2 Module : Gargantext.Prelude
3 Description : Specific Prelude of the project
4 Copyright : (c) CNRS, 2017-Present
5 License : AGPL + CECILL v3
6 Maintainer : team@gargantext.org
7 Stability : experimental
10 Here is a longer description of this module, containing some
11 commentary with @some markup@.
14 {-# OPTIONS_GHC -fno-warn-name-shadowing #-}
15 {-# OPTIONS_GHC -fno-warn-type-defaults #-}
17 {-# LANGUAGE NoImplicitPrelude #-}
19 module Gargantext.Prelude
20 ( module Gargantext.Prelude
31 import GHC.Exts (sortWith)
33 import Control.Monad.IO.Class (MonadIO)
34 import Data.Maybe (isJust, fromJust, maybe)
35 import Protolude ( Bool(True, False), Int, Int64, Double, Integer
36 , Fractional, Num, Maybe(Just,Nothing)
37 , Enum, Bounded, Float
39 , pure, (>>=), (=<<), (<*>), (<$>), panic
42 , Ord, Integral, Foldable, RealFrac, Monad, filter
43 , reverse, map, mapM, zip, drop, take, zipWith
44 , sum, fromIntegral, length, fmap, foldl, foldl'
45 , takeWhile, sqrt, undefined, identity
46 , abs, min, max, maximum, minimum, return, snd, truncate
47 , (+), (*), (/), (-), (.), ($), (&), (**), (^), (<), (>), log
48 , Eq, (==), (>=), (<=), (<>), (/=)
49 , (&&), (||), not, any
51 , elem, die, mod, div, const, either
52 , curry, uncurry, repeat
60 -- TODO import functions optimized in Utils.Count
61 -- import Protolude hiding (head, last, all, any, sum, product, length)
62 -- import Gargantext.Utils.Count
63 import qualified Data.List as L hiding (head, sum)
64 import qualified Control.Monad as M
67 import qualified Data.Map as M
69 import Data.Map.Strict (insertWith)
70 import qualified Data.Vector as V
71 import Safe (headMay, lastMay)
72 import Text.Show (Show(), show)
73 import Text.Read (Read())
74 import Data.String.Conversions (cs)
77 printDebug :: (Show a, MonadIO m) => [Char] -> a -> m ()
78 printDebug msg x = putStrLn $ msg <> " " <> show x
79 -- printDebug _ _ = pure ()
82 map2 :: (t -> b) -> [[t]] -> [[b]]
83 map2 fun = map (map fun)
86 -- Some Statistics sugar functions
87 -- Exponential Average
88 eavg :: [Double] -> Double
89 eavg (x:xs) = a*x + (1-a)*(eavg xs)
94 mean :: Fractional a => [a] -> a
95 mean xs = if L.null xs then 0.0
96 else sum xs / fromIntegral (length xs)
99 sumMaybe :: Num a => [Maybe a] -> Maybe a
100 sumMaybe = fmap sum . M.sequence
102 variance :: Floating a => [a] -> a
103 variance xs = mean $ map (\x -> (x - m) ** 2) xs where
106 deviation :: [Double] -> Double
107 deviation = sqrt . variance
109 movingAverage :: Fractional b => Int -> [b] -> [b]
110 movingAverage steps xs = map mean $ chunkAlong steps 1 xs
112 ma :: [Double] -> [Double]
115 -- | splitEvery n == chunkAlong n n
116 splitEvery :: Int -> [a] -> [[a]]
119 let (h,t) = L.splitAt n xs
120 in h : splitEvery n t
122 -- | Function to split a range into chunks
123 chunkAlong :: Int -> Int -> [a] -> [[a]]
124 chunkAlong a b l = only (while dropAlong)
127 while = takeWhile (\x -> length x >= a)
128 dropAlong = L.scanl (\x _y -> drop b x) l ([1..] :: [Integer])
130 -- | Optimized version (Vector)
131 chunkAlong' :: Int -> Int -> V.Vector a -> V.Vector (V.Vector a)
132 chunkAlong' a b l = only (while dropAlong)
134 only = V.map (V.take a)
135 while = V.takeWhile (\x -> V.length x >= a)
136 dropAlong = V.scanl (\x _y -> V.drop b x) l (V.fromList [1..])
138 -- | TODO Inverse of chunk ? unchunkAlong ?
139 unchunkAlong :: Int -> Int -> [[a]] -> [a]
140 unchunkAlong = undefined
143 -- splitAlong [2,3,4] ("helloworld" :: [Char]) == ["he", "llo", "worl", "d"]
144 splitAlong :: [Int] -> [Char] -> [[Char]]
145 splitAlong _ [] = [] -- No list? done
146 splitAlong [] xs = [xs] -- No place to split at? Return the remainder
147 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
149 takeWhileM :: (Monad m) => (a -> Bool) -> [m a] -> m [a]
150 takeWhileM _ [] = return []
151 takeWhileM p (a:as) = do
155 vs <- takeWhileM p as
160 -- To select the right algorithme according to the type:
161 -- https://github.com/mikeizbicki/ifcxt
163 sumSimple :: Num a => [a] -> a
164 sumSimple = L.foldl' (+) 0
166 -- | https://en.wikipedia.org/wiki/Kahan_summation_algorithm
167 sumKahan :: Num a => [a] -> a
168 sumKahan = snd . L.foldl' go (0,0)
170 go (c,t) i = ((t'-t)-y,t')
175 -- | compute part of the dict
176 count2map :: (Ord k, Foldable t) => t k -> Map k Double
177 count2map xs = M.map (/ (fromIntegral (length xs))) (count2map' xs)
179 -- | insert in a dict
180 count2map' :: (Ord k, Foldable t) => t k -> Map k Double
181 count2map' xs = L.foldl' (\x y -> insertWith (+) y 1 x) M.empty xs
184 trunc :: (RealFrac a, Integral c, Integral b) => b -> a -> c
185 trunc n = truncate . (* 10^n)
187 trunc' :: Int -> Double -> Double
188 trunc' n x = fromIntegral $ truncate $ (x * 10^n)
191 ------------------------------------------------------------------------
192 bool2num :: Num a => Bool -> a
196 bool2double :: Bool -> Double
197 bool2double = bool2num
199 bool2int :: Bool -> Int
201 ------------------------------------------------------------------------
203 -- Normalizing && scaling data
204 scale :: [Double] -> [Double]
207 scaleMinMax :: [Double] -> [Double]
208 scaleMinMax xs = map (\x -> (x - mi / (ma - mi + 1) )) xs'
214 scaleNormalize :: [Double] -> [Double]
215 scaleNormalize xs = map (\x -> (x - v / (m + 1))) xs'
221 normalize :: [Double] -> [Double]
222 normalize as = normalizeWith identity as
224 normalizeWith :: Fractional b => (a -> b) -> [a] -> [b]
225 normalizeWith extract bs = map (\x -> x/(sum bs')) bs'
229 -- Zip functions to add
230 zipFst :: ([b] -> [a]) -> [b] -> [(a, b)]
231 zipFst f xs = zip (f xs) xs
233 zipSnd :: ([a] -> [b]) -> [a] -> [(a, b)]
234 zipSnd f xs = zip xs (f xs)
237 maximumWith :: (Ord a1, Foldable t) => (a2 -> a1) -> t a2 -> a2
238 maximumWith f = L.maximumBy (compare `on` f)