6 files changed, 232 insertions, 312 deletions

diff --git a/packages/base/src/Numeric/LinearAlgebra.hs b/packages/base/src/Numeric/LinearAlgebra.hs
index ad315e4..4ba0c98 100644
--- a/packages/base/src/Numeric/LinearAlgebra.hs
+++ b/packages/base/src/Numeric/LinearAlgebra.hs
@@ -1,22 +1,235 @@
---------------------------------------------------------------------------------
+-----------------------------------------------------------------------------
 {- |
 Module      :  Numeric.LinearAlgebra
-Copyright   :  (c) Alberto Ruiz 2006-14
+Copyright   :  (c) Alberto Ruiz 2006-15
 License     :  BSD3
 Maintainer  :  Alberto Ruiz
 Stability   :  provisional
 
 -}
---------------------------------------------------------------------------------
-{-# OPTIONS_HADDOCK hide #-}
-
+-----------------------------------------------------------------------------
 module Numeric.LinearAlgebra (
-    module Numeric.Container,
-    module Numeric.LinearAlgebra.Algorithms
+
+    -- * Basic types and data processing
+    module Numeric.LinearAlgebra.Data,
+
+    -- * Arithmetic and numeric classes
+    -- |
+    -- The standard numeric classes are defined elementwise:
+    --
+    -- >>>  vector [1,2,3] * vector [3,0,-2]
+    -- fromList [3.0,0.0,-6.0]
+    --
+    -- >>> matrix 3 [1..9] * ident 3
+    -- (3><3)
+    --  [ 1.0, 0.0, 0.0
+    --  , 0.0, 5.0, 0.0
+    --  , 0.0, 0.0, 9.0 ]
+    --
+    -- In arithmetic operations single-element vectors and matrices
+    -- (created from numeric literals or using 'scalar') automatically
+    -- expand to match the dimensions of the other operand:
+    --
+    -- >>> 5 + 2*ident 3 :: Matrix Double
+    -- (3><3)
+    --  [ 7.0, 5.0, 5.0
+    --  , 5.0, 7.0, 5.0
+    --  , 5.0, 5.0, 7.0 ]
+    --
+    -- >>> matrix 3 [1..9] + matrix 1 [10,20,30]
+    -- (3><3)
+    --  [ 11.0, 12.0, 13.0
+    --  , 24.0, 25.0, 26.0
+    --  , 37.0, 38.0, 39.0 ]
+    --
+
+    -- * Products
+    -- ** dot
+    dot, (<·>),
+    -- ** matrix-vector
+    app, (#>), (<#), (!#>),
+    -- ** matrix-matrix
+    mul, (<>),
+    -- | The matrix product is also implemented in the "Data.Monoid" instance, where
+    -- single-element matrices (created from numeric literals or using 'scalar')
+    -- are used for scaling.
+    --
+    -- >>> import Data.Monoid as M
+    -- >>>  let m = matrix 3 [1..6]
+    -- >>> m M.<> 2 M.<> diagl[0.5,1,0]
+    -- (2><3)
+    --  [ 1.0,  4.0, 0.0
+    --  , 4.0, 10.0, 0.0 ]
+    --
+    -- 'mconcat' uses 'optimiseMult' to get the optimal association order.
+
+
+    -- ** other
+    outer, kronecker, cross,
+    scale,
+    sumElements, prodElements,
+
+    -- * Linear Systems
+    (<\>),
+    linearSolve,
+    linearSolveLS,
+    linearSolveSVD,
+    luSolve,
+    cholSolve,
+    cgSolve,
+    cgSolve',
+
+    -- * Inverse and pseudoinverse
+    inv, pinv, pinvTol,
+
+    -- * Determinant and rank
+    rcond, rank,
+    det, invlndet,
+
+    -- * Norms
+    Normed(..),
+    norm_Frob, norm_nuclear,
+
+    -- * Nullspace and range
+    orth,
+    nullspace, null1, null1sym,
+
+    -- * SVD
+    svd,
+    thinSVD,
+    compactSVD,
+    singularValues,
+    leftSV, rightSV,
+
+    -- * Eigensystems
+    eig, eigSH, eigSH',
+    eigenvalues, eigenvaluesSH, eigenvaluesSH',
+    geigSH',
+
+    -- * QR
+    qr, rq, qrRaw, qrgr,
+
+    -- * Cholesky
+    chol, cholSH, mbCholSH,
+
+    -- * Hessenberg
+    hess,
+
+    -- * Schur
+    schur,
+
+    -- * LU
+    lu, luPacked,
+
+    -- * Matrix functions
+    expm,
+    sqrtm,
+    matFunc,
+
+    -- * Correlation and convolution
+    corr, conv, corrMin, corr2, conv2,
+
+    -- * Random arrays
+
+    Seed, RandDist(..), randomVector, rand, randn, gaussianSample, uniformSample,
+
+    -- * Misc
+    meanCov, rowOuters, pairwiseD2, unitary, peps, relativeError, haussholder, optimiseMult, udot, nullspaceSVD, orthSVD, ranksv,
+    ℝ,ℂ,iC,
+    -- * Auxiliary classes
+    Element, Container, Product, Numeric, LSDiv,
+    Complexable, RealElement,
+    RealOf, ComplexOf, SingleOf, DoubleOf,
+    IndexOf,
+    Field,
+--    Normed,
+    Transposable,
+    CGState(..),
+    Testable(..)
 ) where
 
