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                  )
  29
  30 -- TODO import functions optimized in Utils.Count
  31 -- import Protolude hiding (head, last, all, any, sum, product, length)
  32 -- import Gargantext.Utils.Count
  33
  34 import qualified Data.List     as L hiding (head, sum)
  35 import qualified Control.Monad as M
  36 import qualified Data.Map as Map
  37 import qualified Data.Vector as V
  38 import Safe (headMay)
  39 import Text.Show (Show(), show)
  40 import Text.Read (Read())
  41 --pf :: (a -> Bool) -> [a] -> [a]
  42 --pf = filter
  43
  44 pr :: [a] -> [a]
  45 pr = reverse
  46
  47 --pm :: (a -> b) -> [a] -> [b]
  48 --pm = map
  49
  50 map2 :: (t -> b) -> [[t]] -> [[b]]
  51 map2 fun = map (map fun)
  52
  53 pz :: [a] -> [b] -> [(a, b)]
  54 pz  = zip
  55
  56 pd :: Int -> [a] -> [a]
  57 pd  = drop
  58
  59 ptk :: Int -> [a] -> [a]
  60 ptk = take
  61
  62 pzw :: (a -> b -> c) -> [a] -> [b] -> [c]
  63 pzw = zipWith
  64
  65 -- Exponential Average
  66 eavg :: [Double] -> Double
  67 eavg (x:xs) = a*x + (1-a)*(eavg xs)
  68   where a = 0.70
  69 eavg [] = 0
  70
  71 -- Simple Average
  72 mean :: Fractional a => [a] -> a
  73 mean xs = if L.null xs then 0.0
  74                        else sum xs / fromIntegral (length xs)
  75
  76 sumMaybe :: Num a => [Maybe a] -> Maybe a
  77 sumMaybe = fmap sum . M.sequence
  78
  79 variance :: Floating a => [a] -> a
  80 variance xs = mean $ map (\x -> (x - m) ** 2) xs where
  81     m = mean xs
  82
  83 deviation :: [Double] -> Double
  84 deviation = sqrt . variance
  85
  86 movingAverage :: Fractional b => Int -> [b] -> [b]
  87 movingAverage steps xs = map mean $ chunkAlong steps 1 xs
  88
  89 ma :: [Double] -> [Double]
  90 ma = movingAverage 3
  91
  92
  93 -- | Function to split a range into chunks
  94 chunkAlong :: Int -> Int -> [a] -> [[a]]
  95 chunkAlong a b l = only (while  dropAlong)
  96     where
  97         only      = map (take a)
  98         while     = takeWhile  (\x -> length x >= a)
  99         dropAlong = L.scanl (\x _y -> drop b x) l ([1..] :: [Integer])
 100
 101 -- | Optimized version (Vector)
 102 chunkAlong' :: Int -> Int -> V.Vector a -> V.Vector (V.Vector a)
 103 chunkAlong' a b l = only (while  dropAlong)
 104     where
 105         only      = V.map (V.take a)
 106         while     = V.takeWhile  (\x -> V.length x >= a)
 107         dropAlong = V.scanl (\x _y -> V.drop b x) l (V.fromList [1..])
 108
 109 -- | TODO Inverse of chunk ? unchunkAlong ?
 110 unchunkAlong :: Int -> Int -> [[a]] -> [a]
 111 unchunkAlong = undefined
 112
 113
 114 -- splitAlong [2,3,4] ("helloworld" :: [Char]) == ["he", "llo", "worl", "d"]
 115 splitAlong :: [Int] -> [Char] -> [[Char]]
 116 splitAlong _ [] = [] -- No list? done
 117 splitAlong [] xs = [xs] -- No place to split at? Return the remainder
 118 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
 119
 120 takeWhileM :: (Monad m) => (a -> Bool) -> [m a] -> m [a]
 121 takeWhileM _ [] = return []
 122 takeWhileM p (a:as) = do
 123     v <- a
 124     if p v
 125         then do
 126             vs <- takeWhileM p as
 127             return (v:vs)
 128         else return []
 129
 130 -- SUMS
 131 -- To select the right algorithme according to the type:
 132 -- https://github.com/mikeizbicki/ifcxt
 133
 134 sumSimple :: Num a => [a] -> a
 135 sumSimple = L.foldl' (+) 0
 136
 137 -- | https://en.wikipedia.org/wiki/Kahan_summation_algorithm
 138 sumKahan :: Num a => [a] -> a
 139 sumKahan = snd . L.foldl' go (0,0)
 140     where
 141         go (c,t) i = ((t'-t)-y,t')
 142             where
 143                 y  = i-c
 144                 t' = t+y
 145
 146 -- | compute part of the dict
 147 count2map :: (Ord k, Foldable t) => t k -> Map.Map k Double
 148 count2map xs = Map.map (/ (fromIntegral (length xs))) (count2map' xs)
 149
 150 -- | insert in a dict
 151 count2map' :: (Ord k, Foldable t) => t k -> Map.Map k Double
 152 count2map' xs = L.foldl' (\x y -> Map.insertWith' (+) y 1 x) Map.empty xs
 153
 154
 155 trunc :: (RealFrac a, Integral c, Integral b) => b -> a -> c
 156 trunc n = truncate . (* 10^n)
 157
 158 trunc' :: Int -> Double -> Double
 159 trunc' n x = fromIntegral $ truncate $ (x * 10^n)
 160
 161
 162 bool2int :: Num a => Bool -> a
 163 bool2int b = case b of
 164                   True  -> 1
 165                   False -> 0
 166
 167 bool2double :: Bool -> Double
 168 bool2double bool = case bool of
 169                   True  -> 1.0
 170                   False -> 0.0
 171
 172
 173
 174 -- Normalizing && scaling data
 175 scale :: [Double] -> [Double]
 176 scale = scaleMinMax
 177
 178 scaleMinMax :: [Double] -> [Double]
 179 scaleMinMax xs = map (\x -> (x - mi / (ma - mi + 1) )) xs'
 180     where
 181         ma  = maximum xs'
 182         mi  = minimum xs'
 183         xs' = map abs xs
 184
 185 scaleNormalize :: [Double] -> [Double]
 186 scaleNormalize xs = map (\x -> (x - v / (m + 1))) xs'
 187     where
 188         v = variance xs'
 189         m = mean     xs'
 190         xs' = map abs xs
 191
 192
 193
 194 normalize :: [Double] -> [Double]
 195 normalize as = normalizeWith identity as
 196
 197 normalizeWith :: Fractional b => (a -> b) -> [a] -> [b]
 198 normalizeWith extract bs = map (\x -> x/(sum bs')) bs'
 199     where
 200         bs' = map extract bs
 201
 202 -- Zip functions to add
 203 zipFst :: ([b] -> [a]) -> [b] -> [(a, b)]
 204 zipFst  f xs = zip (f xs) xs
 205
 206 zipSnd :: ([a] -> [b]) -> [a] -> [(a, b)]
 207 zipSnd f xs = zip xs (f xs)