearAlgebra.Sparse.SpVector
instance Numeric.LinearAlgebra.Sparse.Set Numeric.LinearAlgebra.Sparse.SpVector
instance Data.Foldable.Foldable Numeric.LinearAlgebra.Sparse.SpVector
instance Numeric.LinearAlgebra.Sparse.Additive Numeric.LinearAlgebra.Sparse.SpVector
instance Numeric.LinearAlgebra.Sparse.VectorSpace Numeric.LinearAlgebra.Sparse.SpVector
instance Numeric.LinearAlgebra.Sparse.FiniteDim Numeric.LinearAlgebra.Sparse.SpVector
instance Numeric.LinearAlgebra.Sparse.HasData Numeric.LinearAlgebra.Sparse.SpVector a
instance Numeric.LinearAlgebra.Sparse.Sparse Numeric.LinearAlgebra.Sparse.SpVector a
instance Numeric.LinearAlgebra.Sparse.Hilbert Numeric.LinearAlgebra.Sparse.SpVector
instance Numeric.LinearAlgebra.Sparse.Normed Numeric.LinearAlgebra.Sparse.SpVector
instance GHC.Show.Show a => GHC.Show.Show (Numeric.LinearAlgebra.Sparse.SpVector a)
instance GHC.Show.Show a => GHC.Show.Show (Numeric.LinearAlgebra.Sparse.SpMatrix a)
instance GHC.Base.Functor Numeric.LinearAlgebra.Sparse.SpMatrix
instance Numeric.LinearAlgebra.Sparse.Set Numeric.LinearAlgebra.Sparse.SpMatrix
instance Numeric.LinearAlgebra.Sparse.Additive Numeric.LinearAlgebra.Sparse.SpMatrix
instance Numeric.LinearAlgebra.Sparse.FiniteDim Numeric.LinearAlgebra.Sparse.SpMatrix
instance Numeric.LinearAlgebra.Sparse.HasData Numeric.LinearAlgebra.Sparse.SpMatrix a
instance Numeric.LinearAlgebra.Sparse.Sparse Numeric.LinearAlgebra.Sparse.SpMatrix a
instance GHC.Show.Show Numeric.LinearAlgebra.Sparse.CGS
instance GHC.Show.Show Numeric.LinearAlgebra.Sparse.BICGSTAB
instance (GHC.Show.Show a, GHC.Num.Num a) => Numeric.LinearAlgebra.Sparse.PrintDense (Numeric.LinearAlgebra.Sparse.SpVector a)
instance (GHC.Show.Show a, GHC.Num.Num a) => Numeric.LinearAlgebra.Sparse.PrintDense (Numeric.LinearAlgebra.Sparse.SpMatrix a)