hstatistics-0.1.0.2: lib/Numeric/GSL/Distribution/Continuous.hs
{-# OPTIONS_GHC -fglasgow-exts #-}
-----------------------------------------------------------------------------
-- |
-- Module : Numeric.GSL.Distribution.Continuous
-- Copyright : (c) Alexander Vivian Hugh McPhail 2010
-- License : GPL-style
--
-- Maintainer : haskell.vivian.mcphail <at> gmail <dot> com
-- Stability : provisional
-- Portability : uses ffi
--
-- GSL continuous random distribution functions
--
-----------------------------------------------------------------------------
module Numeric.GSL.Distribution.Continuous (
ZeroParamDist(..), OneParamDist(..)
, TwoParamDist(..), ThreeParamDist(..)
, MultiParamDist(..)
, BivariateDist(..)
, DistFunc(..)
, random_0p, density_0p
, random_1p, density_1p
, random_2p, density_2p
, random_3p, density_3p
, random_mp, density_mp
, random_biv, density_biv
, spherical_vector
) where
-----------------------------------------------------------------------------
import Data.Packed.Vector
--import Data.Packed.Matrix hiding(toLists)
import Data.Packed.Development
--import Numeric.LinearAlgebra.Linear
import Control.Monad(when)
import Foreign hiding(shift)
import Foreign.ForeignPtr
--import Foreign.Marshal.Alloc(alloca)
import Foreign.C.Types(CInt,CChar)
import Foreign.C.String(newCString,peekCString)
--import GHC.ForeignPtr (mallocPlainForeignPtrBytes)
--import GHC.Base
--import GHC.IOBase
--import Prelude hiding(reverse)
import Numeric.GSL.Distribution.Common
-----------------------------------------------------------------------------
data ZeroParamDist = Landau
deriving Enum
data OneParamDist = Gaussian -- ^ standard deviation
| Exponential -- ^ mean
| Laplace -- ^ width
| Cauchy -- ^ scale
| Rayleigh -- ^ standard deviation
| ChiSq -- ^ degrees of freedom
| TDist -- ^ degrees of freedom
| Logistic -- ^ scale
deriving Enum
data TwoParamDist = GaussianTail -- ^ limit, standard deviation
| ExpPower -- ^ scale, exponent
| RayleighTail -- ^ lower limit, standard deviation
| Levy -- ^ scale, exponent
| Gamma -- ^ par1, par2
| Uniform -- ^ lower, upper
| Lognormal -- ^ offset, standard deviation
| FDist -- ^ degrees of freedom, degrees of freedom
| Beta -- ^ parameter a, parameter b
| Pareto -- ^ exponent, scale
| Weibull -- ^ scale, exponent
| GumbellI -- ^ A, B
| GumbellII -- ^ A, B
deriving Enum
data ThreeParamDist = LevySkew -- ^ scale, exponent, skewness
deriving Enum
data MultiParamDist = Dirichlet -- ^ size, alpha
deriving Enum
data BivariateDist = BiGaussian -- ^ standard deviation, standard deviation, correlation coefficient
deriving Enum
-----------------------------------------------------------------------------
fromei x = fromIntegral (fromEnum x) :: CInt
-----------------------------------------------------------------------------
-- | draw a sample from a zero parameter distribution
random_0p :: ZeroParamDist -- ^ distribution type
-> Int -- ^ random seed
-> Double -- ^ result
random_0p d s = unsafePerformIO $ distribution_random_zero_param (fromIntegral s) (fromei d)
-- | probability of a variate take a value outside the argument
density_0p :: ZeroParamDist -- ^ density type
-> DistFunc -- ^ distribution function type
-> Double -- ^ value
-> Double -- ^ result
density_0p d f x = unsafePerformIO $ do
case d of
Landau -> density_only f d x
where density_only f' d' x' = if f' /= Density
then error "distribution has no CDF"
else distribution_dist_zero_param (fromei f') (fromei d') x'
foreign import ccall "distribution-aux.h random0" distribution_random_zero_param :: CInt -> CInt -> IO Double
foreign import ccall "distribution-aux.h random0_dist" distribution_dist_zero_param :: CInt -> CInt -> Double -> IO Double
