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


-- | Numerical computation in native Haskell
--   
--   Currently the library provides iterative linear solvers, matrix
--   decompositions, eigenvalue computations and related utilities. Please
--   see README.md for details
@package sparse-linear-algebra
@version 0.2.0.9

module Numeric.LinearAlgebra.Class
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

-- | `hilbertDistSq x y = || x - y ||^2`
hilbertDistSq :: (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 > 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 > 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
class IxContainer (c :: * -> *) a where type Ix c :: * where {
    type family Ix c :: *;
}
ixcLookup :: IxContainer c a => Ix c -> c a -> Maybe a
ixcLookupDefault :: IxContainer c a => a -> Ix c -> c a -> a
ixcFilter :: IxContainer c a => (a -> Bool) -> c a -> c a
ixcIfilter :: IxContainer c a => (Ix c -> a -> Bool) -> c a -> c a
ixcInsert :: IxContainer c a => Ix c -> a -> c a -> c a
ixcFromList :: IxContainer c a => [(Ix c, a)] -> c a
ixcToList :: IxContainer c a => c a -> [(Ix c, a)]

module Numeric.Eps

-- | eps = 1e-8
eps :: Double

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

-- | Rounding rule
almostOne :: Double -> Bool
isNz :: 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

module Data.Sparse.Utils

-- | 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)

-- | 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

module Data.Sparse.Types
type Rows = Int
type Cols = Int
type IxRow = Int
type IxCol = Int

module Data.Sparse.IntMap2.IntMap2

-- | Insert an element
insertIM2 :: Key -> Key -> a -> IntMap (IntMap a) -> IntMap (IntMap a)

-- | Lookup a key
lookupIM2 :: Key -> Key -> IntMap (IntMap a) -> Maybe a

-- | Ppopulate an IM2 from a list of (row index, column index, value)
fromListIM2 :: Foldable t => t (Key, Key, a) -> IntMap (IntMap a) -> IntMap (IntMap a)

-- | Indexed left fold over an IM2, with general accumulator
ifoldlIM2' :: (Key -> Key -> a -> b -> b) -> b -> IntMap (IntMap a) -> b

-- | Indexed left fold over an IM2
ifoldlIM2 :: (Key -> Key -> t -> IntMap a -> IntMap a) -> IntMap (IntMap t) -> IntMap a

-- | Left fold over an IM2, with general accumulator
foldlIM2 :: (a -> b -> b) -> b -> IntMap (IntMap a) -> b

-- | Inner indices become outer ones and vice versa. No loss of information
--   because both inner and outer IntMaps are nubbed.
transposeIM2 :: IntMap (IntMap a) -> IntMap (IntMap a)

-- | Map over outer IM and filter all inner IM's
ifilterIM2 :: (Key -> Key -> a -> Bool) -> IntMap (IntMap a) -> IntMap (IntMap a)

-- | Specialized filtering : keep only sub-diagonal elements
filterSubdiag :: IntMap (IntMap a) -> IntMap (IntMap a)
countSubdiagonalNZ :: IntMap (IntMap a) -> Int

-- | List of (row, col) indices of (nonzero) subdiagonal elements
subdiagIndices :: IntMap (IntMap a) -> [(Key, Key)]
rpairs :: (a, [b]) -> [(a, b)]

-- | Map over IM2
mapIM2 :: (a -> b) -> IntMap (IntMap a) -> IntMap (IntMap b)

-- | Indexed map over IM2
imapIM2 :: (Key -> Key -> a -> b) -> IntMap (IntMap a) -> IntMap (IntMap b)

