HNumeric 0.3.1.0 → 0.3.2.0

raw patch · 4 files changed

+116/−25 lines, 4 filesPVP: major bump suggested

API removals or changes: PVP suggests a major version bump

API changes (from Hackage documentation)

Files

• HNumeric.cabal +2/−2
• src/HNum/CSV.hs +7/−19
• src/HNum/Stats.hs +90/−4
• src/HNum/Vector.hs +17/−0

@@ -2,10 +2,10 @@ -- -- see: https://github.com/sol/hpack ----- hash: ce543fbe9d1a2354607564a7cc9b45578ee49880af97240e46e90d23d3a5579b+-- hash: c5d1ade7480449723b6215fe9d6fe260a29e127d440ff4511d5d3f926c680586  name:           HNumeric-version:        0.3.1.0+version:        0.3.2.0 synopsis:       Haskell Numeric Library with pure functionality, R & MATLAB Syntax. description:    Please see the README on GitHub at <https://github.com/Axect/HNumeric#readme> category:       HNum, library, Numeric, LinearAlgebra, Statistics, bsd3

@@ -12,31 +12,20 @@  -- | Type Aliases for convenience type Header = [String]-type Label = [String]  -- | DataFrame structure to write csv-data DataFrame a = DataFrame { header :: Header, dat :: Matrix a, lab :: Label} deriving (Show, Eq)+data DataFrame a = DataFrame { header :: Header, dat :: Matrix a} deriving (Show, Eq) --- | No label dataframe+-- | dataframe constructor dataframe :: Header -> Matrix a -> DataFrame a-dataframe h m | length h == row m = DataFrame h m (replicate n "value")+dataframe h m | length h == row m = DataFrame h m               | otherwise         = error "Length of Header != Length of Data"   where n = length m `div` length h --- | With label dataframe-dataframe' :: Header -> Matrix a -> Label -> DataFrame a-dataframe' h m l-  | length h == row m && row m == length l = DataFrame h m l-  | otherwise = error "Length of Header != Length of Data != Length of Label"---- | No label dataframe from Vectors+-- | dataframe from vectors fromVectors :: Header -> [Vector a] -> DataFrame a fromVectors h vs = dataframe h (matrix vs') where vs' = map toList vs --- | With label dataframe from Vectors-fromVectors' :: Header -> [Vector a] -> Label -> DataFrame a-fromVectors' h vs = dataframe' h (matrix vs') where vs' = map toList vs- instance Functor DataFrame where   fmap f df = df { dat = fmap f (dat df) } @@ -55,10 +44,9 @@   write title m = writeFile title (toString m)  instance CSVtize DataFrame where-  toString (DataFrame h m l) = h' ++ "\n" ++ m'-    where h' = cm h ++ ",label"-          m' = foldr ((\x y -> x ++ "\n" ++ y) . cm) "" $ matForm $ hcat (show <$> transpose m) l'-          l' = transpose $ matrix [l]+  toString (DataFrame h m) = h' ++ "\n" ++ m'+    where h' = cm h+          m' = toString (transpose m)   write title df = writeFile title (toString df)  