-----------------------------------------------------------------------------
-- | draw a sample from a one parameter distribution
random_1p :: OneParamDist -- ^ distribution type
-> Int -- ^ random seed
-> Double -- ^ parameter
-> Double -- ^ result
random_1p d s p = unsafePerformIO $
alloca $ \r -> do
check "random1p" $ distribution_random_one_param (fromIntegral s) (fromei d) p r
r' <- peek r
return r'
-- | probability of a variate take a value outside the argument
density_1p :: OneParamDist -- ^ density type
-> DistFunc -- ^ distribution function type
-> Double -- ^ parameter
-> Double -- ^ value
-> Double -- ^ result
density_1p d f p x = unsafePerformIO $ distribution_dist_one_param (fromei f) (fromei d) x p
foreign import ccall "distribution-aux.h random1" distribution_random_one_param :: CInt -> CInt -> Double -> Ptr Double -> IO CInt
foreign import ccall "distribution-aux.h random1_dist" distribution_dist_one_param :: CInt -> CInt -> Double -> Double -> IO Double
-----------------------------------------------------------------------------
-- | draw a sample from a two parameter distribution
random_2p :: TwoParamDist -- ^ distribution type
-> Int -- ^ random seed
-> Double -- ^ parameter 1
-> Double -- ^ parameter 2
-> Double -- ^ result
random_2p d s p1 p2 = unsafePerformIO $
alloca $ \r -> do
check "random2p" $ distribution_random_two_param (fromIntegral s) (fromei d) p1 p2 r
r' <- peek r
return r'
-- | probability of a variate take a value outside the argument
density_2p :: TwoParamDist -- ^ density type
-> DistFunc -- ^ distribution function type
-> Double -- ^ parameter 1
-> Double -- ^ parameter 2
-> Double -- ^ value
-> Double -- ^ result
density_2p d f p1 p2 x = unsafePerformIO $ do
case d of
GaussianTail -> density_only f d p1 p2 x
ExpPower -> no_inverse f d p1 p2 x
RayleighTail -> density_only f d p1 p2 x
Levy -> error "no PDF or CDF for Levy"
_ -> distribution_dist_two_param (fromei f) (fromei d) x p1 p2
where density_only f' d' p1' p2' x' = if f' /= Density
then error "distribution has no CDF"
else distribution_dist_two_param (fromei f') (fromei d') x' p1' p2'
no_inverse f' d' p1' p2' x' = if (f' == LowInv || f' == UppInv)
then error "distribution has no inverse CDF"
else distribution_dist_two_param (fromei f') (fromei d') x' p1' p2'
foreign import ccall "distribution-aux.h random2" distribution_random_two_param :: CInt -> CInt -> Double -> Double -> Ptr Double -> IO CInt
foreign import ccall "distribution-aux.h random2_dist" distribution_dist_two_param :: CInt -> CInt -> Double -> Double -> Double -> IO Double
-----------------------------------------------------------------------------
-- | draw a sample from a three parameter distribution
random_3p :: ThreeParamDist -- ^ distribution type
-> Int -- ^ random seed
-> Double -- ^ parameter 1
-> Double -- ^ parameter 2
-> Double -- ^ parameter 3
-> Double -- ^ result
random_3p d s p1 p2 p3 = unsafePerformIO $
alloca $ \r -> do
check "random_3p" $ distribution_random_three_param (fromIntegral s) (fromei d) p1 p2 p3 r
r' <- peek r
return r'
-- | probability of a variate take a value outside the argument
density_3p :: ThreeParamDist -- ^ density type
-> DistFunc -- ^ distribution function type
-> Double -- ^ parameter 1
-> Double -- ^ parameter 2
-> Double -- ^ parameter 3
-> Double -- ^ value
-> Double -- ^ result
density_3p d f p1 p2 p3 x = unsafePerformIO $ do
case d of
LevySkew -> error "Levy skew has no PDF or CDF"
where density_only f' d' p1' p2' p3' x' = if f' /= Density
then error "distribution has no CDF"
else distribution_dist_three_param (fromei f') (fromei d') x' p1' p2' p3'
foreign import ccall "distribution-aux.h random3" distribution_random_three_param :: CInt -> CInt -> Double -> Double -> Double -> Ptr Double -> IO CInt