-- | Mapping keys
mapKeysIM2 :: (Key -> Key) -> (Key -> Key) -> IntMap (IntMap a) -> IntMap (IntMap a)
mapColumnIM2 :: (b -> b) -> IntMap (IntMap b) -> Int -> IntMap (IntMap b)
instance Numeric.LinearAlgebra.Class.Set Data.IntMap.Base.IntMap
instance Numeric.LinearAlgebra.Class.Additive Data.IntMap.Base.IntMap
instance Numeric.LinearAlgebra.Class.VectorSpace Data.IntMap.Base.IntMap
instance Numeric.LinearAlgebra.Class.Hilbert Data.IntMap.Base.IntMap
instance Numeric.LinearAlgebra.Class.Normed Data.IntMap.Base.IntMap

module Data.Sparse.SpMatrix
data SpMatrix a
SM :: (Rows, Cols) -> IntMap (IntMap a) -> SpMatrix a
[smDim] :: SpMatrix a -> (Rows, Cols)
[smData] :: SpMatrix a -> IntMap (IntMap a)
sizeStr :: SpMatrix a -> String

-- | `zeroSM m n` : Empty SpMatrix of size (m, n)
zeroSM :: Rows -> Cols -> SpMatrix a
mkDiagonal :: Int -> [a] -> SpMatrix a

-- | `eye n` : identity matrix of rank <tt>n</tt>
eye :: Num a => Int -> SpMatrix a

-- | Permutation matrix from a (possibly incomplete) list of row swaps
--   starting from row 0 e.g. `permutationSM 5 [1,3]` first swaps rows (0,
--   1) and then rows (1, 3) :
--   
--   <ul>
--   <li><i>0,1,0,0,0</i></li>
--   <li><i>0,0,0,1,0</i></li>
--   <li><i>0,0,1,0,0</i></li>
--   <li><i>1,0,0,0,0</i></li>
--   <li><i>0,0,0,0,1</i></li>
--   </ul>
permutationSM :: Num a => Int -> [IxRow] -> SpMatrix a

-- | Permutation matrix from a (possibly incomplete) list of row pair swaps
--   e.g. `permutPairs 5 [(2,4)]` swaps rows (2, 4) :
--   
--   <ul>
--   <li><i>1,0,0,0,0</i></li>
--   <li><i>0,1,0,0,0</i></li>
--   <li><i>0,0,0,0,1</i></li>
--   <li><i>0,0,0,1,0</i></li>
--   <li><i>0,0,1,0,0</i></li>
--   </ul>
permutPairsSM :: Num a => Int -> [(IxRow, IxRow)] -> SpMatrix a

-- | `mkSubDiagonal n o xx` creates a square SpMatrix of size <tt>n</tt>
--   with <tt>xx</tt> on the <tt>o</tt>th subdiagonal
mkSubDiagonal :: Int -> Int -> [a] -> SpMatrix a

-- | Insert an element in a preexisting Spmatrix at the specified indices
insertSpMatrix :: IxRow -> IxCol -> a -> SpMatrix 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)]
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 (no bound checking)
--   
--   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

-- | Zero-default lookup, infix form ("safe" : throws exception if lookup
--   is outside matrix bounds)
--   
--   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

-- | Indexed filtering function
filterSM :: (Key -> Key -> a -> Bool) -> SpMatrix a -> SpMatrix a

-- | Diagonal, subdiagonal, superdiagonal partitions of a SpMatrix (useful
--   for writing preconditioners)
extractDiag :: SpMatrix a -> SpMatrix a

-- | Diagonal, subdiagonal, superdiagonal partitions of a SpMatrix (useful
--   for writing preconditioners)
extractSuperDiag :: SpMatrix a -> SpMatrix a

-- | Diagonal, subdiagonal, superdiagonal partitions of a SpMatrix (useful
--   for writing preconditioners)
extractSubDiag :: SpMatrix a -> SpMatrix a

-- | Extract a submatrix given the specified index bounds, rebalancing keys
--   with the two supplied functions
extractSubmatrixSM :: (Key -> Key) -> (Key -> Key) -> SpMatrix a -> (IxRow, IxRow) -> (IxCol, IxCol) -> SpMatrix a

