src/Gargantext/Prelude.hs

   1 {-# OPTIONS_GHC -fno-warn-name-shadowing #-}
   2 {-# OPTIONS_GHC -fno-warn-type-defaults  #-}
   3 {-# LANGUAGE     NoImplicitPrelude       #-}
   4
   5 {-
   6 TODO: import head impossible from Protolude: why ?
   7 -}
   8
   9 module Gargantext.Prelude
  10   ( module Gargantext.Prelude
  11   , module Protolude
  12   , headMay
  13   , module Text.Show
  14   , module Text.Read
  15   )
  16   where
  17
  18 import Data.Maybe (isJust, fromJust)
  19 import Protolude ( Bool(True, False), Int, Double, Integer
  20                  , Fractional, Num, Maybe(Just,Nothing)
  21                  , Floating, Char, IO
  22                  , pure, (<$>), panic
  23                  , head, flip
  24                  , Ord, Integral, Foldable, RealFrac, Monad, filter
  25                  , reverse, map, zip, drop, take, zipWith
  26                  , sum, fromIntegral, length, fmap
  27                  , takeWhile, sqrt, undefined, identity
  28                  , abs, maximum, minimum, return, snd, truncate
  29                  , (+), (*), (/), (-), (.), ($), (**), (^), (<), (>)
  30                  , Eq, (==), (>=), (<=), (<>)
  31                  , (&&), (||), not
  32                  , fst, snd, toS
  33                  )
  34
  35 -- TODO import functions optimized in Utils.Count
  36 -- import Protolude hiding (head, last, all, any, sum, product, length)
  37 -- import Gargantext.Utils.Count
  38 import qualified Data.List     as L hiding (head, sum)
  39 import qualified Control.Monad as M
  40 import qualified Data.Map as Map
  41 import Data.Map.Strict (insertWith)
  42 import qualified Data.Vector as V
  43 import Safe (headMay)
  44 import Text.Show (Show(), show)
  45 import Text.Read (Read())
  46 --pf :: (a -> Bool) -> [a] -> [a]
  47 --pf = filter
  48
  49 pr :: [a] -> [a]
  50 pr = reverse
  51
  52 --pm :: (a -> b) -> [a] -> [b]
  53 --pm = map
  54
  55 map2 :: (t -> b) -> [[t]] -> [[b]]
  56 map2 fun = map (map fun)
  57
  58 pz :: [a] -> [b] -> [(a, b)]
  59 pz  = zip
  60
  61 pd :: Int -> [a] -> [a]
  62 pd  = drop
  63
  64 ptk :: Int -> [a] -> [a]
  65 ptk = take
  66
  67 pzw :: (a -> b -> c) -> [a] -> [b] -> [c]
  68 pzw = zipWith
  69
  70 -- Exponential Average
  71 eavg :: [Double] -> Double
  72 eavg (x:xs) = a*x + (1-a)*(eavg xs)
  73   where a = 0.70
  74 eavg [] = 0
  75
  76 -- Simple Average
  77 mean :: Fractional a => [a] -> a
  78 mean xs = if L.null xs then 0.0
  79                        else sum xs / fromIntegral (length xs)
  80
  81 sumMaybe :: Num a => [Maybe a] -> Maybe a
  82 sumMaybe = fmap sum . M.sequence
  83
  84 variance :: Floating a => [a] -> a
  85 variance xs = mean $ map (\x -> (x - m) ** 2) xs where
  86     m = mean xs
  87
  88 deviation :: [Double] -> Double
  89 deviation = sqrt . variance
  90
  91 movingAverage :: Fractional b => Int -> [b] -> [b]
  92 movingAverage steps xs = map mean $ chunkAlong steps 1 xs
  93
  94 ma :: [Double] -> [Double]
  95 ma = movingAverage 3
  96
  97
  98 -- | Function to split a range into chunks
  99 chunkAlong :: Int -> Int -> [a] -> [[a]]
 100 chunkAlong a b l = only (while  dropAlong)
 101     where
 102         only      = map (take a)
 103         while     = takeWhile  (\x -> length x >= a)
 104         dropAlong = L.scanl (\x _y -> drop b x) l ([1..] :: [Integer])
 105
 106 -- | Optimized version (Vector)
 107 chunkAlong' :: Int -> Int -> V.Vector a -> V.Vector (V.Vector a)
 108 chunkAlong' a b l = only (while  dropAlong)
 109     where
 110         only      = V.map (V.take a)
 111         while     = V.takeWhile  (\x -> V.length x >= a)
 112         dropAlong = V.scanl (\x _y -> V.drop b x) l (V.fromList [1..])