foreign import ccall "distribution-aux.h random3_dist" distribution_dist_three_param :: CInt -> CInt -> Double -> Double -> Double -> Double -> IO Double
-----------------------------------------------------------------------------
-- | draw a sample from a three parameter distribution
random_mp :: MultiParamDist -- ^ distribution type
-> Int -- ^ random seed
-> Vector Double -- ^ parameters
-> Vector Double -- ^ result
random_mp d s p = unsafePerformIO $ do
r <- createVector $ dim p
app2 (distribution_random_multi_param (fromIntegral s) (fromei d)) vec p vec r "random_mp"
return r
-- | probability of a variate take a value outside the argument
density_mp :: MultiParamDist -- ^ density type
-> DistFunc -- ^ distribution function type
-> Vector Double -- ^ parameters
-> Vector Double -- ^ values
-> Double -- ^ result
density_mp d f p q = unsafePerformIO $ do
case d of
Dirichlet -> density_only f d p q
where density_only f' d' p' q' = if f' /= Density
then error "distribution has no CDF"
else alloca $ \r -> do
app2 (distribution_dist_multi_param (fromei f') (fromei d') r) vec p vec q "density_mp"
r' <- peek r
return r'
foreign import ccall "distribution-aux.h random_mp" distribution_random_multi_param :: CInt -> CInt -> CInt -> Ptr Double -> CInt -> Ptr Double -> IO CInt
foreign import ccall "distribution-aux.h random_mm_dist" distribution_dist_multi_param :: CInt -> CInt -> Ptr Double -> CInt -> Ptr Double -> CInt -> Ptr Double -> IO CInt
-----------------------------------------------------------------------------
-- | draw a sample from a bivariate distribution
random_biv :: BivariateDist -- ^ distribution type
-> Int -- ^ random seed
-> Double -- ^ parameter 1
-> Double -- ^ parameter 2
-> Double -- ^ parameter 3
-> (Double,Double) -- ^ result
random_biv d s p1 p2 p3 = unsafePerformIO $
alloca $ \r1 ->
alloca $ \r2 -> do
distribution_random_bivariate (fromIntegral s) (fromei d) p1 p2 p3 r1 r2
r1' <- peek r1
r2' <- peek r2
return (r1',r2')
-- | probability of a variate take a value outside the argument
density_biv :: BivariateDist -- ^ density type
-> DistFunc -- ^ distribution function type
-> Double -- ^ parameter 1
-> Double -- ^ parameter 2
-> Double -- ^ parameter 3
-> (Double,Double) -- ^ value
-> Double -- ^ result
density_biv d f p1 p2 p3 (x,y) = unsafePerformIO $ do
case d of
BiGaussian -> density_only f d p1 p2 p3 x y
where density_only f' d' p1' p2' p3' x' y' = if f' /= Density
then error "distribution has no CDF"
else distribution_dist_bivariate (fromei f') (fromei d') x' y' p1' p2' p3'
foreign import ccall "distribution-aux.h random_biv" distribution_random_bivariate :: CInt -> CInt -> Double -> Double -> Double -> Ptr Double -> Ptr Double -> IO ()
foreign import ccall "distribution-aux.h random_biv_dist" distribution_dist_bivariate :: CInt -> CInt -> Double -> Double -> Double -> Double -> Double -> IO Double
-----------------------------------------------------------------------------
-- | returns a normalised random direction vector from a multivariate gaussian distribution
spherical_vector :: Int -- ^ seed
-> Int -- ^ vector size
-> Vector Double -- result
spherical_vector s vs = unsafePerformIO $ do
r <- createVector vs
app1 (distribution_spherical_vector (fromIntegral s)) vec r "spherical_vector"
return r
foreign import ccall "distribution-aux.h random_vector" distribution_spherical_vector :: CInt -> CInt -> Ptr Double -> IO CInt
-----------------------------------------------------------------------------
-----------------------------------------------------------------------------
-----------------------------------------------------------------------------