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-rw-r--r--packages/base/src/Numeric/LinearAlgebra/HMatrix.hs228
1 files changed, 5 insertions, 223 deletions
diff --git a/packages/base/src/Numeric/LinearAlgebra/HMatrix.hs b/packages/base/src/Numeric/LinearAlgebra/HMatrix.hs
index 677f9ee..8e67eb4 100644
--- a/packages/base/src/Numeric/LinearAlgebra/HMatrix.hs
+++ b/packages/base/src/Numeric/LinearAlgebra/HMatrix.hs
@@ -1,4 +1,4 @@
1----------------------------------------------------------------------------- 1--------------------------------------------------------------------------------
2{- | 2{- |
3Module : Numeric.LinearAlgebra.HMatrix 3Module : Numeric.LinearAlgebra.HMatrix
4Copyright : (c) Alberto Ruiz 2006-14 4Copyright : (c) Alberto Ruiz 2006-14
@@ -7,229 +7,11 @@ Maintainer : Alberto Ruiz
7Stability : provisional 7Stability : provisional
8 8
9-} 9-}
10----------------------------------------------------------------------------- 10--------------------------------------------------------------------------------
11module Numeric.LinearAlgebra.HMatrix (
12
13 -- * Basic types and data processing
14 module Numeric.LinearAlgebra.Data,
15
16 -- * Arithmetic and numeric classes
17 -- |
18 -- The standard numeric classes are defined elementwise:
19 --
20 -- >>> vector [1,2,3] * vector [3,0,-2]
21 -- fromList [3.0,0.0,-6.0]
22 --
23 -- >>> matrix 3 [1..9] * ident 3
24 -- (3><3)
25 -- [ 1.0, 0.0, 0.0
26 -- , 0.0, 5.0, 0.0
27 -- , 0.0, 0.0, 9.0 ]
28 --
29 -- In arithmetic operations single-element vectors and matrices
30 -- (created from numeric literals or using 'scalar') automatically
31 -- expand to match the dimensions of the other operand:
32 --
33 -- >>> 5 + 2*ident 3 :: Matrix Double
34 -- (3><3)
35 -- [ 7.0, 5.0, 5.0
36 -- , 5.0, 7.0, 5.0
37 -- , 5.0, 5.0, 7.0 ]
38 --
39 -- >>> matrix 3 [1..9] + matrix 1 [10,20,30]
40 -- (3><3)
41 -- [ 11.0, 12.0, 13.0
42 -- , 24.0, 25.0, 26.0
43 -- , 37.0, 38.0, 39.0 ]
44 --
45
46 -- * Products
47 -- ** dot
48 dot, (<·>),
49 -- ** matrix-vector
50 app, (#>), (!#>),
51 -- ** matrix-matrix
52 mul, (<>),
53 -- | The matrix product is also implemented in the "Data.Monoid" instance, where
54 -- single-element matrices (created from numeric literals or using 'scalar')
55 -- are used for scaling.
56 --
57 -- >>> import Data.Monoid as M
58 -- >>> let m = matrix 3 [1..6]
59 -- >>> m M.<> 2 M.<> diagl[0.5,1,0]
60 -- (2><3)
61 -- [ 1.0, 4.0, 0.0
62 -- , 4.0, 10.0, 0.0 ]
63 --
64 -- 'mconcat' uses 'optimiseMult' to get the optimal association order.