-- | Extract a submatrix given the specified index bounds NB : subtracts
--   (i1, j1) from the indices
extractSubmatrixRebalanceKeys :: SpMatrix a -> (IxRow, IxRow) -> (IxCol, IxCol) -> SpMatrix a

-- | Extract a submatrix given the specified index bounds NB : submatrix
--   indices are _preserved_
extractSubmatrix :: SpMatrix a -> (IxRow, IxRow) -> (IxCol, IxCol) -> SpMatrix a
extractRowSM :: SpMatrix a -> IxRow -> SpMatrix a

-- | Extract column within a row range
extractSubRowSM :: SpMatrix a -> IxRow -> (IxCol, IxCol) -> SpMatrix a

-- | Extract column within a row range, rebalance keys
extractSubRowSM_RK :: SpMatrix a -> IxRow -> (IxCol, IxCol) -> SpMatrix a

-- | Extract all column
extractColSM :: SpMatrix a -> IxCol -> SpMatrix a

-- | Extract column within a row range
extractSubColSM :: SpMatrix a -> IxCol -> (IxRow, IxRow) -> SpMatrix a

-- | Extract column within a row range, rebalance keys
extractSubColSM_RK :: SpMatrix a -> IxCol -> (IxRow, IxRow) -> SpMatrix a

-- | Are the supplied indices within matrix bounds?
isValidIxSM :: 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)

-- | 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

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

-- | Sparsify an SpMatrix
sparsifySM :: SpMatrix Double -> SpMatrix Double

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

-- | swap two rows of a SpMatrix (bounds not checked)
swapRows :: IxRow -> IxRow -> SpMatrix a -> SpMatrix a

-- | swap two rows of a SpMatrix (bounds checked)
swapRowsSafe :: IxRow -> IxRow -> SpMatrix a -> SpMatrix a

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

-- | transposeSM, (#^) : Matrix transpose
(#^) :: SpMatrix a -> SpMatrix a
matScale :: Num a => a -> SpMatrix a -> SpMatrix a
normFrobenius :: SpMatrix Double -> Double
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

-- | Contract two matrices A and B up to an index <tt>n</tt>, i.e. summing
--   over repeated indices: Aij Bjk , for j in [0 .. n]
contractSub :: Num a => SpMatrix a -> SpMatrix a -> IxRow -> IxCol -> Int -> a
instance GHC.Show.Show Data.Sparse.SpMatrix.SMInfo
instance GHC.Classes.Eq Data.Sparse.SpMatrix.SMInfo
instance GHC.Classes.Eq a => GHC.Classes.Eq (Data.Sparse.SpMatrix.SpMatrix a)
instance GHC.Show.Show a => GHC.Show.Show (Data.Sparse.SpMatrix.SpMatrix a)
instance GHC.Base.Functor Data.Sparse.SpMatrix.SpMatrix
instance Numeric.LinearAlgebra.Class.Set Data.Sparse.SpMatrix.SpMatrix
instance Numeric.LinearAlgebra.Class.Additive Data.Sparse.SpMatrix.SpMatrix
instance Numeric.LinearAlgebra.Class.FiniteDim Data.Sparse.SpMatrix.SpMatrix
instance Numeric.LinearAlgebra.Class.HasData Data.Sparse.SpMatrix.SpMatrix a
instance Numeric.LinearAlgebra.Class.Sparse Data.Sparse.SpMatrix.SpMatrix a

module Data.Sparse.SpVector
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

-- | Number of nonzeros
nzSV :: SpVector a -> Int
sizeStrSV :: SpVector a -> String

-- | 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

-- | one-hot encoding : `oneHotSV n k` produces a SpVector of length n
--   having 1 at the k-th position
oneHotSVU :: Num a => Int -> IxRow -> SpVector a
oneHotSV :: Num a => Int -> IxRow -> 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
lookupSV :: Key -> SpVector a -> Maybe a