-import Numeric.Container
-import Numeric.LinearAlgebra.Algorithms
+import Numeric.LinearAlgebra.Data
+
 import Numeric.Matrix()
 import Numeric.Vector()
+import Data.Packed.Numeric hiding ((<>), mul)
+import Numeric.LinearAlgebra.Algorithms hiding (linearSolve,Normed,orth)
+import qualified Numeric.LinearAlgebra.Algorithms as A
+import Numeric.LinearAlgebra.Util
+import Numeric.LinearAlgebra.Random
+import Numeric.Sparse((!#>))
+import Numeric.LinearAlgebra.Util.CG
+
+{- | infix synonym of 'mul'
+
+>>> let a = (3><5) [1..]
+>>> a
+(3><5)
+ [  1.0,  2.0,  3.0,  4.0,  5.0
+ ,  6.0,  7.0,  8.0,  9.0, 10.0
+ , 11.0, 12.0, 13.0, 14.0, 15.0 ]
+
+>>> let b = (5><2) [1,3, 0,2, -1,5, 7,7, 6,0]
+>>> b
+(5><2)
+ [  1.0, 3.0
+ ,  0.0, 2.0
+ , -1.0, 5.0
+ ,  7.0, 7.0
+ ,  6.0, 0.0 ]
+
+>>> a <> b
+(3><2)
+ [  56.0,  50.0
+ , 121.0, 135.0
+ , 186.0, 220.0 ]
+
+-}
+(<>) :: Numeric t => Matrix t -> Matrix t -> Matrix t
+(<>) = mXm
+infixr 8 <>
+
+-- | dense matrix product
+mul :: Numeric t => Matrix t -> Matrix t -> Matrix t
+mul = mXm
+
+
+{- | Solve a linear system (for square coefficient matrix and several right-hand sides) using the LU decomposition, returning Nothing for a singular system. For underconstrained or overconstrained systems use 'linearSolveLS' or 'linearSolveSVD'.
+
+@
+a = (2><2)
+ [ 1.0, 2.0
+ , 3.0, 5.0 ]
+@
+
+@
+b = (2><3)
+ [  6.0, 1.0, 10.0
+ , 15.0, 3.0, 26.0 ]
+@
+
+>>> linearSolve a b
+Just (2><3)
+ [ -1.4802973661668753e-15,     0.9999999999999997, 1.999999999999997
+ ,       3.000000000000001, 1.6653345369377348e-16, 4.000000000000002 ]
+
+>>> let Just x = it
+>>> disp 5 x
+2x3
+-0.00000  1.00000  2.00000
+ 3.00000  0.00000  4.00000
+
+>>> a <> x
+(2><3)
+ [  6.0, 1.0, 10.0
+ , 15.0, 3.0, 26.0 ]
+
+-}
+linearSolve m b = A.mbLinearSolve m b
+
+-- | return an orthonormal basis of the null space of a matrix. See also 'nullspaceSVD'.
+nullspace m = nullspaceSVD (Left (1*eps)) m (rightSV m)
+
+-- | return an orthonormal basis of the range space of a matrix. See also 'orthSVD'.
+orth m = orthSVD (Left (1*eps)) m (leftSV m)
 
