1 files changed, 8 insertions, 141 deletions

diff --git a/packages/base/src/Numeric/LinearAlgebra.hs b/packages/base/src/Numeric/LinearAlgebra.hs
index 242122f..ad315e4 100644
--- a/packages/base/src/Numeric/LinearAlgebra.hs
+++ b/packages/base/src/Numeric/LinearAlgebra.hs
@@ -1,4 +1,4 @@
------------------------------------------------------------------------------
+--------------------------------------------------------------------------------
 {- |
 Module      :  Numeric.LinearAlgebra
 Copyright   :  (c) Alberto Ruiz 2006-14
@@ -7,149 +7,16 @@ Maintainer  :  Alberto Ruiz
 Stability   :  provisional
 
 -}
------------------------------------------------------------------------------
-module Numeric.LinearAlgebra (
-
-    -- * Basic types and data processing    
-    module Numeric.LinearAlgebra.Data,
-    
-    -- * Arithmetic and numeric classes
-    -- |
-    -- The standard numeric classes are defined elementwise:
-    --
-    -- >>> fromList [1,2,3] * fromList [3,0,-2 :: Double]
-    -- fromList [3.0,0.0,-6.0]
-    -- 
-    -- >>> (3><3) [1..9] * ident 3 :: Matrix Double
-    -- (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 product
-    (<.>),
-
-    -- | The overloaded multiplication operators may need type annotations to remove
-    -- ambiguity. In those cases we can also use the specific functions 'mXm', 'mXv', and 'dot'.
-    --
-    -- The matrix x 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.
-    --
-    -- >>> let m = (2><3)[1..] :: Matrix Double
-    -- >>> m <> 2 <> 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 products
-    outer, kronecker, cross,
-    scale,
-    sumElements, prodElements, absSum,
-    
-    -- * Linear Systems
-    (<\>),
-    linearSolve,
-    linearSolveLS,
-    linearSolveSVD,
-    luSolve,
-    cholSolve,
-    cgSolve,
-    cgSolve',
-    
-    -- * Inverse and pseudoinverse
-    inv, pinv, pinvTol,
-
-    -- * Determinant and rank
-    rcond, rank, ranksv, 
-    det, invlndet,
-    
-    -- * Singular value decomposition
-    svd,
-    fullSVD,
-    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,
+--------------------------------------------------------------------------------
+{-# OPTIONS_HADDOCK hide #-}
 
-    -- * Nullspace
-    nullspacePrec,
-    nullVector,
-    nullspaceSVD,
-    null1, null1sym,
-    
-    orth,
-
-    -- * Norms
-    norm1, norm2, normInf, pnorm, NormType(..),
-
-    -- * Correlation and convolution
-    corr, conv, corrMin, corr2, conv2,
-
-    -- * Random arrays
-
-    RandDist(..), randomVector, rand, randn, gaussianSample, uniformSample,
-    
-    -- * Misc
-    meanCov, peps, relativeError, haussholder, optimiseMult, dot, udot, mXm, mXv, smXv, (<>), (◇), Seed, checkT,
-    -- * Auxiliary classes
-    Element, Container, Product, Contraction, LSDiv,
-    Complexable(), RealElement(),
-    RealOf, ComplexOf, SingleOf, DoubleOf,
-    IndexOf,
-    Field, Normed,
-    CGMat, Transposable,
-    R,V
+module Numeric.LinearAlgebra (
+    module Numeric.Container,
+    module Numeric.LinearAlgebra.Algorithms
 ) where
 
-import Numeric.LinearAlgebra.Data
-
-import Numeric.Matrix()
-import Numeric.Vector()
 import Numeric.Container
 import Numeric.LinearAlgebra.Algorithms
-import Numeric.LinearAlgebra.Util
-import Numeric.LinearAlgebra.Random
-import Numeric.Sparse(smXv)
-import Numeric.LinearAlgebra.Util.CG
-
+import Numeric.Matrix()
+import Numeric.Vector()