uniformSample

2 files changed, 25 insertions, 3 deletions

diff --git a/lib/Data/Packed/Random.hs b/lib/Data/Packed/Random.hs
index 56d038e..a6145be 100644
--- a/lib/Data/Packed/Random.hs
+++ b/lib/Data/Packed/Random.hs
@@ -15,6 +15,7 @@ module Data.Packed.Random (
     RandDist(..),
     randomVector,
     gaussianSample,
+    uniformSample,
     meanCov,
 ) where
 
@@ -24,7 +25,7 @@ import Numeric.LinearAlgebra.Algorithms
 import Numeric.LinearAlgebra.Instances()
 import Numeric.LinearAlgebra.Interface
 
--- | Obtains a matrix whose rows are pseudorandom samples from a multivariante
+-- | Obtains a matrix whose rows are pseudorandom samples from a multivariate
 -- Gaussian distribution.
 gaussianSample :: Int -- ^ seed
                -> Int -- ^ number of rows
@@ -39,6 +40,22 @@ gaussianSample seed n med cov = m where
     ds = sqrt (abs l)
     m = rs <> (diag ds <> trans v) + meds
 
+-- | Obtains a matrix whose rows are pseudorandom samples from a multivariate
+-- uniform distribution.
+uniformSample :: Int -- ^ 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
+    b = fromList bs
+    cs = zipWith subtract as bs
+    d = dim a
+    dat = toRows $ reshape n $ randomVector seed Uniform (n*d)
+    am = constant 1 n `outer` a
+    m = fromColumns (zipWith (.*) cs dat) + am
+
 ------------ utilities -------------------------------
 
 -- | Compute mean vector and covariance matrix of the rows of a matrix.
diff --git a/lib/Numeric/LinearAlgebra/Tests.hs b/lib/Numeric/LinearAlgebra/Tests.hs
index 097756e..4495396 100644
--- a/lib/Numeric/LinearAlgebra/Tests.hs
+++ b/lib/Numeric/LinearAlgebra/Tests.hs
@@ -131,7 +131,7 @@ rootFindingTest = TestList [ utest "root Hybrids" (fst sol1 ~~ [1,1])
 
 ---------------------------------------------------------------------
 
-randomTest = c :~1~: snd (meanCov dat) where
+randomTestGaussian = c :~1~: snd (meanCov dat) where
     a = (3><3) [1,2,3,
                 2,4,0,
                -2,2,1]
@@ -139,6 +139,10 @@ randomTest = c :~1~: snd (meanCov dat) where
     c = a <> trans a
     dat = gaussianSample 7 (10^6) m c
 
+randomTestUniform = c :~1~: snd (meanCov dat) where
+    c = diag $ 3 |> map ((/12).(^2)) [1,2,3]
+    dat = uniformSample 7 (10^6) [(0,1),(1,3),(3,6)]
+
 ---------------------------------------------------------------------
 
 rot :: Double -> Matrix Double
@@ -237,7 +241,8 @@ runTests n = do
         , utest "polySolve" (polySolveProp [1,2,3,4])
         , minimizationTest
         , rootFindingTest
-        , utest "random" randomTest
+        , utest "randomGaussian" randomTestGaussian
+        , utest "randomUniform" randomTestUniform
         ]
     return ()