statistics 0.16.2.0 → 0.16.2.1

raw patch · 7 files changed

+63/−28 lines, 7 files

Files

• Statistics/Test/StudentT.hs +4/−4
• changelog.md +7/−0
• statistics.cabal +10/−9
• tests/Tests/Correlation.hs +9/−5
• tests/Tests/Distribution.hs +2/−2
• tests/Tests/Matrix.hs +14/−4
• tests/Tests/Matrix/Types.hs +17/−4

@@ -134,16 +134,16 @@   -- Calculate T-statistics for paired sample-tStatisticsPaired :: (G.Vector v (Double, Double), G.Vector v Double)+tStatisticsPaired :: (G.Vector v (Double, Double))                   => v (Double, Double)                   -> (Double, Double) {-# INLINE tStatisticsPaired #-} tStatisticsPaired sample = (t, ndf)   where     -- t-statistics-    t = let d    = G.map (uncurry (-)) sample-            sumd = G.sum d-        in sumd / sqrt ((n * G.sum (G.map square d) - square sumd) / ndf)+    t = let d    = U.map (uncurry (-)) $ G.convert sample+            sumd = U.sum d+        in sumd / sqrt ((n * U.sum (U.map square d) - square sumd) / ndf)     -- degree of freedom     ndf = n - 1     n   = fromIntegral $ G.length sample

@@ -1,3 +1,10 @@+## Changes in 0.16.2.1++ * Unnecessary constraint dropped from `tStatisticsPaired`.++ * Compatibility with QuickCheck-2.14. Test suite doesn't fail every time.++ ## Changes in 0.16.2.0   * Improved precision for `complCumulative` for hypergeometric and binomial

@@ -1,5 +1,5 @@ name:           statistics-version:        0.16.2.0+version:        0.16.2.1 synopsis:       A library of statistical types, data, and functions description:   This library provides a number of common functions and types useful@@ -46,14 +46,15 @@   tests/utils/fftw.c  tested-with:-    GHC ==8.0.2-     || ==8.2.2-     || ==8.4.4-     || ==8.6.5-     || ==8.8.4-     || ==8.10.7-     || ==9.0.1-     || ==9.2.1+    GHC ==8.4.4+    GHC ==8.6.5+    GHC ==8.8.4+    GHC ==8.10.7+    GHC ==9.0.2+    GHC ==9.2.8+    GHC ==9.4.6+    GHC ==9.6.2+  library   default-language: Haskell2010

@@ -5,11 +5,11 @@  import Control.Arrow (Arrow(..)) import qualified Data.Vector as V+import Data.Maybe import Statistics.Correlation import Statistics.Correlation.Kendall-import Test.QuickCheck ((==>),Property,counterexample) import Test.Tasty-import Test.Tasty.QuickCheck+import Test.Tasty.QuickCheck hiding (sample) import Test.Tasty.HUnit  import Tests.ApproxEq@@ -34,15 +34,19 @@  testPearson :: [(Double,Double)] -> Property testPearson sample-  = (length sample > 1) ==> (exact ~= fast)+  = (length sample > 1 && isJust exact) ==> (case exact of+                                               Just e  -> e ~= fast+                                               Nothing -> property False+                                            )   where     (~=) = eql 1e-12     exact = exactPearson $ map (realToFrac *** realToFrac) sample     fast  = pearson $ V.fromList sample -exactPearson :: [(Rational,Rational)] -> Double+exactPearson :: [(Rational,Rational)] -> Maybe Double exactPearson sample-  = realToFrac cov / sqrt (realToFrac (varX * varY))+  | varX == 0 || varY == 0 = Nothing+  | otherwise              = Just $ realToFrac cov / sqrt (realToFrac (varX * varY))   where     (xs,ys) = unzip sample     n       = fromIntegral $ length sample

@@ -348,7 +348,7 @@   quantileIsInvCDF_enabled _ = False   -- We compute CDF and complement using same method so precision   -- should be very good here.-  prec_complementCDF _ = 2 * m_epsilon+  prec_complementCDF _ = 64 * m_epsilon  instance Param ChiSquared where   prec_quantile_CDF _ = (32,32)@@ -367,7 +367,7 @@   -- introduced by exp . logGamma.  This could only be fixed in   -- math-function by implementing gamma   prec_quantile_CDF _ = (24,24)-  prec_logDensity   _ = 64+  prec_logDensity   _ = 512 instance Param GeometricDistribution instance Param GeometricDistribution0 instance Param HypergeometricDistribution

@@ -5,7 +5,6 @@ import Test.Tasty (TestTree, testGroup) import Test.Tasty.QuickCheck (testProperty) import Test.QuickCheck-import Tests.ApproxEq (ApproxEq(..)) import Tests.Matrix.Types import qualified Data.Vector.Unboxed as U @@ -27,9 +26,20 @@ t_transpose m = U.concat (map (column n) [0..rows m-1]) === toVector m   where n = transpose m -t_qr :: Matrix -> Property-t_qr a = hasNaN p .||. eql 1e-10 a p-  where p = uncurry multiply (qr a)+t_qr :: Property+t_qr = property $ do+  a <- do (r,c) <- arbitrary+          fromMat <$> arbMatWith r c (fromIntegral <$> choose (-10, 10::Int))+  let (q,r) = qr a+      a'    = multiply q r+  pure $ counterexample ("A  = \n"++show a)+       $ counterexample ("A' = \n"++show a')+       $ counterexample ("Q  = \n"++show q)+       $ counterexample ("R  = \n"++show r)+       $ dimension a == dimension a'+      && ( hasNaN a'+        || and (zipWith (\x y -> abs (x - y) < 1e-12) (toList a) (toList a'))+         )  tests :: TestTree tests = testGroup "Matrix"

@@ -6,6 +6,8 @@       Mat(..)     , fromMat     , toMat+    , arbMat+    , arbMatWith     ) where  import Control.Monad (join)@@ -32,10 +34,21 @@     arbitrary = small $ join (arbMat <$> arbitrary <*> arbitrary)     shrink (Mat r c xs) = Mat r c <$> shrinkFixedList (shrinkFixedList shrink) xs -arbMat :: (Arbitrary a) => Positive (Small Int) -> Positive (Small Int)-       -> Gen (Mat a)-arbMat (Positive (Small r)) (Positive (Small c)) =-    Mat r c <$> vectorOf r (vector c)+arbMat+  :: (Arbitrary a)+  => Positive (Small Int)+  -> Positive (Small Int)+  -> Gen (Mat a)+arbMat r c = arbMatWith r c arbitrary++arbMatWith+  :: (Arbitrary a)+  => Positive (Small Int)+  -> Positive (Small Int)+  -> Gen a+  -> Gen (Mat a)+arbMatWith (Positive (Small r)) (Positive (Small c)) genA =+    Mat r c <$> vectorOf r (vectorOf c genA)  instance Arbitrary Matrix where     arbitrary = fromMat <$> arbitrary