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+-----------------------------------------------------------------------------
+{- |
+Module      :  Numeric.LinearAlgebra
+Copyright   :  (c) Alberto Ruiz 2006-14
+License     :  BSD3
+Maintainer  :  Alberto Ruiz
+Stability   :  provisional
+
+This module reexports the most common Linear Algebra functions.
+
+-}
+-----------------------------------------------------------------------------
+module Numeric.LinearAlgebra.Base (
+
+    -- * Basic types and data processing    
+    module Numeric.LinearAlgebra.Data,
+    
+    -- | 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 ]
+    --
+
+    -- * Products
+    (<.>),
+    
+    -- | The matrix product is also implemented in the "Data.Monoid" instance for Matrix, 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.
+ 
+    (◇),
+    outer, kronecker, cross,
+    scale,
+    sumElements, prodElements, absSum,
+    
+    -- * Linear Systems
+    (<\>),
+    linearSolve,
+    linearSolveLS,
+    linearSolveSVD,
+    luSolve,
+    cholSolve,
+    
+    -- * 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,
+
+    -- * Nullspace
+    nullspacePrec,
+    nullVector,
+    nullspaceSVD,
+    null1, null1sym,
+    
+    orth,
+
+    -- * Norms
+    norm1, norm2, normInf, pnorm, NormType(..),
+
+    -- * Correlation and Convolution
+    corr, conv, corrMin, corr2, conv2,
+
+    -- * Random arrays
+
+    -- |    rand, randn, RandDist(..), randomVector, gaussianSample, uniformSample
+    
+    -- * Misc
+    meanCov, peps, relativeError, haussholder, optimiseMult, udot
+) where
+
+import Numeric.LinearAlgebra.Data
+
+import Numeric.Matrix()
+import Numeric.Vector()
+import Numeric.Container
+import Numeric.LinearAlgebra.Algorithms
+import Numeric.LinearAlgebra.Util
+
+
+