1 files changed, 0 insertions, 136 deletions
diff --git a/lib/Numeric/HMatrix.hs b/lib/Numeric/HMatrix.hs
deleted file mode 100644
index 2e01454..0000000
--- a/lib/Numeric/HMatrix.hs
+++ /dev/null
@@ -1,136 +0,0 @@
-----------------------------------------------------------------------------
-{- |
-Module      :  Numeric.HMatrix
-Copyright   :  (c) Alberto Ruiz 2006-14
-License     :  GPL
-Maintainer  :  Alberto Ruiz
-Stability   :  provisional
-This module reexports the most common Linear Algebra functions.
-}
-----------------------------------------------------------------------------
-module Numeric.HMatrix (
-    -- * Basic types and data processing    
-    module Numeric.HMatrix.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, cdot, (<.>)
-) where
-import Numeric.HMatrix.Data
-import Numeric.Matrix()
-import Numeric.Vector()
-import Numeric.Container
-import Numeric.LinearAlgebra.Algorithms
-import Numeric.LinearAlgebra.Util

diff --git a/lib/Numeric/HMatrix.hs b/lib/Numeric/HMatrix.hs deleted file mode 100644 index 2e01454..0000000 --- a/lib/Numeric/HMatrix.hs +++ /dev/null
@@ -1,136 +0,0 @@
1	-----------------------------------------------------------------------------
2	{- \|
3	Module : Numeric.HMatrix
4	Copyright : (c) Alberto Ruiz 2006-14
5	License : GPL
6
7	Maintainer : Alberto Ruiz
8	Stability : provisional
9
10	This module reexports the most common Linear Algebra functions.
11
12	-}
13	-----------------------------------------------------------------------------
14	module Numeric.HMatrix (
15
16	-- * Basic types and data processing
17	module Numeric.HMatrix.Data,
18
19	-- \| The standard numeric classes are defined elementwise:
20	--
21	-- >>> fromList [1,2,3] * fromList [3,0,-2 :: Double]
22	-- fromList [3.0,0.0,-6.0]
23	--
24	-- >>> (3><3) [1..9] * ident 3 :: Matrix Double
25	-- (3><3)
26	-- [ 1.0, 0.0, 0.0
27	-- , 0.0, 5.0, 0.0
28	-- , 0.0, 0.0, 9.0 ]
29	--
30	-- In arithmetic operations single-element vectors and matrices
31	-- (created from numeric literals or using 'scalar') automatically
32	-- expand to match the dimensions of the other operand:
33	--
34	-- >>> 5 + 2*ident 3 :: Matrix Double
35	-- (3><3)
36	-- [ 7.0, 5.0, 5.0
37	-- , 5.0, 7.0, 5.0
38	-- , 5.0, 5.0, 7.0 ]
39	--
40
41	-- * Products
42	(×),
43
44	-- \| The matrix product is also implemented in the "Data.Monoid" instance for Matrix, where
45	-- single-element matrices (created from numeric literals or using 'scalar')
46	-- are used for scaling.
47	--
48	-- >>> let m = (2><3)[1..] :: Matrix Double
49	-- >>> m <> 2 <> diagl[0.5,1,0]
50	-- (2><3)
51	-- [ 1.0, 4.0, 0.0
52	-- , 4.0, 10.0, 0.0 ]
53	--
54	-- mconcat uses 'optimiseMult' to get the optimal association order.
55
56	(·), outer, kronecker, cross,
57	scale,
58	sumElements, prodElements, absSum,
59
60	-- * Linear Systems
61	(<\>),
62	linearSolve,
63	linearSolveLS,
64	linearSolveSVD,
65	luSolve,
66	cholSolve,
67
68	-- * Inverse and pseudoinverse
69	inv, pinv, pinvTol,
70
71	-- * Determinant and rank
72	rcond, rank, ranksv,
73	det, invlndet,
74
75	-- * Singular value decomposition
76	svd,
77	fullSVD,
78	thinSVD,
79	compactSVD,
80	singularValues,
81	leftSV, rightSV,
82
83	-- * Eigensystems
84	eig, eigSH, eigSH',
85	eigenvalues, eigenvaluesSH, eigenvaluesSH',
86	geigSH',
87
88	-- * QR
89	qr, rq, qrRaw, qrgr,
90
91	-- * Cholesky
92	chol, cholSH, mbCholSH,
93
94	-- * Hessenberg
95	hess,
96
97	-- * Schur
98	schur,
99
100	-- * LU
101	lu, luPacked,
102
103	-- * Matrix functions
104	expm,
105	sqrtm,
106	matFunc,
107
108	-- * Nullspace
109	nullspacePrec,
110	nullVector,
111	nullspaceSVD,
112	null1, null1sym,
113
114	orth,
115
116	-- * Norms
117	norm1, norm2, normInf, pnorm, NormType(..),
118
119	-- * Correlation and Convolution
120	corr, conv, corrMin, corr2, conv2,
121
122	-- * Random arrays
123	rand, randn, RandDist(..), randomVector, gaussianSample, uniformSample,
124
125	-- * Misc
126	meanCov, peps, relativeError, haussholder, optimiseMult, udot, cdot, (<.>)
127	) where
128
129	import Numeric.HMatrix.Data
130
131	import Numeric.Matrix()
132	import Numeric.Vector()
133	import Numeric.Container
134	import Numeric.LinearAlgebra.Algorithms
135	import Numeric.LinearAlgebra.Util
136