65
66
67 -- ** other
68 outer, kronecker, cross,
69 scale,
70 sumElements, prodElements,
71
72 -- * Linear Systems
73 (<\>),
74 linearSolve,
75 linearSolveLS,
76 linearSolveSVD,
77 luSolve,
78 cholSolve,
79 cgSolve,
80 cgSolve',
81
82 -- * Inverse and pseudoinverse
83 inv, pinv, pinvTol,
84
85 -- * Determinant and rank
86 rcond, rank,
87 det, invlndet,
88
89 -- * Norms
90 Normed(..),
91 norm_Frob, norm_nuclear,
92
93 -- * Nullspace and range
94 orth,
95 nullspace, null1, null1sym,
96
97 -- * SVD
98 svd,
99 thinSVD,
100 compactSVD,
101 singularValues,
102 leftSV, rightSV,
103
104 -- * Eigensystems
105 eig, eigSH, eigSH',
106 eigenvalues, eigenvaluesSH, eigenvaluesSH',
107 geigSH',
108
109 -- * QR
110 qr, rq, qrRaw, qrgr,
111
112 -- * Cholesky
113 chol, cholSH, mbCholSH,
114
115 -- * Hessenberg
116 hess,
117
118 -- * Schur
119 schur,
120
121 -- * LU
122 lu, luPacked,
123
124 -- * Matrix functions
125 expm,
126 sqrtm,
127 matFunc,
128
129 -- * Correlation and convolution
130 corr, conv, corrMin, corr2, conv2,
131
132 -- * Random arrays
133 11
134 Seed, RandDist(..), randomVector, rand, randn, gaussianSample, uniformSample, 12module Numeric.LinearAlgebra.HMatrix (
135 13 module Numeric.LinearAlgebra
136 -- * Misc
137 meanCov, rowOuters, peps, relativeError, haussholder, optimiseMult, udot, nullspaceSVD, orthSVD, ranksv,
138 ℝ,ℂ,iC,
139 -- * Auxiliary classes
140 Element, Container, Product, Numeric, LSDiv,
141 Complexable, RealElement,
142 RealOf, ComplexOf, SingleOf, DoubleOf,
143 IndexOf,
144 Field,
145-- Normed,
146 Transposable,
147 CGState(..),
148 Testable(..)
149) where 14) where
150 15
151import Numeric.LinearAlgebra.Data 16import Numeric.LinearAlgebra
152
153import Numeric.Matrix()
154import Numeric.Vector()
155import Data.Packed.Numeric hiding ((<>), mul)
156import Numeric.LinearAlgebra.Algorithms hiding (linearSolve,Normed,orth)
157import qualified Numeric.LinearAlgebra.Algorithms as A
158import Numeric.LinearAlgebra.Util
159import Numeric.LinearAlgebra.Random
160import Numeric.Sparse((!#>))
161import Numeric.LinearAlgebra.Util.CG
162
163{- | infix synonym of 'mul'
164
165>>> let a = (3><5) [1..]
166>>> a
167(3><5)
168 [ 1.0, 2.0, 3.0, 4.0, 5.0
169 , 6.0, 7.0, 8.0, 9.0, 10.0
170 , 11.0, 12.0, 13.0, 14.0, 15.0 ]
171
172>>> let b = (5><2) [1,3, 0,2, -1,5, 7,7, 6,0]
173>>> b
174(5><2)
175 [ 1.0, 3.0
176 , 0.0, 2.0
177 , -1.0, 5.0
178 , 7.0, 7.0
179 , 6.0, 0.0 ]
180
181>>> a <> b
182(3><2)
183 [ 56.0, 50.0
184 , 121.0, 135.0
185 , 186.0, 220.0 ]
186
187-}
188(<>) :: Numeric t => Matrix t -> Matrix t -> Matrix t
189(<>) = mXm
190infixr 8 <>
191
192-- | dense matrix product
193mul :: Numeric t => Matrix t -> Matrix t -> Matrix t
194mul = mXm
195
196
197{- | 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'.
198
199@
200a = (2><2)
201 [ 1.0, 2.0
202 , 3.0, 5.0 ]
203@
204
205@
206b = (2><3)
207 [ 6.0, 1.0, 10.0
208 , 15.0, 3.0, 26.0 ]
209@
210
211>>> linearSolve a b
212Just (2><3)
213 [ -1.4802973661668753e-15, 0.9999999999999997, 1.999999999999997
214 , 3.000000000000001, 1.6653345369377348e-16, 4.000000000000002 ]
215
216>>> let Just x = it
217>>> disp 5 x
2182x3
219-0.00000 1.00000 2.00000
220 3.00000 0.00000 4.00000
221
222>>> a <> x
223(2><3)
224 [ 6.0, 1.0, 10.0
225 , 15.0, 3.0, 26.0 ]
226
227-}
228linearSolve m b = A.mbLinearSolve m b
229
230-- | return an orthonormal basis of the null space of a matrix. See also 'nullspaceSVD'.
231nullspace m = nullspaceSVD (Left (1*eps)) m (rightSV m)
232
233-- | return an orthonormal basis of the range space of a matrix. See also 'orthSVD'.
234orth m = orthSVD (Left (1*eps)) m (leftSV m)
235 17