diff --git a/packages/base/src/Numeric/LinearAlgebra/HMatrix.hs b/packages/base/src/Numeric/LinearAlgebra/HMatrix.hs
index a640351..8e67eb4 100644
--- a/packages/base/src/Numeric/LinearAlgebra/HMatrix.hs
+++ b/packages/base/src/Numeric/LinearAlgebra/HMatrix.hs
@@ -1,4 +1,4 @@
------------------------------------------------------------------------------
+--------------------------------------------------------------------------------
 {- |
 Module      :  Numeric.LinearAlgebra.HMatrix
 Copyright   :  (c) Alberto Ruiz 2006-14
@@ -7,229 +7,11 @@ Maintainer  :  Alberto Ruiz
 Stability   :  provisional
 
 -}
------------------------------------------------------------------------------
-module Numeric.LinearAlgebra.HMatrix (
-
-    -- * Basic types and data processing
-    module Numeric.LinearAlgebra.Data,
-
-    -- * Arithmetic and numeric classes
-    -- |
-    -- The standard numeric classes are defined elementwise:
-    --
-    -- >>>  vector [1,2,3] * vector [3,0,-2]
-    -- fromList [3.0,0.0,-6.0]
-    --
-    -- >>> matrix 3 [1..9] * ident 3
-    -- (3><3)
-    --  [ 1.0, 0.0, 0.0
-    --  , 0.0, 5.0, 0.0
-    --  , 0.0, 0.0, 9.0 ]
-    --
-    -- In arithmetic operations single-element vectors and matrices
-    -- (created from numeric literals or using 'scalar') automatically
-    -- expand to match the dimensions of the other operand:
-    --
-    -- >>> 5 + 2*ident 3 :: Matrix Double
-    -- (3><3)
-    --  [ 7.0, 5.0, 5.0
-    --  , 5.0, 7.0, 5.0
-    --  , 5.0, 5.0, 7.0 ]
-    --
-    -- >>> matrix 3 [1..9] + matrix 1 [10,20,30]
-    -- (3><3)
-    --  [ 11.0, 12.0, 13.0
-    --  , 24.0, 25.0, 26.0
-    --  , 37.0, 38.0, 39.0 ]
-    --
-
-    -- * Products
-    -- ** dot
-    dot, (<·>),
-    -- ** matrix-vector
-    app, (#>), (<#), (!#>),
-    -- ** matrix-matrix
-    mul, (<>),
-    -- | The matrix product is also implemented in the "Data.Monoid" instance, where
-    -- single-element matrices (created from numeric literals or using 'scalar')
-    -- are used for scaling.
-    --
-    -- >>> import Data.Monoid as M
-    -- >>>  let m = matrix 3 [1..6]
-    -- >>> m M.<> 2 M.<> diagl[0.5,1,0]
-    -- (2><3)
-    --  [ 1.0,  4.0, 0.0
-    --  , 4.0, 10.0, 0.0 ]
-    --
-    -- 'mconcat' uses 'optimiseMult' to get the optimal association order.
-
-
-    -- ** other
-    outer, kronecker, cross,
-    scale,
-    sumElements, prodElements,
-
-    -- * Linear Systems
-    (<\>),
-    linearSolve,
-    linearSolveLS,
-    linearSolveSVD,
-    luSolve,
-    cholSolve,
-    cgSolve,
-    cgSolve',
-
-    -- * Inverse and pseudoinverse
-    inv, pinv, pinvTol,
-
-    -- * Determinant and rank
-    rcond, rank,
-    det, invlndet,
-
-    -- * Norms
-    Normed(..),
-    norm_Frob, norm_nuclear,
-
-    -- * Nullspace and range
-    orth,
-    nullspace, null1, null1sym,
-
-    -- * SVD
-    svd,
-    thinSVD,
-    compactSVD,
-    singularValues,
-    leftSV, rightSV,
-
-    -- * Eigensystems
-    eig, eigSH, eigSH',
-    eigenvalues, eigenvaluesSH, eigenvaluesSH',
-    geigSH',
-
-    -- * QR
-    qr, rq, qrRaw, qrgr,
-
-    -- * Cholesky
-    chol, cholSH, mbCholSH,
-
-    -- * Hessenberg
-    hess,
-
-    -- * Schur
-    schur,
-
-    -- * LU
-    lu, luPacked,
-
-    -- * Matrix functions
-    expm,
-    sqrtm,
-    matFunc,
-
-    -- * Correlation and convolution
-    corr, conv, corrMin, corr2, conv2,
-
-    -- * Random arrays
+--------------------------------------------------------------------------------
 