 113
 114 -- | TODO Inverse of chunk ? unchunkAlong ?
 115 unchunkAlong :: Int -> Int -> [[a]] -> [a]
 116 unchunkAlong = undefined
 117
 118
 119 -- splitAlong [2,3,4] ("helloworld" :: [Char]) == ["he", "llo", "worl", "d"]
 120 splitAlong :: [Int] -> [Char] -> [[Char]]
 121 splitAlong _ [] = [] -- No list? done
 122 splitAlong [] xs = [xs] -- No place to split at? Return the remainder
 123 splitAlong (x:xs) ys = take x ys : splitAlong xs (drop x ys) -- take until our split spot, recurse with next split spot and list remainder
 124
 125 takeWhileM :: (Monad m) => (a -> Bool) -> [m a] -> m [a]
 126 takeWhileM _ [] = return []
 127 takeWhileM p (a:as) = do
 128     v <- a
 129     if p v
 130         then do
 131             vs <- takeWhileM p as
 132             return (v:vs)
 133         else return []
 134
 135 -- SUMS
 136 -- To select the right algorithme according to the type:
 137 -- https://github.com/mikeizbicki/ifcxt
 138
 139 sumSimple :: Num a => [a] -> a
 140 sumSimple = L.foldl' (+) 0
 141
 142 -- | https://en.wikipedia.org/wiki/Kahan_summation_algorithm
 143 sumKahan :: Num a => [a] -> a
 144 sumKahan = snd . L.foldl' go (0,0)
 145     where
 146         go (c,t) i = ((t'-t)-y,t')
 147             where
 148                 y  = i-c
 149                 t' = t+y
 150
 151 -- | compute part of the dict
 152 count2map :: (Ord k, Foldable t) => t k -> Map.Map k Double
 153 count2map xs = Map.map (/ (fromIntegral (length xs))) (count2map' xs)
 154
 155 -- | insert in a dict
 156 count2map' :: (Ord k, Foldable t) => t k -> Map.Map k Double
 157 count2map' xs = L.foldl' (\x y -> insertWith (+) y 1 x) Map.empty xs
 158
 159
 160 trunc :: (RealFrac a, Integral c, Integral b) => b -> a -> c
 161 trunc n = truncate . (* 10^n)
 162
 163 trunc' :: Int -> Double -> Double
 164 trunc' n x = fromIntegral $ truncate $ (x * 10^n)
 165
 166
 167 bool2int :: Num a => Bool -> a
 168 bool2int b = case b of
 169                   True  -> 1
 170                   False -> 0
 171
 172 bool2double :: Bool -> Double
 173 bool2double bool = case bool of
 174                   True  -> 1.0
 175                   False -> 0.0
 176
 177
 178
 179 -- Normalizing && scaling data
 180 scale :: [Double] -> [Double]
 181 scale = scaleMinMax
 182
 183 scaleMinMax :: [Double] -> [Double]
 184 scaleMinMax xs = map (\x -> (x - mi / (ma - mi + 1) )) xs'
 185     where
 186         ma  = maximum xs'
 187         mi  = minimum xs'
 188         xs' = map abs xs
 189
 190 scaleNormalize :: [Double] -> [Double]
 191 scaleNormalize xs = map (\x -> (x - v / (m + 1))) xs'
 192     where
 193         v = variance xs'
 194         m = mean     xs'
 195         xs' = map abs xs
 196
 197
 198
 199 normalize :: [Double] -> [Double]
 200 normalize as = normalizeWith identity as
 201
 202 normalizeWith :: Fractional b => (a -> b) -> [a] -> [b]
 203 normalizeWith extract bs = map (\x -> x/(sum bs')) bs'
 204     where
 205         bs' = map extract bs
 206
 207 -- Zip functions to add
 208 zipFst :: ([b] -> [a]) -> [b] -> [(a, b)]
 209 zipFst  f xs = zip (f xs) xs
 210
 211 zipSnd :: ([a] -> [b]) -> [a] -> [(a, b)]
 212 zipSnd f xs = zip xs (f xs)
 213
 214
 215 -- Just
 216
 217 unMaybe :: [Maybe a] -> [a]
 218 unMaybe = map fromJust . L.filter isJust