Numeric.Container and Numeric.LinearAlgebra moved to base

1 files changed, 84 insertions, 0 deletions

diff --git a/packages/hmatrix/src/Numeric/GSL/Random.hs b/packages/hmatrix/src/Numeric/GSL/Random.hs
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+-----------------------------------------------------------------------------
+-- |
+-- Module      :  Numeric.GSL.Random
+-- Copyright   :  (c) Alberto Ruiz 2009-14
+-- License     :  GPL
+--
+-- Maintainer  :  Alberto Ruiz
+-- Stability   :  provisional
+--
+-- Random vectors and matrices.
+--
+-----------------------------------------------------------------------------
+
+module Numeric.GSL.Random (
+    Seed,
+    RandDist(..),
+    randomVector,
+    gaussianSample,
+    uniformSample,
+    rand, randn
+) where
+
+import Numeric.GSL.Vector
+import Numeric.Container
+import Numeric.LinearAlgebra(Seed,RandDist(..),cholSH)
+import System.Random(randomIO)
+
+
+
+
+-- | Obtains a matrix whose rows are pseudorandom samples from a multivariate
+-- Gaussian distribution.
+gaussianSample :: Seed
+               -> Int -- ^ number of rows
+               -> Vector Double -- ^ mean vector
+               -> Matrix Double -- ^ covariance matrix
+               -> Matrix Double -- ^ result
+gaussianSample seed n med cov = m where
+    c = dim med
+    meds = konst' 1 n `outer` med
+    rs = reshape c $ randomVector seed Gaussian (c * n)
+    m = rs `mXm` cholSH cov `add` meds
+
+-- | Obtains a matrix whose rows are pseudorandom samples from a multivariate
+-- uniform distribution.
+uniformSample :: Seed
+               -> Int -- ^ number of rows
+               -> [(Double,Double)] -- ^ ranges for each column
+               -> Matrix Double -- ^ result
+uniformSample seed n rgs = m where
+    (as,bs) = unzip rgs
+    a = fromList as
+    cs = zipWith subtract as bs
+    d = dim a
+    dat = toRows $ reshape n $ randomVector seed Uniform (n*d)
+    am = konst' 1 n `outer` a
+    m = fromColumns (zipWith scale cs dat) `add` am
+
+-- | pseudorandom matrix with uniform elements between 0 and 1
+randm :: RandDist
+     -> Int -- ^ rows
+     -> Int -- ^ columns
+     -> IO (Matrix Double)
+randm d r c = do
+    seed <- randomIO
+    return (reshape c $ randomVector seed d (r*c))
+
+-- | pseudorandom matrix with uniform elements between 0 and 1
+rand :: Int -> Int -> IO (Matrix Double)
+rand = randm Uniform
+
+{- | pseudorandom matrix with normal elements
+
+>>> x <- randn 3 5
+>>> disp 3 x
+3x5
+0.386  -1.141   0.491  -0.510   1.512
+0.069  -0.919   1.022  -0.181   0.745
+0.313  -0.670  -0.097  -1.575  -0.583
+
+-}
+randn :: Int -> Int -> IO (Matrix Double)
+randn = randm Gaussian
+