-    Seed, RandDist(..), randomVector, rand, randn, gaussianSample, uniformSample,
-
-    -- * Misc
-    meanCov, rowOuters, peps, relativeError, haussholder, optimiseMult, udot, nullspaceSVD, orthSVD, ranksv,
-    ℝ,ℂ,iC,
-    -- * Auxiliary classes
-    Element, Container, Product, Numeric, LSDiv,
-    Complexable, RealElement,
-    RealOf, ComplexOf, SingleOf, DoubleOf,
-    IndexOf,
-    Field,
---    Normed,
-    Transposable,
-    CGState(..),
-    Testable(..)
+module Numeric.LinearAlgebra.HMatrix (
+    module Numeric.LinearAlgebra
 ) where
 
-import Numeric.LinearAlgebra.Data
-
-import Numeric.Matrix()
-import Numeric.Vector()
-import Data.Packed.Numeric hiding ((<>), mul)
-import Numeric.LinearAlgebra.Algorithms hiding (linearSolve,Normed,orth)
-import qualified Numeric.LinearAlgebra.Algorithms as A
-import Numeric.LinearAlgebra.Util
-import Numeric.LinearAlgebra.Random
-import Numeric.Sparse((!#>))
-import Numeric.LinearAlgebra.Util.CG
-
-{- | infix synonym of 'mul'
-
->>> let a = (3><5) [1..]
->>> a
-(3><5)
- [  1.0,  2.0,  3.0,  4.0,  5.0
- ,  6.0,  7.0,  8.0,  9.0, 10.0
- , 11.0, 12.0, 13.0, 14.0, 15.0 ]
-
->>> let b = (5><2) [1,3, 0,2, -1,5, 7,7, 6,0]
->>> b
-(5><2)
- [  1.0, 3.0
- ,  0.0, 2.0
- , -1.0, 5.0
- ,  7.0, 7.0
- ,  6.0, 0.0 ]
-
->>> a <> b
-(3><2)
- [  56.0,  50.0
- , 121.0, 135.0
- , 186.0, 220.0 ]
-
--}
-(<>) :: Numeric t => Matrix t -> Matrix t -> Matrix t
-(<>) = mXm
-infixr 8 <>
-
--- | dense matrix product
-mul :: Numeric t => Matrix t -> Matrix t -> Matrix t
-mul = mXm
-
-
-{- | Solve a linear system (for square coefficient matrix and several right-hand sides) using the LU decomposition, returning Nothing for a singular system. For underconstrained or overconstrained systems use 'linearSolveLS' or 'linearSolveSVD'.
-
-@
-a = (2><2)
- [ 1.0, 2.0
- , 3.0, 5.0 ]
-@
-
-@
-b = (2><3)
- [  6.0, 1.0, 10.0
- , 15.0, 3.0, 26.0 ]
-@
-
->>> linearSolve a b
-Just (2><3)
- [ -1.4802973661668753e-15,     0.9999999999999997, 1.999999999999997
- ,       3.000000000000001, 1.6653345369377348e-16, 4.000000000000002 ]
-
->>> let Just x = it
->>> disp 5 x
-2x3
--0.00000  1.00000  2.00000
- 3.00000  0.00000  4.00000
-
->>> a <> x
-(2><3)
- [  6.0, 1.0, 10.0
- , 15.0, 3.0, 26.0 ]
-
--}
-linearSolve m b = A.mbLinearSolve m b
-
--- | return an orthonormal basis of the null space of a matrix. See also 'nullspaceSVD'.
-nullspace m = nullspaceSVD (Left (1*eps)) m (rightSV m)
-
--- | return an orthonormal basis of the range space of a matrix. See also 'orthSVD'.
-orth m = orthSVD (Left (1*eps)) m (leftSV m)
+import Numeric.LinearAlgebra
 
