----------------------------------------------------------------------------- -- | -- Module : Numeric.LinearAlgebra.Random -- Copyright : (c) Alberto Ruiz 2009-14 -- License : BSD3 -- Maintainer : Alberto Ruiz -- Stability : provisional -- -- Random vectors and matrices. -- ----------------------------------------------------------------------------- module Internal.Random ( Seed, RandDist(..), randomVector, gaussianSample, uniformSample, rand, randn ) where import Internal.Vectorized import Internal.Vector import Internal.Matrix import Internal.Numeric import Internal.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 -> Herm 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` chol 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