@@ -11,13 +11,13 @@ import           HNum.Vector import           Data.Random.Normal import           System.Random+import           HNum.CSV  -- | To contain coefficients of linear regression. type Coeff a = (a, a) -------------------------------------------------------- -- Basic Probability --------------------------------------------------------- -- | Factorial fac :: Integral a => a -> a fac 0 = 1@@ -36,38 +36,116 @@ c :: Integral a => a -> a -> a n `c` r = (n `p` r) `div` fac r -- -------------------------------------------------------- -- Basic Statistics -------------------------------------------------------- -- | Basic Statistics Class for Vector class VecOps v => Statistical v where+  -- | Sample Mean   mean :: Fractional a => v a -> a   -- | Single Valued covariance   cov' :: Floating a => v a -> v a -> a   -- | Covariance Matrix   cov :: Floating a => v a -> v a -> Matrix a+  -- | Sample Variance   var :: Floating a => v a -> a+  -- | Sample Standard deviation   std :: Floating a => v a -> a+  -- | Standard Error+  se :: Floating a => v a -> a   -- | Correlation Coefficient   cor :: Floating a => v a -> v a -> a+  -- | Median+  med :: (Ord a, Floating a) => v a -> a+  -- | Mode+  mode :: Eq a => v a -> a+  -- | Coefficient of Variation+  cv :: Floating a => v a -> a+  -- | Moment+  moment :: Floating a => a -> v a-> a+  -- | Skewness+  skew :: Floating a => v a -> a+  -- | Skewness 2+  skew' :: Floating a => v a -> a+  -- | kurtosis+  kurt :: Floating a => v a -> a  instance Statistical Vector where+  -- mean   mean x = sum x / fromIntegral (length x)+  -- cov'   cov' x y     | length x <= 1 || length y <= 1 = error "Samples are not enough"     | length x /= length y = error "Length is not same"     | otherwise = ((x .- mean x) .*. (y .- mean y)) / fromIntegral (length x - 1)+  -- cov   cov x y = matrix [[var x, cov' x y], [cov' y x, var y]]+  -- var   var v = cov' v v+  -- std   std = sqrt . var+  -- se+  se x = std x / sqrt (fromIntegral (length x))+  -- cor   cor x y = cov' x y / (std x * std y)+  -- med+  med x | even l    = ((qs !! (l'-1)) + (qs !! l')) / 2+        | otherwise = qs !! l'+    where l  = length x+          l' = l `div` 2+          qs = (toList . qsort) x+  -- mode+  mode x = v !! n+    where v  = toList x+          cx = map (`count` v) v+          m  = maximum cx+          n  = head $ dropWhile (\p -> cx !! p /= m) [0..]+  -- cv+  cv x = std x / mean x+  -- moment+  moment n x = sum ((x .- mean x) .^ n)+  -- skew+  skew x = (1 / fromIntegral l) * moment 3 x / std x ^ 3+    where l = length x+  skew' x = (fromIntegral l^2 / fromIntegral ((l-1) * (l-2))) * skew x+    where l = length x+  -- kurt+  kurt x = moment 4 x / (fromIntegral l * std x ** 4) - 3+    where l = length x  ----------------------------------------------------------- Distribution  +-- For IO --------------------------------------------------------+summary :: (Show a, Floating a) => DataFrame a -> IO ()+summary df = do+  putStrLn $ "Mean: " ++ show hm+  putStrLn $ "Var:  " ++ show hv+  putStrLn $ "Std:  " ++ show hs+ where+  h  = header df+  m  = matForm $ dat df+  ms = map (mean . vector) m+  vs = map (var . vector) m+  ss = map (std . vector) m+  hm = zip h ms+  hv = zip h vs+  hs = zip h ss +describe :: (Show a, Floating a, Ord a) => Vector a -> IO ()+describe v = do+  putStrLn $ "n:    " ++ show (length v)+  putStrLn $ "mean: " ++ show (mean v)+  putStrLn $ "std:  " ++ show (std v)+  putStrLn $ "med:  " ++ show (med v)+  putStrLn $ "mode: " ++ show (mode v)+  putStrLn $ "min:  " ++ show (minimum v)+  putStrLn $ "max:  " ++ show (maximum v)+  putStrLn $ "skew: " ++ show (skew v)+  putStrLn $ "kurt: " ++ show (kurt v)+  putStrLn $ "SE:   " ++ show (se v)+--------------------------------------------------------+-- Linear Regression+-------------------------------------------------------- -- | Least Square Method - (Intercept, Slope) lm :: Floating a => Vector a -> Vector a -> Coeff a lm x y = (my - b1 * mx, b1)@@ -87,3 +165,11 @@ -- | Relative Standard Error rse :: Floating a => Vector a -> Vector a -> a rse x y = sqrt (1 / fromIntegral (length x - 2) * rss x y)++--------------------------------------------------------+-- Backend Functions+--------------------------------------------------------++-- | Count Elements+count :: Eq a => a -> [a] -> Int+count p v = length (filter (== p) v)

@@ -20,6 +20,9 @@ vector :: [a] -> Vector a vector = Vector +vec :: [a] -> Vector a+vec = Vector+ -- Instance Section instance Functor Vector where   fmap f (Vector x) = Vector (fmap f x)@@ -238,6 +241,20 @@ (.:) :: Vector a -> Matrix a -> Matrix a v .: m | length v == col m = matrix (toList v : matForm m)        | otherwise         = error "Can't insert length(Vector) /= col(Matrix)"++---------------------------------------------------+-- Sort+---------------------------------------------------+-- | Quick Sort+qsort :: Ord a => Vector a -> Vector a+qsort (Vector []) = vec []+qsort (Vector (x : xs)) =+  (qsort . vec) [ y | y <- xs, y <= x ] `hcat` vec [x] `hcat` (qsort . vec)+    [ y | y <- xs, y > x ]++-- | Merge Sort+--msort :: Ord a => Vector a -> Vector a+--msort   --------------------------------------------------- -- Backend Functions (Do not Understand)