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