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authorAlberto Ruiz <aruiz@um.es>2014-05-20 19:32:19 +0200
committerAlberto Ruiz <aruiz@um.es>2014-05-20 19:32:19 +0200
commit9412ef25f2a9d6f6ca233ef123a01c3f4145ffa4 (patch)
treeb5c7ecd0534d0dc34242e53a3e66b87fc2ec0b0f /packages/base/src/Numeric/LinearAlgebra/Random.hs
parentd0fc6c7192badfa6f03baf0e02e0cf2a73c3906b (diff)
random numbers in base
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1-----------------------------------------------------------------------------
2-- |
3-- Module : Numeric.LinearAlgebra.Random
4-- Copyright : (c) Alberto Ruiz 2009-14
5-- License : BSD3
6-- Maintainer : Alberto Ruiz
7-- Stability : provisional
8--
9-- Random vectors and matrices.
10--
11-----------------------------------------------------------------------------
12
13module Numeric.LinearAlgebra.Random (
14 Seed,
15 RandDist(..),
16 randomVector,
17 gaussianSample,
18 uniformSample,
19 rand, randn
20) where
21
22import Numeric.Vectorized
23import Data.Packed.Numeric
24import Numeric.LinearAlgebra.Algorithms
25import System.Random(randomIO)
26
27
28-- | Obtains a matrix whose rows are pseudorandom samples from a multivariate
29-- Gaussian distribution.
30gaussianSample :: Seed
31 -> Int -- ^ number of rows
32 -> Vector Double -- ^ mean vector
33 -> Matrix Double -- ^ covariance matrix
34 -> Matrix Double -- ^ result
35gaussianSample seed n med cov = m where
36 c = dim med
37 meds = konst' 1 n `outer` med
38 rs = reshape c $ randomVector seed Gaussian (c * n)
39 m = rs `mXm` cholSH cov `add` meds
40
41-- | Obtains a matrix whose rows are pseudorandom samples from a multivariate
42-- uniform distribution.
43uniformSample :: Seed
44 -> Int -- ^ number of rows
45 -> [(Double,Double)] -- ^ ranges for each column
46 -> Matrix Double -- ^ result
47uniformSample seed n rgs = m where
48 (as,bs) = unzip rgs
49 a = fromList as
50 cs = zipWith subtract as bs
51 d = dim a
52 dat = toRows $ reshape n $ randomVector seed Uniform (n*d)
53 am = konst' 1 n `outer` a
54 m = fromColumns (zipWith scale cs dat) `add` am
55
56-- | pseudorandom matrix with uniform elements between 0 and 1
57randm :: RandDist
58 -> Int -- ^ rows
59 -> Int -- ^ columns
60 -> IO (Matrix Double)
61randm d r c = do
62 seed <- randomIO
63 return (reshape c $ randomVector seed d (r*c))
64
65-- | pseudorandom matrix with uniform elements between 0 and 1
66rand :: Int -> Int -> IO (Matrix Double)
67rand = randm Uniform
68
69{- | pseudorandom matrix with normal elements
70
71>>> disp 3 =<< randn 3 5
723x5
730.386 -1.141 0.491 -0.510 1.512
740.069 -0.919 1.022 -0.181 0.745
750.313 -0.670 -0.097 -1.575 -0.583
76
77-}
78randn :: Int -> Int -> IO (Matrix Double)
79randn = randm Gaussian
80