diff --git a/packages/base/src/Numeric/LinearAlgebra/HMatrix/Util.hs b/packages/base/src/Numeric/LinearAlgebra/HMatrix/Util.hs
deleted file mode 100644
index 818b226..0000000
--- a/packages/base/src/Numeric/LinearAlgebra/HMatrix/Util.hs
+++ /dev/null
@@ -1,29 +0,0 @@
------------------------------------------------------------------------------
-{- |
-Module      :  Numeric.LinearAlgebra.HMatrix.Util
-Copyright   :  (c) Alberto Ruiz 2015
-License     :  BSD3
-Maintainer  :  Alberto Ruiz
-Stability   :  provisional
-
--}
------------------------------------------------------------------------------
-
-module Numeric.LinearAlgebra.HMatrix.Util(
-    unitary,
-    pairwiseD2,
-    -- * Tools for the Kronecker product
-    --
-    -- | (see A. Fusiello, A matter of notation: Several uses of the Kronecker product in
-    --  3d computer vision, Pattern Recognition Letters 28 (15) (2007) 2127-2132)
-
-    --
-    -- | @`vec` (a \<> x \<> b) == ('trans' b ` 'kronecker' ` a) \<> 'vec' x@
-    vec,
-    vech,
-    dup,
-    vtrans
-) where
-
-import Numeric.LinearAlgebra.Util
-
diff --git a/packages/base/src/Numeric/LinearAlgebra/Static.hs b/packages/base/src/Numeric/LinearAlgebra/Static.hs
index 4c3186f..25b10b4 100644
--- a/packages/base/src/Numeric/LinearAlgebra/Static.hs
+++ b/packages/base/src/Numeric/LinearAlgebra/Static.hs
@@ -60,13 +60,13 @@ module Numeric.LinearAlgebra.Static(
 
 
 import GHC.TypeLits
-import Numeric.LinearAlgebra.HMatrix hiding (
+import Numeric.LinearAlgebra hiding (
     (<>),(#>),(<·>),Konst(..),diag, disp,(¦),(——),
     row,col,vector,matrix,linspace,toRows,toColumns,
     (<\>),fromList,takeDiag,svd,eig,eigSH,eigSH',
     eigenvalues,eigenvaluesSH,eigenvaluesSH',build,
     qr,size,app,mul,dot,chol)
-import qualified Numeric.LinearAlgebra.HMatrix as LA
+import qualified Numeric.LinearAlgebra as LA
 import Data.Proxy(Proxy)
 import Numeric.LinearAlgebra.Static.Internal
 import Control.Arrow((***))
diff --git a/packages/base/src/Numeric/LinearAlgebra/Static/Internal.hs b/packages/base/src/Numeric/LinearAlgebra/Static/Internal.hs
index ec02cf6..a5fc29b 100644
--- a/packages/base/src/Numeric/LinearAlgebra/Static/Internal.hs
+++ b/packages/base/src/Numeric/LinearAlgebra/Static/Internal.hs
@@ -24,8 +24,8 @@ module Numeric.LinearAlgebra.Static.Internal where
 
