1 files changed, 222 insertions, 9 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)