-- | Lookup an index, return a default value if lookup fails
lookupDefaultSV :: a -> Key -> SpVector a -> a

-- | 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

-- | Filter
filterSV :: (a -> Bool) -> SpVector a -> SpVector a

-- | Indexed filter
ifilterSV :: (Int -> a -> Bool) -> SpVector a -> SpVector a

-- | Generate an arbitrary (not random) vector <tt>u</tt> such that `v dot
--   u = 0`
orthogonalSV :: Fractional a => SpVector a -> SpVector a
instance GHC.Classes.Eq a => GHC.Classes.Eq (Data.Sparse.SpVector.SpVector a)
instance GHC.Base.Functor Data.Sparse.SpVector.SpVector
instance Numeric.LinearAlgebra.Class.Set Data.Sparse.SpVector.SpVector
instance Data.Foldable.Foldable Data.Sparse.SpVector.SpVector
instance Numeric.LinearAlgebra.Class.Additive Data.Sparse.SpVector.SpVector
instance Numeric.LinearAlgebra.Class.VectorSpace Data.Sparse.SpVector.SpVector
instance Numeric.LinearAlgebra.Class.FiniteDim Data.Sparse.SpVector.SpVector
instance Numeric.LinearAlgebra.Class.HasData Data.Sparse.SpVector.SpVector a
instance Numeric.LinearAlgebra.Class.Sparse Data.Sparse.SpVector.SpVector a
instance Numeric.LinearAlgebra.Class.Hilbert Data.Sparse.SpVector.SpVector
instance Numeric.LinearAlgebra.Class.Normed Data.Sparse.SpVector.SpVector
instance GHC.Show.Show a => GHC.Show.Show (Data.Sparse.SpVector.SpVector a)

module Data.Sparse.Common

-- | Insert row , using the provided row index transformation function
insertRowWith :: (IxCol -> IxCol) -> SpMatrix a -> SpVector a -> Key -> SpMatrix a

-- | Insert row
insertRow :: SpMatrix a -> SpVector a -> Key -> SpMatrix a

-- | Insert column, using the provided row index transformation function
insertColWith :: (IxRow -> IxRow) -> SpMatrix a -> SpVector a -> IxCol -> SpMatrix a

-- | Insert column
insertCol :: SpMatrix a -> SpVector a -> IxCol -> SpMatrix a
outerProdSV :: Num a => SpVector a -> SpVector a -> SpMatrix a
(><) :: Num a => SpVector a -> SpVector a -> SpMatrix a

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

-- | promote a SV to SM
svToSM :: SpVector a -> SpMatrix a

-- | Extract jth column
extractCol :: SpMatrix a -> IxCol -> SpVector a

-- | Extract ith row
extractRow :: SpMatrix a -> IxRow -> SpVector a

-- | Generic extraction function
extractVectorDenseWith :: Num a => (Int -> (IxRow, IxCol)) -> SpMatrix a -> SpVector a

-- | Extract ith row (dense)
extractRowDense :: Num a => SpMatrix a -> IxRow -> SpVector a

-- | Extract jth column
extractColDense :: Num a => SpMatrix a -> IxCol -> SpVector a

-- | Extract the diagonal
extractDiagDense :: Num a => SpMatrix a -> SpVector a

-- | extract row interval
extractSubRow :: SpMatrix a -> IxRow -> (IxCol, IxCol) -> SpVector a

-- | extract column interval
extractSubCol :: SpMatrix a -> IxCol -> (IxRow, IxRow) -> SpVector a

-- | extract row interval, rebalance keys by subtracting lowest one
extractSubRow_RK :: SpMatrix a -> IxRow -> (IxCol, IxCol) -> SpVector a