 
 import GHC.TypeLits
-import qualified Numeric.LinearAlgebra.HMatrix as LA
-import Numeric.LinearAlgebra.HMatrix hiding (konst,size)
+import qualified Numeric.LinearAlgebra as LA
+import Numeric.LinearAlgebra hiding (konst,size)
 import Data.Packed as D
 import Data.Packed.ST
 import Data.Proxy(Proxy)
diff --git a/packages/base/src/Numeric/LinearAlgebra/Util.hs b/packages/base/src/Numeric/LinearAlgebra/Util.hs
index 89202d3..370ca27 100644
--- a/packages/base/src/Numeric/LinearAlgebra/Util.hs
+++ b/packages/base/src/Numeric/LinearAlgebra/Util.hs
@@ -16,7 +16,6 @@ Stability   :  provisional
 
 -}
 -----------------------------------------------------------------------------
-{-# OPTIONS_HADDOCK hide #-}
 
 module Numeric.LinearAlgebra.Util(
 
@@ -53,18 +52,7 @@ module Numeric.LinearAlgebra.Util(
     -- ** 1D
     corr, conv, corrMin,
     -- ** 2D
-    corr2, conv2, separable,
-    -- * Tools for the Kronecker product
-    --
-    -- | (see A. Fusiello, A matter of notation: Several uses of the Kronecker product in
-    --  3d computer vision, Pattern Recognition Letters 28 (15) (2007) 2127-2132)
-
-    --
-    -- | @`vec` (a \<> x \<> b) == ('trans' b ` 'kronecker' ` a) \<> 'vec' x@
-    vec,
-    vech,
-    dup,
-    vtrans
+    corr2, conv2, separable
 ) where
 
 import Data.Packed.Numeric
@@ -407,40 +395,6 @@ null1sym = last . toColumns . snd . eigSH'
 
 --------------------------------------------------------------------------------
 
-vec :: Element t => Matrix t -> Vector t
--- ^ stacking of columns
-vec = flatten . trans
-
-
-vech :: Element t => Matrix t -> Vector t
--- ^ half-vectorization (of the lower triangular part)
-vech m = vjoin . zipWith f [0..] . toColumns $ m
-  where
-    f k v = subVector k (dim v - k) v
-
-
-dup :: (Num t, Num (Vector t), Element t) => Int -> Matrix t
--- ^ duplication matrix (@'dup' k \<> 'vech' m == 'vec' m@, for symmetric m of 'dim' k)
-dup k = trans $ fromRows $ map f es
-  where
-    rs = zip [0..] (toRows (ident (k^(2::Int))))
-    es = [(i,j) | j <- [0..k-1], i <- [0..k-1], i>=j ]
-    f (i,j) | i == j = g (k*j + i)
-            | otherwise = g (k*j + i) + g (k*i + j)
-    g j = v
-      where
-        Just v = lookup j rs
-
-
-vtrans :: Element t => Int -> Matrix t -> Matrix t
--- ^ generalized \"vector\" transposition: @'vtrans' 1 == 'trans'@, and @'vtrans' ('rows' m) m == 'asColumn' ('vec' m)@
-vtrans p m | r == 0 = fromBlocks . map (map asColumn . takesV (replicate q p)) . toColumns $ m
-           | otherwise = error $ "vtrans " ++ show p ++ " of matrix with " ++ show (rows m) ++ " rows"
-  where
-    (q,r) = divMod (rows m) p
-
---------------------------------------------------------------------------------
-
 infixl 0 ~!~
 c ~!~ msg = when c (error msg)