From 13856329ed09cd9f70f03363895545a6ca83374c Mon Sep 17 00:00:00 2001
From: Alberto Ruiz <aruiz@um.es>
Date: Fri, 5 Jun 2015 16:43:01 +0200
Subject: move random

---
 packages/base/src/Numeric/LinearAlgebra/Random.hs | 81 -----------------------
 1 file changed, 81 deletions(-)
 delete mode 100644 packages/base/src/Numeric/LinearAlgebra/Random.hs

(limited to 'packages/base/src/Numeric')

diff --git a/packages/base/src/Numeric/LinearAlgebra/Random.hs b/packages/base/src/Numeric/LinearAlgebra/Random.hs
deleted file mode 100644
index b66988e..0000000
--- a/packages/base/src/Numeric/LinearAlgebra/Random.hs
+++ /dev/null
@@ -1,81 +0,0 @@
------------------------------------------------------------------------------
--- |
--- Module      :  Numeric.LinearAlgebra.Random
--- Copyright   :  (c) Alberto Ruiz 2009-14
--- License     :  BSD3
--- Maintainer  :  Alberto Ruiz
--- Stability   :  provisional
---
--- Random vectors and matrices.
---
------------------------------------------------------------------------------
-
-module Numeric.LinearAlgebra.Random (
-    Seed,
-    RandDist(..),
-    randomVector,
-    gaussianSample,
-    uniformSample,
-    rand, randn
-) where
-
-import Numeric.Vectorized
-import Data.Packed
-import Data.Packed.Internal.Numeric
-import Numeric.LinearAlgebra.Algorithms
-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
-
->>> disp 3 =<< randn 3 5
-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
-
-- 
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