-- | extract column interval, rebalance keys by subtracting lowest one
extractSubCol_RK :: SpMatrix a -> IxCol -> (IxRow, IxRow) -> SpVector 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
prd :: PrintDense a => a -> IO ()
instance (GHC.Show.Show a, GHC.Num.Num a) => Data.Sparse.Common.PrintDense (Data.Sparse.SpVector.SpVector a)
instance (GHC.Show.Show a, GHC.Num.Num a) => Data.Sparse.Common.PrintDense (Data.Sparse.SpMatrix.SpMatrix a)

module Numeric.LinearAlgebra.Sparse

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

-- | LU factors
lu :: SpMatrix Double -> (SpMatrix Double, SpMatrix Double)

-- | used for Incomplete LU : remove entries in <tt>m</tt> corresponding to
--   zero entries in <tt>m2</tt>
ilu0 :: 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

-- | 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

-- | `eigsQR n mm` performs <tt>n</tt> iterations of the QR algorithm on
--   matrix <tt>mm</tt>, and returns a SpVector containing all eigenvalues
eigsQR :: Int -> SpMatrix Double -> SpVector Double

-- | `eigsRayleigh n mm` performs <tt>n</tt> iterations of the Rayleigh
--   algorithm on matrix <tt>mm</tt> and returns the eigenpair closest to
--   the initialization. It displays cubic-order convergence, but it also
--   requires an educated guess on the initial eigenpair
eigRayleigh :: Int -> SpMatrix Double -> (SpVector Double, Double) -> (SpVector Double, Double)

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

-- | <a>\</a> : linSolve using the BiCGSTAB method as default
(<\>) :: SpMatrix Double -> SpVector Double -> SpVector Double
cgne :: SpMatrix Double -> SpVector Double -> SpVector Double -> CGNE
tfqmr :: SpMatrix Double -> SpVector Double -> SpVector Double -> TFQMR

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

-- | iterate solver until convergence or until max # of iterations is
--   reached
cgs :: SpMatrix Double -> SpVector Double -> SpVector Double -> SpVector Double -> CGS
bcg :: SpMatrix Double -> SpVector Double -> SpVector Double -> BCG
_xCgne :: CGNE -> SpVector Double
_xTfq :: TFQMR -> SpVector Double
_xBicgstab :: BICGSTAB -> SpVector Double
_x :: CGS -> SpVector Double
_xBcg :: BCG -> SpVector Double

-- | one step of CGS
cgsStep :: SpMatrix Double -> SpVector Double -> CGS -> CGS

-- | one step of BiCGSTAB
bicgstabStep :: SpMatrix Double -> SpVector Double -> BICGSTAB -> BICGSTAB
data CGNE
data TFQMR
data BICGSTAB
data CGS
data BCG

-- | Partition a matrix into strictly subdiagonal, diagonal and strictly
--   superdiagonal parts
diagPartitions :: SpMatrix a -> (SpMatrix a, SpMatrix a, SpMatrix a)
randArray :: PrimMonad m => Int -> Double -> Double -> m [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)

-- | Sparsify an SpVector
sparsifySV :: SpVector Double -> SpVector Double

-- | 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 (i.e. same thing as
--   <a>loopUntilAcc</a> but this one runs in the State monad)
modifyInspectN :: MonadState s m => Int -> ([s] -> Bool) -> (s -> s) -> m s

-- | ", NO convergence check
runAppendN' :: (t -> t) -> Int -> t -> [t]
diffSqL :: Floating a => [a] -> a
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.Classes.Eq Numeric.LinearAlgebra.Sparse.BCG
instance GHC.Classes.Eq Numeric.LinearAlgebra.Sparse.TFQMR
instance GHC.Classes.Eq Numeric.LinearAlgebra.Sparse.CGNE
instance GHC.Show.Show Numeric.LinearAlgebra.Sparse.BCG
instance GHC.Show.Show Numeric.LinearAlgebra.Sparse.CGS
instance GHC.Show.Show Numeric.LinearAlgebra.Sparse.BICGSTAB